在可再生能源系统的气和电池储存领域的能源进步和整合策略
Asif Gulraiz1,2, Azizeh J Al Bastaki3, Khulood Magamal3
1Department of Electrical and Power Engineering, NUST, Karachi, Pakistan.
iScience
|March 10, 2025
概括
能储能 (HES) 为大规模储能需求提供了解决方案,性能优于传统电池. 本综述探讨了HES与可再生能源,人工智能和ML的整合,以优化能源管理.
科学领域:
- 储能系统 储能系统 储能系统
- 整合可再生能源的整合
- 材料科学用于能源.
背景情况:
- 传统的电池系统在快速响应时间和往返效率方面面临限制,以长期大规模储能.
- 由于其高能量密度,长期存储能力和电网适应性,能储能 (HES) 被确定为首选的替代方案.
- 电池技术 (离子,Ni-Cd,Ni/MH,流电池) 的进步与HES方法的创新一起进行了审查.
研究的目的:
- 提供对能储能 (HES) 技术的全面审查.
- 综合最近关于高能耗与可再生能源 (RE) 应用融合的研究.
- 为了确定HES优化关键挑战和新兴技术.
主要方法:
- 关于能源存储的开放获取出版物的综合文献综述.
- 综合研究HES技术及其与可再生能源的整合.
- 分析电池和HES技术的进步.
主要成果:
- HES为大规模储能提供了一个可行的解决方案,解决了传统电池的局限性.
- 像人工智能 (AI) 和机器学习 (ML) 这样的新兴技术显示出优化HES能源管理的前景.
- 确定了系统优化,能源管理策略和HES经济可行性的关键挑战.
结论:
- 高电压是电网规模储能的关键技术,特别是与可再生能源相结合时.
- 需要进一步的研究和开发,以克服HES优化,能源管理和经济可行性的挑战.
- 人工智能和机器学习的整合可以显著提高HES系统的性能和效率.
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