Title :
Dynamic state estimation in power systems using a distributed MAP method
Author :
Yibing, Sun ; Minyue, Fu ; Bingchang, Wang ; Huanshui, Zhang
Author_Institution :
School of Control Science and Engineering, Shandong University, Jinan 250061, P.R. China
Abstract :
This paper studies a dynamic state estimation problem for power systems, which can be seen as the quasi-static systems. The state vector of each subsystem (called node) in power networks is expressed by measurements. Based on a distributed maximum a posteriori (MAP) estimation technique, a fully distributed state estimation method is presented to update the local state at each time instant. Also, the assumption of local observability of every node is no longer needed. Tests on the IEEE 118-bus system are used to show the performance of the proposed approach and compare its results with a centralized state estimation method providing the optimal state estimate for the entire power networks, a local state estimation method using the edge measurements as the local measurements to estimate its local state, and a distributed static state estimation algorithm.
Keywords :
Estimation error; Nickel; Noise; Noise measurement; Observability; State estimation; Distributed state estimation; Kalman filter; MAP estimation; Power networks;
Conference_Titel :
Control Conference (CCC), 2015 34th Chinese
Conference_Location :
Hangzhou, China
DOI :
10.1109/ChiCC.2015.7259611