Electricity market, carbon market and green certificate market integrated transaction evaluation method

Abstract

The invention provides an electricity market, carbon market and green certificate market integrated transaction evaluation method, and relates to the technical field of electricity market transaction evaluation. The method comprises the following steps: constructing an electricity-certificate-carbon integrated transaction operation mechanism according to operation conditions of an electricity market, a carbon market and a green certificate market; according to the clearing models of the electricity market, the carbon market and the green certificate market, screening out influence factors of each electricity-certificate-carbon market and coupling factors of interaction influence among the markets, and qualitatively describing the influence of the change of market operation parameters on the integrated transaction; according to an economics principle, a function relationship between factors is constructed, a model is established from a macroscopic level, the influence of the change of single and multiple market operation parameters on integrated transaction is calculated, and a reference is provided for setting policy parameters of an electricity market, a carbon market and a green certificate market. According to the method, quantitative analysis research on the electricity-certificate-carbon combined market is realized. And a reference is provided for formulating an electricity-certificate-carbon combined market policy goal.

Description

Technical Field

[0001] The present invention relates to the technical field of power market transaction evaluation, and in particular to a transaction evaluation method for integrating power market, carbon market and green certificate market. Background Art

[0002] Green certificate trading and carbon trading are of great significance to promoting renewable energy consumption and carbon emission reduction. Carbon trading and green certificate trading, from the two perspectives of controlling carbon emissions and promoting renewable energy consumption, respectively, help the energy system achieve a clean and low-carbon transformation through the guidance of the market and the coordination of power trading. However, at present, the various markets operate relatively independently, the linkage mechanism between the markets is not clear, and no effective connection has been formed. The current green certificate market has not been established for a long time, the carbon market is in the initial stage of development, and the power market is still in the process of continuous improvement. There are few studies on the integrated trading of electricity, certificate and carbon. There is no research on the analysis of the interaction between electricity, certificate and carbon and the influencing factors of coupling, and the quantitative evaluation model and simulation of the corresponding degree between the various markets have basically not been established.

[0003] Most of the existing studies have only analyzed the mutual impact between the electricity market and the carbon market, the electricity market and the green certificate market, or the green certificate market and the carbon market, and have failed to study the overall operation of the electricity-certificate-carbon joint operation; that is, the existing studies have failed to find out the coupling factors of the interaction between the electricity market, the carbon market and the green certificate market, and have failed to quantitatively describe the impact of changes in single or multiple market operating parameters on the electricity-certificate-carbon joint market; the above studies only study the decision-making behavior of a few market participants in a certain region from a micro level, and lack a macro analysis of the decision-making of a certain type of market group participating in the electricity-certificate-carbon joint market from the provincial, regional or national levels. Summary of the invention

[0004] The present invention aims to solve at least one of the technical problems existing in the prior art.

[0005] To this end, the present invention provides an integrated transaction evaluation method for the electricity market, carbon market and green certificate market.

[0006] The present invention proposes an integrated transaction evaluation method for the electricity market, carbon market and green certificate market, comprising:

[0007] According to the operation status of the electricity market, carbon market and green certificate market, build an electricity-certificate-carbon integrated trading operation mechanism;

[0008] Based on the clearing models of the electricity market, carbon market and green certificate market, the influencing factors of the electricity-certificate-carbon market and the coupling factors of the interaction between the markets are screened out, and the impact of changes in market operating parameters on integrated transactions is qualitatively described;

[0009] Based on the principles of economics, the functional relationship between factors is constructed, and a model is established from a macro level to calculate the impact of changes in single and multiple market operating parameters on integrated transactions, providing a reference for the setting of policy parameters for the electricity market, carbon market and green certificate market.

[0010] According to the above technical solution of the present invention, a method for evaluating integrated trading of electricity market, carbon market and green certificate market may also have the following additional technical features:

[0011] In the above technical solution, the construction of the electricity-certificate-carbon integrated trading operation mechanism includes:

[0012] Clarify the boundaries between the electricity market, carbon market and green certificate market, analyze the market scope from the perspectives of the participants in each market, the decision-making behavior of the participants, and the market clearing model, and then conduct a logical analysis of the correlation between the electricity, certificate and carbon markets to build an integrated electricity, certificate and carbon trading operation mechanism.

[0013] In the above technical solution, the clearing model of the green certificate market includes:

[0014] The organizer of the green certificate trading market adopts centralized matching trading rules based on the quotations of market participants, with the goal of maximizing the total national benefit, and conducts unified clearing; among which, the total national benefit is the difference between the social welfare generated by the total green certificates of each trading match and the transaction cost between the matching pairs, and the objective function of the clearing model is:

[0015] max F=∑(q i ρ m -q j ρ n )

[0016] Among them, ρ m is the price offered by the mth green certificate demander, q i The number of green certificates required, ρ n The quotation for the nth green power manufacturer, q j The number of green certificates sold for it;

[0017] Green certificate demanders can choose to participate in the green certificate trading market to complete the consumption quota requirements, or accept fines if they fail to complete the task, depending on their consideration of income. In order to explore the impact of renewable energy consumption quotas on green certificate demanders, a bidding function with the minimum payment of power sales companies, power grid companies, large users and other entities as the objective function is established:

[0018] min W=Σq i ρ m +M TGC ρ TGC (λγQ i -q i )

[0019] Among them, q i ρ is the cost of purchasing green certificates for power sales company i, M is the penalty coefficient for not completing the quota consumption target, ρ is the green certificate price at the time of clearing, λ is the green certificate consumption ratio, γ is the conversion coefficient between electricity and green certificates, Q i Selling electricity to power sales companies;

[0020] Renewable energy power generation companies participate in the green certificate market to sell green certificates to obtain higher profits. The bidding function of renewable energy power generation companies is:

[0021] maxW=∑q j ×ρ n

[0022] The bidding function constraints of the renewable energy power generators include: upper and lower limit constraints on the number of green certificate transactions, green certificate quotation and green certificate price constraints, and market balance constraints.

[0023] In the above technical solution, according to the clearing model of the green certificate market, it can be concluded that the influencing factors of the green certificate market include green certificate trading volume, green certificate price upper limit, green certificate price lower limit, green certificate clearing price, green certificate quotation, green certificate consumption ratio required by the policy, penalty coefficient for failure to complete consumption target, green certificate supply and green certificate demand;

[0024] Among them, the green certificate trading volume reflects the activity of the green certificate market;

[0025] Green certificate price, green certificate supply, green certificate demand, and green certificate quotation reflect the supply and demand relationship of green certificates in the market;

[0026] The upper and lower limits of green certificate prices, the green certificate consumption ratio required by policies, and the penalty coefficient for failure to achieve the consumption target reflect the influence of regulatory authorities and policies.

[0027] In the above technical solution, the carbon market clearing model includes:

[0028] Clearing with the goal of maximizing social benefits:

[0029] max F=∑(q i ρ m -q j ρ n )

[0030] Among them, q i is the number of carbon quotas proposed by the i-th demander, ρ m Quote for it;q j is the amount of carbon quota proposed by the jth supplier, ρ n Make an offer for it;

[0031] The main participants in the carbon market include traditional energy power generators that sell or purchase carbon quotas. The bidding function of the manufacturers selling carbon quotas is:

[0032] maxW s =q j ×ρ n

[0033] Purchase of carbon quotas Traditional energy power generators can choose to purchase carbon quotas to meet the requirements, or not to purchase carbon quotas and accept penalties. The bidding function is:

[0034]

[0035] Among them, q i ×ρ m The cost of purchasing carbon quotas, for the penalties faced for insufficient carbon quotas;

[0036] Carbon market trading constraints include: the sale and purchase of carbon quotas cannot exceed the upper and lower limits of quota trading quantities, the upper and lower limits of carbon quota market quotations, and market balance constraints.

[0037] In the above technical solution, according to the carbon market clearing model, it can be concluded that the influencing factors of the carbon market include: carbon quota trading volume, carbon quota price upper limit, carbon quota price lower limit, carbon quota clearing price, carbon quota quota quota, initial carbon quota allocated by the regulatory authorities, penalty coefficient for excess carbon emissions, carbon quota supply and carbon quota demand;

[0038] Among them, the carbon quota trading volume reflects the activity of the carbon market;

[0039] Carbon quota prices, carbon quota supply, carbon quota demand, and carbon quota quotations reflect the supply and demand relationship of carbon quotas in the market;

[0040] The upper and lower limits of carbon quota prices, the carbon quotas initially allocated by regulatory authorities, and the penalty coefficient for excess carbon emissions reflect the influence of regulatory authorities and policies.

[0041] In the above technical solution, the electricity market clearing model includes:

[0042] Considering the impact of the green certificate market and the carbon market on the electricity market, the power generation costs for conventional thermal power plants and thermal power plants equipped with carbon capture devices are:

[0043]

[0044] Among them, aP 2 +bP+c is the coal consumption cost, P is the output of the thermal power plant, is the cost of purchasing carbon emission rights, ρ CO2 is the carbon price, is the amount of carbon emission rights purchased or sold, ργλPΔt is the transaction cost of green certificates, and traditional energy power generators can purchase green certificates to offset carbon emissions, ρ TGC is the green certificate price, γ is the conversion coefficient between renewable energy electricity and green certificate quantity, and λ is the green certificate ratio coefficient;

[0045] For renewable energy generators, the cost of electricity generation is:

[0046] f w =aP+b-ρq TGC

[0047] Among them, aP+b is the power generation cost of renewable energy generators, q TGC The number of green certificates sold;

[0048] The bidding function of traditional energy generators is:

[0049]

[0050] Among them, 2aP r +b is the marginal cost of power generation in thermal power plants, is the marginal cost of thermal power plants participating in the carbon market, λγρ is the marginal cost of thermal power plants participating in the green certificate market;

[0051] The quotation function of green power manufacturers is:

[0052]

[0053] Where a is the power generation cost of renewable energy generators, and The marginal benefits generated by green power manufacturers participating in the green certificate market;

[0054] Traditional energy generator profit model:

[0055]

[0056] Green power manufacturer profit model:

[0057] max U w,j =(P j ρ-aP j 2 -bP j -c)Δt+ρ TGC q TGC

[0058] User electricity purchase cost model: Users participate in electricity energy trading based on the minimum electricity purchase cost target. Due to the impact of the renewable energy consumption responsibility assessment system, the user's electricity purchase cost is composed of the electricity purchase fee in the electricity energy market and the cost of purchasing green certificates. The objective function is:

[0059] min F Ld =P k ρ k +ρ TGC q TGC

[0060] Under the current electricity market clearing mode, the total cost of electricity purchase is obtained by settling the system marginal electricity price, with the goal of maximizing overall social welfare. The objective function is:

[0061] max F=∑F Ld -U r,i -U w,j

[0062] The constraints on electricity market transactions include: the output of the generator set should be equal to the total load; the regulatory agency stipulates that the amount of green certificates absorbed by the user side should not be less than a certain constant; the output of each generator set should be between the maximum output and the minimum output; thermal power units should retain a portion of rotating standby capacity; the number of green certificates sold by renewable energy power generators should not exceed the number of green certificates remaining after completing the renewable energy quota assessment; the total amount of free carbon quotas issued by the regulatory agency to thermal power generators should meet the total carbon emission requirements; when the supply of carbon quotas is sufficient, power generators with carbon emissions exceeding the standard will give priority to buying carbon quotas from the carbon market, while power generators that meet the assessment requirements will sell all the remaining carbon quotas on the carbon market trading platform, thereby reducing their own marginal cost of power generation; thermal power unit ramp-up constraints; green electricity trading ratio constraints.

[0063] In the above technical solution, according to the clearing model of the electricity market, it can be concluded that the influencing factors of the electricity market include: renewable energy installed capacity, traditional energy installed capacity, average monthly utilization hours of renewable energy, average monthly utilization hours of traditional energy, profit margin of renewable energy generators, profit margin of traditional energy generators, renewable energy installed capacity, traditional energy installed capacity, renewable energy electricity, traditional energy electricity, electricity supply, electricity demand, electricity demand growth rate and electricity price;

[0064] Among them, electricity price, electricity demand and electricity supply reflect the relationship between supply and demand;

[0065] Traditional energy installed capacity, renewable energy installed capacity, traditional energy installed capacity construction, and renewable energy installed capacity construction reflect the power supply structure.

[0066] In the above technical scheme, the impact of the carbon market on the power market includes: the carbon market will directly affect the order of clearing in the power market and change the existing interest structure of the power generation side; the carbon market will intensify the differentiation of the operating performance of the entities with differentiated emission reduction costs;

[0067] The impact of the electricity market on the carbon market includes: the clearing results of the electricity market can determine the free carbon quota and carbon emissions of power generation companies, thereby affecting the decision-making behavior of power generation companies in the carbon market;

[0068] The impact of the green certificate market on the power market includes: for renewable energy power generation companies, green certificate trading enables them to obtain income from selling electricity in the power market while also obtaining income from selling green certificates, which increases the profits of renewable energy companies, increases their competitive advantage in the power market, and increases their power generation share; at the same time, the income from green certificates can effectively encourage renewable energy power generation companies to increase installed capacity investment, improve green power supply, and promote the green and low-carbon transformation of the power generation industry; for quota fulfillment entities such as power sales companies and users, the costs brought by the quota system assessment will also affect their decision-making behavior in the power market, and thus affect the clearing results of the power market; power sales companies and users consider the goal of minimizing the cost of purchasing electricity and the cost of green certificate transactions to make the best decision;

[0069] The impact of the electricity market on the green certificate market includes: the clearing results of the electricity market determine the supply and demand scale of green certificates, which in turn affects the clearing results of the green certificate market.

[0070] In the above technical solution, the functional relationship between factors is constructed according to economic principles, and a model is established from a macro level to calculate the impact of changes in single and multiple market operating parameters on integrated transactions, providing a reference for the setting of policy parameters for the power market, carbon market and green certificate market, including:

[0071] The state variables of the green certificate market in the established model include: green certificates held by power generation companies, green certificates held by power grids, renewable energy installed capacity under construction, renewable energy installed capacity, traditional energy installed capacity under construction and traditional energy installed capacity. The state variables are used as the stock of the model; the flow variables include the excess demand for green certificates; the auxiliary variables include: expected purchase volume, expected sales volume, green certificate price, renewable energy profit margins as considered by investors, renewable energy electricity, electricity price and traditional energy electricity; the relationship among state variables, auxiliary variables and flow variables is as follows:

[0072]

[0073] in, is the number of green certificates held by power generators, is the initial number of green certificates held by the grid, is the number of green certificates issued to power generators, is the number of green certificates sold to the grid, is the number of green certificates held by the power grid, is the initial number of green certificates held by the power grid, r is the quota ratio, and D is the electricity demand;

[0074]

[0075] P TGC =P TGC,0 +∫ΔP TGC dt

[0076] in, The estimated sales volume of green certificates is is the estimated purchase amount of green certificates, P TGC is the initial price of the green certificate, P TGC,0 is the initial price of the green certificate, is the excess demand for green certificates, ΔP TGC is the price change of green certificate, P TGC is the green certificate price;

[0077]

[0078] Among them, P green For the profit margin of green power manufacturers, P fire For the profit margin of traditional energy companies, P e is the electricity price, P e,0 is the initial value of electricity price, Construction started for green electricity, for the start of construction of traditional energy, γ is the annual growth rate of electricity demand, α1 and α2 are profit adjustment coefficients;

[0079] E green =CAP green ×T green

[0080] E fire =CAP fire ×T fire

[0081] Among them, E green is the green electricity, CAP green is the installed capacity of green electricity, T green is the average monthly utilization hours of green electricity, E fire is the electricity of traditional energy, CAP fire is the installed capacity of traditional energy, T fire is the average monthly utilization hours of traditional energy;

[0082] The state variables of the carbon market in the established model include: changes in carbon quota prices, carbon quotas held by buyer power generation companies, and carbon quotas held by seller power generation companies; rate variables include: excess demand, carbon quota supply, sold carbon quotas, and carbon quota demand; auxiliary variables include: carbon quota prices, profit margins of traditional energy power generators, traditional energy electricity, expected carbon quota purchases, and expected carbon quota sales; the relationship between state variables, auxiliary variables, and rate variables is as follows:

[0083]

[0084] in, is the carbon quota held by the seller's power plant, μ is the proportion of the power industry, θ is the carbon dioxide emissions per unit of GDP, α3 and α4 are carbon quota allocation coefficients, which are determined based on historical emissions. is the carbon quota held by the buyer’s power plant, E fire is the electricity of traditional energy, ρ is the prescribed carbon dioxide emission coefficient of electricity of traditional energy;

[0085]

[0086] P CT =SMOOTH3I(P CT ,5,P CT,0 )

[0087] in, is the expected purchase amount of carbon quota, P CT is the carbon quota price, P CT,0 is the initial price of carbon quota, The estimated sales volume of carbon quotas is is the excess demand for carbon quota, ΔP CT For the change of carbon quota price;

[0088]

[0089] E fire =FAP fire ×T fire

[0090] Among them, P fire To expand the profit margins of traditional energy power generation companies, Construction started for conventional energy, FAP fire is the installed capacity of traditional energy, E fire is the electricity of traditional energy, T fire The average monthly utilization hours of traditional energy generators;

[0091] The state variables of the power market in the established model include: power price changes, renewable energy installed capacity under construction, renewable energy installed capacity, traditional energy installed capacity under construction and traditional energy installed capacity; rate variables include: excess power demand, renewable energy installed capacity started, renewable energy installed capacity completed, traditional energy installed capacity started and traditional energy installed capacity completed; auxiliary variables in the model include: power price, renewable energy profit margins as perceived by investors, renewable energy power generation, profit margins of traditional energy generators, traditional energy power, power supply, real-time demand and sales power price; exogenous variables include: power demand; constants include: network loss and power demand growth rate; the relationship between state variables, auxiliary variables, rate variables, exogenous variables and constants includes:

[0092] D=D0+∫γdt

[0093] P sell =P e +P TGC -P CT ×μ

[0094] E provide =(E green +E fire )×(1-η)

[0095]

[0096] Among them, γ is the average monthly growth rate of electricity demand, P sell is the sales electricity price, μ is the proportionality coefficient, E provide is the power supply, η is the loss in power transmission, Q realtime Real-time demand for electricity;

[0097]

[0098] P e =P e,0 +ΔP e

[0099] Among them, ΔP e For electricity price changes, Excess demand for electricity.

[0100] In summary, due to the adoption of the above technical features, the beneficial effects of the present invention are:

[0101] The present invention comprehensively considers the correlation between the electricity market, the carbon market and the green certificate market, breaks the barriers between the electricity-certificate, electricity-carbon and carbon-certificate joint analysis, forms an electricity-certificate-carbon integrated transaction evaluation method, and realizes the quantitative analysis and research of the electricity-certificate-carbon joint market. The present invention first analyzes the operating mechanisms of the electricity market, the carbon market and the green certificate market respectively, and clarifies the operating mechanism of the electricity-certificate-carbon joint market; then, the operating factors of each market are deeply explored from the aspects of the participants of each market, the decision-making behavior of market participants, and the market clearing model, and the causal relationship of the operating factors is studied to obtain the causal relationship of the electricity-certificate-carbon joint market; finally, combining the principles of economics and the causal relationship between the operating factors, the functional relationship between the quantitative description factors is found, and an electricity-certificate-carbon integrated transaction evaluation model is established, the policy trends of the green certificate market and the carbon market are studied, and the policy combination of the two markets is simulated and analyzed to provide a reference for the formulation of the policy objectives of the electricity-certificate-carbon joint market.

[0102] Additional aspects and advantages of the present invention will become apparent from the following description or may be learned by practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0103] The above and / or additional aspects and advantages of the present invention will become apparent and easily understood from the description of the embodiments in conjunction with the following drawings, in which:

[0104] Figure 1 It is a flow chart of an integrated transaction evaluation method for the electricity market, carbon market and green certificate market according to an embodiment of the present invention;

[0105] Figure 2 It is a schematic diagram of a green electricity trading mechanism in a transaction evaluation method for an integrated electricity market, carbon market and green certificate market according to an embodiment of the present invention;

[0106] Figure 3 It is a schematic diagram of a green certificate trading mechanism in a transaction evaluation method for an integrated power market, carbon market and green certificate market according to an embodiment of the present invention;

[0107] Figure 4 It is a schematic diagram of a carbon trading mechanism in an integrated transaction evaluation method of an electricity market, a carbon market and a green certificate market according to an embodiment of the present invention;

[0108] Figure 5 It is a schematic diagram of an integrated electricity-certificate-carbon transaction mechanism in an integrated transaction evaluation method of an electricity market, a carbon market and a green certificate market according to an embodiment of the present invention;

[0109] Figure 6 It is a schematic diagram of the causal relationship between the carbon market and the power market in a method for evaluating the integrated transaction of the power market, the carbon market and the green certificate market according to an embodiment of the present invention;

[0110] Figure 7 It is a schematic diagram of the causal relationship between the green certificate market and the power market in a transaction evaluation method for an integrated power market, carbon market and green certificate market according to an embodiment of the present invention;

[0111] Figure 8 It is a causal loop diagram of integrated electricity-certificate-carbon transaction in an integrated transaction evaluation method of an electricity market, a carbon market and a green certificate market according to an embodiment of the present invention;

[0112] Fig. 9 It is a schematic diagram of a simulation calculation model of an electricity-certificate-carbon joint market in an integrated transaction evaluation method of an electricity market, a carbon market and a green certificate market in one embodiment of the present invention;

[0113] Fig.10 It is a schematic diagram comparing the changing trends of green certificate prices, carbon prices and electricity prices calculated in a transaction evaluation method for an integrated power market, carbon market and green certificate market according to an embodiment of the present invention;

[0114] Fig.11 It is a schematic diagram comparing the changing trends of renewable energy installed capacity and traditional energy installed capacity calculated in an integrated transaction evaluation method for electricity market, carbon market and green certificate market according to an embodiment of the present invention. DETAILED DESCRIPTION

[0115] In order to more clearly understand the above-mentioned purpose, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0116] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0117] Refer to the following Figures 1 to 11 To describe an integrated transaction evaluation method for the electricity market, carbon market and green certificate market provided according to some embodiments of the present invention.

[0118] The first embodiment of the present invention proposes an integrated transaction evaluation method for the electricity market, carbon market and green certificate market. Figure 1 As shown in the figure, it mainly consists of three parts: electricity-certificate-carbon integrated trading operation mechanism, electricity-certificate-carbon joint market calculation model, and green certificate market and carbon market policy parameter strategy research. Specifically, it includes the following steps:

[0119] According to the operation status of the electricity market, carbon market and green certificate market, build an electricity-certificate-carbon integrated trading operation mechanism;

[0120] Based on the clearing models of the electricity market, carbon market and green certificate market, the influencing factors of the electricity-certificate-carbon market and the coupling factors of the interaction between the markets are screened out, and the impact of changes in market operating parameters on integrated transactions is qualitatively described;

[0121] Based on the principles of economics, the functional relationship between factors is constructed, and a model is established from a macro level to calculate the impact of changes in single and multiple market operating parameters on integrated transactions, providing a reference for the setting of policy parameters for the electricity market, carbon market and green certificate market.

[0122] The entities participating in green electricity transactions include renewable energy power generators, power grid companies, power sales companies and large users who directly participate in the electricity market. The subject matter of the transaction is green electricity, that is, the amount of electricity and its corresponding green certificates. The two parties to the transaction use bilateral agreements, centralized bidding and other methods to conduct transactions. After the transaction is completed, the renewable energy power generator will deliver the electricity and its corresponding number of green certificates to the purchaser in a "certificate-electricity-in-one" manner. While participating in green electricity transactions, renewable energy power generators will also participate in green certificate transactions, that is, a "certificate-electricity separation" method: renewable energy power generators sell electricity in the electricity market and sell green certificates in the green certificate market. While power grid companies, power sales companies and large users obtain green certificates through green electricity transactions, they can also purchase green certificates directly from the green certificate market to meet the assessment requirements of the renewable energy quota system. Green electricity trading mechanisms such as Figure 2 shown.

[0123] The entities involved in green certificate trading are generally the same as those involved in green electricity trading, including renewable energy power generators, power grid companies, power sales companies and large users. The difference is that some traditional energy power generators will also participate in green certificate trading and purchase green certificates, using green certificates to offset carbon quotas and maximize their own economic benefits; some companies and individuals will also participate in the green certificate market, voluntarily purchasing green certificates as a symbol of using green energy, and contributing to the development of green energy and environmental protection. Due to the mandatory compliance characteristics of the renewable energy quota system, power sales companies, power grid companies, large users and other compliance entities need to purchase green certificates from renewable energy power generators or from the green certificate market to complete their renewable energy consumption quotas during the compliance period, otherwise they will be punished. The schematic diagram of the green certificate trading mechanism is as follows: Figure 3 shown.

[0124] The main participants in carbon trading are traditional energy power generators, which can be divided into two categories: traditional energy power generators with high carbon emissions and traditional energy power generators with low carbon emissions. After the regulatory authorities allocate initial carbon quotas based on historical emissions and relevant carbon reduction policies, traditional energy power generators with low carbon emissions make decisions based on their carbon emissions, the number of carbon quotas and carbon quota compliance requirements, and sell part of their carbon quotas to obtain additional income; traditional energy power generators with high emissions also make corresponding decisions to purchase carbon quotas from the carbon market to meet their compliance requirements, or choose to refuse to comply and accept penalties. Carbon trading is carried out through the national carbon emission trading system, and can adopt one-way bidding for agreement transfer or other methods that comply with regulations. Agreement transfer refers to a transaction method in which the two parties to the transaction negotiate to reach a consensus and confirm the transaction, including listing agreement transactions and bulk agreement transactions. Among them, listing agreement transactions refer to a transaction method in which the transaction subject submits a sell or buy listing declaration through the trading system, and the intended transferee or transferor negotiates the listing declaration and confirms the transaction. Bulk agreement transactions refer to a transaction method in which the two parties to the transaction quote, inquire and confirm the transaction through the trading system. One-way bidding refers to a trading method in which the trading subject submits a selling or buying application to the trading institution, the trading institution publishes a bidding announcement, and multiple intended transferees or transferors quote according to the regulations, and the transaction is completed through the trading system within the agreed time. Figure 4 shown.

[0125] In a policy environment where carbon trading and green certificate markets coexist, the power market needs to consider the impact of green certificate trading and carbon trading while conducting electricity trading. Power load demand, total carbon emission quotas and renewable energy consumption ratio are key factors affecting the coupled operation of the power market and carbon market, and the power market and green certificate market. While considering maximizing their own interests, relevant market trading entities are also subject to the above-mentioned multiple policy constraints. The optimization decisions of trading entities in multiple markets will influence and restrict each other. Figure 5 It reflects the behavior of various players in the electricity market under the influence of green certificate trading and carbon trading.

[0126] The key to building an integrated electricity-certificate-carbon trading operation mechanism lies in clarifying the boundaries of the electricity market, carbon market and green certificate market, analyzing the market scope from the perspectives of the participants in each market, the decision-making behavior of the participants, and the market clearing model, and then conducting a logical analysis of the correlation between the electricity-certificate-carbon markets to build an integrated electricity-certificate-carbon trading operation mechanism.

[0127] The organizer of the green certificate trading market adopts centralized matching trading rules based on the quotations of market participants, with the goal of maximizing the total national benefit, and conducts unified clearing. The total national benefit is the difference between the social welfare generated by the total green certificates of each transaction matching pair and the transaction cost between the matching pairs. The objective function of the clearing model is:

[0128] max F=∑(q i ρ m -q j ρ n )

[0129] Where ρ m is the price offered by the mth green certificate demander, q i The number of green certificates required, ρ n The quotation for the nth green power manufacturer, q j The number of green certificates sold for it.

[0130] Green certificate demanders can choose to participate in the green certificate trading market to complete the consumption quota requirements, or accept fines if they fail to complete the task, depending on their consideration of income. In order to explore the impact of renewable energy consumption quotas on green certificate demanders, a bidding function with the minimum payment of power sales companies, power grid companies, large users and other entities as the objective function is established:

[0131] min W=Σq i ρ m +M TGC ρ TGC (λγQ i -q i )

[0132] Where q i ρ is the cost of purchasing green certificates for power sales company i, M is the penalty coefficient for not completing the quota consumption target (M is 0 when the consumption target is completed), ρ is the green certificate price at the time of clearing, λ is the green certificate consumption ratio, γ is the conversion coefficient between electricity and green certificates, Q i Selling electricity to power sales companies.

[0133] Renewable energy power generation companies participate in the green certificate market to sell green certificates to obtain higher profits, so the bidding function of renewable energy power generation companies is:

[0134] maxW=∑q j ×ρ n

[0135] The constraints are as follows:

[0136] (1) To prevent malicious manipulation of the green certificate market price, the upper and lower limits of green certificate trading quantity are set:

[0137]

[0138] (2) Green Certificate Quotation and Green Certificate Price Constraints

[0139] ρ min ≤ρ m ≤ρ max

[0140] ρ min ≤ρn ≤ρ max

[0141] ρ min ≤ρ≤ρ max

[0142] (3) Market balance constraints

[0143] ∑max(q i ,q j )≤λγQ

[0144] Where λγQ is the total number of green certificates that have completed the quota assessment.

[0145] It can be concluded from the clearing model that in the operation of the green certificate market, there are influencing factors such as green certificate trading volume, green certificate price ceiling, green certificate price floor, green certificate clearing price, green certificate quotation, green certificate absorption ratio required by the policy, penalty coefficient for failure to complete the absorption target, green certificate supply, and green certificate demand. The green certificate trading volume reflects the activity level of the green certificate market, and the green certificate price, green certificate supply, green certificate demand, and green certificate quotation reflect the supply and demand relationship of green certificates in the market. The upper and lower limits of green certificate prices, the green certificate absorption ratio required by the policy, and the penalty coefficient for failure to complete the absorption target reflect the influence of regulatory authorities and policies.

[0146] The carbon market can be considered a fully competitive market. All trading entities are recipients of carbon prices. All parties to carbon trading publish the quantity and price information of buying or selling carbon quotas on the carbon trading platform. The trading platform matches according to the principle of price priority and declaration time priority. The quotations of trading entities that buy (sell) quotas will be sorted from high to low (from low to high) to form a quota demand (supply) curve. Trading entities with the same quotations will be sorted according to the declaration time. The quota supply curve and the quota demand curve intersect, and the intersection formed is the market clearing point. The corresponding horizontal axis value is the clearing quota quantity, and the corresponding vertical axis value is the clearing carbon price. The market clearing point can help market participants better understand the market supply and demand relationship and market value.

[0147] The carbon market is cleared with the goal of maximizing social benefits:

[0148] max F=∑(q i ρ m -q j ρ n )

[0149] Where q i is the number of carbon quotas proposed by the i-th demander, ρ m For its quotation, q j is the amount of carbon quota proposed by the jth supplier, ρ n Make a quote for it.

[0150] The main participants in the carbon market are traditional energy power generators that sell or purchase carbon quotas. The bidding function of the manufacturers selling carbon quotas is:

[0151] maxW s =q j ×ρ n

[0152] Purchase of carbon quotas Traditional energy power generators can choose to purchase carbon quotas to meet the requirements, or not to purchase carbon quotas and accept penalties. The bidding function is:

[0153]

[0154] Where q i ×ρ m The cost of purchasing carbon quotas, The penalties faced for not having enough carbon quotas.

[0155] The carbon market trading constraints are as follows:

[0156] (1) To prevent malicious market manipulation, the sale and purchase of carbon quotas cannot exceed the upper and lower limits of quota trading quantities:

[0157] q imin ≤q i ≤q imax

[0158] q jmin ≤q j ≤q jmax

[0159] (2) Upper and lower limits of carbon quota market quotation:

[0160] ρ min ≤ρ m ≤ρ max

[0161] ρ min ≤ρ n ≤ρ max

[0162] ρ min ≤ρ≤ρ max

[0163] (3) Market balance constraint, that is, the total amount of carbon quota trading in a certain period shall not exceed the total amount of carbon quota that can be traded in the carbon market in that period:

[0164] ∑max(q i ,q j )≤q D

[0165] Where q DThe amount of carbon quota trading specified for the market.

[0166] It can be concluded from the clearing model that in the operation of the carbon market, there are influencing factors such as carbon quota trading volume, carbon quota price ceiling, carbon quota price floor, carbon quota clearing price, carbon quota quota quota, initial carbon quota allocated by the regulatory authority, penalty coefficient for excess carbon emissions, carbon quota supply, and carbon quota demand. The carbon quota trading volume reflects the activity of the carbon market, the carbon quota price, carbon quota supply, carbon quota demand, and carbon quota quota quota reflect the supply and demand relationship of carbon quotas in the market, and the upper and lower limits of carbon quota prices, the carbon quota initially allocated by the regulatory authority, and the penalty coefficient for excess carbon emissions reflect the impact of regulatory authorities and policies.

[0167] In a single electricity market, the quotation of a generator set mainly considers the cost of power generation. The unit quotation model based on marginal cost can enable the market to obtain the greatest social benefits. With the development of the carbon market and the green certificate market, the operating costs of units participating in the electricity market include not only the cost of electricity, but also the costs (benefits) generated by carbon emissions and green certificate ratio requirements. The expenditure and income of the unit in the carbon and green certificate market will inevitably affect the quotation level in the electricity market. Conversely, the quotation level of the unit will determine its output in the electricity market, and at the same time affect its income and expenditure in the carbon market and the green certificate market.

[0168] Considering the impact of the green certificate market and the carbon market on the electricity market, the power generation costs for conventional thermal power plants and thermal power plants equipped with carbon capture devices are:

[0169]

[0170] Where aP 2 +bP+c is the coal consumption cost, P is the output of the thermal power plant, is the cost of purchasing carbon emission rights (profit from selling carbon emission rights), ρ CO2 is the carbon price, is the amount of carbon emission rights purchased or sold, purchase is positive, and sale is negative. ργλPΔt is the transaction cost of green certificates. Traditional energy power generators can purchase a certain amount of green certificates to offset carbon emissions. ρ TGC is the green certificate price, γ is the conversion coefficient between renewable energy electricity and green certificate quantity, and λ is the green certificate ratio coefficient.

[0171] For renewable energy generators, the cost of electricity generation is:

[0172] f w =aP+b-ρq TGC

[0173] Where aP+b is the electricity generation cost of renewable energy generators, q TGC The number of green certificates sold.

[0174] Under the current trading mechanism, the quotation function of traditional energy generators is:

[0175]

[0176] Where 2aP r +b is the marginal cost of power generation in thermal power plants, is the marginal cost (benefit) of thermal power plants participating in the carbon market, and λγρ is the marginal cost of thermal power plants participating in the green certificate market. The quotation function of green power manufacturers is: Where a is the power generation cost of renewable energy generators, and The marginal benefits generated by green power manufacturers participating in the green certificate market.

[0177] Traditional energy generator profit model:

[0178]

[0179] Green power manufacturer profit model:

[0180] max U w,j =(P j ρ-aP j 2 -bP j -c)Δt+ρ TGC q TGC

[0181] User electricity purchase cost model:

[0182] Users participate in electricity trading based on the goal of minimizing electricity purchase costs. Due to the impact of the renewable energy consumption responsibility assessment system, the user's electricity purchase cost is composed of the electricity purchase fee in the electricity market and the cost of purchasing green certificates. The objective function is:

[0183] min F Ld =P k ρ k +ρ TGC q TGC

[0184] Under the current electricity market clearing mode, the total cost of electricity purchase is obtained by settling the system marginal electricity price, with the goal of maximizing overall social welfare. The objective function is:

[0185] max F=ΣF Ld -U r,i -U w,j

[0186] Considering carbon trading, green certificate trading and safe and stable operation of the power system, the power market clearing model should meet the following constraints:

[0187] (1) The output of the generator set should be equal to the total load.

[0188] ΣP r +ΣP w =P L

[0189] (2) The regulatory agency stipulates that the amount of green certificates consumed by users (i.e. the green certificate ratio coefficient) should not be lower than a certain constant.

[0190] C≤λ≤1

[0191] In the formula, C is a constant greater than 0 and is determined by policy.

[0192] (3) The output of each generator set should be between the maximum output and the minimum output.

[0193] P rmin ≤P r ≤P rmax

[0194] P wmin ≤P w ≤P wmax

[0195] (4) Due to the randomness and volatility of renewable energy power generation, in order to ensure the safe operation of the power system, thermal power units should retain a portion of rotating reserve capacity, assuming that the upper and lower reserve capacities are equal.

[0196] P r -P rmin ≥P s

[0197] PP≥P

[0198] rmax r

[0199] Where P s For spare capacity.

[0200] (5) In the green certificate market, the number of green certificates sold by renewable energy power generators should not exceed the number of green certificates remaining after completing the renewable energy quota assessment. If the number of green certificates available exceeds the number of green certificates required, renewable energy power generators may not be able to sell all of their green certificates, and the number of green certificates sold is the number of green certificates required by the market. If the number of green certificates available is lower than the number of green certificates required, due to the impact of the renewable energy power generation assessment, renewable energy power generators sell all of their remaining green certificates.

[0201]

[0202] Where (1-λ)γP w Δt is the green certificate remaining after the renewable energy power generator completes the assessment.

[0203] (6) In order to control the total carbon emissions in the region at a low level, the total amount of free carbon quotas issued by the regulatory agency to thermal power companies should meet the following constraints:

[0204]

[0205] Where δ * The base coefficient of carbon quotas issued free of charge. The total amount of CO2 emissions set by regulators.

[0206] (7) The carbon market can be considered a fully competitive market, where all trading entities are recipients of carbon prices. Therefore, when the carbon quota supply is sufficient, power generators with excessive carbon emissions will give priority to buying carbon quotas from the carbon market, while power generators that meet the assessment requirements will sell all the remaining carbon quotas on the carbon market trading platform, thereby reducing their own marginal cost of power generation. The carbon emissions actually bought or sold by thermal power generators in the carbon market are expressed as

[0207]

[0208] Where δ is the actual carbon dioxide emission coefficient of traditional energy power generators, δ * It is the base coefficient of carbon quota issued free of charge.

[0209] (8) Thermal power unit climbing constraints

[0210]

[0211] (9) Green electricity trading ratio

[0212] Since the price of green certificates in the green certificate market fluctuates, in order to avoid the risks caused by price fluctuations, renewable energy power generators will sign a green electricity purchase agreement with the electricity purchaser. When selling electricity, they will also sell the corresponding green certificates to the buyer, thereby obtaining a stable level of income.

[0213] Q' r =αQ r

[0214]

[0215] In the formula, Q' r is the green electricity trading volume, and η is the adjustment coefficient.

[0216] The key to constructing a calculation model for the electricity-certificate-carbon joint market lies in correctly analyzing the causal and functional relationships between the factors that constitute the market. First, the operating mechanisms of the electricity market, carbon market, and green certificate market should be analyzed, the constituent factors of each market should be studied, key factors should be screened, and a causal relationship diagram of the electricity-certificate-carbon joint market should be constructed. The functional relationship between the variables should be established based on the principles of microeconomics, and finally a calculation model should be constructed based on qualitative causal relationships and quantitative functional relationships.

[0217] There are many influencing factors in the electricity market clearing model considering carbon trading and green certificate trading. The green certificate trading part includes variables such as the green certificate consumption ratio, green certificate price, green certificate supply, green certificate demand, green electricity trading volume, green electricity trading ratio, and penalty factor for failure to complete the stipulated consumption ratio stipulated by the renewable energy quota system; the carbon trading part includes variables such as the carbon quota initially allocated by the regulatory department, carbon quota price, carbon quota supply, carbon quota demand, penalty factor for excess carbon emissions, and standard carbon emission coefficient; the electricity market includes variables such as renewable energy installed capacity, traditional energy installed capacity, average monthly utilization hours of renewable energy, average monthly utilization hours of traditional energy, profit margin of renewable energy power generators, profit margin of traditional energy power generators, renewable energy installed capacity, traditional energy installed capacity, renewable energy electricity, traditional energy electricity, electricity supply, electricity demand, electricity demand growth rate, and electricity price. There are many important variables among them, such as the green certificate price, green certificate supply and green certificate demand that reflect the supply and demand relationship of green certificates in the green certificate market, the absorption ratio stipulated in the renewable energy quota system that reflects policy requirements, the carbon quota price, carbon quota supply and carbon quota sales that reflect the supply and demand relationship of carbon quotas in the carbon market, the initial allocation of carbon quotas that reflects the carbon emission reduction policy, the electricity price, electricity demand and electricity supply that reflect the supply and demand relationship in the electricity market, and the traditional energy installed capacity, renewable energy installed capacity, traditional energy installed capacity construction and renewable energy installed capacity construction that reflect the power structure.

[0218] The carbon market has two main impacts on the power market. First, the carbon market will directly affect the order of clearing in the power market and change the existing interest structure on the power generation side. Carbon costs will be included in market dispatch decisions, and the clearing results of the power market will be affected by increasing the utilization rate of power generation technologies with lower carbon emission intensity. Second, the carbon market will intensify the differentiation of the operating performance of entities with differentiated emission reduction costs. Before the inclusion of carbon costs, the marginal costs of conventional coal-fired units are generally lower than those of gas-fired units and carbon capture units. Coal-fired units have a competitive advantage in the power market, and their power generation share accounts for the largest proportion. After the inclusion of carbon emission costs, the marginal costs of coal-fired units with higher carbon emission intensity have increased significantly, while gas-fired units and carbon capture units can obtain income by selling excess carbon quotas. In some scenarios, the marginal costs of gas-fired units and carbon capture thermal power units may be lower than those of conventional coal-fired units. The order of clearing in the power market has changed, and gas-fired units and carbon capture units with lower carbon emission intensity have more competitive advantages. After the introduction of the carbon market, the external costs of carbon emissions have been made explicit and converted into internal costs of emission entities. High-efficiency enterprises can obtain additional income by selling surplus emission reductions. The additional income obtained by selling excess carbon emissions will further promote the development of low-carbon technologies, drive enterprises to obtain more income, and form a positive cycle. Similarly, the clearing results of the electricity market can determine the free carbon quota and carbon emissions of power generation companies to a certain extent, and then affect the decision-making behavior of power generation companies in the carbon market. The clearing results of the medium- and long-term electricity market are an important consideration for the preliminary determination of the scale of carbon emission rights quotas.

[0219] The electricity market and the carbon market influence the decision-making behavior of power generation companies through market mechanisms, mainly through the interactive transmission of the state between the electricity and carbon markets by variables such as electricity prices, carbon prices, power generation, installed capacity, carbon quota supply-demand ratio, and carbon prices. Fossil energy companies generate carbon emissions when supplying electricity. The more power they generate, the greater the demand for carbon quotas. As the demand for carbon quotas increases, the carbon quota supply-demand ratio decreases, causing carbon prices to rise; when carbon prices rise, the carbon cost of fossil energy units increases, and the profits of fossil energy companies decrease. When carbon prices rise to a certain extent, the investment and construction of fossil energy installations slows down, power generation decreases, and the carbon quota demand of related fossil energy companies decreases, causing carbon prices to fall. When electricity prices rise, the profit margins of fossil energy power generation companies increase, fossil energy installed capacity and power generation increase, the power supply in the market increases, and electricity prices fall, thus achieving a dynamic equilibrium. Figure 6 The causal relationship between the carbon market and the electricity market is described.

[0220] Under the renewable energy quota system, the power market and the green certificate market are closely coupled. For renewable energy power generation companies, green certificate transactions enable them to obtain income from selling green certificates while selling electricity in the power market. This increases the profits of renewable energy companies, increases their competitive advantage in the power market, and increases their power generation share. At the same time, the income from green certificates can effectively encourage renewable energy power generation companies to increase installed capacity investment, improve green power supply, and promote the green and low-carbon transformation of the power generation industry. For quota fulfillment entities such as power sales companies and users, the costs brought by the quota system assessment will also affect their decision-making behavior in the power market, and thus affect the clearing results of the power market. Power sales companies and users consider the goal of minimizing the cost of purchasing electricity and the transaction cost of green certificates (consumption volume) to make the best decision. The clearing results of the power market largely determine the supply and demand scale of green certificates, which in turn affects the results of the green certificate market.

[0221] The green certificate market and the electricity market also present a dynamic equilibrium relationship. For example, as electricity demand increases, the renewable energy consumption responsibility weight of relevant trading entities increases, the demand for green certificates increases, and the supply and demand relationship of green certificates tightens, causing the price of green certificates to rise: the rise in the price of green certificates will lead to an increase in the profit margin of renewable energy power generation companies, prompting new energy power generation companies to increase installed capacity and build renewable energy units to increase power generation, increase the supply of green certificates, increase the supply and demand ratio of green certificates, and the price of green certificates tends to fall, eventually reaching a dynamic equilibrium. In addition, the assessment of the weight of renewable energy consumption responsibility determines the minimum clearing scale of renewable energy electricity. Figure 7 It reflects the causal relationship between the green certificate market and the electricity market.

[0222] The electricity market, carbon market and green certificate market have a profound impact on the decision-making of market players through the role of market mechanisms, and have interactive effects through price linkage and supply and demand relationships. Figure 8 It reflects the causal relationship of integrated electricity-certificate-carbon trading.

[0223] In the green certificate market part of the established model, there are several relatively important stocks, namely green certificates held by power generation companies, green certificates held by power grids, renewable energy installed capacity under construction, renewable energy installed capacity, traditional energy installed capacity under construction and traditional energy installed capacity. They interact with each other through the market operation mechanism, and the green certificate market and the electricity market are mainly transmitted through prices. The main flow variables in the model include: excess demand for green certificates, and these flow variables have a direct quantitative relationship with the stock. The auxiliary variables in the model include: expected purchase volume, expected sales volume, green certificate price, renewable energy profit margins as considered by investors, renewable energy electricity, electricity price, and traditional energy electricity. They link various state variables. These variables have the following quantitative relationship:

[0224]

[0225] In the formula, is the number of green certificates held by power generators, is the initial number of green certificates held by the grid, is the number of green certificates issued to power generators, is the number of green certificates sold to the grid, is the number of green certificates held by the power grid, is the initial number of green certificates held by the power grid, r is the quota ratio, and D is the electricity demand.

[0226]

[0227] P TGC =P TGC,0 +∫ΔP TGC dt

[0228] In the formula, The estimated sales volume of green certificates is is the estimated purchase amount of green certificates, P TGC is the initial price of the green certificate, P TGC,0 is the initial price of the green certificate, is the excess demand for green certificates, ΔP TGC is the price change of green certificate, P TGC The price of green certificate.

[0229]

[0230] Where P green For the profit margin of green power manufacturers, P fire For the profit margin of traditional energy companies, P e is the electricity price, P e,0 is the initial value of electricity price, Construction started for green electricity, The construction of traditional energy is started, γ is the annual growth rate of electricity demand, and α1 and α2 are profit adjustment coefficients.

[0231] E green =CAP green ×T green

[0232] E fire =CAP fire ×T fire

[0233] In the formula, E green is the green electricity, CAP green is the installed capacity of green electricity, T green is the average monthly utilization hours of green electricity, E fire is the electricity of traditional energy, CAP fire is the installed capacity of traditional energy, T fireIt is the average monthly utilization hours of traditional energy.

[0234] The main state variables of the carbon market in the established model include: changes in carbon quota prices, carbon quotas held by buyer power generation companies, and carbon quotas held by seller power generation companies. The rate variables in the model include: excess demand, carbon quota supply, sold carbon quotas, and carbon quota demand. The auxiliary variables in the model include: carbon quota prices, profit margins of traditional energy power generators, traditional energy electricity, expected purchases of carbon quotas, and expected sales of carbon quotas. The specific functional relationship between the variables is as follows:

[0235]

[0236] In the formula, is the carbon quota held by the seller's power plant, μ is the proportion of the power industry, θ is the carbon dioxide emissions per unit of GDP, α3 and α4 are carbon quota allocation coefficients, which are determined based on historical emissions. is the carbon quota held by the buyer’s power plant, E fire is the traditional energy electricity, and ρ is the prescribed carbon dioxide emission coefficient of traditional energy electricity.

[0237]

[0238] P CT =SMOOTH3I(P CT ,5,P CT,0 )

[0239] In the formula, is the expected purchase amount of carbon quota, P CT is the carbon quota price, P CT,0 is the initial price of carbon quota, The estimated sales volume of carbon quotas is is the excess demand for carbon quota, ΔP CT Changes in carbon quota prices.

[0240]

[0241] E fire =FAP fire ×T fire

[0242] Where P fire To expand the profit margins of traditional energy power generation companies, Construction started for conventional energy, FAP fire is the installed capacity of traditional energy, E fire is the electricity of traditional energy, T fire It is the average monthly utilization hours of traditional energy power generators.

[0243] The state variables in the electricity market part of the established model include: changes in electricity prices, renewable energy installed capacity under construction, renewable energy installed capacity, traditional energy installed capacity under construction and traditional energy installed capacity. The rate variables in the model include: excess electricity demand, renewable energy installed capacity started, renewable energy installed capacity completed, traditional energy installed capacity started, and traditional energy installed capacity completed. The auxiliary variables in the model include: electricity prices, investors' view of renewable energy profit margins, renewable energy power generation, traditional energy power generators' profit margins, traditional energy power, power supply, real-time demand, and sales electricity prices. The exogenous variables in the model include: electricity demand. The constants in the model include: network loss and electricity demand growth rate. The electricity market is a key link in green certificate trading and carbon quota trading. The specific relationship between the variables is as follows:

[0244] D=D0+∫γdt

[0245] P sell =P e +P TGC -P CT ×μ

[0246] E provide =(E green +E fire )×(1-η)

[0247]

[0248] Where, γ is the average monthly growth rate of electricity demand, P sell is the sales electricity price, μ is the proportionality coefficient, E provide is the power supply, η is the loss in power transmission, Q realtime Real-time demand for electricity.

[0249]

[0250] P e =P e,0 +ΔP e

[0251] In the formula, ΔP e For electricity price changes, Excess demand for electricity.

[0252] According to the causal relationship between the factors of the electricity market, carbon market and green certificate market and the functional relationship between the variables, an electricity-certificate-carbon integrated transaction evaluation calculation model is established. Fig. 9 shown.

[0253] The purpose of the electricity-certificate-carbon joint market calculation model is to quantitatively calculate the overall impact of market factors and policy parameters, and to study the effects of combined policy parameters.

[0254] Both green certificate trading and carbon trading can achieve the policy goals of promoting green electricity consumption and driving carbon emission reduction, but their modes of action and operating mechanisms are different. Green certificate trading promotes investment and construction by increasing the income of renewable energy power generators and promotes the development of new energy. Carbon trading makes the cost of carbon emissions explicit, increases the cost of high-emission traditional energy power generators, increases the profit of low-emission traditional energy power generators, and promotes the development of low-carbon technology. The policy goals of green certificate trading are concentrated in the renewable energy consumption ratio it stipulates. The renewable consumption ratio determines the assessment amount of green certificates in the market and can greatly affect the supply and demand relationship of green certificates. The policy goals of carbon trading are mainly reflected in the carbon emission reduction rate. The carbon emission reduction rate is determined, and the carbon emission reduction rate can affect the supply and demand relationship of carbon quotas to a certain extent. Studying the combined policy of green certificate trading and carbon trading is to study the impact of the renewable energy consumption ratio and the carbon emission reduction rate on the electricity-certificate-carbon joint market.

[0255] In a specific embodiment, Fig.10 and Fig.11 As shown, this disclosure compares and analyzes the changing trends of key factors in the carbon market, green certificate market and electricity market based on the differences in carbon quota auction ratio, carbon emission reduction policy intensity and renewable energy quota ratio. With reference to the current Chinese carbon market and carbon emission reduction policy, the carbon quota auction ratio is set to 0% and 50%. According to the national carbon market carbon price K-line data, the carbon price benchmark price is set to 50 yuan / ton. According to the renewable energy development plan, the renewable energy quota ratio is set to 25% and 30%. The carbon emission intensity reduction rate is set to -0.3% and -0.41%. The policy combination is shown in the following table. Fig.10 and Fig.11 Portfolios 1-6 are indicated as Portfolio1-6.

[0256]

[0257] In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0258] Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A transaction evaluation method for the integrated electricity market, carbon market and green certificate market, characterized in that: include: According to the operation status of the electricity market, carbon market and green certificate market, build an electricity-certificate-carbon integrated trading operation mechanism; Based on the clearing models of the electricity market, carbon market and green certificate market, the influencing factors of the electricity-certificate-carbon market and the coupling factors of the interaction between the markets are screened out, and the impact of changes in market operating parameters on integrated transactions is qualitatively described; Based on the principles of economics, the functional relationship between factors is constructed, and a model is established from a macro level to calculate the impact of changes in single and multiple market operating parameters on integrated transactions, providing a reference for the setting of policy parameters for the electricity market, carbon market and green certificate market.

2. According to claim 1, a method for evaluating the integrated transaction of the electricity market, carbon market and green certificate market is characterized in that: The construction of the electricity-certificate-carbon integrated trading operation mechanism includes: Clarify the boundaries between the electricity market, carbon market and green certificate market, analyze the market scope from the perspectives of the participants in each market, the decision-making behavior of the participants, and the market clearing model, and then conduct a logical analysis of the correlation between the electricity, certificate and carbon markets to build an integrated electricity, certificate and carbon trading operation mechanism.

3. The integrated transaction evaluation method of the electricity market, carbon market and green certificate market according to claim 1 is characterized in that: The green certificate market clearing model includes: The organizer of the green certificate trading market adopts centralized matching trading rules based on the quotations of market participants, with the goal of maximizing the total national benefit, and conducts unified clearing; among which, the total national benefit is the difference between the social welfare generated by the total green certificates of each trading match and the transaction cost between the matching pairs, and the objective function of the clearing model is: maxF=Σ(q i r m -q j r n ) Among them, ρ m is the price offered by the mth green certificate demander, q i The number of green certificates required, ρ n The quotation for the nth green power manufacturer, q j The number of green certificates sold for it; Green certificate demanders can choose to participate in the green certificate trading market to complete the consumption quota requirements, or accept fines if they fail to complete the task, depending on their consideration of income. In order to explore the impact of renewable energy consumption quotas on green certificate demanders, a bidding function with the minimum payment of power sales companies, power grid companies, large users and other entities as the objective function is established: minW=Σq i r m +M TGC r TGC (λγQ i -q i ) Among them, q i ρ is the cost of purchasing green certificates for power sales company i, M is the penalty coefficient for not completing the quota consumption target, ρ is the green certificate price at the time of clearing, λ is the green certificate consumption ratio, γ is the conversion coefficient between electricity and green certificates, Q i Selling electricity to power sales companies; Renewable energy power generation companies participate in the green certificate market to sell green certificates to obtain higher profits. The bidding function of renewable energy power generation companies is: maxW=∑q j ×ρ n The bidding function constraints of the renewable energy power generators include: upper and lower limit constraints on the number of green certificate transactions, green certificate quotation and green certificate price constraints, and market balance constraints.

4. The integrated transaction evaluation method of the power market, carbon market and green certificate market according to claim 3 is characterized in that: According to the clearing model of the green certificate market, it can be concluded that the influencing factors of the green certificate market include green certificate trading volume, green certificate price upper limit, green certificate price lower limit, green certificate clearing price, green certificate quotation, green certificate consumption ratio required by the policy, penalty coefficient for failure to complete consumption target, green certificate supply and green certificate demand; Among them, the green certificate trading volume reflects the activity of the green certificate market; Green certificate price, green certificate supply, green certificate demand, and green certificate quotation reflect the supply and demand relationship of green certificates in the market; The upper and lower limits of green certificate prices, the green certificate consumption ratio required by policies, and the penalty coefficient for failure to achieve consumption targets reflect the influence of regulatory authorities and policies.

5. The integrated transaction evaluation method of the power market, carbon market and green certificate market according to claim 1 is characterized in that: The carbon market clearing model includes: Clearing with the goal of maximizing social benefits: maxF=∑(q i ρ m -q j ρ n ) Among them, q i is the number of carbon quotas proposed by the i-th demander, ρ m Quote for it;q j is the number of carbon quotas proposed by the jth supplier, ρ n Make an offer for it; The main participants in the carbon market include traditional energy power generators that sell or purchase carbon quotas. The bidding function of the manufacturers selling carbon quotas is: maxW s =q j ×ρ n Purchase of carbon quotas Traditional energy power generators can choose to purchase carbon quotas to meet the requirements, or not to purchase carbon quotas and accept penalties. The bidding function is: Among them, q i ×ρ m The cost of purchasing carbon quotas, for the penalties faced for insufficient carbon quotas; Carbon market trading constraints include: the sale and purchase of carbon quotas cannot exceed the upper and lower limits of quota trading quantities, the upper and lower limits of carbon quota market quotations, and market balance constraints.

6. The integrated transaction evaluation method of the power market, carbon market and green certificate market according to claim 5 is characterized in that: According to the carbon market clearing model, the factors affecting the carbon market include: carbon quota trading volume, carbon quota price ceiling, carbon quota price floor, carbon quota clearing price, carbon quota quota quota, initial carbon quota allocated by the regulatory authorities, penalty coefficient for excess carbon emissions, carbon quota supply and carbon quota demand; Among them, the carbon quota trading volume reflects the activity of the carbon market; Carbon quota prices, carbon quota supply, carbon quota demand, and carbon quota quotations reflect the supply and demand relationship of carbon quotas in the market; The upper and lower limits of carbon quota prices, the carbon quotas initially allocated by regulatory authorities, and the penalty coefficient for excess carbon emissions reflect the influence of regulatory authorities and policies.

7. The integrated transaction evaluation method of the power market, carbon market and green certificate market according to claim 1 is characterized in that: The electricity market clearing model includes: Considering the impact of the green certificate market and the carbon market on the electricity market, the power generation costs for conventional thermal power plants and thermal power plants equipped with carbon capture devices are: Among them, aP 2 +bP+c is the coal consumption cost, P is the output of the thermal power plant, is the cost of purchasing carbon emission rights, ρ CO2 is the carbon price, is the amount of carbon emission rights purchased or sold, ργλPΔt is the transaction cost of green certificates, and traditional energy power generators can purchase green certificates to offset carbon emissions, ρ TGC is the green certificate price, γ is the conversion coefficient between renewable energy electricity and green certificate quantity, and λ is the green certificate ratio coefficient; For renewable energy generators, the cost of electricity generation is: f w =aP+b-ρq TGC Among them, aP+b is the power generation cost of renewable energy generators, q TGC The number of green certificates sold; The bidding function of traditional energy generators is: Among them, 2aP r +b is the marginal cost of power generation in thermal power plants, is the marginal cost of thermal power plants participating in the carbon market, λγρ is the marginal cost of thermal power plants participating in the green certificate market; The quotation function of green power manufacturers is: Where a is the power generation cost of renewable energy generators, and The marginal benefits generated by green power manufacturers participating in the green certificate market; Traditional energy generator profit model: Green power manufacturer profit model: maxU w,j =(P j ρ-aP j 2 -bP j -c)Δt+ρ TGC what TGC User electricity purchase cost model: Users participate in electricity energy trading based on the minimum electricity purchase cost target. Due to the impact of the renewable energy consumption responsibility assessment system, the user's electricity purchase cost is composed of the electricity purchase fee in the electricity energy market and the cost of purchasing green certificates. The objective function is: minF Ld =P k r k +r TGC q TGC Under the current electricity market clearing mode, the total cost of electricity purchase is obtained by settling the system marginal electricity price, with the goal of maximizing overall social welfare. The objective function is: maxF=∑F Ld -IN r,i -IN w,j The constraints on electricity market transactions include: the output of the generator set should be equal to the total load; the regulatory agency stipulates that the amount of green certificates absorbed by the user side should not be less than a certain constant; the output of each generator set should be between the maximum output and the minimum output; thermal power units should retain a portion of rotating standby capacity; the number of green certificates sold by renewable energy power generators should not exceed the number of green certificates remaining after completing the renewable energy quota assessment; the total amount of free carbon quotas issued by the regulatory agency to thermal power generators should meet the total carbon emission requirements; when the supply of carbon quotas is sufficient, power generators with carbon emissions exceeding the standard will give priority to buying carbon quotas from the carbon market, while power generators that meet the assessment requirements will sell all the remaining carbon quotas on the carbon market trading platform, thereby reducing their own marginal cost of power generation; thermal power unit ramp-up constraints; green electricity trading ratio constraints.

8. The integrated transaction evaluation method of the power market, carbon market and green certificate market according to claim 7 is characterized in that: According to the clearing model of the electricity market, it can be concluded that the influencing factors of the electricity market include: renewable energy installed capacity, traditional energy installed capacity, average monthly utilization hours of renewable energy, average monthly utilization hours of traditional energy, profit margin of renewable energy generators, profit margin of traditional energy generators, renewable energy installed capacity, traditional energy installed capacity, renewable energy power, traditional energy power, power supply, power demand, power demand growth rate and electricity price; Among them, electricity price, electricity demand and electricity supply reflect the relationship between supply and demand; Traditional energy installed capacity, renewable energy installed capacity, traditional energy installed capacity construction, and renewable energy installed capacity construction reflect the power supply structure.

9. The integrated transaction evaluation method of the power market, carbon market and green certificate market according to claim 1 is characterized in that: The impact of the carbon market on the power market includes: the carbon market will directly affect the order of clearing in the power market and change the existing interest structure of the power generation side; the carbon market will intensify the differentiation of operating performance of entities with differentiated emission reduction costs; The impact of the electricity market on the carbon market includes: the clearing results of the electricity market can determine the free carbon quota and carbon emissions of power generation companies, thereby affecting the decision-making behavior of power generation companies in the carbon market; The impact of the green certificate market on the power market includes: for renewable energy power generation companies, green certificate trading enables them to obtain income from selling electricity in the power market while also obtaining income from selling green certificates, which increases the profits of renewable energy companies, increases their competitive advantage in the power market, and increases their power generation share; at the same time, the income from green certificates can effectively encourage renewable energy power generation companies to increase installed capacity investment, improve green power supply, and promote the green and low-carbon transformation of the power generation industry; for quota fulfillment entities such as power sales companies and users, the costs brought by the quota system assessment will also affect their decision-making behavior in the power market, and thus affect the clearing results of the power market; power sales companies and users consider the goal of minimizing the cost of purchasing electricity and the cost of green certificate transactions to make the best decision; The impact of the electricity market on the green certificate market includes: the clearing results of the electricity market determine the supply and demand scale of green certificates, which in turn affects the clearing results of the green certificate market.

10. The integrated transaction evaluation method of the power market, carbon market and green certificate market according to claim 1 is characterized in that: The functional relationship between factors is constructed based on economic principles, and a model is established at the macro level to calculate the impact of changes in single and multiple market operating parameters on integrated transactions, providing a reference for the setting of policy parameters for the power market, carbon market and green certificate market, including: The state variables of the green certificate market in the established model include: green certificates held by power generation companies, green certificates held by power grids, renewable energy installed capacity under construction, renewable energy installed capacity, traditional energy installed capacity under construction and traditional energy installed capacity. The state variables are used as the stock of the model; the flow variables include the excess demand for green certificates; the auxiliary variables include: expected purchase volume, expected sales volume, green certificate price, renewable energy profit margins as considered by investors, renewable energy electricity, electricity price and traditional energy electricity; the relationship among state variables, auxiliary variables and flow variables is as follows: in, is the number of green certificates held by power generators, is the initial number of green certificates held by the grid, is the number of green certificates issued to power generators, is the number of green certificates sold to the grid, is the number of green certificates held by the power grid, is the initial number of green certificates held by the power grid, r is the quota ratio, and D is the electricity demand; Q TGC =P TGC,0 +∫ΔP TGC dt in, The estimated sales volume of green certificates is is the estimated purchase amount of green certificates, P TGC is the initial price of the green certificate, P TGC,0 is the initial price of the green certificate, is the excess demand for green certificates, ΔP TGC is the price change of green certificate, P TGC is the green certificate price; Among them, P green For the profit margin of green power manufacturers, P fire For the profit margin of traditional energy companies, P e is the electricity price, P e,0 is the initial value of electricity price, Construction started for green electricity, for the start of construction of traditional energy, γ is the annual growth rate of electricity demand, α1 and α2 are profit adjustment coefficients; AND green =ZIP green ×T green AND fire =ZIP fire ×T fire Among them, E green is the green electricity, CAP green is the installed capacity of green electricity, T green is the average monthly utilization hours of green electricity, E fire is the electricity of traditional energy, CAP fire is the installed capacity of traditional energy, T fire is the average monthly utilization hours of traditional energy; The state variables of the carbon market in the established model include: changes in carbon quota prices, carbon quotas held by buyer power generation companies, and carbon quotas held by seller power generation companies; rate variables include: excess demand, carbon quota supply, sold carbon quotas, and carbon quota demand; auxiliary variables include: carbon quota prices, profit margins of traditional energy power generators, traditional energy electricity, expected carbon quota purchases, and expected carbon quota sales; the relationship between state variables, auxiliary variables, and rate variables is as follows: in, is the carbon quota held by the seller's power plant, μ is the proportion of the power industry, θ is the carbon dioxide emissions per unit of GDP, α3 and α4 are carbon quota allocation coefficients, which are determined based on historical emissions. is the carbon quota held by the buyer’s power plant, E fire is the electricity of traditional energy, ρ is the prescribed carbon dioxide emission coefficient of electricity of traditional energy; P CT =SMOOTH3I(P CT ,5,P CT,0 ) in, is the expected purchase amount of carbon quota, P CT is the carbon quota price, P CT,0 is the initial price of carbon quota, The estimated sales volume of carbon quotas is is the excess demand for carbon quota, ΔP CT For the change of carbon quota price; It is fire =FAP fire ×T fire Among them, P fire To expand the profit margins of traditional energy power generation companies, Construction started for conventional energy, FAP fire is the installed capacity of traditional energy, E fire is the electricity of traditional energy, T fire The average monthly utilization hours of traditional energy generators; The state variables of the power market in the established model include: power price changes, renewable energy installed capacity under construction, renewable energy installed capacity, traditional energy installed capacity under construction and traditional energy installed capacity; rate variables include: excess power demand, renewable energy installed capacity started, renewable energy installed capacity completed, traditional energy installed capacity started and traditional energy installed capacity completed; auxiliary variables in the model include: power price, renewable energy profit margins as perceived by investors, renewable energy power generation, profit margins of traditional energy generators, traditional energy power, power supply, real-time demand and sales power price; exogenous variables include: power demand; constants include: network loss and power demand growth rate; the relationship between state variables, auxiliary variables, rate variables, exogenous variables and constants includes: D=D0+∫γdt P sell =P e +P TGC -P CT ×μ AND provide =(And green +E fire )×(1-η) Among them, γ is the average monthly growth rate of electricity demand, P sell is the sales electricity price, μ is the proportionality coefficient, E provide is the power supply, η is the loss in power transmission, Q realtime Real-time demand for electricity; P e =P e,0 +ΔP e Among them, ΔP e For electricity price changes, Excess demand for electricity.

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