Power grid two-stage dynamic correction data asset pricing method, medium and system

Abstract

The invention relates to the technical field of power grid management, is used for solving the problems that power grid data asset pricing is inaccurate and effective operation and management of power grid enterprise data assets are difficult to promote, and particularly relates to a power grid two-stage dynamic correction data asset pricing method, medium and system. According to the method, the market stage is determined based on the market permeability and the product life cycle theory, different pricing methods are adopted, market changes can be accurately adapted, pricing better fits the actual value of data assets, all links of the total cost and various value influence factors are comprehensively considered in the cost correction method, and the cost correction accuracy is improved. Risk coefficients are realized in combination with scientific and quantitative data values, it is ensured that pricing fully reflects real values and potential risks of assets, accurate pricing helps enterprises optimize decisions and reasonably plan related strategies of data assets, competitiveness of the enterprises in the market can be enhanced, healthy, orderly and efficient development of the power grid data asset market is promoted, and economic benefits are increased. And the resource configuration efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid management, and in particular to a power grid dual-stage dynamic correction data asset pricing method, medium and system. Background Art

[0002] In today's digital age, power grid companies have accumulated massive amounts of data resources during their operations. These power grid data assets contain huge potential value. However, accurate evaluation and pricing of power grid data assets face many challenges. On the one hand, power grid data assets are highly complex and diverse. On the other hand, the dynamic changes in the market environment have also put forward higher requirements for the pricing of power grid data assets. In this context, there is an urgent need for a pricing method that can adapt to market dynamics and accurately reflect the value of power grid data assets.

[0003] At present, although there are some pricing methods in the field of data asset evaluation, these methods have certain limitations for power grid data assets. For example, some methods may not fully consider the cost structure characteristics of power grid data assets, including high cost investment and risk factors in the process of data collection, processing and storage; or in the application of market method, there is a lack of effective comparable case selection and adjustment mechanism for the characteristics of power grid data assets, resulting in inaccurate pricing. Therefore, in order to achieve reasonable pricing of power grid data assets, fully tap their economic value, and promote the effective operation and management of power grid enterprise data assets, a solution is proposed. Summary of the invention

[0004] The purpose of the present invention is to provide a two-stage dynamic correction data asset pricing method, medium and system for power grids to solve the technical defects mentioned above. By determining the market stage based on market penetration rate and product life cycle theory, and adopting different pricing methods respectively, it can accurately adapt to market changes and make pricing more in line with the actual value of data assets. The revised cost method comprehensively considers all aspects of the total cost and various value influencing factors, combines the scientific quantification of data value to achieve the risk coefficient, and ensures that the pricing fully reflects the true value and potential risks of the assets. Accurate pricing helps enterprises optimize decision-making, reasonably plan data asset-related strategies, and enhance their competitiveness in the market, promote the healthy, orderly and efficient development of the power grid data asset market, and improve resource allocation efficiency.

[0005] The purpose of the present invention can be achieved by the following technical solution: A two-stage dynamic correction data asset pricing method for a power grid comprises the following steps:

[0006] Step S1: Obtain the user's target data assets, take the target data assets as data asset products, analyze the market penetration rate and product life cycle theory of data asset products, analyze the market stage of data asset products based on the market penetration rate and product life cycle theory, and conduct pricing reliability evaluation feedback analysis on the market stage to obtain reliable instructions or regulatory instructions;

[0007] Step S2: Based on the premise of reliable instructions and the modified cost method, the total cost TC, reasonable profit margin R, applicable tax rate T and data value correction coefficient K of the data asset product are integrated to obtain the cost price Pc;

[0008] Step S3: If the data asset product is in the early stage of market development, then the value Pm1 of the evaluated data asset product in the early stage of market development is obtained based on the pricing Pi of each data asset product and the correction coefficient λi of the pre-acquired comparative asset product; if the data asset product is in the middle or late stage of market development, then the value Pm2 of the evaluated data asset product in the middle or late stage of market development is obtained;

[0009] Step S4: Perform data comparison based on the value Pm1 of the evaluated data asset products in the early stage of market development, the value Pm2 of the evaluated data asset products in the middle and late stages of market development, and the cost price Pc to obtain the pricing standards for data asset products in the early stage of market development or in the middle and late stages of market development, and conduct actual deviation verification and analysis on the pricing standards to obtain expected instructions or control instructions.

[0010] Preferably, the market stage analysis process of the data asset product is as follows:

[0011] Obtain the total number of potential users in the target market and the actual number of users currently using the data asset product, and set the ratio between the total number of potential users in the target market and the actual number of users currently using the data asset product as the market penetration rate;

[0012] At the same time, we also obtain the product life cycle theory of data asset products, which represents the length of time from the moment a data asset product enters the market to the moment it is eliminated and exits the market.

[0013] Determine the stage of data asset products based on market penetration and product life cycle theory, where the stages of data asset products include introduction, growth, maturity and decline;

[0014] If the data asset product is in the introduction stage or the growth stage, then the data asset product is judged to be in the early stage of market development; if the data asset product is in the maturity stage or the decline stage, then the data asset product is judged to be in the middle and late stage of market development.

[0015] Preferably, the pricing reliability evaluation feedback analysis process is as follows:

[0016] The total number of historical pricing times of the data asset products in the early and middle and late stages of market development is obtained, and the number of pricing deviations in the total number of historical pricing times is obtained. The number of pricing deviations indicates the number of times that the difference between the pricing benefit and the preset pricing benefit is greater than the preset threshold. The ratio between the number of pricing deviations in the total number of historical pricing times and the total number of historical pricing times is set as the pricing reliability evaluation coefficient, and the pricing reliability evaluation coefficient is discriminated and processed to obtain reliable instructions or control instructions.

[0017] Preferably, the analysis process of the cost price Pc is as follows:

[0018] Obtain the total cost TC, reasonable profit margin R, applicable tax rate T and data value correction coefficient K of the data asset product, and substitute them into the formula Pc=TC×(1-R)×(1+T)×K to calculate the cost price Pc of the data asset product, where TC is the total cost, R is the reasonable profit margin, T is the applicable tax rate, and K is the data value correction coefficient;

[0019] The process of obtaining the total cost TC is as follows: The total cost of a data asset product represents the sum of the costs incurred in data collection, preprocessing, product development, statistical analysis, marketing, and risk control in the process of forming a data asset product.

[0020] Preferably, the analysis process of the value Pm1 of the data asset product being evaluated is as follows:

[0021] The calculation formula for the value of the data asset product being evaluated, Pm1, is as follows: Where Pi represents the pricing of the i-th data asset product, λi represents the correction coefficient of the comparative asset product, n is a natural number greater than 3, and n represents the total number of data asset products;

[0022] The calculation formula of λi is as follows: Among them, λi is the correction coefficient of the i-th comparative asset product (i≥3), kj is the weight value of the data asset product indicator to be evaluated (j≤m), tj is the weight value of the comparative data asset product indicator (j≤m), j represents the j-th indicator of the data asset product to be evaluated, and m is the number of indicators.

[0023] Preferably, the analysis process of the value Pm2 of the data asset product being evaluated is as follows:

[0024] According to the formula The value Pm2 of the evaluated data asset product is calculated, where Pm2 is the value of the evaluated data asset product, c is the number of data sets into which the evaluated data asset product is decomposed, v is the serial number of the data sets into which the evaluated data asset product is decomposed, Qv is the value of the preset reference data set, and Xev represents the preset total correction coefficient of each decomposed data set.

[0025] Preferably, the pricing standard analysis process is as follows:

[0026] If the data asset product is in the early stage of market development: the ratio between the value Pm1 and the cost price Pc is set as the initial pricing evaluation coefficient, and the initial pricing evaluation coefficient is discriminated: if the initial pricing evaluation coefficient is less than the preset initial pricing evaluation coefficient threshold, the cost price Pc is determined as the pricing standard; if the initial pricing evaluation coefficient is greater than or equal to the preset initial pricing evaluation coefficient threshold, the market price is determined as the pricing standard;

[0027] If the data asset product is in the middle and late stages of market development: the ratio between the value Pm2 and the cost price Pc is set as the middle and late stage pricing evaluation coefficient, and the middle and late stage pricing evaluation coefficient is discriminated: if the middle and late stage pricing evaluation coefficient is less than the preset middle and late stage pricing evaluation coefficient threshold, the cost price Pc is determined as the pricing standard; if the middle and late stage pricing evaluation coefficient is greater than or equal to the preset middle and late stage pricing evaluation coefficient threshold, the market price is determined as the pricing standard;

[0028] The actual deviation verification and analysis process is as follows:

[0029] Set a monitoring period, obtain the pricing returns corresponding to the pricing standards in the early stage of market development or the middle and late stages of market development of the data asset products within the monitoring period, construct a pricing return characteristic curve with a time series, and draw a preset pricing return characteristic curve on the pricing return characteristic curve to obtain the area formed by the line segment of the pricing return characteristic curve below the preset pricing return characteristic curve and the X-axis, and set the area formed by the line segment of the pricing return characteristic curve below the preset pricing return characteristic curve and the X-axis as the expected deviation evaluation value, perform discrimination processing on the expected deviation evaluation value, and obtain expected instructions or control instructions.

[0030] Preferably, a computer-readable storage medium stores computer program instructions, and when the computer program instructions are executed by a processor, the power grid two-stage dynamic correction data asset pricing method is implemented.

[0031] Preferably, a two-stage dynamically revised data asset pricing system for a power grid comprises a processor and a storage medium; the processor is used to execute a computer program stored in the storage medium to implement the two-stage dynamically revised data asset pricing method for a power grid.

[0032] The beneficial effects of the present invention are as follows:

[0033] (1) The present invention determines the market stage based on market penetration and product life cycle theory, and simultaneously performs pricing reliability evaluation feedback analysis on the pricing scheme of data asset products to improve the pricing reliability of data asset products in the early stage of market development or in the middle and late stages of market development;

[0034] (2) The present invention adopts different pricing methods respectively, which can accurately adapt to market changes, make pricing more in line with the actual value of data assets, comprehensively consider all aspects of total cost and various value influencing factors in the revised cost method, and combine scientifically quantified data value to achieve risk coefficients to ensure that pricing fully reflects the true value and potential risks of assets. Accurate pricing helps enterprises optimize decision-making, rationally plan data asset-related strategies, and enhance their competitiveness in the market, promote the healthy, orderly and efficient development of the power grid data asset market, and improve resource allocation efficiency;

[0035] (3) Evaluate pricing standards from the perspective of actual returns to understand whether the actual pricing returns corresponding to the current pricing standards are in line with expectations, so as to make targeted adjustments to improve the rationality of pricing of data asset products. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] The present invention will be further described below in conjunction with the accompanying drawings;

[0037] Figure 1 It is an analysis diagram of the method of the present invention. DETAILED DESCRIPTION

[0038] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0039] Embodiment 1:

[0040] See also Figure 1 As shown, the present invention is a two-stage dynamic correction data asset pricing method for power grid, comprising the following steps:

[0041] Step S1: Obtain the user's target data assets, take the target data assets as data asset products, analyze the market penetration rate and product life cycle theory of data asset products, analyze the market stage of data asset products based on the market penetration rate and product life cycle theory, and conduct pricing reliability evaluation feedback analysis on the market stage to obtain reliable instructions or regulatory instructions;

[0042] Step S2: Based on the premise of reliable instructions and the modified cost method, the total cost TC, reasonable profit margin R, applicable tax rate T and data value correction coefficient K of the data asset product are integrated to obtain the cost price Pc;

[0043] Step S3: If the data asset product is in the early stage of market development, then the value Pm1 of the evaluated data asset product in the early stage of market development is obtained based on the pricing Pi of each data asset product and the correction coefficient λi of the pre-acquired comparative asset product; if the data asset product is in the middle or late stage of market development, then the value Pm2 of the evaluated data asset product in the middle or late stage of market development is obtained;

[0044] Step S4: Perform data comparison based on the value Pm1 of the evaluated data asset products in the early stage of market development, the value Pm2 of the evaluated data asset products in the middle and late stages of market development, and the cost price Pc to obtain the pricing standards for data asset products in the early stage of market development or in the middle and late stages of market development, and conduct actual deviation verification and analysis on the pricing standards to obtain expected instructions or control instructions.

[0045] In the embodiment of the present invention, the market stage of the data asset product is analyzed based on the market penetration rate and product life cycle theory. The specific market stage analysis process of the data asset product is as follows:

[0046] Obtain the total number of potential users in the target market and the actual number of users currently using the data asset product, and set the ratio between the total number of potential users in the target market and the actual number of users currently using the data asset product as the market penetration rate;

[0047] At the same time, we also obtain the product life cycle theory of data asset products, which represents the length of time from the moment a data asset product enters the market to the moment it is eliminated and exits the market.

[0048] Determine the stage of data asset products based on market penetration and product life cycle theory, where the stages of data asset products include introduction, growth, maturity and decline;

[0049] If the data asset product is in the introduction stage or growth stage, it is judged that the data asset product is in the early stage of market development;

[0050] If the data asset product is in the maturity or decline stage, it is judged that the data asset product is in the middle and late stages of market development.

[0051] Conduct pricing reliability evaluation feedback analysis at the market stage to improve the pricing reliability of data asset products in the early stage of market development or in the middle and late stages of market development. The specific pricing reliability evaluation feedback analysis process is as follows:

[0052] The total number of historical pricing of data asset products in the early stage of market development and the middle and late stages of market development is obtained, and the number of pricing deviations in the total number of historical pricing is obtained. The number of pricing deviations indicates the number of times the difference between the pricing benefit and the preset pricing benefit is greater than the preset threshold. The ratio between the number of pricing deviations in the total number of historical pricing and the total number of historical pricing is set as the pricing reliability evaluation coefficient, and the pricing reliability evaluation coefficient is discriminated:

[0053] If the pricing reliability evaluation coefficient is less than the preset pricing reliability evaluation coefficient threshold, a reliable instruction is generated;

[0054] If the pricing reliability evaluation coefficient is greater than or equal to the preset pricing reliability evaluation coefficient threshold, a control instruction is generated. When the control instruction is generated, the preset warning operation corresponding to the control instruction is immediately performed to control the pricing plan of the data asset product, so as to improve the pricing reliability and accuracy of the pricing plan of the data asset product;

[0055] In the embodiment of the present invention, the pricing return represents the sum of the returns of the data asset product in the corresponding periods in the early stage of market development and the middle and late stages of market development.

[0056] Embodiment 2:

[0057] Step S2: Based on the premise of reliable instructions and the modified cost method, the total cost TC, reasonable profit margin R, applicable tax rate T and data value correction coefficient K of the data asset product are integrated to obtain the cost price Pc;

[0058] The analysis process of cost price Pc is as follows:

[0059] Obtain the total cost TC, reasonable profit margin R, applicable tax rate T and data value correction coefficient K of the data asset product, and substitute them into the formula Pc=TC×(1-R)×(1+T)×K to calculate the cost price Pc of the data asset product, where TC is the total cost, R is the reasonable profit margin, T is the applicable tax rate, and K is the data value correction coefficient;

[0060] It should be understood that the cost price Pc refers to the price (including tax) calculated based on the modified cost price method; therefore, when calculating the total cost of data assets, the tax rate, the profit margin of data products required by the enterprise, and various factors affecting the value of data should be considered; among which, the profit margin is determined based on the benchmark rate of return required by the power grid enterprise for related businesses;

[0061] The specific total cost TC acquisition process is as follows:

[0062] The total cost of data asset products refers to the sum of the costs incurred in data collection, preprocessing, product development, statistical analysis, marketing and risk control in the process of forming data asset products;

[0063] The cost of data collection is: the sum of the workload required to obtain basic data using automated tools or manual means and the product of the unit price of relevant personnel + the product of the workload of developing automated tools and the unit price of R&D personnel + the product of the workload of implementing data collection and the unit price of implementing personnel;

[0064] Cost of data preprocessing: the sum of the workload required to convert basic data into the format required for mining and the product of the unit price of relevant personnel + the product of the workload of basic data conversion tool R&D and the unit price of R&D personnel + the product of preprocessing implementation workload and the unit price of centralized procurement personnel;

[0065] The cost of data product development: the sum of the workload required to search for hidden information from a large amount of data and the product of the unit price of the relevant personnel, which specifically includes the product of the product design workload and the unit price of the designer + the product design tool development workload and the unit price of the R&D personnel + the data mining implementation workload and the unit price of the centralized procurement personnel;

[0066] Cost of data statistical analysis: The sum of the workload required to analyze, summarize, understand and extract useful information from the collected data and the product of the unit price of relevant personnel + the product of the workload of data statistical analysis tool research and development personnel unit price + the product of the workload of statistical analysis implementation and the unit price of centralized procurement personnel;

[0067] The cost of data marketing: the sum of the workload required to create, communicate, disseminate and exchange products to bring economic value and the product of the unit price of relevant personnel, among which, specifically, the product of the workload of marketing strategy formulation and the unit price of consulting personnel + the product of the workload of marketing strategy implementation and the unit price of implementation personnel;

[0068] Cost of risk control: The cost of risk control and risk warning for data products through data modeling is composed of the sum of the workload required and the unit price of relevant personnel + the product of the workload of risk control modeling and the unit price of consulting personnel + the workload of risk control strategy formulation and the unit price of consulting personnel + the workload of risk control strategy implementation and the unit price of implementation personnel;

[0069] The specific analysis process of reasonable profit rate R, applicable tax rate T and data value correction coefficient K is as follows:

[0070] Among them, the reasonable profit rate R and applicable tax rate T indicate that the data product provider can set the profit rate to participate in the calculation if it has profit rate requirements, and the applicable tax rate T (mainly value-added tax) is calculated in accordance with the regulations of the tax department of the project location;

[0071] The specific calculation of data value correction coefficient K is as follows:

[0072] The data value correction coefficient K is calculated according to the formula K = αβ(1+L)(1-r), where α is the data quality coefficient; β is the data circulation coefficient; L is the data scarcity coefficient; r is the data value realization risk coefficient. The calculation of the data value correction coefficient is as follows:

[0073] The data quality coefficient represents the average percentage of the test data that passes each core module. The core module includes the data module, test dimension, test standard and test result. The test includes completeness, accuracy and validity.

[0074] Data circulation coefficient = (open data propagation coefficient × open data volume + public data propagation coefficient × public data volume + shared data propagation coefficient × shared data volume) / total data volume, where the propagation coefficient refers to the number of accesses to the data in the network, reflecting the degree of data circulation. If it is non-shared data, the value is generally 1;

[0075] The data scarcity coefficient represents the value obtained by dividing the system data volume by the total data volume related to the data assets, which is used to reflect the scarcity of data;

[0076] The data value realization risk coefficient is calculated by summarizing the scores and weights filled in the questionnaire. It describes the various risks that may exist in realizing data utility from the perspective of data users.

[0077] Embodiment three:

[0078] Step S3: If the data asset product is in the early stage of market development, the value Pm1 of the evaluated data asset product in the early stage of market development is obtained based on the pricing P i of each data asset product and the correction coefficient λi of the pre-acquired comparative asset product. The specific analysis process of the value Pm1 of the evaluated data asset product is as follows:

[0079] The calculation formula for the value of the data asset product being evaluated, Pm1, is as follows: Where Pm1 is the value of the data asset product being evaluated, Pi represents the pricing of the ith data asset product being compared, λi represents the correction coefficient of each compared asset product, and n is a natural number greater than 3, which represents the total number of data asset products.

[0080] Comparative data asset product index correction uses the market method to capture data asset products in the trading market and establish a comparison library for data asset products of the same type; select suitable comparable data asset products, the number of selected data asset products n should be no less than 3, use the same type of transaction data asset product comparison method to select comparable data asset products, and calculate the weight of each indicator of the evaluated data asset product. The indicators of the selected data asset products need to be consistent with those of the evaluated asset products. After the indicator weights of the comparable data asset products are obtained, the evaluated data asset products need to be corrected; the λi calculation formula is as follows: Wherein, λi is the correction coefficient of the i-th comparative asset product (i≥3), kj is the weight value of the data asset product indicator to be evaluated (j≤m), tj is the weight value of the comparative data asset product indicator (j≤m), j represents the j-th indicator of the data asset product to be evaluated, and m is the number of indicators;

[0081] If the data asset product is in the middle or late stage of market development, the value Pm2 of the evaluated data asset product in the middle or late stage of market development is obtained. The specific analysis process of the value Pm2 of the evaluated data asset product is as follows:

[0082] According to the formula Calculate the value Pm2 of the data asset product being evaluated, where Pm2 is the value of the data asset product being evaluated, c is the number of data sets into which the data asset product being evaluated is decomposed, v is the serial number of the data sets into which the data asset product being evaluated is decomposed, Qv is the value of the preset reference data set, Xev represents the preset total correction coefficient of each decomposed data set, Xev = Xv1 × Xv2 × Xv3 × Xv4 × Xv5, Xv1 is the preset technical correction coefficient, Xv2 is the period correction coefficient, the period correction coefficient = the price index on the evaluation base date / the price index on the trading day of the comparable case, Xv3 is the capacity correction coefficient, the capacity correction coefficient = the capacity of the evaluation object / the capacity of the comparable case, Xv4 is the preset value density correction coefficient, and Xv5 is the preset other correction coefficient;

[0083] It should be noted that when the value density of the evaluation object and the comparable case is the same or similar, generally only the impact of data capacity on asset value needs to be considered; when the value density of the evaluation object and the comparable case is significantly different, in addition to considering data capacity, the impact of value density on asset value also needs to be considered;

[0084] It should be noted that the preset value density correction coefficient Xv4 mainly considers the difference in data asset value caused by the different proportions of effective data in the total data. The value density is measured by the value of unit data. The logic of the value density correction coefficient is: the larger the proportion of effective data (referring to the part of the total data that contributes to the overall value) in the total data volume, the higher the total value of the data asset. If a data asset can be further divided into multiple sub-data assets, each sub-data asset may have a different value density, then the overall value density should take into account the value density of each sub-data asset.

[0085] Embodiment 4:

[0086] Step S4: Based on the value Pm1 of the evaluated data asset product in the early stage of market development, the value Pm2 of the evaluated data asset product in the middle and late stages of market development, and the cost price Pc, data comparison processing is performed to obtain the pricing standard of the data asset product in the early stage of market development or the middle and late stages of market development, and the actual deviation verification and analysis of the pricing standard is performed to obtain the expected instructions or control instructions. The specific pricing standard analysis process is as follows:

[0087] If the data asset product is in the early stages of market development:

[0088] The ratio between the value Pm1 and the cost price Pc is set as the initial pricing evaluation coefficient, and the initial pricing evaluation coefficient is discriminated:

[0089] If the initial pricing evaluation coefficient is less than the preset initial pricing evaluation coefficient threshold, the cost price Pc is determined as the pricing standard;

[0090] If the initial pricing evaluation coefficient is greater than or equal to the preset initial pricing evaluation coefficient threshold, the market price is determined to be the pricing standard;

[0091] If the data asset product is in the middle or late stage of market development:

[0092] The ratio between the value Pm2 and the cost price Pc is set as the mid- to late-stage pricing evaluation coefficient, and the mid- to late-stage pricing evaluation coefficient is discriminated:

[0093] If the mid- to late-stage pricing evaluation coefficient is less than the preset mid- to late-stage pricing evaluation coefficient threshold, the cost price Pc is determined as the pricing standard;

[0094] If the mid- to late-stage pricing evaluation coefficient is greater than or equal to the preset mid- to late-stage pricing evaluation coefficient threshold, the market price is determined to be the pricing standard;

[0095] The actual deviation verification and analysis process is as follows:

[0096] Set a monitoring period, obtain the pricing income of the corresponding pricing standard in the early stage of market development or the middle and late stage of market development of the data asset product in the monitoring period, construct a pricing income characteristic curve with time series, and draw a preset pricing income characteristic curve on the pricing income characteristic curve, obtain the area of ​​the region formed by the line segment of the pricing income characteristic curve below the preset pricing income characteristic curve and the X-axis, and set the area of ​​the region formed by the line segment of the pricing income characteristic curve below the preset pricing income characteristic curve and the X-axis as the expected deviation evaluation value, and perform discrimination processing on the expected deviation evaluation value:

[0097] If the corresponding actual pricing profit is greater than or equal to the preset corresponding actual pricing profit threshold, an expected instruction is generated;

[0098] If the corresponding actual pricing profit is less than the preset corresponding actual pricing profit threshold, a control instruction is generated, and the preset warning operation corresponding to the expected instruction or the control instruction is immediately made to control the current pricing standard and improve the pricing rationality of data asset products.

[0099] In the embodiment of the present invention, the pricing standard is evaluated from the perspective of actual benefits to understand whether the actual pricing benefits corresponding to the current pricing standard meet expectations, so as to make targeted adjustments; the larger the value of the expected deviation evaluation value, the smaller the risk that the actual pricing benefits corresponding to the current pricing standard meet expectations;

[0100] A computer-readable storage medium having computer program instructions stored thereon, wherein the computer program instructions, when executed by a processor, implement the power grid two-stage dynamic correction data asset pricing method.

[0101] A power grid two-stage dynamic correction data asset pricing system comprises a processor and a storage medium; the processor is used to execute a computer program stored in the storage medium to implement the power grid two-stage dynamic correction data asset pricing method.

[0102] It should be noted that if the data asset product is in the early stage of market development or in the middle and late stages of market development, when the ratio exceeds the threshold, it means that the influence of market supply and demand factors has caused the actual transaction price of the data asset product in the market to be far higher than the cost price, that is, the pricing of data asset products is mainly determined by market supply and demand, so the market price can be selected as the price of the data asset product; when the ratio does not exceed the threshold, it means that the supply and demand relationship in the market is not very strong, which is not enough to support the economic law of supply being less than demand and price rising, so it is recommended to adopt the cost method, which is more reasonable, which can not only guarantee a certain profit, but also promote market occupation;

[0103] To summarize, by determining the market stage based on market penetration and product life cycle theory, and conducting pricing reliability evaluation and feedback analysis on the pricing scheme of data asset products, the pricing reliability of data asset products in the early stage of market development or in the middle and late stages of market development can be improved. Different pricing methods can accurately adapt to market changes and make pricing more in line with the actual value of data assets. The revised cost method comprehensively considers all aspects of the total cost and various value influencing factors, and combines the scientifically quantified data value to achieve the risk coefficient to ensure that pricing fully reflects the true value and potential risks of assets. Accurate pricing helps companies optimize decision-making, reasonably plan data asset-related strategies, and enhance their competitiveness in the market, promote the healthy, orderly and efficient development of the power grid data asset market, and improve resource allocation efficiency. At the same time, the pricing standards are evaluated from the perspective of actual benefits to understand whether the current pricing standards correspond to actual pricing benefits in line with expectations, so as to make targeted adjustments to improve the pricing rationality of data asset products.

[0104] The threshold is set to facilitate comparison. The size of the threshold depends on the amount of sample data and the number of bases set by technicians in this field for each group of sample data; as long as it does not affect the proportional relationship between the parameter and the quantized value.

[0105] The above formulas are obtained by collecting a large amount of data for software simulation and selecting a formula that is close to the actual value. The coefficients in the formula are set by technical personnel in this field according to actual conditions. The above is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited to this. Any technical personnel familiar with the technical field within the technical scope disclosed by the present invention, according to the technical solution and the inventive concept of the present invention, make equivalent replacement or change, which should be covered within the protection scope of the present invention.

Claims

1. A two-stage dynamic correction data asset pricing method for power grid, characterized in that: The following steps are involved: Step S1: Obtain the user's target data assets, take the target data assets as data asset products, analyze the market penetration rate and product life cycle theory of data asset products, analyze the market stage of data asset products based on the market penetration rate and product life cycle theory, and conduct pricing reliability evaluation feedback analysis on the market stage to obtain reliable instructions or regulatory instructions; Step S2: Based on the premise of reliable instructions and the modified cost method, the total cost TC, reasonable profit margin R, applicable tax rate T and data value correction coefficient K of the data asset product are integrated to obtain the cost price Pc; Step S3: If the data asset product is in the early stage of market development, then the value Pm1 of the evaluated data asset product in the early stage of market development is obtained based on the pricing Pi of each data asset product and the correction coefficient λi of the pre-acquired comparative asset product; if the data asset product is in the middle or late stage of market development, then the value Pm2 of the evaluated data asset product in the middle or late stage of market development is obtained; Step S4: Perform data comparison based on the value Pm1 of the evaluated data asset products in the early stage of market development, the value Pm2 of the evaluated data asset products in the middle and late stages of market development, and the cost price Pc to obtain the pricing standards for data asset products in the early stage of market development or in the middle and late stages of market development, and conduct actual deviation verification and analysis on the pricing standards to obtain expected instructions or control instructions.

2. A two-stage dynamic correction data asset pricing method for power grid according to claim 1, characterized in that: The market stage analysis process of the data asset product is as follows: Obtain the total number of potential users in the target market and the actual number of users currently using the data asset product, and set the ratio between the total number of potential users in the target market and the actual number of users currently using the data asset product as the market penetration rate; At the same time, we also obtain the product life cycle theory of data asset products, which represents the length of time from the moment a data asset product enters the market to the moment it is eliminated and exits the market. Determine the stage of data asset products based on market penetration and product life cycle theory, where the stages of data asset products include introduction, growth, maturity and decline; If the data asset product is in the introduction stage or the growth stage, then the data asset product is judged to be in the early stage of market development; if the data asset product is in the maturity stage or the decline stage, then the data asset product is judged to be in the middle and late stage of market development.

3. A two-stage dynamic correction data asset pricing method for power grid according to claim 2, characterized in that: The pricing reliability evaluation feedback analysis process is as follows: The total number of historical pricing times of the data asset products in the early and middle and late stages of market development is obtained, and the number of pricing deviations in the total number of historical pricing times is obtained. The number of pricing deviations indicates the number of times that the difference between the pricing benefit and the preset pricing benefit is greater than the preset threshold. The ratio between the number of pricing deviations in the total number of historical pricing times and the total number of historical pricing times is set as the pricing reliability evaluation coefficient, and the pricing reliability evaluation coefficient is discriminated and processed to obtain reliable instructions or control instructions.

4. A two-stage dynamic correction data asset pricing method for power grid according to claim 1, characterized in that: The analysis process of the cost price Pc is as follows: Obtain the total cost TC, reasonable profit margin R, applicable tax rate T and data value correction coefficient K of the data asset product, and substitute them into the formula Pc=TC×(1-R)×(1+T)×K to calculate the cost price Pc of the data asset product, where TC is the total cost, R is the reasonable profit margin, T is the applicable tax rate, and K is the data value correction coefficient; The process of obtaining the total cost TC is as follows: The total cost of a data asset product represents the sum of the costs incurred in data collection, preprocessing, product development, statistical analysis, marketing, and risk control in the process of forming a data asset product.

5. A two-stage dynamic correction data asset pricing method for power grid according to claim 1, characterized in that: The analysis process of the value Pm1 of the data asset product being evaluated is as follows: The calculation formula for the value of the data asset product being evaluated, Pm1, is as follows: Where Pi represents the pricing of the i-th data asset product, λi represents the correction coefficient of the comparative asset product, n is a natural number greater than 3, and n represents the total number of data asset products; The calculation formula of λi is as follows: Among them, λi is the correction coefficient of the i-th comparative asset product (i≥3), kj is the weight value of the data asset product indicator to be evaluated (j≤m), tj is the weight value of the comparative data asset product indicator (j≤m), j represents the j-th indicator of the data asset product to be evaluated, and m is the number of indicators.

6. A two-stage dynamic correction data asset pricing method for power grid according to claim 1, characterized in that: The analysis process of the value Pm2 of the data asset product being evaluated is as follows: According to the formula The value Pm2 of the evaluated data asset product is calculated, where Pm2 is the value of the evaluated data asset product, c is the number of data sets into which the evaluated data asset product is decomposed, v is the serial number of the data sets into which the evaluated data asset product is decomposed, Qv is the value of the preset reference data set, and Xev is the preset total correction coefficient of each decomposed data set.

7. A two-stage dynamic correction data asset pricing method for power grid according to claim 1, characterized in that: The pricing standard analysis process is as follows: If the data asset product is in the early stage of market development: the ratio between the value Pm1 and the cost price Pc is set as the initial pricing evaluation coefficient, and the initial pricing evaluation coefficient is discriminated: if the initial pricing evaluation coefficient is less than the preset initial pricing evaluation coefficient threshold, the cost price Pc is determined as the pricing standard; if the initial pricing evaluation coefficient is greater than or equal to the preset initial pricing evaluation coefficient threshold, the market price is determined as the pricing standard; If the data asset product is in the middle and late stages of market development: the ratio between the value Pm2 and the cost price Pc is set as the middle and late stage pricing evaluation coefficient, and the middle and late stage pricing evaluation coefficient is discriminated: if the middle and late stage pricing evaluation coefficient is less than the preset middle and late stage pricing evaluation coefficient threshold, the cost price Pc is determined as the pricing standard; if the middle and late stage pricing evaluation coefficient is greater than or equal to the preset middle and late stage pricing evaluation coefficient threshold, the market price is determined as the pricing standard; The actual deviation verification and analysis process is as follows: Set a monitoring period, obtain the pricing returns corresponding to the pricing standards in the early stage of market development or the middle and late stages of market development of the data asset products within the monitoring period, construct a pricing return characteristic curve with a time series, and draw a preset pricing return characteristic curve on the pricing return characteristic curve to obtain the area formed by the line segment of the pricing return characteristic curve below the preset pricing return characteristic curve and the X-axis, and set the area formed by the line segment of the pricing return characteristic curve below the preset pricing return characteristic curve and the X-axis as the expected deviation evaluation value, perform discrimination processing on the expected deviation evaluation value, and obtain expected instructions or control instructions.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer program instructions, which, when executed by a processor, implement the power grid two-stage dynamic correction data asset pricing method according to any one of claims 1 to 7.

9. A two-stage dynamic correction data asset pricing system for power grid, characterized in that: comprising a processor and a storage medium, wherein the storage medium is the storage medium according to claim 8; The processor is used to execute the computer program stored in the storage medium to implement a two-stage dynamic correction data asset pricing method for a power grid as described in any one of claims 1-7.

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