Power Management and Sizing Optimization for Hybrid Grid-Dependent System Considering Photovoltaic Wind Battery Electric Vehicle
Abdulgader Alsharif, Chee Wei Tan, Razman Ayop, Abdussalam Ali Ahmed, Mohamed Khaleel, Abobaker K Abobaker
Abstract
Energy Management Strategy (EMS) as a control strategy for microgrid (MG) systems is a complex task to operate the integrated power systems and utilize consumer-based. Alternative energy sources such as solar and wind can be used to generate energy that can be used to power electrical appliances when combined with energy storage units. Additionally, with other sources to complement the drawbacks of each source. But the common drawback of the aforementioned sources are naturally unpredictable and climatology changes dependent. The main aim of this study is to minimize the cost and losses of the system, contrary, maximizing the renewability. This study considers a Tripoli-Libya as a case study located in the north of Libya and coordinated between32.88 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">o</sup> N latitude and 13.19 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">o</sup> E longitude. The system utilizes night-time for exchanging the power between the Electric Vehicle (EV) and the utility grid to form Vehicle-to-Grid (V2G) technology. The result of the study shows that the Cost of Energy (COE), Renewable Energy Fraction (REF), and Deficiency Power Supply Probability (DPSP), are an objective of the study along with the analysis of collected data based on the Grasshopper Optimization Algorithm (GOA) using Matlab. The acquired result for the sizing system configuration has been validated with nature-inspired metaheuristic algorithms.