A novel approach for multi-objective optimization of standalone PV/DG hybrid system with considering uncertainty and operating reserve

In this paper, a framework for multi-objective optimization of a hybrid photovoltaic/diesel generator (PV/DG) system has been presented. This study follows the design of the PV/DG system at the lowest cost, lowest emission and highest reliability.The total net present cost (TNPC), CO2 emissions and the loss of power supply probability (LPSP) are selected asthe problem objectives. This system has been designed in three scenarios: 1- without considering uncertainty and operating reserve, 2- with considering uncertainties of the system and 3- with considering uncertainties of the system and using DG as operating reserve. In order to effectively solve this problem, multi-objective versionof crow search algorithm (MO-CSA) has been developed and the results are compared with the results obtained by well-known non-dominated sorting genetic algorithm II (NSGA-II). The coding of the problem has been done in MATLAB environment and the Pareto fronts have been compared. Simulation results indicate that combination of DG and PV is a promising alternative for supplying the electrical demand of stand-alone areas. Moreover, the results obtained by MO-CSA outperform the results obtained by NSGA-II.