退役电动汽车电池与并网混合能源系统的经济技术分析

Abstract The present study aims to conduct a techno-economic analysis of Retired Electric Vehicle Batteries (REVB) with Grid-Connected Hybrid Energy Systems (HES) for Electric Vehicle (EV) charging. This work integrates various parameters for the optimal design of a REVB with a grid-connected HES system. Technical parameters include Renewable factor (RF), Photovoltaic fraction (PVF), as well as Wind fraction (WF); Economic factors considered are Levelized Cost of Energy (LCOE), Net Present Cost (NPC), and Annualized system cost (ASC); and Environmental factors such as Avoided Reduced greenhouse gas emissions (RGGE). Additionally, the social factor of the Human Development Index (HDI), and the Job Creation Factor (JCF) are included in the proposed design. An enhanced optimization algorithm known as the Enhanced Star Fish Optimization Algorithm (EnSFOA) is proposed to address this challenge effectively. Additionally, the effectiveness of the EnSFOA algorithm is assessed through the CEC 2019 and CEC 2022 test suites along with the REVB with Grid-Connected HES design problem. The analysis demonstrates that the EnSFOA algorithm has determined the most cost-effective ASC, LCOE, and NPC for the chosen site, with values of 1.815253E+05 $, 0.2295 $/kWh, and 2.5799E+06 $/year, respectively and these values are assessed to be economically feasible. The EnSFOA algorithm achieves optimum economic effectiveness while concurrently reducing environmental impact while maintaining an excellent JCF and HDI. These results confirm the EnSFOA algorithm as a potential tool for encouraging sustainable energy solutions while addressing the complex nature of REVB with a grid-connected HES system.