基于实测数据的风电综合负荷建模  

Integrated Load Modeling of Wind Power Based on Measured Data

作　　者：季文伟 张伟玲 JI Wen-wei;ZHANG Wei-ling(Beihai District Headquarters of China Coast Guard,Qingdao 266000,China;State Grid Shandong Electric Power Company Qingdao Huangdao Power Supply Company,Qingdao 266000,China)

机构地区：[1]武警海警总队北海海区指挥部,山东青岛266000 [2]国网山东省电力公司青岛市黄岛区供电公司,山东青岛266000

出　　处：《通信电源技术》2019年第11期32-34,共3页Telecom Power Technology

摘　　要：广域测量系统(WAMS)中,PWU能够实时测量广域分布的电力系统状态和各参数量,为此提出了以实测PMU数据的风电综合负荷建模。利用粒子群优化算法,以计算功率值和实测功率值误差最小作为目标函数,利用华北电网220 kV御祥线实测PMU数据,验证了该负荷模型的有效性。结果表明,以辨识参数为基础计算的功率与实测值吻合较好,验证了所提方案能够很好地满足负荷模型参数辨识的要求,使获得的模型和参数具有良好的适应性和精度。In the Wide Area Measurement System(WAMS),PWU can measure the power system state and parameters in real time.Therefore,the wind power integrated load modeling based on the measured PMU data is proposed.Using particle swarm optimization algorithm,the objective function is to minimize the error between the calculated power value and the measured power value.The validity of the load model is verified by using the measured PMU data of 220 kV Yuxiang line in North China power grid.The results show that the power calculated on the basis of identification parameters is in good agreement with the measured values,which proves that the proposed scheme can meet the requirements of load model parameter identification well,and the obtained model and parameters have good adaptability and accuracy.

关 键 词：风电综合负荷模型 PMU数据 粒子群算法 参数辨识 

分 类 号：TM7[电气工程—电力系统及自动化]