中文摘要：

针对核电汽轮机组热效率较低问题,本文建立了核电汽轮机抽汽系统的评价模型,并基于模型编制相应的计算机程序,在此基础上以660 MW核电机组为研究实例,对机组输出功率受汽轮机抽汽参数的影响进行了分析。提出一种将遗传算法和单纯形算法相结合的混合遗传算法,并利用标准测试函数测试了其寻优性能。在给定的约束条件下,选取了合适的优化变量,利用混合遗传算法,对汽轮机抽汽系统参数进行了优化。优化结果显示,与原方案相比,优化方案的机组输出功率提高了7.074 MW,表明该优化方法可以提高核电机组的经济性。

英文摘要：

In order to solve the low-efficiency problem of the turbine unit in nuclear power plant (NPP), an evaluation model of a turbine extraction system was established and the corresponding computer program was developed. Based on the computer program, a case study of a 660 MW NPP was implemented to investigate the influence of the extraction parameters on turbine output power. Furthermore, a genetic algorithm and a simplex algorithm were combined to form a hybrid genetic algorithm (GSA). The performance of the GSA was verified using the standard test function. Given the boundary condition groups, extraction steam parameter optimization was conducted using the GSA to harmonize the selected variables. The result shows that the output power of the optimized scheme increases 7.074 MW comparing with the original scheme, which demonstrates the capability of the GSA to optimize steam extraction schemes in NPPs. ? 2017, Editorial Department of Journal of HEU. All right reserved.