Neural predictive controller of a two-area load frequency control for interconnected power system

The present paper investigates the load-frequency control (LFC) for improving power system dynamic performance over a wide range of operating conditions. This study proposed design and application of the neural network model predictive controller (NN-MPC) on two-area load frequency power systems. Neural network model predictive control (NN-MPC) combines reliable prediction of neural network with excellent performance of model predictive control using nonlinear Levenberg–Marquardt optimization. The controller used the local power area error deviation as a feedback signal. To validate the effectiveness of the proposed controller, two-area power system is simulated over a wide range of operating conditions and system parameters change. Further, the performance of the proposed controller is compared with a fuzzy logic controller (FLC) through simulation studies. Obtained results demonstrate the effectiveness and superiority of the proposed approach.