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Abstract: The electric power industry is currently undergoing an unprecedented reform, ascribable to, one of the most exciting and potentially profitable recent developments in increasing usage of artificial intelligence techniques. The artificial neural network approach has attracted number of applications especially in the field of power system since it is a model free estimator. Neural networks provide solutions to very complex and nonlinear problems. Nonlinear problems, like load forecasting that cannot be solved with standard algorithms but can be solved with a neural network with remarkable accuracy. Modern interconnected power systems often consist of thousands of pieces of equipment each of which may have an effect on the security of the system. Neural networks have shown great promise for their ability to quickly and accurately predict the system security when trained with data collected from a small subset of system variables.
The intention of this paper is to give an overview of application of artificial intelligence and neural network (NN) techniques in power systems to prognosticate load on power plant and contingency in case of any unexpected outage. In this paper we present the key concepts of artificial neural networks, its history, imitation of brain neuron’s architecture and finally the applications (load forecasting and contingency analysis). The applications of artificial intelligence in areas of load forecasting by error Backpropagation learning algorithm and contingency analysis based on Quality index have been perspicuously explained
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