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Urban building energy modeling (UBEM) is arousing interest in building energy modeling, which requires a large building dataset as an input. Building use is a critical parameter to infer archetype buildings for UBEM. This paper presented a case study to determine building use for city-scale buildings by integrating the Geographic Information System (GIS) based point-of-interest (POI) and community boundary datasets. A total of 68,966 building footprints, 281,767 POI data, and 3367 community boundaries were collected for Changsha, China. The primary building use was determined when a building was inside a community boundary (i.e., hospital or residential boundary) or the building contained POI data with main attributes (i.e., hotel or office building). Clustering analysis was used to divide buildings into sub-types for better energy performance evaluation. The method successfully identified building uses for 47,428 buildings among 68,966 building footprints, including 34,401 residential buildings, 1039 office buildings, 141 shopping malls, and 932 hotels. A validation process was carried out for 7895 buildings in the downtown area, which showed an overall accuracy rate of 86%. A UBEM case study for 243 office buildings in the downtown area was developed with the information identified from the POI and community boundary datasets. The proposed building use determination method can be easily applied to other cities. We will integrate the historical aerial imagery to determine the year of construction for a large scale of buildings in the future.
Zhang Deng; Yixing Chen; Xiao Pan; Zhiwen Peng; Jingjing Yang. Integrating GIS-Based Point of Interest and Community Boundary Datasets for Urban Building Energy Modeling. Energies 2021, 14, 1049 .
AMA StyleZhang Deng, Yixing Chen, Xiao Pan, Zhiwen Peng, Jingjing Yang. Integrating GIS-Based Point of Interest and Community Boundary Datasets for Urban Building Energy Modeling. Energies. 2021; 14 (4):1049.
Chicago/Turabian StyleZhang Deng; Yixing Chen; Xiao Pan; Zhiwen Peng; Jingjing Yang. 2021. "Integrating GIS-Based Point of Interest and Community Boundary Datasets for Urban Building Energy Modeling." Energies 14, no. 4: 1049.
The increasing fossil energy demand and carbon emissions pose a significant challenge to the world. According to climate adaptability design, the balcony is open type in Changsha. The study evaluates the energy-saving potential and the economic and environmental feasibility of installing the balcony in living rooms, and considering the effect of balcony orientations and air conditioning types. The economic viability is analyzed using the construction cost of the balcony and the extra market price of a residence with a balcony paid by the holder, respectively. Environmental feasibility assessment mainly adopts the CO2 emission payback period as the index. The annual electricity saving percentage of the split-type air conditioner in the living rooms facing four orientations with a balcony is in between 6.7% and 12.3%. And the balcony's investment payback period facing east or west orientation is less than 50 years based on construction cost. It has better environmental benefits with the CO2 emission payback period of the balcony facing four orientations is in between 10.4 and 24.6 years. Considering a living room constructed with a balcony, it is not feasible for dwellers to use a gas boiler, adopting the radiant floor system during the heating from the perspective of economic and CO2 emission.
Qing Yang; Nianping Li; Yixing Chen. Energy saving potential and environmental benefit analysis of application of balcony for residence in the hot summer and cold winter area of China. Sustainable Energy Technologies and Assessments 2020, 43, 100972 .
AMA StyleQing Yang, Nianping Li, Yixing Chen. Energy saving potential and environmental benefit analysis of application of balcony for residence in the hot summer and cold winter area of China. Sustainable Energy Technologies and Assessments. 2020; 43 ():100972.
Chicago/Turabian StyleQing Yang; Nianping Li; Yixing Chen. 2020. "Energy saving potential and environmental benefit analysis of application of balcony for residence in the hot summer and cold winter area of China." Sustainable Energy Technologies and Assessments 43, no. : 100972.
Urban building energy modeling (UBEM) is attracting increasing attention in the energy modeling filed. Unlike modeling a single building using detailed building systems information, UBEM generally uses limited high-level building stock data to infer default assumptions about building characteristics and operations. This practice inherently brings uncertainty to UBEM. This study introduced a novel method of automatic and rapid calibration of UBEM based on the annual electricity and natural gas energy use data by learning the correlations between crucial model input parameters and the building energy use from the reference building models. A case study was presented to calibrate 72 large office buildings built before 1978 in San Francisco. Seventeen model parameters were selected and Monte Carlo sampling was used to create 1000 samples that reasonably represent the parameter space. Then 1000 simulations were performed for the reference building model to create an energy performance database. The results showed that by learning from the energy performance database, it took less than four simulation runs on average to calibrate a building model. After the calibration, the distributions of each parameter were obtained to replace their single predefined default values. For example, the default lighting power density of 21.39 W/m2 was calibrated to be 7.50 W/m2 on average. The case study successfully demonstrated the effectiveness of the novel calibration method for UBEM in the mild climate. The method will be further tested in future for other climate zones and other building types.
Yixing Chen; Zhang Deng; Tianzhen Hong. Automatic and rapid calibration of urban building energy models by learning from energy performance database. Applied Energy 2020, 277, 115584 .
AMA StyleYixing Chen, Zhang Deng, Tianzhen Hong. Automatic and rapid calibration of urban building energy models by learning from energy performance database. Applied Energy. 2020; 277 ():115584.
Chicago/Turabian StyleYixing Chen; Zhang Deng; Tianzhen Hong. 2020. "Automatic and rapid calibration of urban building energy models by learning from energy performance database." Applied Energy 277, no. : 115584.
Regulations corroborate the importance of retrofitting existing building stocks or constructing new energy-efficient districts. There is, thus, a need for modeling tools to evaluate energy scenarios to better manage and design cities, and numerous methodologies and tools have been developed. Among them, Urban Building Energy Modelling (UBEM) tools allow the energy simulation of buildings at large scales. Choosing an appropriate UBEM tool, balancing the level of complexity, accuracy, usability, and computing needs, remains a challenge for users. The review focuses on the main bottom-up physics-based UBEM tools, comparing them from a user-oriented perspective. Five categories are used: (i) the required inputs, (ii) the reported outputs, (iii) the exploited workflow, (iv) the applicability of each tool, and (v) the potential users. Moreover, a critical discussion is proposed, focusing on interests and trends in research and development. The results highlighted major differences between UBEM tools that must be considered to choose the proper one for an application. Barriers of adoption of UBEM tools include the needs of a standardized ontology, a common three-dimensional city model, a standard procedure to collect data, and a standard set of test cases. This feeds into future development of UBEM tools to support cities’ sustainability goals.
Martina Ferrando; Francesco Causone; Tianzhen Hong; Yixing Chen. Urban building energy modeling (UBEM) tools: A state-of-the-art review of bottom-up physics-based approaches. Sustainable Cities and Society 2020, 62, 102408 .
AMA StyleMartina Ferrando, Francesco Causone, Tianzhen Hong, Yixing Chen. Urban building energy modeling (UBEM) tools: A state-of-the-art review of bottom-up physics-based approaches. Sustainable Cities and Society. 2020; 62 ():102408.
Chicago/Turabian StyleMartina Ferrando; Francesco Causone; Tianzhen Hong; Yixing Chen. 2020. "Urban building energy modeling (UBEM) tools: A state-of-the-art review of bottom-up physics-based approaches." Sustainable Cities and Society 62, no. : 102408.
Yixing Chen; Yixing Hong. Automatic and Rapid Calibration of Urban Building Energy Models by Learning from Energy Performance Database. 2020, 1 .
AMA StyleYixing Chen, Yixing Hong. Automatic and Rapid Calibration of Urban Building Energy Models by Learning from Energy Performance Database. . 2020; ():1.
Chicago/Turabian StyleYixing Chen; Yixing Hong. 2020. "Automatic and Rapid Calibration of Urban Building Energy Models by Learning from Energy Performance Database." , no. : 1.
Buildings consume about 20% of the total primary energy use in China. It is critical to enhancing building energy efficiency for sustainable development. The heating, ventilation, and air-conditioning (HVAC) systems account for about half of the energy consumption in commercial buildings. For large commercial buildings, central chiller plants are typically used to provide chilled water for space cooling and consume lots of energy. This study evaluates the impacts of different chiller design and their operation strategy on the energy performance of central chiller plants. A case study is conducted using an office building located in Beijing, China. Feasible chiller combinations are studied based on 13 available chillers with different capacities. Four control strategies are explored, including three sequencing control strategies based on weekly, daily, and hourly maximum cooling loads and one optimal control strategy. A building energy model is created using DeST to simulate the hourly cooling load of the office building, and calibrated using the measured data. An integration model has been developed in MATLAB scripts to calculate the annual energy consumption of the chillers for each chiller design under each control strategy. The results indicate that it is essential to control the chiller plant hourly; however, the optimal control may not be necessary. It is not good to select the chillers with all the same capacity. The capacity of the chillers should be slightly different to provide flexibility for control. The design of the chiller combination is essential in the design stage. When bad combinations of chillers were designed, the performance of the chiller plant may be low even with optimization control strategies.
Yixing Chen; Chuhao Yang; Xiao Pan; Da Yan. Design and operation optimization of multi-chiller plants based on energy performance simulation. Energy and Buildings 2020, 222, 110100 .
AMA StyleYixing Chen, Chuhao Yang, Xiao Pan, Da Yan. Design and operation optimization of multi-chiller plants based on energy performance simulation. Energy and Buildings. 2020; 222 ():110100.
Chicago/Turabian StyleYixing Chen; Chuhao Yang; Xiao Pan; Da Yan. 2020. "Design and operation optimization of multi-chiller plants based on energy performance simulation." Energy and Buildings 222, no. : 110100.
As the world pays more and more attention to energy conservation and environmental protection, the ground-source heat pump system has been rapidly popularized in China. The machine learning-based automatic control technology can help to improve the energy efficiency of the ground-source heat pump system. However, the quality of the measured data is often not clean enough to train the machine learning algorithms. On the other hand, building energy simulation can generate clean data to support machine learning-based control techniques. This study presents a framework to generate EnergyPlus Functional Mockup Units (FMUs) for co-simulating with Python environment. A case study was presented to create an EnergyPlus FMU of an office building with a ground-source heat pump system in Beijing. The basic EnergyPlus model was generated using the Commercial Building Energy Saver developed by Lawrence Berkeley National Laboratory and modified to include the ground-source heat pump system. The model was calibrated using the measured sub-metering data to meet the ASHRAE 14 requirement. To support the machine learning technique, an EnergyPlus FMU was developed to co-simulate with Python environment. EnergyPlus outputs the current room and system status parameters to Python and obtains the control signals from Python. In the future, we will work with machine learning experts to train and evaluate their control algorithms using the developed co-simulation platform.
Chuhao Yang; Yixing Chen; Nianping Li; Yifu Sun; Ruosa Wu. EnergyPlus and Python Co-simulation Model to Support Machine Learning-Based Control of Ground-Source Heat Pump System. Soil and Recycling Management in the Anthropocene Era 2020, 759 -766.
AMA StyleChuhao Yang, Yixing Chen, Nianping Li, Yifu Sun, Ruosa Wu. EnergyPlus and Python Co-simulation Model to Support Machine Learning-Based Control of Ground-Source Heat Pump System. Soil and Recycling Management in the Anthropocene Era. 2020; ():759-766.
Chicago/Turabian StyleChuhao Yang; Yixing Chen; Nianping Li; Yifu Sun; Ruosa Wu. 2020. "EnergyPlus and Python Co-simulation Model to Support Machine Learning-Based Control of Ground-Source Heat Pump System." Soil and Recycling Management in the Anthropocene Era , no. : 759-766.
Buildings in cities consume up to 70% of all primary energy. To achieve cities’ energy and climate goals, it is necessary to reduce energy use and associated greenhouse gas emissions in buildings through energy conservation and efficiency improvements. Computational tools empowered with rich urban datasets can model performance of buildings at the urban scale to provide quantitative insights for stakeholders and inform their decision making on urban energy planning, as well as building energy retrofits at scale, to achieve efficiency, sustainability, and resilience of urban buildings. Designing and operating urban buildings as a group (from a city block to a district to an entire city) rather than as single individuals requires simulation and optimization to account for interactions among buildings and between buildings and their surrounding urban environment, and for district energy systems serving multiple buildings with diverse thermal loads across space and time. When hundreds or more buildings are involved in typical urban building energy modeling (UBEM) to estimate annual energy demand, evaluate design or retrofit options, and quantify impacts of extreme weather events or climate change, it is crucial to integrate urban datasets and UBEM tools in a seamless automatic workflow with cloud or high-performance computing for users including urban planners, designers and researchers. This paper presents ten questions that highlight significant UBEM research and applications. The proposed answers aim to stimulate discussion and provide insights into the current and future research on UBEM, and more importantly, to inspire new and important questions from young researchers in the field.
Tianzhen Hong; Yixing Chen; Xuan Luo; Na Luo; Sang Hoon Lee. Ten questions on urban building energy modeling. Building and Environment 2019, 168, 106508 .
AMA StyleTianzhen Hong, Yixing Chen, Xuan Luo, Na Luo, Sang Hoon Lee. Ten questions on urban building energy modeling. Building and Environment. 2019; 168 ():106508.
Chicago/Turabian StyleTianzhen Hong; Yixing Chen; Xuan Luo; Na Luo; Sang Hoon Lee. 2019. "Ten questions on urban building energy modeling." Building and Environment 168, no. : 106508.
Urban building energy modeling (UBEM) is becoming a proven tool to support energy efficiency programs for buildings in cities. Development of a city-scale dataset of the existing building stock is a critical step of UBEM to automatically generate energy models of urban buildings and simulate their performance. This study introduces data needs, data standards, and data sources to develop city building datasets for UBEM. First, a literature review of data needs for UBEM was conducted. Then, the capabilities of the current data standards for city building datasets were reviewed. Moreover, the existing public data sources from several pioneer cites were studied to evaluate whether they are adequate to support UBEM. The results show that most cities have adequate public data to support UBEM; however, the data are represented in different formats without standardization, and there is a lack of common keys to make the data mapping easier. Finally, a case study is presented to integrate the diverse data sources from multiple city departments of San Francisco. The data mapping process is introduced and discussed. It is recommended to use the unique building identifiers as the common keys in the data sources to simplify the data mapping process. The integration methods and workflow are applied to other U.S. cities for developing the city-scale datasets of their existing building stock, including San Jose, Los Angeles, and Boston.
Yixing Chen; Tianzhen Hong; Xuan Luo; Barry Hooper. Development of city buildings dataset for urban building energy modeling. Energy and Buildings 2018, 183, 252 -265.
AMA StyleYixing Chen, Tianzhen Hong, Xuan Luo, Barry Hooper. Development of city buildings dataset for urban building energy modeling. Energy and Buildings. 2018; 183 ():252-265.
Chicago/Turabian StyleYixing Chen; Tianzhen Hong; Xuan Luo; Barry Hooper. 2018. "Development of city buildings dataset for urban building energy modeling." Energy and Buildings 183, no. : 252-265.
Urban-scale building energy modeling (UBEM)—using building modeling to understand how a group of buildings will perform together—is attracting increasing attention in the energy modeling field. Unlike modeling a single building, which will use detailed information, UBEM generally uses existing building stock data consisting of high-level building information. This study evaluated the impacts of three zoning methods and the use of floor multipliers on the simulated energy use of 940 office and retail buildings in three climate zones using City Building Energy Saver. The first zoning method, OneZone, creates one thermal zone per floor using the target building’s footprint. The second zoning method, AutoZone, splits the building’s footprint into perimeter and core zones. A novel, pixel-based automatic zoning algorithm is developed for the AutoZone method. The third zoning method, Prototype, uses the U.S. Department of Energy’s reference building prototype shapes. Results show that simulated source energy use of buildings with the floor multiplier are marginally higher by up to 2.6% than those modeling each floor explicitly, which take two to three times longer to run. Compared with the AutoZone method, the OneZone method results in decreased thermal loads and less equipment capacities: 15.2% smaller fan capacity, 11.1% smaller cooling capacity, 11.0% smaller heating capacity, 16.9% less heating loads, and 7.5% less cooling loads. Source energy use differences range from -7.6% to 5.1%. When comparing the Prototype method with the AutoZone method, source energy use differences range from -12.1% to 19.0%, and larger ranges of differences are found for the thermal loads and equipment capacities. This study demonstrated that zoning methods have a significant impact on the simulated energy use of UBEM. One recommendation resulting from this study is to use the AutoZone method with floor multiplier to obtain accurate results while balancing the simulation run time for UBEM.
Yixing Chen; Tianzhen Hong. Impacts of building geometry modeling methods on the simulation results of urban building energy models. Applied Energy 2018, 215, 717 -735.
AMA StyleYixing Chen, Tianzhen Hong. Impacts of building geometry modeling methods on the simulation results of urban building energy models. Applied Energy. 2018; 215 ():717-735.
Chicago/Turabian StyleYixing Chen; Tianzhen Hong. 2018. "Impacts of building geometry modeling methods on the simulation results of urban building energy models." Applied Energy 215, no. : 717-735.
Yixing Chen; Tianzhen Hong; Mary Ann Piette. Automatic generation and simulation of urban building energy models based on city datasets for city-scale building retrofit analysis. Applied Energy 2017, 205, 323 -335.
AMA StyleYixing Chen, Tianzhen Hong, Mary Ann Piette. Automatic generation and simulation of urban building energy models based on city datasets for city-scale building retrofit analysis. Applied Energy. 2017; 205 ():323-335.
Chicago/Turabian StyleYixing Chen; Tianzhen Hong; Mary Ann Piette. 2017. "Automatic generation and simulation of urban building energy models based on city datasets for city-scale building retrofit analysis." Applied Energy 205, no. : 323-335.
Xuan Luo; Tianzhen Hong; Yixing Chen; Mary Ann Piette. Electric load shape benchmarking for small- and medium-sized commercial buildings. Applied Energy 2017, 204, 715 -725.
AMA StyleXuan Luo, Tianzhen Hong, Yixing Chen, Mary Ann Piette. Electric load shape benchmarking for small- and medium-sized commercial buildings. Applied Energy. 2017; 204 ():715-725.
Chicago/Turabian StyleXuan Luo; Tianzhen Hong; Yixing Chen; Mary Ann Piette. 2017. "Electric load shape benchmarking for small- and medium-sized commercial buildings." Applied Energy 204, no. : 715-725.
Occupant behavior (OB) in buildings is a leading factor influencing energy use in buildings. Quantifying this influence requires the integration of OB models with building performance simulation (BPS). This study reviews approaches to representing and implementing OB models in today’s popular BPS programs, and discusses weaknesses and strengths of these approaches and key issues in integrating of OB models with BPS programs. Two key findings are: (1) a common data model is needed to standardize the representation of OB models, enabling their flexibility and exchange among BPS programs and user applications; the data model can be implemented using a standard syntax (e.g., in the form of XML schema), and (2) a modular software implementation of OB models, such as functional mock-up units for co-simulation, adopting the common data model, has advantages in providing a robust and interoperable integration with multiple BPS programs. Such common OB model representation and implementation approaches help standardize the input structures of OB models, enable collaborative development of a shared library of OB models, and allow for rapid and widespread integration of OB models with BPS programs to improve the simulation of occupant behavior and quantification of their impact on building performance.
Tianzhen Hong; Yixing Chen; Zsofia Belafi; Simona D’Oca. Occupant behavior models: A critical review of implementation and representation approaches in building performance simulation programs. Building Simulation 2017, 11, 1 -14.
AMA StyleTianzhen Hong, Yixing Chen, Zsofia Belafi, Simona D’Oca. Occupant behavior models: A critical review of implementation and representation approaches in building performance simulation programs. Building Simulation. 2017; 11 (1):1-14.
Chicago/Turabian StyleTianzhen Hong; Yixing Chen; Zsofia Belafi; Simona D’Oca. 2017. "Occupant behavior models: A critical review of implementation and representation approaches in building performance simulation programs." Building Simulation 11, no. 1: 1-14.
Occupancy has significant impacts on building performance. However, in current building performance simulation programs, occupancy inputs are static and lack diversity, contributing to discrepancies between the simulated and actual building performance. This paper presents an Occupancy Simulator that simulates the stochastic behavior of occupant presence and movement in buildings, capturing the spatial and temporal occupancy diversity. Each occupant and each space in the building are explicitly simulated as an agent with their profiles of stochastic behaviors. The occupancy behaviors are represented with three types of models: (1) the status transition events (e.g., first arrival in office) simulated with probability distribution model, (2) the random moving events (e.g., from one office to another) simulated with a homogeneous Markov chain model, and (3) the meeting events simulated with a new stochastic model. A hierarchical data model was developed for the Occupancy Simulator, which reduces the amount of data input by using the concepts of occupant types and space types. Finally, a case study of a small office building is presented to demonstrate the use of the Simulator to generate detailed annual sub-hourly occupant schedules for individual spaces and the whole building. The Simulator is a web application freely available to the public and capable of performing a detailed stochastic simulation of occupant presence and movement in buildings. Future work includes enhancements in the meeting event model, consideration of personal absent days, verification and validation of the simulated occupancy results, and expansion for use with residential buildings.
Yixing Chen; Tianzhen Hong; Xuan Luo. An agent-based stochastic Occupancy Simulator. Building Simulation 2017, 11, 37 -49.
AMA StyleYixing Chen, Tianzhen Hong, Xuan Luo. An agent-based stochastic Occupancy Simulator. Building Simulation. 2017; 11 (1):37-49.
Chicago/Turabian StyleYixing Chen; Tianzhen Hong; Xuan Luo. 2017. "An agent-based stochastic Occupancy Simulator." Building Simulation 11, no. 1: 37-49.
Xuan Luo; Khee Poh Lam; Yixing Chen; Tianzhen Hong. Performance evaluation of an agent-based occupancy simulation model. Building and Environment 2017, 115, 42 -53.
AMA StyleXuan Luo, Khee Poh Lam, Yixing Chen, Tianzhen Hong. Performance evaluation of an agent-based occupancy simulation model. Building and Environment. 2017; 115 ():42-53.
Chicago/Turabian StyleXuan Luo; Khee Poh Lam; Yixing Chen; Tianzhen Hong. 2017. "Performance evaluation of an agent-based occupancy simulation model." Building and Environment 115, no. : 42-53.
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.
Yixing Chen; Xin Liang; Tianzhen Hong; Xuan Luo. Simulation and visualization of energy-related occupant behavior in office buildings. Building Simulation 2017, 10, 785 -798.
AMA StyleYixing Chen, Xin Liang, Tianzhen Hong, Xuan Luo. Simulation and visualization of energy-related occupant behavior in office buildings. Building Simulation. 2017; 10 (6):785-798.
Chicago/Turabian StyleYixing Chen; Xin Liang; Tianzhen Hong; Xuan Luo. 2017. "Simulation and visualization of energy-related occupant behavior in office buildings." Building Simulation 10, no. 6: 785-798.
Tianzhen Hong; Hongsan Sun; Yixing Chen; Sarah C. Taylor-Lange; Da Yan. An occupant behavior modeling tool for co-simulation. Energy and Buildings 2016, 117, 272 -281.
AMA StyleTianzhen Hong, Hongsan Sun, Yixing Chen, Sarah C. Taylor-Lange, Da Yan. An occupant behavior modeling tool for co-simulation. Energy and Buildings. 2016; 117 ():272-281.
Chicago/Turabian StyleTianzhen Hong; Hongsan Sun; Yixing Chen; Sarah C. Taylor-Lange; Da Yan. 2016. "An occupant behavior modeling tool for co-simulation." Energy and Buildings 117, no. : 272-281.
This paper presents the energy performance of a personalized ventilation (PV) system with individual control of airflow rate in a hot and humid climate. A set of experiments with 46 tropically acclimatized subjects were conducted with ambient temperatures of 23 and 26 °C and PV air temperatures of 20, 23 and 26 °C. It has been found that as the ambient temperature is increased, subjects prefer higher PV airflow rates. While the higher ambient temperature reduces the cooling load, this is partly offset by the increased ventilation load. Therefore, it is not straightforward to quantify the energy savings accurately. In this work, an EnergyPlus simulation model was developed and validated by measurement data. The model was normalized to take into account the effects of the variations of outdoor conditions and the number of occupants. It was then applied to evaluate the energy performance of the PV system. The results show that when the PV air temperature is kept at 20 °C, the energy consumption at an ambient temperature of 23 °C is 10.8% higher than that at 26 °C. The best results are obtained when the PV air temperature is 20 °C and the ambient temperature is 26 °C. It is therefore concluded that increasing the ambient temperature has good potential to reduce energy consumption, whereas increasing the PV temperature does not bring appreciable benefits.
Yixing Chen; Benny Raphael; S.C. Sekhar. Experimental and simulated energy performance of a personalized ventilation system with individual airflow control in a hot and humid climate. Building and Environment 2016, 96, 283 -292.
AMA StyleYixing Chen, Benny Raphael, S.C. Sekhar. Experimental and simulated energy performance of a personalized ventilation system with individual airflow control in a hot and humid climate. Building and Environment. 2016; 96 ():283-292.
Chicago/Turabian StyleYixing Chen; Benny Raphael; S.C. Sekhar. 2016. "Experimental and simulated energy performance of a personalized ventilation system with individual airflow control in a hot and humid climate." Building and Environment 96, no. : 283-292.
Tianzhen Hong; Mary Ann Piette; Yixing Chen; Sang Hoon Lee; Sarah C. Taylor-Lange; Rongpeng Zhang; Kaiyu Sun; Phillip Price. Commercial Building Energy Saver: An energy retrofit analysis toolkit. Applied Energy 2015, 159, 298 -309.
AMA StyleTianzhen Hong, Mary Ann Piette, Yixing Chen, Sang Hoon Lee, Sarah C. Taylor-Lange, Rongpeng Zhang, Kaiyu Sun, Phillip Price. Commercial Building Energy Saver: An energy retrofit analysis toolkit. Applied Energy. 2015; 159 ():298-309.
Chicago/Turabian StyleTianzhen Hong; Mary Ann Piette; Yixing Chen; Sang Hoon Lee; Sarah C. Taylor-Lange; Rongpeng Zhang; Kaiyu Sun; Phillip Price. 2015. "Commercial Building Energy Saver: An energy retrofit analysis toolkit." Applied Energy 159, no. : 298-309.
Energy-related occupant behavior in buildings is difficult to define and quantify, yet critical to our understanding of total building energy consumption. Part I of this two-part paper introduced the DNAS (Drivers, Needs, Actions and Systems) framework, to standardize the description of energy-related occupant behavior in buildings. Part II of this paper implements the DNAS framework into an XML (eXtensible Markup Language) schema, titled 'occupant behavior XML' (obXML). The obXML schema is used for the practical implementation of the DNAS framework into building simulation tools. The topology of the DNAS framework implemented in the obXML schema has a main root element OccupantBehavior, linking three main elements representing Buildings, Occupants and Behaviors. Using the schema structure, the actions of turning on an air conditioner and closing blinds provide two examples of how the schema standardizes these actions using XML. The obXML schema has inherent flexibility to represent numerous, diverse and complex types of occupant behaviors in buildings, and it can also be expanded to encompass new types of behaviors. The implementation of the DNAS framework into the obXML schema will facilitate the development of occupant information modeling (OIM) by providing interoperability between occupant behavior models and building energy modeling programs. © 2015 Elsevier Lt
Tianzhen Hong; Simona D'Oca; Sarah C. Taylor-Lange; William J.N. Turner; Yixing Chen; Stefano P. Corgnati. An ontology to represent energy-related occupant behavior in buildings. Part II: Implementation of the DNAS framework using an XML schema. Building and Environment 2015, 94, 196 -205.
AMA StyleTianzhen Hong, Simona D'Oca, Sarah C. Taylor-Lange, William J.N. Turner, Yixing Chen, Stefano P. Corgnati. An ontology to represent energy-related occupant behavior in buildings. Part II: Implementation of the DNAS framework using an XML schema. Building and Environment. 2015; 94 ():196-205.
Chicago/Turabian StyleTianzhen Hong; Simona D'Oca; Sarah C. Taylor-Lange; William J.N. Turner; Yixing Chen; Stefano P. Corgnati. 2015. "An ontology to represent energy-related occupant behavior in buildings. Part II: Implementation of the DNAS framework using an XML schema." Building and Environment 94, no. : 196-205.