Multi-objective optimization of hybrid solar/wind/diesel/battery system for different climates of Iran

Abstract

In this paper, a wind/photovoltaic/battery/diesel hybrid system with hourly analysis during a year is modeled and optimized for different cities of Iran with various ranges of wind, solar and ambient temperature. A number of solar panels, wind turbines, batteries as well as nominal capacity of diesel engine are considered as design parameters. Fuel ratio and total annual cost (TAC) are selected as two simultaneous objective functions, and particle swarm optimization algorithm is used to find the optimum value of design parameter. The optimum results reveal that Zahedan has the significant lower TAC compared with other studied cases. Optimum cost increases 4.63%, 5.85%, 8.24%, 15.45% and 17.60%, respectively, in the Bushehr, Kerman, Tabriz, Tehran and Mashhad as compared with Zahedan. Optimum results reveal that annual cost extremely increases for the system with the absence of diesel engine (highest fuel ratio). For example, TAC increases at least 100% for the improvement of fuel ratio from 0.8 to 1 for all studied cities. The results also reveal a regular fluctuation in the battery charging and discharging is observed in the high available radiation cities such as Zahedan and Kerman. Furthermore, TAC increases in a linear manner, while fuel ratio increases in an exponentially manner with the increase in the number of PV panels in the optimum situation for all studied cases.