A Point-to-Point Method for Joint Trading of Electric Energy and Green Certificates

Abstract

The present invention provides a method for joint trading of point-to-point electric energy and green certificates. First, an optimization decision-making model for point-to-point electric energy trading among new energy power generation entities, conventional energy power generation entities, and electricity users is established; then, a clearing model for point-to-point electric energy trading between power generation entities and electricity users and a clearing model for point-to-point green certificate trading among electricity users are established; on this basis, a joint clearing model for point-to-point electric energy and green certificate trading is established, and a local optimization decision-making model for power generation entities and electricity users is established based on the alternating direction method of multipliers; finally, a distributed solution method based on the alternating direction method of multipliers is proposed. The method for joint trading of point-to-point electric energy and green certificates of the present invention realizes point-to-point trading of electric energy and green certificates, solves the problem of joint clearing of point-to-point electric energy and green certificate trading, and at the same time, the proposed distributed solution algorithm realizes efficient solution of the equilibrium solution and protects the privacy information of participating entities.

Description

Technical Field

[0001] The present invention belongs to the technical field of power trading, and particularly relates to a method for joint trading of point-to-point electric energy and green certificates. Background Art

[0002] To build a new power system with new energy as the main body, at present, market mechanisms such as renewable energy quota systems and green certificate trading have been piloted. However, these mechanisms mainly target the power generation side. With the vigorous construction and rapid development of distributed energy on the user side, the problem of consuming distributed energy on the user side has become increasingly prominent; at the same time, to establish a low-carbon community, the demand for green electricity on the user side is increasing day by day. It is urgent to innovate the power market trading mechanism to promote the consumption of distributed energy and new energy.

[0003] To promote the consumption of distributed energy, current research mainly focuses on point-to-point electric energy trading. For example, Chinese invention patent CN112862610A, "A method for P2P+ power trading in an active energy body community", discloses a method for P2P+ power trading in an active energy body community, which can better meet the needs of all parties in power trading and improve the trading efficiency and the stability and security of the power system; Chinese invention patent CN115205036A, "A method, device, equipment and storage medium for P2P trading of distributed resources", discloses a method, device, equipment and storage medium for P2P trading of distributed resources, which can obtain a reasonable P2P electric energy trading price curve, promote distributed resources to participate in market trading, and reasonably allocate the shared benefits of electric energy within a certain user group; Chinese invention patent CN110473068A, "A method for end-to-end electric energy trading at the community resident side for the spot market", discloses a method for end-to-end electric energy trading at the community resident side for the spot market, and in the specific trading process, it also improves the local consumption of new energy by promoting residents to provide auxiliary services. However, the above research does not consider the green certificate trading mechanism and only designs different point-to-point electric energy trading methods; in view of the strong willingness and social responsibility of some users to consume green electricity, it is necessary to introduce the green certificate trading mechanism on the user side and propose a new trading mechanism that couples point-to-point electric energy and green certificate trading to promote the consumption of distributed energy and meet the green electricity demand of users. Summary of the Invention

[0004] The present invention overcomes the deficiencies of the prior art and provides a method for joint trading of point-to-point electric energy and green certificates. Optimization decision-making models for point-to-point electric energy trading of new energy power generation entities, conventional energy power generation entities, and power users are respectively established; then, a clearing model for point-to-point electric energy trading between power generation entities and power users and a clearing model for point-to-point green certificate trading of power users are established; on this basis, a joint clearing model for point-to-point electric energy and green certificate trading is established, and local optimization decision-making models for power generation entities and power users are established based on the alternating direction method of multipliers; finally, a distributed solution method based on the alternating direction method of multipliers is proposed. The method for joint trading of point-to-point electric energy and green certificates of the present invention realizes point-to-point trading of electric energy and green certificates, solves the problem of joint clearing of point-to-point electric energy and green certificate trading, and at the same time, the proposed distributed solution algorithm realizes efficient solution of the equilibrium solution and protects the privacy information of participating entities.

[0005] To achieve the above object, the technical solution adopted by the present invention is as follows:

[0006] A method for joint trading of point-to-point electric energy and green certificates, comprising the following steps:

[0007] Step 1: Respectively establish optimization decision-making models for point-to-point electric energy trading of new energy power generation entities, conventional energy power generation entities, and power users;

[0008] Step 2: Respectively establish a clearing model for point-to-point electric energy trading between power generation entities and power users and a clearing model for point-to-point green certificate trading of power users;

[0009] Step 3: Establish a joint clearing model for point-to-point electric energy and green certificate trading, and establish local optimization decision-making models for power generation entities and power users based on the alternating direction method of multipliers;

[0010] Step 4: Propose a distributed solution method for joint clearing of point-to-point electric energy and green certificate trading based on the alternating direction method of multipliers;

[0011] Further, the specific content of the above Step 1 includes:

[0012] Step (1-1): Establish an optimization decision-making model for point-to-point electric energy trading of new energy power generation entities according to Formulas (1) and (2):

[0013] (1)

[0014] (2)

[0015] In the formula, is the operating income objective function of the new energy power generation entity which is composed of the income from selling electricity to the grid and the income from point-to-point electric energy trading; is the set of new energy power generation entities; is the index of new energy output scenarios, and the scenario is the number of scenarios, is the scenario probability; is the on-grid electricity price, is the scenario under which the new energy entity sells the electricity quantity to the power grid company; represents the scenario under which the new energy power generation entity and the electricity user conduct point-to-point electricity trading, is the new energy power generation entity and the electricity user the trading price between them; is the scenario under which the new energy power generation entity actual power generation; is the total on-grid power of the new energy power generation entity;

[0016] Step (1-2): Establish an optimization decision model for point-to-point electricity trading of conventional energy power generation entities according to Equations (3) and (4):

[0017] (3)

[0018] (4)

[0019] In the formula, is the operating income objective function of the conventional energy power generation entity which consists of on-grid electricity sales income, point-to-point electricity trading income and fuel cost; is the set of conventional energy power generation entities; is the on-grid electricity price, is the conventional energy entity selling the electricity quantity to the power grid company; represents the conventional energy power generation entity and the electricity user point-to-point electricity trading, is the conventional energy power generation entity and the electricity user the trading price between them; is the maximum power generation of the conventional energy power generation entity ; is the total on-grid power of the conventional energy power generation entity;

[0020] Step (1-3): Establish an optimization decision model for point-to-point electricity trading of electricity users according to Equations (5) and (6):

[0021] (5)

[0022] (6)

[0023] In the formula, represents the objective function of electricity users which includes four items. The first item is the electricity consumption utility, the second item is the cost of purchasing electricity from the power grid company, the third item is the cost of purchasing electricity from power generators, and the last item is the transmission fee; is the set of electricity users; is the utility coefficient, is the retail electricity price of the power grid company, represents the electricity purchased from the power grid company; is the transmission fee per unit electrical distance, is the new energy power generation entity and the electricity user the electrical distance between; is the electricity user the electricity consumption power of, represents the electricity user from the power generation entity the amount of electricity purchased point-to-point, is the power generation entity and the electricity user the transaction price between; is the electricity user the baseline load of, is the electricity user the maximum demand power of;

[0024] Furthermore, the specific content in step 2 above includes:

[0025] Step (2-1): Establish a point-to-point electricity energy trading clearing model for power generation entities and electricity users according to formula (7):

[0026] (7)

[0027] In the formula, the set of power generation entities, including new energy power generation entities and conventional energy power generation entities; and respectively represent the number of power generation entities and electricity users participating in point-to-point electricity energy trading; the objective function represents maximizing the overall benefits of all power generation entities and electricity users;

[0028] Step (2-2): Establish a point-to-point green certificate trading clearing model for electricity users according to formulas (8)-(10):

[0029] (8)

[0030] (9)

[0031] (10)

[0032] In the formula, represents the green certificate trading revenue of electricity users, and the objective function represents maximizing the green certificate trading revenue of all electricity users; The green certificate trading revenue of electricity users, and the objective function represents maximizing the green certificate trading revenue of all electricity users; represents the number of electricity users participating in point-to-point green certificate trading, represents the price of green certificates in the external green certificate market; represents electricity user The number of green certificates obtained by purchasing green power from new energy power generation entities, represents the green certificate conversion coefficient, that is, the number of green certificates corresponding to unit electricity; represents electricity user The new energy consumption quota, represents the new energy consumption quota coefficient; represents electricity user The number of green certificates traded in the external green certificate market; represents electricity user The expected number of green certificates traded point-to-point with electricity user ; Then it represents electricity user The expected number of green certificates traded point-to-point with electricity user ; is a binary variable used to represent the green certificate buying and selling role of electricity user . If , electricity user is a green certificate seller; if , then electricity user is a green certificate buyer;

[0033] Furthermore, step 3 specifically includes the following steps:

[0034] Step (3-1): Establish a joint clearing model for point-to-point electric energy and green certificate trading according to formulas (11) and (12):

[0035] (11)

[0036] (12)

[0037] Among them, the objective function formula (11) represents maximizing social welfare, that is, maximizing the total revenue of all participants in point-to-point electric energy trading and green certificate trading. The bilateral payments related to point-to-point trading in the objective function cancel each other out; is the set of new energy power generation entities, is the set of conventional energy power generation entities;

[0038] Step (3 - 2): Based on the alternating direction multiplier method, establish the augmented Lagrangian function of the point-to-point electric energy and green certificate trading joint clearing model:

[0039] (13)

[0040] is the Lagrange multiplier, is the penalty factor, and the symbol represents the square of the second-order norm;

[0041] Step (3 - 3): Based on the alternating direction multiplier method, decompose the augmented Lagrangian function of the point-to-point electric energy and green certificate trading joint clearing model into the local optimization decision model of power generation entities (14) and the local optimization decision model of power users (15):

[0042] (14)

[0043] (15)

[0044] Furthermore, the specific steps in the above Step 4 include the following steps:

[0045] Step (4 - 1): Initialize the maximum number of iterations , the iteration convergence accuracy ; Initialize the penalty coefficient and the iteration number ; Initialize the Lagrange multipliers and , initialize and ;

[0046] Step (4 - 2): For each power generation entity , receive the electricity quantity it expects to purchase from all power users; then update the electricity quantity it expects to sell to all power users by solving its distributed optimization operation decision model (14), and send the point-to-point trading strategy to the corresponding power users ;

[0047] Step (4 - 3): For each power user , receive the electricity quantity it expects to sell from all power generation entities, and receive the number of green certificates expected to be traded from other power users ; Then, update the electricity quantity it expects to purchase from all power generation entities by solving its distributed optimal operation decision model (15) , and the number of green certificates it expects to sell to other electricity users , and send the peer-to-peer trading strategy and to the corresponding power generation entities and electricity users ;

[0048] Step (4-4): Update the Lagrange multiplier according to Equation (16):

[0049] (16)

[0050] Step (4-5): Update the iteration number: k = k + 1;

[0051] Step (4-6): Judge the convergence situation of the algorithm. If the iteration termination condition in (17) is satisfied:

[0052] (17)

[0053] Then terminate the iteration. Otherwise, return to step (4-2) of the process and repeat the calculation until the convergence condition is satisfied or the maximum number of iterations is reached.

[0054] The advantages of the present invention compared with the prior art are as follows:

[0055] (1) The present invention solves the problems of joint trading and coupled clearing of peer-to-peer electric energy and green certificates;

[0056] (2) The present invention proposes a new method for coupled trading of peer-to-peer electric energy and green certificates on the user side;

[0057] (3) The present invention uses the alternating direction multiplier method to achieve the joint clearing of peer-to-peer electric energy and green certificate trading and protects the privacy information security of each participating entity;

[0058] The present invention discloses a method for joint trading of peer-to-peer electric energy and green certificates. This method not only overcomes the defect that the existing peer-to-peer electric energy trading method cannot consider the coupled trading of green certificates, realizes the peer-to-peer trading of electric energy and green certificates, solves the problems of coupled trading and joint clearing of peer-to-peer electric energy and green certificate trading, but also the proposed distributed solution algorithm realizes the efficient solution of the equilibrium solution and protects the privacy information of the participating entities. Brief Description of the Drawings

[0059] Figure 1 is a flowchart of the implementation of a method for joint trading of peer-to-peer electric energy and green certificates according to the present invention. Detailed Embodiment

[0060] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0061] A point-to-point electric energy and green certificate joint trading method of the present invention first establishes an optimization decision-making model for point-to-point electric energy trading among new energy power generation entities, conventional energy power generation entities and power users; then establishes a clearing model for point-to-point electric energy trading between power generation entities and power users and a clearing model for point-to-point green certificate trading among power users; on this basis, establishes a joint clearing model for point-to-point electric energy and green certificate trading, and establishes a local optimization decision-making model for power generation entities and power users based on the alternating direction multiplier method; finally, proposes a distributed solution method based on the alternating direction multiplier method. Specifically, as Figure 1 shown, a point-to-point electric energy and green certificate joint trading method of the present invention includes the following steps:

[0062] Step 1: Establish an optimization decision-making model for point-to-point electric energy trading among new energy power generation entities, conventional energy power generation entities and power users respectively, specifically including:

[0063] Step (1-1): Establish an optimization decision-making model for point-to-point electric energy trading of new energy power generation entities according to formulas (1) and (2):

[0064] (1)

[0065] (2)

[0066] In the formula, is the operating revenue objective function of the new energy power generation entity, which consists of the revenue from selling electricity to the grid and the revenue from point-to-point electric energy trading; is the set of new energy power generation entities; is the index of new energy output scenarios, and scenario is the number of scenarios, is the probability of scenario ; is the probability of scenario is the on-grid electricity price, is the electricity quantity sold by the new energy entity to the grid company under scenario ; represents the electricity quantity of point-to-point trading between the new energy power generation entity and the power user under scenario , is the new energy power generation entity and the transaction price with electricity users ; For the scenario the actual power generation of new energy power generation entities ; is the total power of new energy power generation entities connected to the grid;

[0067] Step (1 - 2): Establish an optimized decision-making model for point-to-point electricity trading of conventional energy power generation entities according to Equations (3) and (4):

[0068] (3)

[0069] (4)

[0070] In the formula, is the operating revenue objective function of conventional energy power generation entities, which consists of revenue from selling electricity to the grid, revenue from point-to-point electricity trading, and fuel cost; ; is the set of conventional energy power generation entities; is the grid-connected electricity price, is the electricity quantity sold by conventional energy entities to the grid company; represents the electricity quantity of point-to-point trading between conventional energy power generation entities and electricity users , is the conventional energy power generation entity and electricity users the transaction price between; is the maximum power generation of conventional energy power generation entities ; is the total power of conventional energy power generation entities connected to the grid;

[0071] Step (1 - 3): Establish an optimized decision-making model for point-to-point electricity trading of electricity users according to Equations (5) and (6):

[0072] (5)

[0073] (6)

[0074] In the formula, represents the objective function of electricity users , which includes four items. The first item is the electricity consumption utility, the second item is the cost of purchasing electricity from the grid company, the third item is the cost of purchasing electricity from power generators, and the last item is the transmission fee; is the set of electricity users; is the utility coefficient, is the retail electricity price of the grid company, represents the electricity purchased from the power grid company; is the transmission fee per unit electrical distance, is the new energy power generation entity and the electricity user 's electrical distance; is the electricity consumption power of the electricity user , represents the electricity quantity directly purchased by the electricity user from the power generation entity point-to-point, is the transaction price between the power generation entity and the electricity user ; is the baseline load of the electricity user , is the maximum demand power of the electricity user ;

[0075] Step 2: Establish a point-to-point electricity energy trading clearing model for the power generation entity and the electricity user and a point-to-point green certificate trading clearing model for the electricity user respectively, specifically including:

[0076] Step (2-1): Establish a point-to-point electricity energy trading clearing model for the power generation entity and the electricity user according to Equation (7):

[0077] (7)

[0078] In the formula, is the set of power generation entities, including new energy power generation entities and conventional energy power generation entities; and respectively represent the number of power generation entities and electricity users participating in the point-to-point electricity energy trading; the objective function represents maximizing the overall benefits of all power generation entities and electricity users;

[0079] Step (2-2): Establish a point-to-point green certificate trading clearing model for the electricity user according to Equations (8)-(10):

[0080] (8)

[0081] (9)

[0082] (10)

[0083] In the formula, represents the green certificate trading revenue of the electricity user , and the objective function represents maximizing the green certificate trading revenue of all electricity users; represents the number of electricity users participating in the point-to-point green certificate trading, Represents the green certificate price in the external green certificate market; Represents the electricity user The number of green certificates obtained by purchasing green electricity from new energy power generation entities, Represents the green certificate conversion coefficient, that is, the number of green certificates corresponding to unit electricity; Represents the electricity user The new energy consumption quota volume, Represents the new energy consumption quota coefficient; Represents the electricity user The number of green certificates traded in the external green certificate market; Represents the electricity user The expected number of green certificates for point-to-point trading with electricity user If so, the number of green certificates for point-to-point trading between electricity users Then it represents the electricity user The expected number of green certificates for point-to-point trading with electricity user If so, the number of green certificates for point-to-point trading between electricity users; Is a binary variable used to represent the green certificate buying and selling role of the electricity user If The electricity user Is the seller of green certificates; if If so, then the electricity user Is the buyer of green certificates;

[0084] Step 3: Establish a joint clearing model for point-to-point electric energy and green certificate trading, and establish a local optimization decision model for power generation entities and electricity users based on the alternating direction multiplier method, specifically including:

[0085] Step (3-1): Establish a joint clearing model for point-to-point electric energy and green certificate trading according to equations (11) and (12):

[0086] (11)

[0087] (12)

[0088] Among them, the objective function equation (11) represents maximizing social welfare, that is, maximizing the total income of all participants in point-to-point electric energy trading and green certificate trading. The bilateral payments related to point-to-point trading in the objective function cancel each other out; Is the set of new energy power generation entities, Is the set of conventional energy power generation entities;

[0089] Step (3-2): Establish an augmented Lagrangian function of the joint clearing model for point-to-point electric energy and green certificate trading based on the alternating direction multiplier method:

[0090] (13)

[0091] Among them, is the Lagrange multiplier, is the penalty factor, and the symbol denotes the square of the second-order norm;

[0092] Step (3-3): Based on the alternating direction method of multipliers, decompose the augmented Lagrangian function of the point-to-point electric energy and green certificate trading joint clearing model into the local optimization decision-making model (14) of the power generation entity and the local optimization decision-making model (15) of the power users:

[0093] (14)

[0094] (15)

[0095] Step 4: Propose a distributed solution method for the point-to-point electric energy and green certificate trading joint clearing based on the alternating direction method of multipliers, which specifically includes:

[0096] Step (4-1): Initialize the maximum number of iterations , the iteration convergence accuracy ; Initialize the penalty coefficient and the number of iterations ; Initialize the Lagrange multipliers and , initialize and ;

[0097] Step (4-2): For each power generation entity , receive the electricity quantity it expects to purchase from all power users; then update the electricity quantity it expects to sell to all power users by solving its distributed optimal operation decision-making model (14), and send the point-to-point trading strategy to the corresponding power users ;

[0098] Step (4-3): For each power user , receive the electricity quantity it expects to sell from all power generation entities, and the number of green certificates it expects to trade from other power users; then update the electricity quantity it expects to purchase from all power generation entities, and the number of green certificates it expects to sell to other power users by solving its distributed optimal operation decision-making model (15), and send the point-to-point trading strategies and to the corresponding power generation entities and electricity users ;

[0099] Step (4-4): Update the Lagrange multiplier according to Equation (16):

[0100] (16)

[0101] Step (4-5): Update the iteration number: k = k + 1;

[0102] Step (4-6): Judge the convergence situation of the algorithm. If the iteration termination condition in (17) is satisfied:

[0103] (17)

[0104] Then the iteration terminates. Otherwise, return to process step (4-2) to repeat the calculation until the convergence condition is satisfied or the maximum number of iterations is reached. The above implementation steps are only provided for the purpose of describing the present invention, and are not intended to limit the scope of the present invention. The scope of the present invention is defined by the appended claims. All equivalent substitutions and modifications made without departing from the spirit and principles of the present invention shall be covered within the scope of the present invention.

Claims

1. A peer-to-peer electricity and green certificate joint trading method, characterized in that, It includes the following steps: Step 1: Establish point-to-point power trading optimization decision models for new energy power generation entities, conventional energy power generation entities, and power users respectively; Step 2: Establish point-to-point power trading clearing models for power generation entities and power users and point-to-point green certificate trading clearing models among power users respectively, including: Step (1-1): Establish a point-to-point power trading optimization decision model for new energy power generation entities according to Equations (1) and (2): (1) (2) In the formula, As the main body of new energy power generation The operating revenue objective function is composed of the revenue from grid-connected electricity sales and the revenue from point-to-point electricity trading; It is a collection of new energy power generation entities; Index of new energy output scenarios, scenarios is the number of scenes, For the scene probability; For the on-grid electricity price, For the scene New energy subject The amount of electricity sold to the grid company; Representation scene New energy power generation entities and electricity users The amount of electricity used in peer-to-peer transactions, It is the main body of new energy power generation and electricity users The transaction price between For the scene New energy power generation entities The actual power generation; The total power of renewable energy power generation entities connected to the grid; Step (1-2): Establish a point-to-point power trading optimization decision model for conventional energy power generation entities according to Equations (3) and (4): (3) (4) In the formula, is the operating revenue objective function of the conventional energy power generation entity which consists of the revenue from selling electricity to the grid, the revenue from point-to-point electricity trading, and the fuel cost; is the set of conventional energy power generation entities; is the on-grid electricity price, is the conventional energy entity the electricity quantity sold to the grid company; represents the electricity quantity of point-to-point trading between the conventional energy power generation entity and the electricity user ; is the conventional energy power generation entity and the electricity user the trading price between them; is the maximum power generation of the conventional energy power generation entity ; is the total on-grid power of the conventional energy power generation entity. Step (1-3): Establish a point-to-point power trading optimization decision model for power users according to Equations (5) and (6): (5) (6) In the formula, represents the objective function of electricity users , which includes four items. The first item is the electricity consumption utility, the second item is the cost of purchasing electricity from the power grid company, the third item is the cost of purchasing electricity from power generators, and the last item is the transmission fee; is the set of electricity users; is the utility coefficient, is the retail electricity price of the power grid company, represents the electricity purchased from the power grid company; is the transmission fee per unit electrical distance, is the new energy power generation entity and the electricity user 's electrical distance; is the electricity consumption power of the electricity user , represents the electricity quantity directly purchased by the electricity user from the power generation entity point-to-point, is the transaction price between the power generation entity and the electricity user ; is the baseline load of the electricity user , is the maximum demand power of the electricity user . Step 3: Establish a joint clearing model for point-to-point power and green certificates trading, and establish local optimization decision models for power generation entities and power users based on the alternating direction method of multipliers; Step 4: Propose a distributed solution method for joint clearing of point-to-point power and green certificates trading based on the alternating direction method of multipliers.

2. The peer-to-peer electricity and green certificate joint trading method according to claim 1, characterized in that: The specific content of Step 2 includes: Step (2-1): Establish a point-to-point power trading clearing model for power generation entities and power users according to Equation (7): (7) In the formula, The set of power generation entities, including new energy power generation entities and conventional energy power generation entities; and respectively represent the number of power generation entities and power users participating in point-to-point electric energy transactions; the objective function represents maximizing the overall benefits of all power generation entities and power users; Step (2-2): Establish a point-to-point green certificate trading clearing model for power users according to Equations (8)-(10): (8) (9) (10) In the formula, represents the green certificate trading income of electricity users The objective function represents maximizing the green certificate trading income of all electricity users; represents the number of electricity users participating in peer-to-peer green certificate trading, represents the green certificate price in the external green certificate market; represents electricity user The number of green certificates obtained by purchasing green power from new energy power generation entities, represents the green certificate conversion coefficient, that is, the number of green certificates corresponding to unit electricity; represents electricity user The new energy consumption quota of, represents the new energy consumption quota coefficient; represents electricity user The number of green certificates traded in the external green certificate market; represents electricity user The expected number of green certificates for peer-to-peer trading with electricity user ; then represents the expected number of green certificates for peer-to-peer trading between electricity user and electricity user ; is a binary variable used to represent the green certificate buying and selling role of electricity user . If , electricity user is the green certificate seller; if , then electricity user is the green certificate buyer.

3. The peer-to-peer electricity and green certificate joint trading method according to claim 2, characterized in that: The specific content of Step 3 includes: Step (3-1): Establish a joint clearing model for point-to-point power and green certificates trading according to Equations (11) and (12): (11) (12) Among them, the objective function (11) represents maximizing social welfare, that is, maximizing the total revenue of all participants in point-to-point electricity trading and green certificate trading. The bilateral payments related to point-to-point trading in the objective function cancel each other out; is the set of new energy power generation entities, is the set of conventional energy power generation entities; Step (3-2): Establish an augmented Lagrangian function of the joint clearing model for point-to-point power and green certificates trading based on the alternating direction method of multipliers; (13) Among them, is the Lagrange multiplier, is the penalty factor, and the symbol denotes the square of the second-order norm; Step (3-3): Decompose the augmented Lagrangian function of the joint clearing model for point-to-point power and green certificates trading into a local optimization decision model (14) for power generation entities and a local optimization decision model (15) for power users based on the alternating direction method of multipliers: (14) (15) 。 4. A point-to-point electricity and green certificate combined trading method according to claim 3, characterized in that: The specific steps in Step 4 are as follows: Step (4-1): Initialize the maximum number of iterations of the distributed algorithm for the joint clearing of point-to-point electric energy and green certificates , the iterative convergence accuracy ; Initialize the penalty coefficient and the number of iterations ; Initialize the Lagrange multipliers and , initialize and ; Step (4-2): For each power generation entity , receive the electricity quantity that all electricity users expect to purchase ; then update the electricity quantity that it expects to sell to all electricity users by solving its distributed optimal operation decision model (14) , and send the point-to-point trading strategy to the corresponding electricity users ; Step (4-3): For each electricity user , receive the electricity quantity that each power generation entity expects to sell , and receive the number of green certificates for which other electricity users expect to trade ; then update the electricity quantity that it expects to purchase from all power generation entities by solving its distributed optimal operation decision model (15) , and the number of green certificates that it expects to sell to other electricity users , and send the point-to-point trading strategy and to the corresponding power generation entity and electricity user respectively; Step (4-4): Update the Lagrange multiplier according to Equation (16): (16) Step (4-5): Update the iteration number: k = k + 1; Step (4-6): Judge the convergence situation of the algorithm. If the iteration termination condition (17) is satisfied: (17) Then the iteration terminates. Otherwise, return to process Step (4-2) to repeat the calculation until the convergence condition or the maximum number of iterations is satisfied.

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