Low-Carbon Photovoltaic and Energy Storage Configuration for Highway Service Areas Based on Multi-Objective Traffic Energy Optimization

To enhance service quality, many service areas have introduced fast-charging stations for electric vehicles (EVs). However, these stations often demand substantial charging loads, primarily supplied by traditional energy sources, leading to increased carbon emissions and costs. Therefore, establishing a low-carbon, economical, and energy-efficient energy supply system for highway service area charging stations has become imperative. This involves optimizing the configuration of photovoltaic (PV) systems and energy storage to minimize carbon emissions while maximizing economic benefits and clean energy utilization.In constructing such a low-carbon, economical, and clean energy supply system for highway service area charging stations, this study proposes an integrated PV and energy storage optimization model that considers comprehensive energy efficiency. The model aims to achieve multiple objectives: minimizing carbon emissions, reducing annual operational and investment costs, and maximizing energy self-sufficiency. Constraints include the charging and discharging states of EVs. Given the discrete and discontinuous variables, along with multiple objectives in the established model, the Non-dominated Sorting Genetic Algorithm III (NSGA-III) is employed for optimization.Case studies demonstrate that, within a microgrid model of a highway service area charging station, the system meets EV charging and discharging demands and basic load requirements. This results in improved service levels, reduced carbon emissions, and enhanced power supply reliability. The proposed model is also applicable to other service area charging stations. Integrating a high proportion of renewable energy into the grid can effectively achieve clean, low-carbon, and economical energy supply.