State estimation for power systems with multilayer perceptron neural networks

Abstract

The Static state estimation is widely used in power systems for real time monitoring and analysis. Standard methods, such as the weighted least squares (WLS) algorithm, require the computation of bus admittance and Jacobian matrices and the solution is found in an iterative process. This paper presents an alternative for the classic state estimation (SE) algorithms, which uses a multilayer perceptron for the state estimator. Results are presented for the IEEE 14 bus system.