Improved sensitivity analysis method and decision error discussion for limiting short-circuit current of power grid

This study mainly focuses on the method of limiting short-circuit current of a power grid by partial transmission switching. The restrictive effect of short-circuit current and the integrality of the power grid should be considered before the choosing the transmission lines. By analysing the relatio...

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Bibliographic Details
Main Authors: Shixiong Qi, Xiuli Wang, Shijun Tian, Ruogu Wang
Format: Article
Language:English
Published: Wiley 2019-04-01
Series:The Journal of Engineering
Subjects:
Online Access:https://digital-library.theiet.org/content/journals/10.1049/joe.2018.8522
Description
Summary:This study mainly focuses on the method of limiting short-circuit current of a power grid by partial transmission switching. The restrictive effect of short-circuit current and the integrality of the power grid should be considered before the choosing the transmission lines. By analysing the relationship between transmission switching and self-impedance of bus with increasing short-circuit current magnitude, a sensitivity matrix can be derived. Based on sensitivity analysis, a set of the least transmission switching is chosen, which can limit short-circuit current to the maximum. This study improves the method of transmission lines selection by sensitivity analysis. The improved sensitivity analysis method directly selects a set of transmission switching lines by the maximum value of weighted sensitivity coefficient instead of selecting lines one by one. It requires less calculation and has a high-computation speed, but there are engineering errors. This work also studies the error influencing the decision of lines selection in different power grid scales. The effectiveness of the improved sensitivity analysis method is verified by several case studies. The cases of different power system scales are utilised for discussing the impact of error on decision of lines selection and for drawing the scope of the improved sensitivity analysis method.
ISSN:2051-3305