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Journal Articles Journal of Energy Storage Year : 2023

Co-optimization of a high temperature thermal storage as per its modeling accuracy

Abstract

Coupling energy networks becomes unavoidable in order to decarbonize human usages, increase global energy efficiency and ensure flexibility in so-called “multi-energy” network. In such a network, high temperature thermal energy storage (HTTES) can be a relevant solution when designed and managed in an optimal way. However, the precise modeling of its physical behavior requires complex models whose computational costs are not compatible with optimal control. A fortiori, a co-optimization approach requires to select a less precise but faster model. This article proposes to study the consequences of using a panel of such lighter models, in particular by discussing the modeling of losses. To do so, two business models will be discussed on a case study composed of a heat network linking a concentrated solar power (CSP) to thermal industrial load. When losses are not a consideration, the use of very simplistic models is sufficient to determine a good estimate of storage sizing. However, if losses are included, a proper co-optimization can only be achieved by using a metamodeling approach.
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hal-03985107 , version 1 (21-02-2023)

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Ibrahim Al Asmi, Roman Le Goff Latimier, Yasmine Lalau, Thomas Brian, Hamid Ben Ahmed. Co-optimization of a high temperature thermal storage as per its modeling accuracy. Journal of Energy Storage, 2023, 61, pp.106829. ⟨10.1016/j.est.2023.106829⟩. ⟨hal-03985107⟩
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