Forecast and balance method for tank level of coke oven gas of steel makers

Abstract

The invention discloses a forecast and balance method for tank level of a coke oven gas of steel makers, which comprises the following steps of: determining main gas users having influence on variation of the tank level; based on mass of existing data, creating a tank level forecast model reflecting a relation between the gas tank level and each main gas user through a modern regression modeling method; creating a flux forecast model for each main gas user through the modern regression modeling method by using mass of existing data based on the time sequence forecast thought; forecasting variation trend of the tank level for some time to come; forecasting a gas flux forecasted value of each user according to the created flux forecast model, and inputting the gas flux forecasted value into the tank level forecast model to obtain a forecasted value of variation of the gas tank corresponding to each forecasting time. The forecast and balance method for the tank level of the coke oven gas of the steel makers can accurately forecast variation trends of keeping steady, increasing and descending of the tank level of the gas tank, and can provide rational guidance for on-site dispatchers to finish balance dispatching of the gas.

Description

technical field [0001] The invention relates to the field of information technology, relates to factor correlation analysis theory and data-driven modeling regression prediction technology, and specifically relates to a method for predicting and balancing coke oven gas counters in iron and steel enterprises. Background technique [0002] Iron and steel enterprises are large energy consumers, and the rational use of energy is the goal that iron and steel enterprises have always worked hard for. For the by-product gas system of iron and steel enterprises, in order to achieve a balance between supply and use, at present, it mainly relies on on-site dispatchers to deploy and realize the balance of gas production and sales. However, the production and sale of gas is a dynamic process, and there are many factors that affect the balance of gas production and sales; for example, the experience and methods of dispatchers, etc.; and there is a time lag in the deployment of dispatchers...

AI Technical Summary

Problems solved by technology

However, this method regards each gas user in the gas pipeline network as the input of the counter prediction model, and the redundant input increases the complexity of the model; and the modeling method relies on the traditional regression modeling method, and the built counter prediction model low precision

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