Michiel van Noord

Building-integrated photovoltaics (BIPV) is expected to play a relevant role in decarbonising our cities, both in new buildings and retrofit projects, making them more sustainable, resilient and pleasant. However, BIPV remains a niche market. To understand the reasons and help boost its development, this paper provides insights into BIPV through a holistic and systematic analysis that considers BIPV’s dual nature as both photovoltaic and building product. The methodology is based on the analyses of several BIPV technological innovation systems (TISs) developed in six countries, as well as extensive comparative assessments and investigations to identify key global features of BIPV. Social aspects, market status and forecast, perspectives from the photovoltaic and building sectors, and related regulations and standardisation are key aspects analysed to develop recommendations for policymakers. Outcome examples are low to moderate acceptance of BIPV among building owners, who give cost reasons for choosing building-added photovoltaics (BAPV) over BIPV, as well as a need for information, official guidance, skilled personnel, improved cross-sector collaboration, availability of BIPV products, proper digital tools and specific regulation to improve BIPV’s legitimacy in the construction sector. Essential is developing policies that encourage the adoption of BIPV, including standardisation, promotion and financing.

Snow-induced photovoltaic (PV)-energy losses (snow losses) in snowy and cold locations vary up to 100% monthly and 34% annually, according to literature. Levels that illustrate the need for snow loss estimation using validated models. However, to our knowledge, all these models build on limited numbers of sites and winter seasons, and with limited climate diversity. To overcome this limitation in underlying statistics, we investigate the estimation of snow losses using a PV system’s yield data together with freely available gridded weather datasets. To develop and illustrate this approach, 263 sites in northern Sweden are studied over multiple winters. Firstly, snow-free production is approximated by identifying snow-free days and using corresponding data to infer tilt and azimuth angles and a snow-free performance model incorporating shading effects, etc. This performance model approximates snow-free monthly yields with an average hourly standard deviation of 6.9%, indicating decent agreement. Secondly, snow losses are calculated as the difference between measured and modeled yield, showing annual snow losses up to 20% and means of 1.5–6.2% for winters with data for at least 89 sites. Thirdly, two existing snow loss estimation models are compared to our calculated snow losses, with the best match showing a correlation of 0.73 and less than 1% bias for annual snow losses. Based on these results, we argue that our approach enables studying snow losses for high numbers of PV systems and winter seasons using existing datasets.