A Particle Swarm Optimized Particle Filter for Nonlinear System State Estimation

2006 ◽  
Author(s):  
Guofeng Tong ◽  
Zheng Fang ◽  
Xinhe Xu
Keyword(s):  
Nonlinear System ◽  
Particle Filter ◽  
State Estimation ◽  
Particle Swarm ◽  
System State

Particle swarm optimization for power system state estimation

2015 ◽  
Vol 148 ◽  
pp. 175-180 ◽  
Author(s):  
D.H. Tungadio ◽  
B.P. Numbi ◽  
M.W. Siti ◽  
A.A. Jimoh
Keyword(s):  
Particle Swarm Optimization ◽  
Power System ◽  
State Estimation ◽  
Particle Swarm ◽  
System State ◽  
Swarm Optimization ◽  
Power System State Estimation

scholarly journals Particle filter in power system state estimation – bad measurement data and branch disconnection

2015 ◽  
Vol 64 (2) ◽  
pp. 237-248
Author(s):  
Piotr Kozierski ◽  
Marcin Lis ◽  
Adam Owczarkowski ◽  
Dariusz Horla
Keyword(s):  
Power System ◽  
Particle Filter ◽  
State Estimation ◽  
Measurement Data ◽  
The State ◽  
Filter Method ◽  
System State ◽  
State Variables ◽  
Zero Bias ◽  
Power System State Estimation

Abstract An approach to power system state estimation using a particle filter has been proposed in the paper. Two problems have been taken into account during research, namely bad measurements data and a network structure modification with rapid changes of the state variables. For each case the modification of the algorithm has been proposed. It has also been observed that anti-zero bias modification has a very positive influence on the obtained results (few orders of magnitude, in comparison to the standard particle filter), and additional calculations are quite symbolic. In the second problem, used modification also improved estimation quality of the state variables. The obtained results have been compared to the extended Kalman filter method

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