Multicycle Fuel Loading Pattern Optimization by Multiobjective Simulated Annealing Employing Adoptively Constrained Discontinuous Penalty Function

摘要

The multiobjective simulated annealing (MOSA)-based fuel assembly loading pattern (LP) optimization method, employing the discontinuous penalty function (DPF), is extended for multicycle applications by introducing an adoptively constrained discontinuous penalty function (ACDPF). A discontinuous point in the penalty function is adoptively shifted to a better direction during the course of MOSA such that the search can be more efficient. The advantages of the ACDPF-based MOSA algorithm over the original DPF-based algorithm are first examined with a real single-cycle LP optimization problem of an operating reactor, as well as with a simple LP optimization problem that has known solutions. A direct multicycle LP optimization method is then formulated with an application to the first four cycles of the Younggwang Nuclear Unit 4 (YGN4) core. The rearrangement method is devised as a fuel shuffling method that can avoid drastic changes in the LPs of the subsequent cycles of a seed cycle. It is demonstrated that the ACDPF-based MOSA combined with the rearrangement method produces quite effectively the optimum LP sets for the four cycles, which outperform the LPs generated by a series of cyclewise optimizations as well as the actual LPs of YGN4 that were already used in the plant.