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The 100 largest Swedish district heating (DH)-networks were studied on how DH conservation measures impacts CO2-emission rates taking both direct and indirect (i.e. displaced electricity) emissions into account, applying six different methods for the indirect emissions assessment. When the marginal electricity approach is applied on low CO2-emitting DH-networks with a high share of cogenerated electricity, it resulted in assessments that imply that DH conservation leads to higher CO2 emissions. This was not the case with the efficiency method.

When housing companies plan for energy conserving renovations, costs and amount of saved energy are usually estimated with yearly mean values. Yet the fuel mix varies widely depending on heat demand of district heating system, often with higher cost and CO2 emission rates during winter than summer.

Instead of comparing different energy conserving measures’ potentials with yearly mean values, it would be beneficial to examine them in a higher resolution, e.g. on daily or monthly basis, to identify real effectiveness of different measures in reducing CO2-emissions and primary energy consumption.

In this study, three energy conserving measures are put into a building simulation model to obtain results of hourly energy consumption reduction, which is then fitted into a district heating optimization model to analyze the impact on district heating system.

This study also discuss the correlation between energy cost for the customer and different measures’ environmental impact under new circumstances: seasonal energy price models of district heating, a price model which introduce price fluctuation throughout a year. This new factor provides a more comprehensive incitement to the property owners to encourage them to make environmental friendly decisions when planning for energy conserving renovations.

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.