A bidding device and method for assisting individual power consumers to participate in a power market

Abstract

The application discloses a kind of devices and methods for assisting individual power users to participate in power market quotation, device includes data input module: the type of power market that individual power user participates in is input, the transaction period under the type of participation, the power that each transaction period participates in;Data storage module is arranged by device operator, in networked state, daily update operator issued market information and user information by each device;Data analysis module: for the certain power market of certain time scale of individual power user, carry out the analysis of suggested quotation based on the historical transaction information of power market and the analysis of suggested quotation based on the historical transaction result of individual power user;Data output module: the result obtained by data analysis module, the visualized suggested quotation output for user reference, weaken the hindrance of individual power user participating in power market, promote its enthusiasm of participating in power market transaction, promote demand side resource to participate in power market, guarantee the safe and stable operation of power system.

Description

Technical Field

[0001] This invention relates to the field of electricity market trading technology, and in particular to a device and method for assisting individual electricity users in participating in electricity market bidding. Background Technology

[0002] Currently, with the introduction of "dual carbon" targets and the large-scale integration of new energy sources into the grid, traditional power source resources are often unable to meet the requirements of power system fluctuation mitigation and supply-demand balance. Meanwhile, with the continuous development of demand-side resources, they have gained the ability to participate in the electricity market, and some regions have clearly defined demand-side resources as the main players in electricity trading.

[0003] From the demand side, although individual electricity users have limited ability to support the power grid, their large size gives them significant potential to participate in the market. However, for individual electricity users, a lack of understanding of the electricity market and the inability to make accurate judgments about electricity transactions hinder their participation.

[0004] Therefore, researching a device to assist individual electricity users in bidding, and providing bidding suggestions based on historical electricity market transaction information, can help reduce obstacles to their participation in the electricity market and increase their enthusiasm for participation. This has both theoretical research significance and practical application value. Summary of the Invention

[0005] The problem to be solved by this invention is to provide a bidding device and method to assist individual electricity users in participating in the electricity market, which outputs suggested bids based on historical transaction information of the electricity market and relevant transaction information input by individual electricity users.

[0006] This invention adopts the following technical solution: a bidding device to assist individual electricity users in participating in the electricity market, comprising four parts: a data input module, a data storage module, a data analysis module, and a data output module, as detailed below:

[0007] Data input module: used to collect information and preferences of electricity users, with individual electricity users selecting and inputting data information;

[0008] Data storage module: The information in the module is organized by the bidding device operator. Each bidding device is kept connected to the network and automatically updates and loads the stored information released by the operator, including: market transaction information for the electricity market and user transaction information for individual electricity users;

[0009] Data Analysis Module: For a specific electricity market at a certain time scale, the pricing device analyzes the historical transaction information of the electricity market and the historical transaction results of individual electricity users to obtain two suggested pricing results.

[0010] Data output module: The module outputs a visual suggested price from the two suggested prices obtained from the data analysis module. Individual electricity users can then choose the suggested price and participate in the final price and electricity volume declaration in the electricity market.

[0011] Preferably, the data input module is used to collect user information and intentions, allowing individual electricity users to select the type of electricity market they wish to participate in, the time period for participation, and the corresponding electricity consumption.

[0012] The type of electricity market that individual electricity users choose to participate in is the spot market, which includes intra-provincial day-ahead spot market, inter-provincial day-ahead spot market, intra-provincial real-time spot market, and inter-provincial day-ahead ancillary service market.

[0013] Select the trading period for participating in the electricity market: For the provincial day-ahead spot market on day D, the participation period is t. D-n The smallest time scale is the hour, where n∈[0,24), n∈N, t D-n The period for participating in electricity trading is (n, n+1).

[0014] Preferably, the data storage module is used to store two sets of transaction information: one for the electricity market and one for individual electricity users. The device user needs to maintain an internet connection, and the transaction information will be automatically loaded into the device after being updated via the network at midnight every day.

[0015] The data storage module stores transaction information related to the electricity market, including:

[0016] 1. For D-day, the hourly transaction information of each electricity market within the previous two years shall be based on the official operation time of the market if the electricity market has not been operating for two years; if the hour is not the smallest unit of transaction time, the smallest unit of transaction time shall be used.

[0017] 2. Final clearing prices for each type of electricity market at each time period. Because weather, temperature, renewable energy output, and load electricity consumption are constantly changing, the final clearing price for each hour is a comprehensive reflection of all factors within that hour.

[0018] The data storage module stores transaction information specific to individual electricity users, including:

[0019] 1. For day D, the electricity market transaction information for each hour within the previous two years for this individual electricity user. If the electricity user has participated in the market for less than two years, the length of time in the market shall prevail; if hour is not the smallest unit of time, the smallest unit of time shall prevail.

[0020] 2. The individual electricity user's bid and whether the transaction is completed in each trading session involve the individual electricity user's bidding information. Regardless of whether the electricity market information is public, the information on whether the individual electricity user's bid and transaction are completed is always available.

[0021] Preferably, the data analysis module includes two analysis directions: historical transaction information based on the electricity market and historical transaction results based on individual electricity users.

[0022] Assuming individual electricity users participate on day D-1, and considering the provincial spot market on day D, the minimum trading time scale is the hour, the chosen participation period is a specific hour t on day D. D-n (n∈[0,24),n∈N), where N represents the set of natural numbers.

[0023] The analysis direction based on historical transaction information of the electricity market involves analyzing the transaction information of electricity market clearing prices stored in the storage module, starting from the previous price Pt at a given time. D-n Date Previous Price Pd D-n Historical price Py D-n It consists of three parts.

[0024] Previous price Pt D-n Collect t from storage module D-n The clearing price for the three hours prior to the transaction is P. * t D-n-1 P * t D-n-2 P * t D-n-3 This type of data is for t on that day. D-n The final clearing price three hours before the time, and t D-n At the same time, the weather temperature, renewable energy output, and electricity load were basically similar.

[0025] Because my country implements peak-valley electricity pricing, the period from 8:00 AM to 10:00 PM is peak time, and the period from 10:00 PM to 8:00 AM the following day is valley time. The price Pt prior to the time of day... D-n The analysis and calculations are configured as follows:

[0026]

[0027] It can be seen that when the selected t D-n The time slots are 8:00-9:00 or 22:00-23:00. The first three hours each have distinct peak and trough periods, therefore, there is no previous price Pt for these two time slots. D-n The calculations for these two time periods will be differentiated from those for other time periods in the future.

[0028] Previous Price Pt D-nCollect data from the storage module for the previous 60 trading days (t) of day D. D-n Final clearing price P at time * t D-x-n The closer the trading day of this type of data is to day D, and the closer it is to the weather, temperature, renewable energy output, and electricity load of day D, the stronger its guiding significance will be.

[0029] For the previous price Pd of the date D-n The analysis and calculations are configured as follows:

[0030]

[0031] Historical moment price Py D-n This requires collecting historical data from the storage module for day D, one year ago, and two years ago. Considering that there is no electricity market trading information on weekends or holidays, if there is no trading information for day D one or two years ago, then the nearest trading day D' before day D is selected. Then, select three days before and after day D or D', for a total of seven days (t). D-n The final clearing price at any given moment, P * y -1D-x-n This represents the final clearing price x days before D, one year ago.

[0032] For historical price Py D-n The analysis and calculations are configured as follows:

[0033]

[0034] In summary, the direction of transaction information for electricity market clearing prices, regarding a specific hour t on day D. D-n The first suggested offer is P market-D-n :

[0035]

[0036] Preferably, the analysis direction based on the historical transaction results of individual electricity users involves data analysis of the transaction information of electricity user transaction results stored in the storage module, primarily based on the previous price quote at the specified time (Qt). D-n Previous quote Qd D-n Historical price quotes Qy D-n composition.

[0037] Previous quote from Qt D-n Collect t from storage module D-n The user quotes three hours prior to the time are R. * t D-n-1 R * t D-n-2 R* t D-n-3 and the corresponding market transaction price B * t D-n-1 B * t D-n-2 B * t D-n-3 The reference price is selected based on whether the transaction is completed. If the transaction is completed, the reference price at that moment is the user's current price. If the transaction is not completed, the reference price at that moment is the market transaction price at that moment.

[0038]

[0039] This type of data is for t on that day. D-n User quotes in the three hours prior to the time, compared to t D-n At any given time, the weather temperature, renewable energy output, and electricity load are basically similar, so this type of data has strong guiding significance.

[0040] Therefore, for the previous quote in Qt... D-n The analysis and calculations are configured as follows:

[0041]

[0042] It can be seen that when the selected t D-n The times are 8:00 to 9:00 or 22:00 to 23:00. The first three hours each have different peak and trough periods, so there are no previously quoted prices for these two times. D-n This will distinguish the calculation of these two time periods from other time periods.

[0043] Previous quote Qd D-n It is necessary to collect data from the storage module on the 60 trading days prior to day D. D-n Quotation R at any time * d D-x-n and the corresponding market transaction price B * d D-x-n The reference price is selected based on whether the transaction is completed. If the transaction is completed, the reference price at that moment is the user's current price. If the transaction is not completed, the reference price at that moment is the market transaction price at that moment.

[0044]

[0045] The closer the trading day of this type of data is to day D, and the closer it is to day D's weather conditions, renewable energy output, and electricity load, the stronger its indicative significance. Since my country's electricity market trading is still conducted on weekdays, and not on holidays or weekends, this type of data is collected from the 60 trading days prior to day D to ensure its authenticity and usability. Data closer to day D is more indicative of price trends; therefore, for previous date quotes (Qd)... D-n The analysis and calculations are configured as follows:

[0046]

[0047] Historical moment quotes Qy D-n We need to collect historical data from the storage module for day D, one year ago, and two years ago, including the quote R. * y -1D-x-n Market transaction price B * y -1D-x-n R * y -1D-x-n This represents the individual quote from a user x days prior to date D one year ago, B. * y -1D-x-n This represents the market transaction price x days before D one year ago.

[0048] Similarly, considering that there is no electricity market trading information on weekends or holidays, if there was no trading information on day D one or two years ago, then the nearest trading day D' before day D is selected. The selection is then performed for a total of seven days, including the days before and after day D one or two years ago. D-n The price quote and market transaction price at any given moment. For a given trading session, a reference price is selected based on whether the trade has been completed. If the trade is completed, the reference price for that moment is the user's current price quote; if the trade is not completed, the reference price for that moment is the current market transaction price.

[0049]

[0050] This type of data represents user quotes for relevant dates in previous years, which can reflect the impact of seasonal factors on user quotes. For historical quotes (Qy)... D-n The analysis and calculations are configured as follows:

[0051]

[0052] In summary, regarding the individual electricity user's transaction information, specifically concerning a certain hour t on day D... D-n The second suggested quote is Q user-D-n :

[0053]

[0054] Preferably, the data output module outputs the suggested price result P obtained from the data analysis module based on historical electricity market transaction information. market-D-n Compared with the proposed bid results based on individual electricity users Q user-D-n Users make their own choices and submit their final price and electricity volume declarations to participate in the electricity market.

[0055] The technical solution of this invention also includes a bidding method to assist individual electricity users in participating in the electricity market. Any of the above-mentioned bidding devices for assisting individual electricity users in participating in the electricity market, when submitting price and electricity volume declarations in the electricity market, includes the following steps:

[0056] S1. Collect information and intentions of electricity users, which are selected and input by individual electricity users. This includes: the type of electricity market that the individual electricity user chooses to participate in, the trading period of the electricity market under that type of electricity market, and the amount of electricity to be traded during each trading period.

[0057] S2. The bidding device remains connected to the network and automatically updates and stores the information released by the operator, including: market transaction information for the electricity market and user transaction information for individual electricity users.

[0058] S3. For individual electricity users in a certain electricity market at a certain time scale, based on the historical transaction information of the electricity market and the historical transaction results of the individual electricity users, respectively, perform suggested price analysis to obtain the first suggested price in the direction of transaction information for the electricity market clearing price at a certain hour on day D and the second suggested price in the direction of the individual electricity user's own transaction information.

[0059] S4. Visualize the results of the first and second suggested quotations obtained in step S3 for users to refer to, and allow individual electricity users to make their own selections and participate in the final price and electricity volume declaration in the electricity market.

[0060] The present invention also provides: an electronic device, comprising:

[0061] One or more processors;

[0062] A storage device on which one or more programs are stored;

[0063] When the one or more programs are executed by the one or more processors, the one or more processors implement any of the above-described methods for assisting individual electricity users in participating in the electricity market.

[0064] The present invention also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps in any of the above-mentioned methods for assisting individual electricity users in participating in the electricity market bidding.

[0065] Compared with the prior art, the present invention, employing the above technical solution, has the following technical effects:

[0066] Based on the present invention, a bidding device for assisting individual electricity users in participating in the electricity market allows individual electricity users to input information such as the type of electricity market they wish to participate in, the trading period, and the trading volume. The device combines stored historical electricity market trading information and the individual electricity user's historical trading results, and through the bidding method of the present invention, analyzes and calculates two suggested bids for the electricity user to choose from. This weakens the obstacles for electricity users to participate in the electricity market, promotes their enthusiasm for participating in electricity market transactions, encourages demand-side resources to participate in the electricity market, and ensures the safe and stable operation of the power system. Attached Figure Description

[0067] Figure 1 This is a block diagram of the bidding device of the present invention that assists individual electricity users in participating in the electricity market;

[0068] Figure 2 This is a flowchart of the bidding method for assisting individual electricity users in participating in the electricity market, as described in this invention. Detailed Implementation

[0069] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0070] like Figure 1 As shown, a bidding device for assisting individual electricity users in participating in the electricity market is divided into a data input module, a data storage module, a data analysis module, and a data output module.

[0071] Data input module: used to collect information and preferences of electricity users, with individual electricity users selecting and inputting data information;

[0072] Data storage module: The information in the module is organized by the bidding device operator. Each bidding device is kept connected to the network and automatically updates and loads the stored information released by the operator, including: market transaction information for the electricity market and user transaction information for individual electricity users;

[0073] Data Analysis Module: For a specific electricity market at a certain time scale, the pricing device analyzes the historical transaction information of the electricity market and the historical transaction results of individual electricity users to obtain two suggested pricing results.

[0074] Data output module: The module outputs a visual suggested price from the two suggested prices obtained from the data analysis module. Individual electricity users can then choose the suggested price and participate in the final price and electricity volume declaration in the electricity market.

[0075] In one embodiment of the present invention, based on the above-described bidding device, a bidding method for individual electricity users to participate in the electricity market is as follows: Figure 2 As shown, it includes the following steps:

[0076] S1. Collect information and intentions of electricity users, which are selected and input by individual electricity users. This includes: the type of electricity market that the individual electricity user chooses to participate in, the trading period of the electricity market under that type of electricity market, and the amount of electricity to be traded during each trading period.

[0077] Specifically, the trading timescales vary across different types of electricity markets, but all require individual electricity users to declare their electricity consumption for the specified time period. The amount of electricity consumed depends on the individual user's electricity usage behavior. Since this is a prediction of individual user behavior, the prediction results are relatively accurate, and the closer to day D, the more accurate the prediction of electricity usage behavior on day D becomes.

[0078] For example, if a household electricity user has no travel plans on day D, their electric vehicle can participate in the electricity market on day D as an energy storage resource; if a manufacturer electricity user has fewer work arrangements on day D, they can participate in the electricity market on day D with their surplus power generation plan.

[0079] Individual electricity users, after forecasting their electricity consumption for day D based on their own consumption behavior, can choose whether to participate in the electricity market on day D. Individual electricity users need to meet the access conditions of the electricity market and comply with the trading rules. The main types of electricity markets they can participate in are spot markets, including intra-provincial day-ahead spot markets, inter-provincial day-ahead spot markets, intra-provincial real-time spot markets, and inter-provincial day-ahead ancillary service markets. In the example of the specific implementation method of this disclosure, it is assumed that the individual electricity user's forecasting behavior is carried out on day D-1, targeting the intra-provincial spot market on day D.

[0080] Individual electricity users also need to choose the trading hours to participate in the electricity market.

[0081] In this embodiment, the electricity market operates on a minimum time scale of hours for some parts and 15 minutes for others. Individual electricity users need to choose to participate in the electricity market on a single or multiple time scales for day D. In the example of this specific implementation, it is assumed that an individual electricity user participates in the provincial day-ahead spot market for day D, and the participation time period t... D-n The smallest time scale is the hour, where n∈[0,24), n∈N, t D-n The period for participating in electricity trading is (n, n+1).

[0082] Individual electricity users also need to report the declared electricity volume for each trading period. Because individual electricity users can accurately predict their own electricity consumption behavior, they can accurately report the participating electricity volume for each trading period after selecting the time period for participating in the electricity market. (Regarding t) D-n During this period, the declared electricity consumption was Qt. D-n .

[0083] It should be noted that the data input module is mainly for individual electricity users to select the type of electricity market they want to participate in, the time period they want to participate in, and the corresponding amount of electricity. This module does not involve analysis or calculation; it is responsible for collecting user information and intentions.

[0084] S2. The bidding device remains connected to the network and automatically updates and stores the information released by the operator, including: market transaction information for the electricity market and user transaction information for individual electricity users.

[0085] Specifically, based on the relevant transaction information stored in the data storage module, the device user needs to maintain an internet connection. The transaction information will be automatically loaded into the quotation device after being updated via the network at midnight every day.

[0086] In this embodiment, the stored information includes: 1. For day D, the hourly transaction information of each electricity market within the previous two years. If a certain electricity market has not been operating for two years, the official operation time of the market shall prevail; if the hour is not the smallest unit of transaction time scale, the smallest unit of transaction time scale shall prevail; 2. The final clearing price of each type of electricity market for each time period.

[0087] The stored information also includes: 1. For day D, the electricity market transaction information for each hourly time period within the previous two years for this individual electricity user. If the electricity user has participated in the market for less than two years, the length of time in the market will be used as the standard; if the hour is not the smallest time scale unit, the smallest time scale unit will be used as the standard. 2. The individual electricity user's bids and whether or not a transaction was completed in each trading period.

[0088] The data storage module stores two sets of transaction information: one for the electricity market and one for individual electricity users.

[0089] The transaction information for the electricity market mainly consists of the final clearing price of each type of electricity market at the smallest time scale. The clearing price for each period is stored as the information basis for subsequent quotation recommendations.

[0090] Because weather, temperature, renewable energy output, and electricity load are constantly changing, the final clearing price for each hour is a comprehensive reflection of all factors within that hour. Therefore, this information is of some guiding significance for users' pricing. However, since not all markets have transparent and publicly available final clearing prices, this information cannot be stored and updated in some markets, preventing further data analysis in this area.

[0091] The transaction information for individual electricity users mainly includes the type of electricity market they choose, the trading period they participate in, and the transaction results within that period when they participate in various types of electricity markets. This type of information involves the individual electricity user's bidding information. Regardless of whether the electricity market information is public or not, the information on whether the individual electricity user's bid and the transaction are completed is always available. The above information can reflect the overall situation within that time period, so this type of information is also instructive for user bidding.

[0092] Therefore, the data storage module is primarily internal to the device, updating and storing two types of transaction information via network connectivity. This transaction information is used by the data analysis module to generate recommended quotes. Both types of transaction information, specifically addressing the electricity market clearing price and the electricity user transaction results, have analytical and guiding significance.

[0093] S3. For individual electricity users in a certain electricity market at a certain time scale, based on the historical transaction information of the electricity market and the historical transaction results of the individual electricity users, respectively, perform suggested price analysis to obtain the first suggested price in the direction of transaction information for the electricity market clearing price at a certain hour on day D and the second suggested price in the direction of the individual electricity user's own transaction information.

[0094] This embodiment assumes that the participation of individual electricity users takes place on day D-1. For the provincial spot market on day D, the smallest trading time scale is the hour, and the selected participation period is a specific hour t on day D. D-n (n∈[0,24),n∈N).

[0095] It should be noted that any single segment, multiple segments, or trading sessions with a minimum time scale of 15 minutes can be analyzed using the examples provided in this publication.

[0096] Since the data storage module includes two types of transaction information, the data analysis module also has two analysis directions.

[0097] For the electricity market clearing price transaction information stored in the storage module, data analysis mainly consists of the previous price Pt at the specified time. D-n Date Previous Price Pd D-n Historical price Py D-n It consists of three parts.

[0098] Previous price Pt D-n It is necessary to collect t from the storage module D-n The clearing price for the three hours prior to the transaction is P. * t D-n-1 P * t D-n-2 P * t D-n-3 This type of data is for t on that day. D-n The final clearing price three hours before the time, and t D-n At any given time, the weather temperature, renewable energy output, and electricity load are basically similar, so this type of data has strong guiding significance.

[0099] Specifically, due to my country's peak-valley electricity pricing system, peak hours are from 8:00 AM to 10:00 PM, and valley hours are from 10:00 PM to 8:00 AM the following day. If electricity users choose to participate in the t... D-n When the time coincides with the peak-valley electricity price threshold, the clearing price for the first three hours may vary significantly due to the crossing of peak and valley periods, which is somewhat unreasonable. Therefore, the previous price Pt at that time... D-n The analysis and calculations are configured as follows:

[0100]

[0101] It can be seen that when the selected t D-n The time slots are 8:00-9:00 or 22:00-23:00. The first three hours each have distinct peak and trough periods, therefore, there is no previous price Pt for these two time slots. D-n The calculations for these two time periods will be differentiated from those for other time periods in the future.

[0102] Previous Price Pt D-n It is necessary to collect data from the storage module on the 60 trading days prior to day D. D-n Final clearing price P at time * t D-x-n The closer the trading day of this type of data is to day D, and the closer it is to the weather, temperature, renewable energy output, and electricity load of day D, the stronger its guiding significance will be.

[0103] Since the electricity market in my country is still conducted on weekdays, and does not operate on holidays or weekends, the data collected covers the 60 trading days prior to day D to ensure its authenticity and usability.

[0104] The closer the data is to day D, the more indicative it is of price. Therefore, for prices Pd prior to a given date... D-n The analysis and calculations are configured as follows:

[0105]

[0106] Historical moment price Py D-n This requires collecting historical data from the storage module for day D, one year ago, and two years ago. Considering that there is no electricity market trading information on weekends or holidays, if there is no trading information for day D one or two years ago, then the nearest trading day D' before day D is selected. Then, select three days before and after day D or D', for a total of seven days (t). D-n The final clearing price at any given moment, P * y -1D-x-n This represents the final clearing price x days before date D one year ago. This type of data represents clearing prices for relevant dates in previous years and can reflect the impact of seasonal factors on clearing prices. For historical price Py... D-n The analysis and calculations are configured as follows:

[0107]

[0108] In summary, the direction of transaction information for electricity market clearing prices, regarding a specific hour t on day D. D-n The suggested price is P market-D-n :

[0109]

[0110] For the transaction information of electricity user transaction results stored in the storage module, data analysis mainly consists of the previous quote at the time of the Qt test. D-n Previous quote Qd D-n Historical price quotes Qy D-n composition.

[0111] Previous quote from Qt D-n It is necessary to collect t from the storage module D-n The user quotes three hours prior to the time are R. * t D-n-1 R * t D-n-2 R * t D-n-3 and the corresponding market transaction price B * t D-n-1 B * t D-n-2 B * t D-n-3The reference price is selected based on whether the transaction is completed. If the transaction is completed, the reference price at that moment is the user's current price. If the transaction is not completed, the reference price at that moment is the market transaction price at that moment.

[0112]

[0113] This type of data is for t on that day. D-n User quotes in the three hours prior to the time, compared to t D-n At similar times, weather conditions, renewable energy output, and electricity load are generally similar, making this type of data highly instructive. Because my country implements peak-valley electricity pricing, peak hours are from 8:00 AM to 10:00 PM, and valley hours are from 10:00 PM to 8:00 AM the following day. If electricity users choose to participate in the t... D-n When the time coincides with the threshold of peak-valley electricity pricing, the price quoted in the first three hours may vary significantly due to the crossing of peak and valley periods, which is somewhat unreasonable. Therefore, the previous price quote Qt at that time... D-n The analysis and calculations are configured as follows:

[0114]

[0115] It can be seen that when the selected t D-n The time slots are 8:00 to 9:00 or 22:00 to 23:00. Since the first three hours are characterized by different peak and trough periods, there are no previously quoted prices (Pt) for these two time slots. D-n The calculations for these two time periods will be differentiated from those for other time periods in the future.

[0116] Previous quote Qd D-n It is necessary to collect data from the storage module on the 60 trading days prior to day D. D-n Quotation R at any time * d D-x-n and the corresponding market transaction price B * d D-x-n The reference price is selected based on whether the transaction is completed. If the transaction is completed, the reference price at that moment is the user's current price. If the transaction is not completed, the reference price at that moment is the market transaction price at that moment.

[0117]

[0118] The closer the trading day of this type of data is to day D, and the closer it is to day D's weather conditions, renewable energy output, and electricity load, the stronger its indicative significance. Since my country's electricity market trading is still conducted on weekdays, and not on holidays or weekends, this type of data is collected from the 60 trading days prior to day D to ensure its authenticity and usability. Data closer to day D is more indicative of price trends; therefore, for previous date quotes (Qd)... D-n The analysis and calculations are configured as follows:

[0119]

[0120] Historical moment quotes Qy D-n We need to collect historical data from the storage module for day D, one year ago, and two years ago, including the quote R. * y -1D-x-n Market transaction price B * y -1D-x-n R * y -1D-x-n This represents the individual quote from a user x days prior to date D one year ago, B. * y -1D-x-n This represents the market transaction price x days before D one year ago.

[0121] Similarly, considering that there is no electricity market trading information on weekends or holidays, if there was no trading information on day D one or two years ago, then the nearest trading day D' before day D is selected. The selection is then performed for a total of seven days, including the days before and after day D one or two years ago. D-n The price quote and market transaction price at any given moment. For a given trading session, a reference price is selected based on whether the trade has been completed. If the trade is completed, the reference price for that moment is the user's current price quote; if the trade is not completed, the reference price for that moment is the current market transaction price.

[0122]

[0123] This type of data represents user quotes for relevant dates in previous years, which can reflect the impact of seasonal factors on user quotes. For historical quotes (Qy)... D-n The analysis and calculations are configured as follows:

[0124]

[0125] In summary, regarding the individual electricity user's transaction information, specifically concerning a certain hour t on day D... D-n The second suggested quote is Q user-D-n :

[0126]

[0127] S4. Visualize the results of the first and second suggested quotations obtained in step S3 for users to refer to, and allow individual electricity users to make their own selections and participate in the final price and electricity volume declaration in the electricity market.

[0128] Within the data output module, the final results obtained from the data analysis module are visualized and presented as suggested quotations for user reference. The output module also simultaneously outputs the suggested quotation result P obtained from the data analysis module based on historical electricity market transaction information. market-D-n Compared with the proposed bid results based on individual electricity users Q user-D-n Users make their own choices and submit their final price and electricity volume declarations to participate in the electricity market.

[0129] In this embodiment of the invention, an electronic device is also provided, comprising: one or more processors; a storage device storing one or more programs thereon; when the one or more programs are executed by the one or more processors, the one or more processors implement the bidding method for assisting individual electricity users to participate in the electricity market as described in any of the above embodiments.

[0130] In this embodiment of the invention, a computer-readable storage medium is also provided, on which a computer program is stored. When the program is executed by a processor, it implements the steps in any of the above-described methods for assisting individual electricity users in participating in the electricity market bidding.

[0131] In practical applications, the electricity market pricing device and method of this invention were used to simulate pricing based on publicly available data from a domestic or foreign company. The verification was conducted using a suggested pricing based on historical electricity market transaction information as an example. Assuming the company chose to participate in the provincial real-time spot market and selected 10:00 as the trading time, a suggested pricing was output using the method of this invention, based on the input data and information from historical electricity market transactions. The output pricing result was 81.046, while the actual market clearing price for the user's chosen trading time was 84.68. The small difference indicates that the method of this invention has a beneficial effect on assisting users in pricing.

[0132] The foregoing has shown and described the basic principles, main features, and advantages of this disclosure. Those skilled in the art should understand that this disclosure is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of this disclosure. Various changes and modifications can be made to this disclosure without departing from its spirit and scope, and all such changes and modifications fall within the scope of this disclosure as claimed.

Claims

1. A bidding device to assist individual electricity users in participating in the electricity market, characterized in that, Includes the following modules: Data input module: used to collect information and preferences of electricity users, with individual electricity users selecting and inputting data information; Data storage module: The information in the module is organized by the bidding device operator. Each bidding device is kept connected to the network and automatically updates and loads the stored information released by the operator, including: market transaction information for the electricity market and user transaction information for individual electricity users; Data Analysis Module: For a specific electricity market at a certain time scale, the pricing device analyzes the historical transaction information of the electricity market and the historical transaction results of individual electricity users to obtain two suggested pricing results. Data output module: Visualizes the two suggested quotations obtained from the data analysis module, allowing individual electricity users to select the best offer and participate in the final price and electricity volume declaration in the electricity market; In the data input module, the data information includes: the type of electricity market selected by the individual electricity user, the trading period of the individual electricity user participating in the electricity market under that type of electricity market, and the amount of electricity participated in each trading period; Individual electricity users may choose to participate in the spot market, which includes: intra-provincial day-ahead spot market, inter-provincial day-ahead spot market, intra-provincial real-time spot market, and inter-provincial day-ahead ancillary service market. In the data analysis module, it is assumed that the predictive behavior of individual electricity users is... The analysis will be conducted on the spot market within the province on day D, including: Analysis based on historical transaction information of the electricity market: Analyze the transaction information of the electricity market clearing price stored in the data storage module, specifically analyze the previous price at the current time, the previous price on the current date, and the historical price at the current time, to obtain the first suggested quote in the direction of the transaction information of the electricity market clearing price for a certain hour on day D; Analysis based on the historical transaction results of individual electricity users: This involves analyzing the transaction information of individual electricity users stored in the data storage module, specifically analyzing the previous quote at the current time, the previous quote on the current date, and the historical quote data to obtain... The second suggested quote for an individual electricity user's own transaction information for a specific hour of the day.

2. The bidding device for assisting individual electricity users in participating in the electricity market according to claim 1, characterized in that, In the data storage module, The market transaction information includes: for day D, the transaction information and market clearing price for each period within the previous two years of each electricity market; if an electricity market has not been operating for two years, then the period after the official operation of the electricity market is selected. The user transaction information includes: for day D, the electricity market transaction information of each individual electricity user in each period within the previous two years, as well as the electricity user's bid and whether the transaction was completed in each transaction period; if the electricity user has participated in the electricity market for less than two years, then the period after the electricity user participated in the electricity market is selected.

3. The bidding device for assisting individual electricity users in participating in the electricity market according to claim 1, characterized in that, The data output module visualizes the first suggested price result based on historical transaction information in the electricity market and the second suggested price result based on individual electricity users obtained from the data analysis module. Individual electricity users can then choose the result and participate in the final price and electricity volume declaration in the electricity market.

4. A bidding method to assist individual electricity users in participating in the electricity market, based on the bidding device for assisting individual electricity users in participating in the electricity market as described in any one of claims 1-3, for submitting price and electricity volume declarations in the electricity market, characterized in that, Includes the following steps: S1. Collect information and intentions of electricity users, which are selected and input by individual electricity users. This includes: the type of electricity market that the individual electricity user chooses to participate in, the trading period of the electricity market under that type of electricity market, and the amount of electricity to be traded during each trading period. S2. The bidding device remains connected to the network and automatically updates and stores the information released by the operator, including: market transaction information for the electricity market and user transaction information for individual electricity users. S3. For individual electricity users in a certain electricity market at a certain time scale, based on the historical transaction information of the electricity market and the historical transaction results of the individual electricity users, respectively, perform suggested price analysis to obtain the first suggested price in the direction of transaction information for the electricity market clearing price at a certain hour on day D and the second suggested price in the direction of the individual electricity user's own transaction information. S4. Visualize the results of the first and second suggested quotations obtained in step S3 for users to refer to, and allow individual electricity users to make their own selections and participate in the final price and electricity volume declaration in the electricity market.

5. The bidding method for assisting individual electricity users in participating in the electricity market according to claim 4, characterized in that, Assuming that the forecasting behavior of individual electricity users takes place on day D-1, what is the time period for individual electricity user participation in the provincial spot market on day D? Using hours as the minimum transaction time scale, The period for participating in electricity trading is indicated as follows. , , Represents the set of natural numbers; In step S3, the analysis based on historical transaction information in the electricity market is performed as follows: S3.1.1, Price Before Time Data analysis: collecting data from the data storage module. Clearing price for the three hours prior to the transaction , , The price before the time The analysis and calculations are set as follows: ； The peak time is from 8:00 to 22:00, and the trough time is from 22:00 to 8:00 the next day. When the time period is 8:00-9:00 or 22:00-23:00, the first three hours are different peak and trough periods, and there is no previous price for these two periods. ; S3.1.2, Price Prior to Date Data analysis: Collect data from the data storage module for the 60 trading days prior to day D. Final clearing price at any time Previous price The analysis and calculations are set as follows: ； S3.1.3, Historical Price Data analysis: Historical data for day D is collected from the data storage module. If there is no transaction information for day D one or two years ago, the nearest preceding transaction day is selected. Day, select day D or The day was three days before and three days before and two days before, for a total of seven days. Final clearing price at any given time, historical price at any given time The analysis and calculations are set as follows: ； in, , These represent D-day one year ago and two years ago, respectively. The final clearing price for the day; S3.1.4 Regarding the direction of transaction information for electricity market clearing prices, specifically for a certain hour on day D. The first suggested offer is : 。 6. The bidding method for assisting individual electricity users in participating in the electricity market according to claim 5, characterized in that, In step S3, the analysis based on the historical transaction results of individual electricity users is performed as follows: S3.2.1, Previous quote Data analysis: collecting data from storage modules User quotes for the three hours prior to the transaction , , and the corresponding market transaction price , , The reference price is selected based on whether the transaction is completed. If the transaction is completed, the reference price at that moment is the user's current price. If the transaction is not completed, the reference price at that moment is the current market transaction price, expressed as: ； Since the peak hours are from 8:00 AM to 10:00 PM and the trough hours are from 10:00 PM to 8:00 AM the next day, the price quoted earlier for each time period... The analysis and calculation are configured as follows: ； Among them, if electricity users choose to participate When the time is between 8:00 and 9:00 or between 22:00 and 23:00, which is the threshold between peak and off-peak electricity prices, there is no previous price quote available during these two time periods. ; S3.2.2, Previous Quotation by Date Data analysis: Collect data from the storage module for the 60 trading days prior to day D. Quote for a specific time and the corresponding market transaction price The reference price is selected based on whether the transaction is completed. If the transaction is completed, the reference price at that moment is the user's current price. If the transaction is not completed, the reference price at that moment is the current market transaction price, expressed as: ； Previous quotes The analysis and calculation are performed using the following formula: ； S3.2.3, Historical Price Quotes Data analysis involves collecting historical data from the data storage module, including quotes, for date D, one year ago, and two years ago. Compared with market transaction price , It indicates that one year ago, before D-day Individual user quotes per day It indicates that one year ago, before D-day The market transaction price of the day; If there was no transaction information on day D one or two years ago, then the nearest transaction date prior to day D will be selected. Day, select day D or The day was three days before and three days before and two days before, for a total of seven days. The quoted price and market transaction price at any given time are compared. A reference price is selected based on whether the transaction has been completed. If the transaction is completed, the reference price for that time is the user's current quoted price. If the transaction has not been completed, the reference price for that time is the current market transaction price, expressed as: ； Historical price quotes The analysis and calculations are set as follows: ； S3.2.

4. Regarding the individual electricity user's own transaction information, concerning a certain hour on day D. The second suggested offer is : 。 7. An electronic device, characterized in that, include: One or more processors; A storage device on which one or more programs are stored; When the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in any one of claims 4 to 6.

8. A computer-readable storage medium, characterized in that, It stores a computer program that, when executed by a processor, implements the steps in the bidding method for assisting individual electricity users to participate in the electricity market as described in any one of claims 4 to 6.

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