Optimizing Appliance Scheduling for Solar Energy Management Us-ing Metaheuristic Algorithms

Abstract

Solar energy generation is often misaligned with when households use power, creating a scheduling challenge. We optimize appliance start times in an island microgrid setting to minimize user dissatisfaction while promoting solar use and respecting system constraints. A sequential multi-day scheduling framework using Iterated Local Search (ILS) and Simulated Annealing (SA) considers power consumption, active duration, inverter size, battery limits, and solar forecasts, opening potential to explore trade-offs between cost, system size, and satisfaction.