WIND FullView Initial Site Assessment Yellowstone May 06, 2010 FOR CONTACT Client [email protected]www.3tier.com 2001 6th Avenue, Suite 2100 Seattle, WA 98121-2534 ph: +1 206.325.1573 fax: +1 206.325.1618 NOTICE Copyright c 2010 3TIER, Inc. All rights reserved. 3TIER claims a copyright in all proprietary and copyrightable text and graphics in this Report, the overall design of this Report, and the selection, arrangement and presentation of all materials in this Report. This work may be redistributed only in its entirety. Partial redistribution is prohibited without express written permission from 3TIER. Requests for permission may be directed to [email protected].
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3TIER has been retained by Client to assess the wind resource over the Yellowstone region, and our analysis is presentedin this report. This summary section discusses the overall properties of the project. Following it, section 2 shows the meanwind speed and capacity factor over the entire Yellowstone region, at 200m resolution, and displays turbine and referencepoint locations. Section 3 contains mean wind speeds and wind and power roses at the 5 reference points provided byClient. Project-wide monthly, hourly, and annual means for wind speed and capacity factor can be seen in section 4.
In section 5, tabular data for each turbine are available, including location, base elevation, mean wind speed (at hubheight), mean air density (also at hub height), and wind shear between 30m and 80m. The turbine power curve for theSWT23 (with hub height 80m) is also provided, in Table 5. For overall project data and production statistics, see Table 1directly below. These quantities are computed over every turbine location (see section 5), and do not include data fromthe reference points.
Project mean wind speed 7.97 m/sAverage air density across turbines 0.89 kg/m3
Average turbine base elevation 3024 mProject gross capacity factor 39.5 %Project gross energy production 53.6 MWProject net capacity factor 33.4 %Project net energy production 45.3 MW
Table 1: Project statistics
Statistics for the turbines with the highest and lowest mean gross capacity factor can be seen below, in Table 2. Additionalinformation for these and all 59 turbines can be found in Section 5.
T055 (best)
Mean wind speed 9.88 m/sGross capacity factor 56.1 %Gross energy production 1.3 MW
T007 (worst)
Mean wind speed 6.43 m/sGross capacity factor 25.5 %Gross energy production 0.6 MW
Table 2: Statistics for the best and worst turbines
Client has provided 3TIER with 59 turbine locations to be used in an analysis of the wind resource across the Yellow-stone region (see section 2 for the locations of these turbines). At each of these turbine locations, timeseries data wereextracted from the model output and used to compute the capacity factor for that turbine. Detailed information for eachturbine can be seen in section 5, and the overall production statistics for the project can be seen on the previous pagein Table 1. Additionally, information on the best and worst performing turbines can be seen in Table 2. For referencepurposes, the power curve for the SWT23 turbine is provided in Table 5.
Client has also specified the loss factors listed in Table 3 below. These were used to compute the net production statistics,which can be seen in Table 1 on the previous page, as well as in Figure 8 in section 4.
In addition to turbine locations, Client has provided 5 meteorological reference points, which are labeled on the maps insection 2. Wind speed and direction timeseries were extracted at these points, and an analysis is presented in section 3,which includes the overall mean wind speeds at each reference point, and wind and power roses showing the distributionof wind direction. Section 3 is meant to provide an easily readable overview of the wind resource over the area.
3TIER used a numerical weather prediction model, the Weather Research and Forecasting model (WRF), to analyze thewind resource across the Yellowstone region, and downscaled that dataset to 200m using our proprietary Time-VaryingMicroscale (TVM) model. WRF enables a very sophisticated but computationally intensive simulation of the dynamicaland physical processes of the atmosphere, and the TVM model complements it by using diagnostic techniques to analyzemicroscale processes without the prohibitive computational cost of running WRF at high resolution. Initial and lateralboundary conditions for WRF were extracted from the NCEP/NCAR Reanalysis data, a multi-decadal coarse-resolutionobservational dataset sufficient to provide accurate representation of synoptic-scale processes. In this case, WRF was runon a 5km grid from January 1999 through December 2008, then downscaled to a 200m grid using TVM.
After the spatial dataset was generated, the wind resource was analyzed at each reference point and turbine location (asprovided by Client), and the results are presented in this report. Additionally, several project-wide statistics are computed(see Table 1 above).
Since no observational data were provided within the Yellowstone region, the data in this report represent raw modeloutput only.
This section presents spatial maps of the average simulated wind speed and capacity factor at 80m across the Yellow-stone region. All maps within this section represent the raw model output of the 200m resolution domain. The red boxdenotes the valid study area.
The data presented in this section are derived from the 5 reference points provided by Client. In Table 4 below, locationinformation and mean wind speed are summarized for each reference point, and the following pages contain annual windand power roses for each reference point and monthly wind and power roses for the first reference point specified. Inaddition to the coordinates given in this table, reference point locations are labeled on the maps in section 2.
ID Latitude Longitude Elevation Hub height Mean wind speed(m) (m) (m
These tables contain the mean of each hour (0 through 23) from each month in the year. Each column, therefore, showsthat month’s mean diurnal cycle, and the annual mean diurnal cycle can be read down the rightmost column, which iscomposed of the overall means of each hour. The bottom row contains each month’s mean, and in the bottom right cellis the overall mean. These means are computed across all 59 turbine locations provided by Client, and do not include thereference points.
Figure 8: 12 month by 24 hour table of net capacity factor for the SWT23 turbine. These net values are derived fromthe gross values using the loss factors in Table 3.
All wind speed, capacity factor, and air density values in this table are the overall mean values for that turbine. Shearis computed between 30m and 80m. Each turbine is color-coded according to its gross capacity factor, so that thebest-performing turbines can be easily identified.
ID Latitude Longitude Elevation Wind Speed Gross Capacity Air Density Shear