WSEAS Transactions on Electronics
Print ISSN: 1109-9445, E-ISSN: 2415-1513
Volume 10, 2019
Nonlinear Auto-Regressive Moving Average (NARMA-L2) Controller Design for UPFC
Authors: , ,
Abstract: Unified Power Flow Controller (UPFC) is considered as the most of powerful controller among all the Flexible AC Transmission System (FACTS) technology. It is selected in this study to obtain better utilization and controlling of power over the transmission network. UPFC has the capability of controlling the transmission line parameters and consequently the flow of the active and reactive power in the transmission line. The controllers which are being used in UPFC are very important to control the transmission lines parameters as desired. Artificial intelligence methods such as the neural network can be adopted in such application to identify and control nonlinear dynamic systems as desired. Regardless of the complication of the system, this type of controller will be successfully used to improve its control approach. In this paper, an adaptive control scheme based on a Nonlinear Auto-Regressive Moving Average (NARMA-L2) is designed and investigated. This type of adaptive controller, which is based on Artificial Neural Network (ANN) concept, will be implemented in UPFC, and will be investigated to ensure its robustness, effectiveness and the capability to accommodate any sudden load change in the system of Single Machine to Infinite Bus (SMIB). In addition the dynamic performance of NARMA-12 will be compared with another type of adaptive controller scheme called Neural Network Model Predictive Control (NNMPC).
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Pages: 101-108
WSEAS Transactions on Electronics, ISSN / E-ISSN: 1109-9445 / 2415-1513, Volume 10, 2019, Art. #14