Quantum evolutionary algorithm applied to transient identification of a nuclear power plant

Abstract When transients occur during the operation of Nuclear Power Plants (NPPs), their identification is critically important for both operational and safety reasons. Thus, plant operators have to identify an event based upon the evaluation of several distinct process variables, which might difficult operators’ actions and decisions. Transient identification systems have been proposed in order to support the analysis with the aim of achieving successful or effective courses of action, as well as to reduce the time interval for a decision and corrective actions. This article presents a system for accident and transient identification in a pressurized water reactor NPP whose optimization step of the classification algorithm is based upon the paradigm of the Quantum Computing. In this case, the optimization metaheuristic Quantum Inspired Evolutionary Algorithm (QEA) was implemented and tested. The system is able to identify anomalous events related to transients of the time series of process variables related to postulated accidents. The results of the classification of transients/accidents are compared with other results in the literature.