Applied Energy最新文献_第10页

Coordinated optimization of electricity-hydrogen system considering hydrogen supply chain safety in urban traffic network 城市交通网络中考虑氢供应链安全的电氢系统协同优化

IF 11 1区工程技术 Q1 ENERGY & FUELS

Applied Energy

Pub Date : 2026-01-07 DOI: 10.1016/j.apenergy.2025.127326

Cun Zhang , Yifei Wang , Mohammad Shahidehpour , Yujian Ye , Qingshan Xu , Pei Zhang

With the growing penetration of electric and hydrogen vehicles in urban areas, the integration of transportation networks, power distribution systems, and hydrogen supply chains faces increasing operational and safety challenges. This paper presents a coordinated optimization framework that simultaneously considers the urban transportation network (UTN), power distribution network (PDN), hydrogen production system (HPS), and hydrogen supply chain (HSC). A Mixed User Equilibrium–Traffic Assignment Model is first proposed to capture heterogeneous travel behaviors and energy demand patterns of gasoline, electric, and hydrogen vehicles. To enhance realism, the hydrogen supply chain is segmented to explicitly address vehicle routing with time-window and capacity constraints, while full life cycle safety considerations are embedded to mitigate risks in hydrogen production, storage, transportation, and utilization. By integrating these multi-network interactions, the framework achieves a balanced representation of economic costs, renewable energy utilization, and operational safety. Case studies based on the IEEE-33 bus system and a 20-node transportation network demonstrate that the proposed model effectively alleviates local load concentration at integral charging stations, improves the coordination between electricity and hydrogen systems, and reduces overall operating costs. Moreover, incorporating variable traffic flow into the optimization of hydrogen delivery routes enhances system resilience and safety with only marginal cost increases. These results confirm the practical value of the proposed methodology as a robust decision-making tool for sustainable urban energy–transport planning and the safe, large-scale deployment of hydrogen infrastructure.

随着电动汽车和氢燃料汽车在城市地区的日益普及，交通网络、配电系统和氢燃料供应链的整合面临着越来越多的运营和安全挑战。本文提出了一个同时考虑城市交通网络（UTN）、配电网络（PDN）、制氢系统（HPS）和氢供应链（HSC）的协调优化框架。首先提出了混合用户均衡-交通分配模型，以捕捉汽油、电动和氢燃料汽车的异质出行行为和能源需求模式。为了增强现实性，氢气供应链进行了分段，以明确解决具有时间窗口和容量限制的车辆路线问题，同时嵌入了全生命周期安全考虑，以降低氢气生产、储存、运输和利用中的风险。通过整合这些多网络交互，该框架实现了经济成本、可再生能源利用和运行安全的平衡表示。基于IEEE-33总线系统和20节点交通网络的案例研究表明，该模型有效缓解了整体充电站的局部负荷集中，提高了电力和氢系统之间的协调性，降低了总体运营成本。此外，将可变交通流量纳入氢气输送路线的优化可以提高系统的弹性和安全性，且仅增加边际成本。这些结果证实了所提出的方法作为可持续城市能源运输规划和安全、大规模部署氢基础设施的强大决策工具的实用价值。

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引用次数: 0

Calibration of urban building energy model using smart meter data for district peak load prediction 利用智能电表数据进行区域峰值负荷预测的城市建筑能耗模型标定

IF 11 1区工程技术 Q1 ENERGY & FUELS

Applied Energy

Pub Date : 2026-01-07 DOI: 10.1016/j.apenergy.2025.127348

Wanni Zhang, Kaiyu Sun, Han Li, Luis Rodriguez-Garcia, Miguel Heleno, Tianzhen Hong

Urban building energy modeling (UBEM) is a powerful approach to assessing baseline building energy performance and retrofits with new technologies across building stocks in cities. However, the accuracy of UBEM is often constrained by the limited availability of reliable data about building characteristics and operations, such as envelope efficiency levels, HVAC system performance, and end-use load patterns. Existing research has performed UBEM calibration using annual or monthly energy consumption data, which falls short when higher-resolution time series applications are needed, such as peak load prediction for utility operation planning. This study presents a new framework for calibrating building energy models at urban scale using smart meter data, targeting the accurate prediction of summer peak electricity loads to support robust grid planning. The framework first integrates various data sources to enhance baseline input assumptions for building models, and then calibrates the baseline models through a pattern-matching approach. A case study using CityBES and two years of AMI data from over 9000 residential customers in Portland, Oregon, demonstrated the workflow and its effectiveness. The calibrated models achieved a daily peak load mean absolute percentage error of 2.6 % during the heatwave in the calibration year, and 2.0 % in the validation year using another year of AMI data. Using the calibrated models, we analyzed the demand flexibility potential of the district building stock as an application of UBEM calibration. The findings affirm the appropriate use of UBEM for peak electric load forecasting and demand side management at the utility distribution system level.

城市建筑能源建模（UBEM）是一种评估基线建筑能源性能和城市建筑存量新技术改造的强大方法。然而，UBEM的准确性经常受到建筑特征和操作可靠数据可用性的限制，例如围护结构效率水平、HVAC系统性能和最终使用负载模式。现有的研究使用年度或月度能源消耗数据进行UBEM校准，但当需要更高分辨率的时间序列应用时，例如用于公用事业运营规划的峰值负荷预测，这种方法就会有所不足。本研究提出了一个新的框架，用于使用智能电表数据校准城市规模的建筑能源模型，目标是准确预测夏季峰值电力负荷，以支持稳健的电网规划。该框架首先集成了各种数据源，以增强构建模型的基线输入假设，然后通过模式匹配方法校准基线模型。一个使用CityBES和俄勒冈州波特兰市9000多个住宅客户的两年AMI数据的案例研究展示了该工作流程及其有效性。校准后的模型在校准年热浪期间的日峰值负荷平均绝对百分比误差为2.6%，在使用另一年AMI数据的验证年达到2.0%。利用标定后的模型，分析了UBEM标定应用于区域建筑存量的需求灵活性潜力。研究结果肯定了UBEM在公用事业配电系统水平上用于高峰负荷预测和需求侧管理的适当使用。

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引用次数: 0

Improving real-world execution of optimized trading schedules for large-scale battery storage systems through data-driven component parametrization 通过数据驱动的组件参数化改进大规模电池存储系统优化交易时间表的实际执行

IF 11 1区工程技术 Q1 ENERGY & FUELS

Applied Energy

Pub Date : 2026-01-07 DOI: 10.1016/j.apenergy.2025.127340

Mauricio Celi Cortés , Lucas Koltermann , Najet Nsir , Jonas van Ouwerkerk , Dirk Uwe Sauer

Large-scale battery storage systems (BESS) play a key role in ancillary services and are set to contribute significantly to short-term energy trading. However, linear BESS optimization models for energy trading are often based on simplified assumptions, such as fixed component efficiencies. These simplifications fail to capture crucial operational constraints and result in discrepancies between scheduled and actual state of charge (SOC), leading to unfulfilled power delivery and financial penalties. This study addresses this gap by using field data from a real BESS to parametrize linear load-dependent efficiency models for inverters and transformers. Furthermore, the models are validated in the field by assessing their accuracy in calculating power delivery. This includes accounting for component efficiencies and SOC dynamics and comparing the results to a reference test. The data-driven parametrization presented in this study achieved a reduction of 78.2% in unfulfilled energy delivery and a 71.7% reduction in balancing energy costs caused by deviations compared to the reference test. It also significantly decreased the BESS round-trip efficiency deviation between modeled and measured values, with a 4.2 percentage point improvement over the reference test. The linear inverter model achieved a deviation from the actual measured round-trip efficiency of only 0.55 percentage points. These findings highlight the importance of accurate efficiency modeling in minimizing SOC deviations and fulfilling planned schedules in energy trading applications. Finally, this work proposes a methodology that is broadly applicable not only for energy trading with BESS, but also for ancillary services and multi-use operation.

大型电池储能系统（BESS）在辅助服务中发挥着关键作用，并将为短期能源交易做出重大贡献。然而，用于能源交易的线性BESS优化模型通常基于简化的假设，例如固定组件效率。这些简化未能捕捉到关键的操作限制，导致计划和实际充电状态（SOC）之间存在差异，从而导致无法实现电力交付和经济处罚。本研究通过使用来自真实BESS的现场数据来参数化逆变器和变压器的线性负载相关效率模型来解决这一差距。最后，通过对模型计算功率的准确性进行了验证。这包括考虑组件效率和SOC动态，并将结果与参考测试进行比较。与参考测试相比，本研究中提出的数据驱动参数化使未完成的能源交付减少了78.2%，并使偏差导致的平衡能源成本减少了71.7%。它还显著降低了模拟值和测量值之间的BESS往返效率偏差，比参考测试提高了4.2个百分点。线性逆变器模型与实际测量的往返效率偏差仅为0.55个百分点。这些发现强调了在能源交易应用中，准确的效率建模对于最小化SOC偏差和完成计划进度的重要性。最后，这项工作提出了一种广泛适用的方法，不仅适用于与BESS的能源交易，而且适用于辅助服务和多用途操作。

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引用次数: 0

Optimal LOHC facility sizing: Integrating electrolyzer degradation and carbon pricing 优化LOHC设施规模：整合电解槽降解和碳定价

IF 11 1区工程技术 Q1 ENERGY & FUELS

Applied Energy

Pub Date : 2026-01-07 DOI: 10.1016/j.apenergy.2025.127346

Omar Samir , Hany E.Z. Farag , Hatem Zeineldin , Ehab F. El-Saadany

Liquid Organic Hydrogen Carriers (LOHC) offer a practical solution to overcome the storage and transportation challenges hindering large-scale adoption of green hydrogen. By leveraging existing fuel infrastructure, LOHC eliminates the need for high-pressure or cryogenic conditions, significantly reducing logistical complexity and cost. This paper presents an advanced optimal sizing framework for a renewable-powered, grid-connected LOHC generation facility designed to simultaneously meet transportation-sector hydrogen demand and participate in the ancillary services market. The framework integrates a detailed non-linear electrolyzer degradation–recovery model and incorporates stack replacement cost and carbon pricing directly into the optimization to incentivize renewable energy utilization. It also accounts for seasonal variations in ancillary service requirements. Embedding degradation and replacement effects within the optimization improves electrolyzer efficiency management, reducing annual efficiency degradation from 2.1% to 1% and extending stack lifetime from 5 to 10 years. Consequently, the facility achieves a substantially higher net present value of $88.38 million compared with a base case that neglects these effects during optimization. The results highlight the economic and operational advantages of degradation-aware optimization and comprehensive market modeling in the long-term planning of hydrogen infrastructure.

液态有机氢载体（LOHC）为克服阻碍大规模采用绿色氢的储存和运输挑战提供了一种实用的解决方案。通过利用现有的燃料基础设施，LOHC消除了对高压或低温条件的需求，大大降低了物流的复杂性和成本。本文提出了一个先进的可再生能源、并网LOHC发电设施的最优规模框架，旨在同时满足运输部门的氢需求并参与辅助服务市场。该框架集成了详细的非线性电解槽降解-回收模型，并将堆栈重置成本和碳定价直接纳入优化中，以激励可再生能源的利用。它还说明了辅助服务需求的季节性变化。在优化中嵌入降解和替换效果可以改善电解槽效率管理，将年效率下降从2.1%降低到1%，并将电解槽寿命从5年延长到10年。因此，与在优化过程中忽略这些影响的基本情况相比，该设施实现了8,838万美元的高得多的净现值。研究结果表明，降解感知优化和综合市场建模在氢基础设施长期规划中的经济和运营优势。

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引用次数: 0

Prediction driven control of a gas turbine–battery hybrid power plant providing an ancillary service 提供辅助服务的燃气轮机-电池混合电厂的预测驱动控制

IF 11 1区工程技术 Q1 ENERGY & FUELS

Applied Energy

Pub Date : 2026-01-07 DOI: 10.1016/j.apenergy.2025.127341

Petr Stejskal , Přemysl Šůcha , Ondřej Mamula

Due to the increasing use of renewable resources, such as photovoltaic or wind power plants, there is a growing need for ancillary services to stabilize the grid balance. In this paper, we study the control of a real-world hybrid power plant providing ancillary services formed by a set of fast aeroderivative gas turbines (AGTs) and a large battery energy storage system. Our paper serves as a feasibility study, demonstrating how forecasting of automatic frequency restoration reserve (aFRR) activation could improve the economic performance of the hybrid power plant before the idea is implemented in the real control system. The control of the hybrid power plant is formulated as an optimization problem, while machine learning assists in making better unit commitment decisions. We focus on the aFRR ancillary service. Considering the required service response time and the time parameters of AGTs, it is the most challenging ancillary service to provide from a control algorithm design standpoint. We compare our control with the control that does not exploit machine learning and the theoretical bounds the control can achieve. The comparison illustrates the positive impact of machine learning on the operational costs of the power plant. Experiments show that the behavior of the control with machine learning is close to the optimal control assuming the full knowledge of the aFRR power required in the future. Furthermore, there is a noticeably reduced number of AGT starts and reduced gas consumption by 72 %–90 % of the possible savings, related to the optimal value of gas consumption obtained through the optimal control.

由于越来越多地使用可再生资源，如光伏或风力发电厂，越来越需要辅助服务来稳定电网平衡。本文研究了由一组快速航空衍生燃气轮机（agt）和一个大型电池储能系统组成的提供辅助服务的现实世界混合动力发电厂的控制问题。本文作为一项可行性研究，论证了在实际控制系统中实施自动频率恢复储备（aFRR）激活预测之前，如何提高混合动力电厂的经济性能。混合电厂的控制是一个优化问题，而机器学习有助于做出更好的机组承诺决策。我们专注于aFRR的辅助服务。考虑到agt所需的服务响应时间和时间参数，从控制算法设计的角度来看，提供辅助服务是最具挑战性的。我们将我们的控制与不利用机器学习的控制以及控制可以达到的理论界限进行比较。这一对比说明了机器学习对发电厂运营成本的积极影响。实验表明，在充分了解未来所需aFRR功率的情况下，机器学习控制的行为接近最优控制。此外，通过最优控制获得的最优耗气量值显著减少了AGT的启动次数，并将可能节省的耗气量减少了72% - 90%。

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引用次数: 0

Exploring the optimal size of grid-forming energy storage in an off-grid renewable P2H system under multi-timescale energy management 探索多时间尺度能量管理下离网可再生P2H系统成网储能的最优规模

IF 11 1区工程技术 Q1 ENERGY & FUELS

Applied Energy

Pub Date : 2026-01-07 DOI: 10.1016/j.apenergy.2025.127295

Jie Zhu , Yiwei Qiu , Yangjun Zeng , Yi Zhou , Shi Chen , Tianlei Zang , Buxiang Zhou , Zhipeng Yu , Jin Lin

Utility-scale off-grid renewable power-to-hydrogen systems (OReP2HS), typically comprising photovoltaic plants, wind turbines, electrolyzers (ELs), and battery energy storage system (BESS), require at least one component, generally the BESS, to work with grid-forming ability to provide frequency and voltage references and regulate them through transient power support. However, existing designs of OReP2HS based on the energy management strategies (EMSs) with 5-min or hourly resolution fail to capture fast transients and may underestimate the BESS size required to ensure adequate grid-forming ability. This paper first proposes a framework of multi-timescale EMS that covers power system transient behaviors to second-level EL load adjustments and minute-level intra-day scheduling to coordinate renewable power, BESS, and ELs. Then, an iterative search procedure based on high-fidelity simulation (0.04 ms resolution) is employed to determine the cost-effective BESS size that satisfies grid-forming, long-term energy balancing over 8760 hours, and emergency support requirements. Case studies based on a planned OReP2HS project in Inner Mongolia, China, show that the proposed EMS yields a base-case LCOH of 33.212 CNY/kg (4.581 USD/kg), with CAPEX of BESS accounting for 17.83% of total investment. The optimal BESS capacity represents 13.6% of the rated hourly renewable output and shows a yearly degradation of 4.87%. Sensitivity analysis reveals that reducing the electrolytic load adjustment time step from 90 to 5 s and increasing its ramping limit from 1% to 10% rated power per second, decreases the BESS size by 53.57%, and the LCOH decreases to 25.458 CNY/kg (3.511 USD/kg). Considering the cost of designing and manufacturing utility-scale ELs with fast load regulation capability, a load adjustment time step of 5–10 s and a ramping limit of 4–6% rated power per second are recommended to balance profitability and technological feasibility.

公用事业规模的离网可再生能源制氢系统（OReP2HS）通常由光伏电站、风力涡轮机、电解槽（el）和电池储能系统（BESS）组成，需要至少一个组件（通常是BESS）具备并网能力，提供频率和电压参考，并通过瞬态电源支持对其进行调节。然而，现有的基于5分钟或每小时分辨率的能量管理策略（ems）的OReP2HS设计无法捕获快速瞬变，并且可能低估了确保足够的电网形成能力所需的BESS尺寸。本文首先提出了一个涵盖电力系统暂态行为到二级电电网负荷调整和分钟级日内调度以协调可再生能源、BESS和电电网的多时间尺度电电网框架。然后，采用基于高保真度仿真（0.04 ms分辨率）的迭代搜索过程，确定满足网格形成、8760小时以上长期能量平衡和应急保障需求的经济高效的BESS尺寸。基于中国内蒙古OReP2HS计划项目的案例研究表明，拟议的EMS的基本情况LCOH为33.212元/公斤（4.581美元/公斤），BESS的资本支出占总投资的17.83%。最佳BESS容量占额定小时可再生能源发电量的13.6%，年退化率为4.87%。灵敏度分析表明，将电解负荷调整时间步长从90秒减少到5秒，并将其爬坡限从1%额定功率/秒提高到10%额定功率/秒，可使BESS尺寸减小53.57%，LCOH降至25.458元/千克（3.511美元/千克）。考虑到设计和制造具有快速负荷调节能力的公用事业规模el的成本，建议将负荷调节时间步长为5-10秒，爬坡限制为4-6%额定功率/秒，以平衡盈利能力和技术可行性。

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引用次数: 0

Turbulence modeling and machine learning for performance optimization of solar air heaters: State-of-the-art and future directions 太阳能空气加热器性能优化的湍流建模和机器学习：现状和未来方向

IF 11 1区工程技术 Q1 ENERGY & FUELS

Applied Energy

Pub Date : 2026-01-07 DOI: 10.1016/j.apenergy.2025.127321

Mohd Naved, Anupam Dewan

Solar air heaters (SAHs) offer a sustainable and cost-effective solution for low-grade thermal applications such as space heating, crop drying, and industrial preheating, providing a viable alternative to fossil fuel-based systems. However, their overall performance is strongly governed by the turbulent heat transfer mechanisms, particularly when surface roughness elements or jet impingement are used to increase convective heat transfer between air and absorber plate. Accurately predicting and optimizing such turbulent processes remains challenging using conventional computational approaches. Conventional RANS models exhibit computational efficiency, yet they fail to accurately capture flow separation, reattachment, and anisotropy near walls. High-fidelity methods such as LES, DES, and DNS are too expensive for design optimization and real-time control. Recent advancements in machine learning (ML) have provided data-driven and physics-informed frameworks that improve turbulence modeling, expedite CFD solvers, and facilitate predictive optimization through hybrid ML-Physics models. Innovative concepts, such as digital twin and real-time machine learning-based control systems provide adaptive monitoring and optimization of SAHs in dynamic environments, directly enhancing sustainable energy management and supporting the UN Sustainable Development Goals (SDGs). This review exclusively examines the deficiencies in turbulence modeling research, transitioning from RANS-based methods to Hybrid-ML approaches, emphasizing the use of Physics-Informed Neural Networks (PINNs), data-driven closures, and evolutionary algorithms. By emphasizing the cross-disciplinary convergence of fluid mechanics, computational modeling, and artificial intelligence, the integration of turbulence modeling and machine learning represents a significant advancement in solar air heating solutions that are intelligent, energy-efficient, and scalable.

太阳能空气加热器（SAHs）为空间加热、作物干燥和工业预热等低品位热应用提供了可持续和经济的解决方案，为化石燃料系统提供了可行的替代方案。然而，它们的整体性能受到湍流传热机制的强烈控制，特别是当使用表面粗糙度元素或射流撞击来增加空气与吸收板之间的对流换热时。使用传统的计算方法准确预测和优化这种湍流过程仍然具有挑战性。传统的RANS模型具有较高的计算效率，但它们无法准确捕获壁面附近的流动分离、再附着和各向异性。高保真度方法如LES、DES和DNS对于设计优化和实时控制来说过于昂贵。机器学习（ML）的最新进展提供了数据驱动和物理信息框架，改进了湍流建模，加快了CFD求解速度，并通过ML-物理混合模型促进了预测优化。数字孪生和基于实时机器学习的控制系统等创新概念可在动态环境中对SAHs进行自适应监测和优化，直接加强可持续能源管理，支持联合国可持续发展目标（sdg）。本文专门研究了湍流建模研究的不足，从基于ranss的方法过渡到Hybrid-ML方法，强调了物理信息神经网络（pinn）、数据驱动闭包和进化算法的使用。通过强调流体力学、计算建模和人工智能的跨学科融合，湍流建模和机器学习的集成代表了智能、节能和可扩展的太阳能空气加热解决方案的重大进步。

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引用次数: 0

Advanced electrochemical impedance spectroscopy for high-performance solid oxide fuel cells: A critical review 高性能固体氧化物燃料电池的先进电化学阻抗谱研究进展

IF 11 1区工程技术 Q1 ENERGY & FUELS

Applied Energy

Pub Date : 2026-01-06 DOI: 10.1016/j.apenergy.2025.127347

Muhammad Zubair Khan , Mohsin Saleem , Muhammad Bilal Hanif , Jung-Hyuk Koh , Iftikhar Hussain , Urooba Gulshan , Sumaira Latif , Hanfeng Liang , Abdul Ghaffar , Imran Shakir , Bin Lin

Solid oxide fuel cells (SOFCs) are promising high-efficiency electrochemical systems, yet their performance and durability depend on complex, temperature-dependent processes occurring across electrodes, electrolytes, and interfaces. Electrochemical impedance spectroscopy (EIS) has become a central diagnostic tool for resolving these processes and guiding SOFC optimization. This review provides a focused and critical examination of advanced EIS methodologies for SOFCs. After outlining fundamental principles, instrumentation, and data representations, we highlight modern analysis approaches, including KK consistency validation and distribution of relaxation times (DRT) for deconvoluting overlapping polarization processes. We summarize EIS findings across major SOFC components such as LSM-YSZ and MIEC cathodes, Ni-based anodes, oxygen-ion–conducting electrolytes (YSZ, ScSZ, GDC, SDC, LSGM), interconnects, and sealants, emphasizing how impedance features relate to charge-transfer kinetics, mass-transport limitations, grain-boundary effects, and interfacial reactions. Special attention is given to degradation mechanisms, including carbon deposition, Ni coarsening, sulfur poisoning, and electrode/electrolyte delamination, supported by frequency-resolved analysis. Integrating EIS with complementary techniques (XRD, SEM/TEM, spectroscopy) further links microstructural evolution to impedance response. This review establishes a component-resolved framework for interpreting SOFC impedance behavior and outlines future opportunities in operando EIS, data-driven analysis, and stack-level diagnostics for next-generation SOFC systems.

固体氧化物燃料电池（sofc）是一种很有前途的高效电化学系统，但其性能和耐久性取决于电极、电解质和界面之间发生的复杂、温度相关的过程。电化学阻抗谱（EIS）已成为解决这些过程和指导SOFC优化的核心诊断工具。本综述对sofc的先进环境影响评估方法进行了重点和批判性的研究。在概述了基本原理、仪器和数据表示之后，我们重点介绍了现代分析方法，包括用于反卷积重叠极化过程的KK一致性验证和松弛时间分布（DRT）。我们总结了主要SOFC组件（如LSM-YSZ和MIEC阴极、ni基阳极、氧离子导电电解质（YSZ、ScSZ、GDC、SDC、LSGM）、互连和密封剂）的EIS发现，强调了阻抗特征与电荷传递动力学、质量传递限制、晶界效应和界面反应的关系。特别关注降解机制，包括碳沉积，Ni粗化，硫中毒和电极/电解质分层，支持频率分辨分析。将EIS与互补技术（XRD, SEM/TEM，光谱学）相结合，进一步将微观结构演变与阻抗响应联系起来。本综述建立了一个组件解析框架，用于解释SOFC阻抗行为，并概述了下一代SOFC系统在操作EIS、数据驱动分析和堆栈级诊断方面的未来机会。

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引用次数: 0

Application of the Water-Energy Nexus approach to assess the sustainability of air conditioning systems 应用水-能源联系方法评估空调系统的可持续性

IF 11 1区工程技术 Q1 ENERGY & FUELS

Applied Energy

Pub Date : 2026-01-05 DOI: 10.1016/j.apenergy.2025.127336

Federico Santesi , Luca Socci , Andrea Rocchetti , Chiara Arrighi

In the context of global warming and the increasing demand for air conditioning, understanding the sustainability of energy and water systems is crucial. This paper applies the Water-Energy Nexus approach to air conditioning (HVAC) equipment, comparing traditional systems (TS) based on Vapour Compression Refrigeration with Indirect Evaporative Cooling-based systems (IES), in terms of electricity use and total water consumption. The analysis considers 19 cities across different regions, incorporating national energy mixes, climate data, building types, various HVAC configurations and water stress indicators. The results show that IES can offer significant energy savings – up to 43 % - particularly in dry climates and in buildings with high sensible thermal loads. Although IES generally consumes more water than TS, the Water-Energy Nexus framework reveals that the water evaporated during IES operations must be offset by the water saved through reduced electricity generation. A net total water saving is achieved when the Water Consumption Factor (WCF) of the electricity grid reaches values in the range of tens of m³/MWh. This study, by adopting a life cycle-informed perspective, provides a significant contribution to understanding the overall sustainability of air conditioning systems: it offers a deeper insight into the complex trade-offs between energy efficiency and water use within the HVAC sector and the built environment.

在全球变暖和空调需求不断增长的背景下，了解能源和水系统的可持续性至关重要。本文将水-能源Nexus方法应用于空调（HVAC）设备，比较基于蒸汽压缩制冷的传统系统（TS）和基于间接蒸发冷却的系统（IES）的用电量和总用水量。该分析考虑了不同地区的19个城市，综合了各国的能源结构、气候数据、建筑类型、各种暖通空调配置和水资源压力指标。结果表明，IES可以提供显著的节能-高达43% -特别是在干燥气候和高显热负荷的建筑中。虽然IES通常比TS消耗更多的水，但水-能源联系框架显示，IES运行期间蒸发的水必须通过减少发电节省的水来抵消。当电网的耗水系数（WCF）达到几十立方米/兆瓦时的范围时，实现净总节水。本研究采用了生命周期信息视角，为理解空调系统的整体可持续性做出了重大贡献：它对暖通空调行业和建筑环境中能源效率和用水之间的复杂权衡提供了更深入的见解。

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引用次数: 0

Design, techno-economic analysis, and comparative assessment of high-temperature molten salt electric thermal energy storage systems for industrial heat decarbonization in Alberta, Canada 加拿大艾伯塔省用于工业热脱碳的高温熔盐电热能储存系统的设计、技术经济分析和比较评估

IF 11 1区工程技术 Q1 ENERGY & FUELS

Applied Energy

Pub Date : 2026-01-05 DOI: 10.1016/j.apenergy.2025.127301

Abdul Saboor , Muhammad Taha Naveed , Muhammad Taha Manzoor

Alberta’s industrial sector requires substantial high-temperature process heat, yet its extreme ambient temperatures, which can reach −40

^{\circ}

C, present challenges for thermal energy storage deployment. This study evaluates the techno-economic feasibility of electric thermal energy storage systems using binary chloride salts (50 wt% NaCl: 50 wt% KCl) contained in engineered concrete for delivering industrial heat at approximately 700

^{\circ}

C. A single-tank configuration with an embedded air to salt heat exchanger is operated under different thermal charging configurations, including electric heating powered by solar photovoltaic farms, wind farms, or the grid, and beam-down volumetrically absorbing concentrated solar thermal systems. Nine scenarios were evaluated under four carbon pricing trajectories over a 30-year project lifetime: CP0 (carbon price frozen at $170/tCO₂e after 2030), CP15 (continued rise of $15/tCO₂e annually), CP30 (accelerated increase of $30/tCO₂e annually), and CP45 (high-stringency case with $45/tCO₂e annual increases). Key performance indicators include round-trip efficiency, levelized cost of heat, land footprint, and use-phase emissions. Results are compared against a natural gas boiler as the reference case. Under continued carbon price escalation of $15/tCO₂e annually (CP15), this study highlights the effectiveness of an advanced hybrid concentrated solar thermal system with electric thermal energy storage (CST E-TES), as it achieves high round-trip efficiencies of up to 90 %, the lowest levelized cost of heat among renewable options at 19 $/MWht and 83 % lower emissions than natural gas.

阿尔伯塔省的工业部门需要大量的高温加工热量，但其极端的环境温度可达- 40°C，这对热能储存的部署提出了挑战。本研究评估在工程混凝土中使用二氯盐（50 wt% NaCl: 50 wt% KCl）在约700°C时输送工业热量的电热储能系统的技术经济可行性。内置空气-盐热交换器的单罐配置在不同的热充电配置下运行，包括由太阳能光伏发电场、风力发电场或电网供电的电加热，以及向下体积吸收的集中太阳能热系统。在30年的项目生命周期内，在四种碳定价轨迹下评估了9种情景：CP0（2030年后碳价格冻结在170美元/吨二氧化碳当量）、CP15（每年继续上涨15美元/吨二氧化碳当量）、CP30（每年加速上涨30美元/吨二氧化碳当量）和CP45（每年上涨45美元/吨二氧化碳当量的高严格情况）。关键绩效指标包括往返效率、热能平准化成本、土地足迹和使用阶段排放。并与某天然气锅炉作为参考案例进行了比较。在每年15美元/吨二氧化碳当量（CP15）的碳价格持续上涨的情况下，本研究强调了带有电热能储存（CST E-TES）的先进混合聚光太阳能热系统的有效性，因为它实现了高达90%的高双向效率，在可再生能源选择中最低的热能平均成本为19美元/兆瓦时，排放量比天然气低83%。

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