Neural Network Controller for a Permanent Magnet Generator Applied in Wind Energy Conversion System

Mona N. Eskander 전력전자학회 2002 JOURNAL OF POWER ELECTRONICS Vol.2 No.1

In this paper a neural network controller for achieving maximum power tracking as well as output voltage regulation, for a wind energy conversion system (WECS) employing a permanent magnet synchronous generator is proposed The permanent magnet generator (PMG) supplies a de load via a bridge rectifier and two buck-boost converters Adjusting the switching frequency of the first buck-boost converter achieves maximum power tracking. Adjusting the switching frequency of the second buck-boost converter allows output voltage regulation The on-time of the switching devices of the two converters are supplied by the developed neural network (NN) The effect of sudden changes in wind speed and! or in reference voltage on the performance of the NN controller are explored Simulation results showed the possibility of achieving maximum power tracking and output voltage regulation simultaneously with the developed neural network controllers. The results proved also the fast response and robustness of the proposed control system.

Mitigation of Voltage Dips and Swells in Grid-Connected Wind Energy Conversion Systems

Mona N. Eskander,Sanaa I. Amer 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8

This paper investigates two methods for mitigation of voltage dips and voltage swells in a grid to which a wind energy conversion system (WECS) is connected. The two mitigation methods are the dynamic voltage regulator (DVR), and the static compensator (STATCOM). The wind energy system employs permanent magnet synchronous generator (PMSG). It is well known that the voltage dips affect the PMSG adversely, leading to unlimited increase in its speed. Hence, quick voltage dip mitigation is required. The responses of both DVR and STATCOM to voltage dips as well as voltage swells are investigated and compared. Also the active and reactive power behaviors in each system during and after fault recovery are investigated. The simulation results compared for voltage dips and voltage swells show less harmonic contents for the system employing the DVR. However, the response of the two systems to faults are comparable.

Minimization of Losses in Permanent Magnet Synchronous Motors Using Neural Network

Eskander, Mona N. The Korean Institute of Power Electronics 2002 JOURNAL OF POWER ELECTRONICS Vol.2 No.3

In this paper, maximum efficiency operation of two types of permanent magnet synchronous motor drives, namely; surface type permanent magnet synchronous machine (SPMSM) and interior type permanent magnet synchronous motor(IPMSM), are investigated. The efficiency of both drives is maximized by minimizing copper and iron losses. Loss minimization is implemented using flux weakening. A neural network controller (NNC) is designed for each drive, to achieve loss minimization at difffrent speeds and load torque values. Data for training the NNC are obtained through off-line simulations of SPMSM and IPMSM at difffrent operating conditions. Accuracy and fast response of each NNC is proved by applying sudden changes in speed and load and tracking the UC output. The drives'efHciency obtained by flux weakening is compared with the efficiency obtained when setting the d-axis current component to zero, while varying the angle of advance "$\vartheta$" of the PWM inverter supplying the PMSM drive. Equal efficiencies are obtained at diffErent values of $\vartheta$, derived to be function of speed and load torque. A NN is also designed, and trained to vary $\vartheta$ following the derived control law. The accuracy and fast response of the NN controller is also proved.so proved.

Neural Network Controller for a Permanent Magnet Generator Applied in Wind Energy Conversion System

Eskander, Mona N. The Korean Institute of Power Electronics 2002 JOURNAL OF POWER ELECTRONICS Vol.2 No.1

In this paper a neural network controller for achieving maximum power tracking as well as output voltage regulation, for a wind energy conversion system (WECS) employing a permanent magnet synchronous generator is proposed. The permanent magnet generator (PMG) supplies a dc load via a bridge rectifier and two buck-boost converters. Adjusting the switching frequency of the first buck-boost converter achieves maximum power tracking. Adjusting the switching frequency of the second buck-boost converter allows output voltage regulation. The on-time of the switching devices of the two converters are supplied by the developed neural network (NN). The effect of sudden changes in wind speed and/ or in reference voltage on the performance of the NN controller are explored. Simulation results showed the possibility of achieving maximum power tracking and output voltage regulation simulation with the developed neural network controllers. The results proved also the fast response and robustness of the proposed control system.

NEURAL NETWORK CONTROLLER FOR A PERMANENT MAGNET GENERATOR APPLIED IN WIND ENERGY CONVERSION SYSTEM

Mona N.Eskander 전력전자학회 2001 ICPE(ISPE)논문집 Vol.2001 No.10

In this paper a neural network controller for achieving maximum power tracking as well as output voltage regulation, for a wind energy conversion system(WECS) employing a permanent magnet synchronous generator, is proposed The permanent magnet generator (PMG) supplies a dc load via a bridge rectifier and two buck-boost converters Adjusting the switching frequency of the first buck-boost converter achieves maximum power tracking Adjusting the switching frequency of the second buck-boost converter allows output voltage regulation The on-timesof the switching devices ofthe two converters are supplied by thedeveloped neura! network(NN), The effect of sudden changes in wind speed ,and/or in reference voltage on the performance of the NN controller are explored Simulation results showed the possibility of achieving maximum power tracking and output voltage regulation simultaneously with the developed neural network controller The results proved also the fast response and robustness of the proposed control system.

Minimization of Losses in Permanent Magnet Synchronous Motors Using Neural Network

Mona N,Eskander 전력전자학회 2002 JOURNAL OF POWER ELECTRONICS Vol.2 No.3

In this paper, maximum efficiency operation of two types of permanent magnet synchronous motor drives, namely, surface type permanent magnet synchronous machine (SPMSM) and interior type permanent magnet synchronous motor (IPMSM), are investigated The efficiency of both drives is maximized by minimizing copper and iron losses. Loss minimization is implemented using flux weakening. A neural network controller (NNC) is designed for each drive, to achieve loss minimization at different speeds and load torque values. Data for training the NNC are obtained through off-simulations of SPMSM and IPMSM at different operating conditions Accuracy and fast response of each NNC is proved by applying sudden changes m speed and load and tracking the NNC output The drives' efficiency obtained by flux weakening is compared with the efficiency obtained when setting the d-axis current component to zero, while varying the angle of advance "?" of the PWM inverter supplying the PMSM drive. Equal efficiencies are obtained at different values of ?, derived to be function of speed and load torque A NN is also designed, and trained to vary ? following the derived control law The accuracy and fast response of the NN controller is also proved.

Performance of Double Fed Induction Machine at Sub- and Super-Synchronous Speed in Wind Energy Conversion System

Eskander, Mona N.,Saleh, Mahmoud A.,El-Hagry, Mohsen M.T. The Korean Institute of Power Electronics 2009 JOURNAL OF POWER ELECTRONICS Vol.9 No.4

In this paper two modes of operating a wound rotor induction machine as a generator at sub-and super-synchronous speeds in wind energy conversion systems are investigated. In the first mode, known as double fed induction generator (DFIG), the rotor circuit is fed from the ac mains via a controlled rectifier and a forced commutated inverter. Adjusting the applied rotor voltage magnitude and phase leads to machine operation as a generator at sub-synchronous speeds. In the second mode, the machine is operated in a slip recovery scheme where the slip energy is fed back to the ac mains via a rectifier and line commutated inverter. This mode is described as double output induction generator (DOIG) leading to increase the efficiency of the wind-to electrical energy conversion system. Simulated results of both modes are presented. Experimental verification of the simulated results are presented for the DOIG mode of operation, showing larger amount of power captured and better power factor when compared to conventional induction generators.

Performance of Double Fed Induction Machine at Sub- and Super-Synchronous Speed in Wind Energy Conversion System

Mona N. Eskander,Mahmoud A.Saleh,Mohsen M.T. El-Hagry 전력전자학회 2009 JOURNAL OF POWER ELECTRONICS Vol.9 No.4

In this paper two modes of operating a wound rotor induction machine as a generator at sub-and super-synchronous speeds in wind energy conversion systems are investigated. In the first mode, known as double fed induction generator (DFIG), the rotor circuit is fed from the ac mains via a controlled rectifier and a forced commutated inverter. Adjusting the applied rotor voltage magnitude and phase leads to machine operation as a generator at sub-synchronous speeds. In the second mode, the machine is operated in a slip recovery scheme where the slip energy is fed back to the ac mains via a rectifier and line commutated inverter. This mode is described as double output induction generator (DOIG) leading to increase the efficiency of the wind-to electrical energy conversion system. Simulated results of both modes are presented. Experimental verification of the simulated results are presented for the DOIG mode of operation, showing larger amount of power captured and better power factor when compared to conventional induction generators.