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

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.

Enhancing PEM fuel cell efficiency with flying squirrel search optimization and Cuckoo Search MPPT techniques in dynamically operating environments

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Modeling of intelligent controllers for solar photovoltaic system under varying irradiation conditions

“…Following are the potential advantages or strengths of using MPPTs for solar PV systems (Giurgi et al, 2022;Hadj Salah et al, 2023).…”

Real-Time Implementation of a Hybrid ESC Approach for Maximising the Extracted Photovoltaic Power Under Partial Shading Conditions

“…Several research studies have been carried out to improve the performance of these techniques (Loukriz et al, 2016;Tey and Mekhilef, 2014;Soon and Mekhilef., 2014). As a result, recently, other adaptive algorithms, such as the sliding mode control (SMC) (Menadi et al, 2015), super twisting (ST) control (Hadj Salah et al, 2023) and extremum seeking control (ESC), have been proposed (Krstić, 2000;Leyva et al, 2006). ESC and its applications have been extensively studied, including the MPPT for the PV generators (Malek et al, 2012).…”