Rough Fuzzy Control of SVC for Power System Stability Enhancement


Autoria(s): Mishra, Yateendra; Dong, Z.Y.; Bansal, R; Mishra, S
Contribuinte(s)

Shi, Libao

Dong, Zhao Yang

Data(s)

2009

Resumo

Modern power systems have become more complex due to the growth in load demand, the installation of Flexible AC Transmission Systems (FACTS) devices and the integration of new HVDC links into existing AC grids. On the other hand, the introduction of the deregulated and unbundled power market operational mechanism, together with present changes in generation sources including connections of large renewable energy generation with intermittent feature in nature, have further increased the complexity and uncertainty for power system operation and control. System operators and engineers have to confront a series of technical challenges from the operation of currently interconnected power systems. Among the many challenges, how to evaluate the steady state and dynamic behaviors of existing interconnected power systems effectively and accurately using more powerful computational analysis models and approaches becomes one of the key issues in power engineering. The traditional computing techniques have been widely used in various fields for power system analysis with varying degrees of success. The rapid development of computational intelligence, such as neural networks, fuzzy systems and evolutionary computation, provides tools and opportunities to solve the complex technical problems in power system planning, operation and control.

Identificador

http://eprints.qut.edu.au/81771/

Publicador

Research Signpost

Relação

http://www.ressign.com/UserBookDetail.aspx?bkid=967&catid=195#

Mishra, Yateendra, Dong, Z.Y., Bansal, R, & Mishra, S (2009) Rough Fuzzy Control of SVC for Power System Stability Enhancement. In Shi, Libao & Dong, Zhao Yang (Eds.) Computational Intelligence in Power Systems. Research Signpost, pp. 31-52.

Direitos

Copyright 2009 Research Signpost

Fonte

School of Electrical Engineering & Computer Science; Science & Engineering Faculty

Tipo

Book Chapter