Optimum Network Switching in Power Systems

Miniesy, Samir M.; Bohn, E. V.

doi:10.1109/tpas.1971.293029

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System Investigated For Ann Controlled Application1

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1979

2010

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Cited by 23 publications

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“…A SMIB: A sample system [5] considered for illustrating the procedure for evolving ANN controller in the presence of SMES is given in Fig. 1.…”

Section: System Investigated For Ann Controlled Applicationmentioning

confidence: 99%

Artificial neural network based SMES unit for transient stability improvement

Khanna

Singh

2010

2010 Joint International Conference on Power Electronics, Drives and Energy Systems &Amp; 2010 Power India

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This paper discusses artificial neural network (ANN) controlled superconducting magnetic energy storage (SMES) unit for improvement of transient stability of a power system under various system operating conditions and different fault conditions. The inputs to the ANN controller are the deviation in rotor angular velocity Δω of the machine connected to faulted-bus and the voltage deviation Δv of the faulted bus and are used for estimating the control variables -the active power and the reactive power. The results of investigations carried out regarding effectiveness of ANN controlled SMES in improving transient stability of a critically stable twomachine system are presented and compared with proportional type control of SMES.

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“…A SMIB: A sample system [5] considered for illustrating the procedure for evolving ANN controller in the presence of SMES is given in Fig. 1.…”

Section: System Investigated For Ann Controlled Applicationmentioning

confidence: 99%