电力系统自动化2013，Vol.37Issue(14)：7-12,31,7.DOI:10.7500/AEPS201209163
基于SCADA和支持向量回归的风电机组状态在线评估方法
An Online Wind Turbine Condition Assessment Method Based on SCADA and Support Vector Regression
摘要
Abstract
In order to improve the real-time reliability of grid-connected wind turbines,optimize the maintenance strategy,and reduce the cost of wind power generation,it is necessary to consider the interaction and coupling between components or subsystems of a wind turbine.An online assessment model for the operation conditions of the whole wind turbine is established by data mining technology.Firstly,after analyzing the shortcomings of the supervisory control and data acquisition (SCADA) warning system of wind turbines,a more robust on-line assessment scheme is proposed based on the cooperation of a regression prediction model and the SCADA warning system.Secondly,the regression prediction model is described in detail that the support vector regression (SVR) algorithm is adopted.The inputs of SVR are part of the monitoring projects of the SCADA system,and the output of SVR is the active power of the wind turbine.Finally,measurement results of a wind farm are used to verify the proposed model.关键词
支持向量回归/风电机组/状态评估/数据采集与监控系统/数据挖掘/残差控制Key words
support vector regression (SVR)/ wind turbine/ condition assessment/ supervisory control and data acquisition (SCADA) system/ data mining/ residual control引用本文复制引用
梁颖,方瑞明..基于SCADA和支持向量回归的风电机组状态在线评估方法[J].电力系统自动化,2013,37(14):7-12,31,7.基金项目
国家自然科学基金资助项目(51177039) （51177039）
福建省高等学校新世纪优秀人才支持计划资助项目(2010-24) （2010-24）
中央高校基本科研业务费专项资金资助项目(JB-ZR1125,JB-JC1008).This work is supported by National Natural Science Foundation of China (No.51177039),Program for New Century Excellent Talents in University in Fujian Province (No.2010-24),and the Fundamental Research Funds for the Central Universities (No.JB-ZR1125,No.JB-JC1008). （JB-ZR1125,JB-JC1008）
