On modelling effects in the battery and thermal storage scheduling problem

Journal of Building Performance Simulation, vol. 14, pp. 38–51

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.

Authors 4

1. Alexander Murray corresponding

   Karlsruhe Institute of Technology

   Affiliation as printed

   Institute for Automation and Applied Informatics, Karlsruhe Institute of Technology, Karlsruhe, Germany

2. Guanru Pan

   Karlsruhe Institute of Technology

   Affiliation as printed

   Institute for Automation and Applied Informatics, Karlsruhe Institute of Technology, Karlsruhe, Germany

3. Dirk Müller Aachen Institute for Energy Efficient Buildings and Indoor Climate

   RWTH Aachen University

   Affiliation as printed

   Institute for Energy Efficient Buildings and Indoor Climate, RWTH Aachen, Aachen, Germany

4. Veit Hagenmeyer

   Karlsruhe Institute of Technology

   Affiliation as printed

   Institute for Automation and Applied Informatics, Karlsruhe Institute of Technology, Karlsruhe, Germany