Research On Efficiency Analysis And Diagnostic Of Boiler And Auxiliary System

At present, our country basically for the thermal power units have installed basically Distributed Control System and Supervisory Information System, mainly achieving the function of real-time indication and calculation of important parameters, such as coal consumption rate of power supply, boiler efficiency and so on. For different indexes, different methods were adopted for the determination of target-value and the method of energy loss analysis, to calculate the energy loss caused by running parameters deviating from the benchmark. Which makes the system complicate, and when the energy efficiency index is abnormal, the system lacks the real-time diagnostic function.For the problem mentioned above, the methods for the energy efficiency analysis and diagnosis of boilers and auxiliary systems are studied in this paper. To begin with, the main indicators of affecting the power supply coal consumption are analyzed by applying the formula method, which determine the extent of impact about the main index on the power supply coal consumption rate. Underlying factors that affecting energy efficiency were determined according to energy efficiency diagnosis tree, which are divided to two categories, operation parameters and maintainable fault. Class factor for running parameters, the decision attribute of energy efficiency is determined based on the unit consumption analysis theory, combined with the grey correlation analysis method to determine key energy consumption characteristics variables. When the effect factor is operation parameter, its decision attribute of energy efficiency and characteristic variable of the key energy consumption are determined according to the unit consumption analysis theory and grey correlation analysis method. The same time, good operation date is obtained through filtering stable operation date, dividing work condition and FCM. The final energy consumption decision rules were determined according to the combinations of the four characteristic parameters, which achieve the purpose of improving energy efficiency level by adjusting operation parameters. For the fault classes, factors influencing the energy efficiency were analyzed. It is difficult to obtain parameters in fault, so soft measurement model based on neural network is put forward, which achieve real-time fault diagnosis about influencing energy efficiency combined with principal component analysis diagnosis model.The energy efficiency of 600MW coal-fired boiler in plant was studied, the results indicated that the method can improve the economy of the boiler effectively, make the direction of operation adjustment clear, and has a certain significance on improving pertinence of the operation adjustment.