A method and system for optimizing the layout of pressure sensors in urban gas pipeline networks

Abstract

The present invention discloses an optimization method and system for the layout of pressure sensors in urban gas pipeline networks, comprising a pipeline network simulation unit, an index calculation unit, an importance calculation unit, and a node comparison and optimization unit; the pressure changes of all nodes and pressure regulating stations when the pipeline network leaks at each node or pressure regulating station are simulated by gas pipeline network simulation software, the leakage monitoring coverage, leakage monitoring sensitivity, operating pressure and operating flow of different nodes and pressure regulating stations are calculated, the pipe age and regional grade indicators are introduced, the importance of each node and pressure regulating station is calculated, the nodes are screened and optimized, and the optimal layout points of the pressure sensors are determined; the method of the present invention takes into account the actual operating status of the gas pipeline network, takes into account the cost and monitoring efficiency, takes into account the variability of the evaluation indicators while taking into account the correlation between the indicators, and can provide the layout positions and priority of the pressure sensors in the renovation of the old urban gas pipeline network.

Description

Technical Field

[0001] The present invention relates to a method for optimizing the safety of a town gas pipeline network, and in particular to a method and system for optimizing the arrangement of pressure sensors in a town gas pipeline network. Background Art

[0002] By installing wireless pressure sensors at key nodes of gas pipelines, the pressure changes at each node can be monitored in real time on the gas SCADA monitoring system platform, which is of great significance to ensuring the safe operation of urban gas pipeline networks. However, due to the large number of nodes in urban pipeline networks, the deployment of pressure sensors at each node will greatly increase the construction cost; therefore, it is very important to balance the cost and monitoring efficiency when arranging pressure sensors while considering the current status of pipeline operation.

[0003] The invention patent with publication number CN113094853A proposes "an optimized layout method and system for gas pipeline leak locating". This method obtains the minimum number of required pressure sensors and the necessary sensor point combination based on evaluation indicators. It can obtain the minimum number of required pressure sensors and their point layout without losing leakage identification events.

[0004] The invention patent with publication number CN110657352A proposes "a method, system, equipment and storage medium for optimizing gas pipeline monitoring point layout", analyzes the underground space of all inspection wells along the gas pipeline, and finds the layout location that takes into account both construction cost and monitoring efficiency based on the effective monitoring length, effectively selects the underground space where monitoring sensors need to be deployed, and can give corresponding layout locations according to the requirements of detection efficiency, reducing the blindness of point selection.

[0005] The invention patent with publication number CN113473501A proposes an "optimization method for the deployment of gas pipeline leakage detectors and pressure sensors". The deployment of sensor groups is optimized based on the Levy flight mechanism. The optimized solution avoids the problem of existing optimization methods easily falling into local limits, reduces hardware equipment costs and redundancy of monitoring data.

[0006] It can be seen that the existing patents use different methods to optimize the location of gas pipeline pressure sensors, taking into account factors such as the economy, efficiency and coverage of the layout, to determine the number and location of the pressure sensors; however, the above methods lack consideration of the actual operation status of the urban gas pipeline network. For example, they only consider the topological relationship of the pipeline network, but ignore the pressure levels of different pipeline networks. 55009-2021 "Gas Engineering Project Specification" Clause 5.1.1 stipulates that the transmission and distribution pipelines should be classified according to the maximum working pressure, and divided into ultra-high pressure, high pressure, sub-high pressure, medium pressure and low pressure pipelines, and the sensitivity of pressure sensors to pipeline leakage of different pressure levels is different; and gas pipelines of different pressure levels are connected through pressure regulating devices, and pressure monitoring devices are usually provided on the side of the pressure regulating device to determine whether it is working normally, that is, there are inherent pressure sensors between gas pipelines of different pressure levels, which are necessary and cannot be considered in the optimized sensors; at the same time, the method proposed in the existing patent does not consider the impact of the probability and consequences of gas pipeline leakage on the layout of pressure sensors. Usually, the probability of leakage of old gas pipelines is higher than that of newly built gas pipelines, and the consequences of gas leakage in the first-level area are higher than those in the fourth-level area; that is, the pressure sensor layout optimization methods proposed in the existing patents are mostly aimed at newly built pipelines, without considering the layout optimization on existing old pipelines, and without considering the actual operation characteristics of the pipelines such as pressure, flow, pipe age and other factors, resulting in the inability to give the layout priority and optimization method of pressure sensors in the actual renovation of old pipelines. Summary of the invention

[0007] The purpose of the present invention is to overcome the shortcomings of the prior art and to provide a practical and easy-to-operate method and system for optimizing the layout of pressure sensors in a town gas pipeline network.

[0008] The present invention provides an optimization method for the arrangement of pressure sensors in a town gas network, comprising the following steps:

[0009] Step 1: Take n nodes and pressure regulating stations in the urban gas pipeline network as points to be optimized and number them, naming them A1, A2, ···, A i 、···、A n ; Input the information of each pipeline in the urban gas pipeline network into the gas pipeline network simulation software, simulate and output the operating pressure P and operating flow Q of each point to be optimized in the actual gas pipeline network under normal working conditions; set the leakage flow value ΔQ at each point to be optimized, simulate and output the pressure change value of each point to be optimized in the actual gas pipeline network when leaking and the pressure change value of other points to be optimized caused by leakage, recorded as [ΔP Ai A1 , ΔP Ai A2 , ···, ΔP AiAi , ΔP Ai Aj , ···, ΔP Ai An ], where ΔP Ai Ai Indicates point A to be optimized i The change in pressure during leakage, ΔP Ai Aj Indicates point A to be optimized i In case of leakage j The pressure change value of each optimized point is calculated by using the matrix [T] n×n express:

[0010] ;

[0011] t ij is the matrix [T] n×n The element in row i and column j in t ij =ΔP Ai Aj , i,j=1,2,3,···,n.

[0012] Step 2: Calculate the leakage monitoring coverage N, leakage monitoring sensitivity S, operating pressure P, operating flow Q, pipe age Y, and regional level G index values ​​of each point to be optimized, as follows:

[0013] S201: Calculate the leakage monitoring coverage N of each point to be optimized. The process of calculating N is as follows:

[0014] The first step is to use the matrix [T] in step 1 n×n , calculate the pressure influence coefficient matrix [Y] of each point to be optimized leakage on other points to be optimized n×n , the pressure influence coefficient matrix [Y] n×n The calculation formula for the element Y(i, j) in the i-th row and j-th column is Y(i, j)=t ji / t jj =ΔP Aj Ai / ΔP Aj Aj , i=1,2,3,···,n, j=1,2,3,···,n, n is the number of all points to be optimized; matrix [Y] n×n The elements of the i-th row vector represent the points A to be optimized. i The pressure of is affected by the leakage of other points to be optimized; the elements of the j column vector represent the pressure of other points to be optimized affected by the leakage of the point to be optimized A. j The extent of the impact of the leak;

[0015] The second step is to standardize the matrix [Y] by standard deviation. n×n The standard deviation of each k-column element in is normalized to obtain the pressure influence standard matrix [Y'] n×n ;

[0016] The third step is to use the extreme value normalization method to transform the matrix [Y'] n×n The extreme values ​​of the elements in each column are standardized to obtain the pressure influence extreme value standard matrix [Y''] n×n ;

[0017] The fourth step is to calculate the matrix [Y''] by the Euclidean distance method n×n , and obtain the leakage pressure influence fuzzy similarity matrix [R] n×n ;

[0018] Step 5: Set the pressure correlation distance constraint value μ of the point to be optimized and compare [R] n×n The size of the distance between all elements in and the correlation constraint value μ, when [R] n×n The element r ij ≤μ, the element is converted to 1, otherwise it is converted to 0; the leakage pressure affects the fuzzy similarity matrix [R] n×n Convert to Boolean matrix [r] n×n ; The μ range: 0<u<1; r ij is the fuzzy similarity matrix of leakage pressure influence [R] n×n The element in the i-th row and j-th column, i, j=1,2,3,···,n; r ij The size of the matrix [Y''] n×n The i-th row element and the matrix [Y''] n×n The similarity between the elements in the jth row, i.e. the point A to be optimized i and A j Pressure correlation between

[0019] Step 6: By transforming the Boolean matrix [r] n×n Sum by row to obtain the leakage monitoring coverage N when each point to be optimized is used as a pressure monitoring point;

[0020] S202: Calculate the leakage monitoring sensitivity S of each point to be optimized;

[0021] The pressure influence extreme value standard matrix [Y''] n×n The element Y''(i, j) and the Boolean matrix [r] n×n Multiply the corresponding elements r(i, j) to get the matrix [S] n×n , and for the matrix [S] n×n Sum by row to obtain the leakage monitoring sensitivity S when different points to be optimized are used as pressure monitoring points;

[0022] S203: reading the operating pressure P of each point to be optimized under normal working conditions output in step 1;

[0023] S204: reading the operating flow Q of each point to be optimized under normal working conditions output in step 1;

[0024] S205: Determine the pipe age Y of each pipeline where the optimization point is located through the gas company's pipeline installation completion acceptance record or the gas information management platform;

[0025] S206: Determine the regional level G of the pipeline where each point to be optimized is located through the gas pipeline network geographic information system, the gas information management platform or manual inspection, and the regional level G belongs to the first, second, third and fourth level regions, and G is assigned values ​​of 1, 2, 3 and 4 respectively;

[0026] Step 3: Calculate the importance of each point to be optimized by CRITIC weight method;

[0027] Step 4: Screen and optimize the points to be optimized to obtain the optimal layout points of the pressure sensor.

[0028] The present invention provides an optimization system for the arrangement of pressure sensors in a town gas network, comprising the following units:

[0029] Pipeline network simulation unit: used to simulate the pressure and flow of each point to be optimized in the actual gas pipeline network under normal working conditions; set the leakage flow value at each point to be optimized, simulate and output the pressure change value of each point to be optimized in the actual gas pipeline network when leaking, and the pressure change value of other nodes and pressure regulating stations caused by leakage;

[0030] Index calculation unit: used to calculate the leakage monitoring coverage N, leakage monitoring sensitivity S, operating pressure P, operating flow Q, pipe age Y, and regional grade G index values ​​of each point to be optimized;

[0031] Importance calculation unit: used to calculate the importance of each point to be optimized by CRITIC weight method;

[0032] Node comparison and optimization unit: Sort the points to be optimized according to their importance, screen and optimize the points to be optimized, and output the optimized layout points of the pressure sensors.

[0033] Advantages of the present invention:

[0034] 1. The method of the present invention can maximize the monitoring of information on urban gas pipeline networks, avoid the problem of single-objective consideration of single factors and multi-objective optimization calculation process falling into local optimality, and has good economic efficiency; and considers the variability of evaluation indicators while taking into account the correlation between indicators, and has good objectivity and scientificity;

[0035] 2. The method of the present invention can realize effective monitoring of the gas pipeline network and clarify the monitoring nodes of the pressure sensor monitoring points, which is helpful for judging the range of abnormal pressure monitoring data;

[0036] 3. The method of the present invention takes into account the actual operating status of the gas pipeline network, taking into account both cost and monitoring efficiency, and can provide the layout location and priority of pressure sensors in the renovation of old urban gas pipeline networks, provide a reference for the renovation of gas companies' pressure monitoring equipment, and improve the safety of urban gas pipeline networks. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The accompanying drawings in the specification, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0038] Figure 1 A flow chart of an optimization method for the arrangement of pressure sensors in a town gas network according to the present invention;

[0039] Figure 2 A schematic diagram of the topological relationship of the gas network including all nodes for optimizing the arrangement of pressure sensors in the present invention;

[0040] Figure 3 A schematic diagram of a gas pipe network including an original pressure sensor for which the arrangement of the pressure sensor is optimized according to the present invention;

[0041] Figure 4 A schematic diagram of a gas pipe network after the layout of pressure sensors is optimized according to the present invention;

[0042] Figure 5 The diagram is a schematic diagram of an optimization system for the arrangement of pressure sensors in a town gas network according to the present invention. DETAILED DESCRIPTION

[0043] It should be noted that the following detailed descriptions are illustrative and are intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present application belongs.

[0044] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the plural form according to the present application. In addition, it should be understood that when the terms "include" and / or "include" are used in this specification, they indicate the presence of features, steps, operations, devices, components and / or their combinations.

[0045] In addition, if the embodiments of the present invention involve directional indications (such as up, down, left, right, front, back, etc.), the directional indications are only used to explain the relative position relationship, movement status, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0046] like Figure 1 As shown, an optimization method for the arrangement of pressure sensors in a town gas network of the present invention comprises the following steps:

[0047] Step 1: n nodes in the town gas network (the nodes are the intersections of pipelines in the town gas network structure, and the intersections of gas transmission stations and pipelines in the network) and pressure regulating stations are taken as points to be optimized, and are numbered and named A1, A2, .., A i 、···、A n ; Input the information of each pipeline in the urban gas pipeline network into the gas pipeline network simulation software (such as Synergi Gas, Transient Gas Network, etc.), simulate and output the operating pressure P and operating flow Q of each point to be optimized in the actual gas pipeline network under normal conditions; set the leakage flow value ΔQ at each point to be optimized (the value of ΔQ is usually not more than 5% of the flow Q under normal operating conditions), simulate and output the pressure change value of each point to be optimized in the actual gas pipeline network when leaking and the pressure change value of other points to be optimized caused by leakage, recorded as [ΔP Ai A1 , ΔP Ai A2 , ···, ΔP Ai Ai , ΔP Ai Aj , ···, ΔP Ai An ], where ΔP Ai Ai Indicates point A to be optimized i The change in pressure during leakage, ΔP Ai Aj Indicates point A to be optimized i In case of leakage j The pressure change value of each optimized point is calculated by using the matrix [T] n×n express:

[0048] ;

[0049] t ij is the matrix [T] n×n The element in row i and column j in t ij =ΔPAi Aj , i,j=1,2,3,···,n.

[0050] According to the parameter requirements of the gas network simulation software, the information of each pipeline in the urban gas network includes pipe diameter, length, operating pressure, network topology, gate station pressure and flow, pressure regulating station pressure, user side pressure and flow and other information.

[0051] Step 2: Calculate the leakage monitoring coverage N, leakage monitoring sensitivity S, operating pressure P, operating flow Q, pipe age Y, and regional level G index values ​​of each point to be optimized, as follows:

[0052] S201: Calculate the leakage monitoring coverage N of each point to be optimized. The process of calculating N is as follows:

[0053] The first step is to use the matrix [T] in step 1 n×n , calculate the pressure influence coefficient matrix [Y] of each point to be optimized leakage on other points to be optimized n×n , the pressure influence coefficient matrix [Y] n×n The calculation formula for the element Y(i, j) in the i-th row and j-th column is Y(i, j)=t ji / t jj =ΔP Aj Ai / ΔP Aj Aj , i=1,2,3,···,n, j=1,2,3,···,n, n is the sum of all the points to be optimized. Matrix [Y] n×n The elements of the i-th row vector represent the points A to be optimized. i The pressure of is affected by the leakage of other points to be optimized; the elements of the j column vector represent the pressure of other points to be optimized affected by the leakage of the point to be optimized A. j The impact of the leak.

[0054] The second step is to standardize the matrix [Y] by standard deviation. n×n The standard deviation of each k-column element in is normalized to obtain the pressure influence standard matrix [Y'] n×n , the calculation formula is:

[0055] (i, k=1,2,3,···,n)

[0056] Where Y'(i, k) is the matrix [Y'] n×n The i-th row and k-th column element of for [Y] n×n The average value of the k-th column element Y(i,k), ; S kfor [Y] n×n The standard deviation of the k-th column element Y(i, k) in .

[0057] The third step is to use the extreme value normalization method to transform the matrix [Y'] n×n The extreme values ​​of the elements in each column are standardized to obtain the pressure influence extreme value standard matrix [Y''] n×n , the calculation formula is:

[0058]

[0059] Where Y''(i, k) is the matrix [Y''] n×n The element in row i and column k, is [Y'] n×n The smallest element in the k-th column of , is [Y'] n×n The largest element in the k-th column of .

[0060] The fourth step is to calculate the matrix [Y''] by the Euclidean distance method n×n , and obtain the leakage pressure influence fuzzy similarity matrix [R] n×n , the calculation formula is:

[0061]

[0062] In the formula, r ij is the fuzzy similarity matrix of leakage pressure influence [R] n×n The element in the i-th row and j-th column, i, j=1,2,3,···,n; r ij The size of the matrix [Y''] n×n The i-th row element and the matrix [Y''] n×n The similarity between the elements in the jth row, i.e. the point A to be optimized i and A j Pressure correlation between; Y''(i, k) is the matrix [Y''] n×n The element in row i and column k; Y''(j, k) is the matrix [Y''] n×n The element at row j and column k.

[0063] Step 5: Set the pressure correlation distance constraint value μ of the point to be optimized and compare [R] n×n The size of the distance between all elements and the correlation constraint value μ is such that [R] n×n The element r ij ≤μ, the element is converted to 1, otherwise it is converted to 0; the leakage pressure affects the fuzzy similarity matrix [R] n×n Convert to Boolean matrix [r] n×n ; The μ range is: 0<u<1.

[0064] The constraint value μ is used as the constraint condition for optimizing the selection of pressure monitoring points. ij If it is less than the constraint value μ, it means that the pressure correlation between the points to be optimized is large enough, and the two points to be optimized and the node can monitor each other.

[0065] Step 6: By transforming the Boolean matrix [r] n×n By summing up the rows, we can obtain the leakage monitoring coverage N when each point to be optimized is used as a pressure monitoring point.

[0066] S202: Calculate the leakage monitoring sensitivity S of each point to be optimized.

[0067] The pressure influence extreme value standard matrix [Y''] n×n The element Y''(i, j) and the Boolean matrix [r] n×n Multiply the corresponding elements r(i, j) to get the matrix [S] n×n , S(i, j) is the matrix [S] n×n The element of the i-th row and j-th column, S(i, j)=Y''(i, j)×r(i, j), i, j=1,2,3,···,n, and the matrix [S] n×n By summing up the rows, the leakage monitoring sensitivity S when different points to be optimized are used as pressure monitoring points is obtained.

[0068] S203: Read the operating pressure P of each point to be optimized under normal working conditions output in step 1.

[0069] S204: Read the operating flow Q of each point to be optimized under normal working conditions output in step 1.

[0070] S205: Determine the pipe age Y of each pipe where the point to be optimized is located.

[0071] It is determined based on the installation time of the pipeline where the point to be optimized is located, in years, and can be obtained through the gas company's pipeline installation completion acceptance record or the gas information management platform.

[0072] S206: Determine the regional level G of the pipeline where each point to be optimized is located. If it belongs to the first, second, third and fourth level regions, G is assigned values ​​of 1, 2, 3 and 4 respectively.

[0073] According to the classification method of urban gas pipeline area levels in GB 50028-2006 "Urban Gas Design Code (2020 Edition)", the regional level G of the pipeline where the optimization point is located is determined through the gas pipeline network geographic information system (GIS), gas information management platform or manual inspection, and the regional level G of the pipeline where the optimization point is located is assigned to 1, 2, 3 and 4 for the first, second, third and fourth level areas respectively;

[0074] Step 3: Calculate the importance of each point to be optimized by CRITIC weight method;

[0075] The CRITIC weight method can be found in "Diakoulaki, D., Mavrotas, G., & Papayannakis, L. (1995). Determining objective weights in multiple criteria problems: Thecritic method. Computers & Operations Research, 22(7), 763-770." (Diakoulaki, D., Mavrotas, G., & Papayannakis, L. (1995). Determining objective weights in multiple criteria problems: The CRITIC method, Computers & Operations Research, 22(7), 763-770.), which can specifically include the following steps:

[0076] S301: Set the six evaluation index values ​​B of all the points to be optimized 1×q =B 1×6 =[N,S,P,Q,Y,G] forms the matrix X=[x pq ] n×6 , where x pq is the element in the pth row and qth column of the matrix, representing the point A to be optimized p Evaluation index B q The numerical value is p=1,2,3,···,n, where n is the number of all points to be optimized; q=1,2,3,···,6. The X matrix is ​​as follows:

[0077]

[0078] S302: Define the operating pressure P and operating flow Q under normal working conditions as negative indicators, define the leakage monitoring coverage N, leakage monitoring sensitivity S, pipe age Y and regional level G as positive indicators, and standardize the positive indicator column and negative indicator column of the matrix X respectively to obtain X'=[x' pq ] n×6 , where x' pq The elements contained in the matrix represent the point A to be optimized. p Evaluation index B q Normalizing the values, the X' matrix looks like this:

[0079]

[0080] S303: Calculate the variability of the evaluation index and express it in the form of standard deviation. The formula is as follows:

[0081] (p=1,2,3,···,n; q=1,2,3,···,6)

[0082] Where σ q Represents the standard deviation of the qth column of the matrix X', reflecting the evaluation index B corresponding to this column q The difference in the element values ​​of the evaluation index is shown in Figure 2. The larger the standard deviation, the greater the difference in the value of the evaluation index. q The stronger the evaluation intensity and the greater the variability, the more weight should be assigned to the indicator. is the average value of the qth column of matrix X', .

[0083] S304: Calculate the conflict of evaluation indicators. The conflict reflects the correlation between different indicators. If there is a significant positive correlation, the smaller the conflict value is, the more the same information is reflected, and the more repetitive the evaluation content that can be reflected is, which weakens the evaluation strength of the indicator to a certain extent. The formula is as follows:

[0084] (q, l=1,2,3,···,6)

[0085] Where f q Indicates evaluation index B q With the other five evaluation indicators B l The magnitude of the conflict, Evaluation index B q And evaluation index B l The correlation coefficient between them was Pearson's correlation coefficient.

[0086] S305: Calculate the evaluation index information carrying capacity C q =σ q ×f q .

[0087] S306: Calculate the evaluation index weight, the formula is as follows:

[0088] (q=1,2,3,···,6)

[0089] Where W q Evaluation index B q The weight of .

[0090] S307: Calculate the comprehensive score S of each point to be optimized p , S p As point A to be optimized p The importance of is as follows:

[0091] (p=1,2,3,···,n; q=1,2,3,···,6)

[0092] Step 4: Screen and optimize the nodes to obtain the optimal layout points of the pressure sensors. The process is as follows:

[0093] S401: The importance of all points to be optimized in step 3 is S p Sort by size, then remove the nodes where pressure sensors have been arranged among the points to be optimized (if there is no original pressure sensor, it can be left as is), and other points to be optimized that can be monitored by the original pressure sensor nodes and the pressure regulating station when they are used as pressure sensor arrangement points, from the sorting to obtain the nodes where pressure sensors are to be arranged;

[0094] As an embodiment of the present invention, according to step 2, ij The relationship between the size of the constraint value μ determines whether the two points to be optimized can monitor each other.

[0095] like Figure 3 As shown, it is a schematic diagram of a gas pipeline network including original pressure sensors and pressure regulating stations. The nodes of these original pressure sensors and pressure regulating stations will be removed first when new pressure sensor layout points are added.

[0096] S402: Selecting a node with the greatest importance from among the nodes where pressure sensors are to be arranged as an optimized arrangement point for the pressure sensors, and removing other points to be optimized that can be monitored by the optimized arrangement point;

[0097] S403: Repeat the process of S402 until the node coverage C of the pressure sensor arrangement points meets the preset requirements, such as Figure 4 As shown in the figure, the final pressure sensor optimization layout points are obtained, and the node coverage C is the number of pressure sensor optimization layout points n. c The ratio of n to the number of points to be optimized.

[0098] like Figure 5 As shown, the present invention also provides an optimization system for the layout of pressure sensors in a town gas pipeline network, comprising:

[0099] Pipeline network simulation unit: used to simulate the pressure P and flow Q of each point to be optimized in the actual gas pipeline network under normal working conditions; set the leakage flow value at each point to be optimized, simulate and output the pressure change value of each point to be optimized in the actual gas pipeline network when leaking, and the pressure change value of other nodes and pressure regulating stations caused by leakage.

[0100] Index calculation unit: used to calculate the leakage monitoring coverage N, leakage monitoring sensitivity S, operating pressure P, operating flow Q, pipe age Y, and regional grade G index values ​​of each point to be optimized;

[0101] Importance calculation unit: used to calculate the importance of each point to be optimized by CRITIC weight method;

[0102] Node comparison and optimization unit: Sort the points to be optimized according to their importance, screen and optimize the nodes, and output the optimized layout points of the pressure sensors.

[0103] The above description is only the preferred embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for optimizing the layout of pressure sensors in a town gas network, characterized in that The following steps are involved: Step 1: Take n nodes and pressure regulating stations in the urban gas pipeline network as points to be optimized and number them, naming them A1, A2, ···, A i 、···、A n ; Input the information of each pipeline in the urban gas pipeline network into the gas pipeline network simulation software, simulate and output the operating pressure P and operating flow Q of each point to be optimized in the actual gas pipeline network under normal working conditions; set the leakage flow value ΔQ at each point to be optimized, simulate and output the pressure change value of each point to be optimized in the actual gas pipeline network when leaking and the pressure change value of other points to be optimized caused by leakage, recorded as [ΔP Ai A1 , ΔP Ai A2 , ···, ΔP Ai Ai , ΔP Ai Aj , ···, ΔP Ai An ], where ΔP Ai Ai Indicates point A to be optimized i The change in pressure during leakage, ΔP Ai Aj Indicates point A to be optimized i In case of leakage j The pressure change value of each optimized point is calculated by using the matrix [T] n×n express: ； t ij is the matrix [T] n×n The element in row i and column j in t ij =ΔP Ai Aj , i, j = 1, 2, 3, · · ·, n; Step 2: Calculate the leakage monitoring coverage N, leakage monitoring sensitivity S, operating pressure P, operating flow Q, pipe age Y, and regional level G index values ​​of each point to be optimized, as follows: S201: Calculate the leakage monitoring coverage N of each point to be optimized. The process of calculating N is as follows: The first step is to use the matrix [T] in step 1 n×n , calculate the pressure influence coefficient matrix [Y] of each point to be optimized leakage on other points to be optimized n×n , the pressure influence coefficient matrix [Y] n×n The calculation formula for the element Y(i, j) in the i-th row and j-th column is Y(i, j)=t ji / t jj =ΔP Aj Ai / ΔP Aj Aj , i=1,2,3,···,n, j=1,2,3,···,n, n is the number of all points to be optimized; matrix [Y] n×n The elements of the i-th row vector represent the points A to be optimized. i The pressure of is affected by the leakage of other points to be optimized; the elements of the j column vector represent the pressure of other points to be optimized affected by the leakage of the point to be optimized A. j The extent of the impact of the leak; The second step is to standardize the matrix [Y] by standard deviation. n×n The standard deviation of each k-column element in is normalized to obtain the pressure influence standard matrix [Y'] n×n ; The third step is to use the extreme value normalization method to transform the matrix [Y'] n×n The extreme values ​​of the elements in each column are standardized to obtain the pressure influence extreme value standard matrix [Y''] n×n ; The fourth step is to calculate the matrix [Y''] by the Euclidean distance method n×n , and obtain the leakage pressure influence fuzzy similarity matrix [R] n×n ; Step 5: Set the pressure correlation distance constraint value μ of the point to be optimized and compare [R] n×n The size of the distance between all elements in and the correlation constraint value μ, when [R] n×n The element r ij ≤μ, the element is converted to 1, otherwise it is converted to 0; the leakage pressure affects the fuzzy similarity matrix [R] n×n Convert to Boolean matrix [r] n×n ; The μ range: 0<u<1; r ij is the fuzzy similarity matrix of leakage pressure influence [R] n×n The element in the i-th row and j-th column, i, j=1,2,3,···,n; r ij The size of the matrix [Y''] n×n The i-th row element and the matrix [Y''] n×n The similarity between the elements in the jth row, i.e. the point A to be optimized i and A j Pressure correlation between Step 6: By transforming the Boolean matrix [r] n×n Sum by row to obtain the leakage monitoring coverage N when each point to be optimized is used as a pressure monitoring point; S202: Calculate the leakage monitoring sensitivity S of each point to be optimized; The pressure influence extreme value standard matrix [Y''] n×n The element Y''(i, j) and the Boolean matrix [r] n×n Multiply the corresponding elements r(i,j) to get the matrix [S] n×n , and for the matrix [S] n×n Sum by row to obtain the leakage monitoring sensitivity S when different points to be optimized are used as pressure monitoring points; S203: reading the operating pressure P of each point to be optimized under normal working conditions output in step 1; S204: reading the operating flow Q of each point to be optimized under normal working conditions output in step 1; S205: Determine the pipe age Y of each pipeline where the optimization point is located through the gas company's pipeline installation completion acceptance record or the gas information management platform; S206: Determine the regional level G of the pipeline where each point to be optimized is located through the gas pipeline network geographic information system, the gas information management platform or manual inspection, and the regional level G belongs to the first, second, third and fourth level regions, and G is assigned values ​​of 1, 2, 3 and 4 respectively; Step 3: Calculate the importance of each point to be optimized by CRITIC weight method; Step 4: Screen and optimize the points to be optimized to obtain the optimal layout points of the pressure sensor.

2. The optimization method for the layout of pressure sensors in a town gas network according to claim 1, characterized in that: The step three specifically includes the following steps: S301: Set the six evaluation index values ​​B of all the points to be optimized 1×q =B 1×6 =[N,S,P,Q,Y,G] forms the matrix X=[x pq ] n×6 , where x pq is the element in the pth row and qth column of the matrix, representing the point A to be optimized p Evaluation index B q Numerical value, p=1,2,3,···,n, n is the number of all points to be optimized; q=1,2,3,···,6; S302: Define the pressure P and operating flow Q under normal working conditions as negative indicators, define the leakage monitoring coverage N, leakage monitoring sensitivity S, pipe age Y and regional level G as positive indicators, and standardize the positive indicator column and negative indicator column of the matrix X respectively to obtain X'=[x' pq ] n×6 , where x' pq The elements contained in the matrix represent the point A to be optimized. p Evaluation index B q Normalized values; S303: Calculate the variability of the evaluation index and express it in the form of standard deviation. The formula is as follows: (p=1,2,3,···,n;q=1,2,3,···,6) Where σ q represents the standard deviation of the qth column of the matrix X'; is the average value of the qth column of matrix X', ; S304: Calculate the conflict of evaluation indicators, the formula is as follows: （q, l=1,2,3,···,6） Where f q Indicates evaluation index B q With the other five evaluation indicators B l The magnitude of the conflict, Evaluation index B q And evaluation index B l The correlation coefficient between them was Pearson correlation coefficient; S305: Calculate the evaluation index information carrying capacity C q =σ q ×f q ; S306: Calculate the evaluation index weight, the formula is as follows: （q=1,2,3,···,6） Where W q Evaluation index B q The weight of S307: Calculate the comprehensive score S of each point to be optimized p , S p As the point A to be optimized p The importance of is as follows: (p=1,2,3,···,n;q=1,2,3,···,6)。 3. The optimization method for the layout of pressure sensors in a town gas network according to claim 1 or 2, characterized in that: The specific process of step 4 is as follows: S401: The importance of all points to be optimized in step 3 is S p Sort by size, then remove the pressure regulating stations among the points to be optimized, the nodes where the pressure sensors are originally arranged, and other points to be optimized that can be monitored by the original pressure sensor nodes and pressure regulating stations as pressure sensor arrangement points from the sorting to obtain the nodes where the pressure sensors are to be arranged; S402: Selecting a node with the greatest importance from among the nodes where pressure sensors are to be arranged as an optimized arrangement point for the pressure sensors, and removing other points to be optimized that can be monitored by the optimized arrangement point; S403: Repeat the process of S402 until the node coverage C of the pressure sensor arrangement points meets the preset requirements, and obtain the final pressure sensor optimization arrangement points. The node coverage C is the number of pressure sensor optimization arrangement points n. c The ratio of n to the number of points to be optimized.

4. The optimization method for the layout of pressure sensors in a town gas network according to claim 3 is characterized in that: In step S401, it is determined whether the two points to be optimized can monitor each other using the method in step 2. ij The relationship between the size of the constraint value μ.

5. A system for arranging pressure sensors in a town gas pipeline network, applied to the optimization method for arranging pressure sensors in a town gas pipeline network as claimed in claim 1, characterized in that: The following units are included: Pipeline network simulation unit: used to simulate the pressure and flow of each point to be optimized in the actual gas pipeline network under normal working conditions; set the leakage flow value at each point to be optimized, simulate and output the pressure change value of each point to be optimized in the actual gas pipeline network when leaking, and the pressure change value of other nodes and pressure regulating stations caused by leakage; Index calculation unit: used to calculate the leakage monitoring coverage N, leakage monitoring sensitivity S, operating pressure P, operating flow Q, pipe age Y, and regional level G index values ​​of each point to be optimized; Importance calculation unit: used to calculate the importance of each point to be optimized through the CRITIC weight method; Node comparison and optimization unit: Sort the points to be optimized according to their importance, screen and optimize the points to be optimized, and output the optimized layout points of the pressure sensors.

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