About: Optimization of Predicted Mean Vote Thermal Comfort Index within Model Predictive Control Framework

Facets (new session)
Description
Metadata
Settings
- owl:sameAs
- Inference Rule:

About: Optimization of Predicted Mean Vote Thermal Comfort Index within Model Predictive Control Framework 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)

Attributes	Values
rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	Recently, Model Predictive Control (MPC) for buildings has undergone an intensive research. Usually, according to the international standards, a static range for the air temperature represents the thermal comfort which is being kept making use of MPC while minimizing the energy consumption. On contrary, this paper deals with the optimization of the trade-off between energy consumption and Predicted Mean Vote (PMV) index which, opposed to the static temperature range, describes user comfort directly. PMV index is a nonlinear function of various quantities, which makes the problem more difficult to solve. The paper will show the main differences in MPC problem formulation, propose a tractable approximation strategy and compare the control performance both to the conventional and typical predictive control strategies. The approximation of PMV computation will be shown to be sufficiently precise and moreover, such a formulation keeps the MPC optimization problem convex. Finally, it will be shown that the proposed PMV based optimal control problem formulation shifts the savings potential of typical MPC by additional 10% while keeping the comfort at a desired level. Recently, Model Predictive Control (MPC) for buildings has undergone an intensive research. Usually, according to the international standards, a static range for the air temperature represents the thermal comfort which is being kept making use of MPC while minimizing the energy consumption. On contrary, this paper deals with the optimization of the trade-off between energy consumption and Predicted Mean Vote (PMV) index which, opposed to the static temperature range, describes user comfort directly. PMV index is a nonlinear function of various quantities, which makes the problem more difficult to solve. The paper will show the main differences in MPC problem formulation, propose a tractable approximation strategy and compare the control performance both to the conventional and typical predictive control strategies. The approximation of PMV computation will be shown to be sufficiently precise and moreover, such a formulation keeps the MPC optimization problem convex. Finally, it will be shown that the proposed PMV based optimal control problem formulation shifts the savings potential of typical MPC by additional 10% while keeping the comfort at a desired level. (en)
Title	Optimization of Predicted Mean Vote Thermal Comfort Index within Model Predictive Control Framework Optimization of Predicted Mean Vote Thermal Comfort Index within Model Predictive Control Framework (en)
skos:prefLabel	Optimization of Predicted Mean Vote Thermal Comfort Index within Model Predictive Control Framework Optimization of Predicted Mean Vote Thermal Comfort Index within Model Predictive Control Framework (en)
skos:notation	RIV/68407700:21230/12:00198811!RIV13-MSM-21230___
http://linked.open...avai/predkladatel	Fakulta elektrotechnická
http://linked.open...avai/riv/aktivita	P S
http://linked.open...avai/riv/aktivity	P(FR-TI1/517), P(GAP103/12/1187), P(GAP103/12/1794), S
http://linked.open...vai/riv/dodaniDat	2013
http://linked.open...aciTvurceVysledku	Cigler, Jiří Váňa, Zdeněk Šebek, Michael Prívara, Samuel
http://linked.open.../riv/druhVysledku	D - Článek ve sborníku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	České vysoké učení technické v Praze / Fakulta elektrotechnická
http://linked.open...dnocenehoVysledku	156975
http://linked.open...ai/riv/idVysledku	RIV/68407700:21230/12:00198811
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	Predictive control; PMV index; Thermal comfort; Nonlinear programming (en)
http://linked.open.../riv/klicoveSlovo	Thermal comfort Predictive control Nonlinear programming PMV index
http://linked.open...ontrolniKodProRIV	[39C6FCEB437E]
http://linked.open...v/mistoKonaniAkce	Wailea, Maui, Hawaii
http://linked.open...i/riv/mistoVydani	Piscataway
http://linked.open...i/riv/nazevZdroje	Proceedings of the 51st IEEE Conference on Decision and Control
http://linked.open...in/vavai/riv/obor	BC
http://linked.open...ichTvurcuVysledku	4 (xsd:int)
http://linked.open...cetTvurcuVysledku	5 (xsd:int)
http://linked.open...vavai/riv/projekt	*Control systems for energy consumption optimization in low-energy and passive houses Identification of Stochastic, Nonlinear Systems for Advanced Control Advanced methods for complex systems analysis and control.
http://linked.open...UplatneniVysledku	2012
http://linked.open...iv/tvurceVysledku	Cigler, Jiří Prívara, Samuel Váňa, Zdeněk Šebek, Michael Komárková, D.
http://linked.open...vavai/riv/typAkce	WRD - Světová
http://linked.open.../riv/zahajeniAkce	2012-12-10 (xsd:date)
number of pages	6 (xsd:int)
http://purl.org/ne...btex#hasPublisher	IEEE
https://schema.org/isbn	978-1-4673-2064-1
http://localhost/t...ganizacniJednotka	21230
is http://linked.open...avai/riv/vysledek of	Optimization of Predicted Mean Vote Thermal Comfort Index within Model Predictive Control Framework

Faceted Search & Find service v1.16.118 as of Jun 21 2024

Alternative Linked Data Documents: ODE Content Formats:

RDF

ODATA

Microdata

About

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, 58 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software