分布式变电站动态状态估计  

The Distributed Dynamic State Estimator for Substations

作　　者：陈亮[1] 蒋群[2] 赵思涵[3] 索志刚[4] 王颖[1] 

机构地区：[1]国网河北省电力公司经济技术研究院,河北石家庄050021 [2]国网河北省电力公司保定供电分公司,河北保定071000 [3]国网河北省电力公司检修分公司,河北石家庄050070 [4]河北省电力勘测设计研究院,河北石家庄050031

出　　处：《电力科学与工程》2016年第5期25-31,共7页Electric Power Science and Engineering

摘　　要：相量测量单元(PMU)存在随机误差和坏数据,为了提高PMU数据的可靠性,提出一种基于PMU的分布式变电站动态状态估计方法。在变电站实施基于基尔霍夫电流定律的断路器零阻抗动态状态估计,根据断路器的零阻抗特性构建相应的约束条件,同时计及节点零注入电流约束,从而建立了变电站动态状态估计详细数学模型;利用两参数指数平滑法对状态量进行预报并采用无迹卡尔曼滤波(UKF)算法对模型进行求解。利用IEEE-9节点测试系统对该方法进行仿真研究,状态估计滤波系数均小于1,说明所提出的方法能够有效滤除随机误差和坏数据,并且能够满足实时性的要求。Random errors and bad data can be found in Phasor measurement units （PMU）. In order to enhance the reliability of the measurement, a novel dynamic state estimation method for distributed substations based on PMU is proposed. The dynamic state estimation based on KCL considering the zero-impendence of circuit breakers is carried out in substations. The detailed mathematic model of state estimation considering zero-injected currents is then built. The two-parameter exponential smoothing method is used to predict the states, and the model is solved by the unscented Kalman filter （ UKF）. The proposed method is carried out on the IEEE-9 testing system. The val- ue of the obtained filtering parameter is less than 1, which indicates that the proposed dynamic state estimation method is valid for filtering random errors and bad data with great efficiency while satisfies real-time performance at the same time.

关 键 词：分布式动态状态估计 无迹卡尔曼滤波 变电站 断路器 

分 类 号：TM71[电气工程—电力系统及自动化]