Building Energy Strategies Considering Demand Response and Multi-Objective Optimization

This study focuses on exploring building energy strategies based on demand response and employs a multi-objective optimization approach to balance energy consumption costs and comfort levels. With the increasing number of renewable energy providers, the electricity system faces increasingly complex energy scheduling challenges, particularly due to the significant impact of dynamic building heating and cooling loads on system stability. Therefore, the proposed comprehensive demand response mechanism aims to optimize energy utilization efficiency and reduce energy costs by adjusting building energy consumption patterns to interact effectively with renewable energy providers and the electricity system. Using a multi-objective genetic algorithm, this research seeks to find the optimal balance between minimizing user energy costs and maximizing comfort levels during the adjustment of energy strategies. Simulation results indicate that the proposed method significantly reduces building energy consumption costs while enhancing comfort levels. These findings provide substantial guidance and practical value for the sustainable development of power systems in the context of large-scale renewable energy integration.