电力系统自动化2016，Vol.40Issue(8)：29-35,113,8.DOI:10.7500/AEPS20150610003
基于最小二乘估计融合的分布式电力系统动态状态估计
Distributed Dynamic State Estimation for Power Systems Based on Least Square Estimation Fusion
摘要
Abstract
With the expanding scale of the power system,the distributed state estimation is one of the effective ways to overcome the difficulties of the centralized state estimation,such as too high calculation dimensions and large measurement data processing.This paper adopts the Cabuture Kalman filter to do the local estimation,and employs the least square estimation fusion to coordinate the estimates of the boundary bus states in the coordination center.According to the coordinated estimates of the boundary bus states,each subarea can further correct the local estimates of the internal bus states through the Kalman filter algorithm.Finally,the simulation results show that the estimated precision of the proposed method is close to the centralized method,and the proposed method has a better real-time property.Moreover,the proposed method only need less communication data,which is easy to be implemented.关键词
互联电网/分布式状态估计/最小二乘估计融合/线性等式约束/容积卡尔曼滤波Key words
interconnected power system/distributed state estimation/least square estimation fusion/linear equal constraints/cubature Kalman filter引用本文复制引用
蔡永智,陈皓勇,万楚林..基于最小二乘估计融合的分布式电力系统动态状态估计[J].电力系统自动化,2016,40(8):29-35,113,8.基金项目
国家自然科学基金资助项目(51177049) （51177049）
国家优秀青年科学基金资助项目(51322702)。This work is supported by National Natural Science Foundation of China(No.51177049) and National Science Funds for Excellent Young Scholars of China(No.51322702) （51322702）
