Rapid fault positioning method for compressed air energy storage device of aquifer

Abstract

The invention discloses a rapid fault positioning method for a compressed air energy storage device of an aquifer. Relates to the technical field of aquifer compressed air energy storage, and comprises the following steps: 1, monitoring data acquisition: in the operation process of an energy storage device, continuously acquiring underground pressure, temperature and air flow data, and comparing the data change with a preset threshold value; 2, a fault analysis model: when any monitoring parameter abnormally fluctuates, performing fault probability analysis in combination with environmental data and a gas flow simulation model; and step 3, fault positioning: simulating an air diffusion condition near a fault point based on a hydrodynamic force-gas flow model, and positioning a possible fault point position by comparing observation data with a model calculation result. According to the method disclosed by the invention, the fault diagnosis efficiency of the aquifer compressed air energy storage system is effectively improved, the problems that a traditional method is inaccurate in fault positioning and relatively slow in response speed are solved, and the safety and the stability of an energy storage device are favorably improved.

Description

Technical Field

[0001] The invention relates to the technical field of compressed air energy storage in aquifers, and more particularly to a method for quickly locating faults of compressed air energy storage devices in aquifers. Background Art

[0002] At present, the intermittent supply of renewable energy poses a great challenge to the stability of the power grid. The inherent limitations of renewable energy highlight the urgent need for large-scale energy storage systems around the world. At present, only pumped storage and compressed air storage can provide low-cost, stable, long-term energy storage. However, due to the geographical limitations of pumped storage and the low energy storage efficiency and heat recovery pollution problems of traditional compressed air storage, groundwater aquifer compressed air energy storage has become a trend in the future. Failures in groundwater aquifer compressed air storage systems will reduce energy storage efficiency. If the failures are not resolved in a timely manner, the service life of the equipment will be shortened, the operating and maintenance costs will increase, and even groundwater pollution will occur.

[0003] However, there is no systematic fault analysis and positioning method for groundwater aquifer compressed air energy storage devices in the prior art, and the positioning speed is slow and there is also the problem of low positioning accuracy.

[0004] Therefore, how to provide a method for quickly locating faults in an aquifer compressed air energy storage device that can monitor data in real time, locate faults more quickly and accurately, and continuously optimize the model is an issue that technicians in this field urgently need to solve. Summary of the invention

[0005] In view of this, the present invention provides a method for quickly locating faults in an aquifer compressed air energy storage device, aiming to solve one of the problems in the above-mentioned background technology. It comprehensively applies multiple technologies such as data analysis and model simulation, and can monitor data in real time, locate faults more quickly and accurately, and continuously optimize the model.

[0006] In order to achieve the above object, the present invention adopts the following technical solution:

[0007] A method for quickly locating faults of an aquifer compressed air energy storage device, comprising:

[0008] Step 1: Monitoring data collection: During the operation of the energy storage device, the downhole pressure, temperature, and air flow data are continuously collected, and the data changes are compared with the preset thresholds;

[0009] Step 2: Fault analysis model. When any monitoring parameter fluctuates abnormally, the fault probability analysis is performed by combining environmental data with the gas flow simulation model to determine whether there is air leakage or water cone phenomenon. If the probability of abnormal fluctuation is greater than the preset threshold, there may be a system failure.

[0010] Step 3: Fault location. Based on the hydrodynamic-gas flow model, simulate the air diffusion near the fault point, and compare the observed data with the model calculation results to locate the possible fault point. By adjusting the monitoring and control parameters, verify and optimize the accuracy of the fault diagnosis model.

[0011] Furthermore, the specific process of collecting monitoring data includes: continuously collecting downhole pressure, temperature, and air flow data through sensors in the energy storage device and recording their changes, comparing them with preset thresholds, and performing fault probability analysis if they exceed the preset thresholds.

[0012] Furthermore, the specific process of failure probability analysis includes:

[0013] For abnormal data, analyze the changes in the abnormal data and conduct fault probability analysis by combining environmental data with the gas flow simulation model;

[0014] If the failure probability is less than the preset abnormal fluctuation probability, the failure probability analysis ends.

[0015] Furthermore, the specific process of failure probability analysis also includes:

[0016] If the fault probability is greater than the preset threshold, there may be a system fault, and the fault is located;

[0017] The abnormal data fluctuations are compared, and the midpoint of the abnormal data set is extracted and set as the suspected fault point. Based on the hydrodynamic-gas flow model, the air diffusion near the suspected fault point is simulated. The pressure, temperature, and air flow data obtained by the model simulation are compared with the observed data to determine the location of the fault point.

[0018] Furthermore, the accuracy of the fault diagnosis model is verified and optimized by adjusting the monitoring and control parameters.

[0019] Furthermore, the sensors are arranged in a zoned distribution to collect temperature and air flow parameters at the compressor, turbine and thermal management system, pressure and air flow parameters at the injection well and each pipeline, and water quality parameters at the aquifer.

[0020] Furthermore, the threshold setting is optimized and adjusted according to the fault diagnosis model.

[0021] It can be seen from the above technical solutions that, compared with the prior art, the present invention discloses a method for quickly locating faults in an aquifer compressed air energy storage device. By detecting various data and analyzing them in combination with a model, the fault can be located more quickly and accurately, and can be inspected according to parameters. When an abnormality occurs in the monitoring data in the device, the data can be quickly processed to obtain the fault probability, and then the fault can be accurately located through computational simulation, which is convenient for subsequent troubleshooting and maintenance of device operation. The method provided by the present invention comprehensively applies data analysis and model simulation. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0023] Figure 1 This is an overall flow chart of the method for quickly locating faults in an aquifer compressed air energy storage device provided by the present invention. DETAILED DESCRIPTION

[0024] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0025] See also Figure 1 The embodiment of the present invention discloses a method for quickly locating a fault of an aquifer compressed air energy storage device, comprising the following steps:

[0026] Step 1: Monitoring data collection: During the operation of the energy storage device, the downhole pressure, temperature, and air flow data are continuously collected, and the data changes are compared with the preset thresholds;

[0027] Step 2: Fault analysis model. When any monitoring parameter fluctuates abnormally, the fault probability analysis is performed by combining environmental data with the gas flow simulation model to determine whether there is air leakage or water cone phenomenon. If the probability of abnormal fluctuation is greater than the preset threshold, there may be a system failure.

[0028] Step 3: Fault location. Based on the hydrodynamic-gas flow model, simulate the air diffusion near the fault point, and compare the observed data with the model calculation results to locate the possible fault point. By adjusting the monitoring and control parameters, verify and optimize the accuracy of the fault diagnosis model.

[0029] In this embodiment, the specific process of collecting monitoring data includes: continuously collecting downhole pressure, temperature, and air flow data through sensors in the energy storage device and recording their changes, comparing them with preset thresholds, and performing fault probability analysis if they exceed the preset thresholds; by detecting various data and analyzing them in combination with the model, faults can be located more quickly and accurately, and tests can be performed based on parameters.

[0030] In this embodiment, the specific process of analyzing the failure probability includes:

[0031] For abnormal data, analyze the changes in the abnormal data and conduct fault probability analysis by combining environmental data with the gas flow simulation model;

[0032] If the failure probability is less than the preset abnormal fluctuation probability, the failure probability analysis ends;

[0033] In this embodiment, the specific process of analyzing the failure probability further includes:

[0034] If the fault probability is greater than the preset threshold, there may be a system fault, and the fault is located;

[0035] The abnormal data fluctuations are compared, and the center point of the abnormal data set is extracted and set as the suspected fault point. Based on the hydrodynamic-gas flow model, the air diffusion near the suspected fault point is simulated, and the pressure, temperature, and air flow data obtained by the model simulation are compared with the observed data to determine the location of the fault point. When the monitoring data in the device is abnormal, the data can be processed quickly to obtain the fault probability, and then the fault can be accurately located through computational simulation, which is convenient for subsequent troubleshooting and maintenance of device operation.

[0036] In this embodiment, the accuracy of the fault diagnosis model is verified and optimized by adjusting the monitoring and control parameters.

[0037] In this embodiment, the sensors are arranged in a zoned distribution to collect temperature and air flow parameters at the compressor, turbine and thermal management system, pressure and air flow parameters at the injection well and each pipeline, and water quality parameters at the aquifer.

[0038] In this embodiment, the threshold setting is optimized and adjusted according to the fault diagnosis model.

[0039] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0040] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for quickly locating faults in an aquifer compressed air energy storage device, characterized in that: The following steps are involved: Step 1: Monitoring data collection: During the operation of the energy storage device, the downhole pressure, temperature, and air flow data are continuously collected, and the data changes are compared with the preset thresholds; Step 2: Fault analysis model. When any monitoring parameter fluctuates abnormally, the fault probability analysis is performed by combining environmental data with the gas flow simulation model to determine whether there is air leakage or water cone phenomenon. If the probability of abnormal fluctuation is greater than the preset threshold, there may be a system failure. Step 3: Fault location. Based on the hydrodynamic-gas flow model, simulate the air diffusion near the fault point, and compare the observed data with the model calculation results to locate the possible fault point. By adjusting the monitoring and control parameters, verify and optimize the accuracy of the fault diagnosis model.

2. A method for quickly locating faults of an aquifer compressed air energy storage device according to claim 1, characterized in that: The specific process of collecting monitoring data includes: continuously collecting downhole pressure, temperature, and air flow data through sensors in the energy storage device and recording their changes, comparing them with preset thresholds, and performing fault probability analysis if they exceed the preset thresholds.

3. A method for quickly locating faults of an aquifer compressed air energy storage device according to claim 1, characterized in that: The specific process of failure probability analysis includes: For abnormal data, analyze the changes in the abnormal data and conduct fault probability analysis by combining environmental data with the gas flow simulation model; If the failure probability is less than the preset abnormal fluctuation probability, the failure probability analysis ends.

4. A method for quickly locating faults of an aquifer compressed air energy storage device according to claim 1, characterized in that: The specific process of failure probability analysis also includes: If the fault probability is greater than the preset threshold, there may be a system fault, and the fault is located; The abnormal data fluctuations are compared, and the midpoint of the abnormal data set is extracted and set as the suspected fault point. Based on the hydrodynamic-gas flow model, the air diffusion near the suspected fault point is simulated. The pressure, temperature, and air flow data obtained by the model simulation are compared with the observed data to determine the location of the fault point.

5. A method for quickly locating faults of an aquifer compressed air energy storage device according to claim 1, characterized in that: The accuracy of the fault diagnosis model is verified and optimized by adjusting the monitoring and control parameters.

6. A method for quickly locating faults of an aquifer compressed air energy storage device according to claim 1, characterized in that: The sensors are set up in a zoned distribution to collect temperature and air flow parameters at the compressor, turbine and thermal management system, pressure and air flow parameters at the injection well and each pipeline, and water quality parameters in the aquifer.

7. A method for quickly locating faults of an aquifer compressed air energy storage device according to claim 1, characterized in that: The threshold setting is optimized and adjusted according to the fault diagnosis model.

Images