An optimization method for improving flexible operation of a thermal power unit

Abstract

The application provides an optimization method for improving flexible operation of a thermal power unit, relates to the technical field of big data, and comprises the following steps: analyzing first operation state data obtained by monitoring the operation state of a target unit in real time to obtain a unit operation state result; using a parameter prediction model constructed by using a machine learning algorithm to predict key control parameters of the target unit based on the first operation state data to obtain a control parameter prediction result; and analyzing the control parameter prediction result and the unit operation state result to generate a target adjustment strategy for the target unit. The operation state of the unit is monitored and analyzed in real time to obtain the operation state of the unit at the current time, and the obtained operation state is combined with a control parameter prediction result of the unit obtained by using a parameter prediction model constructed based on a machine learning algorithm to analyze and generate a target adjustment strategy for the unit, so that intelligent control of the key control loop of the unit and flexible adjustment of the parameters are realized, and the unit benefit is maximized.

Images