STATIC SECURITY-BASED AVAILABLE TRANSFER CAPABILITY USING ADAPTIVE NEURO FUZZY INFERENCE SYSTEM

Abstract

In power system deregulation, power transactions between a seller and a buyer can be scheduled only when sufficient available transfer capability (ATC) is available. The information about the ATC is to be continuously updated in real time and made available to the market participants through Internet-based system, open access same-time information system (OASIS). The static security-based ATC is to be computed for the base case system as well as for the critical line outages of the system. The critical line outages are based on static security analysis. Hence the computation of static security-based ATC using conventional method(s) is a tedious and time consuming process. In this paper static security-based ATC has been computed for real-time applications using three artificial intelligent methods viz., (i) back propagation algorithm (BPA), (ii) radial basis function (RBF) neural network and (iii) adaptive Neuro fuzzy inference system (ANFIS). These three different intelligent methods are tested on IEEE 24-bus reliability test system (RTS) and 75-bus practical system. The results are compared with the conventional full ac load flow method for different transactions.