Research On System Modeling And Intelligent Parameter Optimization For The Primary Loop In PWR Nuclear Power Unit

The devastating disaster will be happened because of leakage, which caused by the failure equipment or system and operating miss of nuclear power unit, because the nuclear power plant operation is very complex, and the application in fission reaction itself has some risk. However simulator training of operators has the serious practical effect of safety and economic operation of nuclear power plants. With the development of high precision real time simulation machine, it is very important for large-scale nuclear power generating units to research system modeling, simulation and intelligent parameters optimization. Pressure water reactor modeling, coolant system modeling, modeling and simulation of nuclear power plant primary loop, and model parameter optimization were researched in this paper, using mechanism analysis method, neural network method, fluid network modeling method and so on. The main innovative achievements are:(1) The reactor mixed calculation model based on the combination of neural network and mechanism analysis was set up. In the model of reactive module, we used neural network to realize the reactivity estimation of control rod negative reactivity, Doppler effect, moderator temperature effect, dissolved boron negative reaction. The test results indicated that the satisfactory effects are achieved. Though mechanism analysis, we built the reactor core thermal power calculation model, core heat transfer model and neutron flux by the method of divided instantaneous.(2) All the components mechanism models of the reactor coolant system were established. Through mechanism analysis, the dynamic mathematical model of two-phase natural circulation steam generator with vertical U-shaped tubes were built; by analyzing the characteristics of pressurizer, a two-phase dynamic non equilibrium pressurizer model was built; finally mathematical model of coolant pump was set up by using the method of fluid network.(3) All the component models of primary loop system of PWR nuclear power unit, such as reactor, steam generator, reactor coolant pump and pressurizer, were programmed into algorithms and simulated, taking a900MW PWR nuclear power unit as an example. The simulation results indicated that the trend of model parameters accords with the theoretical analysis, so the rationality of each sub module itself was proved. Depending on those models discussed above, the integral model of primary loop in nuclear power unit was finally established by module overlap method; the correctness of which was verified though analyzing the steady-state and dynamic characteristics. (4) To improve the accuracy of the model, the parameters which were difficult to determine were optimized with intelligent optimization algorithms. In order to improve the convergence speed and the optimization accuracy of QPSO algorithm, a new improved high speed convergence QPSO algorithm (HSCQPSO) was set up. The test results of international standard function indicated that:the convergence speed and the optimization accuracy of this algorithm were satisfied in most function optimization problems. The HSCQPSO algorithm was applied to optimize the parameters of two-phase dynamic pressurizer mechanism model, and improved the model accuracy effectively. Depending on the accurate model established in this paper, we designed pressure control system of pressurizer, and optimized the controller parameters using HSCQPSO algorithm in addition. The simulation results show that the proposed algorithm has better effect.Some innovative achievements are obtained, there are:(1) A method for realizing the reactivity estimation of control rod negative reactivity, Doppler effect, moderator temperature effect, dissolved boron negative reaction used neural network was realized, and calculation model combined mechanism analysis with reactor was proposed.(2) The integral model of primary loop in nuclear power unit was established based on Matlab, it has small steady-state error and reasonable dynamic characteristics.(3) A new improved high speed convergence QPSO algorithm (HSCQPSO) was set up, and was applied to parameters optimization of pressurizer.(4) An IMC-PID controller pressure was designed for pressure system of pressurizer, and optimized the controller parameters using HSCQPSO algorithm. The simulation results show that the proposed algorithm has better effect.