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Efficacy of aluminium oxide nanofluids in passive cooling of direct absorption-based photovoltaic/thermal system: An experimental approach 氧化铝纳米流体在基于直接吸收的光伏/热系统被动冷却中的效果：实验方法

Next Energy

Pub Date : 2025-10-01 DOI: 10.1016/j.nxener.2025.100471

Munna Kumar , Sanjay Kumar , Satyender Singh

Over the last two decades, direct absorption-based Photovoltaic/Thermal system (DAS-PV/T) has emerged as a promising solution considering better thermal management and overall performance enhancement over standalone PV system. However, previous studies reported the testing results either using theoretical models or using laboratory prototypes under controlled conditions or operational parameters. The main bottleneck is that there aren't enough outdoor studies that focuses on thermal performance characterization of direct absorption-based PV/T systems in real-world conditions. Metallic nanoparticles-based nano colloids are proved to be better alternative over conventional cooling fluids such as water, oils or glycols for such DAS-PV/T system. Therefore, for the present work, field experiments are conducted using Al₂O₃ nanofluids at different mass concentrations (ξ_NF) and mass flow rates (Ϻ_F) to assess the energetic and energetic performance of a DAS-PV/T system under actual sun setting conditions. Al₂O₃ nanofluids are characterized for its optical and morphological properties using UV–vis spectrophotometry and field emission-scanning electron microscopy (FE-SEM) techniques. The outdoor testing results showed that tested DAS-PV/T system achieved a maximum photo-thermal, electrical and overall thermal efficiency at higher ξ_NF and Ϻ_F of Al₂O₃ nanofluids over de-ionized (DI) water. Further an average surface temperature of PV cell was recorded about 56.0 ℃ with Al₂O₃ nanofluids, which was about 4.5 °C lower than bare PV system. Further, a maximum overall energetic and exergetic efficiency of values 27.54% and 26.41% was achieved for tested DAS-PV/T system using Al₂O₃ nanofluids at ξ_NF ∼ 0.0004 wt% and Ϻ_F ∼ 0.035 kg/s, respectively. The study concludes that a DAS-PV/T systems is a feasible solution over standalone PV system.

在过去的二十年中，基于直接吸收的光伏/热系统（DAS-PV/T）已经成为一种有前途的解决方案，考虑到比独立光伏系统更好的热管理和整体性能增强。然而，先前的研究报告的测试结果要么是使用理论模型，要么是在受控条件或操作参数下使用实验室原型。主要的瓶颈是，目前还没有足够的户外研究来关注基于直接吸收的PV/T系统在现实条件下的热性能特征。在DAS-PV/T系统中，基于金属纳米颗粒的纳米胶体被证明是比传统冷却流体（如水、油或乙二醇）更好的替代品。因此，本研究采用不同质量浓度（ξNF）和质量流量（ϺF）的Al2O3纳米流体进行了现场实验，以评估DAS-PV/T系统在实际日落条件下的能能和能能性能。利用紫外-可见分光光度法和场发射扫描电子显微镜（FE-SEM）技术对Al2O3纳米流体的光学和形态特性进行了表征。室外测试结果表明，在所测试的DAS-PV/T系统中，Al2O3纳米流体在去离子水（DI）表面具有较高的ξNF和ϺF时，光热效率、电效率和总热效率最高。添加Al2O3纳米流体后，光伏电池的平均表面温度约为56.0℃，比裸PV系统低约4.5℃。此外，在所测试的DAS-PV/T系统中，使用在ξNF ~ 0.0004 wt%和ϺF ~ 0.035 kg/s的Al2O3纳米流体，最大总能和火用效率分别为27.54%和26.41%。研究表明，DAS-PV/T系统是独立光伏系统的可行解决方案。

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引用次数: 0

Mass and volume optimization of PCM-based thermal control for microsatellites: A parametric and sensitivity analysis 基于pcm的微卫星热控制质量和体积优化：参数化和灵敏度分析

Next Energy

Pub Date : 2025-10-01 DOI: 10.1016/j.nxener.2025.100457

Burak İzgi

Thermal control is crucial for ensuring the reliable operation and longevity of electronic devices in microsatellites. Phase change materials (PCMs) offer a promising solution for efficient thermal management in such applications. This study provides a systematic framework for optimizing the mass and volume of PCM-based thermal control units by coupling a comparative analysis of various PCM-filler combinations with a robust Sobol sensitivity analysis. The investigation reveals a critical trade-off between mass and volume. Specifically, configurations using PlusICE with graphite, aluminum, or copper fillers yield the most compact (lowest volume) designs, while glycerol paired with the same high-conductivity fillers provides the most lightweight (lowest mass) solutions among the Pareto-optimal configurations. Conversely, using an inefficient filler like carbon steel can increase total system mass by up to 86% and volume by 74% compared to a graphite-enhanced system, highlighting the critical impact of filler selection. Crucially, the sensitivity analysis quantitatively identifies the primary design drivers: The PCM's latent heat of fusion is the most influential parameter for system mass (total sensitivity index, ST = 0.36), while PCM density is the dominant factor for system volume (ST = 0.81). These findings offer clear, actionable guidelines for engineers, enabling a data-driven approach to material selection and the design of efficient thermal management systems for resource-constrained satellite missions.

热控制是保证微卫星电子设备可靠运行和寿命的关键。相变材料（PCMs）为此类应用中的高效热管理提供了一个有前途的解决方案。本研究通过对各种pcm -填料组合的比较分析和稳健的Sobol敏感性分析，为优化基于pcm的热控制单元的质量和体积提供了一个系统的框架。调查揭示了质量和体积之间的关键权衡。具体来说，使用PlusICE与石墨、铝或铜填料的配置产生了最紧凑（最小体积）的设计，而甘油与相同的高导电性填料配对提供了最轻（最低质量）的解决方案。相反，与石墨增强系统相比，使用低效率的填料（如碳钢）可以使系统总质量增加86%，体积增加74%，这突出了填料选择的关键影响。至关重要的是，灵敏度分析定量地确定了主要的设计驱动因素：PCM的聚变潜热是影响系统质量的最重要参数（总灵敏度指数，ST = 0.36），而PCM密度是影响系统体积的主要因素（ST = 0.81）。这些发现为工程师提供了明确的、可操作的指导方针，为资源受限的卫星任务提供了数据驱动的材料选择和高效热管理系统设计方法。

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引用次数: 0

Biohydrogen production and storage from depleted hydrocarbon reservoirs: A review of the strategies to improve biohydrogen production for sustainable energy transition 枯竭油气储层的生物氢生产和储存：促进可持续能源转型的生物氢生产策略综述

Next Energy

Pub Date : 2025-10-01 DOI: 10.1016/j.nxener.2025.100458

David Abutu , Hafizuddin Wan Yussof , Peter Ikechukwu Nwaichi , Chika Umunnawuike , Francis Nyah , Barima Money , Augustine Agi

Hydrocarbon reservoirs are a rich source of carbon hosting various microorganisms. Many of these reservoirs have reached the late stage of their production, however, a sizeable amount of the initial oil in place is still left unrecovered at abandonment. These depleted reservoirs contain a significant amount of organic matter in the form of residual oil which can be exploited for hydrogen production. Therefore, the objective of this research is to provide a comprehensive review of the strategies to improve hydrogen production from depleted hydrocarbon reservoirs for sustainable energy transition. Herein the different pathways of hydrogen production from depleted hydrocarbon reservoirs were discussed. Likewise, the factors affecting hydrogen production were identified and elucidated. Furthermore, strategies to improve hydrogen production were presented. Also, field applications were reviewed. Finally, the challenges to be encountered during hydrogen production that might hinder the successful energy transition have brought to light novel concepts for research which are highlighted herewith proffered technical solutions. Laboratory studies have shown that hydrogen production from hydrocarbon reservoirs can be enhanced using innovative strategies that incorporate bacteria and immobilization, surfactants, nanoparticles, nutrient injection and gene manipulation. Thus, it can be concluded that with proper optimization strategies, biohydrogen production from depleted reservoirs could significantly contribute to meeting energy demands while reducing carbon emissions and repurposing unused hydrocarbon assets.

油气储集层是蕴藏着各种微生物的丰富碳源。这些油藏中有许多已经进入了生产的后期阶段，然而，在废弃时，仍有相当数量的初始石油未被回收。这些枯竭的储层含有大量的剩余油形式的有机物，可以用于制氢。因此，本研究的目的是提供一个全面的策略，以提高枯竭油气藏的氢气生产可持续能源转型。讨论了枯竭油气藏产氢的不同途径。同时，对影响产氢的因素进行了分析。此外，还提出了提高氢气产量的策略。此外，还对现场应用进行了综述。最后，在氢气生产过程中遇到的挑战可能会阻碍成功的能源转型，这些挑战已经为研究带来了新的概念，本文将重点介绍这些概念，并提供技术解决方案。实验室研究表明，通过结合细菌和固定化、表面活性剂、纳米颗粒、营养注入和基因操作等创新策略，可以提高油气储层的产氢量。因此，可以得出结论，通过适当的优化策略，枯竭储层的生物氢生产可以显著地满足能源需求，同时减少碳排放并重新利用未使用的碳氢化合物资产。

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引用次数: 0

Enhancing peak hour photovoltaic performance via a delayed onset melting strategy with spatially distributed PCM 利用空间分布PCM延迟熔化策略提高峰值光伏性能

Next Energy

Pub Date : 2025-10-01 DOI: 10.1016/j.nxener.2025.100469

Ayesha Khan , Shayan Umar , Nadia Shahzad , Adeel Waqas

A photovoltaic (PV) module’s cells only transform the visible and ultraviolet rays of the solar spectrum into electrical energy, while the infrared portion of the spectrum significantly damages silicon-based PV technology. While passive cooling with phase change materials (PCMs) is a promising solution, many applications suffer from premature melting, rendering them ineffective during peak solar hours. This study analyzes the thermal response of a ternary PCM (MA-PA-SA) providing position specific insights into the PCM behavior by embedding thermocouples in 8 sealed aluminum units affixed to a PV module to examine spatial melting under real outdoor conditions while maintaining free convection. The MA-PA-SA mixture characterized using a range of analytical techniques such as DSC, DTC, XRD, and FTIR. Results indicated that edge located blocks exhibited delayed melting, which contributed to improved thermal regulation during peak hours. Thermal imaging confirmed a uniform temperature distribution, revealing a maximum temperature difference of 0.64 °C between regions covered and uncovered by PCM. The PV_PCM module showed a 0.32 V increment, with a maximum average power gain of 4.16%, demonstrating the effectiveness of the delayed-onset melting strategy for peak hour thermal management. These findings offer insights into optimizing PCM placement and melting characteristics for enhancing PV panel performance under outdoor conditions.

光伏（PV）组件的电池只将太阳光谱中的可见光和紫外线转化为电能，而光谱中的红外部分则严重损害了硅基光伏技术。虽然相变材料（pcm）的被动冷却是一个很有前途的解决方案，但许多应用都存在过早熔化的问题，使它们在太阳能高峰时段失效。本研究分析了三元PCM （MA-PA-SA）的热响应，通过将热电偶嵌入光伏模块上的8个密封铝单元中，以在保持自由对流的情况下检查实际室外条件下的空间熔化，从而对PCM的行为提供了特定位置的见解。采用DSC、DTC、XRD和FTIR等一系列分析技术对MA-PA-SA混合物进行了表征。结果表明，位于边缘的块体表现出延迟熔化，这有助于改善高峰时段的热调节。热成像证实了均匀的温度分布，显示PCM覆盖和未覆盖区域之间的最大温差为0.64 °C。PVPCM模块显示了0.32 V的增量，最大平均功率增益为4.16%，证明了延迟开始熔化策略在高峰时段热管理中的有效性。这些发现为优化PCM的放置和熔化特性以提高光伏板在室外条件下的性能提供了见解。

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引用次数: 0

Improving performances of sulfuric acid production process through genetic optimization and exergy analysis 通过遗传优化和火用分析提高硫酸生产工艺性能

Next Energy

Pub Date : 2025-10-01 DOI: 10.1016/j.nxener.2025.100459

Ghazi Mohamed

This work presents a comprehensive study of an existing sulfuric acid production plant, combining modeling, parametric analysis, genetic algorithm optimization, and exergy analysis to maximize its overall performance. The results show that optimizing chemical, energy and exergy performances at the same time is difficult, with initial improvements of 0.21% reduction in total heat exchanger network size, 4.51% increase in turbine work power output, 2.06% increase in thermal power recovery, 0.03% increase in SO₂ conversion rate, and 1.25% reduction in total exergy destruction. However, a new configuration of the heat exchanger network is proposed, which leads to further improvements, including a 4.22% reduction in total heat exchanger network size, 9.28% increase in turbine work power output, 1.85% increase in thermal power recovery, 0.02% increase in SO₂ conversion rate, and 19.13% reduction in exergy destruction.

本文对现有硫酸生产装置进行了综合研究，结合建模、参数分析、遗传算法优化和火用分析，以最大限度地提高其整体性能。结果表明，同时优化化学、能源和火用性能是困难的，初步改善后总换热网络规模减小0.21%，汽轮机功功率输出增加4.51%，热功率回收提高2.06%，SO2转化率提高0.03%，总火用破坏降低1.25%。然而，提出了一种新的换热网络配置，使换热网络总规模减小4.22%，汽轮机功功率输出提高9.28%，热功率回收提高1.85%，SO2转化率提高0.02%，火用破坏降低19.13%。

引用次数: 0

Enhancing heat transport performance of latent heat thermal energy storage systems with discus mesh fins 提高铁饼网翅片潜热蓄热系统的传热性能

Next Energy

Pub Date : 2025-10-01 DOI: 10.1016/j.nxener.2025.100472

Alok Kumar, Arun Kumar

Renewable energies are unable to provide power continuously as a result of their intermittent availability. To deal with this, thermal energy storage (TES) systems can be used utilizing phase change materials. Shell and finned-tube configurations are considered the most effective ways to transport heat and can be used in a wider range of engineering applications. The storage of thermal energy ensures system stability, power reliability, and financial feasibility, as it is a crucial component of numerous domestic and industrial processes in the power generation systems. The performance of a Latent Heat Thermal Energy Storage (LHTES) system is significantly influenced by the fin configuration and phase change materials of the system. Existing design studies have a constrained design space and limitations, so rarely utilized in the LHTES unit. The present study introduced a novel discus-mesh-shaped fin configuration and numerically investigated the heat transfer mechanism in a vertical shell and multi-finned-tube TES unit, aiming to enhance the energy storage rate during the charging process. The transient temperature distribution along the tube length, melting time, and dynamic changes of the liquid fraction in the discus-mesh-shaped fins configuration of the LHTES unit were investigated at variable heat transfer fluid temperature and mass flow rate. It was found that the percentage reduction in melting time was 13.1 and 12.5% for the discus mesh fins unit in comparison to the system without fins in case 1, case 2, case 3, and case 4 of the study, respectively. Also, it has been found that the heat transfer rate is 0.103, 0.11, 0.106 and 0.113 kJ/sec for the system without fins and 0.119, 0.125, 0.121 and 0.13 kJ/sec for the system with discus mesh fins in case 1, case 2, case 3, and case 4 of the study, respectively. The highest PCM temperatures are obtained 8%, 11%, 8%, and 8% higher for the discus mesh fin system in comparison to the system without fins in case-1, case-2, case-3, and case-4 of the study. The PCM temperature rises with an increase in temperature or mass flow rate of HTF. The best performance of the VLHTES system, i.e., the lowest melting time and highest PCM temperature, is obtained for 95°C HTF temperature and 0.0018 kg/sec HTF mass flow rate for the system with the discus-mesh fins.

可再生能源由于其间歇性可用性而无法持续提供电力。为了解决这个问题，热能储存（TES）系统可以使用相变材料。壳体和翅片管结构被认为是最有效的传热方式，可以在更广泛的工程应用中使用。热能的储存确保了系统的稳定性、电力的可靠性和经济可行性，因为它是许多家庭和工业发电系统中至关重要的组成部分。潜热蓄热系统的性能受到系统翅片结构和相变材料的显著影响。现有的设计研究具有有限的设计空间和局限性，因此很少在LHTES单元中使用。本研究引入了一种新型的网状翅片结构，并对垂直壳式多翅片管式TES装置的传热机理进行了数值研究，旨在提高充电过程中的储能率。研究了在变传热流体温度和变质量流量条件下，LHTES装置的瞬态温度沿管长、熔化时间的分布，以及板状网状翅片结构中液体组分的动态变化。研究发现，在案例1、案例2、案例3和案例4中，与没有鳍的系统相比，铁饼网鳍单元的熔化时间减少百分比分别为13.1%和12.5%。结果表明，无翅片系统的换热速率分别为0.103、0.11、0.106和0.113 kJ/sec；在案例1、案例2、案例3和案例4中，有铁饼网翅片系统的换热速率分别为0.119、0.125、0.121和0.13 kJ/sec。在本研究的病例1、病例2、病例3和病例4中，与无鳍系统相比，铁饼网状鳍系统的最高PCM温度分别高出8%、11%、8%和8%。PCM温度随高温射流温度和质量流量的增加而升高。结果表明，在95℃高温热液温度和0.0018 kg/sec高温热液质量流量条件下，该系统的熔融时间最短，PCM温度最高。

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引用次数: 0

Optimized model predictive control with gray-box modeling for PV-based DC/DC converters 基于pv的DC/DC变换器灰盒建模优化模型预测控制

Next Energy

Pub Date : 2025-10-01 DOI: 10.1016/j.nxener.2025.100468

Kerim Karabacak

This study presents an advanced model predictive control (MPC) framework integrated with a gray-box modeling approach for voltage stabilization in photovoltaic (PV) power systems utilizing a DC/DC boost converter. As a continuation of our previous research, where a gray-box model was developed to accurately represent the boost converter dynamics, this work extends the model's application by designing and implementing a predictive controller. The gray-box model, which combines theoretical equations with empirical system identification, serves as the foundation for the proposed MPC, ensuring precise control action under varying environmental and load conditions. Simulation results indicate that the MPC significantly outperforms conventional proportional-integral-derivative controllers, reducing output voltage ripple to near zero and achieving a settling time of 0.0002 s. Experimental validation confirms the controller’s robustness, maintaining stable voltage regulation under dynamic conditions with minimal transient effects. The findings demonstrate the effectiveness of gray-box-based MPC in enhancing the reliability and efficiency of PV power systems, paving the way for future advancements in intelligent control strategies for renewable energy applications.

本研究提出了一种先进的模型预测控制（MPC）框架，结合灰盒建模方法，用于利用DC/DC升压转换器实现光伏（PV）电力系统的电压稳定。作为我们之前研究的延续，我们开发了一个灰盒模型来准确地表示升压变换器的动力学，这项工作通过设计和实现一个预测控制器来扩展模型的应用。灰盒模型将理论方程与经验系统辨识相结合，作为所提出的MPC的基础，确保了在不同环境和负载条件下的精确控制动作。仿真结果表明，MPC显著优于传统的比例-积分-导数控制器，将输出电压纹波降低到接近零，并实现了0.0002 s的稳定时间。实验验证了控制器的鲁棒性，在动态条件下以最小的瞬态效应保持稳定的电压调节。研究结果证明了灰盒MPC在提高光伏发电系统的可靠性和效率方面的有效性，为可再生能源应用的智能控制策略的未来发展铺平了道路。

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引用次数: 0

Optimizing long short-term memory network with genetic and Bayesian optimization algorithms for accurate forecasting 利用遗传和贝叶斯优化算法优化长短期记忆网络，实现准确预测

Next Energy

Pub Date : 2025-10-01 DOI: 10.1016/j.nxener.2025.100425

M. Zulfiqar

Accurate load forecasting is crucial for effective grid management and strategic decision-making in the energy sector, particularly due to the inherent volatility and nonlinearity in load demand. This paper introduces a hybrid forecasting framework that combines advanced feature selection and Bayesian optimization (BO) to tune the long short-term memory (LSTM) model. The feature selection employs a genetic algorithm-based wrapper to systematically eliminate irrelevant and redundant features, enhancing computational efficiency and addressing dimensionality challenges. Unlike conventional approaches, the proposed framework uses BO for LSTM hyperparameter tuning, overcoming manual tuning limitations and reducing the risk of suboptimal performance. Integrating the search capabilities of the genetic algorithm with LSTM’s nonlinear modeling strengths and the optimization precision of BO, the framework achieves superior accuracy, enhanced stability, and accelerated convergence. The proposed model achieves a mean absolute percentage error of 0.5% by iteration 12, converging 20–40% faster than counterpart algorithms. Whereas, the other models exhibit slower convergences with an error of 1.4–1.6%. Statistical analysis validates the performance of the proposed algorithm marking it as a robust solution for dynamic forecasting, with precision and stability for real-world applications.

准确的负荷预测对于有效的电网管理和能源部门的战略决策至关重要，特别是由于负荷需求固有的波动性和非线性。本文介绍了一种结合高级特征选择和贝叶斯优化（BO）的混合预测框架来调整长短期记忆（LSTM）模型。特征选择采用基于遗传算法的包装器，系统地剔除不相关和冗余的特征，提高了计算效率，解决了维数挑战。与传统方法不同，所提出的框架使用BO进行LSTM超参数调优，克服了手动调优的限制，降低了性能次优的风险。该框架将遗传算法的搜索能力、LSTM的非线性建模优势和BO的优化精度相结合，实现了更高的精度、更强的稳定性和更快的收敛速度。经过第12次迭代，该模型的平均绝对百分比误差为0.5%，收敛速度比同类算法快20-40%。而其他模型的收敛速度较慢，误差为1.4-1.6%。统计分析验证了所提出算法的性能，使其成为动态预测的鲁棒解决方案，在实际应用中具有精度和稳定性。

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引用次数: 0

Optimal parameter design for power electronic converters using a probabilistic learning-based stochastic surrogate model 基于概率学习的随机代理模型的电力电子变流器参数优化设计

Next Energy

Pub Date : 2025-10-01 DOI: 10.1016/j.nxener.2025.100464

Akash Mahajan , Shivam Chaturvedi , Srijita Das , Wencong Su , Van-Hai Bui

The selection of optimal design for power electronic converter parameters involves balancing efficiency and thermal constraints to ensure high performance without compromising safety. This study proposes a novel probabilistic-learning-based stochastic surrogate modeling framework, which simultaneously enables uncertainty-aware predictions and feasibility-guided optimization, a combination not commonly explored in prior converter design studies. The approach begins with a neural network classifier that evaluates the feasibility of parameter configurations, effectively filtering out unsafe and/or impractical inputs. Subsequently, a probabilistic prediction model estimates the converter’s efficiency and temperature while quantifying prediction uncertainty, providing both performance insights and reliability metrics. Finally, a heuristic optimization-based model is employed to optimize a multiobjective function that maximizes efficiency while adhering to thermal constraints. The optimization process incorporates penalty terms to discourage solutions that violate practical thresholds, ensuring actionable and realistic recommendations. An advanced heuristic optimization method is used to find the optimal solution and is compared with several well-known search algorithms, including genetic algorithm, particle swarm optimization, simulated annealing, tabu search, and stochastic hill climbing. The results demonstrate significant improvements in predictive accuracy and optimization outcomes, offering a robust solution for advancing power electronics design. The proposed framework is generalizable and can benefit the broader scientific community by serving as a scalable tool for fast, reliable design space exploration across diverse converter architectures and operating scenarios.

电力电子变换器参数优化设计的选择涉及平衡效率和热约束，以确保在不影响安全性的前提下实现高性能。本研究提出了一种新的基于概率学习的随机代理建模框架，该框架同时实现了不确定性感知预测和可行性指导优化，这是先前转换器设计研究中通常未探索的组合。该方法首先使用神经网络分类器来评估参数配置的可行性，有效地过滤掉不安全和/或不切实际的输入。随后，一个概率预测模型估计转换器的效率和温度，同时量化预测的不确定性，提供性能洞察和可靠性指标。最后，采用启发式优化模型对多目标函数进行优化，使其在遵守热约束的情况下实现效率最大化。优化过程包含惩罚条款，以阻止违反实际阈值的解决方案，确保可操作和现实的建议。采用一种先进的启发式优化方法寻找最优解，并与遗传算法、粒子群优化算法、模拟退火算法、禁忌搜索算法和随机爬坡算法进行了比较。结果表明，预测精度和优化结果显着提高，为推进电力电子设计提供了强大的解决方案。该框架具有通用性，可以作为一种可扩展的工具，在不同的转换器架构和操作场景中进行快速、可靠的设计空间探索，从而使更广泛的科学界受益。

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引用次数: 0

A comprehensive review on heat exchangers in crude oil refineries: Classification, degradation mechanisms, and performance optimization strategies 原油炼油厂热交换器的分类、降解机理和性能优化策略综述

Next Energy

Pub Date : 2025-10-01 DOI: 10.1016/j.nxener.2025.100443

Krishnavel Velandi Nadar, Naser Mullayousef, Saleh Naser Meqwar

This review explores the performance, challenges, and advancements of heat exchangers in crude oil refining industries, focusing on Z-type, spiral wound, pillow plate, and printed circuit configurations. These exchangers operate under harsh thermal and chemical conditions, often leading to failures caused by polythionic acid attack, sulfur dioxide (SO₂), hydrogen sulfide (H₂S), and ammonium chloride fouling. Common corrosion mechanisms such as stress corrosion cracking, oxygen-induced degradation, and localized pitting significantly impact exchanger longevity and efficiency. To address these issues, the review highlights enhancement techniques, including the use of copper oxide nanofluids, pinch analysis for process integration, and thermodynamic principles for optimized design. By consolidating insights into failure mechanisms and efficiency improvements, this review acts as a valuable source for refining industry professionals aiming to bring up the resilience and performance of HE in energy-intensive environments.

本文探讨了原油炼制工业中热交换器的性能、挑战和进展，重点介绍了z型、螺旋缠绕、枕板和印刷电路配置。这些交换器在恶劣的热和化学条件下运行，经常导致由聚硫酸侵蚀、二氧化硫（SO₂）、硫化氢（H₂S）和氯化铵污垢引起的故障。常见的腐蚀机制，如应力腐蚀开裂、氧诱导降解和局部点蚀，严重影响换热器的寿命和效率。为了解决这些问题，本文重点介绍了增强技术，包括氧化铜纳米流体的使用、工艺集成的夹点分析以及优化设计的热力学原理。通过整合对故障机制和效率改进的见解，本综述为炼油行业专业人士提供了宝贵的资源，旨在提高HE在能源密集型环境中的弹性和性能。

引用次数: 0