Research On The Operation Guidance System Of Thermal Power Plant Based On Fine Operation

With the rapid development of the economics and people's living standards in China,the demands for energy are expanding increase,therefore,the contradiction between supply and demand of energy resources and the pollution of ecological environment has become a major challenge in recent years.To solve the problems above,China began to implement the national energy saving action,and put energy saving and emission reduction as the key work.The thermal power plant,which is a large energy consumer,is an important concern for energy saving and consumption reduction.Among the many indexes,coal consumption is the best indicator of energy saving effect in thermal power plant.The coal consumption of the power plant is mainly calculated by the positive balance method and the counter balance method,which involves a complex calculation procedure and requires a large number of later corrections for the results,cannot truly reflect the coal consumption of the power plant.In this paper,the support vector machine(SVM)algorithm is innovatively applied to the coal consumption prediction,which can not only provide new ideas and methods for the economic diagnosis of thermal power units,but also has great enlightening significance to solve the other complicated diagnosis problems.First,starting from machine learning and statistical learning theory,we introduce the support vector machine regression problem from two aspects of linear regression and nonlinear regression,and further analyze the principle of least squares support vector machine(LS-SVM).Secondly,we select part of operating parameters which have great influence on the coal consumption rate and carry out a specific study,then establish the prediction model using the LS-SVM method.The model can build discrimination function and corresponding nonlinear transformation based on some training samples,showing the complex nonlinear relationship between coal consumption and its influencing factors.On this basis,taking a 600 MW unit of a power plant as an example,the results show that the model not only has short training time and good convergence,but also has strong handling capacity for small samples,thus statistical learning can be done well in the case of a small number of samples.Finally,we develop ‘the operation guidance system of thermal power unit based on fine operation' based on the LS-SVM model,which has new and friendly interface,operating briefly and conveniently.The system can provide detailed information database for coal consumption of thermal power plants in advance,calculate the loss of the unit paiameters based on the energy loss analysis theory and provide guidance for operation,and have great practical significance to improve the level of intelligent management of power plants.