Metaheuristic Algorithms Optimize Household Appliance Scheduling for Solar Energy Systems
A new study proposes using Iterated Local Search and Simulated Annealing algorithms to schedule household appliances around solar energy availability, maximizing renewable energy use while minimizing user inconvenience. Unlike prior work, the framework extends scheduling across multiple days to handle tasks that carry over from previous days. The approach could help households better align energy consumption with solar generation patterns, reducing reliance on grid power or battery storage.
Researchers have developed a metaheuristic optimization framework to address the mismatch between solar energy generation—which occurs only during daylight hours—and typical household appliance usage patterns. The system uses Iterated Local Search (ILS) and Simulated Annealing (SA) to determine optimal start times for appliances such as cookers, washing machines, and dryers, while respecting constraints including inverter limits, battery state of charge, and solar generation forecasts. A key distinguishing feature of the work is its multi-day scheduling horizon, which accounts for tasks left unfinished from previous days—referred to as 'spillover'—ensuring operational continuity rather than treating each day in isolation. Experimental results indicate the framework effectively manages system constraints while maintaining user convenience under conditions of exclusive solar generation. The paper, accepted as a poster at GECCO 2026, also identifies future research directions including multi-objective trade-offs between equipment investment costs, return on investment, and user satisfaction.
What's missing
The study's own limitations include that experiments appear to be conducted under simulated or modeled conditions rather than real-world household deployments, and the paper does not report results under mixed solar-and-grid scenarios. The scalability of the approach to larger numbers of appliances or more complex household energy systems is not addressed.
What different sources said
- arXiv cs.AICenter
Optimizing Appliance Scheduling for Solar Energy Management Using Metaheuristic Algorithms
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