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.

翻译：可再生能源对于满足未来能源需求至关重要；然而，太阳能发电仅发生在白天时段，往往与家庭用电模式不一致。诸如电灶、洗衣机和烘干机等家电通常根据用户偏好的时间表而非太阳能可用性来运行，这便构成了一个调度优化问题。其目标是确定最优的家电启动时间，以最大化可再生能源利用率，同时最小化用户不便并满足系统约束。本文提出了一种基于迭代局部搜索（ILS）和模拟退火（SA）的元启发式方法，用于优化家电启动时间，同时考虑家电运行时长、功耗、逆变器限制、电池荷电状态约束以及太阳能发电预测。与大多数现有研究不同，本调度方案将时间跨度从单日扩展至多日，以容纳前一日未完成的任务（溢出效应），从而确保运行的连续性并支持跨多天的顺序操作。实验结果表明，顺序多日调度框架能够有效管理系统约束，同时在纯太阳能发电场景下保障用户便利性。这些发现也为未来研究提供了机遇，可进一步探讨不同规模设备投资、投资回报率与用户满意度之间的多目标权衡。