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

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.