A novel time discretization method for solving complex multi-energy system design and operation problems with high penetration of renewable energy. (July 2022)

• Record Type: Journal Article
• Authors: Weimann, Lukas; Gazzani, Matteo
• Is Part Of: Computers & chemical engineering. Volume 163(2022)
• Publication Date: 2022-07
• Subjects: MILP -- Time discretization -- Energy system model -- Renewable energy -- Optimization; Chemical engineering -- Data processing -- Periodicals; 660.0285
• DOI: 10.1016/j.compchemeng.2022.107816
• Languages: English
• ISSNs: 0098-1354

Abstract

Highlights: Novel method for simplification of time-resolved energy system optimization. Well suited for systems with high penetration of non-dispatchable renewables. Framework-independent and easy to implement for researchers and practitioners alike. 95% saving in computation time with less than 1% error in objective functions. Added value of method shown through application to green hydrogen case study. Abstract: Modelling and optimising modern energy systems is inherently complex and often requires methods to simplify the discretization of the temporal domain. However, most of them are either (i) not well suited for systems with a high penetration of non-dispatchable renewables or (ii) too complex to be broadly adopted. In this work, we present a novel method that fits well with high penetration of renewables and different spatial scales. Furthermore, it is framework-independent and simple to implement. We show that, compared to the full time discretization, the proposed method saves > 90% computation time with < 1% error in the objective function. Moreover, it outperforms commonly used methods of modelling through typical days. Its practical usefulness is demonstrated by applying it to a case study about the optimal hydrogen production from renewable energy. The increased modelling fidelity results in a significantly cheaper design and reveals operational details otherwise hidden by typical days.