基于遗传算法的核电站汽轮机抽汽流量优化计算

Optimization Calculation of Steam Extraction Flow of Steam Turbine in Nuclear Power Plant Based on Genetic Algorithm

为提高核电站汽轮机系统的效率和运行性能,确保经济、稳定和可靠的电力供应,开展基于遗传算法的核电站汽轮机抽汽流量优化计算研究。利用神经网络预测核电站汽轮机抽汽流量,以核电站汽轮机抽汽流量为优化目标,各抽汽口抽汽流量和一、二级再热蒸汽流量为优化变量,采用遗传算法进行核电站汽轮机抽汽流量优化计算目标函数求解,所得最优解即为抽汽流量优化计算结果。实验结果表明,该方法的核电站汽轮机抽汽流量优化计算结果与实际值更接近,说明该方法的计算精准度高,应用效果好。

In order to improve the efficiency and operational performance of steam turbine system in nuclear power plant and realize economic,stable and reliable power supply,the optimization calculation of steam extraction flow of steam turbine in nuclear power plant based on genetic algorithm is carried out.The neural network is used to predict the extraction flow of steam turbines in nuclear power plants.Taking the extraction flow of steam turbines in nuclear power plants as the optimization objective,the extraction flow of each extraction port and the first and second reheat steam flow as the optimization variables,the genetic algorithm is used to solve the objective function of the optimization calculation of extraction flow of steam turbines in nuclear power plants,and the optimal solution is the optimization calculation result of extraction flow.The experimental results show that the optimized calculation result of steam extraction flow rate of steam turbine in nuclear power plant is closer to the actual value,which shows that the method has high calculation accuracy and good practical application effect.