The Risk Quantification Evaluation Strategy for the Distribution Line based on EMLR

The electric power distribution grid directly serves the ordinary users, the stability and reliability of which are crucial to production and life. The traditional operation and maintenance of the distribution grid is based on experience and cannot scientifically predict the state of line faults. In this paper, stepwise regression is used to screen out 8 key influencing factors of line faults, and principal component analysis is performed to find the risk value of each line; so that establishes multiple linear and exponential regression equations for the line risk value. According to the existing data, the risk of the line is predicted, and the GABP neural network model is built so as to accurately predict the risk value of the line.