Next Energy最新文献_第7页

Perovskite solar cells: Efficiency and stability enhancement using covalent organic frameworks 钙钛矿太阳能电池：使用共价有机框架提高效率和稳定性

Next Energy

Pub Date : 2025-10-01 DOI: 10.1016/j.nxener.2025.100451

Reza Feizi , Fatemeh Razi Astaraei , Mohammad Sameti

Perovskite solar cells (PSCs) represent a significant advancement in photovoltaic technology, attracting considerable attention owing to their outstanding power conversion efficiency (PCE). However, their path to widespread commercialization is hindered by challenges such as low stability and the rapid degradation of the perovskite active layer. To address these issues, covalent organic frameworks (COFs) have emerged as an innovative class of materials known for their low density, high porosity, and good stability, rendering them suitable for integration into PSCs. In these solar cells, COFs enhance the crystalline quality of the perovskite layer, align energy levels, and reduce recombination losses, thereby improving both efficiency and stability. This review begins with a bibliometric analysis, examining notable keywords, pioneer countries, and publication growth. It then explores the impact of COFs integrated into key components and interfaces of PSCs, including the perovskite active layer, the hole and electron transport layers (HTL/ETL), and their critical interfaces. The focus is on improvements in structural integrity, PCE gains, and stability enhancements. Additionally, the review elucidates processes behind these beneficial effects and offers insights into how COFs can effectively address current limitations faced by PSCs.

钙钛矿太阳能电池（PSCs）由于其优异的功率转换效率（PCE）而受到广泛关注，是光伏技术的一大进步。然而，钙钛矿活性层的低稳定性和快速降解等挑战阻碍了它们广泛商业化的道路。为了解决这些问题，共价有机框架（COFs）已经成为一类创新的材料，以其低密度、高孔隙率和良好的稳定性而闻名，使其适合集成到psc中。在这些太阳能电池中，COFs提高了钙钛矿层的结晶质量，排列了能级，减少了复合损失，从而提高了效率和稳定性。本综述从文献计量分析开始，考察了著名的关键词、先驱国家和出版物增长。然后探讨了COFs集成到psc的关键组件和界面中的影响，包括钙钛矿活性层、空穴和电子传输层（html /ETL）及其关键界面。重点是改进结构完整性、PCE增益和稳定性增强。此外，该综述阐明了这些有益影响背后的过程，并提供了COFs如何有效解决PSCs当前面临的限制的见解。

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引用次数: 0

Review on hydrogen fuel cells as an alternative fuel 氢燃料电池作为替代燃料的研究进展

Next Energy

Pub Date : 2025-10-01 DOI: 10.1016/j.nxener.2025.100460

Heth Sethia, Abhishek Priyam

The use of hydrogen fuel cells has greatly increased in recent years. Advanced fuel cells are efficiently addressing the needs of portable power, backup power, and even modular power fuel cells. It has also been used to power cars and other vehicles. Hydrogen fuel cells are now specialized under the name portable power modules to highlight their newly discovered vehicle-mountable outboard engines. This review also targets the other issues of handling and encasing hydrogen fuel in specialized containers. All these gaps that revolve around the modern world are intertwined with one advancing vehicle engine to fix the ever-increasing global warming levels. Challenges faced by cost, storage, and infrastructure barriers are addressed, in addition to technological advancements in catalyst effectiveness, membrane technology, and hydrogen supply logistics. The report ends with a visionary outlook, outlining research avenues to drive the shift to a hydrogen economy.

近年来，氢燃料电池的使用大大增加。先进的燃料电池正在有效地解决便携式电源，备用电源，甚至模块化动力燃料电池的需求。它也被用来为汽车和其他车辆提供动力。氢燃料电池现在被专门命名为便携式电源模块，以突出其新发现的可安装在车辆上的舷外发动机。本次审查还针对其他问题的处理和包装氢燃料在专门的容器。所有这些围绕现代世界的差距都与一个先进的汽车发动机交织在一起，以解决不断增加的全球变暖水平。除了催化剂有效性、膜技术和氢供应物流方面的技术进步外，还解决了成本、存储和基础设施障碍等方面面临的挑战。该报告以一个富有远见的展望结束，概述了推动向氢经济转变的研究途径。

引用次数: 0

Advancing MoOx and NiOx as hole transport layers for perovskite solar cells: Experimental and theoretical insights 推进MoOx和NiOx作为钙钛矿太阳能电池的空穴传输层：实验和理论见解

Next Energy

Pub Date : 2025-10-01 DOI: 10.1016/j.nxener.2025.100463

Mohammad Istiaque Hossain , Puvaneswaran Chelvanathan , Amith Khandakar , Kevin Thomas , Brahim Aissa

We have developed crystalline thin metal oxide films (MoOx, NiOx) as hole transport layers with varying stoichiometries for perovskite solar cells applications. Reactive e-beam evaporation was employed to grow the oxides by vaporizing pure metals at different oxygen pressures, followed by thermal annealing at 200 °C. Scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy, contact angle measurements, X-ray diffraction (XRD), and variable angle spectroscopic ellipsometry were used to analyze the grown films. The XRD findings confirm the presence of crystalline phases in the NiO_x thin films when processed at 200 °C, particularly in the most oxygen-rich films (deposited at 2e-4 Torr). In contrast, the MoOx layers exhibit an amorphous phase. Field emission SEM results confirm the production of dense and homogeneous films across the substrate's surface, free from cracks and pinholes. A numerical model utilizing the measured refractive indices suggests that optimizing the device design with these thin films can achieve power conversion efficiencies of over 25%.

我们已经开发出晶体薄金属氧化物薄膜（MoOx, NiOx）作为钙钛矿太阳能电池应用中具有不同化学计量的空穴传输层。采用反应电子束蒸发法，在不同氧压下对纯金属进行汽化，然后在200℃下进行热退火。利用扫描电子显微镜（SEM）、能量色散x射线能谱、接触角测量、x射线衍射（XRD）和变角椭偏光谱对生长膜进行了分析。XRD结果证实，在200°C下处理的NiOx薄膜中存在结晶相，特别是在大多数富氧薄膜中（沉积在2e-4 Torr）。相比之下，MoOx层表现为非晶相。场发射扫描电镜结果证实，在衬底表面产生了致密且均匀的薄膜，没有裂纹和针孔。利用测量的折射率进行的数值模型表明，利用这些薄膜优化器件设计可以实现超过25%的功率转换效率。

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引用次数: 0

Data-driven regression controller-based MPPT with image encryption inspired solar PV array reconfiguration under partial shading conditions 部分遮阳条件下基于数据驱动回归控制器的MPPT图像加密启发太阳能光伏阵列重构

Next Energy

Pub Date : 2025-10-01 DOI: 10.1016/j.nxener.2025.100438

Madavena Kumaraswamy, Kanasottu Anil Naik

Partial shading and environmental variations significantly reduce the power output and efficiency of photovoltaic (PV) systems, posing challenges for conventional maximum power point tracking (MPPT) methods that suffer from slow convergence, local maxima trapping, and high computational cost. To address these limitations, this paper proposes an image encryption-inspired PV array static reconfiguration technique based on the Kolakoski sequence transform (KST), combined with data-driven regression-based MPPT controllers. The proposed KST method minimizes current mismatches by intelligently redistributing shaded modules, while decision tree (DT), support vector machine (SVM), neural network (NN), and machine learning (ML) regression methods are employed to determine the optimal duty cycle for a SEPIC converter under varying irradiance conditions. The system is evaluated on both symmetrical 5 × 5 arrays and unsymmetrical 4 × 6 arrays, including experimental validation using a 250 Wp standalone PV setup. In MPPT performance, the regression-based controllers attain GMP enhancements of 47.09%, 45.14%, 27.27%, 13.62%, and 10.73% for 5 × 5 arrays and 74.96%, 44.11%, 40.14%, 18.29%, and 7.15% for 4 × 6 arrays under diverse environmental conditions. The reconfiguration technique achieves global maximum power (GMP) improvements of 32.79%, 14.98%, and 10.15% across various shading scenarios using 9 × 9 arrays. Notably, the proposed KST integrated with SVM regression-based MPPT delivers up to 68% GMPP enhancement, with >98.5% efficiency, convergence <0.35 s, and ripple ≤1.5%, validated across dynamic shading, temperature variation, rapid irradiance changes, and hotspot conditions. These results confirm the robustness, adaptability, and real-time suitability of the proposed KST integrated with ML-based Regression MPPT approach for practical PV optimization.

部分遮阳和环境变化显著降低了光伏（PV）系统的输出功率和效率，对传统的最大功率点跟踪（MPPT）方法提出了挑战，这些方法存在收敛速度慢、局部最大值捕获和计算成本高的问题。为了解决这些限制，本文提出了一种基于Kolakoski序列变换（KST）的基于图像加密的光伏阵列静态重构技术，并结合基于数据驱动回归的MPPT控制器。提出的KST方法通过智能地重新分配阴影模块来最小化当前的不匹配，而决策树（DT）、支持向量机（SVM）、神经网络（NN）和机器学习（ML）回归方法用于确定不同辐照条件下SEPIC转换器的最佳占空比。系统在对称5 × 5阵列和非对称4 × 6阵列上进行了评估，包括使用250 Wp独立PV装置进行实验验证。在MPPT性能方面，基于回归的控制器在不同环境条件下对5个 × 5阵列的GMP增强率分别为47.09%、45.14%、27.27%、13.62%和10.73%，对4个 × 6阵列的GMP增强率分别为74.96%、44.11%、40.14%、18.29%和7.15%。重新配置技术在使用9 × 9阵列的各种遮光场景下实现了32.79%，14.98%和10.15%的全局最大功率（GMP）改进。值得注意的是，所提出的KST与基于SVM回归的MPPT相结合，提供了高达68%的GMPP增强，效率>；98.5%，收敛<；0.35 s，纹波≤1.5%，在动态遮阳，温度变化，快速光照变化和热点条件下都得到了验证。这些结果证实了所提出的KST与基于ml的回归MPPT方法集成在实际PV优化中的鲁棒性、适应性和实时性。

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引用次数: 0

Enhanced thermal management and energy efficiency in electronic processor cooling using MWCNT-LA NEPCM heat sink with U-tube heat pipes 采用u型管热管的MWCNT-LA NEPCM散热器，提高了电子处理器冷却的热管理和能源效率

Next Energy

Pub Date : 2025-10-01 DOI: 10.1016/j.nxener.2025.100440

S. Kalaiselvam , A. Lakshmi Kanthan Bharathi , A. Ameelia Roseline

This study investigates the efficiency of a multi-walled carbon nanotube-infused lauric acid (MWCNT-LA) heatsink with U-tube heat pipes filled with n-pentane for electronic processor cooling. Experimental evaluations were conducted under varying heat loads and filling ratios to assess processor stability and energy efficiency. The investigation focused on energy savings, the thermal resistance of different heat pipe-assisted heatsink modules with multi-walled carbon nanotube-infused lauric acid phase change material, with its regeneration time, and optimal heat pipe filling ratio. Results showed that the MWCNT-LA heat sink module with 50% n-pentane filling performed best under higher heat loads, achieving the lowest thermal resistance of 0.63 °C/W at 50% filling ratio and 75% heat load. This design was 3.58 times more effective than the unfilled heat pipe version and achieved 78% energy savings with minimal cooling fan energy consumption. The developed heat sink design improves thermal management by utilizing latent heat storage and enhancing heat transport efficiency through the heat pipe, thus optimizing thermal performance, heat dissipation, and temperature regulation. These improvements increased the operational reliability and energy efficiency of processors in data center cooling applications.

本研究研究了一种多壁碳纳米管注入月桂酸（MWCNT-LA）散热器的效率，该散热器采用u型管热管填充正戊烷，用于电子处理器的冷却。在不同的热负荷和填充率下进行了实验评估，以评估处理器的稳定性和能效。研究了多壁碳纳米管注入月桂酸相变材料的不同热管辅助散热器模块的节能性能、热阻、再生时间和最佳热管填充比。结果表明，正戊烷填充率为50%的MWCNT-LA散热器模块在高热负荷下表现最佳，在填充率为50%、热负荷为75%时热阻最低，为0.63°C/W。这种设计的效率是未填充热管版本的3.58倍，以最小的冷却风扇能耗实现了78%的节能。开发的散热器设计通过利用潜热储存和提高热管传热效率来改善热管理，从而优化热性能，散热和温度调节。这些改进提高了数据中心冷却应用中处理器的运行可靠性和能源效率。

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引用次数: 0

Operational and environmental impacts on battery lifetime and vehicle performance: A case study for electric taxis 操作和环境对电池寿命和车辆性能的影响：电动出租车的案例研究

Next Energy

Pub Date : 2025-10-01 DOI: 10.1016/j.nxener.2025.100441

Zisis Lampropoulos , Spyridon Spyridopoulos , Traianos Karageorgiou , Grigorios Koltsakis

The gradual electrification of the road transport sector has raised a lot of concerns about the reliability of battery electric vehicles (BEVs). Many potential customers not only lack awareness about the benefits of electrification, total costs and charging infrastructure, but are especially worried about battery lifetime and vehicle performance, information which manufacturers often struggle to provide accurately. This work proposes a methodology to predict BEV lifetime based on complete vehicle simulation employing a physics-based, electrochemical-thermal-aging battery model. In addition, the model calculates the performance degradation over time in terms of energy consumption, range, battery charging efficiency and vehicle acceleration. Physics-based models are harder to develop and computationally costlier than data-driven models. However, once developed, they can be used in a much broader range of conditions and, more importantly, be applied also when no adequate on-road data are yet available. The proposed methodology is applied in a case study of BEV taxis in the city of Thessaloniki, Greece. In particular, the impact of battery preheating prior to charging is evaluated by simulation, showing that preheating could increase lifetime and mileage of BEV taxis by 14% in South European climates. In another application, it is calculated that mid-shift fast-charging could even double the life of the battery compared to fast-charging only before shift change, leading simultaneously to improved performance when compared within the same operational period. Such results could support battery and vehicle manufacturers as well as fleet managers to guide BEV taxi owners towards optimal charging behavior. The modeling approach presented in this paper can be further extended to other vehicle groups, environmental, driving and charging conditions, making it a powerful tool not only for manufacturers, but also for policymakers and charging infrastructure companies.

道路运输行业的逐步电气化引发了人们对纯电动汽车（bev）可靠性的担忧。许多潜在客户不仅对电气化的好处、总成本和充电基础设施缺乏认识，而且尤其担心电池寿命和车辆性能，而制造商往往难以准确提供这些信息。本研究提出了一种基于整车仿真的方法，该方法采用基于物理的电化学-热老化电池模型来预测纯电动汽车的寿命。此外，该模型还从能耗、续航里程、电池充电效率和车辆加速等方面计算了车辆性能随时间的退化情况。基于物理的模型比数据驱动的模型更难开发，计算成本也更高。然而，一旦开发出来，它们可以在更广泛的条件下使用，更重要的是，在没有足够的道路数据时也可以应用。所提出的方法应用于希腊塞萨洛尼基市纯电动出租车的案例研究。特别是，通过模拟评估了充电前电池预热的影响，结果表明，在南欧气候条件下，预热可以使纯电动出租车的使用寿命和行驶里程增加14%。在另一项应用中，计算出换挡中期快速充电比换挡前快速充电甚至可以使电池的寿命增加一倍，同时在相同的运行周期内，性能也有所提高。这些结果可以帮助电池和汽车制造商以及车队管理者指导纯电动出租车车主采取最佳充电行为。本文提出的建模方法可以进一步扩展到其他车辆组、环境、驾驶和充电条件，使其不仅对制造商，而且对政策制定者和充电基础设施公司都是一个强大的工具。

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引用次数: 0

Semi-empirical calendar capacity degradation modeling of graphite/lithium iron phosphate (LFP) pouch cells: Non-constant fitting coefficient functions 石墨/磷酸铁锂（LFP）袋状电池半经验日历容量退化模型：非常数拟合系数函数

Next Energy

Pub Date : 2025-10-01 DOI: 10.1016/j.nxener.2025.100456

Yu Hui Lui , Xinyou Ke , Sheng Liu , Lei Zhang , Yong Wang , Huanhuan Wang

To accurately and efficiently predict the lifetime of Li-ion batteries for their practical applications in battery electric vehicles, hybrid electric vehicles, plug-in hybrid electric vehicles, energy storage systems, etc., accurate semiempirical life models are desired for battery lifetime simulation. In this work, semiempirical calendar aging models considering nonconstant fitting coefficient functions based on storage aging tests for 20 Ah graphite/lithium iron phosphate pouch cells under various temperatures ranging from 0℃ to 60℃ and state-of-charges ranging from 20% to 100% were developed. It was found that the “best” calendar capacity life model with non-constant fitting coefficient functions compared with the common calendar capacity life model with constant fitting coefficients reduces the mean absolute error and root mean square error of the calendar capacity fitting by 7.4% and 6.6%, respectively. Moreover, the “best” calendar capacity life model proposed in this work outperforms 2 existing reference models reported in the literature, especially at high temperatures, that is, 40℃ and 60℃. It is expected that this work would benefit accurate and efficient calendar capacity prediction of Li-ion batteries.

为了准确有效地预测锂离子电池在纯电动汽车、混合动力汽车、插电式混合动力汽车、储能系统等实际应用中的寿命，需要精确的半经验寿命模型进行电池寿命仿真。本文建立了20个 Ah石墨/磷酸铁锂袋状电池在0℃~ 60℃、20% ~ 100%荷电状态下，考虑非常数拟合系数函数的半经验日历老化模型。结果表明，采用非常数拟合系数的“最佳”日历产能寿命模型与采用常数拟合系数的普通日历产能寿命模型相比，日历产能拟合的平均绝对误差和均方根误差分别降低了7.4%和6.6%。此外，本文提出的“最佳”日历容量寿命模型优于文献报道的2个现有参考模型，特别是在高温下，即40℃和60℃。期望这项工作将有利于锂离子电池准确、高效的日历容量预测。

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引用次数: 0

Gliding arc plasma dry reforming of n-dodecane for H2 production: A mechanism study combined with experimental methods and kinetic modeling 滑行电弧等离子体干重整制氢：实验方法与动力学建模相结合的机理研究

Next Energy

Pub Date : 2025-10-01 DOI: 10.1016/j.nxener.2025.100449

Baowei Wang, Weiyue Huo, Yi Cheng, Shize Liu, Jijun Zou

Dry reforming technology is promising because it can simultaneously produce syngas (H₂ and CO) and efficiently convert the greenhouse gas CO₂. This study investigated the dry reforming (DR) of n-dodecane in a gliding arc plasma (GAP) reactor through integrated experimental and kinetic simulation approaches. Key operating parameters—O/C molar ratio, input power, and residence time—were evaluated for their influence on syngas production and reactant conversion. Optical emission spectroscopy (OES) identified active species, with spectral line intensities analyzed across varying O/C ratios. A validated zero-dimensional kinetic model, aligned with experimental data, revealed that H₂ generation during C₁₂H₂₆ conversion is predominantly driven by recombination of n-dodecane with H atoms. H₂ production primarily arises from hydrocarbon electron impact reactions (e.g., C₂H₆, C₂H₄) and H atom recombination with species such as C₃H₆, CH₄, and C₃H₈. Detailed reaction pathways and mechanisms in the dry reforming system are elucidated through integrated experimental and kinetic modeling analyses. The n-dodecane conversion follows the following order: X(DR) > X(SR) > X(POR).

干式重整技术可以同时生产合成气（H2和CO）并有效地转化温室气体CO2，因此具有广阔的应用前景。采用实验和动力学模拟相结合的方法研究了正十二烷在滑动电弧等离子体反应器中的干重整过程。考察了关键操作参数o /C摩尔比、输入功率和停留时间对合成气产量和反应物转化率的影响。光学发射光谱（OES）鉴定了活性物种，并分析了不同O/C比率下的光谱线强度。验证的零维动力学模型与实验数据一致，表明C12H26转化过程中H2的生成主要是由正十二烷与H原子的重组驱动的。H₂的产生主要来自碳氢化合物的电子冲击反应（例如，C₂H₆，C₂H₄）和H原子与C₃H₆，CH₄和C₃H₈等品种的复合。通过实验和动力学模型的综合分析，详细阐述了干式重整体系的反应途径和机理。正十二烷的转化顺序为：X(DR) >； X(SR) >； X（POR）。

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引用次数: 0

Evaluating the hydrogen supply chain so far—An assessment and review of critical aspects for an economy supported by a “hydrogen infrastructure” 对“氢基础设施”支持的经济的关键方面进行评估和回顾

Next Energy

Pub Date : 2025-10-01 DOI: 10.1016/j.nxener.2025.100448

Julien Göthel , Andreas Corsten , Olena Volkova

This paper critically evaluates hydrogen's role as a decarbonization strategy, addressing key technical and economic constraints that challenge its widespread adoption. We analyze inherent energy conversion losses that make hydrogen-based systems less efficient than direct electrification for many applications, along with persistent issues in scalable storage, distribution, and production costs. The analysis highlights the specific limitations of the 2 primary production pathways: green hydrogen, constrained by the high cost of electrolyzers and the sourcing of critical materials, and blue hydrogen, which faces concerns regarding methane leakage and the long-term viability of carbon capture technologies. We argue that hydrogen's most effective application is as a strategic enabler for hard-to-abate sectors, such as heavy industry and long-distance transport. The paper also explores innovative concepts like thermochemical looping with metal oxides and the integration of hydrogen into a circular carbon economy as pathways to enhance its efficiency and economic viability. Ultimately, the transition to a global hydrogen economy is a complex, multi-decade undertaking that necessitates a pragmatic, targeted approach with substantial investment and coordinated international policy to realize its full potential.

本文批判性地评估了氢作为脱碳战略的作用，解决了挑战其广泛采用的关键技术和经济限制。我们分析了固有的能量转换损失，这使得氢基系统在许多应用中比直接电气化效率低，以及可扩展存储、分配和生产成本方面的持续问题。该分析强调了两种主要生产途径的具体局限性：绿色氢，受到电解槽和关键材料采购的高成本的限制；蓝色氢，面临甲烷泄漏和碳捕获技术长期可行性的担忧。我们认为，氢最有效的应用是作为难以减少的行业（如重工业和长途运输）的战略推动者。本文还探讨了一些创新概念，如金属氧化物热化学环，以及将氢整合到循环碳经济中，作为提高其效率和经济可行性的途径。最终，向全球氢经济过渡是一项复杂的、长达数十年的任务，需要采取务实、有针对性的方法，进行大量投资和协调一致的国际政策，以充分发挥其潜力。

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引用次数: 0

Energizing tomorrow: A scientometric exploration into energy storage integration in hybrid power systems 激励明天：混合动力系统储能集成的科学计量学探索

Next Energy

Pub Date : 2025-10-01 DOI: 10.1016/j.nxener.2025.100450

Alpesh Kumar Dauda, Ambarish Panda

In promoting the decarbonization of power systems, integrating cleaner energy sources is essential. However, the intermittent nature of renewable energy (wind and solar) presents challenges for seamless grid integration. This issue can be mitigated by strategically deploying electrical energy storage (EES) systems in hybrid power systems (HPS), which combine conventional and renewable generators. While prior studies have focused on specific aspects like modeling, sizing, and economic analysis, a comprehensive review of EES integration and operational challenges in HPS is still lacking. This study offers an in-depth overview of recent advancements in EES integration into HPS, highlighting key objectives, operational concerns, and solution methodologies. It explores issues related to small-scale energy storage technologies such as batteries, supercapacitors, superconducting magnetic energy storage (SMES), flywheels, hydrogen fuel cells, and hybrid energy storage systems (ESSs) in HPS. A scientometric analysis based on 250 Scopus-indexed articles is conducted, including co-authorship, citation, and keyword co-occurrence analysis. Key findings include (1) A 510% growth in publications during the last decade (over 120 articles in 2020–2023), reflecting accelerating global attention. (2) China (11%), Iran (11%), and India (9%) contribute most of the journal articles, while Germany achieves the highest average citation impact (229.5 citations per paper) and (3) identification of “SMES” and “flywheels” as underexplored areas, suggesting potential research gaps in the domain of EES-integrated HPS.

为了促进电力系统的脱碳，整合清洁能源是必不可少的。然而，可再生能源（风能和太阳能）的间歇性给无缝电网整合带来了挑战。这个问题可以通过在混合动力系统（HPS）中战略性地部署电能存储（EES）系统来缓解，混合动力系统结合了传统和可再生发电机。虽然之前的研究主要集中在建模、规模和经济分析等具体方面，但对HPS中EES集成和运营挑战的全面审查仍然缺乏。本研究深入概述了EES与HPS集成的最新进展，突出了关键目标、操作关注点和解决方案方法。它探讨了与小型储能技术相关的问题，如电池、超级电容器、超导磁储能（sme）、飞轮、氢燃料电池和HPS中的混合储能系统（ess）。基于250篇scopus索引文章进行了科学计量分析，包括共同作者、引文和关键词共现分析。主要发现包括：(1)在过去十年中，出版物增长了510%（2020-2023年超过120篇），反映了全球关注的加速。(2)中国（11%）、伊朗（11%）和印度（9%）贡献了最多的期刊论文，而德国的平均引用影响最高（229.5次/篇）；(3)“中小企业”和“飞轮”被认为是研究不足的领域，表明ees集成HPS领域存在潜在的研究空白。

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引用次数: 0