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Identification of non-linear autoregressive models with exogenous inputs for room air temperature modelling

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摘要 This paper proposes non-linear autoregressive models with exogenous inputs to model the air temperature ineach room of a Danish school building connected to the local district heating network. To obtain satisfactorymodels, the authors find it necessary to estimate the solar radiation effect as a function of the time of the dayusing a B-spline basis expansion. Furthermore, this paper proposes a method for estimating the valve positionof the radiator thermostats in each room using modified Hermite polynomials to ensure monotonicity of theestimated curve. The non-linearities require a modification in the estimation procedure: Some parametersare estimated in an outer optimisation, while the usual regression parameters are estimated in an inneroptimisation. The models are able to simulate the temperature 24 h ahead with a root-mean-square-errorof the predictions between 0.25℃ and 0.6℃. The models seem to capture the solar radiation gain in away aligned with expectations. The estimated thermostatic valve functions also seem to capture the importantvariations of the individual room heat inputs.
出处 《Energy and AI》 2022年第3期78-87,共10页 能源与人工智能(英文)
基金 funding from the following projects Sustainable plus energy neighbourhoods(syn.ikia)(H2020 No.869918) FMEZEN(Research Council of Norway-257660) Top-up(Innovation Fund Denmark 9045-00017B) SCA+(InterregÖresund-Kattegat-Skagerrak) Flexibile Energy Denmark(FED)(IFD 8090-00069B).

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