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Artificial Intelligence Based MPPT Techniques for Solar Power System: A review
Journal of Modern Power Systems and Clean Energy ( IF 6.3 ) Pub Date : 2020-10-22 , DOI: 10.35833/mpce.2020.000159
Kah Yung Yap , Charles R. Sarimuthu , Joanne Mun-Yee Lim

In the last decade, artificial intelligence (AI) techniques have been extensively used for maximum power point tracking (MPPT) in the solar power system. This is because conventional MPPT techniques are incapable of tracking the global maximum power point (GMPP) under partial shading condition (PSC). The output curve of the power versus voltage for a solar panel has only one GMPP and multiple local maximum power points (MPPs). The integration of AI in MPPT is crucial to guarantee the tracking of GMPP while increasing the overall efficiency and performance of MPPT. The selection of AI-based MPPT techniques is complicated because each technique has its own merits and demerits. In general, all of the AI-based MPPT techniques exhibit fast convergence speed, less steady-state oscillation and high efficiency, compared with the conventional MPPT techniques. However, the AI-based MPPT techniques are computationally intensive and costly to realize. Overall, the hybrid MPPT is favorable in terms of the balance between performance and complexity, and it combines the advantages of conventional and AI-based MPPT techniques. In this paper, a detailed comparison of classification and performance between 6 major AI-based MPPT techniques have been made based on the review and MATLAB/Simulink simulation results. The merits, open issues and technical implementations of AI-based MPPT techniques are evaluated. We intend to provide new insights into the choice of optimal AI-based MPPT techniques.

中文翻译:

基于人工智能的MPPT技术在太阳能发电系统中的应用

在过去的十年中,人工智能(AI)技术已广泛用于太阳能系统中的最大功率点跟踪(MPPT)。这是因为常规MPPT技术无法在部分阴影条件(PSC)下跟踪全局最大功率点(GMPP)。太阳能电池板的功率与电压的输出曲线只有一个GMPP和多个局部最大功率点(MPP)。将AI集成到MPPT中对于确保跟踪GMPP,同时提高MPPT的整体效率和性能至关重要。基于AI的MPPT技术的选择非常复杂,因为每种技术都有其优缺点。一般而言,所有基于AI的MPPT技术都具有收敛速度快,稳态振荡少和效率高的特点,与传统的MPPT技术相比。但是,基于AI的MPPT技术计算量大且实现成本高。总体而言,混合MPPT在性能和复杂性之间取得平衡是有利的,它结合了常规MPPT技术和基于AI的MPPT技术的优势。在这篇论文中,根据综述和MATLAB / Simulink仿真结果,对6种主要的基于AI的MPPT技术之间的分类和性能进行了详细的比较。评估了基于AI的MPPT技术的优点,未解决的问题和技术实现。我们打算为基于AI的最佳MPPT技术的选择提供新见解。混合MPPT在性能和复杂性之间取得平衡是有利的,它结合了常规MPPT技术和基于AI的MPPT技术的优点。在这篇论文中,根据综述和MATLAB / Simulink仿真结果,对6种主要的基于AI的MPPT技术之间的分类和性能进行了详细的比较。评估了基于AI的MPPT技术的优点,未解决的问题和技术实现。我们打算为基于AI的最佳MPPT技术的选择提供新见解。混合MPPT在性能和复杂性之间取得平衡是有利的,它结合了常规MPPT技术和基于AI的MPPT技术的优点。在这篇论文中,根据综述和MATLAB / Simulink仿真结果,对6种主要的基于AI的MPPT技术之间的分类和性能进行了详细的比较。评估了基于AI的MPPT技术的优点,未解决的问题和技术实现。我们打算为基于AI的最佳MPPT技术的选择提供新见解。评估基于AI的MPPT技术的未解决问题和技术实现。我们打算为基于AI的最佳MPPT技术的选择提供新见解。评估基于AI的MPPT技术的未解决问题和技术实现。我们打算为基于AI的最佳MPPT技术的选择提供新见解。
更新日期:2020-12-04
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