Evaluating the Security and Classifying Data Current in Power systems based on Genetic algorithm and Neural network

In this paper, the importance of steady state in power systems and necessity of evaluation of security with an acceptable speed and accuracy we have evaluated the static security assessment in order to determine security level of power system using genetic algorithm and neural network. In this method, at first noise is reduced on the data using filtering method and then data classification is done using genetic algorithm and neural network in order to evaluate static security assessment in power systems. In this research Newton Raphson data set is used to test and evaluate the proposed GA-ANN method and comparing it with other methods. Execution speed and classification accuracy of the proposed method has been better that of other methods.

کلیدواژه ها:

Power systems ، static security assessment (SSA) ، Genetic algorithm ، Neural network