A colored Petri net models with intelligent function for power system restoration of semiconductor industry

Abstract

Intelligent function associated with a colored Petri net (CPN) inference model is developed for service restoration of power system of semiconductor industry (SI). The CPN models for a four-way switch and other power components are proposed to implement proper restoration plan after the faulted location has been identified and isolated. The unfaulted but out of service areas are restored efficiently by applying parallel-like reasoning in the CPN for multiple contingencies simultaneously. To assure the restoration plan can comply with operation regulation, heuristic rules based on the standard operation procedures of power system in SI are included in the best first search of the CPN. For the fault contingency during summer peak season and power component failure, the load shedding is executed and the CPN models are designed to restore service to as many key loads and loads as possible. The priority indices of each feeder and service zone are defined by the key loads within the service territory. A phase power system of semiconductor industry with 4 main XTR, 21 generators, 12 feeders (HV) and 32 feeders (LV) is selected for computer simulation to demonstrate the effectiveness of the proposed methodology. It is found that the service restoration of power system can be obtained very efficiently by applying the proposed CPN model.