This paper is aimed at harvesting the photovoltaic systems extracting power under difficult irradiance and load conditions, by proposing a novel maximum power point tracking (MPPT). This proposed MPPT tactic has been examined under various climatic and load conditions using two powerful and accurate simulation environments for PV systems, MATLAB/Simulink and Proteus. The first implementation using the MATLAB/Simulink software was carried out to examine the performance of the novel MPPT tactic under sudden insolation and load change, where the second implementation using the Proteus software was carried out in order to prove that the novel MPPT tactic can be easily implemented using low-cost components, Arduino board, and LCD display. The simulation results prove that the novel MPPT tactic has a high convergence speed to locate the MPP, especially at fast solar irradiation and load variation with zero oscillation under steady-state operation, which takes less than 9.6 milliseconds (ms) under the MATLAB/Simulink software and 0.24 microseconds (μs) under Proteus environment. That means it is about six times faster than P&O and five times faster than INC MPPT methods, and its tracking efficiency is between 99.40% and 99.86%. Furthermore, the novel MPPT tactic shows the best tracking accuracy and better ability to mitigate power losses under overall simulation scenarios compared with other traditional MPPT methods.
The problem of controlling reduced‐part three‐phase shunt active power filters is addressed in the presence of nonlinear loads. The control objective is twofold: (i) compensation of the current harmonics and the reactive power absorbed by the nonlinear load in order to ensure a satisfactory power factor correction (PFC) at the grid‐filter connection point; (2) regulation of the DC bus voltage at the inverter input. The considered control problem entails several difficulties including: (1) the high dimension and strong nonlinearity of the system; (ii) the numerous state variables that are inaccessible to measurements; (iii) the system parameter uncertainty. The problem is dealt with by designing a nonlinear adaptive controller with cascade structure including two control loops. The inner‐loop regulator is designed using the Lyapunov technique to ensure the PFC objective, while the outer‐loop involves a linear PI type control law for DC bus voltage regulation. The controller also includes an adaptive observer estimating the grid voltages and impedances parameters. The resulting control performances are formally analyzed using the averaging theory. Simulation results are presented illustrating the performances and the strong robustness of the proposed control strategy.
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