基于双重Q学习的动态风速预测模型

doi:10.19595/j.cnki.1000-6753.tces.210272

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Abstract Accurate wind speed prediction is of great significance to the stable operation of new energy grids. In order to improve the accuracy of wind speed prediction, this paper constructs a dynamic wind speed prediction model based on double Q learning. First, build a wind speed Q learning model set consisting of 5 basic prediction algorithms, fully consider wind speed fluctuations and attribute factors, select the best prediction model for each time period through the Q learning, and get the preliminary wind speed prediction results. Calculate the prediction error based on the wind speed prediction result, construct the second-stage error Q learning model library, screen the best model in the model library to correct the preliminary prediction value, obtain the final prediction result. Finally, the effectiveness of the proposed method is verified by predicting the wind speed of the actual wind field in different seasons.

Key words： Wind speed prediction Q learning error correction dynamic model selection

Received: 03 March 2021

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TM715

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	Li Yonggang
	Wang Yue
	Wu Binyuan

Cite this article:

Li Yonggang,Wang Yue,Wu Binyuan. Dynamic Wind Speed Prediction Model Based on Double Q Learning[J]. Transactions of China Electrotechnical Society, 2022, 37(7): 1810-1819.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.210272 OR https://dgjsxb.ces-transaction.com/EN/Y2022/V37/I7/1810

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