Research On Performance Assessment Of Coal-fired Power Plant Thermodynamic Control System Based On Data Mining

Now the operating data of power plant can easily access and storage, which provided wealth resources for people to use historical data analyze and calculate. How to use these history resources effectively, it determine that whether the current control system achieves good results, whether the performance is declining. Thus takes the measure and targets to carry on the re-tune or the maintenance before the problem appears which has become the matter of concern at present. Based on the characteristics of the data mining principle, this paper proposes that it uses data mining theory to coal-fired power thermodynamic control system performance evaluation process. In the process of evaluation, it adopts rough set method of data mining and gives the specific thought and application steps. Primary and secondary direct-contact desuperheater control system estimation scale of superheated steam temperature is scheduled grading as excellent, good, ordinary, poor, finally gives the quality of control system performance.