Energy Use In Residential Buildings Research Articles

Rethinking the concept of building energy rating system in Australia: a pathway to life-cycle net-zero energy building design

Over the last decades, Australia has taken several measures to tackle the increasing trend of energy use in residential buildings. Recently, the Trajectory for Low Energy Buildings has been endorsed aiming to reduce energy usage in residential buildings. However, the primary focus of this trajectory is on decreasing operational energy without considering the embodied energy of the building and systems. This paper aims to address one primary question; ‘can the continued exclusion of embodied energy from the energy efficiency regulations effectively lead to reducing energy consumption in Australian residential buildings?’. The findings indicate that embodied energy becomes a dominating factor as buildings’ thermal performances increase according to the Australian energy efficiency regulations. In transitioning from a standard 6.0-star building to a highly energy-efficient 8.7-star building, the proportion of embodied energy significantly increases from 20–40% to 50–75%. This study recommends establishing minimum mandatory requirements for buildings’ embodied performance.

Predicting U.S. Residential Building Energy Use and Indoor Pollutant Exposures in the Mid-21st Century.

The extent to which climate change and other factors will influence building energy use and population exposures to indoor pollutants is not well understood. Here, we develop and apply nationally representative residential energy and indoor pollutant model sets to estimate energy use, indoor pollutant concentrations, and associated chronic health outcomes across the U.S. residential building stock in the mid-21st century. The models incorporate expected changes in meteorological and ambient air quality conditions associated with IPCC RCP 8.5 and assumptions for changes in housing characteristics and population movements while keeping other less predictable factors constant. Site and source energy consumption for residential space-conditioning are predicted to decrease by ∼37-43 and ∼20-31%, respectively, in the 2050s compared to those in a 2010s reference scenario. Population-average indoor concentrations of pollutants of ambient origin are expected to decrease, except for O3. Holding indoor emission factors constant, indoor concentrations of pollutants with intermittent indoor sources are expected to decrease by <5% (PM2.5) to >30% (NO2); indoor concentrations of pollutants with persistent indoor sources (e.g., volatile organic compounds (VOCs)) are predicted to increase by ∼15-45%. We estimate negligible changes in disability-adjusted life-years (DALYs) lost associated with residential indoor pollutant exposures, well within uncertainty, although the attribution among pollutants is predicted to vary.

Heating and cooling energy consumption prediction model for high-rise apartment buildings considering design parameters

As lots of the total energy was used by buildings, the number of residential buildings has dramatically increased in South Korea. Thus, it is imperative to pay more attention to energy consumption by residential buildings. In addition, it is important to predict energy consumption in residential buildings accurately. While several studies have currently focused on the data-driven method to predict energy consumption, it requires much information for multivariate data. The present study developed a predictive model for energy consumption for residential buildings by using the statistical method. Using the response surface methodology, the relationships between design factors, and heating and cooling energy use in residential buildings were outlined. The response values were calculated by using the simplified geometries in the energy simulation tool. The relationship has confirmed the dependencies of the energy consumption on various design variables of envelope systems in residential buildings in that the predictive model for the heating and cooling energy consumption was developed. The developed model was compared with the data obtained in the apartment buildings in two cities in South Korea. As a result, a coefficient of variation of the root mean squared error (Cv (RMSE)) was ranged from - 0.3% to 15% and all the comparisons were within the acceptable range. Moreover, heating and cooling energy consumption was predicted by varying the values of design variables such as thermal transmittance, solar heat gain coefficient (SHGC), and air infiltration rates. Among the variables, the largest heating energy was required as with the increase in the air infiltration rates, while the largest cooling energy was consumed as the SHGC was increased for both apartment buildings. Moreover, the increase in thermal transmittance values resulted in about 27% - 29% of the increase in the heating energy consumption. For cooling, 8% to 26% of the energy consumption was decreased when the thermal transmittance was increased. As can be shown, the developed model can offer a rapid energy prediction for apartment buildings with simple information on design variables. Furthermore, it can easily figure out the most important design factor to make a more energy-efficient residential building design.

Forecasting Time-Series Energy Data in Buildings Using an Additive Artificial Intelligence Model for Improving Energy Efficiency.

Building energy efficiency is important because buildings consume a significant energy amount. The study proposed additive artificial neural networks (AANNs) for predicting energy use in residential buildings. A dataset in hourly resolution was used to evaluate the AANNs model, which was collected from a residential building with a solar photovoltaic system. The proposed AANNs model achieved good predictive accuracy with 14.04% in mean absolute percentage error (MAPE) and 111.98 Watt-hour in the mean absolute error (MAE). Compared to the support vector regression (SVR), the AANNs model can significantly improve the accuracy which was 103.75% in MAPE. Compared to the ANNs model, accuracy improvement percentage by the AANNs model was 4.6% in MAPE. The AANNs model was the most effective forecasting model among the investigated models in predicting energy consumption, which provides building managers with a useful tool to improve energy efficiency in buildings.

What leads to variations in the results of life-cycle energy assessment? An evidence-based framework for residential buildings

• Sources of variations in LCEAs were investigated • 157 cases of residential buildings that were analysed by LCEA were examined • Four major categories of parameters affecting LCEA results were identified • A conceptual framework was proposed to standardize LCEA in residential buildings Residential buildings are one of the major contributors to climate change due to their significant impacts on global energy consumption. Hence, most countries have introduced regulations to minimize energy use in residential buildings. To date, the focus of these regulations has mainly been on operational energy while excluding embodied energy. In recent years, extensive studies have highlighted the necessity of minimizing both embodied energy and operational energy by applying the life-cycle energy assessment (LCEA) approach. However, the absence of a standardized framework and calculation methodology for the analysis of embodied energy has reportedly led to variations in the LCEA results. Retrospective research endeavoured to explore the causes of variations, with a limited focus on calculating embodied impacts. Despite the undertaken attempts, there is still a need to investigate the key parameters causing variations in LCEA results by examining methodological approaches of the current studies toward quantifications of embodied and operational energies. This paper aims to address three primary questions: ‘what is the current trend of methodological approach for applying LCEA in residential buildings?’; ‘what are the key parameters causing variations in LCEA results?’; and ‘how can the continued variations in the application of LCEA in residential buildings be overcome?’. To this end, 40 LCEA studies representing 157 cases of residential buildings across 16 countries have been critically reviewed. The findings reveal four principal categories of parameters that potentially contribute to the varying results of LCEAs: system boundary definition, calculation methods, geographical context, and interpretation of results. This paper also proposes a conceptual framework to minimize variations in LCEA studies by standardizing the process of conducting LCEAs.

Data-driven predictive models for residential building energy use based on the segregation of heating and cooling days

Abstract Data-driven models can estimate the buildings’ energy consumption using machine learning algorithms. This approach works based on the correlation between energy consumption and various inputs such as weather data, occupancy schedules, heating, air conditioning, and physical properties of buildings. Seasonal changes affect buildings’ energy use. Hence, the required data for data-driven models (DDMs) during the heating and cooling days could be different. Selecting the most impactful inputs can help to choose the type and quantity of sensors for deployment that improve the model’s accuracy and minimize the costs. This paper performs feature selection for heating, cooling, hot water, and ventilation loads in residential buildings under the mixed-humid climate zone. Filter method, wrapper backward elimination, wrapper recursive feature elimination, Lasso regression, linear regression, and Extreme Gradient Boosting (XGBoost) regression are adopted for heating and cooling days, separately. We use twenty-five outputs from a computer model, and the results show that the key features for a DDM are different for heating and cooling days, and XGBoost provides the most accurate forecast. The findings of this paper are useful for selecting proper models, sensors, and inputs for model-predictive control systems during the heating and cooling seasons.

Feasibility of zonal space heating controls in residential buildings in temperate climates: Energy and economic potentials in Spain

This paper explores the effects of multi-zone heating systems in residential buildings in different Mediterranean climates. The aim is to evaluate their potential in residential sectors to provide a general basis from the results (from the energy and economic point of view). In addition, if feasible, a further detailed evaluation of this management strategy for optimising the energy use in residential buildings would also be carried out. To do so, the effects of two different zoning controls in different types of apartment, occupancy patterns, building characteristics and locations in Spain, have been assessed. Different combinations of these parameters have resulted in 336 different scenarios that have been dynamically simulated using Design Builder software. The obtained energy results have been analysed in detail. Moreover, an economic analysis of these results has also been carried out to evaluate the economic feasibility of these systems in residential buildings located in temperate climates. This has been calculated by evaluating the maximum investment that can be assumed in each scenario to achieve different payback periods (namely 10 and 20 years). The results obtained show that these systems could be a cost-effective strategy aimed at reducing the energy consumption in residential buildings, not only in cold climates, such as is shown in the literature (the majority of the studies found are located in the UK and northern countries), but also in more temperate climates, such as that of Spain. Savings of around 20% were obtained in the most usual scenarios in Spain (coherent with results obtained in previous studies in the UK found in the literature), showing that in several cases, the initial investment in zone-controlled systems could be paid off in less than ten years, especially in large apartments and the coldest weather conditions.

Managing thermal comfort in contemporary high-rise residential buildings: Using smart thermostats and surveys to identify energy efficiency and comfort opportunities

Heating, ventilation and air conditioning (HVAC) operation is the largest contributor to residential building energy use and can significantly influence occupant thermal comfort and behaviours. Despite the boom in high-rise residential building construction, little is known about the relationship between occupant comfort and behaviors and HVAC operation in these contemporary buildings. In this study, connected thermostat data and occupant surveys from 55 participants across two contemporary high-rise condominium buildings were used to characterize this relationship to reveal opportunities for improved comfort and energy efficiency. Survey data indicated that occupant thermal discomfort was prevalent across both buildings in the heating and cooling seasons (48% and 53% reporting discomfort in heating and cooling seasons, respectively). The measured data corroborated the survey findings showing that over-conditioning of suites is a chronic issue across seasons. However, investigation into the temperatures of suites located in different parts of the buildings indicated that the overheating was influenced by wind, solar radiation and winter stack effect, but not in the ways suggested by building physics (e.g. air moving in opposite direction of predicted stack effect). This supports our hypothesis that the MAU operational characteristics and incorrect balancing of air duct networks are likely causing over-conditioning but further investigation is ongoing to confirm this. Analysis of suite HVAC unit runtimes also revealed low runtimes in heating season, which may limit the effectiveness of improved (e.g. occupant-based) in-suite HVAC controls, given the minimal space conditioning energy consumption in these particular suites. This study demonstrates the potential for using connected thermostat data as a diagnostic tool to identify opportunities for energy savings in the building.

Clothing behaviour in Belgian homes

Clothing has a direct influence on the thermal comfort of an occupant and so, indirectly on the energy use of a building. Literary sources point out a lack of data about clothing behaviour in residential buildings. In order to assess the clothing behaviour two kinds of surveys are created: logbook surveys and online questionnaires. Both surveys are executed between March 11 and April 5, 2019. The mean clothing insulation worn during the investigation period is 0.58 clo. This clo-value differs from the clothing insulation values provided by Fanger, which are 1.0 clo for winter months and 0.5 clo for summer months. The influence of the indoor temperature, outdoor temperature, weather history memory, gender and age on the clothing behaviour is analysed. All variables have a small significant influence on the clo-value. It was found that occupants tend to wear the same clothes when they are at home. So, each participant clothes him/herself to be comfortable in their clothes and in the temperature of their own room. People who are used to live in lower indoor temperatures will, and are used to, wear more clothing insulation to be thermally comfortable than people living in warmer indoor temperatures. An adjustment in clothing behaviour can make a big impact on the energy use of residential buildings. A decrease in indoor temperature of 1°C can lead to heating energy savings of 10%. To remain thermally comfortable, the occupant must only wear an extra insulation value of 0.17 clo, which corresponds with a shirt. The question remains if occupants will effectively use the opportunity of changing clothes to lower their energy use.

The impacts of different façade types on energy use in residential buildings

Globally, buildings are responsible for a significant share in energy consumption and greenhouse gas emissions profiles. Various attempts are undertaken to increase the energy efficiency of buildings and reduce their environmental impact. In semi-continental climate conditions with very hot summers and extremely cold winters, buildings should be carefully designed to ensure efficient harnessing of solar energy and reducing energy loss due to poor insulation and inappropriate use of materials. Amidst the fast development of the construction industry, different façade systems are used in Kazakhstan. In several cases, the choice of the façade materials is defined not by performance but rather by economic aspects and physical appearance. This project aimed to investigate various types of façades adopted in the construction of residential buildings and assess their performance in terms of their impact on buildings’ energy consumption. The preliminary results indicate that there are five main types of façades widely used. Five different models were therefore built using energy simulation software and the respective energy consumption data were estimated. The results testify that buildings with brickwork (clay bricks) and stonework (travertine) façades were more energy efficient than those with brickwork (silica bricks), aluminum composite panels and decorated plaster façades.

Energy use in residential buildings: Analyses of high-efficiency filters and HVAC fans

This study explores the impact of filtration on energy use in residences based on yearlong measurements in 19 homes in Toronto, Canada. Results show that permanent split capacitor (PSC) motor fans drew approximately 40% more power than electronically commutated motor (ECM) fans and the median efficacy (flow divided by power) of ECM fans was 43% higher than that of PSC motor fans. In response to a pressure drop of 150 Pa, ECM fans drew more power (46% − 58% increase) and generally tended to maintain airflow rate, while PSC motor fans drew less power (10% − 23% decrease), but generally tended to reduce airflow rate. Filter pressure drop was not strongly correlated with filter nominal efficiency; thus, the use of higher-efficiency filters may not impact fan power draw. Fan energy consequences of high-efficiency filters are negligible in our sample, and because HVAC runtimes were generally low (median = 11%), the difference between the energy consumption of ECM and PSC motor fans at typical runtimes was small (less than 10 kWh per month). Filters in systems with ECM fans have higher effectiveness per unit of power draw than those in systems with PSC motor fans.

Upscaling the flexibility potential of space heating in single-family houses

Energy flexibility from residential buildings is foreseen as a solution to facilitate the integration of variable energy sources in the grid. In fact, the energy use in residential buildings is still high despite the different building regulations and some of their usages can be shifted in time. Among these usages, space heating showed an interesting potential for flexibility, especially in France, where 45% of the heating systems is electrical. The objective of this study is to evaluate the flexibility potential in typical French houses, looking at both the energy shifted and thermal comfort. Large differences are highlighted, mainly due to the thermal properties of the envelope and the type of emitter. The temperature drops are quick in poorly insulated building. Underfloor heating systems show a good flexibility potential due to the inertia of this type of emitter. Finally, quantitative data, such as the mean power decrease and power profiles, is provided to help the integration of flexible buildings in future energy grids.

Influence of window opening degree on natural ventilation performance of residential buildings in Hong Kong

Cooling energy use of residential buildings in Hong Kong has been increasing in the past two decades. Natural ventilation is an effective means to reduce cooling energy use. To encourage wider and more efficient use of natural ventilation, previous works have been focused on window designs and the influence of window opening on the discharge coefficient. There is virtually no works on identifying the window opening degree for efficient natural ventilation. In this study, walk-through surveys, site measurements, CFD simulations and statistical analyses were adopted to ascertain Hong Kong households’ window opening habits and to identify the optimum window opening degree. Three window types, operating under nine sets of representative wind conditions in Hong Kong, four possible window orientations and two ventilation modes (single-sided and cross ventilation), to become 1944 cases, were studied. Air change per hour (ACH) was used to quantity the indoor natural ventilation performance. Regression analysis was employed to quantify the influence of different operating characteristics on ACH. The results concluded that Hong Kong households had limited and inefficient use of natural ventilation, while the optimum window opening degree, taking into account seasonal wind conditions and all design options, should be in the range of 0.6 to 0.9.

Climate change implications for environmental performance of residential building energy use: The case of Qatar

Building energy demands in the future could increase due to the climate change driven increase in outdoor temperatures. Gulf countries characterized by extreme climate and dependency on fossil fuels would be especially vulnerable to such impacts. Considering that in such countries about 80% of energy produced is used for cooling services, an increase in cooling demand would affect both building environmental impact and grid stability. The main scope of this study is to quantify such implications by considering the residential sector of Qatar as a case study. A representative building of the national building stock was selected, and energy consumption was modelled for present and forecasted weather conditions. The results indicated that in the future, heat waves will occur more frequently, with a higher intensity and a longer duration. Consequently, building energy consumption will increase for up to 30%. Such increase in energy demand would result in higher CO2 emissions, water and fossil fuel depletion rates, as well as increased impact on already strained local marine ecosystem. In order to mitigate such impacts, New regional environmental policies should be developed for large-scale renovation of the existing building stock and installation of renewable energy systems in order to mitigate the environmental impacts.

Trees in cool climate cities may increase atmospheric carbon by altering building energy use

Urban trees are a critical part of the ‘green infrastructure’ intended to make our growing cities more sustainable in an era of climate change. The potential for urban trees to modify microclimates and thereby reduce building energy use and the associated carbon emissions is a commonly cited ecosystem service used to justify million tree planting campaigns across the US. However, what we know of this ecosystem service comes primarily from unvalidated simulation studies. Using the first dataset of actual heating and cooling energy use combined with tree cover data, we show that contrary to the predictions of the most commonly used simulations, trees in a cool climate city increase carbon emissions from residential building energy use. This is driven primarily by near east (<20 m from building) tree cover. Further analysis of urban areas in the US shows that this is likely the case in cool climates throughout the country, encompassing approximately 39% of the US population and 62% of its area (56%, excluding Alaska). This work adds geographic nuance to our understanding of how urban shade trees affect the carbon budget, and it could have major implications for tree planting programs in cool climates.

Energy Use in Residential Buildings: Impact of Building Automation Control Systems on Energy Performance and Flexibility

This work shows the results of a research activity aimed at characterizing the energy habits of Italian residential users. In detail, by the energy simulation of a buildings sample, the opportunity to implement a demand/response program (DR) has been investigated. Italian residential utilities are poorly electrified and flexible loads are low. The presence of an automation system is an essential requirement for participating in a DR program and, in addition, it can allow important reductions in energy consumption. In this work the characteristics of three control systems have been defined, based on the services incidence on energy consumptions along with a sensitivity analysis on some energy drivers. Using the procedure established by the European Standard EN 15232, the achievable energy and economic savings have been evaluated. Finally, a financial analysis of the investments has been carried out, considering also the incentives provided by the Italian regulations. The payback time is generally not very long: depending on the control system features it varies from 7 to 10 years; moreover, the automation system installation within dwellings is a relatively simple activity, which is characterized by a limited execution times and by an initial expenditure ranging in 1000 € to 4000 €, related to the three sample systems.

Climate-responsive design strategy for Erbil city

PurposeThe purpose of this paper is to investigate passive techniques used in traditional and indigenous architecture in order to decrease energy use in the buildings and to increase thermal and users’ comfort. The city of Erbil is explored where in the rapid transformation and import of Western architectural styles and materials have resulted in ignorance of climate-responsive tradition existing in the city since thousands of years.Design/methodology/approachIn order to propose a design strategy for modern residential buildings in Erbil city, a descriptive and interpretative approach is used as a methodology of this study. A literature review is done to explore the traditional use of passive techniques, and Waziran district of the city is analyzed and used as a pilot site in this study.FindingsDue to the shortage of electric power in the city, residential buildings have limited access to electric power. Therefore, thermal comfort and reduction of the energy use in residential buildings have become vital for Erbil. The use of passive techniques in architectural design will help to reduce energy dependency.Research limitations/implicationsThis study is limited to residential function in Erbil. Waziran district is used for the design proposals where dwellings are in a row context. The proposals are made on a geometrical basis and plan organization; however, the selection of construction materials is not included.Originality/valueThere is a proposal to reduce the use of electricity, which currently has limited access in Erbil city.

Rural Household Energy Use and Thermal Environment in Three Climatic Regions of Nepal

Nepal is a mountainous country with low energy use so far and its climatic patterns remarkably differ from one place to another due to its geographical variation. In the north summer is cool and winter severe, while in the south summer is tropical and winter is mild. Indoor thermal environment and household energy use of residential buildings are in general very much associated so that there have been guide a lot of research; however, there has not been sufficient number of such studies focusing on Nepal. In this study, we aim to analyze the current situation of household energy use and indoor thermal environment of residential buildings in three different ecological regions of Nepal. This study was carried out in mountain, hill and terai regions representing cold, temperate and sub-tropical climate in Nepal from 21st December, 2017 to 20th January, 2018. Indoor and outdoor air temperature and humidity were measured by electronic sensors with the help of data logger for every 10-minute interval from 5 households from each region. The mass of firewood used was also measured at those houses. Household energy-use data of 516 houses were collected by the method of questionnaire survey. We found that mean indoor temperature was 3.6°C, 9.4°C and 19.0°C in cold, temperate and sub-tropical regions respectively. Based on this field study, we concluded that firewood is the primary source of household energy for cooking. The present finding suggests that an intensive and extensive improvements of the indoor thermal environment together with rationalization of energy use must be important especially for winter seasons.

Energy Use in Residential Buildings: Characterisation for Identifying Flexible Loads by Means of a Questionnaire Survey

This work shows the outcomes of a research activity aimed at the energy characterization of residential users. Specifically, by data analysis related to the real energy consumption of sample buildings, the flexible loads amount has been identified so as to investigate on the opportunity to implement a demand/response (DR) program. The most meaningful input data have been collected by an on-line questionnaire created within an Excel spreadsheet allowing one to simulate and compare the calculations with the actual dwellings’ consumption; 412 questionnaires have been used as statistical sample and simulations have been performed based on single-zone dynamic model. Additionally, once the energy consumptions have been sorted by the different services, reference key performance indicators (KPIs) have been also calculated normalising those ones by people and house floor surface. From data analysis, it emerges how the Italian residential users are not very electrified. Furthermore, the flexible loads are low and, implementing minor maintenance interventions, the potential of flexibility can decrease up to 20%. For that reason, the current research can be further developed by investigating on suitable flexibility extensions as well as on the automation system requirements which is needed managing the flexible loads.

The effect of neighbourhood-level urban form on residential building energy use: A GIS-based model using building energy benchmarking data in Seattle

Despite numerous studies on computerised simulations for analysing the relationship between the physical characteristics of an urban environment and energy consumption in buildings, the correlation between the actual energy use and physical parameters influencing a building's energy performance has rarely been explored. Previous research has identified several physical characteristics of the urban environment as potential drivers of a building's energy demand. Using the building energy consumption data from the Seattle city government, and geographic information system (GIS) data obtained from the Washington Geospatial Data Archive, this study presents an investigation of the effect of three urban form variables—horizontal compactness, vertical density, and variation of building heights—on the residential energy consumption of multi-family housings in Seattle. The results of the spatial lag models of building energy use and its neighbourhood-level correlates confirm that the building's energy consumption is spatially dependent. In Seattle, the annual energy use of a multi-family building was reduced with an increased horizontal density and smaller variations in building height. An interpretation of the results is presented with respect to the local climate. Further research is required to examine the association between various urban form factors on a building's energy use in regions with different climatic environments.