A virtual power plant impact assessment method, device, equipment and storage medium

Abstract

The present invention belongs to the field of electric power, and discloses a method, device, equipment and storage medium for evaluating the impact of a virtual power plant, comprising: obtaining electric power data of a virtual power plant in multiple influencing aspects, and inputting the electric power data into a predefined factor value calculation formula corresponding to each influencing factor to calculate the corresponding factor value; analyzing the factor value corresponding to each influencing factor according to the fuzzy matter-element method to obtain an unweighted difference square composite fuzzy matter-element matrix; calculating the objective weight of each influencing factor according to the CRITIC method to obtain a weight matrix; and calculating the impact value of the virtual power plant according to the difference square composite fuzzy matter-element matrix and the weight matrix. Since the fuzzy matter-element method can effectively handle the uncertainty and ambiguity in the evaluation process, the rationality and accuracy of the evaluation results are improved; at the same time, the variability of each factor and the correlation between factors are considered, and the calculation accuracy, objectivity and operation complexity are taken into account.

Description

Technical Field

[0001] The present invention belongs to the field of electromechanics and relates to an evaluation method, and in particular to an impact evaluation method, device, equipment and storage medium for a virtual power plant. Background Art

[0002] A virtual power plant (VPP) is an innovative concept based on information technology and software algorithms. It connects distributed power sources, energy storage systems, adjustable loads, and micro-generation facilities through advanced communications and software control systems, forming a unified dispatchable and manageable power system. A virtual power plant is not a physical power plant, but rather a virtual, networked aggregation of power resources. It integrates multiple distributed energy resources (such as solar photovoltaics, wind power, energy storage systems, and electric vehicles) to achieve optimal resource allocation and efficient utilization.

[0003] With the rapid development of distributed renewable energy and the increasing openness of the electricity market, virtual power plants (VPPs), as a new form of resource aggregation and coordinated optimization, are playing an increasingly important role in power trading. However, the output of the energy sources integrated by VPPs is often uncertain and volatile, making their impact on power trading difficult to assess.

[0004] Many traditional assessment methods rely on precise mathematical models and deterministic analysis, but they are unable to effectively handle the ambiguity and uncertainty inherent in data collection and fail to fully account for the uncertainties and dynamic changes in actual operations. Determining the weights of influencing factors often relies on expert experience and subjective judgment, lacking objectivity and scientific accuracy. Some combined weighting methods involve complex mathematical calculations and model construction, requiring high data requirements and requiring cumbersome calculations, making them unsuitable for practical operation and application. Summary of the Invention

[0005] In view of this, the present invention discloses a virtual power plant impact assessment method, device, equipment and storage medium, which can solve the deficiencies in the related art.

[0006] To achieve the above purpose, the present invention discloses the following technical solutions:

[0007] According to a first aspect of the present invention, a method for impact assessment of a virtual power plant is proposed, the method comprising:

[0008] Obtaining power data of the virtual power plant in multiple influencing aspects, and inputting the power data into predefined factor value calculation formulas corresponding to respective influencing factors to calculate corresponding factor values; wherein each influencing aspect includes at least one influencing factor;

[0009] According to the fuzzy matter-element method, the factor values corresponding to each influencing factor are analyzed to obtain the unweighted difference square composite fuzzy matter-element matrix;

[0010] The objective weights of each influencing factor are calculated according to the CRITIC method to obtain the weight matrix;

[0011] The influence value of the virtual power plant is calculated according to the difference square composite fuzzy matter-element matrix and the weight matrix, and the influence value is used to characterize the degree of influence of the virtual power plant on electricity trading.

[0012] According to a second aspect of the present invention, a device for evaluating the impact of a virtual power plant is provided, the device comprising:

[0013] An acquisition unit is configured to acquire power data of the virtual power plant in multiple influencing aspects and input the power data into a predefined factor value calculation formula corresponding to each influencing factor to calculate a corresponding factor value; wherein each influencing aspect includes at least one influencing factor;

[0014] Analysis unit: Analyze the factor values corresponding to each influencing factor according to the fuzzy matter-element method to obtain an unweighted difference square composite fuzzy matter-element matrix;

[0015] The first calculation unit: calculate the objective weight of each influencing factor according to the CRITIC method to obtain the weight matrix;

[0016] The second calculation unit calculates the impact value of the virtual power plant according to the difference square composite fuzzy matter-element matrix and the weight matrix, and the impact value is used to characterize the degree of influence of the virtual power plant on electricity trading.

[0017] According to a third aspect of the present invention, an electronic device is provided, comprising:

[0018] processor;

[0019] a memory for storing processor-executable instructions;

[0020] The processor implements the steps of the method described in the first aspect by running the executable instructions.

[0021] According to a fourth aspect of the present invention, a computer-readable storage medium is provided, on which computer instructions are stored. When the instructions are executed by a processor, the steps of the method described in the first aspect are implemented.

[0022] It can be seen from the above technical solutions that the impact assessment method of the virtual power plant disclosed in the present invention, on the one hand, analyzes the factor values corresponding to each influencing factor according to the fuzzy matter-element method. Since the fuzzy matter-element method can effectively deal with the uncertainty and ambiguity in the assessment process, the rationality and accuracy of the assessment results are improved; on the other hand, the objective weight of each influencing factor is calculated by the CRITIC method, while taking into account the variability of each factor and the correlation between factors. Moreover, since no human participation is required and no complex mathematical operations and model construction are involved, the present invention takes into account the calculation accuracy, objectivity and operation complexity when calculating the weight. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 It is a flowchart of a method for evaluating the impact of a virtual power plant provided by an exemplary embodiment.

[0024] Figure 2 It is a schematic structural diagram of a device provided by an exemplary embodiment.

[0025] Figure 3 It is a block diagram of a virtual power plant impact assessment device provided by an exemplary embodiment. DETAILED DESCRIPTION

[0026] Exemplary embodiments will be described in detail herein, with examples illustrated in the accompanying drawings. In the following description, when referring to the drawings, like numbers in different figures represent like or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all possible implementations consistent with one or more embodiments of the present invention. Rather, they are merely examples of apparatuses and methods consistent with certain aspects of one or more embodiments of the present invention, as detailed in the appended claims.

[0027] It should be noted that in other embodiments, the steps of the corresponding method are not necessarily performed in the order shown and described in the present invention. In some other embodiments, the method may include more or fewer steps than those described in the present invention. In addition, a single step described in the present invention may be broken down into multiple steps for description in other embodiments, and multiple steps described in the present invention may be combined into a single step for description in other embodiments.

[0028] To further illustrate the present invention, the following examples are provided:

[0029] With the rapid development of distributed renewable energy and the increasing openness of the electricity market, virtual power plants (VPPs), as a new form of resource aggregation and coordinated optimization, are playing an increasingly important role in power trading. However, the output of the energy sources integrated by VPPs is often uncertain and volatile, making their impact on power trading difficult to assess.

[0030] Many traditional assessment methods rely on precise mathematical models and deterministic analysis, but they are unable to effectively handle the ambiguity and uncertainty inherent in data collection and fail to fully account for the uncertainties and dynamic changes in actual operations. Determining the weights of influencing factors often relies on expert experience and subjective judgment, lacking objectivity and scientific accuracy. Some combined weighting methods involve complex mathematical calculations and model construction, requiring high data requirements and requiring cumbersome calculations, making them unsuitable for practical operation and application.

[0031] In order to address the deficiencies in related technologies, the present invention proposes an impact assessment method for a virtual power plant.

[0032] Figure 1 This is a flowchart of a method for evaluating the impact of a virtual power plant provided by an exemplary embodiment. Figure 1 As shown, the method may include the following steps:

[0033] Step 102, obtain the power data of the virtual power plant in multiple influencing aspects, and input the power data into the factor value calculation formula corresponding to each predefined influencing factor to calculate the corresponding factor value; wherein each influencing aspect includes at least one influencing factor.

[0034] A virtual power plant (VPP) is an innovative concept based on information technology and software algorithms. It connects distributed power sources, energy storage systems, adjustable loads, and micro-generation facilities through advanced communications and software control systems, forming a unified dispatchable and manageable power system. A virtual power plant is not a physical power plant, but rather a virtual, networked aggregation of power resources. It integrates multiple distributed energy resources (such as solar photovoltaics, wind power, energy storage systems, and electric vehicles) to achieve optimal resource allocation and efficient utilization.

[0035] Specifically, data can be exchanged with the virtual power plant control system, power trading platform, and weather station interfaces via remote RMI, and exported to the evaluation system. The blockchain distributed system is used to store and transmit data, ensuring timely and accurate data acquisition.

[0036] Obtaining electricity data can be used to collect historical and real-time data on the power generation, power consumption, energy storage charging and discharging status, electricity market transaction prices, transaction volumes, transaction types, weather conditions, and grid load levels of virtual power plants' distributed photovoltaic, wind power, energy storage systems, and controllable loads.

[0037] In one embodiment, impact aspects may include: economic impact, environmental impact, and social impact. In this embodiment, each impact aspect can be considered as the various benefits of the virtual power plant in the power trading market, for example, economic impact corresponds to economic benefits. In this case, the assessment of the impact of the virtual power plant on power trading can be considered as an assessment of the benefits of the virtual power plant's participation in power market trading management.

[0038] Economic impact includes four factors: return on investment (ROI), profit margin, cost-benefit ratio, and investment payback period. The corresponding factor values are calculated as follows:

[0039] Return on investment (ROI): Cumulative revenue - Cumulative cost / Cumulative cost × 100%;

[0040] Profit margin: profit / sales × 100%;

[0041] Cost-effectiveness ratio: total benefits / total costs;

[0042] ‌Investment return period‌: cumulative cost / average annual return.

[0043] The influencing factors of environmental impact are environmental indicators: environmental protection benefits / environmental losses × 100%.

[0044] The factors influencing social impact include employment rate and improvement in quality of life. The corresponding factor value calculation formula is:

[0045] Employment rate: number of employed people / labor force population × 100%;

[0046] Improvement in quality of life: number of beneficiaries / population affected × 100%.

[0047] Step 104 : Analyze the factor values corresponding to the various influencing factors according to the fuzzy matter-element method to obtain an unweighted difference square composite fuzzy matter-element matrix.

[0048] The fuzzy matter-element method (FEM) is a theoretical approach based on fuzzy mathematics and matter-element analysis. It is primarily used to address the evaluation of objects characterized by fuzziness and uncertainty. Matter-element analysis studies the relationship between objects, their characteristic values, and their magnitudes. The FEM incorporates fuzzy mathematics theory into matter-element analysis to address uncertainty and fuzziness in the evaluation process.

[0049] In one embodiment, the factor values corresponding to each influencing factor are analyzed according to the fuzzy matter-element method to obtain an unweighted difference-square composite fuzzy matter-element matrix, including: generating a factor value matrix for each factor value of the virtual power plant; converting the factor value into fuzzy membership, and calculating the square of the difference between each fuzzy membership and the ideal state through difference power operation to construct the unweighted difference-square composite fuzzy matter-element matrix.

[0050] First, define an evaluation object N, which has a fuzzy value v associated with indicator c. A fuzzy matter-element can be represented as an ordered triple R = (N, c, v), where N is the name of the evaluation object, c is its description or indicator, and v is the fuzzy value associated with indicator c. In this example, N represents the influencing aspect, c is the influencing factor, and v is the factor value.

[0051] If there are m evaluation objects and each evaluation object has n indicators, then the n-dimensional composite fuzzy matter-element R of the m evaluation objects is mn It can be expressed as a matrix R mn , expressed as:

[0052] ;

[0053] Among them, v ij It represents the factor value of the i-th influencing aspect on the j-th influencing factor.

[0054] Convert factor values into fuzzy membership , i.e., optimal membership, is to convert the actual factor value into fuzzy membership. The present invention uses the following type of conversion formula:

[0055] For "bigger is better" influencing factors, that is, positive influencing factors (such as profit margin):

[0056] ;

[0057] For “smaller is better” influencing factors, i.e. negative impact factors (such as loss rate):

[0058] ;

[0059] in, is the fuzzy membership of the i-th influencing aspect on the j-th influencing factor, v ij is the corresponding element value, max(v ij ) and min(v ij ) are the maximum and minimum values of the j-th indicator in all samples of power data, respectively.

[0060] Difference-power composite fuzzy matter-element is a model that combines multiple fuzzy matter-elements through difference-power operation. Based on the constructed standard fuzzy matter-element and the preferred membership fuzzy matter-element, the difference-power composite fuzzy matter-element is constructed to conduct comprehensive analysis and evaluation of multiple features or things.

[0061] The power difference composite fuzzy matter-element is constructed by power difference operation, that is, calculating the square of the difference between the fuzzy membership and the ideal state (assuming it is 1):

[0062] ;

[0063] Then, the unweighted squared difference composite fuzzy matter-element R△ is constructed, and the squared difference values of all evaluation objects i and all indicators j are combined to form a matrix, which represents the unweighted squared difference composite fuzzy matter-element R△:

[0064] .

[0065] In this embodiment, the factor values corresponding to the various influencing factors are analyzed according to the fuzzy matter-element method. Since the fuzzy matter-element method can effectively handle the uncertainty and ambiguity in the evaluation process, the rationality and accuracy of the evaluation results are improved.

[0066] Step 106 : Calculate the objective weight of each influencing factor according to the CRITIC method to obtain a weight matrix.

[0067] In one embodiment, the objective weight of each influencing factor is calculated according to the CRITIC method to obtain a weight matrix, including: respectively calculating the contrast intensity and factor conflict of each influencing factor; wherein the contrast intensity is used to characterize the fluctuation of the internal value difference of each influencing factor; the product of the contrast intensity and the factor conflict is used as the information amount of the influencing factor, and the information amount is used to characterize the importance of the corresponding influencing factor in the impact degree assessment; the objective weight of each influencing factor is calculated according to the information amount to generate an objective weight matrix.

[0068] Calculate the contrast intensity and use the standard deviation to express the fluctuation of the internal value difference of each influencing factor, that is, the contrast intensity. The standard deviation of the indicator , the formula is as follows:

[0069] ;

[0070] in, is the first of all samples in the power data The mean of the indicators.

[0071] Calculate the index conflict, calculate the The correlation coefficient of an influencing factor with all other influencing factors , and calculate the conflict accordingly , the formula is as follows:

[0072] ;

[0073] in, -1 is the number of remaining influencing factors after removing the correlation with itself. is the number of evaluation indicators, Indicates the conflict of the j-th indicator.

[0074] Calculate the amount of information, information volume Reflects the The importance of each influencing factor in the entire evaluation system:

[0075] ;

[0076] Calculate the objective weight and determine the objective weight of each influencing factor based on the amount of information :

[0077] ;

[0078] in, -1 is the number of remaining influencing factors after removing the correlation with itself, and p is the number of evaluation indicators.

[0079] In this embodiment, the objective weight of each influencing factor is calculated by the CRITIC method, while taking into account the variability of each factor and the correlation between factors. Since no human participation is required and no complex mathematical operations and model construction are involved, the present invention takes into account calculation accuracy, objectivity and operational complexity when calculating the weight.

[0080] Step 108: Calculate the impact value of the virtual power plant based on the difference square composite fuzzy matter-element matrix and the weight matrix. The impact value is used to characterize the degree of influence of the virtual power plant on power trading.

[0081] The influence value is the product of the difference square composite fuzzy matter-element matrix and the objective weight matrix.

[0082] In this embodiment, on the one hand, the factor values corresponding to each influencing factor are analyzed according to the fuzzy matter-element method. Since the fuzzy matter-element method can effectively deal with the uncertainty and ambiguity in the evaluation process, the rationality and accuracy of the evaluation results are improved; on the other hand, the objective weight of each influencing factor is calculated by the CRITIC method, while taking into account the variability of each factor and the correlation between factors. Moreover, since no human participation is required and no complex mathematical operations and model construction are involved, the present invention takes into account the calculation accuracy, objectivity and operation complexity when calculating the weight.

[0083] In one embodiment, the method further comprises: performing dimensionless processing on the power data. Normalizing the data can eliminate the dimension effect.

[0084] Furthermore, the influencing factors include positive influencing factors and negative influencing factors; and the dimensionless processing of the power data includes:

[0085] The power data corresponding to the positive influencing factors are input into the first range normalization formula, which is expressed as:

[0086] ;

[0087] in, It is Sample No. The dimensionless value of an indicator is It is Sample No. The original value of the indicator, is the first of all samples in the power data A set of raw values of indicators;

[0088] The power data corresponding to the negative impact factors are input into the second range normalization formula, which is expressed as:

[0089] ;

[0090] In this embodiment, different range normalization formulas are used to distinguish between positive impact factors and negative impact factors, so that the dimensionless processing of power data can be more accurate, thereby improving the accuracy of impact assessment.

[0091] Figure 2 This is a schematic structural diagram of a device provided by an exemplary embodiment. Figure 2At the hardware level, the device includes a processor 202, an internal bus 204, a network interface 206, a memory 208, and a non-volatile memory 210. Of course, it may also include hardware required for other functions. One or more embodiments of the present invention can be implemented based on software, such as the processor 202 reading the corresponding computer program from the non-volatile memory 210 into the memory 208 and then running it. Of course, in addition to software implementation, one or more embodiments of the present invention do not exclude other implementation methods, such as logic devices or a combination of software and hardware. In other words, the execution subject of the following processing flow is not limited to each logic unit, but can also be hardware or logic devices.

[0092] Please refer to Figure 3 , a virtual power plant impact assessment device can be applied to Figure 3 In the device shown, to implement the technical solution of the present invention, the device may include:

[0093] An acquisition unit 302 is configured to acquire power data of the virtual power plant in multiple influencing aspects and input the power data into a predefined factor value calculation formula corresponding to each influencing factor to calculate a corresponding factor value; wherein each influencing aspect includes at least one influencing factor;

[0094] An analyzing unit 304 is configured to analyze the factor values corresponding to each influencing factor according to a fuzzy matter-element method to obtain an unweighted difference square composite fuzzy matter-element matrix;

[0095] The first calculation unit 306 is used to calculate the objective weight of each influencing factor according to the CRITIC method to obtain a weight matrix;

[0096] The second calculation unit 308 is used to calculate the impact value of the virtual power plant according to the difference square composite fuzzy matter-element matrix and the weight matrix, and the impact value is used to represent the degree of influence of the virtual power plant on power trading.

[0097] Optionally, the analyzing unit 304 is specifically configured to:

[0098] For each factor value of the virtual power plant, a factor value matrix is generated;

[0099] The factor values are converted into fuzzy memberships, and the square of the difference between each fuzzy membership and the ideal state is calculated by difference power operation to construct the unweighted difference square composite fuzzy matter-element matrix.

[0100] Optionally, the first calculating unit 306 is specifically configured to:

[0101] Calculate the contrast intensity and factor conflict of each influencing factor respectively; wherein the contrast intensity is used to characterize the fluctuation of the internal value difference of each influencing factor;

[0102] The product of the contrast intensity and the factor conflict is used as the information amount of the influencing factor, and the information amount is used to characterize the importance of the corresponding influencing factor in the impact degree assessment;

[0103] The objective weight of each influencing factor is calculated according to the amount of information to generate an objective weight matrix.

[0104] Optionally, the influence value is the product of the difference square composite fuzzy matter-element matrix and the objective weight matrix.

[0105] Optionally, before calculating the factor value, the method further includes:

[0106] The processing unit 310 is configured to perform dimensionless processing on the power data.

[0107] Optionally, the influencing factors include positive influencing factors and negative influencing factors; the processing unit 310 is specifically configured to:

[0108] The power data corresponding to the positive influencing factors are input into the first range normalization formula, which is expressed as:

[0109] ;

[0110] in, It is Sample No. The dimensionless value of an indicator is It is Sample No. The original value of the indicator, is the first of all samples in the power data A set of raw values of indicators;

[0111] The power data corresponding to the negative impact factors are input into the second range normalization formula, which is expressed as:

[0112] .

[0113] Optionally, the impact aspects include: economic impact, environmental impact, and social impact.

[0114] The systems, devices, modules, or units described in the above embodiments may be implemented by computer chips or entities, or by products having certain functions. A typical implementation device is a computer, which may be in the form of a personal computer, laptop computer, cellular phone, camera phone, smartphone, personal digital assistant, media player, navigation device, email transceiver, game console, tablet computer, wearable device, or any combination of these devices.

[0115] In a typical configuration, a computer includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0116] Memory may include non-permanent storage in a computer-readable medium, in the form of random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

[0117] Computer-readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic disk storage, quantum memory, graphene-based storage media or other magnetic storage devices, or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media such as modulated data signals and carrier waves.

[0118] For the computer-readable medium (or computer-readable storage medium) as described above or in any other form, computer instructions may be stored thereon, which, when executed by a processor, implement one or more of the above-mentioned embodiments, thereby realizing the technical solution of the present invention.

[0119] The present invention further provides a computer program that, when executed by a processor, implements one or more of the aforementioned embodiments, thereby realizing the technical solution of the present invention. The computer program may be recorded on the aforementioned or any other form of computer-readable medium, and the present invention is not limited thereto.

[0120] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0121] The foregoing description describes specific embodiments of the present invention. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in an order different from that described in the embodiments and still achieve the desired results. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the specific order shown or the sequential order to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0122] The terms used in one or more embodiments of the present invention are for the purpose of describing specific embodiments only and are not intended to limit one or more embodiments of the present invention. The singular forms "a", "an", "the" and "the" used in one or more embodiments of the present invention and the appended claims are also intended to include plural forms, unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0123] It should be understood that although the terms first, second, third, etc. may be used to describe various information in one or more embodiments of the present invention, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from each other. For example, without departing from the scope of one or more embodiments of the present invention, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining."

[0124] The above description is merely a preferred embodiment of one or more embodiments of the present invention and is not intended to limit one or more embodiments of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of one or more embodiments of the present invention shall be included in the scope of protection of one or more embodiments of the present invention.

Claims

1. A method for impact assessment of a virtual power plant, characterized in that: The method comprises: Obtaining power data of the virtual power plant in multiple influencing aspects, and inputting the power data into predefined factor value calculation formulas corresponding to respective influencing factors to calculate corresponding factor values; wherein each influencing aspect includes at least one influencing factor; For each factor value of the virtual power plant, a factor value matrix is generated; The factor values are converted into fuzzy membership according to the fuzzy matter-element method, and the square of the difference between each fuzzy membership and the ideal state is calculated by difference power operation to construct an unweighted difference square composite fuzzy matter-element matrix; The contrast intensity and factor conflict of each influencing factor are calculated according to the CRITIC method; wherein the contrast intensity is used to characterize the fluctuation of the internal value difference of each influencing factor; The product of the contrast intensity and the factor conflict is used as the information amount of the influencing factor, and the information amount is used to characterize the importance of the corresponding influencing factor in the impact degree assessment; Calculating the objective weight of each influencing factor based on the amount of information to generate an objective weight matrix; The product of the difference square composite fuzzy matter-element matrix and the objective weight matrix is used as the influence value of the virtual power plant, and the influence value is used to characterize the degree of influence of the virtual power plant on electricity trading.

2. The method according to claim 1, characterized in that Before calculating the factor value, the method further includes: The power data is dimensionally non-dimensionalized.

3. The method according to claim 2, characterized in that The influencing factors include positive influencing factors and negative influencing factors; the dimensionless processing of the power data includes: The power data corresponding to the positive influencing factors are input into the first range normalization formula, which is expressed as: ； in, It is Sample No. The dimensionless value of an indicator is It is Sample No. The original value of the indicator, is the first of all samples in the power data The set of raw values of the indicators; The power data corresponding to the negative impact factors are input into the second range normalization formula, which is expressed as: 。 4. The method according to claim 1, wherein The impact aspects include: economic impact, environmental impact, and social impact.

5. A virtual power plant impact assessment device, characterized in that: The device comprises: An acquisition unit is configured to acquire power data of the virtual power plant in multiple influencing aspects and input the power data into a predefined factor value calculation formula corresponding to each influencing factor to calculate a corresponding factor value; wherein each influencing aspect includes at least one influencing factor; Analysis unit: Generates a factor value matrix for each factor value of the virtual power plant; converts the factor value into fuzzy membership according to the fuzzy matter-element method, and calculates the square of the difference between each fuzzy membership and the ideal state through difference power operation to construct an unweighted difference square composite fuzzy matter-element matrix; The first calculation unit calculates the contrast intensity and factor conflict of each influencing factor according to the CRITIC method; wherein the contrast intensity is used to characterize the fluctuation of the internal value difference of each influencing factor; the product of the contrast intensity and the factor conflict is used as the information content of the influencing factor, and the information content is used to characterize the importance of the corresponding influencing factor in the impact degree assessment; the objective weight of each influencing factor is calculated based on the information content to generate an objective weight matrix; The second calculation unit: takes the product of the difference square composite fuzzy matter-element matrix and the objective weight matrix as the influence value of the virtual power plant, and the influence value is used to characterize the degree of influence of the virtual power plant on electricity trading.

6. An electronic device, characterized in that: include: processor; a memory for storing processor-executable instructions; The processor implements the steps of the method according to any one of claims 1 to 4 by running the executable instructions.

7. A computer-readable storage medium having computer instructions stored thereon, characterized in that: When the instruction is executed by a processor, the steps of the method according to any one of claims 1 to 4 are implemented.

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