On modelling effects in the battery and thermal storage scheduling problem. Issue 1 (2nd January 2021)

• Record Type: Journal Article
• Authors: Murray, Alexander; Schütz, Thomas; Pan, Guanru; Müller, Dirk; Hagenmeyer, Veit
• Is Part Of: Journal of building performance simulation. Volume 14:Issue 1(2021)
• Page Start: 38
• Page End: 51
• Publication Date: 2021-01-02
• Subjects: Thermal storages -- battery scheduling -- model predictive control -- mixed integer optimization -- nonlinear optimization -- modelling; 690.0113
• DOI: 10.1080/19401493.2020.1838611
• Languages: English
• ISSNs: 1940-1493

Abstract

ABSTRACT: The growing use of intermittent renewable energy sources requires an increased amount of storage capacity to match uncertain generation with uncertain demand. A possible solution is the use of thermal and electrical storages. This paper compares several model formulations: mixed integer linear programs (MILPs), nonlinear programs (NLPs), mixed integer nonlinear programs (MINLPs) for optimizing the operation of a multi-modal home energy system comprising heating and electricity subsystems. The respective optimization problems are then resolved within a model predictive control scheme and the final solutions are compared in terms of runtime and optimality. The results indicate that a thermocline-based thermal storage model leads to the overall lowest costs while not significantly impeding computing times. Additionally, the results show that a continuous heat pump model leads to reduced computing times without affecting the modelling accuracy.