This paper proposes an integrated simulation framework for both building design and energy performance analysis. Literature review shows that, although many studies exist, most of them did not fully consider the integrated techno-economic evaluation of building-integrated photovoltaic (BIPV) system. Therefore, this research aims to use the interoperability potential offered by applying a building information modelling BIM-friendly software to an integrated simulation tool to conduct a comprehensive techno-economic evaluation of a BIPV system in a building cluster. Through visual integration in a digital mock-up, the solar irradiation, surrounding shadings, BIPV location, BIPV components/system (string, inverter, battery), and economic analysis have been performed on a residential building cluster located in Ludvika, Sweden. The results show the optimal location for the 615 m² BIPV system with a yielding of 27,394 kWh/year. Under the defined boundary conditions, the payback period is 10 years in the mixed feed-in and self-consumption mode, over its 20 years’ life span. Further sensitivity analysis of 18 cases is carried out in order to evaluate the impact of installation position (capacity), future climate change, shadings, and operating mode. This study will help improve decision-making by analysing the impact of the aforementioned factors on a BIPV system techno-economic performance.

Urban energy mapping plays a crucial role in benchmarking the energy performance of buildings for many stakeholders. This study examined a set of buildings in the city of Borlänge, Sweden, owned by the municipality. The aim was to present a digital spatial map of both electricity use and district heating demand in the spatial–temporal dimension. A toolkit for top-down data processing and analysis was considered based on the energy performance database of municipality-owned buildings. The data were initially cleaned, transformed and geocoded using custom scripts and an application program interface (API) for OpenStreetMap and Google Maps. The dataset consisted of 228 and 105 geocoded addresses for, respectively, electricity and district heating monthly consumption for the year 2018. A number of extra parameters were manually incorporated to this data, i.e., the total floor area, the building year of construction and occupancy ratio. The electricity use and heating demand in the building samples were about 24.47 kWh/m² and 268.78 kWh/m², respectively, for which great potential for saving heating energy was observed. Compared to the electricity use, the district heating showed a more homogenous pattern following the changes of the seasons. The digital mapping revealed a spatial representation of identifiable hotspots for electricity uses in high-occupancy/density areas and for district heating needs in districts with buildings mostly constructed before 1980. These results provide a comprehensive means of understanding the existing energy distributions for stakeholders and energy advisors. They also facilitate strategy geared towards future energy planning in the city, such as energy benchmarking policies.