AHP-CRITIC-based ultra-high voltage transmission line risk fuzzy comprehensive assessment method and device

Abstract

The invention discloses an ultra-high voltage transmission line risk fuzzy comprehensive assessment method and device based on AHP-CRITIC, and the method comprises the steps: selecting a corresponding ultra-high voltage transmission line risk assessment index according to the ultra-high voltage transmission line risk, and determining the ultra-high voltage transmission line risk assessment index as a quality assessment factor set for risk assessment, determining a multi-level fuzzy comment set according to the risk of the ultra-high voltage transmission line; calculating subjective weights of evaluation indexes based on an AHP method; calculating objective weights of evaluation indexes based on a CRITIC method; calculating a comprehensive weight in combination with the subjective weight and the objective weight; and performing risk fuzzy comprehensive assessment on the ultra-high voltage transmission line in combination with the comprehensive weight. The ultra-high voltage transmission line risk fuzzy comprehensive assessment method based on AHP-CRITIC is efficient and accurate, and meets actual application requirements.

Description

Technical Field

[0001] This invention belongs to the field of power transmission risk assessment technology, specifically, it relates to a fuzzy comprehensive assessment method and device for risks of ultra-high voltage transmission lines based on AHP-CRITIC. Background Technology

[0002] The large-scale transmission of new energy power, the need for wide-area energy supply and demand balance, and the emergence of new technologies such as high-capacity and high-efficiency converters have brought profound changes and challenges to traditional power transmission technologies. Ultra-high voltage (UHV) transmission line technology, based on traditional transmission technologies, uses new technologies to improve transmission capacity and efficiency, achieving efficient, intelligent, and environmentally friendly power transmission. However, existing research on UHV transmission lines mostly focuses on problems encountered during the operation of UHV transmission line projects and proposes improvement measures for specific problems. In terms of risk assessment, it mainly focuses on the overall risk assessment of the power grid, lacking a comprehensive assessment scheme for the risks of UHV transmission lines. Summary of the Invention

[0003] The main objective of this invention is to provide a fuzzy comprehensive risk assessment method, device, terminal equipment, and storage medium for ultra-high voltage transmission lines based on AHP-CRITIC, aiming to solve the technical problem that existing risk assessments focus on the overall risk assessment of the power grid and lack a comprehensive risk assessment scheme for ultra-high voltage transmission lines.

[0004] In a first aspect, the present invention provides a fuzzy comprehensive risk assessment method for ultra-high voltage transmission lines based on AHP-CRITIC, comprising the following steps:

[0005] S1. Select corresponding UHV transmission line risk assessment indicators based on the risks of UHV transmission lines, and determine the UHV transmission line risk assessment indicators as the quality assessment factor set U for risk assessment, and determine a multi-level fuzzy comment set V based on the risks of UHV transmission lines;

[0006] S2. Calculate the subjective weights θ of the evaluation indicators based on the AHP method;

[0007] S3. Calculate the objective weights ω of the evaluation indicators based on the CRITIC method;

[0008] S4. Calculate the comprehensive weight by combining the subjective weight θ and the objective weight ω;

[0009] S5. A fuzzy comprehensive risk assessment of UHV transmission lines is conducted based on the aforementioned comprehensive weights, specifically including:

[0010] S51. Construct corresponding Gaussian membership functions for the quality assessment factor set U and the multi-level fuzzy comment set V;

[0011] S52. Calculate the fuzzy comprehensive evaluation matrix based on the Gaussian membership function.

[0012] S53. Based on the fuzzy comprehensive evaluation matrix and the comprehensive weight, the overall evaluation of the risk assessment system for ultra-high voltage transmission lines is obtained;

[0013] S54. Based on the overall assessment of the UHV transmission line risk assessment system, the comprehensive assessment results are quantitatively calculated.

[0014] In one specific embodiment, the risk assessment indicators for the ultra-high voltage transmission line include converter valve operation risk, switchgear operation risk, icing risk, and lightning strike risk, and the multi-level fuzzy evaluation set V includes evaluation levels V. k The evaluation level V k It includes Level 1 risk (V1), Level 2 risk (V2), Level 3 risk (V3), Level 4 risk (V4), and Level 5 risk (V5).

[0015] In one specific embodiment, step S2, which involves calculating the subjective weight θ of the evaluation index based on the AHP method, specifically includes:

[0016] S21. Establish a judgment matrix: Compare the importance of the risk assessment indicators for the UHV transmission lines pairwise, and score each indicator using the nine-scale method to construct a judgment matrix A:

[0017]

[0018] Where: a ij To determine the score of the risk assessment index for the UHV transmission line corresponding to the i-th row and j-th column in matrix A;

[0019] S22. Calculate the subjective weight θ: Normalize the judgment matrix A column-wise, and use the arithmetic mean method to calculate the weights to obtain the subjective weight vector θ.

[0020] θ=[θ1 θ2 ··· θ n ]

[0021] S23. Calculate the sorting weight vector and perform a consistency check: Calculate the largest eigenvalue λ. max First, determine the consistency index CI of the judgment matrix, and obtain the average consistency index RI of the judgment matrix A by referring to the average consistency index value table, and calculate the consistency ratio CR:

[0022]

[0023]

[0024] Where: n is the order of the judgment matrix A, that is, the number of risk assessment indicators for the ultra-high voltage transmission line;

[0025] If the consistency ratio CR < 0.1, then the judgment matrix A is confirmed to have passed the consistency test, and the judgment matrix A and the subjective weight vector θ are confirmed to be valid; otherwise, return to step S21, construct a new judgment matrix A, and repeat steps S21-S23 until the judgment matrix A passes the consistency test.

[0026] In one specific embodiment, step S3, which involves calculating the objective weight ω of the evaluation index based on the CRITIC method, specifically includes:

[0027] S31. Data Standardization: A data matrix X = (x...) is constructed using initial data from the UHV transmission line risk assessment. ij ) m×n Next, the initial data is dimensionless and processed using the following formula to further obtain the standardized data matrix Y = (y ij ) m×n :

[0028]

[0029] Where: n is the number of risk assessment indicators for the ultra-high voltage transmission line, m is the number of evaluation objects, and x ij The measured value of the j-th risk assessment index of the i-th evaluation object for the UHV transmission line; max(x j ), min(x j ) represent the maximum and minimum values ​​of the j-th evaluation index for different evaluation objects; y ij The processed standardized data value of the j-th risk assessment index of the UHV transmission line for the i-th evaluation object;

[0030] S32. Calculate the coefficient of variation of the index: coefficient of variation v j The calculation formula is:

[0031]

[0032] Where: s j Let be the standard deviation of the j-th UHV transmission line risk assessment index. The average value of the risk assessment index for the j-th ultra-high voltage transmission line;

[0033] S33. Calculation of Indicator Conflict: Based on the standardized data matrix Y = (y ij ) m×n Calculate the correlation coefficient r between the i-th indicator and the j-th risk assessment indicator for the UHV transmission line. ij Next, the conflict quantification value A is calculated. j :

[0034]

[0035] in: Let the standardize the covariance of the i-th and j-th columns of the matrix;

[0036] S34. Information Content Calculation: The information content E is calculated using the following formula. j :

[0037] E j =v j ×A j

[0038] Where: v j Let A be the coefficient of variation. j This refers to the conflict quantification value;

[0039] S35. Calculation of objective weights for evaluation indicators: For the information quantity E... j Normalization is performed to obtain the objective weight ω of the j-th UHV transmission line risk assessment index. j for:

[0040]

[0041] Where: n is the number of risk assessment indicators for the ultra-high voltage transmission line, E j The amount of information is described above.

[0042] In one specific embodiment, step S4, which involves calculating the comprehensive weight by combining the subjective weight θ and the objective weight ω, specifically includes:

[0043] The subjective weight θ obtained in step S2 and the objective weight ω obtained in step S3 are fused using the Lagrange multiplier method to obtain the comprehensive weight, as shown in the following formula:

[0044]

[0045] Where: θ j ω represents the subjective weight of the j-th UHV transmission line risk assessment indicator. j , where is the objective weight of the j-th risk assessment indicator for the ultra-high voltage transmission line.

[0046] In a specific embodiment, in step S51, the Gaussian membership function f(y) for constructing the corresponding Gaussian membership function for the quality assessment factor set U and the multi-level fuzzy comment set V is specifically:

[0047]

[0048] Where: y is the risk assessment index of the ultra-high voltage transmission line, σ and c are parameters, σ is 0.3; the value of c represents the center position of the Gaussian membership function, and five c values ​​are adopted: c1 = 1, c2 = 0.75, c3 = 0.5, c4 = 0.25, c5 = 0;

[0049] Step S52, which calculates the fuzzy comprehensive evaluation matrix based on the Gaussian membership function, specifically includes:

[0050] The index y in the standardized matrix Y ij Substituting these values ​​into the Gaussian membership functions for the five evaluation levels, we obtain the evaluation matrix F as follows:

[0051]

[0052] Where: f Vk (y ij (k = 1, 2, ... 5; j = 1, 2, ... n) is the index y ij For the evaluation level V k The degree of subordination.

[0053] In one specific embodiment, step S53, which involves obtaining the overall assessment of the UHV transmission line risk assessment system based on the fuzzy comprehensive evaluation matrix and the comprehensive weights, specifically includes:

[0054] Based on the principle of average weighting The operator, combined with the fuzzy comprehensive evaluation matrix and the comprehensive weights, yields the overall evaluation of the UHV transmission line risk assessment system:

[0055] B j =[b i (V1) b i (V2) b i (V3) b i (V4) b i (V5)]

[0056] Where: b i (V k )=∑(λ i ·f V1 (y i1 )), b i (V k ) represents the risk assessment index of each of the ultra-high voltage transmission lines relative to the assessment level V. k Membership degree; It is the indicator y ij For the evaluation level V k The degree of membership;

[0057] In step S54, the calculation formula for the comprehensive assessment result based on the overall assessment system for ultra-high voltage transmission lines is as follows:

[0058]

[0059] Where: b i (V k ) represents the risk assessment index of each of the ultra-high voltage transmission lines relative to the assessment level V. k The membership degree, n is the number of risk assessment indicators for the UHV transmission line, and k is the number of assessment levels.

[0060] Secondly, the present invention provides a fuzzy comprehensive risk assessment device for ultra-high voltage transmission lines based on AHP-CRITIC, comprising:

[0061] The evaluation index selection module is used to select the corresponding UHV transmission line risk assessment index according to the risk of UHV transmission lines, and to determine the UHV transmission line risk assessment index as the quality assessment factor set U of risk assessment, and to determine the multi-level fuzzy comment set V according to the risk of UHV transmission lines;

[0062] The subjective weight calculation module is used to calculate the subjective weight θ of the evaluation index based on the AHP method.

[0063] The objective weight calculation module is used to calculate the objective weight ω of the evaluation index based on the CRITIC method.

[0064] The comprehensive weight calculation module is used to calculate the comprehensive weight by combining the subjective weight θ and the objective weight ω.

[0065] The UHV transmission line risk fuzzy comprehensive assessment module is used to perform a fuzzy comprehensive assessment of UHV transmission line risks by combining the aforementioned comprehensive weights. Specifically, it is used for:

[0066] Construct corresponding Gaussian membership functions for the quality assessment factor set U and the multi-level fuzzy comment set V;

[0067] The fuzzy comprehensive evaluation matrix is ​​calculated based on the Gaussian membership function.

[0068] Based on the fuzzy comprehensive evaluation matrix and the comprehensive weights, the overall evaluation of the risk assessment system for ultra-high voltage transmission lines is obtained;

[0069] Based on the overall assessment of the UHV transmission line risk assessment system, the comprehensive assessment results are quantitatively calculated.

[0070] Thirdly, the present invention provides a terminal device, comprising: a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, it implements a fuzzy comprehensive risk assessment method for ultra-high voltage transmission lines based on AHP-CRITIC as described in the first aspect.

[0071] Fourthly, the present invention provides a computer-readable storage medium storing a computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to perform a fuzzy comprehensive risk assessment method for ultra-high voltage transmission lines based on AHP-CRITIC as described in the first aspect.

[0072] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0073] First, the risk assessment indicators for UHV transmission lines are determined. This invention selects corresponding risk assessment indicators based on the characteristics of UHV transmission lines, enabling a realistic risk assessment of the UHV transmission line system. The subjective and objective weights are obtained using the AHP and CRITIC methods respectively, and combined into a comprehensive weight to determine the indicator weights. This integrates the advantages of both types of weights, reducing the bias caused by a single subjective or objective weight. Compared to existing assessment methods for power grid evaluation, such as principal component analysis and analytic hierarchy process, this method comprehensively considers the subjective and objective weights of each indicator, resulting in more accurate evaluation results. Next, Gaussian membership functions are constructed for the factor set and the comment set, and a fuzzy comprehensive evaluation matrix is ​​calculated. The comprehensive weights and fuzzy comprehensive evaluation matrix are then calculated using fuzzy comprehensive operators to obtain the risk assessment results for UHV transmission lines. Operation and maintenance based on the assessment results provide valuable reference for reducing the risks of UHV transmission lines. Therefore, this invention uses a fuzzy comprehensive evaluation method based on the AHP and CRITIC methods to quantitatively assess the risks of UHV transmission lines, which is efficient, accurate, and more in line with practical needs. Attached Figure Description

[0074] Figure 1 This is a flowchart illustrating a fuzzy comprehensive risk assessment method for ultra-high voltage transmission lines based on AHP-CRITIC, provided in an embodiment of the present invention.

[0075] Figure 2 This is a schematic diagram of risk assessment indicators for ultra-high voltage transmission lines provided in an embodiment of the present invention;

[0076] Figure 3 This is a schematic diagram of the process for calculating subjective weights based on the AHP method according to an embodiment of the present invention;

[0077] Figure 4This is a schematic diagram of the process for calculating objective weights based on the CRITIC method according to an embodiment of the present invention;

[0078] Figure 5 This is a schematic diagram of the risk assessment process for an ultra-high voltage transmission line system provided in an embodiment of the present invention;

[0079] Figure 6 This is a schematic diagram of the structure of an ultra-high voltage transmission line risk fuzzy comprehensive assessment device based on AHP-CRITIC provided in an embodiment of the present invention;

[0080] Figure 7 This is a schematic diagram of the structure of a terminal device provided in an embodiment of the present invention.

[0081] in:

[0082] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0083] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0084] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," and "counterclockwise," etc., indicating orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, features defined with "first" and "second" may explicitly or implicitly include one or more of the stated features. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0085] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "joining" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection, a direct connection, or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0086] In this invention, unless otherwise explicitly specified and limited, "above" or "below" the second feature can include direct contact between the first and second features, or contact between the first and second features through another feature between them. Furthermore, "above," "over," and "on top" of the second feature includes the first feature directly above or diagonally above the second feature, or simply indicates that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" the second feature includes the first feature directly below or diagonally below the second feature, or simply indicates that the first feature is at a lower horizontal level than the second feature.

[0087] To address the issue that existing risk assessment methods focus on the overall risk assessment of the power grid and lack a comprehensive risk assessment scheme for ultra-high voltage (UHV) transmission lines, this invention proposes a fuzzy comprehensive risk assessment method for UHV transmission lines based on AHP (Analytic Hierarchy Process)-CRITIC (Criteria Importance Through Intercrieria Correlation) multi-criteria decision analysis. Please refer to... Figure 1 , Figure 1 This is a flowchart illustrating a fuzzy comprehensive risk assessment method for ultra-high voltage transmission lines based on AHP-CRITIC, provided by an embodiment of the present invention.

[0088] An embodiment of the present invention provides a fuzzy comprehensive risk assessment method for ultra-high voltage transmission lines based on AHP-CRITIC, comprising the following steps:

[0089] S1. Select corresponding UHV transmission line risk assessment indicators based on the risks of UHV transmission lines, and determine the UHV transmission line risk assessment indicators as the quality assessment factor set U for risk assessment, and determine a multi-level fuzzy comment set V based on the risks of UHV transmission lines;

[0090] S2. Calculate the subjective weights θ of the evaluation indicators based on the AHP method;

[0091] S3. Calculate the objective weights ω of the evaluation indicators based on the CRITIC method;

[0092] S4. Calculate the comprehensive weight by combining the subjective weight θ and the objective weight ω;

[0093] S5. Conduct a fuzzy comprehensive risk assessment of UHV transmission lines by combining the aforementioned comprehensive weights.

[0094] In one specific embodiment, such as Figure 2As shown, in step S1, the corresponding UHV transmission line risk assessment index is selected based on the risk of the UHV transmission line, and the UHV transmission line risk assessment index is determined as the quality assessment factor set U for risk assessment. Furthermore, a multi-level fuzzy comment set V is determined based on the UHV transmission line risk. Specifically:

[0095] The operating environment and risks faced by ultra-high voltage (UHV) transmission lines are analyzed, and risk assessment indicators for UHV transmission lines are determined. The indicators are selected as follows:

[0096] S11. Converter Valve Operation Risk: Converter valve equipment failure (misoperation and failure to open) or malfunction due to equipment aging or harsh environments. From the perspective of DC equipment unit operating time efficiency, the operation risk of each equipment unit is considered to be proportional to its cumulative time out of the network. Therefore, the converter valve operation risk index is expressed using the system equipment failure risk probability.

[0097]

[0098] Where: T represents the duration of a maintenance cycle, and t represents the duration of equipment failure within that maintenance cycle.

[0099] S12. Switchgear Operation Risk: Failure or malfunction of other DC transmission equipment due to equipment aging or human factors. The calculation method for switchgear operation risk is as follows:

[0100]

[0101] Where: n is the number of devices, T i t represents the maintenance cycle duration of the i-th device. i This represents the duration of the fault of the i-th device within the maintenance cycle.

[0102] S13. Icing Risk: UHV transmission line projects typically involve large-capacity, long-distance power transmission. These lines often traverse terrain with significant elevation changes and high altitudes, passing through areas prone to medium to heavy icing. Following historical ice storms affecting transmission lines, icing risk has become a key research issue. This invention uses the following formula to calculate icing risk index data:

[0103]

[0104] Where: L is the maximum allowable icing thickness, l is the average icing thickness at the sampling point, and k is the environmental coefficient.

[0105] S14. Lightning Strike Risk: Lightning strikes have long been a frequent threat to the safe and stable operation of the power grid. Ultra-high voltage (UHV) transmission lines have tall towers and high transmission capacity, making them particularly vulnerable to system instability caused by lightning strikes. According to the State Grid's operational experience, lightning strikes cause UHVDC line restarts far more often than UHVAC line trips. Furthermore, several lightning strikes can cause single-pole or double-pole blocking of UHVDC lines, and even affect AC lines. This invention uses the average lightning strike restart rate as a lightning strike risk indicator.

[0106] In summary, the risk assessment indicators for UHV transmission lines include converter valve operation risk, switchgear operation risk, icing risk, and lightning strike risk. The selected UHV transmission line risk assessment indicators constitute the quality assessment factor set U. The multi-level fuzzy evaluation set V includes assessment levels V0. k The evaluation level V k The risk level is divided into five levels: Level 1 (V1), Level 2 (V2), Level 3 (V3), Level 4 (V4), and Level 5 (V5). This forms a five-level fuzzy rating set V: V = {V1 (low risk), V2 (relatively low risk), V3 (moderate risk), V4 (relatively high risk), V5 (high risk)}.

[0107] In one embodiment, the risk quantification and classification of ultra-high voltage transmission lines is shown in Table 1:

[0108] Table 1 Risk Quantification and Classification Table for UHV Transmission Lines

[0109]

[0110] In one specific embodiment, the process of calculating the subjective weight θ of the evaluation index based on the AHP method in step S2 is as follows: Figure 3 As shown, it specifically includes:

[0111] S21. Establish a judgment matrix: Compare the importance of the risk assessment indicators for the UHV transmission lines pairwise, and score each indicator using the nine-scale method to construct a judgment matrix A:

[0112]

[0113] Where: a ij To determine the score of the risk assessment index for the UHV transmission line corresponding to the i-th row and j-th column in matrix A.

[0114] S22. Calculate the subjective weight θ: Normalize the judgment matrix A column-wise, and use the arithmetic mean method to calculate the weights to obtain the subjective weight vector θ.

[0115] θ=[θ1 θ2 ··· θ n ]

[0116] S23. Calculate the sorting weight vector and perform a consistency check: Calculate the largest eigenvalue λ. max First, determine the consistency index CI of the judgment matrix, and then obtain the average consistency index RI of the judgment matrix A by referring to the average consistency index value table (as shown in Table 2 below), and calculate the consistency ratio CR:

[0117] Table 2. Average Consistency Index (RI) Values

[0118]

[0119]

[0120] Where: n is the order of the judgment matrix A, that is, the number of risk assessment indicators for the ultra-high voltage transmission line;

[0121] If the consistency ratio CR < 0.1, then the judgment matrix A is confirmed to have passed the consistency test, and the judgment matrix A and the subjective weight vector θ are confirmed to be valid; otherwise, return to step S21, construct a new judgment matrix A, and repeat steps S21-S23 until the judgment matrix A passes the consistency test.

[0122] In one specific embodiment, the process of calculating the objective weight ω of the evaluation index based on the CRITIC method in step S3 is as follows: Figure 4 As shown, it specifically includes:

[0123] S31. Data Standardization: A data matrix X = (x...) is constructed using initial data from the UHV transmission line risk assessment. ij ) m×n Next, the initial data is processed to be dimensionless. Since the risk assessment indicators for UHV transmission lines include both positive (the larger the better) and negative (the smaller the better) indicators, they need to be processed separately. The processing procedure is as follows: [Formula omitted for brevity], further obtaining the standardized data matrix Y = (y... ij ) m×n :

[0124]

[0125] Where: n is the number of risk assessment indicators for the ultra-high voltage transmission line, m is the number of evaluation objects, and x ij The measured value of the j-th risk assessment index of the i-th evaluation object for the UHV transmission line; max(x j ), min(x j ) represent the maximum and minimum values ​​of the j-th evaluation index for different evaluation objects; y ij The processed standardized data value of the j-th risk assessment index of the UHV transmission line for the i-th evaluation object;

[0126] S32. Calculate the coefficient of variation of the indicators: The coefficient of variation is a quantitative display of the comparative strength of the indicators. j The calculation formula is:

[0127]

[0128] Where: s j Let be the standard deviation of the j-th UHV transmission line risk assessment index. The average value of the risk assessment index for the j-th ultra-high voltage transmission line;

[0129] S33. Calculation of Indicator Conflict: Based on the standardized data matrix Y = (y ij ) m×n Calculate the correlation coefficient r between the i-th indicator and the j-th risk assessment indicator for the UHV transmission line. ij Next, the conflict quantification value A is calculated. j :

[0130]

[0131] in: Let the standardize the covariance of the i-th and j-th columns of the matrix;

[0132] S34. Information Content Calculation: The information content E is calculated using the following formula. j :

[0133] E j =v j ×A j

[0134] Where: v j Let A be the coefficient of variation. j This refers to the conflict quantification value;

[0135] S35. Calculation of objective weights for evaluation indicators: For the information quantity E... j Normalization is performed to obtain the objective weight ω of the j-th UHV transmission line risk assessment index. j for:

[0136]

[0137] Where: n is the number of risk assessment indicators for the ultra-high voltage transmission line, E j The amount of information is described above.

[0138] In this embodiment, for multi-indicator and multi-object assessment problems such as risk assessment of UHV transmission lines, the CRITIC method can eliminate the influence between highly correlated indicators, reduce information overlap, and thus obtain more scientific and reliable assessment results.

[0139] In one specific embodiment, step S4, which involves calculating the comprehensive weight by combining the subjective weight θ and the objective weight ω, specifically includes:

[0140] The subjective weight θ obtained in step S2 and the objective weight ω obtained in step S3 are fused using the Lagrange multiplier method to obtain the comprehensive weight, as shown in the following formula:

[0141]

[0142] Where: θ j ω represents the subjective weight of the j-th UHV transmission line risk assessment indicator. j , where is the objective weight of the j-th risk assessment indicator for the ultra-high voltage transmission line.

[0143] In this embodiment, the subjective weights obtained in step S2 and the objective weights obtained in step S3 are fused using the Lagrange multiplier method to obtain a comprehensive weight, which can effectively resist weight bias.

[0144] In one specific embodiment, the fuzzy comprehensive risk assessment process for ultra-high voltage transmission lines is as follows: Figure 5 As shown, step S5, which involves performing a fuzzy comprehensive risk assessment of UHV transmission lines based on the comprehensive weights, specifically includes:

[0145] S51. Construction of Gaussian membership function: Construct corresponding Gaussian membership functions for the quality assessment factor set U and the multi-level fuzzy evaluation set V obtained in step S1, and calculate the fuzzy comprehensive evaluation matrix.

[0146] The Gaussian membership function f(y) is specifically as follows:

[0147]

[0148] Where: y is the risk assessment index of the ultra-high voltage transmission line, σ and c are parameters; in this invention, σ is taken as 0.3; the value of c represents the center position of the Gaussian membership function, and this invention adopts 5 c values: c1 = 1, c2 = 0.75, c3 = 0.5, c4 = 0.25, c5 = 0;

[0149] S52. Based on the Gaussian membership function, the fuzzy comprehensive evaluation matrix is ​​calculated, specifically including:

[0150] The index y in the standardized matrix Y ij Substituting these values ​​into the Gaussian membership functions for the five evaluation levels, we obtain the evaluation matrix F as follows:

[0151]

[0152] in: It is the indicator y ij For the evaluation level V k The degree of membership;

[0153] S53. Based on the fuzzy comprehensive evaluation matrix and the comprehensive weights, the overall evaluation of the UHV transmission line risk assessment system is obtained, specifically including:

[0154] Based on the principle of average weighting The operator, combined with the fuzzy comprehensive evaluation matrix and the comprehensive weights, yields the overall evaluation of the UHV transmission line risk assessment system:

[0155] B j =[b i (V1) b i (V2) b i (V3) b i (V4) b i (V5)]

[0156] Where: b i (V k )=Σ(λ i ·f V1 (y i1 )), b i (V k ) represents the risk assessment index of each of the ultra-high voltage transmission lines relative to the assessment level V. k Membership degree; It is the indicator y ij For the evaluation level V k The degree of membership;

[0157] S54. Based on the overall assessment of the UHV transmission line risk assessment system, the comprehensive assessment result is quantitatively calculated. The calculation formula for the comprehensive assessment result is as follows:

[0158]

[0159] Where: b i (V k ) represents the risk assessment index of each of the ultra-high voltage transmission lines relative to the assessment level V. k The membership degree, n is the number of risk assessment indicators for the UHV transmission line, and k is the number of assessment levels.

[0160] Based on the comprehensive assessment results of the risks of UHV transmission lines obtained from the calculations and the corresponding risk classification intervals of UHV transmission lines, a rating of the level of risk of UHV transmission lines is obtained, and targeted measures are taken accordingly.

[0161] In summary, the present invention provides a fuzzy comprehensive risk assessment method for UHV transmission lines based on AHP-CRITIC. First, it determines the risk assessment indicators for UHV transmission lines. Based on the characteristics of UHV transmission lines, the present invention selects corresponding risk assessment indicators, enabling a risk assessment of the UHV transmission line system that conforms to the actual situation. Then, it uses the AHP and CRITIC methods to obtain subjective and objective weights respectively, and combines them into a comprehensive weight to determine the indicator weights. This integrates the advantages of both types of weights, reducing the weight bias caused by a single subjective or objective weight. Compared with existing assessment methods for power grid evaluation, such as principal component analysis and analytic hierarchy process, it can comprehensively consider the subjective and objective weights of various indicators, resulting in more accurate evaluation results. Next, it constructs corresponding Gaussian membership functions for the factor set and comment set, and calculates the fuzzy comprehensive assessment matrix. Finally, it uses fuzzy comprehensive operators to comprehensively calculate the comprehensive weights and the fuzzy comprehensive assessment matrix to obtain the risk assessment results for UHV transmission lines. Based on the assessment results, operation and maintenance can be carried out, providing valuable reference for reducing the risks of UHV transmission lines. Therefore, this invention uses a fuzzy comprehensive evaluation method based on the AHP and CRITIC methods to quantitatively evaluate the risks of UHV transmission lines, which is efficient, accurate, and more in line with actual needs.

[0162] Please see Figure 6 , Figure 6 This is a schematic diagram of the structure of an ultra-high voltage transmission line risk fuzzy comprehensive assessment device based on AHP-CRITIC provided in an embodiment of the present invention.

[0163] An embodiment of the present invention provides a fuzzy comprehensive risk assessment device for ultra-high voltage transmission lines based on AHP-CRITIC, comprising:

[0164] The evaluation index selection module is used to select the corresponding UHV transmission line risk assessment index according to the risk of UHV transmission lines, and to determine the UHV transmission line risk assessment index as the quality assessment factor set U of risk assessment, and to determine the multi-level fuzzy comment set V according to the risk of UHV transmission lines;

[0165] The subjective weight calculation module is used to calculate the subjective weight θ of the evaluation index based on the AHP method.

[0166] The objective weight calculation module is used to calculate the objective weight ω of the evaluation index based on the CRITIC method.

[0167] The comprehensive weight calculation module is used to calculate the comprehensive weight by combining the subjective weight θ and the objective weight ω.

[0168] The UHV transmission line risk fuzzy comprehensive assessment module is used to perform a fuzzy comprehensive assessment of UHV transmission line risks by combining the aforementioned comprehensive weights. Specifically, it is used for:

[0169] Construct corresponding Gaussian membership functions for the quality assessment factor set U and the multi-level fuzzy comment set V;

[0170] The fuzzy comprehensive evaluation matrix is ​​calculated based on the Gaussian membership function.

[0171] Based on the fuzzy comprehensive evaluation matrix and the comprehensive weights, the overall evaluation of the risk assessment system for ultra-high voltage transmission lines is obtained;

[0172] Based on the overall assessment of the UHV transmission line risk assessment system, the comprehensive assessment results are quantitatively calculated.

[0173] The present invention provides an AHP-CRITIC-based fuzzy comprehensive assessment device for risks of ultra-high voltage transmission lines, which can perform all the steps and functions of an AHP-CRITIC-based fuzzy comprehensive assessment method for risks of ultra-high voltage transmission lines provided in any of the above embodiments. The specific functions of the device will not be described in detail here.

[0174] Please see Figure 7 , Figure 7 This is a schematic diagram of the structure of a terminal device provided in an embodiment of the present invention.

[0175] The terminal device includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the steps of the AHP-CRITIC-based fuzzy comprehensive risk assessment method for ultra-high voltage transmission lines in the various embodiments described above, for example... Figure 1 The steps S1 to S5 are shown. Alternatively, when the processor executes the computer program, it implements the functions of each module in the above-described device embodiments.

[0176] For example, the computer program can be divided into one or more modules, which are stored in the memory and executed by the processor to complete the present invention. The one or more modules can be a series of computer program instruction segments capable of performing specific functions, which describe the execution process of the computer program in the terminal device. For instance, the computer program can be divided into several modules, the specific functions of which have been described in detail in the AHP-CRITIC-based fuzzy comprehensive risk assessment method for ultra-high voltage transmission lines provided in any of the above embodiments; therefore, the specific functions of this device will not be repeated here.

[0177] The terminal device described can be a desktop computer, laptop, handheld computer, or cloud server, etc. The terminal device may include, but is not limited to, a processor and memory. Those skilled in the art will understand that the schematic diagram is merely an example of a terminal device and does not constitute a limitation on any terminal device. It may include more or fewer components than illustrated, or combine certain components, or use different components. For example, the terminal device may also include input / output devices, network access devices, buses, etc.

[0178] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. The processor is the control center of the terminal device, connecting various parts of the terminal device via various interfaces and lines.

[0179] The memory can be used to store the computer program and / or modules. The processor, by running or executing the computer program and / or modules stored in the memory, and by calling the data stored in the memory, realizes various functions of the AHP-CRITIC-based fuzzy comprehensive risk assessment method for ultra-high voltage transmission lines. The memory may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created based on the use of the mobile phone (such as audio data, phonebook, etc.). In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0180] This invention also provides a computer-readable storage medium storing a computer program, wherein the computer program, when running, controls the device where the computer-readable storage medium is located to execute a fuzzy comprehensive risk assessment method for ultra-high voltage transmission lines based on AHP-CRITIC, as described in the above embodiments.

[0181] If the module integrated into the terminal device is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0182] The above description is merely a preferred embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A fuzzy comprehensive risk assessment method for ultra-high voltage transmission lines based on AHP-CRITIC, characterized in that, Includes the following steps: S1. Select corresponding UHV transmission line risk assessment indicators based on the risks of UHV transmission lines, and determine the UHV transmission line risk assessment indicators as the quality assessment factor set U for risk assessment, and determine a multi-level fuzzy comment set V based on the risks of UHV transmission lines; S2. Calculate the subjective weights θ of the evaluation indicators based on the AHP method; S3. Calculate the objective weights ω of the evaluation indicators based on the CRITIC method; S4. Calculate the comprehensive weight by combining the subjective weight θ and the objective weight ω; S5. A fuzzy comprehensive risk assessment of UHV transmission lines is conducted based on the aforementioned comprehensive weights, specifically including: S51. Construct corresponding Gaussian membership functions for the quality assessment factor set U and the multi-level fuzzy comment set V; S52. Calculate the fuzzy comprehensive evaluation matrix based on the Gaussian membership function. S53. Based on the fuzzy comprehensive evaluation matrix and the comprehensive weight, the overall evaluation of the risk assessment system for ultra-high voltage transmission lines is obtained; S54. Based on the overall assessment of the UHV transmission line risk assessment system, the comprehensive assessment results are quantitatively calculated.

2. The fuzzy comprehensive risk assessment method for UHV transmission lines based on AHP-CRITIC as described in claim 1, characterized in that, The risk assessment indicators for ultra-high voltage transmission lines include converter valve operation risk, switchgear operation risk, icing risk, and lightning strike risk. The multi-level fuzzy evaluation set V includes evaluation levels V. k The evaluation level V k It includes Level 1 risk (V1), Level 2 risk (V2), Level 3 risk (V3), Level 4 risk (V4), and Level 5 risk (V5).

3. The fuzzy comprehensive risk assessment method for UHV transmission lines based on AHP-CRITIC as described in claim 2, characterized in that, Step S2, which involves calculating the subjective weights θ of the evaluation indicators based on the AHP method, specifically includes: S21. Establish a judgment matrix: Compare the importance of the risk assessment indicators for the UHV transmission lines pairwise, and score each indicator using the nine-scale method to construct a judgment matrix A: Where: a ij To determine the score of the risk assessment index for the UHV transmission line corresponding to the i-th row and j-th column in matrix A; S22. Calculate the subjective weight θ: Normalize the judgment matrix A column-wise, and use the arithmetic mean method to calculate the weights to obtain the subjective weight vector θ. θ=[θ1 θ2 ··· θ n ] S23. Calculate the sorting weight vector and perform a consistency check: Calculate the largest eigenvalue λ. max First, determine the consistency index CI of the judgment matrix, and obtain the average consistency index RI of the judgment matrix A by referring to the average consistency index value table, and calculate the consistency ratio CR: Where: n is the order of the judgment matrix A, that is, the number of risk assessment indicators for the ultra-high voltage transmission line; If the consistency ratio CR < 0.1, then the judgment matrix A is confirmed to have passed the consistency test, and the judgment matrix A and the subjective weight vector θ are confirmed to be valid; otherwise, return to step S21, construct a new judgment matrix A, and repeat steps S21-S23 until the judgment matrix A passes the consistency test.

4. The fuzzy comprehensive risk assessment method for UHV transmission lines based on AHP-CRITIC as described in claim 3, characterized in that, Step S3, which involves calculating the objective weights ω of the evaluation indicators based on the CRITIC method, specifically includes: S31. Data Standardization: A data matrix X = (x...) is constructed using initial data from the UHV transmission line risk assessment. ij ) m×n Next, the initial data is dimensionless and processed using the following formula to further obtain the standardized data matrix Y = (y ij ) m×n : Where: n is the number of risk assessment indicators for the ultra-high voltage transmission line, m is the number of evaluation objects, and x ij The measured value of the j-th risk assessment index of the i-th evaluation object for the UHV transmission line; max(x j ), min(x j ) represent the maximum and minimum values ​​of the j-th evaluation index for different evaluation objects; y ij The processed standardized data value of the j-th risk assessment index of the UHV transmission line for the i-th evaluation object; S32. Calculate the coefficient of variation of the index: coefficient of variation v j The calculation formula is: Where: s j Let be the standard deviation of the j-th UHV transmission line risk assessment index. The average value of the risk assessment index for the j-th ultra-high voltage transmission line; S33. Calculation of Indicator Conflict: Based on the standardized data matrix Y = (y ij ) m×n Calculate the correlation coefficient r between the i-th indicator and the j-th risk assessment indicator for the UHV transmission line. ij Next, the conflict quantification value A is calculated. j : in: Let the standardize the covariance of the i-th and j-th columns of the matrix; S34. Information Content Calculation: The information content E is calculated using the following formula. j : E j =v j ×A j Where: v j Let A be the coefficient of variation. j This refers to the conflict quantification value; S35. Calculation of objective weights for evaluation indicators: For the information quantity E... j Normalization is performed to obtain the objective weight ω of the j-th UHV transmission line risk assessment index. j for: Where: n is the number of risk assessment indicators for the ultra-high voltage transmission line, E j The amount of information is described above.

5. The fuzzy comprehensive risk assessment method for UHV transmission lines based on AHP-CRITIC as described in claim 4, characterized in that, Step S4, which involves calculating the comprehensive weight by combining the subjective weight θ and the objective weight ω, specifically includes: The subjective weight θ obtained in step S2 and the objective weight ω obtained in step S3 are fused using the Lagrange multiplier method to obtain the comprehensive weight, as shown in the following formula: Where: θ j ω represents the subjective weight of the j-th UHV transmission line risk assessment indicator. j , where is the objective weight of the j-th risk assessment indicator for the ultra-high voltage transmission line.

6. The fuzzy comprehensive risk assessment method for UHV transmission lines based on AHP-CRITIC as described in claim 5, characterized in that: In step S51, the Gaussian membership function f(y) is constructed for the quality assessment factor set U and the multi-level fuzzy comment set V. Specifically, the Gaussian membership function f(y) is: Where: y is the risk assessment index of the ultra-high voltage transmission line, σ and c are parameters, σ is 0.3; the value of c represents the center position of the Gaussian membership function, and five c values ​​are adopted: c1 = 1, c2 = 0.75, c3 = 0.5, c4 = 0.25, c5 = 0; Step S52, which calculates the fuzzy comprehensive evaluation matrix based on the Gaussian membership function, specifically includes: The index y in the standardized matrix Y ij Substituting these values ​​into the Gaussian membership functions for the five evaluation levels, we obtain the evaluation matrix F as follows: Where: f Vk (y ij (k = 1, 2, ... 5; j = 1, 2, ... n) is the index y ij For the evaluation level V k The degree of subordination.

7. The fuzzy comprehensive risk assessment method for UHV transmission lines based on AHP-CRITIC as described in claim 6, characterized in that: Step S53, which involves obtaining the overall assessment of the UHV transmission line risk assessment system based on the fuzzy comprehensive evaluation matrix and the comprehensive weights, specifically includes: Based on the principle of average weighting The operator, combined with the fuzzy comprehensive evaluation matrix and the comprehensive weights, yields the overall evaluation of the UHV transmission line risk assessment system: B j =[b i (V1)b i (V2)b i (V3)b i (V4)b i (V5)] in: b i (V k ) represents the risk assessment index of each of the ultra-high voltage transmission lines relative to the assessment level V. k Membership degree; (k = 1, 2, ... 5; j = 1, 2, ... n) is the index y ij For the evaluation level V k The degree of membership; In step S54, the calculation formula for the comprehensive assessment result based on the overall assessment system for ultra-high voltage transmission lines is as follows: Where: b i (V k ) represents the risk assessment index of each of the ultra-high voltage transmission lines relative to the assessment level V. k The membership degree, n is the number of risk assessment indicators for the UHV transmission line, and k is the number of assessment levels.

8. A fuzzy comprehensive risk assessment device for ultra-high voltage transmission lines based on AHP-CRITIC, characterized in that, include: The evaluation index selection module is used to select the corresponding UHV transmission line risk assessment index according to the risk of UHV transmission lines, and to determine the UHV transmission line risk assessment index as the quality assessment factor set U of risk assessment, and to determine the multi-level fuzzy comment set V according to the risk of UHV transmission lines; The subjective weight calculation module is used to calculate the subjective weight θ of the evaluation index based on the AHP method. The objective weight calculation module is used to calculate the objective weight ω of the evaluation index based on the CRITIC method. The comprehensive weight calculation module is used to calculate the comprehensive weight by combining the subjective weight θ and the objective weight ω. The UHV transmission line risk fuzzy comprehensive assessment module is used to perform a fuzzy comprehensive assessment of UHV transmission line risks by combining the aforementioned comprehensive weights. Specifically, it is used for: Construct corresponding Gaussian membership functions for the quality assessment factor set U and the multi-level fuzzy comment set V; The fuzzy comprehensive evaluation matrix is ​​calculated based on the Gaussian membership function. Based on the fuzzy comprehensive evaluation matrix and the comprehensive weights, the overall evaluation of the risk assessment system for ultra-high voltage transmission lines is obtained; Based on the overall assessment of the UHV transmission line risk assessment system, the comprehensive assessment results are quantitatively calculated.

9. A terminal device, characterized in that, include: The processor, the memory, and the computer program stored in the memory and configured to be executed by the processor, wherein the processor, when executing the computer program, implements a fuzzy comprehensive risk assessment method for ultra-high voltage transmission lines based on any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to perform a fuzzy comprehensive risk assessment method for ultra-high voltage transmission lines based on AHP-CRITIC as described in any one of claims 1 to 7.

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