Abstract

Based on derivative adaptive critics, neurocontrollers for excitation and turbine control of multiple generators on the electric power grid are presented. The feedback variables are completely based on local measurements. Simulations on a three-machine power system demonstrate that the neurocontrollers are much more effective than conventional PID controllers, the automatic voltage regulators and the governors, for improving the dynamic performance and stability under small and large disturbances

Meeting Name

International Joint Conference on Neural Networks, 2001. IJCNN '01

Department(s)

Electrical and Computer Engineering

Keywords and Phrases

Derivative Adaptive Critics; Dynamics; Excitation; Heuristics; Learning (Artificial Intelligence); Learning Algorithm; Neurocontrollers; Optimisation; Power System Control; Power System Stability; Stability; Three-Machine Power System; Turbine Generator

Document Type

Article - Conference proceedings

Document Version

Final Version

File Type

text

Language(s)

English

Rights

© 2001 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

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