Green power and green certificate collaborative transaction method under regional common power market

Abstract

The invention discloses a green power and green certificate collaborative transaction method in a regional common power market, and belongs to a new energy transaction technology. According to the method, a power system is divided into local power markets according to jurisdictions, then a regional common power market is constructed by a plurality of local power markets, a common power market balance model comprises a power transaction balance model and a green certificate transaction balance model, and a green power transaction mechanism and a green certificate transaction mechanism are correspondingly realized respectively; the electricity transaction mechanism takes benefits in the local electricity market as an optimal target, takes renewable energy quota demands in areas included in the local electricity market into consideration, and forms an inter-provincial transaction quotation curve of the outgoing electricity quantity and the purchased electricity quantity; according to the green certificate transaction mechanism, green power environment value distribution is carried out in a generalized Nash game mode, and a thermal power plant in a region forms a regional green certificate market quotation curve according to a power selling plan and a quota task of the thermal power plant, and then centralized clearing is carried out in the generalized Nash game mode.

Description

Technical Field

[0001] The present invention relates to the field of energy trading technology, and in particular to a method for collaborative trading of green electricity and green certificates in a regional common electricity market. Background Art

[0002] At present, it is a general trend for cross-provincial and cross-regional transactions to bear the responsibility of balancing the market in the receiving province. New energy bases are facing the problem of low actual average transaction prices, mismatched power curves for generation (DC power) and consumption (contracted load within the province), and it is difficult to achieve expected returns. Therefore, a long-term guarantee mechanism for promoting green power consumption is designed under the changes in the future new power system.

[0003] Renewable energy quotas and their supporting green certificate trading mechanism are important policies to encourage the development of green electricity. Domestic and foreign scholars have also conducted many studies on the operation of the power system under the quota system: the existing public data have conducted in-depth research on the market operation in green certificate trading and the connection between green certificates and subsidies. Among them, the market entities participating in green electricity trading are mostly parity new energy power generation projects, which are mainly carried out in the form of bilateral negotiations. However, most users lack power generation resources outside the province and find it difficult to purchase green electricity through bilateral transactions. The enthusiasm for green certificate trading has not been deeply explored.

[0004] At present, the research on optimizing the cross-provincial and cross-regional green electricity trading mechanism mainly focuses on the transaction structure, organizational form and other aspects. There is a lack of specific research on the organizational coordination model of cross-provincial and cross-regional green electricity trading, including the connection mechanism between green certificate trading and the existing electricity market.

[0005] Under the goal of building a regional common electricity market, in order to study the long-term guarantee mechanism to promote the consumption of green electricity and clarify the connection between the green environmental value of renewable energy in various types of markets, a collaborative trading model of green electricity and green certificates in the regional common electricity market is proposed. This model constructs a collaborative trading model of the regional common electricity market that includes traditional electricity trading and green certificate trading, retains the provincial market in electricity trading, and uses the generalized Nash game to distribute environmental value in green certificate trading. While promoting the consumption of renewable energy, it is conducive to the smooth transition of the electricity market to a unified market. Summary of the invention

[0006] The present invention aims to provide a method for collaborative trading of green electricity and green certificates based on a regional common electricity market, which can promote the consumption of renewable energy and facilitate the smooth transition of the electricity market to a unified market.

[0007] Technical solution: A method for collaborative trading of green electricity and green certificates under a regional common electricity market. The method divides the power system into local electricity markets according to jurisdictions, and then constructs a regional common electricity market from a number of local electricity markets. A regional common electricity market equilibrium model is established for the regional common electricity market. The regional common electricity market equilibrium model includes an electricity trading equilibrium model and a green certificate trading equilibrium model, which are used to realize a green electricity trading mechanism and a green certificate trading mechanism respectively;

[0008] The power trading mechanism aims at optimizing the benefits in the local power market, taking into account the renewable energy quota demand in the province, and forming a transaction quota curve between the local power market for the power delivered and the power purchased;

[0009] The green certificate trading mechanism uses the form of generalized Nash game to distribute the environmental value of green electricity. Thermal power plants in the regional common electricity market form a regional green certificate market quotation curve based on their own power sales plans and quota tasks, and then conduct centralized clearing in the form of generalized Nash game.

[0010] Furthermore, the regional common electricity market equilibrium model is composed of N local electricity markets, each of which contains Gn thermal power units and Rn new energy stations; the cost of thermal power units and renewable energy generation is a quadratic function of their output; thermal power units and renewable energy in each local electricity market provide guaranteed power supply for the local electricity demand, and each local electricity market opens a certain ratio of market share to organize the bidding space of the regional electricity market; 1 unit of green certificate can be obtained for every 1MWh of green electricity produced;

[0011] The regional common electricity market equilibrium model specifically includes:

[0012] (1) Electricity trading equilibrium model

[0013] The cost of power generation in the local electricity market includes the fuel cost of thermal power units, the cost of renewable energy power generation and the cost of purchasing certificates in the regional green certificate market, minus or adding the income or expenditure from electricity sales in the regional market. The mathematical expression is as follows:

[0014]

[0015] In the above formula, the first term With the second Represents the cost function of thermal power generation and renewable energy generation, which are respectively With new energy output The third term is the cost of purchasing green certificates in the local power market i; the fourth term is the sales revenue or expenditure of the surplus or deficit electricity in the local power market i in the regional power market;

[0016] Furthermore, the cost function of thermal power generation in the local electricity market and renewable energy generation has the following relationship:

[0017]

[0018] in is the regional market green certificate and electricity transaction price matrix, where It is an n*k matrix, where n represents the index of the province in the region, k represents the index of the new energy power station in the nth local power market, and the elements in the matrix are the green certificate prices of the renewable energy station; It is a 1*(N-1) matrix, and the elements in the matrix are the prices of electricity interactions between local electricity markets; is the interaction power between local power market i and local power market n, there exists in represents the output of thermal power units in the interactive power, It represents the output of renewable energy stations;

[0019] The price of green certificates and electricity interaction is calculated according to the market supply and demand relationship as follows:

[0020]

[0021] Among them, x n,k,t d n,k,t represents the local electricity market n, k represents the intercept and slope of the renewable energy station green certificate supply function, which is related to the coefficient of the quadratic function of power generation cost, A and μ are constants greater than zero, It also represents the deficit electricity demand of the local electricity market i / n, which is determined by the local electricity market n / i;

[0022] The above electricity market equilibrium model also needs to meet the following balance constraints and thermal power unit operation constraints, where D n is the electricity demand of the local electricity market n; are the upper and lower limits of the operation of unit j in the local power market;

[0023]

[0024]

[0025] (2) Green Certificate Trading Equilibrium Model

[0026] Each renewable energy site forms a competitive relationship to meet the green certificate needs of each thermal power station. Since each participant is subject to the green certificate quantity balance constraint, there is coupling between their strategy sets. The strategy space of each participant depends on the strategies of other participants. Then, the generalized Nash game is used to describe the competitive relationship between the participants, as follows:

[0027] Participants are renewable energy sites, with k representing their index;

[0028] strategy, for the power generation of the participants, using express;

[0029] Payment is the income of the participants, including the electricity income through the regional common electricity market, green certificate income minus the cost of renewable energy generation, expressed as follows:

[0030]

[0031] The green certificate trading mechanism also has the following constraints:

[0032] Green certificate quantity constraint: The number of certificates sold by renewable energy stations in the green certificate market shall not exceed the green electricity excluding the station’s own quota, which can be expressed mathematically as:

[0033]

[0034] Regional market power sales constraint: The power sales of renewable energy stations in the local power market in the regional common power market shall not exceed their total power generation, which can be expressed mathematically as:

[0035]

[0036] Green certificate quantity balance constraint:

[0037]

[0038] Output constraints of renewable energy sites:

[0039]

[0040] Energy stations in the local power market need to consider the transaction price of the green certificate market when making power market decisions. and trading volume The impact of; When making decisions on the green certificate market, the output of each thermal power unit needs to be considered Form a two-tier relationship;

[0041] There is a coupling relationship between the upper and lower layers of the model. This method transforms it into constraints for regional common green certificate market decision-making through KKT conditions and duality theory, thereby transforming the two-layer model into a single-layer optimization problem for solution. The transformed single-layer optimization problem has complementary relaxation conditions in the form of 0≤a⊥b≥0, which is linearized using the big M method.

[0042] Furthermore, the power trading mechanism under the regional common power market is as follows:

[0043] (101) Each power plant in each local power market shall report its power generation status, forecast power generation plan and quotation curve to its trading center;

[0044] (102) The trading center of the local power market forms a trading quota curve for the amount of electricity delivered and purchased based on the information reported by the power plants in the region and the load forecast, with the goal of maximizing the benefits within the local trading area and taking into account the renewable energy quota demand in the trading market in the region;

[0045] (103) The common trading market formulates a trading plan between local power markets based on the trading quotation curve reported by the local power market, and then issues it to each local power market to formulate its own power purchase plan.

[0046] Furthermore, the green certificate trading mechanism under the regional common electricity market is as follows:

[0047] (201) The trading center of the local electricity market allocates renewable energy quotas to various types of power plants in the region according to the power purchase plan, and there is a certain amount of α in the total power output of each power plant in the region. i share comes from renewable energy generation;

[0048] (202) The renewable energy sites in the region included in the local electricity market take into account their own power generation costs and the remaining green certificates to form a regional green certificate market quotation curve;

[0049] (203) Thermal power plants in the region corresponding to the local electricity market form a regional green certificate market quotation curve based on their own electricity sales plans and quota tasks;

[0050] (204) The green certificate market within the region corresponding to the regional common market is centrally cleared in the form of a generalized Nash game.

[0051] Beneficial effects: The present invention can cope with the difficulty of integrating the green environmental value of renewable energy in various types of electricity / equity product transactions. The method proposes a regional common electricity market collaborative transaction model that includes electricity transactions and green certificate transactions; the provincial market (local electricity market) is retained in electricity transactions, and each provincial power grid company organizes electricity transactions in the province and uses non-cooperative games in the regional market to sell surplus electricity or purchase electricity from outside the province; finally, in green certificate transactions, the regional common electricity market uses the generalized Nash game to allocate the environmental value of green electricity, thereby achieving a balance between green certificate and green electricity transactions under the regional common electricity market. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 It is a framework diagram of the electricity and green certificate trading mechanism under the regional common electricity market;

[0053] Figure 2It is a two-layer optimization framework for the corresponding model of the regional common electricity market;

[0054] Figure 3 is a typical daily load demand diagram of each province in the embodiment;

[0055] Figure 4 It is the internal electricity balance and green certificate allocation of each province in scenario 1;

[0056] Figure 5 It is the internal electricity balance and green certificate allocation of each province in scenario 2;

[0057] Figure 6 The impact of changes in the sending-end quota on the amount of electricity transmitted;

[0058] Figure 7 The impact of changes in receiving-end quotas on power generation within the province;

[0059] Figure 8 It is the change in the resource allocation coefficient of each renewable energy site in the green certificate transaction caused by the change in the sending / receiving end quota. DETAILED DESCRIPTION

[0060] To illustrate the technical solution disclosed in the present invention in detail, a further introduction is given below in conjunction with the accompanying drawings.

[0061] Taking into account the different energy characteristics of different regions, such as the different advantages of wind power generation, hydropower generation and thermal power generation, there will be different energy supply and demand between regions. In this regard, achieving a smooth transition of the electricity market to a regional unified market is a necessary development trend in the future.

[0062] According to the electricity trading in the power grid, green electricity trading can be further divided into two categories: green electricity trading and green certificate trading. Green electricity trading will trade green electricity and green certificates to electricity users simultaneously, providing power generation companies in parity new energy projects with green electricity value benefits (green electricity) and environmental attribute benefits (green certificates) at one time.

[0063] Based on the solution provided by the above invention, in the actual application process, we regard the power market of each province as a local power market, and establish a regional common power market between each province. The regional common power market includes the establishment of a trading center for processing green power transactions between various local power markets.

[0064] (1) Electricity trading

[0065] The basic feature of the regional common power market model in power trading is to retain the local power market. This embodiment is explained in terms of provincial units. For the provincial market, each provincial power grid company organizes power trading in the province and sells surplus electricity or purchases electricity from outside the province through the inter-provincial and inter-regional market. The organizational process is as follows:

[0066] (101) Power plants in the province submit quotation curves including unit maintenance, power generation costs, operating parameters, and predicted power generation plans to their provincial grid companies;

[0067] (102) Each provincial power grid company shall formulate an inter-provincial transaction quota curve for the amount of electricity transmitted and purchased based on the declaration of power plants in the province and the load forecast in the province, with the goal of optimizing the interests of the province and taking into account the demand for renewable energy quotas in the province;

[0068] (103) Regional power grid companies formulate inter-provincial trading plans based on the inter-provincial trading quotation curves of each province;

[0069] (104) Each province determines its electricity purchasing plan based on the inter-provincial trading plan.

[0070] In the above organizational form, power plants within the province cannot speculate by taking advantage of the differences between provinces or within the provincial market, thus avoiding the cost transfer phenomenon where the price of electricity transmitted to other provinces is lower than the price of electricity trading within the province.

[0071] (2) Green Certificate Trading

[0072] In the green certificate transaction, the regional common power market model uses the generalized Nash game to distribute the environmental value of green power. The organizational process is as follows:

[0073] (201) Each province allocates the renewable energy quota to each power plant according to the power purchase plan of multiple types of power plants in the province, and forms the quota task of each (thermal power, renewable energy) power plant i, that is, each power plant must ensure that α of its total power output i share comes from renewable energy generation.

[0074] (202) Renewable energy stations in the regional common electricity market take into account their own power generation costs and remaining green certificates to form a regional green certificate market quotation curve;

[0075] (203) Thermal power plants in each province form a regional green certificate market quotation curve based on their own electricity sales plans and quota tasks;

[0076] (204) The green certificate market in each province is centrally cleared in the form of a generalized Nash game.

[0077] Under the above organizational form, renewable energy sites in the region can trade green electricity that exceeds their own quota in the form of green certificates in the regional green certificate market with all thermal power plants in the region that need green certificates, so that people within and outside the province can equally enjoy the benefits brought by the optimized resource allocation.

[0078] Based on the above-mentioned electric energy trading and green certificate trading mechanism, the present invention constructs a regional common market green electricity trading model, combined with Figure 1As shown, in this embodiment, the local power market mentioned in the above technical solution is processed as a provincial unit, corresponding to the provincial power market, and thus there are:

[0079] Each provincial power grid system sets up a trading center, taking into account the power generation costs and benefits within the province to give priority to guaranteeing the power of the province, including forecasting the power load of the province, and then setting power generation quotas for each thermal power plant, and submitting quotations or power purchase requests to the regional common power market for surplus or green power;

[0080] The regional common power market is jointly established by several provincial power markets to realize the distribution and trading of electric energy in the region. The regional common power market has a trading center to implement the power trading and green certificate trading mechanism, which is handled in two modes: the power market and the green certificate market. The power market is responsible for the trading of electricity in the regional common power market, safety verification and congestion management, and then forms an inter-provincial trading plan and distributes the trading plan to each provincial power market; the green certificate market is responsible for the clearing of the regional common green certificate market under the generalized Nash equilibrium, including the transfer and cancellation of green certificates.

[0081] For the regional common market equilibrium model, it is constructed as follows:

[0082] First, we make the following settings and considerations:

[0083] 1) A regional common power market consisting of N local power markets (provincial power grids), each province containing Gn thermal power units and Rn new energy stations;

[0084] 2) Consider and construct the cost of thermal power generation units and renewable energy generation in each province as its output, including establishing the corresponding quadratic function relationship representation;

[0085] 3) Assuming that the thermal power units and renewable energy in each province in the regional common market provide guaranteed power supply for the province's electricity needs (excluding revenue), each province opens a certain percentage of market share to organize the bidding space in the regional power market;

[0086] 4) It is set that 1 unit of green certificate can be obtained for every 1MWh of green electricity produced.

[0087] 1. Construction of power market model

[0088] First, consider the cost of power generation in the province, including the fuel cost of thermal power units, the cost of renewable energy power generation and the cost of purchasing certificates in the regional green certificate market, minus or adding the income or expenditure from power sales in the regional market, as follows:

[0089]

[0090] In the above formula, the first term With the second Represents the cost function of thermal power generation and renewable energy generation, which are + thermal power generation With new energy output The function is a quadratic function, as shown in formula (2):

[0091]

[0092] The third item is the cost of province i purchasing certificates in the green certificate market; the fourth item is the income or expenditure from the sale of surplus or deficit electricity in the regional power market. is the regional market green certificate and electricity transaction price matrix, where It is an n*k matrix, where n represents the index of the province in the region, k represents the index of the new energy power station in the nth province, and the elements in the matrix are the green certificate prices of the renewable energy station; It is a 1*(N-1) matrix, and the elements in the matrix are the prices of electricity exchange between provinces. The price of green certificates and electricity exchange is calculated according to the market supply and demand relationship. The specific calculation is shown in formula (3):

[0093]

[0094] Among them, x n,k,t d n,k,t It represents the intercept and slope of the green certificate supply function of the renewable energy station in province n and k, which is related to the coefficient of the quadratic function of power generation cost in equation (2). A and μ are constants greater than zero. It also means that the surplus electricity demand of province i / n will be met by province n / i. is the interaction power between province i and province n, in represents the output of thermal power units in the interactive power, It represents renewable energy sites.

[0095] The above electricity market equilibrium model also needs to meet the following balance constraints and thermal power unit operation constraints, where D n is the electricity demand of province n; are the upper and lower operating limits of unit j in province n.

[0096]

[0097]

[0098] (II) Green Certificate Market Model

[0099] In the regional common green certificate market, the renewable energy sites form a competitive relationship to meet the green certificate needs of each thermal power station. Since each participant is subject to the balance constraint of the number of green certificates, there is coupling between their strategy sets, that is, the strategy space of each participant depends on the strategies of other participants. Then, the generalized Nash game is used to describe the competitive relationship between the participants, as follows:

[0100] a. Participants, which are renewable energy sites in each province, with k representing their index;

[0101] b. Strategy, for the power generation of participants (provinces), express;

[0102] c. Payment is the income of the participants, including the electricity income and green certificate income through the regional common market minus the cost of renewable energy generation, expressed as follows:

[0103]

[0104] The above green certificate market also has the following constraints:

[0105] Green certificate quantity constraint: The number of certificates sold by renewable energy stations in the green certificate market shall not exceed the green electricity excluding the station’s own quota.

[0106]

[0107] The corresponding power sales constraint of the regional common power market: the power sales of renewable energy stations in the regional market through the provincial market shall not exceed their total power generation, which can be expressed as:

[0108]

[0109] Green certificate quantity balance constraint:

[0110]

[0111] Output constraints of renewable energy sites:

[0112]

[0113] (III) Model transformation and solution.

[0114] The power generation decision of renewable energy stations in the electricity and green certificate markets has an interactive relationship. When making decisions in the electricity market, the station needs to consider the transaction price of the green certificate market. and trading volume The impact of; When making decisions on the green certificate market, the output of each thermal power unit needs to be considered Composition Figure 2 The two-tier relationship shown.

[0115] There is a strong coupling relationship between the upper and lower layers of the regional common electricity market model, which is difficult to solve directly. The KKT condition and duality theory are used to transform it into the constraint conditions of the regional common green certificate market decision-making, thereby transforming the two-layer model into a single-layer optimization problem. The transformed single-layer optimization problem has complementary relaxation conditions in the form of 0≤a⊥b≥0, which is linearized using the big M method.

[0116] Example: Consider two provinces interconnected by UHV transmission lines participating in a regional common electricity market. The parameters of power plants in each province are shown in Table 1. The typical daily load of each province is as follows: Figure 3 As shown. Considering the large initial investment in renewable energy power generation equipment, it is assumed that the intercept and slope of its marginal cost are greater than those of thermal power units. Considering the current renewable energy stock subsidy project, it is assumed that the intercept and slope of the green certificate supply function are 0.3 of its corresponding marginal cost. Simplify the market supply and demand relationship of the electricity interactive price to

[0117] Table 1: Parameters of power plants in various provinces

[0118]

[0119]

[0120] Consider the following two scenarios:

[0121] Scenario 1: Non-cooperative and competitive power markets in various provinces + inter-regional matching of green certificate resources under centralized matching: In the power market, each province determines the power generation of thermal power units and renewable energy units based on the minimum power generation cost within the province, and the green certificate market calculates the supply and demand relationship of green certificates based on the power generation plan of the power market, and allocates green certificate resources in the form of centralized matching. In this scenario, there is no mutual influence between the power market and the green certificate market.

[0122] Scenario 2: Non-cooperative competition in electricity markets among provinces + regional matching of green certificate resources under generalized Nash game: Based on the analysis of the method provided by the present invention, it is found that there is a mutual influence relationship between the two markets.

[0123] Figure 4 The internal electricity balance and green certificate allocation of each province in scenario 1. In terms of electricity balance: it can be seen that the power supply and demand balance of Provinces 1 and 2 can be met in the non-cooperative regional common electricity market. Comparing the two figures, it is easy to see that driven by the goal of minimizing the cost of power generation within the province, Province 1 will use the output of parity power generation - thermal power plant 1 (G1) as much as possible to meet the power supply within the province, and use renewable energy power generation for external transmission; because the power generation cost of renewable energy station 3 (R3) in Province 2 is higher than the external transmission power, the electricity demand in Province 2 is mainly met by its internal thermal power plant 3 and external transmission power. Assuming that the renewable energy quota of Province 1 is 20% and that of Province 2 is 15%, Figure 5(c) is the distribution of green certificates in the regional common market under centralized matchmaking. It can be seen that the green certificate demand of G1 and G2 is mainly met by R1 and R2, which is because the slope of the green certificate cost of R1 and R2 is smaller than that of R3.

[0124] Figure 5 The internal electricity balance and green certificate distribution of each province in Scenario 2. Different from Scenario 1, in Scenario 2, the power generation of thermal power units in Provinces 1 and 2 was greatly reduced on the premise of meeting their own power supply and demand balance, with a reduction of 48.36% and 28.31% in Provinces 1 and 2 respectively. The above results indirectly indicate that the proposed regional common market for electricity-green certificates can promote the consumption of renewable energy. The following calculation formula is used to express the renewable energy consumption rate within the province, and Scenario 2 is 83.2% higher than Scenario 1.

[0125]

[0126] Different from Situation 1, the trading volume of green certificates in R3 is relatively large due to the influence of social welfare, which is consistent with the principle of "high-low matching" and more in line with the development law of market economy.

[0127] 1) The impact of changes in sending-end quotas on the structure of power transmission.

[0128] Taking Province 1 as an example, Figure 6 The effect of the transmission quota change on the internal thermal power and renewable energy power transmission is given. Figure 6 It can be seen that when the quota of the sending end is lower than 35%, the amount of electricity transmitted by G1 is on the rise and that transmitted by R1 is on the decline, but the overall change is not obvious; when the quota is higher than 35%, the amount of electricity transmitted by G1 increases significantly; when it is higher than 40%, the amount of electricity transmitted by R1 decreases significantly, and when it is higher than 50%, the amount of electricity transmitted by R2 decreases to 0. The reasons are as follows: the higher the quota of renewable energy, the higher the amount of renewable energy electricity consumed in the province. Under the condition that the regional electricity demand remains unchanged, more renewable energy electricity is consumed locally, and the amount of electricity transmitted is reduced, squeezing the local power supply space of thermal power units, so the amount of electricity transmitted by thermal power increases accordingly.

[0129] 2) The impact of changes in receiving-end quotas on local consumption of renewable energy.

[0130] Take Province 2 as an example, Figure 7 The effect of the receiving-end grid quota change on the internal thermal power and renewable energy power generation is given. Figure 7 It can be seen that when the receiving end quota is lower than 35%, the power generation of G2 shows an upward trend; when the quota is higher than 35%, the power generation of G2 increases significantly; when it is higher than 40%, the power generation of G2 tends to be stable, and the power generation of R3 does not change during this period.

[0131] The reasons are analyzed as follows: the increase in the receiving-end quota will reduce the inflow of transmitted electricity. Due to the mismatch between the transmission and receiving-end quotas, the electricity is required to fulfill the quota task before being transmitted, so the transmitted electricity does not contribute to the completion of the receiving-end quota task. If the power supply demand in the province remains unchanged, the internal thermal power plants and renewable energy sites will increase their power generation if the transmitted electricity is reduced. Since the renewable energy generation in the regional common market proposed by the present invention has a part of the green certificate value in addition to the value of electricity, renewable energy is always in full production regardless of how the quota changes.

[0132] 3) The impact of changes in the quotas of the sending / receiving end on the trading volume of green certificates

[0133] Figure 8 The effect of the quota change on the sending / receiving end on the resource allocation coefficient of each renewable energy station in the green certificate transaction is given. Figure 8 (a) It can be seen that, compared with the sending end, as the quota of the receiving end increases, the allocation coefficient of R1 in the green certificate market gradually increases, with the maximum increase of up to 83.24%; but due to the principle of "high-low matching", R2 has a price advantage in the green certificate market, and its allocation coefficient is less significantly affected by the changes in the quotas of the sending / receiving ends. In addition, compared with the sending end, as the quota of the receiving end increases, the allocation coefficient of R3 in the green certificate market gradually decreases, with the maximum decrease to 56.76%, and the quota of the sending end has a less significant impact on its allocation coefficient.

[0134] The above results show that the quota of the receiving area has a significant impact on the allocation coefficient of renewable energy stations in both the sending and receiving areas, among which it is positively correlated with the renewable energy stations in the sending area and negatively correlated with the renewable energy stations in the receiving area.

[0135] In summary, the verification of the scheme described in the present invention shows that the regional common market green electricity and green certificate collaborative trading mode proposed in the present invention can reduce the power generation of thermal power units at both ends of the transmission / receiving by an average of 38.33%, and increase the renewable energy consumption rate by 83.2%; the increase in the quota at the sending end will squeeze the power supply space of local thermal power units, resulting in a corresponding increase in the amount of thermal power transmitted; the increase in the quota at the receiving end will reduce the amount of power transmitted at the sending end, and the power generation of the thermal power units and renewable energy stations at the receiving end will increase accordingly; the quota in the receiving area has a significant impact on the allocation coefficient of renewable energy stations in green certificate transactions, among which it is positively correlated with the renewable energy stations in the sending area, and negatively correlated with the receiving area.

Claims

1. A method for collaborative trading of green electricity and green certificates in a regional common electricity market, characterized in that: The method divides the power system into local power markets according to jurisdictions, and then constructs a regional common power market from several local power markets. A regional common power market equilibrium model is established for the regional common power market. The regional common power market equilibrium model includes a power trading equilibrium model and a green certificate trading equilibrium model, which are used to realize the green power trading mechanism and the green certificate trading mechanism respectively. The power trading mechanism aims at optimizing the benefits in the local power market, taking into account the renewable energy quota demand in the region to which the local power market belongs, and forming a transaction quotation curve between the local power market and the purchased power. The green certificate trading mechanism uses the form of generalized Nash game to distribute the environmental value of green electricity. Thermal power plants in the regional common electricity market form a regional green certificate market quotation curve based on their own power sales plans and quota tasks, and then conduct centralized clearing in the form of generalized Nash game.

2. The method for collaborative trading of green electricity and green certificates in a regional common electricity market according to claim 1, characterized in that: The regional common electricity market equilibrium model consists of N local electricity markets, each of which contains Gn thermal power units and Rn new energy stations; the cost of thermal power units and renewable energy generation is a quadratic function of their output; thermal power units and renewable energy in each local electricity market provide guaranteed power supply for the local electricity demand, and each local electricity market opens a certain ratio of market share to organize the bidding space of the regional electricity market; One unit of green certificate can be obtained for every 1MWh of green electricity produced; The regional common electricity market equilibrium model includes: (1) Electricity trading equilibrium model The cost of power generation in the local electricity market includes the fuel cost of thermal power units, the cost of renewable energy power generation and the cost of purchasing certificates in the regional green certificate market, minus or adding the income or expenditure from electricity sales in the regional market. The mathematical expression is as follows: In the above formula, the first term With the second Represents the cost function of thermal power generation and renewable energy generation, which are respectively With new energy output The third term is the cost of purchasing green certificates in the local power market i; the fourth term is the sales revenue or expenditure of the surplus or deficit electricity in the local power market i in the regional power market; Furthermore, the cost function of thermal power generation in the local electricity market and renewable energy generation has the following relationship: in is the regional market green certificate and electricity transaction price matrix, where It is an n*k matrix, where n represents the index of the province in the region, k represents the index of the new energy power station in the nth local power market, and the elements in the matrix are the green certificate prices of the renewable energy station; It is a 1*(N-1) matrix, and the elements in the matrix are the prices of electricity interactions between local electricity markets; is the interaction power between local power market i and local power market n, there exists in represents the output of thermal power units in the interactive power, It represents the output of renewable energy stations; The price of green certificates and electricity interaction is calculated according to the market supply and demand relationship as follows: Among them, x n,k,t ,d n,k,t represents the local electricity market n, k represents the intercept and slope of the renewable energy station green certificate supply function, which is related to the coefficient of the quadratic function of power generation cost, A and μ are constants greater than zero, It also represents the deficit electricity demand of the local electricity market i / n, which is determined by the local electricity market n / i; The above electricity market equilibrium model also needs to meet the following balance constraints and thermal power unit operation constraints, where D n is the electricity demand of the local electricity market n; are the upper and lower limits of the operation of unit j in the local power market; (2) Green Certificate Trading Equilibrium Model Each renewable energy site forms a competitive relationship to meet the green certificate needs of each thermal power station. Since each participant is subject to the green certificate quantity balance constraint, there is coupling between their strategy sets. The strategy space of each participant depends on the strategies of other participants. Then, the generalized Nash game is used to describe the competitive relationship between the participants, as follows: Participants are renewable energy sites, with k representing their index; strategy, for the power generation of the participants, using express; Payment is the income of the participants, including the electricity income through the regional common electricity market, green certificate income minus the cost of renewable energy generation, expressed as follows: The green certificate trading mechanism also has the following constraints: Green certificate quantity constraint: The number of certificates sold by renewable energy stations in the green certificate market shall not exceed the green electricity excluding the station’s own quota, which can be expressed mathematically as: Regional market power sales constraint: The power sales of renewable energy stations in the local power market in the regional common power market shall not exceed their total power generation, which can be expressed mathematically as: Green certificate quantity balance constraint: Output constraints of renewable energy sites: Energy stations in the local electricity market need to consider the transaction price of the green certificate market when making decisions in the electricity market. and trading volume The impact of; When making decisions on the green certificate market, the output of each thermal power unit needs to be considered Form a two-tier relationship; There is a coupling relationship between the upper and lower layers of the model. This method transforms it into constraints for regional common green certificate market decision-making through KKT conditions and duality theory, thereby transforming the two-layer model into a single-layer optimization problem for solution. The transformed single-layer optimization problem has complementary relaxation conditions in the form of 0≤a⊥b≥0, which is linearized using the big M method.

3. The method for collaborative trading of green electricity and green certificates in a regional common electricity market according to claim 1 or 2, characterized in that: The specific electricity trading mechanism under the regional common electricity market is as follows: (101) Each power plant in each local power market shall report its power generation status, forecast power generation plan and quotation curve to its trading center; (102) The trading center of the local power market forms a trading quota curve for the amount of electricity delivered and purchased based on the information reported by the power plants in the region and the load forecast, with the goal of maximizing the benefits within the local trading area and taking into account the renewable energy quota demand in the trading market in the region; (103) The common trading market formulates a trading plan between local power markets based on the trading quotation curve reported by the local power markets, and then issues it to each local power market to formulate its own power purchase plan.

4. The method for collaborative trading of green electricity and green certificates in a regional common electricity market according to claim 1 or 2, characterized in that: The green certificate trading mechanism under the regional common electricity market is as follows: (201) The trading center of the local electricity market allocates renewable energy quotas to various types of power plants in the region according to the power purchase plan, and there is a certain amount of α in the total power output of each power plant in the region. i share comes from renewable energy generation; (202) The renewable energy sites in the region included in the local electricity market take into account their own power generation costs and the remaining green certificates to form a regional green certificate market quotation curve; (203) Thermal power plants in the region corresponding to the local electricity market form a regional green certificate market quotation curve based on their own electricity sales plans and quota tasks; (204) The green certificate market within the region corresponding to the regional common market is centrally cleared in the form of a generalized Nash game.

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