遗传算法在压水堆平衡循环优化中的应用研究

PWR Equilibrium Cycle Optimization by Using Genetic Algorithms

建立了遗传算法用于核电站平衡循环优化的数学模型 ;提出了该模型的遗传编码和遗传操作 ,完成相关程序编制 ;并和NNGFM堆芯物理计算程序构成一个完整的堆芯燃料管理程序。为了检验优化效果 ,以大亚湾核电站第 5炉参数作为参考方案 ,在无初值的情况下 ,针对不同的目标函数进行平衡循环优化。结果表明 ,循环长度最大化能延长 1 0EFPD左右 ,功率峰因子最小化使得功率峰因子从1 3 6降低到 1 2 9。

An mathematics model is put forward for the equilibrium cycle optimization of nuclear power plant and new genetic algorithms (GA) encode and operation are adopted. An integrated code for in-core fuel management has been developed on the basis of GA and NNGFM which is a core physics calculation code. In order to verify the optimization effect, the solutions of various optimum objects are attained without initial values. Comparing with the reference pattern of the fifth cycle of Dayabay Nuclear Power Plant, the cycle length maximization can prolong cycle length by 10 EFPD, the power peak factor minimization can decrease power peak factor from 1.36 to 1.29.