Energy Efficiency最新文献

{"title":"XGBoost-PSO: Comparison of decision tree based algorithms by estimating the efficiency of three-phase induction motor","authors":"Kadir Ileri,&nbsp;Adem Dalcali,&nbsp;Rafet Durgut","doi":"10.1007/s12053-026-10469-8","DOIUrl":"10.1007/s12053-026-10469-8","url":null,"abstract":"<div><p>Induction motors are commonly employed in the industry due to their reliability and cost-effectiveness. The efficiency of an induction motor is a critical factor in assessing motor performance, and it can fluctuate under different load conditions. Several methods exist to determine motor efficiency, but most require direct intervention on the motor. In this study, the efficiencies of induction motors have been estimated by using decision tree based machine learning algorithms which are Decision Tree (DT), Random Forest (RF), and Extreme Gradient Boosting (XGBoost). Moreover, the data preprocessing and feature engineering (DPaFE) process have been carried out to increase the performances of the models. Besides, the different load conditions which are half load, 75% load, and full load have been analyzed by using the manufacturer data of 238 different motors. Finally, the models obtained have been optimised by using metaheuristic Particle Swarm Optimisation (PSO) algorithm for different loads separately. The best model has been achieved by XGBoost-PSO with DPaFE for all the loads.</p></div>","PeriodicalId":537,"journal":{"name":"Energy Efficiency","volume":"19 7","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149035259","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 do group-level factors moderate the relationships between information–interaction strategies and the energy-saving behaviours of college students in dormitories?","authors":"Xiaodan Liu,&nbsp;Sisi He,&nbsp;Wentao Peng,&nbsp;Liang Guo,&nbsp;Ling Liao,&nbsp;Wei Hu","doi":"10.1007/s12053-026-10468-9","DOIUrl":"10.1007/s12053-026-10468-9","url":null,"abstract":"<div><p>An energy-saving intervention that combines an information strategy with social interaction is termed an information–interaction strategy. Such an approach is crucial among other strategies designed to guide college students in implementing energy-saving behaviours in dormitories. However, the mechanism through which information–interaction strategies influence the energy-saving behaviour of college students in dormitories remains unclear, and the role of group-level factors such as interpersonal relationships, group identity, and group norms is unknown. Thus, energy managers find it impossible to grasp the pivotal aspects of information–interaction strategies that would enable them to formulate a more reasonable and effective implementation plan that maximizes the energy-saving effects of such an approach. Therefore, an intensive exploration of the mechanisms influencing information–interaction strategies and the effects of group-level factors on the energy-saving behaviours of college students in dormitories is highly practical and theoretically important. This study was grounded in the theory of social interaction and constructed an influence mechanism model of how an information–interaction strategy affects the energy-saving behaviours of college students in dormitories. The proposed model adopted an information–interaction strategy as an antecedent variable and utilized interpersonal relationships, group identity, and group norms as intermediary variables. Data were collected via a questionnaire administered to 434 respondents. Structural equation modelling was subsequently employed to analyse the research model. The results indicated that information–interaction strategies do not directly affect the energy-saving behaviours of college students in dormitories but can improve energy-saving intentions. Information–interaction strategies can influence energy-saving behaviours through three mediating pathways: interpersonal relationships, group norms, and group identity. Information–interaction strategies are most likely to influence energy-saving behaviours through group norms among the three pathways, followed by interpersonal relationships and, finally, group identity.</p></div>","PeriodicalId":537,"journal":{"name":"Energy Efficiency","volume":"19 7","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148986281","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":"Extending passivhaus to non-domestic buildings in the UK: performance under future climate variability and modelling simplification","authors":"Laurence Peinturier,&nbsp;David C. H. Wallom","doi":"10.1007/s12053-026-10467-w","DOIUrl":"10.1007/s12053-026-10467-w","url":null,"abstract":"<div><p>Passivhaus is a world-leading standard for ultra-low energy, zero-carbon buildings. However, the long-term performance of such buildings under future variable climate change remains insufficiently understood. Building Performance Simulation (BPS) is a valuable tool to assess future impacts across scenarios, though workflows can be complex and time-consuming. This paper investigates whether passive building design can maintain thermal comfort and energy performance under future climate variability and evaluates the reliability of simplified BPS models in predicting these effects. The study utilises a recently constructed Passivhaus-certified non-domestic university building in Oxford, UK as case study. Three levels of modelling detail are developed following a previously established simplification framework and simulations are conducted across 12 ensemble members representing natural climate variability for two future periods (2050s and 2070s) under the highest Representative Concentration Pathway (RCP8.5) emission scenario. Results reveal cooling vulnerabilities in current Passivhaus guidance, with indoor temperatures exceeding 28 °C in extreme 2070s scenarios. Although Oxford remains heating-dominated on an annual degree-day basis, the building becomes increasingly cooling-challenged, with overheating certification thresholds met by only 8% of 2050s and 42% of 2070s scenarios. This counterintuitive difference reflects a shift from more frequent moderate threshold exceedances in the 2050s to less frequent but more severe thermal peaks in the 2070s, highlighting the limits of frequency-based overheating criteria. Furthermore, climate variability challenges single-scenario design approaches, yielding substantial ensemble spreads (± 30 MWh/month cooling, ± 1.5 maximum monthly Predicted Mean Vote). Finally, oversimplified models underestimate both summer thermal discomfort levels and variability, underscoring the need to select modelling simplification levels according to analysis objectives. Focusing on the UK context, this research proposes a framework for assessing long-term resilience of passive-design high-performance non-domestic buildings under variable climate conditions. The study aims to guide practitioners in balancing modelling detail and predictive robustness in low-energy and Passivhaus building design for climate adaptation, supporting simplified BPS methods for climate-resilient building design and evaluation.</p></div>","PeriodicalId":537,"journal":{"name":"Energy Efficiency","volume":"19 7","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12053-026-10467-w.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148927671","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":"A consumer-centric evaluation of the attractiveness of demand-side management technologies and business models","authors":"Yijie Su,&nbsp;Ilkka Keppo","doi":"10.1007/s12053-026-10465-y","DOIUrl":"10.1007/s12053-026-10465-y","url":null,"abstract":"<div><p>Demand-Side Management (DSM) plays an important role in stabilizing energy systems and enhancing energy efficiency. DSM technologies optimize residential energy consumption patterns through smart devices, real-time monitoring, and automated control systems. While factors influencing consumer DSM adoption have been extensively studied, less attention has been paid to the role of business models (BMs) in shaping consumer willingness. This study uses survey-based literature to identify the key factors influencing consumers' intention to adopt DSM technologies and analyzes how different BMs incorporate such factors into their offerings. Focusing on Finland, the study categorizes DSM companies into six BM archetypes based on their value propositions and revenue mechanisms. A consumer-centric evaluation is applied to evaluate BM adoption potential, enabling standardized scoring and cross-case comparison. Results indicate that consumers’ willingness to adopt is primarily driven by perceived ease of use and usefulness, while environmental considerations and saving potential are gaining importance. Product-oriented BMs receive slightly higher scores than service-oriented BMs, particularly for features such as remote and automatic control. A geographical sensitivity analysis for the evidence base reveals that Finnish consumers prefer offerings from traditional utilities and smart device providers, instead of software providers. These insights offer valuable guidance for designing consumer-centric DSM BM strategies, emphasizing the necessity of innovation to ensure these BMs effectively support energy transition and sustainability goals.</p></div>","PeriodicalId":537,"journal":{"name":"Energy Efficiency","volume":"19 7","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12053-026-10465-y.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148926549","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":"Dynamic simulation of an energy-efficient residential building integrating passive and solar-assisted energy systems: techno-economic and environmental assessment","authors":"Mohammad Poormohammadi,&nbsp;Rouhollah Ahmadi,&nbsp;Meisam Farajollahi","doi":"10.1007/s12053-026-10466-x","DOIUrl":"10.1007/s12053-026-10466-x","url":null,"abstract":"<div><p>This study investigated building energy efficiency from two complementary perspectives: a passive approach involving systematic variation of building envelope parameters, including external wall composition, insulation thickness, and window and glazing type, across 72 design alternatives, and an active approach based on solar energy integration. The passive evaluation led to the selection of Alt.53, characterized by 5 cm of expanded polystyrene (EPS) insulation in the external walls and UPVC double-glazed windows with low-emissivity glazing, resulting in a 31.5% reduction in cumulative annual heating and cooling loads relative to the reference design. Building on this, a solar-assisted underfloor heating system and a solar absorption cooling system were subsequently modeled in TRNSYS. The solar fractions achieved during January–March, June–September, and November–December were 10.0%, 29.7%, and 19.6%, respectively. The corresponding optimal collector tilt angles for these periods were 65°, 20°, and 75°, respectively. The combined application of passive and active measures yielded a 45.1% reduction in cooling-season energy consumption and a 65.4% reduction in heating-season energy consumption relative to the reference design; this improvement corresponds to a total annual energy saving of 75,577 kWh and a projected CO₂ emission reduction of 53.4 tCO₂/year.</p></div>","PeriodicalId":537,"journal":{"name":"Energy Efficiency","volume":"19 7","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148926550","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":"Electricity price convergence and dynamics in Europe: market integration, decarbonisation, electricity mix, and external shocks","authors":"Kornelia Kłopecka-Miętka,&nbsp;Sławomir Śmiech,&nbsp;Monika Papież,&nbsp;Dawid Bonar","doi":"10.1007/s12053-026-10464-z","DOIUrl":"10.1007/s12053-026-10464-z","url":null,"abstract":"<div><p>This study investigates the convergence of electricity prices across 26 European countries in the context of two major transitions: market integration and decarbonisation. Using a dynamic panel data approach with the Dynamic Common Correlated Effects (DCCE) estimator, we assess both absolute and conditional β-convergence of electricity prices across all countries and within country groups classified according to their electricity generation structure. The analysis incorporates key determinants of price dynamics, including natural gas and coal prices, EU Emissions Trading System (ETS) allowance prices, carbon intensity, and the role of net electricity imports. Our findings confirm the presence of β-convergence across the entire sample and all groupings of countries, indicating progress toward a more integrated EU electricity market. We also find that the sensitivity of electricity prices to fossil fuel and carbon costs varies significantly with the electricity mix. In particular, electricity systems with higher shares of renewables appear less responsive to fossil fuel price shocks, suggesting enhanced resilience. Cross-border electricity trade emerges as a key factor shaping price dynamics, especially in countries dominated by renewables. These results support the continued pursuit of European energy market integration and decarbonisation as mutually reinforcing goals.</p></div>","PeriodicalId":537,"journal":{"name":"Energy Efficiency","volume":"19 7","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12053-026-10464-z.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148837744","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":"Studies on energy characteristics and performance of architectural heritage: methodologies and approaches in Anatolia and Thrace cases","authors":"Barış Ali Timur,&nbsp;Tahsin Başaran,&nbsp;Başak İpekoğlu","doi":"10.1007/s12053-026-10463-0","DOIUrl":"10.1007/s12053-026-10463-0","url":null,"abstract":"<div><p>Studies on the energy characteristics of architectural heritage have been published for decades, concerning the design of retrofitting strategies, reducing energy use and carbon emissions for energy efficiency, and better understanding their thermal behaviors and requirements for architectural conservation. This research aims to evaluate the methods and techniques used in these studies, with a specific geographical focus on Anatolia and Thrace. This historically significant region encompasses a wide range of climatic zones, offering distinctive perspectives within the global discourse on architectural heritage energy research. A total of 134 studies were analyzed, with emphasis on the simulation-based approaches and their modelling practices. The research concludes with a critical assessment of improvement areas, emphasizing the importance of preserving cultural heritage while avoiding interventions that could compromise the historical significance of these buildings. It also highlights key methodological gaps and proposes directions for future research.</p></div>","PeriodicalId":537,"journal":{"name":"Energy Efficiency","volume":"19 7","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148837577","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":"Invisible consumers: how data deficiencies in energy efficiency of micro- enterprises influence policy design","authors":"Ivana Rogulj,&nbsp;Vlasios Oikonomou,&nbsp;Saša Žiković","doi":"10.1007/s12053-026-10461-2","DOIUrl":"10.1007/s12053-026-10461-2","url":null,"abstract":"<div><p>Micro-enterprises represent major share of EU firms and account for almost 19.8% of EU value added, yet they remain <i>invisible</i> in energy statistics and energy efficiency policy evaluation. This invisibility is not only a matter of missing data but also a classification problem, since energy use is commonly allocated to household, commercial, or industrial sectors based on metering and contract arrangements rather than enterprise characteristics. As a result, micro-enterprise energy consumption is embedded in sectoral aggregates and cannot be consistently observed as a distinct analytical category. This paper examines how this statistical invisibility might affect the observability of micro-enterprises in energy efficiency policy design and evaluation. It combines a cross-country assessment of data availability across ten EU Member States with a Croatian case study based on a structured survey of 470 micro-enterprises. The survey investigates household-business overlap in workspace use, energy bills, and vehicle ownership. The cross-country review shows that core indicators needed for policy evaluation, including energy consumption, workspace or building use, transport activity, and size specific sectoral classification, are largely unavailable or only observable at aggregated levels. Financial information is available in some countries but remains weakly harmonised. Complementary sources can improve firm level coverage for economic variables but do not resolve the absence of micro-enterprise specific energy consumption data. The Croatian case study provides empirical evidence of extensive household and business overlap. 43% percent of respondents reported on shared household and business energy bills, and 64% report on shared vehicle use. These overlaps indicate that household energy statistics may overstate residential demand while business statistics may underestimate enterprises’ energy needs, with the strongest overlap among the smallest firms. The findings highlight the need to improve the statistical visibility of micro-enterprises and to explicitly account for mixed household and business energy use in both policy design and evaluation. This is particularly relevant for instruments targeting distributional impacts and vulnerability, including measures linked to the Social Climate Fund.</p></div>","PeriodicalId":537,"journal":{"name":"Energy Efficiency","volume":"19 7","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12053-026-10461-2.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148783172","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":"Investigating purchase intentions for electric vehicles in China considering the removal of incentive policies","authors":"Hongguang Nie,&nbsp;Huiru Yu,&nbsp;Haiyan Lu","doi":"10.1007/s12053-026-10462-1","DOIUrl":"10.1007/s12053-026-10462-1","url":null,"abstract":"<div><p>Switching to electric vehicles (EVs) is essential for reducing carbon emissions and mitigating climate change, but their share in the total car market remains small, especially in emerging economies. In response to this issue, this study investigates the determinants of consumers’ purchase intentions for EVs in China, accounting for the removal of incentive policies, thereby contributing to the field of sustainable consumption. Integrating psychological and environmental variables, this study conceptualizes the effects of EV cognition, environmental knowledge, and environmental concern, which draws on the reasoned action model to investigate consumers’ purchase intentions for EVs. The concept of attitudes without incentives is introduced to capture the effects of removing incentive policies on individual purchase intention. Survey evidence from Beijing, China, validates the model, confirming that attitudes without incentives are influenced by cognition of EVs and environmental knowledge and that attitudes without incentives both directly and indirectly affect purchase intention. The model provides a framework for understanding consumers’ purchase intentions for more environmentally sustainable products, yielding specific, practical insights for promoting the switch to EVs.</p></div>","PeriodicalId":537,"journal":{"name":"Energy Efficiency","volume":"19 6","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148751519","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":"A deep learning based predictive control method for enhancing microgrid resilience","authors":"Hussein A. Taha,&nbsp;Ahmed Abdelrahman,&nbsp;Abdelhamid Mammeri","doi":"10.1007/s12053-026-10459-w","DOIUrl":"10.1007/s12053-026-10459-w","url":null,"abstract":"<div><p>The increasing integration of renewable energy sources into power systems has accelerated the deployment and usage of microgrids. However, the stochastic nature of renewable energy generation and fluctuating power demand pose significant challenges to maintaining grid stability. To address these challenges, this paper proposes an intelligent Model Predictive Control (MPC) framework for optimal power flow management in microgrids, with the objective of enhancing operational resilience, reducing diesel fuel consumption, and preventing blackouts through coordinated electric vehicle (EV) charging and discharging. The proposed MPC is formulated as a nonlinear optimization problem that minimizes operational costs while satisfying dynamic microgrid constraints. A Passive MPC strategy, which relies on predefined EV availability schedules without predictive forecasting, is first investigated to assess the impact of EV participation on microgrid performance. Simulation results show that allowing EV support outside critical hours (9 AM to 7 PM) achieves fuel and CO<span>(_2)</span> emission reductions of approximately 9.11% compared to a baseline scenario without EV integration. When EVs are available throughout the entire day, fuel consumption and CO<span>(_2)</span> emissions are further reduced by up to 33.39%, demonstrating the significant potential of vehicle-to-grid participation. Building upon these results, a Deep Learning–based MPC (DL-MPC) framework is developed to enable proactive and informed control decisions. An LSTM-based forecasting model is employed to predict day-ahead load demand, wind power generation, and solar irradiance, allowing the MPC to anticipate system conditions and mitigate blackout risks more effectively. The forecasting models exhibit strong predictive accuracy, with RMSE values of 3.9194 for wind power, 0.0908 for load demand, and 107.8 for solar irradiance, and corresponding MAPE values of 18.64%, 22.00%, and 22.3%. The proposed framework highlights the potential of combining predictive control with vehicle-to-grid strategies to enhance the sustainability, and efficiency of microgrid operations while effectively mitigating the risk of blackouts.</p></div>","PeriodicalId":537,"journal":{"name":"Energy Efficiency","volume":"19 6","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148750543","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}