Dynamic Prediction of the Heat Demand for Buildings in District Heating Systems
2013 (English)In: Proceedings of the 5th International Conference on Applied Energy, 2013Conference paper (Refereed)
Heat demand is a key parameter for optimizing district heating (DH) systems. A mathematical model employing the Gaussian mixture model (GMM) was developed in order to predict the heat demand in DH systems on the consumer side. Prediction of heat demands needs to consider outdoor temperature and people’s social behaviors. In order to precisely consider the effects of social behaviors, the buildings in DH systems were classified into three types: commercial buildings, office buildings and apartment buildings. The model was trained and validated based on the water flow rate and the temperatures of supply and return water in the DH system. The results showed that the model can predict the heat demand in DH systems with an uncertainty between 4-9%. According to the heat demand predicted by the developed model, the potentials of energy saving in the DH system were analyzed.
Place, publisher, year, edition, pages
Electrical Engineering, Electronic Engineering, Information Engineering Environmental Engineering Civil Engineering
IdentifiersURN: urn:nbn:se:kth:diva-122143OAI: oai:DiVA.org:kth-122143DiVA: diva2:620979
5th International Conference on Applied Energy (ICAE); Pretoria, South Africa, 1–4 July 2013
QC 201308282013-05-132013-05-132013-08-28Bibliographically approved