TECHNICAL PAPERS
Sep 11, 2009

Evaluation of Black-Start Schemes Employing Entropy Weight-Based Decision-Making Theory

Publication: Journal of Energy Engineering
Volume 136, Issue 2

Abstract

Optimization of schemes for black-start is one of the most important factors determining the speed of power system restoration after either a global blackout or a local outage. In this paper a novel method employing the entropy weight-based decision-making theory is proposed for this application. By using the method for the decision making in black start, the subjective weights acquired from knowledge and experience of experts could be used in conjunction with the objective weights (entropy weighs) deduced from some closely related indices. Obviously, the developed method can greatly improve the performance in power system restoration by overcoming the shortcomings of conventional methods that only use either the subjective or the objective weights. Furthermore, the proposed method is applicable in power systems with different levels of black-start experience for assisting the optimal black-start decision making. It is shown that the proposed method is suitable for power systems with different levels of black-start experience.

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Acknowledgments

This work is supported by the Program for New Century Excellent Talents in University of China (Grant No. UNSPECIFIEDNCET-04-0818) and China Postdoctoral Science Foundation Funded Project (Grant No. UNSPECIFIED20090461352).

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Published In

Go to Journal of Energy Engineering
Journal of Energy Engineering
Volume 136Issue 2June 2010
Pages: 42 - 49

History

Received: Mar 21, 2009
Accepted: Aug 10, 2009
Published online: Sep 11, 2009
Published in print: Jun 2010

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Authors

Affiliations

Zhenzhi Lin [email protected]
School of Electrical Engineering, Zhejiang Univ., Hangzhou 310027, People’s Republic of China. E-mail: [email protected]
Fushuan Wen [email protected]
School of Electrical Engineering, Zhejiang Univ., Hangzhou 310027, People’s Republic of China. E-mail: [email protected]
Jiansheng Huang [email protected]
School of Computing and Mathematics, Univ. of Western Sydney, Locked Bag 1797, Penrith South DC, NSW 1797, Australia. E-mail: [email protected]
School of Electrical Engineering, Zhejiang Univ., Hangzhou 310027, People’s Republic of China. E-mail: [email protected]

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