Energy and Buildings最新文献

{"title":"Collaborative optimization scheduling strategy for HVAC with a three-layer optimization architecture","authors":"Yalun Zhu ,&nbsp;Ming Wang ,&nbsp;Dongrun Yang ,&nbsp;Mingyuan Wang ,&nbsp;Qianchuan Zhao ,&nbsp;Xuehan Zheng ,&nbsp;He Gao","doi":"10.1016/j.enbuild.2025.115565","DOIUrl":"10.1016/j.enbuild.2025.115565","url":null,"abstract":"<div><div>Heating, ventilation, and air conditioning (HVAC) systems with different terminal devices can achieve the synergistic effects of multiple heat exchange methods. However, ineffective scheduling strategies for terminal modes during operation hinder cooling (or heating) performance and energy efficiency improvements. Multi-terminal system optimization has the characteristics of multi-variable and multi-objective challenge, which involves a complex coupling problem consisting of condition selection among different decision variables and interference of the same variable to different targets. Single-layer models struggle with coupling interference, while two-layer models only partially address coupling issues. A three-layer optimization architecture is proposed to decouple terminal mode selection from continuous parameter optimization, enhancing scheduling strategies for multi-terminal cooperative operation. And convection-radiation combined cooling system for air-cooled chiller is used as an example to validate the impact of the three-layer optimization architecture on thermal comfort and energy efficiency. The architecture optimizes terminal modes, chilled water flow rates, supply water temperatures, and air supply flow rates for each time period, while minimizing the influence of variable coupling. Additionally, four scheduling strategies are selected for experimental comparison, analyzing the variations in indoor temperature and power consumption to calculate the energy cost and thermal comfort cost for each strategy. The results show that, compared to the other four strategies, the scheduling strategy based on the three-layer optimization architecture can reduce energy costs by 1 % to 45 % and thermal comfort costs by 70 % to 94 %. This architecture enhances the performance of different terminal devices in a coordinated operation process within the HVAC system.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"335 ","pages":"Article 115565"},"PeriodicalIF":6.6,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143591540","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":"Optimizing an expensive multi-objective building performance problem: Benchmarking model-based optimization algorithms against metaheuristics with and without surrogates","authors":"Max Zorn ,&nbsp;Luisa Claus ,&nbsp;Christian Frenzel ,&nbsp;Thomas Wortmann","doi":"10.1016/j.enbuild.2025.115562","DOIUrl":"10.1016/j.enbuild.2025.115562","url":null,"abstract":"<div><div>While simulation-based optimization can effectively find good solutions, the need to simulate hundreds of candidates and consequent long run-times prevent their application in practice. Accurate and fast surrogate models can replace expensive building performance simulations (BPS). Model-based optimization algorithms construct a surrogate during optimization and perform many additional optimization steps quickly. While this strategy has proven effective for expensive single-objective optimization, its performance on multi-objective BPS problems remains understudied. Two questions persist: A) Do model-based multi-objective optimization algorithms outperform metaheuristics and B) How does optimizing on a surrogate model affect the performance of metaheuristic optimization algorithms? Our benchmark results show that the model-based algorithms RBFMOpt and TPE outperform metaheuristics regarding robustness, maximum hypervolume, and the quality of the found Pareto fronts. RBFMOpt yields good solutions within less than 100 function evaluations. Optimizing on surrogate models heavily depends on the surrogates’ ability to estimate precisely but is computationally cheap and allows larger optimization budgets.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"336 ","pages":"Article 115562"},"PeriodicalIF":6.6,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143620980","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":"Design optimization of climate-responsive rural residences in solar rich areas considering sustainability and occupant comfort","authors":"Chenyou Luo ,&nbsp;Chi Feng ,&nbsp;Huizhi Zhong ,&nbsp;Yan Liu ,&nbsp;Mei Dou","doi":"10.1016/j.enbuild.2025.115546","DOIUrl":"10.1016/j.enbuild.2025.115546","url":null,"abstract":"<div><div>Rural residences in solar rich areas (SRA) remain inadequately progress on the challenges of balancing sustainability and occupant comfort simultaneously. Recent advancements in achieving zero-carbon buildings have highlighted the growing demand on climate-responsive strategies that effectively address design considerations of building performances. This paper attempts to explore the optimal design solutions of a case building in Lhasa, a typical city located in SRA, through multi-objective optimization (MOO) based on machine learning in terms of energy, cost, carbon, thermal comfort, and daylight. Initiating comparative selection through representative surrogate models and metaheuristic algorithms, XGBoost achieves the most desirable predictive performances with the least prediction errors, and NSGA-II dominates the superior capability in this case. Based on the solutions discussed through entropy weight and biased weight TOPSIS of objectives, critical outcomes reveal the identification of the optimal building layout in addition to the potential interactions of design variables and building performances investigated. Offering a scalable solution-oriented climate-responsive design pattern, building envelope of the proposed building demonstrates greater potential in balancing building performances, while morphology tends to be comparatively constrained. Results also indicate that, in the most applicable scenario, energy use intensity (EUI) and life cycle carbon emission (LCCE) can be substantially reduced by 47.2% and 38.1%, while concurrently maintaining considerable levels of thermal comfort albeit with acceptable compromises in daylight availability. This paper presents a transferable approach to optimal climate-responsive design solutions, contributing notable insights of data-driven decision-making for rural residences in SRA.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"336 ","pages":"Article 115546"},"PeriodicalIF":6.6,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143629371","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":"Analysing the impact of electric vehicle charging on households: An interrelated load profile generation approach","authors":"Han Wang,&nbsp;Fangce Guo,&nbsp;Aruna Sivakumar","doi":"10.1016/j.enbuild.2025.115558","DOIUrl":"10.1016/j.enbuild.2025.115558","url":null,"abstract":"<div><div>Electric vehicles (EVs) have drawn considerable attention for their role in energy security and efficiency at the household, building and grid levels. As consumers coordinate indoor activities and outdoor trips, their cohesive activity profiles lead to interrelated residential loads and EV charging loads. However, these two types of loads are often generated separately, neglecting the connection between them. This separate EV load generation approach can lead to inaccurate estimations of peak loads and demand flexibility at the household, building and residential grid levels. This study develops a bottom-up approach to simulate interrelated load profiles including the EV charging load and the loads from indoor household appliances. This approach extracts both travel activities and indoor appliance-related activities from the same individuals’ time use surveys to maintain the interconnection between them. Conversion factors, such as appliance load patterns, travel patterns, and EV charging rates, are derived from diverse data sources to translate household activities into load profiles. The output not only provides an accurate estimation of peak loads but also facilitates demand flexibility management for households and residential buildings. In a dataset comprising about 200 households, our load profile simulation indicates that a 100% EV penetration rate may increase the total electricity consumption by 12.9% to 19.0% across three charging scenarios, while peak load increases the range from 14.9% to 35.0%. Furthermore, simple rule-based EV charging power rate limitations are shown to mitigate peak load surges without significantly influencing EV usage. The validation against meter-recorded electricity measurements reveals that the generated household appliance loads capture the fluctuation of the average daily load profiles. This study presents a straightforward method for generating interrelated EV charging loads and indoor household appliance loads, offering valuable inputs and insights for impact analysis, policy-making and demand response.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"335 ","pages":"Article 115558"},"PeriodicalIF":6.6,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143548362","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":"Investigating new measures by jointly employing distinct and local heat transfer enhancement in latent heat thermal energy storage systems for buildings","authors":"Tingsen Chen ,&nbsp;Shuli Liu ,&nbsp;Yihan Wang ,&nbsp;Sheher Yar Khan ,&nbsp;Mahesh Kumar ,&nbsp;Yongliang Shen ,&nbsp;Wenjie Ji ,&nbsp;Mahroo Eftekhari ,&nbsp;Yuliang Zou","doi":"10.1016/j.enbuild.2025.115555","DOIUrl":"10.1016/j.enbuild.2025.115555","url":null,"abstract":"<div><div>To address the issue of decreasing thermal storage capacity during the enhancing of latent heat thermal energy storage (LHTES) in buildings. This study proposes a hybrid two-step method to mitigate this effect. Step one segregates LHTES into fusible and refractory zones based on Phase change material (PCM) melting behavior. Step two employs local enhancements tailored to zone heat transfer characteristics. In this paper, solar radiation intensity, metal foam porosity, and nanoparticle mass fraction effects and sensitivity analysis on locally enhanced LHTES are numerically examined. Five performance indicators were used to evaluate. The results show that employing hybrid two-step method is effective to enhance the synergistic effect on natural convection and heat conduction. When the porosity increases from 92% to 98%, the energy storage capacity can be increased by 10.25%, the energy storage rate is increased by 8.61%, while melting time increased by 4.4%. Every 1 wt% of Graphene nano-particle adds, the heat transfer rate is increased by 0.6%, while energy storage decreases by 3%. The hierarchy of parameters influencing the performance of the LHTES system is as follows: solar radiation intensity holds the highest significance (accounting for 65.31%), followed by porosity (accounting for 31.25%), and then the mass fraction of nanoparticles (accounting for 3.2%). These findings provide valuable insights for the design and optimization of building energy storage systems.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"335 ","pages":"Article 115555"},"PeriodicalIF":6.6,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143591421","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":"Sustainable adaptation of heritage buildings in tropical rainforest climates: The innovative practice of Tanjong Pagar Railway Station in Singapore","authors":"Zhenyu Xiao ,&nbsp;Zihui Tian ,&nbsp;Tianyi Chen ,&nbsp;Chenlu Ouyang ,&nbsp;Yifan Zhou ,&nbsp;Chey Kiang Heng ,&nbsp;Elena Lucchi","doi":"10.1016/j.enbuild.2025.115560","DOIUrl":"10.1016/j.enbuild.2025.115560","url":null,"abstract":"<div><div>Heritage buildings in tropical climates face unique challenges in balancing preservation with modern sustainability goals, particularly in energy efficiency and climate resilience. This study introduces a methodological framework for adapting historic buildings in tropical climates while improving their energy performance. Singapore’s Tanjong Pagar Railway Station serves as the primary case study for this investigation. The methodology combines climate analysis, heritage-compatible redesign, and photovoltaic integration. These elements are validated through sophisticated digital modeling and performance simulations. Results demonstrate significant energy efficiency improvements through custom-designed photovoltaic systems, potentially reducing annual energy consumption by up to 83% while preserving historical integrity. This research provides a scalable model for sustainable heritage conservation in tropical regions. It offers valuable insights for urban planners, policymakers, and conservationists working at the intersection of cultural preservation and sustainable development. The findings can inform policy development and conservation practices across Southeast Asia and similar tropical regions facing heritage adaptation challenges.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"335 ","pages":"Article 115560"},"PeriodicalIF":6.6,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143601552","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 community-based decision support map for building retrofit towards a more sustainable future","authors":"Ezgi Köker Gökgöl ,&nbsp;Esther Linder ,&nbsp;Philipp Schuetz","doi":"10.1016/j.enbuild.2025.115554","DOIUrl":"10.1016/j.enbuild.2025.115554","url":null,"abstract":"<div><div>The energy sector is the source of nearly three-quarters of the global greenhouse gas emissions and buildings form around one-third of it. The largest share of the energy consumption in the buildings belongs to the heating systems which are mostly dependent on fossil fuels. To keep up with the demands of increasing population, it is vital to undergo clean energy transformations effective immediately. In this study, a decision support map was created for a selected community to ease the energy retrofit candidate selection process. Buildings are assessed considering sustainability level of the heating infrastructure, energy use intensity and age, and ranked according to their goodness level on the energy efficiency scale through analytic hierarchy process. Finally, a multi-layered map is created to visualize the outcomes. The decision support map fills a gap in the existing tool landscape as it offers energy consulting on a communal (i.e. not only single building or quarter) level and does not require work from the user as it relies on public data. The results showed that new buildings constructed by environmentally responsible codes tend to have heating systems mostly powered by renewable sources and less level of energy threshold violations while old buildings generally act in the other direction. As the main outcome, the created visuals support the user to have insights about the accumulation areas of the households in low rankings as well as the energy efficiency standing of the individual buildings in comparison with the neighbouring households.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"335 ","pages":"Article 115554"},"PeriodicalIF":6.6,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143591418","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":"Life cycle cost optimization for schools energy retrofit under climate change: Methodological approach and analyses in five different climates","authors":"Ludovica Maria Campagna,&nbsp;Francesco Carlucci,&nbsp;Francesco Fiorito","doi":"10.1016/j.enbuild.2025.115561","DOIUrl":"10.1016/j.enbuild.2025.115561","url":null,"abstract":"<div><div>The energy renovation of existing schools has become a priority, to address which cost-effective retrofit strategies should be identified, considering the unavoidable climatic changes, to maximize the benefits during the whole service life. This paper presents a methodology useful for comparing different retrofit proposals by adopting a cost-optimal approach, in which the effects of future climate variations on energy needs were also considered. The methodology was applied to school buildings located in Italy, considering 5 different cities, with the aim of assessing whether an over-performing building − exceeding the minimum regulatory requirements − could provide economic benefits, considering future climatic evolutions and consequent energy needs variations. Different retrofit measures (active and passive) were identified, each of which was associated with different performance targets, starting with those required by the current national energy standard. Accordingly, 900 retrofit proposals were compared against a baseline retrofit option, that brings the building into compliance with current regulations. Optimal solutions were found through a single-objective optimization, performed combining Python and EnergyPlus, which aimed to minimise the global cost of the intervention over a 30-year time horizon. The evolution of climate conditions was also considered in this time interval, generating future weather files on the basis of the most recent SSP5-8.5 scenario. Results highlighted the importance of careful selection of retrofit measures, showing that exceeding regulatory standards does not automatically lead to economic benefits.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"335 ","pages":"Article 115561"},"PeriodicalIF":6.6,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143591268","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":"Spatial variation of building energy consumption in Egypt based on high-resolution typical meteorological year data","authors":"Mohammed Rady ,&nbsp;Mohammed Magdy Hamed ,&nbsp;Ahmed Abdiaziz Alasow ,&nbsp;Mohd Khairul Idlan Muhammad ,&nbsp;Shamsuddin Shahid","doi":"10.1016/j.enbuild.2025.115553","DOIUrl":"10.1016/j.enbuild.2025.115553","url":null,"abstract":"<div><div>Building energy consumption is a crucial aspect of the construction industry, as it significantly impacts operational costs and environmental sustainability. This study investigates the spatial variations of cooling energy consumption in Egypt, enabling the identification of regions vulnerable to high energy demands. To this end, we utilize high-resolution typical meteorological year (TMY) data developed from the reanalysis ERA5 dataset. EnergyPlus was employed to simulate a small office building for 535 grid points representing populous regions in Egypt. The Sandia method was utilized to generate TMY data for the last 30 years (1991–2020). The results reveal that the demand for cooling energy in the southern regions could be almost 136 % higher than in the northern regions of Egypt. The temporal patterns reveal the adverse influence of climate change on the average cooling energy consumption, with the peak values in July and August. The deviation between the TMY-based and long-term energy consumption showed a good agreement in different grids, with <em>R²</em> greater than 0.9 in all grids and normalized root mean square error (NRMSE) ranging between 12 and 32.2 %. Furthermore, the paired <em>t</em>-test results show no significant difference between energy consumption derived from TMY data and long-term data across 95% of the studied grid points in Egypt, indicating that TMY data effectively represents long-term energy consumption trends. The findings can inform energy-efficient building design strategies and policymakers on improving energy efficiency and reducing environmental impacts.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"336 ","pages":"Article 115553"},"PeriodicalIF":6.6,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143620977","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":"Vision-based personal thermal comfort modeling under facial occlusion scenarios","authors":"Guanying Huang ,&nbsp;Dezhi Li ,&nbsp;S.Thomas Ng ,&nbsp;Lingxiao Wang ,&nbsp;Yubin Zhang","doi":"10.1016/j.enbuild.2025.115566","DOIUrl":"10.1016/j.enbuild.2025.115566","url":null,"abstract":"<div><div>Personal thermal comfort modeling can accurately identify the transient thermal comfort states of individuals, facilitating occupant-centric indoor thermal comfort regulation. Facial temperature is the important data source for developing personal thermal comfort model. However, facial occlusion often occurs in daily life, such as wearing eyeglasses or masks, would hinder the acquisition of facial temperature. Previous studies have ignored the facial occlusion scenarios, which narrowed the application scope of the model. This study proposed a method fusing visible and infrared images to fill this knowledge gap. Firstly, the facial occlusion scenarios and corresponding Regions of Interest (ROIs) were recognized from the visible images based on YOLOv8 and FaceMesh. Secondly, the coordinates of ROIs were mapped from visible images onto the infrared images, and the temperature features of each ROI were calculated. Finally, Random Forest (RF) algorithm-based models were developed to predict the subjective thermal comfort indices. 3029 sets of data were collected in the experiment to verify the prediction models under four facial occlusion scenarios (i.e., without occlusion, wearing eyeglasses, wearing mask, wearing both). The results showed that: (1) the accuracy of the proposed prediction models was improved by 3.30% to 14.17% compared with the baseline model based on environmental parameters, (2) temperature features of hand and median temperature feature type were important for personal thermal comfort modeling, and (3) the addition of air temperature and subjects’ Body Mass Index (BMI) could significantly improve the model performance by 6.34% and 5.39%.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"335 ","pages":"Article 115566"},"PeriodicalIF":6.6,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143579707","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}