Mechanism and brain-like intelligence combined online soft measurement method for quality of coal as fired of power plant

Abstract

The invention discloses a mechanism and brain-like intelligence combined online soft measurement method for quality of coal as fired of a power plant.. The method comprises the steps of collecting monitoring data of 190 conventional monitoring points in real time; and extracting original principal component characteristics of the monitoring data, inputting the original principal component characteristics into a pre-established online soft measurement model of the coal as fired of the thermal power plant, and outputting soft measurement values of online element components and industrial components of the coal as fired. Under the condition of not adding any hardware facility, real-time and accurate online soft measurement of the quality components of the coal as fired can be realized, and areal-time online basis can be provided for combustion optimization, intelligent control and decision making of a thermal power plant; in addition, the method utilizes real-time data of conventional monitoring points of a thermal power plant to realize soft measurement of coal quality of as-fired coal and five element components and four industrial components at the same time; wherein the soft measurement absolute error of each component is less than 1%, and the soft measurement time is less than 1 second.

Description

technical field [0001] The invention relates to the field of smart power plants and artificial intelligence, in particular to an online soft measurement method for coal quality in a power plant that combines a mechanism with brain-inspired intelligence. Background technique [0002] At present, the analysis of the industrial and elemental components of coal quality mainly relies on the power plant operators to regularly sample and test the raw coal every 8 hours and every day. This method has the following shortcomings: the sampling process of raw coal is a random process, and the representativeness of the samples is not good. It must be guaranteed; the raw coal testing process is carried out regularly every day, the minimum period is 8 hours, and the coal composition cannot be analyzed online in real time, and the regular test value is used instead of the 8-hour average value, and there is a certain deviation; the elemental composition and industrial composition of a batch o...

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Problems solved by technology

[0002] At present, the analysis of the industrial and elemental components of coal quality mainly relies on the power plant operators to regularly sample and test the raw coal every 8 hours and every day. This method has the following shortcomings: the sampling process of raw coal is a random process, and the representativeness of the samples is not good. It must be guaranteed; the raw coal testing process is carried out regularly every day, the minimum period is 8 hours, and the coal composition cannot be analyzed online in real time, and the regular test value is used instead of the 8-hour average value, and there is a certain deviation; the elemental composition and industrial composition of a batch of coal samples The analysis results are obtained after 8 hours. It is difficult to guide the energy-saving power generation scheduling plan of coal-fired power plants, and it is difficult to optimize the power generation of coal-fired thermal power units more scientifically and fairly.

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