Energy Demand For Space Heating Research Articles

A Heat Loss Sensitivity Index to Inform Housing Retrofit Policy in the UK

A substantial number of dwellings in the UK have poor building fabric, leading to higher carbon emissions, fuel expenses, and the risk of cold homes. To tackle these challenges, domestic energy efficiency policies are being implemented. One effective approach is the use of energy models, which enable sensitivity analysis to provide valuable insights for policymakers. This study employed dynamic thermal simulation models for 32 housing archetypes representative of solid-walled homes in the UK to calculate the heat loss and the sensitivity coefficient per building fabric feature, after which a metric Heat Loss Sensitivity (HLS) index was established to guide the selection of retrofit features for each archetype. The building fabric features’ inputs were then adjusted to establish both lower and upper bounds, simulating low and high performance levels, to predict the how space heating energy demand varies. The analysis was extended by replicating the process with various scenarios considering climates, window-to-wall ratios, and overshadowing. The findings highlight the external wall as the primary consideration in retrofitting due to its high HLS index, even at high window-to-wall ratios. It was also established that dwelling type is important in retrofit decision-making, with floor and loft retrofits having a high HLS index in bungalows. Furthermore, the analysis underlines the necessity for Standard Assessment Procedure assessors to evaluate loft U-value and air permeability rates prior to implementing retrofit measures, given the significance of these factors in the lower and upper bounds analysis. Researchers globally can replicate the HLS index approach, facilitating the implementation of housing retrofit policies worldwide.

Review of Existing Tools for the Assessment of European Building Stock Energy Demand for Space Heating and Cooling

There is currently a growing interest in lowering energy demand and, consequently, greenhouse gas emissions in all sectors. Several attempts by national governments to reduce energy demand are centered on the residential sector, since it accounts for a significant amount of the final energy demand. In order to estimate its energy demand and to evaluate the techno-economic effects of adopting energy efficiency and renewable energy technologies, there are comprehensive models suited for residential applications, since energy demand characteristics of the residential sector are complicated and interrelated. Based on these models, several tools are nowadays available to support designers and policymakers. These tools are designed to be user-friendly and to include the possibility to develop simulated scenarios for energy demand, production of CO2 emissions, and economic costs. The present study aims to offer an up-to-date extended overview of the most functional and widespread tools for the assessment of the current energy demand of the European building stock for space heating and cooling demand, both regarding open source and commercial licenses. Results highlighted the tools most commonly used by examining real applications, identifying their strengths and weaknesses and pinpointing the primary deficiencies for the benefit of future developers.

Urban Building Energy Modeling to Support Climate-Sensitive Planning in the Suburban Areas of Santiago de Chile

Greenhouse gas emissions depend on natural and anthropic phenomena; however, to reduce emissions, we can only intervene in terms of anthropic causes. Human activity is very different in various countries and cities. This is mainly due to differences in the type of urban environment, climatic conditions, socioeconomic context, government stability, and other aspects. Urban building energy modeling (UBEM), with a GIS-based approach, allows the evaluation of all the specific characteristics of buildings, population, and urban context that can describe energy use and its spatial distribution within a city. In this paper, a UBEM is developed using the characteristics and consumption of eight typical buildings (archetypes) in the climate zone of Santiago de Chile. The archetype-based UBEM is then applied to the commune of Renca, a critical suburb of Santiago, with the use of QGIS to analyze the energy demand for space heating and the potential for energy saving after four retrofitting interventions. Knowing the costs of the retrofitting interventions and the energy price, the simple payback time was evaluated with the reduction in GHG emissions. Starting from the actual building stock, the results show that the most effective retrofitting intervention for the commune of Renca is the thermal insulation of walls and roofs; due to the type of dwellings, this particular intervention could be more convenient if associated with the installation of solar technologies. This methodology can be replicated with the data used by urban planners and public administrations available for many Chilean cities and in other countries.

“En-Solex”: A Novel Solar Exoskeleton for the Energy-efficiency Retrofitting of Existing Buildings

The energy retrofitting of the existing building stock is one of the current challenging strategic objectives on the way to the European target of climate neutrality by 2050. According to the Renovation Wave plan, around 35 million existing buildings need to be upgraded to the highest energy efficiency level by 2030, and innovative technological solutions are required to achieve this ambitious goal. This paper proposes a novel solar exoskeleton for the energy and architectural retrofitting of existing buildings, called En-Solex. The system, which consists of an external steel frame that wraps around buildings like a double skin, combines passive solar gain control (shading and greening) with high-efficiency active solar systems (PV panels) optimised for integration into existing building facades. The energy-saving potential of the system with different façade configurations is evaluated on a multi-family residential building located in a Mediterranean climate. The dynamic energy simulations show that the proposed solution can reduce the energy demand for space heating and cooling by 33.4% and 25.5% respectively. The En-Solex system integration combined with generator replacement results in a maximum heating and cooling reduction equal to 80.7% and 59.6% respectively. The surplus of electricity generated, thanks to the integration of RES, can lead to a net plus target, with the building exceeding its average annual electricity demand.

Impacts of energy saving measures on IEQ, task performance and COVID-19 contagion risk in public buildings: analysis of a case-study in Bozen-Bolzano, Italy

The recent 2022 energy crisis has pushed several Italian public administrations to adopt solutions to reduce energy demand for space heating in public buildings. Reduction of HVAC system operation time, decrease of heating setpoint and changes to ventilation schedules are some examples of typically implemented measures. However, some of them are in direct competition with those adopted so far to limit the risk of COVID-19 contagion, such as higher ventilation rates. Furthermore, limited operation time and lower setpoints can lead to suboptimal thermal comfort conditions for workers in public buildings, with subsequent decrease of their task performances. In this framework, to assess the global efficacy of the most recent energy saving policies in public buildings, this research focuses not only on the quantification of energy savings but also on the analysis of increased COVID-19 contagion risk, as well as performance loss due to suboptimal building operation conditions. To investigate the impact of new building operation policies for energy savings, an intermediate storey of a public office building in Bolzano, Italy, was selected as a case-study.

Thermal performance of residential and non-residential sectors: describing differences and understanding underlying reasons

This paper presents a comparative analysis of thermal performance and heating demand for selected residential (single-family houses, SFHs and multi-family houses, MFHs) and non-residential sectors (Offices and Schools). The thermal performance and space heating demand of the Swiss building stock were analysed by a bottom-up element-based archetypal model. SFHs are characterised by the best envelope thermal performance (average envelope U-value = 0.62 W/(m2K)), followed by MFH (0.73 W/(m2K)), Schools (0.75 W/(m2K)), and Offices (0.84 W/(m2K). Results show significant differences regarding architectural features between building sectors: SFHs are characterised by the highest envelope factor (median value = 2.00), defined as the ratio between external surfaces and heated area, followed by Schools (1.50), MFH (1.30), and Offices (1.25). As a consequence of the above-mentioned differences, SFHs show higher specific final energy demand for space heating (on average 148 kWh/(m2year)), followed by Schools (117 kWh/(m2year)), Offices (100 kWh/(m2year)), and MFH (93 kWh/(m2year)). Moreover, a high potential for decarbonisation of heating systems in the Swiss building stock was identified: more than 70% of the ERA is heated by fossil fuel-based heating systems, with some differences amongst the studied sectors. This analysis serves as an important starting point to examine possible retrofit pathways and policies across sectors.

Integrating Passive Energy Efficient Measures to the Building Envelope of a Multi-Apartment Building in Sweden: Analysis of Final Energy Savings and Cost Effectiveness

A major challenge in building energy renovation is to cost effectively achieve notable energy savings. This paper investigates cost-effective passive energy-efficiency measures for thermal envelope retrofit of a typical Swedish multi-apartment building from the 1970s. Here, the use of different types of insulation materials for the retrofits of roof, exterior walls, and ground floor are analyzed along with changing windows and doors with varying thermal transmittance values. The cost-effectiveness analysis is based on the net present value of the investment costs of the energy-efficiently measures and the achieved energy cost saving. Different economic scenarios and renovation cases are considered in techno-economic analyses to determine the cost-effective energy-efficiency retrofit measures. The results indicate that improved windows reduce energy demand for space heating by up to 23% and yield the highest final energy savings. However, additional mineral wool roof insulation is the most cost-effective measure under all economic scenarios. This measure gave the lowest ratio of cost effectiveness of about 0.1, which was obtained under the stable scenario. The final energy savings that can be achieved in a cost-effective manner vary between 28% and 61%, depending on the economic scenario and renovation case. This analysis emphasizes the influence of different renovation cases and economic parameters on the cost effectiveness of passive energy-efficiency measures.

At the roots of the energy performance gap: Analysis of monitored indoor air before and after building retrofits

The growing concern about climate change and energy security has fostered energy efficiency measures to reduce building consumption in many European countries. The policies and incentives behind these improvements typically rely on pre-calculated expected energy savings. However, evidence shows that the actual energy performance after such interventions often falls short of the expected targets. People's behavior is one of the causes of the energy performance gap between measured and predicted building energy performance. This study contributes to this discussion by analyzing data on air temperature, relative humidity, and Volatile Organic Compounds monitored in eleven apartments in Milan (Italy) before and after building renovation. These data were then used to simulate two representative flats, thus obtaining their energy demand for space heating. The analysis of the measured data shows that users adapt differently to building retrofits. Under the assumption of constant moisture generation during the periods monitored, some occupants appear to increase air change rates and reduce indoor air temperatures, while others show the opposite behaviour. These trends could be related to the fact that some users prioritize air quality over thermal comfort and vice versa. Energy simulations suggest that the former behaviour leads to a larger energy performance gap.

Heating energy demand estimation of the EU building stock: Combining building physics and artificial neural networks

The aim of this study is to present a novel data-driven approach developed for space heating energy demand calculation of the whole EU building stock. To develop a computationally efficient bottom-up model that takes into account building physics parameters and details of the building stock make-up, an artificial neural network (ANN) is trained on a dataset of precise building-physics models. For this purpose, 2025 building energy simulations were performed in this study, ensuring representativeness for the entire EU, in terms of building stock properties (3 building geometries and 27 combinations of building envelope properties) and climatic conditions (25 weather files). The developed model is the first comprehensive hybrid (ANN and building physics) approach based on a condensed selection of input features, yet covering a wide range of climatic and building stock values, hence suitable for consideration of the spatial, temporal and multinational scale of the EU building stock. A unique building stock model was developed for this study at the EU regional level. The performance of the ANNs was validated by assessing the RMSE and R2 against the training (85%), testing (15%) and total dataset (100%, i.e. 2025 data points), to ensure adequate robustness, accuracy and generalisation capacity. As to the application of the ANN model on the building stock of 27 EU countries, a good accordance between ANN model results and measured consumption over the nine years from 2011 to 2019, was obtained, with an average overestimation by 9.3% (standard deviation (SD) = 5%), which confirmed the adequacy of the adopted methodology. Additional consideration of the occupant behaviour resulted in average overestimating the actual measurements by only 2.4% (SD = 4.7%). In addition to the EU and country level, the added value of the implemented bottom-up approach is its ability to assess the heating energy demand at regional level. Overall, the presented approach can be considered accurate and reliable to be used in future research on the long-term impact of building renovation with respect to energy savings and reductions of greenhouse gas emissions.

Impact of Atrium Glazing with and without BIPV on Energy Performance of the Low-Rise Building: A Central European Case Study

This article aims to investigate the impact exerted by different types of covering an atrium with glazing on the energy performance of a kindergarten building, provided by the authors as a conceptual design. The considered types of atria included an open atrium, a glazed atrium, and an atrium that operated as a hybrid system. Additionally, the following aspects were taken into consideration: the effect of a glazing-integrated PV system (BIPV); the variety of thermal features represented by the inner boundary between the conditioned and the unconditioned space (Uiu); and the atrium space air-exchange ratio (nue) on the energy balance of the building. Energy performance indicators, including energy demands for space heating and cooling (Eu), delivered energy (Ed), and primary energy (Ep) indicators for heating and cooling mode were estimated for the moderate climates and two locations of the building model, i.e., for Warsaw (Central Poland) and Ahlbeck (Northern Germany). The research results prove that the glazed atrium exerts the most beneficial impact on the energy performance of the building. Nevertheless, certain variables must be considered, especially the air-exchange ratio of the atrium space, as they significantly influence the total annual energy performance. The results obtained with regard to the effect exerted by the presence of BIPV systems differ from those usually expected. This is due to the effect of the total solar-energy-transmittance value (g) modulation caused by the system and, finally, by a significant reduction in passive solar-gain harvesting, which is important for heating-mode results in examined climate conditions. Taking the present analysis into account, it can be concluded that the energy and environmental effects of the glazed integrated PV systems in temperate climates are strongly influenced by the environmental conditions, and, in some cases, these solutions may prove to be not efficient enough in terms of the energy and costs.

Genelleştirilmiş regresyon modelleri kullanılarak enerji talebi ve tüketimi için bir modelleme yaklaşımı

Energy management is an important process for maintaining available energy resources and meeting basic household energy needs. Many studies seek to optimize the household energy consumption patterns to manage the load demand and minimize energy costs. Adopting such optimizations in conflict-affected countries is more beneficial due to limited energy sources. This study identifies the optimal energy consumption model for households in northern Syria. The objective is to identify the most cost-efficient energy sources while considering the prices, average monthly household income, the main source of electricity, battery storage capacity, and energy demands for space heating, water heating and cooking. One hundred and thirty-six (136) standardized surveys of residential households are collected and used as a test case. Statistical analysis of the data was carried out using the R-Studio software, where Poisson regression and negative binomial regression were employed. Findings revealed that the Negative Binomial (NB) model used has high explanatory power. In addition, the energy sources used for space heating and water heating have a direct impact on monthly expenditures. The produced model showed that the most cost-effective energy sources are coal for space heating and natural gas and kerosene for water heating.

Exploring energy consumption for less energy-hungry building in UK using advanced aerogel window

A common strategy for employing net zero energy buildings (NZEBs) in the United Kingdom (UK) to achieve the national target for 2050 is improving the thermal insulation in glazing units to reduce the space heating load. This study examines the impact of aerogel technologies as an effective strategy for window retrofits under the UK climate. Eleven samples of granular and monolithic aerogel windows were selected across various literature to illustrate the optical properties and thermal characteristics of each glazing structure. In Falmouth, UK, a two-story residential building was selected for simulation to assess the thermal efficiency of various aerogel systems as alternatives for standard double-glazing systems. Results revealed that aerogel technology has high potential in increasing the total solar heat energy through windows by occupying high SHGCs up to 0.738 and low U-values down to 0.381 W/m2K. Monolithic aerogel has more energy-saving potential and can allow greater daylight penetration compared to granular aerogel with a visual transmittance of up to 69%. Increasing the WWR can help reduce the heating load of the building but can also cause the cooling loads to increase from internal overheating. The south-facing facade of the building where most of the windows were present experienced higher cooling loads, indicating that the addition of aerogel glazing causes overheating during summer periods. Applying aerogel for window insulation could increase the total window heat transfer by up to 33% and reduce heat demand by 15.5% compared to a standard double-glazing system. As a result, aerogel technology can prove to be a viable option for decreasing the building energy demand for space heating in the UK.

Social Acceptance of a Thermal Architectural Implementation Proposal

The social acceptance of introducing an improved and sustainable roofing material in multicultural communities in Mexico was addressed. A case history of a community “La Cañada” in Huixquilucan, State of Mexico (19°19′02.81″ N, 99°22′23.21″ W, 3025 m above mean sea level), a village very close to the eastern edge of Mexico City and representative of strong social and transcultural pressures similar to surrounding communities in Mexico City, is reported. The approach considered developing a double-layered roof to reduce the energy demand for space heating in this predominantly cold region, thus significantly contributing to indoor thermal comfort, reducing the need for cutting wood and helping to alleviate the accelerating impacts of deforestation in the area. Two parallel studies were used, whereby the then-current awareness levels of citizens and the factors impacting their commitment to energy sustainability were analysed using multicriteria social parameters, while the second study focused on the analysis of improved comfort when the proposed double roof was implemented, based on the feedback received from a pool of citizens who experienced living in the improved prototype dwellings. Results showed that while the level of awareness on energy efficiency was still low, the influence of media on their decisions and aspirations was strong and this could be constructively used to support the shift towards a more sustainable society and a “solar culture”. Moreover, the developed sustainable double-roof prototype has significantly improved indoor comfort and energy savings for heating, while demonstrating a fast and easy replicability potential in similar dwellings.

Composting Heat Recovery for Residential Consumption: An Assessment of Viability

The European heating sector is currently heavily dominated by fossil fuels. Composting is a naturally occurring process in which heat is liberated from the composting substrate at a higher rate than the process needs to support itself. This difference could be harnessed for low-heat applications such as residential consumption, alleviating some of the impacts fossil fuel emissions represent. In this study, the composting heat recovery reported in the literature was compared to the energy demand for space and water heating in four European countries. A review of potential heat production from the waste representative of the residential sector was performed. We found that the theoretically recoverable composting heat does not significantly reduce the need for district heating. However, it can significantly reduce the energy demand for water heating, being able to supply countries such as Greece with between 36% and 100% of the yearly hot water demand, or 12% to 53% of the yearly hot water of countries such as Switzerland, depending on the efficiency of heat recovery.

Who Produces the Peaks? Household Variation in Peak Energy Demand for Space Heating and Domestic Hot Water

Extensive research demonstrates the importance of user practices in understanding variations in residential heating demand. Whereas previous studies have investigated variations in aggregated data, e.g., yearly heating consumption, the recent deployment of smart heat meters enables the analysis of households’ energy use with a higher temporal resolution. Such analysis might provide knowledge crucial for managing peak demand in district heating systems with decentralized production units and increased shares of intermittent energy sources, such as wind and solar. This study exploits smart meter heating consumption data from a district heating network combined with socio-economic information for 803 Danish households. To perform this study, a multiple regression analysis was employed to understand the correlations between heat consumption and socio-economical characteristics. Furthermore, this study analyzed the various households’ daily profiles to quantify the differences between the groups. During an average day, the higher-income households consume more energy, especially during the evening peak (17:00–20:00). Blue-collar and unemployed households use less during the morning peak (5:00–9:00). Despite minor differences, household groups have similar temporal patterns that follow institutional rhythms, like working hours. We therefore suggest that attempts to control the timing of heating demand do not rely on individual households’ ability to time-shift energy practices, but instead address the embeddedness in stable socio-temporal structures.

A methodology to estimate space heating and domestic hot water energy demand profile in residential buildings from low-resolution heat meter data

This article presents a new methodology to disaggregate the energy demand for space heating (SH) and domestic hot water (DHW) production from single hourly smart heat meters installed in Denmark. The new approach is idealized to be easily applied to several building typologies without the necessity of in-depth knowledge regarding the dwellings and their occupants. This paper introduces, tests, and compares several algorithms to separate and estimate the SH and DHW demand. To validate the presented methodology, a dataset of 28 Danish apartments with detailed energy monitoring (separated SH and DHW usage) is used. The comparison shows that the best method to identify energy demand data points corresponding to DHW production events is the so-called “maximum peaks” approach. Furthermore, the best algorithm to estimate the SH and DHW separately is a combination of two methods: the Kalman filter and the Support Vector Regression (SVR). This new methodology outperforms the current Danish compliances typically used to estimate the annual DHW usage in residential buildings.

Optimizing the Passive House Planning Package simulation tool: A bottom-up dynamic approach to reduce building performance gap

The Passive House Planning Package (PHPP) simulation tool is the only authorized software in Australia for the Passivhaus (PH) certification. Despite its key role in this certification scheme, previous studies have reported significant gaps between the simulated and actual performance. To address this limitation, this study introduces a bottom-up approach to building performance simulation based on a dynamic method combined with advanced appliance profiles. This study uses two-year monitored data in a PH-certified student accommodation building in Australia and validates the proposed bottom-up approach in both annual and monthly granularity. The results show that the level of reliability and robustness of the PHPP tool is substantially improved for three PH criteria (i.e., overheating frequency, space heating energy demand, and primary energy renewable) and three operational variables (i.e., indoor temperature, plug load, and lighting power density), all within the ranges of error allowed by ASHRAE’s Guideline 14–2014. Based on the proposed approach, a set of stepwise retrofit actions was put in place to further improve the energy efficiency and occupant thermal comfort in the case study building.

Space temperature policy towards net-zero: recommendations from a systematic review of UK HEI heating policies

ABSTRACT The UK government has committed to reducing its carbon emissions to net-zero by 2050. Higher education institutions (HEIs) are high energy users, with the largest proportion of their energy demand for space heating; an area still dominated by carbon-intensive fuels. This research addresses the UK HEI space temperature policy landscape, making direct links between space temperature policy and carbon management, advocating the development of evidence-based policies as a critical tool for reducing carbon emissions within the sector. Sixty-six space temperature policies were reviewed, and five experienced energy managers were interviewed to understand the range, development and use of space temperature policies in UK HEIs. The research identified a lack of consistency across these policies, leading to missed opportunities for making energy and carbon savings. The research highlights gaps in the available data and literature needed to connect policy to its effectiveness, and identifies the use of policy as a defensive tool against complaints rather than an active driver of energy reduction. A series of recommendations are proposed for national and institutional policymakers, suggesting areas for improvement and future research to facilitate effective development and practice in space temperature policy towards net-zero.

Determinants of energy demand for residential space heating in Turkey

A significant portion of household energy requirements is used for space heating. Although the fundamental factors determining household energy consumption have been the focus of many studies, they have neglected to consider the effect of unobserved heterogeneity, which has the potential to play a significant role as a determining factor in energy consumption. The study analyzes household decisions in choosing an energy source for residential space heating applying a random effect ordered logit model on Income and Living Conditions Longitudinal Micro Data Set for the years 2016–2019 to fulfill this gap in the literature. The results indicate that selection of residential space heating type (dried animal dung, charcoal, wood, natural gas, electricity) is influenced by socioeconomic and dwelling factors. We also found that the energy ladder hypothesis is valid for households in Turkey.

Impact of the COVID-19 pandemic on the energy performance of residential neighborhoods and their occupancy behavior.

Several contrasting effects are reported in the existing literature concerning the impact assessment of the COVID-19 outbreak on the use of energy in buildings. Following an in-depth literature review, we here propose a GIS-based approach, based on pre-pandemic, partial, and full lockdown scenarios, using a bottom-up engineering model to quantify these impacts. The model has been verified against measured energy data from a total number of 451 buildings in three urban neighborhoods in the Canton of Geneva, Switzerland. The accuracy of the engineering model in predicting the energy demand has been improved by 10%, in terms of the mean absolute percentage error, as a result of adopting a data-driven correction with a random forest algorithm. The obtained results show that the energy demand for space heating and cooling tended to increase by 8% and 17%, respectively, during the partial lockdown, while these numbers rose to 13% and 28% in the case of the full lockdown. The study also reveals that the introduced detailed occupancy scenarios are the key to improving the accuracy of urban building energy models (UBEMs). Finally, it is shown that the proposed GIS-based approach can be used to mitigate the expected impacts of any possible future pandemic in urban neighborhoods.