在高度波动的环境条件下,光伏系统的混合salp swarm最大功率点跟踪算法
Mohd Nasrul Izzani Jamaludin1, Mohammad Faridun Naim Tajuddin2, Tarek Younis3
1Faculty of Electrical Engineering & Technology, Universiti Malaysia Perlis, Arau, 02600, Malaysia.
Scientific reports
|January 3, 2025
概括
本研究介绍了一种混合Salp Swarm算法 (SSA) 和登 (HC) 方法,用于光伏系统中增强的最大功率点跟踪 (MPPT). 这种新的算法能够有效地处理不同的大气条件和部分遮阳,优于现有的MPPT技术.
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:
- 光伏 (PV) 系统的功率输出对辐射,温度和部分阴影等环境因素很敏感.
- 精确的最大功率点跟踪 (MPPT) 对光伏效率至关重要,但在动态条件下具有挑战性.
- 现有的MPPT算法与快速的环境变化和复杂的阴影场景作斗争.
研究的目的:
- 开发一个强大的混合MPPT算法,结合Salp Swarm算法 (SSA) 和Hill Climbing (HC) 以提高光伏系统性能.
- 为了提高MPPT在波动辐射和部分遮阳条件下的效率.
- 根据最先进的方法验证拟议的混合SSA-HC算法.
主要方法:
- 提出了一个混合MPPT算法,集成SSA和HC.
- HC模式在稳定的辐射下跟踪全球最大功率点 (GMPP);在辐射率快速变化时,SSA模式被激活.
- 边界条件被用来管理各种辐射强度波动模式.
主要成果:
- 与标准的SSA和HC相比,混合SSA-HC算法显示出更高的跟踪性能.
- 通过硬件设置和MATLAB模拟的验证证实了在不同辐射和部分阴影条件下的有效性.
- 该算法在稳定状态和动态条件下显示了增强的能力.
结论:
- 拟议的混合SSA-HC MPPT算法为在具有挑战性的环境条件下运行的光伏系统提供了显著的进步.
- 它的自适应性使得它能够有效地提取电力,尽管大气参数的快速波动和部分阴影.
- 这种混合方法代表了当前MPPT技术的优越替代方案,用于最大限度地利用太阳能.
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