Xiao Wang , Xuezheng Wang , Xuyuan Kang , Bing Dong , Da Yan
{"title":"Physics-consistent input convex neural network-driven reinforcement learning control for multi-zone radiant ceiling heating and cooling systems: An experimental study","authors":"Xiao Wang , Xuezheng Wang , Xuyuan Kang , Bing Dong , Da Yan","doi":"10.1016/j.enbuild.2024.115105","DOIUrl":"10.1016/j.enbuild.2024.115105","url":null,"abstract":"<div><div>Radiant ceiling heating and cooling system is a technology used for space heating and cooling. Owing to the variable weather conditions, occupant behavior, and thermal lag of the system, it is challenging to design a control strategy to reduce air-conditioning energy consumption while maintaining the thermal environment. This study is the first pilot implementation of a physics-consistent input convex neural network (PCICNN)-driven reinforcement learning (RL) approach for real-world multi-zone radiant ceiling heating and cooling systems. A multi-zone PCICNN based on a graph neural network (GNN) was developed to simulate the zone temperature. The radiant panel load was simulated using the physics-based ε-NTU method. The PCICNN-driven RL agent was based on the soft actor-critic algorithm and trained in an environment model comprising the PCICNN and ε-NTU models. The proposed controller was deployed in real-time on one floor of an office building for one month. The real-world implementation showed that the proposed PCICNN-driven RL control can reduce the radiant panel cooling load by up to 33% compared with the inherited baseline control strategy under similar weather conditions. This study provides a comprehensive demonstration of real-world data-driven building controls and leverages future research on advanced building control.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"327 ","pages":"Article 115105"},"PeriodicalIF":6.6,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142718351","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Lin Zhou , Shun Li , Zhengxuan Liu , Yuekuan Zhou , Bao-Jie He , Zhenya Zhang , Hanbing Wang , Guoqiang Zhang
{"title":"Advancing zero-carbon community in China: policy analysis, implementation challenges, and strategic recommendations","authors":"Lin Zhou , Shun Li , Zhengxuan Liu , Yuekuan Zhou , Bao-Jie He , Zhenya Zhang , Hanbing Wang , Guoqiang Zhang","doi":"10.1016/j.enbuild.2024.115106","DOIUrl":"10.1016/j.enbuild.2024.115106","url":null,"abstract":"<div><div>Zero-carbon community (ZCC) is essential in addressing critical social and environmental challenges, particularly in reducing energy consumption, lowering carbon emissions, and decreasing reliance on fossil fuels. However, several issues are still unclear, including inconsistent definitions of ZCC, the lack of detailed policy analyses, and limited exploration of implementation challenges and solutions persist. This study addresses these gaps by conducting a comprehensive analysis of the drivers and barriers to ZCC development in China. It begins with a detailed review of the definitions of ZCC, comparing and contrasting them from both domestic and international perspectives. Then, it evaluates existing incentives, categorizes them into policy documents, laws, and standards while assessing their evolution and real-world applications. This study also presents case studies of exemplary ZCC, including the Beddington Community in the UK and the Zero Carbon Pavilion at the Shanghai World Expo Park in China. These cases offer insights into practical approaches, societal impacts, and advanced practices, proposing a ZCC construction model tailored to China’s unique economic and policy environment. Furthermore, the study identifies key barriers to adopting ZCC in China and proposes targeted recommendations across five domains: administrative, economic, technological, socio-cultural, and environmental. A “macro-meso-micro” implementation pathway is developed, emphasizing stakeholder collaboration as a core element for successful execution. This study systematically reviews and critically analyzes current policies and practices related to ZCC, and offering valuable theoretical guidance for developing regulations and standards, along with practical solutions to address current implementation challenges.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"328 ","pages":"Article 115106"},"PeriodicalIF":6.6,"publicationDate":"2024-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142759695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jiaming Cui , Junjie Li , Yi Du , Guillaume Habert
{"title":"Cement-MgO synergetic stabilized earth-straw mix: From material performance to building simulation","authors":"Jiaming Cui , Junjie Li , Yi Du , Guillaume Habert","doi":"10.1016/j.enbuild.2024.115099","DOIUrl":"10.1016/j.enbuild.2024.115099","url":null,"abstract":"<div><div>The production of traditional building materials like cement, lime, and common fired bricks consumes considerable energy and resources and causes atmospheric pollution. Thus, it’s essential to develop more eco-friendly materials for new construction. This research focuses on an earth-straw mixture stabilized hybridly with cement and active MgO. Three aspects scaled from material mix design and mechanical performance to building energy-saving simulation were examined. Three types of earth were considered, and the effects of MgO on M−ME were studied through compression strength, thermal conductivity and TGA tests. The best compressive strength achieved was 12.5 MPa (about 167 % of the standard for non-burned bricks and 125 % of the standard for minimum fired bricks), and the best thermal conductivity was 0.371 / (m·K) (only 44.2 % of that of common fired bricks). Using Design Builder software, energy load differences between M−ME and fired clay brick walls were simulated under given conditions, and the indoor thermal environment was analyzed. Based on the amount of wall earthwork used in the project, the M−ME wall (YC3) can theoretically capture approximately 12.80 kg/m<sup>3</sup> of carbon from the air under natural curing conditions, mean while reducing heating energy consumption by 9.49 %. Overall, the utilization of soil and the presence of plant straw give M−ME advantages in carbon footprint and thermal performance over sintered and concrete bricks. As a new energy-saving material, M−ME significantly contributes to carbon reduction in production and operation phases, possessing great potential in decarbonizing the emission of the building sector.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"327 ","pages":"Article 115099"},"PeriodicalIF":6.6,"publicationDate":"2024-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142701424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Teng Peng , Nianping Li , Yingdong He , Binquan Liang , Qiuping Liu , Xing Chen , Yuqing Sun
{"title":"A novel mathematical control algorithm (HNU Shading) for different window shades based on HNU solar model","authors":"Teng Peng , Nianping Li , Yingdong He , Binquan Liang , Qiuping Liu , Xing Chen , Yuqing Sun","doi":"10.1016/j.enbuild.2024.115101","DOIUrl":"10.1016/j.enbuild.2024.115101","url":null,"abstract":"<div><div>Window shading control helps maximize daylight use for creating comfortable indoor luminous environments and reduces over-illuminance and glare discomfort. This study proposes a novel mathematical algorithm (the HNU Shading algorithm) for calculating the distribution of direct sunlight indoors and adjusting window shades to avoid over-illuminance and glare indoors. The algorithm uses the sun position, window-ambient illuminance, window design parameters, and the controlled area (desktop and occupant’s head) as inputs to control different window shades (the vertical blind, horizontal blind, exterior awning, and interior shutter in this study), and the performance was verified via experiments and simulations. The results show that the HNU Shading algorithm has a high precision level of predicting the distribution area of direct sunlight with the error at 0.01–0.07 m. And it prevents the high illuminance from the desktop and keeps it lower than 3,000 lx under most of conditions with different window directions, shade types, seasons, and sunlight intensities. Meanwhile, with the HNU Shading algorithm, the Daylight Glare Probability (DGP) is lower than 0.4 during the period when intolerable glare happens. This study contributes to configuring practical and universal real-time window shading controls for different buildings with different window shade types, such as offices, classrooms, libraries, airports, and railway stations.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"328 ","pages":"Article 115101"},"PeriodicalIF":6.6,"publicationDate":"2024-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142759746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mohammad Nyme Uddin , Minhyun Lee , Xue Cui , Xuange Zhang
{"title":"Predicting occupant energy consumption in different indoor layout configurations using a hybrid agent-based modeling and machine learning approach","authors":"Mohammad Nyme Uddin , Minhyun Lee , Xue Cui , Xuange Zhang","doi":"10.1016/j.enbuild.2024.115102","DOIUrl":"10.1016/j.enbuild.2024.115102","url":null,"abstract":"<div><div>Accurately predicting occupant energy consumption in buildings is essential for optimizing energy management and promoting sustainability. However, gathering reliable stochastic data on occupant energy consumption poses significant challenges. This research proposes a hybrid approach that integrates Agent-Based Modeling (ABM), System Dynamics (SD), Building Information Modeling (BIM), and Machine Learning (ML) techniques to predict energy consumption in different indoor layout configurations, including rectangular, square, and compound shapes. Initially, the hybrid model (ABM-SD-BIM) focuses on generating a comprehensive and precise dataset. Using this dataset, various ML models are developed to predict energy consumption. The results demonstrate that the ML model outperforms earlier ML models in terms of mean squared error (MSE) and root mean squared error (RMSE), indicating improved prediction accuracy. Specifically, for Layout 3, representing a compound shape configuration, the ML model achieves an MSE of 0.03 and an RMSE of 0.17. Furthermore, the ML model exhibits a high R2 score of 0.92, indicating a good fit to the data. Comparative analysis of different ML models reveals that LightGBM performs the best, with the lowest MSE and RMSE values for the compound shape configuration. On the other hand, XGBoost, RF, and DT models exhibit higher MSE and RMSE values, indicating relatively higher prediction errors. These findings underscore the effectiveness of the hybrid approach, particularly in compound shape configurations, for accurately predicting energy consumption in various indoor layouts.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"328 ","pages":"Article 115102"},"PeriodicalIF":6.6,"publicationDate":"2024-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142759748","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jinhui Tang , Le Sha , Hejiang Sun , Wenshuai Zhang
{"title":"Optimizing energy efficiency in buildings’ cold water systems: A differential pressure control-based global approach","authors":"Jinhui Tang , Le Sha , Hejiang Sun , Wenshuai Zhang","doi":"10.1016/j.enbuild.2024.115108","DOIUrl":"10.1016/j.enbuild.2024.115108","url":null,"abstract":"<div><div>Buildings’ cold water systems have become increasingly complex, with independent equipment control leading to greater energy consumption and greenhouse gas emissions. To improve control efficiency and maximize energy savings, simulation and experimental studies of these systems are essential, although full-scale experimental setups are rare. This paper employs FloMASTER modeling to establish a large-scale practical pipeline network system for validating models, evaluating strategies, and optimizing energy efficiency. The modeling method is validated as accurate, with normalized mean bias error (NMBE) and coefficient of variation of the root mean square error (CVRMSE) values for nodal pressure and flow distribution meeting established evaluation criteria. A quantitative evaluation of constant differential pressure control strategies, considering hydraulic and thermal characteristics as well as energy consumption, reveals that the strategy based on intermediate loop users performs best. This strategy achieves an average hydraulic imbalance rate of only 5.05%, the quickest hydraulic stabilization and restoration time, and comparable secondary pump energy consumption across three control strategies. Furthermore, this simulation study proposes a global combined control strategy that enables more stable operation of the system, reduces chiller energy consumption by 4.66%, secondary pump energy consumption by 9.93%, and overall system energy consumption by approximately 5.38%. These findings suggest that this methodology can be applied to large-scale pipeline networks in complex cold water systems, yielding substantial energy savings.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"327 ","pages":"Article 115108"},"PeriodicalIF":6.6,"publicationDate":"2024-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142701416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kyungjae Lee , Hyunwoo Lim , Jeongyun Hwang , Doyeon Lee
{"title":"Development of building benchmarking index for improving gross-floor-area-based energy use intensity","authors":"Kyungjae Lee , Hyunwoo Lim , Jeongyun Hwang , Doyeon Lee","doi":"10.1016/j.enbuild.2024.115103","DOIUrl":"10.1016/j.enbuild.2024.115103","url":null,"abstract":"<div><div>Energy benchmarking is essential for evaluating building performance and developing energy reduction strategies, typically using floor-area-based energy use intensity (EUI). However, this method has limitations. Studies show that metrics such as site energy, source energy, and CO2 emissions can produce varying benchmark results for the same building, raising concerns about reliability. As carbon reduction in buildings becomes increasingly important, there is a need for comprehensive indicators that assess both energy and carbon efficiency. This study introduces the Building Performance Index (BPI), that integrates energy and carbon emission efficiencies. Using a database of all buildings in Seoul, South Korea, we compared five BPI variants: conventional floor-area-based BPI, floor-area-based BPI adjusted for floor area ratio, volume BPI based on floor area, volume BPI adjusted for floor area ratio, and volume BPI based on building footprint. These were evaluated based on six criteria, including model simplicity, sensitivity analysis, data reliability, and indicator stability. While the relative importance of these criteria was not prioritized, this study proposes a shift from traditional two-dimensional metrics to more comprehensive three-dimensional volume-based metrics, offering practical guidance for decision-makers in selecting more reliable benchmarking methods.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"328 ","pages":"Article 115103"},"PeriodicalIF":6.6,"publicationDate":"2024-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142759745","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Polina Kurtser , Kailun Feng , Thomas Olofsson , Aitor De Andres
{"title":"One-class anomaly detection through color-to-thermal AI for building envelope inspection","authors":"Polina Kurtser , Kailun Feng , Thomas Olofsson , Aitor De Andres","doi":"10.1016/j.enbuild.2024.115052","DOIUrl":"10.1016/j.enbuild.2024.115052","url":null,"abstract":"<div><div>Characterizing the energy performance of building components and locating anomalies is necessary for effectively refurbishing existing buildings. It is often challenging because defects in building envelopes deteriorate without being visible. Passive infrared thermography (PIRT) is a powerful tool used in building inspection. However, thermal image interpretation requires significant domain knowledge and is prone to artifacts arising from a complex interplay of factors. As a result, PIRT-based inspections require skilled professionals, and are labor-intensive and time-consuming. Artificial intelligence (AI) holds great promise to automate building inspection, but its application remains challenging because common approaches rely on extensive labeling and supervised modeling. It is recognized that there is a need for a more applicable and flexible approach to leverage AI to assist PIRT in realistic building inspections. In this study, we present a label-free method for detecting anomalies during thermographic inspection of building envelopes. It is based on the AI-driven prediction of thermal distributions from color images. Effectively the method performs as a one-class classifier of the thermal image regions with a high mismatch between the predicted and actual thermal distributions. The algorithm can learn to identify certain features as normal or anomalous by selecting the target sample used for training. The proposed method has unsupervised modeling capabilities, greater applicability and flexibility, and can be widely implemented to assist human professionals in routine building inspections or combined with mobile platforms to automate the inspection of large areas.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"328 ","pages":"Article 115052"},"PeriodicalIF":6.6,"publicationDate":"2024-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142759653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Chengchu Yan , Kai Hu , Chao Xu , Chaoqun Zhuang , Junjian Fang , Yanfeng Gong
{"title":"A novel high-dimensional sensor calibration framework integrating thermodynamic laws in complex HVAC systems","authors":"Chengchu Yan , Kai Hu , Chao Xu , Chaoqun Zhuang , Junjian Fang , Yanfeng Gong","doi":"10.1016/j.enbuild.2024.115098","DOIUrl":"10.1016/j.enbuild.2024.115098","url":null,"abstract":"<div><div>Accurate calibration of sensors is critical for ensuring energy efficient operation of Heating, Ventilation, and Air Conditioning (HVAC) systems in buildings. Due to the high dimensionality of sensor data and the complexity of multiple-fault scenarios, calibrating sensors in large and complex HVAC systems presents significant challenges. To address this issue, this study introduces a novel sensor calibration framework that integrates thermodynamic laws for high-dimensional sensor calibration in complex HVAC systems. The traditional calibration method heavily relies on accurate data, making it difficult to apply in practical engineering projects. The innovative aspect of our method lies in its integration of thermodynamic laws, such as mass balance and energy conservation, with sensor calibration framework. This approach enables the framework to handle high-dimensional sensor measurements effectively without any training data. We compared five optimization algorithms and applied them to a central cooling system in Hong Kong. The results demonstrated that the simulated annealing (SA) is the most robust for solving the calibration problem, even in scenarios with up to 21 faulty sensors, with the calibrated sensor accuracy meeting the standards for conventional chiller plant operations. This novel framework provides a robust and reliable solution for high-dimensional sensor calibration in large and complex HVAC systems, addressing the growing need for precise sensor calibration as the number of installed sensors increases.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"327 ","pages":"Article 115098"},"PeriodicalIF":6.6,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142701425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Salim Barbhuiya , Bibhuti Bhusan Das , Dibyendu Adak
{"title":"Energy storage potential of cementitious materials: Advances, challenges and future Directions","authors":"Salim Barbhuiya , Bibhuti Bhusan Das , Dibyendu Adak","doi":"10.1016/j.enbuild.2024.115063","DOIUrl":"10.1016/j.enbuild.2024.115063","url":null,"abstract":"<div><div>This review paper investigates the use of cementitious materials for energy storage, emphasizing their role in advancing sustainable development. It starts with a comprehensive overview of energy storage technologies and explores the key properties of cementitious materials that make them suitable for energy storage, alongside the challenges and opportunities they present. The review covers different energy storage mechanisms, including chemical, thermal, and electrical methods, highlighting the efficiency and capacity of each approach. Performance evaluation is addressed through specific criteria, experimental techniques, and case studies, with numerical outcomes provided to illustrate the effectiveness of these materials in energy storage. The paper also discusses potential applications in energy infrastructure and construction, identifying emerging technological advancements and trends. Environmental and economic considerations, such as sustainability benefits and cost analysis, are evaluated in detail. Finally, the review summarizes key insights, outlines the implications for sustainable energy systems, and offers specific recommendations for future research and development to optimize the use of cementitious materials in energy storage.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"327 ","pages":"Article 115063"},"PeriodicalIF":6.6,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142701420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}