Method and system for comprehensively evaluating pipeline transportation energy consumption of long-distance natural gas transportation pipeline

Abstract

The invention belongs to the technical field of pipeline energy consumption, and particularly relates to a comprehensive evaluation method and system for pipeline transportation energy consumption of a long-distance natural gas pipeline, firstly, relatively important evaluation indexes of the pipeline transportation energy efficiency of the long-distance natural gas pipeline are optimized through a Delphi method, the accuracy and comprehensiveness of evaluation results are ensured, and then the evaluation results of the pipeline transportation energy consumption of the long-distance natural gas pipeline are obtained through combination of an entropy weight method and TOPSIS. The natural gas long-distance pipeline energy efficiency evaluation method based on the entropy weight-TOPSIS method is established, the energy consumption reference score lines of the natural gas pipeline under different transportation steps are obtained and compared with the target working condition, and the advantages and disadvantages of production and operation under different pipeline transportation steps can be evaluated more scientifically, objectively and accurately.

Description

Technical Field

[0001] The present invention belongs to the technical field of pipeline energy consumption, and in particular relates to a comprehensive evaluation method and system for pipeline transportation energy consumption of a long-distance natural gas pipeline. Background Art

[0002] At present, natural gas pipelines use a single indicator such as gas consumption percentage or gas unit consumption to evaluate the energy efficiency level of pipeline operation. However, in actual operation, both gas consumption percentage and gas unit consumption increase exponentially with the increase of pipeline transmission volume. Therefore, the use of a single indicator such as gas consumption percentage or gas unit consumption cannot scientifically, objectively and accurately evaluate the advantages and disadvantages of production operation under different pipeline transmission volume steps, which affects the formulation of the optimal operation plan and restricts the efficient operation of the pipeline. Summary of the invention

[0003] In view of the above problems, on the one hand, the present invention proposes a comprehensive evaluation method for the energy consumption of long-distance natural gas pipelines, the method comprising:

[0004] The Delphi method was used to screen and obtain several energy consumption evaluation indicators of pipeline transportation energy consumption;

[0005] Screening of operating data of natural gas pipelines;

[0006] The entropy weight method is used to calculate the weight of each energy consumption evaluation index, and each energy consumption evaluation index is weighted according to the calculation results;

[0007] The energy consumption benchmark scores of each energy consumption evaluation index under different output steps are calculated using the TOPSIS method and the weighted results of each energy consumption evaluation index.

[0008] The energy consumption benchmark score line is compared with the target operating condition data, and the pros and cons of the energy consumption of the long-distance natural gas pipeline operation are evaluated based on the comparison result.

[0009] Furthermore, the Delphi method is used to screen and obtain several energy consumption evaluation indicators of pipeline energy consumption, including the following steps:

[0010] Select multiple expert groups with professional knowledge and experience in natural gas pipeline energy consumption;

[0011] Prepare a questionnaire covering issues related to energy consumption in natural gas pipeline transportation;

[0012] Sending said questionnaire to the expert group to be filled in anonymously;

[0013] Collect the completed questionnaires for summary analysis and provide feedback to the expert group;

[0014] The expert group conducts investigation and analysis based on the analysis results, and fills in the questionnaire again based on the results of the investigation and analysis, forming a cycle;

[0015] After the opinions of the expert group members on the energy consumption of natural gas pipeline transportation are consistent in the final questionnaire results, several energy consumption evaluation indicators for pipeline transportation energy consumption are selected.

[0016] Furthermore, the energy consumption evaluation indexes include self-consumption of gas, gas consumption-to-output ratio, unit turnover operation energy consumption, compressor shaft power and compressor variable efficiency.

[0017] Furthermore, screening the operating data of the natural gas pipeline includes: removing null value data and removing erroneous data in the operating data;

[0018] The method adopted for eliminating erroneous data is to eliminate outliers based on the statistical characteristics presented by most of the running data; the statistical characteristics include the first quartile, the median, the third quartile and the interquartile range.

[0019] Furthermore, the method of calculating the weight of each energy consumption evaluation index by using the entropy weight method includes the following steps:

[0020] Select n samples and m energy consumption evaluation indicators, then x ij is the value of the jth energy consumption evaluation index of the i-th sample;

[0021] Use normalization method to homogenize various energy consumption evaluation indicators;

[0022] Calculate the proportion p of the i-th sample under the j-th energy consumption evaluation index to the index ij ;

[0023] According to the specific gravity p ij Calculate the entropy value e of the jth energy consumption evaluation index j ;

[0024] According to the entropy value e j Calculate the information entropy redundancy d j ;

[0025] According to the information entropy redundancy d j Calculate the weight ω of each energy consumption evaluation index j .

[0026] Furthermore, using the TOPSIS method and the weighted result of each energy consumption evaluation index to calculate the energy consumption benchmark score line under different output steps of each energy consumption evaluation index includes the following steps:

[0027] Determine the ideal solution and negative ideal solution of each energy consumption evaluation index;

[0028] The weighted results of each energy consumption evaluation index are used to calculate the distance between each evaluation target and the ideal solution and the negative ideal solution;

[0029] The energy consumption score values ​​under different output steps are calculated according to the distance, and the comprehensive energy efficiency benchmark score lines under different output steps are drawn according to the energy consumption score values.

[0030] Furthermore, the advantages and disadvantages of the energy consumption of long-distance natural gas pipeline operation are evaluated based on the comparison results:

[0031] The plans corresponding to the working conditions that are higher than or equal to the energy consumption benchmark score line will be adopted, and the plans corresponding to the working conditions that are lower than the energy consumption benchmark score line will be eliminated.

[0032] On the other hand, the present invention proposes a comprehensive evaluation system for energy consumption of long-distance natural gas pipelines, the system comprising:

[0033] An index screening unit, used to screen and obtain several energy consumption evaluation indexes of pipeline transportation energy consumption by using the Delphi method;

[0034] A data screening unit, used to screen the operating data of the natural gas pipeline;

[0035] The first calculation unit calculates the weight of each energy consumption evaluation index by using the entropy weight method, and assigns weight to each energy consumption evaluation index according to the calculation result;

[0036] The second calculation unit is used to calculate the energy consumption benchmark score line of each energy consumption evaluation index under different output steps by using the TOPSIS method and the weighted result of each energy consumption evaluation index;

[0037] The evaluation unit is used to compare the energy consumption benchmark score line with the target operating condition data, and evaluate the pros and cons of the energy consumption of the long-distance natural gas pipeline operation according to the comparison result.

[0038] In a third aspect, the present invention provides an electronic device, comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus;

[0039] Memory for storing computer programs;

[0040] The processor is used to implement the comprehensive evaluation method for energy consumption of long-distance natural gas pipeline transportation when executing the program stored in the memory.

[0041] In a fourth aspect, the present invention proposes a computer-readable storage medium storing a computer-readable program, which, when executed, executes the method for comprehensive evaluation of energy consumption of long-distance natural gas pipelines.

[0042] Beneficial effects of the present invention:

[0043] The present invention firstly selects the more important evaluation index of the long-distance natural gas pipeline transmission energy efficiency through the Delphi method, which can ensure the accuracy and comprehensiveness of the evaluation results, and then combines the entropy weight method with TOPSIS to establish a natural gas long-distance pipeline energy efficiency evaluation method based on the entropy weight-TOPSIS method, and obtains the energy consumption benchmark score line under different flow steps of the natural gas pipeline, and compares it with the target working condition, which can more scientifically, objectively and accurately evaluate the pros and cons of production operation under different pipeline flow steps. In the process of eliminating erroneous data, the present invention analyzes the characteristics presented by most of the previous operation data and eliminates outliers. The method is simple and easy to implement, and can ensure data quality to a certain extent. Compared with the method of manually checking errors and filtering report data according to the possible range of operating parameters, the method of eliminating erroneous data is more efficient and can ensure data quality.

[0044] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures pointed out in the description, claims and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0046] Figure 1 A method flow chart of a comprehensive evaluation method for energy consumption of long-distance natural gas pipeline transportation proposed by the present invention is shown;

[0047] Figure 2 The box plot of the absolute error of the compressor power at the WKC1 station in an embodiment of the present invention is shown;

[0048] Figure 3 The energy consumption benchmark score line and the simulated working condition score diagram under different transmission rates of the Central Asian Natural Gas Pipeline AB Line in the embodiment of the present invention are shown;

[0049] Figure 4 The energy consumption benchmark score line and the simulated working condition score diagram under different transmission rates of the Central Asia Natural Gas Pipeline C Line in the embodiment of the present invention are shown;

[0050] Figure 5 A schematic diagram of a comprehensive evaluation system for energy consumption of long-distance natural gas pipeline transportation in an embodiment of the present invention is shown;

[0051] Figure 6An exemplary structural diagram of an electronic device for comprehensive evaluation of energy consumption of long-distance natural gas pipelines proposed in an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0052] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0053] In view of the current unscientific and inaccurate evaluation of the energy efficiency of natural gas pipelines, which affects the efficient operation of pipelines. The present invention proposes a comprehensive evaluation method for the energy consumption of long-distance natural gas pipelines, which evaluates the comprehensive energy efficiency of natural gas pipelines based on big data analysis and entropy weight method. Five evaluation indicators, including self-consumption gas volume, gas consumption and output volume ratio, gas unit consumption, shaft power, and compressor variable efficiency, are determined through index screening. The weights of each indicator are obtained by using the entropy weight method based on the collated historical data. The TOPSIS evaluation method is used to score each historical operation scheme under different output steps. The near-ideal point multi-objective decision-making method is introduced to define the ideal solution and negative ideal solution of the decision problem. Then, a scheme is found in the feasible scheme so that it is closest to the ideal solution and farthest from the negative ideal solution, so as to obtain the comprehensive energy efficiency score line under different output steps; at the same time, the average score of the top 20% of the scores of the historically connected working conditions is selected as the energy consumption benchmark score line under the output step, and the energy consumption benchmark score line under different output steps of the AB / C line of the natural gas pipeline is obtained, which provides scientific support for the comparison and evaluation of the optimization operation technical scheme.

[0054] In order to more clearly illustrate the execution process of the above method, the Central Asian natural gas pipeline is taken as an example to further illustrate the above method. The Central Asian natural gas pipeline is an important energy strategic channel. In the prior art, the gas consumption ratio or gas unit consumption is generally used as a single indicator to evaluate the pipeline transmission energy efficiency level. The present invention adopts a new long-distance natural gas pipeline transmission energy consumption comprehensive evaluation method. The specific technical solution is as follows: Figure 1 As shown, the following steps are included:

[0055] S1: Several energy consumption evaluation indicators of pipeline transportation energy consumption are screened according to the Delphi method;

[0056] It should be noted that in the process of screening the evaluation index, since single factors such as absolute self-consumption gas and gas consumption and output ratio cannot accurately reflect the energy consumption of the pipeline under different output steps, it is necessary to screen the evaluation index. The screening of the energy consumption evaluation index in the present invention follows the following principles:

[0057] ① The composition of the comprehensive evaluation system must be developed around the purpose of comprehensive evaluation, so that the evaluation conclusion can truly reflect the evaluation intention;

[0058] ②The comprehensive evaluation system must reflect all aspects of the issue being evaluated.

[0059] ③ Each energy consumption evaluation indicator of the comprehensive evaluation system must be operational to ensure that accurate data can be collected in a timely manner.

[0060] ④ The comprehensive evaluation system must be fair and comparable for each evaluation target, and cannot contain indicators with obvious "bias".

[0061] ⑤ The entire comprehensive evaluation system, from its element composition to its structure, and from the calculation content to the calculation method of each energy consumption evaluation indicator, must be scientific, reasonable and accurate.

[0062] ⑥ Establishing a hierarchical structure of the comprehensive evaluation system can create conditions for further factor analysis.

[0063] ⑦ Different comprehensive evaluation methods have different requirements for the evaluation index system. When actually constructing an evaluation index system, it is sometimes necessary to determine the method first and then construct the index.

[0064] Based on the above principles, the present invention adopts the Delphi method to screen the energy consumption evaluation indicators. Before screening, it is necessary to clearly define the problems or topics that require expert consensus. Ensure that the problems are clear so that experts can understand and provide opinions, which specifically includes the following steps:

[0065] Select the expert group: Select a group of experts with professional knowledge and experience in natural gas pipeline energy consumption, who can provide valuable insights and suggestions on the issue of pipeline energy consumption;

[0066] Formulate a questionnaire: Prepare a questionnaire containing a series of statements or questions related to the energy consumption of natural gas pipeline transportation. The questions can be open-ended or closed-ended, and experts can answer them based on their knowledge and opinions;

[0067] Anonymous surveys: Sending questionnaires to panelists and ensuring that responses are anonymous ensures that the experts are not influenced by others and encourages them to express their opinions freely.

[0068] Summary and feedback: Collect the experts' answers, summarize and statistically analyze the results, and feed the results back to the expert group. The results can be presented through averages, medians, or other indicators.

[0069] Iterative loop: Based on the feedback from experts, a series of cyclical surveys are conducted. In each cycle, summaries and statistics of the previous survey results can be provided, and experts are encouraged to reassess and adjust their views.

[0070] Reaching consensus: After multiple cycles, the experts’ opinions may converge. When a certain degree of consensus is reached, the final result can be determined or a decision can be reached.

[0071] These steps may be adapted to the specific situation, and the flexibility of the Delphi method allows it to be adjusted as needed. Overall, the Delphi method provides an effective decision support tool through circular feedback and discussion among experts to gradually reach consensus.

[0072] In order to more clearly illustrate the implementation steps of the evaluation method of the present invention, based on the research on energy efficiency evaluation of natural gas long-distance pipelines in the prior art, this embodiment takes the Central Asian natural gas pipeline as an example, analyzes the evaluation target and constructs energy consumption evaluation indicators as shown in Table 1:

[0073] Table 1

[0074]

[0075]

[0076] For the evaluation system, it is necessary to make it as simple as possible and ensure its accuracy. Therefore, when screening the pre-selected indicators, the number of indicators should be reduced as much as possible, and important indicators should be selected for analysis and evaluation. In actual application, it is necessary to focus on the "main" evaluation indicators and use them in combination with a small number of "secondary" evaluation indicators, so that the indicators are organically combined and the main purpose is clear. Combined with the actual operation of the Central Asian natural gas pipeline, the Delphi method was used to select the indicators shown in Table 2 as evaluation indicators.

[0077] Table 2

[0078] Serial number index 1 Self-consumption of gas 2 Unit turnover operation energy consumption (gas consumption) 3 Gas consumption and output ratio 4 Compressor shaft power (shaft power) 5 Compressor variable efficiency

[0079] S2: Screening the operating data of the natural gas pipeline;

[0080] Obtain the operating data of the natural gas pipeline, including self-consumption of gas, unit weekly operating energy consumption, gas consumption-to-transmission ratio, compressor shaft power and compressor variable efficiency, and filter the acquired data. Data filtering includes eliminating null value data and erroneous data.

[0081] Null value data refers to data with null values ​​in a set of operating data. Such data will be eliminated.

[0082] Error data refers to data that exceeds the allowable error range, such as data that does not satisfy the calculation of a specific formula. Taking the definition of the absolute error and relative error of the characteristic parameters of the compressor unit as an example, the absolute error Error and relative error Error of the characteristic parameters of the compressor unit are further explained. rel The calculation is done using the following formula:

[0083] Error = pro-pro′ (1)

[0084]

[0085] In formulas (1) and (2), pro represents the actual characteristic parameter of the compressor; pro′ represents the characteristic parameter of the compressor calculated according to the characteristic curve provided by the manufacturer, referred to as “factory characteristic parameter”;

[0086] Since some recording errors are unavoidable in the actual operation report, these erroneous data need to be eliminated before the index calculation and energy efficiency evaluation. The method adopted in the embodiment of the present invention is to eliminate outliers based on the characteristics presented by most of the operation data. The advantage of this method is that it is simple and easy to implement, and it can guarantee the data quality to a certain extent. Although this method has certain disadvantages, it cannot guarantee that the eliminated points are definitely wrong, or that the remaining points are definitely correct; and when most of the data are wrong, this method will eliminate the correct points. However, since the Central Asia pipeline in the present invention has been running for a period of time, if there are a large number of operating parameter measurement errors, they will definitely be discovered, so the use of this method in the present invention to eliminate erroneous data can guarantee data quality to a greater extent.

[0087] The statistical characteristics referred to in this embodiment for eliminating erroneous data include:

[0088] First quartile: the 25th percentile of all values ​​in the data sample arranged from small to large;

[0089] Median: The 50th percentile number after all values ​​in the data sample are arranged from small to large;

[0090] The third quartile: the 75th percentile of all values ​​in the data sample arranged from small to large;

[0091] Interquartile range: The distance between the first quartile and the third quartile, denoted as IQR (Inter Quartile Range).

[0092] The reference indicators for eliminating erroneous data include the absolute error and relative error of shaft power, and the absolute error and relative error of compressor efficiency. Data points that exceed the range are considered to be potential error points and are eliminated. In order to more clearly illustrate the impact of the above indicators, this embodiment takes the absolute error of power as an example and draws a box diagram of the absolute error of compressor power at WKC1 station as shown in the figure. Figure 2 As shown, the five vertical lines in the figure represent from left to right:

[0093] A represents the smallest data point that is less than 1.5 times the IQR from the first quartile; B represents the first quartile; C represents the median; D represents the third quartile; and E represents the largest data point that is less than 1.5 times the IQR from the third quartile.

[0094] Points outside the two lines A and E are outliers and are considered potential error points, such as Figure 2 shown.

[0095] S3: Calculate the weight of each energy consumption evaluation index using the entropy weight method, and assign weights to each energy consumption evaluation index according to the calculation results;

[0096] The entropy weight method is a mathematical method that calculates a comprehensive index based on the amount of information provided by various factors. The disorder of information can be represented by the entropy value. The smaller the value, the smaller the disorder of the system. The greater the amount of information, the greater the weight, and vice versa. Using the entropy weight method to calculate weights can avoid human interference, is more objective, and closer to the actual situation.

[0097] The specific steps of this method are:

[0098] (1) Select n samples and m energy consumption evaluation indicators, then x ij is the value of the jth energy consumption evaluation index of the i-th sample (i=1, 2, ..., n; j=1, 2, ..., m);

[0099] (2) Normalization of indicators: homogenization of heterogeneous indicators.

[0100] Since the measurement units of various energy consumption evaluation indicators are not unified, before calculating the comprehensive indicators, each energy consumption evaluation indicator must be standardized, that is, the absolute value of the energy consumption evaluation indicator is converted into a relative value, and x ij =|x ij |, thus solving the homogenization problem of various qualitative index values. Moreover, since the negative values ​​of positive and negative indicators have different meanings (the higher the positive index value, the better, and the lower the negative index value, the better), different algorithms should be used for data standardization for high and low indicators. The specific methods are as follows:

[0101] Positive indicators:

[0102]

[0103] Negative indicators:

[0104]

[0105] Then x ij is the value of the jth energy consumption evaluation index of the i-th sample (i=1, 2, ..., n; j=1, 2, ..., m);

[0106] For convenience, the normalized data x ij Still recorded as x ij .

[0107] (3) Calculate the proportion p of the i-th sample under the j-th energy consumption evaluation index to the index ij :

[0108]

[0109] (4) According to the specific gravity p ij Calculate the entropy value e of the jth energy consumption evaluation index j :

[0110]

[0111]

[0112] k is the penalty factor of entropy;

[0113] (5) According to the entropy value e j Calculate the information entropy redundancy d j ;

[0114] d j =1-e j (8)

[0115] (6) Calculate the weight ω of each energy consumption evaluation index according to the information entropy redundancy j :

[0116]

[0117] S4: Use the TOPSIS method to calculate the energy consumption benchmark score line for each energy consumption evaluation indicator under different output steps; the basic principle of the TOPSIS method is to rank the evaluation target by detecting the distance between it and the optimal solution and the worst solution. If the evaluation target is closest to the optimal solution and farthest from the worst solution, it is the best; otherwise it is not optimal. The values ​​of each indicator of the optimal solution reach the optimal value of each evaluation indicator. The values ​​of each indicator of the worst solution reach the worst value of each evaluation indicator. Through the normalized data normalization matrix, find the optimal target and the worst target among multiple targets, and the optimal target and the worst target are represented by the ideal solution and the negative ideal solution respectively;

[0118] The distances between each evaluation target and the ideal solution and the negative ideal solution are calculated respectively to obtain the closeness of each evaluation target to the ideal solution. The targets are sorted according to the closeness to the ideal solution, which is used as the basis for evaluating the quality of the targets.

[0119] The closeness value is between 0 and 1. The closer the value is to 1, the closer the corresponding evaluation target is to the optimal level; conversely, the closer the value is to 0, the closer the evaluation target is to the worst level.

[0120] The specific steps of this method are:

[0121] (1) Matrix forward conversion: All energy consumption evaluation indicators are uniformly forward converted, that is, the extremely small, intermediate and interval indicators are converted into extremely large indicators.

[0122] In one embodiment of the present invention, the formula for converting a very small index to a very large index is max-x. If all elements are positive numbers, 1 / x can also be used.

[0123] In one embodiment of the present invention, the intermediate index is transformed using the following method:

[0124] Let {x i} is a set of intermediate indicator sequences, and the best data is x best , the formula for the positive transformation of the intermediate index is as follows:

[0125]

[0126] In one embodiment of the present invention, the interval-type index is converted using the following method:

[0127] Let {x i} is a set of interval indicator sequences, and the best interval is [a, b]. The formula for the positive conversion of interval indicators is as follows:

[0128]

[0129] (2) Forward matrix normalization: The purpose of normalization is to eliminate the influence of different dimensions;

[0130] Assuming there are n objects to be evaluated, the forward matrix composed of m evaluation indicators is as follows:

[0131]

[0132] Then the standardized matrix is ​​recorded as Z, and each element of Z is:

[0133]

[0134] That is, (the sum of the squares of the elements in the column under each element / root sign) to obtain the standardized matrix Z:

[0135]

[0136] (3) Calculate the score and normalize it

[0137] Define the maximum value:

[0138] Z + =(max{z 11 ,z 21 ,…,z n1},max{z 12 ,z 22 ,…,z n2},…,max{z 1m ,z 2m ,…,z nm})(15)

[0139] Define the minimum value:

[0140] min{z 11 ,z 21 ,…,z n1},min{z 12 ,z 22 ,…,z n2},…,min{z 1m ,z 2m ,…,z nm}(16)

[0141] Define the distance between the i-th (i=1,2,…,n) energy consumption evaluation index and the maximum value

[0142]

[0143] Among them, ω j is the weight of each energy consumption evaluation index calculated in step S4;

[0144] Define the distance between the i-th (i=1,2,…,n) evaluation target and the minimum value

[0145]

[0146] The unnormalized score S of the i-th evaluation target can be calculated i :

[0147]

[0148] In an embodiment of the present invention, the energy consumption benchmark score lines under different output steps of each energy consumption evaluation index are calculated by using the TOPSIS method, including the following steps:

[0149] Determine the ideal solution and negative ideal solution of each energy consumption evaluation index;

[0150] The weighted results of each energy consumption evaluation index are used to calculate the distance between each evaluation target and the ideal solution and the negative ideal solution;

[0151] The energy consumption score values ​​under different output steps are calculated according to the distance, and the comprehensive energy efficiency benchmark score lines under different output steps are drawn according to the energy consumption score values.

[0152] S5: Compare the energy consumption benchmark score line with the target operating condition, and evaluate the long-distance natural gas pipeline transportation energy consumption according to the comparison result.

[0153] This example evaluates the energy consumption benchmark score line and simulated working conditions under different flow steps of the AB / C line of the Central Asian natural gas pipeline according to the above method. The results are as follows: Figure 3 and Figure 4 As shown, Figure 3 The energy consumption benchmark score line and simulated operating condition score under different output of AB line. It can be seen that AB-300-M has the highest simulated operating condition score, which exceeds the energy consumption benchmark score line. The schemes higher than the energy consumption benchmark score line will be adopted, and the schemes lower than the benchmark line will be eliminated. Figure 4 The energy consumption benchmark scores and simulated operating condition scores under different outputs of Line C. The simulated operating condition score of C-210-M is the highest, while C-190-M1, C-170-M1, C-160-M1, and C-150-M1 are all below the energy consumption benchmark scores. The plans that are higher than the energy consumption benchmark scores will be adopted, and the plans that are lower than the benchmark scores will be eliminated.

[0154] Based on the same concept as the embodiment of the method of the present invention, the embodiment of the present invention also provides a long-distance natural gas pipeline transmission energy consumption comprehensive evaluation system, specifically as follows Figure 5 As shown, the pipeline energy consumption comprehensive evaluation system 5 includes:

[0155] An index screening unit, used to screen and obtain several energy consumption evaluation indexes of pipeline transportation energy consumption by using the Delphi method;

[0156] A data screening unit, used to screen the operating data of the natural gas pipeline;

[0157] The first calculation unit calculates the weight of each energy consumption evaluation index by using the entropy weight method, and assigns weight to each energy consumption evaluation index according to the calculation result;

[0158] The second calculation unit is used to calculate the energy consumption benchmark score line of each energy consumption evaluation index under different output steps by using the TOPSIS method and the weighted result of each energy consumption evaluation index;

[0159] The evaluation unit is used to compare the energy consumption benchmark score line with the target operating condition data, and evaluate the pros and cons of the energy consumption of the long-distance natural gas pipeline operation according to the comparison result.

[0160] Based on the same inventive concept, another exemplary embodiment of the present invention provides an electronic device. Figure 6 As shown, the electronic device includes at least one processor 601, at least one communication interface 602, at least one memory 603 and at least one communication bus 604; wherein the processor 601, the communication interface 602 and the memory 603 communicate with each other through the communication bus 604;

[0161] Memory 603, used for storing computer programs;

[0162] The processor 601 is used to implement the comprehensive evaluation method for the energy consumption of long-distance natural gas pipeline transportation when executing the program stored in the memory 603.

[0163] Optionally, the communication interface may be an interface of a communication module, such as an interface of a GSM module; the processor may be a processor CPU, or an application specific integrated circuit ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement the embodiments of the present invention. The memory may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory. The memory stores a program, and the processor calls the program stored in the memory to execute some or all of the above method embodiments.

[0164] Based on the same inventive concept, the embodiment of the present application further provides a storage medium, including a computer program, which implements part or all of the above method embodiments when executed by a processor. Optionally, the storage medium may be a non-temporary computer-readable storage medium, for example, the non-temporary computer-readable storage medium may be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0165] Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent substitutions for some of the technical features therein; and these modifications or substitutions do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A comprehensive evaluation method for energy consumption of long-distance natural gas pipeline transportation, characterized in that: The method comprises: The Delphi method was used to screen and obtain several energy consumption evaluation indicators of pipeline transportation energy consumption; Screening of operating data of natural gas pipelines; The entropy weight method is used to calculate the weight of each energy consumption evaluation index, and each energy consumption evaluation index is weighted according to the calculation results; The energy consumption benchmark scores of each energy consumption evaluation index under different output steps are calculated using the TOPSIS method and the weighted results of each energy consumption evaluation index. The energy consumption benchmark score line is compared with the target operating condition data, and the pros and cons of the energy consumption of the long-distance natural gas pipeline operation are evaluated based on the comparison result.

2. A comprehensive evaluation method for energy consumption of long-distance natural gas pipeline transportation according to claim 1, characterized in that: The Delphi method is used to screen several energy consumption evaluation indicators for pipeline energy consumption, including the following steps: Select multiple expert groups with professional knowledge and experience in natural gas pipeline energy consumption; Prepare a questionnaire covering issues related to energy consumption in natural gas pipeline transportation; Sending said questionnaire to the expert group to be filled in anonymously; Collect the completed questionnaires for summary analysis and provide feedback to the expert group; The expert group conducts investigation and analysis based on the analysis results, and fills in the questionnaire again based on the results of the investigation and analysis, forming a cycle; After the opinions of the expert group members on the energy consumption of natural gas pipeline transportation are consistent in the final questionnaire results, several energy consumption evaluation indicators for pipeline transportation energy consumption are selected.

3. A comprehensive evaluation method for energy consumption of long-distance natural gas pipeline transportation according to claim 1, characterized in that: The energy consumption evaluation indexes include self-consumption gas volume, gas consumption-to-output ratio, unit turnover operation energy consumption, compressor shaft power and compressor variable efficiency.

4. A comprehensive evaluation method for energy consumption of long-distance natural gas pipeline transportation according to claim 1, characterized in that: Screening the operating data of the natural gas pipeline includes: removing null value data and removing erroneous data in the operating data; The method adopted for eliminating erroneous data is to eliminate outliers based on the statistical characteristics presented by most of the running data; the statistical characteristics include the first quartile, the median, the third quartile and the interquartile range.

5. A comprehensive evaluation method for energy consumption of long-distance natural gas pipeline transportation according to claim 1, characterized in that: The method of calculating the weight of each energy consumption evaluation index by using the entropy weight method includes the following steps: Select n samples and m energy consumption evaluation indicators, then x ij is the value of the jth energy consumption evaluation index of the i-th sample; Use normalization method to homogenize various energy consumption evaluation indicators; Calculate the proportion p of the i-th sample under the j-th energy consumption evaluation index to the index ij ; According to the specific gravity p ij Calculate the entropy value e of the jth energy consumption evaluation index j ; According to the entropy value e j Calculate the information entropy redundancy d j ; According to the information entropy redundancy d j Calculate the weight ω of each energy consumption evaluation index j .

6. A comprehensive evaluation method for energy consumption of long-distance natural gas pipeline transportation according to claim 1, characterized in that: The energy consumption benchmark score line of each energy consumption evaluation index under different output steps is calculated by using the TOPSIS method and the weighted result of each energy consumption evaluation index, including the following steps: Determine the ideal solution and negative ideal solution of each energy consumption evaluation index; The weighted results of each energy consumption evaluation index are used to calculate the distance between each evaluation target and the ideal solution and the negative ideal solution; The energy consumption score values ​​under different output steps are calculated according to the distance, and the comprehensive energy efficiency benchmark score lines under different output steps are drawn according to the energy consumption score values.

7. A comprehensive evaluation method for energy consumption of long-distance natural gas pipeline transportation according to claim 1, characterized in that: According to the comparison results, the advantages and disadvantages of the energy consumption of long-distance natural gas pipeline operation are evaluated as follows: The plans corresponding to the working conditions that are higher than or equal to the energy consumption benchmark score line will be adopted, and the plans corresponding to the working conditions that are lower than the energy consumption benchmark score line will be eliminated.

8. A comprehensive evaluation system for energy consumption of long-distance natural gas pipelines, characterized in that: The system comprises: An index screening unit, used to screen and obtain several energy consumption evaluation indexes of pipeline transportation energy consumption by using the Delphi method; A data screening unit, used to screen the operating data of the natural gas pipeline; The first calculation unit calculates the weight of each energy consumption evaluation index by using the entropy weight method, and assigns weight to each energy consumption evaluation index according to the calculation result; The second calculation unit is used to calculate the energy consumption benchmark score line of each energy consumption evaluation index under different output steps by using the TOPSIS method and the weighted result of each energy consumption evaluation index; The evaluation unit is used to compare the energy consumption benchmark score line with the target operating condition data, and evaluate the pros and cons of the energy consumption of the long-distance natural gas pipeline operation according to the comparison result.

9. An electronic device for comprehensive evaluation of energy consumption of long-distance natural gas pipelines, characterized in that: It includes a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other through the communication bus; Memory for storing computer programs; The processor is used to implement the comprehensive evaluation method for energy consumption of long-distance natural gas pipeline transportation according to any one of claims 1 to 7 when executing the program stored in the memory.

10. A computer-readable storage medium, characterized in that: A computer-readable program is stored, and when the computer-readable program is run, the comprehensive evaluation method for the energy consumption of a long-distance natural gas pipeline according to any one of claims 1 to 7 is executed.

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