Influence assessment method, device and equipment for virtual power plant and storage medium

Abstract

The invention belongs to the field of electric power, and discloses an influence evaluation method, device and equipment for a virtual power plant and a storage medium, and the method comprises the steps: obtaining the electric power data of the virtual power plant in a plurality of influence aspects, inputting the electric power data into a predefined factor value calculation formula corresponding to each influence factor, and obtaining a corresponding factor value through calculation; analyzing the factor value corresponding to each influence factor according to a fuzzy matter element method to obtain an unweighted difference square composite fuzzy matter element matrix; calculating the objective weight of each influence factor according to a CRITIC method to obtain a weight matrix; and calculating an influence value of the virtual power plant according to the difference square composite fuzzy matter element matrix and the weight matrix. Due to the fact that uncertainty and fuzziness in the evaluation process can be effectively processed through the fuzzy matter element method, reasonability and accuracy of the evaluation result are improved; and meanwhile, variability of each factor and correlation among the factors are considered, and calculation accuracy, objectivity and operation complexity are considered.

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] Virtual Power Plant (VPP) is an innovative concept based on information technology and software algorithms. It connects decentralized power sources, energy storage systems, adjustable loads and micro-generation facilities through advanced communication technology and software control systems to form a power system that can be uniformly dispatched and managed. A virtual power plant is not a power plant in the physical sense, but a virtual, networked aggregation of power resources. It can integrate a variety of distributed energy resources (such as solar photovoltaic, wind power generation, energy storage systems, electric vehicles, etc.) to achieve optimal allocation and efficient utilization of resources.

[0003] With the rapid development of distributed renewable energy and the increasing openness of the power market, virtual power plants, as a new type of resource aggregation and coordination optimization, are playing an increasingly important role in power trading. The output of energy integrated by virtual power plants is mostly uncertain and volatile, which also makes it difficult to assess the impact of virtual power plants in power trading.

[0004] In related technologies, many traditional evaluation methods rely on precise mathematical models and deterministic analysis, which cannot effectively deal with the ambiguity and uncertainty when obtaining data, and it is difficult to fully consider the uncertainty and dynamic changes in actual operations. When determining the weights of influencing factors, they often rely on expert experience and subjective judgment, which lacks objectivity and scientificity. Some combined weighting methods involve complex mathematical operations and model construction when conducting evaluations, have high requirements for data, and have cumbersome calculation processes, which are not conducive to practical operations and applications. Summary of the invention

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

[0006] To achieve the above purpose, the present invention discloses the following technical solutions: According to a first aspect of the present invention, a method for evaluating the impact of a virtual power plant is proposed, the method comprising: 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 the corresponding factor value; wherein each influencing aspect includes at least one influencing factor; According to the fuzzy matter-element method, the factor values ​​corresponding to each influencing factor are analyzed to obtain an unweighted difference square composite fuzzy matter-element matrix; The objective weights of each influencing factor are calculated according to the CRITIC method to obtain the weight matrix; 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 influence degree of the virtual power plant on electricity trading.

[0007] According to a second aspect of the present invention, a virtual power plant impact assessment device is provided, the device comprising: An acquisition unit: acquires power data of a virtual power plant in multiple influencing aspects, and inputs 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: 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; The first calculation unit: calculate the objective weight of each influencing factor according to the CRITIC method to obtain the weight matrix; 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.

[0008] According to a third aspect of the present invention, an electronic device is provided, comprising: processor; a memory for storing processor-executable instructions; The processor implements the steps of the method described in the first aspect by running the executable instructions.

[0009] According to a fourth aspect of the present invention, a computer-readable storage medium is provided, on which computer instructions are stored, and when the instructions are executed by a processor, the steps of the method described in the first aspect are implemented.

[0010] 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 result 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 the 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

[0011] Figure 1 It is a flowchart of a method for evaluating the impact of a virtual power plant provided by an exemplary embodiment.

[0012] Figure 2 It is a schematic structural diagram of a device provided by an exemplary embodiment.

[0013] Figure 3 It is a block diagram of an impact assessment device for a virtual power plant provided by an exemplary embodiment. DETAILED DESCRIPTION

[0014] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with one or more embodiments of the present invention. Instead, they are merely examples of devices and methods consistent with some aspects of one or more embodiments of the present invention as detailed in the appended claims.

[0015] 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 steps included in the method may be more or less than those described in the present invention. In addition, a single step described in the present invention may be decomposed 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.

[0016] To further illustrate the present invention, the following examples are provided: With the rapid development of distributed renewable energy and the increasing openness of the power market, virtual power plants, as a new type of resource aggregation and coordination optimization, are playing an increasingly important role in power trading. The output of energy integrated by virtual power plants is mostly uncertain and volatile, which also makes it difficult to assess the impact of virtual power plants in power trading.

[0017] In related technologies, many traditional evaluation methods rely on precise mathematical models and deterministic analysis, which cannot effectively deal with the ambiguity and uncertainty when obtaining data, and it is difficult to fully consider the uncertainty and dynamic changes in actual operations. When determining the weights of influencing factors, they often rely on expert experience and subjective judgment, which lacks objectivity and scientificity. Some combined weighting methods involve complex mathematical operations and model construction when conducting evaluations, have high requirements for data, and have cumbersome calculation processes, which are not conducive to practical operations and applications.

[0018] In order to solve the deficiencies existing in the related art, the present invention proposes an impact assessment method for a virtual power plant.

[0019] Figure 1 FIG. 1 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: Step 102, obtain power data of the virtual power plant in multiple influencing aspects, and input the power data into the predefined factor value calculation formula corresponding to each influencing factor to calculate the corresponding factor value; wherein each influencing aspect includes at least one influencing factor.

[0020] Virtual Power Plant (VPP) is an innovative concept based on information technology and software algorithms. It connects decentralized power sources, energy storage systems, adjustable loads and micro-generation facilities through advanced communication technology and software control systems to form a power system that can be uniformly dispatched and managed. A virtual power plant is not a power plant in the physical sense, but a virtual, networked aggregation of power resources. It can integrate a variety of distributed energy resources (such as solar photovoltaic, wind power generation, energy storage systems, electric vehicles, etc.) to achieve optimal allocation and efficient utilization of resources.

[0021] Specifically, data can be exchanged with the virtual power plant control system, power trading platform and weather station interface through remote RMI, and the data can be exported to the evaluation system. The blockchain distributed system is used to store and transmit data to ensure timely and accurate data acquisition.

[0022] 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.

[0023] In one embodiment, the impact aspects may include: economic impact, environmental impact, and social impact. In this embodiment, each impact aspect may be regarded as various benefits of the virtual power plant in the power trading market, for example, economic impact corresponds to economic benefits. At this time, the evaluation of the impact of the virtual power plant in power trading can be regarded as an evaluation of the benefits of the virtual power plant's participation in power market trading management.

[0024] Economic impact includes four factors: return on investment (ROI), profit margin, cost-effectiveness ratio, and investment return period. The corresponding factor value calculation formula is: ‌Return on investment (ROI)‌: Cumulative income - cumulative cost / cumulative cost × 100%; ‌Profit margin‌: profit / sales × 100%; ‌Cost-effectiveness ratio‌: total benefits / total costs; ‌Investment return period‌: cumulative cost / average annual return.

[0025] The influencing factors of environmental impact are environmental indicators: environmental protection benefits / environmental losses × 100%.

[0026] The factors affecting social impact include employment rate and improvement in quality of life. The corresponding factor value calculation formula is: Employment rate: number of employed people / labor force population × 100%; ‌Level of improvement in quality of life‌: number of beneficiaries / affected population × 100%.

[0027] Step 104: 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.

[0028] Fuzzy matter-element method is a theoretical method based on fuzzy mathematics and matter-element analysis. It is mainly used to deal with the evaluation of things with fuzziness and uncertainty. Matter-element analysis is a method to study the relationship between things and their characteristic values ​​and quantities, and fuzzy matter-element method introduces the theory of fuzzy mathematics into matter-element analysis to solve the uncertainty and fuzziness problems in the evaluation process.

[0029] 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 a fuzzy membership, and calculating the square of the difference between each fuzzy membership and the ideal state through a difference power operation to construct the unweighted difference square composite fuzzy matter-element matrix.

[0030] First, define an evaluation object N, which has a fuzzy value v with respect to the 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 the description or indicator of the evaluation object, and v is the fuzzy value related to the indicator c. In this embodiment, N represents the influencing aspect, c is the influencing factor, and v is the factor value.

[0031] If there are m evaluation objects, each of which 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: ; Among them, v ijIt represents the factor value of the i-th influencing aspect on the j-th influencing factor.

[0032] Convert factor values ​​to 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: For the “bigger is better” type of influencing factors, i.e. positive influencing factors (such as profit margin): ; For the “smaller the better” type of influencing factors, i.e. negative impact factors (such as loss rate): ; 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 jth indicator in all samples of power data, respectively.

[0033] 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 preferred membership fuzzy matter-element, difference-power composite fuzzy matter-element is constructed for comprehensive analysis and evaluation of multiple features or things.

[0034] The difference power composite fuzzy matter-element is constructed by difference power operation, that is, the square of the difference between the fuzzy membership and the ideal state (assuming it is 1) is calculated: ; Then construct the unweighted difference square composite fuzzy matter-element R△, combine the difference square values ​​of all evaluation objects i and all indicators j to form a matrix, which represents the unweighted difference square composite fuzzy matter-element R△: .

[0035] 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 result are improved.

[0036] Step 106, calculating the objective weight of each influencing factor according to the CRITIC method to obtain a weight matrix.

[0037] 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 strength and factor conflict of each influencing factor; wherein the contrast strength is used to characterize the fluctuation of the internal value difference of each influencing factor; taking the product of the contrast strength and the factor conflict 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 according to the information amount to generate an objective weight matrix.

[0038] Calculate the contrast intensity and use the standard deviation to represent 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: ; in, is the first of all samples in the power data The mean of the indicators.

[0039] Calculate the index conflict and calculate the The correlation coefficient of the influencing factor with all other influencing factors , and calculate the conflict accordingly , the formula is as follows: ; 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 jth indicator.

[0040] Calculate the amount of information, the amount of information Reflects the The importance of the influencing factors in the entire evaluation system: ; Calculate the objective weight and determine the objective weight of each influencing factor based on the amount of information : ; in, -1 is the number of remaining influencing factors after removing the correlation with itself, and p is the number of evaluation indicators.

[0041] 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 the factors. In addition, since no human participation is required and no complex mathematical calculations and model construction are involved, the present invention takes into account calculation accuracy, objectivity and operational complexity when calculating the weight.

[0042] Step 108, calculating the impact value of the virtual power plant according to the difference square composite fuzzy matter-element matrix and the weight matrix, wherein the impact value is used to characterize the degree of influence of the virtual power plant on power trading.

[0043] The influence value is the product of the difference square composite fuzzy matter-element matrix and the objective weight matrix.

[0044] In this embodiment, on the one hand, the factor value corresponding to each influencing factor is 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 result 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 the factors. 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.

[0045] In one embodiment, the method further comprises: performing dimensionless processing on the power data. Normalizing the data can eliminate the dimension effect.

[0046] Furthermore, 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 raw value set of indicators; The power data corresponding to the negative impact factors are input into the second range normalization formula, which is expressed as: ; 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.

[0047] Figure 2 is a schematic structural diagram of a device provided by an exemplary embodiment. Figure 2 At 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, and may also include hardware required for other functions. One or more embodiments of the present invention may 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 the software implementation, one or more embodiments of the present invention do not exclude other implementations, such as logic devices or a combination of software and hardware, etc., that is, the execution subject of the following processing flow is not limited to each logic unit, but may also be hardware or logic devices.

[0048] 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: The acquisition unit 302 is used to acquire power data of the virtual power plant in multiple influencing aspects, and input the power data into the predefined factor value calculation formula corresponding to each influencing factor to calculate the corresponding factor value; wherein each influencing aspect includes at least one influencing factor; An analysis unit 304 is used to analyze 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; 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; 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 characterize the impact degree of the virtual power plant on power trading.

[0049] Optionally, the analysis unit 304 is specifically configured to: For each factor value of the virtual power plant, a factor value matrix is ​​generated; 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.

[0050] Optionally, the first calculating unit 306 is specifically configured to: 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; 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 amount of information to generate an objective weight matrix.

[0051] Optionally, the influence value is the product of the difference square composite fuzzy matter-element matrix and the objective weight matrix.

[0052] Optionally, before calculating the factor value, the method further includes: The processing unit 310 is used to perform dimensionless processing on the power data.

[0053] Optionally, the influencing factors include positive influencing factors and negative influencing factors; the processing unit 310 is specifically used to: 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 raw value set of indicators; The power data corresponding to the negative impact factors are input into the second range normalization formula, which is expressed as: .

[0054] Optionally, the impact aspects include: economic impact, environmental impact, and social impact.

[0055] The systems, devices, modules or units described in the above embodiments may be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer, which may be in the form of a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email transceiver, a game console, a tablet computer, a wearable device or a combination of any of these devices.

[0056] In a typical configuration, a computer includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0057] 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.

[0058] Computer-readable media include permanent and non-permanent, removable and non-removable media that can be used to store information by any method or technology. 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 technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, 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 temporary computer-readable media (transitory media), such as modulated data signals and carrier waves.

[0059] With respect to the computer-readable medium (or computer-readable storage medium) as described above or in any other form, computer instructions may be stored thereon, and when the instructions are executed by a processor, one or more of the above-mentioned embodiments are implemented, thereby realizing the technical solution of the present invention.

[0060] The present invention also proposes a computer program, which, when executed by a processor, implements one or more of the above embodiments, thereby realizing the technical solution of the present invention. The computer program may be specifically recorded in the above or any other form of computer-readable medium, and the present invention is not limited thereto.

[0061] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0062] The above describes specific embodiments of the present invention. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0063] The terms used in one or more embodiments of the present invention are only for the purpose of describing specific embodiments, and are not intended to limit one or more embodiments of the present invention. The singular forms of "a", "said" 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 other meanings. 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.

[0064] 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, these information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of one or more embodiments of the present invention, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the 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".

[0065] 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 evaluating the impact of a virtual power plant, characterized in that: The method comprises: 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 the corresponding factor value; wherein each influencing aspect includes at least one influencing factor; According to the fuzzy matter-element method, the factor values ​​corresponding to each influencing factor are analyzed to obtain an unweighted difference square composite fuzzy matter-element matrix; The objective weights of each influencing factor are calculated according to the CRITIC method to obtain the weight matrix; 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 influence degree of the virtual power plant on electricity trading.

2. The method according to claim 1, characterized in that 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: For each factor value of the virtual power plant, a factor value matrix is ​​generated; 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.

3. The method according to claim 1, characterized in that The objective weight of each influencing factor is calculated according to the CRITIC method to obtain a weight matrix, including: 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; 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 amount of information to generate an objective weight matrix.

4. The method according to claim 1, characterized in that: The influence value is the product of the difference square composite fuzzy matter-element matrix and the objective weight matrix.

5. The method according to claim 1, characterized in that: Before calculating the factor value, the method further includes: The power data is dimensionally processed.

6. The method according to claim 5, 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 raw value set of indicators; The power data corresponding to the negative impact factors are input into the second range normalization formula, which is expressed as: 。 7. The method according to claim 1, characterized in that The impact aspects include: economic impact, environmental impact, and social impact.

8. A virtual power plant impact assessment device, characterized in that: The device comprises: An acquisition unit: acquires power data of a virtual power plant in multiple influencing aspects, and inputs 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: 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; The first calculation unit: calculate the objective weight of each influencing factor according to the CRITIC method to obtain the weight matrix; 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.

9. 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 7 by running the executable instructions.

10. 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 7 are implemented.

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