Gulraiz Asif, Al Bastaki Azizeh J, Magamal Khulood, Subhi Mina, Hammad Abdallah, Allanjawi Abdulrahman, Zaidi Sajjad Haider, Khalid Haris M, Ismail Abdulla, Hussain Ghulam Amjad, Said Zafar
Department of Electrical and Power Engineering, NUST, Karachi, Pakistan.
Department of Electrical Engineering, DHA Suffa University, Karachi, Pakistan.
iScience. 2025 Feb 4;28(3):111945. doi: 10.1016/j.isci.2025.111945. eCollection 2025 Mar 21.
The long term and large scale energy storage operations require quick response time and round-trip efficiency, which are not feasible with conventional battery systems. To address this issue while endorsing high energy density, long term storage, and grid adaptability, the hydrogen energy storage (HES) is preferred. This proposed work makes a comprehensive review on HES while synthesizing recent research on energy storage technologies and integration into renewable energy (RE) applications. The proposed research also identifies critical challenges related to system optimization, energy management strategies, and economic viability while featuring emerging technologies like artificial intelligence (AI) and machine learning (ML) for energy management. The proposed survey also discusses key advancements in battery technologies (lithium-ion, Ni-Cd, Ni/MH, and flow batteries) that are examined alongside innovations in HES methods. The proposed survey utilizes an extensive list of publications to date in the open literature to canvass and portray various developments in this area.
长期和大规模的储能运营需要快速响应时间和往返效率,而传统电池系统无法实现这些要求。为了解决这一问题,同时支持高能量密度、长期存储和电网适应性,氢能存储(HES)是首选方案。本提议的工作对氢能存储进行了全面综述,同时综合了近期关于储能技术以及将其集成到可再生能源(RE)应用中的研究。提议的研究还确定了与系统优化、能源管理策略和经济可行性相关的关键挑战,同时介绍了用于能源管理的人工智能(AI)和机器学习(ML)等新兴技术。提议的调查还讨论了电池技术(锂离子电池、镍镉电池、镍氢电池和液流电池)的关键进展,并将这些电池技术与氢能存储方法的创新一起进行了研究。提议的调查利用了公开文献中迄今为止的大量出版物清单,来审视和描绘该领域的各种发展情况。