Artificial fish swarm optimization algorithm for power system state estimation

Abstract

In this paper, the power system state estimation (SE) problem is formulated as a general non-linear programming problem with equality constraints and boundary limits on the state variables. The proposed SE problem is solved using an evolutionary based Artificial Fish Swarm Optimization Algorithm (AFSOA). The AFSOA is a global search algorithm based on the characteristics of fish swarm and its autonomous model. The detailed algorithm with its flow chart is presented in this paper. To show the effectiveness of the proposed SE approach, six bus test system is considered. The obtained results are compared with other algorithms reported in the literature.