采用有限时间平均一致性协议的电力系统分布式状态估计

随着基于相量量测单元的广域量测系统在技术上的成熟与推广应用,利用WAMS量测可实现电力系统线性状态估计.本文基于广域量测系统提出一种全分布式状态估计算法.首先根据拉格朗日乘子法推导了多区域约束加权最小二乘估计模型,然后引入有限时间平均一致性协议,得到系统量测正常情况下的分布式状态估计算法.考虑了系统量测存在异常数据情况,根据最小二乘估计的几何意义扩展推导出修正算法,使其在各区域剔除异常量测后,无需改变信息矩阵,只需执行若干次有限时间平均一致性协议能收敛至信息矩阵修正后的集中式估计值.最后,理论分析和实验结果证明了算法的有效性.

Distributed power system state estimation using finite-time average consensus protocol

With the wide-area measurement system based on phasor measurement unit in the maturity of the technologyand application, usingWAMS measurements can realize the linear power system state estimation. In this paper, we proposea fully-distributed state estimation algorithm based on WAMS. First, the multi-area constrained weighted least squaresestimation model is established by Lagrange Multiplier Method. Then, by introducing the finite-time average consensusprotocol into the multi-area constrained weighted least squares estimation model, the distributed state estimation algorithmwithout abnormal measurements is presented. Moreover, by considering the presence of abnormal measurements, wededuce a modified algorithm according to the geometric meaning of the least squares estimate. After eliminating abnormalmeasurements in each sub-region, the modified algorithm can converge to the centralized estimate without changing theinformation matrix, by executing the finite-time average consensus protocol several times. Finally, theoretical analysis andexperimental results prove the effectiveness of the algorithm.