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Harnessing microalgae from wastewater for biocrude via hydrothermal Liquefaction: A sustainable pathway to biofuels and biochemicals 通过水热液化从废水中利用微藻生产生物原油:生物燃料和生物化学的可持续途径
IF 16.3 1区 工程技术 Q1 ENERGY & FUELS Pub Date : 2026-05-01 Epub Date: 2026-01-25 DOI: 10.1016/j.rser.2026.116759
Ramachandran Sivaramakrishnan , Sandeep Kumar , Hemen Hosseinzadeh , Venkatesh Balan
The search for renewable alternatives has turned attention to microalgae, which grow rapidly, achieve high biomass productivity, and accumulate substantial lipids. Unlike terrestrial feedstocks such as corn or sugarcane, microalgae can be cultivated on non-arable land using saline or wastewater streams, avoiding competition with food supplies. Wastewater cultivation is particularly compelling because municipal and agricultural effluents supply nitrogen, phosphorus, and organic carbon, while algal growth removes excess nutrients that would otherwise drive eutrophication; reported removal efficiencies often exceed 90 % under optimized conditions. Algal–bacterial consortia further enhance performance by generating oxygen through photosynthesis and capturing CO2, thereby lowering aeration costs. The major challenge lies not in cultivation but in conversion. Drying biomass is energy-intensive, whereas hydrothermal liquefaction (HTL) transforms wet algal slurries directly into biocrude at 250–350 °C and 10–20 MPa. Typical yields range from 30 to 50 % of dry weight, with an energy density of 38–41 MJ/kg, along with nutrient-rich aqueous fractions, gases, and char that can be recycled. Key barriers remain in lowering oxygen and nitrogen content, scaling reactors, and reducing upgrading costs. This review evaluates the integration of wastewater-based algal cultivation with HTL for renewable fuel production, examining wastewater characteristics, cultivation strategies, biomass yields, HTL fundamentals and process advances, product upgrading, and techno-economic and environmental aspects. By linking wastewater remediation with biofuel production, the review highlights opportunities for nutrient recycling, greenhouse gas mitigation, and circular-economy applications, while identifying the technical gaps that must be addressed for practical deployment.
寻找可再生替代品已将注意力转向微藻,它们生长迅速,实现高生物量生产力,并积累大量脂质。与玉米或甘蔗等陆地原料不同,微藻可以在非耕地上种植,利用盐水或废水流,避免与粮食供应竞争。废水培养尤其引人注目,因为城市和农业废水提供氮、磷和有机碳,而藻类生长去除多余的营养物质,否则会导致富营养化;据报道,在优化条件下,去除效率通常超过90%。藻类-细菌联合体通过光合作用产生氧气和捕获二氧化碳进一步提高性能,从而降低曝气成本。主要的挑战不在于栽培,而在于转化。干燥生物质是能源密集型的,而水热液化(HTL)在250-350°C和10-20 MPa下将湿藻浆直接转化为生物原油。典型的产率范围为干重的30 - 50%,能量密度为38-41 MJ/kg,以及可循环利用的富含营养的水馏分、气体和炭。关键的障碍仍然是降低氧和氮含量,结垢反应器和降低升级成本。本文综述了将废水藻类培养与HTL相结合用于可再生燃料生产的研究,研究了废水特性、培养策略、生物质产量、HTL基础和工艺进展、产品升级以及技术经济和环境方面的问题。通过将废水修复与生物燃料生产联系起来,该综述强调了养分回收、温室气体减排和循环经济应用的机会,同时确定了为实际部署必须解决的技术差距。
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引用次数: 0
Study on mitigation strategies for heat load induced by wearing personal protective clothing in high-temperature and high-humidity environments 高温高湿环境下个人防护服热负荷缓解策略研究
IF 16.3 1区 工程技术 Q1 ENERGY & FUELS Pub Date : 2026-05-01 Epub Date: 2026-01-28 DOI: 10.1016/j.rser.2026.116761
Yan Wang , Fen Yuan , Wanxiang Yao , Guoqing Yang , Lilu Zhang , Changyuan Wang
With global warming, the impact of high-temperature and high-humidity environments on human heat load has become increasingly significant, particularly in working scenarios requiring personal protective clothing. This study aims to review heat load issues induced by protective clothing and to explore various mitigation strategies along with recent research advancements, providing a scientific foundation for relevant fields. By systematically reviewing and analyzing pertinent literature, this paper proposes a multidimensional mitigation model for protective clothing heat load and develops a comparative framework for various mitigation strategies. The research encompasses multiple aspects, including optimization of protective clothing fabrics and structural designs, the application of microclimate cooling systems, and other auxiliary mitigation measures, comprehensively addressing the characteristics of different approaches, application contexts, and diverse human thermal comfort requirements. The findings indicate that optimizing the fabrics and structural designs of protective clothing, developing efficient microclimate cooling systems, and incorporating auxiliary measures significantly enhance the internal microenvironment of protective clothing, reduce heat load, and improve thermal comfort. Nevertheless, current solutions present limitations such as high material costs, limited cooling effectiveness, and heavy equipment weight. This study provides systematic theoretical support and practical guidelines for mitigating heat load in protective clothing. Future research should concentrate on intelligent fabrics and adaptive controls, unidirectional moisture transfer technologies, and localized heat and humidity management. Such efforts will contribute to the development of more efficient, comfortable, and cost-effective protective equipment, ultimately providing superior protection for workers operating in extreme environments and thereby enhancing their work efficiency and quality of life.
随着全球变暖,高温高湿环境对人体热负荷的影响日益显著,特别是在需要个人防护服的工作场景中。本研究旨在回顾防护服引起的热负荷问题,并结合最新研究进展探讨各种缓解策略,为相关领域提供科学依据。通过系统地回顾和分析相关文献,本文提出了防护服热负荷的多维缓解模型,并开发了各种缓解策略的比较框架。研究内容涉及防护服面料和结构设计优化、微气候冷却系统应用以及其他辅助缓解措施等多个方面,综合解决不同方法的特点、应用环境和不同人体热舒适需求。研究结果表明,优化防护服面料和结构设计,开发高效的微气候冷却系统,并结合辅助措施,可显著改善防护服内部微环境,降低热负荷,提高热舒适性。然而,目前的解决方案存在一些局限性,如材料成本高,冷却效率有限,设备重量大。本研究为减轻防护服热负荷提供了系统的理论支持和实践指导。未来的研究应该集中在智能织物和自适应控制、单向水分转移技术和局部热湿度管理上。这些努力将有助于开发更高效、更舒适、更具成本效益的防护设备,最终为在极端环境下作业的工人提供更好的保护,从而提高他们的工作效率和生活质量。
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引用次数: 0
Blue energy evolution: A full-spectrum review of wave harvesting technologies for unmanned ocean vehicles 蓝色能量演变:无人驾驶海洋航行器波浪收集技术的全面回顾
IF 16.3 1区 工程技术 Q1 ENERGY & FUELS Pub Date : 2026-05-01 Epub Date: 2026-02-04 DOI: 10.1016/j.rser.2026.116782
C. Thangavel, A. Arockia Selvakumar, K. Karunamurthy
The increasing demand for sustainable and long durability power solutions of Unmanned Ocean Vehicles (UOVs) such as Autonomous Underwater Vehicles (AUVs), Remotely Operated Vehicles (ROVs), gliders, drifting buoys, and profiling floats has propelled the research into wave energy harvesting (WEH) methods. This review projects the evolution of Wave Energy Converters (WECs) from their initial mechanical designs to the latest hybrid systems that integrate various methods of energy harvesting. It assesses past milestones, current technological architectures, and upcoming innovations for oceanic autonomous platforms, highlighting design aspects such as miniaturization, hydrodynamics, durability, energy storage and adaptive control. Critical issues including variable oceanic conditions, attachment of barnacles, biofouling, corrosion, low energy density and scalability hurdles are discussed alongside mitigation strategies. Future developments point to hybrid multi source energy harvesting, AI enabled power management, bioinspired designs, and offshore micro-grid docking systems to achieve maintenance free ocean operations. This review places WEH as a transformative enabler for future generation UOVs, unlocking extended autonomy and supporting global efforts for sustainable ocean observation, resource exploration, and marine security.
自动水下航行器(auv)、遥控航行器(rov)、滑翔机、漂流浮标和剖面浮标等无人海洋航行器(UOVs)对可持续和长期耐用动力解决方案的需求日益增长,推动了波浪能收集(WEH)方法的研究。本文回顾了波浪能转换器(WECs)从最初的机械设计到集成各种能量收集方法的最新混合系统的发展历程。它评估了海洋自主平台过去的里程碑、当前的技术架构和即将到来的创新,突出了小型化、流体动力学、耐久性、能量存储和自适应控制等设计方面的问题。关键问题包括多变的海洋条件、藤壶附着、生物污垢、腐蚀、低能量密度和可扩展性障碍,以及缓解战略。未来的发展将指向混合多源能源收集、人工智能电源管理、生物设计和海上微电网对接系统,以实现免维护的海洋作业。该审查将WEH视为下一代无人驾驶飞机的变革性推动者,释放更大的自主权,并支持可持续海洋观测、资源勘探和海洋安全的全球努力。
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引用次数: 0
Review on improved neural network algorithms for battery state of energy estimation in smart grids 智能电网中电池能量状态估计的改进神经网络算法综述
IF 16.3 1区 工程技术 Q1 ENERGY & FUELS Pub Date : 2026-05-01 Epub Date: 2026-02-06 DOI: 10.1016/j.rser.2026.116797
Shunli Wang , Yu Fu , Wenxia Zhang , Carlos Fernandez , Frede Blaabjerg
Efficient and accurate state of energy (SOE) estimation is essential for the efficient operation and optimal management of smart grid energy storage systems (ESS). As lithium-ion batteries become the mainstream energy storage technology, their complex and nonlinear behavior under different operating conditions poses significant challenges for SOE estimation. This paper analyzes the promising application prospects of feedforward neural networks (FNNs), recurrent neural networks (RNNs) and their variants (long short-term memory networks (LSTMs), gated recurrent units (GRUs)), convolutional neural networks (CNNs), and hybrid models. It simultaneously explores data acquisition and preprocessing techniques, performance evaluation metrics, and practical application scenarios, identifying core challenges such as data sparsity, model interpretability, and computational efficiency. Future research directions are proposed, including advanced hybrid modeling, online adaptation, and edge computing integration. Although numerous existing reviews have validated the effectiveness of various neural network algorithms in SOE estimation, most studies focus primarily on algorithm types. Therefore, this paper systematically examines the adaptability and limitations of various algorithms. Based on a comprehensive analysis of specific smart grid scenarios with diverse requirements, this paper explores how to evaluate, select, and optimize neural network algorithms to achieve the optimal balance between estimation accuracy, efficiency, and robustness. Furthermore, through a holistic analysis of existing research, this paper bridges the gap between technical principles and practical applications, providing researchers with more targeted decision-making references.
高效、准确的能量状态估计是智能电网储能系统高效运行和优化管理的关键。随着锂离子电池成为主流储能技术,其在不同运行条件下的复杂非线性行为给SOE估算带来了重大挑战。本文分析了前馈神经网络(fnn)、递归神经网络(rnn)及其变体(长短期记忆网络(LSTMs)、门控递归单元(gru)、卷积神经网络(cnn)和混合模型的应用前景。它同时探讨了数据采集和预处理技术、性能评估指标和实际应用场景,确定了数据稀疏性、模型可解释性和计算效率等核心挑战。提出了未来的研究方向,包括高级混合建模、在线自适应和边缘计算集成。尽管已有大量文献验证了各种神经网络算法在SOE估计中的有效性,但大多数研究主要集中在算法类型上。因此,本文系统地考察了各种算法的适应性和局限性。本文在综合分析具有不同需求的智能电网具体场景的基础上,探讨了如何对神经网络算法进行评估、选择和优化,以达到估计精度、效率和鲁棒性之间的最佳平衡。此外,通过对现有研究的整体分析,弥合了技术原理与实际应用之间的差距,为研究人员提供了更有针对性的决策参考。
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引用次数: 0
A benchmark model for power system restoration studies: Review and application 电力系统恢复研究的基准模型:综述与应用
IF 16.3 1区 工程技术 Q1 ENERGY & FUELS Pub Date : 2026-05-01 Epub Date: 2026-02-13 DOI: 10.1016/j.rser.2026.116787
T. Skrjanc , L. Herman , D. Virginillo , A. Derviškadić , G. Torresan , R. Mihalic , U. Rudez
Recent widespread blackouts in Europe (e.g., the Iberian Peninsula) and worldwide (e.g., Chile) have highlighted the critical importance of robust restoration processes. Traditionally, restoration has relied on synchronous generators and predefined strategies, which have been only partially tested in practice and mainly evaluated with simulators capturing basic system dynamics. The changing grid environment raises question of how these strategies can be further improved. The increasing dominance of inverter-based resources introduces reduced inertia, new dynamic interactions, and greater uncertainty from variable renewable generation. This motivates a re-evaluation and new study of existing restoration approaches. International efforts have proposed updated restoration guidelines and explored advanced technologies such as battery energy storage systems, grid-forming inverters, and high-voltage direct current systems. Yet, despite the growing importance of managing dynamics in the delicate restoration phase, field testing remains limited. This highlights the need for a benchmark restoration model. As a first step toward such a model, this paper reviews existing restoration processes, identifies technical challenges, and develops a simulation framework including key network components typically available during restoration. The model enables scenario-based testing of both conventional and advanced strategies, supporting a better understanding of dynamic behaviour and system stability. The proposed model has been implemented for EMT and RMS simulations using both commercial tools (PowerFactory, PSCAD) and non-commercial tools under development. By providing a flexible platform, it bridges the gap between research and practice, supporting system operators, researchers, and policymakers in designing more resilient and adaptive restoration strategies for future power systems.
最近欧洲(如伊比利亚半岛)和世界范围(如智利)的大范围停电突出了强有力的恢复过程的关键重要性。传统上,恢复依赖于同步发电机和预定义的策略,这些策略仅在实践中进行了部分测试,主要是通过捕获基本系统动力学的模拟器进行评估。不断变化的网格环境提出了如何进一步改进这些策略的问题。基于逆变器的资源日益占主导地位,引入了更少的惯性,新的动态相互作用以及可变可再生能源发电的更大不确定性。这激发了对现有修复方法的重新评估和新的研究。国际上的努力已经提出了更新的恢复指南,并探索了先进的技术,如电池储能系统、并网逆变器和高压直流系统。然而,尽管在精细的恢复阶段管理动态变得越来越重要,但现场测试仍然有限。这突出了对基准恢复模型的需求。作为建立这种模型的第一步,本文回顾了现有的恢复过程,确定了技术挑战,并开发了一个模拟框架,包括恢复过程中通常可用的关键网络组件。该模型支持基于场景的常规和高级策略测试,支持更好地理解动态行为和系统稳定性。所提出的模型已经使用商业工具(PowerFactory, PSCAD)和正在开发的非商业工具实现了EMT和RMS仿真。通过提供一个灵活的平台,它弥合了研究与实践之间的差距,支持系统运营商、研究人员和政策制定者为未来的电力系统设计更具弹性和适应性的恢复策略。
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引用次数: 0
Advances and challenges in deep eutectic solvents pretreatment technologies for bioethanol production from lignocellulosic biomass: A comprehensive review 木质纤维素生物质制备生物乙醇的深度共熔溶剂预处理技术进展与挑战综述
IF 16.3 1区 工程技术 Q1 ENERGY & FUELS Pub Date : 2026-05-01 Epub Date: 2026-01-20 DOI: 10.1016/j.rser.2026.116752
Novia Novia , Asyeni Miftahul Jannah , Elda Melwita , Ahmad Fudholi , Vishnu K. Pareek
The increasing demand for sustainable, renewable energy sources is the primary driver of bioethanol production from lignocellulosic biomass (LCB). In this context, Deep Eutectic Solvents (DES) have emerged as a novel, eco-friendly alternative, offering low toxicity, biodegradability, adjustable properties, and a significant lignin solubilization capability compared to traditional pretreatment methods. Therefore, this article thoroughly reviews recent developments in DES pretreatment technologies, including design and formulation, biomass fractionation mechanisms, and impacts on enzymatic hydrolysis, including fermentation efficiency. Several choline chloride-based and natural DES types have considerably enhanced cellulose accessibility and bioethanol production. However, significant challenges persist, such as the need for economical DES synthesis, effective solvent recovery, and scalable processes for industrial applications. The interaction of these solvents with enzymes and microbial systems necessitates further investigation to optimize integrated bioprocesses. Overcoming these challenges through innovative research and process optimization would facilitate the widespread implementation of DES pretreatment. As a result, this enhanced bioethanol production's sustainability, efficiency, and economic viability.
对可持续、可再生能源日益增长的需求是木质纤维素生物质(LCB)生产生物乙醇的主要驱动力。在这种背景下,深度共熔溶剂(DES)作为一种新颖的、环保的替代方案出现了,与传统的预处理方法相比,它具有低毒、可生物降解、可调节的性能和显著的木质素增溶能力。因此,本文全面回顾了DES预处理技术的最新进展,包括设计和配方,生物质分馏机理,以及对酶水解的影响,包括发酵效率。几种氯化胆碱和天然DES类型大大提高了纤维素的可及性和生物乙醇的生产。然而,重大的挑战仍然存在,例如需要经济的DES合成,有效的溶剂回收和工业应用的可扩展工艺。这些溶剂与酶和微生物系统的相互作用需要进一步研究以优化综合生物过程。通过创新研究和工艺优化来克服这些挑战,将有助于DES预处理的广泛应用。因此,这提高了生物乙醇生产的可持续性、效率和经济可行性。
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引用次数: 0
Smart power distribution systems: A holistic review of core pillars 智能配电系统:核心支柱的整体回顾
IF 16.3 1区 工程技术 Q1 ENERGY & FUELS Pub Date : 2026-05-01 Epub Date: 2026-02-11 DOI: 10.1016/j.rser.2026.116788
Ehab El-Saadany , Moataz Mohamed , Hany Farag , Abdullah Al-Obaidi , Hatem Zeineldin
Smart Power Distribution Systems (SPDS) represent a transformative shift in the design and operation of modern distribution power networks, enabling enhanced intelligence, flexibility, and resilience. These systems integrate a wide array of technologies and components that must function in a coordinated manner to meet the growing demands for sustainability, reliability, and efficiency. This review paper presents a comprehensive analysis of five foundational pillars that define the structure and functionality of SPDS: distributed energy resources (DERs), transportation electrification, microgrids, energy management systems (EMS), and cyber-physical security. Each pillar is examined through a qualitative lens, identifying the latest technological advancements, persistent challenges, and emerging research trends. In addition to exploring each domain individually, the review emphasizes the critical interdependencies and synergies among them, which are often overlooked in existing literature. These interconnections play a pivotal role in shaping SPDS performance, interoperability, and overall grid intelligence. The paper synthesizes these insights to highlight the key enablers as well as the barriers hindering widespread SPDS deployment. Furthermore, the paper offers forward-looking perspectives and research directions necessary to address technical, regulatory, and operational gaps, paving the way for next-generation SPDS capable of supporting the global energy transition. Finally, the review aligns closely with multiple United Nations Sustainable Development Goals (SDGs), including SDGs 7, 9, 11, and 13, underscoring the vital role of SPDS in supporting the global transition toward clean, inclusive, and low-carbon energy systems.
智能配电系统(SPDS)代表了现代配电网络设计和运行的革命性转变,实现了更高的智能、灵活性和弹性。这些系统集成了广泛的技术和组件,必须以协调的方式发挥作用,以满足对可持续性、可靠性和效率日益增长的需求。这篇综述文章全面分析了定义SPDS结构和功能的五个基本支柱:分布式能源(DERs)、交通电气化、微电网、能源管理系统(EMS)和网络物理安全。每个支柱都通过定性的镜头进行检查,确定最新的技术进步,持续的挑战和新兴的研究趋势。除了单独探索每个领域之外,该综述还强调了它们之间的关键相互依赖性和协同作用,这在现有文献中经常被忽视。这些互连在塑造SPDS性能、互操作性和整体网格智能方面发挥着关键作用。本文综合了这些见解,强调了SPDS广泛部署的关键推动因素和障碍。此外,本文还提供了解决技术、监管和运营差距所需的前瞻性观点和研究方向,为能够支持全球能源转型的下一代SPDS铺平了道路。最后,该评估与包括可持续发展目标7、9、11和13在内的多个联合国可持续发展目标(sdg)密切相关,强调了可持续发展目标在支持全球向清洁、包容和低碳能源系统转型方面的重要作用。
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引用次数: 0
Reinforcement learning as a control layer for electric vehicle interaction with multi-energy systems: A comprehensive review 强化学习作为电动汽车与多能系统交互的控制层:综述
IF 16.3 1区 工程技术 Q1 ENERGY & FUELS Pub Date : 2026-05-01 Epub Date: 2026-01-23 DOI: 10.1016/j.rser.2026.116733
Anis ur Rehman
The shift toward sustainable transport and renewable energy has transformed electric vehicles (EVs) from passive loads into active components within integrated energy systems. Their interaction with batteries, charging networks, renewables, and grid services introduces complex uncertainties that conventional methods struggle to manage. In response to these complex and uncertain dynamics, reinforcement learning (RL) is emerging as a powerful adaptive control approach, and this review surveys current peer-reviewed research on its applications within the evolving energy-mobility ecosystem. It systematically examines: (i) EV powertrains and on-board energy management, (ii) hybrid energy storage systems combining batteries and supercapacitors, (iii) charging infrastructure including fast-charging hubs and battery swapping stations, (iv) vehicle-to-grid operations, (v) fleet-level scheduling and mobility services, (vi) microgrids and distributed energy systems, (vii) renewable energy integration, and (viii) resilience and stability of coupled multi-energy systems. The review identifies persistent challenges, including the reliance on simplified models, limited hardware-in-the-loop or real-vehicle validation, the computational intensity of deep RL, the sensitivity to reward design, and the safety risks in real-world deployment. To address these gaps, the review outlines future research directions including physics-informed and degradation-aware RL, hybrid RL-optimization for scalable decision-making, federated and multi-agent learning for large-scale coordination, and uncertainty-aware, explainable policies. It also proposes cross-domain reward functions to capture battery degradation and thermal dynamics, and emphasizes the urgent need for hardware validation to bridge simulation and real-world application.
向可持续交通和可再生能源的转变使电动汽车(ev)从被动负载转变为综合能源系统中的主动组件。它们与电池、充电网络、可再生能源和电网服务的相互作用引入了传统方法难以管理的复杂不确定性。为了应对这些复杂和不确定的动态,强化学习(RL)正在成为一种强大的自适应控制方法,本文综述了目前在不断发展的能量流动生态系统中对其应用的同行评审研究。它系统地检查了:(i)电动汽车动力系统和车载能源管理,(ii)结合电池和超级电容器的混合能源存储系统,(iii)充电基础设施,包括快速充电中心和电池交换站,(iv)车辆到电网的操作,(v)车队级调度和移动服务,(vi)微电网和分布式能源系统,(vii)可再生能源集成,以及(viii)耦合多能系统的弹性和稳定性。该评估指出了持续存在的挑战,包括对简化模型的依赖、有限的硬件在环或真实车辆验证、深度强化学习的计算强度、对奖励设计的敏感性以及实际部署中的安全风险。为了解决这些差距,该综述概述了未来的研究方向,包括物理信息和退化感知强化学习,可扩展决策的混合强化学习优化,大规模协调的联合和多智能体学习,以及不确定性感知,可解释的策略。它还提出了跨域奖励函数来捕捉电池退化和热动力学,并强调迫切需要硬件验证来连接仿真和实际应用。
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引用次数: 0
Diversifying power: Impact of political gender diversity on renewable energy supply chain vulnerability 权力多元化:政治性别多样性对可再生能源供应链脆弱性的影响
IF 16.3 1区 工程技术 Q1 ENERGY & FUELS Pub Date : 2026-05-01 Epub Date: 2026-01-23 DOI: 10.1016/j.rser.2026.116737
Xiaohang Ren , Ruofan Tan , Miaomiao Tao
We examine the relationship between political gender diversity and the vulnerability of renewable energy supply chains. Using a country-product panel dataset covering 61 countries from 2000 to 2023, we document several new empirical insights. First, baseline estimations reveal that greater political gender diversity significantly reduces renewable energy supply chain vulnerability, with each one-unit increase associated with an average decline of 5.8 %. Second, this effect is moderated by women's educational attainment, female labor force participation, and the level of democracy. In countries where these factors are high, inclusive gender governance exhibits a markedly stronger mitigating effect. Finally, heterogeneity analyses indicate that the positive effect of political gender diversity is concentrated in high-income economies, whereas the association turns negative in low-income countries. Notably, in countries adopting voluntary or candidate quotas, political gender diversity contributes to reducing supply chain vulnerability, with the effect being stronger under voluntary quota systems. In contrast, in countries with reserved seat quotas, political gender diversity actually increases the vulnerability of renewable energy supply chains. These results underscore the broader role of inclusive political frameworks in enhancing energy security, providing policymakers with actionable insights as they navigate the challenges of a fragmented and volatile global energy landscape.
我们研究了政治性别多样性与可再生能源供应链脆弱性之间的关系。使用涵盖2000年至2023年61个国家的国家-产品面板数据集,我们记录了一些新的实证见解。首先,基线估计显示,更大的政治性别多样性显著降低了可再生能源供应链的脆弱性,每增加一个单位,平均下降5.8%。其次,这种影响受到女性受教育程度、女性劳动力参与率和民主程度的调节。在这些因素较高的国家,包容性性别治理表现出明显更强的缓解效果。最后,异质性分析表明,政治性别多样性的积极影响主要集中在高收入经济体,而在低收入国家则变为负相关。值得注意的是,在采用自愿配额或候选人配额的国家,政治性别多样性有助于减少供应链脆弱性,在自愿配额制度下效果更强。相反,在保留席位配额的国家,政治性别多样性实际上增加了可再生能源供应链的脆弱性。这些结果强调了包容性政治框架在加强能源安全方面的更广泛作用,为政策制定者提供了可行的见解,帮助他们应对分散和不稳定的全球能源格局的挑战。
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引用次数: 0
Generic wind turbine models for power system stability assessment based on IEC 61400-27: A review 基于IEC 61400-27的电力系统稳定性评估的通用风力发电机模型:综述
IF 16.3 1区 工程技术 Q1 ENERGY & FUELS Pub Date : 2026-05-01 Epub Date: 2026-02-03 DOI: 10.1016/j.rser.2026.116740
Javier Jiménez-Ruiz , Raquel Villena-Ruiz , Andrés Honrubia-Escribano , Jens Fortmann , Emilio Gómez-Lázaro
As wind energy has become increasingly integrated into electrical systems worldwide, several international working groups—most notably the International Electrotechnical Commission and the Western Electricity Coordinating Council have significantly contributed to the development of generic wind turbine models used for dynamic grid stability simulations. These models have been the subject of extensive discussion in recent years, as they are essential for grid operators in network planning, given that detailed manufacturer models are typically unavailable or impractical for such purposes. This article presents the work carried out by the International Electrotechnical Commission in this domain, highlighting the modifications introduced during the development of these models. It also includes a detailed description of the modules that constitute the generic wind turbine models. Furthermore, this work offers deeper insights than previous studies, providing a more comprehensive and updated understanding of these models. As such, the results presented here are highly valuable for grid operators, wind turbine manufacturers, and researchers focused on the integration of wind power into power systems.
随着风能在全球范围内越来越多地集成到电力系统中,几个国际工作组——最著名的是国际电工委员会和西方电力协调委员会——为用于动态电网稳定性模拟的通用风力涡轮机模型的开发做出了重大贡献。这些模型近年来一直是广泛讨论的主题,因为它们对于电网运营商进行网络规划至关重要,因为详细的制造商模型通常无法获得或不切实际。本文介绍了国际电工委员会在该领域开展的工作,重点介绍了这些模型开发过程中引入的修改。它还包括构成通用风力涡轮机模型的模块的详细描述。此外,这项工作比以往的研究提供了更深入的见解,提供了对这些模型更全面和更新的理解。因此,本文提出的结果对电网运营商、风力涡轮机制造商和专注于将风力发电整合到电力系统中的研究人员具有很高的价值。
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Renewable and Sustainable Energy Reviews
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