Power Grid Safety Evaluation Based on Rough Set Neural Network

With the continuous deepening of the power system reform and the blackouts of someplace on the world, the safety of the power grid has received high attention from all sections of the society. The former researches on the power grid safety are mostly about special parts, the method to estimate the whole power grid safety should be improved in the future. In this paper, according to the characters of the modern power grid, an index system of the whole power grid is set up. Meanwhile, the paper syncretizes respective advantages of rough set and artificial neural network, puts forward a evaluation method of the power grid safety- RSANN, which uses rough set to pretreat the input data of neural network, extracts the key components as the network input and improves the convergence rate and approximation accuracy of the neural network. The example shows the method can be used in early warning of the power system. In the era of electric, this is important and practical.