Multi-objective planning of electrical distribution systems using particle swarm optimization

This paper presents a novel approach for single-stage multi-objective planning of electrical distribution systems using particle swarm optimization. The optimization objectives are: minimization of total installation (and operational) cost and total fault cost. The fault cost is a measure of system reliability. The trade-off analysis of these objectives is performed using Pareto-optimality principle. The particle swarm optimization (PSO) is used as the optimization tool to obtain the Pareto-approximation set solutions, where novel cost-biased particle encoding/decoding and conductor size selection algorithms have been used for simultaneous optimization of network topology and branch conductor sizes. The proposed algorithm is implemented on typical 21 and 100-node distribution systems and performance is assessed by statistical test.