Coal-burning boiler system mixing modeling method

Abstract

The invention relates to a coal-fired boiler system hybrid modeling method. In the method, a real-time data driving method is firstly used for establishing a local prediction model; concretely, the collected real-time process running data is taken as a sample set of data driving; based on the set, a local controlled autoregressive moving average model in the form of discrete difference equation based on a least square method is established; secondly, a local error intelligent prediction model is established by an error data driving method; concretely, based on the sample set of the error data driving, a supporting vector optimization method is adopted to establish the local error intelligent prediction model. The local error intelligent prediction model is established by that: the error performance index is given according to process requirements and the judging is then carried out. The modeling method provided by the invention can effectively reduce the error between the model and practical process parameters, compensates the shortages of traditional controllers, ensures that the control device runs under the best state, leads the process parameters of production to be strictly controlled, and effectively improves the precision of the models.

Description

technical field [0001] The invention belongs to the field of information technology and relates to automation technology, in particular to a data-driven and intelligent control-based modeling method for a coal-fired boiler. Background technique [0002] Coal-fired boiler is an important power equipment in the power production department. Its requirement is to supply qualified steam so that the steam output of coal-fired boiler can meet the needs of the load. For this reason, each main process parameter of the production process must be strictly controlled. However, coal-fired boiler equipment is a complex controlled object, and the input and output are interrelated. For example: changes in steam load will inevitably cause changes in drum water level, steam pressure and superheated steam temperature; changes in fuel volume not only affect steam pressure, but also affect drum water level, superheated steam temperature, excess air and furnace negative pressure; water supply T...

AI Technical Summary

Problems solved by technology

These unfavorable factors lead to low accuracy of the model based on traditional modeling theory, which further leads to instability of subsequent production control parameters, low product qualification rate, and low boiler efficiency

At present, the modeling and control of coal-fired boilers are completely dependent on the experience of technicians, which increases the production cost and the control

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