Modular Modeling,Simulation And Dynamic Optimization Of High Temperature Gas-cooled Reactor

As a new type of advanced nuclear power plant with the feature of Generation IV nuclear energy system, the high temperature gas cooled reactor pebble-bed module (HTR-PM) plant is different from the current widely-used Pressurized Water Reactor (PWR) or Boiling Water Reactor (BWR) nuclear power plants in terms of the reactor type and operating mode. HTR-PM is based on the High Temperature Gas-cooled Reactor-Pebble Bed Module using the "Dual-Modules with One-Turbine(DMOT)". It is extremely important to guarantee the steady-operation and safety of the plant with load changing in different levels through simulation and optimization. Currently the technology and DMOT structure of HTR-PM is the first design case in nuclear system operation, so there lacks sufficient experiences domestically or internationally. A simplified dynamic model has been developed and verified by The Institute of Nuclear and New Energy Technology in Tsinghua University. Based on the verified model a new modular and equation-oriented model is developed to improve the performance of simulation. Dynamic optimization is implemented in HTR-PM model to improve the efficiency in load changing and the performance parameters. The contributions of this thesis include the following three aspects.·Dynamic models were developed through the methodology of modularization and equation-oriented approach. The dynamic models were provided for all the control systems of HTR-PM including reactors, steam generators, turbine-generator system and common steam header system. The models were-then verified on their steady-state and transient process, which were shown to be suitable for the control system design and simulation. At the same time accuracy and efficiency are also guaranteed.·Dynamic optimization of HTR-PM at load changing. Because the load change of the system happens frequently, proper tuning of the process to meet the load demand is important. In order to guarantee the smooth operation at load changing, single shooting is applied in the dynamic optimization, we choose continuous piecewise linear control profile. The object of optimization is to get the fastest load changing or get the best performance on the system state variable. The result shows that the objective can be reached by dynamic optimization.·To improve the efficiency and performance of dynamic optimization, in this paper we present two methods for the optimization of dynamic systems using problem-adapted discretizations. There are total three steps in the process with different parameterization strategies. One is based on the linear approximation and another is based on gradient calculation. Compared with the previous calculation process, the reliability of the system optimization is greatly improved with less parameterization control intervals, less calculation time and satisfied optimization object.