Design Robust Power System by Kumar Mahendra (8 results)

Condition: New.

Taschenbuch. Condition: Neu. Neuware -The accurate analysis of higher order systems are complex, uneconomic and complicated to be used in real problems. Therefore, it is reasonable to sacrifice with model accuracy in order to obtain a simpler model. It is recommended to reduce the order of system model while keeping the dominant behavior of the original system. This low-order model will help to better understanding of the physical system, reduce computational complexity, reduce hardware complexity, economic, simplify the controller design and finally, the simulation becomes computationally cheaper, which saves time and resources. This dissertation proposed the designing of robust power system stabilizers (PSSs) using fast output sampling controllers via reduced order model using particle swarm optimization (PSO) method for good damping enhancement for various operating points of multi-machine power systems. Power system stabilizers (PSS) are used to generate supplementary control signals for the excitation system to enhance the damping of electrical power system during low frequency oscillations.Books on Demand GmbH, Überseering 33, 22297 Hamburg 132 pp. Englisch.

Paperback. Condition: Brand New. 132 pages. 8.66x5.91x0.30 inches. In Stock.

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The accurate analysis of higher order systems are complex, uneconomic and complicated to be used in real problems. Therefore, it is reasonable to sacrifice with model accuracy in order to obtain a simpler model. It is recommended to reduce the order of system model while keeping the dominant behavior of the original system. This low-order model will help to better understanding of the physical system, reduce computational complexity, reduce hardware complexity, economic, simplify the controller design and finally, the simulation becomes computationally cheaper, which saves time and resources. This dissertation proposed the designing of robust power system stabilizers (PSSs) using fast output sampling controllers via reduced order model using particle swarm optimization (PSO) method for good damping enhancement for various operating points of multi-machine power systems. Power system stabilizers (PSS) are used to generate supplementary control signals for the excitation system to enhance the damping of electrical power system during low frequency oscillations. 132 pp. Englisch.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The accurate analysis of higher order systems are complex, uneconomic and complicated to be used in real problems. Therefore, it is reasonable to sacrifice with model accuracy in order to obtain a simpler model. It is recommended to reduce the order of system model while keeping the dominant behavior of the original system. This low-order model will help to better understanding of the physical system, reduce computational complexity, reduce hardware complexity, economic, simplify the controller design and finally, the simulation becomes computationally cheaper, which saves time and resources. This dissertation proposed the designing of robust power system stabilizers (PSSs) using fast output sampling controllers via reduced order model using particle swarm optimization (PSO) method for good damping enhancement for various operating points of multi-machine power systems. Power system stabilizers (PSS) are used to generate supplementary control signals for the excitation system to enhance the damping of electrical power system during low frequency oscillations.

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Kumar MahendraMahendra Kumar is a Ph.D. Scholar at Department of Electrical Engineering, IIT Roorkee, India. He has obtained M. Tech (Control and Instrumentation Engg.) and B.Tech (Electronics & Communication Engg.) from Rajasthan Te.

Condition: New. Print on Demand.

Condition: New. PRINT ON DEMAND.