The building sector accounts for a third of the total energy use in Sweden, and district heating provides half of the heating needs. The peak demand loads within a district heating network occur both regularly and irregularly and impose a burden on the energy company to fulfill the demand, often by using more expensive and less environmentally friendly resources (e.g., fossil fuels) instead of the waste heat from industry or biofuels. Heat storage during hours of less demand and prior to colder periods can be used for load management and sustainable planning of energy supply, as well as reduction of total greenhouse gas emissions. Thus, heat supply to the building can be lowered temporarily during the peak power period to utilize the stored thermal energy within the building thermal inertia. The use of indoor temperature decay and the delivery of heating power to a multifamily building are studied here, and heating storage capacity and thermal inertia are calculated. During the performed decay test, the energy supply was estimated to be reduced by 61% for 5 h, which resulted in only a 0.3 °C temperature decay. Therefore, the suggested method can shave eventual peaks in supplied heat with minimal influence on the thermal comfort.

This paper focuses on multi-family buildings in a Swedish city district, erected between 1965 and 1973, which are now in need of renovation. For the two types of multi-family buildings in the district, tower buildings and low-rise buildings, dynamic energy use is predicted by using an energy signature method. The energy signature is then used to calculate the primary energy use number of the building stock, according to calculations methods dictated by Swedish building regulations. These regulations are also used to assess which multi-family buildings are in need of renovation, based on the buildings’ primary energy use. For buildings that need energy renovations, it is simulated so that the energy use of each multi-family building complies with these same building regulations. The proposed methodology for simulating energy renovation also determines new energy signature parameters, related to building heat loss coefficient, balance temperature and domestic hot water usage. The effects of simulated renovation are displayed in a duration diagram, revealing how a large-scale renovation affects the district’s heat load in different annual periods, which affects the local district heating system. Sensitivity analysis is also performed before and after simulated energy renovation.