Study On Forcasting Modeling Of Characteristics Of Coal In Power Plant

As to coal-burning plant unit, the running ability of boiler has intimate relation with the characteristics of the coal in the boiler. Recently in the power plant we could only analysis the industry component of the coal, but can't analysis the element and combustion characteristic under lab circumstance. As a result, it is not good for the security and the economical operation of the boiler. The paper took neural network technology as a tool, researched the prediction model which based on the combustion characteristic of the industry component of the coal. There will be crucial theoretic significance and applied research value.Due to their powerful ability of approximating nonlinear functions, and with the characteristics of adaptive learning, parallel and distributed processing, strong robustness and fault tolerance, neural networks have been an effective approach to model and control the unknown and uncertain nonlinear system. Based on existing learning algorithms for RBF neural networks, novel learning algorithms are proposed in this paper, the application of RBF neural networks with proposed algorithms in nonlinear systems modeling is studied, and simulation study for characteristics of coal. The main works are:1.Research on neural network modeling method. The paper summarized the RBF neural network and advanced a mixing learning method based on hybrid RBF neural network, the memory, learning and self-organization abilities of artificial immune system are introduced into the selecting of the number and position of hidden layer radial basis function centers, the output layer weights are decided with the recursive least squares algorithm. The simulation results prove that it is with good generalization ability.2.Research on combustion characteristic of the utility boiler coal. Including the technical analysis, element analysis , combustion characteristic of the coal ,and so on. Especially, the paper summarized the research methods and influence factors of combustion characteristic and clogging characteristic.3.Set up a predication model of combustion characteristic by RBF neural network. The paper constructed transfer mold between the industry analysis element and the ultimate analysis element by RBF neural network. Just as the model predicating the combustion characteristic by the industry analysis element, and the model predicating the clogging index by the ultimate analysis element. The simulation results prove that the models has a good accuracy and the ability of generalization.4.The apply research on the predication model of combustion characteristic by neural network. The paper advanced the neural network predication model of element analysis model, and bring up the method which accounting the boiler efficiency by transforming the industry component analysis of the coal into element analysis, then compared with the results of boiler efficiency accounting by industry component analysis. The result proved that the accuracy will be enhanced effectively.