wind working group june 13. wind working group seasonality and direction of wind issues – study of...
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![Page 1: Wind Working Group June 13. Wind Working Group Seasonality and direction of wind issues – Study of wind direction at Elkhorn indicated that splitting](https://reader031.vdocuments.us/reader031/viewer/2022032015/56649d2e5503460f94a0503b/html5/thumbnails/1.jpg)
Wind Working GroupJune 13
![Page 2: Wind Working Group June 13. Wind Working Group Seasonality and direction of wind issues – Study of wind direction at Elkhorn indicated that splitting](https://reader031.vdocuments.us/reader031/viewer/2022032015/56649d2e5503460f94a0503b/html5/thumbnails/2.jpg)
Wind Working Group
• Seasonality and direction of wind issues– Study of wind direction at Elkhorn indicated that
splitting wind into two basic directions improved the forecast
– Light load versus heavy load MAE since April are 57/54 MW…respectively. We have wayyyy to much error at night.
• We are patching holes in the dike and not fixing the problem
• A more comprehensive approach is needed
![Page 3: Wind Working Group June 13. Wind Working Group Seasonality and direction of wind issues – Study of wind direction at Elkhorn indicated that splitting](https://reader031.vdocuments.us/reader031/viewer/2022032015/56649d2e5503460f94a0503b/html5/thumbnails/3.jpg)
Wind Working Group
• Seasonality…
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 230
20
40
60
80
100
120
140
160
180 Power Versus Time of Day
June AprilTime of day
Pow
er (M
W)
What is this?
Daily max-imum power shifts to later in the day
Average Power
decreases from Spring to Summer
Spring phenomena?
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Wind Working Group
• Wind Direction…
0 50 100 150 200 250 300 350 4000
5
10
15
20
25
30
35
40
45
50
Wind Power versus Model Forecast Direction
Cassia
Direction (To)
Pow
er (M
W)
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Wind Working Group• Direction…
0-19 20-39 40-59 60-79 80-99 100-119
120-139
140-159
160-179
180-199
200-219
220-239
240-259
260-279
280-299
300-319
320-339
340-360
0
2
4
6
8
10
12
14
16
18
20
Average Power versus Wind Direction
CassiaDirection (To)
Aver
age
Pow
er (M
W)
![Page 6: Wind Working Group June 13. Wind Working Group Seasonality and direction of wind issues – Study of wind direction at Elkhorn indicated that splitting](https://reader031.vdocuments.us/reader031/viewer/2022032015/56649d2e5503460f94a0503b/html5/thumbnails/6.jpg)
Wind Working Group• Direction…
0-19 20-39 40-59 60-79 80-99 100-119
120-139
140-159
160-179
180-199
200-219
220-239
240-259
260-279
280-299
300-319
320-339
340-360
0
5
10
15
20
25
30
35
40
45
50
Average Power versus Wind DirectionCassiaAverage Frequency/10
Direction (To)
Aver
age
Pow
er (M
W)
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Wind Working Group
• Average last four runs of model (or less if unavailable)– Provides the best forecast
over single deterministic model run
– 60 days updated every month• Cutting the pie too small
results in loss of statistical significance
• Addresses seasonality
– Difference between model runs can be used to develop confidence interval
Average last 4 model runs
Carry forward average model
forecast along with max and min wind
speeds
Two coefficient databases need to be developed; 1st is a function of wind direction/time of day; 2nd for hourly
averaged forecast
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Wind Working Group• Divide data by three directions (NW,SE,
All others)– Customize per site
• Golden Triangle may need four directions
– Use model forecast wind (WRF-NAM)• Divide data into eight 3 hour time blocks
• Hourly data would be best but there is not enough data (yet) to be statistically significant
• Addresses time of day/seasonality
• Split by model forecast 80m and 10m winds
• Convert wind speed to power and develop coefficients
Directional Component
80m and 10m wind
3 Hour Time blocks (23-00-01)
Use Power curves to convert wind speed to power; actuals and data passed to Excel/Matlab to develop
regression coefficients as a function of time of day and wind direction
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Wind Working Group• Second step is developing
coefficients for the first and second hour for the hourly averaged forecast– We can either develop the
coefficients as a function of time of day or present method of hour one and two
• Same procedure would be needed as other models are added
• Coefficients database will be updated every 30 days
• Whenever a forecast is generated, the coefficients database would be used with forecast data to obtain the actual forecast
• Same procedure would be accomplished for hour-ahead forecasts with the addition of “persistence” as a forecast
F0,F1,10m,80m variables passed to Excel to develop regression
coefficients for hourly averaged forecast
This establishes the coefficients database.
Time of day coefficients
F0 and F1 coefficients
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Wind Working GroupWRF-NAM
ChronologicalBreakout into3hr blocks
DirectionalBreakout
Wind SpeedBreakout
00z(Hr 6-72+)
Hrs 1-3
Hourly Average
06z(Hr 6-72+)
12z(Hr 6-72+)
18z(Hr 6-72+)
Hrs 4-6
Hrs 1-3NW
Hrs 1-3SE
Hrs 1-3Other
Hrs 1-3NW10m
Hrs 1-3NW80m
Hrs 1-3SE
10m
Hrs 1-3SE
80m
Hrs 1-3Other10m
Hrs 1-3Other80m
Hrs 4-6NW10m
Hrs 4-6NW80m
Hrs 4-6SE
10m
Hrs 4-6SE
80m
Hrs 1-3Other10m
Hrs 1-3Other80m
Hrs 1-3NW
Hrs 1-3SE
Hrs 1-3Other
CoeffSet
CoeffSet
CoeffSet
CoeffSet
CoeffSet
CoeffSet
CoeffSet
CoeffSet
CoeffSet
CoeffSet
CoeffSet
CoeffSet