Cylinder switching and bypass heat supply multi-mode working condition self-adaptive switching decision-making system and method

By adopting a strategy of forward-looking rolling optimization and closed-loop self-learning rule correction in cogeneration units, the lag and parameter overshoot problems of cylinder switching operation and bypass heating mode switching control were solved, realizing economic, stable and intelligent adaptive control of the unit, and improving operational stability and equipment efficiency.

CN122106697APending Publication Date: 2026-05-29CHINA RESOURCES (SHENYANG) PROPERTY CO LTD
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Patent Information

Application Number
CN202610585147.4
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-04-29
Publication Date
2026-05-29

AI Technical Summary

Technical Problem

Existing technologies in cogeneration units suffer from issues such as lag, parameter overshoot, and inability to achieve global optimization in switching control between cylinder cut-off operation and bypass heating modes, leading to unstable unit operation and suboptimal equipment wear.

Method used

The system employs a strategy of forward-looking rolling optimization and closed-loop self-learning rule correction. By acquiring real-time operating parameters and external demands, it performs multi-dimensional rolling optimization calculations to generate optimization decision instructions. It then uses a pre-stored set of operating condition control mapping relationships for continuous control and combines thermodynamic mechanisms and data-driven analysis for online correction to achieve adaptive control.

Benefits of technology

It enables forward-looking prediction and global optimization of future operating conditions, improves the operational economy and stability of the unit during dynamic switching of multiple modes, reduces fluctuations in key parameters, and enhances the robustness and long-term adaptability of the system.

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Abstract

The invention discloses a cylinder switching and bypass heat supply multi-mode working condition self-adaptive switching decision-making system and method, and belongs to the technical field of steam turbine control. The method comprises the steps that real-time operation parameters and external demand parameters of a unit are obtained, and a current working condition state vector is obtained; performing multi-dimensional rolling optimization calculation on the current working condition state vector and the demand prediction parameters in the future time period to generate an optimization decision instruction; using the current working condition state vector to index a pre-stored working condition control mapping relation set, and calculating to obtain a continuous control instruction; performing association evaluation on the current working condition state vector, the execution feedback data of the continuous control instruction and the execution effect data of the optimization decision instruction to generate a rule updating instruction; executing a rule updating instruction, and correcting the working condition control mapping relation set. According to the method, the strategy of combining prospective rolling optimization and closed-loop self-learning rule correction is adopted, and economic, stable and intelligent self-adaptive control over operation mode switching of the steam turbine under the variable working conditions can be achieved.
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