Load regulation strategy making method and related device

Abstract

The invention discloses a method for formulating a load adjustment strategy and a related device. The method comprises the following steps: determining a first electricity selling income of an electricity selling subject before load adjustment and a second electricity selling income of the electricity selling subject after load adjustment; determining an adjustment direction strategy that the user participates in load adjustment; determining a first adjustment income of the user under the adjustment direction strategy; and determining a load adjustment strategy according to the first electricity selling income, the second electricity selling income, the adjustment direction strategy and the first adjustment income. According to the invention, the adjustment potential of the user can be fully stimulated, and a real-time and effective load allocation strategy is constructed, so that resource optimization configuration and cost benefit improvement are realized.

Description

Technical Field

[0001] This application relates to the technical field of power markets, and in particular, to a method for formulating a load regulation strategy and related devices. Background Art

[0002] With the development of the spot market, electricity prices are affected by various factors such as generation costs, energy supply, weather changes, and electricity demand, and the frequency and amplitude of fluctuations have increased significantly. As a market participant, if an electricity sales company cannot adapt to this change in a timely manner and formulate a flexible and efficient load regulation strategy, it will be at a disadvantage in the fierce market competition.

[0003] Electricity sales companies usually adjust loads based on relatively fixed electricity price strategies, resulting in the lack of flexibility and pertinence in the load regulation strategies formulated by electricity sales companies, making it difficult to allocate resources efficiently; and currently, there is a lack of effective incentive mechanisms to guide users to optimize consumption, and users cannot be fully motivated to participate in market-based load regulation. Summary of the Invention

[0004] Embodiments of this application provide a method for formulating a load regulation strategy and related devices to fully stimulate the adjustment potential of users, construct a real-time and effective load allocation strategy, and then achieve optimized resource allocation and improved cost-effectiveness.

[0005] In a first aspect, embodiments of this application provide a method for formulating a load regulation strategy, including:

[0006] Determine the first electricity sales revenue of the electricity sales entity before load regulation and the second electricity sales revenue after load regulation;

[0007] Determine the adjustment direction strategy for users to participate in load regulation;

[0008] Determine the first adjustment revenue of the user under the adjustment direction strategy;

[0009] Determine a load regulation strategy according to the first electricity sales revenue, the second electricity sales revenue, the adjustment direction strategy, and the first adjustment revenue.

[0010] Among them, the determining the first adjustment revenue of the user under the adjustment direction strategy includes:

[0011] Determine the controllable adjustment load of the user under the adjustment direction strategy;

[0012] Obtain the spot electricity price predicted by the electricity sales entity; and, obtain the retail contract electricity price signed between the electricity sales entity and the user; and, obtain the base load of the user;

[0013] Determine the sharing ratio for the electricity sales entity to motivate the user according to the spot electricity price and the retail contract electricity price;

[0014] Determine the first regulation revenue according to the controllable regulated load, the spot electricity price, the retail contract electricity price, the sharing ratio, and the base load.

[0015] Among them, the first regulation revenue satisfies the following formula:

[0016] Among them, profit is the first regulation revenue, P i 0 is the retail contract electricity price, P i rt is the spot electricity price, ΔQ is the controllable regulated load, α is the sharing ratio, is the base load.

[0017] Among them, determining the load regulation strategy according to the first electricity sales revenue, the second electricity sales revenue, the adjustment direction strategy, and the first regulation revenue includes:

[0018] Determine the difference between the first electricity sales revenue and the second electricity sales revenue;

[0019] Adjust the first regulation revenue according to the difference to obtain the second regulation revenue;

[0020] Determine the first regulation strategy according to the second regulation revenue;

[0021] Determine the load regulation strategy according to the first regulation strategy and the adjustment direction strategy.

[0022] Among them, determining the first regulation strategy according to the second regulation revenue includes:

[0023] Obtain the historical electricity consumption data and historical electricity price data of the user; and obtain the current electricity price fluctuation range;

[0024] Determine the revenue threshold of the user according to the historical electricity consumption data, the historical electricity price data, and the electricity price fluctuation range;

[0025] Determine the first regulation strategy according to the revenue threshold and the second regulation revenue.

[0026] Among them, determining the first electricity sales revenue of the electricity sales entity before load regulation and the second electricity sales revenue after load regulation includes:

[0027] Obtain the retail contract electricity price, medium- and long-term contract electricity price, and medium- and long-term contract electricity volume signed between the electricity seller and the user; and, obtain the base load of the user and the actual load after load adjustment; and, obtain the day-ahead market time-of-use electricity price and the day-ahead market winning bid electricity volume of the electricity seller; and, obtain the spot electricity price predicted by the electricity seller;

[0028] Determine the first electricity sales revenue according to the retail contract electricity price, the medium- and long-term contract electricity price, the medium- and long-term contract electricity volume, the base load, the day-ahead market time-of-use electricity price, the day-ahead market winning bid electricity volume, and the spot electricity price;

[0029] Determine the second electricity sales revenue according to the retail contract electricity price, the medium- and long-term contract electricity price, the medium- and long-term contract electricity volume, the actual load, the day-ahead market time-of-use electricity price, the day-ahead market winning bid electricity volume, and the spot electricity price.

[0030] Among them, the first electricity sales revenue satisfies the following formula:

[0031]

[0032] Among them, profit0 is the first electricity sales revenue, P i 0 is the retail contract electricity price, is the base load, P i m is the medium- and long-term contract electricity price, is the medium- and long-term contract electricity volume, P i da is the day-ahead market time-of-use electricity price, is the day-ahead market winning bid electricity volume, is the spot electricity price, m is the number of users corresponding to the electricity seller, and i is any one of the users corresponding to the electricity seller;

[0033] The second electricity sales revenue satisfies the following formula:

[0034]

[0035] Among them, profit1 is the second electricity sales revenue, is the actual load.

[0036] In a second aspect, an embodiment of the present application provides a device for formulating a load adjustment strategy, including:

[0037] A first determination unit, configured to determine the first electricity sales revenue of the electricity seller before load adjustment and the second electricity sales revenue after load adjustment;

[0038] A second determination unit, configured to determine an adjustment direction strategy for the user to participate in load regulation;

[0039] A third determination unit, configured to determine a first regulation benefit of the user under the adjustment direction strategy;

[0040] A fourth determination unit, configured to determine a load regulation strategy according to the first power selling benefit, the second power selling benefit, the adjustment direction strategy, and the first regulation benefit.

[0041] In a third aspect, an embodiment of the present application provides an electronic device, including a memory, a processor, and executable program code stored on the memory and executable on the processor. When the processor executes the executable program code, it executes the steps of the method described in the first aspect.

[0042] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which executable program code is stored. The executable program code includes execution instructions for executing the steps of the method described in the first aspect.

[0043] In a fifth aspect, an embodiment of the present application provides a computer program product. The computer program product includes a non-transitory computer-readable storage medium storing a computer program. The computer program is operable to cause a computer to execute some or all of the steps described in the first aspect of the embodiments of the present application. The computer program product may be a software installation package.

[0044] It can be seen that in the embodiment of the present application, first, a first power selling benefit of the power selling entity before load regulation and a second power selling benefit after load regulation are determined; then, an adjustment direction strategy for the user to participate in load regulation is determined; then, a first regulation benefit of the user under the adjustment direction strategy is determined; and finally, a load regulation strategy is determined according to the first power selling benefit, the second power selling benefit, the adjustment direction strategy, and the first regulation benefit. The present application clarifies the regulation direction and identifies the potential benefit space of the user in this regulation direction. By combining the potential benefit space of the user, the change in the power selling benefit of the power selling company, and the regulation direction, it is beneficial for the power selling company to formulate a real-time and effective load allocation strategy, fully stimulate the regulation potential of the user, convert the user load into a tradable market-oriented resource, and achieve optimal resource allocation and cost-benefit improvement. Description of the Drawings

[0045] To more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the accompanying drawings required for the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can also be obtained based on these drawings.

[0046] Figure 1 is the system architecture diagram of a strategy formulation system provided by an embodiment of the present application;

[0047] Figure 2 is the flowchart of a method for formulating a load regulation strategy provided by an embodiment of the present application;

[0048] Figure 3 is the flowchart of a method for determining the regulation benefit provided by an embodiment of the present application;

[0049] Figure 4 is the flowchart of another method for formulating a load regulation strategy provided by an embodiment of the present application;

[0050] Figure 5 is the flowchart of a method for determining a regulation strategy provided by an embodiment of the present application;

[0051] Figure 6 is the block diagram of the functional units of a device for formulating a load regulation strategy provided by an embodiment of the present application;

[0052] Figure 7 is the block diagram of the functional units of another device for formulating a load regulation strategy provided by an embodiment of the present application;

[0053] Figure 8 is the structural diagram of an electronic device proposed by an embodiment of the present application. Detailed implementation manners

[0054] In order to enable those skilled in the art to better understand the solutions of the present application, the following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, rather than all embodiments. Based on the embodiments of the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present application.

[0055] The terms "first", "second", etc. in the description, claims and the above-mentioned drawings of this application are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally further include steps or units not listed, or may optionally further include other steps or units inherent to these processes, methods, products or devices.

[0056] Reference to "embodiment" herein means that a particular feature, structure or characteristic described in connection with the embodiment can be included in at least one embodiment of this application. The phrase appears at various places in the specification and does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art will explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments.

[0057] At present, electricity selling companies adjust load based on relatively fixed electricity price strategies, ignoring the behavioral differences of users. There are differences in the electricity consumption habits, industry attributes, and sensitivity to electricity prices of different users. Fixed electricity prices cannot conduct refined management for these differences, resulting in the lack of pertinence and flexibility in the load regulation strategies formulated by electricity selling companies, making it difficult to meet the diverse needs of the market. Furthermore, when facing fluctuations in the supply and demand of the electricity market, electricity selling companies are difficult to quickly and accurately adjust trading strategies, leading to low resource allocation efficiency.

[0058] At the same time, there is a lack of an effective incentive mechanism to guide users to optimize the adjustment of electricity consumption at different times, and it is impossible to fully motivate users to participate in market-based load regulation.

[0059] In view of the above problems, the embodiments of this application provide a method for formulating a load regulation strategy and related devices. The embodiments of this application will be introduced in detail below with reference to the drawings.

[0060] Please refer to Figure 1 , Figure 1 which is a system architecture diagram of a strategy formulation system provided by the embodiments of this application. As Figure 1 shown, the strategy formulation system 100 includes a data collection module 101, a revenue analysis module 102, and a strategy formulation module 103. Among them, the data collection module 101, the revenue analysis module 102, and the strategy formulation module 103 are communicatively connected to each other.

[0061] Among them, the data acquisition module 101 is used to collect multi-source data and preprocess the multi-source data to improve data quality, unify data formats and structures. Specifically, the multi-source data may include time-of-use electricity prices such as retail contract electricity prices and spot real-time electricity prices, as well as time-of-use electricity quantities such as user baseline loads, user actual loads, medium- and long-term contract electricity quantities, and day-ahead winning bid electricity quantities. The preprocessing operations may include data cleaning, data conversion, data integration, and other operations.

[0062] Among them, the revenue analysis module 102 is used to receive the data preprocessed by the data acquisition module 101, and is used to calculate the electricity sales revenue of the electricity seller before and after load regulation based on this data, as well as calculate the response revenue of users.

[0063] Among them, the strategy formulation module 103 is used to receive the data preprocessed by the data acquisition module 101 and the multi-subject revenues calculated by the revenue analysis module 102, and then determine the adjustment direction strategy of load regulation based on this data. For example, it is recommended that users reduce power consumption during this period, or it is recommended that users increase power consumption during this period; it can also formulate differentiated regulation strategies for different user response spaces based on this data, convert user loads into tradable market resources, and achieve precise matching of cost minimization and revenue maximization.

[0064] Based on this, the present application provides a method for formulating a load regulation strategy and related devices. The present application will be described in detail below with reference to the accompanying drawings.

[0065] Please refer to Figure 2 , Figure 2 which is a schematic flowchart of a method for formulating a load regulation strategy provided by an embodiment of the present application. As Figure 2 shown, the method includes the following steps:

[0066] S210, determine the first electricity sales revenue of the electricity seller before load regulation and the second electricity sales revenue after load regulation.

[0067] Among them, the electricity seller refers to an economic entity that participates in electricity sales and other businesses in the electricity market, that is, an electricity sales company. The electricity sales company purchases electricity from power generation enterprises or other power suppliers and then sells it to end-users, including industrial and commercial users, residential users, etc. By optimizing procurement strategies and sales models, it realizes profitability while meeting the electricity consumption needs of users. In addition to basic electricity sales, the electricity sales company can also provide users with a variety of value-added services, such as energy-saving consulting, construction of energy management systems, maintenance of electrical equipment, etc., to help users reduce electricity costs and improve energy utilization efficiency. Among them, the electricity sales company can also conduct load management, such as formulating load regulation strategies, guiding users to reasonably adjust their electricity consumption behaviors, achieving peak shaving and valley filling, reducing the peak load of the power grid, and improving the stability and economy of the power system operation.

[0068] In a possible embodiment, determining the first electricity sales revenue of the electricity seller before load regulation and the second electricity sales revenue after load regulation includes: obtaining the retail contract electricity price, medium- and long-term contract electricity price, and medium- and long-term contract electricity quantity signed between the electricity seller and the user; and obtaining the base load of the user and the actual load after load regulation; and obtaining the day-ahead market time-of-use electricity price and the day-ahead market winning bid electricity quantity of the electricity seller; and obtaining the spot electricity price predicted by the electricity seller; determining the first electricity sales revenue according to the retail contract electricity price, the medium- and long-term contract electricity price, the medium- and long-term contract electricity quantity, the base load, the day-ahead market time-of-use electricity price, the day-ahead market winning bid electricity quantity, and the spot electricity price; and determining the second electricity sales revenue according to the retail contract electricity price, the medium- and long-term contract electricity price, the medium- and long-term contract electricity quantity, the actual load, the day-ahead market time-of-use electricity price, the day-ahead market winning bid electricity quantity, and the predicted spot electricity price.

[0069] Among them, the spot electricity price is the real-time electricity price determined by buyers and sellers through bidding according to the current electricity supply and demand situation in the electricity spot market. It reflects the true market value of electricity commodities in a short period of time. For electricity selling companies, accurately predicting the spot electricity price is conducive to formulating reasonable electricity purchase strategies in the electricity wholesale market, and can also provide more accurate electricity price information for users in retail business, so as to optimize the allocation of power resources, reduce the electricity purchase cost, and improve the market competitiveness.

[0070] In a possible embodiment, the spot electricity price can be predicted based on historical electricity price data, power load data, power generation side data, and data affected by external factors.

[0071] Among them, the historical electricity price data includes time series data and price fluctuation data; the time series data is used to record the spot electricity price data in the past period of time, such as the spot electricity price data in the past year or past few months, and the spot electricity price data includes information such as date, time, and electricity price. By analyzing and modeling these historical data, the periodic change rules and trend changes of electricity prices can be found.

[0072] Among them, the price fluctuation data is used to record the fluctuation situation of electricity prices, including the amplitude and frequency of price increase and decrease, etc. According to this data, the fluctuation characteristics of electricity prices can be understood. For example, the electricity price fluctuates greatly in some periods, which may be related to the drastic changes in electricity supply and demand or the behavior of market participants in this period.

[0073] Among them, the power load data includes system load data and user load data; the system load data includes the total power load demand in different regions and different periods. The change of system load directly affects the balance between electricity supply and demand, and thus affects the spot electricity price. Generally speaking, the electricity price is often higher during peak load periods and lower during off-peak periods.

[0074] Among them, the user load data includes the load data for different types of users, such as industrial users, commercial users, and residential users. The electricity consumption behaviors and load characteristics of different users are different. For example, industrial users may have a large electricity consumption during certain specific periods on weekdays, while residential users have obvious differences in their electricity consumption behaviors at night and on weekends.

[0075] Among them, the power generation side data includes the quotation data of power generation enterprises, to understand the quotation situation of power generation enterprises in the electricity spot market, including the quotations of different power generation types. The quotation strategy of power generation enterprises will affect the formation of market prices. For example, when the quotation of a certain power generation enterprise changes abnormally, it may lead to fluctuations in the spot electricity price. The power generation side data also includes the operation data of generator sets. When some thermal power generator sets are under maintenance, the supply capacity of thermal power generation decreases, which may lead to an increase in the spot electricity price in the market.

[0076] Among them, the data affected by external factors includes meteorological data. Weather conditions have a significant impact on power supply and demand. For example, in high-temperature summer weather, the air-conditioning electricity load will increase significantly, resulting in an increase in power demand, and the spot electricity price may also increase accordingly; while in windy weather conditions, the output of wind power increases, which may increase the power supply and exert downward pressure on the electricity price. Therefore, it is necessary to collect meteorological data such as temperature, wind speed, and light intensity.

[0077] Among them, the data affected by external factors also includes economic situation data, including gross domestic product data, industrial added value data, etc. For example, during the period of economic prosperity, industrial production expands, power demand increases, and the spot electricity price may rise; on the contrary, during the period of economic recession, power demand decreases, and the electricity price may fall.

[0078] In a possible embodiment, the spot electricity price can be predicted through an artificial neural network. By constructing a multi-layer neural network structure, the input layer receives various relevant data, such as historical electricity prices, loads, meteorology, etc. After being calculated and processed by the hidden layer, the neurons in the output layer output the predicted spot electricity price.

[0079] It can be seen that in the embodiment of the present application, using information technology to predict the market transaction electricity price is beneficial for the electricity sales company to accurately formulate the electricity price strategy and timely adjust the time-of-use electricity price.

[0080] Among them, the user refers to the retail users agented by the electricity sales company, who are various terminal electricity consumers who sign contracts with the electricity sales company and the electricity sales company provides them with electricity sales and related services, including industrial and commercial users, residential users, agricultural users, etc.

[0081] Among them, the retail contract electricity price is the electricity price agreed upon by the electricity selling company and the electricity user when signing the retail power purchase contract. The medium- and long-term contract electricity price is the electricity price agreed upon by the electricity selling company and the electricity user when signing the medium- and long-term power purchase contract. For users, it can provide more long-term electricity price stability and reduce the risks brought by electricity price uncertainty; for the electricity selling company, it is conducive to stabilizing income and market share and better conducting resource planning and investment.

[0082] In a possible embodiment, when obtaining the retail contract electricity price, medium- and long-term contract electricity price, predicted spot electricity price, and day-ahead market time-of-use electricity price, etc., it is necessary to preprocess them, sort out the data formats of each electricity price, and according to the data types in different time dimensions, it is necessary to merge or split the electricity data segmented by 15 minutes or the peak-valley-flat electricity price data, and convert it into the time-of-use electricity price data format segmented by hour.

[0083] Among them, the medium- and long-term contract electricity quantity is the predicted electricity consumption data in the long-term power supply agreement signed by the electricity selling company and the user. After obtaining the medium- and long-term contract electricity quantity, it is necessary to perform data cleaning and data integration; the cleaning process includes identifying and removing abnormal electricity quantity data, such as extreme values caused by input errors or equipment failures. For the medium- and long-term contract electricity quantity data missing due to data collection problems or other reasons, linear interpolation or trend prediction methods based on historical data are used for filling. Ensure that the units of all electricity quantity data are consistent to avoid errors caused by inconsistent data sources. Among them, the integration process includes re-aggregating or splitting the data of the medium- and long-term contract electricity quantity according to analysis requirements in dimensions such as hour, day, week, month, etc., to ensure consistency with the time granularity of other electricity quantity data.

[0084] Among them, the day-ahead market winning bid electricity quantity is the electricity quantity data won by the electricity selling company in the day-ahead market, which reflects the next-day supply plan obtained according to the market clearing result. When preprocessing the day-ahead market winning bid electricity quantity, it is possible to first verify whether all winning bid electricity quantity data is accurate to avoid data input errors or market data transmission problems. Specifically, it can be compared with the market announcement or winning bid confirmation document to ensure the reliability of the data. Then, the electricity quantity of the same market type is integrated, and for different market types in the same day-ahead market, such as flat period, peak period, etc., unified summary and integration are carried out to ensure the consistency of different electricity quantity data sources.

[0085] Among them, the base load refers to the baseline load of retail users, which is the data of users' regular electricity consumption behavior without any incentives and regulations, and is usually used to evaluate users' responses to regulation strategies. The actual load after load regulation is the real electricity load consumed by retail users at a specific moment or during a specific period in the actual electricity consumption process. After obtaining the baseline load of retail users, the baseline load is divided into hourly time periods to ensure the consistency of the baseline data and the actual load data in the time dimension.

[0086] Specifically, based on the retail contract price and the base load, the amount of electricity charges that the user is expected to pay during this specific period is calculated, which reflects the cost that the user needs to bear for using electricity under normal circumstances.

[0087] Among them, the electricity selling company calculates the total cost that the user pays for purchasing electricity during the contract period according to the medium- and long-term contract electricity quantity actually used by the user and the electricity price stipulated in the contract. Then, this part of the cost is subtracted from the approximate electricity charge expenditure calculated based on the baseline load to obtain a difference, which reflects the change in the user's conventional electricity cost compared with the baseline load after using the medium- and long-term contract electricity quantity.

[0088] Among them, the day-ahead market is a short-term electricity trading market, usually organized for trading every day before the day, used to balance the electricity supply and demand of the next day. Users can trade their demand for the part exceeding the medium- and long-term contract electricity quantity in this market. The electricity selling company needs to calculate the amount of electricity charges that it needs to pay additionally or obtain according to the actual trading situation of the user in the day-ahead market, and subtract this part of the amount from the difference obtained in the previous step to get a difference.

[0089] Specifically, if the winning bid electricity quantity of the user in the day-ahead market exceeds the electricity quantity stipulated in the medium- and long-term contract, the user needs to pay additional electricity charges for the part exceeding the medium- and long-term contract electricity quantity according to the time-of-use electricity price in the day-ahead market. This part of the cost reflects the additional cost generated by the user due to the increased electricity demand in the short-term electricity market. If the winning bid electricity quantity of the user in the day-ahead market is less than the medium- and long-term contract electricity quantity, the electricity selling company should refund or deduct the amount of electricity charges to the user according to the time-of-use electricity price in the day-ahead market, because the actual electricity quantity used by the user is less than the medium- and long-term contract stipulation and the user has overpaid the electricity charges, so corresponding adjustments need to be made.

[0090] Among them, due to the difference between the day-ahead market trading plan and the baseline load in terms of electricity quantity, if the winning bid electricity quantity in the day-ahead market is greater than the originally scheduled baseline load, it means that the electricity quantity obtained in the day-ahead market exceeds the originally expected load demand, and there may be surplus electricity available for allocation on the power generation side; if the winning bid electricity quantity in the day-ahead market is less than the originally scheduled baseline load, the electricity quantity obtained through day-ahead market trading cannot meet the expected load demand, which means that additional electricity needs to be sought to ensure the balance of power supply and demand. Multiply the difference between the winning bid electricity quantity in the day-ahead market and the originally scheduled baseline load by the real-time electricity price to obtain the cost that the user needs to pay for purchasing electricity to make up the electricity gap or the amount of electricity charges that the electricity selling company should refund or deduct to the user. And subtract this part of the amount from the difference obtained in the previous step to finally get the profit of the electricity selling company for this user.

[0091] Among them, the revenue of the electricity sales company before load adjustment is calculated based on the above data. The method for calculating the revenue of the electricity sales company before load adjustment is the same as that for calculating the revenue of the electricity sales company before load adjustment, but the baseline load of the user needs to be adjusted to the actual load after adjustment.

[0092] Specifically, the first electricity sales revenue satisfies the following formula:

[0093]

[0094] Among them, profit0 is the first electricity sales revenue, P i 0 is the retail contract electricity price, is the base load, P i m is the medium- and long-term contract electricity price, is the medium- and long-term contract electricity quantity, P i da is the time-of-use electricity price in the day-ahead market, is the winning electricity quantity in the day-ahead market, is the spot electricity price, m is the number of users corresponding to the electricity sales entity, and i is any one of the users corresponding to the electricity sales entity;

[0095] The second electricity sales revenue satisfies the following formula:

[0096]

[0097] Among them, profit1 is the second electricity sales revenue, is the actual load.

[0098] Among them, the first electricity sales revenue is obtained by adding up the revenues of each retail user before adjustment agented by the electricity sales company.

[0099] Among them, after calculating the first electricity sales revenue, as the electricity sales company is at the electricity sales end of the power market, in order to optimize operating costs, increase revenues, and cooperate with grid dispatching, etc., it will initiate a load adjustment invitation to retail users. For example, under the peak-valley electricity price mechanism, the electricity sales company starts the invitation process during peak electricity consumption periods and initiates an invitation to retail users to reduce their electricity loads. After retail users evaluate their own electricity consumption situations and confirm, they will perform load adjustment operations at the agreed time after accepting the invitation.

[0100] Among them, after the invitation execution ends, the electricity sales revenue after adjustment is calculated based on the actual load after adjustment, and the second electricity sales revenue is obtained by adding up the revenues of each retail user after adjustment agented by the electricity sales company.

[0101] It can be seen that in the embodiments of the present application, the finally obtained electricity sales revenue comprehensively considers factors such as the user's baseline load, medium- and long-term contract electricity quantity and price, day-ahead market transactions, and real-time balancing market adjustments, and can more accurately reflect the actual revenue situation of the electricity sales company in the process of providing power services to users.

[0102] At the same time, when the user increases or decreases the controllable load, the revenue of the electricity sales company can be adjusted. Generating a load regulation strategy based on this revenue is beneficial to stimulating the potential of users to participate in the regulation of the spot market.

[0103] S220. Determine the adjustment direction strategy for the user to participate in load regulation.

[0104] Among them, the adjustment direction strategy is determined according to the difference between the predicted spot electricity price and the current retail electricity price. Specifically, if the predicted spot electricity price is higher than the retail electricity price, the electricity sales company can encourage the user to reduce electricity consumption during the period with a high spot electricity price and transfer the electricity consumption to the low-price period to avoid electricity consumption during the high-price period and reduce the electricity cost. At the same time, the electricity sales company can purchase less electricity during the high-price period to reduce the purchase cost.

[0105] Among them, if the predicted spot electricity price is lower than the retail electricity price, it is recommended that the user increase electricity consumption during this period to reduce the overall electricity cost by using low-price electricity.

[0106] Among them, the adjustment direction strategy can also be determined through the difference between the first electricity sales revenue and the second electricity sales revenue. Specifically, the difference is (P i 0 -P i rt )×ΔQ, where ΔQ is the load adjusted by the user. If the second electricity sales revenue is greater than the first electricity sales revenue, the electricity sales company can encourage the user to reduce electricity consumption during the period with a high spot electricity price and transfer the electricity consumption to the low-price period to avoid electricity consumption during the high-price period and reduce the electricity cost. At the same time, the electricity sales company can purchase less electricity during the high-price period to reduce the purchase cost.

[0107] Among them, if the second electricity sales revenue is lower than the first electricity sales revenue, it is recommended that the user increase electricity consumption during this period to reduce the overall electricity cost by using low-price electricity.

[0108] S230. Determine the first regulation revenue of the user under the adjustment direction strategy.

[0109] Among them, please refer to Figure 3 , Figure 3 is a schematic flowchart of a method for determining the regulation revenue provided by the embodiments of the present application. As Figure 3 shown, it includes the following steps:

[0110] S310. Determine the controllable regulation load of the user under the adjustment direction strategy.

[0111] Among them, the controllable adjustable load is determined according to the adjusted actual load and the base load. Specifically, the difference between the adjusted actual load and the base load is the controllable adjustable load.

[0112] In a possible embodiment, the historical electricity consumption data of the user is analyzed to understand the user's electricity consumption pattern and load characteristics, and the adjustable part is found. For example, some industrial users may have some equipment that can flexibly adjust the operation time during non-production peak periods, or commercial users can turn off some non-essential lighting and equipment at night, and these all belong to the controllable adjustable load.

[0113] Among them, the characteristics of the user's equipment can also be evaluated to understand the characteristics of the electricity-consuming equipment used by the user. Different types of equipment have different adjustment capabilities. For example, some refrigeration equipment can achieve load adjustment by adjusting the temperature setting value or operation time, while some production equipment may need to be comprehensively evaluated according to the production process to determine the adjustable range without affecting the production quality. The electricity sales company can establish a user equipment file and record and analyze the adjustment characteristics of various types of equipment in detail.

[0114] Furthermore, the controllable adjustable load can be adaptively adjusted according to the data obtained from the above analysis and evaluation.

[0115] S320, obtain the spot electricity price predicted by the electricity sales entity; and, obtain the retail contract electricity price signed by the electricity sales entity and the user; and, obtain the base load of the user.

[0116] S330, determine the sharing ratio for the electricity sales entity to incentivize the user according to the spot electricity price and the retail contract electricity price.

[0117] Among them, when the spot electricity price is greater than the retail contract electricity price, it is the first sharing ratio, and when the spot electricity price is less than the retail contract electricity price, it is the second sharing ratio, and the first sharing ratio is less than the second sharing ratio.

[0118] Specifically, the first sharing ratio or the second sharing ratio can be set differently. For example, the sharing ratio can be determined according to the revenue difference before and after adjustment. Each revenue difference corresponds to a preset revenue range, and each preset revenue range corresponds to a sharing ratio. The greater the revenue difference, the higher the sharing ratio.

[0119] Specifically, the sharing ratio can be determined according to the user type and the user's response ability. For example, for industrial users who can reduce the load by more than 30% during peak hours, the sharing ratio can be set at 40%; for commercial users who can reduce the load by 10%-20%, the sharing ratio is 30%; for residential users with a relatively high participation rate, the sharing ratio is 10%-20%. The specific ratio can be adjusted according to the actual situation and the company's strategy.

[0120] S340, determine the first regulation revenue according to the controllable regulated load, the spot electricity price, the retail contract electricity price, the sharing ratio, and the base load.

[0121] Specifically, first calculate the difference between the predicted spot electricity price and the retail contract electricity price, then calculate the product of this difference and the user's controllable regulated load to obtain the revenue earned by the power selling company due to the user's participation in regulation. Furthermore, calculate the product of this revenue and the sharing ratio of the power selling company to obtain the revenue earned by the user due to load reduction and reduced electricity costs. At the same time, add the cost generated by the user's actual electricity consumption settled at the real-time electricity price after load regulation to obtain the load revenue sharing provided by the power selling company.

[0122] In a possible embodiment, the first regulation revenue satisfies the following formula:

[0123] where profit is the first regulation revenue, P i 0 is the retail contract electricity price, P i rt is the spot electricity price, ΔQ is the controllable regulated load, α is the sharing ratio, is the base load.

[0124] Specifically, the load revenue sharing provided by the power selling company includes the revenue sharing for load reduction and the revenue sharing for load increase. Among them, if the predicted spot electricity price is higher than the retail electricity price, the user participates in regulation by reducing the load, and the power selling company provides the revenue sharing for load reduction. The first regulation revenue satisfies the following formula:

[0125] where Profit Reduce 2 is the first regulation revenue under the revenue sharing for load reduction. Among them, the first regulation revenue is obtained from the total reduced electricity bill and the sharing of the power selling company. In this context, the willingness of retail users to reduce the load is relatively strong.

[0126] Among them, if the predicted spot electricity price is lower than the retail electricity price, the user participates in regulation by increasing the load, and the power selling company provides the revenue sharing for load increase. The first regulation revenue satisfies the following formula:

[0127] Among them, Profit Increase 2 is the first adjustment benefit under the ascending load revenue sharing. The benefit is affected by the increase in the total electricity cost caused by the ascending load. In this context, the willingness of retail users to increase the load is highly affected by the sharing ratio of the electricity selling company.

[0128] It can be seen that in the embodiment of the present application, by evaluating the user response space based on the user adjustment benefit of the electricity selling company's sharing model, it is beneficial to dynamically adjust the load regulation strategy in real time.

[0129] S240. Determine the load regulation strategy according to the first electricity selling benefit, the second electricity selling benefit, the adjustment direction strategy, and the first adjustment benefit.

[0130] Among them, please refer to Figure 4 , Figure 4 is a schematic flowchart of another method for formulating a load regulation strategy provided by the embodiment of the present application. As Figure 4 shown, it includes the following steps:

[0131] S410. Determine the difference between the first electricity selling benefit and the second electricity selling benefit.

[0132] Among them, the difference between the first electricity selling benefit and the second electricity selling benefit includes multiple differences. A single difference refers to the change in the benefit of the electricity selling company caused by a single retail user's load regulation.

[0133] S420. Adjust the first adjustment benefit according to the difference to obtain the second adjustment benefit.

[0134] Among them, the second adjustment benefit is the maximum benefit that can be achieved based on the user's response potential.

[0135] Among them, according to the difference between the first electricity selling benefit and the second electricity selling benefit, look up the adjustment coefficient. Each difference corresponds to a threshold range, and each threshold range corresponds to an adjustment coefficient. Through this adjustment coefficient, the user's benefit is maximized to obtain the second adjustment benefit.

[0136] Among them, the types of users represented by the electricity selling company are rich, and the load characteristics are significantly different. It includes both fixed loads with fixed production time and relatively stable electricity consumption, and variable loads that can adjust their electricity consumption behaviors according to electricity prices and incentive signals. Exploring the potential of variable loads and carrying out demand-side response can optimize the allocation of power resources and meet the needs of different users.

[0137] S430. Determine the first adjustment strategy according to the second adjustment benefit.

[0138] Among them, please refer to Figure 5 , Figure 5It is a schematic flowchart of a method for determining an adjustment strategy provided by an embodiment of the present application. As Figure 5 shown, it includes the following steps:

[0139] S510, obtain the historical electricity consumption data and historical electricity price data of the user; and obtain the current electricity price fluctuation range.

[0140] Among them, the historical electricity consumption data may include information such as electricity quantity information, electricity consumption time information, and electricity load information. Specifically, the electricity quantity information includes the total electricity consumption, that is, the total amount of electric energy consumed by the user within a specific time period, in kilowatt-hours, reflecting the user's electricity consumption scale and overall electricity demand.

[0141] Among them, the electricity quantity information also includes the electricity consumption in different time periods, which is the electricity consumption statistics according to different time intervals, such as hourly, daily, weekly, monthly, etc. For example, industrial users may have a relatively large electricity consumption during the day on weekdays, while residential users have a relatively high electricity consumption at night and on weekends. By analyzing the electricity consumption in different time periods, the user's electricity consumption behavior pattern and load characteristics can be understood.

[0142] Among them, the electricity quantity information also includes the electricity consumption of different electrical equipment, that is, the power consumption of different types of electrical equipment, such as air conditioners, refrigerators, lighting equipment, production equipment, etc.

[0143] Among them, the electricity consumption time information includes the start time and end time of electricity consumption, recording the start and end moments of each electricity consumption of the user, which can reflect the user's electricity consumption habits and preferences for electricity consumption periods. For example, some users may be accustomed to using electrical appliances intensively at night, while some users use more during the day working hours.

[0144] Among them, the electricity consumption time information may also include the electricity consumption duration, that is, the length of each electricity consumption process. For some high-power equipment, the length of the electricity consumption duration will have different degrees of impact on the power grid load.

[0145] Among them, the electricity load information includes the maximum load, which is the maximum electric power reached when the user's electrical equipment runs simultaneously within a certain time period, in kilowatts. It reflects the maximum demand of the user for the power grid's power supply capacity and is of great significance for the planning and operation scheduling of the power system.

[0146] Among them, the electricity load information may also include the average load to understand the user's general electricity consumption level and be used to evaluate the user's electricity consumption stability.

[0147] Among them, the electricity load information may also include the load curve, which is a curve plotted with time as the horizontal axis and load power as the vertical axis, intuitively showing the load change of the user at different moments. The load curve can help the power selling company analyze the user's electricity consumption pattern and predict future load demand.

[0148] Among them, the historical electricity price data includes information such as different types of electricity prices, electricity price adjustment records, and regional electricity price differences.

[0149] Among them, different types of electricity prices can include catalog electricity prices, time-of-use electricity prices, real-time electricity prices, etc. Among them, the catalog electricity price refers to the price at which the power grid enterprise sells electric energy to users, which is usually formulated by relevant government departments and varies according to factors such as user types and voltage levels.

[0150] Among them, the time-of-use electricity price means that a day is divided into different time periods, such as peak hours, valley hours, and flat periods, and different electricity prices are implemented in each period. The time-of-use electricity price aims to guide users to reasonably adjust their electricity consumption time, cut peaks and fill valleys, and improve the operating efficiency of the power system.

[0151] Among them, the real-time electricity price refers to the electricity price that dynamically changes according to the real-time supply and demand situation of the power system in the electricity market environment.

[0152] Among them, the electricity price adjustment records include information such as adjustment time, adjustment range, and adjustment reasons. Record the specific date and time of each electricity price adjustment to analyze the time series characteristics of electricity price changes. Clarify the increase or decrease range of electricity prices in different periods, which directly affects the electricity consumption cost and the electricity sales revenue. Among them, the adjustment reasons include factors such as policy changes, adjustment of market supply and demand relations, and fluctuations in energy costs. Understanding the reasons for electricity price adjustments helps to predict future electricity price trends.

[0153] Among them, the regional electricity price difference can indicate the electricity prices in different regions. Due to different factors such as the power resource status, power grid construction costs, and economic development levels in different regions, there will also be differences in electricity prices. The historical electricity price data will include the electricity price information of the user's location and surrounding areas for comparison and analysis.

[0154] Among them, the electricity sales company can obtain the electricity price data in different periods from the platform. By comparing the current electricity price with the electricity price in the same period of history or the previous trading period, the electricity price fluctuation range can be calculated. For example, the day-ahead market can provide the electricity prices of each period of the next day one day in advance. The electricity sales company can compare it with the actual electricity price of the current day to analyze the fluctuation situation; the real-time market is close to the real-time operating state of the system and can reflect the electricity price under the real-time balance of electricity and the safe operation of the power grid, and can be used to monitor the short-term fluctuations of the electricity price in real time.

[0155] S520, determine the revenue threshold of the user according to the historical electricity consumption data, the historical electricity price data, and the electricity price fluctuation range.

[0156] Among them, the system will determine the fluctuation situation between the spot electricity price and the retail electricity price according to the historical electricity price data described above, calculate the amplitude and trend of the electricity price fluctuation, and identify the periodic characteristics and sudden fluctuation events of the electricity price fluctuation. According to the historical electricity consumption data and the electricity price fluctuation law, a dynamic threshold of the user's income is set, and this threshold represents the maximum income that the user can achieve within a specific time period. This threshold is dynamically adjusted according to the amplitude of the real-time electricity price fluctuation to ensure that it can reflect the maximum income potential of the user under different market conditions.

[0157] Specifically, by analyzing the user's historical electricity consumption data and historical electricity price data, the average income and standard deviation under different time periods and electricity price fluctuation conditions are calculated. When setting the dynamic threshold, it can be set by adding or subtracting a certain standard deviation from the average income. For example, the threshold can be the average income plus or minus a certain multiple of the standard deviation, and the exemplary multiple can be 1.5.

[0158] Specifically, determine the multiple and operation method according to the current amplitude of the electricity price fluctuation.

[0159] In a possible embodiment, an optimal load regulation scheme can also be solved using a dynamic programming algorithm based on the user's income function and the dynamic characteristics of the electricity price fluctuation. The dynamic programming decomposes the calculation of the user's income into multiple time periods and adjusts the threshold according to the electricity price fluctuation situation to maximize the total income of the user in each time period.

[0160] In a possible embodiment, personalized income thresholds can also be set according to the user's electricity consumption behavior and load response characteristics. Methods such as cluster analysis can be used to divide users into different groups, and different dynamic thresholds are set for each group. For example, for users with high electricity consumption and sensitive to electricity price fluctuations, a lower threshold is set to trigger load regulation earlier; for users with low electricity consumption or insensitive to electricity price fluctuations, a higher threshold is set to avoid frequent adjustments.

[0161] S530, determine the first regulation strategy according to the income threshold and the second regulation income.

[0162] Among them, compare the income threshold and the second regulation income. When the second regulation income is greater than the income threshold, that is, when the expected income of the current user is higher than the set dynamic threshold, generate the first regulation strategy according to the second regulation income. When the second regulation income is less than the income threshold, that is, when the expected income of the current user is lower than the set dynamic threshold, generate the first regulation strategy according to the income threshold.

[0163] Among them, the first adjustment strategy provides power consumption adjustment suggestions to users according to the electricity price fluctuation trend or the user's revenue potential space, accurately identifies the adjustment time period of the user and the maximum load that can be adjusted in each adjustment time period, so as to maximize the user's revenue and optimize the revenue of the electricity sales company in the spot market.

[0164] S440. Determine the load adjustment strategy according to the first adjustment strategy and the adjustment direction strategy.

[0165] Among them, the load adjustment strategy includes a real-time electricity price plan, an optimized contract package design, an accurate incentive strategy, and a strategy for configuring energy storage devices.

[0166] Specifically, the load adjustment target can be set according to the electricity sales revenue after the load adjustment of the electricity sales company, such as reducing the load during peak hours, increasing the load rate during off-peak hours, optimizing the shape of the overall load curve, reducing the risk of grid congestion, and improving the grid operation efficiency. At the same time, combined with the business objectives of the electricity sales company and market demand, determine the revenue-related objectives, such as maximizing the electricity sales revenue or minimizing the cost on the premise of meeting the grid operation requirements.

[0167] Among them, referring to the load adjustment target, according to the first adjustment strategy and the adjustment direction strategy, a flexible and diverse electricity price plan can be formulated, and a reasonable electricity price level can be set to encourage users to increase electricity consumption when the electricity price is low and reduce electricity consumption when the electricity price is high, so as to guide users to adjust their electricity consumption behavior.

[0168] Among them, the contract package design can also be optimized to design customized contract packages for different users. For example, for users with stable electricity loads but certain sensitivity to electricity prices, design a package based on a combination of fixed electricity prices and time-of-use electricity prices, which can ensure the stability of users' electricity consumption while motivating them to adjust the load to a certain extent through time-of-use electricity prices; for users with large load fluctuations and high sensitivity to electricity prices, design a package based on real-time electricity prices, enabling users to flexibly adjust their electricity consumption behavior according to market electricity price changes, and the electricity sales company can also better guide users' load adjustment.

[0169] At the same time, according to electricity price forecasts and users' electricity consumption characteristics, the electricity sales company can sign interruptible load contracts with some users. When the market electricity price is high or the grid load is tight, the electricity sales company can, in accordance with the contract agreement, give users a certain economic compensation and require users to interrupt some non-critical loads, so as to achieve rapid adjustment of the grid load and save the electricity purchase cost for the electricity sales company at the same time.

[0170] Furthermore, according to the first adjustment strategy and the adjustment direction strategy, the electricity selling company can also communicate with users in advance before the electricity price is about to increase or the grid load is about to reach the peak, inform users of the upcoming electricity price changes and load adjustment requirements, so that users have enough time to make preparations, such as adjusting production plans, arranging equipment operation times, etc., to improve the timeliness and effectiveness of demand response.

[0171] Furthermore, according to the first adjustment strategy and the adjustment direction strategy, the electricity selling company can also achieve precise incentives, and provide precise economic incentive measures for users according to the sensitivity of different users to electricity prices and their load adjustment capabilities. For users who can effectively reduce the load during high electricity price periods, higher rewards or compensations are given to encourage more users to actively participate in demand response and achieve effective load regulation.

[0172] Furthermore, according to the first adjustment strategy and the adjustment direction strategy, the electricity selling company can reasonably allocate energy storage devices. When the electricity price is low, use the energy storage devices to store electrical energy, and when the electricity price is high or the grid load is tight, release the electrical energy in the energy storage devices to meet part of the user's electricity demand, thereby reducing dependence on the grid and also reducing the electricity purchase cost. For example, for some commercial users or industrial parks, equip a certain scale of energy storage devices, optimize the charge and discharge management, and achieve load peak shaving and valley filling. For users with distributed power sources, the electricity selling company can optimize the access and operation methods of the distributed power sources. When the electricity price is high, encourage the distributed power sources to generate more electricity and supply it to the grid; when the electricity price is low, appropriately reduce the power generation of the distributed power sources and give priority to using grid power to achieve the coordinated operation of the distributed power sources and the grid, improve the energy utilization efficiency and overall economic benefits, and also help to regulate the grid load.

[0173] It can be seen that in the embodiments of the present application, the revenue and market competitiveness of the electricity selling company are improved, the market risk is reduced, the response awareness of users is enhanced, and the safety and reliability of the power system are guaranteed.

[0174] It can be seen that in the embodiments of the present application, the adjustment direction is clarified, and the revenue potential space of users in this adjustment direction is identified. Through the combination of the revenue potential space of users, the change in the electricity selling revenue of the electricity selling company and the adjustment direction, it is beneficial for the electricity selling company to formulate real-time and effective load dispatching strategies, fully stimulate the adjustment potential of users, convert the user load into tradable market-oriented resources, and achieve optimal resource allocation and cost-benefit improvement.

[0175] Consistent with the above embodiments, please refer to Figure 6 , Figure 6 is the functional unit composition block diagram of a device for formulating a load adjustment strategy provided by the embodiments of the present application, as Figure 6As shown in the figure, the device 60 for formulating a load regulation strategy includes: a first determination unit 61, configured to determine a first power sales revenue of the power seller before load regulation and a second power sales revenue after load regulation; a second determination unit 62, configured to determine an adjustment direction strategy for the user to participate in load regulation; a third determination unit 63, configured to determine a first regulation revenue of the user under the adjustment direction strategy; and a fourth determination unit 64, configured to determine a load regulation strategy according to the first power sales revenue, the second power sales revenue, the adjustment direction strategy, and the first regulation revenue.

[0176] In a possible embodiment, in terms of determining the first regulation revenue of the user under the adjustment direction strategy, the third determination unit 63 is specifically configured to: determine a controllable regulation load of the user under the adjustment direction strategy; obtain the spot electricity price predicted by the power seller; obtain the retail contract electricity price signed between the power seller and the user; obtain the base load of the user; determine a sharing ratio for the power seller to incentivize the user according to the spot electricity price and the retail contract electricity price; and determine the first regulation revenue according to the controllable regulation load, the spot electricity price, the retail contract electricity price, the sharing ratio, and the base load.

[0177] In a possible embodiment, the first regulation revenue satisfies the following formula:

[0178] where profit is the first regulation revenue, P i 0 is the retail contract electricity price, P i rt is the spot electricity price, ΔQ is the controllable regulation load, α is the sharing ratio, and

[0179] In a possible embodiment, in terms of determining a load regulation strategy according to the first power sales revenue, the second power sales revenue, the adjustment direction strategy, and the first regulation revenue, the fourth determination unit 64 is specifically configured to: determine the difference between the first power sales revenue and the second power sales revenue; adjust the first regulation revenue according to the difference to obtain a second regulation revenue; determine a first regulation strategy according to the second regulation revenue; and determine the load regulation strategy according to the first regulation strategy and the adjustment direction strategy.

[0180] In a possible embodiment, in determining the first adjustment strategy according to the second adjusted revenue, the fourth determination unit 64 is further specifically configured to: obtain the historical electricity consumption data and historical electricity price data of the user; and obtain the current electricity price fluctuation range; determine the revenue threshold of the user according to the historical electricity consumption data, the historical electricity price data and the electricity price fluctuation range; and determine the first adjustment strategy according to the revenue threshold and the second adjusted revenue.

[0181] In a possible embodiment, in determining the first electricity sales revenue of the electricity seller before load adjustment and the second electricity sales revenue after load adjustment, the first determination unit 61 is further specifically configured to: obtain the retail contract electricity price, medium- and long-term contract electricity price, and medium- and long-term contract electricity volume signed by the electricity seller and the user; and obtain the base load of the user and the actual load after load adjustment; and obtain the day-ahead market time-of-use electricity price and the day-ahead market winning bid electricity volume of the electricity seller; and obtain the spot electricity price predicted by the electricity seller; determine the first electricity sales revenue according to the retail contract electricity price, the medium- and long-term contract electricity price, the medium- and long-term contract electricity volume, the base load, the day-ahead market time-of-use electricity price, the day-ahead market winning bid electricity volume and the spot electricity price; and determine the second electricity sales revenue according to the retail contract electricity price, the medium- and long-term contract electricity price, the medium- and long-term contract electricity volume, the actual load, the day-ahead market time-of-use electricity price, the day-ahead market winning bid electricity volume and the spot electricity price.

[0182] In a possible embodiment, the first electricity sales revenue satisfies the following formula:

[0183]

[0184] where profit0 is the first electricity sales revenue, P i 0 is the retail contract electricity price, is the base load, P i m is the medium- and long-term contract electricity price, is the medium- and long-term contract electricity volume, P i da is the day-ahead market time-of-use electricity price, is the day-ahead market winning bid electricity volume, is the spot electricity price, m is the number of users corresponding to the electricity seller, and i is any one of the users corresponding to the electricity seller;

[0185] The second electricity sales revenue satisfies the following formula:

[0186]

[0187] wherein, profit1 is the second electricity sales revenue, is the actual load.

[0188] It can be understood that since the method embodiments and the device embodiments are different presentation forms of the same technical concept, the content of the method embodiments in this application should be synchronously adapted to the device embodiments, which will not be elaborated here.

[0189] In the case of adopting an integrated unit, please refer to Figure 7 , Figure 7 is the functional unit composition block diagram of another load regulation strategy formulation device provided by the embodiments of the present application. As Figure 7 shown, the load regulation strategy formulation device 60 includes: a processing module 602 and a communication module 601. The processing module 602 is used to control and manage the actions of the load regulation strategy formulation device 60. For example, it executes the steps of the first determination unit 61, the second determination unit 62, the third determination unit 63, and the fourth determination unit 64, and / or is used to execute other processes of the technologies described herein. The communication module 601 is used for the interaction between the load regulation strategy formulation device 60 and other devices. As Figure 7 shown, the load regulation strategy formulation device 60 may further include a storage module 603, and the storage module 603 is used to store the program code and data of the load regulation strategy formulation device 60.

[0190] Wherein, the processing module 602 can be a processor or a controller. For example, it can be a central processing unit (CPU), a general-purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute various exemplary logic blocks, modules, and circuits described in combination with the disclosure of the present application. The processor can also be a combination that realizes computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, and so on. The communication module 601 can be a transceiver, an RF circuit, or a communication interface, etc. The storage module 603 can be a memory.

[0191] Wherein, all relevant contents of each scenario involved in the above method embodiments can be cited in the function descriptions of the corresponding functional modules, which will not be elaborated here. The above load regulation strategy formulation device 60 can execute the above Figure 2The method for formulating the load regulation strategy shown

[0192] Please refer to Figure 8 , Figure 8 which is a schematic structural diagram of an electronic device proposed in an embodiment of the present application. As Figure 8 shown, the electronic device 800 includes a processor 810, a memory 820, a communication interface 830, and one or more programs 821. The above one or more programs 821 are stored in the above memory and are configured to be executed by the above processor. When the program is executed, it includes some or all of the steps of any method for formulating the load regulation strategy described in the above method embodiment. The processor, the memory, and the communication interface are interconnected and complete the communication work with each other.

[0193] Among them, the memory can be a volatile memory such as a dynamic random access memory (DRAM), or a non-volatile memory such as a mechanical hard disk. The above memory is used to store a set of executable program codes, and the above processor is used to call the executable program codes stored in the memory and can execute some or all of the steps of any method for formulating the load regulation strategy described in the above method embodiment for formulating the load regulation strategy.

[0194] It can be seen that for the electronic device 800 described in the embodiment of the present application, first, the first power sales revenue of the power sales entity before load regulation and the second power sales revenue after load regulation are determined; then, the adjustment direction strategy for the user to participate in load regulation is determined; then, the first adjustment revenue of the user under the adjustment direction strategy is determined; finally, according to the first power sales revenue, the second power sales revenue, the adjustment direction strategy, and the first adjustment revenue, the load regulation strategy is determined. The present application clarifies the adjustment direction and identifies the revenue potential space of the user in this adjustment direction. By combining the revenue potential space of the user, the change in the power sales revenue of the power sales company, and the adjustment direction, it is beneficial for the power sales company to formulate a real-time and effective load allocation strategy, fully stimulate the adjustment potential of the user, convert the user load into a tradable market-oriented resource, and achieve optimal resource allocation and cost-benefit improvement.

[0195] The embodiment of the present application also provides a computer storage medium. Among them, the computer storage medium stores a computer program for electronic data exchange, and the computer program enables the computer to execute some or all of the steps of any method described in the above method embodiment. The above computer includes an electronic device.

[0196] The embodiments of the present application also provide a computer program product. The computer program product includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute some or all of the steps of any of the methods described in the foregoing method embodiments. The computer program product may be a software installation package, and the computer includes an electronic device.

[0197] It should be noted that, for the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should know that the present application is not limited by the described action sequence, because according to the present application, some steps may be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily essential to the present application.

[0198] In the above embodiments, the descriptions of the respective embodiments have their own emphases. For the parts not detailed in a certain embodiment, reference may be made to the relevant descriptions of other embodiments.

[0199] In several embodiments provided by the present application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are merely 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 coupling or direct coupling or communication connection between each other can be through some interfaces. The indirect coupling or communication connection of the device or unit can be in an electrical or other form.

[0200] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they may be located in one place, or may be distributed to 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.

[0201] In addition, in each embodiment of the present application, the functional units can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above integrated unit can be implemented in the form of hardware or in the form of a software program module.

[0202] When the integrated unit is implemented in the form of a software program module and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of this application. The aforementioned memory includes various media that can store program codes, such as USB flash drives, read-only memories (ROM), random access memories (RAM), mobile hard disks, magnetic disks, or optical discs.

[0203] Those of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing relevant hardware through a program. This program can be stored in a computer-readable memory, and the memory can include: flash drives, read-only memories, random access memories, magnetic disks, or optical discs, etc.

[0204] The above has introduced the embodiments of this application in detail. Specific examples are used in this article to elaborate on the principles and embodiments of this application. The description of the above embodiments is only used to help understand the method and its core idea of this application; at the same time, for those of ordinary skill in the art, according to the idea of this application, there will be changes in the specific embodiments and application scopes. In summary, the content of this specification should not be construed as a limitation to this application.

Claims

1. A method for formulating a load regulation strategy, characterized in that, Including: Determine the first electricity sales revenue of the electricity seller before load regulation and the second electricity sales revenue after load regulation; Determine the adjustment direction strategy for the user to participate in load regulation; Determine the first regulation revenue of the user under the adjustment direction strategy; Determine the load regulation strategy according to the first electricity sales revenue, the second electricity sales revenue, the adjustment direction strategy, and the first regulation revenue.

2. The method according to claim 1, characterized in that, The determining the first regulation revenue of the user under the adjustment direction strategy includes: Determine the controllable regulated load of the user under the adjustment direction strategy; Obtain the spot electricity price predicted by the electricity seller; and, obtain the retail contract electricity price signed between the electricity seller and the user; and, obtain the base load of the user; Determine the sharing ratio for the electricity seller to incentivize the user according to the spot electricity price and the retail contract electricity price; Determine the first regulation revenue according to the controllable regulated load, the spot electricity price, the retail contract electricity price, the sharing ratio, and the base load.

3. The method according to claim 2, wherein The first regulation revenue satisfies the following formula: where profit is the first regulated revenue, P i 0 is the retail contract electricity price, P i rt is the spot electricity price, ΔQ is the controllable regulated load, and α is the sharing ratio, is the base load.

4. The method according to claim 1, characterized in that The determining the load regulation strategy according to the first electricity sales revenue, the second electricity sales revenue, the adjustment direction strategy, and the first regulation revenue includes: Determine the difference between the first electricity sales revenue and the second electricity sales revenue; Adjust the first regulation revenue according to the difference to obtain the second regulation revenue; Determine the first regulation strategy according to the second regulation revenue; Determine the load regulation strategy according to the first regulation strategy and the adjustment direction strategy.

5. The method according to claim 4, characterized in that, The determining the first regulation strategy according to the second regulation revenue includes: Obtain the historical electricity consumption data and historical electricity price data of the user; and, obtain the current electricity price fluctuation range; Determine the revenue threshold of the user according to the historical electricity consumption data, the historical electricity price data, and the electricity price fluctuation range; Determine the first regulation strategy according to the revenue threshold and the second regulation revenue.

6. The method according to claim 1, wherein The determining the first electricity sales revenue of the electricity seller before load regulation and the second electricity sales revenue after load regulation includes: Obtain the retail contract electricity price, medium- and long-term contract electricity price, and medium- and long-term contract electricity volume signed between the electricity seller and the user; and, obtain the base load of the user and the actual load after load regulation; and, obtain the day-ahead market time-of-use electricity price and the day-ahead market winning bid electricity volume of the electricity seller; and, obtain the spot electricity price predicted by the electricity seller; Determine the first electricity sales revenue according to the retail contract electricity price, the medium- and long-term contract electricity price, the medium- and long-term contract electricity volume, the base load, the day-ahead market time-of-use electricity price, the day-ahead market winning bid electricity volume, and the spot electricity price; Determine the second electricity sales revenue according to the retail contract electricity price, the medium- and long-term contract electricity price, the medium- and long-term contract electricity volume, the actual load, the day-ahead market time-of-use electricity price, the day-ahead market winning bid electricity volume, and the spot electricity price.

7. The method according to claim 6, wherein The first electricity sales revenue satisfies the following formula: Among them, profit0 is the first electricity sales revenue, P i 0 is the retail contract electricity price, is the base load, P i m is the medium- and long-term contract electricity price, is the medium- and long-term contract electricity quantity, P i da is the day-ahead market time-of-use electricity price, is the day-ahead market winning bid electricity quantity, is the spot electricity price, m is the number of users corresponding to the electricity seller, and i is any one of the users corresponding to the electricity seller; The second electricity sales revenue satisfies the following formula: wherein, profit1 is the second electricity selling revenue, is the actual load.

8. An apparatus for formulating a load regulation strategy, characterized in that Including: A first determination unit, configured to determine a first electricity sales revenue of the electricity seller before load regulation and a second electricity sales revenue after load regulation; A second determination unit, configured to determine an adjustment direction strategy for the user to participate in load regulation; A third determination unit, configured to determine a first regulation revenue of the user under the adjustment direction strategy; A fourth determination unit, configured to determine a load regulation strategy according to the first electricity sales revenue, the second electricity sales revenue, the adjustment direction strategy, and the first regulation revenue.

9. An electronic device, characterized in that, The device includes: A memory, a processor, and executable program code stored on the memory and executable on the processor, wherein when the processor executes the executable program code, it executes the steps of the method for formulating a load regulation strategy according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, Executable program code is stored on the computer-readable storage medium, and the executable program code includes execution instructions for executing the steps of the method for formulating a load regulation strategy according to any one of claims 1-7.

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