TY - JOUR T1 - A novel approach for selecting typical hot-year (THY) weather data JF - Applied Energy Y1 - 2019 A1 - Siyue Guo A1 - Da Yan A1 - Tianzhen Hong A1 - Chan Xiao A1 - Ying Cui KW - Actual weather data KW - dest KW - Heat wave KW - Multiyear simulation KW - Residential indoor thermal environment KW - Typical hot year AB -

The global climate change has resulted in not only warmer climate conditions but also more frequent extreme weather events, such as heat waves. However, the impact of heat waves on the indoor environment has been investigated in a limited manner. In this research, the indoor thermal environment is analyzed using a building performance simulation tool for a typical residential building in multiple cities in China, over a time period of 60 years using actual measured weather data, in order to gain a better understanding of the effect of heat wave events. The simulation results were used to analyze the indoor environment during hot summers. A new kind of weather data referred to as the typical hot year was defined and selected based on the simulated indoor environment during heat waves. The typical hot-year weather data can be used to simulate the indoor environment during extreme heat events and for the evaluation of effective technologies and strategies to mitigate against the impact of heat waves on the energy demand of buildings and human health. The limitations of the current study and future work are also discussed.

VL - 242 UR - https://linkinghub.elsevier.com/retrieve/pii/S0306261919304659 JO - Applied Energy ER - TY - JOUR T1 - Clustering and statistical analyses of air-conditioning intensity and use patterns in residential buildings JF - Energy and Buildings Y1 - 2018 A1 - Jingjing An A1 - Da Yan A1 - Tianzhen Hong KW - AC usage benchmarking KW - Air-conditioning KW - Clustering analysis KW - KPIs KW - residential building KW - Use pattern AB -

Energy conservation in residential buildings has gained increased attention due to its large portion of global energy use and potential of energy savings. Occupant behavior has been recognized as a key factor influencing the energy use and load diversity in buildings, therefore more realistic and accurate air-conditioning (AC) operating schedules are imperative for load estimation in equipment design and operation optimization. With the development of sensor technology, it became easier to access an increasing amount of heating/cooling data from thermal energy metering systems in residential buildings, which provides another possible way to understand building energy usage and occupant behaviors. However, except for cooling energy consumption benchmarking, there currently lacks effective and easy approaches to analyze AC usage and provide actionable insights for occupants. To fill this gap, this study proposes clustering analysis to identify AC use patterns of residential buildings, and develops new key performance indicators (KPIs) and data analytics to explore the AC operation characteristics using the long-term metered cooling energy use data, which is of great importance for inhabitants to understand their thermal energy use and save energy cost through adjustment of their AC use behavior. We demonstrate the proposed approaches in a residential district comprising 300 apartments, located in Zhengzhou, China. Main outcomes include: Representative AC use patterns are developed for three room types of residential buildings in the cold climate zone of China, which can be used as more realistic AC schedules to improve accuracy of energy simulation; Distributions of KPIs on household cooling energy usage are established, which can be used for household AC use intensity benchmarking and performance diagnoses.

VL - 174 UR - https://linkinghub.elsevier.com/retrieve/pii/S0378778818307199https://api.elsevier.com/content/article/PII:S0378778818307199?httpAccept=text/xmlhttps://api.elsevier.com/content/article/PII:S0378778818307199?httpAccept=text/plain JO - Energy and Buildings ER - TY - JOUR T1 - Comparative Study of Air-Conditioning Energy Use of Four Office Buildings in China and USA JF - Energy and Buildings Y1 - 2018 A1 - Xin Zhou A1 - Da Yan A1 - Jingjing An A1 - Tianzhen Hong A1 - Xing Shi A1 - Xing Jin KW - Building envelope KW - climate KW - energy consumption KW - occupant behavior KW - office buildings KW - technological choice AB -

Energy use in buildings has great variability. In order to design and operate low energy buildings as well as to establish building energy codes and standards and effective energy policy, it is crucial to understand and quantify key factors influencing building energy performance. This study investigates air-conditioning (AC) energy use of four office buildings in four locations: Beijing, Taiwan, Hong Kong, and Berkeley. Building simulation was employed to quantify the influences of key factors, including climate, building envelope and occupant behavior. Through simulation of various combinations of the three influencing elements, it is found that climate can lead to AC cooling consumption differences by almost two times, while occupant behavior resulted in the greatest differences (of up to three times) in AC cooling consumption. The influence of occupant behavior on AC energy consumption is not homogeneous. Under similar climates, when the occupant behavior in the building differed, the optimized building envelope design also differed. Overall, the optimal building envelope should be determined according to the climate as well as the occupants who use the building.

VL - 169 ER - TY - JOUR T1 - Comparison of typical year and multiyear building simulations using a 55-year actual weather data set from China JF - Applied Energy Y1 - 2017 A1 - Ying Cui A1 - Da Yan A1 - Tianzhen Hong A1 - Chan Xiao A1 - Xuan Luo A1 - Qi Zhang KW - Actual weather data KW - building simulation KW - energy use KW - Multiyear simulation KW - Peak load   KW - Typical year AB -

Weather has significant impacts on the thermal environment and energy use in buildings. Thus, accurate weather data are crucial for building performance evaluations. Traditionally, typical year data inputs are used to represent long-term weather data. However, there is no guarantee that a single year represents the changing climate well. In this study, the long-term representation of a typical year was assessed by comparing it to a 55-year actual weather data set. To investigate the weather impact on building energy use, 559 simulation runs of a prototype office building were performed for 10 large cities covering all climate zones in China. The analysis results demonstrated that the weather data varied significantly from year to year. Hence, a typical year cannot reflect the variation range of weather fluctuations. Typical year simulations overestimated or underestimated the energy use and peak load in many cases. With the increase in computational power of personal computers, it is feasible and essential to adopt multiyear simulations for full assessments of long-term building performance, as this will improve decision-making by allowing for the full consideration of variations in building energy use.

VL - 195 ER - TY - JOUR T1 - IEA EBC Annex 66: Definition and simulation of occupant behavior in buildings JF - Energy and Building Y1 - 2017 A1 - Da Yan A1 - Tianzhen Hong A1 - Bing Dong A1 - Ardeshir Mahdavi A1 - Simona D'Oca A1 - Isabella Gaetani A1 - Xiaohang Feng KW - building performance KW - energy modeling KW - energy use KW - IEA EBC Annex 66 KW - Interdisciplinary approach KW - occupant behavior AB -

More than 30% of the total primary energy in the world is consumed in buildings. It is crucial to reduce building energy consumption in order to preserve energy resources and mitigate global climate change. Building performance simulations have been widely used for the estimation and optimization of building performance, providing reference values for the assessment of building energy consumption and the effects of energy-saving technologies. Among the various factors influencing building energy consumption, occupant behavior has drawn increasing attention. Occupant behavior includes occupant presence, movement, and interaction with building energy devices and systems. However, there are gaps in occupant behavior modeling as different energy modelers have employed varied data and tools to simulate occupant behavior, therefore producing different and incomparable results. Aiming to address these gaps, the International Energy Agency (IEA) Energy in Buildings and Community (EBC) Programme Annex 66 has established a scientific methodological framework for occupant behavior research, including data collection, behavior model representation, modeling and evaluation approaches, and the integration of behavior modeling tools with building performance simulation programs. Annex 66 also includes case studies and application guidelines to assist in building design, operation, and policymaking, using interdisciplinary approaches to reduce energy use in buildings and improve occupant comfort and productivity. This paper highlights the key research issues, methods, and outcomes pertaining to Annex 66, and offers perspectives on future research needs to integrate occupant behavior with the building life cycle.

VL - 156 ER - TY - RPRT T1 - A Novel Stochastic Modeling Method to Simulate Cooling Loads in Residential Districts Y1 - 2017 A1 - Jingjing An A1 - Da Yan A1 - Tianzhen Hong A1 - Kaiyu Sun AB -

District cooling systems are widely used in urban residential communities in China. Most district cooling systems are oversized;this leads to wasted investment and low operational efficiency and thus energy wastage. The accurate prediction of district cooling loads that supports rightsizing cooling plant equipment remains a challenge. This study developed a new stochastic modeling method that includes (1) six prototype house models representing a majority of apartments in the district, (2)occupant behavior models in residential buildings reflecting the temporal and spatial diversity and complexity based on a large-scale residential survey in China, and (3) a stochastic sampling process to represent all apartments and occupants in the district. The stochastic method was employed in a case study using the DeST simulation engine to simulate the cooling loads of a real residential district in Wuhan, China. The simulation results agree well with the actual measurement data based on five performance metrics representing the aggregated cooling loads, the peak cooling loads as well as the spatial load distribution,and the load profiles. Two currently used simulation methods were also employed to simulate the district cooling loads. The simulation results showed that oversimplified occupant behavior assumptions lead to significant overestimations of the peak cooling load and total district cooling loads. Future work will aim to simplify the workflow and data requirements of the stochastic method to enable its practical application as well as explore its application in predicting district heating loads and in commercial or mixed-use districts.

ER - TY - JOUR T1 - Spatial Distribution of Internal Heat Gains: A Probabilistic Representation and Evaluation of Its Influence on Cooling Equipment Sizing in Large Office Buildings JF - Energy and Buildings Y1 - 2017 A1 - Qi Zhang A1 - Da Yan A1 - Jingjing An A1 - Tianzhen Hong A1 - Wei Tian A1 - Kaiyu Sun KW - air handling unit KW - chiller plant KW - equipment sizing KW - internal heat gain KW - spatial distribution KW - spatial diversity KW - stochastic AB -

Internal heat gains from occupants, lighting, and plug loads are significant components of the space cooling load in an office building. Internal heat gains vary with time and space. The spatial diversity is significant, even for spaces with the same function in the same building. The stochastic nature of internal heat gains makes determining the peak cooling load to size air-conditioning systems a challenge. The traditional conservative practice of considering the largest internal heat gain among spaces and applying safety factors overestimates the space cooling load, which leads to oversized air-conditioning equipment and chiller plants. In this study, a field investigation of several large office buildings in China led to the development of a new probabilistic approach that represents the spatial diversity of the design internal heat gain of each tenant as a probability distribution function. In a large office building, a central chiller plant serves all air handling units (AHUs), with each AHU serving one or more floors of the building. Therefore, the spatial diversity should be considered differently when the peak cooling loads to size the AHUs and chillers are calculated. The proposed approach considers two different levels of internal heat gains to calculate the peak cooling loads and size the AHUs and chillers in order to avoid oversizing, improve the overall operating efficiency, and thus reduce energy use.

ER - TY - RPRT T1 - Temporal and spatial characteristics of the urban heat island in Beijing and the impact on building design and energy performance Y1 - 2017 A1 - Ying Cui A1 - Da Yan A1 - Tianzhen Hong A1 - Jingjin Ma KW - beijing KW - building design KW - Microclimate KW - Temporal and spatial characteristics KW - urban heat island AB -

With the increased urbanization in most countries worldwide, the urban heat island (UHI) effect, referring to the phenomenon that an urban area has higher ambient temperature than the surrounding rural area, has gained much attention in recent years. Given that Beijing is developing rapidly both in urban population and economically, the UHI effect can be significant. A long-term measured weather dataset from 1961 to 2014 for ten rural stations and seven urban stations in Beijing, was analyzed in this study, to understand the detailed temporal and spatial characteristics of the UHI in Beijing. The UHI effect in Beijing is significant, with an urban-to-rural temperature difference of up to 8℃ during the winter nighttime. Furthermore, the impacts of UHIs on building design and energy performance were also investigated. The UHI in Beijing led to an approximately 11% increase in cooling load and 16% decrease in heating load in the urban area compared with the rural area, whereas the urban heating peak load decreased 9% and the cooling peak load increased 7% because of the UHI effect. This study provides insights into the UHI in Beijing and recommendations to improve building design and decision-making while considering the urban microclimate.

ER - TY - JOUR T1 - Ten Questions Concerning Occupant Behavior in Buildings: The Big Picture JF - Building and Environment Y1 - 2017 A1 - Tianzhen Hong A1 - Da Yan A1 - Simona D'Oca A1 - Chien-Fei Chen KW - Behavior Modeling KW - building performance KW - building simulation KW - energy use KW - interdisciplinary KW - occupant behavior AB -

Occupant behavior has significant impacts on building energy performance and occupant comfort. However, occupant behavior is not well understood and is often oversimplified in the building life cycle, due to its stochastic, diverse, complex, and interdisciplinary nature. The use of simplified methods or tools to quantify the impacts of occupant behavior in building performance simulations significantly contributes to performance gaps between simulated models and actual building energy consumption. Therefore, it is crucial to understand occupant behavior in a comprehensive way, integrating qualitative approaches and data- and model-driven quantitative approaches, and employing appropriate tools to guide the design and operation of low-energy residential and commercial buildings that integrate technological and human dimensions. This paper presents ten questions, highlighting some of the most important issues regarding concepts, applications, and methodologies in occupant behavior research. The proposed questions and answers aim to provide insights into occupant behavior for current and future researchers, designers, and policy makers, and most importantly, to inspire innovative research and applications to increase energy efficiency and reduce energy use in buildings.

 

ER - TY - JOUR T1 - A Thorough Assessment of China’s Standard for Energy Consumption of Buildings JF - Energy and Buildings Y1 - 2017 A1 - Da Yan A1 - Tianzhen Hong A1 - Cheng Li A1 - Qi Zhang A1 - Jingjing An A1 - shan Hu KW - China KW - code and standard KW - energy consumption KW - energy efficiency KW - Energy Use Intensity KW - outcome-based code AB -

China’s Design Standard for Energy Efficiency of Public Buildings (the Design Standard) is widely used in the design phase to regulate the energy efficiency of physical assets (envelope, lighting, HVAC) in buildings. However, the standard does not consider many important factors that influence the actual energy use in buildings, and this can lead to gaps between the design estimates and actual energy consumption. To achieve the national energy savings targets defined in the strategic 12th Five-Year Plan, China developed the first standard for energy consumption of buildings GB/T51161-2016 (the Consumption Standard). This study provides an overview of the Consumption Standard, identifies its strengths and weaknesses, and recommends future improvements. The analysis and discussion of the constraint value and the leading value, two key indicators of the energy use intensity, provide insight into the intent and effectiveness of the Consumption Standard. The results indicated that consistency between China’s Design Standard GB 50189-2015 and the Consumption Standard GB/T51161-2016 could be achieved if the Design Standard used the actual building operations and occupant behavior in calculating the energy use in Chinese buildings. The development of an outcome-based code in the U.S. was discussed in comparison with China’s Consumption Standard, and this revealed the strengths and challenges associated with implementing a new compliance method based on actual energy use in buildings in the U.S. Overall, this study provides important insights into the latest developments of actual consumption-based building energy standards, and this information should be valuable to building designers and energy policy makers in China and the U.S.

ER - TY - JOUR T1 - Advances in research and applications of energy-related occupant behavior in buildings JF - Energy and Buildings Y1 - 2016 A1 - Tianzhen Hong A1 - Sarah C. Taylor-Lange A1 - Simona D'Oca A1 - Da Yan A1 - Stefano P. Corgnati KW - Behavior Modeling KW - Building design and operation KW - building performance simulation KW - energy use KW - occupant behavior AB -

Occupant behavior is one of the major factors influencing building energy consumption and contributing to uncertainty in building energy use prediction and simulation. Currently the understanding of occupant behavior is insufficient both in building design, operation and retrofit, leading to incorrect simplifications in modeling and analysis. This paper introduced the most recent advances and current obstacles in modeling occupant behavior and quantifying its impact on building energy use. The major themes include advancements in data collection techniques, analytical and modeling methods, and simulation applications which provide insights into behavior energy savings potential and impact. There has been growing research and applications in this field, but significant challenges and opportunities still lie ahead.

VL - 116 U2 - LBNL-1004497 ER - TY - JOUR T1 - A Comparative Study on Energy Performance of Variable Refrigerant Flow Systems and Variable Air Volume Systems in Office Buildings JF - Applied Energy Y1 - 2016 A1 - Xinqiao Yu A1 - Da Yan A1 - Kaiyu Sun A1 - Tianzhen Hong A1 - Dandan Zhu KW - building simulation KW - comparative analysis KW - energy performance KW - field measurement KW - Variable Air Volume (VAV) Systems KW - Variable Refrigerant Flow (VRF) Systems AB -

Variable air volume (VAV) systems and variable refrigerant flow (VRF) systems are popularly used in office buildings. This study investigated VAV and VRF systems in five typical office buildings in China, and compared their air conditioning energy use. Site survey and field measurements were conducted to collect data of building characteristics and operation. Measured cooling electricity use was collected from sub-metering in the five buildings. The sub-metering data, normalized by climate and operating hours, show that VRF systems consumed much less air conditioning energy by up to 70% than VAV systems. This is mainly due to the different operation modes of both system types leading to much fewer operating hours of the VRF systems. Building simulation was used to quantify the impact of operation modes of VRF and VAV systems on cooling loads using a prototype office building in China. Simulated results show the VRF operation mode leads to much less cooling loads than the VAV operation mode, by 42% in Hong Kong and 53% in Qingdao. The VRF systems operated in the part-time-part-space mode enabling occupants to turn on air-conditioning only when needed and when spaces were occupied, while the VAV systems operated in the full-time-full-space mode limiting occupants’ control of operation. The findings provide insights into VRF systems operation and controls as well as its energy performance, which can inform HVAC designers on system selection and building operators or facility managers on improving VRF system operations.    


 

 

ER - TY - JOUR T1 - Data Analysis and Stochastic Modeling of Lighting Energy Use in Large Office Buildings in China JF - Energy and Buildings Y1 - 2015 A1 - Xin Zhou A1 - Da Yan A1 - Tianzhen Hong A1 - Xiaoxin Ren KW - building simulation KW - energy use KW - Lighting modeling KW - occupant behavior KW - office buildings KW - Poisson distribution KW - stochastic modeling AB -

Lighting consumes about 20% to 40% of the total electricity use in large office buildings in China. Commonly in building simulations, static time schedules for typical weekdays, weekends and holidays are assumed to represent the dynamics of lighting energy use in buildings. This approach does not address the stochastic nature of lighting energy use, which can be influenced by occupant behavior in buildings. This study analyzes the main characteristics of lighting energy use over various timescales, based on the statistical analysis of measured lighting energy use data from 15 large office buildings in Beijing and Hong Kong. It was found that in these large office buildings, the 24-hourly variation in lighting energy use was mainly driven by the schedules of the building occupants. Outdoor illuminance levels had little impact on lighting energy use due to the lack of automatic daylighting controls (an effective retrofit measure to reduce lighting energy use) and the relatively small perimeter area exposed to natural daylight. A stochastic lighting energy use model for large office buildings was further developed to represent diverse occupant activities, at six different time periods throughout a day, and also the annual distribution of lighting power across these periods. The model was verified using measured lighting energy use from the 15 buildings. The developed stochastic lighting model can generate more accurate lighting schedules for use in building energy simulations, improving the simulation accuracy of lighting energy use in real buildings.

VL - 86 U2 - LBNL-180389 ER - TY - JOUR T1 - Data Mining of Space Heating System Performance in Affordable Housing JF - Building and Environment Y1 - 2015 A1 - Xiaoxin Ren A1 - Da Yan A1 - Tianzhen Hong KW - affordable housing KW - building simulation KW - clustering KW - data mining KW - decision tree KW - occupant behavior KW - space heating AB -

The space heating in residential buildings accounts for a considerable amount of the primary energy use. Therefore, understanding the operation and performance of space heating systems becomes crucial in improving occupant comfort while reducing energy use. This study investigated the behavior of occupants adjusting their thermostat settings and heating system operations in a 62-unit affordable housing complex in Revere, Massachusetts, USA. The data mining methods, including clustering approach and decision trees, were used to ascertain occupant behavior patterns. Data tabulating ON/OFF space heating states was assessed, to provide a better understanding of the intermittent operation of space heating systems in terms of system cycling frequency and the duration of each operation. The decision tree was used to verify the link between room temperature settings, house and heating system characteristics and the heating energy use. The results suggest that the majority of apartments show fairly constant room temperature profiles with limited variations during a day or between weekday and weekend. Data clustering results revealed six typical patterns of room temperature profiles during the heating season. Space heating systems cycled more frequently than anticipated due to a tight range of room thermostat settings and potentially oversized heating capacities. The results from this study affirm data mining techniques are an effective method to analyze large datasets and extract hidden patterns to inform design and improve operations.

VL - 89 U2 - LBNL-180239 ER - TY - JOUR T1 - An Insight into Actual Energy Use and Its Drivers in High-Performance Buildings Y1 - 2015 A1 - Cheng Li A1 - Tianzhen Hong A1 - Da Yan KW - actual energy use KW - building technologies KW - driving factors KW - high-performance buildings KW - integrated design KW - performance rating AB -

Using portfolio analysis and individual detailed case studies, we studied the energy performance and drivers of energy use in 51 high-performance office buildings in the U.S., Europe, China, and other parts of Asia. Portfolio analyses revealed that actual site energy use intensity (EUI) of the study buildings varied by a factor of as much as 11, indicating significant variation in real energy use in HPBs worldwide. Nearly half of the buildings did not meet the American Society of Heating, Refrigerating, and Air Conditioning Engineers (ASHRAE) Standard 90.1-2004 energy target, raising questions about whether a building’s certification as high performing accurately indicates that a building is energy efficient and suggesting that improvement in the design and operation of HPBs is needed to realize their energy-saving potential. We studied the influence of climate, building size, and building technologies on building energy performance and found that although all are important, none are decisive factors in building energy use. EUIs were widely scattered in all climate zones. There was a trend toward low energy use in small buildings, but the correlation was not absolute; some small HPBs exhibited high energy use, and some large HPBs exhibited low energy use. We were unable to identify a set of efficient technologies that correlated directly to low EUIs. In two case studies, we investigated the influence of occupant behavior as well as operation and maintenance on energy performance and found that both play significant roles in realizing energy savings. We conclude that no single factor determines the actual energy performance of HPBs, and adding multiple efficient technologies does not necessarily improve building energy performance; therefore, an integrated design approach that takes account of climate, technology, occupant behavior, and operations and maintenance practices should be implemented to maximize energy savings in HPBs. These findings are intended to help architects, engineers, operators, and policy makers improve the design and operation of HPBs.

U2 - LBNL-180169 ER - TY - JOUR T1 - Occupant Behavior Modeling for Building Performance Simulation: Current State and Future Challenges JF - Energy and Buildings Y1 - 2015 A1 - Da Yan A1 - William O'Brien A1 - Tianzhen Hong A1 - Xiaohang Feng A1 - H. Burak Gunay A1 - Farhang Tahmasebi A1 - Ardeshir Mahdavi KW - building simulation KW - energy efficiency KW - energy modeling KW - energy use KW - occupant behavior AB -

Occupant behavior is now widely recognized as a major contributing factor to uncertainty of building performance. While a surge of research on the topic has occurred over the past four decades, and particularly the past few years, there are many gaps in knowledge and limitations to current methodologies. This paper outlines the state-of-the-art research, current obstacles and future needs and directions for the following four-step iterative process: (1) occupant monitoring and data collection, (2) model development, (3) model evaluation, and (4) model implementation into building simulation tools. Major themes include the need for greater rigor in experimental methodologies; detailed, honest, and candid reporting of methods and results; and development of an efficient means to implement occupant behavior models and integrate them into building energy modeling programs.

VL - 107 U2 - LBNL-1004504 ER - TY - JOUR T1 - Simulation of Occupancy in Buildings JF - Energy and Buildings Y1 - 2015 A1 - Xiaohang Feng A1 - Da Yan A1 - Tianzhen Hong KW - building simulation KW - co-simulation KW - occupancy KW - occupant behavior KW - software module KW - stochastic modeling AB -

Occupants are involved in a variety of activities in buildings, which drive them to move among rooms, enter or leave a building. In this study, occupancy is defined at four levels and varies with time: (1) the number of occupants in a building, (2) occupancy status of a space, (3) the number of occupants in a space, and (4) the space location of an occupant. Occupancy has a great influence on internal loads and ventilation requirement, thus building energy consumption. Based on a comprehensive review and comparison of literature on occupancy modeling, three representative occupancy models, corresponding to the levels 2–4, are selected and implemented in a software module. Main contributions of our study include: (1) new methods to classify occupancy models, (2) the review and selection of various levels of occupancy models, and (3) new methods to integrate these model into a tool that can be used in different ways for different applications and by different audiences. The software can simulate more detailed occupancy in buildings to improve the simulation of energy use, and better evaluate building technologies in buildings. The occupancy of an office building is simulated as an example to demonstrate the use of the software module.

VL - 87 U2 - LBNL-180424 ER - TY - JOUR T1 - Updates to the China Design Standard for Energy Efficiency in Public Buildings JF - Energy Policy Y1 - 2015 A1 - Tianzhen Hong A1 - Cheng Li A1 - Da Yan KW - building design KW - building energy standard KW - China KW - energy efficiency KW - GB 50189 KW - Public buildings AB -

The China Design Standard for Energy Efficiency in public buildings (GB 50189) debuted in 2005 when China completed the 10th Five-Year Plan. GB 50189-2005 played a crucial role in regulating the energy efficiency in Chinese commercial buildings. The standard was recently updated in 2014 to increase energy savings targets by 30% compared with the 2005 standard. This paper reviews the major changes to the standard, including expansion of energy efficiency coverage and more stringent efficiency requirements. The paper also discusses the interrelationship of the design standard with China's other building energy standards. Furthermore, comparisons are made with ASHRAE Standard 90.1-2013 to provide contrasting differences in efficiency requirements. Finally recommendations are provided to guide the future standard revision, focusing on three areas: (1) increasing efficiency requirements of building envelope and HVAC systems, (2) adding a whole-building performance compliance pathway and implementing a ruleset based automatic code baseline model generation in an effort to reduce the discrepancies of baseline models created by different tools and users, and (3) adding inspection and commissioning requirements to ensure building equipment and systems are installed correctly and operate as designed.

VL - 87 U2 - LBNL-1004493 ER - TY - JOUR T1 - Integrated Design for High Performance Buildings Y1 - 2014 A1 - Tianzhen Hong A1 - Cheng Li A1 - Richard C. Diamond A1 - Da Yan A1 - Qi Zhang A1 - Xin Zhou A1 - Siyue Guo A1 - Kaiyu Sun A1 - Jingyi Wang U2 - LBNL-6991E ER - TY - JOUR T1 - Building energy modeling programs comparison Research on HVAC systems simulation part Y1 - 2013 A1 - Xin Zhou A1 - Da Yan A1 - Tianzhen Hong A1 - Dandan Zhu KW - Building energy modeling programs KW - comparison tests KW - HVAC system simulation KW - theory analysis AB -

Building energy simulation programs are effective tools for the evaluation of building energy saving and optimization of design. The fact that large discrepancies exist in simulated results when different BEMPs are used to model the same building has caused wide concern. Urgent research is needed to identify the main elements that contribute towards the simulation results. This technical report summarizes methodologies, processes, and the main assumptions of three building energy modeling programs (BEMPs) for HVAC calculations: EnergyPlus, DeST, and DOE-2.1E, and test cases are designed to analyze the calculation process in detail. This will help users to get a better understanding of BEMPs and the research methodology of building simulation. This will also help build a foundation for building energy code development and energy labeling programs.

ER - TY - RPRT T1 - Comparison of Building Energy Modeling Programs: HVAC Systems Y1 - 2013 A1 - Xin Zhou A1 - Tianzhen Hong A1 - Da Yan U2 - LBNL-6432E ER - TY - RPRT T1 - Data Analysis and Modeling of Lighting Energy Use in Large Office Buildings Y1 - 2013 A1 - Xin Zhou A1 - Da Yan A1 - Xiaoxin Ren A1 - Tianzhen Hong KW - building simulation KW - energy use KW - lighting KW - modeling KW - occupant behavior KW - office buildings KW - Poisson distribution AB -

Lighting consumes about 20 to 40% of total electricity use in large office buildings in the U.S. and China. In order to develop better lighting simulation models it is crucial to understand the characteristics of lighting energy use. This paper analyzes the main characteristics of lighting energy use over various time scales, based on the statistical analysis of measured lighting energy use of 17 large office buildings in Beijing and Hong Kong. It was found that the daily 24-hour variations of lighting energy use were mainly driven by the schedule of the building occupants. Outdoor illumination levels have little impact on lighting energy use in large office buildings due to the lack of automatic daylighting controls and relatively small perimeter areas. A stochastic lighting energy use model was developed based on different occupant activities during six time periods throughout a day, and the annual distribution of lighting power across those periods. The model was verified using measured lighting energy use of one selected building. This study demonstrates how statistical analysis and stochastic modeling can be applied to lighting energy use. The developed lighting model can be adopted by building energy modeling programs to improve the simulation accuracy of lighting energy use.

ER - TY - JOUR T1 - A Detailed Loads Comparison of Three Building Energy Modeling Programs: EnergyPlus, DeST and DOE-2.1E JF - Building Simulation Y1 - 2013 A1 - Dandan Zhu A1 - Tianzhen Hong A1 - Da Yan A1 - Chuang Wang KW - building energy modeling program KW - building thermal loads KW - comparison KW - dest KW - DOE-2.1E KW - energyplus AB -

Building energy simulation is widely used to help design energy efficient building envelopes and HVAC systems, develop and demonstrate compliance of building energy codes, and implement building energy rating programs. However, large discrepancies exist between simulation results from different building energy modeling programs (BEMPs). This leads many users and stakeholders to lack confidence in the results from BEMPs and building simulation methods. This paper compared the building thermal load modeling capabilities and simulation results of three BEMPs: EnergyPlus, DeST and DOE-2.1E. Test cases, based upon the ASHRAE Standard 140 tests, were designed to isolate and evaluate the key influencing factors responsible for the discrepancies in results between EnergyPlus and DeST. This included the load algorithms and some of the default input parameters. It was concluded that there is little difference between the results from EnergyPlus and DeST if the input values are the same or equivalent despite there being many discrepancies between the heat balance algorithms. DOE-2.1E can produce large errors for cases when adjacent zones have very different conditions, or if a zone is conditioned part-time while adjacent zones are unconditioned. This was due to the lack of a strict zonal heat balance routine in DOE-2.1E, and the steady state handling of heat flow through interior walls and partitions. This comparison study did not produce another test suite, but rather a methodology to design tests that can be used to identify and isolate key influencing factors that drive the building thermal loads, and a process with which to carry them out.

PB - Tsinghua University Press VL - 6 IS - 3 ER - TY - CONF T1 - Comparative research in building energy modeling programs T2 - China Annual HVACR Conference Y1 - 2012 A1 - Dandan Zhu A1 - Tianzhen Hong A1 - Da Yan A1 - Chuang Wang KW - advanced building software: energyplus KW - building energy modeling program KW - building simulation KW - comparison KW - dest KW - doe-2 KW - energyplus KW - simulation research group KW - test JF - China Annual HVACR Conference CY - China (in Chinese) ER - TY - CONF T1 - A Comparison of DeST and EnergyPlus T2 - China HVAC Simulation Conference Y1 - 2011 A1 - Dandan Zhu A1 - Chuang Wang A1 - Da Yan A1 - Tianzhen Hong KW - building simulation KW - comparison KW - dest KW - energy modeling KW - energyplus KW - simulation research KW - simulation research group KW - test cases JF - China HVAC Simulation Conference CY - Beijing ER -