This application provides a method, apparatus, device, medium, and product for determining a
charging station configuration scheme, relating to the field of charging equipment. The method acquires historical charging behavior data from multiple vehicles and, based on this data reflecting actual charging patterns, plots a charging load curve for a future second time period. This replaces the fixed or typical day load curve input in existing technologies, aligning with the dynamic characteristics of load changes and avoiding
scenario adaptation bias caused by static assumptions. Furthermore, it integrates a photovoltaic output model, multiple
energy storage system parameters, and multiple preset optimization objectives to construct a multi-objective optimization model that comprehensively covers
energy supply,
energy storage, and demand-side characteristics. This eliminates the need for manual supplementation of
scenario adaptation parameters. Finally, through automatic solving of this multi-objective optimization model, it directly outputs a target configuration scheme that can guide adjustments to
charging station configuration information, reducing the tedious process of manually verifying
model parameters and repeatedly iterating and correcting, thus improving the efficiency of scheme determination.