Wind Power Slope Events Classification and Forecasting Based on Statistical Analysis and Multiple Support Vector Machines

Abstract

Abstract: To evaluate the influence of wind power fluctuations and optimize the control of wind power system, a method of wind power slope events classification and forecasting based on statistical analysis and multiple support vector machine was presented. Firstly, the wind power slope events were defined and classified. Then, the wind power data collected from a wind farm were used to investigate the classification and range of slope events, and the internal laws of slope events were explored. In this context, the binary support vector machine(SVM) was extended to multiple support vector machines(MSVMs) and was applied to the classification of slope down/up events for both one-step and multi-step ahead scenarios. Finally, the numerical results based on the wind power data verify the effectiveness of the proposed approach.

Key words: wind power, slope event, multiple support vector machin(MSVM), classification, forecasting

CLC Number:

TM 614

LI Fu-Dong-1, 2 , WU Min-1, FENG Gao-Yi-3. Wind Power Slope Events Classification and Forecasting Based on Statistical Analysis and Multiple Support Vector Machines[J]. Journal of Shanghai Jiaotong University, 2012, 46(12): 1971-1976.

References

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