Adaptive Control Strategy for Low Voltage Ride Through Capability Enhancement of A Grid-Connected Switched Reluctance Wind Generator

This paper presents the application of an adaptive control strategy to enhance the low voltage ride through (LVRT) capability of a grid-connected switched reluctance wind generator. In this study, the switched reluctance generator (SRG) is driven by a variable-speed wind turbine and connected to the grid through an asymmetric half bridge inverter, DC-link, and DC-AC inverter system. The adaptive proportional-integral (PI) controllers are used to control the power electronic circuits. The Widrow-Hoff adaptation algorithm is used in this study. The Widrow-Hoff delta rule can be used to adapt the PI controllers' parameters. The detailed modelling and control strategies of the overall system are presented. The effectiveness of the proposed control scheme is verified under a severe symmetrical grid fault condition. The validity of the proposed system is verified by the simulation results, which are carried out using PSCAD/EMTDC.

[1]  Hany M. Hasanien,et al.  Transient stability enhancement of wind farms connected to a multi-machine power system by using an adaptive ANN-controlled SMES , 2014 .

[2]  Hany M. Hasanien,et al.  A Set-Membership Affine Projection Algorithm-Based Adaptive-Controlled SMES Units for Wind Farms Output Power Smoothing , 2014, IEEE Transactions on Sustainable Energy.

[3]  Jeffrey H. Lang,et al.  The control of high-speed variable-reluctance generators in electric power systems , 1993 .

[4]  C. Ferreira,et al.  Detailed design of a 30-kW switched reluctance starter/generator system for a gas turbine engine application , 1993, Conference Record of the 1993 IEEE Industry Applications Conference Twenty-Eighth IAS Annual Meeting.

[5]  Hany M. Hasanien,et al.  Torque ripple minimization of axial laminations switched reluctance motor provided with digital lead controller , 2010 .

[6]  Hany M. Hasanien,et al.  Transient stability enhancement of a grid-connected wind farm using an adaptive neuro-fuzzy controlled-flywheel energy storage system , 2015 .

[7]  Hany M. Hasanien,et al.  A Taguchi Approach for Optimum Design of Proportional-Integral Controllers in Cascaded Control Scheme , 2013, IEEE Transactions on Power Systems.

[8]  Hany M. Hasanien,et al.  Affine projection algorithm based adaptive control scheme for operation of variable-speed wind generator , 2015 .

[9]  J. Clare,et al.  Control of a switched reluctance generator for variable-speed wind energy applications , 2005, IEEE Transactions on Energy Conversion.

[10]  Hany M. Hasanien,et al.  FPGA implementation of adaptive ANN controller for speed regulation of permanent magnet stepper motor drives , 2011 .

[11]  Eyhab El-Kharashi,et al.  Reconstruction of the Switched Reluctance Motor Stator , 2012 .

[12]  Hany M. Hasanien,et al.  Dynamic response improvement of doubly fed induction generator-based wind farm using fuzzy logic controller , 2012 .

[13]  Hany M. Hasanien,et al.  Reduction of frequency fluctuation for wind farm connected power systems by an adaptive artificial neural network controlled energy capacitor system , 2012 .

[14]  S. M. Muyeen,et al.  Design Optimization of Controller Parameters Used in Variable Speed Wind Energy Conversion System by Genetic Algorithms , 2012, IEEE Transactions on Sustainable Energy.

[15]  David A. Torrey Variable-reluctance generators in wind-energy systems , 1993, Proceedings of IEEE Power Electronics Specialist Conference - PESC '93.

[16]  R. Cardenas,et al.  Switched reluctance generators for wind energy applications , 1995, Proceedings of PESC '95 - Power Electronics Specialist Conference.

[17]  Iqbal Husain,et al.  Fault analysis and excitation requirements for switched reluctance generators , 1999, IEEE International Electric Machines and Drives Conference. IEMDC'99. Proceedings (Cat. No.99EX272).

[18]  Hany M. Hasanien,et al.  Harmony Search Algorithm-Based Controller Parameters Optimization for a Distributed-Generation System , 2015, IEEE Transactions on Power Delivery.

[19]  Roberto Cárdenas,et al.  Sensorless Control for a Switched Reluctance Wind Generator, Based on Current Slopes and Neural Networks , 2009, IEEE Transactions on Industrial Electronics.

[20]  L. Ribickis,et al.  One-phase reluctance generators in low-power wind plants , 2007, 2007 European Conference on Power Electronics and Applications.