Fast substation service restoration using intelligent Petri-Nets models

This paper proposes a new Petri Nets (PNs) knowledge representation scheme to on-line fast achieve the service restoration plan of a substation. In accordance with the practical guidelines and the heuristic rules obtained by interacting with the dispatchers of distribution systems, a PNs model is first built to represent the related knowledge about the task of substation restoration. The PNs model built is then transformed into matrix forms, which are relied on to infer a restoration plan through simple matrix operations. Due to its graphic representation of the heuristic rules and parallel rule-firing manner via matrix operations, the human expertise on restoration can be advantageously expressed and exploited by means of the PNs knowledge- representing approach. The developed system is illustrated on a sample substation and tested on a practical Taiwan Power (Taipower) substation in Tainan City. Flexibility and effectiveness of the PNs model have been verified as a decision support for restoration scheduling.