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Quantum evolutionary algorithm based power optimization control strategy for China initiative accelerator driven subcritical system

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Abstract The power optimization control strategy for China initiative Accelerator Driven subcritical System (CiADS), which focuses on the study of dynamic features and the stable operation of coupling nuclear system,… Click to show full abstract

Abstract The power optimization control strategy for China initiative Accelerator Driven subcritical System (CiADS), which focuses on the study of dynamic features and the stable operation of coupling nuclear system, is one of the most important research topics for the current engineering stage that is expected to be completed in the year 2025. However, the traditional way in handling the power control problem was carried out by specialists with transcendental knowledge and experiences, which has been believed as the high labor intensity and the brute force trial-and-error process. In this context, the Quantum Evolutionary Algorithm (QEA) has been employed to deal with the CiADS power optimization control strategy in order to fulfill the adaptive searching procedure continuously and automatically. The manipulation of proton beam intensity has been used as the main control approach, and the physical model in describing the dynamic characteristics of power control system has been constructed in coupling the lumped parameter method and the point reactor kinetics method. In addition, the logical structure of Proportional Integral Derivative (PID) controller has been established for the power control process, and the QEA has been adopted to obtain the suitable set of parameters in the PID controller. Finally, the performance of the optimization method has been verified in the predefined control scenarios, and all the numerical results show that the control method has the applicability and feasibility in solving the CiADS power control problems.

Keywords: system; control; power; optimization control; power optimization

Journal Title: Annals of Nuclear Energy
Year Published: 2022

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