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CN-122018286-A - GIS mixed gas air supplementing self-adaptive control method, system, equipment and medium

CN122018286ACN 122018286 ACN122018286 ACN 122018286ACN-122018286-A

Abstract

The application discloses a GIS mixed gas air-supplementing self-adaptive control method, a system, equipment and a medium, which relate to the technical field of GIS air-supplementing control, the self-adaptive control method realizes deep perception and early warning of gas state by multi-source data fusion trend prediction, changes passive air-supplementing into active prevention, the self-adaptive control method adopts a fuzzy PID control algorithm, the controller parameters are finely adjusted according to the deviation, the deviation change rate and the equipment load current, the predicted gas leakage rate is used as a feedforward signal to compensate the leakage quantity, the pressure is finally stabilized at a dynamic pressure set point, the gas proportion is always kept constant, the whole process is smooth and free from impact, the self-adaption to different leakage rates, environmental conditions and equipment load changes can be realized, and the robustness is high; in addition, the self-adaptive control method also adopts a proportioning strategy based on mass flow control, so that the pressure and the proportion of the fed gas reach the optimal set values.

Inventors

  • WANG JIAYI
  • PENG XIONG
  • LUO XINYU
  • XU SHENGDUO

Assignees

  • 国网西南电力研究院有限公司

Dates

Publication Date
20260512
Application Date
20260410

Claims (10)

  1. 1. The GIS mixed gas supplementing self-adaptive control method is characterized by comprising the following steps of: Synchronously acquiring multi-source sensing data of a GIS air chamber and preprocessing the multi-source sensing data, wherein the multi-source sensing data comprises gas pressure, gas temperature, mixed gas proportion and equipment load current; Based on a gas state equation, performing compensation calculation on the gas pressure by using the gas temperature to obtain normalized pressure at a standard temperature; Calculating a future pressure change trend through a time prediction model based on historical normalized pressure time sequence data, and estimating a gas leakage rate; Carrying out grading early warning based on the predicted normalized pressure and the gas leakage rate, wherein when the predicted normalized pressure and the gas leakage rate are both in a normal range or the deviation value from the normal range is smaller than a threshold value, continuing to execute the subsequent steps; dynamically generating a pressure control setpoint based on a target pressure and the gas leak rate; taking the deviation and deviation change rate of the predicted normalized pressure and the pressure control set point and the equipment load current as inputs, adaptively adjusting the parameters of a controller on line through a fuzzy reasoning mechanism, and calculating to obtain a first control quantity; Based on the gas leakage rate, combining feedforward control gain, and calculating to obtain feedforward compensation control quantity; And superposing and limiting the first control quantity and the feedforward compensation control quantity to generate a total control quantity, converting the total control quantity into corresponding control signals and transmitting the corresponding control signals to an execution unit so as to realize accurate and continuous regulation of the proportion of the air make-up flow and the mixed gas.
  2. 2. The method for adaptively controlling the gas make-up of a GIS mixed gas according to claim 1, wherein said performing compensation calculation on said gas pressure using said gas temperature comprises: Converting the gas temperature to a thermodynamic temperature; based on the thermodynamic temperature, calculating a compression factor in the current state and a compression factor in the standard temperature by adopting a compression factor calculation method based on a modified Beneidicke-Wei De-lubine state equation simplification type; Calculating normalized pressure according to the compression factor in the current state and the compression factor in the standard temperature: P_norm = P_m * (293.15 / T_k) * (Z2 / Z1); Wherein, P_norm is normalized pressure, P_m is gas pressure, T_k is thermodynamic temperature, and Z1 and Z2 are compression factor in current state and compression factor in standard temperature respectively.
  3. 3. The method for adaptively controlling the gas make-up of the GIS mixed gas according to claim 2, wherein the calculating the compression factor in the current state and the compression factor in the standard temperature comprises: Calculating a compression factor Z1 in the current state, wherein Z1=1+ (a1+a2/T_k) is P_m+ (a3+a4/T_k) is P_m≡2; Calculating a primary estimated normalized pressure p_est, p_est=p_m×293.15/t_k; Calculating a compression factor Z2 at standard temperature, wherein Z2=1+ (a1+a2/293.15) is P_est+ (a3+a4/293.15) is P_est≡2; wherein a1, a2, a3 and a4 are coefficients related to the ratio of the mixed gas.
  4. 4. The method for adaptively controlling the gas make-up of a GIS gas mixture according to claim 1, wherein the calculating the future pressure trend by the time prediction model and estimating the gas leakage rate comprise: Acquiring historical normalized pressure time sequence data, and setting a sliding analysis window with a preset length; Describing a pressure dynamic change process by adopting a second-order autoregressive model, and estimating model parameters on line in real time by using a recursive least square method with forgetting factors; In each control period, iteratively calculating a normalized pressure prediction sequence for a period of time in the future by using the latest estimated parameters and current sliding analysis window data; extracting a normalized pressure value of a length of the last section in the normalized pressure prediction sequence, and performing linear least square fitting based on the extracted normalized pressure value and a corresponding time index to obtain a slope of a fitting straight line; Calculating the gas leakage rate V_leak from the slope of the fitting straight line, wherein V_leak= - (k_slope/deltat) is 3600, and k_slope is the slope of the fitting straight line and deltat is the sampling period; Updating the sliding analysis window with the new normalized pressure data obtained prepares for model parameter estimation for the next cycle.
  5. 5. The method for adaptively controlling the gas make-up of the GIS mixed gas according to claim 1, wherein the step of adaptively adjusting the parameters of the controller on line by a fuzzy inference mechanism and calculating the first control amount comprises the following steps: Fuzzifying the deviation and deviation change rate of the current input predicted normalized pressure and the pressure control set point and the equipment load rate, and matching corresponding fuzzy rules from a pre-constructed fuzzy rule base according to fuzzy results to obtain corresponding output fuzzy sets, wherein the output fuzzy sets are controller parameter fuzzy sets; performing MAX synthesis on the output fuzzy set, and performing fuzzy solution through a gravity center method to obtain accurate controller parameter adjustment quantity; According to the controller parameter adjustment quantity, updating the controller parameter; Based on the updated controller parameters, an incremental PID algorithm is adopted to calculate and obtain a first control quantity.
  6. 6. The method for adaptively controlling the gas make-up of a GIS gas mixture according to any one of claims 1 to 5, wherein said converting the total control amount into a corresponding control signal includes: Converting the total control quantity into total supplementary air flow under a standard state through table lookup; And calculating the flow set value of each component according to the proportion of the mixed gas and inputting the flow set value of each component into the corresponding mass flow controller.
  7. 7. The method for adaptively controlling the gas make-up of a GIS gas mixture according to claim 6, wherein said converting said total control amount into a corresponding control signal further comprises: when the online gas proportion analyzer is configured to monitor the volume concentration of sulfur hexafluoride in the mixed gas in real time, executing an outer ring correction algorithm, namely reading the actual concentration of sulfur hexafluoride measured by the online gas proportion analyzer, calculating a proportion error, calculating a flow correction value through a PI controller, and correcting the flow set value of each component by utilizing the flow correction value; And/or when the total air supplementing flow is reduced according to the control requirement, updating the flow set values of all components in an equal proportion mode, and meeting the constraint condition in the updating process, wherein the change range of the flow set values per second is not more than 20% of the full range.
  8. 8. The utility model provides a GIS mixed gas tonifying qi self-adaptation control system which characterized in that includes: The pretreatment unit is configured to synchronously acquire and pretreat multi-source sensing data of the GIS air chamber, wherein the multi-source sensing data comprises gas pressure, gas temperature, mixed gas proportion and equipment load current; The compensation unit is configured to carry out compensation calculation on the gas pressure by utilizing the gas temperature based on a gas state equation to obtain normalized pressure at a standard temperature; A trend prediction unit configured to calculate a future pressure variation trend through a time prediction model based on the historical normalized pressure time series data, and estimate a gas leakage rate; The grading early warning unit is configured to perform decomposition early warning based on the normalized pressure and the gas leakage rate which are predicted by the trend prediction unit, and drive the self-adaptive decision unit to work when the predicted normalized pressure and the gas leakage rate are both in a normal range or the deviation value deviating from the normal range is smaller than a threshold value; The self-adaptive decision unit is configured to dynamically generate a pressure control set point according to target pressure and the gas leakage rate, take the deviation and deviation change rate of the predicted normalized pressure and the pressure control set point and the equipment load current as input, self-adaptively adjust the parameters of a controller on line through a fuzzy reasoning mechanism and calculate a first control quantity, calculate a feedforward compensation control quantity based on the gas leakage rate and combining feedforward control gain, superimpose and limit the first control quantity and the feedforward compensation control quantity to generate a total control quantity, convert the total control quantity into corresponding control signals and send the corresponding control signals to an execution unit so as to realize accurate and continuous adjustment of the proportion of the air make-up flow and the mixed gas.
  9. 9. An electronic device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements a GIS mixed gas make-up adaptive control method according to any one of claims 1-7 when executing the computer program.
  10. 10. A computer-readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements a GIS mixed gas make-up adaptive control method according to any one of claims 1-7.

Description

GIS mixed gas air supplementing self-adaptive control method, system, equipment and medium Technical Field The application relates to the technical field of GIS (gas insulated switchgear) gas-supplementing control, in particular to a GIS mixed gas-supplementing self-adaptive control method, a system, equipment and a medium. Background Gas Insulated Switchgear (GIS) using mixed gas such as SF 6/N2 as an insulation and arc extinguishing medium are increasingly being used in power systems. In the processes of GIS production, installation and debugging, actual operation and the like, hidden dangers of defects such as sand holes, poor sealing piece quality, improper field installation sealing surface treatment, aging of sealing materials after long-term operation and the like of the shell can cause leakage of a GIS air chamber, pressure reduction of the air chamber and abnormal gas pressure. If the device is not handled in time, the continuous pressure reduction can cause the rapid reduction of the arc extinguishing capability of the device, and breakdown accidents are extremely easy to be caused to cause power failure accidents. Therefore, the air chamber is required to be electrified and supplemented with air by adopting an air supplementing device, and leakage supplementing measures are required. However, the existing air supplementing technology has the following limitations: (1) Hysteresis, early warning and intervention cannot be carried out in the early stage of slow leakage or slight imbalance of proportion of gas pressure, and potential safety hazard is large; (2) The accuracy is insufficient, a part of automatic air supplementing device adopts a simple control logic of 'low pressure threshold starting and high pressure threshold stopping', the total amount of the supplemented air and the mixing proportion of each component are difficult to accurately control by manual air supplementing or the control of a switch, the proportion of the air after air supplementing can deviate from an optimal design value (such as SF 6 is reduced), and the insulation and arc extinguishing performance of equipment are directly affected; (3) Most of the existing schemes only depend on a single absolute pressure signal, the complex influence of operating state variables such as temperature, load current and the like on gas density and pressure is not comprehensively considered, and the optimal control decision based on the real operating conditions (such as high-load heating) of equipment cannot be realized; (4) Existing automatic control logic (e.g., fixed parameter PID or switch control) cannot adaptively adjust the control strategy based on dynamic changes in leak rate, diurnal seasonal fluctuations in ambient temperature, and changes in device load current. When the working conditions are changed, the problems of control oscillation, excessive air supplement, slow response and the like are easy to occur. Disclosure of Invention In order to overcome the defects of the existing air-supplementing control technology, the application provides a GIS mixed gas air-supplementing self-adaptive control method, a system, equipment and a medium, which can realize early warning, accurate proportioning and smooth air-supplementing through multi-source data fusion sensing, leakage trend prediction and a self-adaptive composite control algorithm under the GIS electrified running state. The application is realized by the following technical scheme: a GIS mixed gas supplementing self-adaptive control method comprises the following steps: Synchronously acquiring multi-source sensing data of a GIS air chamber and preprocessing the multi-source sensing data, wherein the multi-source sensing data comprises gas pressure, gas temperature, mixed gas proportion and equipment load current; Based on a gas state equation, performing compensation calculation on the gas pressure by using the gas temperature to obtain normalized pressure at a standard temperature; Calculating a future pressure change trend through a time prediction model based on historical normalized pressure time sequence data, and estimating a gas leakage rate; Carrying out grading early warning based on the predicted normalized pressure and the gas leakage rate, wherein when the predicted normalized pressure and the gas leakage rate are both in a normal range or the deviation value from the normal range is smaller than a threshold value, continuing to execute the subsequent steps; dynamically generating a pressure control setpoint based on a target pressure and the gas leak rate; taking the deviation and deviation change rate of the predicted normalized pressure and the pressure control set point and the equipment load current as inputs, adaptively adjusting the parameters of a controller on line through a fuzzy reasoning mechanism, and calculating to obtain a first control quantity; Based on the gas leakage rate, combining feedforward control gain, and calculating to obtain feedfo