Dynamic target pressure generation method based on multi-source pressure characteristics and energy efficiency curve

By building an energy efficiency curve library and multi-objective optimization algorithm, the target pressure of the air compressor is dynamically adjusted, and the energy consumption waste problem of traditional air compressor stations is solved, achieving global energy efficiency and operating stability.

CN120487589AActive Publication Date: 2025-08-15SICHUAN BENJIE TECHNOLOGY CO LTD
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Patent Information

Application Number
CN202510880850.3
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-06-27
Publication Date
2025-08-15
Estimated Expiration
2045-06-27

AI Technical Summary

Technical Problem

Traditional air compressor stations adopt fixed pressure control to cause waste of energy consumption, and there are problems of overpressure gas supply or underpressure shutdown.

Method used

By collecting gas pressure data for the main pipe and the end, an energy efficiency curve library is built, the optimal continuous pressure interval is screened, and the target pressure of the air compressor is allocated using a multi-objective optimization algorithm, combining real-time monitoring and PID controller to adjust the frequency to achieve dynamic target pressure control.

Benefits of technology

It achieves optimal global energy efficiency, avoids waste of energy consumption, and improves the accuracy of operating stability and pressure requirements.

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Abstract

The invention discloses a dynamic target pressure generation method based on multi-source pressure characteristics and an energy efficiency curve, and belongs to the technical field of energy-saving control of industrial air compression systems. According to the method, the minimum value, the maximum value, the average value and the mode of tail end pressure are counted, the dynamic range of gas consumption requirements is accurately represented, and the dynamic target pressure is generated. The air compressor energy efficiency curve library is set, the optimal continuous pressure interval is screened instead of single-point optimization, the operation stability and the energy efficiency advantage are considered, finally, the target pressure of each air compressor is distributed through the multi-target optimization algorithm, energy consumption waste caused by pressure overlapping is avoided, and the energy efficiency of the air compressor is improved. The global energy efficiency is optimal, and the problems that due to frequent loading and unloading of the air compressors of an existing air compression station, energy consumption is wasted, the tail end air pressure requirement is lower than the air compressor set value, and the redundancy of the pressure set value is too high when the multiple air compressors operate in parallel are solved.
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