Applied Energy最新文献_第9页

Recent progress in MXene-based electrode materials for aluminum-ion battery: A comprehensive review 铝离子电池用mxene基电极材料研究进展综述

IF 11 1区工程技术 Q1 ENERGY & FUELS

Applied Energy

Pub Date : 2025-12-02 DOI: 10.1016/j.apenergy.2025.127186

Mohan P. Thorat , Karanpal Singh , Abdussalam Usmani , Amir Khan , Bilawal Khan , H. K Shahzad , Bhargav Akkinepally , Iftikhar Hussain

Aluminum-ion batteries (AIBs) represent a promising frontier in energy storage technology, offering advantages in terms of cost-effectiveness, safety, and environmental impact. One drawback is the hindrance in reversible intercalation and rapid transportation of Aluminum ions due to the strong electrostatic attractions between highly charged Al³⁺ and the electrode. However, the advancement in aluminum-ion based batteries is, therefore, restricted by the lack of adequate materials for electrode that can reversibly intercalate Al³⁺ and provide long cycling stability. MXenes, emerging 2D materials, possess significant promising applications for energy storage as they offer outstanding electrical conductivity, extensive surface area, along with robust mechanical properties. In the present article, we provide the progress and achievements of MXene-based electrodes in AIB. This review explores the crucial role of MXenes in combination with a variety of active materials for cathodes, including both inorganic and organic, in addition to metallic anodes. We also provide an overview of the strategies used to design composite structures for electrode applications. By offering a comprehensive view of MXenes as multifunctional material in aluminum-ion batteries, this work intent to provide valuable findings for future research and innovation in the field.

铝离子电池（AIBs）代表了能源存储技术的一个有前途的前沿，在成本效益、安全性和环境影响方面具有优势。一个缺点是由于高电荷Al3+和电极之间的强静电吸引，阻碍了铝离子的可逆插入和快速运输。然而，由于缺乏足够的电极材料，铝离子电池的发展受到限制，这种材料可以可逆地插入Al3+并提供长周期稳定性。MXenes是一种新兴的2D材料，由于具有出色的导电性、广泛的表面积以及强大的机械性能，因此在储能方面具有重要的应用前景。在本文中，我们介绍了基于mxene的电极在AIB中的进展和成就。本文探讨了MXenes与各种活性材料（包括无机和有机阳极）以及金属阳极结合在一起的关键作用。我们还概述了用于设计电极应用的复合结构的策略。通过对MXenes作为铝离子电池多功能材料的全面研究，本工作旨在为该领域未来的研究和创新提供有价值的发现。

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引用次数: 0

Performance benchmark of thermal energy storage concepts in concentrating solar power 聚光太阳能发电中热能存储概念的性能基准

IF 11 1区工程技术 Q1 ENERGY & FUELS

Applied Energy

Pub Date : 2025-12-02 DOI: 10.1016/j.apenergy.2025.127183

Pablo D. Tagle-Salazar , Luisa F. Cabeza , Cristina Prieto

Thermal energy storage (TES) plays a critical role in enhancing the efficiency and dispatchability of concentrating solar power (CSP) plants by mitigating solar energy intermittency. Although molten salts remain the dominant TES solution, alternative systems such as solid-state and latent heat storage offer promising advantages. This study analyses the performance impact of different TES technologies—two-tank molten salt, concrete-based storage, and phase change materials (PCMs)—when integrated into CSP systems. By comparing key performance indicators under identical operating conditions, this study provides insights into the suitability of each TES technology for CSP plant operations. The results highlight the trade-offs between energy yield, efficiency, and footprint. All three concepts demonstrated comparable performance at both the system and TES levels, with disparities of less than 3 %. The advantage of PCM lies in its substantial volume reduction of approximately 27 % compared to molten salt, whereas concrete TES achieves similar outcomes with a slight increase in volume relative to molten salt TES volume.

热储能（TES）通过缓解太阳能的间歇性，在提高聚光太阳能发电（CSP）电厂的效率和可调度性方面起着至关重要的作用。虽然熔融盐仍然是主要的TES解决方案，但固态和潜热储存等替代系统也具有很好的优势。本研究分析了集成到CSP系统中的不同TES技术——双罐熔盐、混凝土基存储和相变材料（pcm）——对性能的影响。通过比较相同运行条件下的关键性能指标，本研究提供了对CSP电厂运行的每种TES技术适用性的见解。研究结果强调了能源产量、效率和碳足迹之间的权衡。这三个概念在系统和TES水平上都表现出可比性，差异小于3%。PCM的优势在于，与熔盐相比，PCM的体积减少了约27%，而混凝土TES的体积相对于熔盐TES的体积略有增加，也达到了类似的效果。

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引用次数: 0

High-speed REPTA algorithm for performance cost optimization in data centers considering workload delay tolerances 考虑工作负载延迟容限的数据中心性能成本优化的高速REPTA算法

IF 11 1区工程技术 Q1 ENERGY & FUELS

Applied Energy

Pub Date : 2025-12-01 DOI: 10.1016/j.apenergy.2025.127156

Lingfang Yang , Mohammad Shahidehpour , Xianqing Chen , Chongyu Wang , Xiaolun Fang , Qiang Yang

The rapid development of data centers (DTCs) has led to substantially increased energy consumption and electricity bills. Thus, this paper aims to minimize the performance costs of geographically distributed DTCs. Firstly, an integrated electricity-heat system model for geographically-distributed DTCs is developed considering renewable energy sources (RESs) and waste heat recovery. Particularly, the differences of delay tolerances in computational tasks are fully considered in the developed model, which aligns with real-world DTCs. Further, to cope with the large-scale decision variables caused by the delay tolerance model, a RES and electricity price aware task assignment (REPTA) algorithm based three-stage energy dispatch strategy is presented, which accelerates the decision-making process. In stage I, an electricity-heat coordinated optimization (EHCO) model is constructed, which preliminarily determines the scheduling plan with the exclusion of delay-tolerant tasks. In stage II, the REPTA algorithm is designed to allocate delay-tolerant tasks according to the complementarities of electricity prices and RESs. Then in stage III, incorporating the task allocation results of stage II, the EHCO model is solved again to obtain the ultimate energy dispatch decisions. Finally, the proposed solution is assessed through comparative experiments based on the data from Parallel Workloads Archive, and the numerical results confirm its effectiveness in both environmental and economic indicators.

随着数据中心（dtc）的快速发展，能源消耗和电费也大幅增加。因此，本文旨在最大限度地降低地理分布的dtc的性能成本。首先，考虑可再生能源和余热回收，建立了地理分布的dtc电-热集成系统模型。特别是，所建立的模型充分考虑了计算任务的延迟容限差异，与实际的延迟容限保持一致。进一步，针对延迟容限模型带来的大规模决策变量，提出了一种基于RES和电价感知任务分配（REPTA）算法的三阶段能源调度策略，加快了决策过程。在第一阶段，构建了热电协调优化（EHCO）模型，初步确定了排除容忍延迟任务的调度方案。在第二阶段，设计REPTA算法，根据电价与RESs的互补性分配容延迟任务。然后在第三阶段，结合第二阶段的任务分配结果，重新求解EHCO模型，得到最终的能源调度决策。最后，通过基于Parallel workload Archive数据的对比实验对该方案进行了评估，数值结果证实了该方案在环境和经济指标上的有效性。

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引用次数: 0

Mapping cost-effective hydrogen production based on renewable resource potential and techno-economic analysis: a case study 基于可再生资源潜力和技术经济分析绘制具有成本效益的氢气生产：一个案例研究

IF 11 1区工程技术 Q1 ENERGY & FUELS

Applied Energy

Pub Date : 2025-12-01 DOI: 10.1016/j.apenergy.2025.127160

Fatemeh Rouzbahani , Mohammad Amin Vaziri Rad , Danyal Aghajani

Finding the optimal location for constructing a renewable-powered electrolyzer plant is fundamental to achieving cost-effective green hydrogen production. However, studies that utilize Geographical Information Systems (GIS) for this purpose commonly rely on resource availability and proximity to national infrastructure as the main techno-economic criteria. These factors, however, may not fully capture the direct impact of renewable resources on techno-economic performance. To address this gap, this study proposes a four-stage mapping approach. In the first stage, a renewable potential map determines the frequency and combination of resources across different geographical coordinates. In the second stage, techno-economic optimization is performed for each level of renewable resource availability. In the third stage, the results are used to generate new map layers in ArcGIS, including the levelized cost of hydrogen (LCOH), plant net present cost (NPC), and electrolyzer capacity factor (CF). Finally, all economic, technical, environmental, and accessibility layers are integrated to identify the optimal location for renewable-powered hydrogen production facilities. The Analytic Network Process (ANP) weighting revealed that NPC, CF, LCOH, distance from power grid, and proximity to potential end users were the most critical criteria, each with 10–12 % importance in the final mapping. The results showed that 10.3 % of Tehran province is classified as completely appropriate and approximately 23 % as appropriate for green hydrogen production. The estimated LCOH ranges from 3.6 to 5.1 $/kg, with an electrolyzer capacity factor of 33–35 % in solar-based areas and 45–61 % in areas utilizing a combination of solar and wind power.

找到建设可再生能源电解槽厂的最佳地点是实现经济高效的绿色制氢的基础。然而，为此目的利用地理信息系统（GIS）的研究通常依赖于资源的可用性和是否接近国家基础设施作为主要的技术经济标准。然而，这些因素可能不能完全反映可再生资源对技术经济绩效的直接影响。为了解决这一差距，本研究提出了一个四阶段的映射方法。在第一阶段，可再生潜力图确定跨不同地理坐标的资源的频率和组合。在第二阶段，对可再生资源的每个水平进行技术经济优化。在第三阶段，将结果用于在ArcGIS中生成新的地图层，包括氢的平化成本（LCOH）、工厂净现值成本（NPC）和电解槽容量因子（CF）。最后，综合所有经济、技术、环境和可达性层面，确定可再生能源制氢设施的最佳位置。分析网络过程（ANP）权重显示，NPC、CF、LCOH、与电网的距离以及与潜在最终用户的接近程度是最关键的标准，每个标准在最终映射中的重要性为10 - 12%。结果表明，德黑兰省10.3%的地区完全适合绿色制氢，约23%的地区适合绿色制氢。估计的LCOH范围为3.6至5.1美元/公斤，在太阳能地区，电解槽容量系数为33 - 35%，在太阳能和风能结合使用的地区，电解槽容量系数为45 - 61%。

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引用次数: 0

Control-oriented modeling and dynamic energy balance control strategy of steam generation system in coal-fired power plants 燃煤电厂蒸汽发生系统面向控制建模及动态能量平衡控制策略

IF 11 1区工程技术 Q1 ENERGY & FUELS

Applied Energy

Pub Date : 2025-12-01 DOI: 10.1016/j.apenergy.2025.127172

Chen Zhu , Guangming Zhang , Keyan Zhu , Qinghua Wang , Jinliang Xu , Yuguang Niu , Jizhen Liu

The integration of molten salt energy storage systems is an effective approach to enhancing the load-following capability of coal-fired power plants (CFPPs). This study proposes an optimized control strategy for molten salt steam generation systems (SGS) that integrates energy balance and multivariable coordinated control. First, a dynamic SGS model tailored for control applications is developed, and its transient response characteristics are analyzed. Second, a direct energy balance (DEB) mechanism is established to correlate turbine load demand, molten salt heat release rate, and system thermal storage variations, achieving dynamic source-load energy balance. Nonlinear model predictive control (NMPC) is introduced to solve the multivariate coupling and nonlinear problems existing in SGS. Finally, the NMPC&DEB multi-loop collaborative control framework is established. Simulation results demonstrate that under continuous ramp-down load conditions of 1.5 %, 3 %, and 6 % Pe/min, the NMPC&DEB strategy reduces the mean absolute error of steam mass flow rate by 76.1 %, 65.5 %, and 9.9 %, respectively, compared to the proportion-integration-differentiation, DEB, and NMPC approaches. Under step load disturbances, the proposed control framework significantly improves both the stability and rapidity of system response. In scenarios with molten salt temperature disturbances, the maximum dynamic deviation is 1.08 t/h, representing reductions of 88.1 %, 80.0 %, and 63.5 % relative to the three strategies. Therefore, the NMPC&DEB strategy enhances the control performance and disturbance rejection capability of the SGS.

熔盐储能系统集成是提高燃煤电厂负荷跟随能力的有效途径。提出了一种能量平衡与多变量协调控制相结合的熔盐蒸汽发生系统优化控制策略。首先，建立了适合控制应用的动态SGS模型，并分析了其瞬态响应特性。其次，建立直接能量平衡（DEB）机制，将汽轮机负荷需求、熔盐放热率和系统蓄热变化联系起来，实现源负荷动态能量平衡。引入非线性模型预测控制（NMPC）来解决自动控制系统中存在的多变量耦合和非线性问题。最后，建立了NMPC&；DEB多环协同控制框架。仿真结果表明，在1.5%、3%和6% Pe/min的连续下降负荷条件下，与比例-积分-微分、DEB和NMPC方法相比，NMPC&；DEB策略将蒸汽质量流量的平均绝对误差分别降低了76.1%、65.5%和9.9%。在阶跃负载扰动下，该控制框架显著提高了系统响应的稳定性和快速性。在存在熔盐温度扰动的情况下，最大动态偏差为1.08 t/h，相对于三种策略分别降低了88.1%、80.0%和63.5%。因此，NMPC&；DEB策略提高了SGS的控制性能和抗扰能力。

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引用次数: 0

Recent progress of chemical looping technology for waste plastic conversion 废塑料转化化学环技术研究进展

IF 11 1区工程技术 Q1 ENERGY & FUELS

Applied Energy

Pub Date : 2025-12-01 DOI: 10.1016/j.apenergy.2025.127180

Yunkun Zhao, Guangxuan Chen, Yibo Guo, Shuting Min, Rongjing Wang, Xiaolong Xu, Jing Huang, Yang Hu, Zhiquan Hu, Xun Wang

Chemical looping technology (CLT) has emerged as a promising solution for converting waste plastics into valuable heat, syngas and H₂ while enabling efficient carbon capture. This technology divides chemical reactions into multiple steps, sequentially in one reactor or simultaneously in independent reactors, offering enhanced control and efficiency. This article comprehensively reviews various CLT, including chemical looping combustion, chemical looping gasification, chemical looping reforming, chemical looping hydrogen generation and their derivative technologies, with a focus on their unique advantages for value-added applications in waste plastics. These processes demonstrate high efficiency in syngas production, CO₂ capture and H₂ generation while maintaining low energy consumption. As the cornerstone in CLT, oxygen carriers have evolved from monometallic oxides to polymetallic oxides designs, leveraging synergistic effects to enhance resistance to carbon deposition and sintering, improve pollutant removal capabilities (such as chlorine capture) and ensure long-term cycling stability. While CLT of waste plastics shows great potential at the laboratory scale, pilot-scale studies remain limited and require further focused attention. As a key pathway for waste plastic valorization and carbon neutrality, CLT not only offers an innovative solution for global plastic pollution management but also drives the deep integration of circular economy principles with clean energy technologies, providing important new avenues for green sustainable development.

化学环技术（CLT）已经成为一种很有前途的解决方案，可以将废塑料转化为有价值的热量、合成气和氢气，同时实现高效的碳捕获。该技术将化学反应分为多个步骤，依次在一个反应器中进行，或同时在独立的反应器中进行，从而提高了控制和效率。本文全面综述了化学环燃烧、化学环气化、化学环重整、化学环制氢及其衍生技术，重点介绍了它们在废塑料增值应用方面的独特优势。这些工艺在合成气生产、二氧化碳捕获和氢气生成方面表现出高效率，同时保持低能耗。作为CLT的基石，氧载体已经从单金属氧化物发展到多金属氧化物设计，利用协同效应增强抗积碳和烧结能力，提高污染物去除能力（如氯捕获），并确保长期循环稳定性。虽然废塑料的CLT在实验室规模上显示出巨大的潜力，但中试规模的研究仍然有限，需要进一步关注。CLT作为废塑料增值和碳中和的关键途径，不仅为全球塑料污染治理提供了创新的解决方案，而且推动了循环经济原则与清洁能源技术的深度融合，为绿色可持续发展提供了重要的新途径。

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引用次数: 0

Transformer-based model predictive control with anode potential awareness for online fast charging optimization of lithium-ion batteries 基于变压器的阳极电位感知模型预测控制的锂离子电池在线快速充电优化

IF 11 1区工程技术 Q1 ENERGY & FUELS

Applied Energy

Pub Date : 2025-12-01 DOI: 10.1016/j.apenergy.2025.127158

Zixian Zhuang , Hongxu Chen , Ying Chen , Weiling Luan , Haofeng Chen , Xiaoyan Ji

Achieving efficient and safe charging while effectively mitigating degradation induced by lithium plating is crucial for fully unleashing the performance and extending the lifespan of lithium-ion batteries. This study proposes a fast charging optimization control method that integrates anode potential awareness with a Transformer-based model predictive control (MPC) framework to address the complex multi-physics coupling constraints during fast charging. To enable multi-step prediction of the anode potential, 30 candidate features are initially constructed based on measurable parameters and their temporal derivatives. A robust feature set is then established by selecting 5 most discriminative input variables through correlation analysis and the Null Importance method. Subsequently, a Transformer-based state predictor is developed to perform accurate joint prediction of voltage, temperature, and anode potential under typical conditions, including dynamic loads and constant current charging. The root mean square errors (RMSE) for voltage, temperature, and anode potential predictions are 11.62 mV, 0.251 °C, and 3.67 mV, respectively. Building on the prediction model, an MPC framework is further developed using the particle swarm optimization (PSO) algorithm. This framework enables real-time optimization of the charging current trajectory under multi-dimensional safety constraints, including voltage upper limit, temperature upper limit, and anode potential lower limit. Results demonstrate that the proposed method can achieve a closed-loop integration of accurate state prediction and optimal control during charging, effectively suppressing constraint violations of key variables while balancing charging efficiency, cycle life, and safety. The method exhibits strong engineering adaptability and promising scalability for practical applications.

实现高效、安全的充电，同时有效减轻锂镀层引起的电池退化，对于充分释放锂离子电池的性能和延长锂离子电池的使用寿命至关重要。为了解决快速充电过程中复杂的多物理场耦合约束问题，提出了一种将阳极电位感知与基于变压器的模型预测控制（MPC）框架相结合的快速充电优化控制方法。为了实现对阳极电位的多步预测，首先基于可测量参数及其时间导数构建了30个候选特征。然后通过相关分析和Null Importance方法选择5个最具判别性的输入变量，建立鲁棒特征集。随后，开发了基于变压器的状态预测器，在动态负载和恒流充电等典型条件下对电压、温度和阳极电位进行准确的联合预测。电压、温度和阳极电位预测的均方根误差（RMSE）分别为11.62 mV、0.251°C和3.67 mV。在预测模型的基础上，利用粒子群优化（PSO）算法进一步开发了MPC框架。该框架能够在电压上限、温度上限和阳极电位下限等多维安全约束条件下实时优化充电电流轨迹。结果表明，该方法能够实现充电过程中精确状态预测与最优控制的闭环集成，在平衡充电效率、循环寿命和安全性的同时，有效抑制关键变量的约束违反。该方法具有较强的工程适应性和较好的可扩展性。

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引用次数: 0

Optimal sizing of renewable hybrid power plants considering component reliability as a multi-discipline optimization under uncertainty 不确定条件下考虑组件可靠性的可再生混合动力电站优化规模问题

IF 11 1区工程技术 Q1 ENERGY & FUELS

Applied Energy

Pub Date : 2025-12-01 DOI: 10.1016/j.apenergy.2025.127138

Rujie Zhu, Juan Pablo Murcia Leon, Mikkel Friis-Møller, Megha Gupta, Kaushik Das

The sizing of grid-connected hybrid power plants (HPPs), integrating wind, photovoltaics (PV), and battery storage, is critical for optimizing economic performance. Traditional sizing approaches typically assume ideal component availability, neglecting failure and repair processes, which can lead to overestimated financial projections. This paper develops a stochastic reliability model to simulate component availability time series over the plant’s lifetime, considering wind turbines, PV strings, PV inverters, battery systems, and transformers. The sizing problem is formulated as a multi-disciplinary optimization under uncertainty, incorporating 13 design variables, including wind turbine rated power, number of turbines, installation density, PV capacity, inverter size etc. The optimization aims to maximize the weighted average of expected net present value (NPV) over capital expenditure (CAPEX) and the conditional value-at-risk of NPV over CAPEX. The proposed methodology is applied to case studies at a Danish and a French site with diverse weather conditions to compare deterministic and stochastic sizing approaches. The out-of-sample experiments demonstrate that incorporating component reliability in the sizing process increases the mean NPV-to-CAPEX ratio, evaluated over 100 reliability scenarios, by 2.5 % and 2.8 % for the two sites, respectively, indicating enhanced investment efficiency.

结合风能、光伏和电池存储的并网混合电厂（HPPs）的规模对于优化经济绩效至关重要。传统的评估方法通常假设理想的组件可用性，忽略了故障和维修过程，这可能导致高估财务预测。本文开发了一个随机可靠性模型来模拟电厂寿命期间组件的可用性时间序列，考虑了风力涡轮机、光伏发电机组、光伏逆变器、电池系统和变压器。该优化问题是一个不确定条件下的多学科优化问题，包含13个设计变量，包括风力机额定功率、风力机数量、安装密度、光伏容量、逆变器尺寸等。优化的目的是最大化预期净现值（NPV）除以资本支出（CAPEX）的加权平均值和NPV除以资本支出的条件风险值。所提出的方法应用于丹麦和法国不同天气条件下的案例研究，以比较确定性和随机规模方法。样本外实验表明，在评估100种可靠性情景时，将组件可靠性纳入规模过程可使两个站点的平均净现值与资本支出比率分别提高2.5%和2.8%，表明投资效率得到了提高。

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引用次数: 0

Resilience enhancement of a distribution system via electric-vehicle garages 通过电动汽车车库提高配电系统的弹性

IF 11 1区工程技术 Q1 ENERGY & FUELS

Applied Energy

Pub Date : 2025-11-29 DOI: 10.1016/j.apenergy.2025.127131

Myung Bae Koh , Antonio J. Conejo , Xuan Wu

We analyze how an electric-vehicle aggregator that manages a number of electric-vehicle garages and is in partnership with a distribution system operator can increase the resilience of the distribution system in which it operates. The study is intended to ensure a resilient operation of the distribution system while satisfying the travel demands of electric-vehicle drivers by identifying the optimal energy contents of the electric-vehicle garages and their operation. In case of a contingency, such energy allows partial supply of the load. For our purposes, an electric-vehicle garage is a distributed energy storage system whose power and energy capacities change over time. Our study relies on a stochastic programming model that represents branch-outage contingencies and substation capacity reduction contingencies in the distribution system. We comprehensively analyze two realistic case studies to illustrate the relevance of the proposed model to improve resilience. The contribution of our paper relies on a convex AC representation of the distribution network with electric-vehicle garages, a detailed stochastic programming model, a focus on distribution system resilience, and a comprehensive analysis using electric-vehicle garages for resilience.

我们分析了一家管理多个电动汽车车库并与分销系统运营商合作的电动汽车集成商如何提高其运营的分销系统的弹性。该研究旨在通过确定电动汽车车库及其运行的最佳能量含量，确保配电系统的弹性运行，同时满足电动汽车驾驶员的出行需求。在意外情况下，这种能量允许部分供应负荷。就我们的目的而言，电动汽车车库是一个分布式能量存储系统，其功率和能量容量随时间而变化。我们的研究依赖于一个随机规划模型来表示配电系统中分支停电和变电站容量减少的偶然性。我们全面分析了两个现实的案例研究，以说明所提出的模型与提高弹性的相关性。本文的贡献依赖于带有电动汽车车库的配电网络的凸交流表示，详细的随机规划模型，对配电系统弹性的关注，以及使用电动汽车车库的弹性的综合分析。

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引用次数: 0

Cavern thermal energy storage: State of play and prospects 洞穴热能储存：现状与展望

IF 11 1区工程技术 Q1 ENERGY & FUELS

Applied Energy

Pub Date : 2025-11-29 DOI: 10.1016/j.apenergy.2025.127141

Dominik Müller , Christoph Bott , Markku Hagström , Peter Bayer

Cavern thermal energy storage (CTES) is a technological variant of underground thermal energy storage that relies on flooding of subsurface cavities or tunnels for long-term heat storage. Such installations are crucial, particularly for conserving excessive solar and waste heat from the warm season to be used during the cold season of the year. This review provides, for the first time, a comprehensive synopsis of different types of these large installations, which are most prominent in Scandinavian countries. It is revealed that CTES can be distinguished between those that are pre-designed and those that are re-engineered former infrastructures (commonly oil reserves), whereas single and multi-cavern systems exist. Based on existing and planned CTES implementations, characteristic design parameters are identified, and a structured insight into common criteria for an optimal layout is provided. While it is most cost-efficient to reuse existing facilities and apply storage volumes of far more than 100,000 m³, a perfect geometric layout needs to account for controlled thermal stratification, attuned aspect ratio, and optimal area-to-volume ratio. One crucial factor is the long-term geo-mechanical stability of the ambient rock mass, which ideally represents compact crystalline rock with negligible groundwater flow. Our study summarizes the findings of existing installations that may serve as blueprints for planning, constructing, operating, and monitoring new CTES, including hot water and pressurized storage concepts.

洞穴蓄热（CTES）是地下蓄热的一种技术变体，依靠地下空腔或隧道的洪水进行长期蓄热。这种装置是至关重要的，特别是为了保存温暖季节多余的太阳能和废热，以便在一年中的寒冷季节使用。这篇综述首次提供了不同类型的大型装置的综合概述，这些装置在斯堪的纳维亚国家最为突出。研究表明，CTES可以区分为预先设计的和重新设计的前基础设施（通常是石油储量），同时存在单洞室和多洞室系统。基于现有的和计划中的CTES实现，确定了特征设计参数，并提供了对最佳布局的通用标准的结构化洞察。虽然重新利用现有设施和应用远远超过100,000立方米的存储容量是最具成本效益的，但完美的几何布局需要考虑到可控的热分层、调节的宽高比和最佳的面积体积比。其中一个关键因素是环境岩体的长期地质力学稳定性，它理想地代表了致密的结晶岩石，地下水流量可以忽略不计。我们的研究总结了现有设施的发现，这些发现可以作为规划、建设、运营和监测新的CTES的蓝图，包括热水和加压存储概念。

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引用次数: 0