Journal of Wind Energy (풍력에너지저널)

Korea Wind Energy Association (한국풍력에너지학회)
권호 표지

Analysis of Ramp Characteristics of Shinan Wind Power Plant

신안풍력발전소의 증감발 특성 분석

  • 김현구 (한국에너지기술연구원, 신재생에너지자원.정책센터) ;
  • 김진영 (한국에너지기술연구원, 신재생에너지자원.정책센터) ;
  • 김창기 (한국에너지기술연구원, 신재생에너지자원.정책센터)
  • Received : 2018.06.06
  • Accepted : 2018.07.05
  • Published : 2018.09.30

⟨ Previous Next ⟩

Abstract

A statistical analysis of the power generation records of the Sinan Wind Power Plant located on the coast of Korea on the South Sea was carried out for an overview of ramp characteristics. It was found that up-ramp and down-ramp showed similar patterns such as the same probability of occurrence and ramp rate distribution. The probability of a significant ramp event exceeding 30 % of the nameplate capacity of the wind power plant was 0.6 %, 1.5 %, and 3.3 % for intervals of 1 min, 10 min, and 1 hour, respectively. In a comparative analysis to confirm whether numerical weather prediction can be used for a ramp diagnosis or forecasting, the reliability of the prediction was poor, although the prediction accuracy of wind speed was high at $R^2=0.72$. Therefore, it was confirmed that the accuracy improvement of short-term prediction is an important issue for ramp forecasting using a numerical weather prediction model.

Keywords

Acknowledgement

Supported by : 한국에너지기술연구원

References

  1. Wan, Y.-H., 2011, Analaysis of Wind Power Ramping Behavior in ERCOT, NREL/TP-5500-49218, National Renewable Energy Laboratory, USA, p. 19.
  2. Sevlian, R., Rajagopal, R., 2012, "Wind Power Ramps: Detection and Statistics," IEEE Power and Energy Society General Meeting, San Diego, CA, USA, 7/22-26.
  3. Zhnag, J., Florita, A., Hodge, B.-M., and Freeman, J., 2014, Ramp Forecasting Performance from Improved Short-Term Wind Power Forecasting, NREL/CP-5D00-61730, National Renewable Energy Laboratory, USA, p. 12.
  4. Cui, T., Zhang, J., Feng, A.R., Sun, Y., and Hodge, B.-M., 2017, "Characterizing and Analyzing Ramping Events in Wind Power, Solar Power, Load, and Netload," Renewable Energy, Vol. 111, pp. 227-244. https://doi.org/10.1016/j.renene.2017.04.005
  5. Lyu, J.-G., Heo, J.-H., and Park, J.-K., 2013, "Evaluation of Ramping Capacity for Day-ahead Unit Commitment Considering Wind Power Variability," Trans. of Korean Institute of Electrical Engineers, Vol. 62, No. 4, pp. 457-466 (in Korean). https://doi.org/10.5370/KIEE.2013.62.4.457
  6. Kwon, H.-G., 2017, Enhanced Ramping Capacity Model Considering Flexibility and its Application to Short-term Generation Scheduling, Ph.D. Thesis, Seoul National University, p. 167 (in Korean).
  7. Kim, H.-G., Kang, Y.-H., Yun, C.-Y., and Jang, M.-S., 2013, "Long-Term Wind Resource Assessment of Shinan-gun Bigeum-do Using The Wind Farm SCADA Data and Reanalysis Data," J. of the Wind Engineering Institute of Korea, Vol. 17, No. 4, pp. 127-132 (in Korean).
  8. Kim, H.-G., 2013, "Analysis on Wind Turbine Degradation of the Shinan Wind Power Plant," J. of Korean Solar Energy Soc., Vol. 33, No. 4, pp. 46-50 (in Korean). https://doi.org/10.7836/kses.2013.33.4.046
  9. Kim, H.-G., Kang, Y.-H., and Yun, C.-Y., 2015, "Derivation of Nacelle Transfer Function Using LiDAR Measurement," Trans. Korean Soc. Mech. Eng. A, Vol. 39, No. 9, pp. 929-936 (in Korean). https://doi.org/10.3795/KSME-A.2015.39.9.929
  10. Kim, H.-G., Lee, H.-W., and Lee, S.-H., 2011, "Development of the Korea Wind Resource Map and Suitability Assessment System for Offshore Wind Farm," Journal of Wind Energy, Vol. 2, No. 2, pp. 17-23 (in Korean).
  11. Kim, H.-G., Kang, Y.-H., and Kim, C.-K., 2017, "Analysis of Wind Energy Status and Capacity Factor of South Korea by EPSIS Wind Power Generation Data," Journal of Wind Energy, Vol. 8, No. 2, pp. 21-27 (in Korean).
  12. Kamath, C., 2010, "Understanding Wind Ramp Events Through Analysis of Historical Data," IEEE PES Transmission and Distribution Conference and Expo, New Orleans, LA, USA, 4/20-22.
  13. Wan, Y.-H., 2011, Analysis of Wind Power Ramping Behavior in ERCOT, NREL/TP-5500-49218, National Renewable Energy Laboratory, USA, p. 20.
  14. Wang, H.-Z., Li, G.-Q., Wang, G.-B., Peng, J.-C., Jiang, H., and Liu, Y.-T., 2017, "Deep Learning Based Ensemble Approach for Probabilistic Wind Power Forecasting," Applied Energy, Vol. 188, pp. 56-70. https://doi.org/10.1016/j.apenergy.2016.11.111
  15. Ren, Y., Suganthan, P.N., and Srikant, N., 2015, "Ensemble Methods for Wind and Solar Power Forecasting - A State-of-the-Art Review," Renewable and Sustainable Energy Reviews, Vol. 50, pp. 82-91. https://doi.org/10.1016/j.rser.2015.04.081