A solid thermal storage model for the optimization of buildings operation strategy. (August 2015)

• Record Type: Journal Article
• Authors: Fazlollahi, Samira; Schüler, Nils; Maréchal, François
• Is Part Of: Energy. Volume 88(2015)
• Page Start: 209
• Page End: 222
• Publication Date: 2015-08
• Subjects: Solid thermal storage -- Demand side management -- Mixed integer linear programming -- Urban system -- Process integration; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2015.04.085
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: With an increasing fluctuation of energy supply due to the integration of renewable energy utilities peak-shaving becomes more and more important. Storage systems are a considerable option for this purpose. For the heat supply in cities the buildings themselves can be employed as solid thermal energy storages utilizing their thermal inertia and applying an operation strategy which takes into account comfort, economic and ecologic considerations. Therefore the present work proposes a MILP (Mixed Integer Linear Programing) model accounting for the system's dynamics to optimize this operation strategy and the according comfort temperature, by taking into account a dynamic effect of the building. The dynamic effect considers that the building can be charged/discharged to a certain degree, depends on the effective heat capacity of the building and the indoor comfort temperature. In order to properly account for the temperature, the model incorporates energy integration techniques. By means of a test case it is shown that the primary energy consumption and the operating expenses can be decreased when operating the building within a given range for the comfort temperature. Highlights: Develop a model to optimize the operation and the comfort temperature of a building. Including energy integration and pinch analysis techniques in the proposed model. Simulate a building as a solid thermal storage system. Using MILP for solving proposed mixed integer optimisation model. Demonstrate the proposed model by means of a case study.