Home > Published Issues > 2021 > Volume 10, No. 2, March 2021 >

Linear Regression Algorithm Results for a PV Dual-Axis Tracking-Type System

Motlatsi C. Lehloka 1, James A. Swart 2, and Pierre E. Hertzog 2
1. Department of Electrical and Mining Engineering, University of South Africa, Florida, Roodepoort, South Africa
2. Central University of Technology, Bloemfontein, South Africa

Abstract—A photovoltaic (PV) module converts solar energy into electrical energy. In order to increase the output power of any PV module, several factors including tilt angle, orientation angle, load profile, environmental condition, latitude of the location site, and energy management techniques should be considered. It is essential to continuously deliver the highest possible power to a load for a given day, which may be achieved by using a tracking-type system as compared to a fixed-type system. The purpose of this paper is to present the results of an algorithm that may be applied to a dual-axis system located in an elevated plateau of the interior of South Africa in order to sustain a high output power. Two identical 310W PV modules were used for a fixed-type and tracking-type system. The fixed-type system was installed at a tilt angle of Latitude minus 10° serving as a baseline to the tracking-type system. A LabView user interface was developed to record and display the voltage and current measurements from the PV modules. Results indicate that the dual-axis tracking-type system extracted more power (on average 39.32% more power) as compared to the fixed-type system. A key recommendation is to use a linear regression algorithm with a tracking-type system to enable a higher output energy yield for a given day.
Index Terms—Photovoltaic, tilt angle, orientation angle, Latitude, LabVIEW

Cite: Motlatsi C. Lehloka, James A. Swart, and Pierre E. Hertzog, "Linear Regression Algorithm Results for a PV Dual-Axis Tracking-Type System," International Journal of Electrical and Electronic Engineering & Telecommunications, Vol. 10, No. 2, pp. 139-144, March 2021. Doi: 10.18178/ijeetc.10.2.139-144

Copyright © 2021 by the authors. This is an open access article distributed under the Creative Commons Attribution License (CC BY-NC-ND 4.0), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.