An Innovative and Robust Algorithm for the Self-Healing of Radial Distribution Networks Based on Graph Theory Concept: A Case Study

To progress toward smart grids, an automatic reconfiguration of radial distribution networks (FRC) is an inevitable necessity. Several drawbacks are associated with existing methods, such as lack of transparency in decision-making, complexity of computation, and the use of non-open source computational engines. In this regard, for the first time, a graph theory-based innovative algorithm (which is called FRANK
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) has been proposed related to the FRC knowledge-based type methods using the concept of energy hubs that can suggest the most appropriate switching operation decisions by considering cost functions such as minimum load outage. Using the proposed algorithm, it is possible to rapidly implement self-diagnosis, self-decision, and self-recovery. Through the described flowchart, the network graph is divided into three proximity, hotline, and flow matrices. This algorithm has been applied to two feeders in the Dowlatabad city of the Khorasan Razavi province, which showed promising results serving as a model for the transition towards smart grids in Iranian SCADA companies. All the codes are developed in the MATLAB environment.
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Feeder Reconfiguration Algorithm with Near Knowledge-based