摘要
电网参数错误是影响状态估计结果准确性的重要因素。文中以加权最小二乘状态估计为基础,分析了不良数据及错误参数集合对总体误差的影响,提出了基于总体误差下降指标的逐次型参数错误与不良数据辨识方法。该方法在辨识单个不良数据或参数错误时与正则化拉格朗日乘子法等价,并具备同时辨识多个不良数据及参数错误的能力。通过IEEE 14节点测试系统的仿真结果验证了所述方法的准确性与优越性。
Network parameter errors are important factors influencing the accuracy of state estimation results.Based on weighted least square state estimation,the influence of bad data and error parameter set on gross error is analyzed and the successive identification method of network parameter and measurement errors based on gross error reduction index is proposed.Along with the ability to identify multiple network parameter and measurement errors simultaneously,this method is equivalent to the normalized Lagrange multiplier method for a single parameter or measurement error identification.The identification results of IEEE 14-bus test system verify the accuracy and superiority of the proposed identification method.
出处
《电力系统自动化》
EI
CSCD
北大核心
2016年第12期184-188,共5页
Automation of Electric Power Systems
基金
国家高技术研究发展计划(863计划)资助项目(2011AA05A118)~~
关键词
参数辨识
不良数据辨识
总体误差
正则化拉格朗日乘子法
状态估计
parameter identification
bad data identification
gross error
normalized Lagrange multiplier method
state estimation
