Occupant behaviour in energy efficient dwellings: evidence of a rebound effect

The energy required for space heating has been significantly reduced in recent decades by making use of insulation and more efficient heating and ventilation systems. Even so, wide variations in energy consumption are still observed between similar dwellings and between actual and predicted levels. It is thought that these variations stem from differences in occupant behaviour, the structural quality of the building, and a rebound effect. This paper statistically examines differences in occupant behaviour in relation to the building characteristics of the housing stock in the Netherlands and explores the possible existence of a rebound effect on the consumption of energy for space heating. Rebound effect can be defined as the increase on energy consumption in services for which improvements in energy efficiency reduce the costs. We found that although energy consumption is lower in energy efficient dwellings, analysis of the behaviour variables indicates their occupants tend to prefer higher indoor temperatures and to ventilate less. This finding might be related to a rebound effect on occupant behaviour. However, the improvement of thermal properties and systems efficiency still lead to a reduction on energy consumption for heating.     

Heat metering: socio-technical challenges in district-heated social housing

Individual heat metering and charging (IMC) are seen as promising methods to reduce domestic heating and hot water use through the provision of financial incentives. The heat consumption measured by meters is influenced by both the dwelling characteristics and the behaviour of the occupant, but heating charges would ideally relate to occupant behaviour only. This dilemma can be especially relevant under two circumstances: if the thermal performance of the dwelling is poor and/or if heating costs represent a substantial part of the occupants' income, i.e. in social housing. The case of a district-heated council block in London is presented where the installation of individual heat meters was planned in 2010 but had to be suspended due to concerns about implications for occupant heating costs in light of the thermal performance of the building. It illustrates a technically and socially complex environment where fairness in allocating heating costs is an important concern. The case also shows how lack of funding or other issues on the infrastructure side can hinder behaviour-orientated measures such as IMC. A holistic energy conservation strategy addressing both physical building properties and occupant behaviour is therefore essential and should be supported by policy.     

Environmental impact of dwellings in use: Maintenance of façade components

The use of dwellings contributes significantly to human-induced environmental burden in a number of ways, including energy consumption and the maintenance and replacement of building components. The present study deals with the maintenance and replacement of external doors and windows in a Dutch reference dwelling and describes how life cycle assessment (LCA) methodology can be applied to quantitatively assess the environmental impact of various maintenance scenarios for the façade components. First, the most effective way to reduce the negative environmental impact in this context is to replace existing single and double glazing with high efficiency double glazing, thereby reducing energy consumption for space heating. Second, the use of timber frames causes less environmental impact than PVC frames with a steel core. Third, extending the service life of building components decreases the input of material resources, production processes and the waste processing of building components during the service life of a dwelling, which is beneficial to the environment. Maintenance activities should only be performed when needed, keeping the building components in good condition while minimising the transportation movements of maintenance workers. Finally, protecting timber components with an alternative paint that contains less solvent does not lower the assessed environmental impact, but low-solvent paint may be preferred because of health aspects both for maintenance workers and occupants of the dwelling.     

Performance gaps in energy consumption: household groups and building characteristics

ABSTRACT

The difference between actual and calculated energy is called the ‘energy-performance gap’. Possible explanations for this gap are construction mistakes, improper adjusting of equipment, excessive simplification in simulation models and occupant behaviour. Many researchers and governmental institutions think the occupant is the main cause of this gap. However, only limited evidence exists for this. Therefore, an analysis is presented of actual and theoretical energy consumption based on specific household types and building characteristics. Using a large dataset (1.4 million social housing households), the average actual and theoretical energy consumptions (gas and electricity) of different household types and characteristics (income level, type of income, number of occupants and their age) were compared for each energy label. Additionally, the 10% highest and lowest energy-consuming groups were analysed. The use of combinations of occupant characteristics instead of individual occupant characteristics provides new insights into the influence of the occupant on energy demand. For example, in contrast to previous studies, low-income households consume more gas per m² (space heating and hot water) than households with a high income for all types of housing. Furthermore, the performance gap is caused not only by the occupant but also by the assumed building characteristics.     

Lighting energy consumption in ultra-low energy buildings: Using a simulation and measurement methodology to model occupant behavior and lighting controls

As building owners, designers, and operators aim to achieve significant reductions in overall energy consumption, understanding and evaluating the probable impacts of occupant behavior becomes a critical component of a holistic energy conservation strategy. This becomes significantly more pronounced in ultra-efficient buildings, where system loads such as heating, cooling, lighting, and ventilation are reduced or eliminated through high-performance building design and where occupant behavior-driven impacts reflect a large portion of end-use energy. Further, variation in behavior patterns can substantially impact the persistence of any performance gains. This paper describes a methodology of building occupant behavior modeling using simulation methods developed by the Building Energy Research Center (BERC) at Tsinghua University using measured energy consumption data collected by the University of Washington Integrated Design Lab (UW IDL). The Bullitt Center, a six-story 4831 m² (52,000 ft²) net-positive-energy urban office building in Seattle, WA, USA, is one of the most energy-efficient buildings in the world (2013 WAN Sustainable Building of the Year Winner). Its measured energy consumption in 2015 was approximately 34.8 kWh/(m²?yr) (11 kBtu/(ft²?yr)). Occupant behavior exerts an out-sized influence on the energy performance of the building. Nearly 33% of the end-use energy consumption at the Bullitt Center consists of unregulated miscellaneous electrical loads (plug-loads), which are directly attributable to occupant behavior and equipment procurement choices. Approximately 16% of end-use energy is attributable to electric lighting which is also largely determined by occupant behavior. Key to the building’s energy efficiency is employment of lighting controls and daylighting strategies to minimize the lighting load. This paper uses measured energy use in a 330 m² (3550 ft²) open office space in this building to inform occupant profiles that are then modified to create four scenarios to model the impact of behavior on lighting use. By using measured energy consumption and an energy model to simulate the energy performance of this space, this paper evaluates the potential energy savings based on different occupant behavior. This paper describes occupant behavior simulation methods and evaluates them using a robust dataset of 15 minute interval sub-metered energy consumption data. Lighting control strategies are compared via simulation results, in order to achieve the best match between occupant schedules, controls, and energy savings. Using these findings, we propose a simulation methodology that incorporates measured energy use data to generate occupant schedules and control schemes with the ultimate aim of using simulation results to evaluate energy saving measures that target occupant behavior.     

A user-centric space heating energy management framework for multi-family residential facilities based on occupant pattern prediction modeling

Space heating is the highest energy consumer in the operation of residential facilities in cold regions. Energy saving measures for efficient space heating operation are thus of paramount importance in efforts to reduce energy consumption in buildings. For effective functioning of space heating systems, efficient facility management coupled with relevant occupant behaviour information is necessary. However, current practice in space heating control is event-driven rather than user-centric, and in most cases relevant occupant information is not incorporated into space heating energy management strategies. This causes system inefficiency during the occupancy phase. For multi-family residential facilities, integrating occupant information within space heating energy management strategies poses several challenges; unlike with commercial facilities, in multi-family facilities occupant behavior does not follow any fixed activity-schedule pattern. In this study, a framework is developed for extracting relevant information about the uncertainties pertaining to occupant patterns (i.e., demand load) in multi-family residential facilities by identifying the factors affecting space heating energy consumption. This is achieved using sensor-based data monitoring during the occupancy phase. Based on the analysis of the monitoring data, a structure is defined for developing an occupant pattern prediction model that can be integrated with energy management strategies to reduce energy usage in multi-family residential facilities. To demonstrate the developed framework, a multi-family residential building in Fort McMurray, Canada, is chosen as a case study. This paper shows that integrating the developed occupant pattern prediction model within space heating energy management strategies can assist facility managers to achieve space heating energy savings in multi-family residential facilities.     

Behavioural Patterns and User Profiles related to energy consumption for heating

The difference between the actual and predicted energy consumption for heating in housing is thought to be partly attributable to the use of HVAC systems. More reliable data on energy consumption could help in determining the actual energy performance of dwellings and in the search for the most adequate design for housing and home amenities. Further reductions on energy consumption might also be achieved if energy-saving policy programmes were geared to different household groups. The aim of this paper is to statistically determine Behavioural Patterns associated with the energy spent on heating and to identify household and building characteristics that could contribute to the development of energy-User Profiles. This study had two outcomes: it identified Behavioural Patterns to be used in energy calculations and it discerned User Profiles with different behaviours. Five underlying groups of behavioural variables were found, which were used to define the Behavioural Patterns and User Profiles. The groups showed statistically significant differences in the scores for most of the behavioural factors. This study established clear relationships between occupant behaviour and household characteristics. However, it seems difficult to establish relationships between energy consumption and Behavioural Patterns and household groups.     

Smart building management vs. intuitive human control—Lessons learnt from an office building in Hungary

Smart building management and control are adopted nowadays to achieve zero-net energy use in buildings. However, without considering the human dimension, technologies alone do not necessarily guarantee high performance in buildings. An office building was designed and built according to state-of-the-art design and energy management principles in 2008. Despite the expectations of high performance, the owner was facing high utility bills and low user comfort in the building located in Budapest, Hungary. The objective of the project was to evaluate the energy performance and comfort indices of the building, to identify the causes of malfunction and to elaborate a comprehensive energy concept. Firstly, current building conditions and operation parameters were evaluated. Our investigation found that the state-of-the-art building management system was in good conditions but it was operated by building operators and occupants who are not aware of the building management practice. The energy consumption patterns of the building were simulated with energy modelling software. The baseline model was calibrated to annual measured energy consumption, using actual occupant behaviour and presence, based on results of self-reported surveys, occupancy sensors and fan-coil usage data. Realistic occupant behaviour models can capture diversity of occupant behaviour and better represent the real energy use of the building. This way our findings and the effect of our proposed improvements could be more reliable. As part of our final comprehensive energy concept, we proposed intervention measures that would increase indoor thermal comfort and decrease energy consumption of the building. A parametric study was carried out to evaluate and quantify energy, comfort and return on investment of each measure. It was found that in the best case the building could save 23% of annual energy use. Future work includes the follow-up of: occupant reactions to intervention measures, the realized energy savings, the measurement of occupant satisfaction and behavioural changes.     

Survey of occupant behaviour and control of indoor environment in Danish dwellings

Repeated surveys of occupant control of the indoor environment were carried out in Danish dwellings from September to October 2006 and again from February to March 2007. The summer survey comprised 933 respondents and the winter survey 636 respondents. The surveys were carried out by sending out invitations to addresses obtained from a Danish register along with information on dwelling characteristics. Meteorological data was obtained from the Danish Meteorological Institute.Four control mechanisms (window open/closed, heating on/off, lighting on/off and solar shading in/not in use) were analysed separately by means of multiple logistic regression in order to quantify factors influencing occupants’ behaviour.The window opening behaviour was strongly related to the outdoor temperature. The perception of the environment and factors concerning the dwelling also impacted the window opening behaviour.The proportion of dwellings with the heating turned on was strongly related to the outdoor temperature and the presence of a wood burning stove. The solar radiation, dwelling ownership conditions and the perception of the indoor environment also affected the use of heating.The results of the statistical analyses form a basis for a definition of standard behaviour patterns which can be used to make calculation of energy consumption of buildings more accurate.     

Energy and exergy analysis of the Greek hotel sector: An application

Energy consumption in buildings vary significantly, depending on factors as the use of the building, the construction type, maintenance, existing heating, cooling and lighting systems and other types of services. Hotel buildings have high energy consumption rate, as a result of their unique operational characteristics. Energy consumption in hotels is among the highest in the non-residential building sector in absolute values. Available specific information on the energy characteristics, thermal performance, energy losses, electric loads, and comfort conditions play significant role for the sustainable development of hotel's systems. These data can also be used to identify whether there is space for improvement in new or existing hotels by comparing them against predicted or actual building energy performance. The aim of the present paper is to analyze the energy and exergy utilization in four hotels in Rethimno, Crete (Southern Greece) and in Kassandra, Halkidiki (Northern Greece).     

Comparing the energy performance of an electrochromic window under various control strategies

Electrochromic glazing can involve substantial energy consumption in the building sector with their optical properties driven either by various occupant needs or environmental conditions. This paper presents comparison of ten different control strategies developed for such a glazing system in terms of specific energy consumption of a PASSYS test cell where the glazing was installed. The control strategies include scheduled ON–OFF controllers, a PID and advanced fuzzy controllers which were developed using experimental data. We used energy simulation to analyse the annual heating, cooling and lighting demands investigating the influence of each control strategy to the thermal behaviour of the building.     

Building signatures: A holistic approach to the evaluation of heating and cooling concepts

A sustainable and environmentally responsible building concept aims at a high workplace comfort, a significantly reduced heating and cooling demand, a high-efficient plant system, and the use of renewable energy sources to condition the built environment. This paper presents a comprehensive analysis of the heating and cooling concepts of 11 low-energy buildings in terms of energy use, efficiency and occupant thermal comfort. All buildings investigated employ environmental energy sources and sinks – such as the ground, ground water, rainwater and the ambient air – in combination with thermo-active building systems. A limited primary energy use of about 100 kWh_prim/(m²_neta) as a target for the complete building service technology (HVAC and lighting) was postulated for all buildings presented. With respect to this premise, a comprehensive long-term monitoring in high time resolution was carried out for two to five years, with an accompanying commissioning of the building performance. Measurements include the useful heating and cooling energy use, auxiliary energy use for the hydraulic system, as well as end and primary energy use, occupant thermal comfort and local meteorological conditions. A new methodology is proposed for a holistic approach to the evaluation of heating and cooling concepts, which not only considers the occupants thermal comfort, but also the useful energy consumption and the efficiency of the generation, distribution and delivery of heating and cooling energy.     

A methodology for modelling energy-related human behaviour: Application to window opening behaviour in residential buildings

An energy simulation of a building is a mathematical representation of its physical behaviour considering all the thermal, lighting, acoustics aspects. However, a simulation cannot precisely replicate a real construction because all the simulations are based on a number of key assumptions that affect the results accuracy. Above all, the real energy performance can be affected by the actual behaviour of the building occupants. Thus, there are great benefits to be derived from improving models that simulate the behaviour of human beings within the context of engineered complex systems. The occupant behaviour related to the building control potentialities is a very complex process that has been studied only in the last years with some focuses related to natural ventilation (window opening behaviour), space heating energy demand (in particular the adjustments in the temperature set-point) and natural light (focusing on window blinds adjustments). In this paper, a methodology is presented to model the user behaviour in the context of real energy use and applied to a case study. The methodology, based on a medium/long-term monitoring, is aimed at shifting towards a probabilistic approach for modelling the human behaviour related to the control of indoor environment. The procedure is applied at models of occupants’ interactions with windows (opening and closing behaviour). Models of occupants’ window opening behaviour were inferred based on measurements and implemented in a simulation program. Simulation results were given as probability distributions of energy consumption and indoor environmental quality depending on user behaviour.     

Evaluating diverse patterns of occupant behavior regarding control-based activities in energy performance simulation

Simulation is recognized as an effective tool for building energy performance assessment during design orretrofit processes. Nevertheless, simulation models yield deviating outcomes from the actual building performance and a significant portion of this deviation originates from the dynamic nature of occupant behavior. Literature on occupant behavior indicates that occupant behavior is not integrated into building energy performance assessment procedures with appropriate resolution, instead they are acceptedas as sumedand fixed data sets that usually represent the presence of occupants. This study attempts to evaluate the effect of diverse patterns of occupant behavior on energy performance simulation for office buildings. Diverse levels of sensitivity of occupant behavior on control-based activities such as using lighting apparatus, adjusting thermostat settings, and presence in space are employed through three diverse occupant behavior patterns. These occupancy patterns are correlated with three identical office spaces simulated within a conceptual office building. EDSL Tas is used to run building energy performance simulations. Effects of occupant behavior patterns on simulation outcomes are compared for five sample winter and summer workdays, with respect to heating and cooling loads. Results present findings on how diversity of occupancy profiles influences the consumption outcomes.     

The impact of window opening and other occupant behavior on simulated energy performance in residence halls

A poor depiction of occupant behavior in building performance simulation frequently results in substantial divergences between real and simulated results. The problem may be of particular concern with simulation supporting the renovation of older multi-unit residential buildings, buildings whose occupants use windows for temperature control even during heating season. Here, we investigated the impact of window operation models (as well as other occupant behaviors) on simulated energy performance in university residence halls. Based on environmental monitoring, along with information collected from occupant surveys and wearable devices, we estimated air exchange rates and developed a probabilistic window-operation prediction model. The data were collected in 76 dormitory rooms sampled from a pre-renovated historic building and two similar buildings. We then evaluated the window-operation model’s predictive performance in 15 dormitory rooms in the post-renovated building with new occupants. The results of our predictive model were also compared with previously reported window-operation models. We implemented each window-operation model in a calibrated EnergyPlus building performance model, comparing the results of each simulation to metered hourly steam consumption. The impact of the different window operation models on simulated heating energy use was significant (annual error ranging from 0.2% to 10%). Our model demonstrated the highest capability of predicting window state (accuracy=85.8%) and steam use (NMBE=?0.2%); however, some previously published windowoperation models also produced satisfactory performance, implying that such models may be generalizable to some extent. The results suggest that data collected from somewhat ubiquitous indoor environmental quality sensors can glean insights into occupant behavior for building performance simulation. Furthermore, the energy impacts resulting from the variations in occupant behavior studied here were large enough to show that the choice of behavior model can have meaningful implications for real-world applications, such as estimating saving from heating and lighting system upgrades.     

Development of Dutch occupancy and heating profiles for building simulation

Building simulations are often used to predict energy demand and to determine the financial feasibility of the low-carbon projects. However, recent research has documented large differences between actual and predicted energy consumption. In retrofit projects, this difference creates uncertainty about the payback periods and, as a consequence, owners are reluctant to invest in energy-efficient technologies. The differences between the actual and the expected energy consumption are caused by inexact input data on the thermal properties of the building envelope and by the use of standard occupancy data. Integrating occupancy patterns of diversity and variability in behaviour into building simulation can potentially foresee and account for the impact of behaviour in building performance. The presented research develops and applies occupancy heating profiles for building simulation tools in order create more accurate predictions of energy demand and energy performance. Statistical analyses were used to define the relationship between seven most common household types and occupancy patterns in the Netherlands. The developed household profiles aim at providing energy modellers with reliable, detailed and ready-to-use occupancy data for building simulation. This household-specific occupancy information can be used in projects that are highly sensitive to the uncertainty related to return of investments.     

Environmental impact of building-related and user-related energy consumption in dwellings

Energy consumption in dwellings contributes significantly to their total negative environmental impact. This paper quantitatively assesses the environmental impact of building-related and user-related gas and electricity consumption in a Dutch apartment dwelling using life cycle assessment (LCA) methodology. Several scenarios for gas and electricity consumption are compared to assess what effect changes in building characteristics and user behaviour have on the environmental impacts of energy consumption. This study shows that gas consumption significantly contributes to four environmental impact categories, which can be most effectively countered by reducing the heat demand of the dwelling. A 23% reduction in gas consumption leads to up to 13% less overall environmental impacts. Particularly in buildings with low heat demand, electricity consumption dominates all environmental impact categories. These can most effectively be reduced by changing the electricity demand of the user: 47% less electricity consumption leads to a 9–45% reduction in the total environmental impact. However, since electricity consumption continues to rise, the environmental effects of electricity use may be better reduced by changing the environmental impact of the electricity supply. Theoretically, when electricity consumption remains the same, over 90% less environmental impact could be reached by using 100% wind power to generate electricity.     

The impact of energy efficient refurbishment on the space heating fuel consumption in English dwellings

The aim of this study is to examine the effect of a major domestic energy efficiency refurbishment programme on domestic space heating fuel consumption. The case study dwellings were monitored either before or after (or both) the introduction of energy efficiency retrofit measures such as cavity wall insulation, loft insulation, draught stripping and energy efficient heating system. Property and utility consumption data were collected and half-hourly living room and main bedroom temperatures were monitored for 2–4 week period over two winters from a total of 1372 households selected from five major urban areas in England. Space heating fuel consumption was normalized to account for variation in the indoor–outdoor temperature difference and the dwelling floor area. The findings show that cavity wall and loft insulation can reduce the space heating fuel consumption by 10% in centrally heated properties and 17% in non-centrally heated properties. However, the introduction of a gas central heating system, although theoretically more efficient, has no significant impact in reducing fuel consumption even after adjusting for increased internal temperature.     

Identification of key factors for uncertainty in the prediction of the thermal performance of an office building under climate change

There is growing concern about the potential impact of climate change on the thermal performance of buildings. Building simulation is well-suited to predict the behaviour of buildings in the future, and to quantify the risks for prime building functions like occupant productivity, occupant health, or energy use. However, on the time scales that are involved with climate change, different factors introduce uncertainties into the predictions: apart from uncertainties in the climate conditions forecast, factors like change of use, trends in electronic equipment and lighting, as well as building refurbishment / renovation and HVAC (heating, ventilation, and air conditioning) system upgrades need to be taken into account. This article presents the application of two-dimensional Monte Carlo analysis to an EnergyPlus model of an office building to identify the key factors for uncertainty in the prediction of overheating and energy use for the time horizons of 2020, 2050 and 2080. The office has mixed-mode ventilation and indirect evaporative cooling, and is studied using the UKCIP02 climate change scenarios. The results show that regarding the uncertainty in predicted heating energy, the dominant input factors are infiltration, lighting gain and equipment gain. For cooling energy and overheating the dominant factors for 2020 and 2050 are lighting gain and equipment gain, but with climate prediction becoming the one dominant factor for 2080. These factors will be the subject of further research by means of expert panel sessions, which will be used to gain a higher resolution of critical building simulation input.     

Behavioral variables and occupancy patterns in the design and modeling of Nearly Zero Energy Buildings

The objective of obtaining high performance energy buildings can be reached considering the contemporaneous effects of technical characteristics and occupancy. Recent studies report that as buildings become more energy efficient, the behavior of occupants plays an increasing role in consumption. Therefore, a construction designed to be a Nearly Zero Energy Building (nZEB) might generate higher consumption than expected if the assumptions made in the simulation process are not respected during the real use. The occupant can modify the control strategies of internal variables (heating/cooling system operation, set point temperature, ventilation, lighting) and the users’ behavior has a high impact on the utilization of plants and equipment. A significant contribution is also represented by the internal gains that have a direct relation with occupancy. The aim of this study is to assess the influence of housing occupancy patterns on the definition of residential nZEB in Italian climatic conditions. The investigation has been carried out considering a case study consisting of a building designed according to the National Standards. Successively, different conditions of the building usage are analyzed using dynamic energy simulations that allow exploration of the different occupation modes. The variability of the family composition and the occupancy scenarios are defined based on the data collected in the specific context. The investigation provides information regarding the effects of human variables (occupants’ needs and preferences) on the final energy performance of low energy buildings and highlights the combination of variables that are important in the definition of nZEB as net zero source energy.