ABSTRACT
This chapter describes development of a fuzzy-logic-based power system stabilizer to maintain stability and enhance closed-loop performance of a power system. The interest in application of artificial intelligence (AI) to dynamic security analysis has been increasing steadily. Development of the artificial neural network (ANN)-enhanced transient energy function (TEF) a tool involves the construction of two modules, corresponding to the training/testing mode of one operation and the recall mode of the other operation respectively. The results obtained by the training procedure were presented to the robust ANN as training data, with the clearing energy functioning as the input stimuli and the stability assessment computed by the TEF method functioning as the desired output value. The robust ANN-based TEF procedure was used to solve the contingency screening problem for dynamic security analysis (DSA). Identifying the safe operating regimes requires analysis of a large number of combinations of outages and the associated derivation and manipulation of the massive data and related sensitivity information.
