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Load decomposition: A conceptual framework for design and control of thermal energy storage systems in buildings

This work proposes a load decomposition framework for the characterization of thermal energy storage systems (TES) in buildings. This conceptual framework makes it possible to rapidly obtain an estimate of the required rating for the primary equipment and the storage device. The proposed approach em...

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Bibliographic Details
Published in:Journal of energy storage 2024-01, Vol.77, p.110030, Article 110030
Main Authors: Nguyen, Alain, Candanedo, José
Format: Article
Language:English
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Summary:This work proposes a load decomposition framework for the characterization of thermal energy storage systems (TES) in buildings. This conceptual framework makes it possible to rapidly obtain an estimate of the required rating for the primary equipment and the storage device. The proposed approach employs mathematical methods from signal processing to break down the building load signal into two sub-signals: (a) a primary load provided by the primary production system, and (b) a balancing load provided by the storage system. This information is used to form a Pareto set of solutions that expresses the trade-off between the storage capacity and the primary system size, and hence, comprises the peak shaving potential of any given configuration. A simple decomposition method based on the concept of ”moving average” is tested within this framework on a representative energy model of an office building in the region of Montréal, Québec (QC). The Pareto set is shown to offer a wide range of design and operation solutions for peak shaving, from small water tanks to large underground reservoirs. The results provide clear evidence that TES system not only contributes to peak shaving and load shifting, but also to significantly reduce the primary production unit size. •A load decomposition framework for the characterization of TES in buildings is proposed.•The output is a wide range of design and operation solutions for peak shaving.•Each solution directly provides relevant design and operation parameters.•The system’s design and operation can then be optimized within this solution set.
ISSN:2352-152X
DOI:10.1016/j.est.2023.110030