Study On The Operation Parameters Of DHL-29Type Boiler Energy Saving Optimization

DHL-29boiler is the traditional heating boiler, so it needs assessment for the energy saving and optimization of operation parameters. Aiming at the demand of boiler transformation, this paper did the selection and optimization of the boiler’s operation parameters.Coal fired boiler is a typical multiple input, multiple output nonlinear system, between each kind of factor coupling, perplexing. Boiler furnace combustion conditions is affected by many factors, such as load, coal quality, concentration of pulverized coal fineness, and types of wind speed, the wind scale, such systems are difficult to use specific function expression the internal relationship of between the parameters.Artificial neural network nonlinear mapping capability is very strong, is a complicated nonlinear system, is composed of many simple neuron, widely which are connected mutually. Artificial neural network through training or learning to automatically summarize the relationship between data without a priori formula, can receive data inherent laws, so it is a kind of effective modeling method. This paper adopts the genetic algorithm global optimization characteristics will run after parameter optimization, and to train the neural network, thereby obtaining better network output. From the influence of boiler thermal efficiency and NOx emissions from the two aspects of factors analysis, to determine the effect of boiler heat efficiency of combustion and NOx emissions of major factors, and then will influence factor as the network input parameters, boiler heat efficiency of combustion and NOx emissions as output of network parameters, to establish a genetic algorithm and BP neural network coupling the" black box" model of boiler combustion characteristics.With the characteristic that genetic algorithm can optimize the model without exact function type, this paper does the optimization of already established good boiler combustion characteristics model, combines the model and genetic algorithm, and it achieves three different optimization objectives of operation optimization search, optimization objectives are: the single optimization the boiler thermal efficiency, individually optimization of NOx emissions, and comprehensive optimization considering the boiler thermal efficiency and NOx emissions. It gets different optimal object corresponding to the input parameter data, guiding the economic and efficient operation of boiler. And then find out the insufficient of the boiler operation to rebuild the power selection which can not meet operation parameters.