In distributed power generation systems, grid-connected inverters are becoming an attractive means of delivering the energy generated from renewable sources into the grid. However, the performance of the current controller drastically decreases in the presence of model uncertainty, grid harmonics, filter parametric, and grid impedance variations, which can jeopardize the entire system’s stability. This paper presents a novel design of a super-twisting integral sliding mode control (ST-ISMC) strategy for the first time in the application of a three-phase voltage source grid-connected inverter. The designed controller has shown robustness and maintains a low total harmonic distortion (THD) in the presence of filter parameters drift, grid impedance variation, and grid harmonics distortion. The super-twisting action is added to remove the chattering problem associated with the conventional SMC strategy, and integral action is adopted to improve the grid’s current steady-state error. The modeling and simulation of a complete system are carried out using MATLAB/SIMULINK. Finally, a real-world hardware prototype system is fabricated to demonstrate the performance and effectiveness of the proposed controller.

Power point tracker algorithms play an important role in the optimization of the power and the efficiency of a photovoltaic generator. This work presents a comparative study of performance Maximum Power Point Tracker (MPPT) algorithms for fast changing conditions on the PV panels. We made the comparison between algorithms currently implemented for the power optimization of photovolatic system. These algorithms are based on the Perturb Observe and the Conductance-Increment methods allowing the Maximum Power Point Tracking MPPT principle. In this study we compares the speed and ripple around the optimal point for each search technique.

The present work describes the analysis, modeling and control of a cascade DC-DC and DC-AC power conditioning stage to control a output voltage to supply a DC and AC load systems. To maximize energy extracted from PV generator and control output voltage a RCC MPPT and backstepping controller are designed. The stability of the control algorithm is demonstrated by means of Lyapunov analysis. The achievement of the DC-DC and DC-AC conversions and the efficient PV's energy extraction are validated with simulation results.

This paper discusses open-circuit fault (OCF) diagnosis and fault-tolerant control strategy (FTCS) of a nonisolated DC-DC converter. The photovoltaic power conversion structure (PPCS) consists of a photovoltaic generator and an interleaved Boost converter (IBC). The maximum power point tracking (MPPT) control of the IBC ensures operation at maximum power. The design of the nonlinear Backstepping control is detailed based on the equivalent average model of IBC, and the stability is studied using Lyapunovs theorem. The proposed OCF fault detection is based on sampling the voltage across the inductor at a much higher frequency than the switching frequency. In an OCF situation occurrence and a high control signal state, the detection of three negative samples is a condition for signaling the presence of an OCF fault; the photovoltaic system continues its normal operation. The simulation results show the validity of the proposed FTCS. The proposed diagnosis and control strategy improves the performance of the IBC in terms of cost, reliability, and service continuity.