Operation Risk Assessment for Distribution System with Photovoltaic Substation Connections

2014 ◽  
Author(s):  
Yuwei Shang ◽  
Jian Liu ◽  
Shenxing Shi ◽  
Bin Wang ◽  
Xinzhou Dong
Keyword(s):  
Risk Assessment ◽  
Distribution System ◽  
Operation Risk

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

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Cunbin Li ◽  
Gefu Qing ◽  
Peng Li ◽  
Tingting Yin
Keyword(s):  
Risk Assessment ◽  
Rough Set ◽  
Power Distribution ◽  
Distribution System ◽  
Distribution Network ◽  
Evidence Theory ◽  
Operational Risk ◽  
Power Distribution System ◽  
Network Equipment ◽  
Operation Risk

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.

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