Thermoeconomic Analysis And Optimization Of The Secondary Loop Of Nuclear Power Thermal System Using Genetic Algorithm

Because of the high capital cost, long building period, complex system structure and the strict security requirements, it is not enough and accurate to analyze the operation conditions of the nuclear power plant, only from the angle of the second law of thermodynamics. With the growing economy of our country and the increasing energy crisis, how to utilize nuclear enrgy safely and efficiently has become a significant topic we concerned about.Thermoeconomics analysis and optimal design of the secondary loop of nuclear power thermal system based on genetic algorithm has important practical significance in reducing the power generation cost, raising the unit efficiency and improving the environment etc..This paper takes the secondary loop of 1000MW Daya bay nuclear power thermal system as the research object. The investment cost model has been established using the cost equations and the Fuel-Product of the subsystem has been determined after the calculation of the exergy of each branch. Secondly, the thermoeconomic cost balance equations have been obtained, and the heat balance calculation of the thermal system is carried out by the M file of Matlab. Then with the balance equation of thermal economy, for all equipment in the system was studied by thermal economic modeling, and the 66 equations into matrix, obtained by singular matrix decomposition method, and calculate the exergy loss cost.The calculation results show that Low pressure steam generator, steam turbine units of the two stage high pressure cylinder of steam turbine, two level, four level of low pressure cylinder of steam turbine in the ratio is bigger, the most optimization potential. Finally, based on thermal economy calculation, performance the heat sensitive analysis of the thermodynamic parameters which be important to the equipment of nuclear power two loops , combined with the graph analysis and guidance to the selected parameter optimization.The paper takes 28 parameters as the optimization objects, the plus of investment cost and the exergy loss cost of each device as the objective function using genetic algorithm.After the optimization, for the steam turbine, steam heater group, and steam generator,parameter optimization of condenser optimization ,results were analyzed and compared. After analysis: optimized by genetic algorithms,the exergy efficiency of each device of two loop thermal systems has different degrees of increase, in the range of parameters that can be accepted, the investment cost and the exergy loss cost of the third unit of the low pressure steam turbine have an obvious changes. Before the optimization, the total cost of the system is 712910$/s, and after the optimization is 657760$/s, it has been reduced by 7.74%.