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Chinese prototype building models for simulating the energy performance of the nationwide building stock

建筑模拟(英文) 2023年第8期16卷 1559-1582页

作者： Jingjing An Yi Wu Chenxi Gui Da Yan School of Environment and Energy Engineering Beijing University of Civil Engineering and ArchitectureBeijingChina Building Energy Research Center School of ArchitectureTsinghua UniversityBeijingChina

Building energy modeling(BEM)has become increasingly used in building energy conservation research.Prototype building models are developed to represent the typical urban building characteristics of a specific building type,meteorological conditions,and construction year.This study included four residential buildings and 11 commercial buildings to represent nationwide building types in China.With consideration of five climate zones and different construction years corresponding to national standards,a total of 151 prototype building models were developed.The building envelope properties,occupancy and energy-related behaviors,and heating,ventilation,and air-conditioning(HVAC)system characteristics were defined according to the corresponding building energy efficiency design standards,HVAC design standards,and through other sources,such as questionnaire surveys,on-site measurements,and literature,which reflect the real situation of existing buildings in China.Based on the developed prototype buildings,a large database of 9225 models in 270 cities was further developed to facilitate users to simulate building energy in different cities.In conclusion,the developed prototype building models can represent realistic building characteristics and construction practices of the most common residential and commercial buildings in China,serving as an important foundation for BEM.The models can be used for analyses related to building energy conservation research on typical individual buildings,including energy-saving technologies,advanced controls,and new policies,and providing a reference for the development of building energy codes and standards.

关键词： prototype building models building stock modeling Chinese building building performance simulation energy conservation

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A global typical meteorological year(TMY)database on ERA5 dataset

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Building Simulation 2023年第6期16卷 1013-1026页

作者： Yi Wu Jingjing An Chenxi Gui Chan Xiao Da Yan Building Energy Research Center School of ArchitectureTsinghua UniversityBeijing100084China School of Environment and Energy Engineering Beijing University of Civil Engineering and ArchitectureBeijing100044China National Climate Center China Meteorological AdministrationBeijingChina

The outdoor climate condition is one of the deterministic factors influencing building energy consumption.Building performance simulation(BPS)tools usually adopt typical meteorological year(TMY)as the outdoor climate input.Despite that many scholars and institutes have developed TMY datasets,these datasets are usually based on distinct data sources and methods.Considering the increase of international cooperation construction projects,compatible TMY dataset for different countries is in urgent need.This paper presents a global typical meteorological year(TMY)database covering 38,947 stations worldwide based on the fifth-generation atmospheric reanalysis product released by the European Center(ERA5).The data is created with Chinese Standard Weather database(CSWD)method to reflect the average level of historical weather.The dataset is saved in a 55 GB database of compressed CSV files and a website is established where users can download their required TMY data for certain cities according to the longitude and latitude information.A systematic validation is conducted to confirm the feasibility of ERA5 as data source and validity of generated TMY data.This TMY-ERA5 dataset is fundamental and essential in building system designs of international construction projects,building performance simulation,especially for some countries lacking ground meteorological stations or missing meteorological year data in the building sector.It can be used as references for other meteorological climate studies.

关键词： typical meteorological year atmospheric reanalysis data building simulation ERA5

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Building Simulation to be published monthly from 2022

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Building Simulation 2022年第1期15卷 1-1页

作者： Da Yan Department of Building Science School of ArchitectureTsinghua UniversityBeijing 100084China

It is my honor to be the Editor-in-Chief of Building Simulation,succeeding Professor Xudong yang,the founding Editor-in-Chief.The Journal is undergoing rapid growth in many ways.To meet the increasing demand from both our readers and authors,the Journal has decided to change the publishing frequency from bi-monthly to monthly,effective Issue 1,Vol.15(2022).We will now publish approximately 120 articles annually.

关键词： annually founding Building

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Challenges and opportunities for carbon neutrality in China’s building sector—Modelling and data

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Building Simulation 2022年第11期15卷 1899-1921页

作者： Shan Hu yang Zhang Ziyi yang Da Yan Yi Jiang Building Energy Research Center School of ArchitectureTsinghua UniversityBeijing 100084China

The building sector is one of the largest energy user and carbon emitter globally.To achieve China’s national carbon target,the building sector in China needs to achieve carbon peaking and neutrality targets by 2030 and 2060,respectively.However,data deficiency on building energy and emissions become barriers for tracking the status of building energy and emissions,and identify potential opportunities for achieving dual carbon targets.To address these shortcomings,this study established an integrated China Building Energy and Emission Model(CBEEM).With CBEEM,this study evaluated the building-construction and building-operation energy and emissions in China,and revealed the status quo and potential challenge and opportunities.According to modelling results,building operation energy use of China was 1.06 billion tce in 2020,accounting for 21%of China’s total primary energy consumption.Building construction energy consumption was 0.52 billion tce in 2020,accounting for another 10%of total primary energy consumption.Key messages found on building carbon emissions are:building construction embodied emissions were 1.5 billion tCO_(2) in 2020 and are declining slowly,building operational carbon emissions were 2.2 billion tCO_(2) in 2020 and are still increasing.International comparisons between China and other countries on building stock,energy use intensity and carbon emission intensity were conducted as well,and help shed a light on the challenges for decarbonization of China’s building sector.Finally,technology perspectives to achieve carbon neutrality target were discussed and related policy suggestions were provided.

关键词： climate change building sector carbon neutrality global comparison China building energy and emission

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Advanced data analytics for building energy modeling and management

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Building Simulation 2021年第1期14卷 1-2页

作者： Cheng Fan Fu Xiao Da Yan Sino-Australia Joint Research Center in BIM and Smart Construction College of Civil and Transportation EngineeringShenzhen UniversityShenzhenChina Department of Building Services Engineering The Hong Kong Polytechnic UniversityHong KongChina Building Energy Research Center School of ArchitectureTsinghua UniversityBeijingChina

The data-driven approach has been widely adopted in fault detection and diagnosis and optimal control of building energy systems for improving building performance since the 1980s,owing to the increasing demands for c... 详细信息

关键词： energy convenient analytic

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Building a greener future—Progress of the green building technology in the “13th Five-Year Plan” of China

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Building Simulation 2022年第10期15卷 1705-1707页

作者： Min Song Xue Liu Shan Hu Quan Wen Da Yan The Administrative Center for China's Agenda 21 Beijing 100038China Building Energy Research Center School of ArchitectureTsinghua UniversityBeijing 100084China

The building sector plays an important role in energyconservation and carbon neutrality in China.Accordingto the Building Energy Research Center of TsinghuaUniversity,carbon dioxide(CO_(2))emissions account for38%of the total emissions,of which 16%and 22%arecontributed by building construction and operation,respectively(Hu et al.2022),Hence,promoting greenbuildings is proposed as an effective solution to the keyproblems of building industry development,including lowlabor productivity,high consumption of building materials,and high COz emissions in construction and operation.Greenbuildings are environmentlly responsible and resource-efficient throughout their life cycle from siting,design,andconstruction to operation,maintenance,renovation,anddeconstruction.They aim to use energy,water,and otherresources ficiently,while protecting occupant health andimproving productivity,adopting eco-friendly materials,and reducing the production of waste and pollution.

关键词： Building emissions construction

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

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

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

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

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

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A novel AC turning on behavior model based on survival analysis

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Building Simulation 2023年第7期16卷 1203-1218页

作者： Yuxin Lu Xinyu yang Xin Zhou Jingjing An Xiaomin Wang Kun Zhang Da Yan School of Architecture Southeast UniversityNanjingJiangsu Province 210096China School of Environment and Energy Engineering Beijing University of Civil Engineering and ArchitectureBeijing 100084China Jiangsu Architectural Design and Research Institute Co. Ltd.NanjingJiangsu Province 210096China School of Architecture Tsinghua UniversityBeijing 100084China

Occupant control behavior is a key factor affecting the energy consumption of building air-conditioners(ACs).The operating behavior of ACs and their models in office buildings have been investigated extensively.However,although the thermal sensation of occupants is affected by their previous thermal experience,few researchers have attempted to incorporate this effect quantitatively in models of AC turning on behavior.Not considering the cumulative effect may result in inaccurate predictions.Therefore,in this study,a survival model is proposed to describe AC turning on behavior in office buildings under the cumulative dimension of time.Based on a dataset containing environmental parameters and occupant behavior information,as well as considering occupants entering a room as the starting event and turning on an air-conditioner as the end event,the endurance time before an AC is turned on is investigated,and a survival model is used to predict the probability of the AC turning on due to environmental factors.Based on a switch curve,confusion matrix,and tolerance–time curve,the prediction results of the survival model are analyzed and validated.The results show that a tolerance temperature of 29℃and a tolerance duration setting of 1 h can effectively model the turning on behavior of the AC.In addition,based on comparison results of different models,the survival model presents a more stable switching curve,a higher F1 score,and a tolerance curve that is more similar to reality.Different tolerance durations,as well as static and dynamic tolerance temperature settings,are considered to optimize the model.Furthermore,the AC energy consumption is calculated under the survival model and the traditional Weibull model.Simulation results were compared with measurement,and the survival model verified the improvement effect of prediction accuracy by 8%than the Weibull model.By considering the time-transformed accumulation of physical environmental factors,the accuracy of AC turning on models can be improved,thus providing an ef

关键词： AC status AC turning on behavior survival models time dependent models prediction accuracy

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A review of validation methods for building energy modeling programs

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Building Simulation 2023年第11期16卷 2027-2047页

作者： Xin Zhou Ruoxi Liu Shuai Tian Xiaohan Shen Xinyu yang Jingjing An Da Yan School of Architecture Southeast UniversityNanjingJiangsu Province210096China College of Architecture and Urban Planning Tongji UniversityShanghai200092China Key Laboratory of Ecology and Energy-saving Study of Dense Habitat Ministry of EducationShanghai200092China School of Environment and Energy Engineering Beijing University of Civil Engineering and ArchitectureBeijing100044China Building Energy Research Center School of ArchitectureTsinghua UniversityBeijing100084China

Building energy simulation analysis plays an important supporting role in the conservation of building energy.Since the early 1980s,researchers have focused on the development and validation of building energy modeling programs(BEMPs)and have basically formed a set of systematic validation methods for BEMPs,mainly including analytical,comparative,and empirical methods.Based on related papers in this field,this study systematically analyzed the application status of validation methods for BEMPs from three aspects,namely,sources of validation cases,comparison parameters,and evaluation indicators.The applicability and characteristics of the three methods in different validation fields and different development stages of BEMPs were summarized.Guidance were proposed for researchers to choose more suitable validation methods and evaluation indicators.In addition,the current development trend of BEMPs and the challenges faced by validation methods were investigated,as well as the existing progress of current validation methods under this trend was analyzed.Subsequently,the development direction of the validation method was clarified.

关键词： building energy simulation performance validation analytical validation comparative validation empirical validation

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Comparative research on different air conditioning systems for residential buildings

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Frontiers of Architectural Research 2017年第1期6卷 42-52页

作者： Xin Zhou Da Yan Xing Shi School of Architecture Southeast University Nanjing 210096 China School of Architecture Tsinghua University Beijing 100084 China

Two types of airconditioning (AC) systems generally exist, namely, centralized and decen-tralized AC systems. This study focuses on three actual engineering projects of residential communities where centralized AC systems are adopted.The applicability of centralized AC systems in residential buildings is discussed and analyzed. In addition, the key elements that lead to different building energy consumptions and system efficiencies between centralized and decentralized AC systems in residential buildings are investigated. This study shows that in residential buildings, at the point where the centralized feature of the system meets the decentralized featureofusers’ load, the problems of high energy consumption and low energy efficiency could easily occur.

关键词： Residential buildings Centralized AC system Decentralized AC system Comparative research

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