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<p>Thermal energy storage (TES) plays a key role in improving the efficiency, reliability, and dispatchability of renewable energy systems, particularly solar power. This review examines recent advances in solar‑integrated TES, focusing on material development, system integration, and performance optimization. A structured framework is used to define system boundaries and evaluate key performance indicators, including cycle efficiency, energy density, and exergy performance, enabling consistent comparison among sensible, latent, and thermochemical storage technologies. Reported studies indicate that sensible thermal energy storage (STES) typically provides energy densities of about 10–50 kWh/m³ with high maturity and low cost, latent thermal energy storage (LTES) can reach 50–150 kWh/m³ with near‑isothermal operation, and thermochemical energy storage (TCES) may exceed 200 kWh/m³, highlighting its potential for high‑density and long‑term storage. The review also highlights the growing role of artificial intelligence (AI) in TES‑assisted solar systems, where machine learning and optimization methods support forecasting, system control, materials discovery, and predictive maintenance. Overall, while STES remains the most commercially established option, advanced LTES and TCES technologies combined with improved system integration and AI‑driven optimization offer strong potential for next‑generation solar energy systems. Key research priorities include enhancing material stability, reducing system costs, developing hybrid TES concepts, and advancing intelligent control strategies to accelerate the deployment of efficient and sustainable thermal energy storage solutions.</p> Graphical Abstract <p></p>

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A review of integrated thermal energy storage systems for intelligent and sustainable solar energy applications

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月6日

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  • Mohammad Reza Assari,
  • Hassan Basirat Tabrizi,
  • Nazanin-Alsadat Torabi,
  • Fariba Mokhtarzadeh,
  • Nastaran Heidary,
  • Maryam Fallahzadeh,
  • Milad Setareh

摘要

Thermal energy storage (TES) plays a key role in improving the efficiency, reliability, and dispatchability of renewable energy systems, particularly solar power. This review examines recent advances in solar‑integrated TES, focusing on material development, system integration, and performance optimization. A structured framework is used to define system boundaries and evaluate key performance indicators, including cycle efficiency, energy density, and exergy performance, enabling consistent comparison among sensible, latent, and thermochemical storage technologies. Reported studies indicate that sensible thermal energy storage (STES) typically provides energy densities of about 10–50 kWh/m³ with high maturity and low cost, latent thermal energy storage (LTES) can reach 50–150 kWh/m³ with near‑isothermal operation, and thermochemical energy storage (TCES) may exceed 200 kWh/m³, highlighting its potential for high‑density and long‑term storage. The review also highlights the growing role of artificial intelligence (AI) in TES‑assisted solar systems, where machine learning and optimization methods support forecasting, system control, materials discovery, and predictive maintenance. Overall, while STES remains the most commercially established option, advanced LTES and TCES technologies combined with improved system integration and AI‑driven optimization offer strong potential for next‑generation solar energy systems. Key research priorities include enhancing material stability, reducing system costs, developing hybrid TES concepts, and advancing intelligent control strategies to accelerate the deployment of efficient and sustainable thermal energy storage solutions.

Graphical Abstract