Title :
A Hopfield neural network based approach for state estimation of power systems embedded with FACTS devices
Author :
Singh, Satish Kumar ; Sharma, Jaydev
Author_Institution :
ABB Ltd., Vadodara
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
Keywords :
Hopfield neural nets; flexible AC transmission systems; load flow; nonlinear programming; power system analysis computing; power system state estimation; Hopfield neural network; flexible AC transmission system; line power flow manipulation; nonlinear programming; optimization tool; power system state estimation; Computer networks; Embedded computing; Hopfield neural networks; Power system measurements; Power system security; Power system simulation; Power systems; Sparse matrices; State estimation; Time sharing computer systems;
Conference_Titel :
Power India Conference, 2006 IEEE
Conference_Location :
New Delhi
Print_ISBN :
0-7803-9525-5
DOI :
10.1109/POWERI.2006.1632574
