在部分阴影条件下使用增强的INC MPPT进行混合全球搜索
Mohamed Zaki1, Ahmed Shahin2, Saad Eskender2
1Electrical Engineering Department, Faculty of Engineering, Mansoura University, Mansoura, Egypt. Mohamed_zaki@mans.edu.eg.
Scientific reports
|December 14, 2023
概括
本研究引入了一种用于光伏系统的新最大功率点跟踪 (MPPT) 方法. 它在部分遮阳下有效地跟踪功率,克服了传统方法的局限性.
科学领域:
- 可再生能源系统可再生能源系统
- 光伏发电是光伏发电的发电方式.
- 电气工程 电气工程
背景情况:
- 光伏 (PV) 系统是关键的可再生能源,但面临着由可变的太阳辐射,温度和部分阴影带来的挑战.
- 传统的最大功率点追踪器 (MPPT) 在部分阴影条件下难以准确.
- 现有的人工智能和MPPT优化技术需要广泛的培训,并且在部分遮阳下很慢地趋同.
研究的目的:
- 为光伏系统提出一个动态和快速的最大功率点 (MPP) 追踪方法.
- 为了提高MPP跟踪的准确性和速度,在均的太阳辐射和部分遮阳条件下.
- 在动态环境中解决传统MPPT和基于AI的缓慢方法的局限性.
主要方法:
- 一种新的MPP跟踪方法,将增强的增量导电性 (INC) 算法与全球搜索算法相结合.
- 全球搜索算法专门设计用于分析部分遮阳下的太阳能电池性能.
- 进行模拟调查以验证拟议方法的性能.
主要成果:
- 拟议的方法实现了精确的MPP跟踪,跟踪时间短于0.2秒.
- 记录了不到0.3%的光伏功率的稳定状态误差.
- 该方法在均太阳辐射和部分遮阳场景下都表现出有效性.
结论:
- 开发的动态MPP跟踪方法比传统技术提供了显著的改进.
- 联合增强的INC和全球搜索算法为光伏系统提供了快速而准确的功率跟踪.
- 这种方法有效地克服了光伏发电中部分遮阳所带来的挑战.
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