Renewable Energy最新文献_第2页

Mitigating pump-turbine hump instabilities via high-pressure edge optimization: Vortex dynamics and pressure fluctuation control 高压边缘优化缓解泵轮机驼峰不稳定性：涡动力学和压力波动控制

IF 9.1 1区工程技术 Q1 ENERGY & FUELS

Renewable Energy

Pub Date : 2025-12-18 DOI: 10.1016/j.renene.2025.125075

Xitong Wu , Chenhao Li , Yang Hu , Xingqi Luo , Jianjun Feng , Guojun Zhu

To assess the influence of various high-pressure edge shapes on hydraulic performance and instability features in a pump-turbine under pumping conditions, three designs—concave, slanted, and convex—were analyzed using the SST k-ω turbulence model. Results revealed flow separation near the guide vane inlet and backflow near the runner outlet under low-flow hump conditions. Different schemes result in varying forms of outlet flow angles, which in turn generate vortices of different intensities in the guide vanes, leading to differences in hump characteristics. Notably, under small flow rates (0.63Q_BEP – 0.69Q_BEP), the convex design excelled, enhancing head and efficiency, boosting hump safety margins, reducing outlet flow angles, and optimizing loss distribution to mitigate excessive hydraulic losses in the hump zone. An evaluation of pressure fluctuations across the flow passage showed that, excluding the vaneless region, slanted and convex designs markedly decreased characteristic frequency amplitudes compared to the concave design. In the vaneless region, these designs also reduced and more evenly distributed amplitudes of mixed-frequency and characteristic frequency. Specifically, guide vane passage pressure fluctuations decreased by 14.6 % and 5.3 % for slanted and convex designs, respectively. These findings offer valuable insights for predicting hump characteristics and optimizing designs.

为了评估不同高压边缘形状对抽水工况下水泵水轮机水力性能和不稳定性特征的影响，采用SST k-ω湍流模型分析了凹型、斜型和凸型三种设计。结果表明，在低流量驼峰条件下，导叶入口附近存在流动分离，流道出口附近存在回流。不同的方案导致不同形式的出口气流角，从而在导叶中产生不同强度的涡，从而导致驼峰特性的差异。值得注意的是，在小流量（0.63QBEP - 0.69QBEP）下，凸面设计表现出色，提高了水头和效率，提高了驼峰安全边际，减小了出口气流角，并优化了损失分配，以减轻驼峰区过大的水力损失。对整个流道压力波动的评估表明，除了无叶区域，倾斜和凸设计与凹设计相比显著降低了特征频率幅值。在无叶区，这些设计还降低了混合频率和特征频率的幅度，并且分布更均匀。具体来说，倾斜设计和凸设计的导叶通道压力波动分别减少了14.6%和5.3%。这些发现为预测驼峰特性和优化设计提供了有价值的见解。

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引用次数: 0

Self-catalyzed in situ transesterification of Mucor circinelloides lipids from waste cooking oil for sustainable biodiesel production 废食用油中环状毛霉脂质的自催化原位酯交换研究

IF 9.1 1区工程技术 Q1 ENERGY & FUELS

Renewable Energy

Pub Date : 2025-12-18 DOI: 10.1016/j.renene.2025.125088

Shulan Ji , Haoran Hu , Yu Zhang , Xun Li , Fei Wang

To address the economic and environmental limitations of conventional biodiesel production, this study developed an integrated, self-catalyzed process using the oleaginous fungus Mucor circinelloides. The methanol-tolerant mutant JLW5, generated through atmospheric and room-temperature plasma (ARTP) mutagenesis, was cultivated on waste cooking oil and optimized for lipid accumulation, enabling endogenous-lipase-mediated (“self-catalyzed”) in situ transesterification. Under optimized culture conditions, JLW5 cultivated on 30 g/L waste cooking oil and 70 g/L bacterial peptone achieved 75 ± 1.6 % lipid content (dry cell weight) and 334 ± 16 U/g lipase activity after 60 h. The lipid profile was dominated by high proportions of saturated and monounsaturated fatty acids, which are suitable for biodiesel production. Biodiesel was directly produced from dried biomass via self-catalyzed in situ transesterification in a solvent- and catalyst-free system. Optimal reaction conditions included ultrasonic pretreatment for 40 min, a methanol-to-oil ratio of 4:1, and 40 % water content at 40 °C, resulting in an 85 ± 1.2 % FAME yield. This integrated strategy eliminates lipid extraction and chemical catalysts, simplifies downstream processing, and provides an economically viable and environmentally friendly route for converting waste cooking oil into biodiesel.

为了解决传统生物柴油生产的经济和环境限制，本研究利用产油真菌毛霉开发了一种集成的、自催化的工艺。通过大气和室温等离子体（ARTP）诱变产生的耐甲醇突变体JLW5在废食用油上培养，并优化其脂质积累能力，实现内源性脂酶介导（“自催化”）原位酯交换。在优化的培养条件下，JLW5在30 g/L废食用油和70 g/L细菌蛋白胨培养基上培养60 h后，脂质含量（干细胞重）为75±1.6%，脂肪酶活性为334±16 U/g，脂质结构以高比例的饱和脂肪酸和单不饱和脂肪酸为主，适合生产生物柴油。在无溶剂和无催化剂的体系中，通过自催化原位酯交换反应直接从干燥的生物质中生产生物柴油。最佳反应条件为超声预处理40 min，醇油比为4:1,40°C条件下，水含量为40%，FAME收率为85±1.2%。这一综合策略消除了脂质提取和化学催化剂，简化了下游加工，为将废食用油转化为生物柴油提供了一条经济可行且环保的途径。

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引用次数: 0

Revisiting the synergistic governance efficiency of industrial pollution and carbon emissions reduction from the perspective of eight comprehensive economic regions in China 中国八大综合经济区视角下工业污染与碳减排协同治理效率研究

IF 9.1 1区工程技术 Q1 ENERGY & FUELS

Renewable Energy

Pub Date : 2025-12-17 DOI: 10.1016/j.renene.2025.125041

Sha Sun , Mingming Zhang , Ying Lu , Xiaosong Ren

Promoting synergistic governance efficiency of industrial pollution and carbon emissions reduction (SGEIPCER) is imperative for achieving industrial green transformation. Based on the industrial input-output data, this study employs the super-efficiency SBM and GML index to reveal the temporal evolution trend of SGEIPCER in China. Meanwhile, spatial differences and convergence are analyzed from the perspective of eight comprehensive economic regions. The results show that the SGEIPCER increases significantly at the national level, with an average annual growth rate of 3.30 %. However, it has remained below 0.4, suggesting notable efficiency loss. Except for Northeast China (NEC) and Northwest China (NWC), the SGEIPCER in other regions shows a fluctuating growth trend during 2011–2023, driven primarily by technological efficiency. Although NWC has a negative annual growth rate (−11.20 %), it has the highest average efficiency at 0.392, approximately 1.5 times that of the second-ranked middle region of the Yellow River. The average overall Gini coefficient is 0.469, revealing significant spatial regional differences. Cross-regional differences and the intensity of trans variation (i.e., the contribution from overlaps in the SGEIPCER distributions between regions) emerge as the primary sources of spatial variation, with average contribution rates of 43.65 % and 44.50 %, respectively. Further, σ convergence is observed in the NEC, NWC, Eastern Coastal Area (ECA), and Southern Coastal Area. All regions except ECA exhibit significant β convergence. However, the middle region of the Yangtze River shows the strongest spatial β convergence. Under the combined influence of external factors, the convergence speed has significantly accelerated, from 5.8 % to 6.4 %.

提升工业污染与碳减排协同治理效率是实现工业绿色转型的必然要求。本研究基于工业投入产出数据，采用超效率SBM和GML指数揭示中国SGEIPCER的时间演化趋势。同时，从八个综合经济区的角度分析了空间差异与趋同。结果表明：在国家层面上，SGEIPCER增长显著，年均增长率为3.30%；然而，它仍然低于0.4，表明明显的效率损失。2011-2023年，除东北地区和西北地区外，其他地区SGEIPCER均呈现波动增长趋势，主要受技术效率驱动。虽然NWC的年增长率为负（- 11.20%），但其平均效率最高，为0.392，约为排名第二的黄河中游地区的1.5倍。总体基尼系数平均值为0.469，空间区域差异显著。跨区域差异和跨区域变异强度（即区域间SGEIPCER分布重叠的贡献）是空间变异的主要来源，平均贡献率分别为43.65%和44.50%。此外，东北、西北、东部沿海和南部沿海地区的σ辐合现象明显。除ECA外，所有区域均表现出显著的β收敛性。而长江中游区域β空间收敛性最强。在外部因素的综合影响下，收敛速度明显加快，从5.8%提高到6.4%。

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引用次数: 0

Coordinated scheduling strategy for coastal industrial park microgrids and distribution network with water-cycling-based green hydrogen system 基于水循环绿色氢系统的沿海工业园区微电网与配电网协调调度策略

IF 9.1 1区工程技术 Q1 ENERGY & FUELS

Renewable Energy

Pub Date : 2025-12-17 DOI: 10.1016/j.renene.2025.125051

Haiteng Han, Zhihao Ya, Simin Zhang, Yizhen Huang, Chuanshen Wu, Sheng Chen, Zhinong Wei

With the ongoing global energy transition, hydrogen is increasingly recognized as a key vector for building a clean and low-carbon energy system. However, the development of hydrogen energy in urban energy systems still face critical challenges, including water scarcity and insufficient integration into local energy system. To address these challenges, this study proposes a coordinated scheduling strategy for coastal industrial park microgrids (CIPM) and the distribution network (DN), incorporating water-cycling-based green hydrogen production system. First, a closed-loop green hydrogen production system is developed for CIPM, integrating reverse osmosis (RO) desalination, water electrolyzer, and fuel cell, while accounting for the dynamic efficiency of desalination. Second, a multi-energy synergistic operation mechanism is further established among water, hydrogen, electricity, and heat flows within the microgrid. At the urban level, a collaborative optimization framework is built, enabling energy exchange among multiple microgrids coordinated by the DN. Finally, a hybrid solution algorithm is designed by combining generalized Bregman Alternating Direction Method of Multiplier (ADMM) with a progressive binary relaxation strategy. Simulation results verify that the proposed approach significantly reduces dependency on external freshwater resources and provides practical insights into the sustainable development of hydrogen-integrated urban energy systems.

随着全球能源转型的持续进行，氢越来越被认为是建设清洁低碳能源系统的关键载体。然而，氢能在城市能源系统中的发展仍然面临着严峻的挑战，包括水资源短缺和与当地能源系统的整合不足。为了解决这些挑战，本研究提出了沿海工业园区微电网（CIPM）和配电网（DN）的协调调度策略，并结合基于水循环的绿色制氢系统。首先，在考虑海水淡化动态效率的前提下，为CIPM开发了一个集反渗透（RO）海水淡化、水电解槽和燃料电池为一体的闭环绿色制氢系统。二是进一步建立微电网内水、氢、电、热流多能协同运行机制。在城市层面，构建协同优化框架，实现由DN协调的多个微电网之间的能量交换。最后，将广义Bregman乘法器交替方向法（ADMM）与渐进式二元松弛策略相结合，设计了一种混合求解算法。模拟结果验证了所提出的方法显著降低了对外部淡水资源的依赖，并为氢集成城市能源系统的可持续发展提供了实际见解。

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引用次数: 0

An interpretable multi-level classification decision-based maximum power point tracking method for photovoltaic systems under partial shading conditions 部分遮阳条件下基于可解释多级分类决策的光伏系统最大功率点跟踪方法

IF 9.1 1区工程技术 Q1 ENERGY & FUELS

Renewable Energy

Pub Date : 2025-12-17 DOI: 10.1016/j.renene.2025.125054

Jishen Li, Linfei Yin

In photovoltaic power generation systems, artificial intelligence technology is widely utilized in areas such as power forecasting, photovoltaic fault diagnosis, and global maximum power point tracking. The nonlinear variation properties of photovoltaic modules in different environmental conditions cause photovoltaic power loss. Meanwhile, photovoltaic systems face the global maximum power point tracking issue under partial shading conditions. Therefore, this study proposes a global maximum power point tracking method based on interpretable multi-level classification decisions (IMCC). The proposed IMCC method establishes an interpretable classification network that divides duty cycle data into various categories. Meanwhile, the IMCC method utilizes a classification decision mechanism divided into intervals and stages to refine the duty cycle change amount. Hence, the proposed IMCC method can realize precise global maximum power point tracking through multi-level classification decisions. In addition, the interpretability of the IMCC method provides transparent and reliable assurance for the control of photovoltaic output power. Finally, this study conducts simulation tests and experimental verification of the IMCC method compared with traditional methods and swarm intelligence algorithms. The experimental results reveal that the IMCC approach increases tracking efficiency by 0.474 % and reduces steady-state oscillations by at least 6.016 W compared to the contrast algorithm.

在光伏发电系统中，人工智能技术被广泛应用于功率预测、光伏故障诊断、全局最大功率点跟踪等领域。光伏组件在不同环境条件下的非线性变化特性导致光伏功率损耗。同时，光伏系统在部分遮阳条件下面临全局最大功率点跟踪问题。为此，本文提出了一种基于可解释多级分类决策（IMCC）的全局最大功率点跟踪方法。该方法建立了一个可解释的分类网络，将占空比数据划分为不同的类别。同时，IMCC方法采用了分段和分段的分类决策机制来细化占空比变化量。因此，该方法可以通过多级分类决策实现精确的全局最大功率点跟踪。此外，IMCC方法的可解释性为光伏输出功率的控制提供了透明、可靠的保证。最后，将IMCC方法与传统方法和群体智能算法进行了仿真测试和实验验证。实验结果表明，与对比算法相比，IMCC方法的跟踪效率提高了0.474%，稳态振荡减少了至少6.016 W。

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引用次数: 0

Unveiling the connotation and significance of wind-solar complementarity from a novel perspective 以新颖的视角揭示风能互补的内涵和意义

IF 9.1 1区工程技术 Q1 ENERGY & FUELS

Renewable Energy

Pub Date : 2025-12-17 DOI: 10.1016/j.renene.2025.125067

Yunxiao Chen, Jinfu Liu, Daren Yu

The integration of variable renewable energy sources like wind and solar power into power systems presents significant challenges due to their inherent volatility and uncertainty. Traditional evaluation methods for wind-solar complementarity primarily focus on correlation or performance improvement of hybrid generation, but overlook the coupling relationships between variable renewable energy and load. To fill this gap, this paper proposes an innovative framework that assesses wind-solar complementarity by emphasizing its impact on net load characteristics, offering a more practical perspective for grid operations. Key contributions include the introduction of novel complementarity indices to quantify improvements in net load stability, fluctuation amplitude, and scheduling risk; the development of high-accuracy white-box mapping models (with coefficient of determination about 0.99) linking renewable energy capacity to net load features; and systematic analysis revealing the advantages of wind-solar complementary on net load characteristics compared to single renewable energy. Validated using data from Belgium's power system, the proposed method demonstrates superior performance.

由于风能和太阳能等可变可再生能源固有的波动性和不确定性，将其整合到电力系统中提出了重大挑战。传统的风光互补评价方法主要关注混合发电的相关性或性能提升，而忽略了可变可再生能源与负荷之间的耦合关系。为了填补这一空白，本文提出了一个创新的框架，通过强调其对净负荷特性的影响来评估风能-太阳能互补性，为电网运行提供了更实用的视角。主要贡献包括引入新的互补指数来量化净负荷稳定性、波动幅度和调度风险的改进；开发将可再生能源容量与净负荷特征联系起来的高精度白盒映射模型（决定系数约为0.99）；并通过系统分析，揭示了风光互补与单一可再生能源相比在净负荷特性上的优势。通过比利时电力系统的数据验证，该方法具有良好的性能。

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引用次数: 0

From lithology prediction to geothermal energy production: Leveraging data-driven and financial insights to unlock geothermal potential of a carbonate reservoir, SE Hungary 从岩性预测到地热能生产：利用数据驱动和财务洞察力来解锁匈牙利东南部碳酸盐岩储层的地热潜力

IF 9.1 1区工程技术 Q1 ENERGY & FUELS

Renewable Energy

Pub Date : 2025-12-17 DOI: 10.1016/j.renene.2025.125031

Mohamed Ayed Elbalawy , Mohamed Hamdy Eid , Mohamed Badawi , Ernő Takács , Felicitász Velledits

Deep Triassic carbonates in Hungary's Pannonian Basin hold substantial geothermal potential but remain difficult to evaluate due to structural complexity, sparse well control, and uncertainty in reservoir continuity. To reduce exploration risk, this study develops a pioneering integrated machine-learning seismic workflow applied to Hungarian geothermal carbonates. A 120 km² post-stack seismic volume and logs from four wells were used to generate 3D lithology, porosity, and temperature models through seismic inversion, probabilistic neural networks, and supervised Bayesian classification. The workflow delineates the spatial extent of fractured dolomitic limestone platforms, quantifies reservoir quality (5–15 % porosity), and estimates the geothermal resource (HIP ≈ 15,600 PJ; Hrec ≈ 1440 MW_th). Probabilistic facies volumes improve the identification of carbonate shale transitions and support uncertainty-aware production scenarios ranging from 48 to 144 MW_th. A heat-led techno-economic assessment indicates that a 2P–1I binary CHP design (3.85 MW_e, 14.31 MW_th) is viable, yielding LCOH values of €102–86/MWh for capacity factors of 0.55–0.65 and annual revenues of €6.9 M from heat sales (plus €0.9 M from seasonal power). Estimated payback ranges from 12.7 to 8.9 years. This integrated geophysical economic framework demonstrates a reproducible pathway for de-risking deep carbonate geothermal systems and supports strategic development of district-heating projects in Hungary.

匈牙利Pannonian盆地的深三叠纪碳酸盐岩具有巨大的地热潜力，但由于构造复杂、井控稀少以及储层连续性的不确定性，仍然难以评估。为了降低勘探风险，本研究开发了一种应用于匈牙利地热碳酸盐岩的开创性集成机器学习地震工作流程。通过地震反演、概率神经网络和监督贝叶斯分类，利用120 km2的叠后地震体积和4口井的测井数据生成三维岩性、孔隙度和温度模型。该工作流程描绘了裂缝状白云岩平台的空间范围，量化了储层质量（5 - 15%孔隙度），并估算了地热资源（HIP≈15,600 PJ; Hrec≈1440 mwith）。概率相体积提高了对碳酸盐岩页岩过渡的识别，并支持48 - 144mth的不确定性生产情景。热主导技术经济评估表明，2P-1I二元热电联产设计（3.85 MWe, 14.31 mth）是可行的，容量系数为0.55-0.65，LCOH值为102-86欧元/MWh，热销售年收入为690万欧元（加上季节性电力收入90万欧元）。估计投资回收期为12.7年至8.9年。这一综合地球物理经济框架为降低深层碳酸盐地热系统的风险提供了可复制的途径，并为匈牙利区域供热项目的战略发展提供了支持。

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引用次数: 0

Enhancing microalgal biohydrogen production: Unlocking higher yields with hydrothermal pretreatment with niobium phosphate 加强微藻生物制氢：用磷酸铌水热预处理解锁更高的产量

IF 9.1 1区工程技术 Q1 ENERGY & FUELS

Renewable Energy

Pub Date : 2025-12-16 DOI: 10.1016/j.renene.2025.125048

Thiago Abrantes Silva , Maurino Magno de Jesus Junior , Matheus Neves de Araujo , Laressa Santos de Castro , Lucas Tadeu Fuess , Fábio de Ávila Rodrigues , Marcelo Zaiat , Alberto José Delgado dos Reis , Maria Lúcia Calijuri

Microalgae cultivated in wastewater hold promise as a substrate for biohydrogen (bioH₂) production. However, their rigid cell walls pose a challenge to fermentability. In this context, this study evaluated hydrothermal pretreatment with niobium phosphate (NbP) at 100–180 °C for 0–70 min, using up to 75 % NbP (relative to the dry weight of microalgal biomass). The hydrothermal pretreatment at 180 °C for 10 min with 75 % NbP released 7431 mg total carbohydrates (CHt) L⁻¹, increasing the availability of fermentable substrates in subsequent dark fermentation (DF). When this pretreated biomass was subsequently fermented at pH 5.0 (sample PB5), bioH₂ production reached 1.03 mmol H₂ mol⁻¹ CHt, with a maximum cumulative output of 0.17 mmol H₂ and a CHt conversion efficiency of 83.6 %. In contrast, pH 5.5 and 6.0 reduced bioH₂ yields and promoted methanogenic activity, while no pH control resulted in negligible bioH₂ evolution. In conclusion, hydrothermal pretreatment with niobium phosphate and pH improvement synergize to enhance hydrogenogenesis, integrating wastewater treatment and renewable biohydrogen production.

在废水中培养的微藻有望成为生产生物氢（bioH2）的底物。然而，它们坚硬的细胞壁对发酵性提出了挑战。在此背景下，本研究评估了用磷酸铌（NbP）在100-180°C下进行0-70分钟的水热预处理，使用高达75%的NbP（相对于微藻生物量的干重）。在180°C、75% NbP条件下，水热预处理10 min，释放出7431 mg总碳水化合物（CHt） L−1，增加了后续暗发酵（DF）中可发酵底物的利用率。当预处理后的生物质在pH 5.0（样品PB5）下发酵时，生物H2产量达到1.03 mmol H2 mol−1 CHt，最大累计产量为0.17 mmol H2， CHt转化效率为83.6%。相比之下，pH为5.5和6.0降低了生物h2产量，促进了产甲烷活性，而不控制pH对生物h2的生成几乎没有影响。综上所述，磷酸铌水热预处理与pH改善协同促进产氢，将废水处理与可再生生物制氢结合起来。

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引用次数: 0

Collaborative advantage: How supply chain alliances drive productivity improvement in renewable energy firms 合作优势：供应链联盟如何推动可再生能源企业提高生产率

IF 9.1 1区工程技术 Q1 ENERGY & FUELS

Renewable Energy

Pub Date : 2025-12-16 DOI: 10.1016/j.renene.2025.125024

Boqiang Lin , Jiawen Xie

With accelerating industrial and energy transitions, promoting cooperation among enterprises within the renewable energy supply chain is crucial for mitigating supply chain risks and enhancing productivity. However, existing studies offered limited evidence on its productivity implications, leaving a critical gap in understanding how synergistic supply chain relationships support renewable energy development. Using data from China's listed renewable energy firms from 2014 to 2023, this paper constructs a Two-Way Fixed-Effects model to investigate how participation in supply chain alliances affects total factor productivity and explores the underlying mechanisms. The findings reveal that: (1) Engaging in supply chain alliances improves the productivity performance of renewable energy companies. It suggests that renewable energy firms that participate in supply chain alliances increase productivity by 9.6 %. This conclusion remains valid after endogeneity analysis and robustness tests. (2) Supply chain alliances can increase productivity by improving the supply chain efficiency and facilitating technological efforts. (3) Renewable energy firms with lower bargaining power and a more optimized human capital structure are more likely to achieve productivity improvement in the supply chain partnerships. (4) Both upstream and downstream partnerships exert significant positive effects. This paper enriches the research on supply chain management and strategic alliances, offering policy insights and empirical evidence to advance renewable energy transition and support high-quality industrial upgrading.

随着产业和能源转型的加快，促进可再生能源供应链企业之间的合作对于降低供应链风险和提高生产力至关重要。然而，现有的研究对其生产力影响提供的证据有限，在理解协同供应链关系如何支持可再生能源发展方面留下了关键空白。本文利用2014 - 2023年中国可再生能源上市公司的数据，构建双向固定效应模型，考察供应链联盟参与对全要素生产率的影响，并探讨其影响机制。研究结果表明：(1)参与供应链联盟提高了可再生能源企业的生产力绩效。研究表明，参与供应链联盟的可再生能源公司的生产率提高了9.6%。经过内生性分析和稳健性检验，这一结论仍然有效。(2)供应链联盟可以通过提高供应链效率和促进技术努力来提高生产率。(3)在供应链合作伙伴关系中，议价能力越低、人力资本结构越优化的可再生能源企业更有可能实现生产率的提升。(4)上下游伙伴关系均具有显著的正向效应。本文丰富了供应链管理和战略联盟的研究内容，为推进可再生能源转型、支持高质量产业升级提供了政策见解和实证证据。

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引用次数: 0

Advanced viscosity prediction in hydrogen storage systems: emphasizing the role of cushion gases in pure and mixture forms 先进的粘度预测在储氢系统：强调缓冲气体在纯和混合形式的作用

IF 9.1 1区工程技术 Q1 ENERGY & FUELS

Renewable Energy

Pub Date : 2025-12-16 DOI: 10.1016/j.renene.2025.125052

Mohammad Behnamnia, Hossein Sarvi, Abolfazl Dehghan Monfared

As global energy systems transition toward low-carbon solutions, hydrogen is emerging as a vital carrier for clean energy storage and transport. Precise knowledge of hydrogen's properties is a key requirement for designing and operating storage and transport systems, particularly when it interacts with cushion gases like methane, carbon dioxide, and nitrogen. In this way, viscosity is key to flow behavior and safe hydrogen handling. This study introduces a machine learning framework to predict the viscosity of pure hydrogen, its binary and multicomponent mixtures with cushion gases, and the pure forms of these gases. A refined dataset of 3547 viscosity measurements was used. A new composite parameter, Beta (β), was developed to improve prediction accuracy. Six advanced machine learning algorithms; decision tree, Gaussian process regression, K-nearest neighbors, random forest, AdaBoosting, and multilayer perceptron were trained and evaluated through statistical and visual metrics. Among them, AdaBoost achieved the highest accuracy with an R² of 0.9953 and a MAPE of 2.8875 %. Sensitivity analysis and SHAP plots identified Beta and pressure as the most influential variables. The model shows strong generalization and reliable trend prediction across various conditions, offering a robust and scalable tool for hydrogen storage and transport applications.

随着全球能源系统向低碳解决方案过渡，氢正在成为清洁能源储存和运输的重要载体。准确了解氢的性质是设计和操作储存和运输系统的关键要求，特别是当它与甲烷、二氧化碳和氮等缓冲气体相互作用时。因此，粘度是流动行为和安全氢气处理的关键。本研究引入了一个机器学习框架来预测纯氢的粘度，它与缓冲气体的二元和多组分混合物，以及这些气体的纯形式。使用了3547个粘度测量值的精炼数据集。为了提高预测精度，提出了新的复合参数β (β)。六种先进的机器学习算法；决策树、高斯过程回归、k近邻、随机森林、AdaBoosting和多层感知器通过统计和视觉指标进行训练和评估。其中AdaBoost的准确率最高，R2为0.9953，MAPE为2.8875%。敏感性分析和SHAP图确定Beta和压力是影响最大的变量。该模型具有较强的泛化能力和可靠的趋势预测能力，为氢的储存和运输应用提供了强大的可扩展工具。

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引用次数: 0