FDAHP-based long-distance gas pipeline design evaluation system and method

Abstract

The invention discloses a long-distance gas pipeline design evaluation system and method based on FDAHP, belongs to the technical field of design evaluation, is used for long-distance gas pipeline process design evaluation, and is characterized in that an input interface module of the system comprises a judgment matrix input module and an index membership degree input module; an output interface module of the system comprises a consistency check module, an index weight calculation module and a sub-target matrix module. The method comprises the following steps: establishing a fuzzy Delphi analytic hierarchy process model and setting an evaluation grade, constructing a judgment matrix, determining an index weight, determining an index membership degree by using the fuzzy Delphi analytic hierarchy process, obtaining a fuzzy comprehensive evaluation result vector, analyzing the result vector, and obtaining a long-distance gas pipeline process design evaluation result. The method is easy and convenient to operate, high in efficiency, good in accuracy and remarkable in effect in the aspects of improving process efficiency, enhancing safety and reliability and reducing investment cost, and technical support is provided for economic benefits and safety guarantee of the long-distance gas conveying pipeline.

Description

Technical Field

[0001] The invention discloses a long-distance gas transmission pipeline design evaluation system and method based on FDAHP, belonging to the technical field of design evaluation. Background Art

[0002] Compared with traditional energy sources such as coal and oil, natural gas not only has a high calorific value, but is also more environmentally friendly and low-carbon. In order to transport natural gas from distant production areas to user terminals economically, efficiently, safely and smoothly, long-distance gas pipeline transportation technology has developed rapidly. The process design of long-distance gas pipelines is an important part of the preliminary planning of pipeline transportation, and is of great significance to the safe, economical and efficient normal operation of pipelines. In terms of long-distance pipeline design, the existing technology is subject to the selection of influencing factors and various evaluation methods, and inaccurate evaluation is prone to occur. In response to such problems, there is an urgent need for a method that is suitable for efficiently, reasonably and stably determining the comprehensive evaluation of the process design of long-distance gas pipelines, thereby saving a lot of manpower and financial resources in the pipeline design stage and improving the safety and economy of long-distance gas transmission. Summary of the invention

[0003] The purpose of the present invention is to provide a long-distance gas pipeline design evaluation system and method based on FDAHP to obtain a more scientific, comprehensive and accurate evaluation, so as to solve the problem in the prior art that the long-distance gas pipeline process design evaluation results are too subjective and lead to inaccurate results.

[0004] The long-distance gas pipeline design and evaluation system based on FDAHP includes an input interface module, an output interface module and a background calculation module. The input interface module includes a judgment matrix input module and an indicator membership input module. The output interface module includes a consistency check module, an indicator weight calculation module and a sub-target matrix module. The sub-target matrix corresponds to the judgment matrix one by one.

[0005] The method for designing and evaluating a long-distance gas pipeline based on FDAHP uses the long-distance gas pipeline design and evaluation system based on FDAHP, and the background computing module runs the method. The method includes constructing an evaluation index system, establishing a fuzzy Delphi hierarchical analysis model and setting evaluation levels, constructing a judgment matrix, determining index weights, using the fuzzy Delphi hierarchical analysis method to determine index membership, obtaining a fuzzy comprehensive evaluation result vector, analyzing the result vector, and obtaining a long-distance gas pipeline process design evaluation result.

[0006] The fuzzy Delphi analytic hierarchy model includes the target layer, the criterion layer and the indicator layer from top to bottom; Setting the evaluation level includes setting the comprehensive benefits into four levels: A, B, C, and D, which respectively represent the best comprehensive benefits, good comprehensive benefits, poor comprehensive benefits, and extremely poor comprehensive benefits.

[0007] The target layer is to optimize the comprehensive benefits of the gas transmission pipeline, the criterion layer includes high process efficiency, high safety and reliability, and low investment cost. In the indicator layer, the indicators with high process efficiency include the first station pressure, design pressure, pipeline diameter, pipeline wall thickness, outlet temperature, pressure drop, and number of compressor stations; the indicators with high safety and reliability include production safety level, hidden danger control, hidden danger identification, emergency response, material applicability, environmental load and human load; the indicators with low investment cost include pipeline construction cost, compressor station construction cost, operation and operation cost, and pipeline maintenance cost.

[0008] Constructing the judgment matrix includes constructing the criterion layer judgment matrix and constructing the indicator layer judgment matrix; Constructing the criterion layer judgment matrix includes calculating the importance between each criterion of the criterion layer and giving the scale value between two criteria; Constructing the indicator layer judgment matrix includes calculating the importance between indicators under the same criterion layer and giving the scale value between two indicators; The scale value includes 9 levels.

[0009] Determine the indicator weights including, S1 calculates the judgment matrix The product of the elements of each row of : ; ; In the formula, is the judgment matrix Middle Line The elements of the column, is the judgment matrix The order of is the multiplication symbol, It is Product of row elements.

[0010] Determine the indicator weights including, S2 calculation of square root : .

[0011] Determine the indicator weights including: S3 Perform normalization: ; In the formula, For the The indicator weight of the row.

[0012] Determining the indicator weights includes: S4 calculating the maximum characteristic root of the judgment matrix : .

[0013] Determine the indicator weights including, S5 solves the consistency indicator , check the consistency of the matrix: ; Find the consistency ratio of the matrix : ; In the formula, is the average random consistency index; when , the matrix is ​​considered to have passed the consistency test.

[0014] Compared with the prior art, the present invention has the following beneficial effects: by using the fuzzy Delphi analytic hierarchy process, the present invention accurately identifies that the design pressure, pipeline diameter, hidden danger identification and investment cost are the key factors affecting the comprehensive benefits of the pipeline, providing a solid scientific basis for the optimization of the design scheme; the comprehensive evaluation results show that the comprehensive benefits of the pipeline have reached the best state in multiple dimensions, especially in improving process efficiency, enhancing safety and reliability, and reducing investment costs, providing strong technical support for the economic benefits and safety guarantees of long-distance gas pipelines; in addition, the calculation speed and result accuracy are greatly improved, providing an efficient and accurate tool for the evaluation and optimization of similar complex projects. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a simplified diagram of the steps of the fuzzy Delphi hierarchical analysis comprehensive evaluation method; Figure 2 This is the diagram of the fuzzy Delphi hierarchical analysis model; Figure 3 It is the calculation diagram of consistency check, weight and sub-goal matrix R1 of judgment matrix B1; Figure 4 This is the result diagram of the indicator layer weight calculation; Figure 5 This is the evaluation result diagram. DETAILED DESCRIPTION

[0016] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention is described clearly and completely below. Obviously, the described embodiments are part of the embodiments of the present invention, but 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.

[0017] The long-distance gas pipeline design and evaluation system based on FDAHP includes an input interface module, an output interface module and a background calculation module. The input interface module includes a judgment matrix input module and an indicator membership input module. The output interface module includes a consistency check module, an indicator weight calculation module and a sub-target matrix module. The sub-target matrix corresponds to the judgment matrix one by one.

[0018] The method for designing and evaluating a long-distance gas pipeline based on FDAHP uses the long-distance gas pipeline design and evaluation system based on FDAHP, and the background computing module runs the method. The method includes constructing an evaluation index system, establishing a fuzzy Delphi hierarchical analysis model and setting evaluation levels, constructing a judgment matrix, determining index weights, using the fuzzy Delphi hierarchical analysis method to determine index membership, obtaining a fuzzy comprehensive evaluation result vector, analyzing the result vector, and obtaining a long-distance gas pipeline process design evaluation result.

[0019] The fuzzy Delphi analytic hierarchy model includes the target layer, the criterion layer and the indicator layer from top to bottom; Setting the evaluation level includes setting the comprehensive benefits into four levels: A, B, C, and D, which respectively represent the best comprehensive benefits, good comprehensive benefits, poor comprehensive benefits, and extremely poor comprehensive benefits.

[0020] The target layer is to optimize the comprehensive benefits of the gas transmission pipeline, the criterion layer includes high process efficiency, high safety and reliability, and low investment cost. In the indicator layer, the indicators with high process efficiency include the first station pressure, design pressure, pipeline diameter, pipeline wall thickness, outlet temperature, pressure drop, and number of compressor stations; the indicators with high safety and reliability include production safety level, hidden danger control, hidden danger identification, emergency response, material applicability, environmental load and human load; the indicators with low investment cost include pipeline construction cost, compressor station construction cost, operation and operation cost, and pipeline maintenance cost.

[0021] Constructing the judgment matrix includes constructing the criterion layer judgment matrix and constructing the indicator layer judgment matrix; Constructing the criterion layer judgment matrix includes calculating the importance between each criterion of the criterion layer and giving the scale value between two criteria; Constructing the indicator layer judgment matrix includes calculating the importance between indicators under the same criterion layer and giving the scale value between two indicators; The scale value includes 9 levels.

[0022] Determine the indicator weights including, S1 calculates the judgment matrix The product of the elements of each row of : ; ; In the formula, is the judgment matrix Middle Line The elements of the column, is the judgment matrix The order of is the multiplication symbol, It is Product of row elements.

[0023] Determine the indicator weights including, S2 calculation of square root : .

[0024] Determine the indicator weights including: S3 Perform normalization: ; In the formula, For the The indicator weight of the row.

[0025] Determining the indicator weights includes: S4 calculating the maximum characteristic root of the judgment matrix : .

[0026] Determine the indicator weights including, S5 solves the consistency indicator , check the consistency of the matrix: ; Find the consistency ratio of the matrix : ; In the formula, is the average random consistency index; when , the matrix is ​​considered to have passed the consistency test.

[0027] The present invention discloses a long-distance gas pipeline design evaluation and method based on FDAHP (FDAHP: fuzzy Delphi hierarchical analysis). The fuzzy Delphi hierarchical analysis method is used to determine the importance of various indicators through MATLAB software, calculate the weights, determine the key factors affecting the design of the pipeline, and perform a comprehensive evaluation based on the membership degree, so that the evaluation results are more objective. A long-distance gas pipeline process design optimization system based on the fuzzy Delphi hierarchical analysis method is proposed, including a parameter input interface, a result output interface and a background calculation module. The system can receive parameters such as judgment matrix and membership degree input by the user. The background calculation module uses the fuzzy Delphi hierarchical analysis method for calculation, including the steps of constructing a judgment matrix, calculating weights, determining membership degree and synthesizing fuzzy comprehensive evaluation results. The consistency index, weight and sub-target matrix and other results are obtained through the background calculation, thereby realizing the quantitative evaluation and optimization of the comprehensive benefits of the long-distance gas pipeline process design. The steps of the long-distance gas pipeline design evaluation method based on FDAHP are as follows: Figure 1 As shown in the figure, it includes (1) constructing a long-distance gas pipeline evaluation index system and establishing a fuzzy Delphi hierarchical analysis model. (2) Setting the evaluation level, the comprehensive benefits can be divided into four levels: A, B, C, and D, representing the best comprehensive benefits, good comprehensive benefits, poor comprehensive benefits, and extremely poor comprehensive benefits, respectively. (3) Determining the judgment matrix and performing a consistency test; if the test passes, proceed to step (4); if the test fails, modify the judgment matrix and re-perform the consistency test until the test passes; calculate the index weight. (4) Determine the underlying index membership. (5) Synthesize the fuzzy comprehensive evaluation result vector. (6) Analyze the result vector.

[0028] The embodiment analyzes the comprehensive benefit case of a long-distance gas pipeline process design. The existing natural gas source E in a certain province cannot meet the gas demand in 2027 and beyond. It is planned to build an LNG receiving station and a supporting external transmission pipeline with a length of about 350km. It is necessary to coordinate the natural gas resources and the gas demand of market users in accordance with the principle of "overall planning, step-by-step implementation, combination of long-term and short-term, and moderate advancement" to design a technically feasible and economically reasonable external transmission pipeline solution.

[0029] According to the characteristics of long-distance gas pipelines, following the principles of constructing an evaluation index system, a preliminary evaluation index system for the process design of long-distance gas pipelines was proposed through literature research, theoretical analysis, expert survey and consultation, and experience selection methods; then the Delphi method was used to screen the evaluation indicators through multiple rounds of expert questionnaires, and finally the evaluation index system for the process design of long-distance gas pipelines was constructed. This process ensures the scientificity and practicality of the index system, and provides a reliable tool for comprehensively evaluating the process design of long-distance gas pipelines. The best comprehensive benefit of gas pipeline is taken as the target layer; the main factors affecting the process design of long-distance gas pipeline are "high process efficiency", "high safety and reliability", and "low capital investment", which are taken as the criterion layer; the factors affecting high process efficiency are the first station pressure, design pressure, pipeline diameter, pipeline wall thickness, outlet temperature, pressure ratio and number of compressor stations; the factors affecting high safety and reliability are production safety level, hidden danger control, hidden danger identification, emergency response, material applicability, environmental load, and human load; the factors affecting low investment cost are pipeline construction cost, compressor station construction cost, operation and operation cost, and pipeline maintenance cost. The above influencing factors are taken as the indicator layer to construct the evaluation index system of long-distance gas pipelines, and establish the fuzzy Delphi hierarchical analysis model. Figure 2 shown.

[0030] The process design evaluation of long-distance gas pipelines is relatively complex, and the importance of each level cannot be directly quantified. In order to objectively and accurately evaluate the best comprehensive benefits of pipeline design, the Delphi method is used to invite authoritative and representative experts in pipeline design, safety analysis, pipe materials, etc. to conduct multiple rounds of questionnaires and summarize opinions, reduce the subjective influence of individual experts, and improve the objectivity of the evaluation results.

[0031] According to the actual project, the factor that has the greatest impact on the comprehensive benefits of long-distance gas pipelines is process efficiency, followed by investment costs. The 1-9 level scaling method is used as shown in Table 1, and the criterion layer judgment matrix is ​​constructed as shown in Table 2. The weights of each criterion are calculated to be 0.5396, 0.1634, and 0.2970 respectively.

[0032] Table 1 Scale values ​​from 1 to 9 and their meanings ; Table 2 Criteria layer judgment matrix ; According to the actual project, the factors that have the greatest impact on the process efficiency of long-distance gas pipelines are pipeline diameter, design pressure and pipeline wall thickness, followed by outlet temperature, and the factors with the smallest impact are pressure drop, number of compressor stations and first station pressure. Using the 1-9 level scaling method, the indicator layer B1 judgment matrix is ​​constructed as shown in Table 3.

[0033] Table 3 Indicator layer B1 judgment matrix ; Among the factors that affect safety and reliability, hidden danger identification can effectively reduce the possibility of danger by predicting potential risk points in advance and taking corresponding measures. Compared with other influencing factors, hidden danger identification is relatively important; materials are the basis of gas pipeline engineering construction, and their quality is directly related to the safety and reliability of the project. Therefore, the adaptability of materials is relatively important. Using the 1-9 level scaling method, the indicator layer B2 judgment matrix is ​​constructed as shown in Table 4.

[0034] Table 4 Indicator layer B2 judgment matrix ; According to the "pipeline construction cost", "compressor station construction cost", "pipeline operation cost" and "pipeline maintenance cost", the impact of the sub-goal "low investment cost" is evaluated, and analyzed and scored according to the actual project situation. It is believed that "pipeline investment cost" and "compressor station investment cost" are equally important, and "operation cost" and "pipeline maintenance cost" are less important than them. Using the 1-9 level scaling method, the indicator layer B3 judgment matrix is ​​constructed as shown in Table 5.

[0035] Table 5 Indicator layer B3 judgment matrix ; Since it is difficult to obtain the specific fuzzy distribution function of each evaluation indicator in the above indicator layer, the Delphi method is used to determine the membership degree of each evaluation indicator as shown in Table 6.

[0036] Table 6 Membership degree of each evaluation index ; Since the matrix order exceeds the fourth order, the calculation process is complicated and inefficient. Therefore, the present invention uses APP Designer in MATLAB software to develop a long-distance gas pipeline design evaluation system based on FDAHP to evaluate the comprehensive benefits of the long-distance gas pipeline process design. The long-distance gas pipeline design evaluation system based on FDAHP mainly includes a parameter input interface and a result output interface. By inputting the judgment matrix, membership degree and other parameters in the input interface, the consistency index CI, whether the consistency test is passed, the indicator weight and the calculation results of the sub-target matrix can be obtained through background calculation. The calculation results of the consistency test of the judgment matrix B1, the weight and the sub-target matrix R1 are shown as follows. Figure 3 shown. Figure 3 In , the order of the matrix can be selected according to the number of indicators; the number of evaluation levels can also be selected according to the evaluation level. The weights of the indicator layer judgment matrix B2 and B3 are determined through the above calculations. In order to make the weight distribution more intuitive, a histogram is used to display the weights, such as Figure 4The sub-goal matrices of judgment matrices B2 and B3 are shown in Table 7.

[0037] Table 7 Sub-goal matrices of judgment matrices B2 and B3 ; With CI < 0.10, it can be considered that the B1 index layer has passed the consistency test relative to the criterion layer. It can be seen that in the design of long-distance gas pipelines, in order to make the pipeline process more efficient, the focus should be placed on the design pressure and pipeline diameter. Once an accident occurs in a natural gas pipeline, it often causes huge economic losses and casualties. Figure 4 Analysis shows that safety and reliability are important factors affecting the design of long-distance gas pipelines. Hidden danger identification is particularly important in safety risks. Therefore, in the design of natural gas pipelines, hidden danger identification devices should be installed to effectively predict the occurrence of hidden dangers and better ensure pipeline safety. In pipeline design, cost investment is the focus of building a complete pipeline. Controlling costs within a certain range is beneficial to the economic benefits of the pipeline. The cost of pipeline investment and compressor station investment must be controlled in the cost. Figure 4 From Table 7, we can know the underlying sub-goal matrix R, and the membership of the total goal is: (0.5396, 0.1634, 0.297) × R = (0.4065, 0.2400, 0.2600, 0.0935); in ; Depend on Figure 5 It can be seen that according to this method, the percentages of the possibility that the comprehensive benefits of gas pipelines belong to the four levels of A, B, C, and D are 40%, 24%, 26%, and 9% respectively. Among them, the possibility that the comprehensive benefits of pipelines belong to level A is the highest, making the comprehensive benefits of long-distance gas pipelines in the best state.

[0038] Taking the B1 judgment matrix of the index layer as an example, when using the long-distance gas transmission pipeline design evaluation system based on FDAHP, the first station pressure, design pressure, pipeline diameter, pipeline wall thickness, outlet temperature, pressure drop, and the importance parameters of the number of compressor stations are input in the input interface. The above formula is written into code and run in the system backend calculation. Through the "consistency calculation" button of the output interface module, the background calculation can be performed to obtain the consistency index CI; according to the different orders of the matrix, the system background automatically searches for the consistency index RI and displays it in the output interface module; according to the background formula calculation, the consistency ratio of the matrix is ​​obtained, and whether it passes the consistency test is displayed in the output interface module. If it passes the consistency test, the output interface will display the "yes" sign; if it fails the consistency test, it will display the "no" sign, which proves that the judgment matrix in the input interface module is wrong or does not conform to reality. If the consistency check is passed, click the "Weight Calculation Results" button to get the calculation results of the weights of each indicator. The weight of the first station pressure is 0.04796, the weight of the design pressure is 0.3042, the weight of the pipeline diameter is 0.3042, the weight of the pipeline wall thickness is 0.1428, the weight of the outlet temperature is 0.09084, the weight of the pressure drop is 0.05506, and the weight of the number of compressor stations is 0.05506. Then, according to the affiliation of each evaluation indicator, the quantitative evaluation of each evaluation indicator is realized, the affiliation of each indicator layer is determined, and the affiliation of each indicator layer is entered in the input interface module. The sub-target matrix results can be obtained through background calculation. According to the comprehensive calculation of each sub-target matrix, the overall target evaluation result can be obtained.

[0039] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some or all of the technical features may be replaced by equivalents, and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. The long-distance gas pipeline design and evaluation system based on FDAHP is characterized by: It includes an input interface module, an output interface module and a background calculation module. The input interface module includes a judgment matrix input module and an indicator membership input module. The output interface module includes a consistency verification module, an indicator weight calculation module and a sub-target matrix module. The sub-target matrix corresponds to the judgment matrix one by one.

2. The long-distance gas pipeline design evaluation method based on FDAHP is characterized by: Using the FDAHP-based long-distance gas pipeline design evaluation system as described in claim 1, the background calculation module runs the method, which includes constructing an evaluation index system, establishing a fuzzy Delphi hierarchical analysis model and setting evaluation levels, constructing a judgment matrix, determining index weights, using the fuzzy Delphi hierarchical analysis method to determine the index membership, obtaining a fuzzy comprehensive evaluation result vector, analyzing the result vector, and obtaining a long-distance gas pipeline process design evaluation result.

3. The long-distance gas pipeline design evaluation method based on FDAHP according to claim 2 is characterized in that: The fuzzy Delphi analytic hierarchy model includes the target layer, the criterion layer and the indicator layer from top to bottom; Setting the evaluation level includes setting the comprehensive benefits into four levels: A, B, C, and D, which respectively represent the best comprehensive benefits, good comprehensive benefits, poor comprehensive benefits, and extremely poor comprehensive benefits.

4. The long-distance gas pipeline design evaluation method based on FDAHP according to claim 3 is characterized in that: The target layer is to optimize the comprehensive benefits of the gas transmission pipeline, the criterion layer includes high process efficiency, high safety and reliability, and low investment cost. In the indicator layer, the indicators with high process efficiency include the first station pressure, design pressure, pipeline diameter, pipeline wall thickness, outlet temperature, pressure drop, and number of compressor stations; the indicators with high safety and reliability include production safety level, hidden danger control, hidden danger identification, emergency response, material applicability, environmental load and human load; the indicators with low investment cost include pipeline construction cost, compressor station construction cost, operation and operation cost, and pipeline maintenance cost.

5. The long-distance gas pipeline design evaluation method based on FDAHP according to claim 3 is characterized in that: Constructing the judgment matrix includes constructing the criterion layer judgment matrix and constructing the indicator layer judgment matrix; Constructing the criterion layer judgment matrix includes calculating the importance between each criterion of the criterion layer and giving the scale value between two criteria; Constructing the indicator layer judgment matrix includes calculating the importance between indicators under the same criterion layer and giving the scale value between two indicators; The scale value includes 9 levels.

6. The long-distance gas pipeline design evaluation method based on FDAHP according to claim 2 is characterized in that: Determine the indicator weights including, S1 calculates the judgment matrix The product of the elements of each row of : ； ； In the formula, is the judgment matrix Middle Line The elements of the column, is the judgment matrix The order of is the multiplication symbol, It is Product of row elements.

7. The FDAHP-based long-distance gas pipeline design evaluation method according to claim 6, characterized in that: Determine the indicator weights including, S2 calculation of square root : 。 8. The FDAHP-based long-distance gas pipeline design evaluation method according to claim 7, characterized in that: Determine the indicator weights including: S3 Perform normalization: ； In the formula, For the The indicator weight of the row.

9. The FDAHP-based long-distance gas pipeline design evaluation method according to claim 8, characterized in that: Determining the indicator weights includes: S4 calculating the maximum characteristic root of the judgment matrix : 。 10. The FDAHP-based long-distance gas pipeline design evaluation method according to claim 9, characterized in that: Determine the indicator weights including, S5 solves the consistency indicator , check the consistency of the matrix: ； Find the consistency ratio of the matrix : ； In the formula, is the average random consistency index; when , the matrix is ​​considered to have passed the consistency test.

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