Zahra Bel Hadj Salah

This article presents a new strategy to enhance the maximum power point tracking method for optimal power extraction from photovoltaic (PV) panels, as well as an inverter control strategy for regulating the active and reactive power injected into the grid in a double-stage single-phase PV installation. The proposed method is based on a robust third-order super-twisting sliding mode control (TOSTC). In the first stage, TOSTC is used to control the boost converter in order to ensure fast and accurate tracking of the maximum power point, even under varying environmental conditions, while reducing chattering and minimizing power losses. In the second stage, TOSTC is applied to control the inverter current, enabling precise regulation of both active and reactive power injection, and significantly reducing harmonic distortion, accordingly, improving the overall power quality delivered to the grid. The article compares the performance of the TOSTC with conventional control methods, namely the proportional-integral controller for the boost converter and the proportional-resonant controller for the inverter, all implemented in the MATLAB/Simulink environment. Simulation results demonstrate the superiority of the TOSTC approach in terms of tracking speed, accuracy, and harmonic reduction. The stability of the proposed controller is validated using Lyapunov criteria, and its effectiveness is confirmed through simulations under both dynamic and steady-state conditions, highlighting the robustness and reliability of this innovative control strategy for grid-connected PV systems.

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.