基于广域量测数据和导纳参数在线辨识的受扰轨迹预测  

RESEARCH ON THE PERTURBED TRAJECTORIES PREDICTION BASED ON WIDE-AREA MEASUREMENT AND ON-LINE ADMITTANCE MATRIX IDENTIFICATION

作　　者：彭疆南[1] 孙元章[1] 王海风[2] 

机构地区：[1]清华大学电机系,北京市100084 [2]Bath大学

出　　处：《电力系统自动化》2003年第22期6-11,共6页Automation of Electric Power Systems

基　　金：国家重点基础研究专项经费资助项目 (G1 9980 2 0 31 5 ) ;国家杰出青年科学基金资助项目 (5 982 5 1 0 4 )。~~

摘　　要：基于相量测量单元 (PMU)广域量测数据应用参数辨识理论提出电力系统故障后导纳参数在线辨识方法 ,研究了电力系统受扰轨迹快速积分预测新方法。该算法基于实时量测量精确构造实际故障后的系统动态方程 ,并快速积分求解系统受扰轨迹。其突出优点在于 :参数辨识使用系统实时数据 ,可考虑复杂的连锁故障事件和不确定的系统拓扑和参数 ;预测基于故障后系统模型积分 ,能够反映系统物理本质 ,对于系统经典模型具有理想预测精度。该算法在多种测试系统中进行了数字仿真实验 ,并用动模实验数据进行了离线验证 。This paper presents the total least square algorithm for parameter estimation of system post-fault configuration based on phasor measurement unit (PMU) real-time measurement. The perturbed trajectories can be predicted by integrating a simplified DAE model by powerful workstations in control centers. The most attractive feature of this method is its ability to identify the post fault system parameters without assuming a specific preconceive contingency. The algorithm is tested for different types of faults occurring at different location in a number of test systems and off-line validated using the data recorded by dynamic simulating experiment with reasonable and promising results.

关 键 词：轨迹预测 辨识 导纳矩阵暂态稳定 广域测量 总体最小二乘法 

分 类 号：TM712[电气工程—电力系统及自动化]