Optimal Sizing of Hybrid PV/Wind/Battery/Diesel Microgrid System Using A Multi-objective Grasshopper optimization Algorithm: A Case Study in Djelfa City Algeria

Abstract

Supplying the residential units with energy using small-scale and off-grid hybrid renewable energy systems (the so-called autonomous microgrid) with technological developments becomes more economical, reliable, and responsive to their environmental values. This study presents the application of a novel method based on a Multi-objective Grasshopper optimization Algorithm (MOGOA) to determine the optimal sizing of hybrid renewable energy sources (HRES) integrated into an autonomous microgrid. It composes of a photovoltaic system (PV), wind turbine generator (WT), battery bank, diesel generator (DG), and inverter. It aims to satisfy the energy demand of five residential units proposed in Djelfa city in Algeria. The loss of power supply probability (LPSP) and the cost of energy (COE) are defined as objective functions and the renewable factor (RF) as constrain. The objective of the suggested approach is to determine three design variables: the nominal power of photovoltaic, the number of wind turbines, and the number of autonomy days. Such that the reliability is maximized and the COE is minimized. The MATLAB software is used to program and simulate the hybrid microgrid (HMG) system. The optimization results utilizing the proposed approach provided a collection of design solutions for the HMG system, which will aid designers in selecting the best HMG system configuration. Furthermore, selecting appropriately sized HMG system components is critical to ensuring that all load needs are satisfied with the least amount of energy and the highest level of reliability.