Building Energy Performance Gap Research Articles

Reducing hot water consumption through real-time feedback and social comparison using persuasive technologies: evidence from a Swiss energy-efficient district

The buildings sector is a substantial contributor to total energy consumption and, according to current forecasts, will remain so in the near future. Technical energy efficiency innovations can reduce energy demand; however, if not accompanied appropriately by building occupants’ behaviour, discrepancies between planned and resulting energy consumption will persist, which is known as the building energy performance gap. To tackle this challenge, interventions such as feedback and social comparison are increasingly applied in combination with persuasive technologies. We report the results from a field experiment conducted in a Swiss energy-efficient district where two consecutive behavioural interventions involving persuasive technologies were tested: (1) real-time hot water consumption feedback while showering and (2) a weekly newsletter with social comparison feedback regarding overall hot water consumption, including hot water saving tips, in addition to real-time feedback. Based on the data from 33 households, we found that, compared with the baseline consumption, hot water consumption was 12.4% lower immediately after the real-time feedback intervention and 16.1% lower after the combined intervention. Hot water consumption increased again after the intervention phase, but it was still 9.7% lower than the baseline consumption 2 months after the combined intervention and 8.6% lower 4.5 months after the combined intervention. While the reductions after the real-time feedback and combined intervention were significant, the reductions 2 and 4.5 months after the combined intervention were not.

Investigation of heating energy performance gap (EPG) in design and operation stages of residential buildings

The Energy Performance Gap (EPG) in buildings is a recognized phenomenon. However, its definition and underlying factors are extensive, necessitating a thorough investigation of the quantitative impact of each factor contributing to the EPG. In this research, a calibration-based approach is employed to identify and measure the contribution of these factors. Questionnaires, measurements, analyses, and calibrations are conducted on the energy performance of four residential units of an apartment block building in Iran as a case study. Subsequently, the impact rates of three key causes of the EPG, namely heating system efficiency, weather data in an EnergyPlus Weather (EPW) format file, and occupant behavior, are determined. By incorporating these causes into the model calibration process, the disparities between the design and operation stages are decreased. The study highlights the significance and quantifiable effects of accurate and measured boiler efficiency, utilizing a genuine EPW file rather than a convenient EPW file e.g., airport stations, and adopting precise and adaptable assumptions for occupant behavior modeling in bridging the EPG between the design and operation stages. There are a number of factors that impact the design stage gap, including boiler efficiency, occupant behavior, and a corrected EPW file, which contribute 43.9%, 26%, and 6.6%, respectively.

Assessing the co-heating test as reference for heat loss coefficient estimation: In-depth analysis on an artificial dataset

In order to bridge the building energy performance gap it is necessary to quantitatively and qualitatively characterize the actual energy demand of buildings and the thermal behaviour of their envelopes. Current European legislation prescribes the assessment of the energy efficiency of the building stock by means of energy performance certification, which labels the building performance based on theoretical data and specifications reflecting the design phase. At the current state, in most European countries such certificates provide the only insight into the overall performance of the building stock, while the need of characterizing the actually achieved building behaviour is recognized. The most common testing procedure used with the aim of characterizing the as-built thermal performance of commissioned dwellings is the co-heating test. It consists of a prescribed measurement procedure where a vacated house is submitted to an elevated indoor temperature. During the experiment, the indoor and outdoor environment, as well as the energy demand needed to maintain the stable indoor temperature are precisely monitored. Up to date, this testing procedure is acknowledged as the most reliable in practice, however, the limitations of the methodology are not yet completely explored and unambiguously defined. Thus, the aim of this work is to explore the limits of the co-heating testing procedure on artificially generated experiments which provide a completely defined environment and reference targets. To assess the impact of different aspects, such as the parameters of the statistical models or monitoring period and length, the artificial datasets provide the ideal conditions since the impact of measurement inaccuracy can be avoided and the expectations of the methodology itself can be evaluated. The main findings complement the prevalent research and indicate the possibility of assessing the building performance in the 10% bounds from the target, however considering idealised monitoring data. The research shows that using global horizontal instead of south vertical irradiation can provide overall more accurate results, especially in transient months. Finally, when assessing suitable periods for performing tests in a moderate climate, only 20% of the whole year can be considered to yield satisfactory results.

A data-driven energy performance gap prediction model using machine learning

The energy performance gap is a significant obstacle to the realization of ambitions to mitigate the environmental impact of buildings. Although extensive research has been conducted on the causes, minimization, or the quantifying of the energy performance gap in buildings, comparatively minimal work has been done on raising decision-makers awareness of a potential gap.This paper positions project risks at the core of the gap and proposes an innovative performance gap prediction model focusing on heating and electricity demand in buildings by utilizing the machine learning classification. In this research, the performance gap and project risks of 77 buildings was collected via a web-based survey. The predictive performance of the four machine learning algorithms, namely i) Naive Bayes, ii) k-Nearest Neighbors, iii) Support Vector Machine, and iv) Random Forest, were compared to determine the best model.The results obtained revealed that Naive Bayes was better able to predict the direction of the heating performance gap (72.50%), the negative heating performance gap (71.81%), the positive electricity performance gap (77.08%), and the negative electricity performance gap (83.85%). Furthermore, k-Nearest Neighbors and Support Vector Machine were more accurate to predict the direction of the electricity performance gap (79.00%), and the positive heating performance gap (76.04%).

A hybrid dynamic model for building energy performance gap analysis: a perspective of energy-related stakeholder collaboration

A hybrid dynamic model for building energy performance gap analysis: a perspective of energy-related stakeholder collaboration

Review of energy performance gap and solutions in residential buildings

The energy consumption in the world due to economic development, rising population, and technological developments is growing, which has led to an increase in global warming. Therefore, there is a strong need to develop new strategies to reduce energy consumption. Buildings account for about 40% of global energy consumption. Since occupancy time in residential buildings is longer than in commercial and office buildings, residential buildings have a more significant impact on energy consumption. Due to this issue, efforts are being made to optimize energy consumption in residential buildings. Evaluating the performance of a building through building certificates that include as-designed and in-operation is essential for improving energy efficiency. Building energy simulations must be performed before construction to ensure that energy consumption in buildings is acceptable. However, it is observed that the energy consumption of the building after construction is higher than what was designed. This difference is defined as the energy performance gap, which indicates extra energy consumption or failure to comply with energy standards in the operation of the building. There are several reasons for the increased energy consumption of an operating building compared to the designed model. So far, studies have been conducted to determine the factors affecting the energy performance gap, but it is necessary to analyze these studies comprehensively. This article investigates the causes of energy performance gaps and ways to reduce this difference through a comprehensive literature review study. In this way, it is possible to achieve solutions in the building certification criteria that minimize the difference in energy consumption between the as-designed model and the in-operation mode of the building. This article can help decision-makers select the certificate that best fits their purposes.

Stakeholder-associated impact factors of building energy performance gap and their intersections: A social network analysis

The building energy performance gap is a critical obstacle to emissions reduction and energy conservation. Previous research mainly focused on identifying the factors contributing to the building energy performance gap (BEPG). Such studies have tended toward an inward-looking perspective that treats impact factors in isolation from one another. In reality, most factors are interrelated and associated with energy-related stakeholders. To address this research gap, this research developed a social network analysis model to investigate the underlying network of stakeholder-related influencing factors. According to nodal degree, status centrality, betweenness centrality, and brokerage roles, 21 factors and 14 links that substantially influence other factors directly or indirectly are identified. Six challenges, including “Challenges to knowledge and experience,” “Challenges in determining who is responsible for BEPG among stakeholders,” “Cost challenges,” “Poor quality challenges,” “Challenges to building operation management,” and “Information integrity challenges,” are further identified. Moreover, six strategies that are useful in controlling and eliminating influencing factors and interactions are proposed. The results show that, after the proposed strategies were conducted, the density and cohesion of the network are reduced by 48.28% and 11.62%, respectively, and the top ten betweenness centrality values for the nodes and links are reduced by at least 30%. This research is expected to aid not only researchers in better understanding the intricate interrelationships among the factors influencing BEPG but also practitioners in effectively controlling the influencing factors of BEPG.

Significance of Occupant Behaviour on the Energy Performance Gap in Residential Buildings

Buildings are an important part of worldwide efforts to reduce energy consumption and mitigate greenhouse gas emissions that contribute to climate change. Despite recent technological developments in the area of energy consumption reduction, energy use is on the rise, highlighting the significance of considering occupant behavior with regard to controlling energy consumption and supporting climate resilience. Energy performance of residential buildings is a function of various aspects such as properties of the building envelope, climatic location characteristics, HVAC system, and, more importantly, occupant behavior and activities towards energy utilization. This study carries out a comprehensive review of the impact of occupant behavior on reducing the energy performance gap in residential buildings since residential buildings account for 70% of building floor area around the globe. Findings have revealed that a dearth of literature on occupants’ behavior scholarship leads to inaccurate simplifications in building modeling and design. Thus, there is a strong need to obtain appropriate occupant behavioral data to develop strategies to close the energy performance gap as much as possible to achieve better energy efficiency in residential buildings to contribute to resilience and sustainability. Findings have also revealed a lack of objective and subjective data on occupants’ behavior towards energy efficiency in residential buildings. In response to these gaps, the current paper has proposed a conceptual framework for occupant behavior toward a modification of thermal comfort to reduce energy use. Based on the findings of this paper, understanding the variety of factors influencing occupants’ behavior should be considered a major influential factor in the design and retrofit of residential buildings with a view toward long-term resilience and sustainability.

A hybrid-model forecasting framework for reducing the building energy performance gap

The performance gap between predicted and actual energy consumption in the building domain remains an unsolved problem in practice. The gap exists differently in both current mainstream methods: the first-principles model and the machine learning (ML) model. Inspired by the concept of time-series decomposition to identify different uncertainties, we proposed a hybrid-model approach by combining both methods to minimize this gap: 1. Use the first-principles method as an encoding tool to convert the building static features and predictable patterns in time-series simulation results; 2. The ML method combines the results as extra inputs with historical records simultaneously, trains the model to capture the implicit performance difference, and aligns to calibrate the output. To extend this approach in practice, a new concept in the modeling process: Level-of-Information (LOI), is introduced to leverage the balance between the investment of simulation modeling detail and the accuracy boost. The approach is tested over a three-year period, with hourly measured energy load from an operating commercial building in Shanghai. The result presents a dominant accuracy enhancement: The hybrid-model shows higher accuracy in prediction with better interpretability; More important, it releases the practitioners from modeling workload and computational resources in refining simulation. In summary, the approach provides a nexus for integrating domain knowledge via building simulation with data-driven methods. This mindset applies to solving general engineering problems and leads to improved prediction accuracy.

Office buildings occupancy analysis and prediction associated with the impact of the COVID-19 pandemic.

Buildings’ occupancy is one of the important factors causing the energy performance and sustainability gap in buildings. Better occupancy prediction decreases this gap both in the design stage and in the use phase of the building. Machine learning-based models proved to be very accurate and fast for occupancy prediction when buildings are exploited under normal conditions. Meanwhile, during the Covid-19 pandemic occupancy of the offices has dramatically changed. The study presents 2 office buildings’ long-term monitoring results for different periods of the pandemic. It aims to analyse actual occupancies during the pandemic and its influence on the ELM (Extreme Learning Machine) based occupancy-forecasting models’ reliability. The results show much lower actual occupancies in the offices than given in standards and methodologies; it is still low even when quarantines are cancelled. Average peak occupancy within the whole measured period is: for Building A – 12–20% and for Building B – 2–23%. The daily occupancy schedules differ for both offices as they belong to different industries. ELM-SA model has shown low accuracies during pandemic periods as a result of lower occupancies – R2 = 0.27–0.56.

The Energy Performance Gap in Swiss residential buildings: a roadmap for improvement

This work deals with the Energy Performance Gap (EPG) in buildings, defined as the difference between actual and theoretical energy consumption. This paper investigates how to close the EPG of existing buildings in Switzerland, by which measures, until when, and at which costs. To address these questions an extensive literature review was conducted combined with qualitative interviews in order to better understand practitioners’ experience and to support the findings from the literature. Several approaches have been found to reduce the EPG. These include both measures to make the building consume as expected and to arrive at a more accurate calculation of the theoretical consumption. We highlight the most relevant solutions for the Swiss context.

Explaining the energy performance gap in buildings with a latent profile analysis

The aim of this research is to identify energy consumption profiles that explain the difference between actual and theoretical energy consumption (the energy performance gap) in the residential sector using latent profile analysis (LPA). The resulting profiles inform behavioral and socio-demographic differences in consumption patterns among households and help explain inconsistencies in prior research on the energy performance gap. This research demonstrates that under-consumption of energy compared with the theoretical measure is partially explained by behavior related to poverty and deprivation. To address this, preventive measures should be put in place that focus on renovation or social housing to enable the poorest households to heat their dwellings adequately. Particular attention could also be paid to households that consume the most to avoid bias in energy forecasting models.

Building Energy Performance Certificate—A Relevant Indicator of Actual Energy Consumption and Savings?

A building energy performance gap can be illustrated as the difference between the theoretical (methodologically defined) and the actual energy consumption. In EU countries, Energy Performance Certificates are issued when buildings are constructed, sold, or leased. This information is the first step in order to evaluate the energy performance of the building stock. In Serbia, when issuing an energy certificate, the adopted national methodology recognizes only energy consumption for heating. The main purpose of this paper is to evaluate the energy gap and estimate the relevance of an Energy Performance Certificate to meet the national energy efficiency or carbon target. An Energy Performance Certificate determines the theoretical residential and commercial building energy efficiency or its “design intent”. This research stresses the necessity of measuring and achieving reductions in actual energy consumption through system regulation and consumers’ self-awareness in buildings. The research compares the performance of the building stock (135) that is connected to the District Heating System (DHS), with its own integrated heat meter, to Individual Gas Boiler (IGB) systems (18), in the city of Novi Sad, Serbia, built after 2014. For the purpose of comparing energy consumption, 16 buildings were selected that are very similar in terms of design, operation, and location. The data used are derived from metered consumption data, official evidence of city service companies, and Energy Performance Certificates of the considered buildings. We have determined that IGB systems have a much wider specific annual performance gap (11.19–101 kWh/m2a) than the buildings in the DHS (3.16–18.58 kWh/m2a).

Managing the risk of the energy performance gap in non-domestic buildings

Energy use in buildings accounts for one-third of the overall global energy consumption and total building floor area continues to increase each year as new developments are constructed and delivered. If stringent climate goals are to be met, these buildings will need to consume less energy and emit less carbon. However, design intentions for energy efficient buildings are not always met in practice. This performance gap between calculated and measured energy use in buildings threatens the progress necessary to meet these energy targets. The aim of this paper is to identify the factors that contribute to the performance gap and propose solutions for reducing the gap in practice. A quantitative and qualitative analysis of two research programmes completed in the past few years was utilized for an in-depth look at the performance of around 50 non-domestic buildings in the United Kingdom. While no direct links were found between any one variable and the performance gap, several correlations exist between contributing factors indicating a complex, entangled web of interrelated problems. The multitude of the variables involved presents a formidable challenge in finding practical solutions. However, the results indicate that the combination of the ventilation strategy of a building and the building services control strategy during partial occupancy is a key determinant of the performance gap. A more straightforward procurement approach with clearly delineated targets and responsibilities, along with advanced and seasonal commissioning instituted at the beginning of a project and implemented after building completion can also be very effective in reducing the gap. Finally, mandatory requirements or an appropriate system of incentives for monitoring and disclosure of performance data can help identify many of the underlying issues affecting performance in-use and untangle some of the web of complex issues across the building sector. Practical application Awareness of the performance gap and knowledge of the factors contributing to its impact on the building industry is important for all stakeholders involved in the design, construction, operation and occupation of non-domestic buildings. Understanding potential solutions to mitigate these risks may help to reduce the prevalence and magnitude of the performance gap.

Managing energy performance in buildings from design to operation using modelling and calibration

To manage the concerns regarding the energy performance gap in buildings, a structured and longitudinal performance assessment of buildings, covering design through to operation, is necessary. Modelling can form an integral part of this process by ensuring that a good practice design stage modelling is followed by an ongoing evaluation of operational stage performance using a robust calibration protocol. In this paper, we demonstrate, via a case study of an office building, how a good practice design stage model can be fine-tuned for operational stage using a new framework that helps validate the causes for deviations of actual performance from design intents. This paper maps the modelling based process of tracking building performance from design to operation, identifying the various types of performance gaps. Further, during the operational stage, the framework provides a systematic way to separate the effect of (i) operating conditions that are driven by the building’s actual function and occupancy as compared with the design assumptions, and (ii) the effect of potential technical issues that cause underperformance. As the identification of issues is based on energy modelling, the process requires use of advanced and well-documented simulation tools. The paper concludes with providing an outline of the software platform requirements needed to generate robust design models and their calibration for operational performance assessments. Practical application The paper’s findings are a useful guide for building industry professionals to manage the performance gap with appropriate accuracy through a robust methodology in an easy to use workflow. The methodological framework to analyse building energy performance in-use links best practice design stage modelling guidance with a robust operational stage investigation. It helps designers, contractors, building managers and other stakeholders with an understanding of procedures to follow to undertake an effective measurement and verification exercise.

Analyzing occupants' control over lighting systems in office settings using immersive virtual environments

Research has identified occupant behavior as one of the key contributors to building energy performance gap. Thus, this study systematically analyzed the impact of having personal control over lighting system on occupants' lighting choices, lighting satisfaction, and task performance in a virtual office setting. For this purpose, 30 participants took part in a 3-phased experiment with immersive virtual environments (IVEs). Each phase of the experiment offered a different degree of control over the lighting. Personality traits were also studied in relation to lighting choices. Finally, a technology acceptance model (TAM) was employed to further investigate the participants’ attitude towards the virtual reality (VR) technology.The findings of this study showed that using an interactive lighting system, which was as satisfactory compared to a conventional lighting system, encouraged the participants to use more natural light. The interactive lighting system imposed the same amount of cognitive load on the participants for performing a reading task as a conventional lighting system, which was significantly lower than their cognitive load scores for performing the task with automated lighting system. Personality analyses demonstrated that the participants with a high score on openness had a wide range of lighting choices either with conventional or with interactive lighting. This study's results differed from the previous studies by highlighting that the participants considered VR as a better fit to an enjoyable experience rather than a useful tool for performing serious tasks.

Stakeholders’ power over the impact issues of building energy performance gap: A two-mode social network analysis

Abstract Energy-related stakeholders play a critical role in energy-saving and emission reduction. However, most previous studies focused on only a few stakeholders (e.g., occupant, designer and owner). Therefore, there is a lack of systematic analysis of energy-related stakeholders. Improving building energy efficiency requires the collaboration of all stakeholders in the building lifecycle. This study applies a two-mode social network model to investigate the stakeholders’ power over the impact issues of building energy efficiency. Results show that all issues can be addressed by at least two stakeholders, thereby indicating the potential of collaboration in building energy management. Designers, manufacturers, commissioning agents and researchers are the most influential stakeholders with the highest degree centrality, betweenness centrality and eigenvector centrality. Insufficient knowledge and experience, lack of information integrity and unclear responsibility are the most influential impact issues. With the density of interaction being 1.000, nine core stakeholders (i.e. owner, designer, contractor, subcontractor, supervisor, manufacturer, commissioning agent, energy manager and researcher) and four core issues (i.e. unclear responsibility, poor collaboration and communication, insufficient knowledge and experience, and lack of information integrity) have intensive relationships. The core stakeholders account for 75% of the total stakeholders, whereas the core issues account for 25% of the total issues. Moreover, five strategies that are useful in promoting collaboration are proposed and validated. After the proposed strategies are implemented, the density of the collaboration network increased from 1.242 to 2.652. This study is not only expected to help researchers in understanding the complex interrelationships between stakeholders and issues but also practitioners in promoting effective collaboration strategies.

Co-heating test as a tool for reduction of energy performance gap in buildings

Co-heating test as a tool for reduction of energy performance gap in buildings

Life-cycle building information modelling (BIM) engaged framework for improving building energy performance

The building sector is responsible for 32% of global energy consumption and 19% of all energy-related greenhouse gas emissions. The urgent requirement for energy conservation and greenhouse gas emission reduction in the building sector has been recognised at the highest level of governments around the world. One potential solution, which has yet to be critically considered, is the application of Building Information Modeling (BIM) to overcome building energy performance gap (BEPG), defined as the discrepancy between the designed and actual energy consumption in buildings. This study performs a systematic and comprehensive literature review to identify the specific causes of the BEPG, and then analyses the application of BIM for addressing the BEPG. A life-cycle BIM engaged framework was developed, including the function of “information exchange”, “design review”, “energy-related quality control”, “life-cycle commissioning”, and “real-time operation and maintenance management”. It is expected that the proposed framework will assist researchers and practitioners better understand application of BIM to systematically improve building energy performance.

The Discrepancy between As-Built and As-Designed in Energy Efficient Buildings: A Rapid Review

Energy efficient buildings are viewed as one of the solutions to reduce carbon emissions from the built environment. However, studies worldwide indicate that there is a significant gap between building energy targets (as-designed) and the actual measured building energy consumption (as-built). Several underlying causes for the energy performance gap have been identified at all stages of the building life cycle. Focus is generally on the post-occupancy stage of the building life cycle. However, issues relating to the construction and commissioning stages of the building are a major concern, though not usually researched. There is uncertainty on how to address the as-designed versus as-built gap. The objective of this review article is to identify causes for the energy performance gap in buildings in relation to the post-design and pre-occupancy stages and review proposed solutions. The methodology applied in this research is the rapid review, which is a variant of the systematic literature review method. Findings suggest that causes for discrepancies between as-designed and as-built energy performance during the construction and commissioning stages relate to a lack of knowledge and skills, lack of communication between stakeholders and a lack of accountability for building performance post-occupancy. Recommendations to close this gap during this period include better training, improved communication standards, collaboration, energy evaluations based on post-occupancy performance, transparency of building performance, improved testing and verification and reviewed building standards.