A Minimum Hitting Set Algorithm With Prejudging Mechanism for Model-Based Fault Diagnosis in Distribution Networks

Abstract

Fault diagnosis has a critical role in maintaining the reliability and stability of distribution networks. Compared with common diagnosis methods, such as expert systems that depend on the professional experience and information of fault, the model-based diagnosis (MBD) has many distinct advantages. However, the efficiency and accuracy of the calculation of the minimum hitting set (MHS) limit the performance of MBD. To overcome these limitations, an MHS algorithm with a prejudging mechanism is proposed in this article. This mechanism is constructed based on the distribution characteristics of MHS. The use of this mechanism prior to MHS calculation enables the removal of most non-HS particles and all super-MHS particles and enables the compression of the MHS calculation solution space several times. Moreover, after compression, only two types of particles remain in the left solution space, which are non-HS and MHS. As a result, the MHS can be picked out directly through the HS fitness function and the HS criterion and by avoiding the participation of the MHS ensured strategy (MHSES). Three cases studies have been introduced to test the effect of the prejudging mechanism on the performance of the MHS calculation. In addition, a discussion on the MBD of the distribution networks has been presented to validate the efficiency and accuracy of the proposed algorithm.