Energy Strategy Reviews最新文献_第3页

Guiding FDI targeting for sectoral energy strategy: PVAR evidence from 43 emerging and developing economies 指导外商直接投资目标的部门能源战略：来自43个新兴和发展中经济体的PVAR证据

IF 7.9 2区工程技术 Q1 ENERGY & FUELS

Energy Strategy Reviews

Pub Date : 2026-01-01 DOI: 10.1016/j.esr.2026.102046

Hichem Saidi , Ayesha Ashraf , Marco Baudino , Nadia Doytch

This study provides sector-level insights to inform energy strategies consistent with SDG 7 and SDG 13. Drawing on a panel of 43 emerging and developing economies (1998–2020), we estimate a GMM panel vector autoregression (PVAR) linking foreign direct investment, sectoral GDP, energy demand, and CO₂ emissions in four sectors of the economy: manufacturing and construction, transportation, commercial and public services, and agriculture and forestry. In manufacturing, FDI shocks increase GDP and are broadly consistent with a short-run halo—lower energy use per unit of output and modest reductions in CO₂—whereas in agriculture and forestry, they raise GDP but are associated with higher CO₂ and only gradual improvements in energy use; in both cases, these environmental effects are front-loaded and attenuate over time. In transportation, the dynamic links between FDI, energy use, and emissions are generally weak, whereas in commercial and public services, energy use and FDI shocks mainly lead to higher CO₂ emissions. Our findings imply two differentiated policy tracks: first, orienting FDI attraction and aftercare toward greener projects, paired with efficiency standards and capability building in production sectors; and second, demand-side efficiency, electrification, and codes/standards for transportation and public and commercial services so that future investment translates into sustained emissions reductions. The estimated sector-level elasticities provide decision-relevant inputs for energy-systems modelling and policy sequencing.

本研究提供了行业层面的见解，为符合可持续发展目标7和13的能源战略提供信息。利用43个新兴和发展中经济体（1998-2020年）的面板，我们估计了GMM面板向量自回归（PVAR）将制造业和建筑业、交通运输业、商业和公共服务以及农业和林业等四个经济部门的外国直接投资、部门GDP、能源需求和二氧化碳排放联系起来。在制造业，外国直接投资冲击增加了GDP，并与短期光环大致一致——单位产出能耗降低，二氧化碳适度减少——而在农业和林业，它们提高了GDP，但与更高的二氧化碳和能源使用的逐步改善有关；在这两种情况下，这些环境影响都是预先产生的，并随着时间的推移而减弱。在交通运输领域，外国直接投资、能源使用和排放之间的动态联系普遍较弱，而在商业和公共服务领域，能源使用和外国直接投资冲击主要导致二氧化碳排放增加。我们的研究结果暗示了两种不同的政策路径：第一，将吸引外国直接投资和后续护理面向更绿色的项目，并与生产部门的效率标准和能力建设相结合；第二，需求侧效率、电气化以及交通运输和公共及商业服务的规范/标准，以便未来的投资转化为持续的减排。估计的部门级弹性为能源系统建模和政策排序提供了与决策相关的输入。

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引用次数: 0

Stakeholder engagement in decarbonisation and ESG strategies: Investigating global patterns of energy companies in CCUS innovation 利益相关者参与脱碳和ESG战略：调查能源公司在CCUS创新中的全球模式

IF 7.9 2区工程技术 Q1 ENERGY & FUELS

Energy Strategy Reviews

Pub Date : 2026-01-01 DOI: 10.1016/j.esr.2025.102013

Zoltán Csedő , Máté Zavarkó , Zoltán Sára , Gábor Pörzse

Formulating decarbonisation strategies with carbon capture, utilization, and storage (CCUS) technologies, as well as integration of an environmental, social, and governance (ESG) strategy into the core business of multinational companies, are highly debated research areas. The former would bring an efficient medium-term solution for industrial decarbonisation but has technological and economic difficulties. The latter would incite corporate sustainability but has concerns about its financial effects. Multinational energy companies, however, face these strategic challenges at the same time. Building on a common theoretical basis, i.e., the stakeholder view, the goal of this study is to explore the interrelations of CCUS innovation, ESG performance, and external stakeholder involvement. The research focused on the largest energy companies worldwide (n = 129). Results show that more than 75 % of companies stepped into the first CCUS technology development phase within the stage-gate innovation process model (discovery). Findings suggest that corporate strategies which include external collaborations result not only in higher CCUS innovation performance, but it also results in higher ESG performance. Nevertheless, only those companies’ ESG scores benefit from CCUS innovation and external stakeholder involvement, which are at least in the first CCUS innovation phase. To the best of our knowledge, this is the first study to analyse decarbonisation strategies with CCUS innovations and ESG performance as central constructs from a stakeholder viewpoint.

利用碳捕获、利用和封存（CCUS）技术制定脱碳战略，以及将环境、社会和治理（ESG）战略整合到跨国公司的核心业务中，是备受争议的研究领域。前者将为工业脱碳带来一个有效的中期解决方案，但存在技术和经济上的困难。后者将促进企业的可持续发展，但人们担心其财务影响。然而，跨国能源公司同时也面临着这些战略挑战。在利益相关者观点这一共同理论基础上，本研究的目标是探索CCUS创新、ESG绩效和外部利益相关者参与之间的相互关系。该研究的重点是全球最大的能源公司（n = 129）。结果表明，在阶段-门创新过程模型（发现）中，超过75% %的公司进入了CCUS技术开发的第一个阶段。研究结果表明，包含外部合作的企业战略不仅能提高企业的CCUS创新绩效，还能提高企业的ESG绩效。然而，只有这些公司的ESG得分受益于CCUS创新和外部利益相关者参与，这至少是在CCUS创新的第一阶段。据我们所知，这是第一个从利益相关者的角度分析以CCUS创新和ESG绩效为核心结构的脱碳战略的研究。

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引用次数: 0

An overview of short-term wind power forecasting: Multi-scale decomposition and multi-model deep learning fusion 短期风电预测综述：多尺度分解与多模型深度学习融合

IF 7.9 2区工程技术 Q1 ENERGY & FUELS

Energy Strategy Reviews

Pub Date : 2026-01-01 DOI: 10.1016/j.esr.2025.102021

Yan Mei , Jinxing Che , Qian Sun , Wei Dong

Accurate wind power forecasting is crucial for the effective scheduling and scientific management of wind energy, enhancing the safety and reliability of power grids. To handle the inherent intermittency of wind energy, forecasting methodologies have evolved from traditional statistical models to deep learning architectures. A dominant paradigm in the field has become the "decomposition-ensemble" framework, which disentangles complex wind power series into more predictable components. However, the efficacy of many existing models is constrained by key limitations, such as adopting a uniform sub-model for all components, insufficient validation on diverse data, and a general neglect of uncertainty quantification. To systematically address these challenges, this paper first provides a review of hybrid forecasting models. Subsequently, it presents a forecasting framework as a case study, which integrates multi-scale signal decomposition with an adaptive multi-model fusion strategy. This approach dynamically assigns suitable models to each decomposed component, and incorporates a non-parametric method for prediction interval generation. The framework’s performance was validated on two heterogeneous datasets representing different geographical locations, seasons, and temporal resolutions. The results demonstrate that the framework outperforms benchmarks in both accuracy and robustness. This study not only offers an effective solution but also highlights the importance of adaptive model selection and the quantification of forecasting uncertainty, charting a course for future research in reliable renewable energy forecasting.

准确的风电功率预测对于风能的有效调度和科学管理，提高电网的安全性和可靠性至关重要。为了处理风能固有的间歇性，预测方法已经从传统的统计模型发展到深度学习架构。该领域的一个主导范式已经成为“分解-集成”框架，它将复杂的风力发电系列分解成更可预测的组件。然而，许多现有模型的有效性受到关键限制的制约，例如对所有组件采用统一的子模型，对不同数据的验证不足，以及普遍忽视不确定性量化。为了系统地解决这些挑战，本文首先对混合预测模型进行了综述。在此基础上，提出了一种结合多尺度信号分解和自适应多模型融合策略的预测框架。该方法动态地为每个分解构件分配合适的模型，并结合非参数方法生成预测区间。在代表不同地理位置、季节和时间分辨率的两个异构数据集上验证了该框架的性能。结果表明，该框架在准确性和鲁棒性方面都优于基准测试。本研究不仅提供了有效的解决方案，而且突出了自适应模型选择和预测不确定性量化的重要性，为未来可靠的可再生能源预测研究指明了方向。

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引用次数: 0

Decision support for energy system transformation – A systematic analysis of MADM software for sustainability assessment 能源系统转型的决策支持——MADM软件可持续性评估的系统分析

IF 7.9 2区工程技术 Q1 ENERGY & FUELS

Energy Strategy Reviews

Pub Date : 2026-01-01 DOI: 10.1016/j.esr.2025.102016

Laura Sofia Mesa Estrada , Martina Haase , Manuel Baumann , Marco Cinelli

Multi-criteria decision analysis (MCDA) methods for sustainability assessment (SA) have been used in various decision-making processes for energy system transformation. However, concerns remain about the complexity and resource intensity of their application. The literature on MCDA and SA involves methodological advances and case studies, but lacks of systematic analysis of MCDA software for decision support. This study conducts a systematic analysis on multi-attribute decision making (MADM) software and their functionality for SA from a theoretical and user perspective. The users are SA practitioners with different levels of knowledge and expertise of MADM methods. The functionality is determined by a set of features gathered from a literature review of studies conducting SA with MADM software and from dedicated literature exploring the capabilities of MADM methods for SA. These features and capabilities are translated into assessment criteria and domains that encompass the entire MADM process, from supporting problem formulation and preference elicitation to robustness analysis. A sample of 25 free MADM software was assessed using 29 criteria across eight domains. Finally, recommendations are provided based on an effort estimation required to extend the software functionality. Results show that the MCDA community aims to provide practitioners with reliable free MADM software. However, weaknesses are identified in the software assessed, particularly in the functionality for stakeholder's involvement, output variability analysis, and problem structuring. Collaborative initiatives involving SA practitioners, software developers and the MCDA community, can help to accordingly enhance MADM software for SA.

可持续性评价的多准则决策分析（MCDA）方法已应用于能源系统转型的各种决策过程中。然而，对其应用的复杂性和资源强度的关注仍然存在。关于MCDA和SA的文献涉及方法上的进步和案例研究，但缺乏对MCDA软件决策支持的系统分析。本研究从理论和用户的角度对多属性决策（MADM）软件及其在SA中的功能进行了系统分析。用户是具有不同水平的MADM方法知识和专业知识的SA从业者。该功能是由一组特征决定的，这些特征来自对使用MADM软件进行SA的研究的文献综述，以及探索MADM方法对SA的能力的专门文献。这些特性和功能被转化为包含整个MADM过程的评估标准和领域，从支持问题表述和偏好激发到健壮性分析。25个免费MADM软件的样本使用8个领域的29个标准进行评估。最后，根据扩展软件功能所需的工作量估计提供建议。结果表明，MCDA社区旨在为从业者提供可靠的免费MADM软件。然而，在评估的软件中识别出弱点，特别是在涉众参与的功能、输出可变性分析和问题结构方面。涉及SA实践者、软件开发人员和MCDA社区的协作计划，可以帮助SA相应地增强MADM软件。

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引用次数: 0

The state of bioenergy research: A bibliometric analysis of review publications 生物能源研究现状：综述出版物的文献计量学分析

IF 7.9 2区工程技术 Q1 ENERGY & FUELS

Energy Strategy Reviews

Pub Date : 2026-01-01 DOI: 10.1016/j.esr.2025.102032

Sai Leung Ng

Bioenergy is increasingly recognized as a cornerstone of the global transition to sustainable energy systems. Given the field's rapid expansion and interdisciplinary scope, this study conducts a meta-level bibliometric analysis of 14,859 review papers indexed in the Scopus database. Using performance analysis and science mapping, the study identifies key research themes, ranging from biodiesel production and anaerobic digestion to sustainability frameworks and thermochemical conversion, and explores their evolution over time. The dissemination landscape is characterized by a dual-channel structure, comprising specialized applied journals and broad-scope interdisciplinary outlets. International collaboration patterns exhibit pronounced regional differentiation, reflecting the diverse research capacities and policy priorities of different countries. These findings provide a comprehensive understanding of the development, organization, and globalization of bioenergy research, offering valuable insights to guide future academic inquiry, policy formulation, and technological innovation.

生物能源日益被认为是全球向可持续能源系统过渡的基石。鉴于该领域的快速扩展和跨学科的范围，本研究对Scopus数据库中索引的14,859篇综述论文进行了元级文献计量分析。通过性能分析和科学制图，该研究确定了关键的研究主题，从生物柴油生产和厌氧消化到可持续性框架和热化学转化，并探索了它们随时间的演变。传播格局的特点是双渠道结构，包括专门的应用期刊和广泛的跨学科渠道。国际合作模式表现出明显的区域差异，反映了不同国家不同的研究能力和政策重点。这些发现提供了对生物能源研究的发展、组织和全球化的全面理解，为指导未来的学术探究、政策制定和技术创新提供了有价值的见解。

引用次数: 0

Cost-effective decarbonization of industrial energy systems through hybrid renewable integration: A long-term MILP optimization 通过混合可再生能源集成的工业能源系统的成本效益脱碳：长期的MILP优化

IF 7.9 2区工程技术 Q1 ENERGY & FUELS

Energy Strategy Reviews

Pub Date : 2026-01-01 DOI: 10.1016/j.esr.2026.102037

Florian Frieden , Jens Leker

Limiting global warming to 1.5 °C requires immediate action. Although allowable global greenhouse gas emissions are well-defined, translating these targets into actionable strategies at the company-level remains challenging. This study addresses critical gaps in understanding transition cost implications and the influence of science-based emission reduction targets on industrial energy systems. We present a novel mixed-integer linear programming (MILP) model that optimizes industrial energy systems until 2050 under climate mitigation constraints. Three scenarios were analyzed: a fossil-fuel reference case, an optimized system without emission constraints, and an optimized system adhering to science-based emission reduction targets. Stochastic programming ensures robust analysis. Three case studies from China, Germany, and the USA illustrated the modeling framework's application. Results indicated that, within the selected case studies and underlying assumptions, optimized hybrid renewable energy systems can achieve substantial cost and emission reductions compared with conventional reference systems. The model demonstrates the feasibility of integrating renewable energy to balance sustainability goals with financial performance. Comparative analysis across international contexts underscores how macroeconomic and regulatory factors shape the economic viability of hybrid renewable energy systems. The findings illustrate the potential of industrial energy system optimization to reduce emissions under favorable techno-economic and regulatory conditions, while highlighting the strong dependence of outcomes on location-specific assumptions.

将全球变暖限制在1.5 °C需要立即采取行动。虽然全球允许的温室气体排放量是明确的，但在公司层面将这些目标转化为可操作的战略仍然具有挑战性。本研究解决了在理解转型成本影响和基于科学的减排目标对工业能源系统的影响方面的关键差距。我们提出了一个新的混合整数线性规划（MILP）模型，该模型在气候减缓约束下优化工业能源系统，直到2050年。分析了三种情景：化石燃料参考案例、无排放约束的优化系统和坚持科学减排目标的优化系统。随机规划保证了分析的鲁棒性。来自中国、德国和美国的三个案例研究说明了建模框架的应用。结果表明，在选定的案例研究和基本假设下，与传统参考系统相比，优化的混合可再生能源系统可以实现大量的成本和排放减少。该模型证明了整合可再生能源以平衡可持续性目标与财务绩效的可行性。跨国际背景的比较分析强调了宏观经济和监管因素如何影响混合可再生能源系统的经济可行性。研究结果表明，在有利的技术经济和监管条件下，工业能源系统优化具有减少排放的潜力，同时强调了结果对特定地点假设的强烈依赖。

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引用次数: 0

Green energy management: Combining sustainable technologies for efficient power generation 绿色能源管理：结合可持续技术实现高效发电

IF 7.9 2区工程技术 Q1 ENERGY & FUELS

Energy Strategy Reviews

Pub Date : 2026-01-01 DOI: 10.1016/j.esr.2026.102071

Wisam Abu Jadayil , Ghada Shwaheen , Mohamad Ramadan , Mohammad Alkhedher

Green technologies are innovative methods for reducing environmental impact and enhancing resource efficiency, thereby significantly promoting sustainable power production. This comprehensive review has been discussed the significant impact of energy management and green technology on advancing sustainable power production. To implement green technology for sustainable energy systems, the study has emphasized the significance of energy management to reduce carbon emissions by integrating renewable energy sources such as solar, wind, hydro, and geothermal power which minimizes waste and ensures that supply matches demand. By managing variations in the output of renewable energy and balancing load, these systems enhance grid stability. In addition, storing excess energy at times of low demand and releasing it during peak hours, energy management has improved the charging and discharging cycles in energy storage devices, such as batteries and pumped hydro storage. Energy waste and greenhouse gas emissions have dramatically decreased because of the adoption of energy efficiency measures and through an analysis of the obstacles and challenges that come with putting these technologies into practice, like high costs and regulations, the study has made recommendations for how to improve the efficacy of green energy management. It has been found that effective energy management is critical to maximize the benefits of green technologies and achieve a more sustainable and efficient energy future.

绿色技术是减少环境影响和提高资源效率的创新方法，从而显著促进可持续电力生产。这篇全面的综述讨论了能源管理和绿色技术对推进可持续电力生产的重要影响。为了在可持续能源系统中实施绿色技术，该研究强调了能源管理的重要性，通过整合太阳能、风能、水力和地热能等可再生能源来减少碳排放，从而最大限度地减少浪费并确保供应与需求相匹配。通过管理可再生能源输出的变化和平衡负荷，这些系统增强了电网的稳定性。此外，通过在低需求时储存多余的能量，并在高峰时段释放，能源管理改善了电池和抽水蓄能等储能设备的充放电周期。由于采用了能效措施，能源浪费和温室气体排放大幅减少，通过分析将这些技术付诸实践所面临的障碍和挑战，如高成本和监管，本研究就如何提高绿色能源管理的效率提出了建议。人们发现，有效的能源管理对于最大限度地发挥绿色技术的效益和实现更可持续、更高效的能源未来至关重要。

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引用次数: 0

Driving the energy transition in the GCC: the role of Artificial Intelligence, technology and energy prices 推动海湾合作委员会能源转型：人工智能、技术和能源价格的作用

IF 7.9 2区工程技术 Q1 ENERGY & FUELS

Energy Strategy Reviews

Pub Date : 2026-01-01 DOI: 10.1016/j.esr.2025.102029

Alanoud Al-Maadid, Mohamed Sami Ben Ali, Kamal Si Mohammed

Amidst global decarbonization dynamics, Artificial Intelligence (AI), the Digital economy, and energy prices are shaping the energy transition in a way that has never been more critical. Using MMQR and IVQR, this research investigates the effects of AI, research and development (R&D), and energy prices on the Energy Transition (ETR) in the Gulf Cooperation Council (GCC) countries. The novel non-parametric quantile analysis results indicate that AI, R&D, and the Digital economy have a positive influence on the energy transition across different quantiles. Oil prices have a negative impact on the energy transition, particularly at the upper quantile, where high oil prices often hinder the transition. AI and the digital economy are important drivers of energy transition in the GCC. This study contributes by showing their significance and offering important insights for policy.

在全球脱碳动态中，人工智能（AI）、数字经济和能源价格正在以前所未有的重要方式塑造能源转型。利用MMQR和IVQR，本研究调查了人工智能、研发（R&；D）和能源价格对海湾合作委员会（GCC）国家能源转型（ETR）的影响。新的非参数分位数分析结果表明，人工智能、研发和数字经济对不同分位数的能源转型具有正向影响。油价对能源转型有负面影响，特别是在高分位数的国家，高油价往往会阻碍能源转型。人工智能和数字经济是海湾合作委员会能源转型的重要推动力。这项研究的贡献在于展示了它们的意义，并为政策提供了重要的见解。

引用次数: 0

Critical minerals and the energy transition 关键矿物和能源转型

IF 7.9 2区工程技术 Q1 ENERGY & FUELS

Energy Strategy Reviews

Pub Date : 2026-01-01 DOI: 10.1016/j.esr.2026.102039

William Grace

The climate crisis requires a transition from a fossil-fuel energy system to renewable energy which is heavily reliant on the so-called critical minerals. Both sets of resources are finite/non-renewable and have been widely used for generations.

Previous energy related studies have identified the increasing energy cost of exploiting fossil fuels (i.e. reducing Energy Return on Energy Invested (EROI)), and several minerals related papers examine potential future scarcity of various minerals. The purpose of the study presented here is to combine both topics to identify whether declining fossil fuel EROI and/or the declining ore grade of critical minerals will constrain the energy transition. A system dynamics model was developed to simulate various energy transition scenarios and the associated additional production energy required as the resources decline in quality to 2100. The study uses four of the IEA's critical minerals as a proxy for demand more generally, namely copper (Cu), cobalt (Co), zinc (Zn) and molybdenum (Mo).

The results indicate that with ambitious growth in renewables, the depletion of mineral resources will lead to unacceptably high production energy requirements some time in the latter half of this century or early in the next. If fossil fuels continue to be retained in the energy mix at high levels, production of oil and gas resources will likely become constrained later this century.

气候危机要求从化石燃料能源系统向严重依赖所谓关键矿物的可再生能源系统过渡。这两种资源都是有限的/不可再生的，并已被广泛使用了几代人。以前与能源有关的研究已经确定了开采化石燃料的能源成本增加（即减少能源投资的能源回报），一些与矿物有关的论文研究了未来各种矿物的潜在短缺。本研究的目的是将这两个主题结合起来，以确定化石燃料EROI的下降和/或关键矿物矿石品位的下降是否会限制能源转型。开发了一个系统动力学模型来模拟各种能源转换情景，以及随着资源质量下降到2100年所需的相关额外生产能源。该研究使用国际能源署的四种关键矿物作为需求的代表，即铜（Cu）、钴（Co）、锌（Zn）和钼（Mo）。结果表明，随着可再生能源的大幅度增长，矿产资源的枯竭将在本世纪下半叶或下个世纪初的某个时候导致不可接受的高生产能源需求。如果化石燃料继续在能源结构中保持高水平，石油和天然气资源的生产可能会在本世纪后期受到限制。

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引用次数: 0

Comprehensive analysis of energy consumption and spatial heterogeneity in urban fringe towns and subdistricts 城市边缘城镇与街道能源消费空间异质性综合分析

IF 7.9 2区工程技术 Q1 ENERGY & FUELS

Energy Strategy Reviews

Pub Date : 2026-01-01 DOI: 10.1016/j.esr.2025.102034

Bo Fu , Hongqing Li , Zheng Yang , Bing Xue , Shuang Gang

Against the background of addressing climate change and promoting low-carbon development, accurately characterizing the spatial distribution of regional energy consumption at the micro-scale holds significant importance. As major hubs for population agglomeration and industrial transition, urban fringe areas urgently require a refined energy consumption accounting method applicable at the subdistrict and town scale. This study integrates remote sensing imagery, POI, road network density, and statistical yearbook data to construct a 300m grid-scale energy consumption estimation model covering four sectors: primary industry, industry, transportation, and residence. We conduct an empirical analysis using Huangyan District in Taizhou City as a case study. The results indicate that energy consumption in Huangyan District exhibits a “one center, multiple clusters” spatial pattern, closely aligning with the regional development plan. Significant differences exist in energy consumption between streets and towns: the eight core subdistricts account for 75 % of total energy use, and their per capita total energy consumption is 1.38 times that of the towns, reflecting clear urbanization characteristics. This study provides a new spatial computation method and foundational dataset for energy analysis at the street and township scales, offering essential support for future investigations into the spatial patterns of energy consumption and spatial governance strategies, while also contributing scientific evidence for urban low-carbon transformation and sustainable development.

在应对气候变化、推动低碳发展的背景下，准确表征区域能源消费的微观空间分布特征具有重要意义。城市边缘区作为人口集聚和产业转型的重要枢纽，迫切需要一种适用于街道和城镇规模的精细化能耗核算方法。本研究结合遥感影像、POI、路网密度、统计年鉴数据，构建了覆盖第一产业、工业、交通、居住四大部门的300米栅格能耗估算模型。本文以泰州市黄岩区为例进行实证分析。结果表明：黄岩区能源消费呈现“一中心、多集群”的空间格局，与区域发展规划高度契合；街道与城镇能耗差异显著：8个核心街道能耗占总能耗的75% %，人均总能耗是城镇的1.38倍，城镇化特征明显。该研究为街道和乡镇尺度的能源分析提供了新的空间计算方法和基础数据集，为未来城市能源消费空间格局和空间治理策略的研究提供了重要支持，同时也为城市低碳转型和可持续发展提供了科学依据。

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引用次数: 0