Heat demand profiles of energy conservation measures in buildings and their impact on a district heating system
2016 (English)In: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 161, 290-299 p.Article in journal (Refereed) Published
This study highlights the forthcoming problem with diminishing environmental benefits from heat demand reducing energy conservation measures (ECM) of buildings within district heating systems (DHS), as the supply side is becoming "greener" and more primary energy efficient. In this study heat demand profiles and annual electricity-to-heat factors of ECMs in buildings are computed and their impact on system efficiency and greenhouse gas emissions of a Swedish biomass fuelled and combined heat and power utilising DHS are assessed. A weather normalising method for the DHS heat load is developed, combining segmented multivariable linear regressions with typical meteorological year weather data to enable the DHS model and the buildings model to work under the same weather conditions. Improving the buildings' envelope insulation level and thereby levelling out the DHS heat load curve reduces greenhouse gas emissions and improves primary energy efficiency. Reducing household electricity use proves to be highly beneficial, partly because it increases heat demand, allowing for more cogeneration of electricity. However the other ECMs considered may cause increased greenhouse gas emissions, mainly because of their adverse impact on the cogeneration of electricity. If biomass fuels are considered as residuals, and thus assigned low primary energy factors, primary energy efficiency decreases when implementing ECMs that lower heat demand.
Place, publisher, year, edition, pages
2016. Vol. 161, 290-299 p.
Building energy simulation, District heating, Energy conservation, Energy system assessment, Typical meteorological year, Weather normalisation, Buildings, Gas emissions, Greenhouse gases, Heating, Heating equipment, Historic preservation, Meteorology, Thermal load, Building energy simulations, Combined heat and power, Energy conservation measures, Energy systems, Multi-variable linear regression, Normalisation, Primary energy efficiencies, Energy efficiency
IdentifiersURN: urn:nbn:se:mdh:diva-29430DOI: 10.1016/j.apenergy.2015.10.024ISI: 000366063100023ScopusID: 2-s2.0-84945219207OAI: oai:DiVA.org:mdh-29430DiVA: diva2:867801