CN117521436A - Dynamic risk assessment method and system for gas gathering station - Google Patents
Dynamic risk assessment method and system for gas gathering station Download PDFInfo
- Publication number
- CN117521436A CN117521436A CN202210910152.XA CN202210910152A CN117521436A CN 117521436 A CN117521436 A CN 117521436A CN 202210910152 A CN202210910152 A CN 202210910152A CN 117521436 A CN117521436 A CN 117521436A
- Authority
- CN
- China
- Prior art keywords
- risk
- gas gathering
- gathering station
- dangerous
- deviation
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
- G06F30/23—Design optimisation, verification or simulation using finite element methods [FEM] or finite difference methods [FDM]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0635—Risk analysis of enterprise or organisation activities
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/02—Reliability analysis or reliability optimisation; Failure analysis, e.g. worst case scenario performance, failure mode and effects analysis [FMEA]
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Human Resources & Organizations (AREA)
- Strategic Management (AREA)
- Entrepreneurship & Innovation (AREA)
- Economics (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Educational Administration (AREA)
- General Physics & Mathematics (AREA)
- Development Economics (AREA)
- Operations Research (AREA)
- General Business, Economics & Management (AREA)
- Tourism & Hospitality (AREA)
- Game Theory and Decision Science (AREA)
- Quality & Reliability (AREA)
- Marketing (AREA)
- Geometry (AREA)
- Computer Hardware Design (AREA)
- Evolutionary Computation (AREA)
- General Engineering & Computer Science (AREA)
- Testing And Monitoring For Control Systems (AREA)
Abstract
The invention discloses a dynamic risk assessment method and a system for a gas gathering station, which can realize the dynamic risk assessment of the gas gathering station, enrich quantitative risk rating, have high safety and reliability, improve the working efficiency of solving accident risks and provide guidance comments for accident prevention. The method comprises the steps of collecting data information of a gas collecting station, and dividing nodes of the gas collecting station according to a process flow; analyzing the technological parameter deviation generated by each node, and identifying the risk scene of each node of the gas gathering station according to the data information and the technological parameter deviation; establishing a process steady-state model of the gas gathering station, and performing process simulation on the identified risk scene; changing process parameters of process simulation to obtain simulation operation results with different deviation degree deviations, and determining dangerous peaks of the process parameters; and dividing the process parameter deviation into intervals according to the condition that the process parameter reaches a dangerous peak value, and judging the risk level of the risk scene of each node according to the number of the dangerous factors in the intervals so as to realize the dynamic risk assessment of the gas gathering station.
Description
Technical Field
The invention relates to the technical field of gas gathering station risk assessment, in particular to a dynamic risk assessment method and a system for a gas gathering station.
Background
Safety instruments (such as sensors, transmitters and the like) are selected based on the normal process flow of the gas gathering station, and the optimal use range of the safety instruments is generally 1/3-2/3 of the range of the safety instruments, because the linearity and repeatability of the safety instruments are best when the use range is larger than 1/3, the relative error is minimum, and the accuracy is high; however, if the device is used for a long time in excess of 2/3 of the measuring range, the measuring function of the internal element can be reduced, so that the zero drift and the change of the measuring range of the instrument are caused, the ageing of the element is accelerated, and the service life is reduced.
When a blowout accident occurs in the high Wen Jingqun gas collecting station, emergency process change is sometimes needed to avoid that blowout gas enters the environment, namely, the blowout well natural gas is connected into an adjacent collecting and conveying system to be collected by virtue of adjacent pipelines and process equipment, and the temperature of the raw gas entering the station in part of the process flow exceeds the original design operation temperature range, for example (the original design temperature range is 10-45 ℃, but the temporary process change causes the process instrument to suddenly experience an abnormal high-temperature working condition close to 75 ℃), so that the instrument does not operate in the designed use range. Engineering cases show that the longer the instrument works in a non-design temperature range, the lower the precision and stability; the higher the temperature exceeds the design use range, the greater the magnitude of the degradation in accuracy and stability. Finally, the problems of instrument indication deviation, fault alarm or false alarm are caused, so that personnel emergency response is not timely, and the risk of continuing production of the gas gathering station is faced with larger uncertainty.
It can be known from the existing literature and practical cases that at present, the influence of the environmental temperature factors on the measurement uncertainty of the instrument is mainly considered in the research of the reliability of the instrument in China, and the research of the influence of the medium overtemperature on the measurement accuracy of the instrument is lacking. The risk assessment method at the present stage mainly aims at obtaining the possibility and the consequence severity of the accident by using the existing risk assessment method, so as to establish a risk assessment model to obtain an assessment result, wherein the risk assessment of the gas gathering station mainly adopts the traditional HAZOP method to search the deviation possibly occurring in the process, and then uses a risk matrix to determine the risk level of the risk scene. However, the method has certain subjectivity, deviation ambiguity and statics, and the analysis result has the defects of no division of primary and secondary, and the like, and no accurate and reliable method for analyzing the reliability of the instrument of the gas gathering station and evaluating the dynamic risk under sudden high-temperature fluctuation exists at present.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides the dynamic risk assessment method and the system for the gas gathering station, which can realize the dynamic assessment of the gas gathering station, enrich the quantitative rating of risks, have high safety and reliability, improve the working efficiency of solving the accident risk and provide guidance for accident prevention.
In order to achieve the above purpose, the present invention provides the following technical solutions:
a method for dynamic risk assessment of a gas gathering station, comprising the steps of:
collecting data information of the gas collecting station, and dividing nodes of the gas collecting station according to a process flow;
analyzing the technological parameter deviation generated by each node, and identifying the risk scene of each node of the gas gathering station according to the data information and the technological parameter deviation;
establishing a process steady-state model of the gas gathering station, and performing process simulation on the identified risk scene;
changing process parameters of process simulation to obtain simulation operation results with different deviation degree deviations, and determining dangerous peaks of the process parameters;
dividing the process parameter deviation into intervals according to the condition that the process parameter reaches a dangerous peak value, and judging risk levels of risk scenes of all nodes according to the number of dangerous factors in the intervals to realize dynamic risk assessment of the gas gathering station, wherein the number of dangerous factors represents the number of dangerous peak values reached by the process parameter in each working condition operation.
Preferably, the data information of the gas gathering station comprises material information, process operation condition information, equipment size information and site information of the gas gathering station.
Preferably, analyzing the deviation of the process parameter generated by each node, and identifying the risk scenario of each node of the gas gathering station according to the data information and the deviation of the process parameter includes:
according to the data information, analyzing the technological parameter deviation of each node of the gas gathering station by using a HAZOP method, wherein the technological parameter deviation comprises the generation reason and the caused result of the deviation;
grading the severity of the consequences caused by the deviation by using a risk matrix method;
and identifying the risk scene of each node of the gas gathering station according to the grading condition, and completing the primary judgment of the risk grade.
Preferably, analyzing the process parameter deviation generated by each node, identifying the risk scene of each node of the gas gathering station according to the data information and the process parameter deviation, and performing reliability analysis on the safety instrument in the identified risk scene of the high-temperature working condition of the gas gathering station, wherein the method specifically comprises the following steps:
obtaining the maximum applicable temperature T of the safety instrument 0 Measuring the temperature value of the over-temperature medium, and establishing a mathematical model of the reliability of the instrument;
inputting multiple groups of measurement data by using a mathematical model of instrument reliability, solving and obtaining maximum error delta of instrument indication value under high-temperature working condition max ；
Maximum error delta of indicating value of comparison instrument max And instrument tolerance error delta x Judging the reliability of the safety instrument:
if it isThe reliability of the safety instrument meets the requirement, the safety instrument is continuously used, and the indicating value of the safety instrument is corrected according to the error value;
otherwise, the reliability of the safety instrument does not meet the requirement, and the safety instrument is replaced.
Preferably, the expression of the instrument reliability mathematical model is:
in which delta is the measured medium temperature of the meter exceedsThe error of the indication value; i g Indicating values for the high-temperature instrument; i s Is a standard indication value; delta is zero drift and time drift of the high-temperature instrument; c is a temperature influence coefficient; t is any temperature value of the super-temperature medium.
Preferably, the process parameter of the process simulation is changed to obtain simulation operation results of deviations of different deviation degrees, and determining the dangerous peak value of the process parameter includes:
and adding a flow regulation controller and a liquid level regulation controller on the basis of steady state operation of the process, obtaining simulation operation results with different deviation degree deviations by changing process parameter conditions of process simulation, converting a steady state process model into a dynamic process model, recording the change of each process parameter, determining boundary conditions of each process parameter, and obtaining dangerous peaks of each process parameter.
Preferably, the process parameters include temperature, pressure and liquid level.
Preferably, after the risk level re-judging is performed on the risk scene of each node according to the number of risk factors in the interval, the method further includes determining a risk transfer path, and specifically includes the following steps:
setting process simulation time in Aspen HYSYS simulation software, carrying out data acquisition on process parameters according to set time intervals, and assembling data acquisition results into a table;
determining the time required by each process parameter to reach a dangerous peak value according to the form analysis, and comparing the time values;
and (3) arranging the sequence of reaching the dangerous peak value of each process parameter according to the comparison result, and taking the sequence as a risk transmission path in the risk scene.
Preferably, the process parameter deviation is divided into intervals according to the condition that the process parameter reaches a dangerous peak value, and the process parameter deviation is divided into intervals according to the condition that the safety instrument in the gas collecting station initially alarms.
A dynamic risk assessment system for a gas gathering station, comprising:
the data acquisition processing unit is used for acquiring data information of the gas gathering station and dividing nodes of the gas gathering station according to the process flow;
the risk level primary judging unit is used for analyzing the technological parameter deviation generated by each node and identifying the risk scene of each node of the gas gathering station according to the data information and the technological parameter deviation;
the process simulation unit is used for constructing a process steady-state model of the gas gathering station by adopting Aspen HYSYS simulation software and performing process simulation on the identified risk scene;
the dangerous peak value acquisition unit is used for changing process parameters of process simulation to acquire simulation operation results with different deviation degree deviations, and determining dangerous peak values of the process parameters;
the risk level secondary judging unit is used for dividing the process parameter deviation into intervals according to the condition that the process parameter reaches the dangerous peak value, judging the risk level again for the risk scene of each node according to the number of the dangerous factors in the intervals, and realizing the dynamic risk assessment of the gas gathering station, wherein the number of the dangerous factors represents the number of the dangerous peak value reached by the process parameter during the operation of each working condition.
Compared with the prior art, the invention has the following beneficial effects:
the invention provides a dynamic risk assessment method of a gas gathering station, which takes the gas gathering station with sudden high-temperature fluctuation as an object, identifies a risk scene existing in the gas gathering station under sudden high-temperature fluctuation by utilizing a traditional HAZOP method, establishes a mathematical model by combining Aspen HYSYS simulation software, and carries out preliminary judgment on the risk level of the high-temperature risk scene of the gas gathering station. Based on the traditional gas station risk assessment method, the quantification of deviation degree of technological parameter deviation in each risk scene is realized by utilizing Aspen HYSYS, and the risk level of the same deviation and different deviation degrees is judged again and secondarily by introducing a risk factor concept, so that the quantitative rating of risks in HAZOP analysis is enriched, the risk assessment is dynamic, the working efficiency of solving dangerous events is improved, the safety and reliability are high, and guidance comments are provided for accident prevention.
Drawings
FIG. 1 is a flow chart of the steps of the dynamic risk assessment method of the present invention;
FIG. 2 is a flow chart of a method embodying the present invention;
FIG. 3 is a graph showing a trend of the medium temperature measured by the safety instrument under abnormal high temperature conditions according to an embodiment of the present invention.
Detailed Description
The principles and features of the present invention are described in further detail below with reference to the attached drawings, and the examples are provided for the purpose of illustrating the invention and are not to be construed as limiting the scope of the invention. It should be noted that the drawings are in a very simplified form and are all to a non-precise scale, merely for convenience and clarity in aiding in the description of embodiments of the invention.
It will be understood that when an element is referred to as being "fixed to" another element, it can be directly on the other element or intervening elements may also be present. When a component is considered to be "connected" to another component, it can be directly connected to the other component or intervening components may also be present. When an element is referred to as being "disposed on" another element, it can be directly on the other element or intervening elements may also be present.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and/or" as used herein includes any and all combinations of one or more of the associated listed items.
The invention provides a dynamic risk assessment method of a gas gathering station, which is shown in fig. 1 and comprises the following steps:
collecting data information of the gas collecting station, and dividing nodes of the gas collecting station according to a process flow;
based on the HAZOP method, analyzing the technological parameter deviation generated by each node, and identifying the risk scene of each node of the gas gathering station according to the data information and the technological parameter deviation;
adopting Aspen HYSYS simulation software to construct a process steady-state model of the gas gathering station, and performing process simulation on the identified risk scene;
changing process parameters of process simulation to obtain simulation operation results with different deviation degree deviations, and determining dangerous peaks of the process parameters;
dividing the process parameter deviation into intervals according to the condition that the process parameter reaches a dangerous peak value, and judging risk levels of risk scenes of all nodes according to the number of dangerous factors in the intervals to realize dynamic risk assessment of the gas gathering station, wherein the number of dangerous factors represents the number of dangerous peak values reached by the process parameter in each working condition operation.
The invention designs a dynamic risk assessment method of a gas collecting station, which takes the gas collecting station with sudden high-temperature fluctuation as an object, identifies a risk scene of the gas collecting station under sudden high-temperature fluctuation by utilizing a traditional HAZOP method, establishes a mathematical model by combining Aspen HYSYS simulation software, and carries out preliminary judgment on the risk level of the high-temperature risk scene of the gas collecting station. Based on the traditional gas station risk assessment method, the quantification of deviation degree of technological parameter deviation in each risk scene is realized by utilizing Aspen HYSYS, and the risk level of the same deviation and different deviation degrees is judged again and secondarily by introducing a risk factor concept, so that the quantitative rating of risks in HAZOP analysis is enriched, the risk assessment is dynamic, the working efficiency of solving dangerous events is improved, the safety and reliability are high, and guidance comments are provided for accident prevention.
The invention also provides a dynamic risk assessment system of the gas gathering station, which is used for realizing the dynamic risk assessment method of the invention, and comprises the following steps:
the data acquisition processing unit is used for acquiring data information of the gas gathering station and dividing nodes of the gas gathering station according to the process flow;
the risk level primary judging unit is used for analyzing the technological parameter deviation generated by each node based on the HAZOP method and identifying the risk scene of each node of the gas gathering station according to the data information and the technological parameter deviation;
the process simulation unit is used for constructing a process steady-state model of the gas gathering station by adopting Aspen HYSYS simulation software and performing process simulation on the identified risk scene;
the dangerous peak value acquisition unit is used for changing process parameters of process simulation to acquire simulation operation results with different deviation degree deviations, and determining dangerous peak values of the process parameters;
the risk level secondary judging unit is used for dividing the process parameter deviation into intervals according to the condition that the process parameter reaches the dangerous peak value, judging the risk level again for the risk scene of each node according to the number of the dangerous factors in the intervals, and realizing the dynamic risk assessment of the gas gathering station, wherein the number of the dangerous factors represents the number of the dangerous peak value reached by the process parameter during the operation of each working condition.
The method for evaluating the dynamic risk of the gas gathering station, as shown in fig. 2, comprises the following specific implementation steps:
(1) And (3) collecting data:
the collected data includes Process Flow Diagrams (PFD), piping and instrumentation (P & ID) diagrams, and the like. To achieve dynamic simulation of a process system, various process related parameters need to be known, including material information, process operating condition information, equipment size information, and the like. To realize the response analysis of the instrument system under the high-temperature working condition, the explanation of the control system of the gas collecting station device, the data of the monitoring instrument manufacturer and the like are required to be collected;
(2) High temperature condition risk analysis:
2.1 node division: the method comprises the steps of integrating material, equipment and facilities, process, operation and place information of a gas collecting station, determining abnormal high-temperature working conditions of the gas collecting station, and dividing nodes according to a process flow;
2.2 high temperature operating mode hazard analysis: and analyzing abnormal high-temperature working conditions of the gas gathering station by using the HAZOP method, analyzing all possible deviations generated by each node, the reasons and the consequences caused by the deviations, grading the severity of the consequences by using the traditional risk matrix method, and identifying a risk scene.
(3) Aspen HYSYS dynamic simulation
3.1 Aspen HYSYS steady state modeling: and establishing a steady-state simulation system of the process in Aspen HYSYS simulation software, and debugging. The process is enabled to run normally, and whether the process is stable and accurate is verified by comparing known related parameters.
3.2 Aspen HYSYS bias dynamic simulation: and adding a flow regulation and liquid level regulation controller on the basis of steady-state operation, determining boundary conditions of all parameters, converting a process model into a dynamic model, and performing process simulation on the identified risk scene. The influence of different deviation degree deviations in HAZOP analysis on the technological process is realized by continuously changing the technological conditions of process simulation, the simulation operation condition of safety measures in HAZOP analysis reports after implementation in dynamic simulation is simulated and verified, the change of parameters is recorded, and the dangerous peak value of each technological parameter is determined.
(4) Safety instrument reliability analysis
And identifying an affected instrument system in the high-temperature working condition risk scene, and judging the reliability of the instrument based on the high-temperature bearing temperature and the high-temperature running time of the instrument.
The variation trend of the medium temperature measured by the instrument under the abnormal high-temperature working condition is shown in fig. 3, and based on the variation trend, the following mathematical model is established for the reliability of the instrument aiming at the over-temperature running temperature:
in which delta is the measured medium temperature of the meter exceedsThe indication error is the same as the allowable error; i g Indicating values for the high-temperature instrument; i S Is a standard indication value; delta is zero drift and time drift of the high-temperature instrument; c is a temperature influence coefficient; t is any temperature value of the super-temperature medium; t (T) 0 The maximum applicable temperature of the instrument is set at DEG C; t (T) 1 The maximum temperature of the medium measured by the instrument is reached; the average temperature of the overtemperature medium measured by the instrument is +.>Duration Δt=t of high temperature condition 2 -t 1 。
The delta value and the c value can be obtained through multiple groups of measurement data, and finally the maximum error delta of the meter indication value under the high-temperature working condition is obtained max And compares it with the allowable error delta of the meter x By comparing, the reliability of the instrument is judged,
if it isThe reliability of the instrument meets the requirement, the instrument can be used continuously, the indicating value of the safety instrument can be corrected according to the error value, and the safety operation of the gas collecting station is ensured;
otherwise, the reliability of the instrument does not meet the requirement, and the instrument should be replaced in time.
For temperature process parameters, the following are exemplified:
under the premise that the safety instrument meets the reliability requirement, judging the risk level of the high-temperature working condition according to the overtemperature and the high-temperature duration:
simulating an average temperature working condition of abnormal high-temperature working conditions by utilizing Aspen HYSYS to obtain the time for each process parameter to reach a dangerous peak value, and selecting the longest time T for the process parameter to reach the dangerous peak value based on conservative analysis S Comparing with the duration deltat of the high-temperature working condition, judging the dangerous grade of the working condition, and judging the specific gradeThe breaking criteria are shown in table 1.
Table 1: high temperature condition risk level determination
(5) Risk assessment and classification
For other technological parameter deviations except for temperature, technological parameter variables, namely temperature, pressure and liquid level, involved in each node can be defined as factors for evaluating risk grades, and the number of dangerous factors corresponding to each working condition is defined as S, which means the number of dangerous peaks of the process when the parameter reaches the operation of the system under each working condition.
The method comprises the steps of simulating deviation results of different deviation degrees based on Aspen HYSYS, analyzing data of the deviation, dividing the deviation into sections according to the condition that technological parameters reach dangerous peak values, and carrying out risk level secondary judgment on dangerous working conditions of the same deviation and different deviation degrees according to the number of dangerous factors in the deviation sections, wherein risk level judgment standards are shown in a table 2, so that dynamic risk assessment of a process is realized, and reference is provided for a next proposed measure to be taken.
Table 2: risk level determination
By way of example, assuming that the node under analysis contains a total of n devices, each involving three process parameters of temperature, pressure, and level, the node has a total of 3n risk factors.
If the simulated abnormal high-temperature working condition contains two devices, and the number of dangerous factors in different valve opening intervals is as follows, the risk level can be secondarily judged according to the following table 3:
table 3: risk level determination based on risk factors
(6) Risk delivery path determination:
the Aspen HYSYS process simulation time is set, the process parameters are acquired according to a certain time interval, and the data acquisition results can be summarized into a table for facilitating analysis. And (3) according to data obtained by table analysis and simulation, determining the time required by each parameter to reach the dangerous peak value, comparing the time values, and summarizing the sequence of the parameter reaching the dangerous peak value, thus obtaining the risk transfer path in the dangerous scene.
(7) Emergency response
And identifying a risk transfer path of a certain risk scene and the time of the technological parameter reaching a dangerous peak under an abnormal working condition according to Aspen HYSYS dynamic risk assessment, and optimizing an emergency response flow. The reasons for the accident dangerous scene can be reversely deduced according to the risk transmission path, so that references are provided for accident prevention.
According to the invention, a traditional HAZOP method system is utilized to identify a risk scene existing in the gas gathering station under sudden high-temperature fluctuation, an instrument system existing in the risk scene is identified, the affected degree of the instrument under the high-temperature working condition is analyzed, the reliability of the safety instrument is evaluated, and the Aspen HYSYS simulation software is combined to judge the risk level of the high-temperature risk scene of the gas gathering station. In addition, aiming at other deviations except the temperature, the deviation can be divided into sections according to the simulation conditions of different deviation degrees, the condition that the technological parameters in each deviation section reach a dangerous peak value (or an initial alarm value of an instrument) is judged, and the risk level is re-judged; and determining a risk transfer path according to the time when each parameter reaches a dangerous peak value, and providing a reference for the safe operation of the gas collecting station under the sudden high-temperature fluctuation working condition.
The above description is only of the preferred embodiments of the present invention, and is not intended to limit the present invention in any way; those skilled in the art will readily appreciate that the present invention may be implemented as shown in the drawings and described above; however, those skilled in the art will appreciate that many modifications, adaptations, and variations of the present invention are possible in light of the above teachings without departing from the scope of the invention; meanwhile, any equivalent changes, modifications and evolution of the above embodiments according to the essential technology of the present invention still fall within the scope of the present invention.
Claims (10)
1. A method for dynamic risk assessment of a gas gathering station, comprising the steps of:
collecting data information of the gas collecting station, and dividing nodes of the gas collecting station according to a process flow;
analyzing the technological parameter deviation generated by each node, and identifying the risk scene of each node of the gas gathering station according to the data information and the technological parameter deviation;
establishing a process steady-state model of the gas gathering station, and performing process simulation on the identified risk scene;
changing process parameters of process simulation to obtain simulation operation results with different deviation degree deviations, and determining dangerous peaks of the process parameters;
dividing the process parameter deviation into intervals according to the condition that the process parameter reaches a dangerous peak value, and judging risk levels of risk scenes of all nodes according to the number of dangerous factors in the intervals to realize dynamic risk assessment of the gas gathering station, wherein the number of dangerous factors represents the number of dangerous peak values reached by the process parameter in each working condition operation.
2. The method of claim 1, wherein the data information of the gas station includes material information, process operating condition information, equipment size information, and location information of the gas station.
3. The method for dynamically evaluating the risk of a gas gathering station according to claim 1, wherein the analyzing the process parameter deviation generated by each node, and identifying the risk scenario of each node of the gas gathering station according to the data information and the process parameter deviation comprises:
according to the data information, analyzing the technological parameter deviation of each node of the gas gathering station by using a HAZOP method, wherein the technological parameter deviation comprises the generation reason and the caused result of the deviation;
grading the severity of the consequences caused by the deviation by using a risk matrix method;
and identifying the risk scene of each node of the gas gathering station according to the grading condition, and completing the primary judgment of the risk grade.
4. The method for evaluating the dynamic risk of a gas gathering station according to claim 1, wherein the analyzing the process parameter deviation generated by each node, and after identifying the risk scene of each node of the gas gathering station according to the data information and the process parameter deviation, further comprises performing reliability analysis on the safety instrument in the identified risk scene of the high-temperature working condition of the gas gathering station, specifically comprising the following steps:
obtaining the maximum applicable temperature T of the safety instrument 0 Measuring the temperature value of the over-temperature medium, and establishing a mathematical model of the reliability of the instrument;
inputting multiple groups of measurement data by using a mathematical model of instrument reliability, solving and obtaining maximum error delta of instrument indication value under high-temperature working condition max ；
Maximum error delta of indicating value of comparison instrument max And instrument tolerance error delta x Judging the reliability of the safety instrument:
if it isThe reliability of the safety instrument meets the requirement, the safety instrument is continuously used, and the indicating value of the safety instrument is corrected according to the error value;
otherwise, the reliability of the safety instrument does not meet the requirement, and the safety instrument is replaced.
5. The method for dynamic risk assessment of a gas station according to claim 4, wherein the expression of the instrument reliability mathematical model is:
in which delta is the measured medium temperature of the meter exceedsT 0 The error of the indication value; i g Indicating values for the high-temperature instrument; i s Is a standard indication value; delta is zero drift and time drift of the high-temperature instrument; c is a temperature influence coefficient; t is any temperature value of the super-temperature medium.
6. The method for dynamic risk assessment of a gas station according to claim 1, wherein the process parameters simulated in the changing process obtain simulated operation results of deviations of different degrees of deviation, and determining dangerous peaks of the process parameters comprises:
and adding a flow regulation controller and a liquid level regulation controller on the basis of steady state operation of the process, obtaining simulation operation results with different deviation degree deviations by changing process parameter conditions of process simulation, converting a steady state process model into a dynamic process model, recording the change of each process parameter, determining boundary conditions of each process parameter, and obtaining dangerous peaks of each process parameter.
7. A method of dynamic risk assessment for a gas station according to claim 1, wherein the process parameters include temperature, pressure and liquid level.
8. The method for dynamic risk assessment of a gas gathering station according to claim 1, wherein after risk level re-determination is performed on risk scenes of each node according to the number of risk factors in an interval, the method further comprises risk transfer path determination, and specifically comprises the following steps:
setting process simulation time in Aspen HYSYS simulation software, carrying out data acquisition on process parameters according to set time intervals, and assembling data acquisition results into a table;
determining the time required by each process parameter to reach a dangerous peak value according to the form analysis, and comparing the time values;
and (3) arranging the sequence of reaching the dangerous peak value of each process parameter according to the comparison result, and taking the sequence as a risk transmission path in the risk scene.
9. The method for dynamic risk assessment of a gas station according to claim 1, wherein the step of dividing the process parameter deviation into intervals according to the condition that the process parameter reaches a dangerous peak value further comprises dividing the process parameter deviation into intervals according to the condition that an initial alarm value of a safety instrument in the gas station is obtained.
10. A system for dynamic risk assessment of a gas gathering station, comprising:
the data acquisition processing unit is used for acquiring data information of the gas gathering station and dividing nodes of the gas gathering station according to the process flow;
the risk level primary judging unit is used for analyzing the technological parameter deviation generated by each node and identifying the risk scene of each node of the gas gathering station according to the data information and the technological parameter deviation;
the process simulation unit is used for constructing a process steady-state model of the gas gathering station by adopting Aspen HYSYS simulation software and performing process simulation on the identified risk scene;
the dangerous peak value acquisition unit is used for changing process parameters of process simulation to acquire simulation operation results with different deviation degree deviations, and determining dangerous peak values of the process parameters;
the risk level secondary judging unit is used for dividing the process parameter deviation into intervals according to the condition that the process parameter reaches the dangerous peak value, judging the risk level again for the risk scene of each node according to the number of the dangerous factors in the intervals, and realizing the dynamic risk assessment of the gas gathering station, wherein the number of the dangerous factors represents the number of the dangerous peak value reached by the process parameter during the operation of each working condition.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210910152.XA CN117521436A (en) | 2022-07-29 | 2022-07-29 | Dynamic risk assessment method and system for gas gathering station |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210910152.XA CN117521436A (en) | 2022-07-29 | 2022-07-29 | Dynamic risk assessment method and system for gas gathering station |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN117521436A true CN117521436A (en) | 2024-02-06 |
Family
ID=89740655
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210910152.XA Pending CN117521436A (en) | 2022-07-29 | 2022-07-29 | Dynamic risk assessment method and system for gas gathering station |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117521436A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN118313698A (en) * | 2024-06-06 | 2024-07-09 | 深圳市同创环保科技有限公司 | Intelligent layout monitoring method, system and medium applied to landfill gas collection |
-
2022
- 2022-07-29 CN CN202210910152.XA patent/CN117521436A/en active Pending
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN118313698A (en) * | 2024-06-06 | 2024-07-09 | 深圳市同创环保科技有限公司 | Intelligent layout monitoring method, system and medium applied to landfill gas collection |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109524139B (en) | Real-time equipment performance monitoring method based on equipment working condition change | |
| CN117690261B (en) | Regional early warning system for monitoring leakage of dangerous chemical gas in factory | |
| EP0843244B1 (en) | Diagnostic trend analysis for aircraft engines | |
| CN110261809B (en) | System and method for determining operation state of capacitive voltage transformer | |
| KR100997009B1 (en) | The method for dynamic detection and on-time warning of industrial process | |
| RU2696919C1 (en) | Method and system for assessment of technical condition of gas turbine units based on temperature fields | |
| CN110907883A (en) | Metering supervision method and system for automatic verification system of electric energy meter | |
| CN116992243B (en) | AIOT-based industrial solid waste treatment material management method and system | |
| CN106872172B (en) | Real-time discrimination method and system for monitoring safety parameters of aero-engine test | |
| CN117155703B (en) | Network security test evaluation system and method | |
| CN110658308A (en) | Method for evaluating safety and reliability of online flue gas monitoring system by considering common cause failure | |
| US6502018B1 (en) | Method for diagnosis of equipment | |
| CN117521436A (en) | Dynamic risk assessment method and system for gas gathering station | |
| CN117168713B (en) | Helium-hydrogen mass spectrometer leak detector signal rapid processing system and method | |
| US20060085102A1 (en) | Methods for establishing alerts and/or alert limits for monitoring mechanical devices | |
| CN116773239A (en) | Intelligent gas meter controller reliability life prediction method | |
| CN105930870A (en) | Engineering safety monitoring data outlier detection method | |
| CN115130049B (en) | Risk control system for aircraft complete machine level high-temperature test and construction method thereof | |
| CN118966581B (en) | AI technology-based intelligent operation and maintenance method for real-time collection of pipe rack by abnormal sensor | |
| CN119334260B (en) | A bridge detection and early warning method and system based on grating sensor | |
| Kulcsár et al. | Statistical process control based performance evaluation of on-line analysers | |
| CN118425421B (en) | Visual gas detection system and method based on artificial intelligence | |
| CN118157325B (en) | Real-time monitoring method and system for new energy power | |
| CN119171403B (en) | Power dispatching automation safety detection system and method based on artificial intelligence | |
| CN111811623B (en) | Auxiliary judgment method for measuring flow of high-pressure gas supply |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |