A multi-day electricity market trading clearing method and related device thereof

Abstract

The application discloses a multi-day power market transaction clearing method and a related device thereof, and the method comprises the following steps: a multi-day dispatch operation simulation model is constructed, expected adjustment power and expected adjustment cost are obtained by solving the multi-day dispatch operation simulation model; based on the expected adjustment power, the listed transaction power and the listed transaction cost, the listing and delisting transactions are carried out to obtain the delisting transaction power and the corresponding delisting transaction cost; the delisting transaction power and the corresponding delisting transaction cost are subjected to power checking and price checking, if the power checking result and the price checking result meet the requirements, the operation benefit checking of the delisting transaction cost is carried out based on the expected adjustment cost, if the operation benefit checking result meets the requirements, the clearing is carried out based on the delisting transaction power and the delisting transaction cost. The application improves the technical problems of increasing the power grid peak shaving pressure and reducing the power grid operation benefit in the prior art.

Description

Technical Field

[0001] This application relates to the field of power market and power dispatch technology, and in particular to a method for clearing multi-day power market transactions and related apparatus. Background Technology

[0002] Currently, a medium- and long-term electricity market covering annual and monthly timescales has been established, and pilot projects for day-ahead and intraday electricity spot markets are underway. To effectively connect medium- and long-term electricity markets with electricity spot market transactions, some provinces and regions have proposed the construction of multi-day electricity markets.

[0003] The current clearing process for multi-day electricity market transactions includes: users can declare their incremental electricity demand, with existing medium- and long-term electricity market transactions serving as the boundary for multi-day electricity market transactions; organizing bidding for incremental electricity demand transactions between power generation and consumption enterprises through bilateral transactions or centralized bidding; and further considering the impact of incremental transactions on grid operation based on the results of medium- and long-term electricity market transactions, implementing safety verification. It is evident that the current multi-day electricity market clearing follows the clearing model of medium- and long-term electricity market transactions, mainly focusing on incremental transactions by market participants, failing to fully leverage the role of connecting medium- and long-term electricity transactions and spot electricity market transactions, and not adequately considering the economic efficiency of grid operation. Grid safety verification uses grid operation safety as the boundary, allowing measures such as deep peak shaving and start-up / shutdown peak shaving to meet transaction requirements. While the current multi-day electricity market transaction results can meet the grid operation safety requirements, they may lead to increased grid peak shaving pressure and reduced grid operation efficiency. These problems will be shared by all market participants, which is not conducive to improving grid operation efficiency through market transactions. Summary of the Invention

[0004] This application provides a method and related apparatus for clearing multi-day electricity market transactions, which aims to improve the technical problems of increased grid peak-shaving pressure and reduced grid operation efficiency in the prior art.

[0005] In view of this, the first aspect of this application provides a method for clearing multi-day electricity market transactions, including:

[0006] A multi-day scheduling operation simulation model is constructed, and the expected adjustment power and expected adjustment cost are obtained by solving the multi-day scheduling operation simulation model.

[0007] Based on the expected adjustment of electricity volume, the listed trading volume and the listing fee, the listing and delisting transactions are carried out to obtain the delisting trading volume and the corresponding delisting fee.

[0008] The electricity volume and corresponding bidding fees of the bidding transactions are verified by electricity volume verification and price verification. If the electricity volume verification result and price verification result meet the requirements, the bidding fees are verified by operational efficiency verification based on the expected adjustment fee. If the operational efficiency verification result meets the requirements, the clearing is carried out based on the bidding electricity volume and bidding fees.

[0009] Optionally, the step of constructing a multi-day scheduling operation simulation model, and obtaining the expected adjustment electricity volume and expected adjustment cost by solving the multi-day scheduling operation simulation model, includes:

[0010] A first multi-day scheduling operation simulation model is constructed with the goal of minimizing the deviation electricity and without calling regulation resources including energy storage and deep peak shaving. The expected adjustment electricity is obtained by solving the first multi-day scheduling operation simulation model. The deviation electricity is the deviation electricity that exceeds the grid absorption capacity caused by not calling regulation resources including energy storage and deep peak shaving, based on the medium and long-term market trading electricity.

[0011] A second multi-day scheduling operation simulation model is constructed with the goal of minimizing the deviation in electricity volume and allowing the use of regulation resources, including energy storage and deep peak shaving, to respond. The expected adjustment cost is obtained by solving the second multi-day scheduling operation simulation model.

[0012] Optionally, the first multi-day scheduling operation simulation model is:

[0013]

[0014] In the formula, ND, NT, and ΔT represent the number of trading days, the number of simulated periods per operating day, and the time interval, respectively; NG represents the number of power generation companies, and NB represents the number of power load nodes. These represent the simulated power generation and traded electricity volume of power generation company g, respectively. The power output of power generation company g during period t on operating day d; P represents the electricity load of node b during time period t on operating day d; s max P s min These represent the maximum and minimum transmission capabilities of the operating section s, respectively; G s,g G s,b These are the power transfer distribution factors between power generation enterprise g, electricity load b, and operating section s, respectively; μ g,d Let g be the operating state variable of power generation enterprise g on operating day d; These are the start-up or shutdown state variables of power generation enterprise g on operating day d; ND S ND D These are the limits for the number of starts and the number of shutdowns, as specified in the operating procedures. These represent the maximum and minimum power generation limits for power generation enterprise g during the time period t of operating day d.

[0015] Optionally, the second multi-day scheduling operation simulation model is:

[0016]

[0017] In the formula, The net exchange power of energy storage during time period t on operating day d; The charging power and discharging power of the energy storage during the time period t of the operating day d; For energy storage, the charging state variables and discharging state variables are defined for time period t on operating day d; P SDMax P SDMin P represents the maximum and minimum charging power of the electrical energy storage system. SCMax P SCMin E represents the maximum and minimum discharge power of the electrical energy storage. Smax E Smin E represents the maximum and minimum energy storage capacity of electrical energy storage. S,0 The initial energy storage capacity; α S,C This is the loss factor calculated from the energy storage to the charging side; The initial and final state variables of the charging state of the energy storage during time period t on operating day d; The initial and final state variables of the discharge state of the energy storage during the time period t on the operating day d; The minimum technical output of power generation enterprise g under deep peak shaving conditions; G s,s denoted as the power transfer distribution factor of the energy storage and operating section s.

[0018] Optionally, the step of performing an operational benefit verification of the bidding fee based on the expected adjustment fee, and if the operational benefit verification result meets the requirements, then clearing is performed based on the bidding transaction volume and the bidding fee, including:

[0019] The trading volumes of the listing party and the delisting party are adjusted according to the delisting trading volume, and the expected adjustment cost after the listing and delisting transactions is obtained by combining the second multi-day scheduling operation simulation model.

[0020] If the expected adjustment cost after the listing and delisting transaction is less than or equal to the expected adjustment cost, then the clearing will be carried out according to the delisting transaction volume and the delisting cost;

[0021] If the expected adjustment cost after the listing and delisting transaction is greater than the expected adjustment cost, then the increase in expected adjustment cost shall be calculated based on the expected adjustment cost after the listing and delisting transaction and the expected adjustment cost.

[0022] Determine whether the difference between the delisting fee and the listing fee is greater than the expected increase in adjustment fees. If so, calculate the clearing fee based on the expected increase in adjustment fees and the delisting fee, and perform clearing based on the clearing fee and the delisting transaction volume.

[0023] Optionally, the method further includes:

[0024] If the expected adjustment costs cannot be completely eliminated through the listing and delisting transactions within the preset time frame, then the cost of sharing the expected adjustment costs among all power generation companies will be calculated based on the proportion of expected adjustment electricity generated by all power generation companies.

[0025] A second aspect of this application provides a multi-day electricity market clearing device, comprising:

[0026] The model building and solving unit is used to build a multi-day scheduling operation simulation model, and to obtain the expected adjustment power and expected adjustment cost by solving the multi-day scheduling operation simulation model.

[0027] The trading unit is used to conduct listing and delisting transactions based on the expected adjusted electricity volume, the listed trading electricity volume and the listing fee, to obtain the delisting trading electricity volume and the corresponding delisting fee.

[0028] The verification unit is used to verify the electricity volume and the corresponding bidding fee of the bidding transaction. If the electricity volume verification result and the price verification result meet the requirements, the bidding fee is verified for operational efficiency based on the expected adjustment fee. If the operational efficiency verification result meets the requirements, the clearing is performed based on the bidding transaction electricity volume and the bidding fee.

[0029] Optionally, the model building and solving unit is specifically used for:

[0030] A first multi-day scheduling operation simulation model is constructed with the goal of minimizing the deviation electricity and without calling regulation resources including energy storage and deep peak shaving. The expected adjustment electricity is obtained by solving the first multi-day scheduling operation simulation model. The deviation electricity is the deviation electricity that exceeds the grid absorption capacity caused by not calling regulation resources including energy storage and deep peak shaving, based on the medium and long-term market trading electricity.

[0031] A second multi-day scheduling operation simulation model is constructed with the goal of minimizing the deviation in electricity volume and allowing the use of regulation resources, including energy storage and deep peak shaving, to respond. The expected adjustment cost is obtained by solving the second multi-day scheduling operation simulation model.

[0032] A third aspect of this application provides a multi-day electricity market transaction clearing device, the device including a processor and a memory;

[0033] The memory is used to store program code and transmit the program code to the processor;

[0034] The processor is configured to execute any of the multi-day electricity market transaction clearing methods described in the first aspect according to the instructions in the program code.

[0035] A fourth aspect of this application provides a computer-readable storage medium for storing program code that, when executed by a processor, implements the multi-day electricity market clearing method described in any of the first aspects.

[0036] As can be seen from the above technical solutions, this application has the following advantages:

[0037] This application provides a method for clearing multi-day electricity market transactions, including: constructing a multi-day dispatch operation simulation model; obtaining the expected adjustment volume and expected adjustment cost by solving the multi-day dispatch operation simulation model; performing pre-clearing of listing and delisting transactions based on the expected adjustment volume, the listed transaction volume, and the listing cost to obtain the pre-clearing result; verifying the volume and price of the pre-clearing result; if the volume and price verification results meet the requirements, then verifying the operational efficiency of the pre-clearing result based on the expected adjustment cost; if the operational efficiency verification result meets the requirements, then performing clearing based on the pre-clearing result.

[0038] In this application, a multi-day dispatching and operation simulation model is constructed to obtain the expected adjustment electricity volume and expected adjustment cost. Based on the expected adjustment electricity volume, bidding and tendering transactions are carried out. The feasibility of the transaction is determined through three aspects: electricity volume verification, price verification, and operation efficiency verification, so as to gradually reduce the expected adjustment cost and improve the grid operation efficiency. Furthermore, power generation companies can obtain the expected adjustment electricity volume through the multi-day dispatching and operation simulation model, and adjust and optimize their trading electricity volume in a timely manner according to the expected adjustment electricity volume, which helps to alleviate the grid operation pressure and reduce operating costs. This improves the technical problems of increasing grid peak-shaving pressure and reducing grid operation efficiency in existing technologies. Attached Figure Description

[0039] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0040] Figure 1 A flowchart illustrating a multi-day electricity market transaction clearing method provided in this application embodiment;

[0041] Figure 2This is a schematic diagram of a multi-day electricity market transaction clearing device provided in an embodiment of this application. Detailed Implementation

[0042] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present application.

[0043] The medium- and long-term electricity market, the multi-day electricity market, and the electricity spot market are interconnected and closely linked electricity market trading processes. Referring to Table 1, the medium- and long-term electricity market primarily operates on longer timescales such as years and months. Its trading objects are the expected electricity volumes between power generation and consumption enterprises, requiring a match between power generation and consumption over a future period. During medium- and long-term electricity market transactions, due to the significant uncertainty in grid operation boundary data, only typical scenario safety verification is generally required, with relatively low safety requirements. Electricity spot market transactions are conducted on a day-ahead and intraday basis, closely reflecting actual operation. Boundary data such as renewable energy generation output, electricity load, and equipment maintenance are largely determined. The transaction results are the power generation and consumption curves for the next day or the next time period. Because it closely reflects actual operation, the electricity spot market has higher safety requirements, demanding that the clearing results meet the needs of safe and stable grid operation.

[0044] Table 1 Comparison of Electricity Duration Transactions

[0045] Time scale Target of the transaction Security requirements Medium and long-term electricity market Year and month as the main factors Electricity trading lower Multi-day electricity market In the coming days, generally 3-5 days Further research is needed. Further research is needed. Electricity spot market days before, within days Electricity trading higher

[0046] The weekly trading that some provinces and regions have already begun implementing is essentially a form of multi-day electricity market trading. As an effective link between the medium- and long-term electricity market and the spot electricity market, the multi-day electricity market mainly plays the following roles in the electricity market trading system:

[0047] (1) Take over the results of electricity trading in the medium and long term electricity market, and convert the electricity trading volume of the main players in the medium and long term electricity market into multi-day electricity generation and consumption curves, giving more consideration to the safety requirements of power dispatch and operation;

[0048] (2) Define a clearing boundary for electricity spot market transactions that better meets operational requirements, and avoid significant discrepancies between the results of medium- and long-term electricity market transactions and the requirements for grid operation safety.

[0049] The current process for clearing out electricity market transactions over several days includes the following main components:

[0050] Step 1: Incremental Trading by Market Participants. This step requires users to declare their incremental electricity demand, with existing medium- and long-term electricity market transactions serving as the boundary for multi-day electricity market transactions;

[0051] Step Two: Pre-clearing of Multi-Day Electricity Market Transactions. This step stipulates that incremental electricity demand transactions between power generation and consumption enterprises can be organized and carried out through bilateral transactions or centralized bidding. Pre-clearing only considers the power generation capacity limitations of the power generation enterprises themselves, and does not consider the grid's absorption capacity limitations; therefore, the clearing result is only a pre-clearing result.

[0052] Step 3: Safety Verification. This step will further consider the impact of incremental transactions on grid operation based on the results of medium- and long-term electricity market transactions, and implement safety verification. If the safety verification is met, the pre-clearing result will be the formal clearing result; otherwise, it will proceed to the pre-clearing stage, increasing the power generation restrictions for power generation companies, and repeating the above process until a multi-day electricity market transaction clearing result that meets the safety verification is obtained.

[0053] As can be seen from the above-mentioned multi-day electricity market clearing process, the current multi-day electricity market clearing follows the clearing model of the medium- and long-term electricity market, mainly carrying out incremental transactions by market participants, and has not fully played its role in connecting medium- and long-term electricity transactions and electricity spot market transactions, resulting in the following problems:

[0054] (1) Multi-day electricity market transactions, which take incremental electricity demand from users as the trading object, do not provide methods for adjusting and optimizing the trading volume of power generation enterprises. The medium- and long-term electricity market transactions do not fully consider the constraints on grid operation, and there is a possibility that the trading volume may not meet the operation requirements.

[0055] (2) Insufficient consideration has been given to the economic efficiency of power grid operation. Power grid safety verification takes power grid operation safety as the boundary and allows for measures such as deep peak shaving and start-up / shutdown peak shaving to meet trading requirements. Although the current multi-day electricity market trading results can meet the requirements of power grid operation safety, they may cause problems such as increased peak shaving pressure on the power grid, thus reducing the economic efficiency of power grid operation. The above problems will be borne by all market participants, which is not conducive to improving the efficiency of power grid operation through market transactions.

[0056] To improve the above issues, please refer to Figure 1 This application provides a method for clearing multi-day electricity market transactions, including:

[0057] Step 101: Construct a multi-day scheduling operation simulation model, and obtain the expected adjustment power and expected adjustment cost by solving the multi-day scheduling operation simulation model.

[0058] A multi-day dispatching operation simulation model is constructed to assess the feasibility of medium- and long-term electricity trading volumes for power generation and consumption enterprises, and to calculate the expected adjustment volume and expected adjustment costs. The expected adjustment volume refers to the deviation in electricity volume beyond the grid's absorption capacity, based on the medium- and long-term market trading volume, without utilizing regulatory resources such as energy storage and deep peak shaving. The expected adjustment cost refers to the increase in the overall grid operating cost resulting from utilizing regulatory resources such as energy storage and deep peak shaving to enhance the grid's absorption capacity to meet the medium- and long-term electricity trading volume requirements of power generation and consumption enterprises. The expected adjustment volume and expected adjustment costs can be obtained by adjusting the optimization objectives and constraints of the multi-day dispatching operation simulation model.

[0059] Electricity storage and deep peak shaving are typical regulatory resources in current power grid operation. This application's embodiments use the participation of these two types of regulatory resources as examples for illustration. If demand response, intraday start-stop peak shaving, and other regulatory resources also exist in the power grid, only optimization of the multi-day dispatch operation simulation model is required. It should be noted that both power generation and consumption entities participate in market transactions; electricity consumption or generation that does not participate in market transactions can be regarded as special transaction electricity with a fixed price, which does not affect the implementation of this application's embodiments.

[0060] Specifically, a first-day scheduling operation simulation model is constructed with the objective of minimizing the deviation in electricity volume and without invoking regulation resources including energy storage and deep peak shaving. The expected adjustment in electricity volume is obtained by solving the first-day scheduling operation simulation model. The first-day scheduling operation simulation model is as follows:

[0061]

[0062] In the formula, ND, NT, and ΔT represent the number of trading days, the number of simulated periods per operating day, and the time interval, respectively; NG represents the number of power generation companies, and NB represents the number of power load nodes. These represent the simulated power generation and traded electricity volume of power generation company g, respectively. The power output of power generation company g during period t on operating day d; P represents the electricity load of node b during time period t on operating day d; s max P s min These represent the maximum and minimum transmission capabilities of the operating section s, respectively; G s,g G s,b These are the power transfer distribution factors between power generation enterprise g, electricity load b, and operating section s, respectively; μ g,d Let g be the operating state variable of power generation enterprise g on operating day d; These are the start-up or shutdown state variables of power generation enterprise g on operating day d; ND S NDD These are the limits for the number of starts and the number of shutdowns, as specified in the operating procedures. These are the maximum and minimum power generation limits for power generation enterprise g during the period t of operating day d. For conventional power sources, the maximum and minimum power generation limits are the maximum technical output and the minimum output corresponding to the basic peak-shaving state, respectively. For new energy sources, the maximum and minimum power generation limits are the predicted power generation and 0, respectively.

[0063] By solving the simulation model of the first multi-day scheduling operation, the expected adjusted electricity volume is obtained, which is the difference between the simulated power generation and its traded electricity volume:

[0064]

[0065] In the formula, Let g be the expected adjustment amount of electricity for power generation company g. If the expected adjustment amount is greater than 0, it indicates that increasing the trading amount of electricity by the power generation company will help alleviate the pressure on the power grid and reduce operating costs; otherwise, it indicates that decreasing the trading amount of electricity by the power generation company will help alleviate the pressure on the power grid and reduce operating costs.

[0066] A second-day scheduling operation simulation model is constructed with the objective of minimizing the deviation in electricity volume and allowing the use of regulation resources including energy storage and deep peak shaving. The expected adjustment cost is obtained by solving the second-day scheduling operation simulation model. The second-day scheduling operation simulation model is as follows:

[0067]

[0068] In the formula, The net exchange power of energy storage during time period t on operating day d; The charging power and discharging power of the energy storage during the time period t of the operating day d; For energy storage, the charging state variables and discharging state variables are defined for time period t on operating day d; P SDMax P SDMin P represents the maximum and minimum charging power of the electrical energy storage system. SCMax P SCMin E represents the maximum and minimum discharge power of the electrical energy storage. Smax E Smin E represents the maximum and minimum energy storage capacity of electrical energy storage. S,0 The initial energy storage capacity; α S,C This is the loss factor calculated from the energy storage to the charging side; The initial and final state variables of the charging state of the energy storage during time period t on operating day d; The initial and final state variables of the discharge state of the energy storage during the time period t on the operating day d; The minimum technical output of power generation enterprise g under deep peak shaving conditions; G s,s denoted as the power transfer distribution factor of the energy storage and operating section s.

[0069] The expected adjustment cost is the operating cost incurred in utilizing energy storage, deep peak shaving, and other regulation resources to ensure the completion of the traded electricity volume, which can be expressed as:

[0070] ΔC EA =C GC +C S

[0071] In the formula, ΔC EA For anticipated adjustment costs, C GC C S These are the deep peak-shaving cost and the energy storage operation cost, respectively. The deep peak-shaving cost is the sum of the products of the deep peak-shaving price and the peak-shaving capacity declared by all power generation companies. The energy storage operation cost is the sum of the products of the declared charging volume price and the charging volume on each operating day. They can be expressed as follows:

[0072]

[0073]

[0074] In the formula, These are the price functions for deep peak shaving and energy storage charging / discharging, respectively, for power generation companies (g). For power generation company g, the deep peak-shaving capacity during period t on operating day d. The amount of charge generated by the energy storage on operating day d can be expressed as follows:

[0075]

[0076]

[0077] The charging power of energy storage during period t on operating day d And the power generation output of power generation company g during the period t of operating day d. This was obtained by solving the second multi-day scheduling operation simulation model.

[0078] Step 102: Based on the expected adjustment of electricity volume, the listed trading volume and the listing fee, conduct listing and delisting transactions to obtain the delisting trading volume and the corresponding delisting fee.

[0079] The organization organizes power generation companies to submit their adjusted electricity volumes and corresponding prices for multi-day electricity market transactions, referencing anticipated adjustments. The multi-day electricity market transaction listing system stipulates that power users with increased electricity demand and power generation companies selling traded electricity volumes must list their increased demand and sales volume, specifying the listing prices. The procedures and standards for power users increasing their electricity demand and power generation companies selling traded electricity are the same in the market transaction clearing process. This application's embodiment uses power generation companies selling traded electricity as an example to illustrate the subsequent implementation process.

[0080] Assume the electricity volume listed for trading by the power generation company is The corresponding listing fee is The expected adjustment volume calculated in step 101 will be used as a reference for power generation and consumption enterprises to submit multi-day electricity market transaction declarations. Power generation enterprises with negative expected adjustment volumes should sell their expected adjustment volumes in this step to reduce the expected adjustment costs of the power grid and improve operational efficiency; otherwise, they will bear the expected adjustment costs incurred.

[0081] Power generation companies can refer to the expected adjustment volume provided in step 101 and consider the power generation company's listed trading volume and listing fees when bidding to obtain the power generation company's bid trading volume. The corresponding delisting fee is

[0082] Step 103: Verify the electricity volume and price of the delisting transaction and the corresponding delisting fee. If the electricity volume verification result and the price verification result meet the requirements, then verify the operational efficiency of the delisting fee based on the expected adjustment fee. If the operational efficiency verification result meets the requirements, then clear the transaction based on the delisting transaction electricity volume and the delisting fee.

[0083] The electricity volume and corresponding bidding fees of the bidding transaction are verified. If the electricity volume verification result and the price verification result meet the requirements, the transaction volume of the listing party and the bidding party is adjusted according to the bidding transaction volume, and the expected adjustment fee after the bidding transaction is obtained by combining the second multi-day scheduling operation simulation model.

[0084] If the expected adjustment fee after delisting is less than or equal to the expected adjustment fee, the clearing will be carried out based on the delisting transaction volume and the delisting fee.

[0085] If the expected adjustment cost after the listing and delisting transaction is greater than the expected adjustment cost, then the increase in expected adjustment cost shall be calculated based on the expected adjustment cost after the listing and delisting transaction and the expected adjustment cost.

[0086] Determine whether the difference between the delisting fee and the listing fee is greater than the expected increase in adjustment fees. If so, calculate the clearing fee based on the expected increase in adjustment fees and the delisting fee, and clear the transaction based on the clearing fee and the trading volume of the delisting transaction.

[0087] The clearing of listing and delisting transactions should meet the following requirements (the process and standards for the clearing of electricity transactions are the same for both electricity users increasing their electricity consumption and power generation companies selling their electricity; this application's embodiment uses the electricity sold by power generation companies as an example for illustration):

[0088] (1) Electricity Verification: The electricity volume traded on the market shall not exceed the electricity volume traded by the listed power generation enterprise itself, and the electricity volume traded by the delisted power generation enterprise shall not exceed the power generation capacity of the delisted power generation enterprise and the electricity volume traded on the market. This can be expressed as:

[0089]

[0090]

[0091]

[0092] In the formula, The maximum power generation capacity of the delisted power generation enterprise during the multi-day electricity market trading period is its maximum power generation capacity and time integral value.

[0093] (2) Price verification: The listing transaction fee should be lower than the delisting transaction fee, which can be expressed as:

[0094]

[0095] (3) Operational benefit verification: Listing and trading should help reduce the operating costs of the power grid. If the expected adjustment costs increase due to listing and delisting transactions, the difference between listing and delisting costs should cover the increase in expected adjustment costs, and the parties to the listing and delisting transactions shall bear the increase in expected adjustment costs in accordance with the prescribed proportion.

[0096] Based on the fact that the electricity volume verification results and price verification results meet the above clearing conditions, the delisting transaction volume is used as the pre-clearing result. The transaction volumes of both the listing and delisting parties are adjusted, and substituted into the second multi-day scheduling and operation simulation model to solve for the expected adjustment cost after the listing and delisting transactions. If the expected adjustment cost after the listing and delisting transactions is less than or equal to the expected adjustment cost in step 101, the clearing conditions are met, and clearing is carried out according to the delisting transaction volume and delisting cost. If the expected adjustment cost after the listing and delisting transactions is greater than the expected adjustment cost, that is, the expected adjustment cost increases, then the difference between the delisting cost and the listing cost and the increase in the expected adjustment cost should meet the judgment condition, that is:

[0097]

[0098] In the formula, ΔC EA,B ΔC represents the expected adjustment costs prior to the implementation of the listing transaction (i.e., the expected adjustment costs calculated in step 101). EA,A This refers to the expected adjustment costs after the listing and trading are implemented.

[0099] If the judgment condition of equation (13) is met under the condition of expected increase in adjustment costs, the listed transaction will be officially cleared, the cleared electricity volume will be the delisted electricity volume, and the clearing cost should take into account the redistribution cost. The actual fees received by the listed power generation enterprise and the actual fees paid by the delisted power generation enterprise can be expressed as follows:

[0100]

[0101]

[0102] In the formula, These represent the actual fees received by the listed power generation companies and the actual fees paid by the delisted power generation companies, respectively, with α being the price difference return coefficient. This clearing fee means that if the transaction results in an increase in expected adjustment costs, the increased expected adjustment costs should be deducted from the delisting and listing fees, and the remaining amount should be returned to both the listing and delisting companies according to the price difference return coefficient.

[0103] In this embodiment, multi-day electricity market listing and trading are conducted according to the principle of time priority, price second, and electricity volume last. Specifically, the listing and delisting clearing is first determined by the listing time and delisting time. If the times are the same, the listing transaction fee or delisting transaction fee is used as the clearing determination condition in descending order. If time and price cannot be effectively distinguished, then the listing and delisting transaction volume is considered, and the transactions are carried out in descending order of volume.

[0104] Furthermore, if the expected adjustment costs cannot be completely eliminated through the listing and delisting transactions within the predetermined time frame, the cost of sharing the expected adjustment costs among all power generation companies will be calculated based on the proportion of their expected adjustment electricity volume. In other words, all power generation companies will share the expected adjustment costs according to their proportion of expected adjustment electricity volume.

[0105] In this embodiment, a multi-day scheduling and operation simulation model is constructed to obtain the expected adjustment power volume and expected adjustment cost. Based on the expected adjustment power volume, bidding and auction transactions are conducted. The feasibility of the transactions is determined through three aspects: power volume verification, price verification, and operational efficiency verification, so as to gradually reduce the expected adjustment cost and improve the grid operation efficiency. Furthermore, power generation companies can obtain the expected adjustment power volume through the multi-day scheduling and operation simulation model, and adjust and optimize their trading power volume in a timely manner according to the expected adjustment power volume, which helps to alleviate the grid operation pressure and reduce operating costs. This improves the technical problems of increasing grid peak-shaving pressure and reducing grid operation efficiency in the existing technology.

[0106] The above is an embodiment of a multi-day electricity market transaction clearing method provided by this application. The following is an embodiment of a multi-day electricity market transaction clearing device provided by this application.

[0107] Please refer to Figure 2This application provides a multi-day electricity market transaction clearing device, comprising:

[0108] The model building and solving unit is used to build a multi-day scheduling operation simulation model, and to obtain the expected adjustment power and expected adjustment cost by solving the multi-day scheduling operation simulation model.

[0109] The trading unit is used to conduct listing and delisting transactions based on the expected adjustment of electricity volume, the listed trading volume, and the listing fee, and to obtain the delisted trading volume and the corresponding delisting fee.

[0110] The verification unit is used to verify the electricity volume and price of the auctioned electricity and the corresponding auction fees. If the electricity volume verification result and the price verification result meet the requirements, the operational efficiency verification of the auction fees is performed based on the expected adjustment fee. If the operational efficiency verification result meets the requirements, the clearing is carried out based on the auctioned electricity volume and auction fees.

[0111] As a further improvement, the model building and solution unit is specifically used for:

[0112] A first multi-day scheduling operation simulation model is constructed with the goal of minimizing the deviation electricity and without calling regulation resources including energy storage and deep peak shaving. The expected adjustment electricity is obtained by solving the first multi-day scheduling operation simulation model. The deviation electricity is the deviation electricity that exceeds the grid absorption capacity caused by not calling regulation resources including energy storage and deep peak shaving, based on the medium and long-term market trading electricity.

[0113] A second multi-day scheduling operation simulation model is constructed with the goal of minimizing the deviation in electricity volume and allowing the use of regulation resources, including energy storage and deep peak shaving, to respond. The expected adjustment cost is obtained by solving the second multi-day scheduling operation simulation model.

[0114] As a further improvement, the verification unit is specifically used for:

[0115] The electricity volume and corresponding bidding fees of the bidding transaction are verified. If the electricity volume verification result and the price verification result meet the requirements, the transaction volume of the listing party and the bidding party is adjusted according to the bidding transaction volume, and the expected adjustment fee after the bidding transaction is obtained by combining the second multi-day scheduling operation simulation model.

[0116] If the expected adjustment fee after delisting is less than or equal to the expected adjustment fee, the clearing will be carried out based on the delisting transaction volume and the delisting fee.

[0117] If the expected adjustment cost after the listing and delisting transaction is greater than the expected adjustment cost, then the increase in expected adjustment cost shall be calculated based on the expected adjustment cost after the listing and delisting transaction and the expected adjustment cost.

[0118] Determine whether the difference between the delisting fee and the listing fee is greater than the expected increase in adjustment fees. If so, calculate the clearing fee based on the expected increase in adjustment fees and the delisting fee, and clear the transaction based on the clearing fee and the trading volume of the delisting transaction.

[0119] As a further improvement, the verification unit is also used for:

[0120] If the expected adjustment costs cannot be completely eliminated through listing and delisting transactions within the predetermined time frame, the cost of sharing the expected adjustment costs among all power generation companies will be calculated based on the proportion of expected adjustment electricity generated by all power generation companies.

[0121] In this embodiment, a multi-day scheduling and operation simulation model is constructed to obtain the expected adjustment power volume and expected adjustment cost. Based on the expected adjustment power volume, bidding and auction transactions are conducted. The feasibility of the transactions is determined through three aspects: power volume verification, price verification, and operational efficiency verification, so as to gradually reduce the expected adjustment cost and improve the grid operation efficiency. Furthermore, power generation companies can obtain the expected adjustment power volume through the multi-day scheduling and operation simulation model, and adjust and optimize their trading power volume in a timely manner according to the expected adjustment power volume, which helps to alleviate the grid operation pressure and reduce operating costs. This improves the technical problems of increasing grid peak-shaving pressure and reducing grid operation efficiency in the existing technology.

[0122] This application also provides a multi-day electricity market transaction clearing device, which includes a processor and a memory;

[0123] The memory is used to store program code and transfer the program code to the processor;

[0124] The processor is used to execute the multi-day electricity market transaction clearing method in the aforementioned method embodiments according to the instructions in the program code.

[0125] This application also provides a computer-readable storage medium for storing program code, which, when executed by a processor, implements the multi-day electricity market transaction clearing method described in the foregoing method embodiments.

[0126] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the above-described apparatus and unit can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0127] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented, for example, in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0128] It should be understood that in this application, "at least one (item)" means one or more, and "more than" means two or more. "And / or" is used to describe the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: only A exists, only B exists, and both A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one (item) of a, b, or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0129] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0130] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0131] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0132] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. 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 the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for executing all or part of the steps of the methods described in the various embodiments of this application through a computer device (which may be a personal computer, server, or network device, etc.). The aforementioned storage medium includes: USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, optical disks, and other media capable of storing program code.

[0133] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method for clearing transactions in a multi-day electricity market, characterized in that, include: A multi-day scheduling operation simulation model is constructed. The expected adjusted electricity volume and expected adjusted cost are obtained by solving the multi-day scheduling operation simulation model, including: A first multi-day scheduling operation simulation model is constructed with the objective of minimizing the deviation in electricity volume without utilizing regulation resources, including energy storage and deep peak shaving. The expected adjustment electricity volume is obtained by solving the first multi-day scheduling operation simulation model. The deviation in electricity volume refers to the amount of electricity volume exceeding the grid's absorption capacity, based on the medium- and long-term market trading volume, without utilizing regulation resources, including energy storage and deep peak shaving. The first multi-day scheduling operation simulation model is as follows: ； In the formula, , , These represent the number of trading days in a multi-day electricity market transaction, the number of simulated time periods per operating day, and the time interval; NG The number of power generation companies. This represents the number of electrical load nodes. , Power generation companies g Simulated power generation and traded electricity volume; For power generation companies g On operating days d time period t The power generation output; For electrical load nodes b On operating days d time period t The electrical load; , They are respectively the operating sections s Maximum and minimum transmission capabilities; , Power generation companies g Electrical load b With the operating section s The power transfer distribution factor between; For power generation companies g On operating days d The running state variables; , Power generation companies g On operating days d Start-up or shutdown status variables; , These are the limits for the number of starts and the number of shutdowns, as specified in the operating procedures. , Power generation companies g On operating days d time period t Maximum power generation output limit and minimum power generation output limit; A second multi-day scheduling operation simulation model is constructed with the objective of minimizing the deviation in electricity volume and allowing the use of regulation resources, including energy storage and deep peak shaving, to respond. The expected adjustment cost is obtained by solving the second multi-day scheduling operation simulation model. The second multi-day scheduling operation simulation model is as follows: ； In the formula, For energy storage on operating days d time period t Net exchange power; , Separate energy storage on operating days d time period Charging power and discharging power; , For energy storage on operating days d time period Charging state variables and discharging state variables; , The maximum and minimum charging power for electrical energy storage; , These represent the maximum and minimum discharge power of the electrical energy storage. , The maximum and minimum energy storage capacities of electrical energy storage; The initial amount of electricity stored; This is the loss factor calculated from the energy storage to the charging side; , For energy storage on operating days d time period t The initial state variable and the final state variable of the charging state; , For energy storage on operating days d time period t The initial state variables and the final state variables of the discharge state; For power generation enterprises under deep peak shaving conditions g Minimum technical output; For energy storage and operation sections s The power transfer distribution factor; Based on the expected adjustment of electricity volume, the listed trading volume and the listing fee, the listing and delisting transactions are carried out to obtain the delisting trading volume and the corresponding delisting fee. The electricity volume and corresponding bidding fees of the bidding transactions are verified by electricity volume verification and price verification. If the electricity volume verification result and price verification result meet the requirements, the bidding fees are verified by operational efficiency verification based on the expected adjustment fee. If the operational efficiency verification result meets the requirements, the clearing is carried out based on the bidding electricity volume and bidding fees.

2. The multi-day electricity market clearing method according to claim 1, characterized in that, The step of performing an operational efficiency verification of the bidding fees based on the expected adjustment fees, and if the operational efficiency verification result meets the requirements, then clearing is performed based on the bidding transaction volume and the bidding fees, including: The trading volumes of the listing party and the delisting party are adjusted according to the delisting trading volume, and the expected adjustment cost after the listing and delisting transactions is obtained by combining the second multi-day scheduling operation simulation model. If the expected adjustment cost after the listing and delisting transaction is less than or equal to the expected adjustment cost, then the clearing will be carried out according to the delisting transaction volume and the delisting cost; If the expected adjustment cost after the listing and delisting transaction is greater than the expected adjustment cost, then the increase in expected adjustment cost shall be calculated based on the expected adjustment cost after the listing and delisting transaction and the expected adjustment cost. Determine whether the difference between the delisting fee and the listing fee is greater than the expected increase in adjustment fees. If so, calculate the clearing fee based on the expected increase in adjustment fees and the delisting fee, and perform clearing based on the clearing fee and the delisting transaction volume.

3. The multi-day electricity market clearing method according to claim 2, characterized in that, The method further includes: If the expected adjustment costs cannot be completely eliminated through the listing and delisting transactions within the preset time frame, then the cost of sharing the expected adjustment costs among all power generation companies will be calculated based on the proportion of expected adjustment electricity generated by all power generation companies.

4. A multi-day electricity market transaction clearing device, characterized in that, include: The model building and solving unit is used to build a multi-day scheduling operation simulation model, and to obtain the expected adjustment power and expected adjustment cost by solving the multi-day scheduling operation simulation model. The model building and solution unit is specifically used for: A first multi-day scheduling operation simulation model is constructed with the objective of minimizing the deviation in electricity volume without utilizing regulation resources, including energy storage and deep peak shaving. The expected adjustment electricity volume is obtained by solving the first multi-day scheduling operation simulation model. The deviation in electricity volume refers to the amount of electricity volume exceeding the grid's absorption capacity, based on the medium- and long-term market trading volume, without utilizing regulation resources, including energy storage and deep peak shaving. The first multi-day scheduling operation simulation model is as follows: ； In the formula, , , These represent the number of trading days in a multi-day electricity market transaction, the number of simulated time periods per operating day, and the time interval; NG The number of power generation companies. This represents the number of electrical load nodes. , Power generation companies g Simulated power generation and traded electricity volume; For power generation companies g On operating days d time period t The power generation output; For electrical load nodes b On operating days d time period t The electrical load; , They are respectively the operating sections s Maximum and minimum transmission capabilities; , Power generation companies g Electrical load b With the operating section s The power transfer distribution factor between; For power generation companies g On operating days d The running state variables; , Power generation companies g On operating days d Start-up or shutdown status variables; , These are the limits for the number of starts and the number of shutdowns, as specified in the operating procedures. , Power generation companies g On operating days d time period t Maximum power generation output limit and minimum power generation output limit; A second multi-day scheduling operation simulation model is constructed with the objective of minimizing the deviation in electricity volume and allowing the use of regulation resources, including energy storage and deep peak shaving, to respond. The expected adjustment cost is obtained by solving the second multi-day scheduling operation simulation model. The second multi-day scheduling operation simulation model is as follows: ； In the formula, For energy storage on operating days d time period t Net exchange power; , Separate energy storage on operating days d time period Charging power and discharging power; , For energy storage on operating days d time period Charging state variables and discharging state variables; , The maximum and minimum charging power for electrical energy storage; , These represent the maximum and minimum discharge power of the electrical energy storage. , The maximum and minimum energy storage capacities of electrical energy storage; The initial amount of electricity stored; This is the loss factor calculated from the energy storage to the charging side; , For energy storage on operating days d time period t The initial state variable and the final state variable of the charging state; , For energy storage on operating days d time period t The initial state variables and the final state variables of the discharge state; For power generation enterprises under deep peak shaving conditions g Minimum technical output; For energy storage and operation sections s The power transfer distribution factor; The trading unit is used to conduct listing and delisting transactions based on the expected adjusted electricity volume, the listed trading electricity volume and the listing fee, to obtain the delisting trading electricity volume and the corresponding delisting fee. The verification unit is used to verify the electricity volume and the corresponding bidding fee of the bidding transaction. If the electricity volume verification result and the price verification result meet the requirements, the bidding fee is verified for operational efficiency based on the expected adjustment fee. If the operational efficiency verification result meets the requirements, the clearing is performed based on the bidding transaction electricity volume and the bidding fee.

5. A multi-day electricity market transaction clearing device, characterized in that, The device includes a processor and a memory; The memory is used to store program code and transmit the program code to the processor; The processor is configured to execute the multi-day electricity market transaction clearing method according to any one of claims 1-3, based on instructions in the program code.

6. A computer-readable storage medium, characterized in that, The computer-readable storage medium is used to store program code, which, when executed by a processor, implements the multi-day electricity market transaction clearing method according to any one of claims 1-3.

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