南方电网技术2023，Vol.17Issue(12)：52-62,11.DOI:10.13648/j.cnki.issn1674-0629.2023.12.007
计及转折性天气过程识别与检验的短期风电功率预测
Short-Term Wind Power Prediction Considering Identification and Testing of Transitional Weather Processes
摘要
Abstract
In order to enhance the significance of numerical weather prediction(NWP)for short-term wind power prediction and take into account the influence of transitional weather processes on power prediction,a short-term wind power prediction method consider-ing identification and testing of transitional weather processes is proposed.The samples with NWP interval 15 min of the time series are identified using a gated recurrent unit(GRU)based classifier for transitional weather processes.Based on the identification results,the wind speed series of transitional weather processes are tested by method for object-based on diagnostic evaluation(MODE),and the NWP forecasting regularity is explored.Based on the results of weather process identification for the time period to be predicted,matching weather processes,different models are selected for short-term wind power prediction.The proposed method is applied to a wind farm in Jilin,China,for arithmetic validation.The results show that the transitional weather process identification method has a high identification accuracy.The average reductions of RMSE value by 2.77%and MAE value by 2.46%for all types of weather process conditions prove the effectiveness of the method.关键词
转折性天气过程识别/MODE空间检验/NWP预报规律性挖掘/短期风电功率预测Key words
identification of transitional weather processes/MODE spatial examination/NWP forecast regularity mining/short-term wind power prediction分类
信息技术与安全科学引用本文复制引用
王勃,冯双磊,刘晓琳,王钊..计及转折性天气过程识别与检验的短期风电功率预测[J].南方电网技术,2023,17(12):52-62,11.基金项目
中国电力科学研究院有限公司长线攻关项目(人工智能与物理机理相结合的新一代数值预报模式研究)(NY83-22-004). Supported by the Long Term Key Project of China Electric Power Research Institute(NY83-22-004). （人工智能与物理机理相结合的新一代数值预报模式研究）
