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In this paper, the design of 3 intelligent control strategies applying fuzzy logic (FL) and artificial neural network (ANN) techniques is investigated to deal with network frequency maintenance against load variations in a largescale multiarea interconnected power system. These intelligent frequency controllers proposed in this study include FL-PI, ANN-NARMA(nonlinear autoregressive moving average)-L2, and ANN-RMC (reference model control). In principle, they are designed depending upon the tie-line bias control method, which has been applied efficiently for damping frequency oscillations. A mathematical model of an n-control-area interconnected power system with different generation units is built first to apply the control methodologies in order to maintain the grid frequency at its nominal value (50 Hz or 60 Hz). Such a model is considered to be typical candidate of a complicated large-scale power system in reality. Numerical simulation with various cases of load conditions are also implemented in this study using the MATLAB/Simulink package to demonstrate the feasibility and effectiveness of the proposed control strategies. It is found that the 3 intelligent controllers presented in this paper are capable of achieving superiority over the conventional integral regulators in system frequency stabilization. The main dynamic control indexes obtained, especially the overshoot and settling time, are highly promising to effectively extinguish the dynamic responses of the frequency and tie-line power deviations. Thus, the steady state of the power network can be restored more quickly after load variation occurrence. In that way, the stability, reliability, and economy of an electric power grid are able to be guaranteed effectively. [ABSTRACT FROM AUTHOR]

Modern and large power systems, which are normally composed of several interconnected generating stations (multiarea), have complex and diverse structures in practice. It is necessary to deal with the automatic generation control to ensure the stability, continuity, and economy of the generation schedule in a power grid. For the automatic generation control strategy, the most important goal is to protect the network frequency from load variations, which can appear randomly in any area. As a result, it is essential to design efficient controllers applied to multiarea interconnected power systems in order to maintain the network frequency at the nominal values (50 Hz or 60 Hz), and keep the tie-line power flow at the scheduled MW. In this paper, we first analyze and build a model of the 6-control-area interconnected power system as the typical case study. Subsequently, different frequency controllers based on tie-line bias control strategy, namely integral, proportional-integral, proportional-integral-derivative, and PI-based fuzzy logic, will be investigated and applied to the power system model. The most important control performances, such as overshoots and settling times, are considered in this study to evaluate the stability of the power system and choose the most suitable controller for maintaining the network frequency. The simulation results have been achieved by using MATLAB/Simulink package version 2013 in this work. According to these results, the maximum overshoots of the PI-based fuzzy logic controller are from 36.56% to 90.13%, and its settling times are from 19.00% to 98.26% in comparison with the other regulators in the given control power system. Therefore, the PI-based fuzzy logic controller has been chosen as the best control solution to bring the grid frequency back to its nominal value as quickly as possible after occurrence of load variations. [ABSTRACT FROM AUTHOR]