<abstract xml:lang="en" xmlns="http://www.w3.org/1999/xhtml"><p>This paper presents an improved stator flux oriented (SFO) control system for a stand-alone induction generator. The induction generator supplies a variable resistive dc load. In order to provide an essentially constant terminal voltage, the product of the rotor speed and the stator flux reference should remain constant. However, in this case the control system is not able to function properly at different loads and dc-link voltages. In this paper, we introduce a new algorithm in which this product is constant at certain dc-load and dc-link voltage references. The dependence of the stator flux reference on the dc load and dc voltage reference is mapped using an artificial neural network (ANN). We also present an analysis of the efficiency of the SFO control system, as well as its performance during transients, over a wide range of both dc-link voltage references and loads. The validity of the proposed approach is verified by realistic simulation in a Matlab-Simulink environment.</p></abstract>

This paper presents an improved stator flux oriented (SFO) control system for a stand-alone induction generator. The induction generator supplies a variable resistive dc load. In order to provide an essentially constant terminal voltage, the product of the rotor speed and the stator flux reference should remain constant. However, in this case the control system is not able to function properly at different loads and dc-link voltages. In this paper, we introduce a new algorithm in which this product is constant at certain dc-load and dc-link voltage references. The dependence of the stator flux reference on the dc load and dc voltage reference is mapped using an artificial neural network (ANN). We also present an analysis of the efficiency of the SFO control system, as well as its performance during transients, over a wide range of both dc-link voltage references and loads. The validity of the proposed approach is verified by realistic simulation in a Matlab-Simulink environment.

A Stand-Alone Induction Generator with Improved Stator Flux Oriented Control

Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split, R. Boškovića 32, 21000 Split, Croatia

Journal of Electrical Engineering

{"article-title":"A Stand-Alone Induction Generator with Improved Stator Flux Oriented Control"}

This paper presents an improved stator flux oriented (SFO) control system for a stand-alone induction generator. The induction generator supplies a variable...

A Stand-Alone Induction Generator with Improved Stator Flux Oriented Control

Online veröffentlicht: 07. Juni 2011

Seitenbereich: 65 - 72

DOI: https://doi.org/10.2478/v10187-011-0011-5

Schlüsselwörter
automation, induction generator, neural networks, efficiency, stator field control

This content is open access.

A Stand-Alone Induction Generator with Improved Stator Flux Oriented Control

Online veröffentlicht: 07. Juni 2011

Seitenbereich: 65 - 72

DOI: https://doi.org/10.2478/v10187-011-0011-5

Schlüsselwörterautomation, induction generator, neural networks, efficiency, stator field control

This content is open access.

Schlüsselwörter
automation, induction generator, neural networks, efficiency, stator field control