Optimizing Appliance Scheduling for Solar Energy Management Using Metaheuristic Algorithms
This paper introduces a metaheuristic approach using Iterated Local Search (ILS) and Simulated Annealing (SA) to optimize appliance scheduling for solar energy management. The goal is to maximize the utilization of solar energy by aligning appliance usage with generation times, while minimizing user inconvenience and adhering to system constraints like battery charge and inverter limits. The proposed method extends scheduling beyond a single day to handle tasks that spill over, ensuring continuity and enabling multi-day sequential operations. AI
IMPACT This research could lead to more efficient home energy management systems by better integrating solar power with appliance usage.