Transactions on Machine Intelligence

Transactions on Machine Intelligence

Dynamic Stability Improvement of Synchronous Generator Using Suggested Controller in Reactive Power Band Of DFIG

Document Type : Original Article

Authors
A. Alavi Eshkaftaki 1
A. Rabiee 1
A. Kargar 2
S. Taghipour Boroujeni 2
1 Department of electrical engineering, Shahrekord University, Shahrekord, Iran
2 Department of Electrical Engineering, Shahrekord University, Shahrekord, Iran
10.47176/TMI.2022.11
Abstract
Ensuring the stability of synchronous generators is a fundamental challenge in modern power systems, particularly as grid dynamics become increasingly complex. Generator stability is typically classified into three categories: steady-state, dynamic, and transient. This study focuses on dynamic stability, which pertains to the system’s ability to maintain synchronism following small disturbances. In parallel, the growing demand for clean energy and the depletion of fossil fuel reserves have accelerated the integration of wind energy into the power grid. Among the various wind generation technologies, the Doubly-Fed Induction Generator (DFIG) has gained prominence due to its operational flexibility and controllability. This paper proposes a control strategy designed to enhance the dynamic stability of synchronous generators using the reactive power control capability of the DFIG. The suggested controller employs two key feedback signals: the rate of change of rotor speed in the synchronous generator and the electromagnetic torque generated by the DFIG. These feedback loops are used to regulate reactive power injection dynamically. The effectiveness of the proposed method is validated through simulations conducted on a test power network subject to two different disturbance scenarios. The results confirm that the controller significantly improves the dynamic response and enhances the overall stability of the synchronous generator.
Keywords
Dynamic Stability
Synchronous Generator
Doubly Fed Induction Generator (DFIG)
Reactive Power Band of DFIG
Speed Derivation Feedback
DFIG Electromagnetic Torque Feedback
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Transactions on Machine Intelligence
Volume 5, Issue 1
Winter 2022
Pages 11-20

  • Receive Date 23 December 2021
  • Revise Date 12 January 2022
  • Accept Date 08 March 2022