A New Hybrid Modified PSO/BFA technique for solving Optimal Location and Sizing of Shunt Capacitors

In this paper, Self-Adaptive Hybrid Modified Particle Swarm optimization (SAHMPSO) with time varying acceleration coefficients and Bacteria Foraging Algorithm (BFA) method is introduced to solve Optimal Location and Size of Capacitor (OLSC) problem in radial distribution networks. To arrive to SAHMPSO/BFA method, two developments have been employed on control parameters of mutation and crossover operators. To expand this study, three load conditions have been considered, i.e., constant, varying and effective loads. Objective function is introduced for the load conditions. The annual cost is objective function of OLSC problem, in addition to this cost, CPU time, voltage profile, active power loss and total installed capacitor banks and their related costs have been used for performance indexes. To confirm the ability of each improvements of SAHMPSO/BFA algorithm, the improvements are studied both in separate and simultaneous conditions. To verify the effectiveness of the proposed method, it is tested on IEEE 10 bus and 34 bus radial distribution networks and compared with other approaches.

A New Hybrid Modified PSO/BFA technique for solving Optimal Location and Sizing of Shunt Capacitors Keywords:

Annual cost , SAHMPSO , BFA algorithm , optimal capacitor allocation , Radial distribution networks