基于小波理论的风电功率实时协同预测研究  

Study on Real-time Cooperative Prediction Based on Wavelet Theory for Wind Power

作　　者：严干贵[1] 熊昊[1] 杨茂[1] 王东[1] 宋薇[1] 

机构地区：[1]东北电力大学微通电力系统研究室,吉林吉林132012

出　　处：《东北电力大学学报》2013年第1期120-125,共6页Journal of Northeast Electric Power University

基　　金：国家自然科学基金(50877009);国家自然科学基金重点项目(60934005);吉林省产业技术研究与开发专项项目(JF2012C018);国家科技支撑计划课题三(2011BAA07B03)

摘　　要：风力发电联网运行是实现风能大规模开发利用的主要途径,准确的风电功率实时预测是实现风能大规模合理调度的有效手段。对风电功率波动特性进行了分析,得到合理的小波分解层数,通过选取各层预测的最优方法,从而得到协同预测模型。最后以吉林省某风场的实测数据为例,阐述了模型选取的准则,预测结果验证了协同预测模型的有效性。Wind power generation with network running is the main way to realize the exploitation and utiliza- tion of wind energy in large-scale. Accurate real-time prediction of wind power is an effective means to achieve rational management of wind energy in large-scale. This paper analyzes the characteristics of wind power fluctu- ations, then it gets reasonable wavelet decomposition layers, by Selecting optimal prediction method for different frequency components, real-time cooperative prediction model based on wavelet theory for wind power is estab- lished. Finally By means of the measured date of a wind farm in Jilin Province, we expound the criteria of mod- el selection, the prediction results show the effectiveness of the cooperative prediction model.

关 键 词：小波理论 实时预测 协同预测 风电功率波动 

分 类 号：TM715[电气工程—电力系统及自动化]