Neural Network Model Predictive Control (NNMPC) Design for UPFC

Abstract

Neural Network Model Predictive Control (NNMPC) is like almost like the model predictive control but the used inboard plant is designed based on using the concept of the artificial neural network to predict the behavior of the plant. The predicted values are fed to the optimizer in order to obtain better control variables. This type of controller will be used instead of the conventional controller in the most versatile FACTS devices, which is the Unified Power Flow Controller (UPFC). UPFC has the capability of controlling the transmission line parameters and consequently the flow of the active and reactive power in the transmission line. So, 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 NNMPC will be compared with another type of adaptive controller scheme called Model Productive Controller (MPC).