Research On Energy Efficiency Evaluation And Diagnosis In Turbine Proper Of Ultra Supercritical Unit

In view of the country’s increasing demands of the development of thermal power,how to effectively reduce the energy use efficiency of thermal power plants has become an important issue in the development of thermal power industry.So it is very important to study the method of condition monitoring,energy efficiency evaluation and energy efficiency abnormity diagnosis in thermal power plant in the present stage.This paper makes an in-depth study on the energy efficiency evaluation and diagnosis method of the steam turbine of a 1000 MW ultra supercritical unit.Mainly solve the following key issues:1.Design of energy efficiency monitoring scheme.It is difficult to get the real time state of the turbine accurately and effectively.So we use the method of hierarchical analysis to establish the monitoring index tree,and study the mathematical model of the index calculation in advance.2.Study on energy efficiency evaluation method.There are two core issues of energy efficiency evaluation: The first one is to calculate the parameter difference factor.The second is to obtain the parameters’ reference state value.If we can’t calculate the parameter consumption factor,then we can’t get the potential of the coal saving index when the index deviates from the reference state,which makes the implementation of energy efficiency evaluation become an empty talk.It is difficult to evaluate parameter reference state.In this paper,the core problem is solved by the combination of data mining and thermodynamic calculation.3.Research on diagnostic methods of energy efficiency anomaly.When monitoring the energy efficiency index is abnormal,it is very important to study the abnormal pattern,the abnormal cause and treatment measures.4.Design and development of energy efficiency evaluation and abnormity diagnosis system for ultra supercritical unit steam turbine.All theoretical studies are needed to test the engineering application.So it is very important to develop the energy efficiency evaluation and diagnosis system.