Title :
State estimation for power systems with multilayer perceptron neural networks
Author :
Ivanov, Ovidiu ; Garvrilas, M.
Author_Institution :
Fac. of Electr. Eng., “Gheorghe Asachi” Tech. Univ. of Iasi, Iasi, Romania
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.
Keywords :
IEEE standards; Jacobian matrices; iterative methods; least squares approximations; multilayer perceptrons; power engineering computing; power system state estimation; IEEE 14 bus system; Jacobian matrices; SE; WLS; bus admittance; iterative process; multilayer perceptron neural networks; power systems; state estimation; static state estimation; weighted least squares algorithm; Artificial neural networks; Load flow; Measurement uncertainty; Power measurement; State estimation; Voltage measurement; multilayer perceptron; state estimation;
Conference_Titel :
Neural Network Applications in Electrical Engineering (NEUREL), 2012 11th Symposium on
Conference_Location :
Belgrade
Print_ISBN :
978-1-4673-1569-2
DOI :
10.1109/NEUREL.2012.6420026
