CN-121676884-B - Self-adaptive adjustment method and system for biomass gas grid-connected conveying

CN121676884BCN 121676884 BCN121676884 BCN 121676884BCN-121676884-B

Abstract

The application discloses a self-adaptive adjustment method and a self-adaptive adjustment system for biomass gas grid-connected delivery, which relate to the technical field of biomass gas, and comprise the steps of generating a quality qualified mark based on scheduling instruction data and quality data of the biomass gas, dynamically adjusting the flow rate of the biomass gas by using a self-adaptive control algorithm, and collecting flow data after adjustment; the method comprises the steps of analyzing whether fuel gas data is abnormal, generating an abnormal mark, detecting and analyzing the pressure data corresponding to the pressure regulating component based on the pressure abnormal mark, and performing corresponding safety control, solving the problem of limitation in the current self-adaptive regulation process of biomass fuel gas grid-connected transmission, detecting a regulating valve based on the abnormal mark, acquiring the data of the regulating valve, calculating to obtain the comprehensive evaluation coefficient of the regulating valve, and simultaneously performing early warning prompt, thereby realizing the feasibility, comprehensiveness and objectivity analysis of the self-adaptive regulation of biomass fuel gas grid-connected transmission.

Inventors

HAO GUANG
WANG GUOHUI
DENG JINYU
MENG NA

Assignees

沈阳城市学院

Dates

Publication Date: 20260512
Application Date: 20251218

Claims (6)

1. The self-adaptive adjustment method for biomass gas grid-connected conveying is characterized by comprising the following steps: Step 1, when a pipe network sends a scheduling instruction or detects a real-time demand signal, pre-acquiring scheduling instruction data, and simultaneously acquiring quality data of the biogas to generate a quality qualification mark; The quality data of the biogas comprises a methane purity value and a total sulfur content value; The generating the quality qualification flag includes: Comparing the methane purity value with a methane purity threshold value, and simultaneously comparing the total sulfur content value with a total sulfur content threshold value, wherein when the methane purity value is greater than or equal to the methane purity threshold value and the total sulfur content value is less than or equal to the total sulfur content threshold value, the quality is qualified, the quality qualified mark is marked as1, and otherwise, the quality is unqualified, and the quality qualified mark is marked as 0; step2, based on the quality qualification mark, dynamically adjusting the biomass gas flow by using a self-adaptive control algorithm, and collecting flow data after adjustment; step3, analyzing whether the fuel gas data is abnormal or not based on the pre-acquired fuel gas data, and generating an abnormal sign; The fuel gas data comprise gas quality fluctuation data, moisture and impurity data and pressure fluctuation data; The analyzing whether the fuel gas data is abnormal or not and generating an abnormal mark comprises the following steps: a1, respectively calculating a gas fluctuation deviation value, a water impurity deviation value and a pressure fluctuation deviation value based on pre-acquired gas fluctuation data, water and impurity data and pressure fluctuation data; A2, comparing the air quality fluctuation deviation value with a preset air quality fluctuation threshold, if the air quality fluctuation deviation value is greater than or equal to the air quality fluctuation threshold, generating an air quality abnormality mark as 1, otherwise, generating an air quality abnormality mark as 0, comparing the moisture impurity deviation value with the preset moisture impurity threshold, if the moisture impurity deviation value is greater than or equal to the moisture impurity threshold, generating a moisture impurity abnormality mark as 1, otherwise, generating a moisture impurity abnormality mark as 0, comparing the pressure fluctuation deviation value with the preset pressure fluctuation threshold, if the pressure fluctuation deviation value is greater than or equal to the pressure fluctuation threshold, generating a pressure abnormality mark as 1, and triggering to carry out step 4, otherwise, generating a pressure abnormality mark as 0; A3, when any one of the gas quality abnormality flag, the water impurity abnormality flag and the pressure abnormality flag is 1, generating an abnormality flag to be 1, otherwise, generating an abnormality flag to be 0; Step 4, detecting and analyzing pressure data corresponding to the pressure regulating component based on the pressure abnormality mark, and performing corresponding safety control; Step 5, detecting the regulating valve based on the abnormal mark, obtaining regulating valve data, and calculating to obtain a comprehensive evaluation coefficient of the regulating valve; And 6, carrying out early warning prompt based on the comprehensive evaluation coefficient of the regulating valve.
2. The method for adaptively adjusting the grid-connected delivery of the biomass gas according to claim 1, wherein the applying the adaptive control algorithm to dynamically adjust the flow rate of the biomass gas and collecting the flow rate data after adjustment comprises: The method comprises the steps of determining a gain parameter set of an adaptive control algorithm based on the quality qualified mark, wherein the gain parameter set comprises a proportional gain, an integral gain and a differential gain, calculating an adjusting signal of the biomass gas flow by applying the adaptive control algorithm, generating the adjusting signal by the adaptive control algorithm based on real-time flow data, target flow data and the gain parameter set, dynamically adjusting the biomass gas flow by using the adjusting signal, and collecting the flow data after adjustment.
3. The self-adaptive adjustment method for biomass gas grid-connected delivery according to claim 1, wherein the detecting and analyzing the pressure data corresponding to the pressure adjusting component and the corresponding safety control based on the pressure abnormality mark comprise: When the pressure abnormality mark is1, acquiring real-time pressure data of the pressure regulating component through a pre-deployed pressure sensor, calculating a pressure evaluation coefficient of the pressure regulating component, comparing the pressure evaluation coefficient of the pressure regulating component with a corresponding preset pressure evaluation threshold value to generate an operation judgment result, and generating a corresponding operation instruction based on the operation judgment result, so as to execute the operation instruction to perform safety control.
4. The method for adaptively adjusting the grid-connected delivery of biomass gas according to claim 3, wherein the detecting the adjusting valve based on the abnormality flag to obtain the adjusting valve data comprises: When the abnormality mark is 1, detecting the regulating valve to obtain regulating valve data, wherein the regulating valve data comprises response speed, abrasion condition, front-back pressure difference, valve internal part condition and valve back discharge flow rate, and calculating the comprehensive evaluation coefficient of the regulating valve based on the regulating valve data.
5. The method for adaptively adjusting the grid-connected delivery of biomass gas according to claim 4, wherein the step of calculating the comprehensive evaluation coefficient of the regulating valve based on the data of the regulating valve comprises the steps of: And carrying out weighted summation on the response speed evaluation coefficient, the wear condition evaluation coefficient, the front-back pressure difference evaluation coefficient, the valve trim condition evaluation coefficient and the valve post-discharge flow evaluation coefficient, and taking the calculation result as a regulating valve comprehensive evaluation coefficient.
6. A conditioning system for performing the biomass gas grid-tie delivery adaptive conditioning method of any of claims 1-5, comprising: the quality qualification mark generation module is used for pre-acquiring scheduling instruction data and simultaneously acquiring quality data of the biogas when the pipe network sends scheduling instructions or detects real-time demand signals, so as to generate a quality qualification mark; The flow data acquisition module is used for dynamically adjusting the biomass gas flow by applying a self-adaptive control algorithm based on the quality qualification mark and acquiring adjusted flow data; The abnormal mark generation module is used for analyzing whether the fuel gas data is abnormal or not based on the pre-acquired fuel gas data and generating an abnormal mark; the safety control module is used for detecting and analyzing the pressure data corresponding to the pressure regulating component based on the pressure abnormality mark and performing corresponding safety control; The regulating valve detection module is used for detecting the regulating valve based on the abnormal mark, acquiring regulating valve data and calculating to obtain a comprehensive evaluation coefficient of the regulating valve; and the early warning terminal carries out early warning prompt based on the comprehensive evaluation coefficient of the regulating valve.

Description

Self-adaptive adjustment method and system for biomass gas grid-connected conveying Technical Field The application relates to the technical field of biomass gas, in particular to a self-adaptive adjustment method and system for biomass gas grid-connected conveying. Background Along with the development of technology, the importance of self-adaptive regulation in the process of biomass gas grid-connected transportation is increasingly highlighted. Traditional conveying mode relies on manual inspection and adjustment, and is low in efficiency and lag in response. The biomass gasification fuel gas conveying system comprises a biomass gasification furnace, a cooling device, a water cooling circulation mechanism, a guide waste discharge barrel cleaning mechanism, a tar dust removing mechanism, an ammonia water supplementing mechanism and a monitoring and purifying mechanism, wherein the cooling device is arranged on a gas output pipeline of the biomass gasification furnace, the water cooling circulation mechanism is connected with the cooling device, the guide waste discharge barrel is connected with an output pipeline of the biomass gasification furnace, the waste discharge barrel cleaning mechanism is arranged on the outer wall of the guide waste discharge barrel, the tar dust removing mechanism is arranged above the guide waste discharge barrel, the ammonia water supplementing mechanism is connected with an input pipeline of the waste discharge barrel cleaning mechanism through the water cooling circulation mechanism, and the monitoring and purifying mechanism is arranged on an output end of the tar dust removing mechanism. Aiming at the scheme, the inventor of the application discovers that the technology at least has the following technical problems that 1, when a pipe network sends a scheduling instruction or detects a real-time demand signal, scheduling instruction data is not obtained at present, meanwhile, quality data of biological fuel gas is obtained, so that a quality qualified mark cannot be generated, parallel threshold comparison is not carried out by adopting an embedded comparator hardware unit, response lag caused by software delay cannot be avoided, instant response of quality detection cannot be ensured, and a foundation is provided for subsequent flow regulation by pre-obtaining the scheduling instruction and the quality data, so that the risk of pipe network corrosion or insufficient heat value caused by unqualified fuel gas cannot be reduced. 2. The method comprises the steps of determining a gain parameter set dynamically based on a quality qualified mark, realizing real-time generation of an adjusting signal, optimizing flow adjusting precision through dynamic gain adjustment, improving system stability, analyzing gas fluctuation, moisture impurity and pressure fluctuation, comparing the gas fluctuation, the moisture impurity and the pressure fluctuation with a preset threshold value to generate an abnormal mark, comprehensively monitoring gas quality, realizing early warning, executing real-time calculation through an embedded processor by a pressure evaluation algorithm, generating an operating instruction, executing safety control automatically, and forming closed-loop control. 3. The current state of health of the valve is not quantitatively regulated, predictive maintenance cannot be realized, and information such as response speed, abrasion condition, front-back pressure difference, valve trim condition, valve rear discharge flow and the like is not integrated with multi-sensor data. Disclosure of Invention Aiming at the technical defects, the application aims to provide a biomass gas grid-connected conveying self-adaptive adjusting method and system. In order to solve the technical problems, the application adopts the following technical scheme that the application provides a self-adaptive adjustment method for biomass gas grid-connected conveying in the first aspect. And 2, dynamically adjusting the biomass gas flow by using a self-adaptive control algorithm based on the quality qualification mark, and collecting flow data after adjustment. And step3, analyzing whether the fuel gas data is abnormal or not based on the pre-acquired fuel gas data, and generating an abnormality mark. And 4, detecting and analyzing pressure data corresponding to the pressure regulating component based on the pressure abnormality mark, and performing corresponding safety control. And 5, detecting the regulating valve based on the abnormal mark, acquiring data of the regulating valve, and calculating to obtain a comprehensive evaluation coefficient of the regulating valve. And 6, carrying out early warning prompt based on the comprehensive evaluation coefficient of the regulating valve. Preferably, the quality data of the biogas includes a methane purity value and a total sulfur content value. Preferably, the generation of the quality qualified mark comprises the steps of comparing a methane purity v