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A Comprehensive Review on Maximum Power Point Tracking (MPPT) using ANN

Jyotsana Pandey*

Department of Electrical Engineering at Raipur Institute of Technology, Raipur, Chhattisgarh, India.

Periodicity:October - December'2021
DOI : https://doi.org/10.26634/jee.15.2.15884

Abstract

Classic maximum power point tracking algorithms ensure correct operation in uniform light conditions. However, when a Photovoltaic (PV) array is under Partial Shading Conditions (PSC), several local maxima appear on the photovoltaic characteristic curve of the photovoltaic array, which is due to the use of bypass diodes to avoid the effect of hot spots. The appearance of these multiple peaks in the characteristics of the PV array makes it difficult to track under these conditions and requires the integration of a more efficient power management system that is able to distinguish between local and global peaks to harvest the maximum possible energy and therefore increase the efficiency of the entire system. In addition to implement global maximum power point tracking strategies, the mismatch loss associated with the shading effect can be further reduced by using alternative PV array configurations. This paper provides an overview of Maximum Power Tracking (MPPT) using Artificial Neural Networks (ANN).

Keywords

Maximum Power Point Tracking (MPPT), Solar Irradiation, Artificial Neural Networks (ANN), Accuracy.

How to Cite this Article?

Pandey, J. (2021). A Comprehensive Review on Maximum Power Point Tracking (MPPT) using ANN. i-manager’s Journal on Electrical Engineering, 15(2), 29-33. https://doi.org/10.26634/jee.15.2.15884

References

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