Energy advancements and integration strategies in hydrogen and battery storage for renewable energy systems

被引:0
|
作者
Gulraiz, Asif [1 ,2 ]
Al Bastaki, Azizeh J. [3 ]
Magamal, Khulood [3 ]
Subhi, Mina [3 ]
Hammad, Abdallah [3 ]
Allanjawi, Abdulrahman [3 ]
Zaidi, Sajjad Haider [1 ]
Khalid, Haris M. [3 ,4 ]
Ismail, Abdulla [5 ]
Hussain, Ghulam Amjad [3 ]
Said, Zafar [6 ]
机构
[1] NUST, Dept Elect & Power Engn, Karachi, Pakistan
[2] DHA Suffa Univ, Dept Elect Engn, Karachi, Pakistan
[3] Univ Dubai, Coll Engn & Informat Technol, Acad City Dubai 14143, U Arab Emirates
[4] Univ Johannesburg, Dept Elect & Elect Engn Sci, ZA-2006 Johannesburg, South Africa
[5] Rochester Inst Technol RIT, Dept Elect Engn & Comp Sci, Dubai, U Arab Emirates
[6] United Arab Emirates Univ, Coll Engn, Mech & Aerosp Engn Dept, Al Ain 15551, U Arab Emirates
关键词
REDOX FLOW BATTERY; FUEL-CELLS; TECHNOECONOMIC ASSESSMENT; ELECTRICITY-GENERATION; MANAGEMENT STRATEGIES; SIZING OPTIMIZATION; ION BATTERIES; HYBRID SYSTEM; SOLAR; TECHNOLOGIES;
D O I
10.1016/j.isci.2025.111945
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
引用
收藏
页数:44
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