Application of Petri nets to solve distribution system contingency by considering customer load patterns

For a distribution contingency such as feeder overloading or short-circuit fault, the artificial intelligent Petri nets (PN) with best-first search approaches is applied in this paper to find the proper switching operation decision to solve the problem. A PN model with inference mechanism is derived for load transfer among distribution feeders after the overloading feeders have been identified or the faulted section has been isolated. To represent the load behavior more accurately, the typical customer load patterns derived by load survey study are used to determine the daily load profiles of each section of distribution feeders. The current flows of line switches and distribution feeders are solved by load flow analysis over a daily period. To demonstrate the effectiveness of the proposed methodology, one of the distribution systems in a Taiwan Power Company (Taipower), which serves the mixture types of customers, is selected to perform the computer simulation. It is found that the PN algorithm can enhance the feeder reconfiguration for system contingency and improve load balance by taking into account the load characteristics of the customers served.