Improvement of the Dynamic Response of Robust Sliding Mode MPPT Controller-Based PSO Algorithm for PV Systems under Fast-Changing Atmospheric Conditions

Abstract

To get the maximum power point (MPP), the algorithms developed in the literature fail for the most part when the atmospheric conditions vary rapidly. This paper presents the optimization by the swarm particles (PSO) of a sliding mode controller (SMC) to optimize photovoltaic systems (PV) evolving under the conditions of a rapid variation of the sunshine. The stochastic PSO algorithm is used in particular to determine the optimal gains of the sliding mode controller, and this algorithm guarantees the stability and global fast convergence of the system. Efficiency of the proposed hybrid algorithm is proved by using a Solarex MSX-60 module connected to a step-up DC-DC converter supplying a resistive load. The performances are compared to the conventional perturb and observe technique (P&O), PSO, CUCKOO, grey wolf optimization (GWO), and Whale Optimization Algorithm (WOA) in terms of convergence speed, i.e., 0.05 s, tracking speed after extreme change in irradiance 0.03 s, high Ability to track large changes in power before 1 s. Simulation results show that this technique is effective in conditions of a rapid variation of the irradiance.

Designing of a PSO-Based Adaptive SMC With a Multilevel Inverter for MPPT of PV Systems Under Rapidly Changing Weather Conditions

“…The SMC-PSO algorithm addresses the issues with the P&O by improving the speed of convergence, minimizing overshoot and oscillation, and enhancing the rate of reaching the MPP when the irradiance undergoes rapid and decreasing changes. This algorithm is shown to rapidly converge, which is faster than other algorithms, such as P&O, CUCKOO, GWO, and WOA [22]. The text asserts that the primary constraint remains energy efficiency.…”

Maximum power point tracker using an intelligent sliding mode controller of a photovoltaic system

“…The solution put forth in this work entails taking into account two controllers working in cascade as the INC controller, which is intended to provide a reference proportional to the photovoltaic generator's PMPP, and the SMC controller, which is in charge of the GPV's regulation. Second order voltage mode (PID) SMC controller is the controller under investigation [26]. In order to lower the steady-state error of the real system managed by the SM, it incorporates an additional integral voltage error component into the control algorithm.…”

Novel robust approach–based dynamic global terminal synergetic tracking control for uncertain second-order systems: Wind turbine system and power converter applications

“…Nevertheless, the challenge of controlling such systems with uncertainties remains a crucial research area in the field of control engineering. In recent years, scientific communities have designed a number of unconventional control algorithms, including sliding mode control (SMC), [1][2][3][4][5] fuzzy logic type I and type II controllers, 6,7 model predictive control, [8][9][10] model independent control, 11,12 and back-stepping control. 13 All these approaches have found use in diverse applications; for instance, in Cuvillon et al, 8 an offset-free nonlinear model predictive control (NMPC) was designed to mitigate platform vibration and reduce the tracking error along complex trajectories of cabledriven parallel robots.…”