Power consumption bill-based power sale package evaluation method and system, terminal and medium

Abstract

The invention relates to the field of power supply, in particular to a power sale package evaluation method and system based on a power consumption bill, a terminal and a medium, and the method comprises the steps: obtaining a power consumption enterprise electric charge bill, and extracting target data from the electric charge bill; acquiring power consumption transaction parameters from a power transaction platform; according to the target data and the electricity consumption transaction parameters, generating a current-month enterprise electricity consumption cost estimation value through an enterprise electricity consumption cost estimation model; a package pricing strategy is set, and a package price estimation value is generated through a package price estimation model according to the package parameters and the real-time electric quantity of the power utilization enterprise in the corresponding time period; according to the current-month enterprise electricity taking cost estimation value and the package price estimation value, the expected income and the risk boundary are obtained, and according to the expected income and the risk boundary, the rationality of the package pricing strategy is evaluated. According to the method, the traceable and quantitative estimation model is established based on the electricity consumption bill, accurate estimation of the electricity taking cost of the electricity selling company and reasonable estimation of the package price are achieved, and the accuracy of estimation of the electricity taking cost and the package price is improved.

Description

Technical Field

[0001] This application relates to the field of power supply, and particularly to a method, system, terminal and medium for evaluating electricity sales packages based on electricity bills. Background Art

[0002] As an important participant in power transactions, the profitability of electricity sales companies depends to a large extent on their mastery of power purchase costs and the formulation of pricing strategies. At present, most electricity sales companies rely on empirical judgment or static models when formulating package prices, lacking in-depth analysis of the actual electricity bill structures of electricity-consuming enterprises, resulting in blind pricing strategies, unclear profit margins, and even risks such as inverted quotes. On the other hand, enterprise electricity bills, as a direct reflection of electricity consumption behavior and electricity price structures, contain a large amount of data resources that can be used for analysis and prediction. However, existing technologies have not fully utilized such data for cost back-calculation and pricing simulation, lacking a systematic set of algorithms and tools to support electricity sales companies in conducting reverse calculations and package optimizations from the perspective of enterprises. Therefore, there is an urgent need to provide a systematic method that combines enterprise electricity bill data, power market rules, and power purchase price models to achieve accurate estimation of the electricity-taking costs of electricity sales companies and reasonable prediction of package prices, thereby enhancing their market competitiveness and profitability. Summary of the Invention

[0003] To solve the above problems, the present invention provides a method, system, terminal and medium for evaluating electricity sales packages based on electricity bills, which establish a traceable and quantifiable estimation model based on electricity bills to achieve accurate estimation of the electricity-taking costs of electricity sales companies and reasonable prediction of package prices, and improve the accuracy of estimating electricity-taking costs and package prices.

[0004] In a first aspect, the technical solution of the present invention provides a method for evaluating electricity sales packages based on electricity bills, including the following steps: Obtain the electricity bill of the electricity-consuming enterprise, with the electricity bill in monthly units, and extract target data from the electricity bill; Obtain electricity trading parameters from the power trading platform; Generate an estimated value of the enterprise's electricity-taking cost for the current month through the enterprise's electricity-taking cost estimation model according to the target data and electricity trading parameters; Set the package pricing strategy, and generate an estimated package price value through the package price prediction model according to the package parameters and the real-time electricity consumption of the electricity-consuming enterprise during the corresponding period; Obtain the expected revenue and risk boundaries through the estimated value of the enterprise's electricity-taking cost for the current month and the estimated package price value, and evaluate the rationality of the package pricing strategy according to the expected revenue and risk boundaries.

[0005] In an alternative embodiment, the target data extracted from the electricity bill includes electricity time, enterprise voltage level, and electricity consumption in each time period; the electricity time includes year and month, and the electricity consumption in each time period includes electricity consumption in peak hours, peak periods, normal periods, valley periods, and deep valley periods.

[0006] In an alternative embodiment, the electricity trading parameters obtained from the power trading platform include time period division and trading electricity prices for each hour of each day for each electricity price type.

[0007] In an alternative embodiment, according to the target data and the electricity trading parameters, an estimated value of the enterprise's electricity acquisition cost for the current month is generated through an enterprise electricity acquisition cost estimation model, specifically including: Configuring measurement conditions, including electricity price type and time-of-use ratio , spot ratio , fixed superposition price , trading price , government authorization ratio , medium- and long-term trading ratio , enterprise floating price ; Calculating the real-time electricity quantity and medium- and long-term electricity quantity for the th day and the th hour of the current month according to the target data and medium- and long-term electricity quantity ; Extracting the trading electricity price for the th day and the th hour of the current month from the electricity trading parameters according to the electricity time and the electricity price type in the measurement conditions ; Calculating the medium- and long-term trading electricity price according to the trading price , government authorization ratio , medium- and long-term trading ratio ; Calculating the estimated value of the enterprise's electricity acquisition cost for the th day through the following formula ; ,

[0008] Calculating the estimated value of the enterprise's electricity acquisition cost for the current month through the following formula,

[0009] wherein, is the total number of days in the current month, is the total electricity consumption of the electricity-consuming enterprise in the current month, which is obtained by summing up the electricity consumption in each time period in the electricity bill.

[0010] In an alternative embodiment, calculating the Tian Di Real-time electricity consumption for hours and medium- and long-term electricity consumption , specifically including: Calculate the proportion of electricity consumption in each time period in the electricity bill through the following formula ,

[0011] Among them, is the electricity consumption in the time period, is the total electricity consumption of the electricity-consuming enterprise in the current month; Obtain the number of days included in the peak period, peak period, normal period, valley period, and deep valley period in the current month from the electricity trading parameters according to the electricity bill time and the enterprise voltage level ; Calculate the time-of-use electricity consumption weight through the following formula ,

[0012] According to the time period division obtained from the power trading platform, divide the time-of-use electricity consumption weight into the electricity consumption weight for each hour , where represents the electricity consumption weight for the Calculate the real-time electricity consumption for the Tian Di hour in the current month through the following formula ,

[0013] Among them, is the total number of days in the current month; Calculate the medium- and long-term electricity consumption for the Tian Di hour in the current month through the following formula ,

[0014] Among them, is the time-of-use ratio for the hour in the decomposition curve.

[0015] In an optional implementation manner, set a package pricing strategy, and generate an estimated package price according to the package parameters and the real-time electricity consumption of the electricity-consuming enterprise in the corresponding time period, specifically including: Divide the time period according to the time period mapping rule and set the price for each time period to generate the current package; Calculate the estimated package price through the following formula ,

[0016] Among them, is the trading electricity price for the th day and the th hour of the current package.

[0017] In an alternative embodiment, after obtaining the electricity bill of the electricity-consuming enterprise, the following steps are further included: Verify the integrity and legality of the electricity bill of the electricity-consuming enterprise; If the verification passes, store the electricity bill of the electricity-consuming enterprise in the database; If the verification fails, discard the electricity bill of the electricity-consuming enterprise.

[0018] In a second aspect, the technical solution of the present invention provides a power sales package evaluation system based on electricity bills, including: An electricity bill acquisition module, configured to acquire the electricity bill of the electricity-consuming enterprise, where the electricity bill is in units of months, and extract target data from the electricity bill; An electricity trading parameter acquisition module, configured to acquire electricity trading parameters from the power trading platform; An enterprise electricity acquisition cost estimation module, configured to generate an estimated value of the enterprise electricity acquisition cost for the current month through an enterprise electricity acquisition cost estimation model according to the target data and the electricity trading parameters; A package price estimation module, configured to set a package pricing strategy, and generate an estimated value of the package price through a package price prediction model according to the package parameters and the real-time electricity consumption of the electricity-consuming enterprise during the corresponding period; A package evaluation module, configured to obtain the expected revenue and risk boundary through the estimated value of the enterprise electricity acquisition cost for the current month and the estimated value of the package price, and evaluate the rationality of the package pricing strategy according to the expected revenue and risk boundary.

[0019] In a third aspect, the technical solution of the present invention provides a terminal, including: A memory, configured to store a power sales package evaluation program based on electricity bills; A processor, configured to implement the steps of the power sales package evaluation method based on electricity bills as described in any one of the above when executing the power sales package evaluation program based on electricity bills.

[0020] In a fourth aspect, the technical solution of the present invention provides a computer-readable storage medium, on which a power sales package evaluation program based on electricity bills is stored, and when the power sales package evaluation program based on electricity bills is executed by a processor, the steps of the power sales package evaluation method as described in any one of the above are implemented.

[0021] As can be seen from the above technical solutions, the present application has the following advantages: extracting target data from the electricity bills of electricity-consuming enterprises, obtaining electricity trading parameters, and then generating the estimated value of the electricity acquisition cost of the enterprise in the current month through the enterprise electricity acquisition cost estimation model. At the same time, according to the package pricing strategy, etc., generating the estimated value of the package price through the package price estimation model, and then obtaining the expected revenue and risk boundary based on the estimated value of the enterprise electricity acquisition cost in the current month and the estimated value of the package price, and evaluating the rationality of the package pricing strategy according to the expected revenue and risk boundary. By obtaining the electricity bills of electricity-consuming enterprises and extracting target data, combining with the electricity trading parameters obtained from the power trading platform, and using the enterprise electricity acquisition cost estimation model to generate the estimated value of the enterprise electricity acquisition cost in the current month, the present invention changes the previous way of electricity sales companies relying on empirical judgment or static models. By analyzing the actual electricity bill structure of electricity-consuming enterprises, it can more accurately grasp the electricity acquisition cost and improve the accuracy of cost estimation. In addition, after setting the package pricing strategy, according to the package parameters and the real-time electricity consumption of the electricity-consuming enterprise in the corresponding period, generating the estimated value of the package price through the package price estimation model, considering dynamic factors such as real-time electricity consumption, compared with the traditional quotation method lacking systematic algorithms and tools, the package price estimation can be made more reasonable and accurate. Then, based on the estimated value of the enterprise electricity acquisition cost in the current month and the estimated value of the package price, obtaining the expected revenue and risk boundary, and then evaluating the rationality of the package pricing strategy, providing a quantitative basis for the electricity sales company to formulate a reasonable package pricing strategy, and helping the electricity sales company to optimize the pricing strategy. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions of the present application, the drawings required for description will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0023] Figure 1 It is a schematic flowchart of a method for evaluating electricity sales packages based on electricity bills provided by an embodiment of the present invention.

[0024] Figure 2 It is a schematic block diagram of the structure of a system for evaluating electricity sales packages based on electricity bills provided by an embodiment of the present invention.

[0025] Figure 3 It is a schematic diagram of the structure of a terminal provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0026] To make the application purpose, features, and advantages of this application more obvious and understandable, specific embodiments and accompanying drawings will be used below to clearly and completely describe the technical solutions protected by this application. Obviously, the embodiments described below are only a part of the embodiments of this application, rather than all embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of this application.

[0027] Unless otherwise defined, all technical and scientific terms used in this application have the same meaning as commonly understood by those of ordinary skill in the technical field to which this invention belongs. The terms used in the description of this invention in this application are only for the purpose of describing specific embodiments and are not intended to limit this invention.

[0028] Figure 1 It is a schematic flowchart of a method for evaluating electricity sales packages based on electricity bills provided by an embodiment of the present invention. Among them, Figure 1 The execution subject can be a system for evaluating electricity sales packages based on electricity bills. The method for evaluating electricity sales packages provided by the embodiments of the present invention is executed by a computer device. Correspondingly, the system for evaluating electricity sales packages based on electricity bills runs in the computer device. According to different requirements, the order of the steps in this flowchart can be changed, and some can be omitted.

[0029] As Figure 1 shown, the method includes the following steps.

[0030] S1. Obtain the electricity bill of the electricity-consuming enterprise. The electricity bill is in units of months, and extract target data from the electricity bill.

[0031] In this step, the electricity bill of the electricity-consuming enterprise is obtained monthly, and core data such as electricity bill time (year / month), enterprise voltage level, and electricity consumption in each period (peak / peak / flat / valley / deep valley) are extracted from it. By structurally extracting the electricity bill data, an electricity consumption behavior file of the electricity-consuming enterprise is established, providing a real and specific data source for subsequent cost estimation and package pricing.

[0032] S2. Obtain electricity trading parameters from the power trading platform.

[0033] Obtain parameters such as period division rules (such as the period type of each hour) and time-of-use trading electricity prices of each electricity price type (including "day-ahead" type and "real-time" type) from the power trading platform. Directly associate with the real-time trading data in the power market to ensure that cost estimation and package pricing comply with current market rules and price fluctuations.

[0034] S3. Generate the estimated value of the enterprise's electricity acquisition cost for the current month through the enterprise's electricity acquisition cost estimation model according to the target data and electricity trading parameters.

[0035] Based on the target data and transaction parameters, this step comprehensively calculates parameters such as time-of-use ratio, spot ratio, and government authorization ratio through the enterprise's electricity procurement cost estimation model to generate the estimated value of the electricity procurement cost for the current month. Compared with the limitations of traditional empirical judgment or static models, this step quantifies each cost component element (such as medium- and long-term trading electricity prices, spot price fluctuations) through a mathematical model to achieve traceable and quantifiable estimation of the electricity procurement cost.

[0036] S4. Set the package pricing strategy. According to the package parameters and the real-time electricity consumption of the electricity-consuming enterprise during the corresponding period, generate the estimated value of the package price through the package price prediction model.

[0037] This step sets the package pricing strategy, including time-of-use pricing. Combining the package parameters and the user's real-time electricity consumption, calculate the package price through the package price prediction model. This step is based on the user's real-time electricity consumption data and market trading electricity prices to estimate the package price and improve the accuracy of the package price estimation.

[0038] S5. Obtain the expected revenue and risk boundary through the estimated value of the enterprise's electricity procurement cost for the current month and the estimated value of the package price, and evaluate the rationality of the package pricing strategy according to the expected revenue and risk boundary.

[0039] This step compares the electricity procurement cost with the package price, calculates the expected revenue and risk boundary, and evaluates whether the pricing strategy is reasonable, realizing data-driven instead of experience-driven. Through the quantitative analysis of the expected revenue and risk boundary, clarify the profit space and risk threshold of different pricing strategies, and provide an accurate basis for the electricity sales company.

[0040] Furthermore, as a refinement and extension of the specific implementation manner of the above embodiment, in order to fully illustrate the specific implementation process in this embodiment, another electricity sales package evaluation method based on electricity bills is provided. The implementation of this method is developed using a front-end and back-end separation architecture. The back-end is built based on the SpringBoot framework, and the front-end uses the Vue framework to implement the interaction interface. This method includes the following steps.

[0041] The first step is to estimate the electricity procurement cost of the electricity sales company.

[0042] S101. Collect and preprocess electricity bill data.

[0043] Obtain the electricity bill of the electricity-consuming enterprise, verify the integrity and legality of the electricity bill of the electricity-consuming enterprise. If the verification passes, store the electricity bill of the electricity-consuming enterprise in the database. If the verification fails, discard the electricity bill of the electricity-consuming enterprise.

[0044] Specifically, use the RESTful interface provided by Spring Boot to receive the electricity bill PDF uploaded by the enterprise, supporting formats such as Excel and CSV. The backend validates the integrity and legality of the bill fields through a data validation tool (such as Hibernate Validator) and stores them in the relational database MySQL.

[0045] S102. Obtain electricity trading parameters from the power trading platform.

[0046] In some alternative embodiments, the electricity trading parameters include time period division and the trading electricity price for each hour of each day for each electricity price type.

[0047] It should be noted that the time periods include peak, high peak, flat, valley, and deep valley periods. Obtain the specific time period division from the power trading platform, that is, the time period type for each hour of each day of a certain month. The electricity price types include day-ahead type and real-time type.

[0048] Specifically, use the Spring Boot scheduling component or the timed task module to regularly pull the disclosure data from the power trading platform.

[0049] S103. Estimate the electricity cost of the enterprise.

[0050] Specifically, extract the target data from the electricity bill, and then generate the estimated value of the enterprise's electricity cost for the current month through the enterprise's electricity cost estimation model based on the target data and the electricity trading parameters. In some alternative embodiments, the target data includes electricity bill time, enterprise voltage level, and electricity consumption in each time period; among them, the electricity bill time includes year and month, and the electricity consumption in each time period includes electricity consumption in peak, high peak, flat, valley, and deep valley periods.

[0051] Before measurement, configure the measurement conditions, including electricity price type, time-of-use ratio 、spot ratio 、fixed superimposed price 、transaction price 、government authorized ratio 、medium- and long-term trading ratio 、enterprise floating price . It should be noted that the transaction price is the transaction price in the electricity bill of the electricity-consuming enterprise, that is, the transaction price of the electricity-consuming enterprise when the electricity bill is generated. The subsequent transaction electricity price is the corresponding transaction electricity price obtained from the data disclosed by the power trading platform.

[0052] S1031. Calculate the real-time electricity quantity for the th day and the th hour of the current month based on the target data .

[0053] Calculate the proportion of power consumption in each time period in the electricity bill by the following formula ,

[0054] where is the power consumption in the time period, and

[0055] is the total power consumption of the electricity-consuming enterprise in the current month.

[0056] It should be noted that the electricity trading parameters initially obtained from the power trading platform include data for multiple years and months, as well as different voltage levels. According to the data of the electricity-consuming enterprise to be evaluated currently, obtain the number of days included in the peak time period, peak time period, normal time period, valley time period, and deep valley time period in the current month from the electricity trading parameters .

[0057] Calculate the time-of-use power consumption weight by the following formula ,

[0058] It should be noted that the time-of-use power consumption weight represents the average proportion of a certain type of time period in the electricity bill of the electricity-consuming enterprise on a daily basis in a month.

[0059] According to the time period division obtained from the power trading platform, divide the time-of-use power consumption weight into the power consumption weight for each hour , where represents the power consumption weight for the

[0060] hour. The monthly electricity bill is decomposed according to the above weights on each day to obtain the 24-hour time-of-use power consumption for each day. Assume that a certain month has days, and the daily serial number is , then calculate the real-time power consumption for the hour on the day of the current month by the following formula .

[0061] S1032, calculate the medium- and long-term power consumption for the hour on the day of the current month according to the target data

[0062] Decompose the monthly electricity bill according to the common decomposition curve of the centralized bidding transactions of the State Grid to calculate the medium- and long-term electricity consumption, where represents the time-of-use ratio at the th hour.

[0063] Specifically, the medium- and long-term electricity consumption at the th day and the th hour of the current month is calculated through the following formula ,

[0064] where is the time-of-use ratio at the th hour in the decomposition curve.

[0065] S1033: Extract the trading electricity price at the th day and the th hour of the current month from the electricity trading parameters according to the electricity bill time and the electricity price type in the measurement conditions .

[0066] S1034: Calculate the medium- and long-term trading electricity price based on the trading price , the government authorized ratio , and the medium- and long-term trading ratio .

[0067]

[0068] where the day serial number is , represents the th hour.

[0069] S1035: Calculate the estimated value of the enterprise's electricity acquisition cost for the th day through the following formula ,

[0070] S1036: Calculate the estimated value of the enterprise's electricity acquisition cost for the current month through the following formula

[0071] represents the electricity consumption cost of the enterprise on the th day is the enterprise floating price is the estimated value of the overall electricity purchase cost corresponding to the electricity bill within the measurement period reflecting the comprehensive electricity consumption cost of the enterprise within the selected time range.

[0072] Step 2, Estimation of package price.

[0073] First, set the package pricing strategy, and then generate the package price estimation value through the package price prediction model according to the package parameters and the real-time power consumption of the electricity-consuming enterprise during the corresponding period.

[0074] S201, Divide the time periods according to the time period mapping rules and set the prices for each time period to generate the current package.

[0075] According to the standard electricity price packages issued by the State Grid, the electricity sales company can customize the package plan on this basis, but the following constraint rules need to be followed.

[0076] (1) Time period mapping rules.

[0077] The time period division customized by the electricity sales company is only allowed to be set as three time periods: "peak", "flat", and "valley", but mapping adjustments need to be made based on the original time period division of the State Grid package. Specifically, the original "super peak" time period can only be divided into "peak", the original "deep valley" time period can only be divided into "valley", the original "flat section" time period can be divided into "peak", "flat", or "valley", the original "valley section" time period can be divided into "flat" or "valley", and the original "peak section" time period can be divided into "peak" or "flat".

[0078] (2) Price constraint rules.

[0079] In the customized package, the "peak" electricity price must not be lower than 1.5 times the "flat" electricity price of the same package, the "valley" electricity price must not be higher than 0.5 times the "flat" electricity price, and the weighted average electricity price of the whole month's package should be equal to the "flat section" electricity price.

[0080] According to the above rules, the electricity sales company can formulate a package, which includes the time period division and the prices of peak , flat , valley . Based on the time period division and the set prices, the trading electricity price for the rd day and the th hour of the current package can be determined .

[0081] S202, Calculate the package price estimation value through the following formula ,

[0082] where, is the trading electricity price for the th day and the th hour of the current package.

[0083] Step 3, Evaluation of the rationality of the package pricing strategy.

[0084] Obtain the expected revenue and risk boundary through the estimated value of the enterprise's electricity cost and the estimated value of the package price in the current month, and evaluate the rationality of the package pricing strategy based on the expected revenue and risk boundary.

[0085] Expected revenue = (Estimated value of package price - Estimated value of enterprise's electricity cost) * Total electricity consumption in the current month.

[0086] The risk boundary means that the estimated package price should be between the estimated value of the enterprise's electricity cost and the state grid's proxy purchase price, that is, the electricity purchase price of the electricity-consuming enterprise from the power sales company should be cheaper than the electricity purchase price from the state grid, and the power sales enterprise should have revenue.

[0087] In some alternative embodiments, the backend generates several package pricing strategies, calculates their respective expected revenues and risk boundaries, and transmits the results to the frontend in JSON format. The frontend is implemented based on Vue + ECharts for chart display and interactive control, supporting the switching of different package conditions and dynamic simulation. Furthermore, the backend can classify customer portraits according to electricity consumption characteristics, output the optimal package combination in combination with the cost and quotation model, and provide corresponding pricing suggestion reports, supporting the export of PDF reports or direct display through the frontend.

[0088] The frontend uses Vue + ElementUI to build the user interface, providing function modules such as data upload, report viewing, package comparison, and customer management. The front and backend achieve asynchronous data interaction through Axios to ensure timely system response. The entire system deployment can adopt the Springboot + Vue architecture, with strong scalability, suitable for internal system integration of small and medium-sized power sales companies or external services in the SaaS mode.

[0089] In the above text, an embodiment of a method for evaluating a power sales package based on electricity bills is described in detail. Based on the method for evaluating a power sales package based on electricity bills described in the above embodiment, an embodiment of the present invention also provides a power sales package evaluation system corresponding to this method.

[0090] Figure 2 It is a schematic block diagram of the structure of a power sales package evaluation system based on electricity bills provided by an embodiment of the present invention. In this embodiment, the power sales package evaluation system 200 based on electricity bills can be divided into multiple function modules according to the functions it performs. The module referred to in the present invention means a series of computer program segments that can be executed by at least one processor and can complete fixed functions, and are stored in the memory.

[0091] The electricity bill acquisition module 210 is used to acquire the electricity bills of electricity-consuming enterprises. The electricity bills are in units of months, and target data is extracted from the electricity bills.

[0092] The electricity consumption transaction parameter acquisition module 220 is used to acquire electricity consumption transaction parameters from the power trading platform.

[0093] The enterprise electricity acquisition cost estimation module 230 is used to generate the estimated value of the enterprise electricity acquisition cost for the current month through the enterprise electricity acquisition cost estimation model according to the target data and the electricity consumption transaction parameters.

[0094] The package price estimation module 240 is used to set the package pricing strategy, and generate the estimated value of the package price through the package price prediction model according to the package parameters and the real-time electricity consumption of the electricity-consuming enterprise during the corresponding period.

[0095] The package evaluation module 250 is used to obtain the expected revenue and risk boundary through the estimated value of the enterprise electricity acquisition cost for the current month and the estimated value of the package price, and evaluate the rationality of the package pricing strategy according to the expected revenue and risk boundary.

[0096] The electricity sales package evaluation system based on the electricity bill in this embodiment is used to implement the aforementioned electricity sales package evaluation method based on the electricity bill. Therefore, the specific implementation in this system can be seen in the embodiment part of the electricity sales package evaluation method based on the electricity bill in the previous text. Therefore, its specific implementation can refer to the descriptions of the corresponding various part embodiments, and will not be elaborated here.

[0097] In addition, since the electricity sales package evaluation system based on the electricity bill in this embodiment is used to implement the aforementioned electricity sales package evaluation method based on the electricity bill, its function corresponds to the function of the above method, and will not be elaborated here.

[0098] Figure 3 The following is a schematic structural diagram of a terminal 300 provided by an embodiment of the present invention, including: a processor 310, a memory 320, and a communication unit 330. When the processor 310 is used to implement the electricity sales package evaluation program stored in the memory 320, the following steps are implemented: Obtain the electricity bill of the electricity-consuming enterprise, with the electricity bill in units of months, and extract the target data from the electricity bill; Obtain the electricity consumption transaction parameters from the power trading platform; Generate the estimated value of the enterprise electricity acquisition cost for the current month through the enterprise electricity acquisition cost estimation model according to the target data and the electricity consumption transaction parameters; Set the package pricing strategy, and generate the estimated value of the package price through the package price prediction model according to the package parameters and the real-time electricity consumption of the electricity-consuming enterprise during the corresponding period; Obtain the expected revenue and risk boundary through the estimated value of the enterprise electricity acquisition cost for the current month and the estimated value of the package price, and evaluate the rationality of the package pricing strategy according to the expected revenue and risk boundary.

[0099] The terminal 300 includes a processor 310, a memory 320, and a communication unit 330. These components communicate via one or more buses. Those skilled in the art can understand that the structure of the server shown in the figure does not limit the present invention. It can be a bus structure, a star structure, and can also include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements.

[0100] Among them, the memory 320 can be used to store the execution instructions of the processor 310. The memory 320 can be implemented by any type of volatile or non-volatile storage terminal or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk, or optical disc. When the execution instructions in the memory 320 are executed by the processor 310, the terminal 300 is enabled to execute some or all of the steps in the above method embodiments.

[0101] The processor 310 is the control center of the storage terminal, connecting various parts of the entire electronic terminal through various interfaces and lines. By running or executing software programs and / or modules stored in the memory 320, and by invoking the data stored in the memory, it executes various functions of the electronic terminal and / or processes data. The processor can be composed of an integrated circuit (IC). For example, it can be composed of a single packaged IC, or can be composed of multiple packaged ICs with the same or different functions connected together. For example, the processor 310 can include only a central processing unit (CPU). In the embodiment of the present invention, the CPU can be a single arithmetic core or can include multiple arithmetic cores.

[0102] The communication unit 330 is used to establish a communication channel so that the storage terminal can communicate with other terminals. It receives user data sent by other terminals or sends user data to other terminals.

[0103] The present invention also provides a computer storage medium. The storage medium here can be a magnetic disk, an optical disc, a read-only memory (ROM), a random access memory (RAM), etc.

[0104] The present invention also provides a computer storage medium, which may be a magnetic disk, an optical disk, a read-only memory (ROM), a random access memory (RAM), or the like.

[0105] The computer storage medium stores an electricity sales package evaluation program based on electricity bills. When the electricity sales package evaluation program based on electricity bills is executed by a processor, the following steps are implemented: Obtain the electricity bill of the electricity-consuming enterprise. The electricity bill is in units of months, and extract target data from the electricity bill; Obtain electricity trading parameters from the power trading platform; Generate an estimated value of the enterprise's electricity acquisition cost for the current month through an enterprise electricity acquisition cost estimation model according to the target data and the electricity trading parameters; Set a package pricing strategy, and generate an estimated package price through a package price prediction model according to the package parameters and the real-time electricity consumption of the electricity-consuming enterprise during the corresponding period; Obtain the expected revenue and risk boundary through the estimated value of the enterprise's electricity acquisition cost for the current month and the estimated package price, and evaluate the rationality of the package pricing strategy according to the expected revenue and risk boundary.

[0106] Those skilled in the art can clearly understand that the technology in the embodiments of the present invention can be implemented by means of software plus a necessary general hardware platform. Based on such an understanding, the technical solutions in the embodiments of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product is stored in a storage medium such as a USB flash drive, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk, or an optical disk, etc., which can store program codes. The computer software product includes several instructions to enable a computer terminal (which may be a personal computer, a server, or a second terminal, a network terminal, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention.

[0107] In several embodiments provided by the present invention, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are only illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed mutual coupling or direct coupling or communication connection may be through some interfaces. The indirect coupling or communication connection of the device or unit may be in an electrical, mechanical, or other form.

[0108] The unit described as a separation component may or may not be physically separated. The component shown as a unit may or may not be a physical unit, that is, it may be located in one place or may be distributed over multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0109] In addition, each functional unit in various embodiments of the present invention may be integrated in a processing unit, may exist separately as individual physical units, or two or more units may be integrated in one unit.

[0110] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present invention. Various modifications to these embodiments will be obvious to those skilled in the art, and the general principles defined in this application can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to these embodiments shown in this application, but will conform to the widest scope consistent with the principles and novel features disclosed in this application.

Claims

1. A method for evaluating electricity sales packages based on electricity bills, characterized in that It includes the following steps: Obtain the electricity bill of the electricity-consuming enterprise. The electricity bill is monthly, and extract the target data from the electricity bill; Obtain the electricity trading parameters from the power trading platform; Generate the estimated value of the enterprise's electricity acquisition cost for the current month through the enterprise's electricity acquisition cost estimation model based on the target data and the electricity trading parameters; Set the package pricing strategy, and generate the estimated package price through the package price prediction model according to the package parameters and the real-time electricity consumption of the electricity-consuming enterprise during the corresponding period; Obtain the expected revenue and risk boundary through the estimated value of the enterprise's electricity acquisition cost for the current month and the estimated package price, and evaluate the rationality of the package pricing strategy according to the expected revenue and risk boundary.

2. The electricity sales package evaluation method based on electricity bills according to claim 1, characterized in that The target data extracted from the electricity bill includes the electricity bill time, the enterprise voltage level, and the electricity consumption in each period; Among them, the electricity bill time includes the year and month, and the electricity consumption in each period includes the electricity consumption during the peak period, the peak period, the normal period, the valley period, and the deep valley period.

3. The method for evaluating power sales packages based on electricity bills according to claim 2, characterized in that, The electricity trading parameters obtained from the power trading platform include the period division and the trading electricity price per hour per day for each electricity price type.

4. The method for evaluating electricity sales packages based on electricity bills according to claim 3, characterized in that, Generate the estimated value of the enterprise's electricity acquisition cost for the current month through the enterprise's electricity acquisition cost estimation model based on the target data and the electricity trading parameters, specifically including: Configure measurement conditions, including electricity price type and time-sharing ratio , spot ratio , fixed superposition price , transaction price , government authorization ratio , medium- and long-term transaction ratio , enterprise floating price ; Calculate the real-time power consumption for the th day and th hour of the current month, as well as the medium- and long-term power consumption ; Extract the transaction electricity price at the th day and th hour of the current month from the electricity consumption transaction parameters according to the electricity bill time and the electricity price type in the measurement conditions ; According to the transaction price , government authorization ratio , medium- and long-term transaction ratio Calculate the medium- and long-term transaction electricity price ; Calculate the estimated electricity cost of the enterprise on the day through the following formula , Calculate the estimated value of the enterprise's electricity acquisition cost for the current month through the following formula In the formula, is the total number of days in the current month, is the total electricity consumption of the electricity-consuming enterprise in the current month, which is obtained by summing up the electricity consumption in each period in the electricity bill.

5. The method for evaluating electricity sales packages based on electricity bills according to claim 4, characterized in that, Calculate the real-time electricity consumption for the th day and the th hour of the current month, as well as the medium- and long-term electricity consumption , specifically including: ​ Calculate the proportion of power consumption in each time period in the electricity bill through the following formula , Among them, is the electricity consumption during a period, and is the total monthly electricity consumption of the electricity-consuming enterprise; Obtain the number of days included in the peak period, peak hours, normal hours, valley hours, and deep valley hours of the current month from the electricity consumption transaction parameters based on the electricity bill time and the enterprise voltage level. ; Calculate the weight of time-sharing electricity consumption through the following formula , According to the time period division obtained from the power trading platform, the time-of-use electricity consumption weight is divided into the electricity consumption weight for each hour , where represents the electricity consumption weight for the th hour; Calculate the real-time power consumption at the th day and th hour of the current month through the following formula: , Among them, is the total number of days in that month; The medium- and long-term power consumption at the th day and th hour of the current month is calculated by the following formula , Among them, is the hourly proportion in the decomposition curve at the th hour.

6. The method for evaluating electricity sales packages based on electricity bills according to claim 5, wherein Set the package pricing strategy, and generate the estimated package price through the package price prediction model according to the package parameters and the real-time electricity consumption of the electricity-consuming enterprise during the corresponding period, specifically including: Divide the periods according to the period mapping rule and set the price for each period to generate the current package; Calculate the estimated package price using the following formula , Among them, is the trading electricity price for the th day and th hour of the current package.

7. The method for evaluating a power sales package based on an electricity bill according to any one of claims 1 to 6, characterized in that, After obtaining the electricity bill of the electricity-consuming enterprise, the following steps are also included: Verify the integrity and legality of the electricity bill of the electricity-consuming enterprise; If the verification passes, store the electricity bill of the electricity-consuming enterprise in the database; If the verification fails, discard the electricity bill of the electricity-consuming enterprise.

8. An electricity sales package evaluation system based on electricity bills, characterized in that, It includes: An electricity bill acquisition module, used to obtain the electricity bill of the electricity-consuming enterprise. The electricity bill is monthly, and extract the target data from the electricity bill; An electricity trading parameter acquisition module, used to obtain the electricity trading parameters from the power trading platform; An enterprise electricity acquisition cost estimation module, used to generate the estimated value of the enterprise's electricity acquisition cost for the current month through the enterprise's electricity acquisition cost estimation model based on the target data and the electricity trading parameters; A package price estimation module, used to set the package pricing strategy, and generate the estimated package price through the package price prediction model according to the package parameters and the real-time electricity consumption of the electricity-consuming enterprise during the corresponding period; A package evaluation module, used to obtain the expected revenue and risk boundary through the estimated value of the enterprise's electricity acquisition cost for the current month and the estimated package price, and evaluate the rationality of the package pricing strategy according to the expected revenue and risk boundary.

9. A terminal, characterized in that, It includes: A memory, used to store the electricity sales package evaluation program based on the electricity bill; A processor, used to implement the steps of the electricity sales package evaluation method based on the electricity bill as described in any one of claims 1 to 7 when executing the electricity sales package evaluation program based on the electricity bill.

10. A computer-readable storage medium, characterized in that, The electricity sales package evaluation program based on the electricity bill is stored on the readable storage medium. When the electricity sales package evaluation program based on the electricity bill is executed by the processor, the steps of the electricity sales package evaluation method based on the electricity bill as described in any one of claims 1 to 7 are implemented.

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