全球储热技术科学知识图谱与前沿趋势分析

周洪; 罗伊默; 丁晓芹; 李永亮; 宋文吉

doi:10.19799/j.cnki.2095-4239.2026.0096

您当前的位置：

首页 >

文章列表页 >

全球储热技术科学知识图谱与前沿趋势分析

储热储冷多场景应用专刊 | 更新时间：2026-07-01

- 全球储热技术科学知识图谱与前沿趋势分析
- Scientific knowledge mapping and emerging trend analysis of global thermal energy storage technologies
- 储能科学与技术 2026年15卷第3期页码：1039-1053
- 作者机构：
  
  1.中国科学院武汉文献情报中心，湖北武汉 430071
  2.湖南大学土木工程学院，湖南长沙 410082
  3.伯明翰大学化学工程学院，英国伯明翰 B15 2TT
  4.中国科学院广州能源研究所，广东广州 510640
- 作者简介：
  
  周洪（1987—），男，博士，副研究员，研究方向为技术创新、战略情报，E-mail：zhouh@mail.whlib.ac.cn；
  宋文吉，博士、研究员、博士生导师，研究方向为大规模储能技术，E-mail：songwj@ms.giec.ac.cn。
- 基金信息：
  
  国家自然科学基金项目(52478089)
- DOI：10.19799/j.cnki.2095-4239.2026.0096
  中图分类号： TK 11
- 收稿：2026-01-29，
  
  修回：2026-02-25，
  
  纸质出版：2026-03-28
- 稿件说明：
移动端阅览
周洪, 罗伊默, 丁晓芹, 等. 全球储热技术科学知识图谱与前沿趋势分析[J]. 储能科学与技术, 2026, 15(3): 1039-1053.

ZHOU Hong, LUO Yimo, DING Xiaoqin, et al. Scientific knowledge mapping and emerging trend analysis of global thermal energy storage technologies[J]. Energy Storage Science and Technology, 2026, 15(3): 1039-1053.
周洪, 罗伊默, 丁晓芹, 等. 全球储热技术科学知识图谱与前沿趋势分析[J]. 储能科学与技术, 2026, 15(3): 1039-1053. DOI： 10.19799/j.cnki.2095-4239.2026.0096.

ZHOU Hong, LUO Yimo, DING Xiaoqin, et al. Scientific knowledge mapping and emerging trend analysis of global thermal energy storage technologies[J]. Energy Storage Science and Technology, 2026, 15(3): 1039-1053. DOI： 10.19799/j.cnki.2095-4239.2026.0096.

摘要

储热技术通过解决热能供需在时间、空间及强度上的不匹配问题，已成为提高能源系统灵活性和可再生能源消纳能力的关键。基于对近三万篇文献的系统性综述与科学知识图谱分析，梳理了储热领域的研究进展、应用脉络与发展趋势。研究发现，储热技术领域研究规模持续快速增长，已形成“材料—系统—应用”多层递进的知识体系，呈现出以中国、美国和欧洲为主导的差异化布局。研究前沿围绕高性能、智能化和系统融合展开，重点聚焦以热化学储热、钙循环为代表的长时储能技术，以MXene基复合材料、磁场调控为代表的智能响应材料，以综合能源系统、卡诺电池为核心的多能耦合集成，以及机器学习赋能的储热全链条优化。为推动储热技术规模化应用，亟需在材料、系统与市场层面协同创新，突破关键技术瓶颈，以支撑未来能源系统的安全高效运行。

Abstract

Thermal energy storage (TES) has emerged as a critical technology for enhancing the flexibility of energy systems and the integration capacity of renewable energy sources by addressing mismatches in the temporal

spatial

and intensity dimensions of energy supply and demand. This study conducted a comprehensive review and analysis of nearly 30000 scholarly publications using systematic review and scientometric knowledge mapping methodologies to delineate the research progress

application landscape

and development trends in the TES field. The investigation reveals that research activity in TES has experienced sustained and rapid growth

evolving into a multi-layered knowledge architecture structured around "Materials-Systems-Applications." A distinct global research landscape has materialized

characterized by a tripartite leadership comprising China

the United States

and Europe

each exhibiting unique strategic focuses and developmental trajectories. The current research frontier is primarily concentrated on the pursuit of high performance

system intelligence

and deep integration. Key areas of intense focus include: (1) long-duration energy storage technologies

notably thermochemical heat storage and calcium looping (CaL) cycles; (2) intelligent responsive materials

such as MXene-based composite materials and those whose properties can be modulated by magnetic fields; (3) multi-energy coupled integration

with core applications in integrated energy systems (IES) and Carnot batteries; and (4) machine learning (ML)-enabled optimization across the entire TES chain

from material discovery to system design and operational control. To propel the large-scale application of TES technologies

concerted innovation across material

system

and market dimensions is urgently required. Future efforts must prioritize overcoming key technical bottlenecks

such as enhancing material cyclability and energy density for long-term storage

improving the efficiency and intelligence of system integration

and developing robust market mechanisms and policy frameworks. This study provides a systematic

data-driven overview that can serve as a foundational reference for researchers

policymakers

and industry stakeholders navigating the evolving landscape of thermal energy storage.

关键词

Keywords

references

SUN M Y, LIU T Z, WANG X L, et al. Roles of thermal energy storage technology for carbon neutrality[J]. Carbon Neutrality, 2023, 2(1): 12. DOI:10.1007/s43979-023-00052-w.

汪翔, 陈海生, 徐玉杰, 等. 储热技术研究进展与趋势[J]. 科学通报, 2017, 62(15): 1602-1610. DOI:10.1360/N972016-00663.

WANG X, CHEN H S, XU Y J, et al. Advances and prospects in thermal energy storage: A critical review[J]. Chinese Science Bulletin, 2017, 62(15): 1602-1610. DOI:10.1360/N972016-00663.

MAHLIA T M I, SAKTISAHDAN T J, JANNIFAR A, et al. A review of available methods and development on energy storage; technology update[J]. Renewable and Sustainable Energy Reviews, 2014, 33: 532-545. DOI:10.1016/j.rser.2014.01.068.

ALI H M, REHMAN T U, ARICI M, et al. Advances in thermal energy storage: Fundamentals and applications[J]. Progress in Energy and Combustion Science, 2024, 100: 101109. DOI:10. 1016/j.pecs.2023.101109.

马鸿坤, 纪明希, 丁玉龙. 中低温吸附式热化学储热研究现状与进展[J]. 储能科学与技术, 2024, 13(12): 4436-4451. DOI:10.19799/j.cnki.2095-4239.2024.0909.

MA H K, JI M X, DING Y L. Current status and advances in the low-to-medium temperature sorption-based thermochemical heat storage[J]. Energy Storage Science and Technology, 2024, 13(12): 4436-4451. DOI:10.19799/j.cnki.2095-4239.2024.0909.

DA Y, ZHOU J L. Multi-doping strategy modified calcium-based materials for improving the performance of direct solar-driven calcium looping thermochemical energy storage[J]. Solar Energy Materials and Solar Cells, 2022, 238: 111613. DOI:10.1016/j.solmat.2022.111613.

LI B Y, LI Y J, DOU Y H, et al. SiC/Mn Co-doped CaO pellets with enhanced optical and thermal properties for calcium looping thermochemical heat storage[J]. Chemical Engineering Journal, 2021, 423: 130305. DOI:10.1016/j.cej.2021.130305.

LIU H, ZHANG J S, WEI J J. Mn and Mg synergistically stabilized CaO as an effective thermochemical material for solar energy storage[J]. Solar Energy Materials and Solar Cells, 2023, 252: 112202. DOI:10.1016/j.solmat.2023.112202.

MEDINA-CARRASCO S, VALVERDE J M. The Calcium Looping process for energy storage: Insights from in situ XRD analysis[J ] . Chemical Engineering Journal, 2022, 429: 132244. DOI:10.1016/j.cej.2021.132244.

LUO T, LUO C, SHI Z W, et al. Optimization of sol-gel combustion synthesis for calcium looping CO 2 sorbents, part Ⅰ: Effects of sol-gel preparation and combustion conditions[J ] . Separation and Purification Technology, 2022, 292: 121081. DOI:10.1016/j.seppur.2022.121081.

CHAI F Y, ZHU P W, XU H R, et al. Mn and Al co-modified CaO-based composites from various calcium precursors for thermochemical energy storage: High energy storage density and excellent solar absorption ability[J]. Solar Energy Materials and Solar Cells, 2024, 269: 112761. DOI:10.1016/j.solmat.2024.112761.

ZHENG H B, LIU X L, XUAN Y M, et al. Efficient direct solar-driven thermochemical energy storage of (AlMgFeMn)O x CaCO 3 pellets in a fluidized bed reactor[J ] . Energy Conversion and Management, 2023, 285: 116990. DOI:10.1016/j.enconman.2023. 116990.

CARRO A, CHACARTEGUI R, ORTIZ C, et al. Integration of calcium looping and calcium hydroxide thermochemical systems for energy storage and power production in concentrating solar power plants[J]. Energy, 2023, 283: 128388. DOI:10.1016/j.energy.2023.128388.

ZHANG C X, LI Y J, YANG L G, et al. Analysis on H 2 production process integrated CaO/Ca(OH) 2 heat storage and sorption enhanced staged gasification using calcium looping[J ] . Energy Conversion and Management, 2022, 253: 115169. DOI:10.1016/j.enconman.2021.115169.

ZHENG Z H, LIU H, WU D Z, et al. Polyimide/MXene hybrid aerogel-based phase-change composites for solar-driven seawater desalination[J]. Chemical Engineering Journal, 2022, 440: 135862. DOI:10.1016/j.cej.2022.135862.

LIU H, TIAN D L, ZHENG Z H, et al. MXene-decorated magnetic phase-change microcapsules for solar-driven continuous seawater desalination with easy salt accumulation elimination[J]. Chemical Engineering Journal, 2023, 458: 141395. DOI:10.1016/j.cej.2023.141395.

GAO Y, TANG Z D, CHEN X, et al. Magnetically accelerated thermal energy storage within Fe 3 O 4 -anchored MXene-based phase change materials[J ] . Aggregate, 2023, 4(1): e248. DOI:10.1002/agt2.248.

CAO Y, ZENG Z H, HUANG D Y, et al. Multifunctional phase change composites based on biomass/MXene-derived hybrid scaffolds for excellent electromagnetic interference shielding and superior solar/electro-thermal energy storage[J]. Nano Research, 2022, 15(9): 8524-8535. DOI:10.1007/s12274-022-4626-6.

QUAN B Q, WANG J Z, LI Y, et al. Cellulose nanofibrous/MXene aerogel encapsulated phase change composites with excellent thermal energy conversion and storage capacity[J]. Energy, 2023, 262: 125505. DOI:10.1016/j.energy.2022.125505.

WENG M M, LIN J H, YANG Y J, et al. MXene-based phase change materials for multi-source driven energy storage, conversion and applications[J]. Solar Energy Materials and Solar Cells, 2024, 272: 112915. DOI:10.1016/j.solmat.2024.112915.

XU W B, HUANG T J, HUANG S M, et al. Regulation mechanism of magnetic field on non-Newtonian melting and energy storage performance of metal foam composite nano-enhanced phase change materials[J]. International Journal of Heat and Mass Transfer, 2023, 200: 123501. DOI:10.1016/j.ijheatmasstransfer. 2022.123501.

KUMAR A, SAHA S K, KUMAR K R, et al. Study of melting of paraffin dispersed with copper nanoparticles in square cavity subjected to external magnetic field[J]. Journal of Energy Storage, 2022, 50: 104338. DOI:10.1016/j.est.2022.104338.

ADNAN, ASHRAF W. Thermal efficiency in hybrid (Al 2 O 3 -CuO/H 2 O) and ternary hybrid nanofluids (Al 2 O 3 -CuO-Cu/H 2 O) by considering the novel effects of imposed magnetic field and convective heat condition[J ] . Waves in Random and Complex Media, 2025, 35(4): 8029-8044. DOI:10.1080/17455030.2022.2092233.

LI H X, ZHUANG Y J, FENG J C. Multi-scale experimental analysis on the coupled effects of ultrasonic field and magnetic field on the melting and energy storage performances for hybrid nano-enhanced phase change materials[J]. Journal of Energy Storage, 2024, 84: 110801. DOI:10.1016/j.est.2024.110801.

ALI RABIENATAJ DARZI A, MOUSAVI S M. Enhancement of charging and discharging of phase change material in annular thermal energy storage unit by applying magnetic field[J]. Numerical Heat Transfer, Part A: Applications, 2023, 83(6): 609-625. DOI:10.1080/10407782.2022.2102315.

LIU C, ZHANG G W, ZHANG H, et al. Construction of Ag/MoS 2 @Fe-CS aerogel as excellent PMS activator via synergistic photocatalysis and photothermal effects[J ] . Chemical Engineering Journal, 2023, 455: 140814. DOI:10.1016/j.cej. 2022.140814.

GAO Y, CHEN X, JIN X, et al. Multifunction integration within magnetic CNT-bridged MXene/CoNi based phase change materials[J]. eScience, 2024, 4(6): 100292. DOI:10.1016/j.esci. 2024.100292.

GU X B, DONG K J, PENG L H, et al. Round-the-clock interfacial solar vapor generator enabled by form-stable phase change materials with enhanced photothermal conversion capacity[J]. Energy Conversion and Management, 2023, 277: 116634. DOI:10.1016/j.enconman.2022.116634.

ZHENG Z H, LIU H, WANG X D. Double-layered hydrogels based on phase change material and pen ink for continuous and efficient solar-driven seawater desalination[J]. Desalination, 2024, 574: 117276. DOI:10.1016/j.desal.2023.117276.

ZHANG J, ZHANG Y, WU S L, et al. Weavable coaxial phase change fibers concentrating thermal energy storage, photothermal conversion and thermochromic responsiveness toward smart thermoregulatory textiles[J]. Chemical Engineering Journal, 2024, 483: 149281. DOI:10.1016/j.cej.2024.149281.

QIN Y X, LIU P, LI Z. Multi-timescale hierarchical scheduling of an integrated energy system considering system inertia[J]. Renewable and Sustainable Energy Reviews, 2022, 169: 112911. DOI:10.1016/j.rser.2022.112911.

LI Y, ZOU Y, TAN Y, et al. Optimal stochastic operation of integrated low-carbon electric power, natural gas, and heat delivery system[J]. IEEE Transactions on Sustainable Energy, 2018, 9(1): 273-283. DOI:10.1109/TSTE.2017.2728098.

YOU M L, WANG Q, SUN H J, et al. Digital twins based day-ahead integrated energy system scheduling under load and renewable energy uncertainties[J]. Applied Energy, 2022, 305: 117899. DOI:10.1016/j.apenergy.2021.117899.

YAN R J, WANG J J, HUO S J, et al. Flexibility improvement and stochastic multi-scenario hybrid optimization for an integrated energy system with high-proportion renewable energy[J]. Energy, 2023, 263: 125779. DOI:10.1016/j.energy.2022.125779.

WANG J J, DENG H D, QI X L. Cost-based site and capacity optimization of multi-energy storage system in the regional integrated energy networks[J]. Energy, 2022, 261: 125240. DOI:10.1016/j.energy.2022.125240.

WANG Y L, LIU C, QIN Y M, et al. Synergistic planning of an integrated energy system containing hydrogen storage with the coupled use of electric-thermal energy[J]. International Journal of Hydrogen Energy, 2023, 48(40): 15154-15178. DOI:10.1016/j.ijhydene.2022.12.334.

REN H B, JIANG Z P, WU Q, et al. Integrated optimization of a regional integrated energy system with thermal energy storage considering both resilience and reliability[J]. Energy, 2022, 261: 125333. DOI:10.1016/j.energy.2022.125333.

BRANDI S, GALLO A, CAPOZZOLI A. A predictive and adaptive control strategy to optimize the management of integrated energy systems in buildings[J]. Energy Reports, 2022, 8: 1550-1567. DOI:10.1016/j.egyr.2021.12.058.

SRITHAPON C, MÅNSSON D. Predictive control and coordination for energy community flexibility with electric vehicles, heat pumps and thermal energy storage[J]. Applied Energy, 2023, 347: 121500. DOI:10.1016/j.apenergy.2023.121500.

ZAMENGO M, YOSHIDA K, MORIKAWA J. Numerical evaluation of a Carnot battery system comprising a chemical heat storage/pump and a Brayton cycle[J]. Journal of Energy Storage, 2021, 41: 102955. DOI:10.1016/j.est.2021.102955.

LI W, ZHANG L J, DENG Y J, et al. Thermo-economic assessment of a salt hydrate thermochemical energy storage-based Rankine Carnot battery system[J]. Energy Conversion and Management, 2024, 312: 118564. DOI:10.1016/j.enconman.2024. 118564.

ZHANG M Y, SHI L F, HU P, et al. Carnot battery system integrated with low-grade waste heat recovery: Toward high energy storage efficiency[J]. Journal of Energy Storage, 2023, 57: 106234. DOI:10.1016/j.est.2022.106234.

EPPINGER B, STEGER D, REGENSBURGER C, et al. Carnot battery: Simulation and design of a reversible heat pump-organic Rankine cycle pilot plant[J]. Applied Energy, 2021, 288: 116650. DOI:10.1016/j.apenergy.2021.116650.

LI W, ZHANG L J, WANG Q W, et al. Techno-economic evaluation of a Rankine Carnot battery coupling air-source energy and salt hydrate thermochemical heat transformer[J]. Energy Conversion and Management, 2025, 339: 119966. DOI:10.1016/j.enconman.2025.119966.

TASSENOY R, COUVREUR K, BEYNE W, et al. Techno-economic assessment of Carnot batteries for load-shifting of solar PV production of an office building[J]. Renewable Energy, 2022, 199: 1133-1144. DOI:10.1016/j.renene.2022.09.039.

MEHRAJ N, MATEU C, CABEZA L F. Use of artificial intelligence methods in designing thermal energy storage tanks: A bibliometric analysis[J]. Journal of Energy Storage, 2024, 97: 112794. DOI:10.1016/j.est.2024.112794.

PENG Z, OHLSON TIMOUDAS T, WANG Q. Building ontologies for 4-5GDHC: A critical evaluation and modeling experiments on building-side components[J]. Journal of Building Engineering, 2025, 114: 114204. DOI:10.1016/j.jobe.2025.114204.

TANG H, YU J, GENG Y, et al. Optimization of operational strategy for ice thermal energy storage in a district cooling system based on model predictive control[J]. Journal of Energy Storage, 2023, 62: 106872. DOI:10.1016/j.est.2023.106872.

ZHOU Y K, ZHENG S Q, HENSEN J L M. Machine learning-based digital district heating/cooling with renewable integrations and advanced low-carbon transition[J]. Renewable and Sustainable Energy Reviews, 2024, 199: 114466. DOI:10.1016/j.rser.2024.114466.

XIAO T, LIU Z G, LU L, et al. LSTM-BP neural network analysis on solid-liquid phase change in a multi-channel thermal storage tank[J]. Engineering Analysis with Boundary Elements, 2023, 146: 226-240. DOI:10.1016/j.enganabound.2022.10.014.

AMINI TOOSI H, DEL PERO C, LEONFORTE F, et al. Machine learning for performance prediction in smart buildings: Photovoltaic self-consumption and life cycle cost optimization[J]. Applied Energy, 2023, 334: 120648. DOI:10.1016/j.apenergy. 2023.120648.

浏览量

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

清洁供暖储热技术现状与趋势

储热技术研究进展与展望

高温烟气加热固体颗粒储热技术研究进展

基于内热源螺旋翅片的CaO/Ca（OH）2热化学储能反应器传热强化

垂直式重力储能系统能效研究