Energy and Buildings最新文献

{"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}

{"title":"Understanding the impacts of space design on local outdoor thermal comfort: An approach combining DepthmapX and XGBoost","authors":"Ye Xia ,&nbsp;Weisheng Lu ,&nbsp;Ziyu Peng ,&nbsp;Jinfeng Lou ,&nbsp;Jianxiang Huang ,&nbsp;Jianlei Niu","doi":"10.1016/j.enbuild.2025.115451","DOIUrl":"10.1016/j.enbuild.2025.115451","url":null,"abstract":"<div><div>Researchers and designers alike are keen to explore proper space designs to alleviate the heat waves. A niche research area of this type focuses on the smaller scale, local communities to achieve the so-called ‘cool spots’ for residents. However, despite the momentum gained so far, it remains unclear what the key design elements are (e.g., space orientation, aspect ratio, or building density) and how they interact with each other in impacting outdoor thermal comfort (OTC), particularly in some complex, vertical ‘spots’. This research aims to provide an improved understanding of cool spot reasoning by proposing a new paradigm to engage DepthmapX (an analytic tool for urban spatial configuration), XGBoost (a machine learning tool), and on-site verification. By implementing the paradigm on a university campus in Hong Kong for the case study, it was discovered that Percentage of View (PV), Average Height Index (AHI), and Connectivity (CON) are the three most influential factors leading to the formation of a ‘cool spot’. DepthmapX can not only help quantify space designs but also help translate the indexes back to real-life space design options. The XGBoost can help better interpret the pathway from different space design indexes to different OTC but more explainable causal relationships are desired. This research advanced our understanding of the impacts of different space designs on OTC and provided references to designers in achieving OTC in smaller--scale, local communities. It also opens a new avenue to understand the causal relationships in a more detailed and explainable fashion.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"332 ","pages":"Article 115451"},"PeriodicalIF":6.6,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143395759","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":"Establishing a local energy planning and evaluation system prototype to support decarbonized community development","authors":"Yujiro Hirano ,&nbsp;Kyoichiro Isozaki ,&nbsp;Kenichi Adachi ,&nbsp;Tsuyoshi Fijita ,&nbsp;Kei Gomi ,&nbsp;Tsuyoshi Yoshioka ,&nbsp;Yukiko Yoshida","doi":"10.1016/j.enbuild.2025.115450","DOIUrl":"10.1016/j.enbuild.2025.115450","url":null,"abstract":"<div><div>The introduction and spread of local energy systems by local governments and other local entities have been attracting attention; however, considering measures tailored to local conditions faces various challenges, and the development of versatile methods has become an important issue. This study aims to develop a prototype of a local energy planning and evaluation system based on detailed energy management simulations, considering regional conditions as a scientific tool. This system can perform simulations that combine electricity and heat demand patterns, renewable energy sources (solar and wind power), district heating and cooling using cogeneration systems, storage batteries and electric vehicles (EVs) used to adjust the supply and demand balance, and hydrogen production, and can consider the optimal system for each region. The developed prototype is designed for scalability across various regions and features an intuitive interface, ensuring ease of use for local government policymakers and energy company employees. Using this system, we evaluated the local energy business development in Shinchi, Fukushima Prefecture, Japan, as a case study. Specifically, we focused on the introduction of a local energy supply through cogeneration and quantified the CO₂ reduction effect obtained by expanding the supply area, increasing the supply of renewable energy, and introducing various energy management technologies to optimize the supply–demand balance.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"332 ","pages":"Article 115450"},"PeriodicalIF":6.6,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143421734","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":"Data-driven pre-training framework for reinforcement learning of air-source heat pump (ASHP) systems based on historical data in office buildings: Field validation","authors":"Wenqi Zhang ,&nbsp;Yong Yu ,&nbsp;Zhongyuan Yuan ,&nbsp;Peipei Tang ,&nbsp;Bo Gao","doi":"10.1016/j.enbuild.2025.115436","DOIUrl":"10.1016/j.enbuild.2025.115436","url":null,"abstract":"<div><div>Reinforcement Learning (RL) has demonstrated potential for optimal control of Heating, Ventilation, and Air Conditioning (HVAC) systems. Current research on RL in HVAC systems control is limited to simulation studies, with few real-world deployments that have minimal focus on supply-side optimization, along with a reliance on building simulation tools for pre-training. This paper proposes a practical data-driven pre-training framework for Air-Source Heat Pump (ASHP) system. The framework integrates data-driven models based on real-world historical data for load forecasting, equipment energy consumption, and heat transfer. As a case study, two classic value-based reinforcement learning agents, Q-learning and Deep Q-Network (DQN), were selected to dynamically control the number and frequency of pumps and the supply water temperature based on the fluctuating outdoor dry bulb temperature and building cooling load. The pre-training results indicate that DQN achieved energy-saving rates of 4.70% for the training data and 4.65% for the testing data, while Q-learning performed at -0.66% and 1.28% respectively, indicating that both agents outperformed historical control strategies, thereby demonstrating the effectiveness of the pre-training framework. After pre-training, each agent was deployed back into the real-world system for two days of field validation. During deployment, both agents outperformed the rule-based control, with DQN achieving an energy-saving rate of 9.28% and Q-learning achieving 9.04%, demonstrating that the proposed framework enables RL agents to continue real-world learning with an enhanced control strategy. This study provides a novel pre-training paradigm for implementing RL agents in supply-side control of HVAC systems, potentially enhancing both RL deployment and its online evolution.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"332 ","pages":"Article 115436"},"PeriodicalIF":6.6,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143388383","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":"A method for recognizing individual dynamic thermal adaptations using wireless signals","authors":"Min Xu ,&nbsp;Yunsong Han ,&nbsp;Nanxi Zhu ,&nbsp;Bin Yang","doi":"10.1016/j.enbuild.2025.115448","DOIUrl":"10.1016/j.enbuild.2025.115448","url":null,"abstract":"<div><div>Recognizing human behaviors offers an effective approach to reduce building energy consumption while maintaining indoor thermal comfort. This study proposed Wi-PTAB, a novel framework designed to recognize personal thermal adaptive behavior (PTAB) using channel state information (CSI) derived from Wi-Fi signals. The key PTABs essential for the framework were identified through a literature review. Building on these key behaviors, the proposed framework comprises three key steps: CSI acquisition, preprocessing and signals of interest (SOI) extraction; CSI image generation; and feature extraction and classification. During the feature extraction and classification phase, two specialized models combining a 2D Convolutional Neural Network (2D CNN) with either Long Short-Term Memory (LSTM) or Gate Recurrent Unit (GRU) were developed. To evaluate the effectiveness of the proposed Wi-PTAB framework and models, CSI data for the key PTABs were collected from two rooms and processed into four structured datasets, using varying temporal feature partitioning parameters, including window size and step size. The evaluation process involved measuring performance indicators for the proposed models on the self-developed datasets and comparing their performance to that of other neural network models. Results revealed that both models outperformed alternatives across most datasets, and model 2D CNN–LSTM achieved the highest average accuracy of 86 % on dataset III with a temporal granularity of 18. Additionally, two guidelines were established for effectively identifying the defined PTAB: (1) data must be collected with actions executed at the center of transceivers and at a 45° angle to the transceiver. (2) signal segments should be processed with a window size of 0.5 s and a step size of 0.2 s. This study provides technical and theoretical support for non-intrusive and private personal thermal comfort prediction and smart building design.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"333 ","pages":"Article 115448"},"PeriodicalIF":6.6,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143444912","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":"Advancing decarbonization through 3D printed concrete formworks: Life cycle analysis of technologies, materials, and processes","authors":"Valentino Sangiorgio ,&nbsp;Iacopo Bianchi ,&nbsp;Archimede Forcellese","doi":"10.1016/j.enbuild.2025.115444","DOIUrl":"10.1016/j.enbuild.2025.115444","url":null,"abstract":"<div><div>3D printing technologies are innovating several industrial fields for their ability to produce complex shapes, reduce material use and obtain high-performance structures. Among the possible applications of 3D printing in the civil construction sector, manufacturing formwork for concrete casting is a promising solution for producing thin-walled and complex structures. Given the increasing interest and numerous applications being developed, comprehensive studies on the sustainability of 3D-printed concrete formwork are required to improve the processes and drive low-carbon construction practices. In this context, the present study provides for the first time an evaluation of the environmental and economic sustainability of concrete structures achieved using 3D printed formwork. The research investigates the influence of various factors such as: i) geometry complexity, ii) printing technology (Fused Deposition Modelling and Material Jetting), iii) process parameters, iv) raw materials (PLA, ABS, PVA, Geopolymers, Cements, Clay) v) machines kinematic systems and vi) End of Life alternatives. To perform such an investigation, a parametric CAD model was developed to define structure geometry; furthermore, Life Cycle Assessment and Life Cycle Costing methodologies were applied to calculate the impacts and cost of the different alternatives. The results showed that a proper choice of the combination of geometry, technology, material, and process parameters is crucial for reducing the carbonization-related impacts associated with 3D-printed formwork production. In addition, reuse and recycling of the formworks cut overall impacts, making 3D printing a sustainable alternative to traditional production processes while allowing greater design freedom.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"332 ","pages":"Article 115444"},"PeriodicalIF":6.6,"publicationDate":"2025-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143388386","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":"Skin temperature indices to evaluate thermal perceptions and cognitive performance in cold environments","authors":"Boyang Sun ,&nbsp;Jiansong Wu ,&nbsp;Chuan Li ,&nbsp;Siyao Shen ,&nbsp;Xinge Han ,&nbsp;Zhuqiang Hu","doi":"10.1016/j.enbuild.2025.115425","DOIUrl":"10.1016/j.enbuild.2025.115425","url":null,"abstract":"<div><div>The human body maintains thermoneutrality by regulating skin temperature, so skin temperature has potential as an index for assessing thermal perception. The connection between skin temperature, thermal perception, and cognitive performance is also undergoing deeper investigation. In this study, the local skin temperature (head, face, ear, hand, finger, arm, chest, thigh, calf and foot), thermal perceptions (thermal sensation and thermal comfort), and cognitive performance of 14 young males were recorded for 65 min at −13℃, −5℃ and 3℃. Cognitive performance was assessed using a Stroop test, where participants identified the color of words that either matched or conflicted with the word’s meaning. The results showed that the drop in ambient temperature resulted in more significant changes in ear, finger, and calf skin temperatures than the decrease in mean skin temperature (MST). Finger skin temperature was strongly linked to the overall thermal perception, and it ranged from 24.48 ℃ to 30.65 ℃ in the thermoneutral range. The quadratic fitting relationships were found in hand, foot, and face between the local skin temperatures and their local thermal perceptions (R² &gt; 0.9). Local skin temperatures (hand, foot and face) all recovered to above 25 ℃ when local thermal sensation vote (TSV) and local thermal comfort vote (TCV) were greater than 0. Cognitive performance is correlated strongly with foot skin temperature. Foot temperatures above 28.83 ℃ were associated with better cognitive performance. Regarding thermal perception, the best cognitive performance was achieved with TSV_Foot of approximately 1.09. This study provides valuable insights into how local skin temperatures can be used as indicators of thermal perception and cognitive function.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"332 ","pages":"Article 115425"},"PeriodicalIF":6.6,"publicationDate":"2025-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143387764","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":"Optimized design and performance study of hybrid energy systems for building clusters based on image recognition and generative models: A case study of office parks","authors":"Yixin Dong ,&nbsp;Li Zhu ,&nbsp;Jiayi Sun ,&nbsp;Pingyi Li ,&nbsp;Tianyu Wang ,&nbsp;Zirui Li","doi":"10.1016/j.enbuild.2025.115438","DOIUrl":"10.1016/j.enbuild.2025.115438","url":null,"abstract":"<div><div>The reasonable design of building hybrid energy system capacity configuration is crucial to ensuring the economic viability and applicability of decarbonized operational building parks. This study proposes an optimal design method for configuring parameters of hybrid energy systems, integrating parametric techniques (Grasshopper) with multiple models to explore the optimal combination of wind power, solar power, heat pump technology, and energy storage systems. The design process incorporates the segmentation and analysis of building site images using the TransU-Net model to assess the suitability of the design location and the installed capacity of system components. Additionally, the SPEA-II optimization algorithm is applied based on four evaluation indices: wind and solar energy complementarity, power supply loss rate, initial system investment, and economic coefficient. This approach enables the optimal solution screening for hybrid energy systems in buildings. Experimental results demonstrate that the optimized energy system increases renewable energy utilization by 5%–10%, enhances stability by 26.09%–56.70%, and reduces economic costs by 24.85%–59.55%. Furthermore, the proposed method achieves a feedback time as short as 320 s, enabling rapid response to pictorial scheme adjustments.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"332 ","pages":"Article 115438"},"PeriodicalIF":6.6,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143377975","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}