TITLE:
Optimal Static State Estimation Using hybrid Particle Swarm-Differential Evolution Based Optimization
AUTHORS:
Sourav Mallick, S. P. Ghoshal, P. Acharjee, S. S. Thakur
KEYWORDS:
Differential Evolution; Ill-conditioned System; Particle Swarm Optimization; State Estimation
JOURNAL NAME:
Energy and Power Engineering,
Vol.5 No.4B,
October
30,
2013
ABSTRACT: In this paper, swarm optimization hybridized with
differential evolution (PSO-DE) technique is proposed to solve static state
estimation (SE) problem as a minimization problem. The proposed hybrid method
is tested on IEEE 5-bus, 14-bus, 30-bus, 57-bus and 118-bus standard test
systems along with 11-bus and 13-bus ill-conditioned test systems under different
simulated conditions and the results are compared with the same, obtained using
standard weighted least square state estimation (WLS-SE) technique and general
particle swarm optimization (GPSO) based technique. The performance of the
proposed optimization technique for SE, in terms of minimum value of the
objective function and standard deviations of minimum values obtained in 100
runs, is found better as compared to the GPSO based technique. The statistical
error analysis also shows the superiority of the proposed PSO-DE based
technique over the other two techniques.