Journal
ENERGY
Volume 34, Issue 10, Pages 1447-1453Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2009.05.035
Keywords
District heating systems; Simulation model; Artificial neural networks models; Prediction; Energy savings
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Funding
- Ministry of Education and Research from Romania
- Research of Excellence Program
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This study develops and analyzes an original methodology for the simulation and prediction of space heating energy consumption in buildings connected to a district heating system, characterized by lack of individual control systems for end-users. The identification of the input parameters is based on both classical engineering equations and statistical analysis of collected data. Two main factors play important roles in the model: (i) climate and (ii) human behavior. Model validation was undertaken through the analysis of field data collected during the winter, via a monitoring system working in a partially-controlled district heating system. The comparison between the results obtained with the proposed model versus classical methods points out the possibility to implement, using the proposed methodology, management policies for a district that offer significant cost-effective energy savings opportunities. (C) 2009 Elsevier Ltd. All rights reserved.
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