A Hopfield neural network based approach for state estimation of power systems embedded with FACTS devices

S.K Singh,J Sharma

doi:10.1109/poweri.2006.1632574

A Hopfield neural network based approach for state estimation of power systems embedded with FACTS devices

S.K Singh, J Sharma

https://doi.org/10.1109/poweri.2006.1632574

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Publication Date: Jan 1, 2006

Citations: 19

Affiliation: Indian Institute of Technology Roorkee

#Flexible A.C. Transmission Systems #Flexible A.C. Transmission Systems Devices + Show 8 more

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Abstract

Flexible A.C. transmission systems (FACTS) are being used more in large power systems for their significance in manipulating line power flows. Traditional state estimation methods without integrating FACTS devices will not be suitable for power systems embedded with FACTS. In this paper the state estimation of power systems in presence of FACTS devices is presented. Hopfield neural network is simulated as an optimization tool to solve the power system state estimation problem.

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