Metaheuristic Algorithms Optimize Household Appliance Scheduling for Solar Energy Systems
Researchers developed optimization algorithms using Iterated Local Search and Simulated Annealing to schedule household appliances in alignment with solar energy generation patterns. The approach addresses the mismatch between when solar power is available (daytime) and when households typically use appliances, while accounting for battery constraints and user preferences. The work demonstrates that multi-day scheduling frameworks can maximize renewable energy utilization while maintaining user convenience in off-grid or solar-dependent systems.
A new study presents a computational approach to optimize when household appliances operate to better align with solar energy availability. The research uses two metaheuristic algorithms—Iterated Local Search and Simulated Annealing—to determine optimal start times for appliances like cookers, washing machines, and dryers while respecting constraints including power consumption limits, battery charge levels, and inverter capacity. A key innovation is extending the optimization beyond single-day scheduling to handle tasks that spill over from previous days, enabling appliances to operate sequentially across multiple days. Experimental results indicate the framework effectively manages system constraints while preserving user convenience under exclusive solar generation. The authors note their findings open avenues for future research on balancing equipment investment costs, return on investment, and user satisfaction in renewable energy systems.
What's missing
The paper does not specify the size or composition of the household test cases, the geographic location or solar irradiance conditions used in experiments, the baseline methods against which the proposed algorithms were compared, or quantitative metrics for user inconvenience. The authors acknowledge but do not detail the multi-objective trade-offs between equipment investment, ROI, and user satisfaction that warrant future research.
What different sources said
- arXiv cs.AICenter
Optimizing Appliance Scheduling for Solar Energy Management Using Metaheuristic Algorithms
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