Gas system optimal scheduling method based on artificial intelligence

Abstract

The invention discloses a gas system optimal scheduling method based on artificial intelligence, and solves the problems that the capacity of an existing iron and steel enterprise energy management center for knowing special working conditions is seriously lagged, and the regulation and control process of the special working conditions is generally lagged. According to the optimal scheduling method for the gas system, a material flow and energy flow cooperative relationship of an iron and steel enterprise serves as a first layer, and stable supply of model basic information is guaranteed; gassupply and demand trend prediction and optimal scheduling are taken as a second layer, so that the scientificity of system decision making is ensured; and a system self-learning function is taken as thethird layer of the model, emergencies are calculated and summarized to form an improved strategy, and the database model is updated. The built coal gas system database can dynamically predict the change trend of the coal gas generation amount, consumption amount and surplus amount; and therefore, violent fluctuation of coal gas is effectively controlled, the efficiency of a gas-fired boiler is improved, reasonable distribution of the coal gas is realized, and benefit maximization is ensured.

Description

technical field [0001] The invention belongs to the technical field of metallurgy automation, and in particular relates to an artificial intelligence-based gas system optimization dispatching method capable of effectively controlling violent gas fluctuations, improving the efficiency of gas boilers, realizing reasonable distribution of gas, and ensuring maximum benefits. Background technique [0002] Apart from supplying gas to each main process in iron and steel enterprises, the remaining part (surplus gas) is used for power generation. All kinds of special working conditions in the gas system will lead to a sudden increase or decrease in the gas volume, which will seriously affect the safety and stable supply of gas in other processes, and will cause obvious environmental problems in a short period of time. However, the ability of the energy management centers of existing iron and steel enterprises to learn about special working conditions is seriously lagging behind, and ...

AI Technical Summary

Problems solved by technology

All kinds of special working conditions in the gas system will lead to a sudden increase or decrease in the gas volume, which will seriously affect the safety and stable supply of gas in other processes, and will cause obvious environmental problems in a short period of time

However, the ability of the energy management centers of existing iron and steel enterprises to learn about special working conditions is seriously lagging behind, and the process of regulating special working conditions is also generally lagging behind

Due to the failure of upstream accidents in the gas system to be fed back to the energy management center in a timely manner, the boilers passively receive the violently fluctuating excess gas, and the lack of reasonable coordinated operation means among the boilers, resulting in high fuel consumption in the self-generation system of the steel plant. low self-generating power

The historical data of the gas system is stored in the steel enterprise resource planning system (ERP), manufacturing execution system (MES) and energy management system (EMS) in a static form, and is used to generate reports and queries, which are not related to each other; resulting in a large number of The data cannot be used to predict the trend of gas supply and demand and to predict the use of subsequent planning

[0003] There are many equipments in the gas system, the structure of the pipeline network is complicated, there are many problems in the collection, transmission and display of gas information, and the energy management center does not have the function of dynamic processing of gas data, so it is impossible to realize the dynamic prediction of gas supply and demand and the online generation of scientific guidance plans

At the same time, there are few operations that can be controlled online by the energy management system. The adjustment of the gas volume of most gas-consuming equipment requires telephone notification and manual operation, and online control cannot be performed. Lag, or even failure

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