Transient stability control of UHVDC based on generalized dynamic fuzzy neural network

UHVDC plays an important role in Project for Delivering Electricity from the West to the East, for its flexible and quick control and large electrical capacity. Its influence on AC system is becoming larger as transferring more DC power. A method using generalized dynamic fuzzy neural network in UHVDC to increase transient stability is presented, which regulates power to supply enough damping with additional control signal. Suitable modulation signal and dimension are chosen. After GD-FNN system is trained, systematic error and e -completeness of fuzzy rules are used as criterion for optimizing system structure. Meanwhile, degree of membership is modified to ensure that the system has a compact structure and a great generalization ability. Simulation shows that the controller designed can increase the generator’s electrical damping remarkably in different conditions and suppress the oscillation effectively, so it has a certain robustness.