scholarly journals Observability and detectability analyses for dynamic state estimation of the marginally observable model of a synchronous machine

2021 ◽  
Author(s):  
Ning Zhou ◽  
Shaobu Wang ◽  
Junbo Zhao ◽  
Zhenyu Huang ◽  
Renke Huang
Keyword(s):  
State Estimation ◽  
Synchronous Machine ◽  
Dynamic State ◽  
Dynamic State Estimation

An extended Kalman particle filter for power system dynamic state estimation

2018 ◽  
Vol 37 (6) ◽  
pp. 1993-2005 ◽  
Author(s):  
Yang Yu ◽  
Zhongjie Wang ◽  
Chengchao Lu
Keyword(s):  
Particle Filter ◽  
State Estimation ◽  
Design Methodology ◽  
High Accuracy ◽  
Synchronous Machine ◽  
Dynamic State ◽  
Content Type ◽  
Dynamic State Estimation ◽  
Practical Implications ◽  
Dynamic States

Purpose The purpose of this paper is to propose an extended Kalman particle filter (EPF) approach for dynamic state estimation of synchronous machine using the phasor measurement unit’s measurements. Design/methodology/approach EPF combines the extended Kalman filter (EKF) with the particle filter (PF) to accurately estimate the dynamic states of synchronous machine. EKF is used to make particles of PF transfer to the likelihood distribution from the previous distribution. Therefore, the sample impoverishment in the implementation of PF is able to be avoided. Findings The proposed method is capable of estimating the dynamic states of synchronous machine with high accuracy. The real-time capability of this method is also acceptable. Practical implications The effectiveness of the proposed approach is tested on IEEE 30-bus system. Originality/value Introducing EKF into PF, EPF is proposed to estimate the dynamic states of synchronous machine. The accuracy of a dynamic state estimation is increased.

Dynamic State Estimation Based Protection on Series Compensated Transmission Lines

2017 ◽  
Vol 32 (5) ◽  
pp. 2199-2209 ◽  
Author(s):  
Yu Liu ◽  
A. P. Sakis Meliopoulos ◽  
Rui Fan ◽  
Liangyi Sun ◽  
Zhenyu Tan
Keyword(s):  
State Estimation ◽  
Transmission Lines ◽  
Dynamic State ◽  
Dynamic State Estimation

scholarly journals Dynamic state estimation of power system with stochastic delay based on neural network

2021 ◽  
Vol 7 ◽  
pp. 159-166
Author(s):  
Guangdou Zhang ◽  
Jian Li ◽  
Dongsheng Cai ◽  
Qi Huang ◽  
Weihao Hu
Keyword(s):  
Neural Network ◽  
Power System ◽  
State Estimation ◽  
Dynamic State ◽  
Stochastic Delay ◽  
Dynamic State Estimation
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