Niroj Gurung

Reduced order model based state feedback control of Doubly Fed Induction Generators

A state feedback control strategy for Doubly Fed Induction Generator (DFIGs) is investigated. Both the rotor side converter and grid side converter control of DFIG has been designed using the proposed state feedback control technique. A comparison between the traditional PI based vector control (VC) of DFIG with the proposed form of control has also been presented. It has been shown that this methodology helps in easier controller design for DFIG, exhibits competitive performance in terms of low interaction between power and voltage control and provides better system damping. The simulation results for a system connected to a grid through a transmission line have been presented and the capabilities of the proposed controller are discussed.

Minimum variance adaptive speed estimation technique for vector control of Doubly Fed Induction Generator

This paper presents a novel sensor-less speed estimation technique applicable for vector control of the Doubly Fed Induction Generator (DFIG). The proposed technique can substitute the use of speed sensors and rotor position measurements. The proposed method is based on online identification of system parameters that minimizes the speed estimation error using minimum variance controller based on the machine rotor currents. The paper explains about the design of the controller and small signal model of the DFIG for the controller design. The technique is validated both in MATLAB Simulink and Opal RTs Real Time simulation platform for a 2kW Doubly Fed Induction Machine setup.

Minimum variance controller based adaptive control for Doubly fed induction generator

This paper presents a system identification based minimum variance controller for active and reactive power control of Doubly Fed Induction Generator (DFIG). The controller is adaptive as the parameters in the control law are updated online based on system identification that relate the output (active and reactive power) and the input (direct and quadrature axis rotor voltages). The main advantage of the proposed controller is the simplicity in design, its adaptability under varying operating conditions and the ability of the controller to perform without the need to measure rotor side quantities. The paper discusses the design of the controller and presents the simulation results from tests performed using MATLAB SimPowerSystems. The results show that the proposed controller can be a better alternative to the existing PI based vector control for DFIG.

Reduced order state observer based feedback control methodologies for doubly fed induction generator (DFIG)

In this paper, a reduced order state observer for DFIG is designed that estimate the states with just using DFIGs stator voltage and power measurements. Further, the proposed state observer is used to provide two control strategies for Rotor Side Converter (RSC) of DFIG a) state estimator based state feedback control and b) state estimator based vector control. The state observer and controllers were tested for varying wind conditions using a full order dynamic model of DFIG with a real-time simulation platform. The results verify that the proposed state observer can augment existing control for DFIG with better tracking of the system output without the need for feedback measurements, and at the same time it can reduce the controller design complexity. Also, these state estimator based controllers eliminate the need of rotor current sensors for DFIG control.

Parametrically robust dynamic speed estimation based control for doubly fed induction generator

This paper presents a speed estimation based vector control architecture for Doubly Fed Induction Generator (DFIG). The main advantage of the proposed architecture is that with this methodology the generator can be operated without a speed sensor and position encoder. The method calculates the machine parameters online using a recursive least square (RLS) technique based on identifying the transfer function relating to rotor speed and position error. A minimum variance regulator ensures that the position error is minimum by proper estimation of the speed. For illustration, first, the small signal model of the machine and the regulator design is discussed. Then, a methodology is proposed, in which machines mutual inductance is estimated online, so that the estimation approach is robust to changes in the machine parameters. Second, the control architecture with the speed estimation technique is discussed. The proposed approach is validated using a real-time simulation platform for a GE 1.5 MW wind turbine and with hardware-in-the-loop experimental set up for a 2kW Doubly Fed Induction Machine (DFIM).

Control of grid connected inverters using minimum variance adaptive architecture

This paper presents a system identification based minimum variance architecture for active and reactive power control of a Grid Connected Inverter (GCI). The controller is adaptive as the parameters in the control law are updated online based on identification that relate the output (active and reactive power) and the input (direct and quadrature axis voltage references). The main advantage of the proposed controller is the simplicity in design and its adaptability under varying operating conditions. The paper discusses the design of the controller and presents the simulation results from tests performed using MATLAB SimPowerSystems along with the Hardware-in-the-loop (HIL) implementation. The results show that the proposed controller can be a better alternative to the existing cascaded PI based vector control for grid connected inverters.

Discrete real-time state observer based feedback control methodology for Doubly Fed Induction machine

In this paper, a discrete form of reduced order state observer for Doubly Fed Induction Generator (DFIG) is designed that estimates the machine states and rotor currents using stator voltage and power measurements. Further, the proposed state observer is used to provide a state feedback control strategy for Rotor Side Converter (RSC) of DFIG. The state observer and controller were tested on varying operating condition in Hardware-in-the-loop (HIL) simulation platform. The results verify that the state observer can be used in existing form of control for DFIG with better tracking of output and at the same time reduce the complexity and need for measurements. Also, these state estimator based controllers eliminate the need of rotor current sensors for DFIG control.