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The accuracy of wind power output prediction directly affects the safety of power system dispatching. A wind power combination prediction method based on variational mode decomposition(VMD) and maximum information coefficient(MIC) was proposed. According to the randomness and fluctuation of wind power time series, the original wind power series were decomposed into modal components with different fluctuation characteristics by VMD. Then, considering the meteorological information and the operating conditions of wind turbines, MIC was used to select the features of each component after considering the time scale. Based on the induced ordered weighted average(IOWA) operator, the combined model components were set up for prediction, and the prediction results of each modal component were superimposed to obtain the final predicted value. Experimental results based on measured data of wind farms showed that the proposed combined prediction model could effectively improve the prediction accuracy.
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Basic Information:
DOI：10.13705/j.issn.1671-6841.2021282
China Classification Code:TM614
Citation Information:
[1]ZHEN Chenggang,ZHANG Zhengpeng.Wind Power Combined Prediction Based on VMD Decomposition and MIC Feature Analysis[J].Journal of Zhengzhou University(Natural Science Edition),2022,54(03):88-94.DOI:10.13705/j.issn.1671-6841.2021282.
Fund Information:
国家重点研发计划项目(2018YFB1500801); 北京市自然科学基金项目(4182061)
2021-11-09
2021-11-09
2021-11-09