The amount of electricity consumed grows exponentially with each passing year. Energy management (EM) has the potential to help satisfy electricity demands more efficiently. It implements strategies to reduce energy consumption during peak time or shift its usage to off-peak hours. This research introduces SPEMS (Sustainable Parasitic EM System), a competitive yet cooperative Multi-agent System (MAS) based framework that optimizes energy cost, consumption, Peak-to-Average Ratio (PAR), and user’s discomfort unobtrusively. The framework devises an optimized load scheduling plan for smart appliances using the Host-Parasite Model where the agents with conflicting objectives need to have a symbiotic relationship. Our work follows a quantitative approach towards evaluating user comfort. It takes into account environmental aspects like user presence and weather elements including user temperature, apparent temperature, and visibility. SPEMS adapts itself to user’s behavior patterns without requiring the user to enter their everyday feedback. The concept of sampled Hall of Fame is incorporated to preserve and use the best schedules from previous days ensuring progress towards finding optimal schedules. Experiments have been performed on real-time data collected from a real home for about one and a half years. Results show that our model is computationally inexpensive, sustainable, and minimizes cost, consumption, and PAR with reduced discomfort of the user.

消耗的电量逐年呈指数增长。能源管理 (EM) 有可能帮助更有效地满足电力需求。它实施策略以减少高峰时段的能源消耗或将其使用转移到非高峰时段。本研究介绍了 SPEMS（可持续寄生 EM 系统），这是一种基于竞争性但协作的多代理系统 (MAS) 的框架，可优化能源成本、消耗、峰均比 (PAR) 和用户的不适感。该框架使用宿主寄生虫模型为智能设备设计了一个优化的负载调度计划，其中具有冲突目标的代理需要具有共生关系。我们的工作遵循评估用户舒适度的定量方法。它考虑了环境因素，如用户存在和天气因素，包括用户温度、表观温度和能见度。SPEMS 可以适应用户的行为模式，而无需用户输入他们的日常反馈。纳入名人堂抽样的概念以保留和使用前几天的最佳时间表，确保在寻找最佳时间表方面取得进展。已经对从真实家庭收集的实时数据进行了大约一年半的实验。结果表明，我们的模型计算成本低、可持续，并且最大限度地减少了成本、消耗和 PAR，同时减少了用户的不适。SPEMS 可以适应用户的行为模式，而无需用户输入他们的日常反馈。纳入名人堂抽样的概念以保留和使用前几天的最佳时间表，确保在寻找最佳时间表方面取得进展。已经对从真实家庭收集的实时数据进行了大约一年半的实验。结果表明，我们的模型计算成本低、可持续，并且最大限度地减少了成本、消耗和 PAR，同时减少了用户的不适。SPEMS 可以适应用户的行为模式，而无需用户输入他们的日常反馈。纳入名人堂抽样的概念以保留和使用前几天的最佳时间表，确保在寻找最佳时间表方面取得进展。已经对从真实家庭收集的实时数据进行了大约一年半的实验。结果表明，我们的模型计算成本低、可持续，并且最大限度地减少了成本、消耗和 PAR，同时减少了用户的不适。