Study on UPFC with energy snubber and its fuzzy neural network control

Unified Power Flow Controller (UPFC) is the most representative FACTS device, which has the functions of series and shunt compensation. The energy snubber can be used to control the real power's distributing, too. It is presented to control UPFC and its energy snubber by using the Fuzzy Neural Network (FNN). At the same time, because of the genetic algorithm's robust and self-adaptability, it is adopted as the learning algorithm of fuzzy neural network (Genetic Algorithm and Least-Square technique are introduced in making the network structure for the membership function and doing the defuzzification, respectively). The FNN control method is differ from the traditional control theory because it has the virtues of fuzzy theory and neural network. Therefore, this control method is more flexible, steady and robust though UPFC is a strongly nonlinear device. The coordination control of UPFC's series and shunt converter is more reliable. This FNN control system is trained using a great deal of sample learning, so it can make UPFC run in all kinds of mode rightly. At last, the reliability of this method is demonstrated by the system simulation.