About: Beyond Theory: the Challenge of Implementing Model Predictive Control in Buildings     Goto   Sponge   NotDistinct   Permalink

An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

AttributesValues
rdf:type
Description
  • Model Predictive Control (MPC) of buildings has gained lot of attention in the recent years. Several research projects have demonstrated that MPC can provide substantial energy savings and improve indoor comfort as compared to traditional control approaches. However, the application of MPC requires extensive knowledge in the areas of mathematical and computer modeling, hard- and software systems, data processing, and optimal control. Therefore its application implies considerable additional cost. The key issue is if corresponding energy savings and comfort improvements can balance this cost. The present paper discusses challenges encountered during the implementation of MPC in two different pilot case studies.The first study focuses on a 50 years old building with Thermally Activated Building Systems (TABS), while the second one deals with a newly built office building. Our experience suggests that a simple (not to be confounded with simplistic) model is sufficient to economically operate MPC on a building. However, firm guidelines allowing investors to assess whether it is worth to embark in MPC for a particular building are still lacking. In our opinion the situation could be much improved if building control would be considered already at the very early stages of the building and technical systems design. In this case we believe that MPC presents an attractive option for optimal supervisory control, in particular for buildings with large thermal storage capacity.
  • Model Predictive Control (MPC) of buildings has gained lot of attention in the recent years. Several research projects have demonstrated that MPC can provide substantial energy savings and improve indoor comfort as compared to traditional control approaches. However, the application of MPC requires extensive knowledge in the areas of mathematical and computer modeling, hard- and software systems, data processing, and optimal control. Therefore its application implies considerable additional cost. The key issue is if corresponding energy savings and comfort improvements can balance this cost. The present paper discusses challenges encountered during the implementation of MPC in two different pilot case studies.The first study focuses on a 50 years old building with Thermally Activated Building Systems (TABS), while the second one deals with a newly built office building. Our experience suggests that a simple (not to be confounded with simplistic) model is sufficient to economically operate MPC on a building. However, firm guidelines allowing investors to assess whether it is worth to embark in MPC for a particular building are still lacking. In our opinion the situation could be much improved if building control would be considered already at the very early stages of the building and technical systems design. In this case we believe that MPC presents an attractive option for optimal supervisory control, in particular for buildings with large thermal storage capacity. (en)
Title
  • Beyond Theory: the Challenge of Implementing Model Predictive Control in Buildings
  • Beyond Theory: the Challenge of Implementing Model Predictive Control in Buildings (en)
skos:prefLabel
  • Beyond Theory: the Challenge of Implementing Model Predictive Control in Buildings
  • Beyond Theory: the Challenge of Implementing Model Predictive Control in Buildings (en)
skos:notation
  • RIV/68407700:21720/13:00207164!RIV14-MSM-21720___
http://linked.open...avai/predkladatel
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(ED2.1.00/03.0091), S
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
  • 63167
http://linked.open...ai/riv/idVysledku
  • RIV/68407700:21720/13:00207164
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Predictive control; Energy savings; Controller deployment (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [E909DE591DBC]
http://linked.open...v/mistoKonaniAkce
  • Praha
http://linked.open...i/riv/mistoVydani
  • Praha
http://linked.open...i/riv/nazevZdroje
  • Clima 2013 - 11th REHVA World Congress & 8th International Conference on IAQVEC - %22Energy Efficient, Smart and Healthy Buildings%22
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...iv/tvurceVysledku
  • Cigler, Jiří
  • Ferkl, Lukáš
  • Gyalistras, D.
  • Široký, J.
  • Tiet, V.- N.
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
http://purl.org/ne...btex#hasPublisher
  • Společnost pro techniku prostředí
https://schema.org/isbn
  • 978-80-260-4001-9
http://localhost/t...ganizacniJednotka
  • 21720
Faceted Search & Find service v1.16.118 as of Jun 21 2024


Alternative Linked Data Documents: ODE     Content Formats:   [cxml] [csv]     RDF   [text] [turtle] [ld+json] [rdf+json] [rdf+xml]     ODATA   [atom+xml] [odata+json]     Microdata   [microdata+json] [html]    About   
This material is Open Knowledge   W3C Semantic Web Technology [RDF Data] Valid XHTML + RDFa
OpenLink Virtuoso version 07.20.3240 as of Jun 21 2024, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (126 GB total memory, 44 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software