Multi-Objective Optimization of PV/Wind/ESS Hybrid Microgrid System Considering Reliability and Cost Indices

Recently, power system planers are moving toward sustainable sources of energy like solar and wind. However, some technical issues such as intermittent behavior of Renewable Energy Source (RES) and its reliability should be taken into account. In this paper, a hybrid PV/Wind system combined with hydrogen ESS system is compared to one with battery storage. Multi-objective Particle Swarm Optimization (MOPSO) is employed to size system components in order to supply the load of an autonomous microgrid considering cost and reliability indices. In this problem, photovoltaic arrays and wind turbines are subject to failure. Moreover, to increase the accuracy of calculation, the annual load, wind, and solar profiles from NREL (Illinois, USA) are applied to the optimization problem. A comprehensive cost function is defined to cover the capital, replacement, operation and maintenance costs as well as the number of replacements and interest rate during the project period (20 years). To increase the reliability of a stand-alone system as well as customer's satisfaction three reliability indices i.e., Loss of Energy Expected (LOEE), Loss of Load Expected (LOLE), and Equivalent Loss Factor (ELF) are taken into account. Results reveal that the proposed method can find the best configuration for both fuel cell/ battery based ESS system with the highest reliability and the lowest cost.