User side marketization transaction data processing method and system considering electricity-carbon coupling mechanism

Abstract

The invention discloses a user side marketization transaction data processing method and system considering an electricity-carbon coupling mechanism, and the method comprises the steps: collecting the declared electric quantity and declared electricity price of each transaction main body at a market side, and obtaining an electric energy clearing price according to the declared electric quantity and the declared electricity price; the transaction main body comprises a demand side main body and a supply side main body; sending the electric energy clearing price to each transaction subject, and receiving a carbon quotation strategy from each transaction subject; the carbon quotation strategy is obtained based on a reinforcement learning algorithm; according to the carbon quotation strategy of each transaction main body, clearing to obtain clearing electric quantity and clearing carbon intensity; and sending the clearing electric quantity to the demand side main body, so that the demand side main body performs local load reduction compensation according to the clearing electric quantity. According to the embodiment of the invention, through two-stage electricity-carbon coupling clearing, the electricity market and the carbon market can be effectively cooperated, and accurate load reduction of the demand side main body is further realized.

Description

Technical Field

[0001] The present invention relates to the technical field of power market regulation, and in particular to a method and system for processing user-side market-based transaction data taking into account an electricity-carbon coupling mechanism. Background Art

[0002] my country is vigorously promoting the construction of green electricity, green certificate markets and carbon markets. Currently, the green electricity and green certificate markets are independent of each other and have not yet been effectively coordinated, which has brought certain resistance to demand-side entities participating in market-based transactions and buying and selling environmental rights.

[0003] The price mechanism of the carbon market is different from that of the electricity market. The carbon price is non-time-varying, which does not reflect the advantages of carbon trading in regulating the supply and demand relationship on a time scale, and cannot motivate demand-side entities to participate in carbon emission reduction in real time according to market conditions. In addition, the transaction target of carbon trading is the difference between the carbon quota allocated to the trading entity and its actual carbon emissions. It is impossible to measure the marginal cost of carbon emissions generated by electricity consumption, resulting in the inability of the demand-side entities to fully exert their carbon reduction capabilities. Summary of the invention

[0004] The technical problem to be solved by the present invention is how to achieve precise carbon reduction of demand-side entities in the electricity-carbon coupling market, and to provide a user-side market-oriented transaction data processing method and system that takes into account the electricity-carbon coupling mechanism. Through two-stage electricity-carbon coupling clearing, the electricity market and the carbon market can effectively coordinate and further achieve precise load reduction for demand-side entities.

[0005] In order to solve the above technical problems, an embodiment of the present invention provides a user-side market-based transaction data processing method considering the electricity-carbon coupling mechanism applied to the market side, including:

[0006] Collect the declared electricity quantity and electricity price of each trading subject, and obtain the electricity clearing price according to the declared electricity quantity and the declared electricity price; the trading subject includes the demand side subject and the supply side subject;

[0007] Sending the electricity clearing price to each trading entity and receiving a carbon quotation strategy from each trading entity; the carbon quotation strategy is obtained based on a reinforcement learning algorithm;

[0008] According to the carbon quotation strategy of each trading entity, clearing is performed to obtain the cleared electricity quantity and cleared carbon intensity;

[0009] The cleared electricity quantity is sent to the demand-side entity, so that the demand-side entity performs local load reduction compensation according to the cleared electricity quantity.

[0010] As an improvement of the above scheme, the method of collecting the declared electricity quantity and the declared electricity price of each trading subject and obtaining the electric energy clearing price according to the declared electricity quantity and the declared electricity price includes:

[0011] Collect the electricity quantity and electricity price declared by each trading entity;

[0012] Matching the declared electricity quantity of the demand-side subject with the declared electricity quantity of the supply-side subject, and obtaining a matching relationship group of the demand-side subject and the supply-side subject according to the matching result of the declared electricity quantity;

[0013] The electricity clearing price is calculated according to the declared electricity price of the matching relationship group.

[0014] As an improvement of the above solution, the clearing electricity quantity and the clearing carbon intensity are obtained by clearing according to the carbon quotation strategy of each trading entity, including:

[0015] Establishing a market clearing model under the joint action of the demand-side subject and the supply-side subject;

[0016] The carbon quotation strategies of the trading entities are input into the market clearing model, and the market clearing model is solved with the goal of maximizing the total revenue to obtain the cleared electricity volume and cleared carbon intensity.

[0017] As an improvement of the above solution, the establishment of a market clearing model under the joint action of the demand-side subject and the supply-side subject includes:

[0018] pass Establishing a market clearing model under the joint action of the demand-side subject and the supply-side subject;

[0019] pass imposing constraints on the market clearing model;

[0020] according to and Calculate the market clearing electricity quantity;

[0021] in, is the carbon quotation strategy of the ith supply-side entity in period t; is the carbon quotation strategy of the jth demand-side entity in period t; is the amount of electricity sold by the i-th supply-side entity in period t; is the amount of electricity purchased by the jth demand-side entity in period t; t is the market clearing carbon intensity at time t.

[0022] The embodiment of the present invention further provides a user-side market-based transaction data processing method considering the electricity-carbon coupling mechanism applied to a demand-side entity, including:

[0023] According to the carbon emission control target, the declared electricity quantity and the declared electricity price are set, the declared electricity quantity and the declared electricity price are sent to the market side, and the electricity clearing price from the market side is received; the electricity clearing price is obtained by clearing the declared electricity quantity and the declared electricity price of each trading entity;

[0024] Establish a carbon quotation strategy generation model based on local electricity costs;

[0025] According to the electricity clearing price, based on the reinforcement learning algorithm, solving the carbon quotation strategy generation model, obtaining the carbon quotation strategy, and sending the carbon quotation strategy to the market side;

[0026] Receive the cleared electricity from the market side, compare the cleared electricity with the bid electricity in the carbon quotation strategy to obtain the local load reduction electricity, and perform local load reduction compensation according to the local load reduction electricity.

[0027] As an improvement to the above scheme, the declared electricity quantity and the declared electricity price are set according to the carbon emission control target, the declared electricity quantity and the declared electricity price are sent to the market side, and the electricity clearing price from the market side is received; the electricity clearing price is obtained by clearing the declared electricity quantity and the declared electricity price of each trading entity;

[0028] Establish a carbon quotation strategy generation model based on local electricity costs;

[0029] According to the electricity clearing price, based on the reinforcement learning algorithm, solving the carbon quotation strategy generation model, obtaining the carbon quotation strategy, and sending the carbon quotation strategy to the market side;

[0030] Receive the cleared electricity from the market side, compare the cleared electricity with the bid electricity in the carbon quotation strategy to obtain the local load reduction electricity, and perform local load reduction compensation according to the local load reduction electricity.

[0031] As an improvement of the above solution, according to the electric energy clearing price, based on the reinforcement learning algorithm, solving the carbon quotation strategy generation model to obtain the carbon quotation strategy, and sending the carbon quotation strategy to the market side, includes:

[0032] Substituting the electricity clearing price into the estimated electricity clearing price in the carbon quotation strategy generation model to obtain an actual carbon quotation strategy generation model;

[0033] Based on the proximal strategy optimization algorithm, the carbon emission cost function in the actual carbon quotation strategy generation model is solved to obtain the bid electricity and the load electricity carbon intensity, and generate a carbon quotation strategy;

[0034] The carbon quotation strategy is sent to the market side.

[0035] As an improvement of the above solution, receiving the cleared electricity from the market side, comparing the cleared electricity with the bid electricity in the carbon quotation strategy to obtain the local load reduction electricity, and performing local load reduction compensation according to the local load reduction electricity, including:

[0036] Receiving the cleared electricity from the market side;

[0037] Subtract the cleared electricity quantity from the bid electricity quantity in the carbon quotation strategy to obtain the local load reduction electricity quantity;

[0038] According to the local load reduction power, a preset local load reduction compensation mechanism is used to perform local load reduction compensation.

[0039] The embodiment of the present invention further provides a user-side market-based transaction data processing system that considers the electricity-carbon coupling mechanism and is applied to the market side, including:

[0040] A pre-clearing module is used to collect the declared electricity quantity and declared electricity price of each trading subject, and obtain the electric energy clearing price according to the declared electricity quantity and the declared electricity price; the trading subject includes a demand side subject and a supply side subject;

[0041] A carbon quotation strategy receiving module, used to send the electric energy clearing price to each trading entity and receive the carbon quotation strategy from each trading entity; the carbon quotation strategy is obtained based on a reinforcement learning algorithm;

[0042] A clearing data calculation module, used for clearing and obtaining clearing electricity and clearing carbon intensity according to the carbon quotation strategy of each trading entity;

[0043] The cleared power transmission module is used to send the cleared power to the demand side entity, so that the demand side entity performs local load reduction compensation according to the cleared power.

[0044] The embodiment of the present invention further provides a user-side market-based transaction data processing system for demand-side entities taking into account the electricity-carbon coupling mechanism, including:

[0045] A data declaration module is used to set the declared electricity quantity and the declared electricity price according to the carbon emission control target, send the declared electricity quantity and the declared electricity price to the market side, and receive the electricity clearing price from the market side; the electricity clearing price is obtained by clearing the declared electricity quantity and the declared electricity price of each trading entity;

[0046] A model building module is used to build a carbon quotation strategy generation model based on local electricity costs;

[0047] A model solving module, used for solving the carbon quotation strategy generation model according to the electric energy clearing price and based on a reinforcement learning algorithm, obtaining a carbon quotation strategy, and sending the carbon quotation strategy to the market side;

[0048] The load reduction module is used to receive the cleared electricity from the market side, compare the cleared electricity with the bid electricity in the carbon quotation strategy, obtain the local load reduction electricity, and perform local load reduction compensation according to the local load reduction electricity.

[0049] Compared with the prior art, the present invention discloses a user-side market-oriented transaction data processing method and system that considers the electricity-carbon coupling mechanism. The market side collects the declared electricity quantity and electricity price of each trading subject, and obtains the electricity clearing price according to the declared electricity quantity and the declared electricity price; the trading subject includes a demand-side subject and a supply-side subject; the electricity clearing price is sent to each trading subject, and the carbon quotation strategy from each trading subject is received; the carbon quotation strategy is obtained based on a reinforcement learning algorithm; according to the carbon quotation strategy of each trading subject, the clearing quantity and clearing carbon intensity are obtained through clearing; the clearing quantity is sent to the demand-side subject, so that the demand-side subject performs local load reduction compensation according to the clearing quantity. By adopting the embodiment of the present invention, the electricity market and the carbon market can be effectively coordinated through two-stage electricity-carbon coupling clearing, and the precise load reduction of the demand-side subject can be further realized. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 It is a timing diagram of data communication between the market side, the supply side and the demand side in a user-side market-based transaction data processing method considering the electricity-carbon coupling mechanism provided by an embodiment of the present invention;

[0051] Figure 2 It is a flowchart of the steps of a user-side market-based transaction data processing method considering the electricity-carbon coupling mechanism applied to the market side provided by an embodiment of the present invention;

[0052] Figure 3 It is a flowchart of the steps of a user-side market-based transaction data processing method considering the electricity-carbon coupling mechanism and applied to a demand-side entity provided by an embodiment of the present invention;

[0053] Figure 4 It is a structural schematic diagram of a user-side market-based transaction data processing system considering the electricity-carbon coupling mechanism and applied to the market side provided by an embodiment of the present invention;

[0054] Figure 5 It is a structural schematic diagram of a user-side market-based transaction data processing system considering the electricity-carbon coupling mechanism and applied to the demand side, as provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0055] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0056] In the description of the specification and claims, it is to be understood that the terms first, second, etc. in the specification and claims are only used for the purpose of describing the same technical features, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated, nor necessarily describing the order or time sequence. The terms are interchangeable where appropriate. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features.

[0057] In the electricity-carbon coupling scenario, the market side, demand side and supply side are interconnected to form an efficient energy trading ecosystem.

[0058] In the current electricity-carbon coupling market, the incentive mechanism on the demand side is often not targeted. Due to the separation of the electricity market and the carbon market, the demand side has not received sufficient incentives to implement low-carbon load reduction. Even if the demand side knows that carbon emissions can be reduced by reducing load, since the electricity-carbon coupling market has no effective linkage mechanism, the existing technology can only set the load reduction amount through experience, and it is difficult for the demand side to accurately reduce carbon emissions.

[0059] Based on the above considerations, the embodiments of the present invention provide a user-side market-oriented transaction data processing method that takes into account the electricity-carbon coupling mechanism, starting from the market side and the demand side entities respectively.

[0060] In the embodiment of the present invention, the participants of the electric-carbon coupling system include the market side, the demand side and the supply side. The data communication timing relationship between the three is as follows: Figure 1 It should be noted that Figure 1 Here, t1, t2, t3 and t4 represent the moments when different data communications are completed. Taking t1 as an example, at moment t1, both the supply-side entity and the demand-side entity have completed the task of sending the declared electricity volume and the declared electricity price to the market side.

[0061] The core function of the market side is to integrate the data of several demand-side entities and several supply-side entities, provide comprehensive information support, and build a trading platform to facilitate transactions between all parties. Through the role of the market side, demand-side entities can better understand factors such as market price changes and carbon emission costs, and then adjust energy use and carbon reduction strategies; supply-side entities can optimize energy production and carbon emission control based on demand-side demand and market prices. The market side not only provides a trading venue, but also provides trading references for participants, helping to achieve coordinated optimization of the electricity and carbon markets.

[0062] See also Figure 2 Some embodiments of the present invention provide a method for processing user-side market-based transaction data taking into account the electricity-carbon coupling mechanism from the market side, which is specifically performed through steps S11 to S14:

[0063] S11. Collect the declared electricity quantity and electricity price of each trading subject, and obtain the electricity clearing price according to the declared electricity quantity and the declared electricity price; the trading subjects include demand-side subjects and supply-side subjects.

[0064] S12. Send the electricity clearing price to each trading entity, and receive the carbon quotation strategy from each trading entity; the carbon quotation strategy is obtained based on a reinforcement learning algorithm.

[0065] S13. According to the carbon quotation strategy of each trading entity, clearing is performed to obtain the cleared electricity quantity and the cleared carbon intensity.

[0066] S14: sending the cleared electricity to the demand-side entity, so that the demand-side entity performs local load reduction compensation according to the cleared electricity.

[0067] In the above scheme, through the two-stage electricity-carbon coupling clearing, the electricity market and the carbon market can effectively coordinate and further realize the precise load reduction of the demand-side entities. The first stage is that the market side clears the declared data of each trading entity to obtain the electricity clearing price for each time period, so that each trading entity can calculate its own carbon quotation strategy. The second stage is that the market side clears the market clearing electricity and market carbon intensity for each time period based on the carbon quotation of each market entity, and finally enables each demand-side entity to adopt corresponding compensation based on the market clearing electricity, and reduce the demand-side entity carbon emissions through market transactions and user-side electricity consumption management.

[0068] As a preferred implementation, step S11, collecting the declared electricity quantity and declared electricity price of each trading subject, and obtaining the electric energy clearing price according to the declared electricity quantity and the declared electricity price, includes:

[0069] Collect the electricity quantity and electricity price declared by each trading entity;

[0070] Matching the declared electricity quantity of the demand-side subject with the declared electricity quantity of the supply-side subject, and obtaining a matching relationship group of the demand-side subject and the supply-side subject according to the matching result of the declared electricity quantity;

[0071] The electricity clearing price is calculated according to the declared electricity price of the matching relationship group.

[0072] Exemplarily, after collecting the declared electricity quantity and declared electricity price of each trading subject, the demand-side subject and the supply-side subject are matched first according to the declared electricity quantity. The quantity matching relationship between the demand-side subject and the supply-side subject can be one-to-one or one-to-many. Preferably, there are multiple groups of matching relationships, and conflicts are allowed between the multiple groups of matching relationships. Then, the declared electricity price is matched, and the supply-side subject with a similar declared electricity price to the demand-side subject is preferentially selected. More preferably, the demand-side subject and the supply-side subject can be further sorted based on the grid topological position relationship to select a matching relationship group and calculate the electricity clearing price.

[0073] As a preferred implementation, step S13, according to the carbon quotation strategy of each trading subject, clearing to obtain the cleared electricity quantity and cleared carbon intensity, includes:

[0074] Establishing a market clearing model under the joint action of the demand-side subject and the supply-side subject;

[0075] The carbon quotation strategies of the trading entities are input into the market clearing model, and the market clearing model is solved with the goal of maximizing the total revenue to obtain the cleared electricity volume and cleared carbon intensity.

[0076] Further, preferably, the establishing of a market clearing model under the joint action of the demand-side subject and the supply-side subject includes:

[0077] pass Establishing a market clearing model under the joint action of the demand-side subject and the supply-side subject;

[0078] pass imposing constraints on the market clearing model;

[0079] according to and Calculate the market clearing electricity quantity;

[0080] in, is the carbon quotation strategy of the ith supply-side entity in period t; is the carbon quotation strategy of the jth demand-side entity in period t; is the amount of electricity sold by the i-th supply-side entity in period t; is the amount of electricity purchased by the jth demand-side entity in period t;t is the market clearing carbon intensity at time t.

[0081] It should be noted that the main participants in the electricity-carbon coupling market are the demand side and the supply side. The market side can act as an intermediary for coordination. In a stable electricity-carbon coupling market with good development momentum, there are generally several demand-side entities and several supply-side entities.

[0082] It should also be noted that the carbon quotation strategy of the general supply-side entity is a monotonically increasing function, while the carbon quotation strategy of the demand-side entity is a monotonically decreasing function. The intersection of the market buyer and seller quotation curves is the market clearing price, at which social welfare can be maximized.

[0083] The input of the market clearing model established by the embodiment of the present invention includes the carbon quotation strategy of the trading entity, and the output includes the market clearing electricity volume and the market clearing carbon intensity. By solving the market clearing model, the changes and mechanisms of carbon prices can be fully and clearly understood to generate market clearing data for reference by demand-side entities. Demand-side entities can accurately perform internal carbon reduction operations based on the two-stage electricity-carbon coupled clearing.

[0084] See also Figure 3 , other embodiments of this embodiment start from the demand side subject, and provide a user side market transaction data processing method considering the electricity-carbon coupling mechanism, which is specifically performed through steps S21 to S24:

[0085] S21. Declared electricity quantity and declared electricity price are set according to the carbon emission control target, the declared electricity quantity and the declared electricity price are sent to the market side, and the electricity clearing price from the market side is received; the electricity clearing price is obtained by clearing the declared electricity quantity and the declared electricity price of each trading entity.

[0086] It should be noted that the declared electricity volume and the declared electricity price are related to market rules, cost structure, and the subject's own goals and constraints. Different demand-side subjects may have different methods for determining the declared electricity volume and the declared electricity price. In the embodiment of the present invention, it is mainly based on the carbon emission control target setting. In other preferred embodiments, it can also be set in combination with cost-effectiveness.

[0087] S22. Establish a carbon quotation strategy generation model based on local electricity costs.

[0088] S23. According to the electricity clearing price and based on a reinforcement learning algorithm, the carbon quotation strategy generation model is solved to obtain a carbon quotation strategy, and the carbon quotation strategy is sent to the market side.

[0089] S24. Receive the cleared electricity from the market side, compare the cleared electricity with the bid electricity in the carbon quotation strategy to obtain the local load reduction electricity, and perform local load reduction compensation according to the local load reduction electricity.

[0090] As a preferred implementation, step S22, establishing a carbon quotation strategy generation model according to local electricity costs, includes:

[0091] Obtain base load demand, bid electricity, expected electricity clearing price, load electricity usage, carbon price and load electricity usage carbon intensity as local electricity cost;

[0092] According to the basic load demand, the load reduction amount is calculated to obtain a user comfort loss cost function;

[0093] Calculating a power purchase cost function according to the bid power and the estimated power clearing price;

[0094] Calculating a carbon emission cost function according to the load power consumption, the carbon price and the load power carbon intensity;

[0095] A carbon quotation strategy generation model is established based on the user comfort loss cost function, the electricity purchase cost function and the carbon emission cost function.

[0096] In some preferred embodiments, the step of calculating the load reduction amount according to the basic load demand to obtain a user comfort loss cost function includes:

[0097] Subtracting the preset user load demand from the basic load demand to obtain a load reduction amount;

[0098] By C L,t =α L (ΔP L,t ) 2 +β L ΔP L,t The user comfort loss cost function is obtained; where ΔP L,t is the load reduction; α L is the preset first coefficient; β L is the preset second coefficient.

[0099] In some preferred embodiments, the electricity purchase cost function is calculated based on the bid electricity amount and the estimated electricity clearing price, including:

[0100] pass The load power consumption corresponding to the same period is multiplied by the power clearing price to obtain the power purchase cost function; where λ t is the electricity clearing price in period t; P in,tis the amount of electricity purchased during period t.

[0101] In some preferred embodiments, the carbon emission cost function is calculated based on the load power consumption, the carbon price and the load power carbon intensity, including:

[0102] Taking a weighted average of the carbon prices in each period to obtain an annual carbon price;

[0103] pass The carbon emission cost function is calculated; where λ c is the annual carbon price; ρ L,t P is the carbon intensity of load electricity consumption in period t; L,t is the load power consumption during period t.

[0104] Further, preferably, the establishing of a carbon quotation strategy generation model according to the user comfort loss cost function, the electricity purchase cost function and the carbon emission cost function comprises:

[0105] pass Establish a carbon quotation strategy generation model; among them, C L,t is the user comfort loss cost function in period t; is the electricity purchase cost function in period t; is the carbon emission cost function for period t; T is the total number of periods.

[0106] Further, as a preferred implementation, step S23, according to the electricity clearing price, based on the reinforcement learning algorithm, solving the carbon quotation strategy generation model to obtain the carbon quotation strategy, and sending the carbon quotation strategy to the market side, includes:

[0107] Substituting the electricity clearing price into the estimated electricity clearing price in the carbon quotation strategy generation model to obtain an actual carbon quotation strategy generation model;

[0108] Based on the proximal strategy optimization algorithm, the carbon emission cost function in the actual carbon quotation strategy generation model is solved to obtain the bid electricity and the load electricity carbon intensity, and generate a carbon quotation strategy;

[0109] The carbon quotation strategy is sent to the market side.

[0110] It should be noted that the Proximal Policy Optimization (PPO) algorithm is a reinforcement learning algorithm based on policy gradient. In the embodiment of the present invention, the Proximal Policy Optimization algorithm is used to optimize the decision-making of the bid power and the load power carbon intensity in the carbon bidding strategy, which can efficiently explore and utilize the power clearing price information.

[0111] As a preferred implementation, step S24, receiving the cleared electricity from the market side, comparing the cleared electricity with the bid electricity in the carbon quotation strategy to obtain the local load reduction electricity, and performing local load reduction compensation according to the local load reduction electricity, includes:

[0112] Receiving the cleared electricity from the market side;

[0113] Subtract the cleared electricity quantity from the bid electricity quantity in the carbon quotation strategy to obtain the local load reduction electricity quantity;

[0114] According to the local load reduction power, a preset local load reduction compensation mechanism is used to perform local load reduction compensation.

[0115] For example, by ΔP in,t =P t -P in,t The difference between the cleared electricity provided by the market side and the bid electricity of the demand side entity in the electricity-carbon coupling scenario is calculated as the local load reduction electricity. Then, the preset local load reduction compensation mechanism is adopted according to the local load reduction electricity.

[0116] It should be noted that the local load reduction compensation mechanism includes upgrading power equipment, adjusting the power consumption structure of electricity and carbon, interruptible load management, etc. The specific local load reduction compensation mechanism is preset by the demand side entity itself, and its implementation method does not affect the beneficial effects produced by the embodiments of the present invention.

[0117] In the above scheme, the demand-side entities can achieve precise load reduction by obtaining two-stage electricity-carbon coupling clearing, so that the electricity market and the carbon market can work together effectively. The first stage is that the market side clears the electricity clearing price for each time period based on the declared data of each trading entity, so that each trading entity can calculate its own carbon quotation strategy. The second stage is that the market side clears the market clearing electricity and market carbon intensity for each time period based on the carbon quotations of each market entity, so that each demand-side entity can adopt corresponding compensation based on the market clearing electricity, and reduce the demand-side entity carbon emissions through market transactions and user-side electricity consumption management.

[0118] The embodiment of the present invention provides a user-side market-based transaction data processing system 10 that is applied to the market side and takes into account the electricity-carbon coupling mechanism. Figure 4 The user-side market-based transaction data processing system 10 considering the electricity-carbon coupling mechanism includes a pre-clearing module 11, a carbon quotation strategy receiving module 12, a clearing data calculation module 13 and a clearing power transmission module 14, wherein:

[0119] The pre-clearing module 11 is used to collect the declared electricity quantity and declared electricity price of each trading subject, and obtain the electric energy clearing price according to the declared electricity quantity and the declared electricity price; the trading subject includes the demand side subject and the supply side subject;

[0120] The carbon quotation strategy receiving module 12 is used to send the electric energy clearing price to each trading entity and receive the carbon quotation strategy from each trading entity; the carbon quotation strategy is obtained based on the reinforcement learning algorithm;

[0121] A clearing data calculation module 13 is used to obtain clearing electricity and clearing carbon intensity according to the carbon quotation strategy of each trading entity;

[0122] The cleared power transmission module 14 is used to send the cleared power to the demand-side entity, so that the demand-side entity performs local load reduction compensation according to the cleared power.

[0123] As a preferred implementation, the pre-clearing module 11 is specifically used for:

[0124] Collect the electricity quantity and electricity price declared by each trading entity;

[0125] Matching the declared electricity quantity of the demand-side subject with the declared electricity quantity of the supply-side subject, and obtaining a matching relationship group of the demand-side subject and the supply-side subject according to the matching result of the declared electricity quantity;

[0126] The electricity clearing price is calculated according to the declared electricity price of the matching relationship group.

[0127] As a preferred implementation, the clearing data calculation module 13 includes:

[0128] A market clearing model establishing unit, used to establish a market clearing model under the joint action of the demand-side subject and the supply-side subject;

[0129] The market clearing model solving unit is used to input the carbon quotation strategies of the trading entities into the market clearing model, solve the market clearing model with the goal of maximizing the total profit, and obtain the clearing electricity and clearing carbon intensity.

[0130] Further, preferably, the market clearing model establishing unit is specifically used to:

[0131] pass Establishing a market clearing model under the joint action of the demand-side subject and the supply-side subject;

[0132] pass imposing constraints on the market clearing model;

[0133] according to and Calculate the market clearing electricity quantity;

[0134] in, is the carbon quotation strategy of the ith supply-side entity in period t; is the carbon quotation strategy of the jth demand-side entity in period t; is the amount of electricity sold by the i-th supply-side entity in period t; is the amount of electricity purchased by the jth demand-side entity in period t; t is the market clearing carbon intensity at time t.

[0135] The embodiment of the present invention provides a user-side market-based transaction data processing system 20 for a demand-side entity that considers the electricity-carbon coupling mechanism. Figure 5 The user-side market-based transaction data processing system 20 considering the electricity-carbon coupling mechanism includes a data reporting module 21, a model building module 22, a model solving module 23 and a load reduction module 24, wherein:

[0136] The data declaration module 21 is used to set the declared electricity quantity and the declared electricity price according to the carbon emission control target, send the declared electricity quantity and the declared electricity price to the market side, and receive the electricity clearing price from the market side; the electricity clearing price is obtained by clearing the declared electricity quantity and the declared electricity price of each trading entity;

[0137] A model building module 22, for building a carbon quotation strategy generation model based on local electricity costs;

[0138] A model solving module 23 is used to solve the carbon quotation strategy generation model according to the electricity clearing price based on a reinforcement learning algorithm to obtain a carbon quotation strategy, and send the carbon quotation strategy to the market side;

[0139] The load reduction module 24 is used to receive the cleared electricity from the market side, compare the cleared electricity with the bid electricity in the carbon quotation strategy, obtain the local load reduction electricity, and perform local load reduction compensation according to the local load reduction electricity.

[0140] As a preferred implementation, the model building module 22 is specifically used for:

[0141] Obtain base load demand, bid electricity, expected electricity clearing price, load electricity usage, carbon price and load electricity usage carbon intensity as local electricity cost;

[0142] According to the basic load demand, the load reduction amount is calculated to obtain a user comfort loss cost function;

[0143] Calculating a power purchase cost function according to the bid power and the estimated power clearing price;

[0144] Calculating a carbon emission cost function according to the load power consumption, the carbon price and the load power carbon intensity;

[0145] A carbon quotation strategy generation model is established based on the user comfort loss cost function, the electricity purchase cost function and the carbon emission cost function.

[0146] Further, as a preferred implementation, the model solving module 23 is specifically used for:

[0147] Substituting the electricity clearing price into the estimated electricity clearing price in the carbon quotation strategy generation model to obtain an actual carbon quotation strategy generation model;

[0148] Based on the proximal strategy optimization algorithm, the carbon emission cost function in the actual carbon quotation strategy generation model is solved to obtain the bid electricity and the load electricity carbon intensity, and generate a carbon quotation strategy;

[0149] The carbon quotation strategy is sent to the market side.

[0150] As a preferred implementation, the load reduction module 24 is specifically used for:

[0151] Receiving the cleared electricity from the market side;

[0152] Subtract the cleared electricity quantity from the bid electricity quantity in the carbon quotation strategy to obtain the local load reduction electricity quantity;

[0153] According to the local load reduction power, a preset local load reduction compensation mechanism is used to perform local load reduction compensation.

[0154] A user-side market-based transaction data processing system that takes into account the electricity-carbon coupling mechanism provided by an embodiment of the present invention enables the electricity market and the carbon market to effectively coordinate through two-stage electricity-carbon coupling clearing, thereby further achieving precise load reduction for demand-side entities.

[0155] A person skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes of the embodiments of the above-mentioned methods. The storage medium can be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc.

[0156] The above is a preferred embodiment of the present invention. It should be pointed out that a person skilled in the art can make several improvements and modifications without departing from the principle of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A user-side market-based transaction data processing method considering the electricity-carbon coupling mechanism, characterized in that: Applied to the market side, including: Collect the declared electricity quantity and electricity price of each trading subject, and obtain the electricity clearing price according to the declared electricity quantity and the declared electricity price; the trading subject includes the demand side subject and the supply side subject; Sending the electricity clearing price to each trading entity and receiving a carbon quotation strategy from each trading entity; the carbon quotation strategy is obtained based on a reinforcement learning algorithm; According to the carbon quotation strategy of each trading entity, clearing obtains the cleared electricity quantity and cleared carbon intensity; The cleared electricity quantity is sent to the demand-side entity, so that the demand-side entity performs local load reduction compensation according to the cleared electricity quantity.

2. A user-side market-based transaction data processing method considering the electricity-carbon coupling mechanism according to claim 1, characterized in that: The collecting of the declared electricity quantity and the declared electricity price of each trading subject, and obtaining the electric energy clearing price according to the declared electricity quantity and the declared electricity price, includes: Collect the electricity quantity and electricity price declared by each trading entity; Matching the declared electricity quantity of the demand-side subject with the declared electricity quantity of the supply-side subject, and obtaining a matching relationship group of the demand-side subject and the supply-side subject according to the matching result of the declared electricity quantity; The electricity clearing price is calculated according to the declared electricity price of the matching relationship group.

3. A user-side market-based transaction data processing method considering the electricity-carbon coupling mechanism according to claim 1, characterized in that: The clearing and obtaining of the cleared electricity and cleared carbon intensity according to the carbon quotation strategy of each trading subject includes: Establishing a market clearing model under the joint action of the demand-side subject and the supply-side subject; The carbon quotation strategies of the trading entities are input into the market clearing model, and the market clearing model is solved with the goal of maximizing the total revenue to obtain the cleared electricity volume and cleared carbon intensity.

4. A user-side market-based transaction data processing method considering the electricity-carbon coupling mechanism as claimed in claim 3, characterized in that: The establishing of a market clearing model under the joint action of the demand-side subject and the supply-side subject includes: pass Establishing a market clearing model under the joint action of the demand-side subject and the supply-side subject; pass imposing constraints on the market clearing model; according to and Calculate the market clearing electricity quantity; in, is the carbon quotation strategy of the ith supply-side entity in period t; is the carbon quotation strategy of the jth demand-side entity in period t; is the amount of electricity sold by the i-th supply-side entity in period t; is the amount of electricity purchased by the jth demand-side entity in period t; t is the market clearing carbon intensity at time t.

5. A user-side market-based transaction data processing method considering the electricity-carbon coupling mechanism, characterized in that: Applicable to demand-side entities, including: According to the carbon emission control target, the declared electricity quantity and the declared electricity price are set, the declared electricity quantity and the declared electricity price are sent to the market side, and the electricity clearing price from the market side is received; the electricity clearing price is obtained by clearing the declared electricity quantity and the declared electricity price of each trading entity; Establish a carbon quotation strategy generation model based on local electricity costs; According to the electricity clearing price, based on the reinforcement learning algorithm, solving the carbon quotation strategy generation model, obtaining the carbon quotation strategy, and sending the carbon quotation strategy to the market side; Receive the cleared electricity from the market side, compare the cleared electricity with the bid electricity in the carbon quotation strategy to obtain the local load reduction electricity, and perform local load reduction compensation according to the local load reduction electricity.

6. A user-side market-based transaction data processing method considering the electricity-carbon coupling mechanism as claimed in claim 5, characterized in that: According to the carbon emission control target, the declared electricity quantity and the declared electricity price are set, the declared electricity quantity and the declared electricity price are sent to the market side, and the electricity clearing price from the market side is received; the electricity clearing price is obtained by clearing the declared electricity quantity and the declared electricity price of each trading entity; Establish a carbon quotation strategy generation model based on local electricity costs; According to the electricity clearing price, based on the reinforcement learning algorithm, solving the carbon quotation strategy generation model, obtaining the carbon quotation strategy, and sending the carbon quotation strategy to the market side; Receive the cleared electricity from the market side, compare the cleared electricity with the bid electricity in the carbon quotation strategy to obtain the local load reduction electricity, and perform local load reduction compensation according to the local load reduction electricity.

7. A user-side market-based transaction data processing method considering the electricity-carbon coupling mechanism as claimed in claim 6, characterized in that: The step of solving the carbon quotation strategy generation model based on the reinforcement learning algorithm according to the electric energy clearing price to obtain the carbon quotation strategy, and sending the carbon quotation strategy to the market side includes: Substituting the electricity clearing price into the estimated electricity clearing price in the carbon quotation strategy generation model to obtain an actual carbon quotation strategy generation model; Based on the proximal strategy optimization algorithm, the carbon emission cost function in the actual carbon quotation strategy generation model is solved to obtain the bid electricity and the load electricity carbon intensity, and generate a carbon quotation strategy; The carbon quotation strategy is sent to the market side.

8. A user-side market-based transaction data processing method considering the electricity-carbon coupling mechanism as claimed in claim 5, characterized in that: The receiving of the cleared electricity from the market side, comparing the cleared electricity with the bid electricity in the carbon quotation strategy to obtain the local load reduction electricity, and performing local load reduction compensation according to the local load reduction electricity, includes: Receiving the cleared electricity from the market side; Subtract the cleared electricity quantity from the bid electricity quantity in the carbon quotation strategy to obtain the local load reduction electricity quantity; According to the local load reduction power, a preset local load reduction compensation mechanism is used to perform local load reduction compensation.

9. A user-side market-based transaction data processing system considering the electricity-carbon coupling mechanism, characterized in that: Applied to the market side, including: A pre-clearing module is used to collect the declared electricity quantity and declared electricity price of each trading subject, and obtain the electric energy clearing price according to the declared electricity quantity and the declared electricity price; the trading subject includes a demand side subject and a supply side subject; A carbon quotation strategy receiving module, used to send the electric energy clearing price to each trading entity and receive the carbon quotation strategy from each trading entity; the carbon quotation strategy is obtained based on a reinforcement learning algorithm; A clearing data calculation module, used for clearing and obtaining clearing electricity and clearing carbon intensity according to the carbon quotation strategy of each trading entity; The cleared power transmission module is used to send the cleared power to the demand side entity, so that the demand side entity performs local load reduction compensation according to the cleared power.

10. A user-side market-based transaction data processing system considering the electricity-carbon coupling mechanism, characterized in that: Applicable to demand-side entities, including: A data declaration module is used to set the declared electricity quantity and the declared electricity price according to the carbon emission control target, send the declared electricity quantity and the declared electricity price to the market side, and receive the electricity clearing price from the market side; the electricity clearing price is obtained by clearing the declared electricity quantity and the declared electricity price of each trading entity; A model building module is used to build a carbon quotation strategy generation model based on local electricity costs; A model solving module, used for solving the carbon quotation strategy generation model according to the electric energy clearing price and based on a reinforcement learning algorithm, obtaining a carbon quotation strategy, and sending the carbon quotation strategy to the market side; The load reduction module is used to receive the cleared electricity from the market side, compare the cleared electricity with the bid electricity in the carbon quotation strategy, obtain the local load reduction electricity, and perform local load reduction compensation according to the local load reduction electricity.

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