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.
李永刚, 王月, 吴滨源. 基于双重Q学习的动态风速预测模型[J]. 电工技术学报, 2022, 37(7): 1810-1819.
Li Yonggang, Wang Yue, Wu Binyuan. Dynamic Wind Speed Prediction Model Based on Double Q Learning. Transactions of China Electrotechnical Society, 2022, 37(7): 1810-1819.
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