Electricity, carbon and green certificate multi-market combined transaction method and system for electricity selling company

Abstract

The invention provides an electricity, carbon and green certificate multi-market combined transaction method and system for an electricity selling company. The method comprises the following steps: constructing a multi-dimensional uncertainty operation scene of the electricity selling company; based on the scene, constructing a model that the electricity selling company participates in the electricity market transaction; based on the transaction model, constructing a carbon market transaction model in which the electricity selling company participates, and obtaining the carbon emission right of the electricity selling company; constructing a model that the electricity selling company participates in the green certificate market transaction; based on a carbon emission permit and green certificate market transaction model, a combined transaction model which considers multiple uncertainties and covers multiple markets is established by combining a multi-dimensional uncertainty operation scene of an electricity selling company and an electricity market transaction model of the electricity selling company, and purchase and use plans of electricity, carbon emission permit and green certificate are respectively designed for different user packages. And multi-market combined transaction of electricity, carbon and green certificates of electricity selling companies is realized. According to the invention, a multi-uncertainty multi-market combined transaction model is provided, and the low-carbon economic operation of the market is realized through the multi-market combined transaction of the electricity, carbon and green certificates of the electricity selling company.

Description

Technical Field

[0001] The present invention relates to the technical field of multi-market trading strategies for power sales companies, and specifically, to a multi-market combination trading method and system for carbon green certificates of power sales companies taking into account multiple uncertainties, as well as a corresponding computer terminal and computer-readable storage medium. Background Art

[0002] At present, the trading strategies of power sales companies generally face insufficient technical capabilities, and most companies have not yet formed a scientific decision-making model based on data-driven. Although some large power sales companies have begun to try to introduce emerging technologies such as machine learning and blockchain for price forecasting and risk management, how to achieve information interaction, risk diversification and profit optimization among multiple markets is still a difficult point in technical research. Therefore, conducting research on multi-market combination trading strategies for electricity, carbon, and green certificates has become an urgent problem to be solved in this field. Summary of the invention

[0003] In view of the above-mentioned deficiencies in the prior art, the present invention provides a multi-market combination trading method and system for carbon green certificates of power sales companies taking into account multiple uncertainties, and also provides a corresponding computer terminal and computer-readable storage medium.

[0004] According to one aspect of the present invention, a multi-market combination trading method for carbon green certificates of a power sales company is provided, comprising: Construct multi-dimensional uncertainty operation scenarios for power sales companies; Based on the multi-dimensional uncertainty operation scenario of the power sales company, a model for the power sales company to participate in the power market transaction is constructed; Based on the electricity sales company's participation in the electricity market trading model, a model for the electricity sales company to participate in the carbon market trading model is constructed to obtain the carbon emission rights of the electricity sales company; Construct a trading model for power sales companies to participate in the green certificate market; Based on the carbon emission rights and green certificate market trading model, combined with the multi-dimensional uncertainty operation scenario of the power sales company and the power sales company's participation in the electricity market trading model, a combined trading model that considers multiple uncertainties and covers multiple markets is established. This model can design procurement and use plans for electricity, carbon emission rights and green certificates for different user packages of the power sales company, and use this model to realize the multi-market combined trading of electricity, carbon and green certificates of the power sales company.

[0005] According to another aspect of the present invention, a multi-market combination trading system for carbon green certificates of power sales companies is provided, comprising: Scenario construction module, which is used to construct multi-dimensional uncertainty operation scenarios for power sales companies; A power sales company transaction strategy building module, which builds a power sales company participation in power market transaction model based on the multi-dimensional uncertainty operation scenario of the power sales company; A carbon emission rights acquisition module, which constructs a carbon market trading model for power sales companies based on the power sales company's participation in the electricity market trading model, and obtains the carbon emission rights of the power sales company; Green certificate market transaction construction module, which is used to build a model for power sales companies to participate in green certificate market transactions; A multi-market combination trading strategy building module is established based on the carbon emission rights and green certificate market trading model, combined with the multi-dimensional uncertainty operation scenario of the power sales company and the power sales company's participation in the electricity market trading model, to establish a combination trading model that takes into account multiple uncertainties and covers multiple markets. This model can design procurement and use plans for electricity, carbon emission rights and green certificates for different user packages, and use this model to realize the multi-market combination trading of electricity, carbon and green certificates of the power sales company.

[0006] According to a third aspect of the present invention, there is provided a computer terminal comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, can be used to execute the method described above in the present invention, or to run the system described above in the present invention.

[0007] According to a fourth aspect of the present invention, there is provided a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, can be used to execute the method described above in the present invention, or to run the system described above in the present invention.

[0008] Due to the adoption of the above technical solution, the present invention has at least one of the following beneficial effects compared with the prior art: The multi-market combination trading method and system for carbon green certificates of power sales companies provided in the present invention model various uncertainty factors through normal distribution, Beta distribution and Weibull distribution, and extract representative operating scenarios by combining Monte Carlo sampling and K-means clustering, which significantly simplifies the processing difficulties of high-dimensional uncertainty faced by power sales companies and improves the scientificity and practicality of uncertain scenario construction.

[0009] The multi-market combination trading method and system for electric carbon green certificates of power sales companies provided by the present invention integrate conventional medium- and long-term transactions, green electricity transactions and spot market transactions in the electricity market trading model, and introduce a dynamic adjustment mechanism to optimize green electricity contracts, thereby enhancing the flexibility of trading strategies and effectively responding to fluctuations in electricity supply and demand.

[0010] The multi-market combination trading method and system for carbon green certificates of power sales companies provided by the present invention construct a multi-market combination trading model, and optimize the cost and risk balance in combination with the CVaR model. The invention provides scientific decision-making support for power sales companies in a multi-market environment to achieve cost minimization and risk control. The multi-market combination trading method and system for carbon green certificates of power sales companies provided by the present invention achieve efficient utilization of power generation and low-carbon emissions, meet the deployment requirements of low-carbon transactions in existing market transactions, and provide a combination trading model that considers multiple uncertainties and covers multiple markets for the existing energy trading market. Through multi-market combination transactions of carbon green certificates of power sales companies, the market can achieve low-carbon economic operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings: Figure 1 This is a workflow diagram of a multi-market combination trading method for electric carbon green certificates of a power sales company in a preferred embodiment of the present invention.

[0012] Figure 2 This is a schematic diagram of the component modules of a multi-market combination trading system for electric carbon green certificates of a power sales company in a preferred embodiment of the present invention. DETAILED DESCRIPTION

[0013] The following is a detailed description of the embodiments of the present invention: This embodiment is implemented on the premise of the technical solution of the present invention, and a detailed implementation method and a specific operation process are given. It should be pointed out that for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention.

[0014] In the prior art, the trading strategies of power sales companies generally face insufficient technical capabilities. Most companies have not yet formed a scientific decision-making model based on data-driven, and how to achieve information interaction, risk diversification and profit optimization among multiple markets is still a difficult point in technical research. In response to the above problems, an embodiment of the present invention provides a multi-market combination trading method for electricity, carbon and green certificates of power sales companies. This method is aimed at the study of multi-market combination trading strategies for electricity, carbon and green certificates, which can not only enhance the competitiveness of power sales companies in uncertain environments, but also provide important support for promoting the efficient operation and green transformation of the energy market.

[0015] Specifically, Figure 1 As shown, the multi-market combination trading method of carbon green certificates of power sales companies provided in this embodiment may include: S1, constructing a multi-dimensional uncertainty operation scenario for power sales companies; S2, based on the multi-dimensional uncertainty operation scenarios of power sales companies, build a model for power sales companies to participate in power market transactions; S3, based on the electricity sales company's participation in the electricity market trading model, build a model for the electricity sales company to participate in the carbon market trading model and obtain the carbon emission rights of the electricity sales company; S4, build a trading model for power sales companies to participate in the green certificate market; S5, based on the carbon emission rights and green certificate market trading model, combined with the multi-dimensional uncertainty operation scenarios of power sales companies and the power sales companies' participation in electricity market trading models, a combined trading model that considers multiple uncertainties and covers multiple markets is established. This model can design procurement and use plans for electricity, carbon emission rights and green certificates for different user packages, and use this model to realize multi-market combined trading of electricity, carbon and green certificates by power sales companies.

[0016] The technical solution provided by the above embodiment of the present invention is further described in detail below in conjunction with the preferred implementation manner.

[0017] In a preferred embodiment, the electric carbon green certificate multi-market combination trading method of the power sales company includes the following steps: S1, construct multiple uncertainty scenarios: construct scenarios for the uncertainties faced by power sales companies in their operational practices, including the spot price of electricity, the price of carbon emission rights, the price of green certificates, the output of new energy, and the carbon emission intensity of spot electricity.

[0018] S2, establishes a model for power sales companies to participate in power market transactions, taking into account conventional medium- and long-term power transactions, green power transactions, and power spot market transactions. For conventional medium- and long-term power transactions, when there is a gap between the power decomposition curve in the contract signed by the power sales company and the benchmark curve, the power generator will need to deviate from the optimal operating state or use other transactions to hedge this deviation. For green power transactions, the green power contract quantity is adjusted in proportion to the actual power generation of the power generator and the actual power consumption of the user, and the smaller value under the constraints of the two is finally taken. For spot market transactions, power spot transactions provide power sales companies with energy balance and power price sources, and user power consumption deviations are settled according to the system marginal power price.

[0019] S3, establish a trading model for power sales companies to participate in the carbon market. Power sales companies fulfill their zero-carbon commitments through carbon market transactions and set limits on the total amount of carbon emission rights purchased in a single month, based on meeting service requirements.

[0020] S4, establish a trading model for power sales companies to participate in the green certificate market, in which the power sales companies do not consider their own renewable energy power generation and can only purchase but not sell green certificates.

[0021] S5, build a multi-market combination trading model for power sales companies that takes into account multiple uncertain risks. The power sales companies will determine the electricity, carbon, and green certificate purchase and use plans for users of different packages, and realize the power sales companies' multi-market combination trading of electricity, carbon, and green certificates.

[0022] In some preferred implementations, in the above S1, the power sales company first needs to build a multi-dimensional uncertainty scenario, including factors such as the spot price of electricity, the price of carbon emission rights, the price of green certificates, the output of new energy power generation, and the carbon emission intensity of spot electricity. The specific implementation methods include: S11. The uncertainties faced by power sales companies that provide green power packages and zero-carbon power packages to power users in their operational practices mainly include the spot power price, carbon emission rights price, green certificate price, new energy output, and spot power carbon emission intensity. Among them: The spot price of electricity, the price of carbon emission rights, and the price of green certificates are characterized by normal distribution, and the specific form is: (1) The uncertainty of the power generation of a photovoltaic power plant is described by the Beta distribution, and its specific formula is: (2) The uncertainty of wind farm power generation is described by Weibull distribution, and its specific formula is: (3) In the formula, is the independent variable, is the dependent variable, , are the mean and variance of the normal distribution, , are the parameters of the Beta distribution, and are the parameters of the Weibull distribution.

[0023] S12, in the generation of operation scenarios of power sales companies, a large number of high-dimensional operation scenarios can be generated by using Monte Carlo sampling method based on parameter distribution. However, due to the extremely large number of scenarios brought by high-dimensional variables, this scenario set will cause the problem of dimensionality curse in the optimization solution process. In order to solve this problem, clustering algorithm, as a mature method, can extract a small number of representative typical scenarios from a large set of scenarios for solving optimization strategies. Among them, k-means clustering is a classic unsupervised classification algorithm that classifies samples in an iterative manner. This method assumes that the similarity between samples is determined by distance, and the closer the distance, the higher the similarity. Specifically, several samples are first randomly selected as the initial cluster centers, and then the distance between each sample and these centers is calculated, and the samples are assigned to the category corresponding to the nearest cluster center. Then, the cluster center is recalculated for each category to update it to the mean position of all samples in the category. Repeat the calculation until the set number of iterations is reached or the cluster center no longer changes. In this way, the originally complex and large set of scenarios can be effectively simplified into a small number of key scenarios, greatly reducing the computational complexity of the optimization solution.

[0024] In some preferred implementations, in the above S2, the power sales company needs to coordinate the participation in conventional medium- and long-term power transactions, green power transactions, and power spot market transactions. In conventional medium- and long-term power transactions, if the power decomposition curve in the contract deviates from the benchmark curve, the power generator needs to hedge the error by adjusting the unit operation or using other transaction forms. Green power transactions dynamically adjust the contract power in proportion to the actual power generation of the power generator and the actual power consumption of the user, and ultimately the lower limit of the constraints of the two shall prevail. Spot market transactions provide power sales companies with energy balancing services and sources of electricity prices, and settle user power consumption deviations through the system marginal electricity price. Specific implementation methods include: S21, establish a model for power sales companies to participate in medium- and long-term transactions of conventional electricity: This step uses a simplified method to model the negotiation behavior between power generators and power sales companies on the price of medium- and long-term power contracts. It is believed that there is a benchmark selling price and a benchmark electricity decomposition curve suitable for the power generation units under its jurisdiction in the decision-making of the power generator. When there is a gap between the electricity decomposition curve in the contract signed by the power sales company and the benchmark curve, the power generator will need to make its power generation units deviate from the optimal operating state or use other transactions to hedge this deviation, which will lead to an increase in costs. The electricity price in the signed contract will increase on the benchmark electricity price. The greater the deviation of the decomposition curve, the higher the contract electricity price. The specific mathematical formula is: (4) In the formula, is the cost of purchasing electricity under the medium- and long-term contract with power generator i, is the medium- and long-term contract power purchase price of power generator i, It is the amount of electricity divided into time period t from the medium- and long-term electricity contract purchased by package j users from power generator i.

[0025] (5) In the formula, is the benchmark price for power purchases under medium- and long-term contracts of power generator i; is the component of the medium- and long-term contract power decomposition curve of power generator i in period t, and satisfies ; is the sensitivity coefficient of generator preference.

[0026] In the above formula, the contract pricing is based on the square of the second norm of the deviation between the actual decomposition curve of the medium- and long-term electricity purchase volume and the benchmark curve. The characteristics of the quadratic function are consistent with the tendency of actual decision-making. When the deviation is small, the price increase caused by the increase of unit deviation is small, and when the deviation is large, the price increase caused by the increase of unit deviation is large. However, if the above continuous model is used for modeling, formula (4) will contain extremely complex bivariate product terms, which cannot guarantee the computational feasibility of the problem and the acquisition of the global optimal solution. Therefore, it is necessary to linearize formula (5). Considering that the price decision of the buyer and seller in actual negotiations is usually not continuous but discrete, the formula can be linearized into the following if-then constraint form: (6) In order to prevent excessive speculation between spot and medium- and long-term transactions by power sales companies, an upper limit constraint on medium- and long-term power transactions is introduced: (7) In the formula, It is the limit coefficient of the amount of electricity that the electricity sales company can purchase on behalf of the users in the medium and long-term market. It is the electricity consumption of all users of package j represented by the electricity sales company during time period t.

[0027] In addition, all medium- and long-term electricity transactions should also meet the transaction feasibility constraints, namely: (8) S22, establish a model for power sales companies to participate in green power trading: When the total green power contract electricity sold by a green power generator in a certain period exceeds the actual power generation, the electricity of each contract must be reduced proportionally to ensure that the total green power contract electricity is equal to the actual power generation; if the total green power contract electricity purchased by the power user in a certain period is less than its actual power consumption, the electricity of each contract shall be reduced proportionally to make the total green power contract electricity consistent with the actual power consumption; for some green power contracts, if the above two rules are in effect at the same time, the smaller value of the two shall be used as the final corrected electricity. Compared with traditional medium- and long-term transactions, green power transactions are uncertain. Power generators usually determine the total amount of green power contracts based on their forecasts of power generation, and the contracts signed between power sales companies and green power generators will correspond to different actual settlement electricity in different operating scenarios: (9) In the formula, Represents the minimum function, which is used to return the smaller value of a and b; It's a scene The amount of green electricity actually settled by the power sales company for the user of package j from the green electricity generator i in period t, is the contractual electricity quantity at the time of signing the contract; , is the predicted power generation and scenario of green power generator i in period t The corresponding actual power generation.

[0028] Under the guidance of the above rules, in order to control the risks of power sales companies, the following constraints are set to reduce the uncertainty of the signed green power contracts: (10) (11) (12) (13) In the formula, It is the risk management coefficient for green electricity package users to purchase green electricity. To control the risk of default, .

[0029] Formula (10) is the feasibility constraint of the green electricity contract. The total contract quantity signed between the power sales company and the green electricity generator is non-negative. When it is believed that the green electricity generator will not sell more electricity than its predicted power generation, Formula (11) restricts the total purchase quantity of the power sales company and a single green electricity generator to not exceed the predicted power generation of the green electricity company. Formula (12) restricts the users of conventional packages and zero-carbon packages that do not mainly purchase green electricity to the amount of green electricity they purchase that does not exceed their actual electricity consumption. Since users of green electricity packages need to purchase green electricity in full, Formula (13) allows the amount of green electricity purchased for users of the package to exceed their load electricity to hedge the uncertainty of green electricity execution.

[0030] Therefore, the cost of purchasing green electricity for power sales companies is: (14) In the formula, It's a scene The cost of the electricity sales company purchasing green electricity from green electricity generator i in the next period t is: It is the green electricity contract price given by green electricity generator i.

[0031] S23, establish a power spot trading model: In the overall transaction portfolio of the power sales company, spot electricity trading mainly plays the role of energy balance, while providing the power sales company with a variety of electricity price sources. In order to simplify the analysis, it is assumed that the power sales company is the price acceptor, and the deviation between the actual electricity consumption of all users it represents and the medium- and long-term contract electricity consumption is settled according to the marginal electricity price centrally cleared by the whole system. Therefore, the cost calculation of spot electricity trading is based on this settlement method: (15) In the formula, , and They are respectively running scenarios The spot electricity purchase cost, spot electricity purchase volume and spot electricity price of the power sales company in time period t.

[0032] The spot purchase quantity in each scenario and time period is determined by the purchase and sales balance constraints of the power sales company. (16) In some preferred implementations, in the above S3, the power sales company focuses on fulfilling its zero-carbon commitment, reasonably purchases carbon emission rights through the carbon market, and sets an upper limit on the total purchase of carbon emission rights each month to ensure that both service requirements are met and additional costs caused by excessive purchases are avoided. Specific implementation methods include: S31, calculate the cost of electricity sales companies participating in carbon market transactions: The users represented by the power sales companies are all residential users, and according to current policies, they have no legal obligation to control greenhouse gas emissions. Therefore, the purpose of the power sales companies participating in the carbon market is to fulfill their zero-carbon commitments by purchasing carbon emission rights when serving zero-carbon package users.

[0033] The cost of electricity sales companies participating in carbon market transactions can be calculated using the following formula: (17) In the formula, , and are the cost of the electricity sales company participating in the carbon market, the carbon emission rights trading volume (buying is positive) and the national carbon emission rights market price in period t respectively; It is the collection of time periods when power sales companies participate in the carbon market. Since carbon market transactions are similar to stock market transactions, no transactions are conducted on weekends and holidays, so a single month is considered to be 22 trading days.

[0034] S32, set constraints on electricity sales companies participating in carbon trading: Carbon market transactions allow buying and selling, so power sales companies can arbitrage from market price fluctuations. To prevent excessive arbitrage, trading restrictions are set for the carbon market.

[0035] The total amount of carbon emission rights purchased in the carbon market in a single month is capped, based on the total amount of carbon emission rights that the power sales company needs to purchase to meet service requirements: (18) In the formula, the function Equivalent to , which is used to retain positive values ​​and discard negative values; is the upper limit factor of carbon emission rights purchased by power sales companies, is the reference electricity carbon emission intensity, It is the low carbon factor of the regular electricity package.

[0036] An upper limit is set on the carbon emission rights held by power sales companies in the carbon market, based on the total amount of carbon emission rights that the power sales companies need to purchase to meet service requirements, and it is required that when selling carbon emission rights, a corresponding number of carbon emission rights must be ensured in the account.

[0037] (19) In the formula, It is the upper limit factor of carbon emission rights holding of power sales companies.

[0038] In some preferred implementations, the above S4, transactions in the green certificate market, the power sales company is limited to purchasing green certificates to meet user needs, does not consider the power sales company's own renewable energy generation capacity, and does not participate in the sale of green certificates. Specific implementation methods include: S41, calculate the cost of electricity sales companies participating in green certificate market transactions: Power sales companies are important entities that need to assume the responsibility of consuming electricity on behalf of their users, and they need to bear the consumption volume corresponding to the amount of electricity they sell.

[0039] The cost for power sales companies to participate in green certificate market transactions is: (20) In the formula, , and are the cost of participating in the green certificate market, green certificate trading volume (buying is positive) and market price of the power sales company in period t respectively; It is the collection of time periods when power sales companies participate in the green certificate market. Since the green certificate market is open for trading all year round, a single month is considered to be 30 trading days.

[0040] S42, set constraints on power sales companies participating in green certificate market transactions: According to the green certificate market trading regulations, green certificates can only be traded once at this stage. Therefore, when the power sales company's self-operated renewable energy power generation is not considered, the power sales company can only buy but not sell green certificates, that is: (twenty one) In some preferred implementations, the above S5 formulates a comprehensive trading strategy covering multiple markets, and designs the purchase and use plans of electricity, carbon emission rights and green certificates for different user packages while considering multiple uncertain risks. The specific implementation methods are as follows: Step S51: Establishing a risk management model for a power sales company: The conditional value at risk (CVaR) model is used to assess the risks faced by power sales companies. Its specific form is: (twenty two) In the formula, is the risk loss value borne by the retailer measured by the conditional value at risk; VaR is the value at risk, which satisfies The confidence level is ; It's a scene The probability of occurrence, It's a scene The profit of the power sales company is the difference between revenue and cost.

[0041] By introducing auxiliary variables The above formula is linearized into the following form: (twenty three) (twenty four) (25) In the formula, Both VAR and VaR are auxiliary variables and do not require prior value assignment.

[0042] Step S52: Establish a multi-market combination transaction of the power sales company taking into account multiple uncertain risks.

[0043] Constraints related to green and low-carbon asset allocation: (26) (27) In the formula, , , and The green certificates purchased by the power sales company for the whole month are The following allocations are used for the consumption responsibility of conventional package users, the consumption responsibility of zero-carbon package users, carbon reduction of conventional packages and carbon reduction of zero-carbon packages, and each share is required to be non-negative.

[0044] (28) (29) In the formula, , The carbon emission rights purchased by the power sales company for the whole month are The following allocations are used for conventional package carbon offsets and zero-carbon package carbon offsets, and require that each allocation amount is non-negative.

[0045] (30) (31) (32) (33) In the formula, , The environmental value of green electricity purchased by the electricity sales company for the regular package in the whole month is The portion allocated below is used for the consumption responsibility and carbon emission offset of regular package users; , The environmental value of the green electricity purchased by the power sales company for the zero-carbon package in the whole month is The following allocation is used for the consumption responsibility of zero-carbon package users and the portion of carbon emissions offset; all allocated amounts are non-negative.

[0046] Regular package fulfillment constraints: Electricity sales companies need to reasonably arrange carbon assets to ensure that conventional package users meet their consumption responsibilities.

[0047] In the formula, It's a scene Under the regular package, users who fail to meet their consumption obligations will be fined. is the renewable energy consumption responsibility weight; the coefficient 30 represents 30 days.

[0048] The carbon inventory formula for conventional package users based on electricity trading is: (34) In the formula, It's a scene The carbon inventory results of regular package users after reasonable carbon asset allocation; and Conventional power generators i Carbon emission intensity and scenarios The spot carbon intensity at time t in the next period; It is the amount of carbon reduction that can be claimed for a single green certificate.

[0049] In addition, in order to prevent the green certificates from being used to declare carbon offset quotas and causing a major impact on the carbon market, similar policy regulations as CCER are adopted to limit the carbon reduction amount declared by green certificates to no more than a certain proportion of the annual carbon emissions of the subject. (35) In the formula, It is the transfer factor of green certificates to offset carbon emissions. The carbon emission intensity of electricity consumption is used as a reference; In addition, since the preferred implementation target is the power sales company with green and low-carbon as its core competitiveness, its regular package users should also enjoy certain green and low-carbon benefits, that is, the average carbon intensity of electricity consumption should be lower than the carbon emission factor of the power grid: (36) In the formula, It is the low-carbon level coefficient given by the electricity sales company to users of regular packages, and its value should be less than 1.

[0050] Green electricity package performance constraints: Since green electricity package users actually consume green electricity to meet the full load as much as possible, their consumption responsibility can be considered to be always met, and no additional consideration is needed. In addition, pure green electricity and carbon neutrality are not demands of the same dimension. For green electricity package users, power sales companies only try to ensure that all their electricity is green electricity and provide corresponding certificates, and no longer consider their carbon inventory situation.

[0051] The power sales company guarantees that it will not allocate any thermal power contracts for the green power package user group, that is, (37) Since green electricity has great uncertainty in both production and consumption, it is impossible for power sales companies to completely hedge the default risk of green electricity packages through medium- and long-term green electricity transactions alone, and they still need to compensate users for their defaults. (38) In the formula, It's a scene The difference between the user load of the green electricity package and the actual settled green electricity volume is the default electricity volume of the power sales company.

[0052] Zero Carbon Package Compliance Constraints: Electricity sales companies need to reasonably arrange carbon assets to ensure that zero-carbon package users meet their consumption responsibilities. (39) In the formula, It's a scene Users of the zero-carbon package who fail to fulfill their consumption responsibilities will be required to pay a fine.

[0053] Carbon neutrality is the core demand of users of zero-carbon packages. Electricity sales companies can achieve carbon neutrality and fulfill their contracts by configuring green electricity contracts, using green certificates to offset carbon emissions, and directly purchasing carbon quotas. The carbon inventory formula for users of zero-carbon packages based on electricity trading is: (40) In the formula, It's a scene The carbon inventory results of users of the zero-carbon package after reasonable carbon asset allocation.

[0054] In addition, the carbon reduction amount reported by the green certificate shall not exceed a certain proportion of the annual carbon emissions of the subject. (41) When the power sales company is unable to achieve carbon neutrality for zero-carbon package users, it needs to pay liquidated damages for the corresponding amount of defaulted electricity. (42) In the formula, It's a scene The power sales company will refund the zero-carbon package users for breach of contract and failure to achieve the carbon neutrality commitment.

[0055] Objective function: (43) In the formula, the first term is the expected return, and the second is the risk loss, It is the risk aversion factor of the power sales company.

[0056] In this preferred implementation, the multi-market combination trading model of the power sales company is essentially a two-stage stochastic programming model, the two stages are the here-and-now stage and the wait-and-see stage. The former corresponds to the medium- and long-term power transactions, carbon transactions, and green certificate trading plans that need to be decided before the uncertainty is observed. These trading decisions should be independent of the scenario, so that an overall decision result can be obtained to provide effective guidance for the combination trading decision; the latter corresponds to the decisions made after the uncertainty is observed, such as spot purchase electricity, green electricity contract settlement electricity, and the use and allocation of carbon assets. These decisions can be dynamically adjusted according to actual conditions.

[0057] Therefore, the operation scenario The complete expression of the expected revenue of the power sales company is: (44) In the formula, , and They are the electricity selling prices of the conventional package, green electricity package, and green certificate package set by the electricity selling company at time period t; , and They are the fines required to be paid for the unfulfilled unit consumption responsibility, the penalty per unit of electricity volume defaulted by the power sales company for the green electricity package users, and the penalty per unit of electricity volume defaulted by the power sales company for the zero-carbon package users. In the formula, the first row is the income that the power sales company can obtain from selling electricity to users, the second row is the cost paid by the power sales company for purchasing electricity and green rights from the electricity carbon green certificate multi-market, and the third row is the default cost that the power sales company needs to pay after comprehensively considering the company's situation and reasonably allocating electricity contracts and carbon assets.

[0058] Based on the same inventive concept, an embodiment of the present invention also provides a multi-market combination trading system for carbon green certificates of power sales companies.

[0059] Specifically, Figure 2 As shown, the multi-market combination trading system of carbon green certificates for power sales companies provided in this embodiment may include: Scenario construction module, which is used to construct multi-dimensional uncertainty operation scenarios for power sales companies; A power sales company transaction strategy building module, which builds a power sales company participation in power market transaction model based on the multi-dimensional uncertainty operation scenario of the power sales company; A carbon emission rights acquisition module, which constructs a carbon market trading model for power sales companies based on the power sales company's participation in the electricity market trading model, and obtains the carbon emission rights of the power sales company; Green certificate market transaction construction module, which is used to build a model for power sales companies to participate in green certificate market transactions; A multi-market combination trading strategy building module is established based on the carbon emission rights and green certificate market trading model, combined with the multi-dimensional uncertainty operation scenario of the power sales company and the power sales company's participation in the electricity market trading model, to establish a combination trading model that takes into account multiple uncertainties and covers multiple markets. This model can design procurement and use plans for electricity, carbon emission rights and green certificates for different user packages, and use this model to realize the multi-market combination trading of electricity, carbon and green certificates of the power sales company.

[0060] It should be noted that the steps in the method provided by the present invention can be implemented by using corresponding modules, devices, units, etc. in the system. Those skilled in the art can refer to the technical solution of the method to realize the composition of the system, that is, the embodiments in the method can be understood as preferred examples for constructing the system, which will not be elaborated here.

[0061] An embodiment of the present invention further provides a computer terminal, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the processor can be used to execute any method of the above-mentioned embodiments of the present invention, or to run any system of the above-mentioned embodiments of the present invention.

[0062] Optionally, the memory is used to store programs; the memory may include volatile memory (English: volatile memory), such as random access memory (English: random-access memory, abbreviated: RAM), such as static random access memory (English: static random-access memory, abbreviated: SRAM), double data rate synchronous dynamic random access memory (English: Double Data Rate Synchronous Dynamic Random Access Memory, abbreviated: DDR SDRAM), etc.; the memory may also include non-volatile memory (English: non-volatile memory), such as flash memory (English: flash memory). The memory is used to store computer programs (such as applications, functional modules, etc. that implement the above method), computer instructions, etc., and the above computer programs, computer instructions, etc. can be partitioned and stored in one or more memories. And the above computer programs, computer instructions, data, etc. can be called by the processor.

[0063] The processor is used to execute the computer program stored in the memory to implement the various steps of the method or various modules of the system involved in the above embodiments. For details, please refer to the relevant descriptions in the above method and system embodiments.

[0064] The processor and the memory may be independent structures or integrated structures. When the processor and the memory are independent structures, the memory and the processor may be coupled and connected via a bus.

[0065] An embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, it can be used to execute any method of the above embodiments of the present invention, or to run any system of the above embodiments of the present invention.

[0066] Among them, computer-readable media include computer storage media and communication media, wherein the communication media include any media that facilitates the transmission of computer programs from one place to another. The storage medium can be any available medium that can be accessed by a general or special-purpose computer. An exemplary storage medium is coupled to the processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be an integral part of the processor. The processor and the storage medium can be located in an ASIC. In addition, the ASIC can be located in a user device. Of course, the processor and the storage medium can also be present in a communication device as discrete components.

[0067] The multi-market combination trading method and system of carbon green certificates for power sales companies provided in the above embodiments of the present invention model various uncertainty factors through normal distribution, Beta distribution and Weibull distribution, and extract representative operation scenarios by combining Monte Carlo sampling and K-means clustering, which significantly simplifies the problem of dealing with high-dimensional uncertainty faced by power sales companies and improves the scientificity and practicality of scenario construction; in the power market trading model, conventional medium- and long-term transactions, green electricity transactions and spot market transactions are integrated, and a dynamic adjustment mechanism is introduced to optimize green electricity contracts; the flexibility of trading strategies is enhanced to effectively respond to fluctuations in power supply and demand; a multi-market combination trading model is constructed, and the CVaR model is combined to optimize the balance between cost (or benefit) and risk, providing scientific decision-making support for power sales companies in a multi-market environment, achieving cost minimization (or benefit maximization) and risk control; achieving efficient utilization of generated power and low-carbon emissions, meeting the deployment requirements of low-carbon transactions in existing market transactions, and providing a combination trading model that considers multiple uncertainties and covers multiple markets for the existing energy trading market, and realizing low-carbon economic operation of the market through multi-market combination trading of carbon green certificates for power sales companies.

[0068] All matters not covered in the above embodiments of the present invention are well known in the art.

[0069] The above describes the specific embodiments of the present invention. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art may make various modifications or variations within the scope of the claims, which do not affect the essence of the present invention.

Claims

1. A multi-market combination trading method for carbon green certificates of power sales companies, characterized in that: include: Construct multi-dimensional uncertainty operation scenarios for power sales companies; Based on the multi-dimensional uncertainty operation scenario of the power sales company, a model for the power sales company to participate in the power market transaction is constructed; Based on the electricity sales company's participation in the electricity market trading model, a model for the electricity sales company to participate in the carbon market trading model is constructed to obtain the carbon emission rights of the electricity sales company; Construct a trading model for power sales companies to participate in the green certificate market; Based on the carbon emission rights and green certificate market trading model, combined with the multi-dimensional uncertainty operation scenario of the power sales company and the power sales company's participation in the electricity market trading model, a combined trading model that considers multiple uncertainties and covers multiple markets is established, and the combined trading model is used to realize the multi-market combined trading of the power sales company's electricity carbon green certificate; The construction of a multi-dimensional uncertainty operation scenario for a power sales company includes: The uncertainties faced by power sales companies in their operations include: spot electricity prices, carbon emission rights prices, green certificate prices, renewable energy power generation output, and spot electricity carbon emission intensity; among them: The uncertainty of electricity spot price, carbon emission rights price and green certificate price is described by normal distribution, and the corresponding parameter distribution expression is obtained as follows: （1） The uncertainty of the power generation of a photovoltaic power plant is described by Beta distribution, and the corresponding parameter distribution expression is: （2） The uncertainty of wind farm power generation is described by Weibull distribution, and the corresponding parameter distribution expression is: （3） In the formula, is the independent variable, is the dependent variable, , are the mean and variance of the normal distribution, , are the parameters of the Beta distribution, and is the parameter of Weibull distribution; Based on the parameter distribution of the above uncertainty scenarios, a Monte Carlo sampling method is used to generate a scenario set containing multi-dimensional uncertainty operation scenarios of multiple power sales companies; The k-means clustering method is used to iteratively classify the scenario set to simplify the multi-dimensional uncertainty operation scenario of the power sales company required in the end; The method of constructing a power sales company's participation in power market transactions based on the multi-dimensional uncertainty operation scenario of the power sales company includes: A model for power sales companies to participate in conventional power medium- and long-term transactions is established, which can be expressed as: （4） In the formula, For power sales companies and power generators i The cost of purchasing electricity through medium- and long-term contracts; For power generators i The medium- and long-term contract power purchase price; Package for electricity sales companies j Users from power generators i The purchased medium- and long-term electricity contracts are broken down into time periods t The amount of electricity; （5） In the formula, For power generators i The benchmark price for electricity purchases under medium- and long-term contracts; For power generators i The mid- and long-term contract electricity decomposition curve is in the period t of weight and satisfy ; For power generators i sensitivity coefficient of preference; Linearize equations (4) and (5) into if-then constraint form, expressed as: （6） Introducing the upper limit constraint of medium- and long-term electricity transactions, expressed as: （7） In the formula, The limit coefficient for the amount of electricity that the electricity sales company can purchase on behalf of users in the medium and long-term market; The power consumption of all users of package j represented by the power sales company during time period t; All medium- and long-term electricity transactions also meet the transaction feasibility constraints, which can be expressed as: （8） A model for power sales companies to participate in green power trading is established, which can be expressed as: （9） In the formula, Represents the minimum function, used to return a , b The smaller value of ; For the scene The electricity sales company is a package j Green power generators i Time t The amount of green electricity actually settled, The contractual electricity quantity at the time of signing the contract; , For green power generators i In the period t Forecasted power generation and scenarios The corresponding actual power generation; The following constraints are set for power sales companies to participate in the green power trading model: （10） （11） （12） （13） In the formula, The risk management coefficient for power sales companies to purchase green electricity for green electricity package users, and meet ; Among them, formula (10) is the feasibility constraint of the green electricity contract; formula (11) is the constraint that the total amount of electricity purchased by the power sales company and a single green electricity generator cannot exceed the predicted power generation of the green electricity company; formula (12) is the constraint that the amount of green electricity purchased by users of conventional packages and / or zero-carbon packages that do not mainly purchase green electricity does not exceed their actual electricity consumption; formula (13) is the constraint that allows users of green electricity packages to purchase green electricity that exceeds their load electricity to hedge the uncertainty of green electricity execution; Therefore, the cost of purchasing green electricity for power sales companies is: （14） In the formula, For the scene Next period t Electricity sales companies from green power generators i The cost of purchasing green electricity, For green power generators i The green power contract price given; The electricity spot trading model is established and expressed as: （15） In the formula, , and Run the scenarios Electricity sales company time period t spot electricity purchase cost, spot electricity purchase quantity and spot electricity price; Determine the spot purchase quantity in each scenario and time period through the purchase and sales balance constraints of the power sales company for: （16）； The method of constructing a carbon market trading model for power sales companies based on the power sales company's participation in the power market trading model to obtain the carbon emission rights of the power sales company includes: The cost of electricity sales companies participating in carbon market transactions is calculated as: （17） In the formula, , and The time periods t The cost of electricity sales companies participating in the carbon market, the volume of carbon emission rights trading, and the national carbon emission rights market price; It is a collection of time periods for power sales companies to participate in the carbon market; Based on the total amount of carbon emission rights that the power sales company needs to purchase to meet service requirements, the upper limit for the total purchase of carbon emission rights in the carbon market in a single month is set as follows: （18） In the formula, the function Equivalent to , which is used to retain positive values ​​and discard negative values; Purchase carbon emission rights cap factors for electricity sales companies; The carbon emission intensity of electricity consumption is used as a reference; The low carbon factor for conventional electricity packages; To balance the purchase and sales of spot electricity through the electricity sales company; Based on the total amount of carbon emission rights that the power sales company needs to purchase to meet service requirements, and requiring that when selling carbon emission rights, the corresponding number of carbon emission rights must be guaranteed in the account, the upper limit of the carbon emission rights held by the power sales company in the carbon market is set as follows: （19） In the formula, It is the upper limit factor of carbon emission rights held by power sales companies; The construction of a trading model for power sales companies to participate in the green certificate market includes: The cost of electricity sales companies participating in green certificate market transactions is calculated as follows: （20） In the formula, , and The time periods t The cost, transaction volume and market price of green certificates for power sales companies participating in the green certificate market; It is a collection of time periods for power sales companies to participate in the green certificate market; Set constraints on power sales companies participating in green certificate market transactions, that is, power sales companies can only buy but not sell green certificates, then: （21）。 2. The multi-market combination trading method of carbon green certificates of power sales companies according to claim 1 is characterized in that: Based on the carbon emission rights and green certificate market transaction model, combined with the multi-dimensional uncertainty operation scenario of the power sales company and the power sales company's participation in the power market transaction model, a combined transaction model that considers multiple uncertainties and covers multiple markets is established, including: The risk management model of power sales companies is established by using the conditional value at risk model to assess the risks faced by power sales companies: （22） In the formula, is the risk loss value borne by the retailer measured using the conditional risk value model; VaR is the risk value and satisfies ; is the confidence level; For the scene The probability of occurrence; For the scene The profit of the power sales company is the difference between revenue and cost; By introducing auxiliary variables , linearize equation (22) into: （23） （24） （25） In the formula, and VaR are auxiliary variables; Establish a multi-market portfolio transaction model for power sales companies that takes into account multiple uncertain risks, including: The relevant constraints for allocating green and low-carbon assets are: （26） （27） In the formula, For the period t The volume of green certificate transactions of power sales companies participating in the green certificate market; , , and The green certificates purchased by the power sales company for the whole month are The following allocations are used for the consumption responsibility of regular package users, the consumption responsibility of zero-carbon package users, carbon reduction of regular packages and carbon reduction of zero-carbon packages, and each allocation is required to be non-negative; （28） （29） In the formula, , The carbon emission rights purchased by the power sales company for the whole month are The following allocations are used for conventional package carbon offsets and zero-carbon package carbon offsets, and each allocation is required to be non-negative; （30） （31） （32） （33） In the formula, , The environmental value of green electricity purchased by the electricity sales company for the regular package in the whole month is The portion allocated below is used for the consumption responsibility and carbon emission offset of regular package users; , The environmental value of the green electricity purchased by the power sales company for the zero-carbon package in the whole month is The following allocations are used for the consumption responsibility of zero-carbon package users and the offset of carbon emissions; all allocations are non-negative; Establishing performance constraints for regular packages of electricity sales companies, including: The establishment of a power sales company to arrange carbon assets should ensure that the constraints on the consumption responsibility of conventional package users are met: ； In the formula, For the scene The unfulfilled amount of consumption responsibility of regular package users; Responsibility weight for renewable energy consumption; The carbon inventory results of regular package users based on electricity trading are calculated as follows: （34） In the formula, For the scene The carbon inventory results of regular package users after reasonable carbon asset allocation; and Conventional power generators i Carbon emission intensity and scenarios Next period t spot carbon intensity at the time of The carbon reduction amount that can be claimed for a single green certificate; The constraint that the carbon reduction amount reported by the green certificate shall not exceed the set proportion of the annual carbon emissions of the subject is established as follows: （35） In the formula, It is the transfer factor of green certificates to offset carbon emissions. The carbon emission intensity of electricity consumption is used as a reference; The constraint that the average carbon intensity of electricity consumption should be lower than the carbon emission factor of the power grid is: （36） In the formula, The low-carbon level coefficient given by the electricity sales company to users of regular packages should be less than 1; Establish green power package performance constraints for power sales companies, including: The constraints for establishing a power sales company to ensure that no thermal power contracts are allocated to green power package user groups are: （37） The constraints for establishing that the power sales company only provides compensation to users through the default volume of green power transactions of medium- and long-term transactions are: （38） In the formula, For the scene The difference between the load of the user of the green electricity package and the actual settled green electricity volume, i.e. the default electricity volume of the power sales company; Establish zero-carbon package compliance constraints, including: The establishment of a power sales company to arrange carbon assets should ensure that the zero-carbon package users meet the following constraints: （39） In the formula, For the scene The unfulfilled amount of consumption responsibility of users of zero-carbon packages; The carbon inventory results of zero-carbon package users based on electricity trading are calculated as follows: （40） In the formula, For the scene Carbon inventory results of users of the zero-carbon package after reasonable carbon asset allocation; The constraint that the carbon reduction amount reported by the green certificate shall not exceed the set proportion of the subject's annual carbon emissions is: （41） When the power sales company fails to achieve carbon neutrality compliance for zero-carbon package users, the corresponding default constraints are established as follows: （42） In the formula, For the scene The electricity sales company defaults on the zero-carbon package users and fails to achieve the carbon neutrality commitment; The objective function is established as: （43） In the formula, the first term is the expected return, the second term For risk loss, is the risk aversion factor of the power sales company; Therefore, the operation scenario The complete expression of the expected revenue of the power sales company is: （44） In the formula, , and The regular packages, green electricity packages and green certificate packages formulated by the power sales company are in the time period t The electricity price at that time; , and They are the fines required to be paid for the unfulfilled consumption responsibility of the unit, the liquidated damages per unit of electricity consumed by the power sales company for the green power package users who breach the contract, and the liquidated damages per unit of electricity consumed by the power sales company for the zero-carbon package users who breach the contract. In formula (44), the first line is the income that the power sales company can obtain from selling electricity to users, the second line is the cost paid by the power sales company to purchase electricity and green rights from the electricity carbon green certificate market, and the third line is the default cost that the power sales company needs to pay after comprehensively considering the company's situation and reasonably allocating electricity contracts and carbon assets.

3. A system for multi-market combination trading of carbon green certificates of power sales companies for implementing the multi-market combination trading method of carbon green certificates of power sales companies as claimed in claim 1 or 2, characterized in that: include: Scenario construction module, which is used to construct multi-dimensional uncertainty operation scenarios for power sales companies; A power sales company transaction strategy building module, which builds a power sales company participation in power market transaction model based on the multi-dimensional uncertainty operation scenario of the power sales company; A carbon emission rights acquisition module, which constructs a carbon market trading model for power sales companies based on the power sales company's participation in the electricity market trading model, and obtains the carbon emission rights of the power sales company; Green certificate market transaction construction module, which is used to build a model for power sales companies to participate in green certificate market transactions; A multi-market combination trading strategy construction module is established based on the carbon emission rights and green certificate market trading model, combined with the multi-dimensional uncertainty operation scenario of the power sales company and the power sales company's participation in the electricity market trading model, to establish a combination trading model that takes into account multiple uncertainties and covers multiple markets, and use the combination trading model to realize the multi-market combination trading of the power sales company's electricity carbon green certificate.

4. A computer terminal comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, it can be used to perform the method described in any one of claims 1 to 2, or to run the system described in claim 3.

5. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, it can be used to perform the method described in any one of claims 1 to 2, or to run the system described in claim 3.

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