DEVELOPED APPROACH BASED ON EQUILIBRIUM OPTIMIZER FOR OPTIMAL DESIGN OF HYBRID PV/WIND/DIESEL/BATTERY MICROGRID IN DAKHLA, MOROCCO

Abstract

ABSTRACT

In this Project, a new application of Equilibrium Optimizer (EO) is proposed for design hybrid microgrid to feed the electricity to Dakhla, Morocco, as an isolated area. EO is selected to design the microgrid system due to its high effectiveness in determining the optimal solution in very short time. EO is presented for selecting the optimal system design which can minimize the cost, improve the system stability, and cover the load at different climate conditions. Microgrid system consists of photovoltaic (PV), wind turbine (WT), battery, and diesel generator. The objective function treated in this Project is to minimize the net present cost (NPC), respecting several constraints such as the reliability, availability, and renewable fraction. The sensitivity analysis is conducted in two stages: Firstly, the impact of wind speed, solar radiation, interest rate, and diesel fuel on the NPC, and levelized cost of energy (LCOE) is analyzed. Secondly, the influence of size variation on loss of power supply probability (LPSP) is investigated. The results obtained by EO are compared with those obtained by recent metaheuristics optimization algorithms, namely, Harris Hawks Optimizer (HHO), Artificial Electric Field Algorithm (AEFA), Grey Wolf Optimizer (GWO), and Sooty Tern Optimization Algorithm (STOA). Where renewable energy sources (PV and WT) represent 97% of the annual contribution and fast convergence characteristics are obtained by EO.

 

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