Self-adaptive multi-working-condition steel secondary energy generation amount dynamic prediction method

Abstract

The invention provides a self-adaptive multi-working-condition steel secondary energy generation amount dynamic prediction method, and relates to the technical field of steel energy prediction. The method comprises the following steps: acquiring coke oven gas generation amount historical data under multiple working conditions, setting a coke oven gas generation amount data preprocessing time interval, reading system clock data, preprocessing the acquired coke oven gas generation amount data, and dividing a multi-working-condition data set; setting particle swarm optimization method parametersand least square support vector machine parameters, initializing the parameters, fitting coke oven gas generation amount prediction model parameters in time series data by utilizing an intelligent method, and identifying working conditions to finish coke oven gas generation amount prediction. Stable, reliable and accurate coke oven gas dynamic multi-working-condition prediction application is realized, prediction model parameters can be learned adaptively, and scientific data support is provided for energy management personnel to make a gas scheduling plan, so that energy diffusion is reduced,refined utilization is improved, production supply is stabilized, and energy cost is reduced.

Description

technical field [0001] The invention relates to the technical field of iron and steel energy forecasting, in particular to an adaptive multi-working-condition iron and steel secondary energy generation dynamic forecasting method. Background technique [0002] The production process of coke oven gas in iron and steel enterprises is complicated. Gas coal, fat coal, coking coal and lean coal with a good ratio are pushed into the coke oven from the carbonization chamber, and reactants are formed under the heating of the combustion holes in the combustion chamber and the mixed air reaction. After the specified coking time, the reactants are coke-extracted and sent to the regenerator for coke quenching operation, thereby generating secondary pyrolysis products such as coke oven gas. After the coke oven gas produced is mixed and pressurized by the gas pressurization station, in addition to participating in the production links such as pelletizing, sintering, and steel rolling mixin...

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Problems solved by technology

[0010] Aiming at the problems existing in the limitations of the existing iron and steel energy prediction technology, the present invention provides an adaptive multi-working-condition steel secondary energy generation dynamic prediction method to realize the stable and reliable coke oven gas dynamic multi-working-condition prediction application , accurate, and can adaptively learn and predict model parameters, providing scientific data support for energy managers to formulate gas dispatching plans to reduce energy emissions, improve refined utilization, stabilize production and supply, and reduce energy costs

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