An Application Review of PCM-based Thermal Storage in Buildings towards Carbon Neutrality: Modeling, Forecasting and Optimal Control with AI

Bei Lu, Jinghui Yu, Wenjing Su, Y. Zong
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Abstract

Due to the rising greenhouse gases in the atmosphere, global warming is becoming a common problem for humankind. Building decarbonisation is one of the important ways to solve the greenhouse effect. In buildings, both active applications of combining phase change materials (PCM) with thermal storage devices, and passive applications of PCM embedded in building walls are very common. This review paper summarizes and classifies the application of PCM based thermal storage in buildings, mainly investigates the models and optimal control strategies of building energy management systems (BEMS) integrating PCM in green buildings’ applications, and discusses in detail the important role of artificial intelligence (AI) in multi-objective optimization and energy consumption prediction for BEMS, and finally proposes future research directions.
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基于pcm的建筑蓄热在碳中和中的应用综述:建模、预测与人工智能最优控制
由于大气中温室气体的增加,全球变暖正成为人类面临的共同问题。建筑脱碳是解决温室效应的重要途径之一。在建筑中,相变材料(PCM)与蓄热装置结合的主动应用和PCM嵌入建筑墙体的被动应用都非常普遍。本文对基于PCM的建筑蓄热应用进行了总结和分类,重点研究了集成PCM的建筑能源管理系统(BEMS)在绿色建筑应用中的模型和最优控制策略,并详细讨论了人工智能(AI)在BEMS多目标优化和能耗预测中的重要作用,最后提出了未来的研究方向。
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