Optimal Static State Estimation Using hybrid Particle Swarm-Differential Evolution Based Optimization

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.

Privacy-Preserving Protocols for IEEE 802.11s-based Smart Grid Advanced Metering Infrastructure Networks

“…In power transmission networks, state estimation at the transmission level has been studied since 1970s [60]. At the the distribution level, there has been several studies in recent years.…”