A modeling architecture is presented to better understand the value of thermomechanical systems with agility: the ability to provide an uninterrupted service to a customer while simultaneously adjusting their own energy consumption based on price signals. The results of this modeling show a significant opportunity for devices with increased thermal agility to provide both financial and environmental benefits to customers who adopt them. Systems with multiple hours of agility via storage, advanced controls, fuel switching, or other means could decrease utility costs by up to 50%.
{"title":"The Value of Agile Thermal Systems: A Real-World Approach to Modeling and Prioritizing Agility Versus Efficiency","authors":"Russell Goldfarbmuren","doi":"10.1115/1.4062764","DOIUrl":"https://doi.org/10.1115/1.4062764","url":null,"abstract":"\u0000 A modeling architecture is presented to better understand the value of thermomechanical systems with agility: the ability to provide an uninterrupted service to a customer while simultaneously adjusting their own energy consumption based on price signals. The results of this modeling show a significant opportunity for devices with increased thermal agility to provide both financial and environmental benefits to customers who adopt them. Systems with multiple hours of agility via storage, advanced controls, fuel switching, or other means could decrease utility costs by up to 50%.","PeriodicalId":326594,"journal":{"name":"ASME Journal of Engineering for Sustainable Buildings and Cities","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130876486","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, a life cycle cost-based optimization analysis is carried out to compare the energy and cost performance of diverse sustainable designs of a residential building. These designs include code optimal, net zero energy building, and passive house. It is found that in the case where natural gas is employed, a total energy savings of 77% is optimal. The cost optimal design for electrification achieves 100.12% of energy savings relative to the baseline design but results slightly high life cycle cost than that of the gas cost optimal design. In addition, the results indicate that due to the additional capital costs for the required energy efficient measures, the passive house case is less economically optimal than NZEB design options. Overall, the most cost-optimal designs are found to be for natural gas heated homes with marginally better energy performance than the applicable currently energy efficiency code with 10 kW solar panels.
{"title":"Comparative Analysis Optimal Designs for Passive, Electrified, and Net Zero Energy Residential Buildings","authors":"E. Schwartz, M. Krarti","doi":"10.1115/1.4062325","DOIUrl":"https://doi.org/10.1115/1.4062325","url":null,"abstract":"\u0000 In this paper, a life cycle cost-based optimization analysis is carried out to compare the energy and cost performance of diverse sustainable designs of a residential building. These designs include code optimal, net zero energy building, and passive house. It is found that in the case where natural gas is employed, a total energy savings of 77% is optimal. The cost optimal design for electrification achieves 100.12% of energy savings relative to the baseline design but results slightly high life cycle cost than that of the gas cost optimal design. In addition, the results indicate that due to the additional capital costs for the required energy efficient measures, the passive house case is less economically optimal than NZEB design options. Overall, the most cost-optimal designs are found to be for natural gas heated homes with marginally better energy performance than the applicable currently energy efficiency code with 10 kW solar panels.","PeriodicalId":326594,"journal":{"name":"ASME Journal of Engineering for Sustainable Buildings and Cities","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131858490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The purpose of this research is to study the structure of a Moroccan consumer's home appliance use and, as a consequence, the different patterns of energy consumption. The data in this study is collected from the open MORED (A Moroccan Building Electricity Dataset) dataset. Machine Learning Algorithms and Data Mining Techniques is employed. The findings of this study enable us to comprehend the behavior of a Moroccan consumer in terms of energy consumption and home appliance use. The Inter-Appliance Association and Peak Hours discovered also will be used to construct an Energy Management System specific to a Moroccan building in the coming years. This can serve to develop the framework for effective Energy Demand Management System (EDMS) while also encouraging end-user participation.
这项研究的目的是研究摩洛哥消费者家用电器的使用结构，以及由此产生的能源消费的不同模式。本研究的数据收集自开放的摩洛哥建筑电力数据集(A Moroccan Building Electricity Dataset)数据集。采用机器学习算法和数据挖掘技术。这项研究的结果使我们能够理解摩洛哥消费者在能源消耗和家电使用方面的行为。未来几年，Inter-Appliance Association和高峰时段发现的数据也将用于建设摩洛哥建筑的能源管理系统。这有助于制定有效的能源需求管理系统(EDMS)框架，同时鼓励最终用户参与。
{"title":"Moroccan consumer Energy Consumption itemsets and Inter-Appliance Associations using Machine Learning Algorithms and Data Mining Techniques","authors":"Abdelfattah Abassi, A. Arid, Hussain Benazza","doi":"10.1115/1.4062113","DOIUrl":"https://doi.org/10.1115/1.4062113","url":null,"abstract":"\u0000 The purpose of this research is to study the structure of a Moroccan consumer's home appliance use and, as a consequence, the different patterns of energy consumption. The data in this study is collected from the open MORED (A Moroccan Building Electricity Dataset) dataset. Machine Learning Algorithms and Data Mining Techniques is employed. The findings of this study enable us to comprehend the behavior of a Moroccan consumer in terms of energy consumption and home appliance use. The Inter-Appliance Association and Peak Hours discovered also will be used to construct an Energy Management System specific to a Moroccan building in the coming years. This can serve to develop the framework for effective Energy Demand Management System (EDMS) while also encouraging end-user participation.","PeriodicalId":326594,"journal":{"name":"ASME Journal of Engineering for Sustainable Buildings and Cities","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127875619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
As the rate of urbanization increases, local vegetation is being replaced with man-made materials, causing increasingly adverse impacts on the surface-atmosphere energy balance. These negative effects can be simulated by modeling the urban landscapes in question; however, the main challenges of modeling urban thermal environments are the scale and resolution at which to perform such tasks. Current modeling of urban thermal environments is typically limited to either mesoscale (1 km to 2,000 km) or microscale (< 1 km) phenomena. In the present work, an open-source framework for one-way upstream coupled multiscale urban thermal environment simulations is examined and validated. This coupled simulation can provide valuable insights about the flow behavior and energy transport between mesoscale and microscale interactions. The mesoscale to microscale boundary conditions are coupled together using simulated data from the Advanced Research Weather Research and Forecasting Model (WRF-ARW), a mesoscale numerical weather prediction software, and assimilating it into Parallelized Large-eddy Simulation Model (PALM), a computational fluid dynamics style (CFD-style) software designed for microscale atmospheric flows. The multiscale simulations are tested for grid sensitivity to variations in model input and control parameters, and then experimentally validated against distributed sensor measurements at the Georgia Institute of Technology (Georgia Tech) in Atlanta, GA. Validated microscale atmospheric models with heterogeneous domains can be used to project the thermal benefits of urban heat mitigation strategies and advise building energy usage modeling and policies.
{"title":"Evaluation and Validation of Microscale Atmospheric Modeling with Offline Weather Research and Forecasting Model to Parallelized Large-eddy Simulation Model Forcing Conditions","authors":"Shuv Dey, Evan Mallen, B. Stone, Yogendra P Joshi","doi":"10.1115/1.4062112","DOIUrl":"https://doi.org/10.1115/1.4062112","url":null,"abstract":"\u0000 As the rate of urbanization increases, local vegetation is being replaced with man-made materials, causing increasingly adverse impacts on the surface-atmosphere energy balance. These negative effects can be simulated by modeling the urban landscapes in question; however, the main challenges of modeling urban thermal environments are the scale and resolution at which to perform such tasks. Current modeling of urban thermal environments is typically limited to either mesoscale (1 km to 2,000 km) or microscale (< 1 km) phenomena. In the present work, an open-source framework for one-way upstream coupled multiscale urban thermal environment simulations is examined and validated. This coupled simulation can provide valuable insights about the flow behavior and energy transport between mesoscale and microscale interactions. The mesoscale to microscale boundary conditions are coupled together using simulated data from the Advanced Research Weather Research and Forecasting Model (WRF-ARW), a mesoscale numerical weather prediction software, and assimilating it into Parallelized Large-eddy Simulation Model (PALM), a computational fluid dynamics style (CFD-style) software designed for microscale atmospheric flows. The multiscale simulations are tested for grid sensitivity to variations in model input and control parameters, and then experimentally validated against distributed sensor measurements at the Georgia Institute of Technology (Georgia Tech) in Atlanta, GA. Validated microscale atmospheric models with heterogeneous domains can be used to project the thermal benefits of urban heat mitigation strategies and advise building energy usage modeling and policies.","PeriodicalId":326594,"journal":{"name":"ASME Journal of Engineering for Sustainable Buildings and Cities","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127684834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Optimization and control of building thermal energy storage holds great potential for unlocking demand-side flexibility. As information regarding grid operations become available, grid-interactive building controls inherently become a multi-objective problem. Typical multi-objective optimization frameworks often introduce greater complexity and are less favorable for achieving widespread adoption. With the goal of easing deployment of advanced building controls and aiding the building-to-grid integration, this work aims to evaluate the trade-offs and degrees of sub-optimality introduced by implementing single-objective controllers only. We formulate and apply a single-objective, model predictive control (MPC) framework to individually optimize building thermal storage assets of two types of commercial buildings, informed by future grid scenarios, around energy, economic, environmental and peak demand objectives. For each day, we compare the building's performance in every category as if it had been controlled by four separate single-objective controllers. We reveal the level of harmony that exists between these simple single-objective problems and quantify the potential loss in three of the objectives if the optimal control problem were to respond to only one of the grid signals. Results show that on most days, the carbon and energy controllers retained most of the savings in energy, cost, and carbon. Trade-offs were observed between the peak demand controller and the other objectives, and during extreme energy pricing events. These observations are further discussed in terms of their implications for the design of grid-interactive building incentive signals and utility tariffs.
{"title":"Analyzing harmony and discord among optimal building controllers responding to energy, cost, and carbon reduction objectives","authors":"Lilyi Li, G. Pavlak","doi":"10.1115/1.4056962","DOIUrl":"https://doi.org/10.1115/1.4056962","url":null,"abstract":"\u0000 Optimization and control of building thermal energy storage holds great potential for unlocking demand-side flexibility. As information regarding grid operations become available, grid-interactive building controls inherently become a multi-objective problem. Typical multi-objective optimization frameworks often introduce greater complexity and are less favorable for achieving widespread adoption. With the goal of easing deployment of advanced building controls and aiding the building-to-grid integration, this work aims to evaluate the trade-offs and degrees of sub-optimality introduced by implementing single-objective controllers only. We formulate and apply a single-objective, model predictive control (MPC) framework to individually optimize building thermal storage assets of two types of commercial buildings, informed by future grid scenarios, around energy, economic, environmental and peak demand objectives. For each day, we compare the building's performance in every category as if it had been controlled by four separate single-objective controllers. We reveal the level of harmony that exists between these simple single-objective problems and quantify the potential loss in three of the objectives if the optimal control problem were to respond to only one of the grid signals. Results show that on most days, the carbon and energy controllers retained most of the savings in energy, cost, and carbon. Trade-offs were observed between the peak demand controller and the other objectives, and during extreme energy pricing events. These observations are further discussed in terms of their implications for the design of grid-interactive building incentive signals and utility tariffs.","PeriodicalId":326594,"journal":{"name":"ASME Journal of Engineering for Sustainable Buildings and Cities","volume":"106 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117341498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Qatar Environment and Energy Research Institute (QEERI) hosted a workshop entitled “Impact of Sustainable Buildings in Arid Environment on the Indoor and Outdoor Air Quality,” held in Doha, Qatar, on May 17–19, 2022, co-funded by the Qatar National Research Fund (QNRF), and co-organized by City College of New York (CCNY). The workshop provided a premier interdisciplinary platform for local researchers and enablers to engage and exchange knowledge and experiences with international leading practitioners and subject matter experts in the fields of sustainable buildings, indoor and outdoor air quality, and the urban heat island phenomena. A diverse number of regional partners and stakeholders were represented. The workshop benefitted from a pool of invited international subject experts from various universities and entities. The outcome-driven workshop included breakout sessions where participants actively engaged in brainstorming discussions guided by facilitators. The discussions focused on driving impact in Qatar and beyond by examining the current research landscape and identifying collaborative opportunities. The short-term and long-term outcomes of potential initiatives and project proposals are outlined in this summary. An example of a short-term outcome is the proposed collaborative project to investigate the impact of almost doubling the state of Qatar’s population (over 1.5 million fans are expected to visit the country during the World Cup causing a shock to the system) on vital elements in the city, such as mobility, telecommunication services, and the local environment. In addition, multiple potential research proposals with international collaborations were proposed. A special issue on the subject in the Journal of Engineering for Sustainable Buildings and Cities was recommended as an immediate actionable outcome.
{"title":"Impact of Sustainable Buildings in Arid Environment on the Indoor and Outdoor Air Quality: Workshop Report","authors":"A. Beitelmal, J. Gonzalez-Cruz, C. Fountoukis","doi":"10.1115/1.4056545","DOIUrl":"https://doi.org/10.1115/1.4056545","url":null,"abstract":"\u0000 Qatar Environment and Energy Research Institute (QEERI) hosted a workshop entitled “Impact of Sustainable Buildings in Arid Environment on the Indoor and Outdoor Air Quality,” held in Doha, Qatar, on May 17–19, 2022, co-funded by the Qatar National Research Fund (QNRF), and co-organized by City College of New York (CCNY). The workshop provided a premier interdisciplinary platform for local researchers and enablers to engage and exchange knowledge and experiences with international leading practitioners and subject matter experts in the fields of sustainable buildings, indoor and outdoor air quality, and the urban heat island phenomena. A diverse number of regional partners and stakeholders were represented. The workshop benefitted from a pool of invited international subject experts from various universities and entities. The outcome-driven workshop included breakout sessions where participants actively engaged in brainstorming discussions guided by facilitators. The discussions focused on driving impact in Qatar and beyond by examining the current research landscape and identifying collaborative opportunities. The short-term and long-term outcomes of potential initiatives and project proposals are outlined in this summary. An example of a short-term outcome is the proposed collaborative project to investigate the impact of almost doubling the state of Qatar’s population (over 1.5 million fans are expected to visit the country during the World Cup causing a shock to the system) on vital elements in the city, such as mobility, telecommunication services, and the local environment. In addition, multiple potential research proposals with international collaborations were proposed. A special issue on the subject in the Journal of Engineering for Sustainable Buildings and Cities was recommended as an immediate actionable outcome.","PeriodicalId":326594,"journal":{"name":"ASME Journal of Engineering for Sustainable Buildings and Cities","volume":"192 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115582640","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Energy conservation is a concern in many commercial industries, and consequently facility operators are turning to various efficiency and alternative measures to reduce electricity costs. Growing use of intermittent resources, energy storage systems (ESSs) and demand side management (DSM) options are also gaining interest to maximize potential energy savings. Here we study the potential of ESSs versus DSM for water utilities through a case study of the National Energy Laboratory of the Hawaii Authority (NELHA). NELHA is a multizone water utility, where most electricity is dedicated to pumping water. In this study the optimization of the NELHA's overall electricity charges, using both ESSs or DSM via pump load shifting and optimization of pump house output is investigated. Optimization is performed to determine the optimal size of the batteries considering the water demand and energy costs in each zone. An extended approach of considering the characteristics of individual pumps on each pump house in the optimization model is applied to provide insight to the proper optimization framework for selecting individual pumps depending on the current zonal load, given pump efficiencies and maximum flow rates from each pump. The outcome from mathematical models using general quadratic pump efficiency functions and a simplified linear version of pump efficiency is compared to determine the significance of this difference in modeling methodology. Additionally, the effect of increasing solar power on electricity purchased is analyzed. This work will help to establish the role of ESS and DSM in energy savings for water utility industry.
{"title":"OPTIMIZATION OF ENERGY STORAGE SYSTEMS AND DEMAND SIDE MANAGEMENT TO MAXIMIZE WATER UTILITY SAVINGS: A HAWAII CASE STUDY","authors":"Yogesh Manoharan, K. Olson, A. Headley","doi":"10.1115/1.4056544","DOIUrl":"https://doi.org/10.1115/1.4056544","url":null,"abstract":"\u0000 Energy conservation is a concern in many commercial industries, and consequently facility operators are turning to various efficiency and alternative measures to reduce electricity costs. Growing use of intermittent resources, energy storage systems (ESSs) and demand side management (DSM) options are also gaining interest to maximize potential energy savings. Here we study the potential of ESSs versus DSM for water utilities through a case study of the National Energy Laboratory of the Hawaii Authority (NELHA). NELHA is a multizone water utility, where most electricity is dedicated to pumping water. In this study the optimization of the NELHA's overall electricity charges, using both ESSs or DSM via pump load shifting and optimization of pump house output is investigated. Optimization is performed to determine the optimal size of the batteries considering the water demand and energy costs in each zone. An extended approach of considering the characteristics of individual pumps on each pump house in the optimization model is applied to provide insight to the proper optimization framework for selecting individual pumps depending on the current zonal load, given pump efficiencies and maximum flow rates from each pump. The outcome from mathematical models using general quadratic pump efficiency functions and a simplified linear version of pump efficiency is compared to determine the significance of this difference in modeling methodology. Additionally, the effect of increasing solar power on electricity purchased is analyzed. This work will help to establish the role of ESS and DSM in energy savings for water utility industry.","PeriodicalId":326594,"journal":{"name":"ASME Journal of Engineering for Sustainable Buildings and Cities","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126582792","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, the energy benefits of dynamic PV-integrated overhang systems are evaluated for office buildings. The benefits of dynamic PV-integrated overhangs combined energy efficiency by decreasing both heating and cooling energy demand and on-site renewable power generation by deploying tracking PV panels. The energy performance of dynamic PV-integrated overhangs is considered for various design and operation conditions. Specifically, the impacts of various design features are considered such as overhang depth, window size, glazing type, and HVAC system type. Moreover, the effects of operating conditions are assessed including the location of the building and the control strategy of the dynamic PV-integrated systems such as load tracking, demand tracking, and PV tracking. The results of the various analyses indicate that the heating and cooling energy demands of the dynamic overhangs are mostly affected by the window glazing type and window overhang depths. The analysis shows that the use of demand tracking maximizes the energy performance of the dynamic PV-integrated overhangs when deployed to US office buildings.
{"title":"Assessment of Dynamic Photovoltaic Shading Systems on Energy Performance of Commercial Buildings","authors":"Dana Alwelayti, Ammar H. A. Dehwah, M. Krarti","doi":"10.1115/1.4056394","DOIUrl":"https://doi.org/10.1115/1.4056394","url":null,"abstract":"\u0000 In this paper, the energy benefits of dynamic PV-integrated overhang systems are evaluated for office buildings. The benefits of dynamic PV-integrated overhangs combined energy efficiency by decreasing both heating and cooling energy demand and on-site renewable power generation by deploying tracking PV panels. The energy performance of dynamic PV-integrated overhangs is considered for various design and operation conditions. Specifically, the impacts of various design features are considered such as overhang depth, window size, glazing type, and HVAC system type. Moreover, the effects of operating conditions are assessed including the location of the building and the control strategy of the dynamic PV-integrated systems such as load tracking, demand tracking, and PV tracking. The results of the various analyses indicate that the heating and cooling energy demands of the dynamic overhangs are mostly affected by the window glazing type and window overhang depths. The analysis shows that the use of demand tracking maximizes the energy performance of the dynamic PV-integrated overhangs when deployed to US office buildings.","PeriodicalId":326594,"journal":{"name":"ASME Journal of Engineering for Sustainable Buildings and Cities","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122489081","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mariana Migliori, H. Najafi, A. Fabregas, Troy V. Nguyen
Building energy models (BEMs) are developed by subject matter experts during the design phase to help with decision making for achieving a more energy-efficient design. A BEM that is created based on “as-designed” condition to predict building energy consumption can become much less accurate during the lifetime of the building given the potential changes to the “in-operation” conditions. While BEMs can be adjusted to address operational changes, the end-user (i.e. building owners) usually do not possess the knowledge to update physics-based models (e.g., eQuest) and therefore the initial BEM may no longer be useful to them. In the present paper, an approach is proposed and assessed through which a physics-based model is developed using eQuest and simulated for several different operating conditions. The resulting data are then used for training an artificial neural network (ANN) which serves as a simple and data-driven model for prediction of building energy consumption in response to changes in operating conditions. A case study is performed for a building in Melbourne, FL to explore the changes occurred in the building schedule of operation during COVID-19 pandemic and it's impact on the performance of BEM. The trained ANN is tested against the actual measured data for energy consumption under different scenarios and good agreement between the results are found. The approach presented can be used to establish data-driven BEMs that remain accurate in response to sudden changes in building operating conditions.
{"title":"Neural Network-Based Building Energy Models for Adapting to Post-Occupancy Conditions: A Case Study for Florida","authors":"Mariana Migliori, H. Najafi, A. Fabregas, Troy V. Nguyen","doi":"10.1115/1.4056393","DOIUrl":"https://doi.org/10.1115/1.4056393","url":null,"abstract":"\u0000 Building energy models (BEMs) are developed by subject matter experts during the design phase to help with decision making for achieving a more energy-efficient design. A BEM that is created based on “as-designed” condition to predict building energy consumption can become much less accurate during the lifetime of the building given the potential changes to the “in-operation” conditions. While BEMs can be adjusted to address operational changes, the end-user (i.e. building owners) usually do not possess the knowledge to update physics-based models (e.g., eQuest) and therefore the initial BEM may no longer be useful to them. In the present paper, an approach is proposed and assessed through which a physics-based model is developed using eQuest and simulated for several different operating conditions. The resulting data are then used for training an artificial neural network (ANN) which serves as a simple and data-driven model for prediction of building energy consumption in response to changes in operating conditions. A case study is performed for a building in Melbourne, FL to explore the changes occurred in the building schedule of operation during COVID-19 pandemic and it's impact on the performance of BEM. The trained ANN is tested against the actual measured data for energy consumption under different scenarios and good agreement between the results are found. The approach presented can be used to establish data-driven BEMs that remain accurate in response to sudden changes in building operating conditions.","PeriodicalId":326594,"journal":{"name":"ASME Journal of Engineering for Sustainable Buildings and Cities","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114375381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In recent years there has been an increased interest in improving the energy efficiency of the Southeast Asian building sector. However, much of this work has focused on residential and commercial buildings rather than industrial buildings. Therefore, this work undertook a case study of the energy used in a Singaporean industrial building complex typical of those used in the light manufacturing sector in the region. A building energy simulation analysis was performed on the x91as built’ building and was validated using measured energy usage data. Subsequently a parametric analysis was utilized to identify opportunities for reducing energy use on the site. The results indicate that energy savings of over 15% could be achieved by improving the performance of the industrial equipment, HVAC system, lighting, and building thermal envelope. Of these factors, improving the energy efficiency of the equipment and relaxing the HVAC setpoint temperature accounted for over 10%. Given the typical nature of the building, it is believed that the results are indicative of what may be achievable in other light manufacturing complexes in Southeast Asia, and in similar locations more generally.
{"title":"Reducing energy use in light industrial buildings in Southeast Asia: A Singaporean case study","authors":"Guo Li, T. Anderson","doi":"10.1115/1.4056201","DOIUrl":"https://doi.org/10.1115/1.4056201","url":null,"abstract":"\u0000 In recent years there has been an increased interest in improving the energy efficiency of the Southeast Asian building sector. However, much of this work has focused on residential and commercial buildings rather than industrial buildings. Therefore, this work undertook a case study of the energy used in a Singaporean industrial building complex typical of those used in the light manufacturing sector in the region. A building energy simulation analysis was performed on the x91as built’ building and was validated using measured energy usage data. Subsequently a parametric analysis was utilized to identify opportunities for reducing energy use on the site. The results indicate that energy savings of over 15% could be achieved by improving the performance of the industrial equipment, HVAC system, lighting, and building thermal envelope. Of these factors, improving the energy efficiency of the equipment and relaxing the HVAC setpoint temperature accounted for over 10%. Given the typical nature of the building, it is believed that the results are indicative of what may be achievable in other light manufacturing complexes in Southeast Asia, and in similar locations more generally.","PeriodicalId":326594,"journal":{"name":"ASME Journal of Engineering for Sustainable Buildings and Cities","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128838017","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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