Energy Strategy Reviews最新文献

{"title":"Corrigendum to “Vehicle-to-grid energy technologies: A patent landscape analysis and technology updates” [Energy Strategy Rev. 66 (2026) 102316, pp.1-21]","authors":"Sazib Mollik, M.A. Hannan, Gilsoo Jang, Safat B. Wali, Sayem M. Abu, M.F. Roslan, Ali Q. Al-Shetwi","doi":"10.1016/j.esr.2026.102350","DOIUrl":"10.1016/j.esr.2026.102350","url":null,"abstract":"","PeriodicalId":11546,"journal":{"name":"Energy Strategy Reviews","volume":"67 ","pages":"Article 102350"},"PeriodicalIF":12.1,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148995638","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":"Artificial intelligence applications in hybrid renewable energy system: A comprehensive review of techniques, applications, and challenges","authors":"Abdus Samad Azad,&nbsp;Nahina Islam,&nbsp;Md Nurun Nabi,&nbsp;Shaminda De Silva,&nbsp;Rajalingam Sokkalingam","doi":"10.1016/j.esr.2026.102329","DOIUrl":"10.1016/j.esr.2026.102329","url":null,"abstract":"<div><div>Hybrid renewable energy system (HRES), which integrate multiple generation sources such as solar photovoltaics, wind turbines, and energy storage systems (ESSs), are increasingly recognized as foundational components in the transition toward low-carbon and resilient energy infrastructures. In this context, artificial intelligence (AI) has emerged as a critical enabler for managing the complexity and variability inherent in HRES operation and planning. This systematic review synthesizes the state of research on AI-driven decision-making frameworks applied to HRES, with a particular focus on machine learning, deep learning, and metaheuristic optimization techniques. Following a rigorous screening process, 270 peer-reviewed publications spanning 2010 to 2025 were analyzed across dimensions of system design, forecasting, real-time control, and lifecycle optimization. The findings reveal that AI technologies significantly enhance forecasting accuracy, improve scheduling efficiency, and contribute to intelligent fault detection and energy dispatch strategies. Applications of deep learning architectures, such as LSTM, GRU, and CNN, demonstrate superior performance in modeling nonlinear temporal dynamics, while reinforcement learning enables adaptive control under uncertainty. Despite these advancements, the review also identifies critical limitations, including high computational demands, limited transferability across geographies, data scarcity in real-world deployments, and insufficient attention to socio-economic and environmental dimensions. By consolidating methodological trends and performance benchmarks, this review offers a research roadmap that advocates for the development of interpretable, scalable, and energy efficient AI solutions. It emphasizes the need for standardized datasets, cross-sector integration, and inclusive design approaches that align with broader energy justice and climate resilience goals. The review contributes a foundational reference for researchers, system designers, and policymakers, positioning AI enhanced HRES as a central pillar in achieving global decarbonization targets.</div></div>","PeriodicalId":11546,"journal":{"name":"Energy Strategy Reviews","volume":"66 ","pages":"Article 102329"},"PeriodicalIF":12.1,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148635043","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI-driven real-time carbon footprint tracking and autonomous reduction for sustainable enterprises","authors":"Yuan Chai,&nbsp;Haytham F. Isleem,&nbsp;P Kumar,&nbsp;Ghanshyam G. Tejani,&nbsp;David Bassir","doi":"10.1016/j.esr.2026.102293","DOIUrl":"10.1016/j.esr.2026.102293","url":null,"abstract":"<div><div>Current practice in enterprise carbon reporting is heavily dependent on periodic emissions inventories and disconnected data streams. As a result, drivers of emissions are not detected quickly enough to enable responsive action. Here we build and validate a near-real-time carbon-intelligence pipeline that incorporates facility IoT telemetry, ERP event logs, grid carbon-intensity feeds, and optionally satellite proxies, for near-real-time estimation of Scope 1-2 emissions at sub-hourly granularity and associated recommendations for abatement actions. The system uses attention-based multimodal fusion, an ensemble of Transformer, CNN, and BiLSTM predictors with calibrated uncertainty, and a multi-objective optimizer (NSGA-III with PSO and simulated-annealing refinement) that balances emissions, cost, and operational disruption. SHAP and LIME provide audit-ready explanations for key predictors and recommended actions. An 18-month matched-pair observational evaluation (January 2023–June 2024) across 247 organizations in four sectors compared the proposed approach with conventional quarterly accounting baselines. The proposed pipeline showed stronger agreement with verified emissions (MAPE 3.2% vs. 18.7%; RMSE 0.087 vs. 0.524 tCO₂e; Pearson r 0.94–0.97). On matched baseline comparisons, sites implementing recommended actions tended to have lower verified emission intensity on average, though results were still impacted by production mix, demand variation, implementation rigor and data quality. Economic impacts, such as estimated ROI, are also derived from observational comparisons without causal attribution. Overall, the findings suggest that explainable and time-resolved emissions intelligence may support enterprise decarbonization planning and operational monitoring.</div></div>","PeriodicalId":11546,"journal":{"name":"Energy Strategy Reviews","volume":"66 ","pages":"Article 102293"},"PeriodicalIF":12.1,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148554983","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":"Bridging urban industrial carbon-peaking targets and feasible transition pathways through an extended Kaya–system dynamics framework","authors":"Liang Zhao,&nbsp;Boyu Guo,&nbsp;Weize Song,&nbsp;Jianbiao Chen,&nbsp;Penglu Dong,&nbsp;Xi Lu","doi":"10.1016/j.esr.2026.102305","DOIUrl":"10.1016/j.esr.2026.102305","url":null,"abstract":"<div><div>The urban industrial sector is central to China's carbon peaking targets, yet feasible and affordable city-level peaking pathways remain unresolved. Existing carbon-emission models show limited depth and transferability because core decision-making factors, including industrial structure, energy mix, and technology adoption rate, are difficult to quantify and are often treated as exogenous. This study develops an Extended Kaya and system dynamics framework to model interactions among economic activity, industrial structure, energy mix, technology adoption rate, and CO₂ emission coefficient for the urban industrial sector. The model couples indicator transparency with endogenous feedbacks and is calibrated using historical series on carbon emissions, energy consumption, energy intensity, and industrial structure. Three policy portfolios are evaluated. Industrial structure regulation improves emission intensity but leaves sizable residual emissions. Energy mix regulation achieves larger reductions through fuel switching and electrification as the grid CO₂ emission intensity declines. The integrated portfolio aligns structural optimization, energy transition, and technological upgrading and delivers the most feasible outcome. Under this pathway, peak emissions reach 91.54 MtCO₂ in 2030, and CO₂ emission intensity reaches 0.58 tCO₂ per 10⁴ RMB, both improvements relative to the current-policy case. The findings provide actionable guidance for industrial planning, fuel and power procurement, and retrofit programs, and they supply a quantitative basis for monitoring, reporting, and verification aligned with urban practice. Because the framework requires only limited parameter recalibration, it can be adapted to other cities to inform tailored strategies that advance carbon peaking and, over a longer horizon, carbon neutrality.</div></div>","PeriodicalId":11546,"journal":{"name":"Energy Strategy Reviews","volume":"66 ","pages":"Article 102305"},"PeriodicalIF":12.1,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148554985","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":"Comparative least-cost electrification pathways in West Africa: A spatially explicit analysis using OnSSET","authors":"Adama Sarr,&nbsp;Cheikh Mouhamed Fadel Kebe,&nbsp;Sebastien Ahmany Dan-Baibe,&nbsp;Babacar Mbaye Ndiaye,&nbsp;Aldo Bischi,&nbsp;Umberto Desideri","doi":"10.1016/j.esr.2026.102319","DOIUrl":"10.1016/j.esr.2026.102319","url":null,"abstract":"<div><div>This study applies the Open Source Spatial Electrification Tool (OnSSET) to assess least-cost electrification pathways across the fifteen ECOWAS countries under harmonized techno-economic assumptions to 2030. Unlike most existing OnSSET applications, which focus on national or sub-national analyses, this study provides a regional-scale comparative assessment of electrification pathways, investment requirements, technology allocation, and spatial cost heterogeneity across West Africa. The analysis examines how settlement density, infrastructure proximity, and technology-specific costs influence electrification outcomes under a consistent modelling framework.</div><div>Results show that grid extension remains cost-effective in dense urban and peri-urban corridors, while decentralized solutions, particularly mini-grid photovoltaic (MG PV) and stand-alone photovoltaic (SA PV) systems, dominate least-cost pathways in remote and low-density areas. Significant cross-country differences are observed in investment requirements, average LCOE, technology shares, and last-mile electrification costs. The findings also reveal a structural distinction between access-oriented technologies that maximize population coverage and energy-oriented technologies that support higher electricity supply levels.</div><div>The results highlight the growing marginal cost of reaching the remaining unelectrified population and emphasize the importance of differentiated electrification strategies combining grid reinforcement, decentralized systems, and regional coordination under the West African Power Pool (WAPP). While the harmonized approach enables systematic comparison across countries, it does not fully capture country-specific financing conditions, productive electricity demand, or institutional constraints. The study nevertheless provides a regional planning perspective that can support ECOWAS electrification strategies and long-term progress toward SDG7.</div></div>","PeriodicalId":11546,"journal":{"name":"Energy Strategy Reviews","volume":"66 ","pages":"Article 102319"},"PeriodicalIF":12.1,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148555323","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":"Can energy use rights trading promote net-zero entrepreneurship? Evidence from China","authors":"Ke-Liang Wang,&nbsp;Zu-Xin Meng,&nbsp;Jia-Hui Peng","doi":"10.1016/j.esr.2026.102332","DOIUrl":"10.1016/j.esr.2026.102332","url":null,"abstract":"<div><div>Achieving net-zero emissions requires not only technological innovation but also the emergence of entrepreneurial activity aligned with climate goals. This study aims to identify the effects of China's energy use rights trading policy (EURT)—a market-based, upstream-control environmental regulation—on net-zero entrepreneurship (NZE). To assess panel data from 30 Chinese provinces from 2011 to 2021, we employ DML and Causal Forest methods to identify causal effects and uncover underlying mechanisms. The results indicate that EURT significantly promotes NZE by enhancing innovation and carbon governance awareness, although it has no significant impact on energy consumption awareness and slightly dampens risk-taking. Mechanism analysis reveals that the policy facilitates NZE by improving the business environment, expanding access to green credit, and encouraging pro-environmental public behavior. The heterogeneity test demonstrates that the positive impacts are more pronounced in central-western, less industrialized, and renewable-rich regions. These findings highlight the potential of market-oriented environmental instruments to foster climate-aligned entrepreneurial ecosystems and inform the design of differentiated, mechanism-sensitive policy interventions.</div></div>","PeriodicalId":11546,"journal":{"name":"Energy Strategy Reviews","volume":"66 ","pages":"Article 102332"},"PeriodicalIF":12.1,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148555326","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":"Electricity retail market digitalisation and integration in Europe from 2015 to January 2026: A review","authors":"Jaakko Hirvensalo,&nbsp;Samuli Honkapuro,&nbsp;Salla Annala","doi":"10.1016/j.esr.2026.102317","DOIUrl":"10.1016/j.esr.2026.102317","url":null,"abstract":"<div><div>Over the past decade, Europe's retail electricity market has evolved under digitalisation, data governance reforms, and energy transition pressures. Building on research, policy, and technical proposals, this paper reviews how electricity retail processes, data exchanges, and consumer participation have developed to support a more integrated and flexible European energy system. Using a PRISMA-based systematic mapping approach, this review screens 1162 records and analyses 57 studies published between 2015 and January 2026 — a low inclusion rate signalling how thinly this intersection has been studied. One recurring finding across the reviewed studies is that, rather than harmonising national retail models, Europe appears to be converging on an integration-first approach: federated data-space concepts, mediator layers, and shared semantic frameworks are proposed for interoperability, allowing national systems to remain diverse while functioning collectively. Parallel to this, consumer roles are expanding from passive customers to prosumers, flexibility providers, and local energy market participants, yet adoption remains highly sensitive to tariff design, data access usability, and trust in privacy safeguards. Cross-border perspectives reveal both promise and constraint: integration improves feasibility and supports flexibility exchange, but retail outcomes remain shaped by taxes, levies, and market structure, meaning digital progress alone does not lower household bills. Five interdependences are identified as jointly necessary for durable progress: interoperable architectures; enforceable data governance; tariff–network co-design; fiscal alignment; and resilient retail structures. The review establishes a systematic mapping of the full four-dimension intersection of retail electricity digitalisation, data-exchange architectures, consumer participation, and cross-border feasibility in the EU/EEA context.</div></div>","PeriodicalId":11546,"journal":{"name":"Energy Strategy Reviews","volume":"66 ","pages":"Article 102317"},"PeriodicalIF":12.1,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148555350","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI-driven organizational adaptation in non-renewable energy sector: A systematic review and theoretical framework development","authors":"Abdirahman Mayow Abdi,&nbsp;Xiuquan Deng,&nbsp;Abdulkadir Jeilani Mohamud","doi":"10.1016/j.esr.2026.102299","DOIUrl":"10.1016/j.esr.2026.102299","url":null,"abstract":"<div><div>The non-renewable energy sector is undergoing profound transformation driven by the diffusion of artificial intelligence (AI) technologies across upstream, midstream, downstream, and strategic decision-making processes. However, the sustainability implications of AI adoption remain theoretically fragmented and empirically inconsistent. This study employs a systematic literature review to analyze AI-driven organizational adaptation mechanisms in the non-renewable energy sector. Using the PRISMA framework, we systematically analyzed 39 publications from 2018 to 2025. Key findings reveal AI disruption operates at operational, analytical, and strategic levels; while organizational adaptation serves as a mediating mechanism linking the AI adoption to sustainability outcomes. Furthermore, the study conceptualizes adaptation as a form of configurational adaptation, through strategic alignment, technical readiness, and human transformation dimensions. Building on these insights, the study advances theory by proposing the integrative AI-DRIVEN ORGANIZATIONAL ADAPTATION MODEL (AD-OAM) framework and provides actionable, sector-specific guidance for digital transformation in the non-renewable energy sector.</div></div>","PeriodicalId":11546,"journal":{"name":"Energy Strategy Reviews","volume":"66 ","pages":"Article 102299"},"PeriodicalIF":12.1,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148540813","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":"Energy transition, economic efficiency, and resource use: Evidence on energy efficiency in APEC economies","authors":"Zhile Liu,&nbsp;Shixiang Lu,&nbsp;Yilin Zhong,&nbsp;Jinjun Zhang","doi":"10.1016/j.esr.2026.102324","DOIUrl":"10.1016/j.esr.2026.102324","url":null,"abstract":"<div><div>Energy inefficiency remains a key challenge for Asia-Pacific Economic Cooperation (APEC) economies despite progress in renewable-energy deployment, industrial modernization, and regional energy-policy cooperation. This study examines the effects of energy transition, economic-energy productivity, industrial structure, population density, and freshwater withdrawals on energy-efficiency performance in 21 APEC economies from 1999 to 2023. Energy efficiency is proxied by energy intensity, where lower energy intensity indicates stronger efficiency performance. The study applies principal component analysis, cross-sectional dependence testing, Westerlund panel cointegration, Driscoll–Kraay fixed-effects estimation, and panel-corrected standard errors. The results show that GDP per unit of energy use is consistently associated with lower energy intensity, while industrial value added is consistently associated with higher energy intensity. Energy transition is negatively associated with energy intensity, although its statistical strength differs across estimators. Population density and freshwater withdrawals show model-sensitive effects and should be interpreted cautiously. The negative coefficient of freshwater withdrawals differs from the initial theoretical expectation, suggesting that the water–energy relationship may depend on sectoral productivity, infrastructure quality, and water-use efficiency. The study contributes by integrating energy transition, economic productivity, industrial structure, urban density, and water-resource pressure into a unified APEC-specific framework. The findings support region-specific energy-efficiency strategies aligned with Sustainable Development Goal 7.</div></div>","PeriodicalId":11546,"journal":{"name":"Energy Strategy Reviews","volume":"66 ","pages":"Article 102324"},"PeriodicalIF":12.1,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148555347","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":"Harmonizing energy policies with sustainable development goals (SDGs): A multidisciplinary review","authors":"Asif Gulraiz,&nbsp;Haris M. Khalid,&nbsp;Zafar Said,&nbsp;Abdulla Ismail,&nbsp;Varun Goel,&nbsp;Sudhir Kumar Pathak,&nbsp;Rudraksh S. Gupta,&nbsp;Prabhakar Sharma","doi":"10.1016/j.esr.2026.102327","DOIUrl":"10.1016/j.esr.2026.102327","url":null,"abstract":"<div><div>The Sustainable Development Goals (SDGs) provide a global framework for addressing interconnected challenges in energy access, environmental sustainability, and social equity. Energy policy is central to this agenda because it shapes access, affordability, decarbonization, and the broader social and economic conditions required for sustainable development. This paper presents a <strong>structured narrative and policy-oriented review</strong> of the alignment between energy policies and the SDGs. The particular emphasis of this study is on SDG 7 (Affordable and Clean Energy) and SDG 13 (Climate Action) while also examining links with equity, economic growth, governance, and sustainable consumption. Drawing on selected peer-reviewed studies and policy-relevant literature published from 1992 through early 2026, the review identifies recurring policy gaps, cross-regional differences, and major trade-offs in policy design and implementation. The paper moves beyond descriptive cataloguing by 1) comparing contradictory findings, 2) tracing the evolution of energy–SDG policy thinking, and 3) outlining future pathways for more coherent and inclusive governance. This review highlights the need for integrated policy frameworks, stronger institutional coordination, and context-sensitive strategies that can better align national energy planning with broader sustainability objectives.</div></div>","PeriodicalId":11546,"journal":{"name":"Energy Strategy Reviews","volume":"66 ","pages":"Article 102327"},"PeriodicalIF":12.1,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148635040","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}