Energy Strategy Reviews最新文献

{"title":"A strategic energy consumption management model: Performance evaluation of policy scenarios under sustainable development toward net zero emissions","authors":"Pruethsan Sutthichaimethee ,&nbsp;Jindamas Sutthichaimethee ,&nbsp;Jianhui Luo ,&nbsp;Supakorn Ukumphan ,&nbsp;Worawat Sa-Ngiamvibool ,&nbsp;Buncha Wattana ,&nbsp;Supannika Wattana","doi":"10.1016/j.esr.2026.102268","DOIUrl":"10.1016/j.esr.2026.102268","url":null,"abstract":"<div><div>This research aims to develop an advanced modeling framework for formulating national strategic management under sustainability toward achieving the net zero emissions target. The study constructs a model referred to as the Generalized Method of Moments based on Path Analysis with Exogenous Variables (GMM-PAXi Model), which demonstrates the highest performance when compared with existing models used in previous studies. A mixed-methods research approach is employed to bridge gaps across individual research dimensions and to enhance the depth and validity of the findings. The results indicate that the technology and energy sector is the most responsive sector to changes, followed by the social sector. The newly proposed policy scenarios emphasize solar cell adoption rates, biomass utilization rates, and public participation rates, which differ significantly from traditional policy frameworks that prioritize the BCG (Bio-Circular-Green) economy. The reliance on BCG alone is found to be insufficient for achieving long-term targets. Under the newly proposed policy scenarios, final energy consumption exhibits a growth rate of only 31.75%, which remains within a feasible range for achieving net zero emissions by 2065. In addition, greenhouse gas emissions show a growth rate of 42.35% (2065/2025), corresponding to an increase of 389.45 Mt CO₂ equivalent, which remains below the carrying capacity threshold. These findings demonstrate that the implementation of appropriate and well-designed new policy scenarios enables the government to formulate effective long-term strategic plans and to achieve sustainability in line with national objectives. Consequently, the proposed model serves as a critical analytical tool for supporting long-term policy formulation and strategic planning for Thailand.</div></div>","PeriodicalId":11546,"journal":{"name":"Energy Strategy Reviews","volume":"65 ","pages":"Article 102268"},"PeriodicalIF":7.9,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147951756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Data element marketization and financing constraints in new energy firms: Evidence from the staggered establishment of big data trading platforms in China","authors":"Zhen Li ,&nbsp;Meizhe Song ,&nbsp;Kaijie Wu","doi":"10.1016/j.esr.2026.102259","DOIUrl":"10.1016/j.esr.2026.102259","url":null,"abstract":"<div><div>Data elements marketization (DEM) has evolved into a pivotal pathway that alleviates financing frictions in new energy firms while facilitating the convergence of digital economy and green development initiatives. Using micro-level data of listed new energy firms in China covering the years 2006 to 2023, the present study harnesses a quasi-natural experimental setting derived from the geographically and temporally staggered establishment of data element trading platforms (DETPs). A multi-period difference-in-differences model is constructed to examine how the DEM affects the financing constraints of new energy firms and to uncover the mechanisms through which this effect operates. Evidence shows that the establishment of data trading platforms exerts a significant mitigating effect on the financing constraints faced by firms. This effect operates primarily through reducing information monopolies, expanding collateralizable asset bases, and enhancing the level of digital innovation. Further heterogeneity analyses show that the alleviating effect is stronger among firms with richer digital footprints, weaker supply chain efficiency, cleaner government–business relations, and lower levels of banking competition. The findings yield actionable implications for new energy enterprises grappling with financing bottlenecks in their participation in data element markets, and further furnish evidence-based guidance for policymakers aiming to advance data element marketization reforms and expedite the achievement of carbon peaking and carbon neutrality goals.</div></div>","PeriodicalId":11546,"journal":{"name":"Energy Strategy Reviews","volume":"65 ","pages":"Article 102259"},"PeriodicalIF":7.9,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147951184","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Market-based coordination of hydrogen energy in integrated energy systems: Evidence from Nash bargaining across households, firms, and industries","authors":"Min Tian ,&nbsp;Jie Yu ,&nbsp;Zohrab Pashayev ,&nbsp;Ganijon Ibragimov","doi":"10.1016/j.esr.2026.102233","DOIUrl":"10.1016/j.esr.2026.102233","url":null,"abstract":"<div><div>This study optimizes the joint dispatch of hydrogen-integrated multi-park energy systems to balance cross-sectoral loads and cut emissions. Using Nash bargaining theory as the theoretical framework, the research develops a cooperative game model to optimize joint dispatching across multiple parks in an integrated energy system. The techno-economic framework incorporates hydrogen-doped electric-to-gas (P2G), combined heat and power (CHP), carbon capture and storage (CCS), and renewable integration. The model, applied to three metropolitan parks (industrial, commercial, and residential) over a 24-h scheduling period, demonstrates that cooperative operation significantly reduces costs, enhances renewable energy utilization, and lowers carbon emissions. Results show that, under the case-study parameters, (1) Nash bargaining decreased electricity purchase costs from $1598.94 to $300.12 (an 81.2% reduction), (2) total cooperative costs were reduced by $2321.35 compared to non-cooperative operation, (3) renewable energy integration increased by 6.81 MW, 3.02 MW, and 3.47 MW in the residential, commercial, and industrial parks respectively, (4) carbon emissions were reduced from 232.16 t to 166.04 t across the three scenarios, and (5) hydrogen energy storage effectively alleviated renewable intermittency by converting surplus wind and solar electricity into storable and dispatchable fuel. These results are deterministic estimates for the specific case-study configuration; sensitivity to key techno-economic parameters is discussed in the Limitations section. Policy implications suggest that legislative frameworks and incentives should encourage multi-sectoral cooperation in hydrogen-based integrated energy systems to foster efficiency, resilience, and sustainability.</div></div>","PeriodicalId":11546,"journal":{"name":"Energy Strategy Reviews","volume":"65 ","pages":"Article 102233"},"PeriodicalIF":7.9,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147858557","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Thin markets, big risks: Uranium supply concentration in the age of AI and nuclear expansion","authors":"Kamel Si Mohammed ,&nbsp;Hind Alofaysan ,&nbsp;Samariddin Makhmudov","doi":"10.1016/j.esr.2026.102261","DOIUrl":"10.1016/j.esr.2026.102261","url":null,"abstract":"<div><div>Uranium markets play a critical role in the expansion of nuclear power but remain structurally vulnerable to volatility. This study quantifies the relationship between supply concentration, contracting structures, and uranium spot price dynamics over the period 2015 to 2024. Using global mine production data, supply concentration is shown to remain persistently high, with the leading producer accounting for 38-46% of global output and Herfindahl–Hirschman Index values consistently exceeding 2700. Quantile regression results reveal strong nonlinear effects, with spot price elasticity to concentration rising from 0.63 at the median to 1.94 at the 90th percentile. A two-state regime-switching model identifies a high-volatility regime with price volatility three times higher than in stable periods and an average duration exceeding 14 months. Interaction models further show that a one percentage point reduction in spot market share increases volatility by approximately 1.6%. These findings illustrate that uranium price volatility is structural rather than episodic, driven by concentrated supply and thin liquidity in the spot market.</div></div>","PeriodicalId":11546,"journal":{"name":"Energy Strategy Reviews","volume":"65 ","pages":"Article 102261"},"PeriodicalIF":7.9,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147858551","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Probabilistic long-term forecasting of solar irradiance under climate change using deep learning and Monte Carlo simulations","authors":"Khaoula Saidani ,&nbsp;Nejla Essaddi ,&nbsp;Mongi Besbes","doi":"10.1016/j.esr.2026.102176","DOIUrl":"10.1016/j.esr.2026.102176","url":null,"abstract":"<div><div>While traditional forecasting models assume a stationary climate, the accelerating impact of climate change in arid zones like Southern Tunisia has introduced significant non-stationarity and variance in Global Horizontal Irradiance (GHI). The objective of this study is not to simulate specific IPCC climate scenarios, but rather to develop a robust hybrid deep learning and Monte Carlo framework capable of capturing the <strong>stochastic complexity and increased uncertainty</strong> inherent in recent historical records. By integrating LSTM and Informer architectures with probabilistic Monte Carlo simulations, this framework provides a distribution of potential outcomes, offering a resilient planning tool that accounts for the heightened climatic variability that characterizes the current transition period.</div><div>This study introduces a novel hybrid framework that combines the Informer and Long Short-Term Memory (LSTM) deep learning models with Monte Carlo simulations to generate probabilistic forecasts of Global Horizontal Irradiance (GHI) over a 30-year horizon (2023–2053) in southern Tunisia. Unlike conventional time series approaches, the Informer architecture is specifically designed to capture long-range temporal dependencies with high computational efficiency, making it well suited for modeling complex atmospheric dynamics. Multivariate climatic inputs including the clear sky index, ambient temperature, and relative humidity are used to enhance both temporal accuracy and climate sensitivity. Monte Carlo simulation integration enables rigorous uncertainty quantification by providing confidence intervals for predicted irradiance values. Notably, relative humidity, often neglected in desert climatology emerges as a key <strong>predictor statistically associated with</strong> irradiance variability, accounting for deviations of up to <span><math><mrow><mo>±</mo><mn>5</mn><mtext>%</mtext></mrow></math></span> in post 2053 projections. By fusing deterministic deep learning with stochastic simulation, the proposed framework offers a scalable and reproducible methodology for long-term solar forecasting. The 30-year projections represent probabilistic risk envelopes rather than deterministic forecasts; high-confidence planning is supported primarily by the first decade (Reliability Zone: PINAW <span><math><mrow><mo>&lt;</mo><mn>0</mn><mo>.</mo><mn>15</mn></mrow></math></span>), while projections beyond 10 years constitute speculative scenarios suitable for stress-testing and strategic risk assessment. These findings provide actionable insights for infrastructure design and strategic planning, particularly in regions vulnerable to climate induced energy fluctuations.</div></div>","PeriodicalId":11546,"journal":{"name":"Energy Strategy Reviews","volume":"65 ","pages":"Article 102176"},"PeriodicalIF":7.9,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147995585","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Energy efficiency technologies for waterborne transport: A systematic review and taxonomy pathway","authors":"Johans Jacobo-Jara ,&nbsp;Mehdi Zadeh ,&nbsp;Li Chin Law ,&nbsp;Dong Trong Nguyen","doi":"10.1016/j.esr.2026.102247","DOIUrl":"10.1016/j.esr.2026.102247","url":null,"abstract":"<div><div>Increasing pressure is being placed on maritime transport to reduce energy demand and greenhouse gas emissions within a multi-level regulatory environment. Although energy efficiency is widely recognized as a cost-effective decarbonization pathway aligned with SDG7 and net-zero objectives, policy instruments remain disproportionately oriented towards fuel substitution over demand reduction. This misalignment is compounded by the existed classification of energy efficiency technologies (EETs) for waterborne transport, which are largely descriptive and fuel-centric, lacking cross-segment comparability, standardized metrics, or simultaneous integration of technical readiness, economic feasibility, and regulatory alignment, conditions necessary for actionable decision-making under binding constraints. <em>To address this structural gap, this study develops a decision-support framework grounded in a taxonomy pathway that bridges policy, technology, and investment perspectives, transforming technology classification into a policy appraisal tool and investment screening instrument.</em> The methodology combines a multi-layer validation, yielding a structured taxonomy of 68 EETs across seven clusters, applied comparatively to Inland Waterway Transport (IWT), Short Sea Shipping (SSS), and Oceangoing (OG) fleets across retrofit and new built lifecycles. The framework is aligned with the European Green Deal, Fit for 55, EU ETS, FuelEU Maritime, and IMO mechanisms (EEDI, EEXI, CII), operationalized through 32 key performance indicators and a size-dependent policy indicator defining a feasible performance corridor. Three findings emerge: (i) coordinated deployment of operational optimization, hydrodynamic efficiency, and power conversion clusters delivers the greatest near-term emissions reductions, though without guaranteed long-term decarbonization impact, (ii) regulatory technological alignment is more advanced in IWT and SSS, while OG vessels face elevated uncertainty from fragmented global frameworks, and (iii) operational optimization and hydrodynamic measures offer the most immediate policy investment returns, whereas electrification is segment-dependent and renewable fuel solutions remain costly with limited near-term scalability. The framework provides a transparent, scalable basis for maritime energy planning, policy calibration, and investment prioritization across fleet segment.</div></div>","PeriodicalId":11546,"journal":{"name":"Energy Strategy Reviews","volume":"65 ","pages":"Article 102247"},"PeriodicalIF":7.9,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147995581","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating corporate social responsibility and renewable energy adoption: A pathway to sustainable performance in ecologically fragile regions","authors":"TongTong ,&nbsp;Muhammad Shahid Mastoi ,&nbsp;Mannan Hassan","doi":"10.1016/j.esr.2026.102272","DOIUrl":"10.1016/j.esr.2026.102272","url":null,"abstract":"<div><div>Ecologically fragile regions face ever-increasing problems due to the twin pressures of economic development and environmental degradation, requiring strategic pathways to achieve sustainable production. Although corporate social responsibility (CSR) has gained significant ground as a critical strategic management instrument for sustainability, the processes through which CSR can deliver quantifiable ecological and economic benefits have yet to be tested, particularly in threatened ecosystems. This study addresses this gap by examining how CSR promotes renewable energy adoption (REA), which in turn contributes to ecological and economic performance (EEP). This analysis is based on Stakeholder Theory and Institutional Theory and is developed to create a comprehensive framework that incorporates the roles of mediation and moderation. The sample comprised 330 enterprises in the Upper Minjiang River Basin, China, and the analysis involved partial least squares structural equation modelling (PLS-SEM). The results show that CSR has a significant positive effect on REA (β = 0.32, p &lt; 0.01), while economic performance shows the highest explained variance (R² = 0.55). REA partially mediates this relationship. In addition, a supportive policy environment (PE) amplifies the impact of REA, while contract-rights structure (CRS) limits its effectiveness. This study contributes to the literature and informs strategic policy and practice regarding the need for institutional support and adaptable governance to advance sustainable transitions in ecologically fragile regions.</div></div>","PeriodicalId":11546,"journal":{"name":"Energy Strategy Reviews","volume":"65 ","pages":"Article 102272"},"PeriodicalIF":7.9,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147995577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unveiling unspanned macroeconomic factors in oil futures price dynamics: Evidence from China's oil futures market","authors":"Zhihao Ji ,&nbsp;Jiangfeng Liu ,&nbsp;Li Gao","doi":"10.1016/j.esr.2026.102267","DOIUrl":"10.1016/j.esr.2026.102267","url":null,"abstract":"<div><div>Global energy security and the stability of industrial chains increasingly hinge on the accuracy of crude oil futures price (COFP) discovery. Traditional models often overlook the unspanned macroeconomic factors (UMFs), which represent latent risks existing outside the immediate pricing information of futures contracts yet remain critical for long-term strategic planning. Therefore, the UMFs are extracted through principal component analysis, with bootstrapping employed to mitigate potential endogeneity concerns. Subsequently, a time-varying parameter vector autoregression (TVP-VAR) model is developed to investigate the dynamic interactions between UMFs and COFPs. To validate the framework, we conduct an empirical analysis of the Shanghai crude oil futures (SC) market. The results demonstrate that CPI, industrial added value and the U.S. economic policy uncertainty enhance the predictive accuracy of oil futures returns, particularly during extreme events. The effects of macroeconomic conditions on oil prices are both lagged and time-dependent. Robustness checks further confirm that UMFs capture this delayed relationship more effectively. This underscores their key role in explaining how changes in the macroeconomy affect SC prices over time. Furthermore, SC prices demonstrate significant lagged and asymmetric effects on the macroeconomy, whereby price decreases exert considerably stronger impacts than increases, suggesting that oil-importing nations like China benefit disproportionately from falling prices. We provide insights into the mechanisms linking the macroeconomy and the emerging market.</div></div>","PeriodicalId":11546,"journal":{"name":"Energy Strategy Reviews","volume":"65 ","pages":"Article 102267"},"PeriodicalIF":7.9,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148184876","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Participatory energy governance in the era of sustainability: Ranking strategies","authors":"Mohammad Abdolhosseinzadeh ,&nbsp;Babak Amiri ,&nbsp;Mahdi Abdolhamid ,&nbsp;Mohammad Hasan Seifdar","doi":"10.1016/j.esr.2026.102257","DOIUrl":"10.1016/j.esr.2026.102257","url":null,"abstract":"<div><div>This study addresses the critical challenge of prioritizing participatory energy governance strategies for sustainable development, particularly within the context of developing nations. Facing escalating energy demands and the urgent need for climate action, effectively ranking and diagnosing governance approaches is paramount for a successful renewable energy transition. To achieve this, the research employs a novel hybrid methodology, integrating Neural Network Models (NNM) for robust strategy prioritization with Importance-Performance Analysis (IPA) to formulate prescriptive policy measures. This quantitative modeling is enriched by qualitative expert insights derived from a rigorous Delphi method. The findings provide a nuanced, structural evaluation of current governance frameworks. Notably, strategies such as “strengthening multi-level energy governance” and “expanding solar energy usage through citizen participation” demonstrate both high importance and high performance. These succeed primarily as “soft governance” mechanisms that foster local trust and community empowerment. Conversely, critically important strategies like “developing rural energy networks” and “creating financial incentives for clean energy” exhibit severe performance deficits. A deeper root-cause analysis reveals that these bottlenecks stem from prohibitive financial costs and governmental capacity constraints, rather than a lack of social acceptance. Furthermore, the study identifies significant risks of institutional inertia—where resources are misallocated to overperforming but low-priority sectors—while highlighting the context-dependent value of niche strategies like localized biomass. Ultimately, this research underscores the necessity of decentralized local governance. It provides a data-driven framework urging policymakers to pivot from conventional top-down approaches toward targeted interventions, such as innovative public-private partnerships (PPPs) and decentralized micro-financing, to ensure an equitable and sustainable energy transition.</div></div>","PeriodicalId":11546,"journal":{"name":"Energy Strategy Reviews","volume":"65 ","pages":"Article 102257"},"PeriodicalIF":7.9,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147951183","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparative analysis of price-maker bidding strategies in electricity markets in the context of rising share of new technologies","authors":"Henrik Mantke ,&nbsp;Jilles Carlos De Blauwe ,&nbsp;Georg Frey ,&nbsp;Dogan Keles ,&nbsp;Marc Deissenroth-Uhrig","doi":"10.1016/j.esr.2026.102246","DOIUrl":"10.1016/j.esr.2026.102246","url":null,"abstract":"<div><div>The expansion of renewable generation, demand response and transmission capacities between electricity markets in different countries and regions change electricity markets by increasing heterogeneity in the cost structure of generation and demand. This creates new opportunities for strategic bidding behavior. Moreover sector coupling raises the importance of a cheap and reliable electricity supply for residential heat, mobility and industry applications. This literature review gives an overview of recent research on price-maker bidding strategies in electricity markets in the context of rising share of new technologies and their impact on the market outcome. First the review extracts focal points of the research by classifying the analyzed case studies based on bidding strategy, market and modeling environment including an evaluation of the degree of realism. Second it analyzes the influence of bidding strategies on market prices and bidder’s profits on the basis of a comparative analysis. The results for the influence of strategic bidding on these variables differ by several orders of magnitude. Compared to non-strategic bidding, the maximum market price change reported is 3000% while the minimum observed change is less than 2%. The 3000% market price change is the result of an analysis of strategic bidding of fast ramping power plants during transmission constraints in the Australian Wholesale market. The market price change is enhanced by the specific market rules. Comparable results can be found for bidder’s profit. The reported results show a trend towards lower reported market price changes due to strategic bidding of variable renewable generators compared to that of conventional generators. The influence of strategic of flexible demand lies somewhere in between.</div></div>","PeriodicalId":11546,"journal":{"name":"Energy Strategy Reviews","volume":"65 ","pages":"Article 102246"},"PeriodicalIF":7.9,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147951752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}