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Ian Snow

ENGR 3060

Astrid Fehling

Jennifer Smith

Patrycja Einarsdóttir

Ísafjörður – Iceland’s Energy Frontier:

A Basic Wind Resource Assessment

Abstract

This paper is a preliminary investigation of wind resources surrounding the town of Ísafjörður,

Iceland. The purpose is to determine the viability of adding wind power to the electrical grid in the capital

of the Westfjords region, in order to improve self-sufficiency. This research is important as the region

currently purchases a large portion of its electricity from producers in Reykjavík, through an unreliable

grid connection. Little to no research has been done on the feasibility of employing wind energy in the

area. The paper uses wind data provided by the Snjóflóðasetur branch of Veðurstofa Íslands for the years

of 2013 and 2014, finding that there are suitable wind resources in the Westfjords capital region for

valuable wind development, which will be fully exploitable with further research investment.

Background

Of the few truly renewable electricity sources, wind turbine energy is arguably the most “mature”

technology. It can produce a large amount of power, with more certainty than solar power, has less

environmental impact than hydropower, and is more available than geothermal. Even in a country like

Iceland, where there is an abundance of hydro and geothermal energy, there are areas, specifically the

Westfjords, which could benefit from wind energy to increase energy supply and self-sufficiency.

Iceland as a whole produces nearly all of its electricity through hydropower harnessed from the

large glacial rivers, which flow all year round. Most of the country’s hot water and space heating comes

from natural geothermal sources that are prominent near the largest population centers of Iceland. These

volcanic hot spots arise because the Mid-Atlantic rift runs nearly through the middle of the country.

However, towards the east and west coasts of Iceland, where the crust is oldest and furthest from the rift,

there are only low temperature geothermal springs, unsuitable for electricity production (Dvorak 2015).

Due to the comparatively low geothermal resource in the Westfjords, 70 percent of heating is provided by

electricity (Magnússon 2015), making the electricity demand of the region much higher than the rest of

the country residentially. In addition, there is not enough geothermal or hydropower electricity in the

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Westfjords in total, and the power provider Orkubú Vestfjarða, must purchase 55 percent of the electricity

they distribute from the primary producer, state-run Landsvirkjun (Haraldsson 2015, 4). Finally, there are

indications that a trash incinerator will need to be introduced in the future, increasing total energy demand

for the area (Trylla 2015). A local and small-scale wind power development would increase self-

sufficiency and production within the region itself, alleviating the impacts of these issues.

Despite a generally harsh climate, the coastal areas of the Westfjords do offer the opportunity for

wind development, as there are constant land and sea breezes, which may offer a sufficient wind resource

to power the largest towns of the Westfjords, Ísafjörður and Bolungarvík.

Research Question

Are there any suitable sites for wind power development surrounding Ísafjörður based on a

variety of criteria, and which of those sites has the strongest wind resource?

Review of Literature

Due to the current energy situation in Iceland, where most if not all electricity is created through

geothermal and hydropower, there are doubts that “electricity generated by wind power will become

competitive in Iceland,” (Askja 2011). This may be true on a large scale, but in the way that Iceland is a

microcosm of economy, so are the Westfjords to the country as a whole. With such a frame, it is easy to

see that there is room for wind development, with Orkubú Vestfjarða buying so much through the grid

connected to Reykjavík. In terms of security and self-sufficiency, it is also beneficial that “wind has a

maximum power generation potential at winter time while hydro at summer time,” (Ragnarsson 2014, 6).

This conclusion appears concurrent with many assessments, finding that “average power density in winter

is increased throughout Iceland...with the largest increases…along the complex coastline of the

Westfjords,” (Nawri et al. 2015). This means that during the winter, when the Westfjords must buy even

more heating power from Reykjavík, wind turbines would be able to compensate for the diminished

hydropower and maintain the local base load. Despite these possible applications, all of the in-depth wind

assessments for Iceland have been large scale, modeling the entire resource of Iceland. This is simply

because there are higher capacity factors and therefore economic possibilities; even the best sites in the

Westfjords are often ranked lowest among those surveyed (Helgasson 2012).

Despite the disregard by large developers, the area surrounding Ísafjörður offers several

promising sites for small wind development that might prove useful in reducing the Westfjords’ grid

dependency. To find wind these resources, it is first necessary to understand the basic and agreed upon

assumptions about what constitutes a good wind resource for power generation. The quantities used to

describe and categorize wind are generally wind speed, direction, turbulence, temperature, pressure,

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moisture, and density (Lundquist 2015). Some of these values such as pressure, moisture, and density can

be assumed for normal conditions and a basic assessment; but speed, direction, turbulence, and

temperature need to be measured directly. The most important of these factors is wind speed, as higher

velocity contains more kinetic energy that can be harnessed and turned into mechanical energy and finally

electricity by a turbine. Wind speed is affected by friction with the ground and objects, and therefore

higher speeds are found aloft or where there is low surface roughness (Lundquist 2015). Additionally,

topography can affect wind flow significantly in mountainous areas like the Westfjords. For example, it is

assumed that wind speeds increase over peaks, and are funneled through valleys, both prevalent in the

area (Lundquist 2015). Additionally, there are diurnal forces like land-sea breezes, slope-wind, and along-

valley systems, where varying temperature and pressure gradients between elevation or land and sea

cause winds to blow nearly all the time and in predictable directions, making them valuable for wind

development (Lundquist 2015).

Hypothesis

If several weather station sites surrounding Ísafjörður and Bolungarvík are profiled for wind

resources, Þverfjall will prove the best site, because it is affected both by land-sea breezes as well as a

slope wind system and has very low surface roughness, as the high elevation is often covered with snow

and has little to no vegetation.

Methods

Magni Jónsson of Veðurstofa Íslands was able to offer advice about four meteorological station

sites around Ísafjörður, best suited for wind resource profiling: Ísafjörður, Bolungarvík, Þverfjall, and

Seljalandsdalur (See Figure 1). He suggests that the higher elevation sites (Seljalandsdalur and Þverfjall)

might be the best for wind resources. This is concurrent with information about where wind resources are

typically found, as previously discussed.

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Figure 1 Sites for Consideration

Jónsson provided four sets of hourly wind data, comprised of two years’ worth of wind speed,

direction, and temperature spanning from January 22, 2013 to January 22, 2015 (See Appendix A Figures

1-4). The data is used to determine which area has the most optimal average wind speed, the most

constant wind direction, expected capacity factor, the best temperature environment, maximum speed,

and minimum temperature.

All of the values will be calculated assuming the installation of Enercon E44 turbines as they are

the preferred turbine model for Iceland, used in several professional modelling studies (Nawri et al.

2015), as well as the only installed turbines in Iceland at Búrfell. The average wind speed at a typical hub

height of 50m for Enercon E44 turbines was derived from a series of equations. All of the raw data was

collected at surface level (2m), so each wind speed datum required extrapolation to a 50m speed using the

equation shown in Figure 2, called the Power Law.

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Figure 2 The Power Law for Wind Shear. Source: Lundquist 2015.

Here the desired height is 50m and the reference height 2m, and alpha is a value that depends on

the environment of the site, as described by Table 1.

Table 1.

Typical Wind Shear Exponents.

Source: Julie Lundquist, Estimating the Wind Resource (University of Colorado Boulder, 2015).

The Bolungarvík and Ísafjörður meteorological sites most closely resemble sloping terrain with

drainage flows, as they sit in the mouth/ low valleys of fjords. Therefore, the mean value of that shear

range (0.125) was used. The Þverfjall and Seljalandsdalur sites are at higher elevations above the edge of

the fjords however, and therefore resemble exposed ridgetops, and will have the mean alpha value of that

range (0.12). These values match previous studies, which assumed an alpha of 0.12 for all locations

(Helgason 2012).

Calculating the average wind speed followed the equation in Figure 3, by first binning all the

wind speed data in Excel in 1m/s bins ranging from the minimum to maximum wind speeds observed.

Then the speed column was multiplied by the frequency. The final step is to divide that product by the

number of observations that were recorded (substituting for 8760 in the figure).

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Figure 3 Calculation for Mean Hourly Frequency. Source: Dvorak 2015.

An ideal site will have an average wind speed near 15m/s at 50m height and not exceed 28m/s

(Dvorak 2015) considering the size and technical operating capabilities of the Enercon E44.

To compare the wind directions of each site, it is helpful to find the percentage of time at which

the wind blows in certain directions. To do this, the direction data was similarly binned in Excel, filling

bins of 30 degrees, by closest values. These bins therefore give a percentage for each direction when

divided by the total number of data points. These percentages can be used to create wind roses. An ideal

site will have the least amount of variability in wind direction.

The temperature data was averaged over the two years using the same frequency binning method.

An ideal site will have the highest temperatures, as icing can be detrimental for wind turbines, particularly

in a climate such as Iceland’s.

Another data manipulation that is possible with the calculations already given is to calculate an

estimated capacity factor following the equation in Figure 4.

Figure 4 Capacity Factor for Electrical Generation. Source: Lundquist 2015.

Capacity factor was determined for each site by first collecting the frequency of wind speeds up

to 28 m/s, the cutout speed of the E-44 turbine. Those frequencies were then multiplied by the power in

kW depending on speed, as calculated by Enercon (see Appendix B Figure 1), giving actual generation

expected. Maximum generation is found by multiplying the rated capacity (910 kW) by the number of

observations (Enercon 2012).

Finally, the maximum wind speeds and minimum temperatures at each site were determined, as

those factors can be detrimental in generating wind, where either can damage the turbine and require

curtailment.

As a supplementary, but non-data based factor, each site was analyzed in terms of visual and

noise pollution for residents, based on the locations of each site on the topographical map.

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Results

After calculation, the six values considered were compiled in Table 2. The table reads top to

bottom, from highest average speed to lowest, as this is often the most essential component of a wind

resource. Though average speed and capacity factor appear to be directly related, the other factors are not

consistently ranked, and therefore fall in no particular order, reading left to right. Noise and visual

pollution are represented in the results table as simple a Y for yes or N for no pollution effects based upon

their location in figure 1. The table demonstrates that Þverfjall had the most desirable values for average

speed, direction, capacity factor, and pollution.

Table 2.

Wind Resource Assessment Results.

The wind direction data was also used to create wind roses (See Annex B Figures 2-5), useful for

visualizing the wind direction for potential developers, as well as for comparing the sites. A site with

most of the shape in one direction is desirable, showing not only where the highest percentage of

observations were, but also how closely the rest of the data surrounds that direction.

Discussion

The results of the data analysis are ample to answer the original research question, showing that

there are certainly suitable wind power development sites surrounding Ísafjörður. This can be seen from

the capacity factors as “typical wind power capacity factors have been shown to be in the range 20-40%,”

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(Helgason 2012, 12). All of the calculated capacities are within this range or above, and therefore viable

wind development sites in terms of possible power production. However, Bolungarvík and

Seljalandsdalur performed poorly compared to Þverfjall and Ísafjörður, and therefore will not be

discussed further.

Analysis of Þverfjall

Regarding average speed and capacity factor, the results appear to confirm the hypothesis and

assumption that Þverfjall has the greatest and most exploitable wind resource. The mean average wind

speed is near double that of all the other sites, a convincing metric that the wind resource at Þverfjall is

the most powerful. Moreover, “a capacity factor above 40% is regarded very good for wind turbine

location,” (Helgason 2012, 33) and the Þverfjall 56% is significantly higher than the measured “average

capacity factor of 40.51%” (Ragnarsson 2014, 39) at the only Icelandic turbine site at Búrfell.

However, an expected capacity factor resulting from a wind speed calculation is not always

perfectly representative. There are studies showing in fact, that it is almost predictable that expected

capacity factors are higher than realized values where it “has been assumed in the 30–35% range … Yet,

the mean realized value for Europe over the last five years is below 21%,” (Boccard 2009, 1). This is

crucial for Þverfjall because there are two important figures that must be considered, as they will likely

result in curtailments. Specifically, Þverfjall performed worst in both average temperature and maximum

wind speed.

The temperature performance is rather complicated, where the very low minimum observed at

Þverfjall is not as troublesome as the average temperature there. At first, it would seem that a minimum

temperature of -17.8°C would be very detrimental to a wind development project and might even be a

deciding barrier against construction. However, the measured temperatures at the current wind site at

Búrfell showed that “the temperature went below -20 C, 20 times in total… the site does not qualify as a

LTC site according to IEA,” (Ragnarsson 2014, 38) where an LTC is a Low Temperature Climate

deemed unsuitable for any turbines. Thus, the temperature observed at Þverfjall is more favorable than

those at Búrfell, so the value of minimum temperature can be considered negligible for this and the other

four sites. The more concerning output value is the average -0.8°C at Þverfjall. This is because according

to the International Energy Agency (IEA), anything below 0°C is considered an Icing Climate for wind

turbines (International Energy Agency 2011, 16). Thus, any time spent below zero degrees has the

potential to reduce energy production, and thereby the realized capacity factor.

The maximum wind speed is perhaps the more concerning metric for developing at Þverfjall. This

is because the “E44 wind turbine … is guaranteed by the manufacturer to withstand at least 50 m/s wind

speed,” (Ragnarsson 2014, 38). This means that any wind values above 50 m/s present a potential

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structural hazard for the turbine itself. In the data analysis, there were 14 hours during which the wind

speed exceeded 50 m/s at hub height. Though this is a low number of observations when compared with

nearly 20,000 total datum, it might be enough to deter a wind developer from the site, as any structural

damage to a turbine is a terrible cost, not only in terms of replacement, but in terms of production time

lost during repair.

Analysis of Ísafjörður

Considering the detrimental values observed at Þverfjall, the best option for development will be

Ísafjörður itself. This site performed favorably in precisely the areas that discourage Þverfjall, average

temperature and maximum speed. With the highest average temperature, there will be fewer curtailments

and losses due to icing. With a lower maximum wind speed, there will also be less damage risk than

presented at Þverfjall, and therefore more attractive to development. Although the capacity factor is

significantly lower in Ísafjörður, it is still well within the typical range already discussed. Despite this

trade-off, it is likely that more certainty provided at Ísafjörður will be valued more than a predictably

unpredictable capacity factor at Þverfjall.

Despite the advantages of Ísafjörður, one negative factor is important to consider. Constructing

wind turbines, even if only a few, within the limits of Ísafjörður presents an issue of noise and visual

pollution. There are guidelines for noise disruption of wind turbines, where more than a quarter mile

distance from residences and less than a 5-decibel change in ambient noise level at residences is expected

to garner no community response (Lundquist 2015). These guidelines ought not to be devastating,

considering the low population of Ísafjörður and much unused space. The more serious issue is that of

visual pollution, where 50 meter tall turbines will be noticeable anywhere near the town, and could

impact the tourist industry in terms of visually polluting what is authentic nature and culture. This is a

crucial consideration as tourism in Iceland has surpassed fisheries and aluminum smelting as the

country’s largest industry and income, with Ísafjörður being the third most visited town by cruise ships

(Óladóttir 2014, 2-4). Additionally, there are already many people leaving Ísafjörður and Bolungarvík due

to lack of job opportunities. Therefore, it is absolutely necessary that any wind development does not

negatively affect tourism and the income from that business.

In terms of the visual and noise pollution, Þverfjall is likely the best site, as it is located far from

the towns, atop the wall of a neighboring fjord. Nevertheless, considering the drawbacks there, it is

worthwhile to consider how the pollution problem might be avoided in Ísafjörður. There are methods that

can determine if there will be a negative effect on tourism if turbines are constructed. For example, a

survey of inhabitants should be conducted to determine support and public outreach must explain the risk

of effects on tourism. Furthermore, it is possible to conduct surveys with current and former tourists to

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determine the opinion on whether or not turbines would lessen attraction to the area. This might be done

using an economic travel cost method, where tourists state how much money they have spent on a certain

travel location and how much they would spend there in the future based on criteria such as untouched

nature, authenticity, etc. (Peterson 2015).

Of course, there are several other important investigations needed for a full resource and

feasibility analysis before development can commence in Ísafjörður, but these are beyond the scope of

this study. These would include economic considerations like the cost of installation and effects on

electricity price, more extensive data collection, and in depth wind modelling of the fjord environment. If

Ísafjörður were to perform well in all these aspects, then it would be ready for development. If not, the

same investigations should be conducted for Þverfjall.

Limitations

There are several limitations to this study, primarily related to the available data. Because there

was a time constraint on the project, it was only possible to consider two years’ worth of data for four

sites, where a professional assessment would include many more years’ worth of data and additional sites.

Moreover, the data available only included wind speed, direction, and temperature. As stated in the

background section a proper wind assessment would also include turbulence, pressure, moisture, and

density. This study is also limited due to available resources, contacts, time, and scope, only briefly

stating the considerations of economics, public support, cost, etc. which must all be researched fully for a

true resource assessment.

The most significant limitation for this study, within its scope however, is that the data was only

available at surface level. This is a problem because it was necessary to estimate the alpha factor in

extrapolating wind speeds at elevation. Although the values used have extensive research backing, it is

ideal to have at least a small data set at elevated height, even at only 10 meters, as this can be used to

calculate a more accurate alpha value (See Appendix B Figure 6) and used for all of the data in that area.

There is also no method for extrapolating temperature at height, though it can be assumed that it is lower

than at surface level, and therefore a similar weakness of this study.

In addition to no tall towers for direct measurement at height, the only anemometers used to

measure wind speed were prop anemometers with an attached wind vane for direction measurement.

These type of anemometers are prone to “under-speeding” (Lundquist 2015), meaning that measured and

extrapolated wind speeds are likely below the real world value, an important implication for cut-out

speeds and dangerous maximum speeds.

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Conclusion and Suggestions

Although the original hypothesis that Þverfjall would prove the most suitable site for wind

development near Ísafjörður was not accurate after analysis of intangible factors, the study was useful in

showing that there are significant wind resources in the region. This is evident considering the typical

calculated capacity factors and predictable wind directions for the sites considered, particularly Þverfjall

and Ísafjörður. When comparing the results of all sites and six important factors, within the limits of the

town of Ísafjörður appears to be the most reliable site for wind development.

Considering the limitations of the results for Ísafjörður, the most apparent suggestion is to first

survey tourists and locals. The next step will be to conduct further modeling and data collection by

constructing meteorological towers and using multiple instruments, in locations near the original data

collection site. With adequate further research and planning, wind development near Ísafjörður may prove

important in creating a secure and renewable electricity future for the area.

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References

Boccard, Nicolas. 2009. “Capacity Factor of Wind Power Realized Values vs. Estimates.” Energy Policy 37 (7): 2679–88. doi:10.1016/j.enpol.2009.02.046.

Dvorak, David. "Wind Energy." Engineering 3000. University of the Westfjords, Ísafjörður. 29 May 2015. Lecture.

“Enercon Product Review.” Enercon, last modified April 2012. http://www.enercon.de/p/downloads/ENERCON_PU_en.pdf

“Enercon System Concept.” Enercon, accessed July 11, 2015, http://www.enercon.de/en-en/60.htm.

Haraldsson, Kristján. “Ársskýrsla 2014” Orkubú Vestfjartha. 2014. Web. 26 July 2015. < https://www.ov.is/um_fyrirtaekid/arsskyrslur/skra/317/>.

Helgason, Kristbjorn. Selecting Optimum Location and Type of Wind Turbines in Iceland. Diss. Reykjavík U, 2012. Reykjavík: School of Science and Engineering, 2012. Print.

Icelandic Tourist Board. Tourism in Iceland in Figures – April 2014. By Oddný Þóra Óladóttir. April 2014. Web. 27 July 2015.<http://www.ferdamalastofa.is/static/files/ferdamalastofa/Frettamyndir/2014/mai/toursim_in_icland_infigf2014.pdf>

International Energy Agency. Executive Committee for Research, Development and Deployment on Wind Energy Conversion Systems. Wind Energy Projects in Cold Climates. By Ian Baring-Gould, Rene Cattin, Michael Durstewitz, Mira Hulkkonen, Andrea Krenn, Tim Laakso, Antoine Lacroix, Esa Peltola, Goran Ronsten, Lars Tallhaug, Tomas Wallenius. May 22, 2012.

Lundquist, Julie. "Estimating the Wind Resource." Wind Energy Meteorology 4770. University of Colorado, Boulder. 24 Feb. 2015. Lecture.

Magnússon, Halldór. “Orkubú Vestfjarða.” Presentation at University Centre of the Westfjords, Ísafjörður, Iceland, June 25, 2015.

Nawri, Nikolai. "The Wind Energy Potential of Iceland." ScienceDirect. Elsevier, n.d. Web. 30 June 2015. <http://www.sciencedirect.com/science/article/pii/S0960148114002043>.

Ragnarsson, Birgir. Wind Energy Potential Assessment & Cost Analysis of a Wind Power Generation System at Búrfell . Diss. U of Iceland, 2014. Reykjavík: School of Engineering and Natural Science, 2014. Print.

Richardson, Peter. “Valuation.” Environmental Economics 3545. University of Colorado, Boulder. 5 March 2015. Lecture.

Trylla, Ralf. “Environmental Management” Engineering 3000. University of the Westfjords. Ísafjörður. 1 June 2015. Lecture.

"Wind Energy Potentials." Askja Energy The Independent Icelandic Energy Portal. N.p., 11 Nov. 2011. Web. 30 June 2015. <http://askjaenergy.org/iceland-renewable-energy-sources/wind-energy-potentials/>.

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Appendix A Condensed Data

Figure 1 Þverfjall Condensed Data

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Figure 2 Ísafjörður Condensed Data

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Figure 3 Seljalandsdalur Condensed Data

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Figure 4 Bolungarvík Condensed Data

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Appendix B Supplementary Figures

Figure 1 Expected Power Generation by Wind Speed for the E-44. Source: Enercon 2012.

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Figure 2 Þverfjall Wind Direction Rose Figure 3 Ísafjörður Wind Direction Rose

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Figure 4 Seljalandsdalur Wind Direction Rose Figure 5 Bolungarvík Wind Direction Rose

Figure 3 Calculation for the Wind Shear Exponent. Source: Lunduist 2015