Using Intelligent Control to Improve PV Systems Efficiency

TL;DR

This paper introduces an intelligent control approach for PV systems that simultaneously manages multiple parameters, including temperature, using probability theory to enhance efficiency, supported by practical testing and simulations.

Contribution

It presents a novel intelligent control method that considers temperature and predictive modeling, surpassing conventional techniques limited to fewer parameters.

Findings

Improved PV system efficiency demonstrated through simulations.

Effective control of temperature and power point movement.

Potential for further advancements in PV control strategies.

Abstract

One of the important technologies in renewable energy is the Photovoltaic (PV), which is the direct conversion of light into electricity at the atomic level, and improving the efficiency of PV systems is one of the very important factors in getting the most out of this invaluable renewable resource of energy. While most research work we studied used conventional techniques to control two parameters at most, like power and change in power, or voltage and change in voltage, etc., we implemented unconventional techniques, namely intelligent control to control more than two parameters at a time, including change in temperature which had been ignored by many researchers for various reasons, as well as the use of probability theory to predict the location of power point and control how it would move before not after it did. Practically, we utilized available PV systems devices to test our controlled systems and we used simulations and compare our findings with previous work done by others in this area and our techniques showed good improvement in efficiency and we believe that it could open the door for other colleagues to add valuable work in this important field.