A power transmission network performance evaluation method and system, an electronic device and a storage medium

Abstract

The present application relates to a kind of power transmission network performance evaluation method, system, electronic equipment and storage medium, belong to power transmission network field, first establish power transmission network performance index evaluation system, then determine the CRITIC weight and entropy weight weight of each index, further by combination game theory determines the combination weight of each index, finally based on the combination weight of each target area power transmission network performance is evaluated and assigned, i.e. Numerical value is obtained to power transmission network performance, to realize the comprehensive evaluation of each target area power transmission network performance, can more objectively compare and evaluate the performance of each target area power transmission network.

Description

Technical Field

[0001] This invention relates to the field of power transmission networks, and in particular to a method, system, electronic device, and storage medium for evaluating the performance of power transmission networks. Background Technology

[0002] The direction of energy and power transformation is to accelerate the development of new energy sources and restrict the construction of new inefficient thermal power plants. This places higher demands on the low-carbon transformation of power transmission networks. Due to differences in topography, geographical location, and historical background, there are differences in energy development between regions, resulting in regional differences in power transmission networks. As energy and power transformation progresses, power transmission networks will reveal some significant problems. For example, the development of regional power transmission networks relying on traditional thermal power generation will be limited, and the installed capacity of new energy sources in regions with high wind and solar curtailment rates will be significantly reduced. Currently, most existing technical solutions focus on specific regions and do not study the comprehensive performance evaluation of power transmission networks in different regions from a low-carbon and energy-saving perspective. They cannot objectively compare and evaluate the current development status of power transmission networks in different regions, and therefore cannot propose corresponding improvement suggestions to address the current shortcomings of the power transmission network and promote the transformation of energy and power. Summary of the Invention

[0003] The purpose of this invention is to provide a method, system, electronic device, and storage medium for evaluating the performance of a power transmission network, so as to achieve a comprehensive evaluation of the performance of the power transmission network in each target area.

[0004] To achieve the above objectives, the present invention provides the following solution:

[0005] A method for evaluating the performance of a power transmission network, comprising:

[0006] Establish a performance evaluation system for power transmission networks;

[0007] Obtain the original data for each indicator in the power transmission network performance evaluation system for each target region and each year;

[0008] Standardize all the raw data to obtain standardized data;

[0009] Based on the standardized data, the CRITIC weight of each indicator is determined using the CRITIC method;

[0010] Based on the standardized data, the entropy weight of each indicator is determined using the entropy weight method.

[0011] The game theory-based combined weighting method combines CRITIC weights and entropy weights to determine the combined weights of each indicator.

[0012] Based on the combined weights of each indicator and the original data of each indicator for each target region in each year, the comprehensive evaluation value of the power transmission network performance for each target region in each year is determined.

[0013] Optionally, the power transmission network performance indicator evaluation system includes: low-carbon performance, social performance, and operational performance;

[0014] The low-carbon performance includes installed capacity of new energy sources, power generation of new energy sources, installed capacity of thermal power, and power generation of thermal power.

[0015] The social performance includes total electricity consumption, per capita electricity consumption, and per capita residential electricity consumption.

[0016] The operational performance includes line loss rate, circuit length, and number of transformers;

[0017] Among them, the installed capacity of new energy, the power generation of new energy, the total electricity consumption of the whole society, the per capita electricity consumption, and the per capita residential electricity consumption are all positive indicators; the installed capacity of thermal power, the power generation of thermal power, the line loss rate, the circuit length, and the number of transformers are all negative indicators.

[0018] Optionally, the formula for standardizing all the raw data is as follows:

[0019]

[0020] In the formula, x ij This represents the raw data for the j-th indicator in the i-th year of the target region, x. j Let j represent the j-th indicator, (x j ) min and (x) j ) max Let x′ represent the minimum and maximum raw data of the j-th indicator, respectively. ij This represents the standardized data of the j-th indicator in the i-th year of the target region.

[0021] Optionally, the formula for calculating the CRITIC weight of each indicator using the CRITIC method is as follows:

[0022]

[0023]

[0024]

[0025] In the formula, R j r represents the degree of conflict between the j-th indicator and other indicators. kj S represents the correlation coefficient between the k-th and j-th indicators. j C represents the standard deviation of the j-th indicator. j w represents the information content of the j-th indicator. jLet represent the CRITIC weight of the j-th indicator, K represent the number of indicators other than the j-th indicator, and n represent the total number of indicators.

[0026] Optionally, the formula for calculating the entropy weight of each indicator using the entropy weight method is as follows:

[0027]

[0028]

[0029]

[0030] In the formula, p ij Let x′ represent the ratio of the j-th indicator under each option. ij E represents the standardized data of the j-th indicator in the i-th year of the target region. j Let w' represent the information entropy of the j-th indicator. j Let m represent the entropy weight of the j-th indicator, m represent the total number of years, and n represent the total number of all indicators.

[0031] Optionally, the game theory-based combined weighting method combines the CRITIC weight and the entropy weight to determine the combined weight of each indicator, specifically including:

[0032] The objective function for combined weighting is determined as follows: In the formula, z = 1, 2, ∝ k Represents the combination coefficients of the weighting method. This represents one type of basic weight set, which is composed of and Together, they form the index weight vector, which is composed of the CRITIC weights of all indicators. The index weight vector, composed of the entropy weights of all indicators, is... This represents the basic weights before being weighted by the combined weights;

[0033] The first derivative of the objective function is obtained as follows:

[0034] Transforming the first derivative into a system of linear equations is:

[0035] Solving the system of linear equations yields the solution (∝1, ∝2), and the formula is used... Normalize the solution to the equation; where, This represents the normalized solution to the equation;

[0036] Based on the normalized solution of the equation, using the formula Determine the combined weights w * .

[0037] Optionally, the formula for calculating the comprehensive performance evaluation value of the transmission network for each target region in each year is as follows:

[0038]

[0039] In the formula, S i This represents the comprehensive performance evaluation value of the power transmission network in the target region in year i. Let x′ represent the combined weight of the j-th indicator. ij This represents the standardized data of the j-th indicator in the i-th year of the target region, where n represents the total number of all indicators.

[0040] A power transmission network performance evaluation system, comprising:

[0041] The evaluation system establishment module is used to establish an evaluation system for power transmission network performance indicators.

[0042] The indicator data acquisition module is used to acquire the original data of each indicator in the power transmission network performance indicator evaluation system for each target region and each year.

[0043] The standardization module is used to standardize all the raw data to obtain standardized data;

[0044] The CRITIC weight determination module is used to determine the CRITIC weight of each indicator based on the standardized data using the CRITIC method.

[0045] The entropy weight determination module is used to determine the entropy weight of each indicator based on the standardized data using the entropy weight method.

[0046] The combined weight determination module is used to combine the CRITIC weight and entropy weight based on the game theory-based combined weighting method to determine the combined weight of each indicator.

[0047] The comprehensive evaluation module is used to determine the comprehensive evaluation value of the power transmission network performance for each target region for each year, based on the combined weight of each indicator and the original data of each indicator for each target region for each year.

[0048] An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the power transmission network performance evaluation method as described above.

[0049] A computer-readable storage medium having a computer program stored thereon, which, when executed, implements the power transmission network performance evaluation method as described above.

[0050] According to specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0051] This invention discloses a method, system, electronic device, and storage medium for evaluating the performance of a power transmission network. First, a performance indicator evaluation system for the power transmission network is established. Then, the CRITIC weight and entropy weight of each indicator are determined. Next, the combined weight of each indicator is determined through combinatorial game theory. Finally, the performance of the power transmission network in each target area is evaluated and assigned a value based on the combined weight, thus quantifying the performance of the power transmission network. This enables a comprehensive evaluation of the performance of the power transmission network in each target area, allowing for a more objective comparison and evaluation of the performance of the power transmission network in each target area. Attached Figure Description

[0052] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0053] Figure 1 A flowchart of a power transmission network performance evaluation method provided in an embodiment of the present invention;

[0054] Figure 2 A schematic diagram of a power transmission network performance evaluation method provided in an embodiment of the present invention;

[0055] Figure 3 A schematic diagram of the power transmission network performance indicator evaluation system provided in an embodiment of the present invention;

[0056] Figure 4 This is a schematic diagram illustrating the combined game theory evaluation results of six regions provided in an embodiment of the present invention. Detailed Implementation

[0057] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0058] The purpose of this invention is to provide a method, system, electronic device, and storage medium for evaluating the performance of a power transmission network, so as to achieve a comprehensive evaluation of the performance of the power transmission network in each target area.

[0059] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0060] This invention provides a method for evaluating the performance of power transmission networks, such as... Figure 1 As shown, it includes the following steps:

[0061] Step S1: Establish a performance evaluation system for the power transmission network.

[0062] Figure 3 This diagram illustrates the structure of the power transmission network performance evaluation system. The system comprises three components: low-carbon performance, social performance, and operational performance. Low-carbon performance includes installed capacity of new energy sources, new energy power generation, installed capacity of thermal power plants, and thermal power generation. Social performance includes total electricity consumption, per capita electricity consumption, and per capita residential electricity consumption. Operational performance includes line loss rate, circuit length, and the number of transformers.

[0063] Among them, the installed capacity of new energy, the power generation of new energy, the total electricity consumption of the whole society, the per capita electricity consumption, and the per capita residential electricity consumption are all positive indicators; the installed capacity of thermal power, the power generation of thermal power, the line loss rate, the circuit length, and the number of transformers are all negative indicators.

[0064] Step S2: Obtain the original data of each indicator in the power transmission network performance evaluation system for each target region and each year.

[0065] Step S3: Standardize all the raw data to obtain standardized data.

[0066] The raw data is standardized according to the positive and negative attributes of each indicator:

[0067]

[0068] The formula above the curly braces represents the data processing method for positive indicators, while the formula below the curly braces represents the data processing method for negative indicators. Subsequent calculations are based on the processed data obtained in this step. ij This represents the raw data for the j-th indicator in the i-th year of the target region, x. j Let j represent the j-th indicator, (x j ) min and (x) j ) max Let x′ represent the minimum and maximum raw data of the j-th indicator, respectively. ij This represents the standardized data of the j-th indicator in the i-th year of the target region.

[0069] Step S4: Based on the standardized data, determine the CRITIC weight of each indicator using the CRITIC method.

[0070] The index weight vector was obtained by performing the CRITIC method on the processed data using SPSSAU software.

[0071] The CRITIC method is another objective weighting method proposed by Diakoulaki. Its basic idea is to determine the objective weights of indicators based on two fundamental concepts.

[0072] First, there's the contrast strength, which represents the magnitude of the difference in values ​​between different evaluation schemes for the same indicator, expressed as the standard deviation S. j The standard deviation is expressed in the form of a standard deviation, indicating the magnitude of the difference in values ​​among different options within the same indicator. The larger the standard deviation, the greater the difference in values ​​among the options. Secondly, it evaluates the conflict between indicators. The conflict between indicators is based on their correlation. For example, if two indicators have a strong positive correlation, it indicates that the conflict between the two indicators is low.

[0073]

[0074]

[0075]

[0076] Among them, R j R represents the quantification of the conflict between j indicators and other indicators. kj C is the correlation coefficient between evaluation indicators k and j. j It refers to the information content of the indicator, w j This is the CRITIC weight of the j-th indicator. The indicator weight vector composed of the CRITIC weights of these n indicators is...

[0077] Standard deviation S j It was calculated from standardized data.

[0078] Step S5: Based on the standardized data, determine the entropy weight of each indicator using the entropy weight method.

[0079] The SPSSAU software was used to obtain the index weight vector by applying the entropy weight method to the processed data.

[0080] Entropy, originally a thermodynamic concept, was first introduced into information theory by Shannon and is now widely used in engineering, technology, socio-economics, and other fields. Information entropy can be used to calculate the weights of various indicators, providing a basis for comprehensive evaluation of multiple indicators.

[0081] Generally, if the information entropy E of a certain indicator j The smaller the value, the greater the variability of the indicator value, and therefore the greater its weight should be. Conversely, the larger the information value E of an indicator, the greater its weight. jThe larger the value, the smaller the degree of variation in its indicator value, the less information it provides, and the smaller its role in the comprehensive evaluation. Therefore, its weight should also be smaller.

[0082]

[0083]

[0084]

[0085] Where, p ij It is the ratio of each indicator under each plan, E j It is the information entropy of each indicator, w′ j This is the entropy weight of the j-th indicator. The indicator weight vector composed of the entropy weights of these n indicators is... x′ ij This represents the standardized data of the j-th indicator in the i-th year of the target region, where m represents the total number of years.

[0086] Step S6: Based on the game theory-based combined weighting method, the CRITIC weight and entropy weight are combined to determine the combined weight of each indicator.

[0087] Solve the combinatorial weights using Matlab R2018a based on combinatorial game theory.

[0088] The game theory-based combined weighting method is the process of combining weights obtained from different methods to find the most reasonable index weights. Its working principle is to ensure the minimum discrete condition between the combined weights and the weights calculated by the two methods, as follows:

[0089]

[0090] In the formula, z = 1, 2, ∝ k Represents the combination coefficients of the weighting method. This represents one type of basic weight set, which is composed of and Together, they form the index weight vector, which is composed of the CRITIC weights of all indicators. The index weight vector, composed of the entropy weights of all indicators, is... This represents the basic weights before being weighted by combined weights. The objective function aims to find the optimal w. * That is, for the weighting coefficients ∝ k Optimize to make w * With each w k Minimize the deviation between them.

[0091] Based on the differential properties of matrices, the first derivative of the above equation is:

[0092]

[0093] Transforming the above expression into a system of linear equations, we have:

[0094]

[0095] Solving the above matrix equations using Matlab.R2018a yields the solution (∝1, ∝2). Normalizing this solution, we have:

[0096] The combined weight w is obtained by arbitrarily linearly combining these two vectors. * for:

[0097]

[0098] in, The index weight vector is calculated using the CRITIC method. To calculate the index weight vector using the entropy weight method, ∝ k The combination coefficients of the weighting method.

[0099] Step S7: Determine the comprehensive performance evaluation value of the power transmission network for each target region for each year based on the combined weight of each indicator and the original data of each indicator for each target region for each year.

[0100] Using the obtained combined weight values ​​and the standardized index data, multiply and sum them:

[0101]

[0102] In the formula, S i This represents the comprehensive performance evaluation value of the power transmission network in the target region in year i. Let x′ represent the combined weight of the j-th indicator. ij This represents the standardized data of the j-th indicator in the i-th year of the target region, where n represents the total number of all indicators.

[0103] This invention employs combinatorial game theory, which can largely overcome the single-method shortcomings of the CRITIC method and the entropy weight method, making the weighting results more accurate, scientific, and comprehensive.

[0104] The study evaluated the power transmission network performance of six major regions in China—North China, Central China, East China, Northeast China, Northwest China, and South China—from 2014 to 2020.

[0105] Reference Figure 2The power transmission network performance evaluation method of this invention constructs a power transmission network performance evaluation index system from three aspects: low-carbon performance, social performance, and operational performance. Furthermore, it utilizes a combination of game theory based on the CRITIC method and the entropy weight method to evaluate the power transmission network performance in six regions of China (North China, Northeast China, East China, Central China, Northwest China, and Southern China) from 2014 to 2020. The evaluation results are as follows: Figure 4 As shown.

[0106] By observing and comparing the performance of power transmission networks in different regions from both temporal and geographical perspectives, we can also analyze the most weighted indicators for each region. This makes it easier to propose constructive suggestions for addressing these issues and provides more sufficient evidence for the power transmission network to achieve its low-carbon transformation goals.

[0107] Based on the assessment results, the following improvement measures are proposed: On the one hand, enhance the absorption capacity of new energy in the transmission and distribution network. This can be achieved by vigorously developing the "new energy + energy storage" model, which can smooth power output, improve the grid connection regulation capacity of new energy power generation, and enhance the utilization efficiency of grid equipment. On the other hand, improve the overall energy efficiency of electricity consumption in society, strengthen the demand response capability of users, enable them to actively respond to grid demand, promote the integration of demand-side adjustable resources into the power grid, give full play to the role of time-of-use pricing, release demand-side resources, and promote the balance of power supply and demand.

[0108] This invention also provides a power transmission network performance evaluation system, comprising:

[0109] The evaluation system establishment module is used to establish an evaluation system for power transmission network performance indicators.

[0110] The indicator data acquisition module is used to acquire the original data of each indicator in the power transmission network performance indicator evaluation system for each target region and each year.

[0111] The standardization module is used to standardize all the raw data to obtain standardized data;

[0112] The CRITIC weight determination module is used to determine the CRITIC weight of each indicator based on the standardized data using the CRITIC method.

[0113] The entropy weight determination module is used to determine the entropy weight of each indicator based on the standardized data using the entropy weight method.

[0114] The combined weight determination module is used to combine the CRITIC weight and entropy weight based on the game theory-based combined weighting method to determine the combined weight of each indicator.

[0115] The comprehensive evaluation module is used to determine the comprehensive evaluation value of the power transmission network performance for each target region for each year, based on the combined weight of each indicator and the original data of each indicator for each target region for each year.

[0116] The power transmission network performance evaluation system provided in this embodiment of the invention has a similar working principle and beneficial effects to the power transmission network performance evaluation method described in the above embodiments, so it will not be described in detail here. For details, please refer to the introduction of the above method embodiments.

[0117] This invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the power transmission network performance evaluation method as described above.

[0118] Furthermore, when the computer program in the aforementioned memory 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, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory, random access memory, magnetic disks, or optical disks.

[0119] Furthermore, embodiments of the present invention also provide a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed, implements the power transmission network performance evaluation method as described above.

[0120] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the systems disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple; relevant parts can be referred to the method section.

[0121] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. Furthermore, those skilled in the art will recognize that, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method of transmission grid performance assessment, characterized in that, The method comprises the following steps: establishing a power transmission network performance index evaluation system; the power transmission network performance index evaluation system comprises low-carbon performance, social performance and operation performance; the low-carbon performance comprises new energy installed capacity, new energy power generation, thermal power installed capacity and thermal power generation; the social performance comprises total social power consumption, per capita power consumption and per capita living power consumption; the operation performance comprises line loss rate, loop length and transformer quantity; wherein the new energy installed capacity, the new energy power generation, the total social power consumption, the per capita power consumption and the per capita living power consumption are all positive indexes; the thermal power installed capacity, the thermal power generation, the line loss rate, the loop length and the transformer quantity are all negative indexes; obtaining original data of each index in each target region in each year in the power transmission network performance index evaluation system; standardizing all the original data to obtain standardized data; determining the CRITIC weight of each index by using the CRITIC method according to the standardized data; determining the entropy weight of each index by using the entropy weight method according to the standardized data; combining the CRITIC weight and the entropy weight by using a combination weighting method based on game theory to determine the combination weight of each index; determining the power transmission network performance comprehensive evaluation value of each target region in each year according to the combination weight of each index and the original data of each index in each target region in each year.

2. The power grid performance assessment method according to claim 1, characterized in that, The formula for standardizing all the original data is where x ij represents the original data of the jth index of the ith year of the target area, x j represents the jth index, (x j ) min and (x j ) max respectively represent the minimum and maximum original data of the jth index, x' ij represents the standardized data of the jth index of the ith year of the target area.

3. The power grid performance assessment method of claim 1, wherein, The calculation formula for determining the CRITIC weight of each index by using the CRITIC method is where R j represents the confliction size of the jth indicator with other indicators, r kj represents the correlation coefficient between the kth indicator and the jth indicator, S j represents the standard deviation of the jth indicator, C j represents the information amount of the jth indicator, w j represents the CRITIC weight of the jth indicator, K represents the number of indicators other than the jth indicator, and n represents the number of all indicators.

4. The method of claim 1, wherein, The calculation formula for determining the entropy weight of each index by using the entropy weight method is where p ij represents the ratio of the jth index under each scheme, x' ij represents the standardized data of the jth index of the target region in the ith year, E j represents the information entropy of the jth index, w j represents the entropy weight of the jth index, m represents the total number of years, and n represents the number of all indexes.

5. The method of claim 1, wherein, The combination weighting method based on game theory combines the CRITIC weight and the entropy weight to determine the combination weight of each index, which specifically comprises: The target function of combination weighting is determined as In the formula, z = 1, 2, α k The combination coefficient representing the weighting method, One of the basic weight sets is represented by And The index weight vector composed of the CRITIC weight of all indexes is The index weight vector composed of the entropy weight of all indexes is The basic weight before being weighted by the combination weight is represented. obtaining a first derivative of the objective function is Converting the first derivative into a system of linear equations is Solving the linear equations yields the equation solution (α1, α2), and using the formula normalizing the equation solution; in which, denotes the normalized equation solution; According to the normalized equation solution, the formula determines the combination weight w * .

6. The method of claim 1, wherein, The calculation formula for the power transmission network performance comprehensive evaluation value of each target region in each year is In the formula, S i represents the comprehensive evaluation value of the power grid performance in the i th year of the target region, represents the combined weight of the j th index, x' ij represents the standardized data of the j th index in the i th year of the target region, and n represents the number of all indexes.

7. A power grid performance assessment system, characterized by, The method comprises the following steps: an evaluation system establishing module for establishing a power transmission network performance index evaluation system; the power transmission network performance index evaluation system comprises low-carbon performance, social performance and operation performance; the low-carbon performance comprises new energy installed capacity, new energy power generation, thermal power installed capacity and thermal power generation; the social performance comprises total social power consumption, per capita power consumption and per capita living power consumption; the operation performance comprises line loss rate, loop length and transformer quantity; wherein the new energy installed capacity, the new energy power generation, the total social power consumption, the per capita power consumption and the per capita living power consumption are all positive indexes; the thermal power installed capacity, the thermal power generation, the line loss rate, the loop length and the transformer quantity are all negative indexes; an index data obtaining module for obtaining original data of each index in each target region in each year in the power transmission network performance index evaluation system; a standardization module for standardizing all the original data to obtain standardized data; a CRITIC weight determining module for determining the CRITIC weight of each index by using the CRITIC method according to the standardized data; an entropy weight determining module for determining the entropy weight of each index by using the entropy weight method according to the standardized data; a combination weight determination module configured to determine a combination weight of each index by combining the CRITIC weight and the entropy weight based on a combination weighting method of game theory; a comprehensive evaluation module configured to determine a comprehensive evaluation value of the performance of the power transmission network in each target region in each year according to the combination weight of each index and the original data of each index in each target region in each year.

8. An electronic device, comprising: A computer program product, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor implements the power transmission network performance evaluation method according to any one of claims 1 to 6 when executing the computer program.

9. A computer-readable storage medium, characterized in that, A computer program product, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor implements the power transmission network performance evaluation method according to any one of claims 1 to 6 when executing the computer program. A computer program product, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor implements the power transmission network performance evaluation method according to any one of claims 1 to 6 when executing the computer program.

Images