Sensorless model predictive control scheme of wind-driven doubly fed induction generator in dc microgrid

Research output: Contribution to journalArticle

33 Citations (Scopus)

Abstract

This study presents a novel sensorless model predictive control (MPC) strategy of a wind-driven doubly fed induction generator (DFIG) connected to a dc microgrid. In this configuration, the stator is directly connected to the dc microgrid through a diode rectifier, and the rotor is fed by only a voltage source converter (VSC). This connection structure brings considerable benefits such as simple control scheme and reduced power converter cost. In order to obtain sensorless operation, a simple and effective sensorless position detection technique has been proposed. It is based on the detection of the stator frequency, and it is designed to operate without any machine parameters. Thus, the proposed sensorless method offers as a model-free solution. In addition, the MPC strategy has been used as a current controller to overcome the weaknesses of the inner control loop and to consider the discrete-Time operation of the VSC. The proposed control system is robust against machine parameters, speed, and load variations. To verify the dynamic and steady-state performances of the proposed sensorless MPC scheme under various speed and load conditions, experimental studies are performed with 6.4 kW DFIG. Experimental results aim to show that the proposed sensorless MPC strategy works properly at steady state and in transient.

Original languageEnglish
Pages (from-to)514-521
Number of pages8
JournalIET Renewable Power Generation
Volume10
Issue number4
DOIs
Publication statusPublished - 1 Apr 2016

Fingerprint

Asynchronous generators
Model predictive control
Stators
Electric potential
Power converters
Diodes
Rotors
Control systems
Controllers
Costs

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment

Cite this

Sensorless model predictive control scheme of wind-driven doubly fed induction generator in dc microgrid. / Bayhan, Sertac; Abu-Rub, Haitham; Ellabban, Omar.

In: IET Renewable Power Generation, Vol. 10, No. 4, 01.04.2016, p. 514-521.

Research output: Contribution to journalArticle

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