Protection scheme for EHV transmission systems with thyristor controlled series compensation using radial basis function neural networks

Since the complex variation of line impedance measured is controlled by thyristors and is accentuated as the capacitor's own protection equipment operates randomly under fault conditions in controllable series compensated transmission systems (CSC), conventional distance protection schemes are limited to certain applications. The authors have extensively addressed the development of new protection techniques for such systems using multilayer percetrons. The basic idea of the method is to design a protection scheme using a neural network approach by catching the feature signals in a certain frequency range under fault conditions. This is different from conventional schemes that are based on deriving implicit mathematical equations based on the information obtained by complex filtering techniques. This paper presents some recent results of employing radial basis function neural networks (RBFN) for this particular application. The use of RBFN is because it has a number of advantages over multilayer percetrons. The study shows that the RBFN based protection works well in CSC systems under a number of system and fault conditions.