模拟模型的数据用于光伏系统的最大功率点跟踪,使用顺序的蒙特卡洛算法
Alhaj-Saleh A Odat1, Moayyad Shawaqfah2, Fares Al-Momani3
1Department of Renewable Energy Engineering, Al Al-Bayt University, Mafraq, Jordan.
Data in brief
|January 4, 2024
概括
本研究提供了用于在部分遮阳下复制光伏 (PV) 系统中的顺序蒙特卡罗 (SMC) 追踪的数据. 这使得各种最大功率点跟踪算法的性能比较成为可能.
科学领域:
- 电气工程 电气工程
- 可再生能源系统可再生能源系统
- 计算智能是一种计算智能.
背景情况:
- 光伏 (PV) 系统在不同的条件下需要高效的最大功率点跟踪 (MPPT).
- 部分遮阳显著降低了光伏系统的性能,需要强大的MPPT算法.
- 序列蒙特卡洛 (SMC) 方法为先进的光伏系统跟踪提供了潜力.
研究的目的:
- 详细说明输入数据和部分遮阳条件,用于复制基于SMC的MPPT模型.
- 为了方便SMC,扰乱和观察 (P&O),粒子群优化 (PSO) 和花粉算法 (FPA) 之间的性能比较.
- 为验证和推进光伏系统跟踪技术提供可重复的数据集.
主要方法:
- 利用以前建立的光伏系统的数学设计和方法 [1].
- 定义特定的输入数据和模拟部分遮阳场景.
- 使用复制模型来评估不同的MPPT算法.
主要成果:
- 提供的数据允许精确复制模拟输出.
- 通过数据复制,可以显著减少模拟时间.
- 该数据集允许与现有的MPPT算法性能数据进行直接比较 [2,3].
结论:
- 该数据集对于基于SMC的MPPT技术的准确复制和验证至关重要.
- 这项工作支持在现实条件下对各种MPPT算法的比较分析.
- 这些数据有助于开发用于光伏系统的新和实用的MPPT解决方案.
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