Single Person Offices Research Articles

Changing the direction of the luminaire: A strategy to improve lighting energy efficiency in offices

Light environment’s non-visual effects influence people’s health and work efficiency. However, considering non-visual requirements in addition to traditional visual requirements may significantly increase lighting energy consumption. This study utilized simulation software to explore energy saving potential of changing the direction of the luminaire. A model of a single-person office with the luminaire attached to the ceiling right above the workstation was built in ECOTECT. Vertical eye-level illuminance and horizontal work-plane illuminance were calculated with luminaires of different luminous fluxes and elevation angles from downward vertical (0°-180° at an interval of 10° on both sides) using RADIANCE. Furthermore, six cases of different lighting requirements and light correlated color temperatures were considered. Based on the illuminance-versus-luminous flux coefficients obtained from simulation results, luminous fluxes were calculated to fulfill both visual and non-visual requirements under different elevation angles in all cases. It was found that compared to traditional lighting design with the luminaire facing vertically downwards, turning the luminaire at an elevation angle of 50° reduced the required luminous flux by up to 22.7%, which would benefit energy savings. Therefore, changing the direction of the luminaire has the potential to improve office lighting energy efficiency when considering both visual and non-visual requirements.

Grey-box Model Develop and MPC Simulation of Campus Office Zone Based on Actual Measurement

This study aimed to develop a grey-box building model in a zone of a high-rise building on a university campus and to simulate model-based predictive control. Grey-box modeling was performed using various indoor and external environment data measured within a single-person office space on a high floor. The residence schedule was indirectly calculated using values such as indoor CO2 concentration and plug power. In addition, the catalog rating value was applied as the cooling energy value of the indoor 4-ways air conditioner as this could not be measured. Measurements were performed for approximately 4-weeks, and operating data of the heat pump and non-operating (i.e., free-floating) data were obtained according to the weekday and weekend schedules. The grey-box model was parameterized using the linear time-invariant and linear time-variant models. Both models showed good predictive performance with a root mean square error of less than 1°C in the 2-week estimation and 2-week validation results. Based on these results, an MPC simulation was performed. MPC simulation in a single zone were conducted for various electricity cost structures to derive quantitative electricity cost savings compared to those of feedback control.

Research on air-conditioning usage behaviour in offices with different occupancy

Occupant behaviours in the buildings are not only random and uncertain but also related to each occupant’s habitual preference. This leads to the performance gap between actual and expected energy consumption in buildings. Therefore, accurate information and modelling with regard to occupant behaviour are important for reliable energy simulation and energy-saving optimization design. Existing studies on occupant behaviour models in office space usually focus on single-person offices or full-floor buildings, without considering the behavioural differences among offices with different occupancy. Therefore, this study established the air-conditioning usage behaviour models in offices with different occupancy based on questionnaires and measured data. The results show that occupant compromise and clustering effect will increase with the increase of occupancy. Using the established models as input, this study compared the simulation results with that under the standard schedule. The difference rate is as high as 32.19% in winter and 13.07% in the whole year. And for areas with high energy consumption in winter, the gap may be bigger.

Energy saving at work: Understanding the roles of normative values and perceived benefits and costs in single-person and shared offices in the United States

Developing and maintaining efficient energy-saving behaviors in the workplace is an important factor in reducing energy consumption and greenhouse gas emissions. Building on integrated theories, including a recently developed theoretical approach to studying the dynamics of social norms and decision-making, the theory of planned behavior, the norm activation model, and the motivation-opportunity-ability model, this study analyzes the influence of normative values, office design, and perceived benefits and costs on energy-saving behaviors in different office settings. Based on a survey from 555 U.S. employees, this study found that occupants in single-person offices were influenced by a combination of descriptive, injunctive, and personal norms, while those in shared offices tended to align their actions with injunctive norms and ascription of responsibility. Descriptive norms had a stronger effect on energy-saving behaviors in single-person offices than in shared offices. Ascription of responsibility, however, had a stronger effect on energy-saving behaviors in shared offices. The perceived ease of access to building control features significantly influenced energy-saving behaviors of shared-office occupants only. Time availability had no significant effect on energy-saving behaviors of occupants in both single-person and shared offices. This study provides policy recommendations for building architects, engineers, managers, and policymakers to enhance energy-saving behaviors.

Clustering of office workers from the OFFICAIR study in The Netherlands based on their self-reported health and comfort

The growing field of indoor health and comfort studies recently shifted from predicting the average comfort and wellbeing of a large population into identifying the needs of individuals in different scenarios. This study aimed to identify different profiles of office workers in the Netherlands who took part in the OFFICAIR study, based on their self-reported health and comfort. Associations of respondents’ health and comfort with gender and type of office indicated that female occupants experienced significantly higher numbers of building-related symptoms and consistently lower satisfaction levels of their office environment than male occupants. Workers in open space offices without partitions reported lower satisfaction and suffered from building-related symptoms more frequently than occupants in single person offices. TwoStep cluster analysis revealed three profiles of occupants: Healthy and satisfied workers, Moderate healthy and noise-bothered workers and Unhealthy and Air and temperature-bothered workers. While the first group was by far the healthiest, significant higher risks for building-related symptoms such as dry eyes (OR: 3.38), dry skin (OR: 2.87) and watering, itchy eyes (OR: 2.7) were identified for the unhealthy group than for the moderate healthy group. The results confirm the need of an integrated approach to better understand moderate and unhealthy groups in order to provide customised solutions for individuals with different complaints and needs.

Energy Saving at Work: Exploring the Role of Social Norms, Perceived Control and Ascribed Responsibility in Different Office Layouts

Reducing energy consumption in office buildings is critical for improving energy efficiency and decarburization at the large scale. This study (N=854) investigated the influence of social-psychological factors on energy-saving intention and behaviors in single-person versus shared offices based on the extend model of Theory of Planned Behavior (TPB). We found that ascription of responsibility, a variable added to the TPB, is the strongest predictor of energy-saving intentions for both single-person and shared offices. Interestingly, while injunctive norms are an important predictor of behavioral intention for single-person offices, descriptive norms are an important one for shared offices. Energy-saving intention mediates the influences of the aforementioned variables on energy-saving behaviors. Contrary to our hypotheses, perceived control over energy-saving and perceived ease of access to building control features have no direct impacts on energy-saving behaviors in single-person offices, but they have impacts on energy-saving behaviors in shared offices. This study provides useful insights for building designers and occupant behavior and energy modeling researchers.

Choregia and trierarchy as profit-oriented entrepreneurships

With regards to the model of the homo oeconomicus this paper argues that incentives for performing liturgies in classical Athens were based on profit-oriented calculation rather than desire to gain support for public offices. In classical Athens democratic measures diminished the power of single-person offices which led to a decrease in the desire to hold such offices by the aristocracy. Simultaneously, recourse to altruistic incentives is incompatible with the costs of liturgies and the effort some members of Athens society made in order to perform them. Careful examination of past research on liturgical spending in classical Athens and an analysis of coeval conditions show the validity of economic instruments that lead to a rational-actor perspective on public spending under the incentive of financial gain rather than non-monetary profit.

Thermal mass and thermal comfort in offices – experimental studies of a concrete floor

Previous studies demonstrated that the use of thermal mass in buildings can contribute to reduce the energy demand and improve the thermal comfort. The thermal mass effect strongly depends on the properties of the materials facing the internal environment. High thermal capacity and conductivity are vital to achieve the desired effects. Concrete have both and it is a common building material. However, scientifically sound experimental studies that quantify the effects in a controlled environment are scarce. The aim is to study the effects of thermal mass on indoor environment and comfort in a quantifiable way in an extensive experimental campaign where comparative measurements were carried out in The ZEB TestCell Laboratory in Trondheim, Norway. The facility consists of two identical real-weather exposed rooms the size of a single person office. One of the rooms was constructed with a 70 mm thick concrete flooring, the other with an 18 mm wood-flooring. Free-floating temperature propagations were measured in different natural ventilation scenarios. The results showed that peak temperatures were notably reduced in the test room with the concrete flooring. During the warmest periods, a temperature peak reduction of more than 10% was found compared to the wooden-floored room.

Using machine learning techniques for occupancy-prediction-based cooling control in office buildings

Heating, ventilation, and air-conditioning (HVAC) are among the major energy demand in the buildings sector globally. Improving the energy efficiency of such systems is a critical objective for mitigating greenhouse gas emissions and transitioning towards renewable sources of energy supply. The interest of this paper is to explore means to increase the efficiency of HVAC systems in accommodating occupants’ behavior in real time. For instance, rooms in office buildings are not always occupied by occupants during scheduled HVAC service periods. This offers an opportunity to reduce unnecessary energy demands of HVAC systems associated with occupants’ behavior. An in-depth analysis of occupants’ stochastic behavior within an office building is conducted in this paper. A demand-driven control strategy is proposed that automatically responds to occupants’ energy-related behavior for reducing energy consumption and maintains room temperature for occupants with similar performances as a static cooling. In this control strategy, two types of machine learning methods – unsupervised and supervised learning – are applied to learn occupants’ behavior in two learning processes. The occupancy-related information learned by the algorithms is used by a set of specified rules to infer real-time room setpoints for controlling the office's space cooling system. This learning-based approach intends to reduce the need for human intervention in the cooling system’s control. The proposed strategy was applied to control the cooling system of the office building under real-world conditions. Eleven case study office spaces were selected, representing three typical office uses: single person offices, multi-person offices, and meeting rooms. The experimental results report between 7% and 52% energy savings as compared to the conventionally-scheduled cooling systems.

Testing the accuracy of low-cost data streams for determining single-person office occupancy and their use for energy reduction of building services

We explored methods of detecting occupancy in single-person offices using data already collected by the occupant’s PC, or data from relatively cheap sensors added to the PC. We collected data at 15-s intervals for up to 31 days in each of 28 offices. A combination of low/no cost sensors (webcam-based motion detection, and keyboard and mouse activity) was much more accurate at detecting occupancy than a commercial ceiling-based passive infrared (PIR) sensor, and provided overall daytime accuracy >90%, with very low false negative rates. This enhanced detection performance would enable a reduction in the timeout periods for building service curtailment on space vacancy. For example, lighting switch-off timeout could be reduced from the current energy code standard of 20min to less than 5min, increasing energy savings potential by 25–45%. We then deployed this system in a proof-of-concept demonstration, using it to control lighting, heating, ventilation, and air conditioning (HVAC), and plug loads in a mock-up office environment. Tests were run over nine occupied days (six in cooling season, three in heating season). The system delivered energy savings of 15–68%, with no reported false negative errors.

Comparing occupancy models and data mining approaches for regular occupancy prediction in commercial buildings

Occupancy information can help us to achieve high energy-efficient buildings. Previous works mainly focus on predicting the presence and absence of occupants in homes or single person offices. We attempt to predict regular occupancy level in a commercial building deployment scenario. The occupancy prediction models can be divided into two categories of occupancy models and data mining approaches. For the occupancy models, we shall investigate the efficiencies of two widely used multi-occupant models, that is, inhomogeneous Markov chain and multivariate Gaussian. For the data mining approaches, we propose the application of autoregressive integrated moving average, artificial neural network and support vector regression. Experiments have been conducted using actual occupancy data under four different prediction horizons, that is, 15 min, 30 min, 1 and 2 h. The results demonstrated a guideline in how to choose a proper method for the prediction of occupancy in commercial buildings under different prediction horizons.

The effect of occupancy on perceived control, neutral temperature, and behavioral patterns

Agent-based modeling (ABM) allows implementing negotiated behaviors between individual agents. Little is known on how individually preferred behavioral patterns adapt within office spaces used by multiple people. Even less is known about the effect of such negotiated behaviors on the occupants’ satisfaction in terms of preferred indoor thermal conditions and the level of perceived control. In order to gain insights into these processes, an experimental study in a field laboratory was conducted. The 36 subjects worked in the facility for three days: one day in a single person office, one in an office for two people, and one in an office for four people. They were allowed to tilt windows, close blinds, use a ceiling fan, or adjust their clothing levels. The data was analyzed quantitatively and qualitatively. The results suggest that perceived control is negatively affected by the number of people, neutral temperatures are negatively affected by a lack of perceived control, actions on windows are increasing and actions on blinds and fans are decreasing. Based on the results, suggestions for advancements of ABM are given. However, further studies – especially field studies – are necessary before these results can be applied to models applicable for a broader usage.

Experimental and Modelling Investigations of Air Exchange and Infection Transfer due to Hinged-Door Motion in Office and Hospital Settings

Occupants spend a significant amount of time indoors where temperature and air quality has an important impact on their comfort, health and work performance. Understanding the role of airflow exchange between spaces is crucial to describe the processes of mixing and transport of substances driven by air motion and therefore essential for evaluating indoor air quality. This work presents the results of field measurements and laboratory experiments designed to characterise door operation and to quantify its influence on air volumes exchanged between rooms due to door motion. The field study was conducted to identify typical total door cycle times in single person offices. The laboratory experiments were conducted in a scale model to investigate the exchange flow between two generic rooms. The model consisted of a water filled tank divided into two equal rooms, which were connected by a computer-controlled hinged door. Flow visualisations were used to describe flow patterns and concentration measurements of Rhodamine WT were performed to quantify exchange volumes. With hold open times of between 0s and 26.67s the total fluid volume exchanged was found to be between 67% and 98% of the total volume swept. Based on the exchange volume found in these experiments combined with the Wells-Riley equation the effect of ventilation rate on the probability of occupants in an adjacent room becoming infected was investigated. With ventilation rates for a medium air quality the risk of infection is low (<0.05). However, the probability of infection quickly rises with lower ventilation rates.

Flow pattern and thermal comfort in office environment with active chilled beams

In modern offices, the heat load per floor area has increased. With high cooling loads, the possibility of draft problems increases. The purpose of this article was to study the flow patterns and draft risk in an office environment where cooling and air distribution is implemented with active chilled beams. The study is based on experiments in a laboratory mock-up room in three load conditions: summer, winter, and midseason (spring/autumn). Thermal plumes from heat sources and warm or cold windows had a notable effect on the flow pattern and velocity distribution in the occupied zone. Areas with increased draft risk were found in locations where the supply jet turns down to the occupied zone. Draft risk can also be high at the floor level as a result of a circulating flow pattern in the room. This article concentrates on measurement and modeling results in a single-person office room. Comparisons are made with corresponding results in an open-plan office.

05/01245 Modeling occupancy in single person offices

05/01245 Modeling occupancy in single person offices

Modeling occupancy in single person offices

This paper examines the statistical properties of occupancy in single person offices of a large office building in San Francisco. A probabilistic model to predict and simulate occupancy in single person offices is proposed. It is found that vacancy intervals are exponentially distributed and that the coefficient of the exponential distribution for a single office could be treated as a constant over the day. Occupancy intervals are more complex than vacancy intervals. The distribution of occupancy intervals is time varying. Variations among different offices are examined. The implications of the findings on thermal and air quality control are discussed.

Feasibility of a practical clinical trial for asthma conducted in primary care.

Practical clinical trials (PCTs) are essential to generate relevant evidence-based information to improve patient health. Primary care physicians' experience performing randomized controlled trials (RCTs) on representative patient populations is limited. We implemented a pilot practice-based asthma PCT to answer the following feasibility questions: (1) Was clinician interest initiated and maintained? (2) Did clinicians enroll patients into an RCT and complete follow-up? (3) Was an interactive voice-response (IVR) telephone system useful to collect patient-reported data? The protocol included (1) broadly representative adult asthma eligibility criteria, (2) self-reported patient-oriented outcomes, and (3) use of IVR to collect these data. Physicians in practice-based research networks, managed care organizations, and academic networks volunteered to participate. Of 13 physician volunteers, 10 (8 single-person office practices, 1 emergency department physician, 1 clinical researcher) from 4 states and 1 Canadian province enrolled 58 subjects and randomized 45 meeting final eligibility criteria; 39 (87%) attended the follow-up visit. However, only 34 (76%) provided adequate follow-up IVR self-report data, and subjects with less than a high school education provided significantly (P <.001) less data than other groups. Physician recruiting, randomizing, and completing a representative sample of adult asthma patients was feasible. The utility of IVR in primary care research requires further study.