Performance Evaluation Of Control System Of 300 MW Thermal Power

With the rapid development of the world,people are increasingly demanding automation.About 60%of PID control loops have a certain degree of performance defects.With the increasing production scale,the number of control system loops is also increasing,and it is not possible to rely on manual inspection and maintenance of the control system.When the performance of the control system deteriorates,the quality of the product and the life of the production equipment will be seriously affected;in addition,even if the controller runs well,after a long period of operation,the control performance will gradually decrease and so on.It is known that the control system is full throughout the power generation process,and the performance evaluation and fault diagnosis of the control system can identify and diagnose problems in the system at an early stage,improve the effectiveness of the control,and prolong the service life of the equipment.Therefore,it is necessary to evaluate the performance of the power generation process.For the performance evaluation and optimization of thermal power process control system,the main work and achievements of this paper are mainly reflected in the following aspects:Firstly,the minimum information entropy performance evaluation benchmark is introduced for the univariate system under non-Gaussian perturbation,and the coefficient of performance evaluation index is proposed.Based on the minimum information entropy performance index,the minimum information entropy performance evaluation index based on coefficient of variation is proposed,which is extended to the univariate non-Gaussian control system and the multivariable non-Gaussian control system.And through the simulation analysis,the feasibility and accuracy of the method are verified,and the theoretical preparation for the subsequent evaluation work is made.Secondly,for the system under non-Gaussian perturbation,the minimum rational entropy performance evaluation index is introduced.Based on the minimum rational entropy performance index,the performance evaluation index of non-Gaussian system based on the minimum rational entropy benchmark of coefficient of variation is proposed.Then extend it to a multivariable non-Gaussian control system.At the same time,a performance evaluation index of Gaussian system based on probability density function which can be calculated based on operational data is introduced and extended to non-Gaussian systems.The simulations verify that these three indicators can evaluate the performance of univariate control systems and multivariable control systems well under non-Gaussian noise disturbances.Finally,the unit coordination control system of thermal power plant is introduced,and combined with the equivalent transfer function theory and minimum information entropy performance index,equivalent transfer function theory and minimum information entropy performance index based on coefficient of variation,equivalent transfer function theory and minimum rational entropy performance index,equivalent transfer function theory and based on the minimum rational entropy performance index of the coefficient of variation is used to evaluate the multivariate actual system.The simulation results show that the four evaluation indexes can evaluate the performance of the multivariable actual control system well under non-Gaussian noise disturbance.