A New Efficient Cuckoo Search MPPT Algorithm Based on a Super-Twisting Sliding Mode Controller for Partially Shaded Standalone Photovoltaic System

Zahra Bel Hadj Salah (), Saber Krim, Mohamed Ali Hajjaji, Badr M. Alshammari, Khalid Alqunun, Ahmed Alzamil and Tawfik Guesmi
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Zahra Bel Hadj Salah: Electronic and Micro-Electronic Laboratory, LR99ES30, Faculty of Sciences, University of Monastir, Monastir 5000, Tunisia
Saber Krim: Laboratory of Automatic, Electrical Systems and Environment, National Engineering School of Monastir, University of Monastir, Monastir 5000, Tunisia
Mohamed Ali Hajjaji: Electronic and Micro-Electronic Laboratory, LR99ES30, Faculty of Sciences, University of Monastir, Monastir 5000, Tunisia
Badr M. Alshammari: Department of Electrical Engineering, College of Engineering, University of Ha’il, Ha’il 2240, Saudi Arabia
Khalid Alqunun: Department of Electrical Engineering, College of Engineering, University of Ha’il, Ha’il 2240, Saudi Arabia
Ahmed Alzamil: Department of Electrical Engineering, College of Engineering, University of Ha’il, Ha’il 2240, Saudi Arabia
Tawfik Guesmi: Department of Electrical Engineering, College of Engineering, University of Ha’il, Ha’il 2240, Saudi Arabia

Sustainability, 2023, vol. 15, issue 12, 1-38

Abstract: The impact of Partial Shading Conditions (PSCs) significantly influences the output of Photovoltaic Systems (PVSs). Under PSCs, the Power-Voltage (P-V) characteristic of the PVS unveils numerous power peaks, inclusive of local maxima and a global maximum. The latter represents the optimum power point. Traditional Maximum Power Point Tracking (MPPT) algorithms struggle to track the Global Maximum Power Point (GMPP). To address this, our study emphasizes the creation of a novel algorithm capable of identifying the GMPP. This approach combines the Cuckoo Search (CS) MPPT algorithm with an Integral Super-Twisting Sliding Mode Controller (STSMC) using their benefits to enhance the PVS performance under PSCs in terms of high efficiency, low power losses, and high-speed convergence towards the GMPP. The STSMC is a second-order Sliding Mode Control strategy that employs a continuous control action that attenuates the “chattering” phenomenon, caused when the first-order SMC technique is employed. Indeed, the proposed CS-STSMC-MPPT algorithm consists of two parts. The first one is based on the CS algorithm used for scanning the power-voltage curve to identify the GMPP, and subsequently generating the associated optimal voltage reference. The second part aims to track the voltage reference by manipulating the duty cycle of the boost converter. The proposed CS-STSMC-MPPT algorithm is featured by its strength against uncertainties and modeling errors. The obtained simulation results underline a high convergence speed and an excellent precision of the proposed method in identifying and tracking the GMPP with high efficiency under varying shading scenarios. For comparative purposes, this method is set against the hybrid CS-Proportional Integral Derivative, the conventional CS, the Particle Swarm Optimization, and the Perturb and Observe algorithms under different PSCs, including zero, weak, and severe shading. Simulation conducted in the Matlab/Simulink environment confirms the superior performance of the proposed CS-STSMC-MPPT algorithm in terms of precision, convergence speed, efficiency, and resilience.

Keywords: photovoltaic system; partial shading conditions; maximum power point tracking; cuckoo search algorithm; second-order super-twisting sliding mode control (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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