提出了一种既能提供能源效率又能满足居民需求的基于人工智能的城市家庭能源能效管理系统。本文提出3种预测机制:舒适温度的推导、无设备的睡眠预测、基于入住概率的外出预测。基于这些机制,设计了4种智能加热器控制策略:外出、入住、舒适和基于睡眠的控制。最后构建了一个实验测试台并进行了测量评估,在48天的评估中,该系统的节能率约为14%,居民满意度约为91%。实验结果表明,该系统在保持高满意度的同时可以节省能源。
Abstract
In the paper,a urban household energy efficiency management system is proposed that can provide both energy efficiency and meet residents' needs.Three prediction mechanisms are proposed for deriving comfortable temperatures,predicting sleep without devices,and predicting going out based on occupancy probability.Based on these mechanisms,four intelligent heater control strategies are proposed:going out,occupancy,comfort,and sleep-based control.Finally,an experiment test platform is constructed and evaluated,and over a 48-day evaluation period,the system achieved an energy saving rate of approximately 14% and a resident satisfaction rate of approximately 91%.The results show that the system can save energy while maintaining high satisfaction levels.
关键词
物联网 /
智能家居 /
AI-HEMS
Key words
IoT /
smart home /
AI-HEMS
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参考文献
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