@article {32166, title = {Ten questions on urban building energy modeling}, journal = {Building and Environment}, volume = {168}, year = {2020}, month = {Jan-01-2020}, pages = {106508}, abstract = {

Buildings in cities consume up to 70\% of all primary energy. To achieve cities{\textquoteright} 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.

}, issn = {03601323}, doi = {10.1016/j.buildenv.2019.106508}, author = {Tianzhen Hong and Chen, Yixing and Luo, Xuan and Luo, Na and Lee, Sang Hoon} } @article {31305, title = {Translating climate change and heating system electrification impacts on building energy use to future greenhouse gas emissions and electric grid capacity requirements in California}, journal = {Applied Energy}, volume = {225}, year = {2018}, month = {09/2018}, pages = {522 - 534}, abstract = {

Climate change and increased electrification of space and water heating in buildings can significantly affect future electricity demand and hourly demand profiles, which has implications for electric grid greenhouse gas emissions and capacity requirements. We use EnergyPlus to quantify building energy demand under historical and under several climate change projections of 32 kinds of building prototypes in 16 different climate zones of California and imposed these impacts on a year 2050 electric grid configuration by simulation in the Holistic Grid Resource Integration and Deployment (HIGRID) model. We find that climate change only prompted modest increases in grid resource capacity and negligible difference in greenhouse gas emissions since the additional electric load generally occurred during times with available renewable generation. Heating electrification, however, prompted a 30{\textendash}40\% reduction in greenhouse gas emissions but required significant grid resource capacity increases, due to the higher magnitude of load increases and lack of readily available renewable generation during the times when electrified heating loads occurred. Overall, this study translates climate change and electrification impacts to system-wide endpoint impacts on future electric grid configurations and highlights the complexities associated with translating building-level impacts to electric system-wide impacts.

}, keywords = {Building Energy Demand, Climate Change Impacts, electric grid, Heating Electrification Effects}, issn = {03062619}, doi = {10.1016/j.apenergy.2018.05.003}, url = {https://linkinghub.elsevier.com/retrieve/pii/S0306261918306962https://api.elsevier.com/content/article/PII:S0306261918306962?httpAccept=text/xmlhttps://api.elsevier.com/content/article/PII:S0306261918306962?httpAccept=text/plain}, author = {Brian Tarroja and Felicia Chiang and Amir AghaKouchak and Scott Samuelsen and Shuba V. Raghavan and Max Wei and Kaiyu Sun and Tianzhen Hong} } @article {30032, title = {Temporal and spatial characteristics of the urban heat island in Beijing and the impact on building design and energy performance}, year = {2017}, abstract = {

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{\textcelsius} 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.

}, keywords = {beijing, building design, Microclimate, Temporal and spatial characteristics, urban heat island}, author = {Ying Cui and Da Yan and Tianzhen Hong and Jingjin Ma} } @article {30315, title = {Ten Questions Concerning Occupant Behavior in Buildings: The Big Picture}, journal = {Building and Environment}, year = {2017}, abstract = {

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.

}, keywords = {Behavior Modeling, building performance, building simulation, energy use, interdisciplinary, occupant behavior}, author = {Tianzhen Hong and Da Yan and Simona D{\textquoteright}Oca and Chien-Fei Chen} } @article {30303, title = {A Thorough Assessment of China{\textquoteright}s Standard for Energy Consumption of Buildings}, journal = {Energy and Buildings}, year = {2017}, month = {03/2017}, abstract = {

China{\textquoteright}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{\textquoteright}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{\textquoteright}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.

}, keywords = {China, code and standard, energy consumption, energy efficiency, Energy Use Intensity, outcome-based code}, doi = {10.1016/j.enbuild.2017.03.019}, author = {Da Yan and Tianzhen Hong and Cheng Li and Qi Zhang and Jingjing An and shan Hu} } @conference {30147, title = {A Tale of Three District Energy Systems: Metrics and Future Opportunities}, booktitle = {2016 ACEEE Summer Study on Energy Efficiency in Buildings}, year = {2016}, month = {08/2017}, abstract = {

Improving the sustainability of cities is crucial for meeting climate goals in the next several decades. One way this is being tackled is through innovation in district energy systems, which can take advantage of local resources and economies of scale to improve the performance of whole neighborhoods in ways infeasible for individual buildings. These systems vary in physical size, end use services, primary energy resources, and sophistication of control. They also vary enormously in their choice of optimization metrics while all under the umbrella-goal of improved sustainability.

This paper explores the implications of choice of metric on district energy systems using three case studies: Stanford University, the University of California at Merced, and the Richmond Bay campus of the University of California at Berkeley. They each have a centralized authority to implement large-scale projects quickly, while maintaining data records, which makes them relatively effective at achieving their respective goals. Comparing the systems using several common energy metrics reveals significant differences in relative system merit. Additionally, a novel bidirectional heating and cooling system is presented. This system is highly energy-efficient, and while more analysis is required, may be the basis of the next generation of district energy systems

}, author = {Rebecca Zarin Pass and Michael Wetter and Mary Ann Piette} } @article {59963, title = {A Technical Framework to Describe Occupant Behavior for Building Energy Simulations}, year = {2014}, abstract = {

Green buildings that fail to meet expected design performance criteria indicate that technology alone does not guarantee high performance. Human influences are quite often simplified and ignored in the design, construction, and operation of buildings. Energy-conscious human behavior has been demonstrated to be a significant positive factor for improving the indoor environment while reducing the energy use of buildings. In our study we developed a new technical framework to describe energy-related human behavior in buildings. The energy-related behavior includes accounting for individuals and groups of occupants and their interactions with building energy services systems, appliances and facilities. The technical framework consists of four key components:

  1. the drivers behind energy-related occupant behavior, which are biological, societal, environmental, physical, and economical in nature
  2. the needs of the occupants are based on satisfying criteria that are either physical (e.g. thermal, visual and acoustic comfort) or non-physical (e.g. entertainment, privacy, and social reward)
  3. the actions that building occupants perform when their needs are not fulfilled
  4. the systems with which an occupant can interact to satisfy their needs

The technical framework aims to provide a standardized description of a complete set of human energy-related behaviors in the form of an XML schema. For each type of behavior (e.g., occupants opening/closing windows, switching on/off lights etc.) we identify a set of common behaviors based on a literature review, survey data, and our own field study and analysis. Stochastic models are adopted or developed for each type of behavior to enable the evaluation of the impact of human behavior on energy use in buildings, during either the design or operation phase. We will also demonstrate the use of the technical framework in assessing the impact of occupancy behavior on energy saving technologies. The technical framework presented is part of our human behavior research, a 5-year program under the U.S. - China Clean Energy Research Center for Building Energy Efficiency.

}, keywords = {building simulation, energy efficiency, framework, occupant behavior, XML schema}, author = {William J. N. Turner and Tianzhen Hong} } @article {3443, title = {Transforming BIM to BEM: Generation of Building Geometry for the NASA Ames Sustainability Base BIM}, year = {2013}, month = {01/2013}, author = {James O{\textquoteright}Donnell and Tobias Maile and Cody Rose and Natasa Mrazovic and Elmer Morrissey and Cynthia Regnier and Kristen Parrish and Vladimir Bazjanac} } @article {56946, title = {The Two-Day CERC-BEE Forum on Building Integrated Design and Occupant Behavior: Presentations and Summary}, year = {2013}, author = {Tianzhen Hong and William J. N. Turner and Cheng Li} } @article {421, title = {Technical Assistance to Beichuan Reconstruction: Creating and Designing Low- to Zero-carbon Communities in New Beichuan}, year = {2009}, month = {2009}, institution = {LBNL}, issn = {LBNL-2819E}, url = {http://www.escholarship.org/uc/item/0vv4m1gb}, author = {Tengfang T. Xu and Chuang Wang and Tianzhen Hong and Mark D. Levine} } @article {239, title = {Towards a Very Low Energy Building Stock: Modeling the US Commercial Building Stock to Support Policy and Innovation Planning}, journal = {Building Research and Information}, volume = {37:5}, year = {2009}, chapter = {610}, abstract = {

This paper describes the origin, structure and continuing development of a model of time varying energy consumption in the US commercial building stock. The model is based on a flexible structure that disaggregates the stock into various categories (e.g. by building type, climate, vintage and life-cycle stage) and assigns attributes to each of these (e.g. floor area and energy use intensity by fuel type and end use), based on historical data and user-defined scenarios for future projections. In addition to supporting the interactive exploration of building stock dynamics, the model has been used to study the likely outcomes of specific policy and innovation scenarios targeting very low future energy consumption in the building stock. Model use has highlighted the scale of the challenge of meeting targets stated by various government and professional bodies, and the importance of considering both new construction and existing buildings.

}, author = {Brian E. Coffey and Sam Borgeson and Stephen E. Selkowitz and Joshua S. Apte and Paul A. Mathew and Philip Haves} } @proceedings {2808, title = {Thermal Performance Simulation of an Atrium Building}, journal = {eSim 2006}, year = {2006}, month = {05/2006}, address = {Toronto, Canada}, author = {{\"O}zg{\"u}r G{\"o}{\c c}er and Aslihan Tavil and Ertan {\"O}zkan} } @conference {295, title = {Thermal analysis of climate environments based on weather data in Singapore for naturally ventilated buildings}, booktitle = {the 10th International conference on Indoor Air Quality and Climate,Beijing}, year = {2005}, month = {2005}, author = {Liping Wang and Nyuk Hien Wong} } @article {387, title = {Thermal Conductivity of Nanoscale Colloidal Solutions (Nanofluids)}, journal = {Physical Review Letters}, volume = {94}, year = {2005}, chapter = {025901-1}, author = {Ravi S. Prasher and Prajesh Bhattacharya and Patrick E. Phelan} } @conference {3382, title = {Two DOE-2 functions}, booktitle = {IBPSA Building Simulation}, year = {2005}, month = {2005}, address = {Canada}, abstract = {This paper presents two DOE-2 functions to expand the modeling capability of DOE-2.1E, a popular calculation engine for building energy simulations. The first function models sensible and total heat recovery between outside air and exhaust air, with optional evaporative precooling of exhaust air before the heat recovery. The existing heat recovery of DOE-2 only allows preheating outside air when exhaust air is more than 10{\textdegree}F warmer than outside air. The second function models distributed energy storage for direct expansion air conditioners which cannot be modeled by any existing system type of DOE-2.1E.}, url = {http://www.ibpsa.org/proceedings/BS2005/BS05_0419_426.pdf}, author = {Tianzhen Hong and Charles N. Eley and Erik Kolderup} } @conference {2669, title = {Two DOE-2 Functions}, booktitle = {IBPSA Building Simulation 2005}, year = {2005}, month = {08/2005}, address = {Montreal, Canada}, author = {Tianzhen Hong and Charles N. Eley and Erik Kolderup} } @proceedings {2824, title = {Transferred Just on Paper? Why Doesn{\textquoteright}t the Reality of Transferring/Adapting Energy Efficiency Codes and Standards Come Close to the Potential?}, journal = {ACEEE Summer Study on Energy Efficiency in Buildings}, year = {2004}, month = {08/2004}, address = {Pacific Grove, California, USA}, author = {Joseph J Deringer and Maithili Iyer and Yu Joe Huang} } @conference {55643, title = {Thermal Energy Storage System Sizing}, booktitle = {IBPSA Building Simulation {\textquoteright}89}, year = {1989}, month = {01/1989}, address = {Vancouver, BC, Canada}, url = {http://www.ibpsa.org/proceedings/BS1989/BS89_357_362.pdf}, author = {Dominique Dumortier and Ron C. Kammerud and Birdsall, Bruce E. and Brandt Andersson and Joseph H. Eto and William L. Carroll and Frederick C. Winkelmann} } @conference {349, title = {Towards an Environment for HVAC Control System Evaluation}, booktitle = {USER-1 Building Simulation Conference}, series = {European Society for Computer Simulation}, year = {1988}, month = {09/1988}, address = {Ostend, Belgium}, author = {Philip Haves and Trewella, D.} } @proceedings {368, title = {The Thermal Benefits and Cost Effectiveness of Earth Berming}, journal = {5th National Passive Solar Conference}, volume = {5.1}, year = {1980}, month = {10/1980}, address = {Amherst, MA}, abstract = {

A number of advantages are claimed for earth sheltered buildings; the earth provides both insulation and thermal storage and also serves to reduce infiltration and noise. This paper seeks to quantify the thermal advantages of both earth sheltering and perimeter insulation by comparing the simulated thermal performance of an earth sheltered house, a house with perimeter insulation and a house with neither. The fuel savings are then compared to the estimated construction costs to determine cost-effectiveness. The major saving from an earth sheltered building is obtained in colder climates where the effective elevation of the frost line due to the earth berms considerably reduces the cost of the foundation.

}, author = {Speltz, J. and Philip Haves} }