Energy consumption prediction from usage data for decision support on investments: The EnPROVE approach

Simple item page
dc.contributor.authorNeves-Silva, Rui
dc.contributor.authorRuzzelli, Antonio
dc.contributor.authorFuhrmann, Peter
dc.contributor.authorBourdeau, Marc
dc.contributor.authorPérez, Juan
dc.contributor.authorMichaelis, Eberhard
dc.contributor.institutionSG
dc.date.accessioned2024-07-24T11:48:18Z
dc.date.available2024-07-24T11:48:18Z
dc.date.issued2010
dc.description.abstractWhen intending to renovate an existing building, with energy efficiency and greenhouse gas emissions in mind, a building owner is always questioning himself if the available investment resources are being directed to an effective return and if there are ways to improve this return? This paper presents the innovative approach from EnPROVE project that responds the previous question in a positive way. The approach is based on predicting the energy consumption of a specific building, with different scenarios implementing energy-efficient technologies and control solutions, based on actual measured performance and usage data of the building itself. The key hypothesis of EnPROVE is that it is possible, from adequate gathering and assessing data on how a structure performs and is being used by its occupants from an energy viewpoint, to build highly accurate and specific energy consumption models relevant for prediction of alternative scenarios. The EnPROVE software tools assess the energyefficiency impact of alternative technologies for which available investment resources can be directed and, thus, support the decision maker finding the optimized set of energy-efficient solutions to be implemented. These results are tailored to the actual building itself, through automated measurements of building usage and energy consumption.en
dc.description.sponsorshipAuthors express their acknowledgement to the consortium of the project EnPROVE, Energy consumption prediction with building usage measurements for software-based decision support. The EnPROVE project is supported by funding under the Seventh Research Framework Program of the European Union, with the grant agreement FP7-2009-ICT-248061.
dc.description.statusPeer reviewed
dc.format.extent5
dc.identifier.citationNeves-Silva , R , Ruzzelli , A , Fuhrmann , P , Bourdeau , M , Pérez , J & Michaelis , E 2010 , Energy consumption prediction from usage data for decision support on investments : The EnPROVE approach . in IFAC Conference on Control Methodologies and Technology for Energy Efficiency, CMTEE'2010 - Proceedings . PART 1 edn , IFAC Proceedings Volumes (IFAC-PapersOnline) , no. PART 1 , vol. 1 , IFAC Secretariat , pp. 48-52 . https://doi.org/10.3182/20100329-3-pt-3006.00011
dc.identifier.doi10.3182/20100329-3-pt-3006.00011
dc.identifier.isbn9783902661685
dc.identifier.issn1474-6670
dc.identifier.urihttps://hdl.handle.net/11556/1753
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=80051992425&partnerID=8YFLogxK
dc.language.isoeng
dc.publisherIFAC Secretariat
dc.relation.ispartofIFAC Conference on Control Methodologies and Technology for Energy Efficiency, CMTEE'2010 - Proceedings
dc.relation.ispartofseriesIFAC Proceedings Volumes (IFAC-PapersOnline)
dc.relation.projectIDSeventh Research Framework Program
dc.relation.projectIDEuropean Commission, EC, FP7-2009-ICT-248061
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.subject.keywordsDecision-support systems
dc.subject.keywordsEnergy consumption models
dc.subject.keywordsEnergy efficiency
dc.subject.keywordsEnergy prediction
dc.subject.keywordsControl and Systems Engineering
dc.subject.keywordsSDG 7 - Affordable and Clean Energy
dc.subject.keywordsSDG 12 - Responsible Consumption and Production
dc.subject.keywordsSDG 13 - Climate Action
dc.titleEnergy consumption prediction from usage data for decision support on investments: The EnPROVE approachen
dc.typeconference output
Files