This paper presents the design of an optimal dynamic neurocontroller for a new type of FACTS device - the gate controlled series capacitor (GCSC) incorporated in a multi-machine power system. The optimal neurocontroller is developed based on the heuristic dynamic programming (HDP) approach. In addition, a dynamic identifier/model and controller structure using the recurrent neural network trained with backpropagation through time (BPTT) is employed. Simulation results are presented to show the effectiveness of the dynamic neurocontroller and its performance is compared with that of the conventional PI controller under small and large disturbances.

Meeting Name

13th International Conference on, Intelligent Systems Application to Power Systems, 2005


Electrical and Computer Engineering

Keywords and Phrases

FACTS Device; Backpropagation; Backpropagation Through Time; Dynamic Neurocontroller; Flexible AC Transmission Systems; Gate Controlled Series Capacitor; Heuristic Dynamic Programming; Multimachine Power System; Neurocontrollers; Optimal Control; Optimal Dynamic Neurocontrol; Power Capacitors; Power System Control; Recurrent Neural Nets; Recurrent Neural Network

Document Type

Article - Conference proceedings

Document Version

Final Version

File Type





© 2005 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

Publication Date

01 Jan 2005