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Abstract Building-integrated photovoltaic (BIPV) panels are emerging as a useful technology for helping to achieve net-zero energy buildings. At this time, the main drawback with BIPV systems is the cost per kilowatt per hour of electricity generated. Besides cheaper production of photovoltaic panels, increases in their efficiency can be obtained by reducing panel temperatures. This is often achieved by adding a cavity beneath the panels to allow ventilation of the rear of the panel. However, the details of airflow in the cavity and the effect on cooling have not been rigorously researched. Life-time enhancement against degradation is also an effective technique to reduce the cost of electricity generated. Moisture ingress and thermal stresses are among the primary reasons for degradation of BIPVs; these processes are directly affected by air and moisture flow around the panels. The surface temperature thermography and airflow observations performed in this work helps to understand the transport mechanisms above and below the panels. For this purpose, a novel setup was developed consisting of a building model with a mock BIPV panel plus a solar simulator placed inside an atmospheric wind tunnel. Particle image velocimetry (PIV) and infra-red thermography were performed to simultaneously monitor the surface temperature and airflow above and below the panel. The study clearly shows how the accelerated airflow within the cavity increases the heat exchange between the PV and airflow and consequently reduces the PV temperature. It is also shown that the stepped open arrangement of panels is more effective in reducing the temperature comparing to a flat arrangement. This arrangement also has a better resistant against the air and moisture ingress.

Abstract We present a simple method for measuring Henry’s constant k H of ethanol using photoacoustic spectroscopy. At T = 298.1 K the measured value for k H is (0.877 ± 0.039)kPa · kg · mol − 1 . Our data show that Henry’s law is valid at ethanol molalities between 0.1 mol · kg − 1 and 1.4 mol · kg − 1 . The temperature dependence of Henry’s constant was carefully examined by measuring the ethanol vapour pressure of six different aqueous solutions between T = 273.1 K and T = 298.1 K. By analysing the gas phase concentration and applying Henry’s law, an ethanol molality of 0.864 mol · kg − 1 in the liquid phase can be measured with an error of ± 0.038mol · kg − 1 . The detection limit of the photoacoustic sensor is a gaseous ethanol pressure of 10 − 3 kPa. Ethanol molality changes as low as 1.10 − 3 mol · kg − 1 can be measured.

The International Building Physics Toolbox (IBPT) is a software library developed originally for heat, air and moisture system analysis in building physics. The toolbox is constructed as a modular structure of standard building elements, using the graphical programming language Simulink. To enable development of the toolbox, a common modelling platform is defined: a set of unique communication signals, material database and documentation protocol. The IBPT is an open source and available on the Internet. Any user can utilize, expand and develop the contents of the toolbox. This paper presents structure and essence of the library. Potential applications of the toolbox are illustrated through examples.

Abstract According to its ‘Energy Strategy 2050’ (case ‘new energy policy’) Switzerland aims to reduce its industrial electricity demand by 25% and 35% in 2035 and 2050 respectively compared to 2010. Electric motor driven systems in Swiss industry, which currently account for approximately 69% of the sector’s total electricity demand, are expected to contribute significantly to this strategy. This study assesses the potential of electricity savings for electric motor driven systems in industry and its associated specific costs and presents the results in the form of energy efficiency cost curves. For the short term, the economic potential for electricity savings in Swiss industrial electric motor systems is estimated at approximately 17%. The importance of accounting for additionality by using energy-relevant investment instead of total investment for the cost-benefit analysis in order to avoid underestimation of the economic electricity savings potential is demonstrated. The results of this analysis can serve as basis for formulating more effective policies and may also be applicable to other countries with similarly ambitious targets.

An augmented measurement uncertainty approach for CO2 emissions from coal-fired power plants with a focus on the often forgotten contributions from sampling errors occurring over the entire fuel-to-emission pathway is presented. Current methods for CO2 emission determination are evaluated in detail, from which a general matrix scheme is developed that includes all factors and stages needed for total CO2 determination, which is applied to the monitoring plan of a representative medium-sized coal-fired power plant. In particular sampling involved significant potential errors, as identified and assessed by the Theory of Sampling (TOS), which also shows how these can be eliminated and/or minimised. Since coal-related CO2 emission calculations not only require analytical results of the carbon content of coal itself but also of the by-products fly ash and bottom ash, sampling procedures of these three materials were also given full attention. A systematic error (bias) is present in the current sampling approach, which increases the present uncertainty estimate unnecessarily. For both primary sampling and analytical sample extraction steps, random variations, which hitherto only have been considered to a minor extent, have now also been fully quantified and included in the overall uncertainty. Elimination of all identified sampling errors lead to modified CO2 determination procedures, which indicate that the actual CO2 emission is approximately 20,000 t higher than the present estimate. Based on extensive empirical sampling experiments, a fully comprehensive uncertainty estimate procedure has been devised. Even though uncertainties increased (indeed one particular factor is substantially higher, the so-called “emission factor”), the revised CO2 emission budget for the case plant complies with the official pre-determined uncertainty levels maxima in the EU guidelines.

Abstract Reducing space heating demand from the residential building stock has been established as a crucial element of the energy transition across Europe. Focusing on Switzerland, this paper presents a bottom-up model (SwissRes) which allows to analyse the demand for space heating by building element and by building archetype (54 archetypes in total). The model is based on detailed data on the building envelope and heating systems of over 25,000 Cantonal Building Energy Performance Certificates (CECB PLUS). We identify three building characteristics which result in above-average final energy demand: rural typology (18% higher than urban), single-family houses (41% higher than multi-family) and in particular age of buildings (525% higher from newest to oldest). In combination, these three factors can lead to up to seven times higher demand per m2 and year in extreme cases compared to the most efficient archetype. Among buildings constructed before 1970, single-family houses (SFH) show very high specific final energy demand for space heating ranging between 170 and 200 kWh/m². On the national level, SFHs and multi-family houses (MFH) are featuring almost identical shares of total final energy demand. Buildings in suburban areas account for almost 50% of the total final energy demand. In total, the buildings constructed before 1980 account for 70% of the national final energy demand for space heating, with buildings constructed before 1920 contributing 22%. Most heat is lost through walls (40%) followed by windows (25%), roofs (17%) and the floor (18%). Losses from walls are particular high (73 kWh/m²) for buildings constructed between 1920 and 1945. Given the scalability of the model, it is readily applicable not only for the country as a whole but also for a province (canton), a city or a larger neighbourhood. The energy demand by archetype and building element identified with the SwissRes model can be used to assess the techno-economic potential of large-scale energy retrofit scenarios.