Grid integrated renewable DG systems: A review of power quality challenges and state-of-the-art mitigation techniques

The doubly fed induction generator (DFIG)-based wind energy conversion systems (WECSs) are prone to certain uncertainties, nonlinearities, and external disturbances. The maximum power transfer from WECS to the utility grid system requires a high-performance control system in the presence of such nonlinearities and disturbances. This paper presents a nonlinear robust chattering free super twisting fractional order terminal sliding mode control (ST-FOTSMC) strategy for both the grid side and rotor side converters of 2 MW DFIG-WECS. The Lyapunov stability theory was used to ensure the stability of the proposed closed-loop control system. The performance of the proposed control paradigm is validated using extensive numerical simulations carried out in MATLAB/Simulink environment. A detailed comparative analysis of the proposed strategy is presented with the benchmark sliding mode control (SMC) and fractional order terminal sliding mode control (FOTSMC) strategies. The proposed control scheme was found to exhibit superior performance to both the stated strategies under normal mode of operation as well as under lumped parametric uncertainties.

A Super Twisting Fractional Order Terminal Sliding Mode Control for DFIG-Based Wind Energy Conversion System

Grid synchronization techniques play a significant role in integrating renewable energy sources to the electric power grid. In this context, estimating the phase and frequency of the grid voltage signal is an interesting problem. Out of various techniques available in the literature, linear Kalman filter (LKF) is one of the most popular one. In this article, we propose an alternative implementation of the LKF for grid synchronization application. The proposed implementation uses a linear parametric model of the grid voltage signal including dc offset. It does not involve any quadrature signal generation, rather it works by estimating the phase angle. This helps to estimate the unknown grid frequency directly from the phase angle. This clearly differentiates the proposed alternative implementation with respect to the existing implementations. Performance improvement by the proposed technique is verified extensively through comparative numerical simulation and experimental studies. Comparative results demonstrate the suitability of the proposed technique with respect to other state-of-the-art techniques namely second-order generalized integrator phase-locked loop and enhanced phase-locked loop.

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Linear Kalman Filter-Based Grid Synchronization Technique: An Alternative Implementation

Les neurones, au nombre d’une centaine de milliards, sont les cellules de base du systeme nerveux central. Chaque neurone recoit des influx nerveux a travers ses dendrites (recepteurs), les integre pour en former un nouvel influx nerveux qu’il transmet a un neurone voisin par le biais de son axone (emetteur).

Réseaux de neurones

This Letter proposes demodulation type PLL for phase and frequency estimation of single-phase system that can reject DC offset. Using results from the adaptive estimation literature, this Letter proposes a linear parametric model-based initial phase angle estimation approach. Then by using differentiation and integration operation on the estimated initial phase angle, the frequency is estimated. This avoids the use of any low-pass filter unlike conventional demodulation-based technique. Moreover, unlike existing demodulation-based technique, the proposed technique can completely reject DC offset. Comparative experimental results, provided with state-of-the-art DC offset rejection-based enhanced phase locked-loop, clearly demonstrate the suitability of the proposed technique.

https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/el.2019.3718

Demodulation type single-phase PLL with DC offset rejection

This paper presents a novel robust phase locking control scheme for active power filters namely multiple self-tuning filters phase locked loop (M-STFs-PLL). This method uses a multiple self-tuning filters in stationary reference frame to cleanly extract and separate the positive and negative sequences voltage to improve the traditional PLL under highly unbalanced and/or distorted source voltage. The resultant M-STFs-PLL conducts then to a fast, precise and robust positive sequence. To demonstrate the effectiveness of the proposed approach, the direct shunt active power filter control method with the proposed PLL scheme is adopted and its performance is verified by means of simulation with different supply systems.

A novel robust PLL algorithm applied to the control of a shunt active power filter using a self tuning filter concept

By using the direct torque control (DTC), robust response in ac drives can be produced. Ripples of currents, torque and flux are oberved in steady state. space vector modulation (SVM) applied in DTC and used for a sensorless induction motor (IM) with fuzzy sliding mode speed controller (FSMSC) is studied in this paper. This control can minimize the torque, flux, current and speed pulsations in steady state. To estimate the rotor speed and stator flux the model reference adaptive system (MRAS) is used that is designed from identified voltages and currents. The FSMSC is used to enhance the efficiency and the robustness of the presented system. The DTC transient advantage are maintained, while better quality steady-state performance is produced in sensorless implementation for a wide speed range. The drive system performances have been checked by using Matlab Simultaion, and successful results have been obtained. It is deduced that the proposed control system produces better results than the classical DTC.

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DTC based on SVM for induction motor sensorless drive with fuzzy sliding mode speed controller

Contrôle avec les techniques de l’intelligence artificielle d’une source d’énergie éolienne à base d’une machine asynchrone à double alimentation

In this paper, neuronal direct power control (DPC) strategy is applied for a doubly fed induction generator (DFIG) based wind energy generation system. Used in three level neutral point clamped (NPC) rectifiers, to directly control of the active and reactive power, switching vectors for rotor side converter were selected from the optimal switching table using the estimated stator flux position and the errors of the active and reactive power, also the grid side is controlled by direct power control based a grid voltage position to ensure a constant DC- link voltage. This approach is validated by using MATLAB/SIMULINK software and simulation results can prove the excellent performance of this control as improving power quality and stability of wind turbine.

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Three-level NPC Converter-based Neuronal Direct Active and Reactive Power Control of the Doubly Fed Induction Machine for Wind Energy Generation

In this paper, we present the linearizing control technique controlled by a neuro-fuzzy regulator applied to the permanent magnet synchronous machine (PMSM). It permits decoupling and linearizing the system without taking into accounts the flux orientation. The nonlinear control (NLC) applied to the PMSM decompose the system into two mono variable, linear and independent subsystems. The neuro-fuzzy control permits to the speed and the Id current control is carried out by neuro-fuzzy regulators (ANFIS). The analysis of the results obtained by this type of nonlinear regulator shows the robustness characteristic with respect to the load perturbations and the parametric variations. A qualitative analysis of the evolution of the principal variables describing the behaviour of the global system (PMSM-Inverter (PWM)-Control) is developed by several tests of digital simulation in last stage.

Sarra Massoum

Papers

A novel robust PLL algorithm applied to the control of a shunt active power filter using a self tuning filter concept

DTC based on SVM for induction motor sensorless drive with fuzzy sliding mode speed controller

Contrôle avec les techniques de l’intelligence artificielle d’une source d’énergie éolienne à base d’une machine asynchrone à double alimentation

Three-level NPC Converter-based Neuronal Direct Active and Reactive Power Control of the Doubly Fed Induction Machine for Wind Energy Generation

Neuro-fuzzy control of an input output linearization of a permanent magnet synchronous machine fed by a three levels inverter