Energy Strategy Reviews最新文献_第4页

Smart and transparent grid stability prediction for efficient energy management using explainable AI 使用可解释的人工智能进行高效能源管理的智能透明电网稳定性预测

IF 7.9 2区工程技术 Q1 ENERGY & FUELS

Energy Strategy Reviews

Pub Date : 2026-03-01 Epub Date: 2026-01-24 DOI: 10.1016/j.esr.2026.102083

Gulfaraz Anis , Naila Samar Naz , Taher M. Ghazal , Muhammad Sajid Farooq , Muhammad Saleem , Chan Yeob Yeun , Munir Ahmad , Khan Muhammad Adnan

The incorporation of modern trends and renewable power systems, coupled with smart grids, has made grid stability prediction increasingly challenging. The limitations of traditional stability prediction systems arise from dynamic power usage, along with unavoidable variations in renewable power supplies, and the models’ inability to track real-time changes. Transparency issues within traditional stability prediction systems hinder grid operators’ understanding of how predictions are formed. Transparent models play a crucial role in building trust and enabling informed decisions, but non-interpretable models pose significant problems by obscuring transparency in critical decisions. In this research, a transparent and smart Explainable Artificial Intelligence (XAI) model is proposed to operate within this framework to address existing issues. The Local Interpretable Model-agnostic Explanations (LIME) framework is integrated to improve the interpretability of model predictions, thereby increasing the transparency of the decision-making process. In this study, grid stability is represented by the dataset label ‘’stabf’’, which classifies each energy load instance as stable or unstable, rather than simulating the physical grid or modeling its dynamics. The integration of Machine Learning (ML) with XAI techniques in the proposed model enables more efficient and transparent operations, resulting in improved predictive performance and accurate real-time predictions. Simulation results have demonstrated the outstanding performance of this proposed model, which achieves an impressive accuracy of 99.92 % and a miss-rate of 0.08 %, outperforming previously published approaches.

现代趋势和可再生能源系统的结合，再加上智能电网，使得电网稳定性预测越来越具有挑战性。传统稳定性预测系统的局限性来自于动态电力使用，以及不可避免的可再生能源供应变化，以及模型无法跟踪实时变化。传统稳定性预测系统的透明度问题阻碍了电网运营商理解预测是如何形成的。透明模型在建立信任和实现知情决策方面发挥着至关重要的作用，但不可解释的模型由于模糊了关键决策的透明度而造成了重大问题。在本研究中，提出了一个透明和智能的可解释人工智能（XAI）模型，以在此框架内运行，以解决现有问题。集成了局部可解释模型不可知论解释（LIME）框架，以提高模型预测的可解释性，从而增加决策过程的透明度。在本研究中，电网稳定性由数据集标签“stabf”表示，它将每个能源负荷实例分类为稳定或不稳定，而不是模拟物理电网或对其动态建模。在提出的模型中，机器学习（ML）与XAI技术的集成使操作更高效、更透明，从而提高了预测性能和准确的实时预测。仿真结果证明了该模型的优异性能，其准确率达到99.92 %，缺失率为0.08 %，优于先前发表的方法。

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引用次数: 0

A bibliometric mapping and trend analysis of MCDM in renewable energy research MCDM在可再生能源研究中的文献计量制图与趋势分析

IF 7.9 2区工程技术 Q1 ENERGY & FUELS

Energy Strategy Reviews

Pub Date : 2026-03-01 Epub Date: 2026-01-31 DOI: 10.1016/j.esr.2026.102079

Gülay Demir , Fatih Ecer , Serhat Yüksel , Hasan Dinçer

This paper examines the connection between renewable energy and Multi-Criteria Decision Making (MCDM) through an extensive bibliometric mapping and trend analysis covering 2014–2024. Concerns about climate change and energy security have brought the transition to renewable sources to the forefront of international discussion and action, highlighting the need for effective support systems to aid decisions that reduce dependence on fossil fuels. MCDM methods, which evaluate and prioritize competing criteria, are crucial in these contexts. Using a collection of 1322 peer-reviewed articles from the Scopus database and tools like Biblioshiny and CiteSpace, there is clear evidence of a rapid increase in publication activity, with a compound annual growth rate of approximately 15.2 %, along with significant methodological progress in this research area. The analysis indicates that current studies are shifting from project-specific investigations (such as site selection and feasibility analyses for energy sites) to broader applications involving systems like micro-grids and hydrogen-based networks. The findings reveal a rapid increase in publication activity after 2018, with sustainability, CO₂ emissions, energy transition, and system-level applications emerging as dominant research themes. Digital integration with AI and blockchain is a major emerging trend. A notable emerging trend is the integration of digital and techno-scientific fields, including AI and Blockchain, with MCDM techniques. Decision criteria, considering various policy initiatives and international agreements like the Paris Agreement and COP29, now emphasize energy justice and circular economy principles. Geographically, key contributions come from China, Turkey, and India, although advancements in solar and wind energy research show higher levels of sophistication. Future research priorities include exploring the role of green hydrogen chains for energy production and distribution, evaluating energy storage potential, developing climate resilience models, measuring energy justice, and enhancing digital and technological interfaces in this field.

本文通过广泛的文献计量制图和趋势分析，研究了可再生能源与多标准决策（MCDM）之间的联系。对气候变化和能源安全的担忧使向可再生能源的过渡成为国际讨论和行动的前沿，突出表明需要有效的支持系统来帮助做出减少对化石燃料依赖的决策。MCDM方法，评估和优先考虑竞争标准，在这些情况下至关重要。通过对Scopus数据库中1322篇同行评议文章以及Biblioshiny和CiteSpace等工具的分析，我们可以清楚地看到，论文发表活动在快速增长，复合年增长率约为15.2% %，同时该研究领域的方法学也取得了重大进展。分析表明，目前的研究正在从特定项目的调查（如选址和能源站点的可行性分析）转向涉及微电网和氢基网络等系统的更广泛的应用。研究结果显示，2018年之后，论文发表量迅速增加，可持续性、二氧化碳排放、能源转型和系统级应用成为主导研究主题。与人工智能和区块链的数字集成是一个主要的新兴趋势。一个显著的新兴趋势是数字和科技领域（包括人工智能和区块链）与MCDM技术的融合。考虑到各种政策倡议和国际协议，如《巴黎协定》和COP29，决策标准现在强调能源正义和循环经济原则。从地理上看，主要贡献来自中国、土耳其和印度，尽管太阳能和风能研究的进步显示出更高的复杂程度。未来的研究重点包括探索绿色氢链在能源生产和分配中的作用，评估能源储存潜力，开发气候适应能力模型，衡量能源正义，以及加强该领域的数字和技术接口。

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引用次数: 0

Asymmetric effects of oil price fluctuations on financial stress 石油价格波动对金融压力的不对称影响

IF 7.9 2区工程技术 Q1 ENERGY & FUELS

Energy Strategy Reviews

Pub Date : 2026-03-01 Epub Date: 2026-01-24 DOI: 10.1016/j.esr.2026.102074

George N. Apostolakis

Fluctuations in oil prices transmit greater uncertainty in financial markets depending on the current market conditions or the direction of price movement. We employ nonlinear autoregressive distributive lag (NARDL) and Markov switching regression autoregressive conditionally heteroskedastic (MSWARCH) models to examine the effects of the asymmetric transmission of oil price innovations on financial stress in a sample of oil-importing economies. The analysis results demonstrate the important roles of the demand side and risk in shaping financial system stability. In particular, the results from the NARDL model indicated a greater negative impact of oil demand shocks on financial stress than a smaller positive effect of oil risk shocks. The results from the NARDL model and the cumulative dynamic multipliers reveal asymmetric effects of oil price shocks of different origins in the short term. More specifically, we find evidence of short-run asymmetries after an oil risk shock for China and the Euro Area and after an oil demand shock for the U.S. and the UK. The results from the MSWARCH approach indicate a significant impact on financial stress after oil demand and oil risk shocks for numerous economies without confirming any asymmetric effects. Our findings are important to investors for portfolio diversification purposes and to policymakers responsible for monitoring and ensuring the stability of the financial system.

根据当前的市场状况或价格走势，石油价格的波动给金融市场带来了更大的不确定性。我们采用非线性自回归分布滞后（NARDL）和马尔可夫切换回归自回归条件异方差（MSWARCH）模型来检验石油价格创新的不对称传导对石油进口经济体金融压力的影响。分析结果表明，需求侧和风险在塑造金融体系稳定性中的重要作用。特别是，NARDL模型的结果表明，石油需求冲击对金融压力的负面影响大于石油风险冲击的正面影响。NARDL模型和累积动态乘数的结果揭示了不同来源的油价冲击在短期内的不对称效应。更具体地说，我们发现在中国和欧元区的石油风险冲击以及美国和英国的石油需求冲击之后，短期不对称的证据。mswatch方法的结果表明，在石油需求和石油风险冲击之后，对许多经济体的金融压力产生了重大影响，但没有证实任何不对称效应。我们的研究结果对投资组合多样化目的的投资者和负责监督和确保金融体系稳定的政策制定者都很重要。

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引用次数: 0

Bridging the energy divide. China energy loans and rural electrification in developing countries 弥合能源鸿沟。中国能源贷款和发展中国家农村电气化

IF 7.9 2区工程技术 Q1 ENERGY & FUELS

Energy Strategy Reviews

Pub Date : 2026-03-01 Epub Date: 2026-01-30 DOI: 10.1016/j.esr.2026.102066

Haoru Yang , Vincent Tawiah , Hela Borgi

This study investigates the impact of Chinese energy loans on rural electrification in 68 emerging countries from 2001 to 2023, addressing a critical gap in understanding the role of external financing in alleviating energy poverty. Using country fixed-effect and System Generalized Method of Moments (S-GMM) models, the findings provide robust evidence that a 1 % increase in Chinese energy loans leads to an average increase of approximately 0.10 percentage points in rural electricity access. However, corruption significantly attenuates this relationship, underscoring the importance of institutional quality in mediating the impact of infrastructure outcomes. Drawing on development economics theory, the analysis demonstrates that Chinese energy loans help address capital and infrastructural deficits in rural areas by facilitating the expansion of national grids, promoting off-grid renewable solutions, and supporting critical energy infrastructure. Illustrative examples, such as the Kafue Gorge Lower Hydropower Project in Zambia and the Karuma Hydropower Project in Uganda, underscore the transformative potential of such investments. The study offers novel empirical insights into how Chinese financing contributes to Sustainable Development Goal 7 (universal energy access). Policy implications suggest that while Chinese energy loans are effective in improving rural electrification, complementary reforms in governance and transparency are essential to maximise their developmental impact.

本研究调查了2001年至2023年间中国能源贷款对68个新兴国家农村电气化的影响，解决了理解外部融资在缓解能源贫困方面的关键空白。利用国家固定效应和系统广义矩量法（S-GMM）模型，研究结果提供了强有力的证据，表明中国能源贷款每增加1% %，农村电力接入平均增加约0.10个百分点。然而，腐败大大削弱了这种关系，强调了制度质量在调节基础设施成果影响方面的重要性。根据发展经济学理论，该分析表明，中国的能源贷款通过促进国家电网的扩张、推广离网可再生能源解决方案和支持关键的能源基础设施，有助于解决农村地区的资本和基础设施赤字。赞比亚Kafue Gorge下游水电项目和乌干达Karuma水电项目等说明性的例子强调了此类投资的变革潜力。该研究为中国融资如何促进可持续发展目标7（普遍能源获取）提供了新的实证见解。政策含义表明，尽管中国能源贷款在改善农村电气化方面是有效的，但在治理和透明度方面的配套改革对于最大限度地发挥其发展影响至关重要。

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引用次数: 0

Enhancing the understanding of China's wind power development: Spatial-temporal dynamics and determinants from a whole industry chain perspective 增强对中国风电发展的认识：全产业链视角下的时空动态与决定因素

IF 7.9 2区工程技术 Q1 ENERGY & FUELS

Energy Strategy Reviews

Pub Date : 2026-03-01 Epub Date: 2026-01-30 DOI: 10.1016/j.esr.2026.102105

Yadong Wang, Zhengyuan Zhai, Zhewen Kang, Mingjie Wang, Qingting Cai, Delu Wang

As China's wind power industry shifts from scale expansion toward value enhancement, improving development performance increasingly depends on coordination across segments of the industry chain. This study provides a comprehensive analysis of China's wind power development (CWPD) from a whole industry chain perspective, covering innovation, investment, production and consumption. Using exploratory spatial data analysis and the geographical detector model, this study examines the spatial-temporal characteristics and key determinants of CWPD from 2005 to 2021. Results show that: (1) At the national level, spatial agglomeration in investment, production and consumption has generally weakened over time, while innovation has shown a renewed tendency toward spatial concentration; (2) Spatially, CWPD follows a pattern characterized by the coastal concentration of innovation, resource-driven investment and production in northern regions, and demand-oriented consumption in eastern regions. However, the persistent separation among innovation, deployment, and demand centers leads to structural mismatches along the industry chain; (3) Wind resource endowment shapes the spatial-temporal patterns, while GDP, green finance, and urbanization further intensify agglomeration. Economic policy uncertainty and environmental regulations serve as external driving forces for the transformation of spatial-temporal characteristics, while technology acts as an internal driving force. Based on these findings, this study advises Chinese policymakers to facilitate a shift from capacity-oriented expansion toward coordinated whole industry chain planning, prioritizing a short-term emphasis on local absorption and system integration in wind-rich regions, a medium-term focus on cross-regional grid and market coordination, and long-term strategies promoting functional complementarity among innovation, deployment, and consumption centers.

随着中国风电产业从规模扩张向价值提升转变，提高发展绩效越来越依赖于产业链各环节的协调。本研究从创新、投资、生产、消费等全产业链角度对中国风电发展进行了全面分析。利用探索性空间数据分析和地理探测器模型，研究了2005 - 2021年中国CWPD的时空特征及其关键影响因素。结果表明：①在国家层面上，投资、生产和消费的空间集聚随着时间的推移逐渐减弱，而创新则呈现出新的空间集聚趋势；(2)从空间上看，东北沿海地区呈现创新集中、资源驱动型投资和生产、需求驱动型消费的格局。然而，创新中心、部署中心和需求中心之间的持续分离导致产业链上的结构性不匹配；③风资源禀赋塑造了时空格局，GDP、绿色金融和城市化进一步强化了集聚。经济政策的不确定性和环境规制是时空特征转变的外部驱动力，而技术是时空特征转变的内部驱动力。基于这些研究结果，本研究建议中国政策制定者促进从以产能为导向的扩张转向协调的全产业链规划，优先考虑短期重点放在风电资源丰富地区的本地吸收和系统集成上，中期重点放在跨区域电网和市场协调上，长期战略重点放在促进创新、部署和消费中心之间的功能互补上。

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引用次数: 0

The more government subsidies, the lower the green innovation efficiency? Evidence from China's energy-intensive industries 政府补贴越多，绿色创新效率越低？证据来自中国的能源密集型产业

IF 7.9 2区工程技术 Q1 ENERGY & FUELS

Energy Strategy Reviews

Pub Date : 2026-03-01 Epub Date: 2026-02-14 DOI: 10.1016/j.esr.2026.102133

Feng Peng , Cong Yu , Shuzhen Zhou

Promoting green innovation in energy-intensive industries is of strategic significance for achieving sustainable economic and social development. However, the role of government subsidies in improving green innovation efficiency (GIE) remains unclear. This study employs a combined approach—network DEA, regression analysis, Bootstrap method, and qualitative comparative analysis (QCA)—to examine the complex effects of government subsidies on GIE in energy-intensive sectors. Results show that, from a net effect perspective, high levels of government subsidies have a significant negative impact on GIE. This adverse effect is mitigated by market competition. In contrast, configurational analysis reveals that high government subsidies are not a necessary condition for achieving high GIE. One configuration leads to high efficiency under high-subsidy conditions, while two distinct pathways emerge under non-high subsidy regimes, indicating equifinality. These findings suggest that the relationship between government subsidies and GIE is not deterministic but depends on the interaction of multiple conditions—including market competition, and human resource. Rather than adopting uniform subsidy policies, policymakers should implement differentiated and context-sensitive strategies, strengthen market mechanisms, and optimize policy bundling. By combining net effect analysis and configurational effect analysis, this study provides a more comprehensive understanding of how government subsidies influence GIE. It advances analytical methods in green innovation research and offers empirical support for refining subsidy policies in energy-intensive sectors.

推进高耗能产业绿色创新，对实现经济社会可持续发展具有战略意义。然而，政府补贴在提高绿色创新效率中的作用尚不明确。本研究采用网络DEA、回归分析、Bootstrap方法和定性比较分析（QCA）相结合的方法，考察了政府补贴对能源密集型行业GIE的复杂影响。结果表明，从净效应的角度来看，高水平的政府补贴对GIE有显著的负面影响。市场竞争减轻了这种不利影响。相反，结构分析表明，高政府补贴并不是实现高GIE的必要条件。一种配置在高补贴条件下导致高效率，而在非高补贴制度下出现两种不同的路径，表明平等。这些研究结果表明，政府补贴与GIE之间的关系不是确定性的，而是取决于多种条件（包括市场竞争和人力资源）的相互作用。政策制定者不应采取统一的补贴政策，而应实施差异化和因地制宜的补贴策略，加强市场机制，优化政策捆绑。本研究通过结合净效应分析和配置效应分析，更全面地了解了政府补贴对GIE的影响。推进了绿色创新研究的分析方法，为完善能源密集型产业补贴政策提供了实证支持。

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引用次数: 0

Energy transition policies and the corporate AI adoption: Evidence from new energy cities 能源转型政策与企业人工智能应用：来自新能源城市的证据

IF 7.9 2区工程技术 Q1 ENERGY & FUELS

Energy Strategy Reviews

Pub Date : 2026-03-01 Epub Date: 2026-02-19 DOI: 10.1016/j.esr.2026.102110

Pin Shen , Sihua Xie , Lingli Qing , Farhad Taghizadeh-Hesary

This paper investigates the impact of urban energy transition policies on the adoption of AI applications by enterprises, utilizing evidence from China's New Energy Demonstration Cities (NEDC) initiative. Using a difference-in-differences methodology on 3024 A-share-listed companies from 2005 to 2022, we estimate the causal effect of the policy on enterprises' adoption of AI. The findings indicate that urban energy transition policies considerably expedite corporate AI adoption, with the policy increasing the likelihood of firm-level AI adoption by roughly 0.1238. Mechanism analyses demonstrate that the transition strategy primarily facilitates AI adoption by increasing R&D spending, fostering AI innovation, and increasing the proportion of highly educated personnel. A heterogeneity study indicates more pronounced consequences for private organizations, high-tech enterprises, low-pollution firms, and companies operating in less regulated contexts. The findings indicate that urban energy transition significantly accelerates AI adoption at the corporate level, providing policy recommendations for integrating energy transition activities with digital transformation plans.

本文利用中国新能源示范城市（NEDC）倡议的证据，研究了城市能源转型政策对企业采用人工智能应用的影响。本文采用差分法对2005年至2022年3024家a股上市公司进行分析，估计了政策对企业采用人工智能的因果效应。研究结果表明，城市能源转型政策大大加快了企业对人工智能的采用，该政策将企业层面采用人工智能的可能性提高了约0.1238。机制分析表明，转型战略主要通过增加研发支出、促进人工智能创新和增加高学历人员比例来促进人工智能的采用。一项异质性研究表明，私营组织、高科技企业、低污染企业和在监管较少的环境中运营的公司的后果更为明显。研究结果表明，城市能源转型显著加速了企业层面对人工智能的采用，为将能源转型活动与数字化转型计划相结合提供了政策建议。

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引用次数: 0

Do dynamic retail energy tariffs threaten the economic viability of ECs operating under static EC-internal energy prices? — Initial insights 动态零售能源关税是否会威胁到在静态欧共体内部能源价格下运营的欧共体的经济可行性？-初步见解

IF 7.9 2区工程技术 Q1 ENERGY & FUELS

Energy Strategy Reviews

Pub Date : 2026-03-01 Epub Date: 2026-02-24 DOI: 10.1016/j.esr.2026.102167

Bernadette Fina

The vast majority – if not all – energy communities (ECs) use static EC-internal energy prices for the billing of energy flows within their virtual borders. At the same time, however, recent trends point strongly towards an increased dynamification of EC-external price components. Therefore, the objective of this work is to provide a generally-applicable framework to assess the economic impact of dynamic retail offers on ECs operating under static EC-internal energy prices. This includes determining (i) the number of time-steps per year in which static EC-internal energy prices are superior to (= better, cheaper than) a retailer’s offer (and vice versa), (ii) the height of actual price differences per 15-min time-step, (iii) the resulting total positive or negative price offset within a year – (iv) for ECs only based on solar generation and (v) for ECs having various generation sources at their disposal. The framework is applied to a representative Austrian case study, considering a range of different scenarios, encompassing the permutations of a variety of static EC-internal energy prices and dynamic retail energy prices. Benchmarked against a dynamic retail tariff (based on day-ahead market price data of 2023) of a comparably cheap Austrian retailer, a low static EC-internal energy price of 12c/kWh makes the EC’s price offer preferable at 65.9% of all time-steps; in contrast, assuming a comparably high static EC-internal energy price of 16c/kWh leads to the almost opposite situation with the retailer’s offer being preferable at 64.4% of all 15-min time-steps over a year. Results are aimed at supporting ECs in their strategic decisions with regard to determining the height of their static EC-internal energy price in an increasingly dynamified external price environment, and in evaluating their potential of economically viable operation in the medium-term. Also, guidance shall be provided for policy decision makers in their process of designing potentially necessary financial support mechanisms for ECs.

绝大多数（如果不是全部的话）能源社区（ec）使用静态的ec内部能源价格对其虚拟边界内的能源流量进行计费。然而，与此同时，最近的趋势强烈表明，欧盟外部价格组成部分的活力日益增强。因此，这项工作的目标是提供一个普遍适用的框架，以评估动态零售报价对在静态ec内部能源价格下运行的ec的经济影响。这包括确定(i)每年的时间步数，其中静态ec内部能源价格优于（=更好，更便宜）零售商的报价（反之亦然），（ii）每15分钟时间步的实际价格差异的高度，（iii）一年内产生的总正或负价格抵消- (iv)仅基于太阳能发电的ec和(v)拥有各种发电源的ec。该框架应用于一个具有代表性的奥地利案例研究，考虑了一系列不同的场景，包括各种静态欧共体内部能源价格和动态零售能源价格的排列。以一家相对便宜的奥地利零售商的动态零售电价（基于2023年日前市场价格数据）为基准，12c/kWh的低静态EC内部能源价格使EC的价格在所有时间步长中占65.9%；相比之下，假设相对较高的静态ec -内部能源价格为16c/kWh，则会导致几乎相反的情况，零售商的报价在一年中所有15分钟时间步长中占64.4%。结果的目的是在日益活跃的外部价格环境下，支持欧洲共同体就确定其静态欧洲共同体内部能源价格的高度作出战略决定，并评价它们在中期经济上可行的运作潜力。此外，还应为政策决策者在为共同体设计可能必要的财政支持机制的过程中提供指导。

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引用次数: 0

Is the provincial government better at high-carbon energy control? 省级政府在高碳能源控制方面做得更好吗？

IF 7.9 2区工程技术 Q1 ENERGY & FUELS

Energy Strategy Reviews

Pub Date : 2026-03-01 Epub Date: 2026-02-22 DOI: 10.1016/j.esr.2026.102117

Mengchan Zhao , Yangyang Cheng , Yongsheng Cheng , Ziai Wu , Yigen Wu

To address the limitations of locally led environmental regulation in China, the Vertical Reform of Environmental Administration (VREA) has recentralized oversight to provincial governments in selected regions. Employing the VREA as a quasi-natural experiment and a staggered difference-in-differences design, this study assesses the efficacy of provincial governments in curbing high-carbon energy use. Contrary to its intended objectives, the VREA implementation correlates with an average annual increase of 11.95 kilotons of standard coal consumption for petrol, 4.23 kilotons for diesel, and 11.57 kilotons less for natural gas as a cleaner energy source. Mechanism analysis reveals that the VREA undermines local governments' environmental engagement, reducing green investment while escalating punitive measures, and leaving enterprises inadequately equipped to transition away from high-carbon energy. These results highlight a consequential gap between centralized policy design and implementation realities, underscoring critical trade-offs in environmental governance. The study offers practical implications for refining China's regulatory architecture and invites broader reflection on how policy instruments perform across varying institutional and industrial contexts.

为了解决中国地方主导的环境监管的局限性，环境行政垂直改革（VREA）在选定的地区将监管重新集中到省级政府。本研究采用VREA作为准自然实验，采用交错差中差设计，对省级政府在抑制高碳能源使用方面的效果进行了评估。与预期目标相反，VREA的实施导致汽油标准煤消耗量平均每年增加11.95千吨，柴油标准煤消耗量增加4.23千吨，作为清洁能源的天然气标准煤消耗量减少11.57千吨。机制分析表明，VREA破坏了地方政府的环境参与，减少了绿色投资，同时加重了惩罚性措施，使企业没有充分的能力从高碳能源转型。这些结果突出了集中式政策设计与实施现实之间的差距，突出了环境治理中的关键权衡。该研究为完善中国的监管架构提供了实际意义，并引发了对政策工具在不同制度和行业背景下如何发挥作用的更广泛思考。

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引用次数: 0

The challenge of planning long-term GHG mitigation while diversifying the economy in Gulf Cooperation Council countries 在海湾合作委员会国家实现经济多样化的同时规划长期温室气体减缓的挑战

IF 7.9 2区工程技术 Q1 ENERGY & FUELS

Energy Strategy Reviews

Pub Date : 2026-03-01 Epub Date: 2026-02-20 DOI: 10.1016/j.esr.2026.102165

Marcello Contestabile , Pankaj Kumar , Carlos Mendez , Ariane Millot , Shivika Mittal , Maroua Benlahrech , Adam Hawkes

GCC countries face the challenge of having to rapidly reduce their domestic GHG emissions while moving away from an economic model that developed around abundant and cheap fossil fuels. They aim to transform into more diversified, less-carbon intensive, knowledge-based economies, the future structure of which, however, remains largely uncertain. The possible implications of uncertainty around future economic diversification pathways on climate change policy and long-term infrastructure planning in Gulf Cooperation Council (GCC) countries have so far not received much attention in the policy discourse and scientific literature. Therefore, the aim of the research is to explore this relationship and derive insights for GCC governments on how to design strategies that are robust under uncertainty. The study critically assesses climate change and economic diversification policies of the GCC countries; it finds that, while governments are generally aware of their interconnectedness, they are not always developing them jointly and mostly not accounting for possible uncertainties. The study further takes Qatar as a case study and explores selected economic diversification and climate change mitigation scenarios with Qatar TIMES, an energy systems model of Qatar. It finds that climate change policy is sensitive to uncertainty around economic diversification pathways and, importantly, that the two areas of policy influence one another in significant ways. The study therefore recommends that the two policy areas be carefully coordinated, also at sectoral level. To develop a better understanding of uncertainties and their impacts, policymakers should employ suitable analytical tools, including energy systems models and economic models.

海湾合作委员会成员国面临的挑战是，必须迅速减少国内温室气体排放，同时摆脱以丰富而廉价的化石燃料为基础的经济模式。他们的目标是转变为更多样化、低碳密集型、知识型经济，然而，未来的经济结构在很大程度上仍不确定。海湾合作委员会（GCC）成员国未来经济多样化路径的不确定性对气候变化政策和长期基础设施规划可能产生的影响，迄今尚未在政策论述和科学文献中得到太多关注。因此，本研究的目的是探索这种关系，并为海湾合作委员会各国政府在不确定性下如何设计稳健的战略提供见解。该研究批判性地评估了海湾合作委员会国家的气候变化和经济多样化政策；报告发现，虽然各国政府普遍意识到它们之间的相互联系，但它们并不总是共同发展这些联系，而且大多没有考虑到可能出现的不确定性。本研究进一步以卡塔尔为例，利用卡塔尔能源系统模型“卡塔尔时代”探索选定的经济多样化和减缓气候变化情景。研究发现，气候变化政策对经济多样化途径的不确定性很敏感，重要的是，这两个政策领域在很大程度上相互影响。因此，研究报告建议也在部门一级仔细协调这两个政策领域。为了更好地理解不确定性及其影响，决策者应该采用合适的分析工具，包括能源系统模型和经济模型。

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