HomeMy WebLinkAboutKivalina Wind-Intertie Project Conceptual Design Report - May 2014 - REF Grant 7030016Kivalina Wind-Diesel Conceptual Design
Report
This report prepared for
Alaska Village Electric Cooperative
by
and
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This report was written by Douglas Vaught, P.E. of V3 Energy, LLC under contract to WHPacific, Inc. for
development of wind power in the village of Kivalina, Alaska. This analysis is part of a wind energy
feasibility project for Northwest Arctic Borough, NANA Regional Corporation and Alaska Energy
Authority.
Contents
Introduction ............................................................................................................................................ 1
Project Management ........................................................................................................................... 1
Kivalina.................................................................................................................................................... 1
Kivalina Power Plant ............................................................................................................................ 3
Wind-Diesel Philosophy ........................................................................................................................... 4
Wind-Diesel Hybrid System Overview ...................................................................................................... 5
Wind-diesel Design Options ................................................................................................................. 6
Low Penetration Configuration ........................................................................................................ 6
Medium Penetration Configuration ................................................................................................. 7
High Penetration Configuration ....................................................................................................... 7
Wind-Diesel System Components ........................................................................................................ 9
Wind Turbine(s) ............................................................................................................................... 9
Supervisory Control System ............................................................................................................. 9
Synchronous Condenser .................................................................................................................. 9
Secondary Load ............................................................................................................................. 10
Deferrable Load ............................................................................................................................. 10
Interruptible Load .......................................................................................................................... 10
Storage Options ............................................................................................................................. 11
Kivalina-based Wind Power Project ....................................................................................................... 12
Wind Resource Assessment - Kivalina ................................................................................................ 12
Met tower data synopsis................................................................................................................ 12
Wind Speed ................................................................................................................................... 12
Wind Rose ..................................................................................................................................... 13
Temperature ................................................................................................................................. 14
Turbulence Intensity ...................................................................................................................... 14
Extreme Winds .............................................................................................................................. 15
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Kivalina Wind Site Options ................................................................................................................. 15
WAsP Modeling ................................................................................................................................. 18
Turbine Site Options ...................................................................................................................... 18
Wind Turbine Options, Kivalina .......................................................................................................... 21
Northern Power Systems 100 (NPS 100) ........................................................................................ 21
Vestas V20 and V17 ....................................................................................................................... 23
Cold Climate Considerations of Wind Power ...................................................................................... 25
Wind-Diesel HOMER Model, Kivalina ..................................................................................................... 26
Kivalina Powerplant ........................................................................................................................... 27
Electric Load ...................................................................................................................................... 27
Thermal Load..................................................................................................................................... 28
Wind Turbine Configuration Options ................................................................................................. 28
System Modeling and Technical Analysis ............................................................................................... 29
Model Results – Wulik River Site ........................................................................................................ 30
Northern Power NPS 100-24, two (2) turbines ............................................................................... 30
Vestas V20, two (2) turbines .......................................................................................................... 31
Model Results – Kisimigiuktuk Hill Site ............................................................................................... 32
Northern Power NPS 100-21, two (2) turbines ............................................................................... 33
Northern Power NPS 100-21, three (3) turbines ............................................................................. 34
Vestas V17, two (2) turbines .......................................................................................................... 35
Vestas V17, three (3) turbines ........................................................................................................ 36
Economic Analysis ................................................................................................................................. 37
Fuel Cost ........................................................................................................................................... 37
Wind Turbine Project Costs................................................................................................................ 37
Economic Model Results .................................................................................................................... 38
Red Dog Port-based Wind Power Project ............................................................................................... 39
Wind Resource Assessment – Red Dog Port ....................................................................................... 40
Met tower data synopsis................................................................................................................ 40
Data Recovery ............................................................................................................................... 40
Wind Speed ................................................................................................................................... 40
Wind Rose ..................................................................................................................................... 41
Turbulence Intensity ...................................................................................................................... 42
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Extreme Winds .............................................................................................................................. 42
Red Dog Port Wind Site Options ........................................................................................................ 43
WAsP Modeling ............................................................................................................................. 43
Wind Turbine Option, Red Dog Port ................................................................................................... 44
EWT DW 52-900 ............................................................................................................................ 44
Red Dog Port Powerplant .................................................................................................................. 46
Electric Load .................................................................................................................................. 46
Thermal Load ................................................................................................................................. 47
System Modeling and Technical Analysis ........................................................................................... 48
Model Results – Red Dog Port............................................................................................................ 49
EWT DW 52-900, one (1) turbine, 75 m hub height, 90% net AEP ................................................... 49
EWT DW 52-900, two (2) turbines .................................................................................................. 50
Economic Analysis ................................................................................................................................. 51
Fuel Cost ........................................................................................................................................... 51
Wind Turbine Project Costs................................................................................................................ 52
Economic Model Results .................................................................................................................... 53
Development Considerations................................................................................................................. 53
Geology ............................................................................................................................................. 53
Environmental Review ....................................................................................................................... 54
Vegetation ..................................................................................................................................... 54
Avian Resources............................................................................................................................. 54
Other Mammals............................................................................................................................. 55
Fisheries ........................................................................................................................................ 55
Threatened and Endangered Species ............................................................................................. 55
Cultural Resources ......................................................................................................................... 56
Permitting and Agency Consultation Requirements ........................................................................... 56
Wetlands and Waterways .............................................................................................................. 56
Alaska Pollution Discharge Elimination System............................................................................... 57
US. Fish and Wildlife Service/National Marine Fisheries Service ..................................................... 57
Federal Aviation Administration ..................................................................................................... 57
U.S. Army Corps of Engineers ......................................................................................................... 57
Alaska Department of Fish and Game ............................................................................................ 58
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State Historic Preservation Office .................................................................................................. 58
Discussion ............................................................................................................................................. 58
Cost ................................................................................................................................................... 59
Aesthetics .......................................................................................................................................... 59
Redundancy....................................................................................................................................... 59
Support ............................................................................................................................................. 59
Commonality ..................................................................................................................................... 59
Recommendation .................................................................................................................................. 60
Appendix A – Kivalina Wind Resource Report .......................................................................................... A
Appendix B – Red Dog Port Wind Resource Report .................................................................................. B
Appendix C – FAA Notice Criteria Tool, Wulik River Site ........................................................................... C
Appendix D – FAA Notice Criteria Tool, Kisimigiuktuk Hill Site ..................................................................D
Appendix E – FAA Notice Criteria Tool, Red Dog Port Site ........................................................................ E
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Introduction
Alaska Village Electric Cooperative (AVEC) is the electric utility for the City of Kivalina. WHPacific is
working with Northwest Arctic Borough and NANA Regional Corporation to consider renewable energy
options in Kivalina. WHPacific has contracted V3 Energy, LLC to help prepare this conceptual design
report. The primary focus is to evaluate wind power options at the met tower site for the village at its
present location. A secondary focus is to model the wind resource at Kisimigiuktuk Hill, which is the
planned new location for the village after relocation, and consider wind power options in that location.
Additionally, an electrical distribution intertie has been proposed to connect between Red Dog Port and
Kivalina. Should this connection be constructed, the presumed location for wind power development
would be Red Dog Port with larger utility-scale turbines. This scenario is evaluated in this report.
Project Management
Alaska Village Electric Cooperative, Key Accounts Department, has executive oversight over
development of wind power in Kivalina. AVEC, Northwest Arctic Borough, NANA Regional Corporation,
and the City of Kivalina wish to install wind turbines in Kivalina primarily to reduce diesel fuel
consumption and save money, but also to:
Reduce long-term dependence on outside sources of energy
Reduce exposure to fuel price volatility
Reduce air pollution resulting from less fossil fuel combustion
Reduce possibility of spills from fuel transport & storage
Reduce Northwest Arctic Borough’s carbon footprint and its contribution to climate change.
Kivalina
Kivalina is at the tip of an 8-mile barrier reef located between the Chukchi Sea and Kivalina River. It lies
80 air miles northwest of Kotzebue. It lies in the transitional climate zone, which is characterized by
long, cold winters and cool summers. The average low temperature during January is -15 °F; the average
high during July is 57 °F. Temperature extremes have been measured from -54 to 85 °F. Annual snowfall
averages 57 inches, with 8.6 inches of precipitation per year. The Chukchi Sea is ice-free and open to
boat traffic from mid-June to the first of November.
Kivalina has long been a stopping-off place for seasonal travelers between Arctic coastal areas and
Kotzebue Sound communities. It is the only village in the Northwest Arctic Borough region where people
hunt the bowhead whale. At one time, the village was located at the north end of the Kivalina Lagoon. It
was reported as "Kivualinagmut" in 1847 by Lt. Zagoskin of the Russian Navy. Lt. G.M. Stoney of the U.S.
Navy reported the village as "Kuveleek" in 1885. A post office was established in 1940. An airstrip was
built in 1960 using metal mattings. Kivalina incorporated as a city in 1969. During the 1970s, new
houses, a new school, and an electric system were constructed in the village. Prior to 1976, high school
students from Noatak would attend school in Kivalina and board with local families. Due to severe
erosion and wind-driven ice damage, the city intends to relocate to a new site 2.5 miles away.
Relocation alternatives have been studied, and a new site has been designed and engineered.
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Kivalina is a traditional Inupiat Eskimo village. Subsistence activities, including whaling, provide most
food sources.
Topographic map of Kivalina
Google Earth image of Kivalina
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Kivalina Power Plant
The Kivalina powerplant is owned and operated by AVEC. Operating personnel are village residents and
employed by AVEC. The following information was obtained by WHPacific in 2011 and for this report is
considered current.
Equipment Data
Unit Engine Mfr Engine Generator Generator Model Set Rating
1 Detroit Diesel DDEC3-S60 Kato 6P4-1025 229
2 Caterpillar D353 Kato 6P4-1700 337
3 Cummins LTA 10 Kato 4P3-1475 203
4 Detroit Diesel DDEC4-S60 Newage HCI504C 363
Generating voltage: 480Y/277
The Kivalina power plant is currently equipped with two peak load generator sets, each capable of
individually meeting the current peak load requirements. The highest output unit is a relatively high-
efficiency 1800 rpm Detroit Diesel Series 60. The next highest output unit, a Caterpillar D353, is no
longer manufactured. The Kivalina power plant is also equipped with two remote radiators on the 1800
rpm Detroit Diesel Series 60 which provide redundant cooling capacity along with a heat exchanger and
hydronic heating system for transfer of heat to the plant structures.
The Kivalina tank farm has adequate useable fuel storage capacity to meet the annual requirements of
the next two-year period. Major system improvements completed for the Kivalina distribution system
include replacement of the remaining URD (underground residential distribution) sections of the
distribution system with overhead lines. Major systems improvements planned for the Kivalina
generation system include replacement of rusted powerplant step-up transformers.
Existing features Powerplant shortcomings
Low system losses in 2004, 2006
and 2008
Two redundant peak load generator
sets
One fireproof generator set module
Three redundant remote radiators
Welded fuel fill line
Impermeable liner underneath tank
farm
New bulk fuel storage tank bottoms
Slightly excess fuel storage capacity
Two state-of-the-art electronically
timed diesel sets
High overall operating efficiency in
1998, 2002, 2006 and 2010
Relatively high generating efficiency
High station energy consumption
Undeveloped wind energy potential
One remaining non-manufactured Cat D353
No engine jacket water heat recovery system
Low 208 volt generation
Three year pattern of increasing average outage time;
many outages in 2010
No blending system for used lubricating oil
No fence around power plant site
Fluctuating system losses and station energy consumption
Fluctuating overall adjusted operating efficiency
Fluctuating adjusted generating efficiency
Large fuel adjustment in 2010
Five year pattern of increasing fuel costs
Power plant and tank farm located adjacent to beach
potentially subject to erosion
Tank farm located far from power plant
Remote location of tank farm requires long transfers of
fuel
Fuel transfers increase spill risk
Declining unadjusted generating efficiency
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Existing features Powerplant shortcomings
Unrealistically high adjusted generating efficiency
Larger fuel adjustments since tank farm was located to a
remote location from previoustank farm
Wind-Diesel Philosophy
Installing wind turbines and creating a wind-diesel power system in an Alaskan village is a demanding
challenge. At first glance, the benefits of wind power are manifest: the fuel is free and it is simply a
manner of capturing it. The reality of course is more complicated. Wind turbines are complex machines
and integrating them into the diesel power system of a small community is complicated. With wind-
diesel, a trade-off exists between fuel savings and complexity. A system that is simple and inexpensive
to install and operate will displace relatively little diesel fuel, while a wind-diesel system of considerable
complexity and sophistication can achieve very significant fuel savings.
The ideal balance of fuel savings and complexity is not the same for every community and requires
careful consideration. Not only do the wind resource, electric and thermal load profiles, and
powerhouse suitability vary between villages, so does technical capacity and community willingness to
accept the opportunities and challenges of wind power. A very good wind-diesel solution for one village
may not work as well in another village, for reasons that go beyond design and configuration questions.
Ultimately, the electric utility and village residents must consider their capacity, desire for change and
growth, and long-term goals when deciding the best solution to meets their needs.
The purpose of this conceptual design report is to introduce and discuss the viability of wind power in
Kivalina. Many options are possible, ranging from a very simple low penetration system to a highly
complex, diesels-off configuration potentially capable of displacing 50 percent or more of fuel usage in
the community. It is possible that AVEC and Kivalina residents ultimately will prefer a simple, low
penetration wind power system, or alternatively a very complex high penetration system, but from past
discussions and work it appears that a moderate approach to wind power in Kivalina is preferable, at
least initially.
With a moderately complex project design framework in mind, a configuration of relatively high wind
turbine capacity with no electrical storage and no diesels-off capability was chosen. This provides
sufficient wind capacity to make a substantive impact on fuel usage but does not require an abrupt
transition of Kivalina’s power generation from low to high complexity. Although conceptually elegant,
there is a trade-off to consider with this approach. Installing a large amount of wind power (200 to 300
kW of wind capacity are recommended) is expensive, but without electrical or thermal storage some of
the benefits of this wind power capacity may not always be used to best advantage.
The thermodynamics of energy creation and use dictates that wind power is more valuable when used
to offset fuel used by diesel generators to generate electricity than fuel used in fuel oil boilers to serve
thermal loads. Referring to the energy production summaries for the turbine configurations under
Modeling Results, one can see that the wind turbines are expected to produce relatively small amounts
of excess electricity, even at 85 percent turbine availability. This excess electricity, although minimal,
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must be shunted via a secondary load controller to the diesel generator heat recovery loop or simple
radiation heaters to avoid curtailing wind turbines during periods of high wind and relatively light
electrical load.
Although perhaps not readily apparent in the report, this compromise of wind capacity versus
complexity is contained within the economic benefit-to-cost tables. This compromise, which is endemic
to wind-diesel, results in high capital costs, but usage of the energy generated is imperfect from an
efficiency point of view. The most efficient usage of wind energy from a technical point of view – offset
of electrical power, may be too expensive from a cost-benefit perspective.
It is important not to focus strictly on benefit-to-cost ratio of a particular configuration design or
particular turbine option, but also consider a wider view of the proposed wind project for Kivalina.
Installing 200 to 300 kW wind power capacity has considerable short-term benefit with reduction of
diesel fuel usage, but more importantly it would provide a platform of sustainable renewable energy
growth in Kivalina for many years to come. This could include enhancements such as additional thermal
load offset, battery storage and/or use of a flywheel to enable diesels-off capability, creation of deferred
heat loads such as water heating, and installation of distributed electrical home heat units (Steffis
heaters or similar) controlled by smart metering. The latter, presently operational to a limited extent in
the villages of Kongiganak, Kwigillingok, Tuntutuliak, has enormous potential in rural Alaska to not only
reduce the very high fuel oil expenses borne by village residents, but also to improve the efficiency and
cost benefit of installed and future wind power projects. These opportunities and benefits are tangible
and achievable, but their cost benefit was not modeled in this report.
Lastly, it must be acknowledged that a wind power project in Kivalina will provide benefits that are not
easily captured by economic modeling. These are the externalities of economics that are widely
recognized as valuable, but often discounted because they are considered by some as soft values
compared to the hard numbers of capital cost, fuel quantity displaced, etc. These include ideals such as
long-term sustainability of the village, independence from foreign-sourced fuel, reduction of Kivalina’s
carbon footprint, and opportunities for education and training of local residents. Beyond these
somewhat practical considerations, there is the simple moral argument that renewable energy is the
right thing to do, especially in a community such as Kivalina that is in the vanguard of risk from climate
change due to global warming.
Wind-Diesel Hybrid System Overview
There are now over twenty-four wind-diesel projects in the state, making Alaska a world leader in wind-
diesel hybrid technology. There are a variety of system configurations and turbine types in operation
and accordingly there is a spectrum of success in all of these systems. As experience and statewide
industry support has increased so has overall system performance. The following figure illustrates the
locations of installed wind projects in Alaska.
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Alaska wind-diesel projects
Wind-diesel Design Options
Wind-diesel power systems are categorized based on their average penetration levels, or the overall
proportion of wind-generated electricity compared to the total amount of electrical energy generated.
Commonly used categories of wind-diesel penetration levels are low penetration, medium penetration,
and high penetration. The wind penetration level is roughly equivalent to the amount of diesel fuel
displaced by wind power. Note however that the higher the level of wind penetration, the more
complex and expensive a control system and demand-management strategy is required. This is a good
compromise between of displaced fuel usage and relatively minimal system complexity and is the
preferred system configuration of Alaska Village Electric Cooperative (AVEC). AVEC is Alaska’s leading
utility developer of wind-diesel power systems, and a useful guide for North Slope Borough.
Low Penetration Configuration
Low-penetration wind-diesel systems require the fewest modifications to the existing system. However,
they tend to be less economical for village installations due to the limited annual fuel savings compared
to the total wind system installation costs.
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Medium Penetration Configuration
Many of the AVEC communities, Toksook Bay for example, have 24% of their energy from wind. The
figure below indicates the configuration and key points on using a medium penetration, wind-diesel
system.
High Penetration Configuration
Other communities, such as Kokhanok, are more aggressively seeking to offset diesel used for thermal
and electrical energy. They are using configurations which will allow for the generator sets to be turned
off and use a significant portion of the wind energy for various heating loads. The potential benefit of
these systems is the highest, however currently the commissioning for these system types due to the
increased complexity, can take longer. The figure below indicates the configuration and key points on
using a high-penetration, wind-diesel system.
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The above system descriptions can be summarized in the table below. The level of instantaneous
penetration is important for power quality design considerations. The annual amount of wind energy on
the system is considered the average penetration level and helps to provide a picture of the overall
economic benefit.
Categoriesofwind-diesel penetrationlevels
Penetration
Category
Wind Penetration Level
OperatingCharacteristicsandSystem Requirements
Instantaneous Average
Very Low <60%<8%Diesel generator(s) runs full time
Wind power reduces net load on diesel
All wind energy serves primary load
No supervisory control system
Low 60 to 120%8 to 20%Diesel generator(s) runs full time
At high wind power levels, secondary loads are
dispatched to insure sufficient diesel loading, or wind
generation is curtailed
Relatively simple control system
Medium 120 to 300%20 to 50%Diesel generator(s) runs full time
At medium to high wind power levels, secondary
loads are dispatched to insure sufficient diesel
loading
At high wind power levels, complex secondary load
control system is needed to ensure heat loads do not
become saturated
Sophisticated control system
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Penetration
Category
Wind Penetration Level
OperatingCharacteristicsandSystem RequirementsInstantaneous Average
High
(Diesels-off
Capable)
300+%50 to 150% At high wind power levels, diesel generator(s) may be
shut down for diesels-off capability
Auxiliary components required to regulate voltage
and frequency
Sophisticated control system
Wind-Diesel System Components
Listed below are the main components of a medium to high-penetration wind-diesel system:
Wind turbine(s), plus tower and foundation
Supervisory control system
Secondary load (plus controller)
Deferrable load
Interruptible load
Storage
Synchronous condenser
Wind Turbine(s)
Village-scale wind turbines are generally considered to be 50 kW to 500 kW rated output capacity. This
turbine size once dominated with worldwide wind power industry but has long been left behind in favor
of much larger 1,500 kW plus capacity turbines. Conversely, many turbines are manufactured for home
or farm application, but generally these are 10 kW capacity or less. Consequently, few new village size-
class turbines are on the market, although a large supply of used and/or remanufactured turbines are
available. The latter typically result from repowering older wind farms in the United States and Europe
with new, larger wind turbines.
Supervisory Control System
Medium- and high-penetration wind-diesel systems require fast-acting real and reactive power
management to compensate for rapid variation in village load and wind turbine power output. A wind-
diesel system master controller, also called a supervisory controller, would be installed inside the
Kivalina power plant or in a new module adjacent to it. The supervisory controller would select the
optimum system configuration based on village load demand and available wind power.
Synchronous Condenser
A synchronous condenser, also referred to as a synchronous compensator, is a specialized synchronous-
type electric motor with an output shaft that spins freely. Its excitation field is controlled by a voltage
regulator to either generate or absorb reactive power as needed to support grid voltage or to maintain
the grid power factor at a specified level. A synchronous condenser or similar device is needed to
operate in diesels-off mode with wind turbines equipped with asynchronous (induction) type
generators. This is to provide the reactive power necessary for operation of the asynchronous
generator.
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Synchronous condenser at the Kokhonak, AK powerplant
Secondary Load
A secondary or “dump” load during periods of high wind is required for a wind-diesel hybrid power
system to operate reliably and economically. The secondary load converts excess wind power into
thermal power for use in space and water heating through the extremely rapid (sub-cycle) switching of
heating elements, such as an electric boiler imbedded in the diesel generator jacket water heat recovery
loop. As seen in Figure 16, a secondary load controller serves to stabilize system frequency by providing
a fast responding load when gusting wind creates system instability.
An electric boiler is a common secondary load device used in wind-diesel power systems. An electric
boiler (or boilers), coupled with a boiler grid interface control system, could be installed in Kivalina to
absorb excess instantaneous energy (generated wind energy plus minimum diesel output exceeds
electric load demand). The grid interface monitors and maintains the temperature of the electric hot
water tank and establishes a power setpoint. The wind-diesel system master controller assigns the
setpoint based on the amount of unused wind power available in the system. Frequency stabilization is
another advantage that can be controlled with an electric boiler load. The boiler grid interface will
automatically adjust the amount of power it is drawing to maintain system frequency within acceptable
limits.
Deferrable Load
A deferrable load is electric load that must be met within some time period, but exact timing is not
important. Loads are normally classified as deferrable because they have some storage associated with
them. Water pumping is a common example - there is some flexibility as to when the pump actually
operates, provided the water tank does not run dry. Other examples include ice making and battery
charging. A deferrable load operates second in priority to the primary load and has priority over
charging batteries, should the system employ batteries as a storage option.
Interruptible Load
Electric heating either in the form of electric space heaters or electric water boilers could be explored as
a means of displacing stove oil with wind-generated electricity. It must be emphasized that electric
heating is only economically viable with excess electricity generated by a renewable energy source such
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as wind and not from diesel-generated power. It is typically assumed that 40 kWh of electric heat is
equivalent to one gallon of heating fuel oil.
Storage Options
Electrical energy storage provides a means of storing wind generated power during periods of high
winds and then releasing the power as winds subside. Energy storage has a similar function to a
secondary load but the stored, excess wind energy can be converted back to electric power at a later
time. There is an efficiency loss with the conversion of power to storage and out of storage. The
descriptions below are informative but are not currently part of the overall system design.
Flywheels
A flywheel energy system has the capability of short-term energy storage to further smooth out short-
term variability of wind power, and has the additional advantage of frequency regulation. The smallest
capacity flywheel available from Powercorp (now ABB), however, is 500 kW capacity, so it is only
suitable for large village power generation systems.
Batteries
Battery storage is a generally well-proven technology and has been used in Alaskan power systems
including Fairbanks (Golden Valley Electric Association), Wales and Kokhanok, but with mixed results in
the smaller communities. Batteries are most appropriate for providing medium-term energy storage to
allow a transition, or bridge, between the variable output of wind turbines and diesel generation. This
“bridging” period is typically 5 to 15 minutes long. Storage for several hours or days is also possible with
batteries, but this requires higher capacity and cost. In general, the disadvantages of batteries for utility-
scale energy storage, even for small utility systems, are high capital and maintenance costs and limited
lifetime. Of particular concern to rural Alaska communities is that batteries are heavy and expensive ship
and most contain hazardous substances that require special removal from the village at end of service
life and disposal in specially-equipped recycling centers.
There are a wide variety of battery types with different operating characteristics. Advanced lead acid
and zinc-bromide flow batteries were identified as “technologically simple” energy storage options
appropriate for rural Alaska in an Alaska Center for Energy and Power (ACEP) July, 2009 report on
energy storage. Nickel-cadmium (NiCad) batteries have been used in rural Alaska applications such as
the Wales wind-diesel system. Advantages of NiCad batteries compared to lead-acid batteries include a
deeper discharge capability, lighter weight, higher energy density, a constant output voltage, and much
better performance during cold temperatures. However, NiCads are considerably more expensive than
lead-acid batteries and one must note that the Wales wind-diesel system had a poor operational history
and has not been functional for over ten years.
Because batteries operate on direct current (DC), a converter is required to charge or discharge when
connected to an alternating current (AC) system. A typical battery storage system would include a bank
of batteries and a power conversion device. The batteries would be wired for a nominal voltage of
roughly 300 volts. Individual battery voltages on a large scale system are typically 1.2 volts DC. Recent
advances in power electronics have made solid state inverter/converter systems cost effective and
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preferable a power conversion device. The Kokhanok wind-diesel system is designed with a 300 volts DC
battery bank coupled to a grid-forming power converter for production of utility-grade real and reactive
power. Following some design and commissioning delays, the solid state converter system in Kokhanok
should be operational by late 2013 and will be monitored closely for reliability and effectiveness.
Kivalina-based Wind Power Project
This section examines the options for a wind project based in or near Kivalina and serving only electric
and thermal loads in the village.
Wind Resource Assessment - Kivalina
The wind resource measured in Kivalina is good, with measured power class 3 to 4 winds. In addition to
high annual mean wind speed and wind power density, Kivalina experiences directional prevailing winds,
low turbulence and calculations indicate low extreme wind speed probability.
A 30 meter met tower was installed in May 2011 about two miles south of Kivalina near the Wulik River
at the planned re-location site for the village. The met tower datalogger failed in May 2012 and the met
tower itself collapsed in a severe wind storm with accompanying flooding in autumn 2012. The met
tower debris was removed from the site in August 2013 and remaining rebar guy wires anchors were
cut-off at ground level in February 2014. The complete Kivalina wind resource report, dated June 2012,
is included in Appendix A of this report.
Met tower data synopsis
Data dates May 9, 2011 to May 18, 2012 (12.3 months)
Site number 9750
Site location (NAD83) N 67° 43’ 26.64”; W 164° 26’ 25.38”
Wind power class Class 3 to Class 4
Wind power density mean, 30 m 325 W/m2
Wind speed mean, 30 m 5.84 m/s
Max. 10-min wind speed average 26.7 m/s
Maximum 2-sec. wind gust 33.6 m/s (November, 2011)
Weibull distribution parameters k = 1.65, c = 6.51 m/s
Wind shear power law exponent Not determined due to faulty 20 m anemometer
Roughness class Not determined due to faulty 20 m anemometer
IEC 61400-1, 3rd ed. classification Class III-C
Turbulence intensity, mean 0.075 (at 15 m/s)
Calm wind frequency (at 33 m)35% (< 4 m/s)
Wind Speed
Anemometer data obtained from the met tower, from the perspectives of both mean wind speed and
mean wind power density, indicate a good wind resource. Mean wind speeds are greater at higher
elevations on the met tower as one would expect. Note that the cold mean annual air temperature in
Kivalina contributed to a higher wind power density than otherwise expected for the mean wind speeds.
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use elsewhere in this report.
problems with the 20 meter level anemometer.
Anemometer data summary
Variable
Speed 30 m
A
Speed 30 m
B
Speed 37 m
synthesized
Measurement height (m) 30 30 37
Mean wind speed (m/s) 5.84 5.79 6.02
Max 10-min avg wind speed (m/s) 26.7 26.7 27.5
Max gust wind speed (m/s) 33.2 33.6
Weibull k 1.65 1.61 1.65
Weibull c (m/s) 6.51 6.44 6.71
Mean power density (W/m²) 323 321 353
Mean energy content (kWh/m²/yr) 2,830 2,810 3,090
Energy pattern factor 2.43 2.48 2.43
Wind speed profile
Wind Rose
Wind frequency rose data indicates that winds at Kivalina are relatively directional, with north-
northeasterly and east-northeasterly predominating. The mean value rose indicates that infrequent
southeasterly winds, when they do occur, are of high energy and hence likely are storm winds. The wind
energy rose indicates that winds for wind turbine operations power-producing are northerly and
southeasterly dominant. Calm frequency (percent of time that winds at the 30 meter level are less than
4 m/s) was 34 percent during the met tower test period.
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Wind frequency rose Wind energy rose
Temperature
Kivalina has an exceptionally cold climate with a below freezing mean annual temperature and a
minimum measured temperature during the test period of -48.7° C (-55.7° F). Summer temperatures
can be quite warm however.
Kivalina temperature data
Mean Mean Min Min Max Max
Month (°C) (°F) (°C)(°F) (°C)(°F)
Jan -30.7 -23.2 -44.5 -48.1 -8.9 16.0
Feb -15.9 3.3 -48.7 -55.7 2.7 36.9
Mar -20.2 -4.4 -34.5 -30.1 -7.4 18.7
Apr -7.9 17.7 -28.4 -19.1 10.6 51.1
May 1.8 35.2 -15.4 4.3 25.0 77.0
Jun 12.2 54.0 0.7 33.3 28.1 82.6
Jul 12.9 55.2 2.6 36.7 28.9 84.0
Aug 11.3 52.4 0.4 32.7 23.5 74.3
Sep 6.8 44.3 -5.1 22.8 19.3 66.7
Oct -3.5 25.8 -17.6 0.3 8.7 47.7
Nov -16.5 2.2 -31.5 -24.7 1.8 35.2
Dec -15.5 4.0 -35.0 -31.0 0.5 32.9
Annual -5.4 22.3 -48.7 -55.7 28.9 84.0
Turbulence Intensity
Turbulence intensity (TI) at the Kivalina met tower site is well within acceptable standards with an IEC
61400-1, 3rd edition (2005) classification of turbulence category C, which is the lowest defined. The
mean TI at 15 m/s is 0.075 and the representative TI at 15 m/s is 0.105 (30 m A anemometer), both
which can be considered very low and hence very desirable for wind turbine operations.
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Turbulence intensity, 30 m A anemometer, all direction sectors
Extreme Winds
A modified Gumbel distribution analysis, based on monthly maximum winds vice annual maximum
winds, was used to predict extreme winds at the Kivalina met tower site. Industry standard reference of
extreme wind is the 50 year probable (50 year return period) ten-minute average wind speed, referred
to as Vref. For Kivalina, this calculates to 35.8 m/s (at 30 meters), which qualifies as an International
Electrotechnical Commission (IEC) 61400-1, 3rd edition criteria Class III site, the lowest defined. All wind
turbines are designed for IEC 61400-1 Class III conditions.
Extreme wind probability table, 30 m A data
Vref Gust IEC 61400-1, 3rd ed.
Period (years) (m/s) (m/s) Class Vref, m/s
3 26.8 32.8 I 50.0
10 30.7 37.5 II 42.5
20 32.9 40.2 III 37.5
30 34.2 41.8 S designer-
specified 50 35.8 43.8
100 38.0 46.5
Kivalina Wind Site Options
The primary difficulty in identifying and selecting a wind turbine site in Kivalina is the status of the
village. Wind turbines in or very near Kivalina are not possible due to the very confined nature of the
community and the alignment of the runway which precludes large structures near the village. But, due
to the ever-increasing erosion of the barrier island that Kivalina occupies which separates the
community from Kivalina Lagoon and the Bering Sea, the village may move to a more secure location.
Several years ago the preferred new location was one mile up the Wulik River (about two miles from the
present village site), very near the site of the Kivalina met tower. This location, however, was deemed
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unsuitable by the U.S. Army Corps of Engineers due to flooding risk, hence a site on the east slope of
Kisimigiuktuk Hill (“stands alone”; also Kisimiguiqtuq) was chosen for re-location of the village.
Kisimigiuktuk Hill is seven miles northeast of Kivalina and would require construction of a causeway
across Kivalina Lagoon and a substantial road construction project to cross several miles of marshy
tundra. Kisimigiuktuk Hill is stable and dry upland terrain and suitable for construction of infrastructure.
Kivalina site options
Wulik River site, view to west
Kisimigiuktuk Hill
Wulik River site;
met tower site
Kivalina
Kivalina
Wulik River
site; met
tower site
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Kisimigiuktuk Hill, view to west
Kivalina wind turbine site options table
Wind Turbine Site Advantages Disadvantages
Wulik River Near the existing village location
Site large enough to accommodate
several wind turbines with sufficient
room for future expansion
Sufficient distance from the Kivalina
airport to allay air traffic operations
concerns
Two miles of new distribution
line required; complicated
distribution line route with water
crossing
This site is no longer the
preferred location for the re-
location of Kivalina
Marshy permafrost site;
expensive foundation;
substantial fill required
Summer access undeveloped;
would require improved boat
landing on the Wulik River
Winter construction required
Kisimigiuktuk Hill Area of the preferred site for re-
location of Kivalina
Very good wind exposure
Rocky eroded mountain geotech;
ballast type foundation possible
Site large enough to accommodate
several wind turbines with sufficient
room for future expansion
Presumes re-location of Kivalina
without which this turbine site is
not viable
Road must be constructed to top
of Kisimigiuktuk Hill (presuming
preceding construction of road
from Kivalina to Kisimigiuktuk Hill
Kisimigiuktuk Hill
Kivalina
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Wind Turbine Site Advantages Disadvantages
Presuming Kivalina airport is not
relocated from the barrier island, no
turbine height limitations
Dry site; likely good geotech
conditions for turbine foundations
WAsP Modeling
WAsP (acronym for Wind Atlas and Application Program) is a PC-based software to predict wind climate,
wind resource and power production for wind turbines and wind farms. WAsP modeling was used in
this conceptual design report to predict the wind resource on Kisimigiuktuk Hill with the Kivalina met
tower as the wind resource reference point.
WAsP modeling begins with import from the National Elevation Dataset of a digital elevation map (DEM)
of the subject site and surrounding area and conversion of coordinates to Universal Transverse Mercator
(UTM). UTM is a geographic coordinate system that uses a two-dimensional Cartesian coordinate
system to identify locations on the surface of Earth. UTM coordinates reference the meridian of its
particular zone (60 longitudinal zones are further subdivided by 20 latitude bands) for the easting
coordinate and distance from the equator for the northing coordinate. Units are meters. Elevations of
the DEMs are converted to meters if necessary for import into WAsP software. Kivalina is within the
boundary of new, high resolution elevation data with modern datum geographic reference. This new
data was used for the WAsP analysis in this report.
Once converted for use in WAsP software, a met tower reference point is added to the DEM, wind
turbine locations identified, and a wind turbine type selected to perform the calculations. WAsP
considers the orographic (terrain) effects on the wind (plus surface roughness and obstacles) and
calculates wind flow increase or decrease at each node of the DEM grid. The mathematical model has a
number of limitations, including the assumption that wind regime of the turbine site is similar to that of
the met tower reference site, prevailing weather conditions are stable over time, and the surrounding
terrain at both sites is sufficiently gentle and smooth to ensure laminar, attached wind flow. WAsP
software is not capable of modeling turbulent wind flow resulting from sharp terrain features such as
mountain ridges, canyons, shear bluffs, etc. Turbulent flow modeling requires computation fluid
dynamics methods.
Turbine Site Options
As previously described, there are two site options: the Wulik River site at or near the met tower
location, and on the summit of Kisimigiuktuk Hill, presuming eventual relocation of the village of Kivalina
to this area due to the accelerating trend and increasing risk of erosion and coastal flooding.
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WAsP wind speed overlay, Wulik River site and Kisimigiuktuk Hill
WAsP wind speed overlay, Kisimigiuktuk Hill site area
Kisimigiuktuk Hill
Wulik River site
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WAsP wind speed overlay with wind rose, Kisimigiuktuk Hill Site, view to the west
Comparative prediction of Kivalina met tower and wind turbine sites
Location
Wind Speed
(annual mean),
(m/s)
Power Density,
(annual mean),
(W/m2) Weibull k
Weibull
A, (m/s)
IEC
61400-1
classif.
Kivalina met tower (30 m A
measured with synthesis) 5.84 323 1.65 6.71 III-C
Kivalina met tower (37 m
6.02 353 1.65 6.71
Kivalina met tower (37 m
WAsP observed wind
climate) 6.11 328* 1.57 6.60
Wulik River site (37 m
WAsP predicted) 6.14 331 1.68 6.90 III-C
Kisimigiuktuk Hill site (37 m
WAsP predicted) 8.28 830 1.60 8.70 II-C**
*WAsP wind power density calculation does not consider temperature/air density
**predicted/assumed
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WAsP observed wind climate (37 m extrapolated), from Windographer data file
Wind Turbine Options, Kivalina
The wind power options for a Kivalina-based project are limited to robust turbines in the approximately
100 kW capacity range. For the Wulik River site, these are the Northern Power NPS 100-24 and the
Vestas V20. Given the prediction of much higher wind speeds at the Kisimigiuktuk Hill site, the Northern
Power NPS 100-21 and the Vestas V17 are a more conservative consideration and likely more
appropriate with respect to IEC classification of extreme wind speed probability.
Northern Power Systems 100 (NPS 100)
At 100 kilowatts of rated power, the Northern Power 100 (previously known as the Northwind 100) is an
innovative wind turbine with gearless direct drive design, permanent magnet generator, best-in-class
reliability, and pleasing aesthetics. The turbine is marketed in two versions: the NPS 100 for
temperature climates and the NPS 100 Arctic for cold climates such as Alaska. Differences between the
two include heaters and insulation for the Arctic version, plus certification that metal used in the tower
and nacelle frame are appropriate for operation to -40° C (-40° F).
Power Curve (NPS 100-24) Power Curve (NPS 100-21)
Basic NPS 100 turbine features, beyond those noted above, are a 21 meter rotor for IEC Class II wind
environments and a 24 meter rotor (21 meter rotor blades with blade root extenders) for IEC Class III/s
wind environments. In a suitable wind regime, the NPS 100-24 can generate 10 to 15 percent more
energy per year than the NPS 100-21. Northern Power noted that new full span blades (no blade
extenders) for the NPS 100-24 will be available soon that will boost energy production even further,
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perhaps by additional 12 percent over the present NPS 100-24 configuration. The NPS 100 turbine is
normally available on 23, 30 and 37 meter tubular towers. A future option of a 48 meter lattice tower is
planned.
The generator and rotor of the NPS 100 are directly coupled and rotate at the same speed. By
eliminating the gearbox, Northern Power has simplified the drivetrain design by significantly reducing
the number of moving parts and wear items. This gearless design results in a high reliability turbine with
lower operating costs. The turbine’s relatively simple design allows owners and operators to perform
their own O&M functions (with factory training), saving service calls and increasing wind plant
availability and performance.
The proprietary permanent magnet generator is central to the design of the NPS 100 drivetrain.
Permanent magnet generators offer high efficiency energy conversion, particularly at partial load, and
require no separate field excitation system. Permanent magnet generators are lighter, more efficient,
and require less assembly labor than competing designs.
The Northern Power permanent magnet generator was designed in conjunction with its power
converter to create an optimized solution tailored for high energy capture and low operating costs. The
NPS 100-21 generator is passively cooled directly by the wind with no requirement for auxiliary fans or
air transfer through the generator. The new NPS 100-24 configuration uses active fan cooling to ensure
full system output during the warmer summer months, and/or during extended periods of high energy
production.
A key element of Northern Power’s direct drive wind turbine design is the power converter used to
connect the permanent magnet generator output to the local power system. Northern Power designs
and manufactures power converters for its wind turbines in-house, with complete hardware, control
design, and software capabilities.
In 2006, the American Wind Energy Association (AWEA) awarded its annual Technical Achievement
Award to Northern Power’s Chief Engineer, Jeff Petter. It recognized his expertise and leadership in the
development of Northern Power Systems’ FlexPhase™ power converter for mega-watt scale wind
turbine applications. The FlexPhase power converter combines a unique, patent-pending circuit design
with a high bandwidth control system to provide unique generator management, power quality, and
grid support features. The FlexPhase converter platform offers a modular approach with a very small
footprint and 20-year design life.
The Northern Power System NPS 100 wind turbine is manufactured by Northern Power Systems in
Barre, Vermont. The NPS 100 turbine is rated at 100 kW, is stall-regulated and operates upwind with
active yaw control, has a direct-drive permanent magnet synchronous generator, comes equipped with
a 21 meter or 24 meter diameter rotor, and is available on 30 and 37 meter tubular steel monopole
towers, or on a 48 meter four-leg lattice tower.
The NPS 100-21 is the most represented village-scale wind turbine in Alaska with a significant number of
installations in the Yukon-Kuskokwim Delta region of the state, and also in Gambell and Savoonga on St.
Lawrence Island. More information can be found at: http://www.northernpower.com/.
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Design class of the NPS 100-21 (21 meter rotor) is IEC (International Electrotechnical Commission) Class
II-A (air density 1.225 kg/m3, average wind speed below 8.5 m/s, and 50-year peak gust below 59.5 m/s).
Northern Power Systems 100 wind turbines, Toksook Bay, Alaska
Vestas V20 and V17
The Vestas V20 and V17 wind turbines were originally manufactured by Vestas Wind Systems A/S in
Denmark and are no longer in production. They are, however, available as remanufactured units from
Halus Power Systems in California (represented in Alaska by Marsh Creek, LLC). The V20 is similar to the
V17 but designed for lower wind speed environments. The drivetrain and control system of the two
turbines are identical, but the V20 is equipped with dissimilar rotor blades (not just blade root
extenders) from the V17. The V20 and V17 turbines are equipped fixed-pitch, stall-regulated rotor
coupled to asynchronous (induction) generators via gearbox drives. The original turbine designs
included low speed and high speed generators in order to optimize performance at low and high wind
speeds. The two generators are connected to the gearbox with belt drives and a clutch mechanism. In
some installations though – especially sites with a high mean wind speeds – the low speed generator is
removed to eliminate a potential failure point.
Vestas V20 Vestas V17
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Vestas began mass production of wind turbines in the mid 1980’s with a 55 kW model. Thousands of
Vestas turbines were installed in California in the 1980’s and most of these turbines are still
operational. Vestas is the largest wind turbine manufacturer in the world and the only major Danish
pioneer wind turbine manufacturer still in business. Although the sub-megawatt Vestas turbine models
offered by Halus Power have not been manufactured for a number of years, Vestas still sells new parts
for these units, enabling easier operations and maintenance than with turbines from manufacturers
who no longer in business.
For the fixed pitch V17 and V20, Halus manufactures an after-market controllers as replacements for
Vestas’ original turbine controllers. Unlike PLC-based controllers with generic PLC’s designed for a wide
variety of industrial control systems, Halus’ microprocessor-based controllers are designed specifically
for stall-regulated wind turbines. As a result, according to Halus, the new controllers enable more
functionality and are easier to troubleshoot than a PLC-based controller. Some of the controller
features:
Advanced soft-start motor control with user-definable thyristor trigger angle and cut-in slope
Automatic motor start support for two-generator (low speed/high speed) designs, common on
many wind turbines
Power factor control including user-definable delay for capacitor connection and capacitor
discharging time
User-definable grid frequency, voltage, and current ranges
Remote monitoring and control system (similar to SCADA systems used by wind farm operators)
Optional relay protection system to meet utility interconnection IEEE standards
Pre-mounted on galvanized steel stand to minimize labor time in the field
If desired by the client, Halus offers remote monitoring and control of their turbine models (the turbine
can be accessed by the customer as well). Some of the available remote functions are: monitoring of
voltage, current, power, energy, frequency, wind speed, generator and rotor rpm, temperature, and
system status, modification of controller limits, sending commands to the turbine, reading and resetting
the error list, and generating power curves. This type of functionality may be more suitable, however,
may be more suitable for utility-connected stand-alone turbines that for isolated grid applications.
Remanufactured Vestas turbines installed in cold climates are equipped with heaters controlled by
digital temperature controllers that have network connectivity options, extra insulation of components,
and application of black coatings to absorb heat.
Tower options include tubular, lattice, tower extensions, and custom colors. For remote locations
where turbine erection by crane is not possible, tilt-up installation is possible on select turbine models.
Additionally, customer logos on the turbine nacelle cover or (tubular) tower are possible. The logos are
high-quality outdoor vinyl with ten-plus year life.
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Vestas V17 wind turbines in Kokhanok, Alaska
Cold Climate Considerations of Wind Power
Kivalina’s harsh climate condition is an important consideration should wind power be developed in the
community. The principal challenges with respect to turbine selection and subsequent operation is
severe cold and icing. Many wind turbines in standard configuration are designed for a lower operating
temperature limit of -4° C (-20° F), which clearly would not be suitable for Kivalina. A number of wind
turbine manufacturers offer their turbine in an “arctic” configuration which includes verification that
structural and other system critical metal components are fatigue tested for severe cold capability
and/or a proven history of extensive cold climate operations. In addition, arctic-rated turbines are fitted
with insulation and heaters in the nacelle and power electronics space to ensure proper operating
temperatures. With an arctic rating, the lower temperature operating limit generally extends to -40° C (-
40° F). On occasion during winter Kivalina may experience temperatures colder than -40° C which would
signal the wind turbines to curtail. Temperatures below -40° C are relatively infrequent however and
when they do occur, are generally accompanied by lighter winds.
A second aspect of concern regarding Kivalina’s arctic climate is icing conditions. Atmospheric icing is a
complex phenomenon characterized by astonishing variability and diversity of forms, density, and
tenacity of frozen precipitation, some of which is harmless to wind turbine operations and others highly
problematic. Although highly complex, with respect to wind turbines five types of icing are recognized:
clear ice, rime ice, mixed ice, frost ice, and SLD ice (www.Wikipedia.org/wiki/icing_conditions). Rime
would not be expected at the sea-level Wulik River site, but possibly may occur to a limited extent on
Kisimigiuktuk Hill.
Clear ice is often clear and smooth. Super-cooled water droplets, or freezing rain, strike a
surface but do not freeze instantly. Forming mostly along the stagnation point on an airfoil, it
generally conforms to the shape of the airfoil.
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Rime ice is rough and opaque, formed by super-cooled drops rapidly freezing on impact. Often
"horns" or protrusions are formed and project into the airflow.
Mixed ice is a combination of clear and rime ice.
Frost ice is the result of water freezing on unprotected surfaces. It often forms behind deicing
boots or heated leading edges of an airfoil and has been a factor airplane crashes.
SLD ice refers to ice formed in super-cooled large droplet (SLD) conditions. It is similar to clear
ice, but because droplet size is large, it often extends to unprotected parts of a wind turbine (or
aircraft) and forms large ice shapes faster than normal icing conditions.
SLD ice on an airplane
Wind-Diesel HOMER Model, Kivalina
Considering AVEC’s goal of displacing as much diesel fuel for electrical generation as possible and yet
recognizing the present limitations of high penetration wind power in Alaska and AVEC’s desire to
operate a highly stable and reliable electrical utility in Kivalina, only the medium penetration wind-diesel
configuration scenario was modeled with HOMER software. Note that low penetration wind was not
modeled as this would involve use of smaller farm-scale turbines that are not designed for severe cold
climates, and low penetration would not meet AVEC’s goal of significantly displacing fuel usage in
Kivalina.
As previously noted, a medium penetration wind-diesel configuration is a compromise between the
simplicity of a low penetration wind power and the significant complexity and sophistication of the high
penetration wind. With medium penetration, instantaneous wind input is sufficiently high (at 100 plus
percent of the village electrical load) to require a secondary or diversion load to absorb excess wind
power, or alternatively, to require curtailment of wind turbine output during periods of high wind/low
electric loads. For Kivalina only, appropriate wind turbines for medium wind penetration are generally
in the 100 to 300 kW range with more numbers of turbines required for lower output machines
compared to larger output models.
There are a number of comparative medium penetration village wind-diesel power systems presently in
operation in Alaska. These include the AVEC villages of Toksook Bay, Chevak, Savoonga, Kasigluk,
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Hooper Bay, among others. All are characterized by wind turbines directly connected to the AC
distribution system. AC bus frequency control during periods of high wind penetration, when diesel
governor control would be insufficient, is managed by the sub-cycle, high resolution, and fast-switching
capability of the secondary load controller (SLC). Ideally, the SLC is connected to an electric boiler
serving a thermal load as this will enhance overall system efficiency by augmenting the operation of the
fuel oil boiler(s) serving the thermal load.
Kivalina Powerplant
AVEC powerplant configuration information indicates that four diesel generators are in use, as
presented in the table below. Should the village relocate to the Kisimigiuktuk Hill area, it is possible that
new diesel generators would be installed in the new powerplant. Given the likelihood of an upgraded
powerplant for Kivalina prior to development of wind power, diesel generator fuel consumption is
modeled as equivalent for all four units for this study.
Diesel generator HOMER modeling information
Diesel generator DD S60D3 Cat D353 CMS LTA10 DD S60K4
Power output (kW)229 337 250 363
Intercept coeff. (L/hr/kW)0.04 0.04 0.04 0.04
Slope (L/hr/kW output) 0.22 0.22 0.22 0.22
Minimum electric
load (%)
15.0%
(35kW)
15.0%
(51 kW)
15.0%
(37 kW)
15.0%
(55 kW)
Heat recovery ratio (% of
generator waste heat energy
available to serve the thermal
load; when modeled)
35 35 35 35
Notes: Intercept coefficient – the no-load fuel consumption of the generator divided by its capacity
Slope – the marginal fuel consumption of the generator
Electric Load
AVEC monitors Kivalina with a data logger that records energy demand on 15 minute intervals. With
some data processing, Homer can import this data as hourly or 15 minute data points. For this report,
the 15 minute interval was used as it is more granular than hourly. Data interval obtained from AVEC
was December 23, 2012 to December 29, 2013. Additionally, data from August 17, 2012 to August 24,
2012 was used as most data of that time period in 2013 was missing due to a telephone
communications problem in Kivalina. Excel software was used to combine the data into a
representative year for transfer to Homer software.
Kivalina 15 min. interval electric load data from AVEC
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Kivalina electric load data
Baseline Scaled
Average (kWh/d) 3,553 3,553
Average (kW) 148 148
Peak (kW) 362 283
Load factor 0.523 0.523
Thermal Load
At present, there is not an operational recovered heat system in Kivalina, hence thermal loads are not
modeled. Jacket water heat is dissipated to the atmosphere by the radiators in the powerplant. Should
wind turbines be installed at the Wulik River site to serve Kivalina in its present location, excess wind
energy could be diverted to thermal loads such as the school or water plant via a secondary load
controller and electric boiler configured as a remote node. The thermal load demand of these facilities,
however, is unknown at present. Should the village of Kivalina be re-located to the Kisimigiuktuk Hill site
area, presumably the new powerplant would be constructed with recovered heat capability to serve
thermal energy demand in the new community, but estimating that load is beyond the scope of this
report.
Wind Turbine Configuration Options
AVEC’s goals with their wind-diesel systems is to offset a significant percentage of fuel used in the
powerplant, but not create a highly complex system with significant thermal offset and/or electrical
storage capability. This philosophy dictates a medium penetration design approach where wind power
is approximately one-third of the annual electric energy demand, but at least one diesel generator is
always online to provide spinning reserve. Medium penetration design, though, means that
instantaneous wind power will at times be well over 100 percent of the load. This may result in unstable
grid frequency, which can occur when electrical power generated exceeds the load demand. In a wind-
diesel power system without electrical storage, there are two options to prevent this possibility:
1. Curtail one or more wind turbines to prevent instantaneous wind penetration from exceeding
100 percent (one must also account for minimum loading of the diesel generator).
2. Install a secondary load controller with a resistive heater. The secondary load controller is the
fast-acting switching mechanism commanding heating elements to turn on and off to order to
maintain stable frequency. The resistive heater can be as simple as a heater ejecting energy to
the atmosphere or an interior air space or, more desirably, a boiler serving one or more thermal
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loads. The boiler can be installed in the powerplant heat recovery loop and operated in parallel
with fuel oil boilers.
In either case, system frequency control features are necessary in medium penetration design as,
generally speaking, the diesel generator paralleled with the wind turbines during periods of high wind
energy input may not have sufficient inertia to control frequency by itself. This design philosophy is
typical of most wind-diesel systems presently operational in Alaska and provides a solid compromise
between the minimal benefit of low penetration wind systems and the cost and complexity of high
penetration wind systems.
Many utilities prefer to install more than one wind turbine in a village wind power project to provide
redundancy and continued renewable energy generation should one turbine be out-of-service for
maintenance or other reasons. Referencing the medium wind power penetration design philosophy
discussed above, the Northern Power NPS 100 and the Vestas V17 and V20 turbines are considered for a
Kivalina-based wind power project. Turbine types are not mixed, however, as it is assumed that AVEC
will select only one type of wind turbine.
System Modeling and Technical Analysis
Installation of wind turbines in medium penetration mode is evaluated in this report to demonstrate the
economic impact of these turbines with the following configuration philosophy: turbines are connected
to the electrical distribution system to serve the electrical load and a secondary load controller and an
electric heater or boiler to divert excess electrical power to offset thermal load(s) via a secondary load
controller.
HOMER energy modeling software was used to analyze the Kivalina power generation system. HOMER
was designed to analyze hybrid power systems that contain a mix of conventional and renewable energy
sources, such as diesel generators, wind turbines, solar panels, batteries, etc. and is widely used to aid
development of Alaska village wind power projects. The following wind-diesel system configurations
were modeled for this conceptual design report.
Modeled wind-diesel configurations
Site Turbine
No.
Turbines
Installed
kW Tower Type
Hub Height
(meters)
Wulik River
Northern Power
NPS 100-24 2 200 Monopole 37
Vestas V20 2 240 Monopole 30
Kisimigiuktuk Hill
Northern Power
NPS 100-21
2 200 Monopole 37 3 300
Vestas V17 2 180 Monopole 30 3 270
Modeling assumes that wind turbines constructed in Kivalina would operate in parallel with the diesel
generators. Although excess energy will serve thermal loads via a secondary load controller and electric
boiler that would augment the existing jacket water heat recovery system, it is not modeled as such to
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conform to AEA’s methods with use of the ISER cost model spreadsheet. Installation cost of this turbine
project assumes three-phase upgrade of the distribution system to the wind turbine site.
Technical modeling assumptions
Operating Reserves
Load in current time step 10%
Wind power output 50% (diesels always on)
Fuel Properties (no. 2 diesel for
powerplant)
Heating value 46.8 MJ/kg (140,000 BTU/gal)
Density 830 kg/m3 (6.93 lb./gal)
Fuel Properties (no. 1 diesel to serve
thermal loads)
Heating value 44.8 MJ/kg (134,000 BTU/gal)
Density 830 kg/m3 (6.93 lb./gal)
Diesel Generators
Efficiency 13.6 kWh/gal (FY2013 PCE report data)
Minimum load 15%
Schedule Optimized
Wind Turbines
Net capacity factor 85% (adjusted by reducing mean wind speed in Homer
software)
Turbine hub height 37 m (NPS 100); 30 m (V20 and V17)
Wind speed – Wulik River 5.84 m/s at 30 m level at met tower site; wind speed scaled
to 5.26 m/s for 85% turbine net AEP
Wind speed – Kisimigiuktuk Hill 8.01 m/s at 30 m level at met tower site; wind speed scaled
to 6.70 m/s for 85% turbine net AEP
Density adjustment Density not adjusted (i.e., STP turbine power curves)
Energy Loads
Electric 3,467 kWh/day mean annual electrical load
Thermal Not modeled but possible with remote node to absorb
excess energy
Fuel oil boiler efficiency 85%(not modeled)
Electric boiler efficiency 100%
Model Results – Wulik River Site
The Wulik River site wind resource is nearly identical to that measured by the met tower. This site likely
is not height restricted, hence large wind turbines and/or high hub heights are possible, although given
Kivalina’s modest electric load, turbines larger than 100 kW class are considered impractical at the
present time. Note that turbine energy production is modeled at 85 percent net.
Northern Power NPS 100-24, two (2) turbines
This configuration models two Northern Power NPS 100-24 wind turbines at Wulik River site at a 37
meter hub height and generating 85 percent of maximum annual energy production.
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Two NPS 100-24’s, Wulik River, 37 m hub height, 85% net AEP
Chart, two NPS 100-24 turbines, Wulik River
Vestas V20, two (2) turbines
This configuration models two Northern Power NPS 100-24 wind turbines at Wulik River site at a 37
meter hub height and generating 85 percent of maximum annual energy production.
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Two V20’s, Wulik River, 30 m hub height, 85% net AEP
Chart, two V20 turbines, Wulik River
Model Results – Kisimigiuktuk Hill Site
The projected wind resource at the top of Kisimigiuktuk Hill was modeled with WAsP software and
transferred to Homer software for wind-diesel energy balance modeling. Compared to the Wulik River
site, turbine options were modified to the NPS 100-21 and the V17, both of which are more suitable for
0
20
40
60
80
100
120
140
1 2 3 4 5 6 7 8 9 10 11 12Energy, MWhElectric Load Turbine Energy Excess Energy to Thermal
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the presumed high energy, potentially IEC 61400-1 Class I or II wind resource at the top of Kisimigiuktuk
Hill. Note that turbine energy production is modeled at 85 percent net.
Northern Power NPS 100-21, two (2) turbines
This configuration models two Northern Power NPS 100-21 wind turbines at Kisimigiuktuk Hill at a 37
meter hub height and generating 85 percent of maximum annual energy production.
Two NPS 100-21’s, Kisimigiuktuk Hill, 37 m hub height, 85% net AEP
Chart, two NPS 100-21 turbines, Kisimigiuktuk Hill
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Northern Power NPS 100-21, three (3) turbines
This configuration models three Northern Power NPS 100-21 wind turbines at Kisimigiuktuk Hill at a 37
meter hub height and generating 85 percent of maximum annual energy production.
Three NPS 100-21’s, Kisimigiuktuk Hill, 37 m hub height, 85% net AEP
Chart, three NPS 100-21 turbines, Kisimigiuktuk Hill
Month
Electric
Load
Turbine
Energy
Energy
Generated
Turbine
Energy to
E. Load
Wind
Penetra-
tion
Excess
Energy to
Thermal
Excess
Energy to
Thermal
kWh kWh kWh kWh % kWh %
1 130,706 59,770 150,707 39,769 39.7% 20,001 9.0%
2 120,024 98,997 154,071 64,950 64.3% 34,047 16.8%
3 122,140 93,716 157,236 58,620 59.6% 35,096 16.5%
4 116,441 66,643 140,705 42,378 47.4% 24,264 11.6%
5 105,313 81,917 134,043 53,187 61.1% 28,730 15.9%
6 76,898 66,229 106,808 36,319 62.0% 29,910 19.5%
7 79,555 68,175 110,948 36,783 61.4% 31,392 18.4%
8 88,480 74,038 119,521 42,998 61.9% 31,041 18.5%
9 102,637 104,225 148,009 58,852 70.4% 45,373 23.8%
10 115,766 87,886 146,394 57,258 60.0% 30,628 14.9%
11 118,042 97,046 150,343 64,745 64.6% 32,301 16.2%
12 120,850 136,007 180,738 76,118 75.3% 59,889 26.6%
Annual 1,296,852 1,034,650 1,699,523 631,979 60.9% 402,671 17.3%
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Vestas V17, two (2) turbines
This configuration models two Northern Power NPS 100-24 wind turbines at Wulik River site at a 37
meter hub height and generating 85 percent of maximum annual energy production.
Two V17’s, Kisimigiuktuk Hill, 30m hub height, 85% net AEP
Chart, two V17 turbines, Kisimigiuktuk Hill
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Vestas V17, three (3) turbines
This configuration models two Northern Power NPS 100-24 wind turbines at Wulik River site at a 37
meter hub height and generating 85 percent of maximum annual energy production.
Three V17’s, Kisimigiuktuk Hill, 30m hub height, 85% net AEP
Chart, three V17 turbines, Kisimigiuktuk Hill
Month
Electric
Load
Turbine
Energy
Energy
Generated
Turbine
Energy to
E. Load
Wind
Penetra-
tion
Excess
Energy to
Thermal
Excess
Energy to
Thermal
kWh kWh kWh kWh % kWh %
1 130,706 47,860 144,234 34,332 33.2% 13,528 6.6%
2 120,024 80,951 142,439 58,536 56.8% 22,415 12.1%
3 122,140 74,401 145,083 51,457 51.3% 22,943 11.7%
4 116,441 53,385 132,329 37,497 40.3% 15,888 8.2%
5 105,313 61,766 120,877 46,202 51.1% 15,564 9.7%
6 76,898 50,004 96,628 30,274 51.7% 19,729 14.0%
7 79,555 51,550 100,987 30,118 51.0% 21,432 13.7%
8 88,480 55,580 107,731 36,330 51.6% 19,250 12.5%
9 102,637 82,665 132,857 52,444 62.2% 30,221 17.2%
10 115,766 68,193 135,875 48,085 50.2% 20,109 10.6%
11 118,042 76,521 138,029 56,533 55.4% 19,988 11.0%
12 120,850 113,585 164,920 69,515 68.9% 44,070 21.2%
Annual 1,296,852 816,461 1,561,990 551,323 52.3% 265,138 12.4%
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Economic Analysis
Modeling assumptions are detailed in the table below. Many assumptions, such as project life, discount
rate, operations and maintenance (O&M) costs, etc. are AEA default values. Other assumptions, such as
diesel overhaul cost and time between overhaul are based on general rural Alaska power generation
experience. The base or comparison scenario is the Kivalina powerplant with its present configuration
of diesel generators and the existing thermal loads connected to the heat recovery loop.
Fuel Cost
A fuel price of $6.11/gallon was chosen for the economic analysis by reference to Alaska Fuel Price
Projections 2013-2035, prepared for Alaska Energy Authority by the Institute for Social and Economic
Research (ISER), dated June 30, 2013 and the 2013_06_R7Prototype_final_07012013 Excel spreadsheet,
also written by ISER. This price reflects the average value of all fuel prices between the 2016 (the
assumed project start year) fuel price of $5.00/gallon and the 2035 (20 year project end year) fuel price
of $7.26/gallon using the medium price projection analysis with an average CO2-equivalent allowance
cost of $0.59/gallon included.
By comparison, the fuel price for Kivalina reported to Regulatory Commission of Alaska for the 2013 PCE
report is $4.17/gallon, without inclusion of the CO2-equivalent allowance cost. Assuming a CO2-
equivalent allowance cost of $0.40/gallon (ISER Prototype spreadsheet, 2013 value), the 2013 Kivalina
fuel price was $4.57/gallon.
Heating fuel displacement by excess energy diverted to thermal loads is valued at $7.16/gallon as an
average price for the 20 year project period. This price was determined by reference to the
2013_06_R7Prototype_final_07012013 Excel spreadsheet where heating oil is valued at the cost of
diesel fuel (with CO2-equivalent allowance cost) plus $1.05/gallon, assuming heating oil displacement
between 1,000 and 25,000 gallons per year.
Kivalina fuel cost table, CO2-equivalent allowance cost included
ISER med. projection
2015 (/gal) 2034 (/gal)
Average
(/gallon)
Diesel Fuel $5.00 $7.26 $6.11
Heating Oil $6.05 $8.31 $7.16
Wind Turbine Project Costs
Construction cost for wind turbine installation and integration with the diesel power plant will be
accurately defined during the design phase of the project. Project costs are estimated in this conceptual
design report in order to provide comparative valuation. The Wulik River and Kisimigiuktuk Hill site
options are presented separately, both with start years of 2016. It is recognized, however, that although
possible for Wulik River, re-locating the village of Kivalina to Kisimigiuktuk Hill and initiating a wind
project by 2016 is unrealistic. But, for purposes of comparative consistency, 2016 is retained as the
project start date for the Kisimigiuktuk Hill site option.
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Economic modeling assumptions
Economic Assumptions
Project life 20 years (2016 to 2035)
Discount rate for NPV 3% (ISER spreadsheet assumption)
System fixed capital cost (plant
upgrades required to accommodate
wind turbines)
Included in turbine project cost
Fuel Properties (no. 2 diesel for
powerplant)
Price (20 year average; ISER 2013,
medium projection plus social cost of
carbon)
$6.11/gal
Fuel Properties (no. 1 diesel to serve
thermal loads)
Price (20 year average; ISER 2013,
medium projection plus social cost of
carbon)
$7.16/gal
Diesel Generators
Generator capital cost $0 (already installed)
O&M cost $0.02/kWh (ISER spreadsheet assumption)
Efficiency 13.6 kWh/gal (Homer model)
Wind Turbines
Net capacity factor 85% (adjusted by reducing mean wind speed in Homer
software)
O&M cost $0.049/kWh (ISER spreadsheet assumption)
Wind Turbine Project Costs, Wulik River Site
Wind Turbine Project Costs, Kisimigiuktuk Hill Site
Economic Model Results
Economic benefit-to-cost is shown by the ISER method. This method does not account for heat loss
from the diesel engines due to reduced loading and subsequent impact on heating fuel usage to serve
the thermal loads. ISER cost modeling assumptions are noted above or are discussed in the
2013_06_R7Prototype_final_07012013 Excel spreadsheet. Net annual energy production of the wind
Config-
uration
No.
Turbs Turbine Freight Install Civil
Distribu-
tion
Power-
plant
Project
Cost
Cost/
kW
NPS 100-
24 2 200 0.70 0.40 0.80 1.00 0.70 0.20 3.80 19,000
Vestas
V20 2 240 0.28 0.30 0.70 1.00 0.70 0.20 3.18 13,300
Wind
Capacity
(kW)
Estimated Cost (in $millions)
Config-
uration
No.
Turbs Turbine Freight Install Civil
Distribu-
tion
Power-
plant
Project
Cost
Cost/
kW
2 200 0.66 0.40 0.60 0.70 0.30 0.10 2.76 13,800
3 300 0.99 0.60 0.85 0.95 0.30 0.10 3.79 12,600
2 180 0.26 0.30 0.55 0.65 0.30 0.10 2.16 12,000
3 270 0.39 0.45 0.80 0.80 0.30 0.10 2.84 10,500
NPS 100-
21
Vestas
V17
Wind
Capacity
(kW)
Estimated Cost (in $millions)
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turbines was assumed at 85 percent to reflect production losses due to operations and maintenance
down time, icing loss, wake loss, hysteresis, etc.
As one can in the tables below, it is anticipated that developing wind power at the Kisimigiuktuk Hill site
has a significant economic advantage over development of the Wulik River site. This is readily
understandable from the higher (projected) wind speeds and lower project development costs at the
Kisimigiuktuk Hill site compared to Wulik River. But, this presupposes that an access road to
Kisimigiuktuk Hill is developed and that the residents of Kivalina commit to moving their village to the
slopes of Kisimigiuktuk Hill. The Kisimigiuktuk Hill site electrical distribution connection, for instance, is
assumed to be the short distance from the Kisimigiuktuk Hill site to the planned new village location on
the east slope of the hill, not the seven mile distance to the existing village location on the barrier island.
Economic valuation table, Wulik River site
Economic valuation table, Kisimigiuktuk Hill site
Red Dog Port-based Wind Power Project
This section assesses the possibility of a wind power project based at Port of Red Dog with the port as
the major electrical energy load and Kivalina served via an intertie, which must be constructed. A
WHPacific and V3 Energy, LLC report titled Red Dog Port to Kivalina Transmission Line was submitted to
Alaska Village Electric Cooperative in May 2014. This report details right of way considerations, required
environmental documentation, power needs and alternatives, and permitting requirements for
construction of an electrical intertie connecting Kivalina, 25 miles distant, from Red Dog Port. In this
scenario, all electric power – diesel and wind-generated – would be located at Red Dog Port and
supplied to Kivalina. The Kivalina powerplant would no longer function as a primary generating station
and would be transitioned to a standby facility for use in the event of loss of power from Red Dog Port.
Given the larger electrical load at Red Dog Port and its industrial nature and greater support, larger wind
turbines are possible. This is advantageous as larger wind turbines generally are lower cost per kilowatt
Config-
uration
Project
Cost
NPV
Benefits
NPV
Costs B/C
NPS 100-
24 200 3.80 2.60 3.38 0.77 32,371 2,165 34,536
Vestas
V20 240 3.18 1.98 2.83 0.70 26,698 2,031 28,729
Diesel
Fuel
Saved
(gal/yr)
Wind
Turbine
Capacity
(kW)
Heating
Oil Saved
(gal/yr)
Petroleum
Fuel
Saved
(gal/yr)
(in $ millions)
Config-
uration
Project
Cost
NPV
Benefits
NPV
Costs B/C
200 2.76 3.34 2.45 1.36 40,127 3,887 44,014
300 3.79 5.25 3.37 1.56 65,865 3,887 69,752
180 2.16 2.51 1.92 1.31 34,331 2,154 36,485
270 2.84 3.37 2.52 1.34 41,144 6,778 47,921
NPS 100-
21
Vestas
V17
Diesel
Fuel
Saved
(gal/yr)
Heating
Oil Saved
(gal/yr)
Petroleum
Fuel
Saved
(gal/yr)
(in $ millions)
Wind
Turbine
Capacity
(kW)
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of installed capacity. This is due to the cost of the turbine itself and also lower costs for foundations,
roads and pads, distribution connections, and overall construction time.
Wind Resource Assessment – Red Dog Port
A 33 meter Rohn lattice-type communications tower at Red Dog Port was equipped with wind
measurement sensors in 2008 and data was collected for a 34 month period. The Rohn tower, located
about two miles inland from the coast on the connecting road to Red Dog Mine, is near the primary
prospective wind turbine site and was outfitted with sensors as a substitute for erection of a met tower.
The complete Red Dog Port wind resource report, dated September 2011, is included in Appendix B of
this report.
Met tower data synopsis
Data dates October 10, 2008 to August 10, 2011 (34 months)
Wind power class Class 4 to 5 (good to excellent)
Wind power density mean, 33 m 574 W/m2
Wind speed mean, 33 m 6.05 m/s
Max. 10-min wind speed average 38.5 m/s
Maximum 2-sec. wind gust 43.5 m/s (January, 2009)
Weibull distribution parameters k = 1.24, c = 6.52 m/s
Wind shear power law exponent 0.180 (moderate)
Roughness class 0.73 (lawn grass)
IEC 61400-1, 3rd ed. classification Class II-C
Turbulence intensity, mean 0.119 (at 15 m/s)
Calm wind frequency (at 33 m)45% (< 4 m/s)
Data Recovery
Data quality was very good with data recovery of all four anemometers greater than 96 percent and
data recovery of the wind vane greater than 95 percent. Data loss is limited to winter months only and
is attributable to icing events which are characterized by non-variant output of the anemometer at the
minimum offset value (essentially zero) and by non-variant output of the direction vane at the last
operable direction with temperatures near or less than zero degrees Centigrade and relative humidity at
or near 100 percent.
Wind Speed
Anemometer data obtained from the Red Dog Port communications tower, from the perspectives of
both mean wind speed and mean wind power density, indicate an excellent wind resource. Mean wind
speeds are greater at higher elevations on the tower, as one would expect. Note that cold temperatures
contributed to a higher wind power density than otherwise might have been expected for the mean
wind speeds. Also note, as discussed in the previous section, that anemometer summary information is
the table below is post gap-fill. Non-gap-filled mean wind speeds and power densities are slightly higher
than below.
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Anemometer data summary
Variable
Speed 33 m
A
Speed 33 m
B
Speed 21 m
A
Speed 21 m
B
Measurement height (m) 33 33 21 21
Mean annual wind speed (m/s) 6.02 6.02 5.71 5.68
Max 10-min avg wind speed (m/s) 38.5 36.7 36.1 34.4
Max gust wind speed (m/s) 43.5 41.8 42.0 40.5
Weibull k 1.24 1.26 1.28 1.31
Weibull c (m/s) 6.52 6.52 6.22 6.21
Mean wind power density (W/m²) 577 529 467 435
Mean energy content (kWh/m²/yr) 5,050 4,634 4,093 3,810
Energy pattern factor 4.08 3.75 3.89 3.66
Frequency of calms (%) 44.5 43.3 45.9 44.9
1-hr autocorrelation coefficient 0.945 0.942 0.941 0.940
Diurnal pattern strength 0.046 0.041 0.066 0.062
Hour of peak wind speed 15 15 15 15
MMM = mean of monthly means
Time series calculations indicate high mean wind speeds during the winter months with more moderate
mean wind speeds during summer months. This correlates well with the a typical village load profile
where winter months have a high electric and heat demand and summer months a lesser demand. The
opposite load profile exists however at Red Dog Port where summer loads are high and winter low.
Wind speed profile
Wind Rose
Wind frequency rose data indicates that winds at Red Dog Port are highly directional, with northeasterly
and southeasterly wind predominating. The mean value rose indicates that southeasterly winds, when
they do occur, are of high energy and hence likely storm winds. The wind energy rose indicates that for
wind turbine operations power-producing winds are very strongly southeastern dominant. Calm
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frequency (percent of time that winds at the 33 meter level are less than 4 m/s) was a very high 45
percent during the met tower test period.
Wind frequency rose Wind energy rose
Turbulence Intensity
Turbulence intensity (TI) at the Red Dog Port test site is well within acceptable standards with an IEC
61400-1, 3rd edition (2005) classification of turbulence category C, which is the lowest defined. The
mean TI at 15 m/s is 0.069 and the representative TI at 15 m/s is 0.096, both which can be considered
extraordinarily low and hence very desirable for wind turbine operations.
Turbulence intensity, 33m B, all direction sectors
Extreme Winds
A modified Gumbel distribution analysis, based on monthly maximum winds vice annual maximum
winds, was used to predict extreme winds at Red Dog Port. Due to the unusual seasonal variation in
wind speeds at the site and in an effort to better match the monthly data Gumbel approach to the
annual data approach, a modification to the analysis was made to exclude May through September
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data. Note below that the extreme wind analysis shows relatively energetic extreme wind probability
compared to measured mean wind speed.
Extreme wind probability table, 33 m A data
Vref Gust IEC 61400-1, 3rd ed.
Period (years) (m/s) (m/s) Class Vref, m/s
3 33.4 38.7 I 50.0
10 37.3 43.2 II 42.5
20 39.5 45.8 III 37.5
30 40.8 47.3 S designer-
specified5042.4 49.2
100 44.6 51.7
Red Dog Port Wind Site Options
A likely and hence presumed wind turbine site at Red Dog Port is an exposed outcropping of rock and
gravel a short distance west of the communication tower that served as a met tower for the Red Dog
Port wind resource study. The advantage of this site is that it is a very short distance from the Red Dog
mine-port road, it would have minimal impact to tundra, and a relatively short distribution line upgrade
is required. Other sites in the port area are possible though.
Red Dog Port wind site option
WAsP Modeling
WAsP software modeling indicates relatively consistent winds across the port area with the exposed
rock and gravel outcroppings both east and west of the communication tower wind reference point (Red
Prospective RDP
wind turbine site
Wind data site
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Dog port Site 9476 placemark) as slightly better wind resource than the lower-lying terrain surrounding
them. Wind speeds are higher, however, on the eroded mountains and hills east of the port, but
installing wind turbines in this area is somewhat impractical. Note that the vertical blue and green line
in the image below is an artifact of merging two digital elevation maps for use by WAsP software.
WAsP wind speed overlay, Red Dog Port area
Wind Turbine Option, Red Dog Port
For the option of wind turbines at Red Dog Port that supplies power to both Red Dog Port and Kivalina,
the EWT DW 52-900 is evaluated in this report, although other wind turbines such as the 750 kW
Aeronautica AW 750 and the 500 kW Vestas V39 and 600 kW Vestas V44 are highly suitable as well.
Should a wind project based at Red Dog Port proceed, additional analysis to include these other turbines
should be considered.
EWT DW 52-900
The DW 52/54-900 is a direct-drive, pitch-regulated wind turbine with a synchronous generator and
inverter-conditioned power output. More information regarding the EWT DW 52/54-900 wind turbine is
attached and available on EWT’s website: http://www.ewtdirectwind.com/. The turbine boasts a track
record of over 400 operating turbines in many different wind climates. At present, five DW 900 turbines
have been installed in Alaska: one in Delta Junction, two in Kotzebue and two in Nome. For Red Dog
Port, the 52 meter rotor version likely would be most optimal.
Type DW 54 / DW 52
Rotor diameter 54.0 m / 51.5 m
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Variable Rotor Speed 12 to 28 rpm
Nominal Power Output 900 kW
Cut-in wind speed 2.5 m/s
Rated wind speed 13 m/s
Cut-out wind speed (10 minute average)25 m/s
Survival wind speed 59.5 m/s
Power output control Pitch controlled variable speed
Type Certificate
IEC 61400 wind class IIIA (DW 54)
IEC 61400 wind class IIA (DW 52)
Drive System
Generator Synchronous air-cooled EWT-design, multi-pole, wound-rotor.
Power converter Full-power, IGBT-controlled AC-DC-AC ‘back-to-back’ type.
Control System
Bachman PLC control system.
Possibility for remote access via TCP / IP internet and the DMS 2.0 * SCADA system.
Tower
Type Conical tubular steel, internal ascent.
Hub heights 40, 50 and 75 meters.
Safety systems
Main brake action Individual rotor blade pitch (three independent brakes).
Fail-safe brake Individual rotor blade pitch by three independent battery-powered back-up units.
EWT DW 52-900 wind turbines in Kotzebue
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Red Dog Port Powerplant
The current redundant power generation capability at Red Dog Port is 1,300 kW. This is comprised of
two 650 kW generators running in parallel with one extra as backup. In order for RDP to provide full
redundancy at the projected output requirement of 2,362 kW peak, two sets of one 1285 kW generator
plus one 650 kW generator running in parallel are required. Hence, one new 1285 kW generator would
be required. Future provisions in the existing distribution equipment exist for this; however, the current-
carrying capacity of the generator paralleling power system is insufficient at 3000 amps.
A total new Red Dog Port station load of 2,362 kW equates to 3,552 amps at 0.80 power factor. The
existing distribution equipment would need to be upgraded to at least 4000 amps with the addition of
the new 1285 kW generator mentioned above. Should the potential addition of mining equipment or
infrastructure become necessary in the future, taking a long range view on the power distribution
equipment would justify upgrading the distribution equipment to 6000 amps now to prevent additional
down time.
Diesel generator HOMER modeling information
Diesel generator Gen 1 Gen 2 Gen 3 Gen 4
Power output (kW)1,285 650 650 650
Intercept coeff. (L/hr/kW)0.04 0.04 0.04 0.04
Slope (L/hr/kW output) 0.22 0.22 0.22 0.22
Minimum electric
load (%)
15.0%
(193 kW)
15.0%
(98 kW)
15.0%
(98 kW)
15.0%
(98 kW)
Notes: Intercept coefficient – the no-load fuel consumption of the generator divided by its capacity
Slope – the marginal fuel consumption of the generator
Electric Load
Red Dog Port electric load data was obtained from Teck Alaska in 2011 for a wind power review project.
Loads may have changed since that time, although it is believed that no major system upgrades have
occurred since 2011, hence the 2011 load profile is modeled as current in this report. Note that counter
to a typical village or city seasonal load profile that has higher loads during the cold winter months,
highest load demand at Red Dog Port occurs during the summer months when the port is ice-free. It is
during this period that the ore is loaded onto barges and ships.
Red Dog Port electric load data from Teck Alaska
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Red Dog Port electric load data
Baseline Scaled
Average (kWh/d) 22,296 22,296
Average (kW) 929 929
Peak (kW) 1,988 1,988
Load factor 0.467 0.467
Shown below is the Red Dog Port electric load profile and Red Dog Port electric load combined with that
of Kivalina. The latter is used in the wind turbine analysis in this section of this report.
Red Dog Port and Kivalina combined electric loads
Red Dog Port-Kivalina combined electric load data
Baseline Scaled
Average (kWh/d) 25,849 25,849
Average (kW) 1,077 1,077
Peak (kW) 2,151 2,151
Load factor 0.501 0.501
Thermal Load
Although Teck Alaska makes extensive use of waste heat from the Red Dog Port powerplant recovered
heat system to supply thermal loads in the facility, these thermal loads are not defined and hence are
not specifically modeled in this report. If wind turbine(s) are installed at Port of Red Dog to serve the
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facility and Kivalina, excess wind energy could be absorbed by the recovered heat loop or be diverted to
a remote thermal load at the Port or in Kivalina.
System Modeling and Technical Analysis
Installation of wind turbines in medium penetration mode is evaluated in this report to demonstrate the
economic impact of these turbines with the following configuration philosophy: turbines are connected
to the electrical distribution system to serve the electrical load and a secondary load controller and an
electric heater or boiler to divert excess electrical power to offset thermal load(s) via a secondary load
controller.
HOMER energy modeling software was used to analyze the Red Dog Port power generation system.
HOMER was designed to analyze hybrid power systems that contain a mix of conventional and
renewable energy sources, such as diesel generators, wind turbines, solar panels, batteries, etc. and is
widely used to aid development of Alaska village wind power projects. The following wind-diesel system
configurations were modeled for this conceptual design report.
Modeled wind-diesel configurations
Site Turbine
No.
Turbines
Installed
kW Tower Type
Hub Height
(meters)
Red Dog Port EWT DW 52-900 1 900 Monopole 75
EWT DW 52-900 2 1,800 Monopole 75
Modeling assumes that wind turbines constructed in Kivalina would operate in parallel with the diesel
generators. Although excess energy will serve thermal loads via a secondary load controller and electric
boiler that would augment the existing jacket water heat recovery system, it is not modeled as such to
conform to AEA’s methods with use of the ISER cost model spreadsheet. Installation cost of this turbine
project assumes three-phase upgrade of the distribution system to the wind turbine site.
Technical modeling assumptions
Operating Reserves
Load in current time step 10%
Wind power output 50% (diesels always on)
Fuel Properties (no. 2 diesel for
powerplant)
Heating value 46.8 MJ/kg (140,000 BTU/gal)
Density 830 kg/m3 (6.93 lb./gal)
Fuel Properties (no. 1 diesel to serve
thermal loads)
Heating value 44.8 MJ/kg (134,000 BTU/gal)
Density 830 kg/m3 (6.93 lb./gal)
Diesel Generators
Efficiency 13.8 kWh/gal (Homer model)
Minimum load 15%
Schedule Optimized
Wind Turbines
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Net capacity factor 90% (adjusted by reducing mean wind speed in Homer
software)
Turbine hub height 75 meters
Wind speed 6.02 m/s at 33 m level at met tower site; wind speed scaled
to 5.60 m/s for 90% turbine net AEP
Power law exponent 0.123
Density adjustment Density not adjusted (i.e., STP turbine power curves)
Energy Loads
Electric 25,849 kWh/day mean annual electrical load
Thermal Not modeled but possible with remote node to absorb
excess energy
Fuel oil boiler efficiency 85%(not modeled)
Electric boiler efficiency 100%
Model Results – Red Dog Port
The wind resource at the presumed Red Dog Port wind turbine site is nearly identical to that measured
on the nearby communications tower. This site will not be height restricted, hence large wind turbines
and/or high hub heights are possible. Note that the DW 52-900 annual energy production is modeled at
90 percent net compared to 85 percent net for the NPS 100 and Vestas turbines in the Kivalina only
option. This is due to the sophistication of the larger EWT turbine and a presumed enhanced
operational focus of a wind turbine at an industrial facility compared to a village setting.
EWT DW 52-900, one (1) turbine, 75 m hub height, 90% net AEP
This configuration models one EWT DW 52-900 wind turbine at Red Dog Port (prospective site) at a 75
meter hub height and generating 90 percent of maximum annual energy production.
One DW 52-900, Red Dog Port, 75 m hub height, 90% net AEP
Month
Electric
Load
Turbine
Energy
Energy
Generated
Turbine
Energy to
E. Load
Wind
Penetra-
tion
Excess
Energy to
Thermal
Excess
Energy to
Thermal
kWh kWh kWh kWh % kWh %
1 858,271 162,421 858,531 162,161 18.9% 260 0.0%
2 772,986 182,357 774,499 180,845 23.5% 1,512 0.2%
3 819,735 188,663 821,829 186,569 23.0% 2,094 0.3%
4 749,274 136,467 750,336 135,404 18.2% 1,062 0.1%
5 703,608 92,944 704,059 92,493 13.2% 451 0.1%
6 587,705 59,504 588,793 58,416 10.1% 1,088 0.2%
7 792,258 83,525 792,895 82,887 10.5% 637 0.1%
8 854,746 112,930 856,442 111,234 13.2% 1,696 0.2%
9 739,069 119,908 740,057 118,920 16.2% 988 0.1%
10 860,465 207,665 861,568 206,562 24.1% 1,103 0.1%
11 803,579 183,052 804,853 181,778 22.7% 1,274 0.2%
12 893,169 289,933 893,821 289,281 32.4% 652 0.1%
Annual 9,434,865 1,819,368 9,447,682 1,806,551 19.3% 12,817 0.1%
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Chart, one DW 52-900 turbine, Red Dog Port
EWT DW 52-900, two (2) turbines
This configuration models two EWT DW 52-900 wind turbines at Red Dog Port (prospective site) at a 75
meter hub height and generating 90 percent of maximum annual energy production.
Two DW 52-900’s, Red Dog Port, 75 m hub height, 90% net AEP
Month
Electric
Load
Turbine
Energy
Energy
Generated
Turbine
Energy to
E. Load
Wind
Penetra-
tion
Excess
Energy to
Thermal
Excess
Energy to
Thermal
kWh kWh % %
1 858,271 324,841 935,408 247,703 34.7% 77,138 5.9%
2 772,986 364,715 874,500 263,201 41.7% 101,514 8.5%
3 819,735 377,326 929,428 267,634 40.6% 109,693 8.3%
4 749,274 272,933 817,532 204,675 33.4% 68,258 5.6%
5 703,608 185,887 734,666 154,829 25.3% 31,058 2.7%
6 587,705 119,008 605,602 101,111 19.7% 17,897 1.8%
7 792,258 167,049 809,070 150,237 20.6% 16,812 1.5%
8 854,746 225,860 885,608 194,997 25.5% 30,862 2.7%
9 739,069 239,817 774,344 204,542 31.0% 35,275 3.2%
10 860,465 415,330 958,409 317,386 43.3% 97,944 7.7%
11 803,579 366,103 890,505 279,177 41.1% 86,926 7.0%
12 893,169 579,867 1,050,942 422,094 55.2% 157,773 11.9%
Annual 9,434,865 3,638,736 10,266,015 2,807,586 35.4% 831,150 5.5%
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Chart, two DW 52-900 turbines, Red Dog Port
Economic Analysis
Modeling assumptions are detailed in the table below. Many assumptions, such as project life, discount
rate, operations and maintenance (O&M) costs, etc. are AEA default values. Other assumptions, such as
diesel overhaul cost and time between overhaul are based on general rural Alaska power generation
experience. The base or comparison scenario is the Red Dog Port powerplant with its present
configuration of diesel generators and the existing thermal loads connected to the heat recovery loop.
Fuel Cost
A fuel price of $5.03/gallon was chosen for the economic analysis by reference to Alaska Fuel Price
Projections 2013-2035, prepared for Alaska Energy Authority by the Institute for Social and Economic
Research (ISER), dated June 30, 2013 and the 2013_06_R7Prototype_final_07012013 Excel spreadsheet,
also written by ISER. This price reflects the average value of all fuel prices between the 2016 (the
assumed project start year) fuel price of $4.08/gallon and the 2035 (20 year project end year) fuel price
of $6.02/gallon using the medium price projection analysis with an average CO2-equivalent allowance
cost of $0.59/gallon included. Because fuel costs for Teck Alaska are not available, the ISER fuel cost
tables of nearby Kotzebue are used as stand-in data for economic valuation.
Heating fuel displacement by excess energy diverted to thermal loads is valued at $6.08/gallon as an
average price for the 20 year project period. This price was determined by reference to the
2013_06_R7Prototype_final_07012013 Excel spreadsheet where heating oil is valued at the cost of
diesel fuel (with CO2-equivalent allowance cost) plus $1.05/gallon, assuming heating oil displacement
between 1,000 and 25,000 gallons per year.
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Red Dog Port (Kotzebue cost reference) fuel cost table, CO2-equivalent allowance cost included
ISER med. projection
2015 (/gal) 2034 (/gal)
Average
(/gallon)
Diesel Fuel $4.08 $6.02
$5.03
Heating Oil $5.13 $6.07
$6.08
Wind Turbine Project Costs
Construction cost for wind turbine installation and integration with the diesel power plant will be
accurately defined during the design phase of the project. Project costs are estimated in this conceptual
design report in order to provide comparative valuation. The Wulik River and Kisimigiuktuk Hill site
options are presented separately, both with start years of 2016. It is recognized, however, that although
possible for Wulik River, re-locating the village of Kivalina to Kisimigiuktuk Hill and initiating a wind
project by 2016 is unrealistic. But, for purposes of comparative consistency, 2016 is retained as the
project start date for the Kisimigiuktuk Hill site option.
Economic modeling assumptions
Economic Assumptions
Project life 20 years (2016 to 2035)
Discount rate for NPV 3% (ISER spreadsheet assumption)
System fixed capital cost (plant
upgrades required to accommodate
wind turbines)
Included in turbine project cost
Fuel Properties (no. 2 diesel for
powerplant)
Price (20 year average; ISER 2013,
medium projection plus social cost of
carbon)
$5.03/gal
Fuel Properties (no. 1 diesel to serve
thermal loads)
Price (20 year average; ISER 2013,
medium projection plus social cost of
carbon)
$6.08/gal
Diesel Generators
Generator capital cost $0 (already installed)
O&M cost $0.02/kWh (ISER spreadsheet assumption)
Efficiency 13.8 kWh/gal (Homer model)
Wind Turbines
Net capacity factor 90% (adjusted by reducing mean wind speed in Homer
software)
O&M cost $0.049/kWh (ISER spreadsheet assumption)
Wind Turbine Project Costs, Red Dog Port and Kivalina
Config-
uration
No.
Turbs Turbine Freight Install Civil
Distribu-
tion
Power-
plant
Project
Cost
Cost/
kW
1 900 1.85 0.50 1.50 1.80 0.50 0.30 6.45 7,200
2 1,800 3.70 0.90 2.80 2.20 0.60 0.30 10.50 5,800
Wind
Capacity
(kW)
Estimated Cost (in $millions)
DW 900
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Economic Model Results
Economic benefit-to-cost is shown by the ISER method. This method does not account for heat loss
from the diesel engines due to reduced loading and subsequent impact on heating fuel usage to serve
the thermal loads. ISER cost modeling assumptions are noted above or are discussed in the
2013_06_R7Prototype_final_07012013 Excel spreadsheet. Net annual energy production of the wind
turbines was assumed at 85 percent to reflect production losses due to operations and maintenance
down time, icing loss, wake loss, hysteresis, etc.
As one can see in the table below, EWT DW 52-900 wind turbines, in both one and two turbine
configurations, are projected to be economically beneficial over a 20 year project life. Note however
that this economic evaluation does not include construction cost of an electrical distribution intertie
between Red Dog Port and Kivalina, at either its present location on the barrier island or at Kisimigiuktuk
Hill. The projected distribution cost only assumes connection from the wind turbine(s) to the Red Dog
Port powerplant or nearest three-phase connection point.
Economic valuation table, Red Dog Port and Kivalina
Development Considerations
Given that a Kivalina-only wind power development scenario is most likely with Kisimigiuktuk Hill as the
project site, geotechnical, environmental and permitting will focus on it alone. Some of these
considerations will apply to Red Dog Port as well, but because an electrical intertie must be constructed
for this wind power development scenario to be possible, geotechnical, environmental and permitting
for Red Dog Port won’t be addressed in this report.
Geology
Kisimigiuktuk Hill is a semi-isolated, low, rounded knob located approximately seven miles inland
(northeast) from the village of Kivalina. The elevation of the peak is approximately 460 feet above sea
level. The upper elevations, above the vegetated areas, are quite steep, but at the lower elevations, the
slopes are generally less than ten percent grade.
The hill is characterized by exposed limestone subcrop and rock rubble at the surface. The surface rocks
have been frost-fractured to a depth of approximately three feet. While no large outcrops of limestone
were observed, it is anticipated that below the surface larger frost-fractured rocks and boulders may
exist. The slopes on all sides of Kisimigiuktuk Hill are mantled with limestone rubble, which terminates
abruptly at the toe of the hill. The transition to tundra, which has well-developed tussocks, takes place
within 100 to 150 feet.
Config-
uration
Project
Cost
NPV
Benefits
NPV
Costs B/C
900 6.45 7.46 5.73 1.30 123,736 328 124,064
1,800 10.50 13.26 9.33 1.42 192,300 21,246 213,546
Diesel
Fuel
Saved
(gal/yr)
Heating
Oil Saved
(gal/yr)
Petroleum
Fuel
Saved
(gal/yr)
Wind
Turbine
Capacity
(kW)
(in $ millions)
DW 900
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The surface rock observed is composed of fine- to medium-grained crystalline limestone. The limestone
is occasionally oolitic (limestone comprised of minute rounded concretions resembling fish roe), emits a
fetid (hydrocarbon) odor upon breaking, and reacts strongly to dilute HCL. Further exploration and
testing will be required to identify the depths, extents, and quality of the underlying bedrock.
At this point it appears that a driven pile foundation system, as was proposed for the Buckland Wind
Turbine project, might be an appropriate turbine foundation. Alternatively, a conventional concrete
foundation tied back to bedrock with rock anchors may be feasible. However, this will need to be
confirmed with a geotechnical investigation to determine the depth, type, and strength of the bedrock
at the hill.
Environmental Review
This environmental review addresses issues of concern with respect to flora and fauna of the area.
Vegetation
Terrestrial vegetation in the vicinity of the Kisimigiuktuk Hill is expected to transition from wet tundra at
the base of the hill to sparsely vegetated uplands near the top of the hill. The soils on the upper reaches
of the hill are thin and the area is exposed creating habitat supporting a sparse sub-alpine type
vegetation regime characterized as dryas-sedge dwarf shrub tundra.
Avian Resources
Birds are numerous in the Kivalina vicinity, and include many migratory species such as Canada Goose,
Sandhill Crane, White-fronted Goose, Tundra Swan, all four species of loon (Yellow-billed, Common,
Pacific, Red-throated), and both Steller’s Eider and Spectacled Eider. The area around Kivalina is a
staging area for migratory waterfowl in the spring and fall (USEPA 2009). The Red Dog Mine EIS (USEPA
2009) states that the adjacent areas are high quality habitat for breeding and molting Canada geese.
Tundra provides critical breeding, feeding and molting habitat for many different species of migratory
birds. Lagoons, wetlands and barrier islands provide important nesting, molting and staging habitat
(North Slope Borough 2006). Bird species are especially sensitive in nesting and molting areas. Because
of their federal status, Yellow-billed loon, Steller’s eider, and Spectacled eider are species of particular
concern in the Kivalina area and in relation to the proposed evacuation route.
Yellow-billed Loon
Kivalina is included in the breeding range for Yellow-billed Loon, however the highest concentrations are
on the North Slope (USFWS 2006). Yellow-billed loons nest in coastal and inland low-lying tundra with
permanent fish-bearing lakes and forage in nearshore and offshore waters near their breeding grounds
during summer (USFWS 2009). Migration routes are thought to be primarily marine (USFWS 2006), but
during spring and fall migration these birds use coastal waters, rivers, and large inland bodies of water
(Audubon).
The yellow-billed loon is a candidate for federal listing under the Endangered Species Act. Breeding is
thought to be limited by available habitat (USFWS 2006). These birds are shy and will flee their nest if
disturbed, leaving eggs or young vulnerable to predation (Audubon). Gravel extraction and road
construction are two of the main conservation concerns for YBLO, and their habitat is sensitive to
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infrastructure development disturbance, wetland filling, hydrology alterations or thermokarst action
(USFWS 2006). Interviews with Kivalina residents and Kivalina Subsistence Committee (7/9/2012)
suggest that YBLO are seen on occasion in the Kivalina Lagoon, but occurrences are typically sporadic
and likely associated with migrations or transient individuals.
Steller’s and Spectacled Eiders
Kivalina is not within the breeding, molting or wintering range of the Steller’s eider, or Spectacled eiders,
both of which are federally listed as. Kivalina is within the historic breeding range of the spectacled
eider (USFWS 2012). The breeding ranges for both species are far to the north of the Kivalina area and
the molting and wintering ranges are far to the south. However, they could be in the project area at
times and will require Section 7 consultation. Both species of eiders are not typically observed inland
preferring to remain close to shore or over open water (Jewell Bennett personal interview 2014,
USFWS).
Bats
No bat species are known to range in the vicinity of Kivalina.
Other Mammals
Mammals that may occur in the Kivalina area include caribou (Rangifer tarandus granti), Muskox (Ovibos
moschatus), moose (Alces alces), brown bear (Ursus arctos horribilis), grey wolf (Canis lupus), wolverine
(Gulo gulo), and small fur-bearing animals such as fox, hair, marmot, beaver, muskrat and voles (Red
Dog Mine EIS, 2009). Many of these terrestrial mammals are hunted for subsistence, primarily caribou
and furbearers. The species listed here have generally healthy population numbers, and are not
federally listed as species of concern in Alaska. Polar bears (Ursus maritimus) are considered marine
mammals and are listed under the Federal Endangered Species Act.
Fisheries
The Wulik River and the Kivalina River are listed anadromous streams by the Alaska Department of Fish
and Game (ADFG 2011). The Wulik River supports chum salmon (Oncorynchus keta), coho salmon (O.
kisutch), Chinook salmon (O. tshawytscha), pink salmon (O. gorbuscha), sockeye salmon (O. nerka), Dolly
Varden (Salvelins malma), and whitefish species (Coregonus spp., Prosopium cylindraceum). The
Kivalina River supports Chinook, coho, sockeye, chum, and pink salmon, Dolly Varden, broad whitefish,
Arctic grayling (Thymallus arcticus), and possibly least ciscoes (Coregonus sardinella). The Kivalina
Lagoon contains coho, chum, Chinook, pink, sockeye, Dolly Varden, and undifferentiated whitefish. The
Wulik River is also the main source of freshwater for the village.
Threatened and Endangered Species
Species most at risk from wind development projects varieties of birds with habitat in the project
vicinity. The United States Fish and Wildlife Service (USFWS) lists three species including the Steller’s
eider, spectacled eider and the yellow-billed loon as federally listed species with habit potentially
ranging through the project area. Both the Steller’s eider and the spectacled eider are federally listed as
threatened species and the yellow-billed loon is a federally listed candidate species.
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Other listed species are present in the region; however, they are marine or terrestrial species that would
likely not be impacted by the proposed project, or bird species with no range in the area. These include
the short tailed albatross, polar bear (discussed above), Kittlitz’s murrelet, Pacific walrus, bearded seal
and ring seal. The project area is within polar bear critical habitat, as both Barrier Island Critical Habitat
and Sea Ice Critical Habitat extend 25 miles inland.
Cultural Resources
Kivalina has remained a traditional Inupiat Eskimo village, relying on an understanding of the
environment for subsistence activities such as hunting, fishing, berry picking and egg gathering for many
food and cultural resources. Caribou are the largest part of the subsistence diet in Kivalina with marine
mammals also representing a significant component as does the fall and late spring fisheries for Dolly
Varden in the Kivalina Lagoon and Wulik River.
The first recorded history of the village occurred in 1847 when Lt. Zagoskin of the Russian Navy noted
the small community at the northern end of Kivalina Lagoon, he wrote the name of the village as
“Kivualinagmut” (City of Kivalina 2012). According to the City of Kivalina website, the original population
consisted of survivors of aboriginal Kivalinarmuit Society as well as refugees from the Shishmaref,
Noatak, and Kotzebue regions (City of Kivalina 2012).
Historically, the Kivalina area was a stopping place and meeting area for trade, to gather food and for
communication for people living on the mainland, or traveling by land or by sea (Northwest Arctic
Borough 2009). The current village site was established in 1905 when a federal school was established.
The forced migration to the barrier island in order for the children to go to school caused a lot of stress
in the early population. The population of Kivalina was decimated by disease and starvation in the early
20th century (City of Kivalina 2012). Missionaries came to Kivalina in the early 20th century and the
Episcopal Church ordained at least two residents as ministers in early years. The first post office in
Kivalina was established in 1940; the first airstrip was built in 1960; and Kivalina was incorporated as a
city in 1969. The 1970’s brought a new school, new houses, and a modern electric system. The Alaska
Native Claims Settlement Act (ANCSA) established the regional corporations in 1971 (City of Kivalina
2012). NANA Regional Corporation is the area corporation (State of Alaska 2012).
The majority of the city currently does not have modern plumbing. Water is collected from the Wulik
River during months when the river and ground are not frozen, and at times of lower turbidity. This
water is stored in large tanks in the center of town, where villagers collect for household use (Personal
communication with Kivalina Village, 7/9/2012).
Permitting and Agency Consultation Requirements
The environmental permitting requirements listed below are discussed in Alaska Wind Energy
Development: Best Practices Guide to Environmental Permitting and Consultations, a study prepared by
URS Corporation for the Alaska Energy Authority in 2009.
Wetlands and Waterways
Kisimigiuktuk Hill is an upland area and does not have any wetlands or “Waters of the United States”
that would require permits in order to place fill. The project area is, however, surrounded by a vast
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area of wetlands associated with the Wulik and the Kivalina Rivers. As stated, the Wulik and Kivalina
Rivers are located in the vicinity of the project area.
Alaska Pollution Discharge Elimination System
State regulations (18 AAC 83) require that all discharges to surface waters, including storm water runoff,
be permitted under the Alaska Pollution Discharge Elimination System (APDES). The goal of the program
is to reduce or eliminate pollution and sediments in stormwater and other discharges to surface water.
Under the state APDES program, projects that disturb one or more acre of ground are subject to the
terms of the Alaska Construction General Permit (CGP) and are required to develop a project Storm
Water Pollution Prevention Plan (SWPPP) outlining measures to control or eliminate pollution and
sediment discharges. A wind project in Kivalina is likely to disturb more than one acre of ground during
the construction of wind turbines, supporting infrastructure and access roads and would be subject to
the requirements of the CGP. Prior to construction, the contractor would be required to file a Notice of
Intent (NOI) with the Alaska Department of Environmental Conservation (ADEC) prior to submitting the
project SWPPP. ADEC would issue an APDES permit following the public comment period.
US. Fish and Wildlife Service/National Marine Fisheries Service
Although the project is not a Federal action and effects on bird and animal species will likely be minor,
consultation with the USFWS is necessary to insure there are no unintended impacts as a result of the
project. Consultation will also establish post construction monitoring guidelines, if determined to be
necessary, to comply with the Migratory Bird Treaty Act (MBTA) and/or the Bald and Golden Eagle
Protection Act.
USFWS regulations and guidance under the MBTA prohibits the taking of active bird nests, eggs and
young. In their Advisory: Recommended Time Periods for Avoiding Vegetation Clearing in Alaska in order
to protect Migratory Birds, USFWS has developed “bird windows” statewide that prohibit clearing
activity. The bird window for the Northern region of Alaska, including Kivalina is June 1st – July 31st for
shrub and open type habitats (tundra and wetlands) and May 20th – September 15th for nesting seabird
colonies. The clearing window for black scoter habitat is through August 10th. Clearing prior to these
dates is allowed. If clearing has already occurred then construction may proceed during these dates.
USFWS Wind Turbine Guidelines Advisory Committee developed guidelines and recommendations for
wind power projects to avoid impacts to birds and bats. These recommendations have been released to
the public as draft U.S. Fish and Wildlife Service Land-Based Wind Energy.
Federal Aviation Administration
Prior to turbine construction an FAA Notice of Proposed Construction or Alteration (Form 7460-1) is
required to be completed. Filing a 7460-1 may result in additional discussions with the FAA regarding
turbine siting and appropriate lighting requirements that would need to be incorporated into the project
specifications.
U.S. Army Corps of Engineers
The US Army Corps of Engineers (USACE) requires a permit for the placement of fill in “waters of the
United States”, including wetlands and streams, under Section 404 of the Clean Water Act (CWA). The
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proposed Kisimigiuktuk Hill turbine site is no likely to be wetlands as there is exposed bedrock at the
site. If, however, some component of infrastructure or access road is determined to be within waters of
the U.S. a Section 404 permit from the Alaska District USACE and an accompanying U.S. Environmental
Protection Agency (EPA) Section 401 Water Quality Certification would need to be obtained. Currently,
Individual Permits and Nationwide 12 permits are being issued for wind power projects in Alaska. An
individual permit would be required for activities related to the construction of access roads or pads in
wetlands. A Nationwide 12 Permit would be appropriate for activities related to utility installation (i.e.
power lines). Depending on the site selection and potential impacts, a jurisdictional determination
(wetland delineation) may be necessary to obtain a Section 404 permit. WHPacific, Inc. and V3 Energy,
LLC 1 May 2014
Alaska Department of Fish and Game
The Alaska Department of Fish and Game (ADF&G) oversees activities that may have an impact on fish
habitat and anadromous fish streams. An ADF&G Title 16 Fish Habitat Permit would be required if the
proposed project includes construction of access roads and infrastructure that may impact fish habitat
or would involve installing a culvert in a fish stream.
State Historic Preservation Office
Consultation with the State Historic Preservation Office (SHPO) for State of Alaska-funded projects is
required under the State Historic Preservation Act. The act requires that all state projects be reviewed
for potential impacts to cultural and historic resources. During the permitting phase of the project prior
to construction, consultation with the SHPO would be initiated to determine if the project may impact
these resources. The extent of needed infrastructure (pads and new roads) and the presence of known
archaeological sites in the vicinity of the project area may trigger the SHPO to recommend an
archaeological survey of the site.
Discussion
For this conceptual design report, only proven and robust wind turbines were considered for evaluation,
hence any of the evaluated configurations can be designed and operated to meet expectations of high
performance and reliability. Integration requirements will vary depending on the type of electrical
generator in the turbine (synchronous vs. asynchronous), inverter-conditioning, soft-start or other
similar grid stability control features, VAR support if necessary, minimum loading levels of the diesel
generators as a percentage of the electric load, secondary load controller resolution and response time,
among others. These design elements are beyond the scope of this conceptual design project, but the
technology is mature enough to be assured that the wind turbines operating in a medium
penetration/non-storage mode in Kivalina are controllable.
With these issues in mind, the primary deciding factors for selection of wind turbine(s) for Kivalina will
be cost, aesthetics, redundancy, support, and commonality.
WHPacific, Inc. and V3 Energy, LLC 7 May 2014
Kivalina Conceptual Design Report P a g e | 59
Cost
The highest benefit-to-cost ratio wind turbine configuration calculated in this conceptual design is the
Northern Power NPS 100-21 turbine at the Kisimigiuktuk Hill site, although the projected benefit-to-cost
ratio of Vestas V17 turbines is high as well. Note however that the cost estimates in this report were
not produced at the same level of precision and accuracy as will occur during the design phase and so
should be considered with a level of caution. Also note that many cost parameters such as operations
and maintenance costs over the life of the project are estimated using Alaska Energy Authority default
values and may not be realistic for a particular turbine configuration option.
Aesthetics
This is a highly subjective consideration that may elicit strong and conflicting opinions. Ultimately,
Kivalina residents must collectively agree on the aesthetic impact of wind turbines in their community,
especially at Kisimigiuktuk Hill as the turbines will be near the new community and easily visible on a
prominent landmark. Should an intertie to Red Dog Port be constructed to supply electrical power to
Kivalina, wind turbines at Red Dog Port would not be visible from Kivalina and would only present an
aesthetic consideration for Teck Alaska. Given the industrial nature of the port facility, aesthetic
objections to wind turbine(s) at Red Dog Port are unlikely.
Redundancy
A single wind turbine would be redundant in the sense that diesel generation will continue to exist to
meet electrical load demand should the turbine be off-line for maintenance or a fault condition. On the
other hand, a single wind turbine is not redundant with respect to wind generation itself. Should the
turbine be out of service for an extended period of time, wind power would not be generated during the
outage and the community would revert to a diesels-only mode of operation.
Support
Manufacturer warranty and support will be a primary consideration of AVEC given its responsibility as
electrical utility for Kivalina. The Borough must have confidence that the turbine manufacturer and/or
its representatives will be available throughout the life of the project. This is a matter of trust and
ultimately a value that AVEC must determine for itself.
Commonality
This is a practical consideration in that several AVEC communities are equipped with Northern Power
wind turbines, which can be considered to be AVEC’s “fleet” turbine. There are many desirable aspects
of a fleet turbine of value to AVEC: a single supplier and point of contact, a common control system for
all turbines in the fleet, common parts, and technicians that must learn only one turbine, not two or
more. On the other hand, AVEC has at times expressed interest in working with other wind turbine
suppliers and developing alternative wind power configurations.
WHPacific, Inc. and V3 Energy, LLC 7 May 2014
Kivalina Conceptual Design Report P a g e | 60
Recommendation
The configuration of two Northern Power 100-21 wind turbines at the Kisimigiuktuk Hill site is
recommended as the AVEC’s best option for wind power development in Kivalina, assuming a Kivalina-
only configuration. This recommendation is based on the following considerations:
Cost – Development of wind power at the Kisimigiuktuk Hill site is recommended, but as noted
elsewhere in this report, this assumes relocation of the village to the Kisimigiuktuk Hill area.
This recommendation also assumes that relocation costs will be borne by other funding sources.
This report does not recommend development of wind power at Kisimigiuktuk Hill to served
Kivalina at its present location on the barrier island.
With respect to development of wind power for Kivalina in its present location, although this is
possible at the Wulik River site, this option is not cost effective with the evaluated wind
turbines, and is not recommended. Note that should wind turbines be installed at the Wulik
River site to serve Kivalina and then the village subsequently re-located to Kisimigiuktuk Hill, the
turbines would be orphaned in an undesirable location.
Aesthetics – Presuming the relocation of Kivalina to Kisimigiuktuk Hill area and wind power
development on Kisimigiuktuk Hill, undeniably wind turbines will be have an aesthetic impact.
This can be perhaps be partially mitigated by microsite decisions regarding view angles and
exact turbine location. Should an intertie to Red Dog Port be constructed and wind power
developed at the port, aesthetic considerations will be a moot point for Kivalina residents.
Redundancy – Installing at least two wind turbines enables continuity of wind power production
should one turbine be out of service for an extended period of time and is recommended for a
Kivalina-only wind power project. Should an intertie be constructed and wind power developed
at Red Dog Port, redundancy considerations will be the province of Teck Alaska to decide,
although two or more wind turbines would be recommended for Red Dog Port for the same
reason they are recommended for a Kivalina-only option: continuity of wind power should one
turbine be off-line.
Support – All three (two when considering Kivalina-only options) turbine manufacturers
evaluated in this conceptual design report are professional companies with extensive depth and
capability to provide warranty and continuing support over time with both factory personnel
and Alaska-based representatives. But, given AVEC’s long history with Northern Power Systems,
continuation of this relationship in Kivalina is recommended.
Commonality – Given AVEC’s long history with Northern Power Systems, NPS 100 turbines
would be most straightforward for AVEC to integrate into its operations department.
It must be emphasized that for this report the wind resource at Kisimigiuktuk Hill was modeled by
reference to only one year of met tower data collected five miles distant at the Wulik River site. With
that in mind, a met tower should be installed on Kisimigiuktuk Hill to verify the wind resource modeled
in this report. At publication of this report, it was reported that WHPacific, AVEC, Alaska Energy
WHPacific, Inc. and V3 Energy, LLC 7 May 2014
Kivalina Conceptual Design Report P a g e | 61
Authority, and NANA Regional Corp. are working to accomplish that goal during the summer 2014 field
season.
WHPacific, Inc. and V3 Energy, LLC 7 May 2014
Kivalina Conceptual Design Report P a g e | A
Appendix A – Kivalina Wind Resource Report
WHPacific, Inc. and V3 Energy, LLC 7 May 2014
Kivalina Wind Resource Report
Kivalina aerial photo by Doug Vaught, July 2011
June 27, 2012
Douglas Vaught, P.E.
dvaught@v3energy.com
V3 Energy, LLC
Eagle River, Alaska
Kivalina Wind Resource Report P a g e | 2
Purpose
The Kivalina wind resource report is a component of a larger feasibility study to install wind turbines in
either Kivalina or at the Red Dog Port facility located 27 km (17 miles) to the southeast. The feasibility
study includes an analysis of a potential electrical intertie connecting Kivalina to Red Dog Port. A follow-
on version of this wind resource report will include a comparison of wind data being collected at Red
Dog Port.
Summary
The wind resource measured at the Kivalina met tower site is good with measured wind power class 4
(description: good) if considering power density and wind power class 3 (description: fair) if considering
only mean wind speed. Given the cold temperatures in Kivalina, higher wind density results in a higher
power density than at standard temperature and pressure. In other respects, Kivalina’s wind
characteristics are ideal with exceptionally low turbulence and low wind shear. Kivalina experiences
very cold winter temperatures, which will increase energy production of both variable pitch and stall-
regulated wind turbines, but the low elevation of the site keeps it free of problematic rime icing
problems that have been noted elsewhere in northern Alaska.
The Kivalina wind resource study was funded by the Alaska Energy Authority and managed by WHPacific
for the Alaska Village Electric Cooperative (AVEC). WHPacific contracted V3 Energy, LLC to write this
wind resource report. AVEC and WHPacific points of contact, respectively, are Brent Petrie, Key
Accounts Manager (bpetrie@avec.org), and Katherine Keith, Distributed Energy Specialist
(kkeith@whpacific.com).
Met tower data synopsis
Data dates May 9, 2011 to May 18, 2012 (12.3 months);status:
operational
Wind power class Class 3 to Class 4
Wind power density mean, 30 m 325 W/m2
Wind speed mean, 30 m 5.87 m/s
Max. 10-min wind speed average 26.7 m/s
Maximum 2-sec. wind gust 33.6 m/s (November, 2011)
Weibull distribution parameters k = 1.66, c = 6.56 m/s
Wind shear power law exponent 0.194 (moderate)(see report for notes)
Roughness class 2.11 (few trees)(see report for notes)
IEC 61400-1, 3rd ed. classification Class III-C
Turbulence intensity, mean 0.075 (at 15 m/s)
Calm wind frequency (at 33 m)34% (<4 m/s)
Kivalina Wind Resource Report P a g e | 3
Test Site Location
Wind measurement instrumentation was installed on a six-inch diameter 30 meter NRG tubular Tall
Tower (met tower) approximately three kilometers (two miles) east of the village of Kivalina and
approximately 1.5 km (1 mile) from the Chukchi Sea coast. The tower is located on open tundra in the
general vicinity of the new Kivalina town site should the village be relocated due to continuing erosion
and flooding risk at the existing village location, which is on an exposed coastal barrier island. The met
tower was installed on May 6, 2011 by Echelon Energy Corp. of San Jose, California.
Site information
Site number 9750
Latitude/longitude N 67° 43’29.64”W 164° 26’25.38”, NAD 83
Site elevation 3 meters (10 ft)
Datalogger type NRG Symphonie, 10 minute time step
Tower type NRG Tall Tower, 30 meters, six-inch diameter
Topographic map
Kivalina Wind Resource Report P a g e | 4
Google Earth image
Tower sensor information
Channel Sensor type Height Multiplier Offset Orientation
1 NRG #40 anemometer 30 m A 0.765 0.35 north
2 NRG #40 anemometer 30 m B 0.765 0.35 south
3 NRG #40 anemometer 20 m 0.765 0.35 north
7 NRG #200P wind vane 29 m 0.351 351 351° T
9 NRG #110S Temp C 3 m 0.138 -86.3 north
Tower sensors photo (view to the southwest)
Kivalina Wind Resource Report P a g e | 5
Data Quality Control
Data quality is generally very good for the 30 meter level anemometers, excellent for the wind vane and
temperature sensor, and very poor for the 20 meter level anemometer. An installation error with the 20
meter anemometer resulted in it being located directly in line with the north-facing third-level guy wire,
resulting in fouling of the sensor in the wire after the tower settled in the tundra a bit and the guy wires
slackened. In the data analysis, a filter was used to remove 20 meter anemometer data significantly
divergent from 30 meter A anemometer data, but that is not a precise tool and it is not possible to
definitively determine all times that the 20 m anemometer was fouled. Recovered 20 m level
anemometer data is not usable by itself for wind speed or other data, but it is usable, with qualification,
for calculation of the wind shear coefficient.
Data loss due to icing conditions was very infrequent in Kivalina compared to coastal sites in western
Alaska. This may be due to the extremely cold winter of 2011/2012 and the otherwise normal extensive
sea ice offshore of Kivalina and resulting low moisture content in the air. Icing conditions in the
anemometer data are characterized by output of the anemometer at the minimum offset value of 0.4
m/s, standard deviation of zero, and temperatures less than 1 degree Centigrade. For wind direction
data, icing is characterized by non-variant output at the last operable wind direction (standard deviation
of zero) and temperature less than 1 degree Centigrade.
In addition to icing, 30 meter level anemometer data was filtered for tower shadow using an algorithm
that identifies wind from a 30 degree sector opposite the anemometer and filters that data. With
frequent northerly winds, the south-facing 30 m B anemometer was filtered more frequently than the
north-facing 30 m A anemometer.
Data recovery summary table
Possible Valid Recovery
Sensor Units Height Records Records Rate (%)
Speed 30 m A m/s 30 m 54,018 51,676 95.7
Speed 30 m B m/s 30 m 54,018 47,240 87.5
Speed 20 m m/s 20 m 54,018 15,965 29.6
Direction 29 m ° 29 m 54,018 53,408 98.9
Temperature °C 54,018 53,868 99.7
Anemometer and wind vane data recovery
30 m A 30 m B 20 m Vane Temp
Year Month Recovery Recovery Recovery Recovery Recovery
Rate (%) Rate (%) Rate (%) Rate (%) Rate (%)
2011 May 88.6 92.2 43.7 95.5 100.0
2011 Jun 93.9 88.5 9.7 100.0 100.0
2011 Jul 93.7 95.5 5.7 100.0 100.0
2011 Aug 94.5 96.2 15.3 100.0 100.0
2011 Sep 96.2 81.4 25.8 100.0 100.0
2011 Oct 99.3 90.5 25.0 98.3 100.0
Kivalina Wind Resource Report P a g e | 6
30 m A 30 m B 20 m Vane Temp
Year Month Recovery Recovery Recovery Recovery Recovery
Rate (%) Rate (%) Rate (%) Rate (%) Rate (%)
2011 Nov 99.4 85.5 18.5 100.0 100.0
2011 Dec 90.8 80.5 57.2 91.4 96.8
2012 Jan 98.0 87.2 54.7 100.0 100.0
2012 Feb 97.8 84.3 44.0 100.0 100.0
2012 Mar 99.3 74.8 27.0 100.0 100.0
2012 Apr 94.7 93.0 26.0 100.0 100.0
2012 May 96.0 89.1 39.8 99.8 99.8
All Data 95.7 87.5 29.6 98.9 99.7
Data flag statistics
Anemometer
Possible
Records Icing %
Low
quality %
Tower
shading %
Speed 30 m A 54,018 0.4% 0.0% 3.6%
Speed 30 m B 54,018 0.4% 0.0% 11.4%
Speed 20 m 54,018 24.4% 68.6% 0.0%
Note: low quality and icing flags of 20 m anemometer often overlap.
Fouled 20 meter anemometer
Wind Speed
Anemometer data obtained from the met tower, from the perspectives of both mean wind speed and
mean wind power density, indicate a good wind resource. Mean wind speeds are greater at higher
elevations on the met tower as one would expect. Note that the cold mean annual air temperature in
Kivalina contributed to a higher wind power density than otherwise expected for the mean wind speeds.
Kivalina Wind Resource Report P a g e | 7
Anemometer data summary
Variable
Speed 30 m
A
Speed 30 m
B
Measurement height (m) 30 30
Mean wind speed (m/s) 5.87 5.52
Median wind speed (m/s) 5.20 5.00
Max 10-min avg wind speed (m/s) 26.7 26.7
Max gust wind speed (m/s) 33.2 33.6
Weibull k 1.66 1.62
Weibull c (m/s) 6.56 6.15
Mean power density (W/m²) 325 274
Mean energy content (kWh/m²/yr) 2,845 2,398
Energy pattern factor 2.41 2.47
Frequency of calms (%) 34.4 37.3
Time Series
Time series calculations indicate high mean wind speeds during the winter months with more moderate
mean wind speeds during summer months. This correlates well with the typical village load profile
where winter months have a high electric and heat demand and summer months a lesser demand. The
a diurnal profile indicates remarkably stable wind speeds throughout the day with a minor “valley” of
wind speeds during the morning hours and a minor “peak” of wind speeds during late afternoon.
30 m A anemometer data summary
Mean
Max 10-
min
Max
Gust
Std.
Dev.
Weibull
k
Weibull
c
Year Month (m/s) (m/s) (m/s) (m/s) (-) (m/s)
2011 May 5.58 14.0 17.2 2.83 2.04 6.29
2011 Jun 5.09 14.9 18.3 2.70 1.95 5.73
2011 Jul 4.71 13.8 17.9 2.53 1.92 5.29
2011 Aug 4.98 12.5 15.6 2.35 2.19 5.60
2011 Sep 6.45 17.8 22.9 3.14 2.15 7.28
2011 Oct 5.69 18.5 22.9 3.08 1.92 6.42
2011 Nov 6.88 26.7 33.2 4.08 3.55 10.12
2011 Dec 8.51 21.2 25.6 4.19 2.14 9.60
2012 Jan 4.81 24.7 27.1 4.24 1.17 5.08
2012 Feb 7.17 21.2 24.8 4.43 1.64 8.00
2012 Mar 5.94 16.7 19.5 3.47 1.71 6.63
2012 Apr 4.94 17.6 22.9 3.87 1.21 5.24
2012 May 5.41 13.5 16.1 2.60 2.19 6.10
All Data 5.87 26.7 33.2 3.63 1.66 6.56
Mean of monthly means 5.88
Kivalina Wind Resource Report P a g e | 8
Wind speed time series graph
Diurnal profile
Note: disregard the Speed 20 m curve due to problems with data recovery
Wind Speed Distribution
The probability distribution function (PDF), or histogram, of Kivalina wind speed data indicates a shape
curve somewhat dominated by lower wind speeds, as opposed to a “normal” shape curve, known as the
Rayleigh distribution (Weibull k = 2.0), which is defined as the standard wind distribution for wind power
analysis. As one can see in the PDF of 30 meter A anemometer, the most frequently occurring wind
speeds are between 4 and 6 m/s with very few wind events exceeding 25 m/s (the cutout speed of most
wind turbines; see following wind speed statistical table).
Kivalina Wind Resource Report P a g e | 9
Wind speed distribution of 30 m A anemometer
Weibull k shape curve table
Weibull comparison table
Algorithm
Weibull Weibull Proportion Power R
k c Mean Above Density Squared
(-) (m/s) (m/s) 5.872 m/s (W/m2) (-)
Maximum likelihood 1.660 6.560 5.864 0.435 291.8 0.977
Least squares 1.704 6.586 5.875 0.439 283.8 0.980
WAsP 1.603 6.496 5.823 0.427 299.2 0.970
Actual data (51,676 time steps)5.872 0.427 299.2
Kivalina Wind Resource Report P a g e | 10
Occurrence by wind speed bin
Bin Endpoints
(m/s) Occurrences
Bin Endpoints
(m/s) Occurrences
Lower Upper No. Percent Lower Upper No. Percent
0 1 2,224 4.5% 14 15 604 1.2%
1 2 3,420 6.9% 15 16 443 0.9%
2 3 5,226 10.5% 16 17 287 0.6%
3 4 6,219 12.5% 17 18 180 0.4%
4 5 6,821 13.7% 18 19 122 0.2%
5 6 6,261 12.6% 19 20 78 0.2%
6 7 5,213 10.5% 20 21 37 0.1%
7 8 4,327 8.7% 21 22 18 0.0%
8 9 3,236 6.5% 22 23 13 0.0%
9 10 2,271 4.6% 23 24 17 0.0%
10 11 1,610 3.2% 24 25 22 0.0%
11 12 1,270 2.5% 25 26 25 0.1%
12 13 962 1.9% 26 27 13 0.0%
13 14 757 1.5% all 49,817 100.0%
Wind Shear and Roughness
A wind shear power law exponent () of 0.194 indicates moderate wind shear at the site. Related to
wind shear, a calculated surface roughness of 0.114 meters (indicating the height above ground level
where wind velocity would be zero) indicates moderately rough terrain (roughness description: few
trees) surrounding the met tower. This data is comprised however by very poor data recovery from the
20 meter level anemometer, which was installed such that it was often fouled in the third level north-
facing guy wire. The power law exponent is calculated only with time step data with valid anemometer
data from the selected sensors (the 30 m A anemometer and the 20 meter anemometer); in this case
only 28 percent of the time steps qualified. This is a statistically sufficient amount of data except that
filtering of the 20 meter data to remove the time steps where the anemometer was fouled is not precise
and some data that should have been filtered was undoubtedly retained. Although the power law
exponent and roughness length are generally reasonable, one might expect both values to be lower
considering the flat, featureless, and typically snow-covered terrain surrounding the met tower.
Kivalina Wind Resource Report P a g e | 11
Vertical wind shear profile
Comparative wind shear profiles
Extreme Winds
A modified Gumbel distribution analysis, based on monthly maximum winds vice annual maximum
winds, was used to predict extreme winds at the Kivalina met tower site. Industry standard reference of
extreme wind is the 50 year probable (50 year return period) ten-minute average wind speed, referred
to as Vref. For Kivalina, this calculates to 35.8 m/s (at 30 meters), which qualifies as an International
Electrotechnical Commission (IEC) 61400-1, 3rd edition criteria Class III site, the lowest defined. All wind
turbines are designed for IEC 61400-1 Class III conditions.
Extreme wind probability table, 30 m A data
Vref Gust IEC 61400-1, 3rd ed.
Period (years) (m/s) (m/s) Class Vref, m/s
3 26.8 32.8 I 50.0
10 30.7 37.5 II 42.5
20 32.9 40.2 III 37.5
30 34.2 41.8 S designer-
specified5035.8 43.8
100 38.0 46.5
Kivalina Wind Resource Report P a g e | 12
Extreme wind graph
Temperature and Density
Kivalina experiences cool summers and very cold winters with resulting higher than standard air density.
Calculated annual mean air density during the met tower test period exceeds by 7.8 percent the 1.225
kg/m3 standard air density at a 3 meter elevation. This is advantageous in wind power operations as
wind turbines typically produce more power at low temperatures/high air density than at standard
temperature and density.
Temperature and density table
Temperature Density
Month Mean Min Max Mean Min Max
(°C) (°C) (°C) (kg/m³) (kg/m³) (kg/m³)
Jan -30.7 -44.5 -8.9 1.456 1.335 1.543
Feb -15.9 -48.7 2.7 1.374 1.279 1.572
Mar -20.2 -34.5 -7.4 1.395 1.327 1.478
Apr -7.9 -28.4 10.6 1.331 1.243 1.441
May 1.8 -15.4 25.0 1.284 1.183 1.369
Jun 12.2 0.7 28.1 1.237 1.171 1.288
Jul 12.9 2.6 28.9 1.234 1.168 1.279
Aug 11.3 0.4 23.5 1.240 1.189 1.290
Sep 6.8 -5.1 19.3 1.260 1.206 1.316
Oct -3.5 -17.6 8.7 1.308 1.252 1.380
Nov -16.5 -31.5 1.8 1.376 1.283 1.460
Dec -15.5 -35.0 0.5 1.367 1.224 1.481
Annual -5.2 -48.7 28.9 1.321 1.168 1.572
25.0
30.0
35.0
40.0
45.0
50.0
55.0
0 10 20 30 40 50 60 70 80 90 100
Period, years
Vref
gust
Kivalina Wind Resource Report P a g e | 13
Annual temperature boxplot
Air density DMap
Wind Speed Scatterplot
The wind speed versus temperature scatterplot below indicates that a substantial percentage of wind in
Kivalina coincides with cold temperatures as one would expect. During the met tower test period,
temperatures fell below -40°C, the minimum operating temperature for arctic-capable wind turbines, on
a number of occasions. Wind speeds during periods of extreme cold are generally low, however, and
loss of wind turbine availability during these times would not be significant. Also note that periods of
high winds (wind speeds greater than 20 m/s) are characterized by cold temperatures, between 0°C and
-25°C.
Kivalina Wind Resource Report P a g e | 14
Wind speed/temperature
Wind Direction
Wind frequency rose data indicates that winds at Kivalina are relatively directional, with north-
northeasterly and east-northeasterly predominating. The mean value rose indicates that infrequent
southeasterly winds, when they do occur, are of high energy and hence likely storm winds. The wind
energy rose indicates that winds for wind turbine operations power-producing are northerly and
southeasterly dominant. Calm frequency (percent of time that winds at the 30 meter level are less than
4 m/s) was 34 percent during the met tower test period.
Wind frequency rose Mean value rose (30 m A anem.)
Kivalina Wind Resource Report P a g e | 15
Wind energy rose (30 m A anem.) Scatterplot rose of 30m A wind power density
Monthly wind energy roses (common scale)
Kivalina Wind Resource Report P a g e | 16
Turbulence
Turbulence intensity (TI) at the Kivalina met tower site is well within acceptable standards with an IEC
61400-1, 3rd edition (2005) classification of turbulence category C, which is the lowest defined. The
mean TI at 15 m/s is 0.075 and the representative TI at 15 m/s is 0.105 (30 m A anemometer), both
which can be considered very low and hence very desirable for wind turbine operations.
Turbulence intensity, 30 m A anemometer, all direction sectors
Turbulence table, 30 m A data
Bin Endpoints
Records
Standard
Representative
TI
Lower Upper Mean Deviation Peak
(m/s) (m/s) in Bin TI of TI TI
0.5 1.5 2,744 0.363 0.155 0.561 1.091
1.5 2.5 4,280 0.180 0.090 0.295 0.800
2.5 3.5 5,847 0.126 0.064 0.209 0.815
3.5 4.5 6,725 0.100 0.049 0.163 0.771
4.5 5.5 6,568 0.086 0.041 0.138 0.633
5.5 6.5 5,732 0.081 0.038 0.130 0.468
6.5 7.5 4,858 0.076 0.032 0.117 0.299
7.5 8.5 3,763 0.076 0.032 0.117 0.364
8.5 9.5 2,704 0.076 0.029 0.114 0.299
Kivalina Wind Resource Report P a g e | 17
Bin Endpoints
Records
Standard
Representative
TI
Lower Upper Mean Deviation Peak
(m/s) (m/s) in Bin TI of TI TI
9.5 10.5 1,883 0.077 0.028 0.113 0.269
10.5 11.5 1,398 0.078 0.028 0.114 0.252
11.5 12.5 1,155 0.078 0.027 0.112 0.265
12.5 13.5 808 0.074 0.023 0.104 0.167
13.5 14.5 662 0.076 0.023 0.105 0.174
14.5 15.5 545 0.075 0.023 0.105 0.166
15.5 16.5 347 0.076 0.023 0.105 0.167
16.5 17.5 241 0.074 0.019 0.099 0.145
17.5 18.5 151 0.073 0.016 0.094 0.120
18.5 19.5 98 0.068 0.013 0.084 0.115
19.5 20.5 58 0.069 0.012 0.085 0.100
20.5 21.5 24 0.072 0.014 0.089 0.103
21.5 22.5 16 0.078 0.015 0.097 0.103
22.5 23.5 12 0.080 0.024 0.111 0.104
23.5 24.5 17 0.090 0.016 0.110 0.120
24.5 25.5 28 0.087 0.015 0.106 0.108
25.5 26.5 20 0.090 0.006 0.097 0.104
26.5 27.5 4 0.086 0.003 0.091 0.091
Wind Turbine Performance
The selection of suitable wind turbines for a wind power project in Kivalina is beyond the scope of this
report, but for initial planning purposes, predicted annual energy output and capacity factor for the 100
kW Northwind 100 B model (21 meter rotor, 37 meter hub height) is presented below.
Note that the Alaska Energy Authority considers 82 percent turbine availability (percent of time that the
turbine is operational and available to produce power, irrespective of wind speed) as the default value
for planning village power projects. Many wind turbines in rural Alaska operate with better than 82
percent availability, but for a number of reasons some operate with lower than 82 percent availability.
For this turbine performance analysis, adjustment of power output (from standard temperature and
pressure conditions) of the NW100 turbine due to air density was not considered as Northern Power
Systems has not published density-specific power curves for the turbine.
NW100B/21 at 37 m, 82% availability
Hub Height Time At Time At Mean Net Mean Net Net
Wind
Speed
Zero
Output
Rated
Output
Power
Output
Energy
Output
Capacity
Factor
Month (m/s) (%) (%) (kW) (kWh/yr) (%)
Jan 5.03 41.1 2.6 16.1 12,001 16.1
Feb 7.48 14.6 4.8 30.1 20,242 30.1
Mar 6.17 20.3 1.9 22.9 17,036 22.9
Kivalina Wind Resource Report P a g e | 18
Hub Height Time At Time At Mean Net Mean Net Net
Wind
Speed
Zero
Output
Rated
Output
Power
Output
Energy
Output
Capacity
Factor
Month (m/s) (%) (%) (kW) (kWh/yr) (%)
Apr 5.08 38.1 2.5 17.6 12,655 17.6
May 5.60 21.2 0.0 18.5 13,758 18.5
Jun 5.26 21.0 0.1 15.4 11,071 15.4
Jul 4.93 24.5 0.0 13.4 9,993 13.4
Aug 5.27 18.7 0.0 15.2 11,272 15.2
Sep 6.87 10.8 2.7 26.2 18,896 26.2
Oct 5.95 15.7 1.7 19.9 14,817 19.9
Nov 7.22 8.8 2.2 24.9 17,928 24.9
Dec 8.76 8.2 5.5 40.4 30,036 40.4
Annual 6.10 20.4 1.9 21.5 188,215 21.5
Kivalina Conceptual Design Report P a g e | B
Appendix B – Red Dog Port Wind Resource Report
WHPacific, Inc. and V3 Energy, LLC 7 May 2014
Red Dog Port Wind Resource Report
Red Dog Port communication tower, view to the southeast, D. Vaught photo
September 7, 2011
Douglas Vaught, P.E.
V3 Energy, LLC
Eagle River, Alaska
Red Dog Port Wind Resource Report P a g e | 2
Summary
The wind resource measured at the Red Dog Port communication tower (Site 5) is very good with
measured wind power class 6 (outstanding) if considering power density, but wind power class 3 (fair) if
considering only mean wind speed. Given the cold temperatures of Red Dog Port area, higher wind
density results in a higher power density than at standard temperature and pressure. This increases
wind turbine power production, but the boost is not linear. By more useful measure with respect to
potential wind turbine energy production, the site would classify as Class 4 to 5 (good to excellent),
depending on individual turbine performance.
In a general sense, wind classification at Red Dog Port should be viewed with caution as the statistical
characteristics of the wind at this site are somewhat unusual with a wind speed probability distribution
skewed toward lower wind speeds but also comprised of high wind events, the latter which strongly
influence the mean annual wind power density. Intuitively, this can be grasped by considering that
although the mean annual wind power density is quite high, the site experiences 45 percent calm winds
(wind speeds less than four meters per second). Another indication of the periodic high winds at Red
Dog Port is the extreme wind probability calculation which, depending on one’s assumptions, classifies
the site as IEC Class I or II.
In other respects, however, Red Dog Port wind characteristics are ideal with exceptionally low
turbulence and low surface roughness. The Port experiences very cold temperatures, which will
increase energy production of both variable pitch and stall-regulated wind turbines, but the low
elevation of the site keeps it free of problematic rime icing problems that have been noted elsewhere in
northern Alaska.
Met tower data synopsis
Data dates October 10, 2008 to August 10, 2011 (34 months);
status: operational
Wind power class Difficult to classify; likely Class 4 to 5 (good to excellent)
Wind power density mean, 33 m 574 W/m2
Wind speed mean, 33 m 6.05 m/s
Max. 10-min wind speed average 38.5 m/s
Maximum 2-sec. wind gust 43.5 m/s (January, 2009)
Weibull distribution parameters k = 1.24, c = 6.52 m/s
Wind shear power law exponent 0.180 (moderate)
Roughness class 0.73 (lawn grass)
IEC 61400-1, 3rd ed. classification Class II-C
Turbulence intensity, mean 0.119 (at 15 m/s)
Calm wind frequency (at 33 m)45% (<4 m/s)
Test Site Location
Wind measurement instrumentation was installed on an existing 33 meter Rohn lattice-type
communication tower at the Red Dog Port area and approximately three kilometers (two miles) from
Red Dog Port Wind Resource Report P a g e | 3
the Chukchi Sea coast. The tower is located on a small gravel pad immediately adjacent to the haul road
which connects Red Dog Mine to Red Dog Port. There is considerable area in the near vicinity of the
Port complex to accommodate several or more large turbines.
Site information
Site number 9476
Latitude/longitude N 67° 35’ 48.90” W 163° 59’ 42.10”, WGS 84
Site elevation 49 meters (160 ft)
Datalogger type NRG Symphonie, 10 minute time step
Tower type Rohn lattice tower, 33 meter height
Topographic maps
Red Dog Port Wind Resource Report P a g e | 4
Google Earth image
Tower sensor information
Channel Sensor type Height Multiplier Offset Orientation
1 NRG #40 anemometer 32.6 m (33 m A) 0.760 0.36 000°T
2 NRG #40 anemometer 32.6 m (33 m B) 0.757 0.41 115° T
3 NRG #40 anemometer 20.7 m (21 m A)0.761 0.33 000°T
4 NRG #40 anemometer 20.7 m (21 m B) 0.758 0.33 115° T
7 NRG #200P wind vane 29.0 m 0.351 180 000° T
9 NRG #110S Temp C 3 m 0.138 -86.3 N
10 iPack batter voltmeter n/a 0.021 0 n/a
12 RH-5 relative humidity 2 m 0.098 0 N
Red Dog Port Wind Resource Report P a g e | 5
Tower sensors photo
Data Quality Control
Data quality is very good with data recovery of all four anemometers greater than 96 percent and data
recovery of the wind vane greater than 95 percent. Data loss is limited to winter months only and is
attributable to icing events which are characterized by non-variant output of the anemometer at the
minimum offset value (essentially zero) and by non-variant output of the direction vane at the last
operable direction with temperatures near or less than zero degrees Centigrade and relative humidity at
or near 100 percent.
Data recovery summary table
Label Units Height
Possible
Records
Valid
Records
Recovery
Rate (%)
Speed 33 m A m/s 32.6 m 148,962 144,189 96.8
Speed 33 m B m/s 32.6 m 148,962 143,962 96.6
Speed 21 m A m/s 20.7 m 148,962 144,176 96.8
Speed 21 m B m/s 20.7 m 148,962 144,871 97.3
Direction 29 m ° 29 m 148,962 142,369 95.6
Temperature °C 148,962 148,841 99.9
Voltmeter volts 148,962 148,841 99.9
RH-5 Humidity %RH %RH 148,962 148,841 99.9
Red Dog Port Wind Resource Report P a g e | 6
Anemometer and wind vane data recovery
33 m A 33 m B 21 m A 21 m B Vane
Possible Valid Recovery Recovery Recovery Recovery Recovery
Year Month Records Records Rate (%) Rate (%) Rate (%) Rate (%) Rate (%)
2008 Oct 3,168 2,862 90.3 90.3 89.8 90.3 76.3
2008 Nov 4,320 3,553 82.3 83.1 81.8 90.9 87.1
2008 Dec 4,464 4,188 93.8 93.8 93.8 93.8 95.1
2009 Jan 4,464 4,464 100.0 100.0 100.0 100.0 85.3
2009 Feb 4,032 4,032 100.0 100.0 100.0 100.0 100.0
2009 Mar 4,464 4,464 100.0 100.0 100.0 100.0 100.0
2009 Apr 4,320 4,200 97.2 97.2 97.2 97.2 97.2
2009 May 4,464 4,165 93.3 96.8 96.7 97.1 92.2
2009 Jun 4,320 4,320 100.0 100.0 100.0 100.0 100.0
2009 Jul 4,464 4,464 100.0 100.0 100.0 100.0 100.0
2009 Aug 4,464 4,464 100.0 100.0 100.0 100.0 100.0
2009 Sep 4,320 4,320 100.0 100.0 100.0 100.0 100.0
2009 Oct 4,464 4,157 93.1 93.1 93.1 87.4 95.7
2009 Nov 4,320 3,355 77.7 78.3 77.3 76.6 100.0
2009 Dec 4,464 3,981 89.2 89.2 89.2 89.2 100.0
2010 Jan 4,464 4,464 100.0 100.0 100.0 100.0 100.0
2010 Feb 4,032 4,032 100.0 100.0 100.0 100.0 100.0
2010 Mar 4,464 4,464 100.0 91.7 100.0 95.1 100.0
2010 Apr 4,320 4,320 100.0 100.0 100.0 100.0 84.8
2010 May 4,464 4,464 100.0 100.0 100.0 100.0 100.0
2010 Jun 4,320 4,320 100.0 100.0 100.0 100.0 100.0
2010 Jul 4,464 4,464 100.0 100.0 100.0 100.0 100.0
2010 Aug 4,464 4,464 100.0 100.0 100.0 100.0 100.0
2010 Sep 4,320 4,320 100.0 100.0 100.0 100.0 100.0
2010 Oct 4,464 4,464 100.0 100.0 100.0 100.0 100.0
2010 Nov 4,320 3,189 73.8 72.0 71.3 89.1 54.6
2010 Dec 4,464 4,464 100.0 100.0 100.0 100.0 74.7
2011 Jan 4,464 4,464 100.0 100.0 100.0 100.0 100.0
2011 Feb 4,032 4,032 100.0 100.0 100.0 100.0 100.0
2011 Mar 4,464 4,464 100.0 100.0 100.0 100.0 100.0
2011 Apr 4,320 4,320 100.0 100.0 100.0 100.0 100.0
2011 May 4,464 4,345 97.3 97.3 97.3 97.3 100.0
2011 Jun 4,320 4,320 100.0 100.0 100.0 100.0 100.0
2011 Jul 4,464 4,464 100.0 100.0 100.0 100.0 100.0
2011 Aug 1,362 1,362 100.0 100.0 100.0 100.0 100.0
All data 148,962 144,189 96.8 96.6 96.8 97.3 95.6
Red Dog Port Wind Resource Report P a g e | 7
Icing Event
The Red Dog Port communication tower site is at an elevation of less than 50 meters; hence rime icing is
not a concern. But freezing rain and other similar cold climate events do occur on occasion which can
compromise anemometer and wind vane data, but are not likely to seriously impede wind turbine
operations.
Apparent icing event, November 2009, temp and RH data
Apparent icing event, November 2009, anemometer data
Data Gap-fill
Although the overall loss of anemometer data due to icing was less than 95 percent, this includes the
summer months which naturally do not experience icing conditions. Wintertime icing loss was higher,
with data recovery of the anemometers in the 75 to 80 percent range in November 2011. In the quality
control process, ice event data is removed from the file to avoid biasing the mean wind speed low (i.e.,
logging zero wind speed when the wind is likely blowing), but that can create the opposite situation,
where the data set bias is high (i.e., no recorded wind speed during the ice periods, leaving just higher
wind speeds in the data set). To overcome these errors, a data gap-fill algorithm contained in
Windographer software was employed to synthesize missing data and create a statistically truer
representation of the Red Dog Port wind resource than the data without the gaps filled. Note: dotted
lines below are synthesized data.
Red Dog Port Wind Resource Report P a g e | 8
Gap-fill of November 2009 icing event
Wind Speed
Anemometer data obtained from the met tower, from the perspectives of both mean wind speed and
mean wind power density, indicate an excellent wind resource. Mean wind speeds are greater at higher
elevations on the met tower, as one would expect. Note that cold temperatures contributed to a higher
wind power density than otherwise might have been expected for the mean wind speeds. Also note, as
discussed in the previous section, that anemometer summary information is the table below is post gap-
fill. None gap-filled mean wind speeds and power densities are slightly higher than below.
Anemometer data summary
Variable
Speed 33 m
A
Speed 33 m
B
Speed 21 m
A
Speed 21 m
B
Measurement height (m) 33 33 21 21
Mean wind speed (m/s) 6.06 6.05 5.74 5.71
MMM wind speed (m/s) 6.02 6.02 5.71 5.68
Max 10-min avg wind speed (m/s) 38.5 36.7 36.1 34.4
Max gust wind speed (m/s) 43.5 41.8 42.0 40.5
Weibull k 1.24 1.26 1.28 1.31
Weibull c (m/s) 6.52 6.52 6.22 6.21
Mean power density (W/m²) 596 546 483 449
MMM power density (W/m²) 577 529 467 435
Red Dog Port Wind Resource Report P a g e | 9
Mean energy content (kWh/m²/yr) 5,223 4,782 4,232 3,935
MMM energy content (kWh/m²/yr) 5,050 4,634 4,093 3,810
Energy pattern factor 4.08 3.75 3.89 3.66
Frequency of calms (%) 44.5 43.3 45.9 44.9
1-hr autocorrelation coefficient 0.945 0.942 0.941 0.940
Diurnal pattern strength 0.046 0.041 0.066 0.062
Hour of peak wind speed 15 15 15 15
MMM = mean of monthly means
Time Series
Time series calculations indicate high mean wind speeds during the winter months with more moderate
mean wind speeds during summer months. This correlates well with the a typical village load profile
where winter months have a high electric and heat demand and summer months a lesser demand. The
opposite load profile exists however at Red Dog Port where summer loads are high and winter low.
33 m A anemometer data summary
Mean Max Gust
Std.
Dev.
Weibull
k
Weibull
c
Year Month (m/s) (m/s) (m/s) (m/s) (-) (m/s)
2008 Oct 6.89 20.2 23.1 4.59 1.50 7.62
2008 Nov 6.03 18.2 20.4 3.63 1.68 6.74
2008 Dec 11.21 28.9 32.6 7.20 1.45 12.27
2009 Jan 6.18 38.5 43.5 7.11 0.96 6.05
2009 Feb 7.92 30.8 36.7 7.53 0.97 7.83
2009 Mar 9.57 31.5 36.0 6.58 1.42 10.49
2009 Apr 5.91 22.7 28.0 4.96 1.13 6.17
2009 May 4.79 21.0 27.7 3.10 1.63 5.36
2009 Jun 4.12 14.9 19.3 2.56 1.67 4.62
2009 Jul 4.60 18.4 24.6 2.83 1.67 5.15
2009 Aug 5.12 18.1 22.4 3.08 1.70 5.74
2009 Sep 5.10 15.0 17.8 2.70 1.94 5.74
2009 Oct 5.69 21.0 24.6 3.80 1.54 6.33
2009 Nov 5.20 19.1 22.7 3.77 1.37 5.68
2009 Dec 8.52 27.4 32.6 6.55 1.29 9.21
2010 Jan 5.46 23.1 26.1 5.01 1.15 5.75
2010 Feb 5.01 17.1 19.7 3.82 1.27 5.39
2010 Mar 5.25 26.1 30.3 4.97 1.15 5.54
2010 Apr 5.43 27.3 32.1 4.42 1.33 5.94
2010 May 3.62 16.4 19.7 2.52 1.57 4.06
2010 Jun 3.36 13.7 18.9 2.36 1.51 3.74
2010 Jul 4.24 12.7 16.7 2.55 1.73 4.76
2010 Aug 4.71 15.5 21.6 3.11 1.55 5.24
2010 Sep 5.64 18.0 21.2 2.99 1.96 6.35
Red Dog Port Wind Resource Report P a g e | 10
2010 Oct 7.88 23.1 28.0 4.34 1.87 8.86
2010 Nov 8.14 20.2 25.0 5.24 1.61 9.10
2010 Dec 9.62 28.3 32.1 6.37 1.46 10.57
2011 Jan 7.00 25.9 29.5 6.74 0.97 6.92
2011 Feb 9.93 30.5 34.1 7.56 1.21 10.55
2011 Mar 5.99 25.7 29.1 6.47 0.90 5.69
2011 Apr 4.70 20.3 22.4 3.87 1.21 5.01
2011 May 5.02 19.3 21.9 3.77 1.41 5.54
2011 Jun 4.21 14.9 17.1 2.54 1.73 4.73
2011 Jul 4.47 15.4 21.6 2.72 1.70 5.01
2011 Aug 5.49 13.2 16.7 2.85 1.95 6.15
All data 6.06 38.5 43.5 5.11 1.24 6.52
MMM 6.02
Seasonal time series graph
Annual daily wind profile
Red Dog Port Wind Resource Report P a g e | 11
Monthly daily wind profile
Probability Distribution Function
The probability distribution function (PDF), or histogram, of Red Dog Port wind speed indicates a shape
curve dominated by lower wind speeds, as opposed to a “normal” shape curve, known as the Rayleigh
distribution (Weibull k = 2.0), which is defined as the standard wind distribution for wind power analysis.
As one can see in the PDF of 33 m A anemometer, the most frequently occurring wind speeds are
between 2 and 5 m/s with a number of wind events exceeding 25 m/s (the cutout speed of most wind
turbines; see following wind speed statistical table). Note also the Weibull k value which describes the
Red Dog Port site is unusually low and indicative, as one can see, of a site dominated by calm winds but
periodically exposed to high winds.
PDF of 33 m A anemometer
Red Dog Port Wind Resource Report P a g e | 12
Weibull k shape curve table
Occurrence by wind speed bin
Bin Endpoints
(m/s) Occurrences
Bin Endpoints
(m/s) Occurrences
Lower Upper No. Percent Lower Upper No. Percent
0 1 12,529 8.64% 20 21 878 0.61%
1 2 15,229 10.50% 21 22 733 0.51%
2 3 18,666 12.88% 22 23 610 0.42%
3 4 18,537 12.79% 23 24 482 0.33%
4 5 15,125 10.43% 24 25 374 0.26%
5 6 12,586 8.68% 25 26 290 0.20%
6 7 10,116 6.98% 26 27 202 0.14%
7 8 8,187 5.65% 27 28 141 0.10%
8 9 6,488 4.48% 28 29 88 0.06%
9 10 5,123 3.53% 29 30 76 0.05%
10 11 4,478 3.09% 30 31 47 0.03%
11 12 3,483 2.40% 31 32 23 0.02%
12 13 2,981 2.06% 32 33 12 0.01%
13 14 2,569 1.77% 33 34 11 0.01%
14 15 2,220 1.53% 34 35 9 0.01%
15 16 1,836 1.27% 35 36 2 0.00%
16 17 1,299 0.90% 36 37 3 0.00%
17 18 1,242 0.86% 37 38 3 0.00%
18 19 1,169 0.81% 38 39 2 0.00%
19 20 1,113 0.77% 39 40 0 0.00%
Wind Shear and Roughness
A wind shear power law exponent () of 0.127 indicates low to moderate wind shear at the site. Related
to wind shear, a calculated surface roughness of 0.0079 meters (indicating the height above ground
level where wind velocity would be zero) indicates very smooth terrain (roughness description: lawn
Red Dog Port Wind Resource Report P a g e | 13
grass) surrounding the met tower. These data indicate that it might be possible to construct turbines at
a lower hub height for cost saving purposes, yet still obtain high energy production.
Vertical wind shear profile
Comparative wind shear profiles
Extreme Winds
A modified Gumbel distribution analysis, based on monthly maximum winds vice annual maximum
winds, was used to predict extreme winds at Red Dog Port. Due to the unusual seasonal variation in
wind speeds at the site and in an effort to better match the monthly data Gumbel approach to the
annual data approach, a further modification to the analysis was made to exclude May through
September data.
Note below that the extreme wind analysis shows relatively energetic extreme winds compared to the
measured mean wind speeds. Industry standard reference of extreme wind is the 50 year probable (50
year return period) ten-minute average wind speed, referred to as Vref. For Red Dog Port, with the
assumptions noted above, this calculates to 42.4 m/s (at 33 meters), which is on the threshold of
International Electrotechnical Commission (IEC) 61400-1, 3rd edition criteria Class I site and possibly
Red Dog Port Wind Resource Report P a g e | 14
should be considered as such. Note that Class I or II extreme wind classifications indicate the possibility
of highly energetic wind events. Not all wind turbines are designed for IEC Class I or II winds, so this
must be considered during turbine selection.
Extreme wind probability table, 33 m A data
Vref Gust IEC 61400-1, 3rd ed.
Period (years) (m/s) (m/s) Class Vref, m/s
3 33.4 38.7 I 50.0
10 37.3 43.2 II 42.5
20 39.5 45.8 III 37.5
30 40.8 47.3 S designer-
specified5042.4 49.2
100 44.6 51.7
average gust
factor: 1.16
Extreme wind graph
Temperature, Density, and Relative Humidity
The Red Dog Port area experiences cool summers and very cold winters with resulting higher than
standard air density. Calculated mean-of-monthly-mean air density during the met tower test period
exceeds the 1.219 kg/m
3 standard air density for a 49 meter elevation by 7.0 percent. This is
advantageous in wind power operations as wind turbines produce more power at low temperatures
(high air density) than at standard temperature and density.
25.0
30.0
35.0
40.0
45.0
50.0
55.0
0 10 20 30 40 50 60 70 80 90 100
Period, years
Vref
gust
Red Dog Port Wind Resource Report P a g e | 15
Temperature and density table
Temperature Air Density
Month Mean Min Max Mean Min Max
(°C) (°C) (°C) (kg/m³) (kg/m³) (kg/m³)
Jan -17.6 -36.2 3.7 1.375 1.267 1.481
Feb -16.7 -39.8 3.4 1.370 1.269 1.504
Mar -14.9 -36.7 3.3 1.360 1.269 1.484
Apr -7.6 -24.9 9.1 1.321 1.219 1.413
May 2.4 -14.9 23.6 1.274 1.182 1.359
Jun 9.9 -3.2 26.7 1.240 1.170 1.300
Jul 12.2 -0.4 28.8 1.230 1.162 1.286
Aug 10.4 -2.8 22.2 1.238 1.188 1.298
Sep 5.9 -10.5 19.1 1.258 1.201 1.336
Oct -3.4 -18.8 10.9 1.301 1.219 1.379
Nov -11.9 -28.2 2.3 1.343 1.274 1.432
Dec -12.8 -33.9 6.3 1.348 1.256 1.466
Annual -3.6 -39.8 28.8 1.305 1.162 1.504
Annual temperature boxplot
Temperature data, measurement period
Red Dog Port Wind Resource Report P a g e | 16
Air density DMap
Wind Speed Scatterplot
The wind speed versus temperature scatterplot below indicates that a substantial percentage of wind at
Red Dog Port coincides with cold temperatures, as one would expect. However, during the met tower
test periods, temperatures did not fall below -40°C, which is the minimum operating temperature for
arctic-capable wind turbines, but did fall below -30°C on a substantial number of occasions, but as one
can see, periods of extreme cold are characterized by relatively light winds. Also note that periods of
very high winds (wind speeds greater than 30 m/s) are also characterized by cold temperatures,
between -5°C and -20°C. Colder temperatures than recorded during the test period may occur during
particular severe winters, but it is likely that temperatures colder than -40°C are extremely rare at the
site. Hence, restrictions of wind turbine operations due to extreme cold should not be expected.
Wind speed/temperature
Red Dog Port Wind Resource Report P a g e | 17
Wind Direction
Wind frequency rose data indicates that winds at Red Dog Port are highly directional, with northeasterly
and southeasterly wind predominating. The mean value rose indicates that southeasterly winds, when
they do occur, are of high energy and hence likely storm winds. The wind energy rose indicates that for
wind turbine operations power-producing winds are very strongly southeastern dominant. Calm
frequency (percent of time that winds at the 50 meter level are less than 4 m/s) was a very high 45
percent during the met tower test period.
Wind frequency rose Mean value rose (33 m A anem.)
Wind energy rose (33 m A anem.) Scatterplot rose of 33m A wind power density
Red Dog Port Wind Resource Report P a g e | 18
Wind density roses by month (common scale)
Turbulence
Turbulence intensity (TI) at the Red Dog Port test site is well within acceptable standards with an IEC
61400-1, 3rd edition (2005) classification of turbulence category C, which is the lowest defined. The
mean TI at 15 m/s is 0.069 and the representative TI at 15 m/s is 0.096, both which can be considered
extraordinarily low and hence very desirable for wind turbine operations.
Turbulence intensity, 33m B, all direction sectors
Red Dog Port Wind Resource Report P a g e | 19
Turbulence table, 33m B data
Bin Endpoints
Records
in Bin Mean TI SD of TI
Representative
TI Peak TI
Lower Upper
(m/s) (m/s)
0.5 1.5 12,626 0.420 0.172 0.640 1.333
1.5 2.5 15,946 0.217 0.116 0.366 1.067
2.5 3.5 17,579 0.152 0.080 0.254 0.840
3.5 4.5 15,929 0.124 0.067 0.210 0.875
4.5 5.5 12,858 0.103 0.057 0.176 0.681
5.5 6.5 11,533 0.092 0.048 0.154 0.691
6.5 7.5 9,401 0.086 0.045 0.144 0.681
7.5 8.5 7,922 0.081 0.038 0.130 0.494
8.5 9.5 6,081 0.080 0.035 0.125 0.418
9.5 10.5 4,894 0.081 0.033 0.123 0.418
10.5 11.5 4,088 0.079 0.029 0.116 0.333
11.5 12.5 3,351 0.076 0.027 0.110 0.271
12.5 13.5 2,826 0.072 0.025 0.104 0.291
13.5 14.5 2,477 0.069 0.023 0.098 0.229
14.5 15.5 1,819 0.069 0.021 0.096 0.243
15.5 16.5 1,575 0.066 0.020 0.092 0.172
16.5 17.5 1,324 0.068 0.019 0.093 0.155
17.5 18.5 1,235 0.066 0.019 0.090 0.167
18.5 19.5 1,072 0.065 0.017 0.087 0.168
19.5 20.5 841 0.063 0.015 0.083 0.150
20.5 21.5 659 0.063 0.016 0.084 0.156
21.5 22.5 574 0.063 0.017 0.085 0.148
22.5 23.5 394 0.060 0.013 0.077 0.123
23.5 24.5 305 0.060 0.013 0.077 0.110
24.5 25.5 217 0.058 0.011 0.073 0.093
25.5 26.5 132 0.059 0.010 0.072 0.089
26.5 27.5 90 0.060 0.010 0.073 0.083
27.5 28.5 68 0.061 0.009 0.073 0.079
28.5 29.5 38 0.058 0.011 0.072 0.093
29.5 30.5 20 0.057 0.006 0.064 0.070
30.5 31.5 9 0.053 0.010 0.066 0.068
31.5 32.5 11 0.049 0.008 0.059 0.060
32.5 33.5 6 0.056 0.007 0.064 0.067
33.5 34.5 3 0.051 0.004 0.057 0.056
34.5 35.5 3 0.054 0.005 0.060 0.058
35.5 36.5 3 0.052 0.005 0.059 0.058
36.5 37.5 1 0.052 0.000 0.052 0.052
Kivalina Conceptual Design Report P a g e | C
Appendix C – FAA Notice Criteria Tool, Wulik River Site
WHPacific, Inc. and V3 Energy, LLC 7 May 2014
Kivalina Conceptual Design Report P a g e | D
Appendix D – FAA Notice Criteria Tool, Kisimigiuktuk Hill Site
WHPacific, Inc. and V3 Energy, LLC 7 May 2014
Kivalina Conceptual Design Report P a g e | E
Appendix E – FAA Notice Criteria Tool, Red Dog Port Site
WHPacific, Inc. and V3 Energy, LLC 7 May 2014