IF 9.4 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2025-12-29 DOI: 10.1016/j.energy.2025.139828

Depeng Wei, Qingguo Peng, Ruixue Yin, Hao Wang, Zhixin Huang, Xinghua Tian, Feng Yan, Peng Zhou

To enhance the efficiency of waste heat recovery, a coupled power generation system integrating thermoelectric generator (TEG) with diesel particulate filter (DPF) is proposed and optimized for engine exhaust applications. The system harnesses both the exhaust heat and the substantial thermal energy generated by DPF regeneration for thermoelectric conversion. Effects of key parameters, such as exhaust gas velocity V_e, heat sink setting, porosity P_e of multi-layer porous media, and two-stage TEG design, on system thermal and working performance are tested and analyzed. The results demonstrate that the augment of V_e enhances the electrical power output of the TEG-DPF system, while the advantages diminish at high V_e and are accompanied by a reduction in thermoelectric conversion efficiency. Enhancing heat dissipation can be achieved by increasing fin height while reducing fin spacing and thickness to effectively mitigate the negative impact of high V_e, enabling the system to maintain efficient operating condition. Additionally, the arrangement of multi-layer porous media in the DPF significantly influences gas-solid heat transfer, and the DPF with a porosity gradient P_e = 0.3 + 0.4+0.5 is more conducive to improving the energy conversion and efficiency of the integrated system. Furthermore, the implementation of the two-stage thermoelectric modules further boosts electrical output, where the generator with PbTe-Bi₂Te₃ modules significantly broadens the operational temperature range and achieves the maximum output power of 15 W at V_e = 20 m/s. These findings provide a theoretical foundation and technical reference for the efficient integrated design of thermoelectric and waste heat recovery systems.

为了提高余热回收效率，提出了一种热电发电机（TEG）与柴油机微粒过滤器（DPF）相结合的耦合发电系统，并对其进行了优化。该系统利用废热和DPF再生产生的大量热能进行热电转换。测试分析了排气速度Ve、散热器设置、多层多孔介质孔隙度Pe、两级TEG设计等关键参数对系统热性能和工作性能的影响。结果表明，Ve的增大增大了TEG-DPF系统的电功率输出，而在高Ve时，这种优势减弱，并伴随着热电转换效率的降低。通过增加散热片高度，减小散热片间距和厚度，有效缓解高Ve的负面影响，使系统保持高效运行状态。此外，多层多孔介质在DPF内的排列对气固换热影响显著，孔隙度梯度Pe = 0.3 + 0.4+0.5的DPF更有利于提高集成系统的能量转换和效率。此外，两级热电模块的实现进一步提高了电力输出，其中带有PbTe-Bi2Te3模块的发电机显着拓宽了工作温度范围，并在Ve = 20 m/s时实现了15 W的最大输出功率。研究结果为热电与余热回收系统的高效集成设计提供了理论基础和技术参考。

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引用次数: 0

Reliable cross-domain lifetime prediction for fuel cells: A time-frequency fusion transfer learning architecture 燃料电池可靠的跨域寿命预测：一种时频融合迁移学习架构

IF 9.4 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2025-12-29 DOI: 10.1016/j.energy.2025.139854

Hangyu Wu , Fulin Fan , Kai Song , Chuanyu Sun , Yang Li , Changjun Xie , Xuan Meng , Jian Mei , Siew Hwa Chan

Current transfer learning-based methods for predicting the degradation of proton exchange membrane fuel cells (PEMFCs) commonly face insufficient elimination of inter-domain distribution shifts and low knowledge transfer efficiency. Traditional approaches typically extract domain-invariant features by filtering multi-dimensional operational parameters. This process is not only complex but may also introduce interference weakly correlated with voltage degradation, thereby compromising the stability and reliability of cross-domain predictions. To address these challenges, this paper proposes a time-frequency fusion transfer learning (TF-TL) architecture. Unlike existing methods that filter domain-invariant features from multi-dimensional operational parameters, the proposed approach directly aligns domains by leveraging the intrinsic frequency-domain characteristics of voltage signals. The integrated Frequency Domain Adaptation (FDA) technique employs Fast Fourier Transform (FFT) to extract intrinsic low-frequency components from voltage signals. It then aligns features between source and target domains using an enhanced Maximum Mean Discrepancy (MMD) metric. This voltage-centric, frequency-domain alignment avoids dependence on complex auxiliary parameters, thus improving the interpretability and stability of transfer learning. Experimental results show that TF-TL significantly improves generalization across devices and operating conditions, with FDA effectively reducing inter-domain distribution divergence. In multiple transfer tasks, the framework achieves highly accurate and reliable remaining useful life estimation with a relative error below 1.9 %. The proposed architecture provides a theoretical foundation for deploying rapid and reliable online prognostic systems for PEMFCs under complex operating conditions.

目前基于迁移学习的质子交换膜燃料电池（pemfc）降解预测方法普遍存在消除域间分布转移不足和知识迁移效率低等问题。传统的方法通常是通过过滤多维操作参数来提取域不变特征。这个过程不仅复杂，而且还可能引入与电压退化弱相关的干扰，从而损害跨域预测的稳定性和可靠性。为了解决这些问题，本文提出了一种时频融合迁移学习（TF-TL）架构。与现有的从多维操作参数中过滤域不变特征的方法不同，该方法通过利用电压信号的固有频域特性直接对齐域。集成频域自适应（FDA）技术采用快速傅立叶变换（FFT）从电压信号中提取固有低频分量。然后，它使用增强的最大平均差异（MMD）度量来对齐源域和目标域之间的特征。这种以电压为中心的频域对齐避免了对复杂辅助参数的依赖，从而提高了迁移学习的可解释性和稳定性。实验结果表明，TF-TL显著提高了跨设备和操作条件的泛化，FDA有效地减少了域间分布差异。在多传输任务中，该框架实现了高度准确可靠的剩余使用寿命估计，相对误差低于1.9%。所提出的体系结构为在复杂工况下部署快速可靠的pemfc在线预测系统提供了理论基础。

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引用次数: 0

Feasible operating envelopes via thermal assessment of partially cracked ammonia-fueled megawatt gas turbine systems 通过对部分裂解氨燃料兆瓦燃气轮机系统的热评估，得出可行的运行包壳

IF 9.4 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2025-12-28 DOI: 10.1016/j.energy.2025.139823

Jing Zhou, Fei Duan

Transition from hydrocarbon to zero-carbon fuels is essential for achieving deep decarbonization in power generation. Partially cracked ammonia (PCA) combines both advantages of hydrogen and ammonia fuels, thereby mitigating the challenges of hydrogen flashback and high ammonia ignition energy. However, a unified framework for performance evaluation, system integration, and feasible operating envelopes of PCA-fueled gas turbines has yet to be established. Comprehensive parameter studies are performed to assess the off-design gas turbine performance under various fuel types and injections. Under the identical turbine inlet temperature and compression ratio, the ammonia-fueled gas turbine has the narrowest load range that can be expanded by almost twofold through higher compression ratios, improved combustion stability, and partial ammonia cracking. With the ambient temperature increasing from 15 °C to 45 °C, ammonia and PCA fuels cause 2.7% and 3.6% reduction in gas turbine exergy efficiency, lower than those of natural gas and hydrogen, suggesting the better suitability for tropical climates. Preliminary system integration and feasible operating envelopes of 30 MW partially cracking ammonia-fueled gas turbine are constructed and evaluated. Case analysis indicates that the cracking reaction temperature is more influential in determining fuel condition ranges than costly cracker design alternatives. Incorporating considerations of nozzle-based fuel flexibility, cracker–turbine coupling, and system safety, the thermal efficiency of single-cycle integrated system varies between 43.1% and 46.0% and the cogeneration efficiency ranges from 81.7% to 82.5%.

从碳氢化合物燃料到零碳燃料的过渡是实现发电深度脱碳的必要条件。部分裂解氨（PCA）结合了氢燃料和氨燃料的优点，从而减轻了氢闪回和高氨点火能量的挑战。然而，对于pca燃料燃气轮机的性能评估、系统集成和可行的运行包线，尚未建立统一的框架。对不同燃料类型和不同喷注量下的非设计燃气轮机性能进行了综合参数研究。在涡轮进口温度和压缩比相同的情况下，氨燃料燃气轮机的负荷范围最窄，通过提高压缩比、改善燃烧稳定性和部分氨裂解，负荷范围几乎可以扩大两倍。当环境温度从15℃升高到45℃时，氨燃料和PCA燃料分别使燃气轮机的火用效率降低2.7%和3.6%，低于天然气和氢气燃料，表明其更适合热带气候。对30 MW部分裂解氨燃料燃气轮机的初步系统集成和可行运行包线进行了构建和评价。实例分析表明，裂化反应温度比昂贵的裂化装置设计方案对燃料工况范围的影响更大。综合考虑喷嘴燃料灵活性、裂纹-涡轮耦合和系统安全性等因素，单循环集成系统热效率在43.1% ~ 46.0%之间，热电联产效率在81.7% ~ 82.5%之间。

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引用次数: 0

Mechanistic entrainment model of vertical steam-water annular flow based on disturbance wave force analysis 基于扰动波力分析的蒸汽-水垂直环流机械夹带模型

IF 9.4 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2025-12-28 DOI: 10.1016/j.energy.2025.139836

Zicheng Tang , Quan Zhou , Min Zeng , Ting Ma , Qiuwang Wang

The droplet entrainment (DE) fraction is a crucial parameter that significantly influences the heat transfer coefficient, pressure drop and critical heat flux of the high-pressure steam-water annular flow in the cooling tubes of boiling water reactors. Accurate prediction of the DE fraction depends on reasonable models for the DE rate and droplet deposition (DD) rate. In this study, a mechanistic entrainment model based on disturbance wave force analysis is proposed for the DE fraction in the vertical upward high-pressure steam-water annular flow. The new model improves the existing force balance theory by assuming a physically reasonable wave crest shape and incorporating the inertial force. Additionally, an improved data processing method is employed to guarantee the validity of the correction factor for the maximum DE rate. The prediction results of the new model are compared to the experimental results based on the typical operating conditions of the boiling water reactor and the results of the existing prediction models based on the high-pressure steam-water databases. The proposed DE rate model and DE fraction model exhibit superior performance with mean relative errors (MREs) as low as 18.3 % and 1.76 %, respectively.

液滴夹带分数是影响沸水堆冷却管内高压蒸汽-水环流换热系数、压降和临界热流密度的重要参数。准确预测DE分数取决于合理的DE率和液滴沉积（DD）率模型。本文提出了一种基于扰动波力分析的高压蒸汽-水垂直向上环空流动中DE组分的机械夹带模型。新模型通过假设物理上合理的波峰形状并考虑惯性力，改进了现有的力平衡理论。此外，采用改进的数据处理方法，保证了最大DE率下校正因子的有效性。将新模型的预测结果与基于沸水堆典型工况的实验结果和基于高压蒸汽-水数据库的现有预测模型的预测结果进行了比较。DE率模型和DE分数模型的平均相对误差（MREs）分别为18.3%和1.76%。

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引用次数: 0

Energy system planning and operation for emerging countries, the case of Iraq 新兴国家能源系统规划与运作，以伊拉克为例

IF 9.4 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2025-12-28 DOI: 10.1016/j.energy.2025.139833

Nooriya A. Mohammed , Gregor Zöttl

The transition to sustainable electricity systems in many emerging countries is constrained by limited access to capital, fuel supply bottlenecks, and underdeveloped infrastructure-factors often insufficiently represented in energy system modelling. This study presents a high-resolution electricity system framework that explicitly captures these challenges. Using a mixed-integer linear programming formulation with hourly temporal and regional spatial resolution, the model jointly optimizes investment and operation of generation and transmission infrastructure under alternative financing regimes.

To illustrate its specific applicability, we consider the case of Iraq, a fragile, oil-dependent economy facing severe electricity shortages and growing demand. Three financing scenarios are examined: limited public investment, participation of independent power producers, and access to high-interest international capital. Results show that strict financing constraints lead to extensive load curtailment and high system costs, whereas alternative financing options enable renewable deployment, eliminate curtailment, reduce emissions, and substantially lower total system costs.

Overall, the study demonstrates how explicitly accounting for financial and fuel constraints in optimization models can support effective energy planning in emerging economies, offering transferable insights for the Global South.

许多新兴国家向可持续电力系统的过渡受到资本获取有限、燃料供应瓶颈和基础设施不发达等因素的制约，这些因素在能源系统建模中往往没有得到充分体现。这项研究提出了一个高分辨率的电力系统框架，明确地抓住了这些挑战。该模型采用具有小时时间和区域空间分辨率的混合整数线性规划公式，共同优化发电和输电基础设施在替代融资制度下的投资和运营。为了说明其具体适用性，我们考虑伊拉克的情况，这是一个脆弱的、依赖石油的经济，面临严重的电力短缺和日益增长的需求。本文考察了三种融资方案：有限的公共投资、独立电力生产商的参与以及获得高息国际资本。研究结果表明，严格的融资约束导致大量弃电和高系统成本，而替代融资方案能够实现可再生能源部署，消除弃电，减少排放，并大幅降低系统总成本。总体而言，该研究表明，在优化模型中明确考虑金融和燃料限制因素，可以为新兴经济体的有效能源规划提供支持，为全球南方国家提供可转移的见解。

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引用次数: 0

Preparation of cold-storage microencapsulated phase change suspension: dispersion stability and thermal conductivity performance improvement 冷库微囊化相变悬浮液的制备：分散稳定性和导热性能的改善

IF 9.4 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2025-12-27 DOI: 10.1016/j.energy.2025.139777

Yiting Yang , Ming Li , Shengmei Zhang , Yali Liu , Ying Zhang

Microencapsulated phase change slurry has become a research hotspot in the field of cold energy storage due to its high latent heat and microconvection effects. However, its instability and low thermal conductivity limit its practical applications. This study adopted the phase-change microcapsules with a tetradecane core and a polymethyl methacrylate shell, which is suitable for the food preservation temperature range between 3 °C–8 °C. The effects of different kinds of carrier fluids, surfactant types and graphene concentrations on the materials thermal performance and thermal conductivity were explored experimentally. The results indicate that the optimal carrier liquids consisted of deionized water and isopropyl alcohol in a mass ratio of 3.58:4.24, with a carrier liquid density of 0.87 g/cm³. The phase-change microcapsule suspension maintained dispersion stability for 30 days when the hydrophilic-lipophilic balance value of the sodium dodecyl sulfate and Hexadecyl trimethyl ammonium chloride composite surfactant was 27.9 and their mass ratio was 1:1. The thermal conductivity and circulation stability of phase-change microcapsule suspensions were enhanced by incorporating highly thermally conductive two-dimensional graphene materials. The highest thermal conductivity reaches 0.3092 W/(m·K) with the graphene concentration of 1 wt%, representing a 7.26% improvement compared to the suspension without graphene. After 100 clod thermal cycles, the latent heat loss of the composite suspension remained within 14.5%, which means the graphene improved the cycle stability of the suspension. The study gives a reference for the preparation of high-efficiency energy storage functional fluids.

微囊化相变浆料因其高潜热和微对流效应而成为冷储能领域的研究热点。然而，它的不稳定性和低导热性限制了它的实际应用。本研究采用十四烷为核，聚甲基丙烯酸甲酯为壳的相变微胶囊，适用于3℃- 8℃的食品保鲜温度范围。实验考察了不同载体流体、表面活性剂类型和石墨烯浓度对材料热性能和导热系数的影响。结果表明，最佳载体液为去离子水与异丙醇的质量比为3.58:4.24，载体液密度为0.87 g/cm3。当十二烷基硫酸钠与十六烷基三甲基氯化铵复合表面活性剂的亲水亲脂平衡值为27.9，质量比为1:1时，相变微胶囊悬浮液保持了30 d的分散稳定性。通过加入高导热的二维石墨烯材料，增强了相变微胶囊悬浮液的导热性和循环稳定性。当石墨烯浓度为1 wt%时，最高导热系数达到0.3092 W/(m·K)，与不含石墨烯的悬浮液相比，导热系数提高了7.26%。经过100次冷热循环后，复合悬浮液的潜热损失保持在14.5%以内，表明石墨烯提高了悬浮液的循环稳定性。该研究为制备高效储能功能流体提供了参考。

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引用次数: 0

Designing permit discount rate in intertemporal carbon market coordinating with carbon offset scheme 与碳补偿机制相协调的跨期碳市场许可折现率设计

IF 9.4 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2025-12-27 DOI: 10.1016/j.energy.2025.139815

Liqing Huang

Carbon market and carbon offset (CO) scheme are important policy instruments to achieve carbon peaking and neutrality. Taking carbon market and CO scheme in the same analytical framework, this paper constructs the intertemporal carbon emission trading model to explore the optimal intertemporal permit discount rate (IPDR) and CO scheme to enhance effective carbon market management in six mechanism scenarios. Mechanisms of CO accounted for carbon permits and accounted for carbon emissions, permit allocation based on grandfathering rule (PAGR) and based on benchmarking rule (PABR) are considered. The conditions of achieving intertemporal carbon market efficiency are derived. The results suggest that IPDR adjustment promotes emission reduction when the discount rate threshold is lower than IPDR grandfathering threshold in scenarios with PAGR. Profits decrease with the increase of CO price in scenarios with PAGR. When IPDR is designed equal to interest discount rate, carbon price volatility reduces and intertemporal carbon market efficiency is achieved in scenarios with PAGR and with PABR covering one industry, while benchmark carbon production intensity should be the same across industries simultaneously in scenarios with PABR covering more than one industry. These findings provide guidance for policy makers designing effective coordination systems between carbon market and CO scheme.

碳市场和碳补偿计划是实现碳峰值和碳中和的重要政策工具。本文将碳市场与CO机制置于同一分析框架下，构建跨期碳排放交易模型，探讨在6种机制情景下，跨期许可折现率和CO机制的优化，以增强碳市场的有效管理。考虑了CO计算碳许可和碳排放的机制、基于祖父规则（PAGR）和基于基准规则（PABR）的许可分配。推导了实现跨期碳市场效率的条件。结果表明，在PAGR情景下，当贴现率阈值低于IPDR祖父阈值时，IPDR调整有利于减排。在PAGR情景下，利润随着CO价格的升高而下降。当IPDR设计为等于利率贴现率时，在PAGR和PABR覆盖一个行业的情景下，碳价格波动减小，实现了跨期碳市场效率，而在PABR覆盖多个行业的情景下，基准碳生产强度应该是相同的。这些发现为决策者设计有效的碳市场与CO计划协调体系提供了指导。

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引用次数: 0

Operational optimization of multi-unit parallel pressure differential power generation in natural gas networks 天然气管网多机组并联压差发电的运行优化

IF 9.4 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2025-12-27 DOI: 10.1016/j.energy.2025.139826

Jun Zhou , Zhifu Cheng , Guangchuan Liang , Tao Wang , Xuan Jiang , Yue Wu

In the practical operation of natural gas network pressure differential power generation (PDPG) systems, the operational parameters of the expander power generation units directly affect the power output, thereby influencing the final generation revenue. To explore the optimal operating range of natural gas PDPG unit parameters, this paper investigates the operational optimization of natural gas network PDPG technology for multiple units operating in parallel. An optimization model is developed to maximize the operational profit of the natural gas network PDPG system. The impact of isentropic efficiency (IE) on the unit's energy efficiency is clarified, and isentropic efficiency-flow curves for different unit configurations are plotted. Using two operating conditions with different flow rates as examples, the effectiveness of the optimization model is verified from the perspectives of the number of operating power generation units, split ratio of the power generation units, economic performance of the PDPG system, and power output of the system. For the low-flow condition, the optimized unit efficiencies are between 0.7 and 0.75, the overall optimized power output increases by 324.85 kW, and the economic benefit improves by 3.02 %. For the high-flow condition, it is necessary to split the upstream gas flow and divert part of the flow through a bypass pipeline in the PDPG process to the users, ensuring that the operating parameters of the units do not exceed the rated parameters, thereby maintaining the safe and stable operation of the units.

在天然气管网压差发电（PDPG）系统的实际运行中，膨胀发电机组的运行参数直接影响输出功率，从而影响最终发电收益。为探索天然气PDPG机组参数的最佳运行范围，对多机组并联运行的天然气管网PDPG技术运行优化进行了研究。建立了天然气管网PDPG系统运行利润最大化的优化模型。阐明了等熵效率对机组效率的影响，绘制了不同机组配置的等熵效率-流量曲线。以两种不同流量工况为例，从运行发电机组数量、发电机组分流比、PDPG系统经济性能、系统输出功率等方面验证优化模型的有效性。在低流量工况下，优化后的机组效率在0.7 ~ 0.75之间，优化后的总输出功率提高了324.85 kW，经济效益提高了3.02%。对于大流量工况，在PDPG工艺中需要对上游气体流量进行分流，将部分流量通过旁通管道分流给用户，保证机组运行参数不超过额定参数，从而保持机组安全稳定运行。

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引用次数: 0

Online optimization and dynamic prediction of an intermediate-circuit thermal management system based on physical-data dual-driven modeling and experimental validation 基于物理数据双驱动建模和实验验证的中路热管理系统在线优化与动态预测

IF 9.4 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2025-12-27 DOI: 10.1016/j.energy.2025.139827

Lingyao Zhao , Wei Shao , Chen Zheng , Jiahua Xu , Lipeng Song , Chenghang Pan , Zheng Cui

Thermal management systems (TMS) have broad application prospects in the optimization of complex thermal systems due to their ability to effectively enhance heat transfer efficiency. However, TMS often experience performance degradation and load fluctuations during actual operation, which render default control strategies insufficient to achieve optimal system performance. Distinct from existing research on independent prediction and optimization based on offline data, this study proposes a closed-loop online optimization framework integrating real-time data interaction, parameter identification, steady-state optimization, and dynamic prediction for a thermal management system. The heat current method is used to describe the heat transfer constraints and an artificial neural network (ANN) model is employed for predicting the real-time thermal conductance of heat exchangers. A Long Short-Term Memory (LSTM) model based on real-time data is established to predict the systematic dynamic responses. Finally, the Lagrange Multiplier Method is used to optimize the operating frequencies of variable frequency pumps to maximize system heat transfer rate. To further validate the effectiveness of the proposed method especially the data communications, it is deployed in a thermal management system including an intermediate loop. The results of disturbance conditions indicate that the strategy operates well and all the parameters respond correctly. Furthermore, under thermal disturbance conditions, the total heat transfer rate of the system increased from 2112.3 W to 2402.1 W through online optimization control, achieving the performance improvement of 13.72 %. The proposed method provides powerful tools for the high-efficient thermal management and energy conservation.

热管理系统（TMS）能够有效地提高传热效率，在复杂热系统优化中具有广阔的应用前景。然而，TMS在实际运行中经常会出现性能下降和负载波动，这使得默认的控制策略不足以达到最佳的系统性能。与现有的基于离线数据的独立预测和优化研究不同，本研究提出了一个集实时数据交互、参数识别、稳态优化和动态预测于一体的热管理系统闭环在线优化框架。采用热流法描述传热约束条件，采用人工神经网络模型实时预测换热器导热系数。建立了基于实时数据的长短期记忆（LSTM）模型来预测系统的动态响应。最后，利用拉格朗日乘数法优化变频泵的工作频率，使系统换热率最大化。为了进一步验证所提出方法的有效性，特别是数据通信，它被部署在一个热管理系统中，包括一个中间回路。扰动条件下的结果表明，该策略运行良好，各参数响应正确。在热扰动条件下，通过在线优化控制，系统总换热率由2112.3 W提高到2402.1 W，性能提高13.72%。该方法为高效热管理和节能提供了有力的工具。

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引用次数: 0

Autothermal Aspen modelling for bubbling fluidized bed integrated with heat loss prediction: biomass gasification performance analysis, optimization, and system efficient design 与热损失预测集成鼓泡流化床的自热阿斯彭模型：生物质气化性能分析，优化和系统高效设计

IF 9.4 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2025-12-27 DOI: 10.1016/j.energy.2025.139821

Hao Shi , Yaji Huang , Yizhuo Qiu , Jun Zhang , Huikang Song , Tianhang Tang , Hao Liu , Shuanzhu Sun , Jiewen Zhu

Biomass gasification is well-applied in industrial bubbling fluidized bed (BFB) for producing high-quality syngas and integration with other chemical processes. However, corresponding autothermal Aspen models, which are crucial for process optimization and analysis, stay underexplored in existing researches. This study introduces a unique Aspen modelling incorporating machine learning for predict fast pyrolysis products, regression expressions of heat loss prediction with operating variables, iteration solutions for mass & energy equilibrium equations and Aspen-MATLAB-EXCEL data interaction. The model was validated using experimental data, and parametric studies were carried out on gasification performance with common operating variables. The results prove that current model gains a breakthrough in predicting temperature profiles and enables accurate simulation syngas compositions and gasification performance metrics in an autothermal BFB, with relative errors of involved parameters basically within ±10 %. The model was validated using experimental data, and parametric studies were carried out on gasification performance with common operating variables. Detailed calculation and discussions on model's industrial applications are conducted including gasification conditions optimization, mass & energy distribution, heat exchange network construction and gasifier design. Current Aspen model serves as a valuable tool for process optimization and technical-economic analyses in industrial BFB biomass gasification, offering promising insights for further research and practical applications.

生物质气化在工业鼓泡流化床（BFB）中得到了广泛的应用，用于生产高质量合成气并与其他化学工艺相结合。然而，对于工艺优化和分析至关重要的自热Aspen模型，在现有的研究中尚未得到充分的探索。本研究引入了一种独特的Aspen模型，该模型结合了预测快速热解产物的机器学习、热损失预测与操作变量的回归表达式、质量和能量平衡方程的迭代解以及Aspen- matlab - excel数据交互。利用实验数据对模型进行了验证，并对常用操作变量下的气化性能进行了参数化研究。结果表明，该模型在预测温度分布方面取得了突破，能够准确模拟自热BFB合成气组成和气化性能指标，相关参数的相对误差基本在±10%以内。利用实验数据对模型进行了验证，并对常用操作变量下的气化性能进行了参数化研究。对模型的工业应用进行了详细的计算和讨论，包括气化条件优化、质量和能量分配、换热网络建设和气化炉设计。目前的Aspen模型为工业BFB生物质气化过程优化和技术经济分析提供了有价值的工具，为进一步的研究和实际应用提供了有希望的见解。

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引用次数: 0

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