Trend analysis to automatically identify heat program changes
2016 (English)Conference paper (Refereed)
The aim of this study is to improve the monitoring and controlling of heating systems located at customer buildings through the use of a decision support system. To achieve this, the proposed system applies a two-step classifier to detect manual changes of the temperature of the heating system. We apply data from the Swedish company NODA, active in energy optimization and services for energy efficiency, to train and test the suggested system. The decision support system is evaluated through an experiment and the results are validated by experts at NODA. The results show that the decision support system can detect changes within three days after their occurrence and only by considering daily average measurements.
Place, publisher, year, edition, pages
Seoul: Korea District Heating & Cooling Association , 2016.
District heating, Trend analysis, Change detection, Smart automated system
IdentifiersURN: urn:nbn:se:bth-12894OAI: oai:DiVA.org:bth-12894DiVA: diva2:974391
15th International Symposium on District Heating and Cooling (DHC2016), Seoul, Korea, September 4-7
FunderKnowledge Foundation, 20140032