Energy Efficiency最新文献

{"title":"Enhancing circularity in EU product policymaking: A case study of a domestic oven using the EcoReport tool","authors":"María González-Torres,&nbsp;Chiara Magrini,&nbsp;Judit Rodriguez-Manotas,&nbsp;Vincenzo Senatore,&nbsp;David Bernad Beltran,&nbsp;Miguel Gama Caldas","doi":"10.1007/s12053-026-10423-8","DOIUrl":"10.1007/s12053-026-10423-8","url":null,"abstract":"<div><p>Although supported by the scientific community and increasingly widespread in industry, the transition from a linear to a circular economy will be hampered if it is not accelerated through adequate policy measures. Therefore, integrating circularity into existing policies becomes imperative. Within the European Union (EU), the Ecodesign framework has been identified as one of the key legislative tools to foster products’ circularity, as it makes it legally possible to transform circularity principles into requirements, e.g. resource use, reparability, durability and recyclability. For the definition of requirements and their level of stringency, an assessment of economic and environmental impacts needs to be conducted. So far, this assessment has been supported by the EcoReport tool, to perform a simplified Life Cycle Assessment. The aim of this paper is to present how the EU is integrating circularity in the assessments that support product policymaking and to describe how the EcoReport tool is being adapted. Using an oven as a case study, the differences compared to the previous version of the tool are identified and discussed. The implications in terms of data requirements and results are presented. A more detailed and time-consuming process for data collection allows for more robust results of the impacts all over the life cycle. Moreover, guidance on how to further integrate circularity strategies, specifically on closing and slowing resource loops, is proposed in order to fill the gaps in the current assessment. However, a balance needs to be maintained, as adding complexity to the assessments could delay the policymaking, hindering the timely development of measures. The paper aims not only to draw lessons from the EU's transition experience but also to advocate their applicability and adaptability to shape policy frameworks across other regions and countries.</p></div>","PeriodicalId":537,"journal":{"name":"Energy Efficiency","volume":"19 4","pages":""},"PeriodicalIF":4.0,"publicationDate":"2026-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12053-026-10423-8.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147643042","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"Biophysical and thermodynamic foundations of energy economics: introducing the novel concept of econobolism","authors":"Xiangdong Xu,&nbsp;Faeze Akbariresketi,&nbsp;Vahid Taghvaee","doi":"10.1007/s12053-026-10428-3","DOIUrl":"10.1007/s12053-026-10428-3","url":null,"abstract":"<div><p>In biophysics and thermodynamics, organisms’ energy use is proportional to their mass, whereby larger organisms are more energy-efficient, according to the Kleiber and Constructal laws, respectively. This raises questions in energy economics about whether energy consumption is proportional to economic size, and whether larger economies are more energy efficient. To answer these questions, this research aims to examine the Kleiber and Constructal laws in the context of energy economics. To this end, it combines machine learning and econometric methods including k-clustering, Fixed Effects (FE), Random Effects (RE), Generalized Least Squares (GLS), and Driscoll and Kraay (<i>The Review of Economics and Statistics, 80</i>(4), 549–560, 1998) standard errors (SCC). These models analyze data from 217 countries between 1974 and 2023 to estimate metabolism rate in the context of energy economics, to introduce a novel concept, called “econobolism rate”. The results of the k-clustering method accept the Constructal law of thermodynamics by indicating that countries with large economic size have more energy efficiency. Moreover, the results of econometric methods accept Kleiber’s law by showing that the estimated econobolism rates range within 81% and 85% which are, respectively, 6% and 10% greater than the metabolic rate of Kleiber’s law, 75%. This result confirms that energy consumption is a sublinear proportion of economic size, which affirms Kleiber’s law where energy consumption of a biological organism is a proportion of its mass. These findings incorporate biophysics and thermodynamics into energy economics by estimating the econobolic rate, which open new horizons in research on the nexus of energy consumption and economic development.</p></div>","PeriodicalId":537,"journal":{"name":"Energy Efficiency","volume":"19 4","pages":""},"PeriodicalIF":4.0,"publicationDate":"2026-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147607317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adaptive climate zoning for sustainable energy performance of window systems: A comparative study of unsupervised clustering algorithms","authors":"Mojgan Moradi","doi":"10.1007/s12053-026-10427-4","DOIUrl":"10.1007/s12053-026-10427-4","url":null,"abstract":"<div><p>Reliable climate classification is essential for evaluating building components that strongly impact heating and cooling energy demand. Among building components, windows play a significant role in thermal exchange and are commonly assessed through climate-dependent energy labeling programs. In Iran, the current classification system based on ISO 18292:2011 divides the country into ten climatic zones relying on temperature and solar radiation. However, this classification does not fully reflect Iran’s climatic diversity, potentially misrepresenting window performance and energy consumption. This study proposes an adaptive approach incorporating local climate data to define suitable window properties, improve energy efficiency, and reduce greenhouse gas emissions while supporting the United Nations Sustainable Development Goal (SDG) 11 for resilient urban development. To develop and validate the framework, ten years of historical observed meteorological data from 158 stations of the Iran Meteorological Organization were analyzed based on degree-days and solar irradiance conversion to vertical surfaces. Two unsupervised clustering algorithms, K-means and hierarchical clustering, were adopted to define climatic zones. Ward’s hierarchical method identified 11 clusters validated by the Silhouette Coefficient, while EnergyPlus simulations showed improved annual window heating and cooling performance under the proposed zoning. Kernel interpolation with barriers was utilized to generate a thorough geographical representation of climatic diversity across 468 counties. The proposed approach demonstrates how machine learning and spatial analysis can be integrated to improve climate zoning. The resulting climate map provides a more reliable basis for climate-responsive window design and future updates of national energy performance standards.</p></div>","PeriodicalId":537,"journal":{"name":"Energy Efficiency","volume":"19 4","pages":""},"PeriodicalIF":4.0,"publicationDate":"2026-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147607029","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating the impacts of defrost mode in cold climate residential heat pumps","authors":"Kevin Keene,&nbsp;Vrushali Mendon,&nbsp;Michael Brambley,&nbsp;Samuel Rosenberg,&nbsp;Julia Rotondo","doi":"10.1007/s12053-026-10424-7","DOIUrl":"10.1007/s12053-026-10424-7","url":null,"abstract":"<div><p>Air source heat pumps (HPs) are a highly efficient space heating technology that have been used for decades; however, there is a scarcity of published field data characterizing their performance. This research utilizes data collected from pre-commercial residential cold climate HPs developed for the U.S. Department of Energy’s Residential Cold Climate Heat Pump Challenge. This research investigates defrost mode specifically, which is necessary for optimal heating functionality when frost forms on the outdoor unit. This paper presents findings from 22 residential sites concerning the characteristics of defrost operation, its impact to performance, and a categorization of various strategies employed by the units. The results suggest that defrost mode becomes more prevalent at higher humidities and at outdoor air temperatures from 10 °F to 30 °F (-12.2 °C to -1.1 °C). None of the strategies for defrost were observed to have significant impacts to average room temperature throughout the homes (median impact all less than 1 °F [0.6 °C]). However, the units that ran the indoor supply fan during defrost (except the ones that simultaneously supplied 10 kW or more of auxiliary heat) were associated with low supply air temperatures during defrost mode (median values less than 60 °F [15.5 °C]), which could have comfort impacts during winter to occupants especially near supply vents. It was observed that many of the units were initiating defrost cycles at times where there did not appear to be a need for it, either due to a fixed interval feature or control settings that did not consider frost formation or impact to performance. Although these units are pre-commercial and may undergo modifications before entering the market, the findings underscore the importance of developing a deeper understanding of the energy and comfort impacts of defrost mode strategies for improving HP performance.</p></div>","PeriodicalId":537,"journal":{"name":"Energy Efficiency","volume":"19 4","pages":""},"PeriodicalIF":4.0,"publicationDate":"2026-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12053-026-10424-7.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147560436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"Optimizing renewable energy in education: a techno-economic study of rooftop solar PV systems in Malaysia","authors":"Nor Hazlina Md Khairi,&nbsp;Yutaro Akimoto,&nbsp;Keiichi Okajima","doi":"10.1007/s12053-026-10418-5","DOIUrl":"10.1007/s12053-026-10418-5","url":null,"abstract":"<div><p>The rising cost of energy, coupled with the global emphasis on sustainability, has spurred a broad shift towards cleaner and more efficient energy solutions. Educational institutions, with their extensive rooftop areas and high energy consumption due to operational and human activity, are particularly well-positioned to contribute to this transition. This study evaluates the techno-economic feasibility of rooftop solar PV systems in Malaysian educational institutions, providing insights into energy savings and grid dependency reduction and aiming to support the adoption of rooftop PV systems in educational buildings. Using the NREL System Advisor Model (SAM), simulations were performed on PV systems sized at 100 kW, 500 kW, and 1000 kW, focusing on key financial metrics: Net Present Value (NPV), Discounted Payback Period (DPP), and Levelized Cost of Electricity (LCOE). The results show that a 500 kW system can reduce grid electricity use by 57% to 78%, yielding NPVs between 479,442 MYR (105,477 USD) and 4,865,835 MYR (1,070,484 USD), DPPs ranging from 6.3 to 10.9 years, and LCOE values from 0.2141 to 0.2506 MYR (0.0471 to 0.0551 USD). These findings demonstrate the economic benefits of rooftop solar PV systems in educational settings, positioning them as a valuable tool for supporting Malaysia’s renewable energy targets, addressing sustainability goals, and fostering a low-carbon future.</p></div>","PeriodicalId":537,"journal":{"name":"Energy Efficiency","volume":"19 4","pages":""},"PeriodicalIF":4.0,"publicationDate":"2026-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147560278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Energy efficient street lighting framework: An archived multi-objective simulated annealing based approach","authors":"Pragna Labani Sikdar,&nbsp;Samarjit Kar,&nbsp;Parag Kumar Guha Thakurta","doi":"10.1007/s12053-026-10426-5","DOIUrl":"10.1007/s12053-026-10426-5","url":null,"abstract":"<div><p>An archived multi objective simulated annealing based energy efficient street lighting framework is proposed to maximize the energy efficiency and uniformity of the system while minimizing the power requirement of the luminaries. The proposed methodology considers the initial population in terms of the combination of the input parameters, such as the inter-distance between two consecutive street lights, luminary height, road width and average illuminance. The crossover and the clustering are used to check the domination status between the earlier and the new population as well as to reduce an excessive amount of possible solutions generated. The convergence and the diversity of the obtained solution set are evaluated for the proposed work over other alternative multiobjective optimization algorithms by four performance metrics, such as Generational Distance, Inverted Generational Distance, minimal-spacing, and purity, to highlight the energy efficiency in the proposed street lighting framework. The result obtained from the proposed approach amidst others, in terms of convergence and diversity, is validated using DIALux (an open source lighting software) to ensure the standard recommendation. Several improvements, in terms of various facets, resulting from the proposed work over other existing approaches are highlighted.</p></div>","PeriodicalId":537,"journal":{"name":"Energy Efficiency","volume":"19 3","pages":""},"PeriodicalIF":4.0,"publicationDate":"2026-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147441780","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"User tariff classification with multi-dimensional deep learning on electricity consumption data","authors":"Zumerya Ustundag,&nbsp;Fatih Serttas","doi":"10.1007/s12053-026-10425-6","DOIUrl":"10.1007/s12053-026-10425-6","url":null,"abstract":"<div><p>Electricity load is crucial to managing energy grids and determining energy policies. Electricity tariffs offer diverse opportunities to consumers at different prices, necessitating proper usage, detection of non-compliant users, and appropriate sanctions. This study utilizes real-life electricity load data from 310 users in Türkiye's five most common tariff classes to create a three-channel time series. An innovative method combining Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) models is proposed to predict tariff groups based on electricity load data. After preprocessing, the time series are converted into two-dimensional matrices, and features are extracted using a 2D CNN network. These features are then utilized in an LSTM network to highlight sequential relationships. The developed model achieved 87% accuracy in training and 83% in validation, demonstrating its effectiveness in predicting tariff groups from electricity load data. This study proposes and validates a hybrid CNN-LSTM-based tariff classification approach using real-world electricity consumption data for smart grid management and energy pricing, thereby contributing to the research on analyzing and utilizing electricity load data.</p></div>","PeriodicalId":537,"journal":{"name":"Energy Efficiency","volume":"19 3","pages":""},"PeriodicalIF":4.0,"publicationDate":"2026-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12053-026-10425-6.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147441576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"Application of classical optimization methods to reduce demand for contracted energy in the Brazilian public sector","authors":"Rodrigo Cabral de Freitas,&nbsp;Ronaldo Malheiros Gregorio,&nbsp;Marcelo Dib Cruz","doi":"10.1007/s12053-026-10421-w","DOIUrl":"10.1007/s12053-026-10421-w","url":null,"abstract":"<div><p>Growing global interest in environmental issues and the need to maintain energy sustainability have increased debates around the appropriate management of energy resources. For Brazil, continually adjusting the electrical system to meet contractual requirements is an extremely challenging problem. Likewise, the complexity of the UFRRJ university’s energy matrix and the difficulty of controlling additional energy demand are critically important. This study aims to investigate classical optimization methods that help reduce energy demand contracts in the public sector, using UFRRJ as a case study. The incorporation of quadratic programming, Lagrange multipliers, conjugate gradient method, gradient descent, penalty methods, Newton’s method, and genetic algorithms aims to improve the terms of demand contracts, promoting sustainability and cost reduction at the institution. Testing the methods and tools demonstrate their effectiveness in reducing energy costs and provides a basis for their implementation in real-world scenarios.</p></div>","PeriodicalId":537,"journal":{"name":"Energy Efficiency","volume":"19 3","pages":""},"PeriodicalIF":4.0,"publicationDate":"2026-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12053-026-10421-w.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147342369","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"Governance for net zero project evaluation: Experiences from UK local authorities","authors":"Daniel Kerr,&nbsp;Andrew Reeves,&nbsp;John Rowlatt","doi":"10.1007/s12053-026-10422-9","DOIUrl":"10.1007/s12053-026-10422-9","url":null,"abstract":"<div><p>The United Kingdom has committed, through a legally-binding target, to achieve net zero emissions in the UK economy by 2050. The UK government envisages local authorities as being critical actors in achieving net zero. However, no coherent national guidance regarding net zero implementation exists for local governments. In the context of evolving national- and regional- scale energy planning, with the formation of Great British Energy, the National Energy System Operator and other bodies, local authorities will have an increasing role in energy planning. However, funding environments, human resources and technical capacity remain constrained. Strong governance mechanisms will be required to manage the socio-technical transition to a net zero future in the UK, and to engage with multiple actors across spatial and political scales. This article draws on research examining the challenges that UK local authorities (at County Council, District Council and Combined Authority scales) are having with access to and analysis of data for meaningful evaluation of current projects and future project planning. Through semi-structured interviews with 19 separate actors from UK local authorities, national bodies and consultancies working in net zero with UK local governments, we: • Examine the evaluation gap in carbon reduction, project costs and progress to net zero. • Consider the effect that an uncoordinated national policy framework for net zero is having on the ability for local authorities to effectively evaluate future project development routes. • Discuss how the increasingly adopted Local Area Energy Planning methodology is affecting local net zero policy and spatial planning, and what governance frameworks are needed to ensure that a net zero project is well-facilitated, timely and accelerated. Our findings highlight principles for how governance for monitoring and evaluation of net zero projects is a necessary foundation for assessing the success or failure of interventions, having relevance in the UK and beyond.</p></div>","PeriodicalId":537,"journal":{"name":"Energy Efficiency","volume":"19 3","pages":""},"PeriodicalIF":4.0,"publicationDate":"2026-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12932288/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147300764","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"Worldwide scientific landscape on district heating systems","authors":"Alberto-Jesus Perea-Moreno,&nbsp;David Muñoz-Rodríguez,&nbsp;Quetzalcoatl Hernandez-Escobedo,&nbsp;Esther Salmerón-Manzano,&nbsp;Francisco Manzano-Agugliaro","doi":"10.1007/s12053-026-10419-4","DOIUrl":"10.1007/s12053-026-10419-4","url":null,"abstract":"<div><p>This study aims to assess the research trends and progress in the field of district heating, a key technology for improving energy efficiency and environmental sustainability. By analyzing bibliometric indicators such as publication volume, citations, authorship, and keywords, the study provides insights into the growth, regional focus, and thematic evolution of district heating research from 2004 to 2023. The study employs a bibliometric analysis of Scopus-indexed publications on district heating, spanning from 2004 to 2023. Using the Vosviewer software, a cluster analysis was conducted to categorize the research landscape into distinct themes. The results indicate a steady increase in publications on district heating, especially over the last decade, with a significant proportion of research output originating from China and Europe. The cluster analysis identified five primary themes in district heating research: energy sustainability, thermal and geothermal energy, renewable energy integration and district heating networks, buildings, and cogeneration. Furthermore, an analysis of the evolution of research keywords reveals a transition from the focus on renewable energy integration (2014–2016) to a shift towards network optimization techniques (2018) and, more recently (2020), towards digitalization and automation. This evolution is characterised by a focus on digital storage, model predictive control, and demand-side management to enhance system efficiency. The present study provides a comprehensive bibliometric overview and introduces a novel integrative perspective by systematically linking the temporal evolution of scientific production with thematic clustering and policy-relevant implications. It highlights how emerging trends, such as digitalisation, low-temperature networks and sector coupling, are reshaping the future of district heating systems. The findings reveal the growing importance of digital and automated approaches to enhance district heating efficiency and sustainability.</p></div>","PeriodicalId":537,"journal":{"name":"Energy Efficiency","volume":"19 3","pages":""},"PeriodicalIF":4.0,"publicationDate":"2026-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12053-026-10419-4.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147340784","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}