An Intelligent Optimization Parameter Identification Method Used In The Steam Turbine And Its Governing System

The proportion of large capacity unit in power grid is steadily enlarging along withthe scale of modern power generation system, and the economic，safety and powersupply quality of the unit and power grid directly affected by the controllingperformance of the large capacity turbine. However, due to the long–time operation andits aging, the current characteristics of a turbine and its governing system can be muchdifferent from the design parameters. In order to achieve the detailed performanceparameters of a turbine and its governing system, an accurate model is necessary toanalyze its dynamic characteristics. Since there is no enough measured data to satisfythe mode building based on the basic theories, the parameter identification method playsan important role in this field.For reduction the complexity of processes, time-consuming and manual labor intraditional parameter identification methods of steam turbine and its speed governorsystem, a new one-touch intelligent method is introduced and used in parametersidentification of steam turbine and its governing system in this thesis which is morepractical, convenient and efficient compared with the traditional parameteridentification methods. The main work and achievements of this thesis are listed asfollows:(1) A new serial parameter identification method is proposed. In order to solve theserious problem of traditional parallel identification method, a new serial method usedto identify all the parameters for steam turbine and its governing system was built. Theparallel method and the new serial method are used to identify the parameters of theturbine and its governing system, based on the operation dada of a600MW power unit,and the comparison results show that the new serial identification method is much moreefficient.(2) The efficiencies of the three typical parameters identification algorithms areanalyzed. The genetic algorithm, an improved particle swarm optimization and animproved gravitational search algorithm are used to identify the parameters of a600MW steam turbine system and a300MW steam turbine system. It’s good for theengineers to select the suitable identification method.(3) A convenient intelligent parameter identification process is propose, combiningthe serial identification method, intelligent optimization algorithms and the automatic method of getting the data of a specific step disturbance. In the identification process,the step time, initial value, final value and the valid data can be set automatically, and ithas the advantages of the ness human work and repeatability.The new intelligent parameter identification method is applied to identifyparameters of a600MW steam turbine system and300MW steam turbine system. It isproved that it is more precise and efficient compared with the traditional methods. It hasprovided a new idea for turbine and its governing system’s parameters identification.