General information:www.springer.com/12273 Electronic content:link.springer.com/journal/12273 Submit online:www.editorialmanager.com/buil 1.Permissions Authors wishing to include figures,tables,or text passages that h...General information:www.springer.com/12273 Electronic content:link.springer.com/journal/12273 Submit online:www.editorialmanager.com/buil 1.Permissions Authors wishing to include figures,tables,or text passages that have already been published elsewhere are required to obtain permission from the copyright owner(s)and to include evidence that such permission has been granted when submitting their papers.Any material received without such evidence will be assumed to originate from the author(s).展开更多
Aims and Scope Building Simulation publishes original,high quality,peer-reviewed research papers and review articles dealing with modeling and simulation of buildings including their systems.The goal is to promote the...Aims and Scope Building Simulation publishes original,high quality,peer-reviewed research papers and review articles dealing with modeling and simulation of buildings including their systems.The goal is to promote the field of building science and technology to such a level that modeling will eventually be used in every aspect of building construction as a routine instead of an exception.展开更多
General information:www.springer.com/12273 Electronic content:link.springer.com/journal/12273 Submit online:www.editorialmanager.com/buil 1.Permissions Authors wishing to include figures,tables,or text passages that h...General information:www.springer.com/12273 Electronic content:link.springer.com/journal/12273 Submit online:www.editorialmanager.com/buil 1.Permissions Authors wishing to include figures,tables,or text passages that have already been published elsewhere are required to obtain permission from the copyright owner(s)and to include evidence that such permission has been granted when submitting their papers.Any material received without such evidence will be assumed to originate from the author(s).展开更多
Aims and Scope Building Simulation publishes original,high quality,peer-reviewed research papers and review articles dealing with modeling and simulation of buildings including their systems.The goal is to promote the...Aims and Scope Building Simulation publishes original,high quality,peer-reviewed research papers and review articles dealing with modeling and simulation of buildings including their systems.The goal is to promote the field of building science and technology to such a level that modeling will eventually be used in every aspect of building construction as a routine instead of an exception.展开更多
General information:www.springer.com/12273,Electronic content:link.springer.com/journal/12273,Submit online:www.editorialmanager.com/buil.1.Permissions.Authors wishing to include figures,tables,or text passages that h...General information:www.springer.com/12273,Electronic content:link.springer.com/journal/12273,Submit online:www.editorialmanager.com/buil.1.Permissions.Authors wishing to include figures,tables,or text passages that have already been published elsewhere are required to obtain permission from the copyright owner(s)and to include evidence that such permission has been granted when submitting their papers.Any material received without such evidence will be assumed to originate from the author(s).展开更多
It is my pleasure to announce that the following paper has been honored with the Best Review Paper 2023.This paper has distinguished itself among the 20 review papers published in Building Simulation from 2019(Volume ...It is my pleasure to announce that the following paper has been honored with the Best Review Paper 2023.This paper has distinguished itself among the 20 review papers published in Building Simulation from 2019(Volume 12)to 2023(Volume 16):lCheng Fan,Da Yan,Fu Xiao,Ao Li,Jingjing An&Xuyuan Kang.“Advanced data analytics for enhancing building performances:From data-driven to big data-driven approaches.”Building Simulation,2021,14(1):3–24.展开更多
Building simulation(BS)increasingly relies on data-driven models that extract patterns directly from measured data.However,these models often conflate statistical dependency with causal relationship.The idea of a caus...Building simulation(BS)increasingly relies on data-driven models that extract patterns directly from measured data.However,these models often conflate statistical dependency with causal relationship.The idea of a causal lens introduces structural causal diagrams and do-operators to distinguish true causations from spurious associations.The“causal lens”perspective highlights how confounding bias can arise in observational modeling and emphasizes the importance of extracting true causality from building data.This suggests that BS move beyond pattern replication to enable counterfactual reasoning,thereby supporting reliable decision-making.展开更多
This paper presents a novel approach for evaluating the air impact on urban microclimate and building loads.Traditional software tools,such as TRNSYS and EnergyPlus,often employ the surface-to-surface method for radia...This paper presents a novel approach for evaluating the air impact on urban microclimate and building loads.Traditional software tools,such as TRNSYS and EnergyPlus,often employ the surface-to-surface method for radiation transfer calculations,which neglects the influence of air.To address this limitation,this work integrates the discrete ordinates method(DOM)with the spectral-line weighted-sum-of-gray-gases(SLW)air model to develop a microclimate energy approach.The SLW model uses outdoor temperature and humidity data to compute absorption coefficients,leveraging the air spectrum provided by the HITRAN database.The DOM is then employed to calculate both solar and infrared radiation transfers within the urban environment.A transient simulation is conducted over one year for an urban scene in Suzhou,China.The results indicate that the air impact on radiation transfer increases with rising outdoor temperature and humidity.Overall,the results demonstrate that air effects exert a non-negligible influence on building heating and cooling load calculations,with an impact magnitude comparable to the introduction of an auxiliary thermal source.This study highlights the significance of considering air properties in urban microclimate and building energy simulations for more accurate results.展开更多
Climate change presents a major threat to the built environment and therefore requires reliable future climate data for building performance simulation(BPS).The implementation of advanced statistical downscaling metho...Climate change presents a major threat to the built environment and therefore requires reliable future climate data for building performance simulation(BPS).The implementation of advanced statistical downscaling methods remains difficult in BPS studies because specific historical weather data and complex implementation procedures are usually requested.The current statistical downscaling methods that are frequently used in BPS analysis were rarely validated against measurements to see if ongoing climate change process and weather extremes can be represented.This paper presents a new Distribution Adjusted Temporal Mapping(DATM)technique for downscaling future hourly weather data from the monthly GCM(Global Climate Model)data with Typical Meteorological Year(TMY)data being the baseline.The proposed method involves fitting probability distributions to TMY data for each climate variable,modifying these distributions according to the projected monthly changes from GCMs,and then mapping the future hourly weather data from the adjusted distributions.DATM is compared with the“morphing”technique for various climate variables and locations,and is validated against ten years onsite measured hourly weather data from 2015 to 2024.The outcomes reveal that DATM outperforms the morphing method in temperature downscaling in terms of reproducing climate variabilities and extreme events.For relative humidity and wind speed,DATM is slightly better in capturing the full range of variables even though both methods have their limitations.For solar radiation,DATM can reflect realistic peak solar radiation prediction in future climate downscaling.It also shows better performance in capturing the changes in temperature variability and extremes that are essential for the overall building resilience analysis.The results of both methods depend on climate zones and variables,which underlines the necessity of considering regional factors in climate data preprocessing.With climate change affecting the built environment,the proposed method in this research offers BPS researchers a more reliable way of evaluating future building performance under future emission scenarios.展开更多
With the increasing volume of data from buildings and affordable powerful computing,artificial intelligence(AI)has been explored in various applications for building energy modeling(BEM),including collecting input dat...With the increasing volume of data from buildings and affordable powerful computing,artificial intelligence(AI)has been explored in various applications for building energy modeling(BEM),including collecting input data,creating and tuning energy models,managing simulation runs,and extracting insights from large volume of simulation output to inform decision making across a building’s life cycle for energy efficiency,demand flexibility,climate resilience,and occupant comfort and health.However,significant challenges remain to address,including AI-ready data,selecting fit-for-purpose AI models or tools,BEM workforce training,standard benchmark datasets and methods.This perspective article describes how AI is transforming BEM workflows and the larger ecosystem focusing on four major AI themes of data,models,computing,and applications,highlighting the associated opportunities,challenges,and future trends.展开更多
General information:www.springer.com/12273 Electronic content:link.springer.com/journal/12273 Submit online:www.editorialmanager.com/buil 1.Permissions Authors wishing to include figures,tables,or text passages that h...General information:www.springer.com/12273 Electronic content:link.springer.com/journal/12273 Submit online:www.editorialmanager.com/buil 1.Permissions Authors wishing to include figures,tables,or text passages that have already been published elsewhere are required to obtain permission from the copyright owner(s)and to include evidence that such permission has been granted when submitting their papers.Any material received without such evidence will be assumed to originate from the author(s).展开更多
Demand Response(DR)is a critical strategy for managing the integration of renewable energy sources into the power grid,addressing the challenges posed by their intermittent and unpredictable nature.This study introduc...Demand Response(DR)is a critical strategy for managing the integration of renewable energy sources into the power grid,addressing the challenges posed by their intermittent and unpredictable nature.This study introduces a rapid evaluation method for assessing the DR potential of large-scale Heating,Ventilation,and Air Conditioning(HVAC)systems,focusing on the significant role these systems play in energy consumption and grid flexibility.Firstly,the methodology involves constructing a simulation model library that encompasses three dimensions including room type,room location,and internal heat gain mode to reflect the dynamic characteristics of cooling load.Additionally,batch simulations generate DR profiles under various typical weather conditions,and surrogate models are trained for each simulation model,leveraging feature engineering and cross-validation to enhance accuracy.The Multi-Layer Perceptron(MLP)surrogate models achieve high accuracy in predicting DR potential under various scenarios,with R^(2) values exceeding 0.95.This study provides a robust framework that enables load aggregators to accurately estimate the demand response potential of large-scale HVAC systems.It supports the quantification of response capabilities and facilitates participation in bidding processes.Furthermore,it highlights the potential of data-driven models to enable rapid and scalable energy management.展开更多
Predicting wind flow statistics in urban areas is important for various environmental and engineering applications.Currently,building-resolved computational fluid dynamics(CFD)simulations are the most commonly used an...Predicting wind flow statistics in urban areas is important for various environmental and engineering applications.Currently,building-resolved computational fluid dynamics(CFD)simulations are the most commonly used and reliable methods to simulate urban wind flows but they are time-consuming which limits their use in real applications.Therefore,our objective is to develop a surrogate model based on deep learning(DL),which can be used as a faster alternative to CFD methods for urban flows.The proposed model hypothesis is that the spatial distributions of the time-averaged flow quantities within urban canopies are highly correlated to the local urban geometries.To test this hypothesis,we developed a model to predict the flow in uniform urban street canyons by constructing a geometry reading filter to convert local urban geometry information around the targeted locations into a numerical array as DL model inputs.A standard feedforward DL model is then trained using large-eddy simulation(LES)results to predict the mean wind and turbulence within uniform street canyons.Our results show that the model can give fast and accurate predictions compared to LES results.The prediction errors are found to range from 5.8%to 36%,and the normalized mean bias magnitudes range from 6.6×10^(−3) to 1.6×10^(−1) for the different flow quantities.The DL model is also found to predict the flow patterns reasonably well,consistent with experimental data similar to the results of coarse-resolution LESs.This model has the potential to be further developed into a robust and practical tool for fast urban flow predictions.展开更多
Previous research was limited to flat-façade buildings when evaluating the indoor and outdoor ventilation performance in a multi-story building.However,envelope features can provide the shading effect to induce t...Previous research was limited to flat-façade buildings when evaluating the indoor and outdoor ventilation performance in a multi-story building.However,envelope features can provide the shading effect to induce the temperature difference between surfaces exposed to direct solar radiation and those without solar radiation.This temperature difference between surfaces can enhance the thermal buoyancy and change indoor and outdoor ventilation performance.We conducted scaled outdoor experiments to examine the impact of various envelope features on indoor and outdoor ventilation performance in multi-story buildings.Compared to the flat-façade multi-building,the average normalized horizontal airflow velocity of overhang,small wing wall,and large wing wall multi-buildings increased by 12.41%,10.56%,and 5.56%,respectively.Cross-ventilation is more susceptible to envelope features than single-sided ventilation in air change per hour(ACH).Specifically,the ACH values of cross-ventilation for large wing wall,small wing wall,and balcony multi-buildings decreased by 69.98%,25.79%,and 12.12%relative to the flat-façade building.For the same envelope feature building,the ACH values of single-sided ventilation on the windward side are better than those on the leeward side,particularly the building with small wing walls,with an improvement of 12.77%compared to flat-façade.This study contributes to advancing the understanding of urban ventilation,and provides a valid basis for designing envelope features in urban buildings.展开更多
Air pollution in vehicle cabin environment has gained increasing concern recently.This study addresses the necessity to predict and regulate the emissions of volatile organic compounds(VOCs)from interior materials to ...Air pollution in vehicle cabin environment has gained increasing concern recently.This study addresses the necessity to predict and regulate the emissions of volatile organic compounds(VOCs)from interior materials to improve in-cabin air quality.We focus on how the selection of interior materials influences formaldehyde concentration levels under multi-source emission scenarios.Chamber experiments were conducted to determine the three key parameters of formaldehyde emissions from five typical interior materials(carpet,car door,sealing strip,and two adhesives)using the C-history method.By applying a multi-source emission model with the measured key parameters,various cabin emission scenarios are predicted and evaluated.Comparison of formaldehyde concentration levels between experimental data and simulated results demonstrates the effectiveness of the model.Analysis based on the model indicates that adhesives contribute significantly to in-cabin air pollution,and the impact of different key parameters on the emission behaviors is different.Adhesives with higher ratio of initial emittable concentration to partition coefficient will prolong the emission period and increase the health risks.The ventilation requirements for different multi-source emission scenarios are also quantified.These results underscore the critical role of material selection in controlling formaldehyde emissions and the necessity of developing low-emitting materials to improve air quality and occupant safety in vehicle cabins.展开更多
Urban pollution leaks threaten people’s lives and cause environmental pollution.However,there is a lack of a lightweight algorithm that can be embedded in portable devices to estimate the location and dynamic release...Urban pollution leaks threaten people’s lives and cause environmental pollution.However,there is a lack of a lightweight algorithm that can be embedded in portable devices to estimate the location and dynamic release strength of the pollution source rapidly and accurately.This study introduced a spatiotemporally separated source term estimation method that integrated the Gaussian equation with adjoint theory,known as the lightweight adjoint method(LAM).The adjoint method was initially utilized to identify the high probability spatial region of the pollution source.The regularization method was then used to determine the temporal release characteristics of potential sources in the region.Finally,the residual function was used to determine the real source location.The adjoint method based on the validated CFD model was employed to compare with the LAM in Mock Urban Setting Test(MUST).The results show that the LAM can rapidly estimate the location and dynamic strength of different pollution sources in the urban environment.It was particularly effective for source localization under the neutral atmospheric condition,achieving a maximum localization error of 22.1 m.Additionally,it was more suitable for calculating source intensity for the pulse source,with the maximum mean absolute percentage error(MAPE)of 15.1%.展开更多
Buildings use a large amount of energy in the United States.It is important to optimally manage and coordinate the resources across building and power distribution networks to improve overall efficiency.Optimizing the...Buildings use a large amount of energy in the United States.It is important to optimally manage and coordinate the resources across building and power distribution networks to improve overall efficiency.Optimizing the power grid with discrete variables was very challenging for traditional computers and algorithms,as it is an NP-hard problem.In this study,we developed a new optimization solution based on quantum computing for BTG integration.We first used MPC for building loads connected with a commercial distribution grid for cost reduction.Then we used discretization and Benders Decomposition methods to reformulate the problem and decompose the continuous and discrete variables,respectively.We used D-Wave quantum computer to solve dual problems and used conventional algorithm for primal problems.We applied the proposed method to an IEEE 9-bus network with 3 commercial buildings and over 300 residential buildings to evaluate the feasibility and effectiveness.Compared with traditional optimization methods,we obtained similar solutions with some fluctuations and improved computational speed from hours to seconds.The time of quantum computing was greatly reduced to less than 1% of traditional optimization algorithm and software such as MATLAB.Quantum computing has proved the potential to solve large-scale discrete optimization problems for urban energy systems.展开更多
Urban outdoor spaces are vital for our daily lives and activities. However, unlike indoor environments, outdoor spaces are characterized by unpredictable climatic conditions and a lack of mature control over environme...Urban outdoor spaces are vital for our daily lives and activities. However, unlike indoor environments, outdoor spaces are characterized by unpredictable climatic conditions and a lack of mature control over environmental quality. Thus, this study explores the utilization of an intelligent kinetic canopy (KCP) to enhance the quality of the outdoor thermal environment. The KCP was conducted using various technologies, including the Internet of Things, motor automation control, web crawler, simulation, machine learning, optimization algorithms, and kinetic architecture theory. KCP can adjust its own form in real-time according to weather changes and can significantly improve thermal quality in local outdoor spaces. To quantify its ability, the effects of the three algorithms on the Universal Thermal Climate Index (UTCI) values and the associated annual thermal neutral hours on the original open-state site were compared. The control strategy based on genetic algorithms yielded leading performance, achieving 1193 h of annual thermal neutral time increments compared with the original site, approximately 3.3 h daily. Compared with the best static canopy, its neutral period is 696 h longer, or 140% better in creating additional thermally neutral hours. These findings demonstrate the ability of the KCP to further unleash the potential of space design to improve the thermal comfort of outdoor spaces, which broadens the conceptual scope for similar design and research on outdoor spaces and provides architects and designers with insights into specific technical applications and strategies for implementation.展开更多
Aims and Scope.Building Simulation publishes original,high quality,peer-reviewed research papers and review articles dealing with modeling and simulation of buildings including their systems.The goal is to promote the...Aims and Scope.Building Simulation publishes original,high quality,peer-reviewed research papers and review articles dealing with modeling and simulation of buildings including their systems.The goal is to promote the field of building science and technology to such a level that modeling will eventually be used in every aspect of building construction as a routine instead of an exception.Of particular interest are papers that reflect recent developments and applications of modeling tools and their impact on advances of building science and technology.展开更多
For Authors Submission of a manuscript implies:that the work described has not been published before(except in form of an abstract or as part of a published lecture,review or thesis);that it is not under consideration...For Authors Submission of a manuscript implies:that the work described has not been published before(except in form of an abstract or as part of a published lecture,review or thesis);that it is not under consideration for publication elsewhere;that its publication has been approved by all co-authors,if any,as well as-tacitly or explicitly——by the responsible authorities at the institution where the work was carried out.展开更多
文摘General information:www.springer.com/12273 Electronic content:link.springer.com/journal/12273 Submit online:www.editorialmanager.com/buil 1.Permissions Authors wishing to include figures,tables,or text passages that have already been published elsewhere are required to obtain permission from the copyright owner(s)and to include evidence that such permission has been granted when submitting their papers.Any material received without such evidence will be assumed to originate from the author(s).
文摘Aims and Scope Building Simulation publishes original,high quality,peer-reviewed research papers and review articles dealing with modeling and simulation of buildings including their systems.The goal is to promote the field of building science and technology to such a level that modeling will eventually be used in every aspect of building construction as a routine instead of an exception.
文摘General information:www.springer.com/12273 Electronic content:link.springer.com/journal/12273 Submit online:www.editorialmanager.com/buil 1.Permissions Authors wishing to include figures,tables,or text passages that have already been published elsewhere are required to obtain permission from the copyright owner(s)and to include evidence that such permission has been granted when submitting their papers.Any material received without such evidence will be assumed to originate from the author(s).
文摘Aims and Scope Building Simulation publishes original,high quality,peer-reviewed research papers and review articles dealing with modeling and simulation of buildings including their systems.The goal is to promote the field of building science and technology to such a level that modeling will eventually be used in every aspect of building construction as a routine instead of an exception.
文摘General information:www.springer.com/12273,Electronic content:link.springer.com/journal/12273,Submit online:www.editorialmanager.com/buil.1.Permissions.Authors wishing to include figures,tables,or text passages that have already been published elsewhere are required to obtain permission from the copyright owner(s)and to include evidence that such permission has been granted when submitting their papers.Any material received without such evidence will be assumed to originate from the author(s).
文摘It is my pleasure to announce that the following paper has been honored with the Best Review Paper 2023.This paper has distinguished itself among the 20 review papers published in Building Simulation from 2019(Volume 12)to 2023(Volume 16):lCheng Fan,Da Yan,Fu Xiao,Ao Li,Jingjing An&Xuyuan Kang.“Advanced data analytics for enhancing building performances:From data-driven to big data-driven approaches.”Building Simulation,2021,14(1):3–24.
文摘Building simulation(BS)increasingly relies on data-driven models that extract patterns directly from measured data.However,these models often conflate statistical dependency with causal relationship.The idea of a causal lens introduces structural causal diagrams and do-operators to distinguish true causations from spurious associations.The“causal lens”perspective highlights how confounding bias can arise in observational modeling and emphasizes the importance of extracting true causality from building data.This suggests that BS move beyond pattern replication to enable counterfactual reasoning,thereby supporting reliable decision-making.
文摘This paper presents a novel approach for evaluating the air impact on urban microclimate and building loads.Traditional software tools,such as TRNSYS and EnergyPlus,often employ the surface-to-surface method for radiation transfer calculations,which neglects the influence of air.To address this limitation,this work integrates the discrete ordinates method(DOM)with the spectral-line weighted-sum-of-gray-gases(SLW)air model to develop a microclimate energy approach.The SLW model uses outdoor temperature and humidity data to compute absorption coefficients,leveraging the air spectrum provided by the HITRAN database.The DOM is then employed to calculate both solar and infrared radiation transfers within the urban environment.A transient simulation is conducted over one year for an urban scene in Suzhou,China.The results indicate that the air impact on radiation transfer increases with rising outdoor temperature and humidity.Overall,the results demonstrate that air effects exert a non-negligible influence on building heating and cooling load calculations,with an impact magnitude comparable to the introduction of an auxiliary thermal source.This study highlights the significance of considering air properties in urban microclimate and building energy simulations for more accurate results.
文摘Climate change presents a major threat to the built environment and therefore requires reliable future climate data for building performance simulation(BPS).The implementation of advanced statistical downscaling methods remains difficult in BPS studies because specific historical weather data and complex implementation procedures are usually requested.The current statistical downscaling methods that are frequently used in BPS analysis were rarely validated against measurements to see if ongoing climate change process and weather extremes can be represented.This paper presents a new Distribution Adjusted Temporal Mapping(DATM)technique for downscaling future hourly weather data from the monthly GCM(Global Climate Model)data with Typical Meteorological Year(TMY)data being the baseline.The proposed method involves fitting probability distributions to TMY data for each climate variable,modifying these distributions according to the projected monthly changes from GCMs,and then mapping the future hourly weather data from the adjusted distributions.DATM is compared with the“morphing”technique for various climate variables and locations,and is validated against ten years onsite measured hourly weather data from 2015 to 2024.The outcomes reveal that DATM outperforms the morphing method in temperature downscaling in terms of reproducing climate variabilities and extreme events.For relative humidity and wind speed,DATM is slightly better in capturing the full range of variables even though both methods have their limitations.For solar radiation,DATM can reflect realistic peak solar radiation prediction in future climate downscaling.It also shows better performance in capturing the changes in temperature variability and extremes that are essential for the overall building resilience analysis.The results of both methods depend on climate zones and variables,which underlines the necessity of considering regional factors in climate data preprocessing.With climate change affecting the built environment,the proposed method in this research offers BPS researchers a more reliable way of evaluating future building performance under future emission scenarios.
基金Hong’s work was supported by the Assistant Secretary for Energy Efficiency and Renewable Energy,Office of Building Technologies of the United States Department of Energy,under Contract No.DE-AC02-05CH11231.
文摘With the increasing volume of data from buildings and affordable powerful computing,artificial intelligence(AI)has been explored in various applications for building energy modeling(BEM),including collecting input data,creating and tuning energy models,managing simulation runs,and extracting insights from large volume of simulation output to inform decision making across a building’s life cycle for energy efficiency,demand flexibility,climate resilience,and occupant comfort and health.However,significant challenges remain to address,including AI-ready data,selecting fit-for-purpose AI models or tools,BEM workforce training,standard benchmark datasets and methods.This perspective article describes how AI is transforming BEM workflows and the larger ecosystem focusing on four major AI themes of data,models,computing,and applications,highlighting the associated opportunities,challenges,and future trends.
文摘General information:www.springer.com/12273 Electronic content:link.springer.com/journal/12273 Submit online:www.editorialmanager.com/buil 1.Permissions Authors wishing to include figures,tables,or text passages that have already been published elsewhere are required to obtain permission from the copyright owner(s)and to include evidence that such permission has been granted when submitting their papers.Any material received without such evidence will be assumed to originate from the author(s).
基金supported by the State Grid Headquarters Science and Technology Fund(5400-202340383A-2-3-XG).
文摘Demand Response(DR)is a critical strategy for managing the integration of renewable energy sources into the power grid,addressing the challenges posed by their intermittent and unpredictable nature.This study introduces a rapid evaluation method for assessing the DR potential of large-scale Heating,Ventilation,and Air Conditioning(HVAC)systems,focusing on the significant role these systems play in energy consumption and grid flexibility.Firstly,the methodology involves constructing a simulation model library that encompasses three dimensions including room type,room location,and internal heat gain mode to reflect the dynamic characteristics of cooling load.Additionally,batch simulations generate DR profiles under various typical weather conditions,and surrogate models are trained for each simulation model,leveraging feature engineering and cross-validation to enhance accuracy.The Multi-Layer Perceptron(MLP)surrogate models achieve high accuracy in predicting DR potential under various scenarios,with R^(2) values exceeding 0.95.This study provides a robust framework that enables load aggregators to accurately estimate the demand response potential of large-scale HVAC systems.It supports the quantification of response capabilities and facilitates participation in bidding processes.Furthermore,it highlights the potential of data-driven models to enable rapid and scalable energy management.
基金supported by the National Natural Science Foundation of China(42375193,42325504)the National Key Research and Development Program of China(2023YFC3706205)+3 种基金the Shenzhen Key Laboratory of Precision Measurement and Early Warning Technology for Urban Environmental Health Risks(ZDSYS20220606100604008)the Shenzhen Science and Technology Program(KQTD20210811090048025,JCYJ20220818100611024)the Guangdong Province Major Talent Program(2019CX01S188)the High-level University Special Fund(G03050K001).
文摘Predicting wind flow statistics in urban areas is important for various environmental and engineering applications.Currently,building-resolved computational fluid dynamics(CFD)simulations are the most commonly used and reliable methods to simulate urban wind flows but they are time-consuming which limits their use in real applications.Therefore,our objective is to develop a surrogate model based on deep learning(DL),which can be used as a faster alternative to CFD methods for urban flows.The proposed model hypothesis is that the spatial distributions of the time-averaged flow quantities within urban canopies are highly correlated to the local urban geometries.To test this hypothesis,we developed a model to predict the flow in uniform urban street canyons by constructing a geometry reading filter to convert local urban geometry information around the targeted locations into a numerical array as DL model inputs.A standard feedforward DL model is then trained using large-eddy simulation(LES)results to predict the mean wind and turbulence within uniform street canyons.Our results show that the model can give fast and accurate predictions compared to LES results.The prediction errors are found to range from 5.8%to 36%,and the normalized mean bias magnitudes range from 6.6×10^(−3) to 1.6×10^(−1) for the different flow quantities.The DL model is also found to predict the flow patterns reasonably well,consistent with experimental data similar to the results of coarse-resolution LESs.This model has the potential to be further developed into a robust and practical tool for fast urban flow predictions.
基金supported by the Key Laboratory of Ecology and Energy Saving Study of Dense Habitat,Ministry of Education,Tongji University(Grant No.20220104)the National Natural Science Foundation of China(Grant Nos.52378026 and 42175095)the Shenzhen Science and Technology Program(No.20220809120650001).
文摘Previous research was limited to flat-façade buildings when evaluating the indoor and outdoor ventilation performance in a multi-story building.However,envelope features can provide the shading effect to induce the temperature difference between surfaces exposed to direct solar radiation and those without solar radiation.This temperature difference between surfaces can enhance the thermal buoyancy and change indoor and outdoor ventilation performance.We conducted scaled outdoor experiments to examine the impact of various envelope features on indoor and outdoor ventilation performance in multi-story buildings.Compared to the flat-façade multi-building,the average normalized horizontal airflow velocity of overhang,small wing wall,and large wing wall multi-buildings increased by 12.41%,10.56%,and 5.56%,respectively.Cross-ventilation is more susceptible to envelope features than single-sided ventilation in air change per hour(ACH).Specifically,the ACH values of cross-ventilation for large wing wall,small wing wall,and balcony multi-buildings decreased by 69.98%,25.79%,and 12.12%relative to the flat-façade building.For the same envelope feature building,the ACH values of single-sided ventilation on the windward side are better than those on the leeward side,particularly the building with small wing walls,with an improvement of 12.77%compared to flat-façade.This study contributes to advancing the understanding of urban ventilation,and provides a valid basis for designing envelope features in urban buildings.
基金supported by the National Natural Science Foundation of China(Grant No.52178062)the Opening Fund of State Key Laboratory of Green Building(Grant No.LSKF202311).
文摘Air pollution in vehicle cabin environment has gained increasing concern recently.This study addresses the necessity to predict and regulate the emissions of volatile organic compounds(VOCs)from interior materials to improve in-cabin air quality.We focus on how the selection of interior materials influences formaldehyde concentration levels under multi-source emission scenarios.Chamber experiments were conducted to determine the three key parameters of formaldehyde emissions from five typical interior materials(carpet,car door,sealing strip,and two adhesives)using the C-history method.By applying a multi-source emission model with the measured key parameters,various cabin emission scenarios are predicted and evaluated.Comparison of formaldehyde concentration levels between experimental data and simulated results demonstrates the effectiveness of the model.Analysis based on the model indicates that adhesives contribute significantly to in-cabin air pollution,and the impact of different key parameters on the emission behaviors is different.Adhesives with higher ratio of initial emittable concentration to partition coefficient will prolong the emission period and increase the health risks.The ventilation requirements for different multi-source emission scenarios are also quantified.These results underscore the critical role of material selection in controlling formaldehyde emissions and the necessity of developing low-emitting materials to improve air quality and occupant safety in vehicle cabins.
基金supported by Jiangsu Province Science and Technology Program Special Funds(Key R&D Program Social Development)Project(No.BE2022820)National Engineering Research Center for Digital Construction and Evaluation Technology of Urban Rail Transit(No.2023HJ02).
文摘Urban pollution leaks threaten people’s lives and cause environmental pollution.However,there is a lack of a lightweight algorithm that can be embedded in portable devices to estimate the location and dynamic release strength of the pollution source rapidly and accurately.This study introduced a spatiotemporally separated source term estimation method that integrated the Gaussian equation with adjoint theory,known as the lightweight adjoint method(LAM).The adjoint method was initially utilized to identify the high probability spatial region of the pollution source.The regularization method was then used to determine the temporal release characteristics of potential sources in the region.Finally,the residual function was used to determine the real source location.The adjoint method based on the validated CFD model was employed to compare with the LAM in Mock Urban Setting Test(MUST).The results show that the LAM can rapidly estimate the location and dynamic strength of different pollution sources in the urban environment.It was particularly effective for source localization under the neutral atmospheric condition,achieving a maximum localization error of 22.1 m.Additionally,it was more suitable for calculating source intensity for the pulse source,with the maximum mean absolute percentage error(MAPE)of 15.1%.
基金supported by the Collaboration for Unprecedented Success and Excellence(CUSE)Grant at Syracuse University under Ⅱ-3267-2022by the U.S.National Science Foundation under Award No.1949372.
文摘Buildings use a large amount of energy in the United States.It is important to optimally manage and coordinate the resources across building and power distribution networks to improve overall efficiency.Optimizing the power grid with discrete variables was very challenging for traditional computers and algorithms,as it is an NP-hard problem.In this study,we developed a new optimization solution based on quantum computing for BTG integration.We first used MPC for building loads connected with a commercial distribution grid for cost reduction.Then we used discretization and Benders Decomposition methods to reformulate the problem and decompose the continuous and discrete variables,respectively.We used D-Wave quantum computer to solve dual problems and used conventional algorithm for primal problems.We applied the proposed method to an IEEE 9-bus network with 3 commercial buildings and over 300 residential buildings to evaluate the feasibility and effectiveness.Compared with traditional optimization methods,we obtained similar solutions with some fluctuations and improved computational speed from hours to seconds.The time of quantum computing was greatly reduced to less than 1% of traditional optimization algorithm and software such as MATLAB.Quantum computing has proved the potential to solve large-scale discrete optimization problems for urban energy systems.
基金supported by the Department of Education of Guangdong Province(2023ZDZX4078)Shenzhen Science and Technology Innovation Committee(WDZC20231129201240001).
文摘Urban outdoor spaces are vital for our daily lives and activities. However, unlike indoor environments, outdoor spaces are characterized by unpredictable climatic conditions and a lack of mature control over environmental quality. Thus, this study explores the utilization of an intelligent kinetic canopy (KCP) to enhance the quality of the outdoor thermal environment. The KCP was conducted using various technologies, including the Internet of Things, motor automation control, web crawler, simulation, machine learning, optimization algorithms, and kinetic architecture theory. KCP can adjust its own form in real-time according to weather changes and can significantly improve thermal quality in local outdoor spaces. To quantify its ability, the effects of the three algorithms on the Universal Thermal Climate Index (UTCI) values and the associated annual thermal neutral hours on the original open-state site were compared. The control strategy based on genetic algorithms yielded leading performance, achieving 1193 h of annual thermal neutral time increments compared with the original site, approximately 3.3 h daily. Compared with the best static canopy, its neutral period is 696 h longer, or 140% better in creating additional thermally neutral hours. These findings demonstrate the ability of the KCP to further unleash the potential of space design to improve the thermal comfort of outdoor spaces, which broadens the conceptual scope for similar design and research on outdoor spaces and provides architects and designers with insights into specific technical applications and strategies for implementation.
文摘Aims and Scope.Building Simulation publishes original,high quality,peer-reviewed research papers and review articles dealing with modeling and simulation of buildings including their systems.The goal is to promote the field of building science and technology to such a level that modeling will eventually be used in every aspect of building construction as a routine instead of an exception.Of particular interest are papers that reflect recent developments and applications of modeling tools and their impact on advances of building science and technology.
文摘For Authors Submission of a manuscript implies:that the work described has not been published before(except in form of an abstract or as part of a published lecture,review or thesis);that it is not under consideration for publication elsewhere;that its publication has been approved by all co-authors,if any,as well as-tacitly or explicitly——by the responsible authorities at the institution where the work was carried out.
