Energy and Buildings最新文献

{"title":"Impacts of radiative cooling paints for CO2 reduction and global warming mitigation","authors":"Emily Barber ,&nbsp;Navdeep Vansal ,&nbsp;Ziqi Fang ,&nbsp;Yu-Wei Hung ,&nbsp;Joseph Peoples ,&nbsp;Rebecca Ciez ,&nbsp;Travis Horton ,&nbsp;Xiulin Ruan","doi":"10.1016/j.enbuild.2025.115458","DOIUrl":"10.1016/j.enbuild.2025.115458","url":null,"abstract":"<div><div>Daytime radiative cooling has attracted significant interest recently because it uses the high reflection of sunlight and emission of thermal radiation to cool objects below the ambient temperature without power consumption. However, the year-round impact of modern daytime radiative cooling paints on carbon reduction and global warming mitigation as compared to conventional black roofs and previous cool roofs is not well understood. Here we choose ultrawhite CaCO₃ cooling paint used on buildings as a prototype system and conduct a comprehensive analysis of the impact of two distinct mechanisms on global climate. The first mechanism is carbon emission reduction at power plants due to building air conditioning power savings. The second mechanism is due to increased direct heat rejection by the ultrawhite roof to deep space, where the thermal effect is equivalent to CO₂ reduction from the atmosphere. Our results show that the impact of the paints on the climate was always positive for all climate zones, reducing up to 665 lbs of CO_2eq from the atmosphere per m² of paint applied over a 100-year span. Additionally, the paints are most effective in hot/warm/mild and dry climates, and depending on climate zone, 0.94 % − 2.02 % coverage of the paint on the earth’s total surface could stop the global warming trend.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"332 ","pages":"Article 115458"},"PeriodicalIF":6.6,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143421735","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}

{"title":"Autoencoder reconstruction residual-Wasserstein distance based in-situ calibration for indoor environment spatial expansion virtual sensors","authors":"Hakjong Shin,&nbsp;Seng-Kyoun Jo,&nbsp;Won-Kyu Choi","doi":"10.1016/j.enbuild.2025.115452","DOIUrl":"10.1016/j.enbuild.2025.115452","url":null,"abstract":"<div><div>Increasing reliance on digital twin technology for managing indoor environments necessitates the development of spatial expansion virtual sensors (SEVS). However, in practical applications, SEVS performance often deteriorates due to shifts in data distribution and environmental conditions, presenting challenges for consistent reliability. Most existing SEVS research has primarily focused on initial model development, with limited consideration to in-situ calibration strategies. This study introduces an autoencoder reconstruction residual-Wasserstein distance (AR-WD)-based error estimation model, designed for spatial expansion virtual sensors with the primary objective of enhancing their performance in practical applications. The proposed model utilizes residuals from autoencoders and Wasserstein features, which can be derived without additional sensor installations, for real-time calibration. A comprehensive evaluation was conducted using temperature data from a pigsty, where the AR-WD model demonstrated robust performance across various machine learning algorithms, particularly with random forest and XGBoost, showing high predictive accuracy with a mean absolute error as low as 0.086. These findings suggest that the integration of AR-WD features significantly enhances the reliability and accuracy of virtual sensors. In addition, the AR-WD model leverages the unique characteristics of SEVS to enable real-time error estimation based solely on input data variations, thereby addressing common limitations of non-intrusive calibration methods. This research not only advances the field of virtual sensor development but also provides critical insights for optimizing sensor systems in complex indoor settings.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"333 ","pages":"Article 115452"},"PeriodicalIF":6.6,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143427771","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}

{"title":"A review of buildings dynamic life cycle studies by bibliometric methods","authors":"Lin Zheng ,&nbsp;Xiaoyu Yan","doi":"10.1016/j.enbuild.2025.115453","DOIUrl":"10.1016/j.enbuild.2025.115453","url":null,"abstract":"<div><div>This paper presents a bibliometric analysis examining dynamic life cycle (LC) studies in the building sector from 2007 to 2024, focusing on works that integrate or apply three key methods: Building Information Modelling (BIM), Machine Learning (ML), and Geographic Information Systems (GIS). By analysing a broad range of publications from the Web of Science database and Scopus database, we investigate publication trends and impacts, collaboration patterns, and highly cited work. A total of 549 core articles were identified within the study scope, with 3,136 additional records included for a sensitivity analysis. Our findings indicate that BIM-LC is the most prevalent, with extensive international collaborations. ML-LC, although a newer area, shows a rapid growth rate and potential in this area. GIS-LC shows steady contributions reflecting ongoing relevance to spatial sustainability. We also propose a conceptual framework illustrating how BIM, ML, and GIS can enhance dynamic LC studies in buildings, highlighting opportunities for practical application, such as standardised dynamic data and workflows, advanced algorithms, pilot experiments and real-world validation. By providing insights into bibliometric analysis and a conceptual framework, this review advances understanding of dynamic LC studies in the building sector.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"332 ","pages":"Article 115453"},"PeriodicalIF":6.6,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143395765","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}

{"title":"Experimental and numerical investigation of vertical temperature gradients in warehouses: Retrofit interventions to manage temperature sensitive products","authors":"Mümine Gerçek Şen,&nbsp;Tahsin Başaran","doi":"10.1016/j.enbuild.2025.115456","DOIUrl":"10.1016/j.enbuild.2025.115456","url":null,"abstract":"<div><div>This paper investigates vertical temperature gradients in warehouse design to ensure optimal storage conditions. In warehouses with ceilings over 10.0 m high, buoyancy-driven warm air often causes significant temperature disparities. This study uses a combination of field measurements and computational fluid dynamics (CFD) simulations to measure thermal stratification. It also examines the impact of mechanical systems, such as ceiling-mounted radiant cooling and floor heating. CFD simulations are validated against field data, showing that destratification cooling systems can reduce ceiling temperatures by up to 4.0 °C in summer. These systems can also raise floor temperatures by 7.0 °C during heating. Field data collected over a year show vertical temperature gradients up to 3.0 °C. However, the temperature difference between ceiling and floor remains below 0.2 °C, keeping indoor temperatures within an ideal range of 20.0–24.0 °C year-round. The study highlights the benefits of combining radiant cooling with floor heating to achieve temperature uniformity. Floor heating scenarios generate air velocities of up to 0.8 m/s, with an average velocity of 0.2 m/s. In contrast, ceiling-mounted cooling systems result in slightly lower air velocities, reaching a maximum of 0.5 m/s and an average of 0.1 m/s. This research is especially relevant for temperature-sensitive products, as illustrated by a case study involving cured tobacco bales. The retrofit proposals ensure optimal indoor conditions and reduce vertical temperature gradients. These findings validate the proposed methodology as a reliable approach for managing temperature variations in warehouses handling temperature-sensitive goods.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"332 ","pages":"Article 115456"},"PeriodicalIF":6.6,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143421721","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}

{"title":"Control strategies for heat pumps in a residential area under consideration of system operator benefits and grid stability","authors":"J. Meiers ,&nbsp;M. Ortleb ,&nbsp;D. Jonas ,&nbsp;L. Tadayon ,&nbsp;G. Frey","doi":"10.1016/j.enbuild.2025.115442","DOIUrl":"10.1016/j.enbuild.2025.115442","url":null,"abstract":"<div><div>The energy sector faces challenges due to the increasing use of weather-depending renewables in power generation. The resulting fluctuations must be balanced through storage technologies and Demand Side Management (DSM) methods. Heat pumps are generally recognized as shiftable loads for DSM. More and more heat pump manufacturers in Germany are using the Smart-Grid- (SG-) Ready interface, which enables grid operators on the one hand and system operators on the other hand to control heat pumps for the purpose of DSM aiming at either grid power balancing (grid operator friendly) or to increase the self-consumption rate of the residential energy system (system operator friendly). The presented work aims at a compromise between those two goals. To this end, different control strategies for SG-Ready enabled solar and heat pump systems are implemented in a simulation framework and evaluated for a residential area using different key performance indicators. The results show that a control strategy based on a dynamic price signal (<em>PRBC2</em>) with rule-based control and well-chosen switching points, taking into account considered building energy systems and environmental conditions used here, represents the best compromise between system operator friendly behavior and grid operator serviceability. The choice of switching points for the heat pump in the course of the price signal is crucial here, and must take into account the consumption and generation profiles of the local residential areas. The fulfillment value of the key indicators considered here for the representative residential area is 63.9%, whereas the value with the reference operating strategy, in which the heat pump is operated exclusively in SG-Ready Mode 2, is only 50.6%.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"332 ","pages":"Article 115442"},"PeriodicalIF":6.6,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143403157","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}

{"title":"Simulating land surface temperature impacts of proposed land use and land cover plans using an integrated deep neural network approach","authors":"Jiongye Li ,&nbsp;Yingwei Yan ,&nbsp;Rudi Stouffs","doi":"10.1016/j.enbuild.2025.115437","DOIUrl":"10.1016/j.enbuild.2025.115437","url":null,"abstract":"<div><div>The increase in urban temperature driven by rapid urbanization, industrialization, and population growth has posed significant adverse impacts on public health, air quality, and ecosystems. Researchers have employed various machine learning models to simulate urban temperature based on land use/land cover (LULC) and other identified environmental factors, aiming to mitigate urban temperature through optimized LULC planning and other strategies. However, current research lacks a quantitative and spatial assessment of the impact of new LULC designs on land surface temperature (LST), making it challenging for urban planners to effectively utilize these simulations. This study proposes a novel approach that combines the ResNet model, known for its ability to capture complex features, with the U-Net model, which specializes in image segmentation, to assess the impact of LULC changes on LST. Using Singapore as the research site, we trained both ResNet and U-Net models, achieving high accuracy validated by several essential evaluation metrics. Applying the proposed method to assess several redevelopment plans for Paya Lebar Air Base in Singapore, we found that option 1 reduced the area with temperatures exceeding 33°C by 5.52%, while option 2 achieved an 8.77% reduction compared to the current LULC plan. These reductions result from converting airbase land into residential areas, green spaces, and commercial zones. The proposed research method offers urban planners and researchers valuable tools to assess the impacts of proposed LULC plans on LST, ensuring that new urban development strategies align with the goal of mitigating rising temperatures.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"332 ","pages":"Article 115437"},"PeriodicalIF":6.6,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143395762","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}

{"title":"Developing reference building models for the non-residential sector to support public policies in Brazil","authors":"Matheus Geraldi,&nbsp;Liége Garlet,&nbsp;Natasha Gapski,&nbsp;Tiago Quevedo,&nbsp;Ana Paula Melo,&nbsp;Roberto Lamberts","doi":"10.1016/j.enbuild.2025.115419","DOIUrl":"10.1016/j.enbuild.2025.115419","url":null,"abstract":"<div><div>This study introduces a methodology to develop reference building models for energy simulations in non-residential building sector in Brazil. The method uses data from national energy efficiency regulations and research projects to model thermal properties, internal gains, schedules of operation, HVAC systems, and geometries obtained from representative archetypes. These reference models represent typical characteristics of the Brazilian commercial building stock and are designed to assist in predicting energy consumption and support the Brazilian Building Energy Labeling Program. Benchmarks for thermal loads and electricity end-uses were calculated and compared across building types in Brazil, revealing significant variations in performance. Generalization analysis of the models showed the relevance of building orientation and operational schedules on energy use, highlighting their importance in the analysis. Reference building energy use intensity (EUI) was also compared with actual data from the Brazilian building stock, demonstrating that most reference models have a higher EUI than the average but remain below maximum values. This work fills a gap in the development of reference buildings for the non-residential sector in Brazil, offering validated models that can be applied in energy planning and used to evaluate the impact of new technologies in specific building types.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"332 ","pages":"Article 115419"},"PeriodicalIF":6.6,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143421719","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}

{"title":"Examining the reasons for changes in buildings’ energy consumption in the United States, China and the European Union","authors":"M. González-Torres ,&nbsp;L. Pérez-Lombard ,&nbsp;E.L. Clementi ,&nbsp;J.F. Coronel","doi":"10.1016/j.enbuild.2025.115461","DOIUrl":"10.1016/j.enbuild.2025.115461","url":null,"abstract":"<div><div>Buildings are responsible for one third of global operational energy consumption and greenhouse gas (GHG) emissions. Addressing their impact requires the development and monitoring of effective policies, supported by detailed and costly data on building stock and energy use as well as their corresponding analysis. The paper proposes a pyramidal approach to decompose buildings’ energy use into drivers —activity, structure, and efficiency— considering factors like population, floor area, urbanisation, building size, occupancy and climate. Energy-use intensity measures efficiency, while shifts among the residential and tertiary subsectors are captured as structural impacts. The relevance of the methodology is underscored by its potential to assess and quantify the causes of energy consumption changes, guiding policy-making. Applying this approach to China, the United States (US) and the European Union (EU), the paper criticises the lack of data, disaggregates energy consumption changes, outlines policy implications and validates the methodology’s added value. The analysis reveals the increased floor area as the primary driver of rising energy consumption over the past two decades (contributing to changes by 9% in the US, 24% in the EU and 97% in China). This may be reduced by managing urbanisation rates and compensated by an improvement in efficiency. While this has been sufficient to stabilise consumption in the EU, a slight rebound is observed in the US due to the increase in population and in the demand for buildings per capita. In China, the urbanisation trend behind the rise in energy demand is approaching EU levels, highlighting the importance of mindful actions to ensure the sustainability of future expansion. Despite the limited geographical coverage, this study provides a pertinent analysis of almost half of the building energy consumption in the world (China, the US and the EU), offering insights into the sector’s current state and directions for future policy development.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"332 ","pages":"Article 115461"},"PeriodicalIF":6.6,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143421733","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}

{"title":"Liquid sorption storage for high solar fraction heat supply in residential buildings under different climatic conditions","authors":"Robert Weber ,&nbsp;Benjamin Fumey ,&nbsp;Luca Baldini","doi":"10.1016/j.enbuild.2025.115446","DOIUrl":"10.1016/j.enbuild.2025.115446","url":null,"abstract":"<div><div>Thermochemical energy storage is an attractive option for seasonal thermal energy storage, particularly in building applications. However, several research gaps in the field of sorption storage systems such as restricted focus on specific reactor concepts or sorption couples or lack of systematic performance studies hinder their practical implementation. This study addresses these gaps by evaluating the performance and cost-effectiveness of a solar thermal space heating system integrated with liquid sorption storage across various building types (single and multi-family homes with different envelope qualities) and climates (Zurich, Switzerland; Harbin, China; Helsinki, Finland). The study systematically investigates the impact of different sizes of individual system components (number of ground heat exchangers, solar collector area, sorption reactor capacity, size and distribution of thermal buffers) on the overall system performance using a previously presented greybox sorption reactor model based on a lab-scale prototype. The simulation results demonstrate that high solar fractions above 80 % can be achieved with long-term sorption storage. To reach this, substantial storage volumes of around 0.8––1 m³ per m² of solar collector area are needed for the multi-family home cases in Zurich climate despite the increased volumetric energy density of sorption storage when compared to classical water storage. This emphasizes the significance of building envelope quality, available roof area, and careful system component sizing for enhancing solar fractions and cost-effective renewable heat generation. The findings provide valuable insights into optimizing sorption storage systems, fostering the practical implementation of renewable energy solutions for space heating in buildings.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"332 ","pages":"Article 115446"},"PeriodicalIF":6.6,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143421558","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}

{"title":"AI-driven design optimization for sustainable buildings: A systematic review","authors":"Piragash Manmatharasan ,&nbsp;Girma Bitsuamlak ,&nbsp;Katarina Grolinger","doi":"10.1016/j.enbuild.2025.115440","DOIUrl":"10.1016/j.enbuild.2025.115440","url":null,"abstract":"<div><div>Buildings are major contributors to global carbon emissions, accounting for a substantial portion of energy consumption and environmental impact. This situation presents a critical opportunity for energy conservation through strategic interventions in both building design and operational phases. Artificial Intelligence (AI) has emerged as a transformative approach in this context, enhancing the efficiency and precision of energy management efforts. In the operational phase, AI is extensively utilized as smart controllers for Heating, Ventilation, and Air Conditioning (HVAC) systems and passive energy gains, as well as for fault detection. In the design phase, AI is pivotal as a surrogate model, enabling rapid and accurate evaluation of design options and allowing designers to optimize building performance with minimal computational resources. As the early-stage optimization is more cost-effective than post-construction modifications, design phase optimization has a great potential. Consequently, this paper examines recent advancements in surrogate-assisted design optimization for sustainable buildings, providing a comprehensive overview of the entire optimization process, from data preparation and surrogate model training to final optimization. The review categorizes studies based on experimental approaches and methodologies, identifying trends, gaps, and opportunities in the field. Notably, it highlights how modern AI techniques can incorporate previously unexplored dimensions into surrogate-assisted optimization, broadening the scope and potential of surrogate models. Therefore, this study provides guidance for future research and practical applications of AI-driven strategies in sustainable building practices.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"332 ","pages":"Article 115440"},"PeriodicalIF":6.6,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143395761","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}