Main steam temperature prediction control method, device, equipment and medium based on fusion model

By constructing a fusion prediction model and optimizing the objective function, and combining historical data from coal-fired power units, adaptive control is achieved, which solves the problems of insufficient intelligence and energy saving in the control strategy of coal-fired power units, improves the accuracy of main steam temperature prediction and system response capability, and enhances the stability and economy of the equipment.

CN120669533BActive Publication Date: 2026-06-02SICHUAN GUANGAN POWER GENERATION CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
SICHUAN GUANGAN POWER GENERATION CO LTD
Filing Date
2025-06-13
Publication Date
2026-06-02

AI Technical Summary

Technical Problem

The existing control strategies of coal-fired power units are not intelligent enough and not energy-efficient enough, and cannot effectively cope with complex and ever-changing operating environments, resulting in insufficient equipment stability and economy.

Method used

A fusion prediction model is constructed based on the superheater dynamic heat transfer theory. The model is updated by combining historical operating data of coal-fired units. The operating mode is automatically switched by optimizing the objective function, including stable mode, variable load mode and extreme mode, to achieve adaptive control.

Benefits of technology

It improves the accuracy of main steam temperature prediction and the intelligence level of the control system, optimizes energy efficiency, enhances the operational stability and economy of coal-fired units, and can maintain safety and responsiveness in complex environments.

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Abstract

The application discloses a main steam temperature prediction control method, device and equipment based on a fusion model and a medium, and relates to the field of coal-fired unit control. The method comprises the following steps: constructing a fusion prediction model based on the dynamic heat transfer theory of a superheater; updating the fusion prediction model based on the historical operation data of the coal-fired unit; determining the predicted main steam temperature of the coal-fired unit based on the fusion prediction model, and constructing an optimization objective function according to the predicted main steam temperature; solving the optimization objective function under preset constraint conditions to obtain an optimization objective; and determining the working mode of the coal-fired unit based on the function value of the optimization objective, wherein the working mode comprises a stable mode, a variable load mode and a limit mode. The application can improve the intelligent degree of the coal-fired unit control.
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