基于相似日和人工神经网络的风电功率短期预测  

Short-Term Wind Power Forecasting Based on Similar Days and Artificial Neural Network

作　　者：孟洋洋[1] 卢继平[1] 孙华利[2] 潘雪[1] 高道春[1] 廖勇[1] 

机构地区：[1]输配电装备及系统安全与新技术国家重点实验室(重庆大学),重庆市沙坪坝区400044 [2]云南电力调度中心,云南省昆明市650000

出　　处：《电网技术》2010年第12期163-167,共5页Power System Technology

基　　金：重庆市科委科技计划攻关项目(CSTC2008AB3047)的资助

摘　　要：风电场发电功率短期预测对并网风力发电系统的安全性和稳定性具有重要意义。根据影响风电出力的因素,提出了选择风电场发电功率相似日的方法,设计了基于相似日和Chebyshev神经网络的风电功率短期预测模型,根据云南某风电场数据对该模型进行验证,分析了预测误差及其概率分布,结果表明该预测模型具有较高的预测精度,可为风电功率预测提供参考。It is significant to forecast short-term generated power of wind farm for the security and stability of grid-connected wind farm. According to the factors impacting wind power output a method to select similar days of wind farm’s generated power is proposed and a short-term wind power forecasting model based on similar days and Chebyshev neural network is designed. The designed model is verified by the data of a certain wind farm located in Yunnan province, and the forecasting error and its probability distribution are analyzed. Analysis results show that the results forecasted by the designed forecasting model possess high accuracy, so it is available for reference in wind power forecasting.

关 键 词：风力发电 风电场 短期预测 相似日 人工神经网络 

分 类 号：TM72[电气工程—电力系统及自动化]