Optimization of prosumer household with solar, battery and electric vehicle: enhancing residential energy management considering non-constant efficiency

This study presents an optimization algorithm for residential households with photovoltaic system, battery storage, and electric vehicle, focusing on the dynamic, power-dependent efficiency of electric vehicles and its impact on grid power exchange. We developed a mixed-integer linear programming model using Gurobi optimizer to enhance household energy management by strategically managing energy distribution and storage based on vehicle battery charging efficiencies, which vary with power input levels. The dynamic efficiency function for vehicle charging impacts energy distribution strategies by maximizing solar energy utilization during peak times. The model adapts to fluctuations in solar output and household consumption, optimizing economic outcomes. Simulation results using real-world data demonstrate improved energy flow management between solar panels, batteries, vehicles, and the grid. The approach minimizes grid feed-in during peak times, maximizes on-site solar utilization, and aligns vehicle charging with excess solar production, thereby reducing costs and enhancing grid stability.