Qi HUANG, NgocKhoat NGUYEN, Thi-Mai-Phuong DAO

Modeling and control of a 6-control-area interconnected power system to protect the network frequency applying different controllers

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.

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