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In this study, we explored the effects of different design strategies on final and primary energy use for production and operation of a newly constructed apartment building. We analysed alternatives of the building “As built” as well as to energy efficiency levels of the Swedish building code and passive house criteria. Our approach is based on achieving improved versions of the building alternatives from combination of design strategies giving the lowest space heating and cooling demand and primary energy use, respectively. We found that the combination of design strategies resulting in the improved building alternatives varies depending on the approach. The improved building alternatives gave up to 19–34% reduction in operation primary energy use compared to the initial alternatives. The share of production primary energy use of the improved building alternatives was 39–54% of the total primary energy use for production, space heating, space cooling and ventilation over 50-year lifespan, compared to 31–42% for the initial alternatives. This study emphasises the importance of incorporating appropriate design strategies to reduce primary energy use for building operation and suggests that combining such strategies with careful choice of building frame materials could result in significant primary energy savings in the built environment.

This paper presents a method, implemented as a freely available computer programme, which is used to estimate the economics of renewable microgeneration of electricity from wind and solar energy sources. A variety of commercial small wind turbines and photovoltaic (PV) panels are considered and combined with raw energy data gathered from a variety of locations. Both residential and holiday home user profiles are available and options are selectable concerning feed-in tariffs (if available), government incentive schemes and the cost of capital borrowing. The configuration of the generation setup, which can consist of wind, PV and combination of wind/PV, is fully selectable by the user, with a range of appropriate default data provided. A numerical example, based on Irish data, is presented, which suggests that payback periods for solar and wind microgeneration systems can vary greatly (2.5–500 years), depending on the location, installation and economic variables.