Review and Analysis of Sustainable Optimization Strategies for Electric Vehicle Charging

More flexible electrical vehicle charging stations particularly in lower distribution networks are a challenge to grid operators. This paper seeks to justify the use of electric vehicles as a means of energy storage and control and how plug-in electric vehicles (PEVs) could reduce energy costs to residential consumers by using supplementary stored energy. The research proposes an algorithm-based framework designed to optimize energy management by enabling PEVs to make informed decisions regarding battery charging and discharging, based on real-time grid prices and the energy cost associated with storage capacity, referred to as the energy price tag (EPT). This study aims to optimize the energy exchange between PEVs and the grid, focusing on three primary objectives: effectiveness, reliability, and economy. The proposed approach uses enhanced versions of an example of sophisticated computation algorithms that include the ordinary particle swarm optimization algorithm to match the charging and discharging of PEVs with grid requirements. Some of the research focuses are presented, such as the charging schedule with the grid requirements integration, adjustable energy distribution, accurate scaling of energy computations, and an assessment of related technologies. Filling these research gaps is essential for establishing systematic PEV-grid ties and extending the transition of the energy-related sector to sustainable solutions. The existing methodologies are presented, the applicability of the methodologies is evaluated, and the areas of improvement are discussed to give specific guidance on how energy management systems can be improved based on the ranking results of the methodologies in this paper. These findings are meant to inform the development of further research on how to better integrate PEV operations with the grid as a part of an overall resilient and effective energy system.