Optimization of grid independent diesel-based hybrid system for power generation using improved particle swarm optimization algorithm

The power supply of remote sites and applications at minimal cost and with low emissions is an important issue when discussing future energy concepts. This paper presents modeling and optimization of a photovoltaic (PV)/wind/diesel system with batteries storage for electrification to an off-grid remote area located in Rafsanjan, Iran. For this location, different hybrid systems are studied and compared in terms of cost. For cost analysis, a mathematical model is introduced for each system's component and then, in order to satisfy the load demand in the most cost-effective way, particle swarm optimization algorithm are developed to optimally size the systems components. As an efficient search method, IPSO has simple concept, is easy to implement, can escape local optima, by use of probabilistic mechanisms, and only needs one initial solution to start its search. Simulation results indicate that, the role of the diesel generator decreases in hybrid (PV/wind/diesel/battery) energy systems.