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Journal of Applied Mathematics
Volume 2013, Article ID 263905, 7 pages
http://dx.doi.org/10.1155/2013/263905
Research Article

Operational Risk Assessment of Distribution Network Equipment Based on Rough Set and D-S Evidence Theory

1School of Economics and Management, North China Electric Power University, Beijing 102206, China
2State Grid East Inner Mongolia Electric Power Co., Ltd., Hohhot Power Supply Bureau, Hohhot 010050, China

Received 29 August 2013; Revised 22 November 2013; Accepted 22 November 2013

Academic Editor: Antonio J. M. Ferreira

Copyright © 2013 Cunbin Li et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

With the increasing complication, compaction, and automation of distribution network equipment, a small failure will cause an outbreak chain reaction and lead to operational risk in the power distribution system, even in the whole power system. Therefore, scientific assessment of power distribution equipment operation risk is significant to the security of power distribution system. In order to get the satisfactory assessment conclusions from the complete and incomplete information and improve the assessment level, an operational risk assessment model of distribution network equipment based on rough set and D-S evidence theory was built. In this model, the rough set theory was used to simplify and optimize the operation risk assessment indexes of distribution network equipment and the evidence D-S theory was adopted to combine the optimal indexes. At last, the equipment operational risk level was obtained from the basic probability distribution decision. Taking the transformer as an example, this paper compared the assessment result obtained from the method proposed in this paper with that from the ordinary Rogers ratio method and discussed the application of the proposed method. It proved that the method proposed in this paper is feasible, efficient, and provides a new way to assess the distribution network equipment operational risk.