Developed Approach Based on Equilibrium Optimizer for Optimal Design of Hybrid PV/Wind/Diesel/Battery Microgrid in Dakhla, Morocco

Mohammed Kharrich,Salah Kamel,Omar Hazem Mohammed,Mohamed Abdeen,Sang-Bong Rhee,Mohammed Akherraz,Tahir Khurshaid

doi:10.1109/access.2021.3051573

Abstract

In this paper, 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 paper 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). The results show that the optimal system design is achieved by the proposed EO, where renewable energy sources (PV and WT) represent 97% of the annual contribution and fast convergence characteristics are obtained by EO. The best NPC, LCOE, and LPSP are obtained via EO achieving 74327 $, 0.0917 $/kWh, and 0.0489, respectively.

Highlights

Due to the rapid consumption and environmental pollution of fossil fuel, the renewable energy sources (RESs) should be integrated into the power system in order to meet the future requirements
The results obtained by the proposed algorithm are compared with other recent approaches, Harris Hawks Optimizer (HHO), Artificial Electric Field Algorithm (AEFA), Grey Wolf Optimizer (GWO), and Sooty Tern Optimization Algorithm (STOA), to validate the effectiveness of the proposed Equilibrium Optimizer (EO) in achieving the best reliability and minimum cost
EO has the best performance where it is faster than HHO, AEFA, GWO, and STOA

Summary

INTRODUCTION

Due to the rapid consumption and environmental pollution of fossil fuel, the renewable energy sources (RESs) should be integrated into the power system in order to meet the future requirements. M. Kharrich et al.: Developed Approach Based on EO for Optimal Design of Hybrid PV/Wind/Diesel/Battery Microgrid sources and energy storage have been added to ensure the continuous and stable power supply [3], [4]. In [16], an efficient metaheuristic technique based on artificial bee swarm was exploited for sizing optimization of wind/PV/hydrogen energy system. In [17], a metaheuristic optimization algorithm called grasshopper optimization algorithm (GOA) was applied to determine the optimal sizing of PV/wind/battery/ diesel generator. The recent EO is applied to obtain the optimal design of the microgrid system (PV/WT/battery/diesel generator). M. Kharrich et al.: Developed Approach Based on EO for Optimal Design of Hybrid PV/Wind/Diesel/Battery Microgrid TABLE 1.

PV SYSTEM

NET PRESENT COST

ENERGY MANAGEMENT STRATEGY

LOCATION AND SPECIFICATION OF THE STUDIED SYSTEM

RESULTS AND DISCUSSION

CONCLUSION