Magaji , N. and Mustafa, Mohd. Wazir (2009) Optimal thyristor control series capacitor neuro-controller for damping oscillations. Mohd. Wazir Mustafa, 5 (12). pp. 980-987. ISSN 1549-3636
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Official URL: http://dx.doi.org/10.3844/jcssp.2009.980.987
This study applies a neural-network-based optimal TCSC controller for damping oscillations. Optimal neural network controller is related to model-reference adaptive control, the network controller is developed based on the recursive â€œpseudo-linear regression. Problem statement: The optimal NN controller is designed to damp out the low frequency local and inter-area oscillations of the large power system. Approach: Two multilayer-perceptron neural networks are used in the design-the identifier/model network to identify the dynamics of the power system and the controller network to provide optimal damping. By applying this controller to the TCSC devices the damping of inter-area modes of oscillations in a multi-machine power system will be handled properly. Results: The effectiveness of the proposed optimal controller is demonstrated on two power system problems. The first case involves TCSC supplementary damping control, which is used to provide a comprehensive evaluation of the learning control performance. The second case aims at addressing a complex system to provide a very good solution to oscillation damping control problem in the Southern Malaysian Peninsular Power Grid. Conclusion: Finally, several fault and load disturbance simulation results are presented to stress the effectiveness of the proposed TCSC controller in a multi-machine power system and show that the proposed intelligent controls improve the dynamic performance of the TCSC devices and the associated power network.
|Uncontrolled Keywords:||associated power network, large power system, power system problems|
|Subjects:||T Technology > T Technology (General)|
T Technology > TK Electrical engineering. Electronics Nuclear engineering
|Deposited By:||INVALID USER|
|Deposited On:||17 Jan 2012 06:48|
|Last Modified:||12 Feb 2017 06:45|
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