RT Conference Proceedings
T1 Energy consumption prediction from usage data for decision support on investments: 												The EnPROVE approach
A1 Neves-Silva, Rui
A1 Ruzzelli, Antonio
A1 Fuhrmann, Peter
A1 Bourdeau, Marc
A1 Pérez, Juan
A1 Michaelis, Eberhard
AB When 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.
PB IFAC Secretariat
SN 9783902661685
SN 1474-6670
YR 2010
FD 2010
LK https://hdl.handle.net/11556/1753
UL https://hdl.handle.net/11556/1753
LA eng
NO Neves-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
NO Authors 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.
DS TECNALIA Publications
RD 2 sept 2024