在动态操作环境中,通过飞搜索优化和Cuckoo Search MPPT技术提高PEM燃料电池效率
Assala Bouguerra1, Abd Essalam Badoud2, Saad Mekhilef3,4
1Automatic Laboratory of Setif, Electrical Engineering Department, University Ferhat Abbas of Setif 1, City of Maabouda, Algeria.
Scientific reports
|June 17, 2024
概括
与Cuckoo Search (CS) 相比,飞搜索优化 (FSSO) 显著提高了质子交换膜 (PEM) 燃料电池的效率,通过改善功率提取和更快地适应不断变化的条件. 这增强了绿色能源解决方案.
科学领域:
- 可再生能源系统可再生能源系统
- 电气工程 电气工程
- 优化算法 优化算法
背景情况:
- 质子交换膜 (PEM) 燃料电池对于绿色能源至关重要,但对环境变化敏感.
- 高效运行需要先进的最大功率点跟踪 (MPPT),以适应压力和温度波动等动态条件.
研究的目的:
- 评估和比较飞搜索优化 (FSSO) 和子搜索 (CS) 算法在不同环境条件下在PEM燃料电池中MPPT的有效性.
- 评估这些MPPT算法的与提升转换器的集成,以提高系统可靠性和生产率.
主要方法:
- 对PEM燃料电池系统应用的FSSO和CS算法的比较模拟和分析.
- 整合MPPT算法与提升转换器,以优化功率提取.
- 基于输出功率,适应环境变化 (压力,温度) 的适应性,以及接近最大功率点 (MPP) 的速度的性能评估.
主要成果:
- 与CS相比,FSSO表现优越,从PEM燃料电池中提取电力的平均增加了12.5%.
- 与CS相比,FSSO表现出更强的适应性,以适应不同的运营条件,并与MPP相比25%更快的融合率.
- 与助推转换器的集成进一步提高了PEM燃料电池系统的可靠性和生产率.
结论:
- FSSO是一种高效和强大的MPPT方法,用于优化PEM燃料电池性能,在效率和速度上优于CS.
- 该研究为FSSO在推进绿色能源技术方面的潜力提供了定量证据.
- 建议进一步研究燃料电池系统的混合优化方法.
关键词:
提升转换器集成的整合.子搜索 (CS) 是一个搜索工具.动态运行环境 动态运行环境飞天松鼠搜索优化 (FSSO) 的一个例子.最大功率点跟踪 (MPPT) 是指最大功率点的跟踪.在PEM燃料电池中,燃料电池是最重要的.更多相关视频
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