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Comparative Analysis of Conventional and Artificial Intelligence-based Maximum Power Point Tracking Algorithms for Solar Photovoltaic Applications
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 184 - Number 42 |
| Year of Publication: 2023 |
| Authors: Vineeth Kumar P.K., Jijesh J.J. |
10.5120/ijca2023922526
|
Vineeth Kumar P.K., Jijesh J.J. . Comparative Analysis of Conventional and Artificial Intelligence-based Maximum Power Point Tracking Algorithms for Solar Photovoltaic Applications. International Journal of Computer Applications. 184, 42 ( Jan 2023), 39-48. DOI=10.5120/ijca2023922526
Abstract
Maximum Power Point Tracking (MPPT) algorithms are utilized in solar photovoltaic systems to enhance the overall performance. Various conventional MPPT algorithms are employed in solar photovoltaic systems. Nevertheless, those algorithms are futile in the Partial Shaded condition (PSC) and impotent in identifying the maximum power point. Also, the conventional algorithms failed to bi-furcate the local and global maxima during the partial shaded condition. The impact of partial shading results in the false selection of extreme power points in solar photovoltaic sources, and the total efficiency of the PV system comes down. The researchers' advanced MPPT algorithm overcomes the conventional MPPT algorithm. This research deals with the comparative analysis of conventional MPPT algorithm with Artificial Intelligence based MPPT algorithm (AI MPPT) by considering the parameters such as speed of convergence, tracking accuracy, cost of implementation, and efficiency. Moreover, the issues and challenges of selecting an optimized algorithm are discussed in this research work. The performance parameters of MPPT are evaluated individually. The fuzzy logic-based MPPT algorithm performs better than other MPPT algorithms.
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