Prioritised objectives for model predictive control of building heating systems

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O'Dwyer, Edward
De Tommasi, Luciano
Kouramas, Konstantinos
Cychowski, Marcin
Lightbody, Gordon
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Elsevier B.V.
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Advantages of Model Predictive Control (MPC) strategies for control of building energy systems have been widely reported. A key requirement for successful realisation of such approaches is that strategies are formulated in such a way as to be easily adapted to fit a wide range of buildings with little commissioning effort. This paper introduces an MPC-based building heating strategy, whereby the (typically competing) objectives of energy and thermal comfort are optimised in a prioritised manner. The need for balancing weights in an objective function is eliminated, simplifying the design of the strategy. The problem is further divided into supply and demand problems, separating a high order linear optimisation from a low order nonlinear optimisation. The performance of the formulation is demonstrated in a simulation platform, which is trained to replicate the thermal dynamics of a real building using data taken from the building.
Lexicographic MPC , Prioritised objectives , Building energy , Fault tolerance , System identification
O'Dwyer, E., De Tommasi, L., Kouramas, K., Cychowski, M. and Lightbody, G. (2017) 'Prioritised objectives for model predictive control of building heating systems', Control Engineering Practice, 63, pp. 57-68. doi:10.1016/j.conengprac.2017.03.018
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