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Performance Improvement of Maximum Power Point Tracker of Solar Panels using Artificial Neural Networks

Nitin Sharma*, Nafees Ahamad**

*-*** Department of Electrical Electronics and Communication Engineering, DIT University, Dehradun, Uttarakhand, India.

Periodicity:January - March'2021
DOI : https://doi.org/10.26634/jee.14.3.18284

Abstract

Very common and reliable source of energy is received on the earth from the sun as the photon band. Solar energy is changed into useful form of energy using photovoltaic cells. The photovoltaic solar arrays, i.e., the combination of more than one photovoltaic cells collect the solar energy in the form of energy packets called photons and give the output in terms of direct electric current. The problem faced by photovoltaic arrays is the inefficiency in operation of energy conversion due to the variations in position of the sun throughout the day for a whole year. To optimize the efficacy, MPPT which stands for Maximum Power Point Tracking is utilized that helps PV (Photovoltaic) arrays to get themselves perched in the direction or at a specific point where the reception of sun's energy is maximum. The issue with conventional MPPT systems is the convoluted mathematical computations involved in the procedure of tracking the spot of maximum power. We have to calculate various geographical and energy parameters like longitude, latitude, tilt angle, solar irradiance, temperature etc. in traditional MPPT construction. To avoid these labyrinthine calculations and make MPPT systems cognizant enough to predict the position points of maximum power based upon their prior knowledge we employed artificial neural network in association with MPPT systems.

Keywords

ANN, Photovoltaic, MPPT, Irradiance.

How to Cite this Article?

Sharma, N., and Ahamad, N. (2021). Performance Improvement of Maximum Power Point Tracker of Solar Panels using Artificial Neural Networks. i-manager's Journal on Electrical Engineering, 14(3), 40-48. https://doi.org/10.26634/jee.14.3.18284

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