Energy Policy最新文献_第6页

A multi-faceted analysis of the influence of state energy policies on spatial clustering of wind and solar farms in the U.S. 国家能源政策对美国风能和太阳能发电场空间集聚影响的多方面分析

IF 9.2 2区经济学 Q1 ECONOMICS

Energy Policy

Pub Date : 2026-01-12 DOI: 10.1016/j.enpol.2026.115073

Anton Rozhkov, Koyel Das

This study examines the spatial clustering of large-scale wind and solar farms in the United States to evaluate the impact of state energy policies and natural resources on the distribution of renewable energy, utilizing the framework of artificial intelligence (AI) and geospatial analysis. We develop an AI-GIS workflow that translates unstructured state policy documents into comparable, dimension-specific policy scores using a rubric-guided large language model (LLM) and links these measures to statistically significant clustering patterns via hexagon-based overlay analysis. By integrating policy scores, analyzed using an LLM, clustering measures, and natural resource availability, we conducted an overlay analysis to identify patterns of co-occurrence. Results show that while solar farm development is strongly influenced by policy incentives, wind farm locations are primarily dictated by natural wind conditions. Unlike sunlight, which is available to some extent in most regions, wind energy requires specific speed thresholds for efficient power generation, making natural resource availability a more decisive factor. Our overlay results show that large-scale solar hot spots align most with strong policy environments, especially comprehensive climate strategies, renewable portfolio standards (RPS) presence, solar-specific support, and grid-readiness measures, whereas large onshore wind clustering aligns predominantly with high wind speeds, with policy variables (e.g., RPS and grid/interconnection readiness) playing a secondary, enabling role. These findings highlight technology-specific pathways, such as policy-responsive solar versus resource-constrained wind, and help identify policy-resource mismatches that may indicate unrealized deployment potential.

本研究利用人工智能（AI）和地理空间分析的框架，考察了美国大型风能和太阳能发电场的空间集群，以评估国家能源政策和自然资源对可再生能源分布的影响。我们开发了一个AI-GIS工作流，该工作流使用规则引导的大型语言模型（LLM）将非结构化的国家政策文档转换为可比较的、特定维度的政策分数，并通过基于六边形的覆盖分析将这些措施与统计上显著的聚类模式联系起来。通过整合使用LLM分析的政策得分、聚类措施和自然资源可用性，我们进行了覆盖分析，以确定共同发生的模式。结果表明，虽然太阳能发电场的发展受到政策激励的强烈影响，但风力发电场的位置主要由自然风力条件决定。与大多数地区在某种程度上可以获得的阳光不同，风能需要特定的速度阈值才能有效发电，这使得自然资源的可用性成为更具决定性的因素。我们的覆盖结果表明，大型太阳能热点与强大的政策环境最为一致，尤其是综合气候战略、可再生能源组合标准（RPS）的存在、太阳能特定支持和电网准备措施，而大型陆上风电集群主要与高风速一致，政策变量（例如RPS和电网/互联准备）起着次要的促进作用。这些发现强调了特定于技术的途径，例如政策响应型太阳能与资源受限型风能，并有助于确定可能表明未实现部署潜力的政策-资源不匹配。

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引用次数: 0

From exposure to preference: How solar electrification experiences shape long-term sustainability in rural Pakistan 从暴露到偏好：太阳能电气化经验如何影响巴基斯坦农村的长期可持续性

IF 9.2 2区经济学 Q1 ECONOMICS

Energy Policy

Pub Date : 2026-01-12 DOI: 10.1016/j.enpol.2025.115062

Marco Nilgen , Johannes Linde , Björn Vollan

Rural electrification initiatives involving the dissemination of solar home systems (SHS) are regarded as an important puzzle piece in the push toward the Sustainable Development Goal of universal electrification. Yet, the evidence on the long-term socioecological implications of such projects remains scarce. Based on a survey of n = 1206 households, this paper examines a large-scale SHS electrification program implemented in rural Sindh, Pakistan, combining a propensity-weighted observational comparison with a life-cycle assessment and a discrete choice experiment. While we are able to identify appliance uptake among beneficiary households, we also find that about ten years after SHS dissemination, only one-third retained a functioning system. We show that this limited durability hampers socioeconomic benefits and severely compromises the project's energetic-payback efficiency: under realistic assumptions, most households fall short of achieving meaningful energy payback thresholds. We also find that households with positive long-term SHS experience exhibit a significantly higher willingness to pay for sustainability indicators, whereas negative experience erodes trust in such quality signals. Reflecting the notion behind our findings, we highlight the concept of conditional durability-based sustainability. In doing so, this study contributes a novel lens to debates on sustainable energy access and long-term market formation in the Global South.

涉及推广太阳能家庭系统（SHS）的农村电气化倡议被视为推动实现普遍电气化这一可持续发展目标的重要拼图。然而，关于这些项目的长期社会生态影响的证据仍然很少。本文基于对n = 1206户家庭的调查，结合倾向加权观察比较、生命周期评估和离散选择实验，研究了在巴基斯坦信德省农村实施的大规模SHS电气化计划。虽然我们能够确定受益家庭对家电的使用情况，但我们也发现，在SHS推广大约十年后，只有三分之一的家庭保留了一个正常运行的系统。我们发现，这种有限的耐久性阻碍了社会经济效益，并严重损害了项目的能源回报效率：在现实的假设下，大多数家庭都达不到有意义的能源回报阈值。我们还发现，拥有积极的长期住房服务经验的家庭对可持续性指标的支付意愿明显更高，而消极的经验则会削弱对此类质量信号的信任。为了反映我们研究结果背后的概念，我们强调了基于条件耐久性的可持续性的概念。在此过程中，本研究为关于可持续能源获取和全球南方长期市场形成的辩论提供了一个新的视角。

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引用次数: 0

Solar irrigation and just energy transitions in agriculture: Insights from evaluation of Gujarat's SKY program 太阳能灌溉和农业能源转换：来自古吉拉特邦SKY项目评估的见解

IF 9.2 2区经济学 Q1 ECONOMICS

Energy Policy

Pub Date : 2026-01-10 DOI: 10.1016/j.enpol.2025.114999

Deepak Varshney , Aditi Mukherji , Kriti Sharma , Anurag Banerjee , Alok Sikka

Set against the backdrop of reducing agricultural emissions, improving smallholder livelihoods, and promoting sustainable groundwater use, this paper evaluates the Surya Shakti Kisan Yojana (SKY)—the world's first large-scale grid-connected solar irrigation pump (SIP) scheme, launched in Gujarat, India in 2018. Using real-time monitoring data from 4321 farmers and a primary survey of 2435 farmers, the study addresses three core objectives. First, it examines the determinants of SKY participation and evaluates the scheme's technical performance, financial features, and income effects. Our findings reveal that financial constraints and risk aversion among smallholder farmers hinder scheme adoption. Farmers earn up to ₹ 21,917 (∼USD 257) annually from electricity sales—43 % of their crop income—even after repaying an annual loan of ₹ 105,000 (∼USD 1235). The simulation suggests that extending the loan repayment period from 7 to 10 years could nearly double farmers' income from energy sales. Second, the study assesses SKY's impact on energy use for groundwater extraction. During the Rabi (dry) season, SKY-enrolled farmers show significantly slower growth in energy consumption than non-enrolled farmers, indicating more sustainable water use. No such difference is observed in the Kharif (monsoon) season. Third, it estimates SKY's climate mitigation potential. Each participant offsets about 12.34 metric tons of CO₂ annually—over twice the impact of off-grid systems—yielding 53,308 metric tons of CO₂ abatement across 4321 farmers. These findings demonstrates grid-connected SIP as a scalable, climate-aligned model for energy transitions in the Global South, offering practical insights for integrated energy-water-livelihood strategies.

在减少农业排放、改善小农生计和促进地下水可持续利用的背景下，本文评估了Surya Shakti Kisan Yojana （SKY）——世界上第一个大型并网太阳能灌溉泵（SIP）计划，该计划于2018年在印度古吉拉特邦启动。利用来自4321名农民的实时监测数据和对2435名农民的初步调查，该研究解决了三个核心目标。首先，本文考察了SKY参与的决定因素，并评估了该方案的技术性能、财务特征和收入效应。我们的研究结果表明，小农的资金约束和风险规避阻碍了计划的采用。农民每年从电力销售中赚取高达21,917卢比（约257美元）-占其作物收入的43% -即使在偿还年度贷款105,000卢比（约1235美元）之后。模拟表明，将贷款还款期从7年延长到10年，可以使农民的能源销售收入增加近一倍。其次，该研究评估了SKY对地下水开采能源使用的影响。在Rabi（干旱）季节，参加sky计划的农民的能源消耗增长明显低于未参加sky计划的农民，这表明用水更加可持续。在Kharif（季风）季节没有观察到这种差异。第三，它估计了天空的气候减缓潜力。每个参与者每年抵消约12.34公吨二氧化碳，是离网系统影响的两倍多，为4321名农民减少了53,308公吨二氧化碳。这些发现表明，并网SIP是全球南方国家能源转型的可扩展、与气候相适应的模式，为综合能源-水-生计战略提供了实际见解。

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引用次数: 0

Regional heterogeneity and policy evolution of China's new energy vehicle development: A multi-dimensional analysis based on dynamic time warping clustering and dual policy frameworks 中国新能源汽车发展的区域异质性与政策演变——基于动态时间规整聚类和双重政策框架的多维分析

IF 9.2 2区经济学 Q1 ECONOMICS

Energy Policy

Pub Date : 2026-01-10 DOI: 10.1016/j.enpol.2026.115072

Chunning Wang, Yifen Yin, Jingwen Cai, Haoqian Hu

Addressing the critical challenge of regional imbalance in China's new energy vehicle (NEV) industry, this study investigates the dynamic co-evolution between regional development patterns and policy intervention logics. We analyzed multidimensional provincial time-series data (2014–2023) covering NEV production, sales, ownership, and infrastructure, alongside 950 provincial policy documents (2009–2023). Methodologically, dynamic time warping (DTW) clustering was employed to capture non-linear development trajectories, while a dual analytical framework combining Hood's NATO typology and Vedung's trichotomy assessed the evolution of policy attention and instrument mixes. Key findings reveal six unique NEV development patterns driven by distinct system logics. Crucially, normalized policy analysis uncovers structural mechanisms underlying this heterogeneity: Innovation-Leading regions employ a “dual-engine” strategy of high regulation and incentives; Follow-up Development regions rely on a “compensatory strategy” with the highest intensity of fiscal subsidies to overcome latecomer disadvantages; while Potential Cultivation regions exhibit a “state-entrepreneurship” model prioritizing organizational tools for infrastructure creation. The research further identifies a spatially staggered transition in policy evolution, highlighting a shift from single-tool dominance to synergistic policy mixes. This study establishes an industry-policy co-evolutionary framework, offering crucial insights for optimizing regional NEV strategies—such as pivoting to carbon trading in leading regions and focusing on energy-transport coupling in lagging regions—ultimately fostering more balanced and sustainable growth.

针对中国新能源汽车产业区域失衡的严峻挑战，本研究探讨了区域发展模式与政策干预逻辑之间的动态协同演化。我们分析了多维省时间序列数据（2014-2023），涵盖新能源汽车的生产、销售、所有权和基础设施，以及950个省政策文件（2009-2023）。在方法上，采用动态时间扭曲（DTW）聚类来捕捉非线性发展轨迹，而结合Hood的北约类型和Vedung的三分法的双重分析框架评估了政策关注和工具组合的演变。主要发现揭示了六种独特的新能源汽车发展模式，这些模式由不同的系统逻辑驱动。至关重要的是，规范化的政策分析揭示了这种异质性背后的结构性机制：创新领先地区采用了高度监管和激励的“双引擎”战略；后续发展区域依靠财政补贴力度最大的“补偿性战略”来克服后发劣势；而潜力培育区则表现出“国家创业”模式，优先考虑基础设施建设的组织工具。该研究进一步确定了政策演变的空间交错过渡，突出了从单一工具主导向协同政策组合的转变。本研究建立了一个产业政策协同进化框架，为优化区域新能源汽车战略提供了重要见解，例如在领先地区转向碳交易，在落后地区关注能源运输耦合，最终促进更平衡和可持续的增长。

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引用次数: 0

Renewable energy communities and energy poverty: Social and policy insights from empirical research in Italy 可再生能源社区和能源贫困：来自意大利实证研究的社会和政策见解

IF 9.2 2区经济学 Q1 ECONOMICS

Energy Policy

Pub Date : 2026-01-10 DOI: 10.1016/j.enpol.2026.115078

Paolo Basilico , Giuliana Michela Cartanese , Idiano D'Adamo , Marco Ferrazza , Massimo Gastaldi , Antonio Felice Uricchio

Renewable energy communities (RECs), energy policy, and energy poverty are closely interlinked within the broader context of the ecological transition. The present study investigates participation in RECs, with particular attention to the distribution of economic benefits, perceptions of climate change, misinformation, and policies targeting energy poverty. The research methodology is based on two online surveys conducted in Italy, comprising 403 and 407 respondents respectively. The results highlight a strong preference for RECs, especially among individuals aged 25–50, driven by both environmental and economic motivations. Women demonstrate slightly greater sensitivity to principles of equity and collective action, while energy self-consumption is identified as the most significant criterion for the distribution of benefits. Respondents stated intentions align with a preference for supporting vulnerable households, suggesting that RECs can serve as effective tools for alleviating energy poverty. The sample indicates a heightened perception of climate change severity, particularly among women. Respondents who perceive higher risks attach greater importance to information campaigns and policies aimed at combating energy poverty. Misinformation is attributed to the limited integration of climate issues into educational curricula and the tendency to perceive climate change as a remote concern — both temporally and geographically. Economic incentives for renewable energy, energy efficiency interventions, and the equitable sharing of benefits within RECs are viewed as the most appropriate policy measures. Overall, RECs emerge as vital instruments for advancing Sustainable Development Goal 7, particularly by addressing the escalating challenge of energy poverty, even in high-income countries.

可再生能源社区（rec）、能源政策和能源贫困在更广泛的生态转型背景下密切相关。本研究调查了参与RECs的情况，特别关注经济利益的分配、对气候变化的看法、错误信息和针对能源贫困的政策。研究方法基于在意大利进行的两项在线调查，分别有403名和407名受访者。结果显示，受环境和经济动机的驱动，人们对RECs有着强烈的偏好，尤其是在25-50岁的人群中。妇女对公平和集体行动的原则表现出稍高的敏感性，而能源的自我消耗被确定为分配利益的最重要标准。受访者表示，他们的意图与支持弱势家庭的倾向是一致的，这表明RECs可以作为缓解能源贫困的有效工具。该样本表明，人们对气候变化严重性的认识有所提高，尤其是在女性中。认为风险较高的受访者更重视旨在消除能源贫困的宣传活动和政策。错误信息归因于气候问题被有限地纳入教育课程，以及人们倾向于将气候变化视为一个遥远的问题——无论是在时间上还是在地理上。对可再生能源的经济激励、能源效率干预和在区域经济合作区内公平分享利益被认为是最适当的政策措施。总体而言，可持续发展区域经济是推进可持续发展目标7的重要工具，特别是通过解决日益严重的能源贫困挑战，即使在高收入国家也是如此。

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引用次数: 0

The green and brown sides of industrial robots: Innovations, AI-Driven patents, energy policy interventions, and emissions dynamics 工业机器人的绿色和棕色两面：创新、人工智能驱动的专利、能源政策干预和排放动态

IF 9.2 2区经济学 Q1 ECONOMICS

Energy Policy

Pub Date : 2026-01-10 DOI: 10.1016/j.enpol.2026.115077

Busra Agan Celik

The rapid diffusion of artificial intelligence (AI) and automation has accelerated the adoption of industrial robots, raising important questions about their environmental impact. This study examines the dual environmental role of industrial robots across the five largest robot-adopting economies—China, Germany, Japan, South Korea, and the United States—over the period 2011–2022. The novelty of this study lies in distinguishing the green and brown channels of automation by incorporating clean energy patents, dirty energy patents, and AI-driven innovation as mediating mechanisms, while simultaneously accounting for heterogeneous environmental policy frameworks. Using panel data estimations with country and time fixed effects, the analysis evaluates both the direct effects of industrial robot adoption on CO₂ emissions and the moderating roles of innovation and policy instruments through interaction terms. The results indicate that industrial robots are interacting with clean energy innovation and AI-based patents significantly reduce emissions, whereas reliance on dirty innovation channels exacerbates environmental degradation. Moreover, market-based environmental policies mitigate the emission-enhancing effects of automation, while non-market-based policies tend to amplify emissions by facilitating large-scale industrial automation. These findings highlight that the environmental impact of industrial robots critically depends on the direction of innovation and the design of environmental policies.

人工智能（AI）和自动化的迅速普及加速了工业机器人的采用，引发了有关它们对环境影响的重要问题。本研究考察了中国、德国、日本、韩国和美国这五个最大的机器人采用经济体在2011-2022年期间工业机器人在环境方面的双重作用。本研究的新颖之处在于，通过将清洁能源专利、肮脏能源专利和人工智能驱动的创新作为中介机制，区分了自动化的绿色和棕色渠道，同时考虑了异质性的环境政策框架。利用具有国家和时间固定效应的面板数据估计，分析评估了工业机器人采用对二氧化碳排放的直接影响，以及创新和政策工具通过相互作用项的调节作用。研究结果表明，工业机器人与清洁能源创新和基于人工智能的专利相互作用显著减少了排放，而对肮脏创新渠道的依赖加剧了环境恶化。此外，基于市场的环境政策减缓了自动化的排放增强效应，而非基于市场的政策往往通过促进大规模工业自动化来放大排放。这些发现强调，工业机器人对环境的影响关键取决于创新的方向和环境政策的设计。

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引用次数: 0

Fuel tax loss in a world of electric mobility: A window of opportunity for congestion pricing 电动汽车时代的燃油税损失：拥堵收费的机会之窗

IF 9.2 2区经济学 Q1 ECONOMICS

Energy Policy

Pub Date : 2026-01-09 DOI: 10.1016/j.enpol.2026.115068

Thi Ngoc Nguyen, Felix Müsgens

The transition to electric mobility will decrease energy tax revenues worldwide while urban congestion intensifies. This paper assesses the effectiveness of congestion pricing to offset fuel tax loss while simultaneously enhancing transport sector efficiency. Using the Berlin metropolitan area as a case study, we estimate fuel tax losses in 2030 under dynamic EV adoption and simulate congestion-based tolls using multi-agent transport simulation (MATSim). We find that congestion toll revenue in a single metropolitan area can fully compensate for regional fuel tax losses while generating substantial welfare gains. The policy reduces travel delays by 1.16 million hours and cuts CO2 emissions by over 42,000 tonnes annually. Distributional analysis reveals that progressive revenue recycling targeting middle- and low-income residents and outer boroughs is essential for public acceptability. Our findings suggest that the fuel tax revenue crisis provides both fiscal necessity and political justification for implementing this economically superior but historically difficult policy.

向电动交通的过渡将减少世界范围内的能源税收，同时城市拥堵加剧。本文评估了拥堵定价在抵消燃油税损失的同时提高运输部门效率的有效性。以柏林市区为例，我们估算了动态电动汽车采用情况下2030年的燃油税损失，并使用多智能体交通模拟（MATSim）模拟了基于拥堵的通行费。我们发现，一个大都市地区的拥堵费收入可以完全弥补区域燃油税损失，同时产生可观的福利收益。该政策每年减少了116万小时的交通延误，减少了4.2万吨的二氧化碳排放。分配分析表明，针对中低收入居民和郊区的渐进式收入回收是公众接受的必要条件。我们的研究结果表明，燃油税收入危机为实施这一经济上优越但历史上困难的政策提供了财政必要性和政治理由。

引用次数: 0

The evolving impact of U.S. monetary policy on real oil prices: A time-varying Granger predictability and local projections approach 美国货币政策对实际油价的演变影响：时变格兰杰可预测性和局部预测方法

IF 9.2 2区经济学 Q1 ECONOMICS

Energy Policy

Pub Date : 2026-01-09 DOI: 10.1016/j.enpol.2025.115052

Max Gillman , Emrah I. Cevik , Sel Dibooglu

This paper examines the dynamic relationship between real oil prices and U.S. monetary policy instruments over more than fifty years. Using symmetric and asymmetric time-varying Granger predictability tests alongside time-varying local projections with stochastic volatility, the study assesses how U.S. monetary aggregates and interest rates predict real oil prices—and how oil prices, in turn, predict monetary variables. The results show that both narrow and broad monetary aggregates, as well as short- and long-term interest rates, Granger predict real oil prices to varying degrees since the 1970s, with notable differences between symmetric and asymmetric specifications. Predictability is bidirectional, yet oil price responses vary substantially over time. Local projections show that interest rates shock real oil prices with high magnitude during early conventional times, especially the 1973 and 1979 oil shocks plus some in the 1980s, but diminish markedly thereafter. In contrast, monetary aggregate shocks dominate in magnitude after 2008, as unconventional monetary policy became manifest. Money supply shocks strongly influence oil prices during the global financial crisis, the 2015–2019 normalization period, the COVID-19 episode, and the 2021–2023 inflation surge. Findings highlight historical time-varying asymmetry in how monetary policy interacts with oil markets, providing implications for policy.

本文考察了50多年来实际石油价格与美国货币政策工具之间的动态关系。利用对称和非对称时变格兰杰可预测性测试以及随机波动的时变局部预测，该研究评估了美国货币总量和利率如何预测实际油价，以及油价如何反过来预测货币变量。结果表明，自20世纪70年代以来，狭义货币总量和广义货币总量以及短期和长期利率都能不同程度地格兰杰预测实际油价，且对称和不对称指标之间存在显著差异。可预测性是双向的，但油价的反应随时间变化很大。当地预测显示，在常规时期早期，利率对实际石油价格的冲击幅度很大，特别是1973年和1979年的石油冲击以及1980年代的一些冲击，但此后明显减弱。相比之下，2008年之后，随着非常规货币政策变得明显，货币总量冲击在规模上占主导地位。在全球金融危机、2015-2019年正常化时期、COVID-19事件以及2021-2023年通胀飙升期间，货币供应冲击对油价产生了强烈影响。研究结果强调了货币政策与石油市场相互作用的历史时变不对称性，为政策提供了启示。

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引用次数: 0

Understanding behavioral factors influencing EV smart charging: A mixed-method study of citizens’ capabilities, opportunities, and motivations 理解影响电动汽车智能充电的行为因素：公民能力、机会和动机的混合方法研究

IF 9.2 2区经济学 Q1 ECONOMICS

Energy Policy

Pub Date : 2026-01-08 DOI: 10.1016/j.enpol.2025.115060

Janna A. de Graaf, F. Marijn Stok, John B.F. de Wit, Michèlle Bal

Objective

The increasing adoption of EVs presents challenges in balancing energy supply and demand. Smart charging offers a potential solution. This study examined which factors support citizen engagement with smart charging, using the Capability-Opportunity-Motivation-Behavior model and related specific mechanisms of actions.

Methods

Using an exploratory sequential mixed-methods design, Study 1 involved semi-structured interviews with 47 EV users in a major city in the Netherlands anticipating (increasing) grid congestion issues, applying a thematic abductive analysis. Findings informed a cross-sectional survey in Study 2 (N = 282), with hierarchical multiple regression analyses assessing the (relative) influence of key factors.

Results

Overall willingness for smart charging of EVs was high. Engagement with smart charging was influenced by opportunities (charging at home or using public charging stations, concerns regarding availability of a charging station, social norms about occupying charging stations), and motivational factors (preference for green energy, importance of grid stability, financial benefits, and trust in the charging system). Capabilities played a less prominent role.

Conclusion

Using a mixed-methods approach, EV users’ willingness to engage with smart charging was shown to be shaped by individual as well as contextual factors. Findings offer valuable guidance for policymakers and stakeholders seeking to promote smart charging. These include, the importance of addressing charging infrastructure availability, social norms against prolonged use of public charging stations, and appealing to attitudinal drivers to promote smart charging behavior effectively.

随着电动汽车的普及，能源供需平衡面临挑战。智能充电提供了一个潜在的解决方案。本研究采用能力-机会-动机-行为模型和相关的具体行为机制，考察了哪些因素支持公民参与智能充电。研究1采用探索性顺序混合方法设计，对荷兰一个主要城市的47名电动汽车用户进行了半结构化访谈，应用主题推导分析，预测（日益增加的）电网拥堵问题。研究2 （N = 282）采用分层多元回归分析评估关键因素的（相对）影响。结果消费者对电动汽车智能充电的总体意愿较高。智能充电的参与受到机遇（在家中或使用公共充电站充电、对充电站可用性的担忧、占用充电站的社会规范）和激励因素（对绿色能源的偏好、电网稳定性的重要性、经济效益和对充电系统的信任）的影响。能力所起的作用不那么突出。结论采用混合方法，电动汽车用户参与智能充电的意愿受到个人因素和环境因素的影响。研究结果为寻求推广智能充电的政策制定者和利益相关者提供了有价值的指导。其中包括，解决充电基础设施可用性的重要性，反对长期使用公共充电站的社会规范，以及呼吁态度端正的司机有效促进智能充电行为。

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引用次数: 0

The digital and green transition dilemma: Is there room for everything? Insights from the next decade (2025–2035) in Aragón (Spain) 数字化和绿色转型的困境：一切都有发展空间吗？展望未来十年（2025-2035）Aragón（西班牙）

IF 9.2 2区经济学 Q1 ECONOMICS

Energy Policy

Pub Date : 2026-01-08 DOI: 10.1016/j.enpol.2025.115061

Jorge Torrubia, Alessandro Lima, Alicia Valero, Antonio Valero

The simultaneous green and digital transitions are creating new land and water demands that compete with traditional uses. Using Aragón (Spain) as a case study, this work examines whether these transitions are compatible. Aragón was selected for its strong renewable energy potential, low population density (allowing land availability), and government support for green hydrogen (GH) and data center (DC) projects, though these initiatives face growing local opposition. We analyzed projected impacts for 2025–2035 estimating electricity and water consumption for DC and GH, and land needs for wind and photovoltaic electricity under three scenarios. Results indicate Aragón's electricity demand could rise sixfold to fifteenfold by 2035, with DC and GH production representing 85 % of total demand. Supplying Aragón's electricity would require 9–39 % of land to host renewables, and depending on renewables deployment, Aragón could shift from a historic electricity exporter to an importer. Water use could grow 41–124 % relative to current economic consumption, and seasonal demand from DC could lead to conflicts. These findings call into question the current pace and compatibility of the twin transition. We recommend integrated planning that prioritizes the green transition, imposes environmental limits, and compensates affected regions to ensure a sustainable, equitable transition.

同时，绿色和数字化转型正在创造新的土地和水需求，与传统用途竞争。以Aragón（西班牙）为例，本研究考察了这些过渡是否兼容。Aragón因其强大的可再生能源潜力，低人口密度（允许土地可用性）以及政府对绿色氢（GH）和数据中心（DC）项目的支持而被选中，尽管这些举措面临着越来越多的当地反对。我们分析了在三种情景下对2025-2035年的影响，估计了直流和GH的电力和水消耗，以及风能和光伏发电的土地需求。结果表明，到2035年，Aragón的电力需求将增长6倍至15倍，直流和GH产量将占总需求的85%。供应Aragón的电力将需要9 - 39%的土地来容纳可再生能源，根据可再生能源的部署，Aragón可能会从历史上的电力出口国转变为进口国。相对于目前的经济消费，用水量可能会增长41 - 124%，而来自DC的季节性需求可能会导致冲突。这些发现对目前双生子转变的速度和兼容性提出了质疑。我们建议综合规划，优先考虑绿色转型，施加环境限制，并补偿受影响地区，以确保可持续、公平的转型。

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