A Review of Multi-Objective Optimization Methods of Grid-Connected Hybrid Renewable Energy Systems Combined with Electrical Vehicle Technique - Al-Sahlawi, Ameer A. Kareim; Shahrin bin Md. Ayob; Chee Wei Tan; Hussein Mohammed Ridha (ELEKTRIKA- Journal of Electrical Engineering, 2024)
Renewable Energy Sources (RESs) are regarded as highly promising and rapidly advancing forms of renewable energy. The commonly used RESs are solar energy and wind energy. However, obstacles are found in designing RESs. Using vehicle-to-grid (V2G) technology in combination with electric vehicles (EVs) and RESs in smart grid are of great significance for ensuring energy security, preventing air pollution, and promoting energy saving and emission reduction. Over the past decade, V2G technology has enabled EVs to become a potential energy storage capacity for alleviating the random fluctuation in renewable energy generation. Nevertheless, the primary drawbacks of these systems are inefficient energy conversion and substantial initial investment. The sizing of each piece of equipment in the hybrid renewable energy system (HRES) is challenging. Hence, it is imperative to employ a precise sizing technique to determine an ideal arrangement and meet the requisite load requirements. Hence, before the installation of RESs, it is crucial to consider the types and arrangements of photovoltaic (PV) panels and wind turbines (WTs), mathematical models of PV modules and WTs, storage battery options, environmental-economic-technical considerations, sizing methods based on techno-economic objectives, and the ultimate selection of the most optimal configuration. This work lists the general classification of optimization formulation framework, and multi-objective optimization methods of HRESs integrated with electrical vehicle technique are reviewed. This work provided a thorough examination of the current advancements in the design optimization of HRESs using multi-objective optimization (MOO). This study aims to select the most appropriate design before installing HRESs and provides a foundational platform for scholars interested in exploring the integration of RESs with EVs for further advancement.