Vehicle network interactive service multi-dimensional effect evaluation method and system

Abstract

The invention relates to the technical field of vehicle network interaction evaluation, and particularly discloses a vehicle network interaction service multi-dimensional effect evaluation method and system, and the method comprises the steps: constructing a hierarchical structure model of a vehicle network interaction evaluation index system; obtaining an index weight of the vehicle network interaction evaluation index system; constructing a fuzzy judgment matrix, calculating an initial weight of an index, and carrying out consistency check; constructing a fuzzy comprehensive evaluation model; and performing fuzzy comprehensive evaluation to obtain a comprehensive evaluation result. Different sub-targets are selected from the technical, economic, environmental and social dimensions, and target acquisition means are formulated, so that a vehicle network interactive service multi-dimensional effect evaluation index system is constructed. The index weight is determined through the fuzzy analytic hierarchy process, the fuzzy comprehensive evaluation method combines fuzzy mathematics and the membership principle, some fuzzy evaluation standards which are difficult to express by accurate digits are considered, the fuzzy decision problem is solved, qualitative analysis and quantitative analysis are combined, and the evaluation result is more comprehensive and reasonable.

Description

Technical Field

[0001] This invention relates to the field of vehicle-to-everything (V2X) interaction evaluation technology, specifically to a multi-dimensional effectiveness evaluation method and system for V2X services. Background Technology

[0002] With the development and popularization of electric vehicles, vehicle-grid integration (VGI) technology has made significant progress. VGI refers to improving the stability and flexibility of the power system through energy and information exchange between electric vehicles and the power grid. The main methods of VGI include unidirectional ordered charging and bidirectional charging / discharging. Unidirectional ordered charging balances the power load and optimizes grid operation by regulating charging periods and charging power. Bidirectional charging / discharging allows electric vehicles to feed power back into the grid when needed, increasing grid flexibility and the utilization rate of renewable energy. VGI technology has a significant impact on the electric vehicle industry. It can help solve the bottleneck of charging infrastructure application and connection, making charging more convenient than refueling, reducing the cost of electric vehicles, promoting the comprehensive electrification transformation of electric vehicles, and further promoting the integration of smart grids and electric vehicles.

[0003] However, with the surge in the number of electric vehicles, their large-scale grid connection will inevitably bring many instabilities to the power grid in some areas. The uncertainty of electric vehicles will affect the overall level of the power grid and impact its stability. For example, when using fast charging and ultra-fast charging technologies, the high-power charging demand will have a greater impact on the voltage stability of the power grid. Therefore, to address the impact of the influx of electric vehicles on the power grid, it is necessary to assess the comprehensive interaction between electric vehicles and the distribution network, formulate vehicle-grid interaction strategies based on the assessment results, and adjust them in a timely manner to adapt to the dynamic power grid and user behavior, thereby ensuring and improving the normal operation of the vehicle-grid system.

[0004] Vehicle-to-everything (V2X) interaction assessment technology emerged to address the aforementioned issues, but existing technologies still have the following drawbacks:

[0005] (1) Most of the evaluation indicators set for the target scheduling scheme do not take into account the impact on society and users;

[0006] (2) Chinese patent application with publication number CN 120031247 A discloses a method, device, computer equipment and storage medium for evaluating the comprehensive effect of vehicle-to-grid interaction, but it does not take into account the technical factors related to vehicle-to-grid interaction equipment in the evaluation of the whole system;

[0007] (3) Chinese patent application with publication number CN 119885864 B discloses a vehicle-network interactive guidance simulation method and system. However, when making optimal strategy decisions, the weight selection of each influencing factor is not clear, and the importance of each factor has a certain degree of ambiguity and reproducibility.

[0008] In conclusion, it is necessary to propose a multi-dimensional effectiveness evaluation method and system for vehicle-to-everything (V2X) interactive services to address the technical issues of existing evaluation methods being insufficiently comprehensive, accurate, and reasonable. Summary of the Invention

[0009] The technical problem this invention aims to solve is to overcome the shortcomings of existing technologies and provide a more comprehensive, reasonable, and accurate multi-dimensional effectiveness evaluation method and system for vehicle-to-everything (V2X) interactive services. The specific technical solution is as follows:

[0010] Firstly, a multi-dimensional effectiveness evaluation method for vehicle-to-everything (V2X) interactive services is provided, the method comprising:

[0011] S1: Construct a hierarchical structure model for the vehicle-to-network interaction evaluation index system;

[0012] S2: Obtain the indicator weights of the vehicle-to-network interaction evaluation indicator system based on the expert group's evaluation results;

[0013] S3: Construct a fuzzy judgment matrix;

[0014] S4: Calculate the initial weights of the indicators based on the fuzzy judgment matrix and perform a consistency check;

[0015] S5: Construct a fuzzy comprehensive evaluation model;

[0016] S6: Perform fuzzy comprehensive evaluation to obtain the comprehensive evaluation result.

[0017] As a further improvement to the above technical solution:

[0018] The hierarchical structure model includes a target layer, a criterion layer, and an indicator layer;

[0019] The target layer is the evaluation of the effectiveness of vehicle-to-everything (V2X) interactive services;

[0020] The criteria layer is divided into four evaluation dimensions: technology, economy, environment and society.

[0021] The indicator layer consists of evaluation indicators for each evaluation dimension.

[0022] As a further improvement to the above technical solution:

[0023] The evaluation indicators include:

[0024] Control precision, adjustable capacity, and response time from a technical perspective;

[0025] The control precision is used to keep the vehicle battery in the optimal charging state during the charging process, and to avoid overcharging or over-discharging, which could damage the battery.

[0026] The adjustable capacity includes the maximum adjustable power and the average adjustable power, and the maximum adjustable power satisfies the following calculation formula: ;

[0027] In the formula: This refers to the maximum adjustable power of the power station at time t; This refers to the maximum charging power of the i-th charging pile at time t; This refers to the minimum charging power of the i-th charging pile at time t; It is the power limit constraint for electric vehicle charging stations or battery swapping stations; It represents the total number of electric vehicle charging stations or battery swapping stations with charging piles at time t.

[0028] The average adjustable power satisfies the following calculation formula: ;

[0029] In the formula: This refers to the average controllable power of the power station; This refers to the total charging power of an electric vehicle charging station or battery swapping station at time t on day j, based on historical data. This refers to the minimum charging power of the i-th charging pile at time t; It is the sampling interval time for collecting power at electric vehicle charging stations or battery swapping stations; It represents the total number of electric vehicle charging stations or battery swapping stations with charging piles at time t. It is the number of power samples collected from electric vehicle charging stations or battery swapping stations during a specified interactive scenario period; It is the number of sampling days for collecting power at electric vehicle charging stations or battery swapping stations during a specified interactive scenario period;

[0030] From an economic perspective, the utilization rate of power distribution equipment, the benefits of vehicle-to-grid interaction, and market potential.

[0031] The utilization rate of the power distribution equipment Based on the transformer area load report, the following calculation formula is satisfied: ;

[0032] In the formula: This represents the number of lightly loaded and normally loaded transformer areas. It refers to the change in the number of light-load rate and normal-load rate power stations that can be achieved after equipping the vehicle-to-grid project development equipment and vehicle-to-grid interaction strategies.

[0033] The benefits of vehicle-to-everything (V2X) interaction From the perspectives of the power grid and users, comparing the economic benefits of disordered charging and V2G, and then generalizing the results, the following calculation formula is satisfied: ;

[0034] In the formula: The increased load caused by disordered charging necessitates additional equipment investment and operating costs. The user-side cost is calculated according to the following formula: ;

[0035] In the formula: For users' electricity purchase costs, For battery wear and tear costs, Benefits derived from user participation in vehicle-to-everything (V2X) interaction and dispatching;

[0036] The market potential Based on the growth rate of new energy penetration and the growth rate of the number of charging piles It satisfies the following calculation formula: ; ; ; ;

[0037] In the formula: Indicates the transparency of new energy vehicles. This indicates the number of new energy vehicles in the next stage. This indicates the current number of new energy vehicles. This indicates the penetration rate of new energy vehicles in the next stage. This indicates the current penetration rate of new energy vehicles. This indicates the number of new energy charging piles to be installed in the next phase. This indicates the current number of new energy charging piles installed.

[0038] The impact of climate on the distributed resource output of power distribution networks and the recycling rate of renewable energy in the environmental dimension;

[0039] The impact of climate on distributed resource output of power distribution networks This represents the difference between the output and load of distributed resources that the current regional vehicle-to-everything (V2X) interaction strategy needs to compensate for, and is calculated according to the following formula: ;

[0040] In the formula: T is the total test duration, and T1 is the moment when there is a difference between distributed generation and load demand;

[0041] The renewable energy recycling rate is used to reflect the effectiveness of vehicle-to-grid (V2G) services in promoting the consumption and recycling of renewable energy.

[0042] User satisfaction and policy alignment from a social perspective;

[0043] The user satisfaction refers to the user satisfaction status of the test distribution network area. The policy fit is determined by examining the degree of conformity and synergistic effect between the vehicle-to-grid interaction service and relevant national and local policies. The user satisfaction and policy fit are also evaluated by establishing a hierarchical evaluation set.

[0044] As a further improvement to the above technical solution:

[0045] The construction of the fuzzy judgment matrix includes:

[0046] Construct fuzzy judgment matrices for the criterion layer and the indicator layer respectively;

[0047] The technical dimensions of the criteria layer are evaluated using a scoring method. Economic dimension Environmental dimension Social dimension Perform pairwise importance comparisons and construct fuzzy judgment matrices. ;

[0048] in, Representation of the criteria layer Compared to The degree of importance, and and They complement each other.

[0049] As a further improvement to the above technical solution:

[0050] The step of calculating the initial weights of the indicators based on the fuzzy judgment matrix and performing a consistency check includes:

[0051] Based on the fuzzy judgment matrix, the initial weights of the four evaluation dimensions (technology, economy, environment, and society) in the criterion layer are calculated, and their weight vectors are... The following calculation formula must be satisfied: ;

[0052] In the formula: Let be the element located in the i-th row and j-th column of matrix R. The number of evaluation dimensions in the criteria layer;

[0053] Its matrix elements Satisfy the following expression: ;

[0054] The compatibility index is calculated using the feature matrix. To perform a consistency check, the expression is as follows: ;

[0055] If CR is less than the preset value, the consistency check is passed.

[0056] As a further improvement to the above technical solution:

[0057] The construction of the fuzzy comprehensive evaluation model includes:

[0058] Determine the set of factors for evaluating the effectiveness of vehicle-to-everything (V2X) interactive services;

[0059] Determine the evaluation criteria and set the evaluation criteria. First, establish a fuzzy performance rating system for the vehicle-to-everything (V2X) interactive service, including five levels: Excellent, Good, Average, Poor, and Very Poor. Then, establish a rating set that satisfies the following expression: ;

[0060] Determine the weights of the evaluation indicators;

[0061] Establish a fuzzy evaluation matrix and combine the membership degrees of each indicator into matrix C, where rows represent indicators and columns represent evaluation levels.

[0062] As a further improvement to the above technical solution:

[0063] The comprehensive evaluation results obtained by the comprehensive evaluation include:

[0064] Construct a weight calculation matrix and use a weighted average calculation method. Multiply the fuzzy evaluation matrix with the weight calculation matrix to obtain the evaluation score of each indicator.

[0065] Secondly, a multi-dimensional performance evaluation system for vehicle-to-everything (V2X) interactive services is provided, including:

[0066] The user management module is used to import vehicle-to-everything (V2X) interaction evaluation index data from the vehicle-to-everything (V2X) interaction system terminal through the From File module in Simulink.

[0067] The data query module is used to build a database for vehicle-to-everything (V2X) interactive services, update the data in real time, and query the multi-dimensional performance evaluation results of V2X interactive services.

[0068] The data analysis module is used to perform preliminary processing on the raw data imported from the From File module, including handling missing and outlier values ​​and normalizing the raw data.

[0069] The comprehensive evaluation module is used to obtain comprehensive evaluation results through fuzzy hierarchical analysis. It includes constructing a fuzzy judgment matrix, calculating the initial weights of the indicators based on the fuzzy judgment matrix and performing consistency checks, constructing a fuzzy comprehensive evaluation model, and performing fuzzy comprehensive evaluation to obtain comprehensive evaluation results.

[0070] The evaluation report module is used to generate evaluation reports and evaluations of influencing factors by taking the scores and weights obtained from fuzzy hierarchical analysis as input.

[0071] Thirdly, a computer system is provided, comprising: a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the multi-dimensional effectiveness evaluation method for vehicle-to-everything (V2X) interactive services as described above.

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

[0073] This invention discloses a multi-dimensional effectiveness evaluation method for vehicle-to-everything (V2X) interactive services, comprising: constructing a hierarchical structure model of a V2X interactive evaluation index system; obtaining the index weights of the V2X interactive evaluation index system based on expert group evaluation results; constructing a fuzzy judgment matrix; calculating the initial weights of the indicators based on the fuzzy judgment matrix and performing consistency checks; constructing a fuzzy comprehensive evaluation model; and performing fuzzy comprehensive evaluation to obtain the comprehensive evaluation result. By selecting different sub-objectives from four dimensions—technology, economy, environment, and society—and formulating target acquisition methods, a multi-dimensional effectiveness evaluation index system for V2X interactive services is constructed. The index weights are determined using fuzzy hierarchical analysis. The fuzzy comprehensive evaluation method combines fuzzy mathematics and the membership principle, considering the fuzziness of some evaluation standards that are difficult to express with precise numbers, thus solving the fuzzy decision-making problem. Combining qualitative and quantitative analysis makes the evaluation results more comprehensive and reasonable. Attached Figure Description

[0074] Figure 1 This is a flowchart illustrating a multi-dimensional effectiveness evaluation method for vehicle-to-everything (V2X) interactive services according to an embodiment of the present invention.

[0075] Figure 2 This is a schematic diagram of the hierarchical structure model of an embodiment of the present invention.

[0076] Figure 3 This is an architecture diagram of the multi-dimensional effectiveness evaluation system for vehicle-to-everything (V2X) interactive services according to an embodiment of the present invention. Detailed Implementation

[0077] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0078] like Figure 1 As shown, this implementation provides a multi-dimensional effectiveness evaluation method for vehicle-to-everything (V2X) interactive services, including the following steps:

[0079] S1: Construct a hierarchical structure model for the vehicle-to-network interaction evaluation index system;

[0080] An evaluation index system is a combination of various indicators selected to comprehensively and objectively reflect the overall characteristics of an evaluation object, centered around a specific object and with a defined purpose or goal. The vehicle-to-everything (V2X) interaction evaluation index system in this embodiment is constructed according to the following principles:

[0081] (1) Principle of Goal Orientation: The indicators selected for the comprehensive benefit evaluation of vehicle-to-grid interaction are directional indicators that reflect the current status and development requirements of vehicle-to-grid interaction. The indicators reflect the most fundamental purpose of the evaluation work. Therefore, the evaluation indicators should be able to most realistically reflect the technical level and development of vehicle-to-grid interaction, reveal the problems existing in the construction and improvement of vehicle-to-grid interaction, and ensure the high-quality development of vehicle-to-grid interaction.

[0082] (2) Dynamic optimization principle: Vehicle-to-grid interaction is an emerging concept that has emerged with the development of electric vehicles. With the continuous construction and improvement of new power systems, the connotation of vehicle-to-grid interaction will be continuously enriched. The comprehensive benefit evaluation of vehicle-to-grid interaction should keep pace with the times and be dynamically adjusted and optimized.

[0083] (3) Principle of mutual independence: Each index at the same level in the evaluation index system is independently measured. There should be no potential relationship such as overlap, causality, or inclusion that may affect the final evaluation result; otherwise, the evaluation work will not be of reference value.

[0084] (4) Principle of Quantifiability: Evaluation indicators should be quantified as much as possible. However, some indicators (such as policies) are difficult to quantify. In such cases, qualitative indicators can be used to describe them, so as to make scientific evaluation conclusions on the evaluated object from both qualitative and quantitative perspectives. Indicators should have clear meanings and be based on available statistical data, thus allowing for calculation and analysis based on quantity. At the same time, the number of indicator items should be appropriate, and the content should be concise. Evaluation should be as simple as possible while ensuring validity.

[0085] (5) Comprehensive principle: Evaluation indicators should be evaluated from multiple aspects such as technology, ecology, and economy, making full use of multidisciplinary knowledge, interdisciplinary and comprehensive knowledge to ensure the comprehensiveness and credibility of the comprehensive evaluation. The indicator system should be able to fully reproduce and reflect the comprehensive benefits brought to the power system by vehicle-grid interaction. This includes not only the direct benefits of stable power system operation and new energy consumption, but also environmental benefits, economic benefits and social recognition.

[0086] Regarding the multi-dimensional effectiveness evaluation of vehicle-to-everything (V2X) interaction services, based on existing policies and guidelines, the following principles should also be followed:

[0087] A. Data Support: The evaluation process establishes a complete data support system to ensure that the basic data used is accurate, timely, and traceable, and that the data source and collection methods are verifiable;

[0088] B. Technological and economic efficiency: The design of the evaluation method should take into account the implementation cost while meeting the requirements of evaluation accuracy, and give priority to the technical path with the best cost-effectiveness to ensure the economy and feasibility of the evaluation work.

[0089] C. Expansion and Compatibility: The evaluation framework has good compatibility and scalability, adapting to the development and iteration of electric vehicle and grid technologies, as well as the changing needs of electricity market rules and policies. It reserves scalable interfaces to support future functional upgrades and optimizations.

[0090] This embodiment constructs an evaluation index system and establishes a hierarchical structure model according to the aforementioned principles. For the multi-dimensional effectiveness evaluation of vehicle-to-everything (V2X) interactive services, it clearly defines the primary key evaluation dimensions based on technology, economy, environment, and society, and further refines these into a closely related secondary evaluation index system, specifically covering various sub-indicators, aiming to achieve a more comprehensive and in-depth evaluation. This structure forms a hierarchical model, the framework of which is as follows: Figure 2 As shown, it includes a target layer, a criterion layer, and an indicator layer; the target layer is for evaluating the effectiveness of vehicle-to-everything (V2X) interactive services; the criterion layer is divided into four evaluation dimensions: technology, economy, environment, and society; and the indicator layer consists of evaluation indicators for each evaluation dimension.

[0091] Furthermore, the specific evaluation indicators are:

[0092] Control precision, adjustable capacity, and response time from a technical perspective;

[0093] The control precision is used to ensure that the vehicle battery is in the optimal charging state during the charging process, avoiding damage to the battery from overcharging or over-discharging; high-precision control helps to improve charging efficiency and battery life, while ensuring the stable operation of the power grid.

[0094] The adjustable capacity includes the maximum adjustable power and the average adjustable power, and the maximum adjustable power satisfies the following calculation formula: ;

[0095] In the formula: This refers to the maximum adjustable power of the power station at time t; This refers to the maximum charging power of the i-th charging pile at time t; This refers to the minimum charging power of the i-th charging pile at time t; It is the power limit constraint for electric vehicle charging stations or battery swapping stations; It represents the total number of electric vehicle charging stations or battery swapping stations with charging piles at time t.

[0096] The average adjustable power satisfies the following calculation formula: ;

[0097] In the formula: This refers to the average controllable power of the power station; This refers to the total charging power of an electric vehicle charging station or battery swapping station at time t on day j, based on historical data. This refers to the minimum charging power of the i-th charging pile at time t; It is the sampling interval time for collecting power at electric vehicle charging stations or battery swapping stations; It represents the total number of electric vehicle charging stations or battery swapping stations with charging piles at time t. It is the number of power samples collected from electric vehicle charging stations or battery swapping stations during a specified interactive scenario period; It is the number of sampling days for collecting power at electric vehicle charging stations or battery swapping stations during a specified interactive scenario period;

[0098] The response time of an electric vehicle charging station or battery swapping station reflects the time required from receiving a regulation command to actually executing the regulation. It is affected by communication delays between the charging (swapping) station and the charging pile, charging processing delays, and charging pile execution delays. Evaluation indicators are calculated to address these delays. Its response time is evaluated using the following formula: ;

[0099] In the formula: For response time; It is the time it takes for the instruction to be received by the i-th charging pile; It is the time when the i-th charging pile processes the instruction and starts adjusting the charging power. It is the actual time for the i-th charging pile to complete the power adjustment.

[0100] From an economic perspective, the utilization rate of power distribution equipment, the benefits of vehicle-to-grid interaction, and market potential.

[0101] The utilization rate of the power distribution equipment Based on the transformer area load report, the following calculation formula is satisfied: ;

[0102] In the formula: This represents the number of lightly loaded and normally loaded transformer areas. It refers to the change in the number of light-load rate and normal-load rate power stations that can be achieved after equipping the vehicle-to-grid project development equipment and vehicle-to-grid interaction strategies.

[0103] The benefits of vehicle-to-everything (V2X) interaction From the perspectives of the power grid and users, comparing the economic benefits of disordered charging and V2G, and then generalizing the results, the following calculation formula is satisfied: ;

[0104] In the formula: The increased load caused by disordered charging necessitates additional equipment investment and operating costs. The user-side cost is calculated according to the following formula: ;

[0105] In the formula: For users' electricity purchase costs, For battery wear and tear costs, Benefits derived from user participation in vehicle-to-everything (V2X) interaction and dispatching;

[0106] The market potential Based on the growth rate of new energy penetration and the growth rate of the number of charging piles It satisfies the following calculation formula: ; ; ; ;

[0107] In the formula: Indicates the transparency of new energy vehicles. This indicates the number of new energy vehicles in the next stage. This indicates the current number of new energy vehicles. This indicates the penetration rate of new energy vehicles in the next stage. This indicates the current penetration rate of new energy vehicles. This indicates the number of new energy charging piles to be installed in the next phase. This indicates the current number of new energy charging piles installed.

[0108] The impact of climate on the distributed resource output of power distribution networks and the recycling rate of renewable energy in the environmental dimension;

[0109] The impact of climate on distributed resource output of power distribution networks This represents the difference between the output and load of distributed resources that the current regional vehicle-to-everything (V2X) interaction strategy needs to compensate for, and is calculated according to the following formula: ;

[0110] In the formula: T is the total test duration, and T1 is the moment when there is a difference between distributed generation and load demand;

[0111] The renewable energy recycling rate is used to reflect the effectiveness of vehicle-to-grid (V2G) interaction in promoting the consumption and recycling of renewable energy. Through V2G interaction, vehicles can charge when there is a surplus of renewable energy generation and store the excess electricity. When the grid needs it, the stored electricity is released back to the grid, realizing the effective use of renewable energy, reducing wind and solar curtailment, increasing the proportion of renewable energy in the energy structure, and reducing carbon emissions.

[0112] The amount of wind and solar power curtailed under the vehicle-to-grid (V2G) interaction model reflects the energy-saving and emission-reduction benefits of the distribution network. The standard for the wind and solar curtailment rate is based on the "Methods and Standards for Environmental Monitoring and Evaluation of Photovoltaic Power Generation Market" issued by the National Energy Administration, and is scored according to the degree of solar curtailment in the evaluation year and in combination with the completion of guaranteed hours.

[0113] Those who do not discard light will receive 30 points;

[0114] A score of 29 is awarded for a light rejection rate of no more than 1%.

[0115] A score of 28 is awarded for a light rejection rate higher than 1% but not exceeding 2%.

[0116] A score of 27 is awarded for a light rejection rate higher than 2% but not exceeding 3%.

[0117] A waste of light rate higher than 3% but not exceeding 3.5% will receive 25 points;

[0118] A waste of light rate higher than 3.5% but not exceeding 4% will receive 23 points;

[0119] A waste rate higher than 4% but not exceeding 4.5% will receive 21 points;

[0120] A light rejection rate higher than 4.5% but not exceeding 5% will receive 18 points;

[0121] A light rejection rate higher than 5% but not exceeding 6% will receive 15 points;

[0122] A light rejection rate higher than 6% but not exceeding 7% will receive 12 points;

[0123] A light rejection rate higher than 7% but not exceeding 8% will receive 9 points;

[0124] 5 points for no wind loss:

[0125] A solar curtailment rate of no more than 5% and a wind curtailment rate of less than 10% will receive 3 points.

[0126] A solar curtailment rate higher than 5% and a wind curtailment rate higher than 10% will receive 1 point.

[0127] A curtailment rate of more than 8% for solar power and more than 10% for wind power is 0 points.

[0128] If there is no wasted light but the score for this item is less than 3 points, it will be counted as 3 points.

[0129] Based on the above indicators, they are converted into percentages using a normalization method.

[0130] User satisfaction and policy alignment from a social perspective;

[0131] The user satisfaction level refers to the user satisfaction status of the test distribution network area, and the method used is a questionnaire survey. The questionnaire is generally divided into five levels: satisfied, basically satisfied, average, somewhat dissatisfied, and dissatisfied, establishing a graded evaluation set. ; correspond , , , , .

[0132] The policy alignment is determined by examining the degree of compliance and synergistic effect between vehicle-to-the-net (V2N) interaction services and relevant national and local policies; for example, whether they comply with new energy vehicle development policies, power grid planning policies, and energy conservation and emission reduction policies. V2N interaction services that are highly aligned with policies can obtain more policy support and resource allocation, which is conducive to promoting the rapid development of the business and also helps to achieve policy objectives and promote sustainable social development.

[0133] The survey investigated relevant policies and categorized policy relevance into three levels: compliant, basically compliant, and non-compliant. A tiered evaluation system was then established. ; correspond , , .

[0134] If the number of relevant policies is N, then the policy fit is expressed as follows: ;

[0135] Taking a regional power distribution network with a basic power capacity of about 60MVA as an example of vehicle-grid interaction operation sample data, the regional power grid has 3 centralized charging stations with a total capacity of 20MW, and also has photovoltaic power generation panels with a capacity of 25MW.

[0136] In the case of disordered charging, centralized charging stations offer rapid recharging capabilities, and electric vehicle users charge at these stations as needed, resulting in potential charging loads at any time of day. Simulations show that the maximum active power of the regional distribution network increases from 40MW to 57.33MW, a 43.32% increase; the peak-to-valley difference increases from 21.33MW to 38.67MW, an 81.29% increase; and the load standard deviation increases from 5.97MW to 10.28MW, a 72.19% increase. Conversely, under ordered charging conditions, the maximum active power decreases from 40MW to 37.33MW, a 6.68% decrease; the peak-to-valley difference decreases from 21.33MW to 4.48MW, a 79% decrease; and the load standard deviation decreases from 5.97MW to 0.95MW, an 84.09% decrease. Under ordered charging and discharging conditions, the maximum active power decreases from 40MW to 33.12MW, a 17.2MW decrease. Meanwhile, in the disordered charging mode, because the electric vehicle charging load cannot be well matched with the photovoltaic power, there is a curtailment of 28.41 MWh of solar power, with a curtailment rate of 18.71%; while in the ordered charging mode, the curtailment is 0.31 MWh, with a curtailment rate of 0.20%. Based on this scenario, various evaluation indicators were calculated, and then the evaluation model was verified. The verification process is shown in S2-S6.

[0137] S2: Obtain the indicator weights of the vehicle-to-network interaction evaluation indicator system based on the expert group's evaluation results;

[0138] The method of determining indicator weights using the analytic hierarchy process (AHP) typically relies on a comprehensive evaluation by an expert panel. The number of experts participating in the evaluation is usually between 5 and 20, both to ensure the scientific validity of the evaluation results and to avoid excessive workload. In this embodiment, an expert panel was formed during the identification of evaluation indicators for the effectiveness of vehicle-to-everything (V2X) interactive services.

[0139] S3: Construct a fuzzy judgment matrix. After obtaining the expert panel's evaluation results, construct a fuzzy judgment matrix for further analysis, including:

[0140] Construct fuzzy judgment matrices for the criterion layer and the indicator layer respectively;

[0141] The technical dimensions of the criteria layer are evaluated using a scoring method. Economic dimension Environmental dimension Social dimension Perform pairwise importance comparisons and construct fuzzy judgment matrices. ;

[0142] in, Representation of the criteria layer Compared to The degree of importance, and and They complement each other, for example when ,So The fuzzy judgment matrix obtained in this embodiment is shown in the table below:

[0143] S4: Calculate the initial weights of the indicators based on the fuzzy judgment matrix and perform consistency checks, including:

[0144] Based on the fuzzy judgment matrix, the initial weights of the four evaluation dimensions (technology, economy, environment, and society) in the criterion layer are calculated, and their weight vectors are... The following calculation formula must be satisfied: ;

[0145] In the formula: Let be the element located in the i-th row and j-th column of matrix R. In this embodiment, n=4, which represents the number of evaluation dimensions for the criteria layer.

[0146] In fuzzy comprehensive evaluation, if the judgment matrix does not meet the consistency requirements, the criterion weights calculated using that matrix may be distorted. Therefore, to ensure the logical rationality of the matrix, a consistency check is necessary. Its matrix elements Satisfy the following expression: ;

[0147] The compatibility index is calculated using the feature matrix. To perform a consistency check, the expression is as follows: ;

[0148] If CR is less than the preset value, the consistency check is passed.

[0149] The data used in the Analytic Hierarchy Process (AHP) to determine the weights of the evaluation indicators for vehicle-to-everything (V2X) interactive services was derived by experts based on their accumulated experience, and therefore contains a degree of subjectivity. To ensure the rationality and scientific validity of the data, a consistency check was performed on the results. The verification results of this embodiment are as follows:

[0150] A) Consistency check: —Conformity passed;

[0151] B1) Consistency check: —Conformity passed;

[0152] B3) Consistency check: —Conformity passed;

[0153] B3) Consistency check: ;

[0154] B4) Consistency check: ;

[0155] S5: Construct a fuzzy comprehensive evaluation model, specifically:

[0156] Determine the set of factors for evaluating the effectiveness of vehicle-to-everything (V2X) interactive services;

[0157] Determine the evaluation criteria and set the evaluation criteria. First, establish a fuzzy performance rating system for the vehicle-to-everything (V2X) interactive service, including five levels: Excellent, Good, Average, Poor, and Very Poor. Then, establish a rating set that satisfies the following expression: ; Corresponding advantages ,good ,generally Poor ,Difference .

[0158] Determine the weights of the evaluation indicators;

[0159] Establish a fuzzy evaluation matrix and combine the membership degrees of each indicator into matrix C, where rows represent indicators and columns represent evaluation levels.

[0160] Considering the complexity of the multi-dimensional performance evaluation system for vehicle-to-everything (V2X) interaction services and the presence of numerous fuzzy factors (such as market potential and user satisfaction), a fuzzy comprehensive evaluation method was chosen. Furthermore, the weight vectors of the evaluation factors determined by the analytic hierarchy process in the previous chapter were used to derive precise evaluation results, aiming to achieve a more accurate and comprehensive performance assessment.

[0161] The weights of the vehicle-to-network interaction evaluation indicators calculated in this embodiment are shown in the table below:

[0162] S6: Perform fuzzy comprehensive evaluation to obtain the comprehensive evaluation result, specifically:

[0163] Construct a weight calculation matrix and use a weighted average calculation method. Multiply the fuzzy evaluation matrix with the weight calculation matrix to obtain the evaluation score of each indicator.

[0164] The comprehensive evaluation result can be obtained by combining the weight vector W and the membership matrix R, and the calculation formula is B=W*R. Based on the data above, the membership matrices R of the four primary indicators are as follows: ;

[0165] The weight vector W = [0.4710, 0.2783, 0.1580, 0.0928].

[0166] The matrix multiplication method yields: B = W * R_total = [0, 0.0632, 0.2009, 0.4295, 0.3064]. The above results are all normalized and correspond to the membership degrees of "Very Poor (I), Poor (II), Medium (III), Good (IV), Excellent (V)" in the evaluation set V.

[0167] As shown in the table above, the membership degrees corresponding to the five levels in the comprehensive evaluation of the multi-dimensional effectiveness of the vehicle-to-the-net (V2N) interactive service are different. The "Good" level has the highest membership degree (0.4295), while the "Very Poor" level has the lowest (0), followed by "Medium," "Excellent," and "Poor." Based on the principle of maximum membership degree, the comprehensive evaluation level of the V2N interactive service is determined to be "Good." In terms of actual business implementation, the V2N interactive service has achieved certain results in terms of technical control, economic benefits, environmental adaptability, and user feedback. For example, the control accuracy compliance rate is relatively high, the benefits of V2N interactive services are gradually emerging, and the utilization rate of renewable energy is steadily increasing, which is basically consistent with the evaluation results.

[0168] Further calculations of the above results showed that the weighted sum of the membership degrees for the "Excellent" and "Good" levels was 0.7359; the weighted sum of the membership degrees for the "Medium," "Poor," and "Very Poor" levels was 0.2641. Overall, the effectiveness of this car-to-everything (C2X) interactive service falls between "Excellent" and "Good," indicating good overall performance, but there is still room for improvement.

[0169] Based on the above performance evaluation results and the classification of vehicle-to-everything (V2X) interaction business performance levels, the multi-dimensional performance level of this V2X interaction business is judged to be "relatively good". According to this classification, in subsequent business optimization, we can specifically strengthen the improvement of weak links (such as improving response speed and responding to climate impacts).

[0170] 7) Evaluation Result Analysis

[0171] Analysis of the above research results reveals that while there are differences in the effectiveness evaluation results across the four dimensions, the overall picture is relatively balanced. The social dimension (control precision, adjustable capacity, response speed) accounts for the highest proportion at 32.1%, reflecting the project's focus on user experience and policy alignment. This is followed by the economic dimension (power distribution equipment utilization rate, vehicle-to-grid interaction benefits, market potential) at 23.6%, directly impacting business sustainability. The technological dimension (control precision, adjustable capacity, response speed) accounts for approximately 22.6%, representing the core factor influencing the effectiveness of vehicle-to-grid interaction services. The environmental dimension (climate impact, renewable energy utilization rate) has the lowest proportion at approximately 21.7%, requiring further reflection of the business's ecological value. A detailed analysis follows:

[0172] Technical Dimension (Core Technical Capabilities): In vehicle-to-grid (V2G) interaction services, technical dimension 1 plays a crucial role. Control precision directly affects the stability of power grid dispatch, adjustable capacity relates to load regulation capability, and response speed determines emergency response efficiency. Currently, in the business, control precision, response speed, and adjustable capacity basically meet the requirements (their membership levels are "Good," "Good," and "Excellent," respectively).

[0173] Economic Dimension (Business Sustainability): The economic dimension is key to the promotion of vehicle-to-grid (V2G) services. V2G benefits and market potential are performing well (ranked as "Good" and "Excellent" respectively), indicating that the business has profitability prospects and market expansion space. However, the utilization rate of power distribution equipment is low (ranked as "Medium"), mainly due to the inflexible equipment scheduling mechanism, resulting in equipment idleness during certain periods. Going forward, it is necessary to optimize equipment scheduling strategies, combining user charging demand with grid load fluctuations, to improve equipment utilization efficiency and reduce unit costs.

[0174] Environmental Dimension (Ecological Value): The environmental dimension reflects the green attributes of the vehicle-to-grid (V2G) business. Renewable energy recycling rates are good (affiliation level: "Excellent"). However, the impact of climate on distributed power output in the distribution network is poor (affiliation level: "Poor"). For example, strong winds and high temperatures can easily cause fluctuations in distributed photovoltaic and wind power output, affecting business stability. It is necessary to strengthen the coordination between climate early warning and resource scheduling, establish backup power and load regulation schemes for extreme weather conditions, and reduce the interference of environmental factors on the business.

[0175] Policy Dimension (User and Policy Adaptation): User satisfaction and policy alignment are crucial for long-term business development. High user satisfaction (ranked "Excellent") indicates user approval of the business experience. Simultaneously, high policy alignment (ranked "Excellent") demonstrates clear local policies regarding subsidies and grid connection standards for vehicle-to-everything (V2X) projects, leading to smoother business progress. Further strengthening communication with local energy departments to refine policies and ensure close alignment between business and policy guidance is possible. Additionally, user surveys can be used to further optimize services and enhance user engagement.

[0176] This embodiment also provides a multi-dimensional performance evaluation system for vehicle-to-everything (V2X) interactive services, including:

[0177] The user management module is used to import vehicle-to-everything (V2X) interaction evaluation index data from the vehicle-to-everything (V2X) interaction system terminal through the From File module in Simulink.

[0178] The data import module utilizes the From File module in Simulink. This module can directly import external file data into the Simulink model, reusing previously simulated data files or using measured data files to verify the model's performance under specific inputs. It supports various file formats, such as MAT files and text files, and allows for flexible configuration of the data within the files, such as selecting different variables or specifying the time range. Since the data originates from a file, simulations can be repeated as long as the file content remains unchanged, ensuring consistent simulation results. It also facilitates integration with external data sources, such as experimental measurement data and historical simulation data, allowing the model to simulate under the drive of real data. Furthermore, it avoids manually setting complex signal sources within the model, directly driving the model with file data, making the model more concise and readable.

[0179] Technical metrics collected from the vehicle-to-everything (V2X) system terminal include control precision, adjustable capacity, and response speed.

[0180] The system derives the power output and renewable energy recycling rate from the following indicators: the utilization rate of distribution equipment in the economic dimension, the impact of climate on the output of distributed resources in the distribution network, and the renewable energy recycling rate from the environmental dimension.

[0181] In addition, advance research and data collection yielded economic indicators such as vehicle-to-everything (V2X) interaction benefits and market potential scores, as well as social indicators such as user satisfaction and alignment with relevant government policies.

[0182] After collecting the above data, it is classified and imported into a file using the evaluation system described above. The file is then imported into the model using the From File module.

[0183] The data query module is used to build a vehicle-to-everything (V2X) interaction business database, update the data in real time, and query the multi-dimensional effectiveness evaluation results of the V2X interaction business. By building the V2X interaction business database, the module enables one-click query analysis results, and the data is updated in real time, making data analysis flexible and simple.

[0184] The data analysis module is used to perform preliminary processing on the raw data imported from the From File module, including handling missing and outlier values ​​and normalizing the raw data.

[0185] Basic data processing plays a crucial role in the multi-dimensional evaluation simulation model of vehicle-to-everything (V2X) interaction. It is responsible for the initial processing of the raw data imported from the From File module, providing high-quality data for subsequent operations such as normalization, fuzzy hierarchical analysis, and comprehensive evaluation. This includes handling missing and outlier values ​​in the raw data.

[0186] Missing data is handled using linear interpolation. Linear interpolation assumes that two data points are known (…). )and( ), for the x ( ) between two data points The missing value y at position ) is interpolated using the following formula: ;

[0187] Outliers are handled using the standard deviation method. Let the dataset be... , ,..., The mean is The standard deviation is Will satisfy (k is usually taken as 3) data points These are considered outliers and should be deleted.

[0188] In the simulation system of the multi-dimensional evaluation system for vehicle-to-grid interaction, normalization is a crucial step in ensuring the accuracy of system analysis and the reliability of evaluation results. In this system, data indicators involve multiple scenarios, such as electrical, economic, and environmental scenarios. If these parameters are not normalized to eliminate dimensional differences, it will lead to an imbalance in the indicator weights in the subsequent fuzzy hierarchical algorithm, resulting in distorted final evaluation results.

[0189] Min-Max normalization is used to normalize the coarsely processed data. This method performs a linear transformation based on the maximum and minimum values ​​of the original data, mapping the data to a specified interval, typically [0,1]. The calculation formula is as follows: ;

[0190] in These are the original data points. It is the minimum point in the dataset. It is the point with the maximum value in the dataset. It is the normalized data.

[0191] The comprehensive evaluation module is used to obtain comprehensive evaluation results through fuzzy hierarchical analysis. It includes constructing a fuzzy judgment matrix, calculating the initial weights of the indicators based on the fuzzy judgment matrix and performing consistency checks, constructing a fuzzy comprehensive evaluation model, and performing fuzzy comprehensive evaluation to obtain comprehensive evaluation results.

[0192] Traditional Analytic Hierarchy Process (AHP) is based on precise mathematics and constructs a judgment matrix through pairwise comparisons by experts. It requires precise numerical values ​​and accurate judgments, making it difficult to handle fuzzy information. Some indicators in a project are fuzzy data and cannot be used. Furthermore, the weights are highly subjective, and the generated weights are greatly influenced by expert experience. Expert opinions may be distorted due to repeated adjustments.

[0193] The fuzzy hierarchical analysis method (FAHP), which incorporates fuzzy mathematics, can handle fuzzy data, better aligns with the fuzziness of human thinking, and is closer to the actual decision-making process.

[0194] The evaluation report module is used to generate evaluation reports and evaluations of influencing factors by taking the scores and weights obtained from fuzzy hierarchical analysis as input.

[0195] The scores and weights obtained from the fuzzy hierarchical analysis are used as input to the evaluation report generation module, which generates an evaluation report and an evaluation of the influencing factors. The table header includes the dimension category, relevant factors, overall weight of the fuzzy evaluation value, weighted evaluation value, and weighted sort. The table content contains the weights, evaluation values, score rankings, and the final overall evaluation value for each dimension and indicator.

[0196] Based on the evaluation scores and weighted ranking, and considering the actual situation, the results of each indicator are manually analyzed. The final score is then correlated with the comment set mentioned earlier, and a comprehensive analysis is performed to generate a complete evaluation report. The overall functional architecture is as follows: Figure 3 As shown.

[0197] This embodiment also provides a computer system, including: a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the multi-dimensional effectiveness evaluation method for vehicle-to-everything (V2X) interactive services as described above.

[0198] The computer system can be a computing device such as a mobile phone, desktop computer, laptop, handheld computer, or cloud server. The computer system may include, but is not limited to, a processor and memory. For example, the computer system may also include input / output devices, network access devices, and a bus.

[0199] The above description is merely a preferred embodiment of the present invention, and the scope of protection of the present invention is not limited to the above embodiments. For those skilled in the art, improvements and modifications obtained without departing from the inventive concept should also be considered within the scope of protection of the present invention.

Claims

1. A multi-dimensional effectiveness evaluation method for vehicle-to-everything (V2X) interactive services, characterized in that, The method includes: S1: Construct a hierarchical structure model for the vehicle-to-network interaction evaluation index system; S2: Obtain the indicator weights of the vehicle-to-network interaction evaluation indicator system based on the expert group's evaluation results; S3: Construct a fuzzy judgment matrix; S4: Calculate the initial weights of the indicators based on the fuzzy judgment matrix and perform a consistency check; S5: Construct a fuzzy comprehensive evaluation model; S6: Perform fuzzy comprehensive evaluation to obtain the comprehensive evaluation result.

2. The multi-dimensional effectiveness evaluation method for vehicle-to-everything (V2X) interactive services according to claim 1, characterized in that, The hierarchical structure model includes a target layer, a criterion layer, and an indicator layer; The target layer is the evaluation of the effectiveness of vehicle-to-everything (V2X) interactive services; The criteria layer is divided into four evaluation dimensions: technology, economy, environment and society. The indicator layer consists of evaluation indicators for each evaluation dimension.

3. The multi-dimensional effectiveness evaluation method for vehicle-to-everything (V2X) interactive services according to claim 2, characterized in that, The evaluation indicators include: Control precision, adjustable capacity, and response time from a technical perspective; The control precision is used to keep the vehicle battery in the optimal charging state during the charging process, and to avoid overcharging or over-discharging, which could damage the battery. The adjustable capacity includes the maximum adjustable power and the average adjustable power, and the maximum adjustable power satisfies the following calculation formula: ； In the formula: This refers to the maximum adjustable power of the power station at time t; This refers to the maximum charging power of the i-th charging pile at time t; This refers to the minimum charging power of the i-th charging pile at time t; It is the power limit constraint for electric vehicle charging stations or battery swapping stations; It represents the total number of electric vehicle charging stations or battery swapping stations with charging piles at time t. The average adjustable power satisfies the following calculation formula: ； In the formula: This refers to the average controllable power of the power station; This refers to the total charging power of an electric vehicle charging station or battery swapping station at time t on day j, based on historical data. This refers to the minimum charging power of the i-th charging pile at time t; It is the sampling interval time for collecting power at electric vehicle charging stations or battery swapping stations; It represents the total number of electric vehicle charging stations or battery swapping stations with charging piles at time t. It is the number of power samples collected from electric vehicle charging stations or battery swapping stations during a specified interactive scenario period; It is the number of sampling days for collecting power at electric vehicle charging stations or battery swapping stations during a specified interactive scenario period; From an economic perspective, the utilization rate of power distribution equipment, the benefits of vehicle-to-grid interaction, and market potential. The utilization rate of the power distribution equipment Based on the transformer area load report, the following calculation formula is satisfied: ； In the formula: This represents the number of lightly loaded and normally loaded transformer areas. It refers to the change in the number of light-load rate and normal-load rate power stations that can be achieved after equipping the vehicle-to-grid project development equipment and vehicle-to-grid interaction strategies. The benefits of vehicle-to-everything (V2X) interaction From the perspectives of the power grid and users, comparing the economic benefits of disordered charging and V2G, and then generalizing the results, the following calculation formula is satisfied: ； In the formula: The increased load caused by disordered charging necessitates additional equipment investment and operating costs. The user-side cost is calculated according to the following formula: ； In the formula: For users' electricity purchase costs, For battery wear and tear costs, Benefits derived from user participation in vehicle-to-everything (V2X) interaction and dispatching; The market potential Based on the growth rate of new energy penetration and the growth rate of the number of charging piles It satisfies the following calculation formula: ； ； ； ； In the formula: Indicates the transparency of new energy vehicles. This indicates the number of new energy vehicles in the next stage. This indicates the current number of new energy vehicles. This indicates the penetration rate of new energy vehicles in the next stage. This indicates the current penetration rate of new energy vehicles. This indicates the number of new energy charging piles to be installed in the next phase. This indicates the current number of new energy charging piles installed. The impact of climate on the distributed resource output of power distribution networks and the recycling rate of renewable energy in the environmental dimension; The impact of climate on distributed resource output of power distribution networks This represents the difference between the output and load of distributed resources that the current regional vehicle-to-everything (V2X) interaction strategy needs to compensate for, and is calculated according to the following formula: ； In the formula: T is the total test duration, and T1 is the moment when there is a difference between distributed generation and load demand; The renewable energy recycling rate is used to reflect the effectiveness of vehicle-to-grid (V2G) services in promoting the consumption and recycling of renewable energy. User satisfaction and policy alignment from a social perspective; The user satisfaction refers to the user satisfaction status of the test distribution network area. The policy fit is determined by examining the degree of conformity and synergistic effect between the vehicle-to-grid interaction service and relevant national and local policies. The user satisfaction and policy fit are also evaluated by establishing a hierarchical evaluation set.

4. The multi-dimensional effectiveness evaluation method for vehicle-to-everything (V2X) interactive services according to claim 3, characterized in that, The construction of the fuzzy judgment matrix includes: Construct fuzzy judgment matrices for the criterion layer and the indicator layer respectively; The technical dimensions of the criteria layer are evaluated using a scoring method. Economic dimension Environmental dimension Social dimension Perform pairwise importance comparisons and construct fuzzy judgment matrices. ; in, Representation of the criteria layer Compared to The degree of importance, and and They complement each other.

5. The multi-dimensional effectiveness evaluation method for vehicle-to-everything (V2X) interactive services according to claim 4, characterized in that, The step of calculating the initial weights of the indicators based on the fuzzy judgment matrix and performing a consistency check includes: Based on the fuzzy judgment matrix, the initial weights of the four evaluation dimensions (technology, economy, environment, and society) in the criterion layer are calculated, and their weight vectors are... The following calculation formula must be satisfied: ； In the formula: Let be the element located in the i-th row and j-th column of matrix R. The number of evaluation dimensions in the criteria layer; The verification process requires the construction of a feature matrix. Its matrix elements Satisfy the following expression: ； The compatibility index is calculated using the feature matrix. To perform a consistency check, the expression is as follows: ； If CR is less than the preset value, the consistency check is passed.

6. The multi-dimensional effectiveness evaluation method for vehicle-to-everything (V2X) interactive services according to claim 5, characterized in that, The construction of the fuzzy comprehensive evaluation model includes: Determine the set of factors for evaluating the effectiveness of vehicle-to-everything (V2X) interactive services; Determine the evaluation criteria and set the evaluation criteria. First, establish a fuzzy performance rating system for the vehicle-to-everything (V2X) interactive service, including five levels: Excellent, Good, Average, Poor, and Very Poor. Then, establish a rating set that satisfies the following expression: ； Determine the weights of the evaluation indicators; Establish a fuzzy evaluation matrix and combine the membership degrees of each indicator into matrix C, where rows represent indicators and columns represent evaluation levels.

7. The multi-dimensional effectiveness evaluation method for vehicle-to-everything (V2X) interactive services according to claim 6, characterized in that, The comprehensive evaluation results obtained by the comprehensive evaluation include: Construct a weight calculation matrix and use a weighted average calculation method. Multiply the fuzzy evaluation matrix with the weight calculation matrix to obtain the evaluation score of each indicator.

8. A multi-dimensional performance evaluation system for vehicle-to-everything (V2X) interactive services, characterized in that, include: The user management module is used to import vehicle-to-everything (V2X) interaction evaluation index data from the vehicle-to-everything (V2X) interaction system terminal through the From File module in Simulink. The data query module is used to build a database for vehicle-to-everything (V2X) interactive services, update the data in real time, and query the multi-dimensional performance evaluation results of V2X interactive services. The data analysis module is used to perform preliminary processing on the raw data imported from the From File module, including handling missing and outlier values ​​and normalizing the raw data. The comprehensive evaluation module is used to obtain comprehensive evaluation results through fuzzy hierarchical analysis. It includes constructing a fuzzy judgment matrix, calculating the initial weights of the indicators based on the fuzzy judgment matrix and performing consistency checks, constructing a fuzzy comprehensive evaluation model, and performing fuzzy comprehensive evaluation to obtain comprehensive evaluation results. The evaluation report module is used to generate evaluation reports and evaluations of influencing factors by taking the scores and weights obtained from fuzzy hierarchical analysis as input.

9. A computer system, characterized in that, It includes a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the multi-dimensional effectiveness evaluation method for vehicle-to-everything (V2X) interactive services as described in any one of claims 1-7.

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