An Innovative Minimum Hitting Set Algorithm for Model-Based Fault Diagnosis in Power Distribution Network

Abstract

The distribution network plays a great role in the power system, and any fault in it may threaten the safe and stable operation of the power system. Hence, fault diagnosis has an important role in protecting the distribution network and maintaining power system stability. The model-based diagnosis (MBD) is one of the diagnostic methods that have some advantages compared with the common diagnosis methods. The latter, such as expert diagnosis systems depend on the professional experience and fault information. However, the inefficiency and incomplete calculation of the minimum hitting set (MHS) limits the performance of the MBD. In this paper, to overcome these limitations, an innovative MHS algorithm which considers the nature and characteristics of the distribution network is proposed. In the proposed algorithm, a new fitness function is constructed by a weighted combination method, which allows particles to move directly toward the MHS without the effect of non-hitting set particles. Finally, three cases studies and discussion on the distribution network are introduced to validate the advantages of the proposed algorithm, in terms of the computation efficiency and accuracy.