Retail market power consumer 24-point time-sharing price generation method, device and equipment

Abstract

The invention relates to the technical field of time-of-use electricity prices, in particular to a 24-point time-of-use price generation method for electricity consumers in a retail market, which can acquire electricity consumption data of a consumer main body in a preset time period, and judge the attribution category of the consumer main body according to the electricity consumption data; obtaining predicted spot price difference related data corresponding to the affiliation category of the user main body; reference price data is calculated according to the predicted spot price difference related data, and a price curve is calculated according to the reference price data; obtaining electric charge data according to the power consumption data and a preset submitted price, and obtaining a price coefficient according to the power consumption data and the electric charge data; and obtaining an electricity price curve according to the price coefficient and the price curve. According to the technical scheme, the price curves can be obtained according to the types of the users and the power consumption curves, the price curves of all the users are different, and the main function of the market can be fully played.

Description

Technical Field

[0001] The present invention relates to the technical field of time-of-use electricity prices, and in particular to a method, device and equipment for generating a 24-hour time-of-use price for electricity users in a retail market. Background Art

[0002] In November 2015, my country gradually began to reform transmission and distribution prices, build a power market, establish and regulate power trading institutions, orderly release power consumption plans, and reform the power sales side. my country's power reform has achieved considerable results.

[0003] From the perspective of the market as a whole, the number of market entities has increased significantly. Since October 2021, the number of market entities in the operating area of ​​​​the State Grid Corporation has increased significantly, with more than 145,000 new market entities, and the cumulative number of registered market entities has reached 420,000. Among the new users, 18,000 are direct electricity users, accounting for 12.27%; and 127,000 are retail users, accounting for 87.73%. From November last year to February this year, the average monthly increase in market entities exceeded 30,000. With the entry of all industrial and commercial users into the market, the number of market entities and market electricity will continue to grow this year. However, there are currently about 40 million users who still purchase electricity through power grid companies, including general industry and commerce, small and micro enterprises, and other enterprises.

[0004] In terms of electricity volume, the transaction volume has grown dramatically. With all industrial and commercial users entering the market, the market transaction volume has increased significantly, and the overall monthly direct transaction volume in various provinces has increased by more than 120 billion kWh month-on-month.

[0005] From the perspective of the trading market, “no spot, no market” has been widely accepted. The spot market electricity price signals fully encourage peak power generation of various power sources and guide users to reduce electricity load during peak hours to reduce electricity purchase costs, giving full play to the decisive role of the market in the optimal allocation of power resources.

[0006] However, since the retail market in the electricity spot market scenario fully plays the role of the main body of the market, the electricity price signal effectively guides the user's electricity usage habits to reduce costs. Since each electricity user has a different electricity usage curve, if the price curve is the same, the main body of the market cannot be fully played, and the electricity price signal cannot play an effective guiding role. Summary of the invention

[0007] In view of this, the purpose of the present invention is to provide a method, device and equipment for generating 24-hour time-of-use prices for electricity users in the retail market, so as to solve the problem in the prior art that each electricity user has a different electricity consumption curve but the same price curve.

[0008] According to a first aspect of an embodiment of the present invention, a method for generating a 24-hour time-of-use price for power users in a retail market is provided, comprising: Acquire the power consumption data of the user subject within a preset time period, and determine the category of the user subject according to the power consumption data; Obtain data related to the estimated spot price spread corresponding to the user subject's classification; Calculate benchmark price data based on the estimated spot price spread related data, and calculate a price curve based on the benchmark price data; The electricity fee data is obtained based on the electricity consumption data and the preset reported price, and the price coefficient is obtained based on the electricity consumption data and the electricity fee data; An electricity price curve is obtained according to the price coefficient and the price curve.

[0009] Preferably, the benchmark price data is calculated based on the estimated spot price difference related data, including: The data related to the estimated spot price spread include the spot price of the same period last year, the spot price of the previous month and the market marginal information disclosed in the current month; The benchmark price data is calculated based on the spot price of the same period last year, the spot price of the previous month and the market marginal information disclosed in the current month.

[0010] Preferably, the calculating a price curve according to the benchmark price data includes: Determine the benchmark time-sharing price and the benchmark price arithmetic mean based on the benchmark price data; A price curve is obtained based on the benchmark time-sharing price and the arithmetic mean of the benchmark price.

[0011] Preferably, the step of obtaining electricity fee data based on electricity consumption data and preset reporting prices includes: The total amount of electricity is obtained according to the electricity consumption data, and the electricity fee data is calculated according to the total amount of electricity and the reported price.

[0012] Preferably, the price coefficient is obtained based on the electricity consumption data and the electricity fee data, including: Deriving a time-sharing value of the price curve according to the price curve, obtaining a time-sharing quantity of electricity according to the electricity consumption data, and calculating an electricity fee baseline according to the time-sharing value of the price curve and the time-sharing quantity of electricity; The time-sharing value of the electricity fee baseline and the sum of the electricity fee baseline are obtained according to the electricity fee baseline, and the time-sharing ratio of the electricity fee is calculated according to the time-sharing value of the electricity fee baseline and the sum of the electricity fee baseline; An electricity charge curve is calculated based on the electricity charge time-sharing ratio and the electricity charge data; The time-sharing value of the electricity rate curve is obtained according to the electricity rate curve, and the price coefficient is calculated according to the time-sharing power, the time-sharing value of the electricity rate curve and the time-sharing value of the price curve.

[0013] Preferably, the attribution categories include at least: peak-period users, valley-period users and general users.

[0014] According to a second aspect of an embodiment of the present invention, a device for generating a 24-hour time-sharing price for power users in a retail market is provided, comprising: A data acquisition module is used to acquire the electricity consumption data of the user subject within a preset time period, determine the category of the user subject according to the electricity consumption data, and acquire the estimated spot price difference related data corresponding to the category of the user subject; A price curve generating module, used for calculating benchmark price data according to the estimated spot price difference related data, and calculating a price curve according to the benchmark price data; The data calculation module is used to obtain electricity fee data according to electricity consumption data and preset reported prices, obtain price coefficients according to electricity consumption data and electricity fee data; and obtain electricity price curves according to the price coefficients and the price curves.

[0015] According to a third aspect of an embodiment of the present invention, a 24-hour time-of-use price generating device for power users in a retail market is provided, comprising: A main controller, and a memory connected to the main controller; The memory stores program instructions; The main controller is used to execute program instructions stored in the memory to perform any of the above methods.

[0016] The technical solution provided by the embodiments of the present invention may have the following beneficial effects: It can be understood that the technical solution shown in the present invention can obtain the electricity consumption data of the user subject within a preset time period, determine the user subject's belonging category based on the electricity consumption data; obtain the estimated spot price difference related data corresponding to the user subject's belonging category; calculate the benchmark price data based on the estimated spot price difference related data, and calculate the price curve based on the benchmark price data; obtain the electricity fee data based on the electricity consumption data and the preset reported price, and obtain the price coefficient based on the electricity consumption data and the electricity fee data; and obtain the electricity price curve based on the price coefficient and the price curve. This technical solution can obtain a price curve based on the user's category and electricity consumption curve. The price curve of each user is different, which can give full play to the main role of the market.

[0017] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0019] Figure 1 is a schematic block diagram of a controller update control system according to an exemplary embodiment; Figure 2 The figure is a schematic diagram showing calculation of a user's estimated electricity consumption curve according to an exemplary embodiment. DETAILED DESCRIPTION

[0020] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Instead, they are merely examples of devices and methods consistent with some aspects of the present invention as detailed in the appended claims.

[0021] In one embodiment, Figure 1 is a schematic block diagram of a controller updating control system according to an exemplary embodiment. Figure 1 , a method for generating a 24-hour time-of-use price for power users in a retail market is provided, comprising: Step S11: Obtain the electricity usage data of the user subject within a preset time period, and determine the category of the user subject according to the electricity usage data.

[0022] In actual practice, since the electricity consumption data of each user is different, users can be classified according to their electricity consumption data, and then the corresponding benchmark prices can be set.

[0023] It should be noted that the attribution categories include at least: peak-time users, valley-time users and general users.

[0024] Specific peak and valley periods can be set according to local electricity consumption policies. For example, in a certain place, the document stipulates that the time-of-use electricity price is divided according to the following time periods: peak period 18:00-20:00 (two-part system users implement it in January, July, August and December each year); peak period 8:00-11:00, 17:00-23:00; normal period 7:00-8:00, 13:00-17:00, 23:00-24:00; valley period 0:00-7:00, 11:00-13:00. Therefore, if the user's electricity consumption data shows that the peak period consumes more electricity, it is a peak period user, and the valley period consumes more electricity, it is a valley period user, and the rest of the users are general users.

[0025] Step S12: Obtain data related to the estimated spot price difference corresponding to the category of the user subject.

[0026] In practice, for each category of users, the corresponding estimated spot price spread data is obtained, and different benchmark price data can be obtained based on the estimated spot price spread data. Different user categories have different applicable benchmark prices, and the peak-to-valley spreads throughout the day are different. It is necessary to make two or more benchmark prices based on different user types.

[0027] The purpose of time-sharing trading is to guide users' electricity consumption behavior through price signals, so that users can use electricity more economically. Based on this purpose, the price difference of electricity consumption in peak period users during different periods of the day should be higher than the price difference of electricity consumption in valley period users during different periods of the day.

[0028] Step S13: Calculate benchmark price data based on the estimated spot price difference related data, and calculate a price curve based on the benchmark price data.

[0029] It should be noted that the calculated benchmark price data specifically includes: the estimated spot price spread related data include the spot price of the same period last year, the spot price of last month and the market marginal information disclosed in the current month; the benchmark price data is calculated based on the spot price of the same period last year, the spot price of last month and the market marginal information disclosed in the current month.

[0030] It should be noted that calculating the price curve specifically includes: obtaining a benchmark time-sharing price and a benchmark price arithmetic mean according to the benchmark price data; and obtaining a price curve according to the benchmark time-sharing price and the benchmark price arithmetic mean.

[0031] Price curve = benchmark intraday price / arithmetic mean of benchmark price, which actually expresses the peak-to-valley difference ratio of the benchmark price.

[0032] Step S14: derive electricity charge data based on the electricity consumption data and the preset reported price, and derive a price coefficient based on the electricity consumption data and the electricity charge data.

[0033] It should be noted that the electricity fee data obtained based on the electricity consumption data and the preset reported price includes: The total amount of electricity is obtained according to the electricity consumption data, and the electricity fee data is calculated according to the total amount of electricity and the reported price.

[0034] In specific practice, the reported price is the estimated settlement price after negotiation between price marketing personnel and users. When the electricity consumption data is the estimated electricity consumption data for next month and the reported price is the estimated settlement price for next month, the price curve for next month can be estimated.

[0035] Preferably, an electricity consumption curve can be derived based on the electricity consumption data, and the product of the total amount of the electricity consumption curve and the reported price is the electricity fee data: electricity fee = total electricity consumption of the electricity consumption curve × reported price.

[0036] It should be noted that the price coefficient obtained based on the electricity consumption data and electricity fee data includes: The time-sharing value of the price curve is obtained according to the price curve, the time-sharing power quantity is obtained according to the power consumption data, and the electricity fee baseline is calculated according to the time-sharing value of the price curve and the time-sharing power quantity.

[0037] Electricity fee baseline = time-of-use electricity consumption × time-of-use value of price curve.

[0038] The time-sharing value of the electricity fee baseline and the sum of the electricity fee baseline are obtained according to the electricity fee baseline, and the time-sharing ratio of the electricity fee is calculated according to the time-sharing value of the electricity fee baseline and the sum of the electricity fee baseline.

[0039] The time-of-use ratio of electricity charges = the time-of-use value of the electricity charge baseline / the total of the electricity charge baselines.

[0040] An electricity charge curve is calculated based on the electricity charge time-sharing ratio and the electricity charge data.

[0041] Electricity charge curve = electricity charge × electricity charge time-sharing ratio.

[0042] The time-sharing value of the electricity rate curve is obtained according to the electricity rate curve, and the price coefficient is calculated according to the time-sharing power, the time-sharing value of the electricity rate curve and the time-sharing value of the price curve.

[0043] Price coefficient = time-of-use value of electricity rate curve / time-of-use electricity consumption / time-of-use value of price curve.

[0044] Step S15: derive an electricity price curve according to the price coefficient and the price curve.

[0045] Electricity price curve = price curve × price coefficient.

[0046] It can be understood that the technical solution shown in this embodiment can obtain the electricity consumption data of the user subject within a preset time period, determine the user subject's belonging category based on the electricity consumption data; obtain the estimated spot price difference related data corresponding to the user subject's belonging category; calculate the benchmark price data based on the estimated spot price difference related data, and calculate the price curve based on the benchmark price data; derive the electricity fee data based on the electricity consumption data and the preset reported price, and derive the price coefficient based on the electricity consumption data and the electricity fee data; and derive the electricity price curve based on the price coefficient and the price curve. The technical solution shown in this embodiment can derive a price curve based on the user's category and electricity consumption curve. The price curve for each user is different, and the main role of the market can be fully utilized.

[0047] In actual practice, the above method can be integrated into a calculation model. When using it, you only need to change the benchmark price, the user's expected electricity consumption curve and the reported price to generate the user's corresponding electricity price curve.

[0048] Figure 2 shows the electricity consumption data of a specific user, see Figure 2 The benchmark price refers to the 24-hour average price of the spot market clearing last month, and the price reported by the user is 411. After calculation, the user is a peak user and is subject to time-of-use prices. The total electricity fee is calculated by the formula to be 56,434.41 yuan, and the price coefficient is 417.56. The price curve × price coefficient finally results in the price curve to be reported as shown in the last column of the figure.

[0049] According to a second aspect of an embodiment of the present invention, a device for generating a 24-hour time-sharing price for power users in a retail market is provided, comprising: A data acquisition module is used to acquire the electricity consumption data of the user subject within a preset time period, determine the category of the user subject according to the electricity consumption data, and acquire the estimated spot price difference related data corresponding to the category of the user subject; A price curve generating module, used for calculating benchmark price data according to the estimated spot price difference related data, and calculating a price curve according to the benchmark price data; The data calculation module is used to obtain electricity fee data according to electricity consumption data and preset reported prices, obtain price coefficients according to electricity consumption data and electricity fee data; and obtain electricity price curves according to the price coefficients and the price curves.

[0050] It can be understood that the technical solution shown in this embodiment can obtain the electricity consumption data of the user subject within a preset time period, determine the user subject's belonging category based on the electricity consumption data; obtain the estimated spot price difference related data corresponding to the user subject's belonging category; calculate the benchmark price data based on the estimated spot price difference related data, and calculate the price curve based on the benchmark price data; derive the electricity fee data based on the electricity consumption data and the preset reported price, and derive the price coefficient based on the electricity consumption data and the electricity fee data; and derive the electricity price curve based on the price coefficient and the price curve. This technical solution can derive a price curve based on the user's category and electricity consumption curve. The price curve of each user is different, and the main role of the market can be fully utilized.

[0051] According to a third aspect of an embodiment of the present invention, a 24-hour time-of-use price generating device for power users in a retail market is provided, comprising: A main controller, and a memory connected to the main controller; The memory stores program instructions; The main controller is used to execute program instructions stored in the memory to perform any of the above methods.

[0052] It can be understood that the same or similar parts of the above embodiments can be referenced to each other, and the contents not described in detail in some embodiments can refer to the same or similar contents in other embodiments.

[0053] It should be noted that, in the description of the present invention, the terms "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance. In addition, in the description of the present invention, unless otherwise specified, the meaning of "plurality" refers to at least two.

[0054] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code that includes one or more executable instructions for implementing the steps of a specific logical function or process, and the scope of the preferred embodiments of the present invention includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present invention belong.

[0055] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0056] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0057] In addition, each functional unit in each embodiment of the present invention may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0058] The storage medium mentioned above can be a read-only memory, a magnetic disk or an optical disk, etc.

[0059] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0060] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

Claims

1. A method for generating 24-hour time-sharing prices for power users in a retail market, characterized in that: include: Acquire the power consumption data of the user subject within a preset time period, and determine the category of the user subject according to the power consumption data; Obtain data related to the estimated spot price spread corresponding to the user subject's classification; Calculate benchmark price data based on the estimated spot price spread related data, and calculate a price curve based on the benchmark price data; The electricity fee data is obtained based on the electricity consumption data and the preset reported price, and the price coefficient is obtained based on the electricity consumption data and the electricity fee data; An electricity price curve is obtained according to the price coefficient and the price curve.

2. The method according to claim 1, characterized in that: The benchmark price data calculated based on the estimated spot price difference related data includes: The data related to the estimated spot price spread include the spot price of the same period last year, the spot price of the previous month and the market marginal information disclosed in the current month; The benchmark price data is calculated based on the spot price of the same period last year, the spot price of the previous month and the market marginal information disclosed in the current month.

3. The method according to claim 1, characterized in that The step of calculating a price curve based on the benchmark price data includes: Determine the benchmark time-sharing price and the benchmark price arithmetic mean based on the benchmark price data; A price curve is obtained based on the benchmark time-sharing price and the arithmetic mean of the benchmark price.

4. The method according to claim 3, characterized in that The electricity fee data obtained based on the electricity consumption data and the preset reported price includes: The total amount of electricity is obtained according to the electricity consumption data, and the electricity fee data is calculated according to the total amount of electricity and the reported price.

5. The method according to claim 4, characterized in that The price coefficient obtained based on the electricity consumption data and electricity fee data includes: Deriving a time-sharing value of the price curve according to the price curve, obtaining a time-sharing quantity of electricity according to the electricity consumption data, and calculating an electricity fee baseline according to the time-sharing value of the price curve and the time-sharing quantity of electricity; The time-sharing value of the electricity fee baseline and the sum of the electricity fee baseline are obtained according to the electricity fee baseline, and the time-sharing ratio of the electricity fee is calculated according to the time-sharing value of the electricity fee baseline and the sum of the electricity fee baseline; An electricity charge curve is calculated based on the electricity charge time-sharing ratio and the electricity charge data; The time-sharing value of the electricity rate curve is obtained according to the electricity rate curve, and the price coefficient is calculated according to the time-sharing power, the time-sharing value of the electricity rate curve and the time-sharing value of the price curve.

6. The method according to claim 1, characterized in that The attribution categories include at least: peak-time users, valley-time users and general users.

7. A 24-hour time-sharing price generation device for power users in the retail market, characterized in that: include: A data acquisition module, used to acquire the power consumption data of the user subject within a preset time period, and determine the category of the user subject according to the power consumption data; Obtain data related to the estimated spot price spread corresponding to the user subject's classification; A price curve generating module, used for calculating benchmark price data according to the estimated spot price difference related data, and calculating a price curve according to the benchmark price data; The data calculation module is used to obtain electricity fee data according to electricity consumption data and preset reported prices, obtain price coefficients according to electricity consumption data and electricity fee data; and obtain electricity price curves according to the price coefficients and the price curves.

8. A 24-hour time-sharing price generation device for power users in the retail market, characterized in that: include: A main controller, and a memory connected to the main controller; The memory stores program instructions; The main controller is used to execute program instructions stored in the memory and execute the method according to any one of claims 1 to 6.

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