Buildings play a significant role in global carbon emissions, and offer substantial potential for energy savings and emission reduction. This research delves into the Emission Factor Discrepancy (EFD)—the variance in CO2 emission reduction projections obtained by employing either annual or hourly average Emission Factor (EF) for electricity generation. Through two detailed case studies in the Netherlands and incorporating emission data from the Netherlands, Sweden, and France, the study uncovers the potential magnitude and country-specific variability of the EFD. By demonstrating how the energy mix of a country influences the EFD, the research offers valuable insights into the accuracy of emission calculations for different circumstances, particularly in the context of transitioning to renewable energy sources. We have found that countries with energy sources having low load-following capability and low EFs exhibit a large EFD. Whereas, countries with high EFs and large deployment of Photovoltaics (PV) show a notably large EFD on emission reduction related to PV production. This highlights the importance of carefully selecting EFs when evaluating building retrofits in the context of smart city initiatives. This research highlights the need for establishing a uniform framework for calculating carbon emissions associated with retrofitting in buildings in conjunction with the granularity of data and the specific energy mix of a country. 

The aim of this work has been to study everyday energy-related behaviour in homes. All residents in 57 Swedish homes, living in three housing areas, have recorded time diaries over a period of four days, during the same time period in each area. The technical differences between the houses are limited, as the building designs within each housing area are the same. On an aggregated level, the diary data has been analysed with and without typical power data of appliances as well as in relation to measured total energy use, indoor temperature and water usage. Cluster analyses have been performed in order to find characteristics of groups of residents with regard to their energy-related behaviour. Some of the findings were that residents report long time use/operating time for activities related to electronic equipment (45% of total reported time). Residents which used energy to a greater extent than others were characterised by performing activities with long operating times, in combination with high, and fairly high, typical power ratings. The majority of residents showed many different energy-related behaviours, which indicates that a number of strategies to influence the behaviours - not just one - will be required.

Objective For the evaluation of the energetic performance of combined renewable heating systems that supply space heat and domestic hot water for single family houses, dynamic behaviour, component interactions, and control of the system play a crucial role and should be included in test methods. Methods New dynamic whole system test methods were developed based on "hardware in the loop" concepts. Three similar approaches are described and their differences are discussed. The methods were applied for testing solar thermal systems in combination with fossil fuel boilers (heating oil and natural gas), biomass boilers, and/or heat pumps. Results All three methods were able to show the performance of combined heating systems under transient operating conditions. The methods often detected unexpected behaviour of the tested system that cannot be detected based on steady state performance tests that are usually applied to single components. Conclusion Further work will be needed to harmonize the different test methods in order to reach comparable results between the different laboratories. Practice implications A harmonized approach for whole system tests may lead to new test standards and improve the accuracy of performance prediction as well as reduce the need for field tests.

A large part of the energy consumption in the European Union member states is related to space heating, a significant share of which is due to transmission losses through the building envelope. Vacuum insulation panels (VIPs), with unique thermal insulation properties, do therefore provide an interesting alternative for the building industry. This paper presents the results of a life cycle analysis (LCA) study that compares the environmental impact of three hypothetical buildings, a standard residential building, a regular well-insulated building and a building insulated with VIPs. The environmental impact includes the global warming potential (GWP) and the primary energy (PE) use, from the material production stage to the building operational phase (50 years). The cradle-to-gate environmental impact categories of ozone depletion potential (ODP), acidification potential (AP) and eutrophication potential (EP) of all building components are also assessed. The study shows a comparatively lower operational energy for the VIP insulated building and a relatively lower total greenhouse gas emission as well as the possibility to save significant living space. The results also show that the VIPs have measurable environmental impact during the product stage while the core material of the VIPs has considerable impact on the results.

Abstract The EU directive to create Energy Performance Certificates (EPC) for all buildings was implemented in Sweden as a tool to advise building owners on possible improvements and to give energy efficiency visible market value. The Swedish EPCs include measured energy usage. Currently 82% of the buildings have EPCs; this database makes it possible to create overview and to validate models of the building stock in an unprecedented high detail. However, the process of issuing Swedish EPCs has received criticism from real estate agents, real estate owners, Energy Experts, and Boverket, the national agency responsible for EPC data collection. In order to use the EPC data for describing the building stock it is necessary to assess and remediate the data quality. This has been done by merging the EPC data with databases of the Housing and Urban Development office and one of the larger real estate companies in Sweden, Riksbyggen. The Swedish EPC specific area measurement, Atemp, is found to vary according to methods of derivation. The method of estimating Atemp is improved using a stepwise regression model (R2 = 0.979). This method can be applied to subsets of EPCs depending on the intended way of describing the building stock. 

The European building stock was renewed at a rapid pace during the period 1950-1975. In many European countries the building stock from this time needs to be renovated. There is an opportunity to introduce energy efficiency measures in the renovation process, but in this process social aspects should also be taken into account. The purpose of this article is to provide an estimate of the economic and societal challenge of renovating and energy retrofitting the aging building stock. Building specific data on energy usage and previous renovation investments made in the multi-family dwellings in Gothenburg (N = 5 098) is aligned with data on tenure type and average income. Based on conducted energy retrofitting projects, costs are estimated for renovating and energy retrofitting multi-family dwellings that will reach the service life of 50 years before 2026. It is found that the pace of renovation needs to increase and that there is risk of increasing societal inequity due to rent increases in renovated buildings. © 2016 The Authors.

An important aspect of demand response (DR) is to make accurate predictions for the consumption in the short term, in order to have a benchmark load profile which can be compared with the load profile influenced by DR signals. In this paper, a data analysis approach to predict electricity consumption on load level in office buildings on a day-ahead basis is presented. The methodology is: (i) exploratory data analysis, (ii) produce linear models between the predictors (weather and occupancies) and the outcomes (appliance, ventilation, and cooling loads) in a step wise function, and (iii) use the models from (ii) to predict the consumption levels with day-ahead prognosis data on the predictors. The data has been collected from a Swedish office building floor. The results from (ii) show that occupancy is correlated with appliance load, and outdoor temperature and a temporal variable defining work hours are connected with ventilation and cooling load. It is concluded from the results in (iii) that the error rate decreases if fewer predictors are included in the predictions. This is because of the inherent forecast errors in the day-ahead prognosis data. The achieved error rates are comparable with similar prediction studies in related work

Green roofs are complex systems, with a vegetation layer covering the outermost surface of the building shell. An effective design may confer environmental and energy benefits. Most field studies evaluating green roof performance have been conducted in warmer climates with few studies of full-scale green roofs in cold regions. No study has so far evaluated the energy performance of a green roof in a sub-arctic climate. This study demonstrates the heat flow and thermal effect of an extensive green roof versus a black bare roof area on a highly insulated building in the sub-arctic town of Kiruna, Sweden, for the period from November 2016 to February 2018. Measured temperature and heat flux values were consistently higher and more variable for the black roof than the green roof, except during the snow-covered winter months when the responses were similar. The cumulative heat flux showed that the net heat loss was greater through the black than the green roof, but the values remained low. Overall, the study confirms that the energy benefit of a green roof on a highly insulated building in a subarctic climate is low.

Several building-stock modelling techniques have been employed to investigate the impact of energy efficiency measures (EEM), where the description of the building-stock generally consists of an age-type classification to specify building characteristics for groups of buildings. Such descriptions lack the appropriate level of detail to differentiate the potential for EEM within age groups. This paper proposes a methodology for building-stock description using building-specific data and measured energy use to augment an age-type building-stock classification. By integrating building characteristics from energy performance certificates, measured energy use and envelope areas from a 2.5D GIS model, the building-stock description reflects the heterogeneity of the building-stock. The proposed method is validated using a local building portfolio (N = 433) in the city of Gothenburg, where modelled results for space heating and domestic hot water are compared to data from measurements, both on an individual building level and for the entire portfolio. Calculated energy use based on the building-stock description of the portfolio differ less than 3% from measured values, with 42% of the individual buildings being within a 20% margin of measured energy use indicating further work is needed to reduce or quantify the uncertainty on a building level.