Advanced Variable Step Size Incremental Conductance MPPT for a Standalone PV System Utilizing a GA-Tuned PID Controller

Adeel Feroz Mirza, Majad Mansoor, Qiang Ling, Muhammad Imran Khan and Omar M. Aldossary
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Adeel Feroz Mirza: Department of Automation, University of Science and Technology of China, Hefei 230027, China
Majad Mansoor: Department of Automation, University of Science and Technology of China, Hefei 230027, China
Qiang Ling: Department of Automation, University of Science and Technology of China, Hefei 230027, China
Muhammad Imran Khan: Hefei National Lab for Physical Sciences at the Microscale and the Centers for Biomedical Engineering, University of Science and Technology of China, Hefei 230027, China
Omar M. Aldossary: Department of Physics and Astronomy, College of Science, King Saud University, PO Box 2455, Riyadh 11451, Saudi Arabia

Energies, 2020, vol. 13, issue 16, 1-25

Abstract: In this article, a novel maximum power point tracking (MPPT) controller for the fast-changing irradiance of photovoltaic (PV) systems is introduced. Our technique utilizes a modified incremental conductance (IC) algorithm for the efficient and fast tracking of MPP. The proposed system has a simple implementation, fast tracking, and achieved steady-state oscillation. Traditional MPPT techniques use a tradeoff between steady-state and transition-state parameters. The shortfalls of various techniques are studied. A comprehensive comparative study is done to test various existing techniques against the proposed technique. The common parameters discussed in this study are fast convergence, efficiency, and reduced oscillations. The proposed method successfully addresses these issues and improves the results significantly by using a proportional integral deferential (PID) controller with a genetic algorithm (GA) to predict the variable step size of the IC-based MPPT technique. The system is designed and tested against the perturbation and observation (P&O)-based MPPT technique. Our technique effectively detects global maxima (GM) for fast-changing irradiance due to the adopted GA-based tuning of the controller. A comparative analysis of the results proves the superior performance and capabilities to track GM in fewer iterations.

Keywords: genetic algorithm (GA); photovoltaic (PV); maximum power point tracking (MPPT); incremental conductance (IC); proportional integral deferential (PID); local maxima (LM); global maxima (GM) (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

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