Renewable and Sustainable Energy Reviews最新文献

From electricity to economy-wide Net-Zero: Comparative analysis of global energy pathways 从电力到全经济净零：全球能源路径的比较分析

IF 16.3 1区工程技术 Q1 ENERGY & FUELS

Renewable and Sustainable Energy Reviews

Pub Date : 2026-01-31 DOI: 10.1016/j.rser.2026.116771

Abbas Rabiee , Saman Nikkhah , Dariush Salehi , Hannele Holttinen , Niina Helistö , Lisa Göransson , Matti Juhani Koivisto , Yoh Yasuda

The transition to Net Zero (NZ) energy systems has become a global priority for combating climate change and achieving sustainable energy systems. This paper presents a systematic review of national NZ electricity and energy system studies, with a primary focus on country-based modeling practices rather than purely academic literature. The review highlights how NZ pathways across nations reflect their unique energy resources, policy priorities, technological capabilities, and socio-economic contexts. Drawing from studies conducted after the Paris Agreement, the paper classifies NZ work into four categories: (I) clean electricity (CE) system studies, (II) NZ electricity system studies, (III) economy-wide NZ studies, and (IV) worldwide NZ economy studies. For each category, it examines the modeling frameworks used, the treatment of key technologies, and the integration of policy and market considerations. The analysis highlights significant differences in assumptions, time horizons, technology portfolios, and the treatment of grid reliability, flexibility, and seasonal balancing. By synthesizing results from multiple countries, including the United States, Japan, South Korea, China, the UK, Sweden, Thailand, France, Canada, Australia, Colombia, Indonesia, Vietnam, and EU member states, the paper identifies common challenges such as long-duration storage needs, transmission expansion, and operational stability under high inverter-based resource penetration. The findings reveal that while renewable energy and storage dominate most NZ strategies, achieving reliable and cost-effective transitions will require integrated planning across sectors, coordinated infrastructure investment, and context-specific policy design. This country-comparative perspective offers insights for policymakers, system planners, and researchers seeking to adapt global NZ strategies to national realities.

向净零（NZ）能源系统过渡已成为应对气候变化和实现可持续能源系统的全球优先事项。本文提出了国家新西兰电力和能源系统研究的系统回顾，主要侧重于基于国家的建模实践，而不是纯粹的学术文献。该报告强调了新西兰在各国的发展路径如何反映了各国独特的能源资源、政策重点、技术能力和社会经济背景。根据巴黎协定后进行的研究，本文将新西兰的工作分为四类：(I)清洁电力（CE）系统研究，（II）新西兰电力系统研究，（III）新西兰经济范围的研究，（IV）全球新西兰经济研究。对于每个类别，它检查所使用的建模框架，关键技术的处理，以及政策和市场考虑的集成。分析强调了在假设、时间范围、技术组合以及对电网可靠性、灵活性和季节性平衡的处理方面的显著差异。通过综合包括美国、日本、韩国、中国、英国、瑞典、泰国、法国、加拿大、澳大利亚、哥伦比亚、印度尼西亚、越南和欧盟成员国在内的多个国家的研究结果，本文确定了在高逆变器资源渗透率下的长期存储需求、传输扩展和运行稳定性等共同挑战。研究结果显示，虽然可再生能源和储能在新西兰的大多数战略中占主导地位，但实现可靠和具有成本效益的转型将需要跨部门的综合规划、协调的基础设施投资和具体情况的政策设计。这种国家比较的观点为政策制定者、系统规划者和研究人员寻求使全球新西兰战略适应国家现实提供了见解。

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引用次数: 0

Liquid amine-based CO2 capture: A review of absorbent systems innovation, multi-scenario applications, and machine learning-assisted optimization 基于液态胺的二氧化碳捕获：吸收系统创新，多场景应用和机器学习辅助优化的综述

IF 16.3 1区工程技术 Q1 ENERGY & FUELS

Renewable and Sustainable Energy Reviews

Pub Date : 2026-01-30 DOI: 10.1016/j.rser.2026.116754

Jingwen Chang , Kailun Chen , Jinglin Li , Li Lin , Endian Hu , Ke Liu , Jianguo Jiang

Liquid amine-based CO₂ capture has the advantage of high absorbing capacity and rate, ideal reusability, and low cost, making it one of the most widely investigated and applied carbon capture technologies all over the world. In this review, the absorbent systems, as the fundament of liquid-amine based CO₂ capture, were summarized and divided into three categories by their components, namely amine-water, ionic liquid-based, and water-lean/nonaqueous systems. Furthermore, application scenarios based on different absorbent systems as well as techno-economic analysis (TEA) and life cycle assessment (LCA) were discussed. Based on the understanding of absorbent systems and application scenarios, studies of machine learning (ML)-assisted optimization in liquid amine-based CO₂ capture were elucidated from molecular and process levels. To uncover the full potential of liquid amine-based CO₂ capture technology, current challenges and further perspectives were proposed. This review aims to help researchers gain a deep understanding of liquid amine-based CO₂ capture technology and further promoting more proper absorbent systems for practical usage.

液态胺基CO2捕集具有吸收率高、可重复利用性好、成本低等优点，是目前国际上研究和应用最广泛的碳捕集技术之一。本文综述了作为液体胺基CO2捕集基础的吸收体系，并根据其组成将其分为三类：胺-水体系、离子液体体系和水/非水体系。讨论了不同吸收体系的应用场景，以及技术经济分析（TEA）和生命周期评价（LCA）。基于对吸收体系和应用场景的理解，从分子和工艺水平阐述了机器学习（ML）辅助优化液体胺基CO2捕集的研究。为了揭示液态胺基CO2捕集技术的全部潜力，提出了当前的挑战和进一步的展望。本文综述旨在帮助研究人员对液态胺基CO2捕集技术有更深入的了解，并进一步促进更合适的吸收系统的实际应用。

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引用次数: 0

Smart meter data intelligence for sustainable distribution network operations: State-of-the-Art applications and pathways toward net-zero 可持续配电网运行的智能电表数据智能：最先进的应用和实现净零的途径

IF 16.3 1区工程技术 Q1 ENERGY & FUELS

Renewable and Sustainable Energy Reviews

Pub Date : 2026-01-30 DOI: 10.1016/j.rser.2026.116723

Nameer Al Khafaf , Hui Song , Ammar Kamoona , Nasser Sabar , Brendan McGrath , Xinghuo Yu , Mahdi Jalili

The transition toward smarter, more sustainable power systems has positioned data analytics at the core of modern electricity distribution network operations. Enabled by widespread smart meter deployment and advanced sensing technologies, distribution network operators now have access to high-resolution data that supports real-time monitoring, forecasting, and control. This paper presents a comprehensive review of state-of-the-art applications of data analytics in distribution networks, focusing on operational areas such as demand forecasting, electricity theft detection, outage identification, anomaly detection, topology identification, and integration of electric vehicles and energy storage systems. It highlights how advanced techniques, including machine learning, clustering, and deep learning, are being applied to transform raw smart meter data into actionable intelligence. Additionally, the paper discusses the enabling role of digital twins, fog computing, and network intelligence in managing grid complexity, improving system resilience, and supporting decarbonisation goals. Challenges related to data quality, scalability, and interpretability are also explored, emphasizing the need for coordinated technical, regulatory, and institutional responses. The findings underline the critical role of data intelligence in building adaptive, data-driven distribution networks capable of supporting the evolving demands of a low-carbon, decentralized energy future.

向更智能、更可持续的电力系统过渡，使数据分析成为现代配电网络运营的核心。通过广泛的智能电表部署和先进的传感技术，配电网运营商现在可以访问高分辨率数据，支持实时监控、预测和控制。本文全面回顾了数据分析在配电网中的最新应用，重点关注需求预测、电力盗窃检测、停电识别、异常检测、拓扑识别以及电动汽车和储能系统的集成等运营领域。它强调了包括机器学习、聚类和深度学习在内的先进技术如何被应用于将原始智能电表数据转化为可操作的智能。此外，本文还讨论了数字孪生、雾计算和网络智能在管理网格复杂性、提高系统弹性和支持脱碳目标方面的使能作用。还探讨了与数据质量、可扩展性和可解释性相关的挑战，强调了协调技术、监管和机构响应的必要性。研究结果强调了数据智能在构建自适应、数据驱动的配电网络方面的关键作用，这些网络能够支持低碳、分散的能源未来不断变化的需求。

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引用次数: 0

Integrating scenarios, policies, and pathways for effective climate policy analysis: An extended concept and analysis framework 整合有效气候政策分析的情景、政策和途径：一个扩展的概念和分析框架

IF 16.3 1区工程技术 Q1 ENERGY & FUELS

Renewable and Sustainable Energy Reviews

Pub Date : 2026-01-30 DOI: 10.1016/j.rser.2026.116770

Jiawei Shi , Yigang Wei

Achieving the Paris Agreement's 1.5 °C and 2 °C temperature goals requires robust climate policy scenarios to evaluate mitigation pathways and policy effectiveness. However, existing research is fragmented, with inconsistencies in scenario development, policy formulation, and model assumptions, limiting its utility for policy design. This study systematically reviews the literature on climate policy scenarios, identifying key sources of uncertainty and proposing an integrated “Scenario-Policy-Pathway” analytical framework. This framework clarifies the relationships between climate policies and temperature targets by identifying the types, components, and construction logic of climate policy scenarios, and emphasizing low-carbon policy as the primary driver of mitigation pathways. It highlights how low-carbon policies instruments influence the timing of implementation, incentivize specific technologies, and embed equity principles into scenario design, thereby improving the interpretability of modeled trajectories. By synthesizing multi-scenario carbon emission forecasts and empirical Chinese case studies, this framework shows strong potential for policy simulation and pathway analysis support. This study provides a comprehensive and powerful tool for climate policy analysis, bridging research and implementation to support global climate objectives.

实现《巴黎协定》的1.5°C和2°C温控目标需要强有力的气候政策情景来评估缓解途径和政策有效性。然而，现有的研究是碎片化的，在情景发展、政策制定和模型假设方面不一致，限制了其对政策设计的效用。本研究系统地回顾了有关气候政策情景的文献，确定了不确定性的主要来源，并提出了一个综合的“情景-政策-路径”分析框架。该框架通过识别气候政策情景的类型、组成部分和构建逻辑，明确了气候政策与温度目标之间的关系，并强调低碳政策是减缓路径的主要驱动因素。它强调了低碳政策工具如何影响实施时间，激励特定技术，并将公平原则纳入情景设计，从而提高建模轨迹的可解释性。通过综合多情景碳排放预测和中国实证案例研究，该框架显示出强大的政策模拟和路径分析支持潜力。这项研究为气候政策分析提供了一个全面而有力的工具，将研究与实施联系起来，以支持全球气候目标。

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引用次数: 0

Human-centered collaborative design in green buildings: A comprehensive review of neurotechnology integration 绿色建筑中以人为中心的协同设计：神经技术集成的综合综述

IF 16.3 1区工程技术 Q1 ENERGY & FUELS

Renewable and Sustainable Energy Reviews

Pub Date : 2026-01-30 DOI: 10.1016/j.rser.2026.116772

Hanliang Fu , Yuxuan Hao , Zhifang Wu , Hongbin Xu , Jian Zuo

Green building research is shifting from a sole focus on physical performance to a human-centered, collaborative approach that integrates environmental sustainability with user well-being. However, a critical gap remains in understanding how built environments influence physiological, emotional, and cognitive processes. This review examines the integration of neuroscientific tools - including electroencephalography (EEG), functional magnetic resonance imaging (fMRI), event-related potentials (ERPs), eye-tracking (ET), and functional near-infrared spectroscopy (fNIRS) - into green building research. These technologies enable objective and fine-grained measurement of human responses to architectural spaces. We demonstrate how multimodal neurotechnologies facilitate real-time detection of human–environment interactions, supporting dynamic spatial optimization, health-oriented performance enhancement, and the subconscious reinforcement of sustainable behaviors. Beyond synthesizing empirical evidence, we propose an AI-augmented collaborative design framework that connects neural data with environmental parameters, bridging aesthetic, scientific, technical, and ethical rationalities. This framework provides a transformative pathway towards carbon neutrality while enhancing cognitive and emotional well-being, positioning neuroscience as a cornerstone of next generation green building research.

绿色建筑研究正在从单纯关注物理性能转向以人为本的协作方法，将环境可持续性与用户福祉相结合。然而，在理解建筑环境如何影响生理、情感和认知过程方面，仍然存在一个关键的差距。本文综述了神经科学工具-包括脑电图（EEG），功能磁共振成像（fMRI），事件相关电位（ERPs），眼动追踪（ET）和功能近红外光谱(fNIRS) -在绿色建筑研究中的整合。这些技术能够客观和细致地测量人类对建筑空间的反应。我们展示了多模态神经技术如何促进人与环境相互作用的实时检测，支持动态空间优化，以健康为导向的性能增强，以及可持续行为的潜意识强化。除了综合经验证据，我们提出了一个人工智能增强的协作设计框架，将神经数据与环境参数联系起来，弥合美学、科学、技术和伦理理性。该框架提供了一条通往碳中和的变革性途径，同时增强了认知和情感健康，将神经科学定位为下一代绿色建筑研究的基石。

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引用次数: 0

AI-driven optimization of photocatalytic hydrogen production: Integrating techno-economic analysis and regional environmental constraints 人工智能驱动的光催化制氢优化：整合技术经济分析和区域环境约束

IF 16.3 1区工程技术 Q1 ENERGY & FUELS

Renewable and Sustainable Energy Reviews

Pub Date : 2026-01-29 DOI: 10.1016/j.rser.2026.116748

Juyoung Byun , Yurim Kim , Jonghun Lim , Minseong Kim , Junghwan Kim

Photocatalytic (PC) hydrogen production offers a promising pathway for sustainable hydrogen generation. However, most existing studies mainly aim to increase the hydrogen evolution rate (HER), overlooking that high-performing catalysts are not necessarily economically viable. Real-world deployment requires simultaneous optimization of catalyst performance and system-level economics under varying environmental conditions. To bridge this gap, this study introduces an AI-integrated framework combining surrogate modeling of HER with techno-economic optimization and regional constraint analysis. Thirty-five machine learning models were benchmarked, and the Voting CGF ensemble achieved the best predictive performance (R² = 0.9427, MSE = 0.0009), with conduction band position (Ec) identified as the most influential feature. This framework was used to evaluate 1320 catalyst designs comprising four photocatalysts, 30 cocatalysts, and 11 sacrificial agents. Simultaneous optimization of LCOH and HER uncovers distinct catalyst design strategies often overlooked by conventional HER-focused approaches. Notably, [g-C₃N₄, Group A, None] combination achieved a levelized cost of hydrogen (LCOH) as low as $0.487/kg, challenging the idea that sacrificial agents are always needed for economic viability. Furthermore, regional analysis also provided a critical insight: locational constraints can be more impactful than catalyst choice. Freshwater availability was the most critical constraint, with LCOH varying more than 13-fold under identical catalyst designs. This novel framework enables rapid identification of catalyst designs satisfying simultaneous HER, LCOH, and regional requirements without repeated experiments, paving the way for scalable and cost-effective PC hydrogen production.

光催化制氢为可持续制氢提供了一条很有前途的途径。然而，大多数现有的研究主要是为了提高析氢速率（HER），而忽略了高性能催化剂不一定具有经济可行性。实际应用需要在不同环境条件下同时优化催化剂性能和系统级经济性。为了弥补这一差距，本研究引入了一个将HER代理建模与技术经济优化和区域约束分析相结合的人工智能集成框架。对35个机器学习模型进行了基准测试，投票CGF集合的预测性能最好（R2 = 0.9427, MSE = 0.0009），其中传导带位置（Ec）被认为是最具影响力的特征。该框架用于评估1320种催化剂设计，包括4种光催化剂、30种助催化剂和11种牺牲剂。LCOH和HER的同时优化揭示了不同的催化剂设计策略，这些策略通常被传统的以HER为中心的方法所忽视。值得注意的是，[g-C3N4， A组，None]组合使氢（LCOH）的平均成本低至0.487美元/千克，挑战了为了经济可行性总是需要牺牲剂的观点。此外，区域分析还提供了一个关键的见解：区位约束可能比催化剂选择更有影响力。淡水可用性是最关键的限制因素，在相同的催化剂设计下，LCOH变化超过13倍。这种新颖的框架可以快速识别同时满足HER， LCOH和区域要求的催化剂设计，而无需重复实验，为可扩展和具有成本效益的PC制氢铺平了道路。

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引用次数: 0

Hydrogen-electricity-heat sector Coupling: Review of integrated models, control strategies, challenges, and future research directions 氢-电-热耦合：综合模型、控制策略、挑战和未来研究方向综述

IF 16.3 1区工程技术 Q1 ENERGY & FUELS

Renewable and Sustainable Energy Reviews

Pub Date : 2026-01-29 DOI: 10.1016/j.rser.2026.116756

Manzoore Elahi M. Soudagar , Bandi Maheswara Rao , Vinayagam Mohanavel , Manikandan Ayyar , Ramya Maranan , R. Venkatesh , Lalitha Gnanasekaran , D. Shanmugapriya , M. Santhamoorthy

The integration of hydrogen, electrical, and thermal energy systems represents a crucial direction for deep decarbonization by enhancing energy flexibility, maximizing the use of renewable resources, and facilitating inter-sectoral energy exchanges aligned with consistent climate and energy availability objectives. This review consolidates recent developments in the integrated modeling and control of hydrogen-electricity-heat (HEH) coupling, emphasizing optimization, real-time operational strategies, and data-driven methodologies that enhance resource efficiency and system robustness. Empirical data from simulations and pilot investigations indicate that synchronized HEH operations can reduce renewable energy cutting , increase overall system and decrease CO₂ emissions compared to uncoupled systems. We scrutinize deterministic, stochastic, dynamic, and hybrid physics-artificial intelligence (AI) frameworks, including novel AutoML-assisted methodologies, alongside hierarchical and predictive control strategies. Outstanding challenges in scalability, multi-time-scale coordination, uncertainty mitigation, interoperability, and market structuring are identified, and a strategic framework is proposed for hybrid physics-ML modeling, decentralized multi-agent control, and digital-twin-enabled optimization to encourage equitable, cost-effective, and climate-resilient HEH energy ecosystems across varied geographical and socio-economic contexts globally.

氢能、电能和热能系统的整合是实现深度脱碳的一个重要方向，可以增强能源灵活性，最大限度地利用可再生资源，促进与气候和能源可用性目标一致的部门间能源交换。本文综述了氢-电-热（HEH）耦合集成建模和控制的最新进展，强调优化、实时操作策略和数据驱动方法，以提高资源效率和系统鲁棒性。来自模拟和试点调查的经验数据表明，与不耦合系统相比，同步HEH操作可以减少可再生能源的削减，增加整个系统并减少二氧化碳排放。我们仔细研究了确定性、随机、动态和混合物理-人工智能（AI）框架，包括新的自动辅助方法，以及分层和预测控制策略。确定了可扩展性、多时间尺度协调、不确定性缓解、互操作性和市场结构方面的突出挑战，并提出了混合物理- ml建模、分散多智能体控制和数字双胞胎优化的战略框架，以鼓励全球不同地理和社会经济背景下公平、具有成本效益和气候适应性的HEH能源生态系统。

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引用次数: 0

Feasibility of machine learning application in pavement life cycle assessment: A review 机器学习在路面生命周期评估中的可行性研究综述

IF 16.3 1区工程技术 Q1 ENERGY & FUELS

Renewable and Sustainable Energy Reviews

Pub Date : 2026-01-29 DOI: 10.1016/j.rser.2026.116757

Bhaskar Pratim Das , Shankar Deka , Taavi Dettenborn , Sanandam Bordoloi

The need to mitigate the environmental impacts of pavement systems has increased interest in life cycle assessment (LCA), but its implementation often faces challenges, such as data uncertainties, inconsistent impact methods, and limited decision-support capabilities. This review explores the utilization of machine learning (ML) to address these challenges and enhance LCA workflows. This review addresses the current practices and challenges in pavement LCA by structuring it around its four phases, i.e., goal and scope definition, inventory analysis, impact assessment, and interpretation. Diverse applications of data-driven ML techniques in pavement systems and LCA are highlighted. Review indicates that ML can enhance pavement LCA by predicting context-specific inventory data, clustering diverse datasets to detect inconsistencies, and simulating different allocation scenarios. Moreover, multiple impact categories forecasting seems possible with ML-based inventory analysis. ML-based visualisations, such as decision trees, can clarify variables’ contributions to environmental outcomes. ML can also support sensitivity and uncertainty analyses to strengthen decision-making.

减轻路面系统对环境影响的需求增加了人们对生命周期评估（LCA）的兴趣，但其实施往往面临挑战，例如数据不确定、影响方法不一致以及决策支持能力有限。本文探讨了利用机器学习（ML）来应对这些挑战并增强LCA工作流程。本文围绕四个阶段，即目标和范围定义、清单分析、影响评估和解释，阐述了当前路面LCA的实践和挑战。强调了数据驱动的ML技术在路面系统和LCA中的各种应用。回顾表明，ML可以通过预测上下文特定的库存数据，聚类不同的数据集来检测不一致性，以及模拟不同的分配场景来增强路面LCA。此外，基于机器学习的库存分析似乎可以预测多个影响类别。基于机器学习的可视化，如决策树，可以澄清变量对环境结果的贡献。机器学习还可以支持敏感性和不确定性分析，以加强决策。

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引用次数: 0

Photoelectrochemical pathways to green hydrogen. analysis, overview, and foresight 绿色氢的光电化学途径。分析、概述和预见

IF 16.3 1区工程技术 Q1 ENERGY & FUELS

Renewable and Sustainable Energy Reviews

Pub Date : 2026-01-29 DOI: 10.1016/j.rser.2026.116753

Ye. Shevchenko , N. Bakranov , A. Serikkanov , D. Bakranova

Photoelectrochemical (PEC) water splitting represents a promising pathway for sustainable hydrogen production by directly converting solar energy into chemical fuel within a single integrated system. Despite decades of intensive research on semiconductor photoelectrodes, PEC technologies remain largely confined to laboratory-scale demonstrations due to limited solar-to-hydrogen efficiency, insufficient operational stability, and challenges related to scalability and system integration. This review provides a critical and technology-oriented synthesis of recent advances in PEC hydrogen generation, focusing on material platforms, device architectures, and modification strategies that govern performance and durability. Emphasis is placed on oxide, nitride, chalcogenide, and hybrid photoelectrode systems, alongside interface engineering approaches such as heterojunction formation, defect and vacancy control, surface passivation, and cocatalyst integration. Beyond materials-level considerations, the analysis situates PEC water splitting within a broader technoeconomic and system context, addressing cost drivers, integration with variable renewable energy supply, and infrastructure constraints. Drawing on representative academic results and patent-informed technological developments, the review identifies key bottlenecks limiting practical deployment and highlights pathways for translating laboratory advances toward demonstrator-scale systems. On this basis, a foresight-oriented roadmap extending to 2035 is proposed, outlining strategic milestones in efficiency, stability, system integration, and policy alignment required for PEC water splitting to emerge as a viable contributor to the future hydrogen economy.

光电化学（PEC）水分解是一种有前途的可持续制氢途径，通过在单一集成系统内直接将太阳能转化为化学燃料。尽管对半导体光电极进行了数十年的深入研究，但由于太阳能制氢效率有限，操作稳定性不足，以及与可扩展性和系统集成相关的挑战，PEC技术仍然主要局限于实验室规模的演示。本文综述了PEC制氢技术的最新进展，重点介绍了材料平台、设备架构以及控制性能和耐久性的修改策略。重点放在氧化物、氮化物、硫族化物和混合光电极系统，以及界面工程方法，如异质结形成、缺陷和空位控制、表面钝化和助催化剂集成。除了材料层面的考虑，分析将PEC水分解置于更广泛的技术经济和系统背景下，解决成本驱动因素，与可变可再生能源供应的整合以及基础设施限制。根据具有代表性的学术成果和专利知情的技术发展，该综述确定了限制实际部署的关键瓶颈，并强调了将实验室进展转化为示范规模系统的途径。在此基础上，提出了一个延伸至2035年的前瞻性路线图，概述了PEC水分解成为未来氢经济可行贡献者所需的效率，稳定性，系统集成和政策一致性的战略里程碑。

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引用次数: 0

Ammonia as a strategic fuel in SOFC-gas-turbine hybrid systems for carbon-neutral power generation 氨作为sofc -燃气轮机混合动力系统中碳中和发电的战略燃料

IF 16.3 1区工程技术 Q1 ENERGY & FUELS

Renewable and Sustainable Energy Reviews

Pub Date : 2026-01-29 DOI: 10.1016/j.rser.2026.116742

Baozuo Sun , Yu Liu , Zhao Yin , Hualiang Zhang , Yujie Xu , Haisheng Chen

Ammonia is emerging as a viable carbon-free energy carrier with strong potential to power high-efficiency hybrid systems. Among such systems, solid-oxide fuel cell (SOFC)-gas turbine (GT) systems offer an integrated platform that combines electrochemical and thermodynamic energy conversion. In this review, the feasibility of using ammonia as the sole fuel for SOFC-GT hybrid systems is critically evaluated by independently examining its roles in direct ammonia-fed solid oxide fuel cells (DA-SOFCs) and ammonia-fired GTs (NH₃-GTs). For DA-SOFCs, we summarize recent advances in electrolyte architectures, catalytic anode materials, NO_x mitigation, and durability strategies. For NH₃-GTs, we review the combustion characteristics of ammonia and explore enhancement methods including co-firing with hydrogen or methane, staged combustion, and catalytic combustion approaches. By comparing performance, challenges, and system integration strategies across both components, we demonstrate the technical viability of ammonia as a unified fuel and highlights its potential to support high-efficiency, low-emission, and carbon-free SOFC-GT power generation. The insights presented provide a foundation for the future development of ammonia-based hybrid energy systems in the global transition toward carbon neutrality.

氨正在成为一种可行的无碳能源载体，具有为高效混合动力系统提供动力的强大潜力。在这些系统中，固体氧化物燃料电池(SOFC)-燃气轮机（GT）系统提供了一个结合电化学和热力学能量转换的集成平台。在这篇综述中，通过独立研究氨在直接供氨固体氧化物燃料电池（DA-SOFCs）和氨燃烧燃料电池（nh3 - gt）中的作用，严格评估了氨作为SOFC-GT混合动力系统唯一燃料的可行性。对于da - sofc，我们总结了电解质结构、催化阳极材料、NOx减排和耐久性策略的最新进展。对于NH3-GTs，我们回顾了氨的燃烧特性，并探索了与氢或甲烷共烧、分级燃烧和催化燃烧的增强方法。通过比较两种组件的性能、挑战和系统集成策略，我们证明了氨作为统一燃料的技术可行性，并强调了其支持高效、低排放和无碳SOFC-GT发电的潜力。提出的见解为全球向碳中和过渡的氨基混合能源系统的未来发展奠定了基础。

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引用次数: 0