Particle Swarm Optimization of a Microgrid’s Cost Function Involving Distributed Generation and Highly Fluctuating Load

This paper presents a particle swarm optimization of the cost function of a microgrid that contains distributed photovoltaic (PV) generation, wind farms, conventional fuel generation, battery storage elements, and imports from neighboring microgrids. The hybrid generation is intended for feeding a highly fluctuating industrial load (whose data is taken from a steel factory in Amman, Jordan) in the most cost-effective manner. The discharging rate of the battery storage system is optimized such that the amount of injected renewable power generation is maximized, resulting in minimizing the generation cost function in indirect manner. The results show that there exists a non-linear relationship between the discharging rate and the amount of the injected renewable power generation into the grid.