基于测量不确定度的电力系统状态估计 (二)方法研究  

Power System Static-state Estimation Based on Uncertainty of Measurement Part Two A New Method

作　　者：何光宇[1] 董树锋[1] 

机构地区：[1]清华大学电机系电力系统国家重点实验室,北京市100084

出　　处：《电力系统自动化》2009年第20期32-36,共5页Automation of Electric Power Systems

基　　金：国家自然科学基金资助项目(50507013);国家电网公司重点科技项目~~

摘　　要：基于正常测点概念构造了相应测点评价函数,用于评价测点是正常测点还是异常测点;在此基础上,提出了以测点正常率最大为目标函数的状态估计新模型。为使估计结果更接近于实际运行情况,模型中可考虑潮流约束和实际物理约束。用现代内点法求解该模型,计算速度快,收敛性好。与以往方法相比,文中所述方法的状态估计结果测点正常率高,可自动辨识不良数据,估计结果不易受不良数据影响,有较强的抗差性;所求得的解为潮流解,满足各种物理约束,更加接近实际;计算中无需进行不良数据检验,无需主观设定测点权重,大幅度减少了调试和维护工作量。Based on the concept of normal measuring point, evaluation function of measuring point is constructed to judge whether a measuring point is normal or exceptional. Then, a new model of state estimation is proposed which takes the maximum of normal rate of measuring point as the objective. The model can consider power flow constraints and other physical constraints to make the estimation results close to the actual scenario. The model can be successfully solved by modern interior point method which has short CPU time and good convergence property. Comparing with other state estimation methods, the proposed method has the following advantages： higher normal rate of measuring point, capability of automatically identifying bad data, stronger anti-error characteristics, and capability of obtaining solutions suits practical scenario better because of consideration of power flow constraints and other physics constraints in the solution process. At the same time, the method does not need to perform additional observability analysis, bad data detection or subjective weighting factors setting, thus substantial reduction in maintenance efforts can be achieved.

关 键 词：状态估计 测点正常率 测点评价函数 测量不确定度 

分 类 号：TM73[电气工程—电力系统及自动化] TM744