Conference article

Methodology for Obtaining Linear State Space Building Energy Simulation Models

Damien Picard
Mechanical engineering, KU Leuven, Belgium

Filip Jorissen
Mechanical engineering, KU Leuven, Belgium / EnergyVille, Waterschei, Belgium

Lieve Helsen
Mechanical engineering, KU Leuven, Belgium / EnergyVille, Waterschei, Belgium

Download articlehttp://dx.doi.org/10.3384/ecp1511851

Published in: Proceedings of the 11th International Modelica Conference, Versailles, France, September 21-23, 2015

Linköping Electronic Conference Proceedings 118:5, s. 51-58

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Published: 2015-09-18

ISBN: 978-91-7685-955-1

ISSN: 1650-3686 (print), 1650-3740 (online)

Abstract

Optimal climate control for building systems is facilitated by linear, low-order models of the building structure and of its Heating, Ventilation and Air Conditioning (HVAC) systems. However, obtaining these models in a practical form is often difficult, which greatly hampers the commercial implementation of optimal controllers. This work describes a methodology for obtaining a linear State Space Model (SSM) of Building Energy Simulation (BES) models, consisting of walls, windows, floors and the zone air. The methodology uses the Modelica library IDEAS to develop a BES model, including its non-linearities, and automates its linearisation. The Dymola function Linearize2 is used to generate the state space formulation, facilitating further mathematical manipulations, or simulation in different environments. Optionally this model can then be reduced for control purposes using model order reduction (MOR) techniques. The methodology is illustrated for an office building for which a maximum error of 0.7 K between the Modelica BES model and the SSM is observed.

Keywords

building energy simulation model; linearization; Dymola; model predictive control; model order reduction

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