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  • Modern control methods such as Model Predictive Control (MPC) are getting popular in recent years in many fields of industry. One of the branches that have witnessed great increase of interest in use of the MPC over the last few years is the building climate control area. According to the studies, the energy used in the building sector counts for 20-40%20-40% of the overall energy consumption. Almost half of this amount consists of heating, ventilation and air-conditioning (HVAC) costs which implies that energy consumption decrease in this area is one of the most interesting challenges today. Besides enormous potential in reduction of energy consumed by heating, ventilation and air conditioning (HVAC) systems brought by such controller, it suffers from a bottleneck being the necessity of having a reliable mathematical model of the building at disposal. By finding a mathematical model appropriate for the MPC, it is meant to obtain such a model that is able to predict the behavior of the building sufficiently accurately for several hours ahead, which is an especially delicate task. This task is getting even more complicated in case of a real-life application. In this paper, we are looking for a reliable model of a huge three-storey office building in Hasselt, Belgium. For parameter estimation, an advanced identification approach is used – its advantage is that it attacks the problem of minimization of multi-step prediction error and in this way, it corresponds to MPC requirements for a good multi-step predictor. Moreover, we discuss not only the identification approach itself but we also focus on accompanying problems with real-operation data acquisition, processing and special treatment which is an indispensable step for achieving satisfactory identification results. The chosen model is now used in real operation with MPC at Hollandsch Huys.
  • Modern control methods such as Model Predictive Control (MPC) are getting popular in recent years in many fields of industry. One of the branches that have witnessed great increase of interest in use of the MPC over the last few years is the building climate control area. According to the studies, the energy used in the building sector counts for 20-40%20-40% of the overall energy consumption. Almost half of this amount consists of heating, ventilation and air-conditioning (HVAC) costs which implies that energy consumption decrease in this area is one of the most interesting challenges today. Besides enormous potential in reduction of energy consumed by heating, ventilation and air conditioning (HVAC) systems brought by such controller, it suffers from a bottleneck being the necessity of having a reliable mathematical model of the building at disposal. By finding a mathematical model appropriate for the MPC, it is meant to obtain such a model that is able to predict the behavior of the building sufficiently accurately for several hours ahead, which is an especially delicate task. This task is getting even more complicated in case of a real-life application. In this paper, we are looking for a reliable model of a huge three-storey office building in Hasselt, Belgium. For parameter estimation, an advanced identification approach is used – its advantage is that it attacks the problem of minimization of multi-step prediction error and in this way, it corresponds to MPC requirements for a good multi-step predictor. Moreover, we discuss not only the identification approach itself but we also focus on accompanying problems with real-operation data acquisition, processing and special treatment which is an indispensable step for achieving satisfactory identification results. The chosen model is now used in real operation with MPC at Hollandsch Huys. (en)
Title
  • Towards the Real-life Implementation of MPC for an Office Building: Identification Issues
  • Towards the Real-life Implementation of MPC for an Office Building: Identification Issues (en)
skos:prefLabel
  • Towards the Real-life Implementation of MPC for an Office Building: Identification Issues
  • Towards the Real-life Implementation of MPC for an Office Building: Identification Issues (en)
skos:notation
  • RIV/68407700:21720/14:00219699!RIV15-MSM-21720___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(ED3.1.00/13.0283), P(GAP103/12/1187), P(GC13-12726J), S
http://linked.open...iv/cisloPeriodika
  • December
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 50851
http://linked.open...ai/riv/idVysledku
  • RIV/68407700:21720/14:00219699
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Building modeling; System identification; Model predictive control (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...odStatuVydavatele
  • GB - Spojené království Velké Británie a Severního Irska
http://linked.open...ontrolniKodProRIV
  • [A5A2CCE4FDF9]
http://linked.open...i/riv/nazevZdroje
  • Applied Energy
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...v/svazekPeriodika
  • 135
http://linked.open...iv/tvurceVysledku
  • Cigler, Jiří
  • Váňa, Zdeněk
  • Žáčeková, Eva
http://linked.open...ain/vavai/riv/wos
  • 000345470100006
issn
  • 0306-2619
number of pages
http://bibframe.org/vocab/doi
  • 10.1016/j.apenergy.2014.08.004
http://localhost/t...ganizacniJednotka
  • 21720
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