A TBM suitability evaluation method for underground caverns in pumped storage power stations

Abstract

The present invention provides a TBM suitability evaluation method for underground caverns of pumped-storage power stations, comprising: establishing an evaluation model of a target layer, a criterion layer, a sub-criterion layer and a scheme layer; constructing a judgment matrix, determining a scoring rule and assigning a value to the judgment matrix, calculating a weight after a consistency test, and performing a correlation calculation on the weights of each layer to obtain a total score for the TBM suitability evaluation of underground caverns of pumped-storage power stations. The present invention provides a TBM suitability evaluation method for underground caverns of pumped-storage power stations, which is a TBM suitability evaluation method for underground caverns of pumped-storage power stations based on a hierarchical analysis method and comprehensive qualitative and quantitative evaluation, fully considering the project characteristics of different pumped-storage power stations, quantitatively determining evaluation indicators and scoring rules, and performing quantitative evaluation, and quantitatively obtaining a more reasonable scheme through the size of the weight, so as to achieve the purpose of improving the scientificity, rationality and accuracy of decision-making application.

Description

Technical Field

[0001] The invention belongs to the technical field of pumped storage power station design, and in particular relates to a TBM applicability evaluation method for an underground cavern of a pumped storage power station. Background Art

[0002] In the design study of pumped-storage power stations, the use of TBM equipment to construct underground cavern groups can speed up the project progress and generate electricity in advance, thus bringing considerable economic benefits.

[0003] However, the geological conditions, hub layout, construction period requirements, investment cost, equipment manufacturing cycle, equipment status, and potential amortization length of the project are all different. Not every project's underground cavern is suitable for TBM equipment. Therefore, it is necessary to conduct a TBM suitability evaluation on the project's underground cavern.

[0004] The traditional TBM suitability evaluation method is the hierarchical analysis method, whose evaluation indicators are mainly determined by the experience of decision makers, which has great inaccuracy and cannot make an accurate and reliable evaluation of the suitability of TBM equipment for power stations. Summary of the invention

[0005] In view of the defects of the prior art, the present invention provides a TBM suitability evaluation method for underground caverns of pumped-storage power stations, which can effectively solve the above problems.

[0006] The technical solution adopted by the present invention is as follows:

[0007] The present invention provides a TBM suitability evaluation method for an underground cavern of a pumped storage power station, comprising the following steps:

[0008] Step 1: Based on the principle of hierarchical analysis method, the evaluation indicators are determined in combination with the characteristics of pumped storage power stations and TBM equipment conditions, so as to establish an evaluation model with a hierarchical structure, which is the target layer A, the criterion layer B, the sub-criterion layer C and the scheme layer D from top to bottom;

[0009] The target layer A is the root node, which is the TBM suitability evaluation target for the underground cavern of the pumped storage power station. The direct lower layer of the target layer A is the criterion layer B, which includes the geological factor evaluation index B1, the technical factor evaluation index B2, the economic factor evaluation index B3, the construction period factor evaluation index B4 and the equipment factor evaluation index B5. For each evaluation index B of the criterion layer B, i Further refined into multiple evaluation indicators, thereby obtaining a sub-criteria layer C; wherein i = 1, 2, 3, 4, 5; the scheme layer D has M schemes of underground cavern TBM applicability levels, namely schemes D1, D2, ..., D M ;

[0010] Step 2: construct the judgment matrix F(B) of the criterion layer B, the judgment matrix F(C) of the sub-criterion layer C, and the judgment matrix F(D) of the solution layer D respectively;

[0011] Among them: the judgment matrix F(B) of the criterion layer B is a matrix formed by comparing the influence of the five criterion layer evaluation indicators, namely, geological factor evaluation index B1, technical factor evaluation index B2, economic factor evaluation index B3, construction period factor evaluation index B4 and equipment factor evaluation index B5, on the scheme layer D.

[0012] The judgment matrix F(C) of the sub-criteria layer C includes five judgment matrices, namely: the sub-criteria layer judgment matrix F(C1) for the geological factor evaluation index B1, the sub-criteria layer judgment matrix F(C2) for the technical factor evaluation index B2, the sub-criteria layer judgment matrix F(C3) for the economic factor evaluation index B3, the sub-criteria layer judgment matrix F(C4) for the construction period factor evaluation index B4, and the sub-criteria layer judgment matrix F(C5) for the equipment factor evaluation index B5; for each sub-criteria layer judgment matrix F(C i ), is the corresponding evaluation index B i Among the further refined evaluation indicators of each sub-criteria layer, the matrix formed by the relative comparison of the impact degree on the solution layer D is formed;

[0013] The judgment matrix F(D) of the scheme layer D is the applicability level of each underground cavern TBM scheme D m , m=1,2,…,M, a matrix formed by the influence degree of evaluation indicators of each sub-criteria layer;

[0014] Step 3: Determine the scoring rules for each evaluation indicator in the criterion layer B, the scoring rules for each evaluation indicator in the sub-criterion layer C, and the scoring rules for each solution in the solution layer D;

[0015] Step 4: According to the scoring rules determined in step 3, assign values ​​to the elements in the judgment matrices constructed in step 2, thereby obtaining the assigned judgment matrix F(B) of the criterion layer B, the judgment matrix F(C) of the sub-criterion layer C, and the judgment matrix F(D) of the solution layer D;

[0016] Step 5: Perform consistency check on each judgment matrix after assignment obtained in step 4, and execute step 6 after passing the check;

[0017] Step 6: Analyze the judgment matrix F(B) of the criterion layer B, the judgment matrix F(C) of the sub-criterion layer C, and the judgment matrix F(D) of the solution layer D after the assignment, and obtain the weight of each evaluation index of the criterion layer B on the solution layer D, the weight of each evaluation index of the sub-criterion layer C on the solution layer D, and the weight of each solution in the solution layer D affected by each evaluation index of the sub-criterion layer C;

[0018] Step 7: According to the order of the levels from top to bottom, the weights of each layer are correlated and calculated to obtain the total score of the TBM suitability evaluation of the underground cavern of the pumped-storage power station. According to the total score of the TBM suitability evaluation of the underground cavern of the pumped-storage power station, the degree of TBM suitability of the underground cavern of the pumped-storage power station is quantitatively determined.

[0019] Preferably, for each evaluation index B of the criterion layer B i Further refine it into multiple evaluation indicators to obtain the sub-criteria layer C, specifically:

[0020] Geological factor evaluation index B1 is refined into surrounding rock lithology evaluation index C 11 , Surrounding rock type evaluation index C 12 , surrounding rock strength evaluation index C 13 And water inrush evaluation index C 14 ;

[0021] Technical factor evaluation index B2, which is refined into cave length evaluation index C 21 , Cavern slope evaluation index C 22 And the cavern turning radius evaluation index C 23 ;

[0022] Economic factor evaluation index B3, which is refined into equipment investment evaluation index C 31 , Advance power generation benefit evaluation index C 32 and advance generation capacity price benefit evaluation index C 33 ;

[0023] The construction period factor evaluation index B4 is refined into the key line evaluation index C 41 And the evaluation index C of the construction period ahead of schedule 42 ;

[0024] Equipment factor evaluation index B5 is refined into equipment manufacturing cycle evaluation index C 51 and equipment amortization evaluation index C 52 .

[0025] Preferably, the scoring rule for each evaluation index in the criterion layer B is a 1-9 scale scoring method, and the judgment matrix F(B) of the criterion layer B after the assignment is obtained by using the scoring rule, which is specifically:

[0026] The criterion layer B has five evaluation indicators. Therefore, the judgment matrix F(B) is a 5*5 matrix. ij , i=1,2,3,4,5, j=1,2,3,4,5, represents the evaluation index B i And evaluation index B j Compared with the evaluation index B iThe specific scoring rules for the impact on solution level D are as follows:

[0027] If the evaluation index B i And evaluation index B j have equal importance, then the element F ij =1;

[0028] If the evaluation index B i Ratio evaluation index B j Slightly more important, then the element F ij =3;

[0029] If the evaluation index B i Ratio evaluation index B j Obviously important, then the element F ij =5;

[0030] If the evaluation index B i Ratio evaluation index B j Strongly important, then the element F ij =7;

[0031] If the evaluation index B i Ratio evaluation index B j Extremely important, then element F ij =9;

[0032] If it is between equally important and slightly important, then the element F ij = 2; if it is between slightly important and significantly important, then the element F ij = 4; if it is between obviously important and strongly important, then the element F ij = 6; if it is between strongly important and extremely important, then the element F ij =8;

[0033] And, define the element F ij and F ji The reciprocals of each other, that is: F ij =1 / F ji ;

[0034] The values ​​are assigned through the scoring rules to obtain the judgment matrix F(B) of the criterion layer B after the assignment.

[0035] Preferably, the scoring rule for each evaluation indicator in the sub-criteria layer C is a 1-9 scale scoring method, which is the same as the scoring rule for each evaluation indicator in the criterion layer B.

[0036] Preferably, in the scheme layer D having M schemes of underground cavern TBM applicability levels, M=2, and therefore, there are schemes with high underground cavern TBM applicability and schemes with low underground cavern TBM applicability.

[0037] Preferably, the scoring rules for each solution in the solution layer D, and the judgment matrix F(D) of the solution layer D after the assignment, are specifically:

[0038] Assume that there are N evaluation indicators in the sub-criteria layer, expressed as: Evaluation indicator C n , n=1,2,…,N; the scheme layer D has two schemes, namely: scheme D1: a scheme with high applicability of underground cavern TBM; scheme D2: a scheme with low applicability of underground cavern TBM;

[0039] Then the judgment matrix F(D) of the solution layer D is an N*2 matrix. For the element F nk , k = 1 or 2, representing the evaluation index C n For Plan D k The specific scoring rules are as follows:

[0040] The N evaluation indicators in the sub-criteria layer are divided into qualitative evaluation indicators and quantitative evaluation indicators; among them, the qualitative evaluation indicators include the surrounding rock lithology evaluation index C 11 , Surrounding rock type evaluation index C 12 , surrounding rock strength evaluation index C 13 , Water inrush evaluation index C 14 And whether it is in the critical line evaluation index C 41 ; Each qualitative evaluation index has a significant impact on solution D k The degree of impact is determined using a 1 to 9 scale rating method;

[0041] The quantitative evaluation index includes the cave length evaluation index C 21 , Cavern slope evaluation index C 22 , Evaluation index of cavern turning radius C 23 , Equipment investment evaluation index C 31 , Advance power generation benefit evaluation index C 32 , Evaluation index of benefit of advance power generation capacity and electricity price C 33 , Evaluation index C of construction period advance situation 42 , Equipment manufacturing cycle evaluation index C 51 and equipment amortization evaluation index C 52 ; The quantitative evaluation indexes for scheme D k The scoring rules for the degree of impact are:

[0042] Set Scheme D1: The initial score of the scheme with high applicability of underground cavern TBM is 0;

[0043] The initial score of scheme D2: the scheme with low applicability of underground cavern TBM is set to 0;

[0044] Set the basic value of cavern length, basic value of cavern slope, basic value of cavern turning radius, basic value of equipment investment, basic value of advance power generation benefit, basic value of advance power generation capacity price benefit, basic value of advance construction period, basic value of equipment manufacturing cycle, and base value of equipment amortization respectively;

[0045] The scoring rules are as follows:

[0046]

[0047]

[0048] Among them: For each of the above evaluation indicators, after determining the score of one scheme, the score of the other scheme is the reciprocal of the determined score scheme;

[0049] Thus, the judgment matrix F(D) of the scheme layer D after the assignment can be determined.

[0050] Preferably, step 5: performing consistency check on each judgment matrix after assignment obtained in step 4, specifically:

[0051] Step 5.1: Each judgment matrix is ​​uniformly represented as: judgment matrix H; the rank of judgment matrix H is d; each element of judgment matrix H is represented as: h xy , where x = 1, 2, ..., d, y = 1, 2, ..., d;

[0052] Step 5.2: Use the following formula to get the eigenvector W of the judgment matrix H x :

[0053]

[0054] Each feature vector W x Standardize to obtain the standardized feature vector W = (W1, W2,,, W d ) T ;

[0055] Step 5.3: Calculate the maximum eigenvalue λ of the judgment matrix H max :

[0056]

[0057] Step 5.4: Calculate the consistency index CI

[0058]

[0059] Step 5.5: According to the rank d of the judgment matrix H, look up the following table to determine the corresponding average random consistency index RI:

[0060]

[0061]

[0062] Step 5.6: Calculate the consistency ratio CR

[0063]

[0064] If CR<0.1, the judgment matrix H passes the consistency test; if CR>0.1, the judgment matrix H does not meet the consistency requirements and needs to be revised.

[0065] Preferably, in step 6, the weights are obtained according to the judgment matrix, specifically:

[0066] The standardized feature vector W obtained in step 5.2 is W = (W1, W2,,, W d ) T , which is the weight vector corresponding to the judgment matrix H, namely: W1,W2,,,W d , are the weights of each evaluation index of the judgment matrix H.

[0067] Preferably, in step 7, the following method is used to obtain the total score of TBM suitability evaluation for the underground cavern of the pumped storage power station:

[0068] For each evaluation index of sub-criteria layer C, assuming that its weight on solution layer D is β1, the weight of the evaluation index of the criterion layer B directly associated with it on solution layer D is α1, and the weight of a solution in solution layer D affected by the evaluation index of sub-criteria layer C is γ1, then according to the formula S1 = α1β1γ1, the score obtained by the evaluation index of sub-criteria layer C is obtained;

[0069] For each evaluation index of the sub-criteria layer C, a score is calculated, and then the scores are added together to obtain the final total score for the TBM suitability evaluation of the underground cavern of the pumped-storage power station.

[0070] The TBM suitability evaluation method for underground caverns of pumped storage power stations provided by the present invention has the following advantages:

[0071] The present invention provides a suitability evaluation method for TBM in underground caverns of pumped-storage power stations. The method is based on analytic hierarchy process and comprehensive qualitative and quantitative evaluation. The method fully considers the project characteristics of different pumped-storage power stations, quantitatively determines evaluation indicators and scoring rules, and conducts quantitative evaluation. A more reasonable solution is quantitatively obtained through weighting, so as to achieve the purpose of improving the scientificity, rationality and accuracy of decision-making application. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] The drawings constituting a part of the present application are used to provide a further understanding of the present application. The illustrative embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application.

[0073] Figure 1 It is a flow chart of a TBM suitability evaluation method for an underground cavern of a pumped storage power station provided by the present invention;

[0074] Figure 2 It is a structural block diagram of a method for evaluating the suitability of underground cavern TBM equipment application according to the present invention. DETAILED DESCRIPTION

[0075] The technical solutions 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; it is obvious that the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments, and all other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making creative work are within the scope of protection of the present invention.

[0076] In view of the defects and shortcomings of the existing analysis methods, the present invention provides a TBM suitability evaluation method for underground caverns (traffic tunnels, ventilation tunnels, drainage corridors, waterway systems, etc.) of pumped-storage power stations based on hierarchical analysis method and comprehensive qualitative and quantitative evaluation. It fully considers the project characteristics of different pumped-storage power stations, quantitatively determines the evaluation indicators and scoring rules, and conducts quantitative evaluation. A more reasonable solution is quantitatively obtained through the size of weights, so as to achieve the purpose of improving the scientificity, rationality and accuracy of decision-making applications.

[0077] See also Figure 1-2 The present invention provides a TBM suitability evaluation method for an underground cavern of a pumped storage power station, comprising the following steps:

[0078] Step 1: Based on the principle of hierarchical analysis method, the evaluation indicators are determined in combination with the characteristics of pumped storage power stations and TBM equipment conditions, so as to establish an evaluation model with a hierarchical structure, which is the target layer A, the criterion layer B, the sub-criterion layer C and the scheme layer D from top to bottom;

[0079] Step 2: construct the judgment matrix F(B) of the criterion layer B, the judgment matrix F(C) of the sub-criterion layer C, and the judgment matrix F(D) of the solution layer D respectively;

[0080] Step 3: Determine the scoring rules for each evaluation indicator in the criterion layer B, the scoring rules for each evaluation indicator in the sub-criterion layer C, and the scoring rules for each solution in the solution layer D;

[0081] Step 4: According to the scoring rules determined in step 3, assign values ​​to the elements in the judgment matrices constructed in step 2, thereby obtaining the assigned judgment matrix F(B) of the criterion layer B, the judgment matrix F(C) of the sub-criterion layer C, and the judgment matrix F(D) of the solution layer D;

[0082] Step 5: Perform consistency check on each judgment matrix after assignment obtained in step 4, and execute step 6 after passing the check;

[0083] Step 6: Analyze the judgment matrix F(B) of the criterion layer B, the judgment matrix F(C) of the sub-criterion layer C, and the judgment matrix F(D) of the solution layer D after the assignment, and obtain the weight of each evaluation index of the criterion layer B on the solution layer D, the weight of each evaluation index of the sub-criterion layer C on the solution layer D, and the weight of each solution in the solution layer D affected by each evaluation index of the sub-criterion layer C;

[0084] Step 7: According to the order of the levels from top to bottom, the weights of each layer are correlated and calculated to obtain the total score of the TBM suitability evaluation of the underground cavern of the pumped-storage power station. According to the total score of the TBM suitability evaluation of the underground cavern of the pumped-storage power station, the degree of TBM suitability of the underground cavern of the pumped-storage power station is quantitatively determined.

[0085] The following describes steps 1 to 7 in detail:

[0086] Step 1: Based on the principle of hierarchical analysis method, the evaluation indicators are determined in combination with the characteristics of pumped storage power stations and TBM equipment conditions, so as to establish an evaluation model with a hierarchical structure, which is the target layer A, the criterion layer B, the sub-criterion layer C and the scheme layer D from top to bottom;

[0087] Among them, the target layer A is the root node, which is the TBM suitability evaluation target of the underground caverns (traffic tunnels, ventilation tunnels, drainage galleries and waterway systems) of the pumped storage power station;

[0088] The direct lower layer of the target layer A is the criterion layer B, which includes five evaluation indicators: geological factor evaluation indicator B1, technical factor evaluation indicator B2, economic factor evaluation indicator B3, construction period factor evaluation indicator B4 and equipment factor evaluation indicator B5;

[0089] According to the subordinate relationship, for each evaluation index B of the criterion layer B i Further refine it into multiple evaluation indicators, so as to obtain the sub-criteria layer C; where i = 1, 2, 3, 4, 5. As an example, the evaluation indicators in the sub-criteria layer C are specifically:

[0090] Geological factor evaluation index B1 is refined into surrounding rock lithology evaluation index C 11 , Surrounding rock type evaluation index C 12 , surrounding rock strength evaluation index C13 And water inrush evaluation index C 14 ;

[0091] Technical factor evaluation index B2, which is refined into cave length evaluation index C 21 , Cavern slope evaluation index C 22 And the cavern turning radius evaluation index C 23 ;

[0092] Economic factor evaluation index B3, which is refined into equipment investment evaluation index C 31 , Advance power generation benefit evaluation index C 32 and the benefit evaluation index C of the advance power generation capacity price 33 ;

[0093] The construction period factor evaluation index B4 is refined into the key line evaluation index C 41 And the evaluation index C of the construction period ahead of schedule 42 ;

[0094] Equipment factor evaluation index B5 is refined into equipment manufacturing cycle evaluation index C 51 and equipment amortization evaluation index C 52 .

[0095] The scheme layer D has M schemes of underground cavern TBM applicability levels, namely schemes D1, D2, ..., D M ;

[0096] As an example, among the solutions in solution layer D having M underground cavern TBM applicability levels, M=2, and therefore, there are solutions with high underground cavern TBM applicability and solutions with low underground cavern TBM applicability.

[0097] Step 2: Construct the judgment matrix F(B) of the criterion layer B, the judgment matrix F(C) of the sub-criterion layer C, and the judgment matrix F(D) of the solution layer D respectively;

[0098] in:

[0099] The judgment matrix F(B) of the criterion layer B is a matrix formed by comparing the influence of the five criterion layer evaluation indicators, namely, geological factor evaluation index B1, technical factor evaluation index B2, economic factor evaluation index B3, construction period factor evaluation index B4 and equipment factor evaluation index B5, on the scheme layer D.

[0100] The judgment matrix F(C) of the sub-criteria layer C includes five judgment matrices, namely: the sub-criteria layer judgment matrix F(C1) for the geological factor evaluation index B1, the sub-criteria layer judgment matrix F(C2) for the technical factor evaluation index B2, the sub-criteria layer judgment matrix F(C3) for the economic factor evaluation index B3, the sub-criteria layer judgment matrix F(C4) for the construction period factor evaluation index B4, and the sub-criteria layer judgment matrix F(C5) for the equipment factor evaluation index B5; for each sub-criteria layer judgment matrix F(C i ), is the corresponding evaluation index B i Among the further refined evaluation indicators of each sub-criteria layer, the matrix formed by the relative comparison of the impact degree on the solution layer D is formed;

[0101] The judgment matrix F(D) of the scheme layer D is the applicability level of each underground cavern TBM scheme D m , m=1,2,…,M, a matrix formed by the influence degree of evaluation indicators of each sub-criteria layer;

[0102] Step 3: Determine the scoring rules for each evaluation indicator in the criterion layer B, the scoring rules for each evaluation indicator in the sub-criterion layer C, and the scoring rules for each solution in the solution layer D;

[0103] Step 4: According to the scoring rules determined in step 3, assign values ​​to the elements in the judgment matrices constructed in step 2, thereby obtaining the assigned judgment matrix F(B) of the criterion layer B, the judgment matrix F(C) of the sub-criterion layer C, and the judgment matrix F(D) of the solution layer D;

[0104] (I) Judgment matrix F(B) of criterion layer B

[0105] The scoring rule for each evaluation index in the criterion layer B is a 1-9 scale scoring method. The scoring rule is adopted and the expert scoring is performed to obtain the judgment matrix F(B) of the criterion layer B after the assignment, which is specifically:

[0106] The criterion layer B has five evaluation indicators. Therefore, the judgment matrix F(B) is a 5*5 matrix. ij , i=1,2,3,4,5, j=1,2,3,4,5, represents the evaluation index B i And evaluation index B j Compared with the evaluation index B i The specific scoring rules for the impact on solution level D are as follows:

[0107] If the evaluation index B i and evaluation index B j have equal importance, then the element F ij =1;

[0108] If the evaluation index Bi Ratio evaluation index B j Slightly more important, then the element F ij =3;

[0109] If the evaluation index B i Ratio evaluation index B j Obviously important, then the element F ij =5;

[0110] If the evaluation index B i Ratio evaluation index B j Strongly important, then the element F ij =7;

[0111] If the evaluation index B i Ratio evaluation index B j Extremely important, then element F ij =9;

[0112] If it is between equally important and slightly important, then the element F ij = 2; if it is between slightly important and significantly important, then the element F ij = 4; if it is between obviously important and strongly important, then the element F ij = 6; if it is between strongly important and extremely important, then the element F ij =8;

[0113] And, define the element F ij and F ji The reciprocals of each other, that is: F ij =1 / F ji ;

[0114] The values ​​are assigned through the scoring rules to obtain the judgment matrix F(B) of the criterion layer B after the assignment.

[0115] The scoring method of 1 to 9 scale is shown in Table 1:

[0116] Table 1: Scoring method on a scale of 1 to 9

[0117]

[0118] As an example, the criterion layer scoring results are shown in Table 2:

[0119] Table 2: Criteria level scoring results

[0120] Geological factors Technical factors Economic factors Duration Factor Equipment Factors Geological factors 1 3 1 / 7 1 / 6 1 / 4 Technical factors 1 / 3 1 1 / 8 1 / 5 1 / 2 Economic factors 7 8 1 2 3 Duration Factor 6 5 1 / 2 1 3 Equipment Factors 4 2 1 / 3 1 / 3 1

[0121] (II) Judgment Matrix F(C) of Sub-Criteria Layer C

[0122] The scoring rule for each evaluation indicator in the sub-criteria layer C is a 1-9 scale scoring method, which is the same as the scoring rule for each evaluation indicator in the criterion layer B.

[0123] As an example, sub-criteria layer C has the following five scoring tables:

[0124] Table 3: Geological factor sub-criteria layer scoring table

[0125] Geological factors Surrounding rock lithology Surrounding rock type Surrounding rock strength Water inrush Surrounding rock lithology 1 2 1 / 4 1 / 2 Surrounding rock type 1 / 2 1 1 / 4 1 / 2 Surrounding rock strength 4 4 1 4 Water inrush 2 2 1 / 4 1

[0126] Table 4: Technical factor sub-criteria level scoring table

[0127] Technical factors Chamber length Cavern slope Turning radius of the cave Chamber length 1 4 2 Cavern slope 1 / 4 1 1 / 2 Turning radius of the cave 1 / 2 2 1

[0128] Table 5: Economic factor sub-criteria level scoring table

[0129] Economic factors Equipment investment Early power generation benefits Benefits of early generation capacity price Equipment investment 1 1 / 2 1 / 8 Early power generation benefits 2 1 1 / 2 Benefits of early generation capacity price 8 2 1

[0130] Table 6: Scoring table for sub-criteria of construction period factors

[0131] Duration Factor Is it on the critical path? Construction schedule ahead of schedule Is it on the critical path? 1 1 / 4 Construction schedule ahead of schedule 4 1

[0132] Table 7: Equipment factor sub-criteria level scoring table

[0133] Equipment Factors Equipment manufacturing cycle Equipment amortization Equipment manufacturing cycle 1 1 / 3 Equipment amortization 3 1

[0134] (III) Judgment matrix F(D) of solution level D

[0135] The scoring rules for each solution in the solution layer D and the judgment matrix F(D) of the solution layer D after the assignment are as follows:

[0136] Assume that there are N evaluation indicators in the sub-criteria layer, expressed as: Evaluation indicator C n , n=1,2,…,N; the scheme layer D has two schemes, namely: Scheme D1: a scheme with high applicability of underground cavern TBM; Scheme D2: a scheme with low applicability of underground cavern TBM;

[0137] Then the judgment matrix F(D) of the solution layer D is an N*2 matrix. For the elements F nk , k = 1 or 2, representing the evaluation index C n For Plan D k The specific scoring rules are as follows:

[0138] The N evaluation indicators in the sub-criteria layer are divided into qualitative evaluation indicators and quantitative evaluation indicators; among them, the qualitative evaluation indicators include the surrounding rock lithology evaluation index C 11 , Surrounding rock type evaluation index C 12 , surrounding rock strength evaluation index C 13 , Water inrush evaluation index C14 And whether it is in the critical line evaluation index C 41 ; Each qualitative evaluation index has a significant impact on solution D k The degree of impact is determined using a 1 to 9 scale rating method;

[0139] The quantitative evaluation index includes the cave length evaluation index C 21 , Cavern slope evaluation index C 22 , Evaluation index of cavern turning radius C 23 , Equipment investment evaluation index C 31 , Advance power generation benefit evaluation index C 32 , Evaluation index of benefit of advance power generation capacity and electricity price C 33 , Evaluation index C of construction period advance situation 42 , Equipment manufacturing cycle evaluation index C 51 and equipment amortization evaluation index C 52 ; The quantitative evaluation indexes for scheme D k The scoring rules for the degree of impact are:

[0140] Set Scheme D1: The initial score of the scheme with high applicability of underground cavern TBM is 0;

[0141] The initial score of scheme D2: the scheme with low applicability of underground cavern TBM is set to 0;

[0142] Set the basic value of cavern length, basic value of cavern slope, basic value of cavern turning radius, basic value of equipment investment, basic value of advance power generation benefit, basic value of advance power generation capacity electricity price benefit, basic value of advance construction period, basic value of equipment manufacturing cycle, and basic value of equipment amortization respectively; Note: the basic value is for the case where TBM is not used in the underground cavern of pumped-storage power station.

[0143] The scoring rules are as shown in Table 8:

[0144] Table 8: Scoring rules for the quantitative evaluation indicators at the sub-criteria level to the solution level

[0145]

[0146]

[0147] Among them: For each of the above evaluation indicators, after determining the score of one scheme, the score of the other scheme is the reciprocal of the determined score scheme;

[0148] Thus, the judgment matrix F(D) of the scheme layer D after the assignment can be determined.

[0149] As an example, for the qualitative evaluation index surrounding rock lithology evaluation index C in the sub-criteria layer 11 , Surrounding rock type evaluation index C 12, surrounding rock strength evaluation index C 13 , Water inrush evaluation index C 14 And whether it is in the critical line evaluation index C 41 , and the evaluation results of its impact on each solution in the solution layer are as follows:

[0150] Table 9: Scoring results of qualitative evaluation indicators at the sub-criteria level on the solution level

[0151] TBM has high applicability TBM has low applicability Surrounding rock lithology 2 1 / 2 Surrounding rock type 1 1 Surrounding rock strength 4 1 / 4 Water inrush 1 1 Is it on the critical path? 6 1 / 6

[0152] As an example, for the quantitative evaluation indicators in the sub-criteria layer, including the cave length evaluation indicator C 21 , Cavern slope evaluation index C 22 , Evaluation index of cavern turning radius C 23 , Equipment investment evaluation index C 31 , Advance power generation benefit evaluation index C 32 , Evaluation index of benefit of advance power generation capacity and electricity price C 33 , Evaluation index C of construction period advance situation 42 , Equipment manufacturing cycle evaluation index C 51 and equipment amortization evaluation index C 52 The evaluation results of its impact on each solution in the solution layer are shown in Table 10:

[0153] Table 10: Scoring results of the scheme-level quantitative evaluation indicators at the sub-criteria level

[0154]

[0155]

[0156] Step 5: Perform consistency check on each judgment matrix after assignment obtained in step 4, and execute step 6 after passing the check;

[0157] Step 5.1: Each judgment matrix is ​​uniformly represented as: judgment matrix H; the rank of judgment matrix H is d; each element of judgment matrix H is represented as: h xy , where x = 1, 2, ..., d, y = 1, 2, ..., d;

[0158] The judgment matrix has the following properties: element h xy >0;h xy =1 / h yx ;h xx =1;

[0159] When filling in, fill in h first xx =1 part, and then we only need to determine and fill in the d(d-1) / 2 elements of the upper triangle or the lower triangle.

[0160] Step 5.2: Use the following formula to get the eigenvector W of the judgment matrix H x :

[0161]

[0162] Each feature vector W x Standardize to obtain the standardized feature vector W = (W1, W2,,, W d ) T ;

[0163] Step 5.3: Calculate the maximum eigenvalue λ of the judgment matrix H max :

[0164]

[0165] Step 5.4: Calculate the consistency index (CI)

[0166]

[0167] Step 5.5: According to the rank d of the judgment matrix H, look up the following table to determine the corresponding average random consistency index RI (random index):

[0168] Table 11: Average random consistency index RI table (1000 times of positive reciprocal matrix calculation results)

[0169]

[0170]

[0171] Step 5.6: Calculate the consistency ratio CR

[0172]

[0173] If CR<0.1, the judgment matrix H passes the consistency test; if CR>0.1, the judgment matrix H does not meet the consistency requirements and needs to be revised.

[0174] Step 6: Analyze the judgment matrix F(B) of the criterion layer B, the judgment matrix F(C) of the sub-criterion layer C, and the judgment matrix F(D) of the solution layer D after the assignment, and obtain the weight of each evaluation index of the criterion layer B on the solution layer D, the weight of each evaluation index of the sub-criterion layer C on the solution layer D, and the weight of each solution in the solution layer D affected by each evaluation index of the sub-criterion layer C;

[0175] The weights are obtained according to the judgment matrix: The standardized feature vector W obtained in step 5.2 is W = (W1, W2,,, W d ) T , which is the weight vector corresponding to the judgment matrix H, namely: W1,W2,,,W d , are the weights of each evaluation index of the judgment matrix H.

[0176] As an example, the judgment matrix and weights of the criterion layer are shown in Table 12:

[0177] Table 12: Judgment matrix and weights of criterion layer

[0178] Geological factors Duration Factor Technical factors Equipment Factors Economic factors Eigenvector Weight value (%) Geological factors 1 0.167 3 0.25 0.143 0.447 6.448 Duration Factor 6 1 5 3 0.5 2.141 30.883 Technical factors 0.333 0.2 1 0.5 0.125 0.334 4.82 Equipment Factors 4 0.333 2 1 0.5 1.059 15.278 Economic factors 7 2 8 2 1 2.952 42.572

[0179] As an example, the judgment matrix and weights of the sub-criteria layer are shown in Tables 13 to 17:

[0180] Table 13: Judgment matrix and weights of geological factor sub-criteria layers

[0181] Surrounding rock lithology Surrounding rock type Surrounding rock strength Water inrush Eigenvector Weight value (%) Surrounding rock lithology 1 0.5 0.25 0.5 0.5 9.929 Surrounding rock type 2 1 0.25 0.5 0.707 14.042 Surrounding rock strength 4 4 1 4 2.828 56.169 Water inrush 2 2 0.25 1 1 19.859

[0182] Table 14: Judgment matrix and weights of the sub-criteria layer of the construction period factor

[0183] Is it on the critical path? Construction schedule ahead of schedule Eigenvector Weight value (%) Is it on the critical path? 1 0.25 0 20.000 Construction schedule ahead of schedule 4 1 0 80.000

[0184] Table 15: Judgment matrix and weights of technical factor sub-criteria layer

[0185] Chamber length Cavern slope Turning radius of the cave Eigenvector Weight value (%) Chamber length 1 0.25 3 0.909 21.764 Cavern slope 4 1 6 2.884 69.096 Turning radius of the cave 0.333 0.167 1 0.382 9.14

[0186] Table 16: Judgment matrix and weights of equipment factor sub-criteria layer

[0187] Equipment manufacturing cycle Equipment amortization Eigenvector Weight value (%) Equipment manufacturing cycle 1 0.333 0 25.000 Equipment amortization 3 1 0 75.000

[0188] Table 17: Judgment matrix and weights of economic factor sub-criteria layer

[0189] Equipment investment Early power generation benefits Benefits of early generation capacity price Eigenvector Weight value (%) Equipment investment 1 0.5 0.125 0.397 10.132 Early power generation benefits 2 1 0.5 1 25.532 Benefits of early generation capacity price 8 2 1 2.52 64.336

[0190] In addition, all the above judgment matrices have passed the consistency test, as follows:

[0191] The weight calculation results show that the weight of geological factors is 6.448%, the weight of construction period factors is 30.883%, the weight of technical factors is 4.82%, the weight of equipment factors is 15.278%, and the weight of economic factors is 42.572%. The maximum weight of the indicator is economic factors (42.572), and the minimum is technical factors (4.82). The maximum characteristic root is 5.348, and the corresponding RI value is 1.11 according to the RI table. Therefore, CR = CI / RI = 0.078 ≤ 0.1, passing the one-time test.

[0192] The weight calculation results show that the weight of surrounding rock lithology is 9.929%, the weight of surrounding rock category is 14.042%, the weight of surrounding rock strength is 56.169%, and the weight of water inflow is 19.859%. The maximum weight of the indicator is surrounding rock strength (56.169), and the minimum weight is surrounding rock lithology (9.929). The maximum characteristic root is 4.121, and the corresponding RI value is 0.882 according to the RI table. Therefore, CR = CI / RI = 0.046 ≤ 0.1, passing the one-time test.

[0193] The weight calculation results show that the weight of the cave length is 21.764%, the weight of the cave slope is 69.096%, and the weight of the cave turning radius is 9.14%. The maximum weight of the indicator is the cave slope (69.096), and the minimum weight is the cave turning radius (9.14). The maximum characteristic root is 3.054, and the corresponding RI value is 0.525 according to the RI table. Therefore, CR = CI / RI = 0.051 ≤ 0.1, passing the one-time test.

[0194] The weight calculation results show that the weight of equipment investment is 10.132%, the weight of advance power generation benefit is 25.532%, and the weight of advance power generation capacity price benefit is 64.336%. The maximum indicator weight is advance power generation capacity price benefit (64.336), and the minimum is equipment investment (10.132). The maximum characteristic root is 3.054, and the corresponding RI value is 0.525 according to the RI table. Therefore, CR = CI / RI = 0.051 ≤ 0.1, passing the one-time test.

[0195] Step 7: According to the order of the levels from top to bottom, the weights of each layer are correlated and calculated to obtain the total score of the TBM suitability evaluation of the underground cavern of the pumped-storage power station. According to the total score of the TBM suitability evaluation of the underground cavern of the pumped-storage power station, the degree of TBM suitability of the underground cavern of the pumped-storage power station is quantitatively determined.

[0196] In step 7, the following method is used to obtain the total score of TBM suitability evaluation for underground caverns of pumped storage power stations:

[0197] For each evaluation index of sub-criteria layer C, assuming that its weight on solution layer D is β1, the weight of the evaluation index of the criterion layer B directly associated with it on solution layer D is α1, and the weight of a solution in solution layer D affected by the evaluation index of sub-criteria layer C is γ1, then according to the formula S1 = α1β1γ1, the score obtained by the evaluation index of sub-criteria layer C is obtained;

[0198] For each evaluation index of the sub-criteria layer C, a score is calculated, and then the scores are added together to obtain the final total score for the TBM suitability evaluation of the underground cavern of the pumped-storage power station.

[0199] For the above table example, the weight of each evaluation index for the decision-making target is synthesized layer by layer. Through quantitative comparison of the weights, the best solution for TBM suitability evaluation is TBM with high suitability, and its quantitative score is 0.542.

[0200] The present invention also proposes a TBM suitability evaluation system for underground caverns of a pumped storage power station, comprising:

[0201] The decision model construction module constructs a criterion layer based on the evaluation factors of TBM application in underground caverns of pumped storage power stations, constructs a sub-criterion layer based on the sub-factors affecting each evaluation factor, and constructs a judgment layer based on the suitability scheme of TBM in underground caverns;

[0202] The evaluation index scoring rule determination and expert scoring module are used to obtain the scores of the comparison of the importance of the elements of the criterion layer, the comparison of the importance of the sub-criterion layer, and the importance of each factor of the sub-criterion layer to the solution layer;

[0203] The criterion layer weight determination module determines the weight of each factor in the criterion layer, the weight of each factor in the sub-criterion layer, and the weight of each factor in the sub-criterion layer relative to each solution in the solution layer through scoring and hierarchical analysis method;

[0204] The module for determining the degree of suitability is used to multiply the weights of each factor at the scheme level to each factor at the sub-criterion level with the weights of each factor at the sub-criterion level corresponding to each factor at the criterion level, obtain the importance ranking matrix of each factor at the scheme level to each factor at the criterion level, and multiply the importance ranking matrix with the weights of each factor at the corresponding criterion level to obtain the score of the degree of suitability;

[0205] The evaluation result acquisition module is used to select the scheme with the highest score as the suitability evaluation result of TBM application in the underground cavern of the pumped storage power station.

[0206] The present invention provides a suitability evaluation method for TBM in underground caverns of pumped-storage power stations. The method is based on analytic hierarchy process and comprehensive qualitative and quantitative evaluation. The method fully considers the project characteristics of different pumped-storage power stations, quantitatively determines evaluation indicators and scoring rules, and conducts quantitative evaluation. A more reasonable solution is quantitatively obtained through weighting, so as to achieve the purpose of improving the scientificity, rationality and accuracy of decision-making application.

[0207] The embodiments described above are only used to illustrate the technical ideas and features of the present invention, and their purpose is to enable those skilled in the art to understand the contents of the present invention and implement them accordingly. The patent scope of the present invention cannot be limited only by this embodiment, that is, any equivalent changes or modifications made to the spirit disclosed by the present invention still fall within the patent scope of the present invention.

Claims

1. A method for evaluating the suitability of TBM for underground caverns in pumped storage power stations, characterized in that: The following steps are involved: Step 1: Based on the principle of hierarchical analysis method, the evaluation indicators are determined in combination with the characteristics of pumped storage power stations and TBM equipment conditions, so as to establish an evaluation model with a hierarchical structure, which is the target layer A, the criterion layer B, the sub-criterion layer C and the scheme layer D from top to bottom; The target layer A is the root node, which is the TBM suitability evaluation target for the underground cavern of the pumped storage power station. The direct lower layer of the target layer A is the criterion layer B, which includes the geological factor evaluation index B1, the technical factor evaluation index B2, the economic factor evaluation index B3, the construction period factor evaluation index B4 and the equipment factor evaluation index B5. For each evaluation index B of the criterion layer B, i Further refined into multiple evaluation indicators, thereby obtaining a sub-criteria layer C; wherein i = 1, 2, 3, 4, 5; the scheme layer D has M schemes of underground cavern TBM applicability levels, namely schemes D1, D2, ..., D M ; Where: for each evaluation index B of the criterion layer B i Further refine it into multiple evaluation indicators to obtain the sub-criteria layer C, specifically: Geological factor evaluation index B1 is refined into surrounding rock lithology evaluation index C 11 , Surrounding rock type evaluation index C 12 , surrounding rock strength evaluation index C 13 And water inrush evaluation index C 14 ; Technical factor evaluation index B2, which is refined into cave length evaluation index C 21 , Cavern slope evaluation index C 22 And the cavern turning radius evaluation index C 23 ; Economic factor evaluation index B3, which is refined into equipment investment evaluation index C 31 , Advance power generation benefit evaluation index C 32 and advance generation capacity price benefit evaluation index C 33 ; The construction period factor evaluation index B4 is refined into the key line evaluation index C 41 And the evaluation index C of the construction period ahead of schedule 42 ; Equipment factor evaluation index B5 is refined into equipment manufacturing cycle evaluation index C 51 and equipment amortization evaluation index C 52 ; Among them: in the scheme layer D with M underground cavern TBM applicability levels, M=2, therefore, there are schemes with high underground cavern TBM applicability and schemes with low underground cavern TBM applicability; Step 2: Construct the judgment matrix F(B) of the criterion layer B, the judgment matrix F(C) of the sub-criterion layer C, and the judgment matrix F(D) of the solution layer D respectively; Among them: the judgment matrix F(B) of the criterion layer B is a matrix formed by comparing the influence of the five criterion layer evaluation indicators, namely, geological factor evaluation index B1, technical factor evaluation index B2, economic factor evaluation index B3, construction period factor evaluation index B4 and equipment factor evaluation index B5, on the scheme layer D. The judgment matrix F(C) of the sub-criteria layer C includes five judgment matrices, namely: the sub-criteria layer judgment matrix F(C1) for the geological factor evaluation index B1, the sub-criteria layer judgment matrix F(C2) for the technical factor evaluation index B2, the sub-criteria layer judgment matrix F(C3) for the economic factor evaluation index B3, the sub-criteria layer judgment matrix F(C4) for the construction period factor evaluation index B4, and the sub-criteria layer judgment matrix F(C5) for the equipment factor evaluation index B5; for each sub-criteria layer judgment matrix F(C i ), is the corresponding evaluation index B i Among the further refined evaluation indicators of each sub-criteria layer, the matrix formed by the relative comparison of the impact degree on the solution layer D is formed; The judgment matrix F(D) of the scheme layer D is the applicability level of each underground cavern TBM scheme D m , m=1,2,…,M, a matrix formed by the influence degree of evaluation indicators of each sub-criteria layer; Step 3: Determine the scoring rules for each evaluation indicator in the criterion layer B, the scoring rules for each evaluation indicator in the sub-criterion layer C, and the scoring rules for each solution in the solution layer D; Step 4: According to the scoring rules determined in step 3, assign values ​​to the elements in the judgment matrices constructed in step 2, thereby obtaining the assigned judgment matrix F(B) of the criterion layer B, the judgment matrix F(C) of the sub-criterion layer C, and the judgment matrix F(D) of the solution layer D; Among them: the scoring rules of each solution in the solution layer D, and the judgment matrix F(D) of the solution layer D after the assignment, are specifically: Assume that there are N evaluation indicators in the sub-criteria layer, expressed as: Evaluation indicator C n , n=1,2,…,N; the scheme layer D has two schemes, namely: Scheme D1: a scheme with high applicability of underground cavern TBM; Scheme D2: a scheme with low applicability of underground cavern TBM; Then the judgment matrix F(D) of the solution layer D is an N*2 matrix. For the elements F nk , k = 1 or 2, representing the evaluation index C n For Plan D k The specific scoring rules are as follows: The N evaluation indicators in the sub-criteria layer are divided into qualitative evaluation indicators and quantitative evaluation indicators; among them, the qualitative evaluation indicators include the surrounding rock lithology evaluation index C 11 , Surrounding rock type evaluation index C 12 , surrounding rock strength evaluation index C 13 , Water inrush evaluation index C 14 And whether it is in the critical line evaluation index C 41 ; Each qualitative evaluation index has a significant impact on solution D k The degree of impact is determined using a 1 to 9 scale rating method; The quantitative evaluation index includes the cave length evaluation index C 21 , Cavern slope evaluation index C 22 , Evaluation index of cavern turning radius C 23 , Equipment investment evaluation index C 31 , Advance power generation benefit evaluation index C 32 , Evaluation index of benefit of advance power generation capacity and electricity price C 33 , Evaluation index C of construction period advance situation 42 , Equipment manufacturing cycle evaluation index C 51 and equipment amortization evaluation index C 52 ; The quantitative evaluation indexes for scheme D k The scoring rules for the degree of impact are: Set Scheme D1: The initial score of the scheme with high applicability of underground cavern TBM is 0; The initial score of scheme D2: the scheme with low suitability for underground cavern TBM is set to 0; Set the basic value of cavern length, basic value of cavern slope, basic value of cavern turning radius, basic value of equipment investment, basic value of advance power generation benefit, basic value of advance power generation capacity price benefit, basic value of advance construction period, basic value of equipment manufacturing cycle, and base value of equipment amortization respectively; The scoring rules are as follows: Among them: For each of the above evaluation indicators, after determining the score of one scheme, the score of the other scheme is the reciprocal of the determined score scheme; Thus, the judgment matrix F(D) of the scheme layer D after the assignment can be determined; Step 5: Perform consistency check on each judgment matrix after assignment obtained in step 4, and execute step 6 after passing the check; Step 6: Analyze the judgment matrix F(B) of the criterion layer B, the judgment matrix F(C) of the sub-criterion layer C, and the judgment matrix F(D) of the solution layer D after the assignment, and obtain the weight of each evaluation index of the criterion layer B on the solution layer D, the weight of each evaluation index of the sub-criterion layer C on the solution layer D, and the weight of each solution in the solution layer D affected by each evaluation index of the sub-criterion layer C; Step 7: According to the order of the layers from top to bottom, the weights of each layer are correlated and calculated to obtain the total score of the TBM suitability evaluation of the underground cavern of the pumped-storage power station. According to the total score of the TBM suitability evaluation of the underground cavern of the pumped-storage power station, the degree of TBM suitability of the underground cavern of the pumped-storage power station is quantitatively determined; 2. A TBM suitability evaluation method for underground caverns of a pumped storage power station according to claim 1, characterized in that: The scoring rule for each evaluation index in the criterion layer B is a 1-9 scale scoring method. The judgment matrix F(B) of the criterion layer B after the assignment is obtained by using the scoring rule, which is specifically: The criterion layer B has five evaluation indicators. Therefore, the judgment matrix F(B) is a 5*5 matrix. ij , i=1,2,3,4,5, j=1,2,3,4,5, represents the evaluation index B i And evaluation index B j Compared with the evaluation index B i The specific scoring rules for the impact on solution level D are as follows: If the evaluation index B i and evaluation index B j have equal importance, then the element F ij =1; If the evaluation index B i Ratio evaluation index B j Slightly more important, then the element F ij =3; If the evaluation index B i Ratio evaluation index B j Obviously important, then the element F ij =5; If the evaluation index B i Ratio evaluation index B j Strongly important, then the element F ij =7; If the evaluation index B i Ratio evaluation index B j Extremely important, then element F ij =9; If it is between equally important and slightly important, then the element F ij = 2; if it is between slightly important and significantly important, then the element F ij = 4; if it is between obviously important and strongly important, then the element F ij = 6; if it is between strongly important and extremely important, then the element F ij =8; And, define the element F ij and F ji The reciprocals of each other, that is: F ij =1 / F ji ; The values ​​are assigned through the scoring rules to obtain the judgment matrix F(B) of the criterion layer B after the assignment.

3. A TBM suitability evaluation method for underground caverns of a pumped storage power station according to claim 1, characterized in that: The scoring rule for each evaluation indicator in the sub-criteria layer C is a 1-9 scale scoring method, which is the same as the scoring rule for each evaluation indicator in the criterion layer B.

4. A method for evaluating the suitability of a TBM for an underground cavern of a pumped storage power station according to claim 1, characterized in that: Step 5: Perform consistency check on each judgment matrix after assignment obtained in step 4, specifically: Step 5.1: Each judgment matrix is ​​uniformly represented as: judgment matrix H; the rank of judgment matrix H is d; each element of judgment matrix H is represented as: h xy , where x = 1, 2, ..., d, y = 1, 2, ..., d; Step 5.2: Use the following formula to get the eigenvector W of the judgment matrix H x : Each feature vector W x Standardize to obtain the standardized feature vector W = (W1, W2,,, W d ) T ; Step 5.3: Calculate the maximum eigenvalue λ of the judgment matrix H max : Step 5.4: Calculate the consistency index CI Step 5.5: According to the rank d of the judgment matrix H, look up the following table to determine the corresponding average random consistency index RI: Step 5.6: Calculate the consistency ratio CR If CR<0.1, the judgment matrix H passes the consistency test; if CR>0.1, the judgment matrix H does not meet the consistency requirements and needs to be revised.

5. A method for evaluating the suitability of TBM for underground caverns of a pumped storage power station according to claim 4, characterized in that: In step 6, the weights are obtained according to the judgment matrix, specifically: The standardized feature vector W obtained in step 5.2 is W = (W1, W2,,, W d ) T , which is the weight vector corresponding to the judgment matrix H, namely: W1,W2,,,W d , are the weights of each evaluation index of the judgment matrix H.

6. A method for evaluating the suitability of TBM for underground caverns of a pumped storage power station according to claim 5, characterized in that: In step 7, the following method is used to obtain the total score of TBM suitability evaluation for underground caverns of pumped storage power stations: For each evaluation index of sub-criteria layer C, assuming that its weight on solution layer D is β1, the weight of the evaluation index of the criterion layer B directly associated with it on solution layer D is α1, and the weight of a solution in solution layer D affected by the evaluation index of sub-criteria layer C is γ1, then according to the formula S1 = α1β1γ1, the score obtained by the evaluation index of sub-criteria layer C is obtained; For each evaluation index of the sub-criteria layer C, a score is calculated, and then the scores are added together to obtain the final total score for the TBM suitability evaluation of the underground cavern of the pumped-storage power station.

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