Mohand Ouhrouche

Wind speed sensorless maximum power point tracking control of variable speed wind energy conversion systems

A maximum power point tracking (MPPT) controller for variable speed wind energy conversion system (WECS) is proposed. The proposed method, without requiring the knowledge of wind speed, air density or turbine parameters, generates at its output the optimum speed command for speed control loop of rotor flux oriented vector controlled machine side converter control system using only the instantaneous active power as its input. The optimum speed commands which enable the WE to track peak power points are generated in accordance with the variation of the active power output due to the change in the command speed generated by the controller. The concept is analyzed in a direct drive variable speed permanent magnet synchronous generator (PMSG) WECS with back-to-back IGBT frequency converter. Vector control of the grid side converter is realized in the grid voltage vector reference frame. Simulation is carried out in order to verify the performance of the proposed controller.

MPPT Control Methods in Wind Energy Conversion Systems

Wind energy conversion systems have been attracting wide attention as a renewable energy source due to depleting fossil fuel reserves and environmental concerns as a direct consequence of using fossil fuel and nuclear energy sources. Wind energy, even though abundant, varies continually as wind speed changes throughout the day. The amount of power output from a wind energy conversion system (WECS) depends upon the accuracy with which the peak power points are tracked by the maximum power point tracking (MPPT) controller of the WECS control system irrespective of the type of generator used. This study provides a review of past and present MPPT controllers used for extracting maximum power from the WECS using permanent magnet synchronous generators (PMSG), squirrel cage induction generators (SCIG) and doubly fed induction generator (DFIG). These controllers can be classified into three main control methods, namely tip speed ratio (TSR) control, power signal feedback (PSF) control and hill-climb search (HCS) control. The chapter starts with a brief background of wind energy conversion systems. Then, main MPPT control methods are presented, after which, MPPT controllers used for extracting maximum possible power in WECS are presented.

A new scheme for sensorless induction motor control drives operating in low speed region

A novel simple stator resistance estimation technique for high-performance induction motor drives is proposed. It makes use of a synchronously revolving reference frame aligned with the stator current vector, so that the resistance can be straightforwardly derived from the mathematical model of the induction motor. A sensorless direct field orientation scheme is employed to validate the proposed solution, with the drive operating in the critical area of low speeds. A combination of two observers is used: a Kalman filter observer to estimate the rotor flux, and a MRAS observer for speed estimation. The stator resistance estimator alleviates the usual performance degradation of MRAS-based drives at low speeds, caused by the thermal drift of stator resistance. Computer simulations, including realistic disturbances, show high effectiveness of the described approach.

Original articles: Nonlinear predictive controller for a permanent magnet synchronous motor drive

A nonlinear predictive controller (NPC) for a permanent magnet synchronous motor (PMSM) is proposed in this paper. Its objective is high performance tracking of the rotor speed trajectory while maintaining the d-axis component of the armature current at zero. The load torque and the mismatched parameters are considered to be unknown perturbations. To ensure robustness against these perturbations, a disturbance observer is designed using a new gain function, and integrated into the control law. The combination of the nonlinear predictive controller and the disturbance observer works as a nonlinear controller. The overall closed-loop system is proved to be globally asymptotically stable depending on the design parameters. The validity of the proposed controller was tested by simulations. Satisfactory results were obtained with respect to the tracking of the speed trajectory and disturbance rejection.

Artificial neural network-based maximum power point tracking control for variable speed wind energy conversion systems

A new maximum power point tracking (MPPT) controller using artificial neural networks (ANN) for variable speed wind energy conversion system (WECS) is proposed. The algorithm uses Jordan recurrent ANN and is trained online using back propagation. The inputs to the networks are the instantaneous output power, maximum output power, rotor speed and wind speed, and the output is the rotor speed command signal for the WECS. The network output after a time step delay is used as the feed-back signal completing the Jordan recurrent ANN. Simulation is carried out in order to verify the performance of the proposed algorithm.

Nonlinear Predictive Control with Disturbance Observer for Induction Motor Drive

A nonlinear predictive control (NPC) law with a disturbance observer is presented. It is applied to induction motor in order to track speed and flux profiles. The prediction defined on finite horizon is carried out via Taylor series expansion. The load torque is considered as an unknown disturbance and it is estimated by a nonlinear observer. Using the nonlinear predictive control has simplified the structure of the dynamic observer. The combination of the predictive controller and the observer works as a nonlinear controller with an integral action. The stability of the whole system can be achieved by simple design parameters. The simulations show very satisfactory performance of the proposed controller for trajectories tracking, the robustness to parameters variations and the disturbance rejection are successfully achieved

Real time simulation of nonlinear generalized predictive control for wind energy conversion system with nonlinear observer

In order to make a wind power generation truly cost-effective and reliable, an advanced control techniques must be used. In this paper, we develop a new control strategy, using nonlinear generalized predictive control (NGPC) approach, for DFIG-based wind turbine. The proposed control law is based on two points: NGPC-based torque-current control loop generating the rotor reference voltage and NGPC-based speed control loop that provides the torque reference. In order to enhance the robustness of the controller, a disturbance observer is designed to estimate the aerodynamic torque which is considered as an unknown perturbation. Finally, a real-time simulation is carried out to illustrate the performance of the proposed controller.

A Novel Predictive Direct Torque Controller for Induction Motor Drives

A predictive direct torque controller (PDTC) for induction motors (IM) is proposed. It combines the direct torque control (DTC) and the predictive control (PC), and uses a predictive switching table to enhance the overall performance of the motor. A new type of PC is adopted for speed regulation with the use of a load torque observer, the torque being considered an unknown perturbation. A Kalman filter (KF) is used for reliable flux estimation. The validity of the proposed controller was experimentally confirmed on a rapid control prototyping station. The obtained results have proven superiority of the proposed control with respect to the speed trajectory tracking, torque and flux dynamic responses, and disturbance rejection. Also, a lower current distortion was observed with PDTC, in comparison with the regular DTC, due to increased mean inverter switching frequency.

Robust nonlinear generalized predictive control of a permanent magnet synchronous motor with an anti-windup compensator

This paper presents a robust nonlinear generalized predictive control (RNGPC) strategy applied to a permanent magnet synchronous motor (PMSM) for speed trajectory tracking and disturbance rejection. The nonlinear predictive control law is derived by using a newly defined design cost function. The Taylor series expansion is used to carry out the prediction in a finite horizon. No information about the external perturbation and parameters uncertainties are needed to ensure the robustness of the proposed RNGPC. Moreover, to maintain the phase current within the limits using saturation blocks, a cascaded structure is adopted and an anti-windup compensator is proposed. The validity of the proposed control strategy is implemented on a dSPACE DS1104 board driving in real-time a 0.25 kW PMSM. Experimental results have demonstrated the stability, robustness and the effectiveness of the proposed control strategy regarding trajectory tracking and disturbance rejection.

Sensorless control of PMSG in variable speed wind energy conversion systems

A sensorless control strategy for a permanent magnet synchronous generator (PMSG) in variable speed wind energy conversion system (WECS) is proposed. The proposed method is based on recursive least square estimation (RLSE) algorithm for rotor speed estimation using an equation containing only stator flux and current. Further, rotor position information used for coordinate transformation is computed using the estimated speed. Stator flux required for speed estimation is obtained using a programmable low pass filter (PLPF). The estimated speed is used as the feedback signal for the speed control loop of the vector controlled machine side converter control system whose command speed is obtained from a wind speed sensorless maximum power point tracking (MPPT) controller. The front end converter is vector controlled in grid voltage reference frame. Simulation is carried out in order to verify the proposed algorithm.