Smart Grid Renewable Energy Configuration Decision Model Based on Multi-Objective Optimization

The paper constructs a multi-objective decision-making model in the configuration of renewable energy in the smart grid. This is a management tool for finding the configuration of renewable energy in the smart grid to get the maximum economic benefit and use energy most efficiently while considering environmental protection. This paper uses economic theory fully in the application, mathematical modeling, methods for conducting cost-benefit analysis, and optimization algorithms. The power demand, renewable energy supply, and economic and environmental data between the years 2020 and 2024 in one region are used in testing the performance and optimization of the model using genetic algorithms. The results show that the optimization model has significant effects in reducing costs, improving economic benefits and reducing environmental impacts, and the optimized energy configuration scheme significantly reduces CO2 emissions. More references are given on how a multi-objective optimization model is constructed and proved for its practicality for scientific planning and optimization of renewable energy in a smart grid, with high-level feasibility and application value in practicality.