Gas storage energy consumption comprehensive evaluation method based on comprehensive index system

Abstract

The invention discloses a gas storage energy consumption comprehensive evaluation method based on a comprehensive index system, and the method comprises the following steps: S1, collecting data affecting the energy consumption of a gas storage, building a gas storage energy consumption evaluation index system, and building a comment set; s2, based on a 1-9 scale method, establishing a judgment matrix for primary indexes and secondary indexes of the gas storage energy consumption evaluation index system, solving a gas storage energy consumption evaluation index weight vector after consistency check, and establishing a factor weight set; and S3, determining a membership function, and substituting the first-level indexes and the second-level indexes into the membership function to obtain a gas storage energy consumption evaluation index evaluation matrix. The method effectively solves the problems that in the prior art, main links for generating energy consumption of the gas storage are lacked, energy consumption influence factors cannot be analyzed, energy consumption evaluation of the gas storage cannot be determined, and a gas storage energy consumption evaluation index system cannot be established by quantifying qualitative indexes through a reasonable method.

Description

Technical Field

[0001] The present invention belongs to the technical field of energy consumption of natural gas underground storage reservoirs, and relates to a comprehensive evaluation method for energy consumption of gas storage reservoirs based on a comprehensive indicator system. Background Art

[0002] With the proposal of the "dual carbon" strategic goal, my country's energy structure will transform to green and low-carbon energy. Compared with traditional fossil energy, natural gas has the characteristics of high calorific value, cleanliness and stability. Therefore, it is bound to become a transitional product for new energy. At present, my country's natural gas consumption continues to grow, and the peak-to-valley difference in natural gas consumption is also increasing. Affected by various factors at home and abroad, the contradiction between natural gas supply and demand is prominent. Since gas storage has super peak-shaving capacity, it plays an important role in alleviating the contradiction between natural gas supply and demand. As an important part of the natural gas supply system, the energy consumption of gas storage has attracted much attention. Before saving energy and reducing consumption in gas storage, it is necessary to The energy consumption of existing gas storage facilities is analyzed and evaluated. Due to the late development of gas storage facilities in my country, there are currently few studies on the energy consumption evaluation of gas storage facilities, and there is no complete set of scientific and systematic energy consumption evaluation technical solutions. Therefore, the main links of gas storage energy consumption are analyzed, the factors affecting energy consumption are analyzed, the quantitative and qualitative indicators of energy consumption evaluation are determined, and the qualitative indicators are quantified through reasonable methods. A gas storage energy consumption evaluation index system is established, forming a comprehensive energy consumption evaluation method for gas storage facilities based on the comprehensive index system. Corresponding measures are taken based on the evaluation results. This has great reference significance for energy saving and consumption reduction in the actual operation of gas storage facilities.

[0003] A Chinese patent with authorization number CN107169633B discloses a comprehensive evaluation method for gas transmission pipeline and gas storage peak-shaving schemes, which includes: step 1, city gas load prediction: using an artificial neural network model to establish a city gas load prediction model, and using a differential evolution extreme learning machine algorithm to predict the gas load of the city to be peak-shaving, thereby determining the peak-shaving amount; step 2, gas storage peak-shaving optimization: based on previous gas storage peak-shaving operation experience, fitting the relationship between gas storage operating parameters and peak-shaving amount, and obtaining the gas storage gas production rate under a certain peak-shaving amount; step 3, pipeline network peak-shaving amount simulation, to obtain a pre-selected peak-shaving scheme; step 4, comprehensive evaluation of peak-shaving schemes: comprehensively evaluating different peak-shaving schemes to obtain the optimal peak-shaving scheme. This invention comprehensively considers conditions such as user peak gas consumption, pipeline peak-shaving capacity, and gas storage peak-shaving capacity, effectively improving the optimality and scientificity of peak-shaving plan formulation and arrangement; however, this technical solution lacks the main links in the generation of gas storage energy consumption, and cannot analyze its energy consumption influencing factors and uncertain gas storage energy consumption evaluation, as well as the problem of qualitative indicators being quantified through reasonable methods to establish a gas storage energy consumption evaluation index system. Therefore, there is an urgent need for a comprehensive evaluation method for gas storage energy consumption based on a comprehensive index system. Summary of the Invention

[0004] In response to the above problems, the present invention proposes a comprehensive evaluation method for gas storage energy consumption based on a comprehensive indicator system, which effectively solves the problems in the existing technology of lacking the main links in the generation of gas storage energy consumption, being unable to analyze its energy consumption influencing factors, determining the quantitative and qualitative indicators of energy consumption evaluation, and being unable to quantify qualitative indicators through reasonable methods to establish a gas storage energy consumption evaluation index system.

[0005] In order to achieve the above object, the technical solution adopted by the present invention is as follows:

[0006] A casing for a comprehensive evaluation method of energy consumption of a gas storage facility based on a comprehensive index system comprises the following steps;

[0007] S1. Collect data on factors affecting gas storage energy consumption, establish a gas storage energy consumption evaluation index system, and create a comment set;

[0008] S2. Based on the 1-9 scaling method, a judgment matrix is ​​established for the primary and secondary indicators of the gas storage reservoir energy consumption evaluation index system. After consistency testing, the weight vector of the gas storage reservoir energy consumption evaluation index is solved and a factor weight set is established;

[0009] S3. Determine a membership function, substitute the above-mentioned primary and secondary indicators into the membership function, and obtain a gas storage energy consumption evaluation index evaluation matrix;

[0010] S4. Using fuzzy comprehensive evaluation, multiply the weight vector of the gas storage energy consumption evaluation index and the evaluation matrix of the gas storage energy consumption evaluation index, and normalize the evaluation result vector;

[0011] S5. Process and analyze the above fuzzy evaluation results to determine the energy consumption evaluation level of the gas storage reservoir.

[0012] Preferably, in step S2, the gas storage energy consumption evaluation index system includes three first-level indicators, namely the gas production system, the gas injection system and the public service system.

[0013] Preferably, the secondary indicators in the gas production system include: heat medium furnace efficiency, external transmission pump efficiency, alcohol injection pump efficiency, ethylene glycol pump efficiency, adaptability of three-stream heat exchanger, adaptability of gas-gas heat exchanger, heat medium furnace power consumption, pump unit energy consumption and heat medium furnace gas consumption;

[0014] The secondary indicators in the gas injection system are: compressor unit efficiency, compressor energy consumption and injection station;

[0015] The secondary indicators in the public service system are: heating furnace efficiency, apartment electricity consumption, public electricity consumption, heating furnace gas consumption and apartment water consumption.

[0016] Preferably, the review set is V = {v1, v2, v3, v4}, representing poor, medium, good, and good respectively.

[0017] Preferably, the judgment matrix form of step S2 is as follows:

[0018]

[0019] Among them, A represents the judgment matrix; u mn is the element of the judgment matrix, indicating the importance of the mth indicator to the nth indicator;

[0020] In step S2, the consistency index value in the gas storage energy consumption evaluation index system is subjected to a consistency test with the average random consistency index value, so that the ratio of the consistency index value in the gas storage energy consumption evaluation index system to the average random consistency index value, i.e., CR=CI / RI, is satisfied. If CR is less than 0.1, the consistency test is passed; otherwise, the judgment matrix should be modified and retested.

[0021] Among them, CR represents the ratio of the consistency index value in the gas storage energy consumption evaluation index system to the average random consistency index value; CI represents the consistency index value in the gas storage energy consumption evaluation index system; RI represents the average random consistency index value;

[0022] Among them, the CI calculation formula is:

[0023]

[0024] Among them, CI represents the consistency index value, λ max represents the maximum eigenvalue of the judgment matrix, and n represents the order of the judgment matrix.

[0025] The weight vector solution steps in step S2 are as follows:

[0026] Calculate the weight vector using the "square root method":

[0027]

[0028] in, represents the i-th component of the weight vector; i represents the row of the judgment matrix; j represents the column of the judgment matrix; n represents the order of the judgment matrix; u ij is the element of the judgment matrix, indicating the importance of the i-th indicator to the j-th indicator; Represents the product of each row element in the judgment matrix;

[0029] Normalize the calculation results to obtain the weight vector Wi:

[0030]

[0031] Among them, W i Represents the i-th component of the normalized weight vector; represents the i-th component of the weight vector; represents the kth component of the weight vector before normalization; n is the number of weight vector components; k and i represent loop variables.

[0032] The weight vector W of the gas storage energy consumption evaluation index can be obtained by multiplying the obtained secondary index weight with the corresponding primary index weight. 总 :

[0033] W 总 =W 一级指标 W 二级指标 (5)

[0034] Preferably, in step S3, the membership function is a parabolic distribution function. The membership functions representing the four types of comments, namely poor, medium, good, and good, are as follows:

[0035]

[0036] The evaluation matrix R is obtained by substituting the evaluation index scores into the membership function, and its form is:

[0037]

[0038] in, represents the membership function; x represents the independent variable.

[0039] Preferably, in step S4, the multiplication formula of the gas storage energy consumption evaluation index weight vector and the gas storage energy consumption evaluation index judgment matrix is:

[0040]

[0041] Among them, B represents the judgment result vector of fuzzy comprehensive evaluation; W 总 represents the weight vector of gas storage energy consumption evaluation indicators; R represents the evaluation matrix; W m Represents the mth component of the evaluation index weight vector; r mn represents the element in the mth row and nth column of the evaluation matrix; b n Represents the nth component of the judgment result vector of fuzzy comprehensive evaluation;

[0042] The normalization formula is:

[0043]

[0044] Among them, c i represents the i-th component of the normalized judgment result vector of the fuzzy comprehensive evaluation; b i Represents the i-th component of the judgment result vector of fuzzy comprehensive evaluation before normalization.

[0045] Preferably, in step S5, the maximum membership principle is adopted to determine the comprehensive evaluation level of the gas storage energy consumption.

[0046] Compared with the prior art, the present invention has the following beneficial effects:

[0047] 1. The present invention introduces the fuzzy comprehensive evaluation method into the energy consumption evaluation of gas storage, combines qualitative indicators with quantitative indicators, and provides a scientific evaluation method for gas storage in the actual production process.

[0048] 2. The present invention takes into account the links that generate energy consumption during the operation of the gas storage reservoir, and can effectively evaluate the comprehensive energy consumption level of the gas storage reservoir. According to the comprehensive evaluation results of the gas storage reservoir energy consumption, corresponding measures can be taken to reduce the energy consumption of the gas storage reservoir and reduce the waste of resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 It is a schematic diagram of the process of the present invention.

[0050] Figure 2 It is a schematic diagram of the primary and secondary indicators in the gas storage energy consumption evaluation index system of the present invention. DETAILED DESCRIPTION

[0051] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0052] See also Figure 1-2 ,The present invention provides a technical solution: a comprehensive evaluation method for energy consumption of a gas storage facility based on a comprehensive index system, comprising the following steps;

[0053] S1. Collect data on factors affecting gas storage energy consumption, establish a gas storage energy consumption evaluation index system, and create a comment set;

[0054] S2. Based on the 1-9 scaling method, a judgment matrix is ​​established for the primary and secondary indicators of the gas storage reservoir energy consumption evaluation index system. After consistency testing, the weight vector of the gas storage reservoir energy consumption evaluation index is solved and a factor weight set is established;

[0055] The meaning of the 1-9 scale is shown in Table 1;

[0056] Table 1 Meaning of 1-9 scaling method

[0057]

[0058] S3. Determine a membership function, substitute the above-mentioned primary and secondary indicators into the membership function, and obtain a gas storage energy consumption evaluation index evaluation matrix;

[0059] S4. Using fuzzy comprehensive evaluation, multiply the weight vector of the gas storage energy consumption evaluation index and the evaluation matrix of the gas storage energy consumption evaluation index, and normalize the evaluation result vector;

[0060] S5. Process and analyze the above fuzzy evaluation results to determine the energy consumption evaluation level of the gas storage reservoir.

[0061] In step S2, the gas storage energy consumption evaluation index system includes three first-level indicators, namely the gas production system, the gas injection system and the public service system.

[0062] The secondary indicators in the gas production system are: heat medium furnace efficiency, external transmission pump efficiency, alcohol injection pump efficiency, ethylene glycol pump efficiency, adaptability of three-stream heat exchanger, adaptability of gas-to-gas heat exchanger, heat medium furnace power consumption, pump unit energy consumption and heat medium furnace gas consumption;

[0063] The secondary indicators in the gas injection system are: compressor unit efficiency, compressor energy consumption and injection station;

[0064] The secondary indicators in the public service system are: heating furnace efficiency, apartment electricity consumption, public electricity consumption, heating furnace gas consumption and apartment water consumption.

[0065] In this embodiment, the calculation results of the secondary index weights of the gas production system are as follows:

[0066]

[0067] Where, B1 represents the gas production system; C 11-19 Represents the secondary indicators under the gas production system.

[0068] W B1 =(0.0945, 0.1169, 0.0387, 0.7502, 0.0481, 0.1472, 0.1773, 0.1303, 0.1717)

[0069] Similarly, the weight vectors of the gas injection system, public service system and system layer A are calculated.

[0070] W B2 =(0.5748, 0.2551, 0.1741)

[0071] W B3 =(0.2522, 0.1625, 0.0793, 0.3609, 0.1449)

[0072] W A=(0.117, 0.811, 0.072)

[0073] Among them, W B1 Represents the weight vector of the gas production system; W B2 Represents the weight vector of the gas injection system; W B3 represents the weight vector of the public service system; WA represents the weight vector of system layer A, that is, the weight vector between the gas production system, gas injection system and public service system.

[0074] Furthermore, the weight vector of evaluation indexes of the gas storage injection and production system is calculated:

[0075] W 总 =(0.0111, 0.0137, 0.0045, 0.0877, 0.0056, 0.0172, 0.0207, 0.0152, 0.0200, 0.4661, 0.2069, 0.1411, 0.0181, 0.0117, 0.0057, 0.0259, 0.0104)

[0076] The review set is V = {v1, v2, v3, v4}, where v1 represents poor, v2, v3, and v4 respectively.

[0077] The judgment matrix of step S2 above is as follows:

[0078]

[0079] Among them, A represents the judgment matrix; u mn is an element of the judgment matrix, which indicates the importance of the mth indicator to the nth indicator, where u 11 Indicates the importance of the first indicator to the first indicator;

[0080] In step S2, the consistency index value in the gas storage reservoir energy consumption evaluation index system is tested for consistency with the average random consistency index value. The ratio of the consistency index value in the gas storage reservoir energy consumption evaluation index system to the average random consistency index value is CR = CI / RI. If CR is less than 0.1, the consistency test is passed. Otherwise, the judgment matrix should be corrected and retested.

[0081] Among them, CR represents the ratio of the consistency index value in the gas storage energy consumption evaluation index system to the average random consistency index value; CI represents the consistency index value in the gas storage energy consumption evaluation index system; RI represents the average random consistency index value;

[0082] Among them, the CI calculation formula is:

[0083]

[0084] Among them, CI represents the consistency index value, λmax represents the maximum eigenvalue of the judgment matrix, and n represents the order of the judgment matrix.

[0085] The average random consistency index value RI can be obtained by looking up Table 2.

[0086] Table 2 RI value table

[0087] Matrix order 1 2 3 4 5 6 7 8 9 RI 0 0 0.58 0.9 1.12 1.24 1.32 1.41 1.45

[0088] The weight vector solution steps in step S2 are as follows:

[0089] Calculate the weight vector using the "square root method":

[0090]

[0091] in, represents the i-th component of the weight vector; i represents the row of the judgment matrix; j represents the column of the judgment matrix; n represents the order of the judgment matrix; u ij is the element of the judgment matrix, indicating the importance of the i-th indicator to the j-th indicator; Represents the product of each row element in the judgment matrix;

[0092] Normalize the calculation results to obtain the weight vector Wi:

[0093]

[0094] Among them, W i Represents the i-th component of the normalized weight vector; represents the i-th component of the weight vector; represents the kth component of the weight vector before normalization; n is the number of weight vector components; k and i represent loop variables.

[0095] The weight vector W of the gas storage energy consumption evaluation index can be obtained by multiplying the secondary index weight obtained above with the corresponding primary index weight. 总 :

[0096] W 总 =W 一级指标 W 二级指标 (5)

[0097] In step S3, the membership function is a parabolic distribution function. The membership functions representing the four types of comments, namely poor, medium, good, and good, are as follows:

[0098]

[0099] The evaluation matrix R is obtained by substituting the evaluation index into the membership function, and its form is:

[0100]

[0101] in, represents the membership function; x represents the independent variable.

[0102] In step S4, the multiplication formula of the gas storage energy consumption evaluation index weight vector and the gas storage energy consumption evaluation index judgment matrix is:

[0103]

[0104] Among them, B represents the judgment result vector of fuzzy comprehensive evaluation; W 总 represents the weight vector of gas storage energy consumption evaluation indicators; R represents the evaluation matrix; W m Represents the mth component of the evaluation index weight vector; r mn represents the element in the mth row and nth column of the evaluation matrix; b n Represents the nth component of the judgment result vector of fuzzy comprehensive evaluation.

[0105] The normalization formula is:

[0106]

[0107] Among them, c i represents the i-th component of the normalized judgment result vector of the fuzzy comprehensive evaluation; b i represents the i-th component of the fuzzy comprehensive evaluation result vector before normalization, b k Represents the kth component of the fuzzy comprehensive evaluation result vector before normalization;

[0108] In this embodiment, the scoring results of the secondary indicators of gas storage energy consumption are shown in the following table:

[0109] Ci C11 C12 C13 C14 C15 C16 C17 C18 C19 Score 7.2 7.5 7.5 6.3 3.5 7.2 7 8 7 Ci C21 C22 C23 C31 C32 C33 C34 C35 Score 8.5 7 5 8 7.5 6 5.5 4

[0110] In the table, Ci represents the secondary index of gas storage energy consumption, and the corresponding secondary index is

[0111] Furthermore, the secondary evaluation index is substituted into the membership function to obtain the evaluation index judgment matrix R, the matrix R T Each column vector in represents the membership vector of each evaluation index:

[0112] In this embodiment, the multiplication result of the gas storage energy consumption evaluation index weight vector and the gas storage energy consumption evaluation index judgment matrix is ​​as follows:

[0113]

[0114] Furthermore, the results are normalized:

[0115] C=(0,0.0469,0.6469,0.3061)

[0116] Wherein, C represents the result value of normalization processing;

[0117] In step S5, the maximum membership principle is adopted to determine the comprehensive evaluation level of the gas storage energy consumption.

[0118] In this embodiment, the fuzzy comprehensive evaluation result of the gas storage system is C=(0, 0.0469, 0.6469, 0.3061). According to the maximum membership principle, the comprehensive evaluation level of energy consumption of the gas storage is good.

[0119] Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments, or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A comprehensive evaluation method for gas storage energy consumption based on a comprehensive index system, characterized by: The method includes the following steps: S1. Collect data on factors affecting gas storage energy consumption, establish a gas storage energy consumption evaluation index system, and create a comment set; S2. Based on the 1-9 scaling method, a judgment matrix is ​​established for the primary and secondary indicators of the gas storage reservoir energy consumption evaluation index system. After consistency testing, the weight vector of the gas storage reservoir energy consumption evaluation index is solved and a factor weight set is established; S3. Determine a membership function, substitute the above-mentioned primary and secondary indicators into the membership function, and obtain a gas storage energy consumption evaluation index evaluation matrix; S4. Using fuzzy comprehensive evaluation, multiply the weight vector of the gas storage energy consumption evaluation index and the evaluation matrix of the gas storage energy consumption evaluation index, and normalize the evaluation result vector; S5. Process and analyze the above fuzzy evaluation results to determine the energy consumption evaluation level of the gas storage reservoir.

2. The comprehensive evaluation method for gas storage energy consumption based on a comprehensive index system according to claim 1 is characterized by: In step S2, the gas storage energy consumption evaluation index system includes three first-level indicators, namely the gas production system, the gas injection system and the public service system.

3. The comprehensive evaluation method for gas storage energy consumption based on a comprehensive index system according to claim 2 is characterized by: The secondary indicators in the gas production system are: heat medium furnace efficiency, external transmission pump efficiency, alcohol injection pump efficiency, ethylene glycol pump efficiency, adaptability of three-stream heat exchanger, adaptability of gas-to-gas heat exchanger, heat medium furnace power consumption, pump unit energy consumption and heat medium furnace gas consumption; The secondary indicators in the gas injection system are: compressor unit efficiency, compressor energy consumption and injection station; The secondary indicators in the public service system are: heating furnace efficiency, apartment electricity consumption, public electricity consumption, heating furnace gas consumption and apartment water consumption.

4. The comprehensive evaluation method for gas storage energy consumption based on a comprehensive index system according to claim 1 is characterized by: The review set is V = {v1, v2, v3, v4}, which represent poor, medium, good, and good respectively.

5. The comprehensive evaluation method for gas storage energy consumption based on a comprehensive index system according to claim 1 is characterized by: The judgment matrix of step S2 above is as follows: Among them, A represents the judgment matrix; u mn is the element of the judgment matrix, indicating the importance of the mth indicator to the nth indicator; In step S2, the consistency index value in the gas storage energy consumption evaluation index system is subjected to a consistency test with the average random consistency index value, so that the ratio of the consistency index value in the gas storage energy consumption evaluation index system to the average random consistency index value, i.e., CR=CI / RI, is satisfied. If CR<0.1, the consistency test is passed; otherwise, the judgment matrix should be modified and retested. Among them, CR represents the ratio of the consistency index value in the gas storage energy consumption evaluation index system to the average random consistency index value; CI represents the consistency index value in the gas storage energy consumption evaluation index system; RI represents the average random consistency index value: Among them, the CI calculation formula is: Among them, CI represents the consistency index value, λ max represents the maximum eigenvalue of the judgment matrix, and n represents the order of the judgment matrix. The weight vector solution steps in step S2 are as follows: Use the "square root method" to calculate the weight vector: in, represents the i-th component of the weight vector; i represents the row of the judgment matrix; j represents the column of the judgment matrix; n represents the order of the judgment matrix; u ij is the element of the judgment matrix, indicating the importance of the i-th indicator to the j-th indicator; Represents the product of each row element in the judgment matrix; Normalize the calculation results to obtain the weight vector Wi: Among them, W i Represents the i-th component of the normalized weight vector; represents the i-th component of the weight vector; represents the kth component of the weight vector before normalization; n is the number of weight vector components; k and i represent loop variables. The weight vector W of the gas storage energy consumption evaluation index can be obtained by multiplying the obtained secondary index weight with the corresponding primary index weight. 总 : IN 总 =In 一级指标 ·IN 二级指标 (5)。 6. The comprehensive evaluation method for gas storage energy consumption based on a comprehensive index system according to claim 1 is characterized by: In step S3, the membership function is a parabolic distribution function. The membership functions representing the four types of comments, namely poor, medium, good, and good, are as follows: The evaluation matrix R is obtained by substituting the evaluation index scores into the membership function, and its form is: in, represents the membership function; x represents the independent variable.

7. The comprehensive evaluation method for gas storage energy consumption based on a comprehensive index system according to claim 1 is characterized by: The multiplication formula of the gas storage energy consumption evaluation index weight vector and the gas storage energy consumption evaluation index judgment matrix is: Among them, B represents the judgment result vector of fuzzy comprehensive evaluation; W 总 represents the weight vector of gas storage energy consumption evaluation indicators; R represents the evaluation matrix; W m Represents the mth component of the evaluation index weight vector; r mn represents the element in the mth row and nth column of the evaluation matrix; b n Represents the nth component of the judgment result vector of fuzzy comprehensive evaluation. The normalization formula is: Among them, c i represents the i-th component of the normalized judgment result vector of the fuzzy comprehensive evaluation; b i represents the i-th component of the fuzzy comprehensive evaluation result vector before normalization; b k Represents the kth component of the fuzzy comprehensive evaluation result vector before normalization.

8. The comprehensive evaluation method for energy consumption of a gas storage facility based on a comprehensive index system according to claim 1, characterized in that: In step S5, the maximum membership principle is adopted to determine the comprehensive evaluation level of the gas storage energy consumption.

Images