Study On Dynamic Simulation And Operating Optimization Of Large-scale Steam Turbine Unit

The electricity industry is the key field to reduce the energy consumption, and it is critical to energy reduction targets in the12th Five-Year Plan. Pursuing profits is the major goal for a power plant in the constraints of security and reliability. In current power production market, the major research aspects among colleges and institutes are how to improve the security and ecomomic of generator unit.This article analyzed the optimization technology of steam turbine and the simulation technology of power plant all over the world, and then proposed that the digital simulation technology is applied into the steam turbine engineering research. The purpose is to optimize the steam turbine operating factors, and to improve the real-time performance monitor.The major research findings are:Discovered the potential excessive security issues in the current stream turbine operating process. The author suggested that we could use the massive data from power plant’s DCS system, together with data mining technology to determine the route of the optimizing operation. This system used the DCS database as the basis for the system data analysis, and used the neural network model online analysis to obtain the best correct value.Proposed the adoption of simulation technology to study the optimization of the stream turbine operation, and to use the advanced control strategy to improve the current control system. The technical foundation to implement this new technology is to build the high accuracy dynamic mathematical model. After discussing this new technical application’s feasibility, the author established some system analysis mathematical models of equipments related with stream turbine operating, which include turbine unit, regenerative heating system, condensing water and circulating water system and stream turbine pipeline mathematical model. A great improvement has been made toward the current flaws such as the simplifications, lack of considering the actual device parameter. At the end, the author assembled the stream turbine and other device into the regeneration heating system, condensing water and circulating water system and other system models, and he has done plenty simulation tests on all kinds of operating condition to test the static and dynamic characteristic of his models. The simulation test results proved that the mathematical model has high precision, very good dynamic characteristics, and full consideration of the coordination between the static and the dynamic states. The simulation results are consistent with the actual production process in power plants. Established the regression model that is related to the stream turbine system major factors, and he has trained twenty-four networks to improve the accuracy of this regression model. The testing data proved the accuracy of these trained networks, and the deviation meets all the requirements. The author analyzed the method to determine the system equipment parameters under stream turbine operating conditions, he also discussed how to determine the optimized main stream turbine pressure value considering outside conditions and the economical factors.Based on the optimized value of the stream turbine operation, and from the energy-loss analysis for the steam turbine system, the author built the operational performance optimization model. The author proposed the guidance to the optimized economical operation based on the equipment performance status analysis and operational factor analysis. He also had conducted through research on a power plant simulation platform on various factors, which reduced the unit economical efficiency.Established the energy loss calculation model which can be used for the heater operating status, and this model can also be used to determine if the heater operating status is normal, which also been known as the state benchmark. Secondly, the author gave the energy loss calculation model that is used for the heater. This model can be used to decide how the physical characteristic difference affects the terminal difference. If the terminal difference is abnormal, then it indicates that there is fouling or air in the heater. The author also established the energy loss calculation model for the extraction line. This model can be used to find out if there is any abnormal status such as blockage or erosion.Proposed the method to implement the large-scale stream turbine optimized system as well as the hardware architecture for the Supervisory Information System (SIS) optimized system at the factory level, which provided the support for implementing the optimizing functionalities into the power plants’SIS.