A generalised stochastic model for the simulation of occupant presence

This paper describes an algorithm for the simulation of occupant presence, to be later used as an input for future occupant behaviour models within building simulation tools. By considering occupant presence as an inhomogeneous Markov chain interrupted by occasional periods of long absence, the model generates a time series of the state of presence (absent or present) of each occupant of a zone, for each zone of any number of buildings. Tested on occupancy data from private offices, the model has proven its capacity to realistically reproduce key properties of occupant presence such as times of arrival and departure, periods of intermediate absence and presence as well as periods of long absence from the zone. This model (due to related metabolic heat gains), and associated behavioural models which use occupants’ presence as an input, have direct consequences for building energy consumption.     

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.     

Indoor environmental quality differences between office types in LEED-certified buildings in the US

The study compared IAQ, thermal quality, and lighting quality between 5 different office types in LEED-certified buildings in relation to employees' environmental satisfaction and their job performance. This was to provide workplaces where workers in each specific office environment could be provided with appropriate office settings regarding these IEQ criteria when organizations comply with LEED standards. The five types of office included private enclosed, private shared, open-plan with high cubicle over 5′, open-plan with low cubicle lower than 5′, and open-plan with no partitions (bullpen) offices. The study found IAQ enhanced workers' job performance in enclosed private offices more than both high cubicles and low cubicles. All four office types had higher satisfaction with the amount of light and visual comfort of light as well as more enhancement with job performance due to lighting quality than high cubicles. There was no difference in thermal quality between the five office types. IAQ and lighting quality were not different between enclosed private, enclosed shared, and bullpen office types, either. The study findings suggest a careful workplace design considering the height of partitions in LEED-certified buildings to improve employee's environmental satisfaction and job performance.     

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.     

Effect of thermostat and window opening occupant behavior models on energy use in homes

Existing dynamic energy simulation tools exceed the static dimension of the simplified methods through a better and more accurate prediction of energy use; however, their ability to predict real energy consumption is undermined by a weak representation of human interactions with the control of the indoor environment. The traditional approach to building dynamic simulation considers energy consumption as fully deterministic, taking into account standardized input parameters and using fixed and unrealistic schedules (lighting level, occupancy, ventilation rate, thermostat set-point). In contrast, in everyday practice occupants interact with the building plant system and building envelope in order to achieve desired indoor environmental conditions. In this study, occupant behavior in residential building was modelled accordingly to a probabilistic approach. A new methodology was developed to combine probabilistic user profiles for both window opening and thermostat set-point adjustments into one building energy model implemented in the dynamic simulation tool IDA Ice. The aim of the study was to compare mean values of the probabilistic distribution of the obtained results with a singular heating energy consumption value obtained by means of standard deterministic simulations. Major findings of this research demonstrated the weakness of standardized occupant behavior profile in energy simulation tools and the strengths of energy models based on measurements in fields and probabilistic modelling providing scenarios of occupant behavior in buildings.     

Indoor air quality and occupant satisfaction in five mechanically and four naturally ventilated open-plan office buildings

Occupant responses and indoor environment characteristics were recorded and compared in five mechanically and four naturally ventilated open-plan office buildings by using a simple approach that enabled us to survey many buildings simultaneously. All occupant responses were obtained during one afternoon. In a pre-experiment, temperature and the concentration of CO₂ were monitored in 2–10 locations/office to evaluate the variation throughout the offices. A representative measurement point was subsequently selected and measurements of the same parameters were made during one week. All offices were monitored during the same week and occupant responses to the indoor environment were collected via the internet on the same day within that week. The temperature and the CO₂ concentration varied more and were in some cases higher in the naturally ventilated buildings, but occupant responses in terms of symptoms and adverse perceptions differed only modestly between the two building types. Although rarely supported by statistical significance, the results indicated a somewhat higher degree of satisfaction with the indoor environment and a lower prevalence/intensity of symptoms among the occupants in the naturally ventilated buildings.     

A novel approach for building occupancy simulation

Building occupancy is an important basic factor in building energy simulation but it is hard to represent due to its temporal and spatial stochastic nature. This paper presents a novel approach for building occupancy simulation based on the Markov chain. In this study, occupancy is handled as the straightforward result of occupant movement processes which occur among the spaces inside and outside a building. By using the Markov chain method to simulate this stochastic movement process, the model can generate the location for each occupant and the zone-level occupancy for the whole building. There is no explicit or implicit constraint to the number of occupants and the number of zones in the model while maintaining a simple and clear set of input parameters. From the case study of an office building, it can be seen that the model can produce realistic occupancy variations in the office building for a typical workday with key statistical properties of occupancy such as the time of morning arrival and night departure, lunch time, periods of intermediate walking-around, etc. Due to simplicity, accuracy and unrestraint, this model is sufficient and practical to simulate occupancy for building energy simulations and stochastic analysis of building heating, ventilation, and air conditioning (HVAC) systems.     

Evaluation of distributed environmental control systems for improving IAQ and reducing energy consumption in office buildings

Conventional heating, ventilation, and air conditioning (HVAC) systems are incapable of providing control over individual environments or adjusting fresh air supply based on the dynamic occupancy of individual rooms in an office building. This paper introduces the concept of distributed environmental control systems (DECS) and shows that improvement in indoor air quality (IAQ) and energy efficiency can be achieved by providing required amounts of fresh air directly to the individual office spaces through distributed demand controlled ventilation (DDCV). In DDCV, fresh air is provided to each micro-environment (room or cubicle) based on input from distributed sensors (CO₂, VOC, occupancy, etc.) or intelligent scheduling techniques to provide acceptable IAQ for each occupant, rather than for groups or populations of occupants. In order to study DECS, a numerical model was developed that incorporates some of the best available models for studying building energy consumption, indoor air flow, contaminant transport and HVAC system performance. The developed model was applied to a DECS in a model office building equipped with a DDCV system. By implementing DECS/DDCV and intelligent scheduling techniques it is possible to achieve an improvement in IAQ along with a reduction in annual energy consumption compared to conventional ventilation systems.     

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.     

Modeling occupancy and behavior for better building design and operation—A critical review

People spend more than 90% of their life time in buildings, which makes occupant behavior one of the leading influences of energy consumption in buildings. Occupancy and occupant behavior, which refer to human presence inside buildings and their active interactions with various building system such as lighting, heating, cooling, ventilation, window blinds, and plugs, attract great attention of research with regard to better building design and operation. Due to the stochastic nature of occupant behavior, prior occupancy models vary dramatically in terms of data sampling, spatial and temporal resolution. This paper provides a comprehensive review of the current modeling efforts of occupant behavior, summarizes occupancy models for various applications including building energy performance analysis, building architectural and engineering design, intelligent building operations and building safety design, and presents challenges and areas where future research could be undertaken. In addition, modeling requirement for different applications is analyzed. Furthermore, a few commonly used statistical and data mining models are presented. The purpose of this paper is to provide a modeling reference for future researchers so that a proper method or model can be selected for a specific research purpose.     

Occupant behaviour simulation for cellular offices in early design stages—Architectural and modelling considerations

Building simulation is most useful and most difficult in early design stages. Most useful since the optimisation potential is large and most difficult because input data are often not available at the level of resolution required for simulation software. The aim of this paper is to addresses this difficulty, by analysing the predominantly qualitative information in early stages of an architectural design process in search for indicators towards quantitative simulation input. The discussion in this paper is focused on cellular offices. Parameters related to occupancy, the use of office equipment, night ventilation, the use of lights and blinds are reviewed based on simulation input requirements, architectural considerations in early design stages and occupant behaviour considerations in operational stages. A worst and ideal case scenario is suggested as a generic approach to model occupant behaviour in early design stages when more detailed information is not available. Without actually predicting specific occupant behaviour, this approach highlights the magnitude of impact that occupants can have on comfort and building energy performance and it matches the level of resolution of available architectural information in early design stages. This can be sufficient for building designers to compare the magnitude of impact of occupants with other parameters in order to inform design decisions. Potential indicators in early design stages towards the ideal or worst case scenario are discussed.     

Indoor environmental quality,occupant satisfaction,and acute building‐related health symptoms in Green Mark‐certified compared with non‐certified office buildings

Indoor environmental quality (IEQ) has become an important component of green building certification schemes. While green buildings are expected to provide enhanced IEQ, higher occupant satisfaction, and less risks of occupant health when compared with non‐green buildings, the literature suggests inconsistent evidence due to diverse research design, small sample size, and weak statistical analysis. This study compared several outcomes pertinent to IEQ performance in green and non‐green office buildings in Singapore. Adopting a cross‐sectional study design, objective measurements were taken in eight green and six non‐green buildings, and satisfaction and acute health symptom risks of 367 occupants were obtained. Green buildings exhibited lower concentration of PM2.5, bacteria, and fungi and maintained temperature and humidity more consistently compared to non‐green counterparts. The mean ratings for satisfaction with temperature, humidity, lighting level, air quality, and indoor environment were higher in green buildings (with statistical significance P < 0.05). There was statistically significant reduction in risk of occupants having headache, unusual fatigue, and irritated skin in green buildings. Although matching of buildings and occupant characteristics, survey participation bias, and sampling duration (a 1‐week snapshot) of IEQ monitoring remain as limitations, this study offered positive association of green buildings with qualitatively and quantitatively measured performance of IEQ.     

Conditional Random Fields - based approach for real-time building occupancy estimation with multi-sensory networks

Automated real-time occupancy monitoring in buildings plays an important role in increasing energy efficiency and provides facility managers with useful information about the usage of different spaces. In this paper, a novel approach is proposed for estimating real-time occupancy in buildings, based on Conditional Random Field probabilistic models, utilizing data from different sensor types. Three different types of occupancy information are considered: presence/absence, actual number of occupants and occupancy density. The proposed occupancy estimation method has been applied to four spaces with different characteristics in a real-life testbed environment. Experimental results revealed that the proposed method yielded high accuracy for different sensor combinations in all tested configurations regarding the occupancy granularity and the space type, and outperformed the Hidden Markov Model based method.     

Simulation and visualization of energy-related occupant behavior in office buildings

In current building performance simulation programs, occupant presence and interactions with building systems are over-simplified and less indicative of real world scenarios, contributing to the discrepancies between simulated and actual energy use in buildings. Simulation results are normally presented using various types of charts. However, using those charts, it is difficult to visualize and communicate the importance of occupants’ behavior to building energy performance. This study introduced a new approach to simulating and visualizing energy-related occupant behavior in office buildings. First, the Occupancy Simulator was used to simulate the occupant presence and movement and generate occupant schedules for each space as well as for each occupant. Then an occupant behavior functional mockup unit (obFMU) was used to model occupant behavior and analyze their impact on building energy use through co-simulation with EnergyPlus. Finally, an agent-based model built upon AnyLogic was applied to visualize the simulation results of the occupant movement and interactions with building systems, as well as the related energy performance. A case study using a small office building in Miami, FL was presented to demonstrate the process and application of the Occupancy Simulator, the obFMU and EnergyPlus, and the AnyLogic module in simulation and visualization of energy-related occupant behaviors in office buildings. The presented approach provides a new detailed and visual way for policy makers, architects, engineers and building operators to better understand occupant energy behavior and their impact on energy use in buildings, which can improve the design and operation of low energy buildings.     

A case for ‘active’ daylighting by appropriate management of electric lighting

Understanding of how occupants of non-domestic buildings use electric lighting, gained from behavioural studies, indicates that the mere provision of daylighting is unlikely to lead to its useful uptake. It is suggested that the design of appropriate electric lighting control systems, including those requiring occupant action, can be related to occupancy patterns of space use and daylight availability in the space and that provision of such systems should be seen as ‘active daylighting’. It is also suggested that design for ‘active daylighting’ requires more accurate prediction of daylight availability in interiors.     

Energy efficient design and occupant well-being: Case studies in the UK and India

The purpose of this paper is to demonstrate the relationships between sustainable building design and occupant well-being. It starts with a definition of sustainable design and well-being, and focuses on the relationships between energy performance and occupant feedback. Methodologically it draws on detailed monitoring and surveys of 12 case study office buildings in the UK and India, and the paper uses the data to explore whether energy use and associated CO₂ emissions are correlated to occupant satisfaction and comfort. The results demonstrate that increased energy use in the case study buildings is associated with increased mechanisation (e.g. centralised air conditioning) and reduced occupant control. This reduced control in turn is shown to relate to reduced occupant comfort and satisfaction. Finally, the paper reveals that the reported health conditions of occupants correlates strongly with their levels of satisfaction. The overall conclusion is that energy use in typical office buildings is inversely correlated with the well-being of the occupants: more energy use does not improve well-being.     

Understanding occupancy pattern and improving building energy efficiency through Wi-Fi based indoor positioning

Detailed visualisation and data analysis of occupancy patterns including spatial distribution and temporal variations are of great importance to delivering energy efficient and productive buildings. An experimental study comprising 24-h monitoring over 30 full days was conducted in a university library building.Occupancy profiles have been monitored and analysis has been carried out. Central to this monitoring study is the Wi-Fi based indoor positioning system based on the measured Wi-Fi devices' number and locations and data mining methods. Distinct from traditional occupancy and energy studies,more detailed informationrelated to the indoor positions and number of occupants has offered a better understanding of building user behaviour. The implication of the occupancy patterns for energy( e. g. lighting and other building services) efficiency is assessed,assisted with data from lighting sensors where needed. It is found occupancy patterns change dramatically with time. Also,the energy waste patterns have been identified through the method of data association rule mining. If the identified energy waste is removed,the total energy consumption can be reduced by 26. 1%. The indoor positioning information also has implications for optimizing space use,opening hours as well as staff deployment. The work could be extended to more rooms with diverse functions,other seasons and other types of non-domestic buildings for a more comprehensive understanding of building user behaviour and energy efficiency.     

Energy performance assessment of occupied buildings using model identification techniques

Model identification allows the assessment of energy performance of buildings based on measured data. However, model identification of occupied buildings is difficult because the disturbances introduced by the occupants are usually not measured. For office buildings, we propose a method to estimate the occupancy in function of electrical energy consumption. To determine the complexity of the model, SVD is used for the number of thermal zones and statistical analysis is used for the model order. The estimated model was evaluated by simulation, consistency of input–output behaviour and uncertainty analysis. The RMS of the simulation error is less than 0.7 °C for the training data set. The proposed method allows calculating macroscopic parameters of the building (such as thermal loss and time constants), showing the relative weights for heat losses and estimation of energy savings by heating control.     

On the influence of building design,occupants and heat waves on comfort and greenhouse gas emissions in naturally ventilated offices. A study based on the EN 15251 adaptive thermal comfort model in Athens,Greece

According to the Intergovernmental Panel on Climate Change the buildings sector has the largest mitigation potential for CO₂ emissions. Especially in office buildings, where internal heat loads and a relatively high occupant density occur at the same time with solar heat gains, overheating has become a common problem. In Europe the adaptive thermal comfort model according to EN 15251 provides a method to evaluate thermal comfort in naturally ventilated buildings. However, especially in the context of the climate change and the occurrence of heat waves within the last decade, the question arises, how thermal comfort can be maintained without additional cooling, especially in warm climates. In this paper a parametric study for a typical cellular naturally ventilated office room has been conducted, using the building simulation software EnergyPlus. It is based on the Mediterranean climate of Athens, Greece. Adaptive thermal comfort is evaluated according to EN 15251. Variations refer to different building design priorities, and they consider the variability of occupant behaviour and internal heat loads by using an ideal and worst case scenario. The influence of heat waves is considered by comparing measured temperatures for an average and an exceptionally hot year within the last decade. Since the use of building controls for shading affects thermal as well as visual comfort, daylighting and view are evaluated as well. Conclusions are drawn regarding the influence and interaction of building design, occupants and heat waves on comfort and greenhouse gas emissions in naturally ventilated offices, and related optimisation potential.