FUZZY LOAD MODELING AND LOAD FLOW STUDY USING

In this paper load flow study is carried out by modeling the load using the concepts of Fuzzy Set Theory (FST).The input load patterns are generated by adopting Trapezoidal Membership Function(TMF) for both real and reactive power demands. The NRLF is used to obtain the voltage magnitudes and phase angle of the buses for different loads obtained by the TMF. The RBF neural network is trained to learn the features of the load to estimate the bus bar voltage and angles. The ANN is used to instantly recall the output for an untrained set of inputs without going through the conventional iteration procedure. The RBF’s are easy to train and the training time required is observed to be less. The load flow study of that forecasted data is carried out on an IEEE-14 bus test system. The Recall response of RBFN for untrained set of load is close agreement with the standard Newton-Raphson Load Flow (NRLF) algorithm