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The present study sheds new light on advanced control methods of photovoltaic (PV) emulators using finite set model predictive control (FS-MPC). In the first part of the study, a predictive PV emulator (P-PVE) based on a Buck converter is proposed and tested under hard climatic conditions and load variations. The high performance of the P-PVE in terms of dynamic response, reference tracking, accuracy, simplicity, and efficiency is confirmed experimentally when compared with those of the commonly used one based PI controller. The second part of the study proposes an efficient cascaded predictive control (CPC) method applied on two topologies of PV systems, namely the stand-alone system and the grid-connected system. In each topology, the P-PVE is cascaded to a maximum power point tracking Boost converter in order to track efficiently the maximum power point. In addition to the high performance offered by the FS-MPC, the proposed control strategy allows to control all cascaded converters at the same time in one stage instead of controlling them separately, thus providing more flexibility and simple controllability. Extensive experimental results are done confirming the correctness and the effectiveness of the proposed CPC under hard climatic conditions, even in the presence of distorted grid voltage.

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The paper presents a predictive direct power control of a Doubly Fed Induction Generator (DFIG) via a Direct Matrix Converter (DMC) for use in variable speed Wind Energy Conversion System (WECS). The proposed control method combines the merits of Finite States Model Predictive Control (FSMPC) in term of flexibility to the ones of DFIG control in term of maximum power extraction over a large range of wind speeds. The proposed control algorithm selects the switching state of the Direct Matrix Converter (DMC) that minimizes the error between rotor currents predictions to their computed values for all different voltage vectors.The optimal voltage vector that minimizes a cost function is then applied to the DFIG rotor terminal. Moreover, the proposed predictive control is easily extended to minimize the stator and rotor reactive power with unity power factor operation. Simulation results show that the proposed control method is intuitive since it is simple, multiobjective, avoids inner loops and provides best dynamic performance.

This paper presents an improved control method of variable speed Wind Energy Conversion System (WECS). The power conversion chain uses Doubly Fed Induction Generator (DFIG) supplied via Matrix Converter (MC) to ensure reliability and good energy conversion management. The proposed hybrid control method combines the merits of Sliding Mode Control (SMC) in term of robustness and high dynamic response in transients to those of Proportional Integral (PI) regulators in term of stability in steady state for constant references. The designed method uses a Fuzzy Logic Supervisor (FLS) that can switches between the two modes according to desired performance. The proposed hybrid controller is applied as a Maximum Power Point Tracker (MPPT) for two wind speed profiles, the first changes abruptly, and here we had take into account the low frequency component of the wind speed model, and the second profile take the complete wind speed model (low and high frequency components). The purpose of using two wind profile is to depict the advantages and disadvantageous of each control mode. The proposed control method provides best efficiency of the conversion chain especially for medium and high power generation systems, also, very attractive results in term of reference tracking and oscillations around Optimal Power Points (OPP) are achieved providing quick and smooth energy conversion. In addition, a unified power factor and low harmonic distortion are also achieved in the grid side.

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