Peer-Reviewed Journal Details
Mandatory Fields
O'Dwyer, E;De Tommasi, L;Kouramas, K;Cychowski, M;Lightbody, G
2016
October
Energy and Buildings
Modelling and disturbance estimation for model predictive control in building heating systems
Validated
WOS: 15 ()
Optional Fields
ENERGY-EFFICIENT BUILDINGS ARTIFICIAL NEURAL-NETWORK CLIMATE CONTROL STOCHASTIC-MODEL THERMAL CONTROL SIMULATION IDENTIFICATION OPTIMIZATION TEMPERATURE PERFORMANCE
130
532
545
As research in the area of model predictive control (MPC) for building energy systems intensifies, appropriate methods are required to model a building's thermodynamic properties. In this paper, building models are considered from two perspectives - simulation and optimisation. First, a methodology is devised for the development of complex simulation models for control strategy comparison and analysis. A novel spatio-temporal filtering technique for estimation of disturbances is devised and combined with metaheuristic search methods to allow for models to be derived from data in which typical disturbances are present. Adapting the disturbance estimation techniques, methods are then proposed for deriving low-order models from data, suitable for use within an optimisation-based MPC strategy. The modelling concepts are implemented using data from a real building and a potential MPC formulation is assessed. (C) 2016 Elsevier B.V. All rights reserved.
LAUSANNE
0378-7788
10.1016/j.enbuild.2016.08.077
Grant Details