Specific resistance soft measurement method and optimization control method based on electric precipitation control system

By implementing the resistivity soft measurement and optimization control method in the electrostatic precipitator control system, the problems of high energy consumption and poor stability of the electrostatic precipitator system were solved, and the energy consumption optimization and stability improvement of the electrostatic precipitator system were achieved.

CN120733877APending Publication Date: 2025-10-03NANCHANG KECHEN ELECTRIC POWER TEST & RES CO LTD
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Patent Information

Application Number
CN202511211359.8
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-08-28
Publication Date
2025-10-03

AI Technical Summary

Technical Problem

The existing electrostatic precipitator control system has problems such as high energy consumption, high development complexity, poor stability, and low code reuse rate. It also lacks real-time resistivity monitoring and optimization control methods, resulting in unstable electrostatic precipitator efficiency.

Method used

By implementing the resistivity soft measurement method in the electrostatic precipitator control system, including steady-state judgment, data mining and resistivity interval statistics, combined with the global bit number real-time database and improved function block structure, the controller is optimized to adjust the dust concentration set value and realize dynamic adjustment of the resistivity.

Benefits of technology

Under the premise of ensuring dust removal efficiency, the overall energy consumption of the electrostatic precipitator system is reduced, the stability and development efficiency of the system are improved, and the maintenance workload is reduced.

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Abstract

The invention discloses a specific resistance soft measurement method and optimization control method based on an electric precipitation control system. The specific resistance soft measurement method comprises the following steps: a DCS (Distributed Control System) acquires field data such as unit load and dry electricity outlet concentration; the optimization controller also collects field data and calculates the adjustment amount of a dry power concentration set value, and the process is as follows: firstly, performing steady state judgment, and obtaining a power mean value and a sample number under a stable working condition to determine whether data mining succeeds or not; if the deviation between the current working condition and the last time is large or the excavation time is too long, new excavation is carried out; calculating the current specific resistance, determining the interval of the current specific resistance, and outputting the adjustment amount according to the interval; and when conditions such as specific resistance optimization control starting are met, the adjustment amount is taken as a real-time adjustment amount, otherwise, adjustment is not carried out. On the premise that the dust concentration of the dry electricity outlet meets the emission requirement, the total energy consumption is reduced.
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