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On the applicability of various levels of detail for occupant behavior representation and modeling in building performance simulation

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Building Simulation 2023年第8期16卷 1481-1498页

作者： Jeetika Malik Handi Chandra Putra Kaiyu Sun Tianzhen Hong Building Technology and Urban System Division Lawrence Berkeley National LaboratoryBerkeleyCA 94720USA

occupant behavior(OB)is one of the significant sources of uncertainty in building performance *** OB modeling has received increased attention in the past decade,research on the degree of granularity or level of detail(LoD)required for representing occupants is still in the nascent *** paper analyzes the modeling and applicability of three LoDs to represent occupants in building performance assessment.A medium-sized prototype office building located in Chicago,Illinois is used as the simulation case *** occupant-centric attributes are adopted to develop the LoDs for OB *** first demonstrate the different modeling approaches required for simulating the three fidelity ***,we illustrate the suitability of the developed LoDs in supporting six building performance use cases across different lifecycle *** study intends to provide guidance for the building simulation community on appropriate OB representation to support various use cases.

关键词： occupant behavior agent-based modeling building performance simulation level of detail fit-for-purpose office buildings

The reinforcement learning method for occupant behavior in building control:A review

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Energy and Built Environment 2021年第2期2卷 137-148页

作者： Mengjie Han Jing Zhao Xingxing Zhang Jingchun Shen Yu Li School of Technology and Business Studies Dalarna UniversityFalun 79188Sweden Leisure Management College Xi’an Eurasia UniversityYanta DistrictXi’anChina Luxembourg Institute of Science and Technology LIST 5Avenue des Hauts-FourneauxL-4362 Esch-sur-AlzetteLuxembourg

occupant behavior in buildings has been considered the major source of uncertainty for assessing energy con-sumption and building *** frameworks are usually built to accomplish a certain task,but the stochasticity of the occupant makes it difficult to apply that experience to a similar but distinct *** complex and dynamic environments,the development of smart devices and computing power makes intelligent control methods for occupant behaviors more *** is expected that they will make a substantial contribution to reducing global energy *** these control techniques,the reinforcement learning(RL)method seems distinctive and *** success of the reinforcement learning method in many artificial intelligence applications has given an explicit indication of how this method might be used to model and adjust occupant behavior in building *** algorithms complement each other and guarantee the quality of the ***,the examination of occupant behavior based on reinforcement learning methodologies is not well *** way that occupant interacts with the RL agent is still *** study briefly reviews the empirical applications using reinforcement learning,how they have contributed to shaping the modeling paradigms and how they might suggest a future research direction.

关键词： Reinforcement learning occupant behavior Energy efficiency Building control Smart building

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

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Frontiers of Architectural Research 2018年第2期7卷 167-179页

作者： Basak Gucyeter Department of Architecture Faculty of Engineering and Architecture Eskisehir Osmangazi University Eskisehir Turkey

Simulation is recognized as an effective tool for building energy performance assessment during design or retrofit 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 accepted as assumed and 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.

关键词： occupant behavior Building energy performance assessment Modeling and simulation Probabilistic approaches

The Impact of occupant behavior on Daylight Performance of an Office Room in a Tropical Climate

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Journal of Civil Engineering and Architecture 2018年第3期12卷 205-212页

作者： Juliana Portela Vilar de Carvalho Viviane Diniz Hazboun Allyson Santos Carvalho Aldomar Pedrini Departamento de Pós-graduacao em Arquitetura e Urbanismo Universidade Federal do Rio Grande do Norte (UFRN) Natal 59079970 Brazil

This work explores three patterns of occupants’ control of window blinds and the potential influence on daylight performance of an office room in a tropical climate. In this climate, windows are frequently obstructed by curtains to avoid glare, despite the daylighting and the exterior view. The consequences are obstructed outside view, poor daylight quality and dependency on artificial lighting. This paper assesses the impact on available daylight using parametric analysis based on daylighting dynamic computer simulations using Grasshopper and Daysim software, combining WWR （window-to-wall ratio）（40% and 80%）, SVF （sky view factor）（small and large） and occupant behavior （active, intermediate and passive users）. The user patterns are based in an office buildings survey that identifies preferences concerning daylight use and control of shading devices. The daylight performance criteria combine UDI （useful daylight illuminance）（500-5,000 lux） and illuminance uniformity distribution. Results confirm the impact of occupant behavior on daylighting performance. The optimum combination of external shading devices, high SVF and high window size results in a useful daylighting for 1/3 of the time for passive users and 2/3 for active users.

关键词： Daylighting occupant behavior fenestration systems.

Room zonal location and activity intensity recognition model for residential occupant using passive-infrared sensors and machine learning

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Building Simulation 2022年第6期15卷 1133-1144页

作者： Jingsi Zhang Ting Zhao Xiang Zhou Jilong Wang Xinyue Zhang Chaokui Qin Maohui Luo School of Mechanical Engineering Tongji UniversityShanghai200092China

Given the importance of recognizing indoor occupant’s location and activity intensity to the control of intelligent homes,exploring approaches that can detect occupants’location and activity types while protecting occupants’privacy is *** this study,occupants’zonal location and activity intensity recognition models were developed using passive infrared(PIR)sensors and machine learning algorithms.A PIR sensor array with 15 nodes was employed to monitor indoor occupant’s and cat’s behavior in a case residential building for 71 *** output signals of PIR sensors varied with different locations and activity *** analyzing the PIR data feature,models were established using six machine learning algorithms and two sets of *** comparing model performance,the support vector machine(SVM)algorithm was selected to establish the final *** model input was optimized by accumulating the PIR *** PIR original counting values in 1-minute and 30-minute accumulated data as input features,the optimized SVM model can achieve 99.7%accuracy under the 10-fold cross-validation for the training data set,and 90.9%accuracy for the test data *** cat’s activity intensity is much weaker than that of occupant,yielding much smaller PIR output,which helped the SVM model to distinguish cat’s activity from occupant’s with>90%*** model’s recognition accuracy decreases with the decrease of sensor numbers and nine sensors were *** findings obtained in this study support the promising future of applying PIR sensors in smart homes.

关键词： PIR sensor machine learning occupant behavior pet behavior smart home

Energy and comfort performance of occupant-centric air conditioning strategy in office buildings with personal comfort devices

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Building Simulation 2022年第5期15卷 899-911页

作者： Jingsi Zhang Xiang Zhou Song Lei Maohui Luo School of Mechanical Engineering Tongji UniversityShanghai 200092China East China Architectural Design and Research Institute 151 Hankou RoadShanghaiChina

The personal comfort system(PCS)aims to meet individual thermal comfort demands efficiently to achieve higher thermal comfort satisfaction while reducing air conditioning energy *** date,many PCS devices have been developed and evaluated from the perspective of thermal *** will be useful for future PCS development if an approach to quantify the thermal comfort and energy performance of certain PCS devices and their combinations with consideration of user behaviors can be *** study attempted to fill this gap by integrating thermal comfort experiments,occupancy simulations,usage behavior modeling,and building energy simulation ***,human subject experiments were conducted to quantify the thermal comfort effects of the ***,the Markov chain model and conditional probability model were employed to describe the room occupancy and PCS usage ***,the extended comfort temperature range and user behavior models were imported into the building energy simulation tool to analyze the energy-saving potential of the *** results show that the use of PCS can significantly improve occupants,thermal comfort and satisfaction rate under both warm and cool *** a cooling cushion and desktop fan can lift the upper limit of the comfortable temperature to 29.5℃while the heated cushion can extend the lower limit to 15℃.By increasing the air conditioning temperature setpoint by 2℃in summer and reducing by 2.5℃the heating temperature setpoint in winter,PCS devices can reduce heating and air conditioning energy consumption by 25%-40%while maintaining occupants’thermal comfort.

关键词： thermal comfort personal comfort system occupant behavior building energy simulation building energy saving

A review of current research on occupant-centric control for improving comfort and energy efficiency

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Building Simulation 2024年第10期17卷 1675-1692页

作者： Yue Yuan Chengcheng Song Liying Gao Kejun Zeng Yixing Chen College of Civil Engineering Hunan UniversityChangsha 410082China Key Laboratory of Building Safety and Energy Efficiency of Ministry of Education Hunan UniversityChangsha 410082China

occupant-centric control(OCC)is intelligent control of building systems based on the real comfort needs of *** paper provides a comprehensive review of how real-world data on energy-related occupant behavior(OB)can be integrated and applied in OCC *** aim is to accurately portray the real occupant needs and improve energy efficiency without sacrificing occupant *** paper first introduces two types of OB:detailed occupancy states and energy-interaction behaviors,including methods to monitor,establish,and predict these ***,OCC is divided into real-time control and model-based predictive control,and each of these four scenarios is *** extensively reviews OCC methods for different equipment in four cases,covering control strategies,control scales,comfort enhancement scenarios,and energy-saving potential for each *** is summarized that despite extensive research on OB,there are still significant challenges in integrating this research into OCC.A major issue is the lack of a bridge connecting monitoring acquired information and *** addition,the article reviews the current state of OCC platform *** future direction should be combined with advanced Internet of Things(IoT)technologies,WiFi,and other communication technologies to obtain information about people’s behavior and real needs in order to create truly energy efficient and comfortable smart *** article also discusses how enhancing the real-time feedback capability of the OCC system can help improve the overall control system capability and the importance of testing through experimentation.

关键词： occupant-centric control occupant behavior occupancy data-driven models IoT technology

A data-driven model predictive control for lighting system based on historical occupancy in an office building: Methodology development

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Building Simulation 2021年第1期14卷 219-235页

作者： Yuan Jin Da Yan Xingxing Zhang Jingjing An Mengjie Han School of Architecture Tsinghua UniversityBeijing100084China School of Industrial Technology and Business Studies Dalarna UniversityFalun79188Sweden

The lighting system accounts for 8%of the total electricity consumption in commercial buildings in the United States and 12%of the total electricity consumption in public buildings *** consumption share can be effectively reduced using the demand-response *** traditional lighting system control method commonly depends on the real-time occupancy data collected using the passive infrared(PIR)***,the detection inaccuracy of the PIR sensor usually results in *** diminish the false-error frequency,the existing lighting system control simply deploys a delayed reaction period(e.g.,5 to 20 min),which is not sufficiently accurate for the demand-response ***,in this research,a novel data-driven model predictive control(MPC)method that is based on the temporal sequential-based artificial neural network(TS-ANN)is proposed to overcome this challenge using an updated historical occupancy *** an office as case study,the proposed model is also compared with the traditional lighting system control *** the proposed model,the occupancy data was trained to predict the occupancy pattern to improve the *** was found that the occupancy prediction mainly correlates with the historical occupancy ratio and the time sequential *** simulation results indicated that the proposed method achieved higher accuracy(97.4%)and fewer false-offs(from 79.5 with traditional time delay method to 0.6 times per day)are achieved by the MPC *** proposed TS-ANN-MPC method integrates the analysis of the occupant behavior routine into on-site control and has the potential to further enhance the control performance practice for maximum energy conservation.

关键词： lighting system occupant behavior data-driven model predictive control

IDENTIFYING occupantS’APPROPRIATE SEATING POSITION AND VIEW DIRECTION IN OFFICE BUILDINGS:A STOCHASTIC SHADE CONTROL BASED MULTI-OBJECTIVE VISUAL COMFORT OPTIMIZATION

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Journal of Green Building 2020年第1期15卷 15-36页

作者： Jian Yao Department of Architecture Ningbo UniversityNingboChina

Manually operated solar shades have a significant impact on indoor visual *** research investigates occupants’appropriate seating position and view direction in a west-facing office cell using a previously developed shade behavior *** non-dominant sorting genetic algorithm(NSGA-II)based Multi-objective optimization was adopted to identify the optimal and near optimal *** and glare index were used as two visual comfort objectives for optimization and robustness of optimization results against shade behavior uncertainty that was analyzed using statistical *** show that near optimal solutions can be used instead of the optimal one since they provide more flexibility in seating positions while maintaining almost the same visual comfort *** thus,the appropriate seating position considering occupants’preference is 1.5m away from the external window with two view directions near parallel to the window for west-facing office rooms.

关键词： manual solar shades occupant behavior visual comfort Multi-objective optimization seating position