基于最小化发电成本的聚变驱动次临界堆参数优化分析

利用自主发展的聚变驱动次临界堆 (FDS)系统分析软件SYSCODE ,通过遗传算法求解以最小化发电成本为目标函数 ,以聚变功率、中子壁负载、安全因子和包层平均热功率密度限等为约束条件的最优化模型 ,得到FDS的包层能量增益因子 (Qb) ,等离子体位形参数 :环径比 (A)、拉长比 (κ)和三角变形因子 (δ) ,工程与物理参数 :规一化比压 (βN)、轴上纵场 (BT)与等离子体电流 (IP)等的最优化设计 ,并详细分析了发电成本对最优设计点的敏感性。分析分两种情况 :一是聚变功率为定值 (设为 1 5 0MW ) ;二是包层平均热功率密度为定值 (分别设为 1 5、5 0、1 0 0和 5 0 0MW /m3)。

Optimization of design parameters based on minimizing the cost of electricity of the fusion-driver sub-critical system

Optimization of design parameters of FDS(Fusion-Driven Su b-critical System )and the sensitivities of COE to the optimal design points ar e discussed with the objective function of minimizing the cost of electricity(CO E) subjected to the given fusion power,and density of thermal power of the blan ket. The optimal designs of the engineering parameters of the blanket and of the plasma configuration/geometry and of the plasma physical and engineering pa rameters are figured out by the genetic algorithm(GA). Two cases are dicussed, one is that the fusion power is 150 MW, the other is that the average density o f thermal power of the blanket is 10, 50, 100 and 500 MW/m3, respective ly. The sensitivities of COE to design parameters at the optimal design points a re discussed.