用智能算法优化家电时间，让太阳能用得更省心。
Optimizing Appliance Scheduling for Solar Energy Management Using Metaheuristic Algorithms
- 结合迭代局部搜索与模拟退火，动态调整家电启停时间。
- 多日连续调度可处理未完成任务，提升系统稳定性。
- 兼顾用户习惯与设备限制，适合家庭光伏系统部署。
可再生能源对满足未来能源需求至关重要；然而，太阳能仅在白天发电，常与家庭用电高峰不匹配。电饭煲、洗衣机、烘干机等家电通常按用户偏好使用，而非太阳能可用性，形成调度优化难题。目标是确定最优启动时间，以最大化可再生能源利用率，同时最小化用户不便并遵守系统约束。本文提出基于迭代局部搜索（ILS）与模拟退火（SA）的元启发式方法，考虑家电运行时长、功耗、逆变器功率限制、电池电量状态及太阳能发电预测。不同于多数现有研究，该调度扩展至多日周期，支持前一日未完成任务的延续（任务溢出），确保操作连续性，实现跨日连续运行。实验表明，该多日序列调度框架能有效管理各类约束，并在纯太阳能供电下保障用户便利。研究也为未来多目标权衡（如设备投资规模、回报率与用户满意度）提供了新方向。
原文摘要 · Abstract (English)
Renewable energy is essential for meeting future energy demands; however, solar energy generation, which occurs only during daylight hours often does not align with household consumption patterns. Appliances such as cookers, washing machines, and dryers are typically operated according to user preferred schedules rather than solar energy availability, creating a scheduling optimization problem. The objective is to determine optimal appliance start times to maximize renewable energy utilization while minimizing user inconvenience and adhering to system constraints. This paper presents a metaheuristic approach using Iterated Local Search (ILS) and Simulated Annealing (SA) to optimize appliance start times, while considering appliance operating durations, power consumption, inverter limit, battery state of charge constraints, and solar generation forecasts. Unlike most existing work, the scheduling is extended beyond a single day to accommodate unfinished tasks from previous days (spillover), ensuring operational continuity and enabling sequential operation across multiple days. Experimental results show that the sequential multi-day scheduling framework effectively manages system constraints while ensuring user convenience under exclusive solar generation. These findings also open opportunities for future research on multi-objective trade-offs between investment in equipment of various sizes, return on that investment, and user satisfaction.
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