Stochastic Prediction of Wind Generating Resources Using the Enhanced Ensemble Model for Jeju Island’s Wind Farms in South Korea
Abstract
:1. Introduction
2. Enhanced Ensemble Model Based on Spatial Techniques
2.1. Step 1: Establish the Wind Speed Database Using a Spatial Modeling
2.2. Step 2: Estimate the Average Wind Turbine Output Using a Weibull Distribution
2.3. Estimation of Average Wind Turbine Output Using a Weibull Distribution
3. Case Study: Stochastic Prediction of Wind Generating Resources in Jeju Island’s Wind Farms in South Korea
3.1. Empirical Data and Estimated Wind Speed Using a Spatial Interpolation
3.2. Estimate the Average Wind Turbine Output Using a Weibull Distribution
4. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Wind Speed Shear | Terrain Characteristic |
---|---|
0.95 | Coastal waters of inland sea |
0.121 | Flat shore of ocean small islands |
0.130–0.135 | Open grasslands without trees |
0.143 | Open slightly rolling farm land |
0.128–0.170 | Open level agricultural land with isolated trees |
0.200 | Open fields divided by los stone walls |
0.220 | Rough coast |
0.230 | Gently rolling country with bushes and small trees |
0.250–0.303 | Level country uniformly covered with scrub oak and pine |
0.357 | Wooded and treed farm land |
Name | Longitude (Degree) | Latitude (Degree) | Elevation (Meter) |
---|---|---|---|
MET Tower A | 126.7090 | 33.4824 | 252 |
MET Tower B | 126.1628 | 33.2938 | 71.5 |
MET Tower C | 126.5297 | 33.5140 | 20.45 |
MET Tower D | 126.7794 | 33.5616 | 34 |
MET Tower E | 126.8777 | 33.5198 | 18 |
MET Tower F | 126.9542 | 33.5228 | 6.36 |
MET Tower G | 126.8168 | 33.3535 | 77.2 |
MET Tower H | 126.8802 | 33.3867 | 17.75 |
MET Tower I | 126.7692 | 33.5281 | 110.5 |
MET Tower J | 126.4224 | 33.2914 | 425 |
Potential Wind Farm A | 126.7151 | 33.5352 | 61 |
Potential Wind Farm B | 126.8208 | 33.5570 | 10 |
Potential Wind Farm C | 126.1663 | 33.3387 | 9 |
Potential Wind Farm D | 126.8211 | 33.3992 | 141 |
Technical Specifications | Values |
---|---|
Cut-in speed | 3.5 m/s |
Rated speed | 12.5 m/s |
Cut-out speed | 20 m/s |
Rated power | 2000 kW |
Hub height | 85 m |
Wind turbine generation type | Doubly Fed Induction Generation (DFIG) |
Pitch controller | Individual Pitch Control |
Potential Wind Farm | Wind Shear Exponent |
---|---|
Site A | 0.23 |
Site B | 0.121 |
Site C | 0.121 |
Site D | 0.22 |
Neighbor Site | Weights () for Potential Wind Farm A | Weights () for Potential Wind Farm B | Weights () for Potential Wind Farm C | Weights () for Potential Wind Farm D |
---|---|---|---|---|
MET Tower A | 0.7219 | 0.0087 | −0.7748 | 0.5461 |
MET Tower B | −0.1026 | 0.1034 | 0.6325 | −0.1165 |
MET Tower C | 0.0977 | 0.0460 | −0.0223 | 0.1281 |
MET Tower D | 0.1735 | 0.1601 | −0.0230 | 0.1263 |
MET Tower E | 0.1218 | 0.2223 | −0.1326 | 0.2505 |
MET Tower F | 0.2174 | 0.0235 | −0.2519 | 0.2429 |
MET Tower G | −0.0841 | 0.0817 | 0.4461 | −0.0330 |
MET Tower H | 0.1588 | 0.0531 | −0.1071 | 0.2632 |
MET Tower I | −0.4763 | 0.2393 | 1.3864 | −0.5911 |
MET Tower J | 0.1667 | 0.0553 | −0.0863 | 0.1674 |
Potential Wind Farm | Value | Shape Parameter | Scale Parameter |
---|---|---|---|
Site A | Mean value | 2.5073 | 6.8842 |
97.5% Confidence interval | |||
Site B | Mean value | 2.4589 | 7.7656 |
97.5% Confidence interval | |||
Site C | Mean value | 2.3920 | 9.3654 |
97.5% Confidence interval | |||
Site D | Mean value | 2.6308 | 6.1867 |
97.5% Confidence interval |
Set No. | Wind Speed (m/s) | Probability (Lower) | Probability (Mean) | Probability (Upper) | Turbine Output (kW) |
---|---|---|---|---|---|
9 | 5 | 0.039035 | 0.040732 | 0.042758 | 103.36 |
10 | 5.5 | 0.042055 | 0.044388 | 0.047103 | 164.52 |
11 | 6 | 0.044505 | 0.047403 | 0.050724 | 241.67 |
12 | 6.5 | 0.046346 | 0.049701 | 0.053495 | 325.1 |
13 | 7 | 0.047553 | 0.051231 | 0.055328 | 429.92 |
14 | 7.5 | 0.048124 | 0.05197 | 0.056176 | 549.42 |
15 | 8 | 0.048073 | 0.051924 | 0.056032 | 711.73 |
16 | 8.5 | 0.047433 | 0.051125 | 0.054935 | 846.29 |
Set No. | Wind Speed (m/s) | Turbine Output (Lower) (kW) | Turbine Output (Mean) (kW) | Turbine Output (Upper) (kW) |
---|---|---|---|---|
1 | 1 | 0.00 | 0.00 | 0.00 |
... | ... | ... | ... | ... |
9 | 5 | 6.4220 | 6.7013 | 7.0345 |
10 | 5.5 | 10.1633 | 10.7273 | 11.3835 |
11 | 6 | 14.4687 | 15.4109 | 16.4903 |
12 | 6.5 | 19.9249 | 21.3676 | 22.9984 |
13 | 7 | 26.1265 | 28.1473 | 30.3983 |
14 | 7.5 | 34.2512 | 36.9885 | 39.9819 |
15 | 8 | 40.6840 | 43.9425 | 47.4197 |
16 | 8.5 | 47.3906 | 51.0800 | 54.8862 |
... | ... | … | … | … |
39 | 20 | 0.0000 | 0.0000 | 0.0000 |
Expected turbine output | 935.8888 | 985.9220 | 1,023.7511 |
Value | Potential Wind Farm A | Potential Wind Farm B | Potential Wind Farm C | Potential Wind Farm D |
---|---|---|---|---|
Average output | 562.94 | 736.18 | 985.92 | 418.91 |
Confidence interval | 512.82~611.47 | 684.95~782.32 | 935.88~1,023.75 | 375.62~463.55 |
Capacity Factor | 0.281 | 0.368 | 0.493 | 0.209 |
Potential Wind Farm | February (kWh) | May (kWh) | September (kWh) | December (kWh) |
---|---|---|---|---|
Site A (Confience interval) | 562.94 (518.82~611.47) | 178.94 (147.74~214.06) | 65.56 (53.02~80.33) | 388.90 (340.15~438.22) |
Site B (Confience interval) | 736.18 (684.95~782.32) | 261.67 (220.82~305.40) | 114.53 (95.16~136.95) | 521.60 (467.91~572.70) |
Site C (Confience interval) | 985.92 (935.88~1,023.75) | 404.61 (353.13~455.61) | 186.61 (160.68~215.64) | 787.75 (734.56~832.57) |
Site D (Confience interval) | 418.91 (375.62~463.55) | 127.84 (103.98~155.53) | 51.56 (41.64~63.21) | 290.52 (250.53~333.25) |
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Kim, D.; Hur, J. Stochastic Prediction of Wind Generating Resources Using the Enhanced Ensemble Model for Jeju Island’s Wind Farms in South Korea. Sustainability 2017, 9, 817. https://doi.org/10.3390/su9050817
Kim D, Hur J. Stochastic Prediction of Wind Generating Resources Using the Enhanced Ensemble Model for Jeju Island’s Wind Farms in South Korea. Sustainability. 2017; 9(5):817. https://doi.org/10.3390/su9050817
Chicago/Turabian StyleKim, Deockho, and Jin Hur. 2017. "Stochastic Prediction of Wind Generating Resources Using the Enhanced Ensemble Model for Jeju Island’s Wind Farms in South Korea" Sustainability 9, no. 5: 817. https://doi.org/10.3390/su9050817