A predictive control strategy for energy management in buildings with radiant floors and thermal storage

S. Rastegarpour, Mahshid Ghaemi, L. Ferrarmi
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引用次数: 13

Abstract

Due to the growing energy demand in residential building, the need to reduce carbon footprint, and the smart grid paradigm, thermal energy control and overall power consumption reduction have become a hot research topic. The development of an energy management system able to modify consumer's energy consumption patterns while preserving comfort is a substantial solution. Hence, for load shaping in demand side management, particularly useful is the usage of a thermal energy storage (TES). It gives the possibility to shape the demand profile in an economic way based on dynamic electricity tariffs, by storing energy in thermal terms during off-peak hours. This paper focuses on the development of a novel control model for the integration of TES, HVAC system, building and local renewable energy sources to be used with optimization techniques. The presented control framework is based on Model Predictive Control (MPC) to better anticipate the effects of disturbances (e.g. weather conditions and user requirements on the load side, electricity price, etc.). A distributed structure has also been considered, to follow the modular structure of the system under control with the aim of optimizing the energy consumption costs and improving the indoor comfort level. Furthermore, the novel configuration of TES coupled with a heat pump and a radiant floor building giving rise to a more complex model with respect to the literature ones.
具有辐射地板和蓄热的建筑能源管理的预测控制策略
由于住宅建筑能源需求的不断增长,减少碳足迹的需要,以及智能电网的范例,热能控制和整体功耗降低已成为研究热点。能源管理系统的发展能够改变消费者的能源消耗模式,同时保持舒适是一个实质性的解决方案。因此,对于需求侧管理中的负载塑造,特别有用的是使用热能储存(TES)。它提供了一种基于动态电价的经济方式来塑造需求概况的可能性,通过在非高峰时段以热能形式储存能源。本文的重点是开发一种新的控制模型,将TES、HVAC系统、建筑和当地可再生能源与优化技术相结合。所提出的控制框架是基于模型预测控制(MPC),以更好地预测干扰的影响(例如,天气条件和用户对负荷侧的需求,电价等)。我们还考虑了分布式结构,遵循控制系统的模块化结构,以优化能耗成本和提高室内舒适度。此外,与文献中的模型相比,与热泵和辐射地板建筑相结合的TES的新配置产生了更复杂的模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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