Particle Swarm Optimization for Sizing Hybrid Power Systems Incorporating Demand Response

This paper presents an optimal sizing method for a hybrid wind, solar, battery storage and diesel generation units designed to meet a specific demand. The energy output and load demand used in the model is structured in one hour intervals over the course of a year. In addition, demand response is implemented showing a direct relationship with total system price. Based on generating unit capital and variable costs, the particle swarm optimization (PSO) algorithm is implemented. The yearly normalized total system cost is taken as the objective function which is based on the generating technologies life cycle. PSO exhibits an optimum generating unit sizing assuming 5 percent of the average load as demand response power capacity.