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A comprehensive survey of distributed optimization methods and technological enablers for sustainable energy communities 可持续能源社区分布式优化方法和技术推动者的综合调查

IF 9.4 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2026-01-08 DOI: 10.1016/j.energy.2026.139983

Kivanc Basaran , Pierluigi Siano , Messlem Abdelkader , Alper Kağan Candan , Mohsen Mohammadpour Kivi , Nazmus Sakib , Yılmaz Seryar Arikuşu , George Cristian Lazaroiu

Sustainable energy communities (ECs) are rapidly expanding in scale and heterogeneity, making fully centralized energy management increasingly impractical due to computational burden and privacy concerns. In this context, this review synthesizes distributed optimization (DO) as a practical management paradigm for ECs, identifies key application areas (demand response, distributed generation and storage management, and microgrid or smart-grid integration) and profiles scalability, privacy, and resilience characteristics. The survey follows a systematic protocol: records are sourced from Scopus, filtered with iteratively refined keyword sets, and screened following a PRISMA flow. Key technological enablers, such as blockchain/distributed ledgers, artificial intelligence, and game-theoretic constructs, are assessed and analyzed for how they support secure data exchange, real-time coordination, and incentive compatibility across multi-agent energy networks. The analysis highlights persistent challenges for DO at EC scale, including convergence under heterogeneity, time-varying conditions, communication delays, cybersecurity and privacy guarantees, while recent advances (e.g., ADMM) partially mitigate these issues without sacrificing local autonomy. Across representative studies, DO achieves near-centralized optimality with 0.0029 % gap. Overall, we present an integrative framework that maps DO families to EC use cases and outlines research directions toward robust, privacy-preserving, and scalable EC optimization.

可持续能源社区（ec）的规模和异质性正在迅速扩大，由于计算负担和隐私问题，完全集中的能源管理越来越不现实。在此背景下，本文综合了分布式优化（DO）作为ec的实用管理范例，确定了关键应用领域（需求响应、分布式发电和存储管理、微电网或智能电网集成），并概述了可扩展性、隐私性和弹性特征。调查遵循一个系统的协议：记录来自Scopus，用迭代改进的关键字集进行过滤，并按照PRISMA流程进行筛选。对区块链/分布式账本、人工智能和博弈论结构等关键技术因素进行了评估和分析，以了解它们如何支持跨多代理能源网络的安全数据交换、实时协调和激励兼容性。该分析强调了在EC规模下DO面临的持续挑战，包括异质性下的融合、时变条件、通信延迟、网络安全和隐私保障，而最近的进展（例如ADMM）在不牺牲本地自主权的情况下部分缓解了这些问题。在具有代表性的研究中，DO实现了接近集中的最优性，差距为0.0029%。总体而言，我们提出了一个综合框架，将DO家族映射到EC用例，并概述了健壮、隐私保护和可扩展的EC优化的研究方向。

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引用次数: 0

Review of solar spectral irradiance modelling at ground level: Current methods and machine learning opportunities 地面太阳光谱辐照度建模综述：当前方法和机器学习机会

IF 9.4 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2026-01-08 DOI: 10.1016/j.energy.2026.139967

Yuexing Yang , Xiao Liu , Yupeng Wu

The accurate acquisition of solar spectral irradiance is crucial for the efficient utilisation of solar energy and the strategic planning of solar energy harvesting systems. Due to the high costs associated with specialised measurement instruments, spectral irradiance modelling has become a popular alternative in various fields, including industrial electricity generation, agriculture, and building applications. This review provides a thorough evaluation of existing methods for modelling spectral irradiance at the Earth’s surface, while also exploring the potential of machine learning (ML) in this domain. The review begins by examining the atmospheric parameters (e.g., components of gas, aerosol and cloud) that influence spectral irradiance, summarising their wavelength-specific effects and accessibility via different physical or numerical models. A systematic comparison of various mainstream physical models reveals that using more relevant atmospheric parameters as input and enhancing the spatial–temporal resolutions could improve the accuracy of spectral irradiance prediction. However, their accuracy still depends on the accurate parameter acquisition by either measurement or modelling. In contrast, statistical parameterisation approaches can reduce dependence on complex input data, which enhances computational efficiency and maintains high accuracy under certain conditions, such as clear-sky conditions. In addition, machine learning is a promising method that can further enhance the accuracy and efficiency of spectral irradiance modelling. By leveraging large datasets and advanced algorithms, ML models can capture complex patterns and relationships in the data that are difficult to represent with traditional physical models. This enables more accurate predictions of spectral irradiance under a wide range of atmospheric conditions. However, compared to the ML models for total irradiance predictions, ML approaches for spectral modelling are still in the development stage. The challenge is to establish reliable wavelength-dependent correlations between atmospheric parameters and spectral irradiance outputs. Through this review, we aim to provide a comprehensive foundation for researchers and practitioners to better understand the current state of spectral irradiance modelling and to identify key areas for future development.

太阳光谱辐照度的准确采集对太阳能的有效利用和太阳能收集系统的战略规划至关重要。由于与专业测量仪器相关的高成本，光谱辐照度建模已成为各个领域的流行替代方案，包括工业发电，农业和建筑应用。这篇综述对地球表面光谱辐照度建模的现有方法进行了全面的评估，同时也探索了机器学习（ML）在这一领域的潜力。本报告首先审查影响光谱辐照度的大气参数（例如气体、气溶胶和云的成分），总结其波长特异性效应以及通过不同的物理或数值模型的可及性。通过对各种主流物理模式的系统比较表明，使用更多相关的大气参数作为输入，提高时空分辨率可以提高光谱辐照度预测的精度。然而，它们的精度仍然依赖于通过测量或建模获得准确的参数。相比之下，统计参数化方法可以减少对复杂输入数据的依赖，从而提高计算效率，并在某些条件下保持较高的精度，例如晴天条件。此外，机器学习是一种很有前途的方法，可以进一步提高光谱辐照度建模的准确性和效率。通过利用大型数据集和高级算法，机器学习模型可以捕获传统物理模型难以表示的数据中的复杂模式和关系。这使得在广泛的大气条件下更准确地预测光谱辐照度。然而，与用于总辐照度预测的ML模型相比，用于光谱建模的ML方法仍处于发展阶段。挑战在于在大气参数和光谱辐照度输出之间建立可靠的波长相关关系。通过这篇综述，我们旨在为研究人员和从业人员更好地了解光谱辐照度建模的现状和确定未来发展的关键领域提供一个全面的基础。

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引用次数: 0

Magnetically coupled piezoelectric wind energy harvester with dual stable output zones 具有双稳定输出区的磁耦合压电风能采集器

IF 9.4 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2026-01-07 DOI: 10.1016/j.energy.2025.139862

Zhenli Kuang , Mengsong Zhu , Lingqi Luo , Weilin Liao , Shijie Lin , Zhonghua Zhang , Junwu Kan

Recently, wind piezoelectric energy harvesters have gained attention for powering wireless sensor networks and IoT devices. A novel magnetically coupled piezoelectric wind energy harvester (MC-PWEH) with dual stable output zones is proposed. By introducing a downstream arc plate and magnetic coupling, the MC-PWEH achieves high-stable output voltage at low wind speeds and low-stable output voltage at high wind speeds. Its viability is confirmed through theoretical assessments, Computational Fluid Dynamics simulations, and experimental validation. Results show that the initial vibration wind speed (v_r) and output voltage (U) can be adjusted by varying the distance between the arc plate and cylinder (d) and the distance between the exciting and excited magnets (l_m). The minimum initial vibration wind speed is 2.4 m/s at d = 20 mm and l_m = 15 mm. The maximum output voltage reaches 29.8 V, 52.3 times higher than without the arc plate. Additionally, a maximum output power of 1.34 mW is achieved at 200 kΩ and 10 m/s. The MC-PWEH can power 50 LEDs and low-power devices like electronic thermometers through a charged capacitor.

最近，风力压电能量采集器在为无线传感器网络和物联网设备供电方面受到了关注。提出了一种新型的双稳定输出区磁耦合压电风能采集器（MC-PWEH）。MC-PWEH通过引入下游电弧板和磁力耦合，实现了低风速下的高稳定输出电压和高风速下的低稳定输出电压。通过理论评估、计算流体动力学模拟和实验验证，证实了其可行性。结果表明，通过改变电弧板与圆筒的距离d和励磁与被激磁体的距离lm，可以调节初始振动风速vr和输出电压U。d = 20 mm, lm = 15 mm时，最小初始振动风速为2.4 m/s。最大输出电压达到29.8 V，比无弧板高52.3倍。此外，在200 kΩ和10m /s的速度下，最大输出功率为1.34 mW。MC-PWEH可以通过充电电容器为50个led和电子温度计等低功耗设备供电。

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引用次数: 0

Enhancing canned motor pump performance in energy systems: A novel structure for particle wear mitigation and flow efficiency preservation 提高屏蔽电机泵在能源系统中的性能：一种新型结构的颗粒磨损缓解和流动效率的保存

IF 9.4 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2026-01-07 DOI: 10.1016/j.energy.2026.139943

Ze Chen , Yandong Gu , Weigang Lu , Mengying Liu

Canned motor pumps are widely used in liquid cooling systems for energy systems, serving as the core component for thermal regulation of various modules. However, particles enter the canned motor gap with coolant. Prolonged operation causes motor wear, jeopardizing equipment longevity and system safety. To address this issue, this study introduces a novel and straightforward L-structure to prevent particle-induced wear in motor gaps. Numerical simulations using the Discrete Phase Model for solid-liquid two-phase flow were validated by experimental results. L-structure geometric parameters were optimized with particle interception and hydraulic performance as objectives. Orthogonal designs and Pearson correlation analysis identified outer diameter and thickness as primary influencing factors. With the optimized L-structure, the particle interception ratio reaches 53.57 %, motor gap erosion amount is reduced by 50.43 %, head coefficient marginally improves by 1.37 %, efficiency slightly increases by 0.89 %, and motor gap leakage loss ratio decreases by 0.1 %. Flow fields reveal significantly reduced particle trajectories and erosion distributions in the motor gap. The L-structure mitigates wear via two mechanisms: inertial-separation and entrainment-mitigation, with inertial-separation being dominant. The inertial-separation mechanism results in a significant reduction in velocity at the L-structure, thereby decreasing particle inertia and facilitating effective particle interception. Meanwhile, the entrainment-mitigation mechanism attenuates leakage by increasing local flow resistance, decreasing particles entering motor gap. Additionally, the L-structure decreases pump entropy generation, marginally improving flow efficiency. This straightforward and cost-effective design enhances the operational performance and service life of canned motor pumps, which is crucial for the reliability and efficiency of energy systems.

屏蔽式电机泵广泛应用于能源系统的液冷系统中，是各模块热调节的核心部件。然而，颗粒进入屏蔽电机间隙与冷却剂。长时间运行导致电机磨损，危及设备寿命和系统安全。为了解决这个问题，本研究引入了一种新颖而直接的l型结构，以防止电机间隙中颗粒引起的磨损。实验结果验证了采用离散相模型对固液两相流动进行数值模拟的正确性。以截留颗粒和水力性能为目标，对l型结构几何参数进行优化。正交设计和Pearson相关分析确定外径和厚度为主要影响因素。优化后的l型结构，颗粒截留率达到53.57%，电机间隙侵蚀量减少了50.43%，水头系数略微提高了1.37%，效率略微提高了0.89%，电机间隙漏损比降低了0.1%。流场显示明显减少粒子轨迹和侵蚀分布在电机间隙。l型结构通过两种机制减轻磨损：惯性分离和夹带减缓，其中惯性分离占主导地位。惯性分离机制导致l结构处的速度显著降低，从而降低了颗粒的惯性，有利于有效的颗粒拦截。同时，夹带-减缓机制通过增加局部流动阻力，减少颗粒进入电机间隙来减弱泄漏。此外，l型结构降低了泵的熵产，略微提高了流动效率。这种简单而经济的设计提高了屏蔽电机泵的运行性能和使用寿命，这对能源系统的可靠性和效率至关重要。

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引用次数: 0

Optimizing blue hydrogen production in Türkiye: Techno-economic and environmental assessment of SMR with carbon capture under evolving carbon policy 优化<s:1> rkiye蓝色氢生产：碳政策下具有碳捕集的SMR的技术经济和环境评价

IF 9.4 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2026-01-06 DOI: 10.1016/j.energy.2026.139949

Celal Erbay

This study evaluates hydrogen production pathways in Türkiye, focusing on the economic and environmental viability of blue hydrogen produced via steam methane reforming (SMR) with carbon capture and storage (CCS). Using a techno-economic model, levelized cost of hydrogen (LCOH) values are calculated for 2023 and 2035 under carbon tax scenarios ranging from $0 to $100 per ton of CO₂. Results show that although gray hydrogen is the lowest-cost option in 2023 ($1.7/kg), its high emissions make it unsustainable in the long term. By 2035, under a $100 CO₂ tax and under a low domestic natural gas price scenario with a 48 % drop compared to today, SMR with 90 % CCS becomes the most competitive option at $1.31–1.79/kg, achieving significant emission reductions. The study includes sensitivity analyses assessing the influence of CAPEX, OPEX, fuel, and carbon costs on hydrogen pricing. It also compares the environmental performance of gray, blue, and green hydrogen, incorporating CO₂ emissions, water usage, and methane leakage. Findings highlight the importance of high-efficiency CCS technologies and policy tools—particularly carbon pricing—for enabling a cost-effective transition toward low-carbon hydrogen. The results align with Türkiye's Hydrogen Strategy Roadmap and its broader decarbonization and energy security goals. This research offers one of the first region-specific, scenario-based techno-economic assessments of blue hydrogen in Türkiye. It provides actionable insights for policymakers and industry stakeholders aiming to position the country as a competitive player in the global hydrogen economy.

本研究评估了 rkiye的制氢途径，重点研究了通过蒸汽甲烷重整（SMR）和碳捕集与封存（CCS）生产蓝氢的经济和环境可行性。利用技术经济模型，在每吨二氧化碳征收0美元至100美元的碳税情景下，计算了2023年和2035年氢的平准化成本（LCOH）值。结果表明，尽管灰氢在2023年是成本最低的选择（每公斤1.7美元），但其高排放使其长期不可持续。到2035年，在100美元的二氧化碳税和较低的国内天然气价格（与目前相比下降48%）的情况下，拥有90% CCS的SMR成为最具竞争力的选择，价格为1.31-1.79美元/公斤，实现了显著的减排。该研究包括敏感性分析，评估资本支出、运营支出、燃料和碳成本对氢定价的影响。它还比较了灰氢、蓝氢和绿氢的环境性能，包括二氧化碳排放量、用水量和甲烷泄漏。研究结果强调了高效CCS技术和政策工具的重要性，特别是碳定价，以实现向低碳氢的成本效益过渡。结果与 rkiye公司的氢战略路线图及其更广泛的脱碳和能源安全目标一致。这项研究提供了第一个针对 rkiye蓝色氢的特定区域、基于场景的技术经济评估之一。它为政策制定者和行业利益相关者提供了可行的见解，旨在将该国定位为全球氢经济中的竞争对手。

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引用次数: 0

Low-carbon economic dispatch of electrified transportation networks considering grid parity and mixed traffic of human-driven and autonomous vehicles 考虑电网平价和人工驾驶与自动驾驶混合交通的电气化交通网络低碳经济调度

IF 9.4 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2026-01-05 DOI: 10.1016/j.energy.2026.139941

Jia Li , Bin Li , Zhitao Liu , Hongye Su

The rapid proliferation of electric vehicles (EVs) has intensified the coupling between transportation networks (TNs) and power distribution networks (PDNs). Simultaneously, the growth of renewable energy sources (RES) and the implementation of grid parity policies, along with the coexistence of autonomous vehicles (AVs) and human-driven vehicles (HVs), present both opportunities and challenges for the realization of low-carbon electrified transportation networks (ETNs). To address these challenges, this paper proposes a low-carbon economic dispatch model for ETNs aimed at minimizing operational costs, reducing wind and solar curtailment, and lowering carbon emissions. The model incorporates the effects of grid parity for RES and centralized AV control, treating EVs (including AVs) as dynamic decarbonization resources. By optimizing the spatiotemporal distribution of charging loads, the model improves RES utilization and reduces carbon emissions within ETNs. Given the high non-convexity of the semi-dynamic traffic assignment under the mixed user equilibrium-system optimal framework, the problem is reformulated as a variational inequality and solved using an efficient fixed-point algorithm. Additionally, a bidirectional independent charging pricing strategy is introduced to optimize the spatiotemporal distribution of EVs, thereby reducing both carbon emissions and economic costs. Then a decentralized iterative algorithm is developed to solve the bi-level ETN model. Numerical results from two test systems demonstrate the effectiveness of the proposed model and strategy, while also highlighting the model’s robustness in handling the uncertainties associated with RES and traffic demand. The impacts of various parameters on ETN operation are analyzed.

随着电动汽车的快速发展，交通网络与配电网络之间的耦合日益加剧。同时，可再生能源（RES）的增长和电网平价政策的实施，以及自动驾驶汽车（AVs）和人类驾驶汽车（HVs）的共存，为实现低碳电气化交通网络（etn）提供了机遇和挑战。为了应对这些挑战，本文提出了一个etn的低碳经济调度模型，旨在最大限度地降低运营成本，减少风能和太阳能弃风，降低碳排放。该模型结合了电网平价对可再生能源和自动驾驶汽车集中控制的影响，将电动汽车（包括自动驾驶汽车）视为动态脱碳资源。该模型通过优化充电负荷的时空分布，提高了可再生能源的利用率，降低了etn内的碳排放。针对混合用户均衡-系统最优框架下的半动态流量分配问题的高度非凸性，将该问题重新表述为变分不等式，并采用高效的不动点算法求解。此外，引入双向独立充电定价策略，优化电动汽车的时空分布，从而降低碳排放和经济成本。在此基础上，提出了求解双层ETN模型的分散迭代算法。两个测试系统的数值结果证明了所提出的模型和策略的有效性，同时也突出了模型在处理RES和交通需求相关的不确定性方面的鲁棒性。分析了各参数对ETN运行的影响。

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引用次数: 0

The resilience of energy trade networks in countries along “The Belt and Road” and the risk resistance capacity of China “一带一路”沿线国家能源贸易网络弹性与中国抗风险能力

IF 9.4 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2026-01-05 DOI: 10.1016/j.energy.2025.139856

Kai Wu, Yingying Qiu, Jing Deng, Zimo Feng

In the context of the Belt and Road trade cooperation and energy transition, analyzing the trade network characteristics and evolutionary trends of traditional and renewable energy in the countries along the route aids in optimizing and transforming their energy structures. Furthermore, assessing the resilience of different energy trade networks and the risk resistance of key countries is crucial for maintaining energy security. This paper constructs trade networks for crude oil, natural gas, and solar photovoltaic energy, comparing their characteristics and evolution. It also evaluates the resilience of these energy networks and China’s risk resistance through simulated attacks. The main conclusions are as follows:First, the indicators of the solar photovoltaic network show a significant gap compared to crude oil and natural gas, with high density, efficiency, strong clustering, and short paths. Second, countries with extensive traditional energy trading, such as Qatar and Kazakhstan, lack significant node importance, whereas Singapore has emerged as the solar photovoltaic network’s central hub due to its strategic location. Third, the resilience of three energy trade networks exhibits an upward trend, with the solar photovoltaic network demonstrating greater resilience. Ultimately, China plays a significant bridging role and has the highest resistance to risks in the natural gas network. These findings highlight the policy need to prioritize renewable cooperation, strengthen hub connectivity, and foster resilient photovoltaic investment.

在“一带一路”贸易合作和能源转型背景下，分析沿线国家传统能源和可再生能源贸易网络特征及其演化趋势，有助于沿线国家能源结构的优化和转型。此外，评估不同能源贸易网络的弹性和主要国家的风险抵抗能力对于维护能源安全至关重要。本文构建了原油、天然气和太阳能光伏的贸易网络，比较了它们的特点和演变。它还通过模拟攻击评估了这些能源网络的弹性和中国的风险抵抗能力。主要结论如下：第一，太阳能光伏网络各项指标与原油、天然气相比存在明显差距，具有密度大、效率高、集聚性强、路径短等特点；其次，拥有广泛传统能源贸易的国家，如卡塔尔和哈萨克斯坦，缺乏显著的节点重要性，而新加坡由于其战略位置而成为太阳能光伏网络的中心枢纽。三种能源交易网络弹性均呈上升趋势，其中太阳能光伏网弹性更强。最终，中国在天然气网络中发挥着重要的桥梁作用，具有最高的抗风险能力。这些发现强调了政策需要优先考虑可再生能源合作，加强枢纽连通性，促进有弹性的光伏投资。

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引用次数: 0

Performance enhancement of thermoelectric modules through the introduction of macro-porous thermoelectric leg 通过引入大孔热电腿提高热电模块的性能

IF 9.4 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2026-01-05 DOI: 10.1016/j.energy.2026.139942

Boyang Liang , Xiangning Meng , Zhuang Miao , Xi Li

Thermoelectric modules (TEMs) can directly convert heat energy into electrical energy through thermoelectric conversion, but their conversion efficiency remains relatively low. The dense arrangement of thermoelectric legs (TELs) restricts airflow and causes heat concentration, which degrades performance and shortens service life. Introducing pore structures in TELs has been proposed as an effective approach to alleviate heat concentration and improve thermal uniformity. However, their impact on entire TEMs has generally been overlooked. This study employs numerical simulations to investigate the effects of pore structures on TELs and entire TEMs. The results show that circular pores of medium size provide the most balanced thermomechanical performance. They reduce the maximum thermal stress and deformation by 8.34 % and 5.98 %, respectively, while improving the uniformity of current distribution. The analysis of entire TEMs shows that the number of macro-porous thermoelectric legs (MPTELs) significantly affects internal convection and power generation performance. An optimized configuration enhances heat transfer and alleviates heat concentration. As a result, the maximum output power and conversion efficiency reach 6.31 W and 5.19 %, respectively. These results demonstrate that optimizing pore structures can simultaneously enhance thermal stability and power generation performance of TEMs. This provides important insights for the design of high-performance thermoelectric systems.

热电模块（TEMs）可以通过热电转换直接将热能转化为电能，但其转换效率相对较低。热电腿（tel）的密集排列限制了气流，导致热量集中，从而降低了性能并缩短了使用寿命。在电晶体中引入孔隙结构是缓解热集中和改善热均匀性的有效途径。然而，它们对整个tem的影响通常被忽视了。本文采用数值模拟的方法研究了孔隙结构对电晶体和整个电晶体的影响。结果表明，中等尺寸的圆形孔隙提供了最平衡的热力学性能。使最大热应力和最大变形分别降低8.34%和5.98%，同时提高了电流分布的均匀性。整个tem的分析表明，大孔热电腿的数量对内部对流和发电性能有显著影响。优化的配置增强了传热，减轻了热量集中。最大输出功率和转换效率分别达到6.31 W和5.19%。这些结果表明，优化孔隙结构可以同时提高tem的热稳定性和发电性能。这为高性能热电系统的设计提供了重要的见解。

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引用次数: 0

Source domain selection with early-cycle features for transfer learning-based prediction of lithium-ion battery degradation trajectories 基于迁移学习的锂离子电池退化轨迹预测的早期周期特征源域选择

IF 9.4 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2026-01-04 DOI: 10.1016/j.energy.2026.139928

Kai Huang , XinYu Zhang , Yongfang Guo , MengShi Li

Predicting the remaining useful life (RUL) of batteries is critical for ensuring equipment safety and optimizing maintenance strategies. However, due to the complicated nonlinear degradation of batteries, accurate prediction based on early-cycle data remains a significant challenge. Thus, a transfer learning prediction framework based on source domain selection using early-cycle degradation features is proposed. First, features reflecting the internal aging state are extracted from charging voltage-capacity data in early cycles. Then, a hybrid distance-dynamic time warping (HD-DTW) source domain battery selection method is developed to select similar batteries based on the features and capacity data. Finally, based on the selected source domain batteries and the early-cycle data of the target battery, an elastic net model is established to generate the degradation trajectory for the target battery. The performance of the proposed framework is validated based on open-source datasets. The results show that it can accurately predict RUL in the early stage, achieving an average absolute percentage error of 7.23 % and a root mean square error of 81.52 cycles.

预测电池的剩余使用寿命（RUL）对于确保设备安全和优化维护策略至关重要。然而，由于电池复杂的非线性退化，基于早期循环数据的准确预测仍然是一个重大挑战。在此基础上，提出了一种基于源域选择的迁移学习预测框架。首先，从前期充电电压-容量数据中提取反映内部老化状态的特征；然后，提出了一种混合距离-动态时间规整（HD-DTW）源域电池选择方法，根据特征和容量数据选择相似的电池。最后，基于选定的源域电池和目标电池的早期循环数据，建立弹性网络模型，生成目标电池的退化轨迹。基于开源数据集验证了该框架的性能。结果表明，该方法能较准确地在早期预测RUL，平均绝对百分比误差为7.23%，均方根误差为81.52个周期。

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引用次数: 0

Thermal energy storage and leakage prevention of phase change materials via one-step impregnation and in-situ polymerization process in hardwood 硬木一步浸渍原位聚合相变材料的储热防漏

IF 9.4 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2026-01-04 DOI: 10.1016/j.energy.2025.139874

Jakub Grzybek , Gabriel Zsembinszki , Emiliano Borri , Alina Meindl , Zuzana Paschová , Alexander Petutschnigg , Luisa F. Cabeza , Thomas Schnabel

Wood is a versatile material widely used in building construction, but its low thermal mass limits its ability to regulate indoor temperatures and mitigate thermal load peaks. Phase change materials are effective at storing thermal energy, but when impregnated into wood, they leak out, compromising performance and restricting their use in buildings.

This study introduces a novel one-step impregnation process combined with in-situ polymerization using furfuryl alcohol and a capric-stearic acid phase change material mixture to create a sustainable material for thermal energy storage. Various formulations were tested on European beech (Fagus sylvatica L.) to evaluate effectiveness of the approach.

The results confirm that this method successfully prevents phase change material leakage. Moreover, differential scanning calorimetry and nuclear magnetic resonance verified that phase change materials retain their thermal energy storage functionality, with no chemical cross-linking between the phase change materials and furfuryl alcohol. The treated wood showed up to 185 % higher thermal energy storage capacity, enhanced dimensional stability (anti-swelling efficiency up to 87 %), and 28 % higher compressive strength than untreated wood. It is a step towards sustainable, multifunctional, leakage-free, enhanced mechanical properties, improved dimensional stability wood for thermal energy storage for building applications, with potential for further optimisation and characterisation.

木材是一种广泛用于建筑施工的多功能材料，但其低热质量限制了其调节室内温度和减轻热负荷峰值的能力。相变材料在储存热能方面是有效的，但是当渗透到木材中时，它们会泄漏，从而影响性能并限制其在建筑物中的使用。本研究介绍了一种新的一步浸渍工艺，并结合原位聚合，利用糠醇和卡普-硬脂酸相变材料混合物制备了一种可持续的储能材料。在欧洲山毛榉（Fagus sylvatica L.）上试验了各种配方，以评价该方法的有效性。结果表明，该方法成功地防止了相变材料的泄漏。此外，差示扫描量热法和核磁共振验证了相变材料保留了其储热功能，相变材料与糠醇之间没有化学交联。与未经处理的木材相比，经过处理的木材的储热能力提高了185%，尺寸稳定性增强（抗膨胀效率高达87%），抗压强度提高了28%。这是朝着可持续、多功能、无泄漏、增强机械性能、改善尺寸稳定性的一步，用于建筑应用的热能储存，具有进一步优化和表征的潜力。

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