Energy Efficiency最新文献

{"title":"The impact of digital inclusive finance on energy poverty: evidence from China","authors":"Xiuqing Li,&nbsp;Luping Li,&nbsp;Yaofeng Yang","doi":"10.1007/s12053-026-10448-z","DOIUrl":"10.1007/s12053-026-10448-z","url":null,"abstract":"<div><p>Energy poverty is a significant challenge facing sustainable human development. As the world’s largest developing country, China is confronted with particularly acute energy challenges. With the advancement of technology and the transformation of the financial sector, digital inclusive finance, as a new financial model, offers new possibilities for alleviating energy poverty. Consequently, digital inclusive finance has become vital in China’s efforts to mitigate energy poverty. Using balanced panel data from 31 provinces in China from 2011 to 2022, this paper theoretically analyzes and empirically tests whether digital inclusive finance can mitigate energy poverty and explores possible mechanisms of impact. The findings reveal that: (1) Digital inclusive finance can alleviate energy poverty, a conclusion that holds even after a series of robustness checks and handling endogeneity. (2) From a mechanistic perspective, digital inclusive finance reduces energy poverty by enhancing environmental regulation, narrowing the urban–rural income gap, promoting industrial structure optimization, and boosting technological innovation. (3) Regional examination shows that digital inclusive finance primarily mitigates energy poverty in the eastern and central regions. (4) Further studies indicate that the breadth of coverage, depth of use, and degree of digitization of digital inclusive finance all contribute to alleviating energy poverty.</p></div>","PeriodicalId":537,"journal":{"name":"Energy Efficiency","volume":"19 6","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148323753","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":"How energy savings and other gains from application of the energy efficiency first principle may be estimated","authors":"Stefan Thomas,&nbsp;Jan Kaselofsky,&nbsp;Annette Kindl,&nbsp;Arnau Luke Dedeu Dunton,&nbsp;Ina Martin","doi":"10.1007/s12053-026-10449-y","DOIUrl":"10.1007/s12053-026-10449-y","url":null,"abstract":"<div><p>The Energy Efficiency First principle (EE1st principle) was defined in the 2018 EU Governance Regulation, and further elaborated in the 2023 recast of the Energy Efficiency Directive, which specifies concrete requirements for Member States in its articles 3 and 27. The application of the EE1st principle requires the identification of alternative cost-efficient energy efficiency measures optimising energy demand and supply. These measures must still achieve the objectives of the relevant sectoral policy, planning, and/or major investment decisions. In this paper, we present a methodology for estimating the cost-efficient potential for end-use energy savings and for other energy efficiency gains relevant to the energy system, which may particularly stem from demand-side response and storage but also targeted energy savings. The overarching methodology differentiates between the energy sector and the energy end-use sectors or areas. For the energy end-use sectors/areas, the methodology focuses on estimating energy savings potentials. The energy end-use sectors/areas included in the study were: transportation, industry, buildings, ICT services, water and wastewater management, and agriculture. A simplified methodology was applied to estimate the EU-wide energy savings potential for these energy end-use sectors/areas. For the energy sector—particularly in the electricity sector—the methodology incorporates additional steps to estimate the impact of energy efficiency on the load profile from energy savings, demand-side response and storage. These steps require a dynamic methodological approach, based on forecasting and modelling. We also discuss the proposed methodology’s limitations depending on its application in practice and currently available knowledge, using the results of an application for the transport sector as an illustration, and future research options to improve the assessment of the potentials of the EE1st principle in policy, planning and major investment decisions.</p></div>","PeriodicalId":537,"journal":{"name":"Energy Efficiency","volume":"19 6","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12053-026-10449-y.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148323588","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":"Does energy efficiency credit policy promote corporate green innovation? Evidence from a quasi-natural experiment in China","authors":"Xiaoxu Guo,&nbsp;Yue Zhang","doi":"10.1007/s12053-026-10450-5","DOIUrl":"10.1007/s12053-026-10450-5","url":null,"abstract":"<div><p>This study examines the impact of energy efficiency credit policy on corporate green innovation, using China’s policy as a quasi-natural experiment. Previous research has emphasized the relationship between energy efficiency and bank credit; however, few studies have focused on the economic consequences of energy efficiency credit from a policy analysis perspective. Using a difference-in-differences model and data from listed companies in China from 2008 to 2023, this study demonstrates that energy efficiency credit policy promotes corporate green innovation. The findings confirm that credit support, external financing, and green agency costs are the mechanisms through which energy efficiency credit policy fosters green innovation. Additionally, the effectiveness of the policy is more pronounced in regions with stringent environmental regulations, among firms with a higher propensity for risk-taking, and for state-owned enterprises. This study is the first to empirically substantiate the beneficial role of energy efficiency credit policy in advancing green innovation.</p></div>","PeriodicalId":537,"journal":{"name":"Energy Efficiency","volume":"19 6","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148323352","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":"Consumers’ preferences for energy efficiency in refrigerators: a choice experiment in South Korea","authors":"Ji-Yu Kim,&nbsp;Hong-Won Choi,&nbsp;Seung-Hoon Yoo","doi":"10.1007/s12053-026-10451-4","DOIUrl":"10.1007/s12053-026-10451-4","url":null,"abstract":"<div><p>This study investigates South Korean households’ preferences for refrigerator attributes using a choice experiment with 1,000 respondents from across the nation, analyzed via a mixed logit model to account for preference heterogeneity. Five key attributes—energy efficiency, warranty period, storage capacity, upper cooling compartment, and price—yielded statistically significant coefficients consistent with economic theory. Energy efficiency grade emerged as the most influential attribute, with an estimated mean marginal willingness to pay (MWTP) of KRW 471.6 thousand (USD 339.8) for a one-level improvement in efficiency grade as indicated by the mandatory energy label. This suggests that households place greater value on the actual efficiency performance conveyed by the label rather than its mere presence. The MWTP for storage capacity was comparatively small, amounting to KRW 5.4 thousand (USD 3.9) per additional liter. In contrast, Upper cooling compartment was associated with a considerable MWTP of KRW 442.8 thousand (USD 319.0) when compared with a lower cooling compartment, while an additional year of warranty period received a relatively modest valuation. Simulations for hypothetical refrigerator profiles confirmed efficiency’s centrality amid usability trade-offs. The findings underscore efficiency’s dual economic-environmental appeal, advocating tiered incentives and refined labelling that better convey the economic value of higher efficiency grades revealed in this study, thereby aligning label design with consumers’ willingness to pay for efficiency improvements.</p></div>","PeriodicalId":537,"journal":{"name":"Energy Efficiency","volume":"19 6","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148323268","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":"Physical-based models and load forecasting to improve flexibility and energy efficiency in residential segments","authors":"Antonio Gabaldon,&nbsp;Maria Carmen Ruiz-Abellón,&nbsp;Luis Alfredo Fernández-Jiménez,&nbsp;Antonio Guillamón","doi":"10.1007/s12053-026-10446-1","DOIUrl":"10.1007/s12053-026-10446-1","url":null,"abstract":"<div><p>This paper analyzes the optimization of electricity consumption in the residential sector through improved energy management and planning, combining probabilistic load estimation techniques with demand management policies. First, considering that load forecasting becomes more complex as the level of aggregation decreases, probabilistic demand forecasting methods may be particularly relevant for the participation of small customer segments in energy markets. Second, in order to mitigate the uncertainty associated with forecasts, several demand response and energy storage strategies are proposed and simulated hour-ahead to bound such uncertainty by providing demand flexibility without being limited to load shedding; the drawbacks of the proposed methodology, from the perspectives of control and energy efficiency, are also analyzed for the flexibility deployed in the hour-ahead timeframe. The proposed methodology explores synergies among Probabilistic Prediction, Load Modeling, Demand Response, Energy Storage, and Energy Efficiency. Schematically, a machine learning technique is first employed to estimate the quantiles of the conditional distribution function, generating a set of probabilistic demand predictions for both the day-ahead and hour-ahead horizons. Based on these demand predictions, Demand Response and Storage Strategies are simulated to reduce prediction uncertainty between the day-ahead and the hour-ahead scenarios. In addition, different demand management options are analyzed within the hour-ahead window from an Energy Efficiency perspective, considering the use of grey-box load models for two main residential end uses: Domestic Water Heating and Electric Space Heating. As mentioned above, the ability of Demand Flexibility to compensate for imbalances between actual load and forecasts requires both increases and decreases in demand during the control period; however, such policies may affect the overall efficiency of the appliances involved in flexibility programs. For these reasons, this work proposes the joint evaluation of both flexibility and energy efficiency, resulting in an hour-ahead scenario in which each end use is assigned a specific role to better achieve efficiency and flexibility objectives. The proposed approach is applied to consumption data from a substation with a high share of residential customers.</p></div>","PeriodicalId":537,"journal":{"name":"Energy Efficiency","volume":"19 6","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12053-026-10446-1.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148261886","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":"What is in the policy mix? The effectiveness and cost-effectiveness of energy efficiency instruments in the EU countries at the crossroads of two periods","authors":"Daniel Nigohosyan,&nbsp;Albena Vutsova","doi":"10.1007/s12053-026-10443-4","DOIUrl":"10.1007/s12053-026-10443-4","url":null,"abstract":"<div><p>This study explores how the design of national policy mixes influenced the achievement of energy efficiency targets in the European Union (EU) during two programming periods (2014–2020 and 2021–2030). In particular, it examines the interplay between energy efficiency obligation schemes, financial and fiscal incentives, and taxation measures. Using descriptive statistics and comparative analysis across EU Member States, the study finds that greater diversity in the policy instruments generally contributed to better target achievement. The results suggest that while no universal policy mix exists, Member States relying exclusively on a single instrument type faced higher risks of non-achievement. Moreover, energy efficiency obligation schemes consistently proved to be more cost-effective (up to ten times) compared to financial and fiscal incentives. Nevertheless, financing schemes/fiscal incentives were by far the most numerous type of measures in the 2014–2020 period and experienced a significant increase in 2021–2030 in number and volume. Given the emphasis on cost-effectiveness and budgetary constraints in EU energy policy, future strategies may benefit from reinforcing the role of obligation schemes within a diversified policy mix.</p></div>","PeriodicalId":537,"journal":{"name":"Energy Efficiency","volume":"19 6","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148261812","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":"Scenario-based sensitivity analysis for tailoring regional energy-saving strategies in residential buildings: a comparative study of Japan and Vietnam","authors":"Le Na Tran,&nbsp;Weijun Gao,&nbsp;Huong Thanh Hoang","doi":"10.1007/s12053-026-10445-2","DOIUrl":"10.1007/s12053-026-10445-2","url":null,"abstract":"<div><p>Residential building energy consumption is a complex interplay of geography, architecture, and human behavior. However, current models fail to adequately integrate these factors, leading to generic strategies that lack regional specificity. This study introduces a physics-based End-Use Energy Predictive Model (EUE-PM) that explicitly quantifies the sensitivity of energy use to regional climate conditions, main facade orientation, and HVAC operational behaviors. The scenario-based comparative simulation addresses these factors across diverse climates and represents a significant advancement over previous approaches. We developed a database of climatic conditions and building archetypes to simulate 80 energy models across 40 cities in Japan and Vietnam, spanning a wide range of latitudes and climate zones. Our analysis reveals two key findings. First, sensitivity to building orientation is highly latitude-dependent, with high-latitude Japanese cities showing up to 16% energy savings from south-facing bedrooms, whereas this factor was less critical in tropical Vietnam. Second, modulating occupant behavior within thermal comfort bounds presented the highest energy-saving potential (up to 50%) in Vietnam, whereas Japanese energy use was highly sensitive to the orientation of localized architectural archetypes. The EUE-PM successfully defined the influence of each factor, providing a clear hierarchy for intervention. The proposed EUE-PM moves beyond mere prediction to offer a sensitivity-driven decision-making tool. It enables the development of tailored, region-specific energy conservation guidelines, which is a crucial step toward achieving sustainable development goals in the built environment of Asia and other climatically diverse regions.</p></div>","PeriodicalId":537,"journal":{"name":"Energy Efficiency","volume":"19 6","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148261910","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":"What drives the adoption of green energy technologies in Slovenian SMEs","authors":"Nevenka Hrovatin,&nbsp;Janez Dolšak,&nbsp;Jelena Zorić","doi":"10.1007/s12053-026-10442-5","DOIUrl":"10.1007/s12053-026-10442-5","url":null,"abstract":"<div><p>Green energy technologies are crucial for sustainable development, particularly in small and medium-sized enterprises (SMEs). In SMEs, these investments predominantly involve energy efficiency (EE) and renewable energy (RE) technologies. Despite their importance, research on SMEs' environmental behaviour is limited, often focusing on large corporations instead. This study investigates the internal and external determinants influencing Slovenian SMEs' decisions to invest in EE and RE technologies. Using a cross-sectional sample of SMEs from the Slovenian Business Register and data from a self-administered survey conducted in 2020, we estimate separate probit models for investments in EE and RE, and a joint model for investments in green energy technologies (GEI), looking for the complementarities in determinants of both investment types. Key findings indicate that ownership of premises, investment in R&amp;D, and having a dedicated energy manager are significant positive predictors of GEI. Energy audits and advice also positively influence EE and RE investments. A novel finding is that higher indebtedness (debt ratio) is positively associated with RE investment, while not affecting EE, consistent with greater use of external financing for RE. The study underscores the critical role of SMEs in the EU's green energy transition and highlights the importance of asset ownership, innovativeness among technology push factors, and proactive energy management practices in driving GEI. These insights can inform policymakers and business leaders aiming to enhance the adoption of sustainable energy practices among SMEs by promoting voluntary energy networks for peer learning, encouraging the appointment of dedicated energy managers, through awareness campaigns, and considering financial incentives to support energy-related initiatives.</p></div>","PeriodicalId":537,"journal":{"name":"Energy Efficiency","volume":"19 5","pages":""},"PeriodicalIF":4.0,"publicationDate":"2026-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12053-026-10442-5.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148236786","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":"Role of machine learning and deep learning in optimizing smart home energy management systems: Advancements and technical factors","authors":"N. Mathangi,&nbsp;S. Malathi","doi":"10.1007/s12053-026-10439-0","DOIUrl":"10.1007/s12053-026-10439-0","url":null,"abstract":"<div><p>Smart Home Energy Management Systems (SHEMS) play a vital role in improving residential energy efficiency, reducing costs, and supporting the integration of renewable energy sources. This review systematically examines recent advancements in Machine Learning (ML) and Deep Learning (DL) techniques for optimizing SHEMS, covering studies published between 2018 and 2024. Using the PRISMA-based structured review methodology, 80 high-quality research articles are analysed to evaluate algorithmic performance, technical challenges, security considerations, and economic viability. The findings indicate that traditional ML models, such as Support Vector Machines (SVM), and regression techniques, remain effective for structured data and resource-constrained environments. However, DL approaches, including Long Short-Term Memory (LSTM), CNN-based hybrid models, and Deep Reinforcement Learning, consistently outperform conventional methods in real-time energy demand forecasting, adaptive load scheduling, and handling renewable energy intermittency, achieving prediction accuracies above 95% and energy savings of 25–40%. Hybrid models integrating ML/DL with metaheuristic optimization techniques further enhance system robustness and multi-objective optimization performance. The review also highlights growing attention to security and privacy, where advanced encryption and multi-factor authentication significantly improve protection, though implementation gaps remain. Economic analysis reveals that intelligent optimization improves long-term return on investment despite high initial costs. Overall, the study identifies key research gaps in benchmarking, scalability, security validation, and techno-economic assessment, providing directions for future intelligent and secure SHEMS deployment.</p></div>","PeriodicalId":537,"journal":{"name":"Energy Efficiency","volume":"19 5","pages":""},"PeriodicalIF":4.0,"publicationDate":"2026-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148173481","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":"Exploring transaction cost barriers for energy efficiency renovations in multi-family buildings – a case study of municipal housing companies in Sweden","authors":"Lena Neij,&nbsp;Sofie Sandin Lompar","doi":"10.1007/s12053-026-10440-7","DOIUrl":"10.1007/s12053-026-10440-7","url":null,"abstract":"<div><p>Municipal housing companies have been recognised for their potential in taking on a leadership role in terms of energy efficiency in buildings, raising the question of what the transaction cost barriers are in these companies’ internal operations for undertaking energy efficiency measures. In this study, we thus explore transaction costs barriers in municipal housing companies in Sweden. Data on qualitative transaction cost barriers in the planning and implementation of energy-efficiency renovations was collected through interviews with six companies, two of which were also able to present data and quantitative transaction costs. The study illustrates the characteristics of transaction costs barriers, and the results indicate these barriers result in conventional energy efficiency technologies and measures rather than more innovative measures. This is due to asset specificity, uncertainty, and bounded rationality. The study indicates that learning can be essential in reducing transaction cost barriers, this through capacity building, demonstration projects and interaction among different types of actors. Feedback and structured learning, as in demonstration projects, will be essential in reducing transaction costs and supporting the implementation of new (innovative) energy-efficiency measures. The study specifically highlights the need for local initiatives supporting (local) learning, by strengthening the role of municipalities and municipal housing companies.</p></div>","PeriodicalId":537,"journal":{"name":"Energy Efficiency","volume":"19 5","pages":""},"PeriodicalIF":4.0,"publicationDate":"2026-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12053-026-10440-7.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148173482","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}