Carbon electricity market transaction strategy optimization method and system based on risk assessment

Abstract

The invention provides a carbon electricity market transaction strategy optimization method and system based on risk assessment, and the method comprises the steps: combining a carbon electricity price conduction mechanism and a pre-constructed risk assessment model for a user to participate in a carbon electricity market transaction based on a predetermined index system influencing the carbon electricity market transaction and a carbon quota related constraint; constructing a carbon electricity market transaction simulation model by adopting a system dynamics method; based on historical production data of enterprises in a to-be-optimized park, different carbon electricity market transaction scenes are constructed respectively by adjusting a free quota issuing proportion and a carbon quota risk control scale; based on the constructed different carbon electricity market transaction scenes, performing simulation analysis through the constructed carbon electricity market transaction simulation model to obtain carbon electricity transaction costs and carbon electricity transaction risk levels of the to-be-optimized park corresponding to the different scenes; the carbon electricity transaction cost and the carbon electricity transaction risk level of the park to be optimized are used as dependent variables, the free quota issuing proportion and the carbon quota risk control scale are used as independent variables, and fitting of relation curves is carried out; and determining an optimal carbon electricity market transaction strategy based on the obtained relation curve.

Description

Technical Field

[0001] The present invention belongs to the technical field of power systems, and in particular relates to a method and system for optimizing carbon power market transaction strategies based on risk assessment. Background Art

[0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] Compared with traditional parks, low-carbon and near-zero-carbon parks have higher requirements for carbon emissions, and high-energy-consuming enterprises as the main body of the park can ensure the social and ecological benefits of the carbon trading system through timely and efficient carbon compliance. As an emerging market, the carbon market mainly trades carbon emission rights. Whether the emission-controlled enterprises can fulfill their compliance responsibilities and emission reduction obligations is affected by various factors such as relevant policies, quotas, and carbon prices.

[0004] The inventors found that traditional carbon-electricity market trading strategy optimization solutions usually only consider the carbon-electricity market transaction costs, but lack consideration of user compliance risks, resulting in a large number of users being unable to fulfill their obligations during the execution of the obtained optimization solution, which in turn causes the obtained optimization solution to be unable to be effectively implemented. Secondly, traditional carbon-electricity market trading strategies cannot well consider the market trading activity levels of users in different compliance stages, resulting in the obtained optimization solution being very likely to cause problems such as insufficient carbon quotas or excessive costs for users. Summary of the invention

[0005] The present invention provides a method and system for optimizing carbon power market trading strategies based on risk assessment, so as to solve the problem that traditional methods usually only consider the transaction costs of the carbon power market, but lack consideration of the user's performance risk, resulting in a large number of users being unable to fulfill their contracts during the execution of the obtained optimization plan, which in turn causes the obtained optimization plan to be unable to be effectively executed. Secondly, the traditional carbon power market trading strategy cannot well consider the market trading activity level of users in different performance stages, resulting in the obtained optimization plan being very likely to cause the user's carbon quota to be insufficient or the cost to be too high.

[0006] According to a first aspect of an embodiment of the present invention, a method for optimizing a carbon power market trading strategy based on risk assessment is provided, comprising:

[0007] Based on the causal relationship of carbon-electricity market transactions, determine the indicator system that affects carbon-electricity market transactions; wherein the indicator system includes indicators that affect electricity market transactions and indicators that affect carbon market transactions;

[0008] Based on the carbon market rules and the historical carbon compliance data of enterprises in the park to be optimized, carbon quota related constraints are constructed; wherein the carbon quota related constraints are formulated by dividing the entire carbon compliance process into a quota pre-allocation period, a quota issuance period and a compliance window period;

[0009] Based on the determined indicator system and carbon quota-related constraints that affect carbon power market transactions, combined with the carbon power price transmission mechanism and the pre-built risk assessment model for users participating in carbon power market transactions, a carbon power market transaction simulation model is constructed using the system dynamics method.

[0010] Based on the historical production data of enterprises in the park to be optimized, different carbon power market trading scenarios are constructed by adjusting the free quota issuance ratio and the carbon quota risk control scale;

[0011] Based on the different carbon power market transaction scenarios, the carbon power market transaction simulation model is constructed to conduct simulation analysis to obtain the carbon power transaction costs and carbon power transaction risk levels of the parks to be optimized corresponding to different scenarios;

[0012] The carbon power transaction cost and carbon power transaction risk level of the park to be optimized are taken as dependent variables, and the free quota issuance ratio and carbon quota risk control scale are taken as independent variables, and the relationship curves are fitted respectively; the optimal carbon power market trading strategy is determined based on the obtained relationship curves.

[0013] Furthermore, the indicators that affect power market transactions include thermal power and green power contract volume and price, spot trading volume and price, user output, power consumption, and renewable energy consumption ratio indicator factors, which are specifically expressed as follows:

[0014] C Q =Q c ×p c +Q g ×p g +Q r ×p r ;

[0015] Q c =Q×(1-α)×a+Q βc ;

[0016] Q g =Q×α×a+Q βg ;

[0017] Q r =Q βc +Q βg ;

[0018] Among them, Q cis the medium- and long-term thermal power purchase, Q is the output, α is the renewable energy consumption ratio; a is the unit output power consumption, Q βc is the thermal power deviation quantity, Q βg is the green power deviation quantity, Q r is the spot purchase quantity, C Q is the electricity purchase cost, p c 、p g and p r They are the medium- and long-term electricity prices for thermal power, the medium- and long-term electricity prices for green power, and the spot electricity prices.

[0019] Furthermore, the indicators that affect carbon market transactions include carbon price fluctuations and quota trading volume indicators, which are specifically expressed as follows:

[0020] T c =T e -T g +T t +T r ;

[0021] C t =Q quota ×P c

[0022] Among them, T c is the total carbon emissions, T e is the carbon emissions of net purchased electricity, T g is the implicit emission of carbon sequestration products, T t is the emission from industrial production process, T r is the fuel combustion emission, C t is the carbon trading cost, Q quota is the quota transaction volume, P c The carbon price.

[0023] Furthermore, the construction of the carbon quota-related constraints is specifically as follows: the entire carbon compliance process is divided into a quota pre-allocation period, a quota issuance period and a compliance window period in chronological order, and carbon quota constraints are formulated separately; among them, for the quota pre-allocation period, the quota trading volume is predicted based on historical data; for the quota issuance period, the quota trading volume is determined based on the free quota ratio, the carbon emission intensity of the enterprise in the past three years, and the production plan reported by the user this year; for the compliance window period, the quota trading volume is determined based on the actual carbon emissions of the enterprise.

[0024] Furthermore, the construction of the risk assessment model for users participating in carbon electricity market transactions is specifically as follows: based on risk theory, a risk indicator system for users participating in carbon electricity market transactions is constructed; the weight of each risk indicator is determined by using the analytic hierarchy process; based on the risk indicators in the indicator system, combined with their weights, the risk assessment results of users participating in carbon electricity market transactions are obtained through weighted summation, thereby realizing the construction of a risk assessment model for users participating in carbon electricity market transactions.

[0025] Furthermore, the simulation analysis process is performed based on the PDCA theory.

[0026] Furthermore, the optimal carbon electricity market trading strategy is determined based on the obtained relationship curve, specifically: the first relationship curve is determined with the carbon electricity trading cost of the park to be optimized as the dependent variable, and the free quota issuance ratio and the carbon quota risk control scale as independent variables; the second relationship curve is determined with the carbon electricity trading risk level of the park to be optimized as the dependent variable, and the free quota issuance ratio and the carbon quota risk control scale as independent variables; the first relationship curve and the second relationship curve are summed to obtain a fusion relationship curve; based on the trend of the obtained fusion relationship curve, the carbon electricity market trading strategy of the park enterprises under the relatively optimal situation of carbon electricity trading cost and carbon electricity trading risk is determined.

[0027] According to a second aspect of an embodiment of the present invention, a carbon power market transaction strategy optimization system based on risk assessment is provided, comprising:

[0028] An indicator system construction unit, which is used to determine an indicator system affecting carbon-electricity market transactions based on the causal relationship of carbon-electricity market transactions; wherein the indicator system includes indicators affecting electricity market transactions and indicators affecting carbon market transactions;

[0029] A constraint formulation unit, which is used to construct carbon quota related constraints based on carbon market rules and historical carbon compliance data of enterprises in the park to be optimized; wherein the carbon quota related constraints are formulated by dividing the entire carbon compliance process into a quota pre-allocation period, a quota issuance period and a compliance window period;

[0030] A simulation model building unit, which is used to build a carbon power market transaction simulation model based on the determined indicator system and carbon quota-related constraints that affect carbon power market transactions, combined with the carbon power price transmission mechanism and a pre-built risk assessment model for users participating in carbon power market transactions, using a system dynamics method;

[0031] A scenario generation unit is used to construct different carbon power market transaction scenarios based on the historical production data of enterprises in the park to be optimized by adjusting the free quota issuance ratio and the carbon quota risk control scale;

[0032] A simulation analysis unit, which is used to perform simulation analysis based on different constructed carbon power market transaction scenarios through the constructed carbon power market transaction simulation model, to obtain the carbon power transaction cost and carbon power transaction risk level of the park to be optimized corresponding to different scenarios;

[0033] The trading strategy optimization unit is used to fit the relationship curves with the carbon power trading cost and carbon power trading risk level of the park to be optimized as dependent variables, and the free quota issuance ratio and the carbon quota risk control scale as independent variables; and determine the optimal carbon power market trading strategy based on the obtained relationship curves.

[0034] According to a third aspect of an embodiment of the present invention, there is provided an electronic device comprising a memory, a processor and a computer program stored and running on the memory, wherein when the processor executes the program, the method for optimizing a carbon power market trading strategy based on risk assessment is implemented.

[0035] According to a fourth aspect of an embodiment of the present invention, a non-transitory computer-readable storage medium is provided, on which a computer program is stored, and when the program is executed by a processor, the method for optimizing a carbon power market trading strategy based on risk assessment is implemented.

[0036] One or more of the above technical solutions have the following beneficial effects:

[0037] The present invention provides a method and system for optimizing carbon power market transaction strategies based on risk assessment. In the process of optimizing carbon power market transactions, the scheme introduces consideration of user performance risk while considering transaction costs. By constructing a risk assessment model for users participating in carbon power market transactions, the user's performance risk can be accurately assessed. By balancing transaction costs and performance risks, the carbon power market transaction optimization scheme can better meet the actual implementation situation.

[0038] When introducing carbon quota-related constraints, the solution described in the present invention can effectively adapt to the market transaction activity levels at different stages by considering different stages of the compliance process separately, and to a certain extent can avoid the problem of insufficient carbon quotas or excessive costs for users.

[0039] Advantages of additional aspects of the present invention will be given in part in the following description, and in part will become obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The accompanying drawings in the specification, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0041] Figure 1It is a framework diagram of a carbon electricity market transaction simulation model based on the PDCA model described in an embodiment of the present invention;

[0042] Figure 2 It is a schematic diagram of the power market transaction stock model described in an embodiment of the present invention;

[0043] Figure 3 A schematic diagram of a carbon market trading stock model described in an embodiment of the present invention;

[0044] Figure 4 A schematic diagram of the causal relationship of carbon power market risks described in an embodiment of the present invention;

[0045] Figure 5 A diagram of a carbon power market risk assessment indicator system described in an embodiment of the present invention;

[0046] Figure 6 This is a flow chart of the carbon power market transaction strategy optimization method based on risk assessment described in an embodiment of the present invention. DETAILED DESCRIPTION

[0047] It should be noted that the following detailed descriptions are exemplary and are intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present invention belongs.

[0048] It should be noted that the terms used herein are for describing specific embodiments only and are not intended to be limiting of exemplary embodiments according to the present invention.

[0049] In the absence of conflict, the embodiments of the present invention and the features of the embodiments may be combined with each other.

[0050] Terminology explanation:

[0051] Carbon-electricity market: The carbon-electricity market is a market system that integrates the carbon market and the electricity market. The carbon market mainly trades carbon emission rights, with the aim of controlling greenhouse gas emissions. By allocating certain carbon emission quotas to enterprises and allowing them to buy and sell these quotas in the market, emission reduction targets can be achieved. The electricity market is a place for electricity trading, including wholesale and retail of electricity and other forms of trading.

[0052] It should be noted that the “carbon” mentioned in the present invention specifically refers to the carbon in “carbon emission rights”.

[0053] In one or more embodiments, Figure 6 As shown, this embodiment provides a carbon power market transaction risk assessment method, which specifically includes the following processing procedures:

[0054] Step 1: Based on the causal relationship of carbon-electricity market transactions, determine the indicator system that affects carbon-electricity market transactions; wherein the indicator system includes indicators that affect electricity market transactions and indicators that affect carbon market transactions;

[0055] In the specific implementation, the indicators that affect electricity market transactions include contract volume and prices of thermal power and green power, spot trading volume and prices, user output, power consumption and renewable energy absorption ratio indicators; the indicators that affect carbon market transactions include carbon price fluctuations and quota trading volume indicators.

[0056] Specifically, the determination of the above indicator system includes the following processing:

[0057] Step 101: By sorting out the cause-effect relationship of electricity market transactions, considering factors such as user output, power consumption, renewable energy consumption ratio, thermal power and green power contract volume and electricity price, spot trading volume and electricity price, etc., construct an indicator representation that affects electricity market transactions.

[0058] Among them, the relevant formulas for thermal power purchase, green power purchase, spot power purchase and power purchase cost are as follows:

[0059] Q c =Q×(1-α)×a+Q βc

[0060] Q g =Q×α×a+Q βg

[0061] Q r =Q βc +Q βg

[0062] C Q =Q c ×p c +Q g ×p g +Q r ×p r

[0063] Among them, Q c is the medium- and long-term thermal power purchase, in 10,000 kWh; the output is Q, in 10,000 t; α is the renewable energy consumption ratio; a is the unit power consumption, in kwh / t; Q βc is the thermal power deviation quantity, in ten thousand kWh; Q βg is the green power deviation quantity, in ten thousand kWh; Q r is the spot purchase electricity, in 10,000 kWh; C Q is the electricity purchase cost, in ten thousand yuan; p c 、p g and p rThey are the medium- and long-term electricity prices for thermal power, the medium- and long-term electricity prices for green electricity, and the spot electricity price, in yuan / kWh.

[0064] Step 102: By sorting out the causal relationship of carbon market transactions, considering the impact of carbon price fluctuations and quota trading volume on transactions, determine the indicators that affect carbon market transactions. Among them, the total carbon emissions and carbon trading cost formulas are as follows:

[0065] T c =T e -T g +T t +T r

[0066] C t =Q quota ×P c

[0067] Where, T c is the total carbon emissions, in 10,000 tCO2; T e is the carbon emission of net purchased electricity, in 10,000 tCO2; T g is the implicit emission of carbon sequestration products, in 10,000 tCO2; T t is the emission from industrial production process, in 10,000 tCO2; T r is the emission of fuel combustion, in 10,000 tCO2; C t is the carbon trading cost, in ten thousand yuan; Q quota is the quota trading volume, in 10,000 tCO2; P c is the carbon price, in yuan / tCO2.

[0068] Step 2: Based on the carbon market rules and the historical carbon compliance data of enterprises in the park to be optimized, construct carbon quota related constraints; wherein the carbon quota related constraints are formulated by dividing the entire carbon compliance process into a quota pre-allocation period, a quota issuance period and a compliance window period;

[0069] In the specific implementation, the construction of the carbon quota-related constraints is specifically as follows: the entire carbon compliance process is divided into a quota pre-allocation period, a quota issuance period and a compliance window period in chronological order, and carbon quota constraints are formulated separately; among them, for the quota pre-allocation period, the quota trading volume is predicted based on historical data; for the quota issuance period, the quota trading volume is determined based on the free quota ratio, the carbon emission intensity of the enterprise in the past three years, and the production plan reported by the user this year; for the compliance window period, the quota trading volume is determined based on the actual carbon emissions of the enterprise.

[0070] Specifically, the construction of carbon quota related constraints includes the following processing procedures:

[0071] Based on the investigation and analysis of carbon market rules and the compliance process of park enterprises, the user's compliance period is divided according to the enterprise carbon trading behavior and the carbon quota issuance cycle, as shown in Table 1, and different carbon quota allocation rules are formulated.

[0072] Step 201: Pre-allocation of quotas (corresponding to the pre-allocation period of quotas). No quotas will be issued from January to April. Market entities will estimate the amount of quotas to be paid this year based on last year's quota settlement, carbon emission intensity over the years, and production plans, and conduct carbon trading based on actual conditions such as carbon prices. At the end of April, pre-allocated quotas will be issued based on 70% of the enterprise's quota allocation in the previous year and production and operation data.

[0073] Step 202: Quota issuance (corresponding to the quota issuance period). The ecological environment department shall complete the carbon emissions accounting work for the previous year by the end of July. Determine the free quota ratio according to the different carbon-containing energy ratios. Apply the updated carbon emissions and production and operation data to calculate the weighted average of carbon emission intensity and the free quota issuance ratio in the past three years, and calculate the quota for the year together with the production plan reported by the user for the year. Based on the updated quota issuance data, carbon quotas are issued according to the principle of more refund and less supplement.

[0074] Step 203: Carbon compliance (corresponding to the compliance window period). Complete the quota clearance work at the end of the year based on the carbon emission intensity and actual production and operation conditions. For enterprises that fail to complete the compliance, a fine of 3 to 5 times will be imposed depending on the severity of the breach of contract.

[0075] Table 1 Division of performance period

[0076]

[0077] Step 3: Based on the determined indicator system and carbon quota-related constraints that affect carbon power market transactions, combined with the carbon power price transmission mechanism and the pre-built risk assessment model for users participating in carbon power market transactions, a system dynamics method is used to construct a carbon power market transaction simulation model;

[0078] In the specific implementation, the construction of the risk assessment model for users participating in carbon electricity market transactions is specifically as follows: based on risk theory, a risk indicator system for users participating in carbon electricity market transactions is constructed; the weight of each risk indicator is determined by using the hierarchical analysis method; based on the risk indicators in the indicator system, combined with their weights, the risk assessment results of users participating in carbon electricity market transactions are obtained through weighted summation, thereby realizing the construction of a risk assessment model for users participating in carbon electricity market transactions.

[0079] Specifically, the construction of the risk assessment model includes the following processing steps:

[0080] Taking into account the various risk factors in the process of park users participating in market transactions, a risk indicator system for users participating in carbon power market transactions is established based on risk theory, and the weight of each risk indicator is confirmed using the hierarchical analysis method to construct a risk assessment model for users participating in carbon power market transactions. Specifically, it includes:

[0081] (1) In light of the current market situation, based on risk theory, the risks that users need to face in carbon electricity trading are divided into carbon market risks and electricity market risks. The transaction risks in the electricity market and carbon market are composed of credit risk, liquidity risk and policy risk.

[0082] (2) The analytic hierarchy process is used to confirm the weight of each risk indicator. In order to compare the impact of the lower-level indicators on the upper-level indicators, a judgment matrix is ​​constructed and assigned values ​​using the 1-9 scaling method. Table 2 shows the scaling method of the judgment matrix.

[0083] Table 2 Scaling method of judgment matrix

[0084]

[0085] (3) The consistency test of each risk indicator is carried out according to the judgment matrix, as shown in Tables 3 to 5.

[0086]

[0087] Table 3 Judgment matrix of policy risk indicators

[0088]

[0089] According to Table 3, the maximum characteristic root can be obtained as λ max =2, consistency index RI=0,CR=0<0.1. Passed the consistency test.

[0090] Table 4. Judgment matrix of carbon market risk indicators

[0091]

[0092] According to Table 4, the maximum characteristic root can be obtained as λ max =3.039, consistency index RI=0.525, Pass the consistency check.

[0093] Table 5 Judgment matrix of various indicators of power market risk

[0094]

[0095] According to Table 5, the maximum characteristic root can be obtained as λ max =2, consistency index RI=0,CR=0<0.1. Passed the consistency test.

[0096] Table 6 Judgment matrix of each indicator of total risk level

[0097]

[0098]

[0099] According to Table 6, the maximum characteristic root can be obtained as λ max =2, consistency index RI=0,CR=0<0.1. Passed the consistency test.

[0100] (4) Calculate the weights based on the consistency test results. Table 7 shows the weights of each risk indicator.

[0101]

[0102] Table 7 Weight values ​​of various risk factors

[0103]

[0104] Specifically, based on the indicators in the constructed risk indicator system for users participating in carbon power market transactions, combined with the above indicator weight determination method, the risk of users participating in carbon power market transactions is obtained through weighted summation. Specifically, Figure 4 The indicators associated with different risks are shown.

[0105] In a specific implementation, the determination of the carbon electricity price transmission mechanism specifically includes the following processing procedures:

[0106] Determine the key factors of coupling between carbon and electricity markets. Consider the key direct variables such as user electricity consumption, electricity purchase price, carbon purchase price, and the role of auxiliary variables such as social economy, technological progress and policy in building a carbon-electricity market coupling simulation model.

[0107] Construct a transmission mechanism between electricity prices and carbon prices in the two markets. Analyze the main transmission paths between electricity prices and carbon prices, including the impact of carbon prices on electricity production costs, the impact of production costs on electricity market prices, and the feedback mechanism between the two.

[0108] Step 4: Based on the historical production data of enterprises in the park to be optimized, different carbon power market trading scenarios are constructed by adjusting the free quota issuance ratio and the carbon quota risk control scale;

[0109] In the specific implementation, the construction of the carbon power market trading scenario is specifically based on the historical production data of enterprises in the park to be optimized, and is determined by adjusting the free quota issuance ratio and the carbon quota risk control scale, wherein the adjustment of the free quota issuance ratio includes gradually increasing the free quota issuance ratio or gradually reducing the free issuance ratio. As shown in Table 8, some construction methods of carbon power market trading scenarios are shown.

[0110] Step 5: Based on the different carbon power market transaction scenarios constructed, a simulation analysis is performed through the constructed carbon power market transaction simulation model to obtain the carbon power transaction cost and carbon power transaction risk level of the park to be optimized corresponding to different scenarios;

[0111] Specifically, the simulation analysis includes the following processing steps:

[0112] (1) Based on the trading behavior of park users, the key factors affecting the power trading and carbon trading of park users and the risk factors faced by carbon-electricity trading are screened out, the system time boundary is confirmed to be one compliance cycle, the time step is one month, and the modeling boundary of the simulation model is set.

[0113] (2) Based on the constructed carbon electricity trading system simulation model, the user's market trading situation is simulated.

[0114] (3) Assess the risks of users participating in market transactions based on free quota ratios, risk preferences, etc.

[0115] Table 8 Baseline scenario and optimized scenario settings

[0116]

[0117] Step 6: Take the carbon power transaction cost and carbon power transaction risk level of the park to be optimized as dependent variables, and the free quota issuance ratio and carbon quota risk control scale as independent variables, and fit the relationship curves respectively; determine the optimal carbon power market trading strategy based on the obtained relationship curves.

[0118] In the specific implementation, the optimal carbon electricity market trading strategy is determined based on the obtained relationship curve, specifically: taking the carbon electricity trading cost of the park to be optimized as the dependent variable, and the free quota issuance ratio and the carbon quota risk control scale as independent variables, to determine the first relationship curve; taking the carbon electricity trading risk level of the park to be optimized as the dependent variable, and the free quota issuance ratio and the carbon quota risk control scale as independent variables, to determine the second relationship curve; summing the first relationship curve and the second relationship curve to obtain a fusion relationship curve; based on the trend of the obtained fusion relationship curve, determine the carbon electricity market trading strategy of the park enterprises under the relatively optimal conditions of carbon electricity trading cost and carbon electricity trading risk.

[0119] In a specific implementation, the simulation analysis process of this embodiment is performed based on the PDCA (Plan Do Check Action) theory, wherein, as shown in Table 9, the PDCA specifically includes:

[0120] (1) Plan. The main research objective is to optimize the carbon-electricity market transaction strategy and determine the initial conditions for the carbon-electricity market coupling.

[0121] (2) DO execution: Use system dynamics method to implement market simulation modeling.

[0122] (3) Check: Based on the case simulation results, summarize the model execution process and find out the problems.

[0123] (4) Act ion processing improvement: Set up multivariate scenarios, adjust model parameters under multivariate scenarios and propose improvement measures.

[0124] Table 9 PDCA operation steps and methods

[0125]

[0126] In one or more embodiments, corresponding to the above method, this embodiment provides a carbon power market transaction strategy optimization system based on risk assessment, including:

[0127] An indicator system construction unit, which is used to determine an indicator system affecting carbon-electricity market transactions based on the causal relationship of carbon-electricity market transactions; wherein the indicator system includes indicators affecting electricity market transactions and indicators affecting carbon market transactions;

[0128] A constraint formulation unit, which is used to construct carbon quota related constraints based on carbon market rules and historical carbon compliance data of enterprises in the park to be optimized; wherein the carbon quota related constraints are formulated by dividing the entire carbon compliance process into a quota pre-allocation period, a quota issuance period and a compliance window period;

[0129] A simulation model building unit, which is used to build a carbon power market transaction simulation model based on the determined indicator system and carbon quota-related constraints that affect carbon power market transactions, combined with the carbon power price transmission mechanism and a pre-built risk assessment model for users participating in carbon power market transactions, using a system dynamics method;

[0130] A scenario generation unit is used to construct different carbon power market transaction scenarios based on the historical production data of enterprises in the park to be optimized by adjusting the free quota issuance ratio and the carbon quota risk control scale;

[0131] A simulation analysis unit, which is used to perform simulation analysis based on different constructed carbon power market transaction scenarios through the constructed carbon power market transaction simulation model, to obtain the carbon power transaction cost and carbon power transaction risk level of the park to be optimized corresponding to different scenarios;

[0132] The trading strategy optimization unit is used to fit the relationship curves with the carbon power trading cost and carbon power trading risk level of the park to be optimized as dependent variables, and the free quota issuance ratio and the carbon quota risk control scale as independent variables; and determine the optimal carbon power market trading strategy based on the obtained relationship curves.

[0133] It can be understood that the system described in this embodiment corresponds to the method embodiment, and its technical details have been described in detail in the above embodiments, so they will not be repeated here.

[0134] Also available:

[0135] An electronic device includes a memory and a processor, and computer instructions stored in the memory and executed on the processor, wherein when the computer instructions are executed by the processor, the method described in Embodiment 1 is performed. For the sake of brevity, no further description is given here.

[0136] It should be understood that in this embodiment, the processor may be a central processing unit CPU, and the processor may also be other general-purpose processors, digital signal processors DSP, application-specific integrated circuits ASIC, off-the-shelf programmable gate arrays FPGA or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0137] The memory may include a read-only memory and a random access memory, and provide instructions and data to the processor. A portion of the memory may also include a non-volatile random access memory. For example, the memory may also store information about the device type.

[0138] A computer-readable storage medium is used to store computer instructions. When the computer instructions are executed by a processor, the method described in embodiment 1 is completed.

[0139] The method in the first embodiment can be directly embodied as a hardware processor, or a combination of hardware and software modules in the processor. The software module can be located in a mature storage medium in the field such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory, and the processor reads the information in the memory and completes the steps of the above method in combination with its hardware. To avoid repetition, it will not be described in detail here.

[0140] A computer program product includes a computer program, wherein the computer program implements the method described in Embodiment 1 when executed by a processor.

[0141] Those skilled in the art will appreciate that the units, i.e., algorithm steps, of the various examples described in the present embodiment can be implemented in electronic hardware or in a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0142] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A carbon power market transaction strategy optimization method based on risk assessment, characterized in that: include: Based on the causal relationship of carbon-electricity market transactions, determine the indicator system that affects carbon-electricity market transactions; wherein the indicator system includes indicators that affect electricity market transactions and indicators that affect carbon market transactions; Based on the carbon market rules and the historical carbon compliance data of enterprises in the park to be optimized, carbon quota related constraints are constructed; wherein the carbon quota related constraints are formulated by dividing the entire carbon compliance process into a quota pre-allocation period, a quota issuance period and a compliance window period; Based on the determined indicator system and carbon quota-related constraints that affect carbon power market transactions, combined with the carbon power price transmission mechanism and the pre-built risk assessment model for users participating in carbon power market transactions, a carbon power market transaction simulation model is constructed using the system dynamics method. Based on the historical production data of enterprises in the park to be optimized, different carbon power market trading scenarios are constructed by adjusting the free quota issuance ratio and the carbon quota risk control scale; Based on the different carbon power market transaction scenarios, the carbon power market transaction simulation model is constructed to conduct simulation analysis to obtain the carbon power transaction cost and carbon power transaction risk level of the park to be optimized corresponding to different scenarios; The carbon power transaction cost and carbon power transaction risk level of the park to be optimized are taken as dependent variables, and the free quota issuance ratio and carbon quota risk control scale are taken as independent variables, and the relationship curves are fitted respectively; the optimal carbon power market trading strategy is determined based on the obtained relationship curves.

2. A carbon power market transaction strategy optimization method based on risk assessment as claimed in claim 1, characterized in that: The indicators that affect power market transactions include thermal power and green power contract volume and price, spot trading volume and price, user output, power consumption and renewable energy consumption ratio indicator factors, which are specifically expressed as follows: C Q =Q c ×p c +Q g ×p g +Q r ×p r ; Q c =Q×(1-α)×a+Q βc ; Q g =Q×α×a+Q βg ; Q r =Q βc +Q βg ; Among them, Q c is the medium- and long-term thermal power purchase, Q is the output, α is the renewable energy consumption ratio; a is the unit output power consumption, Q βc is the thermal power deviation quantity, Q βg is the green power deviation quantity, Q r is the spot purchase quantity, C Q is the electricity purchase cost, p c 、p g and p r They are the medium- and long-term electricity prices for thermal power, the medium- and long-term electricity prices for green power, and the spot electricity prices.

3. A carbon power market transaction strategy optimization method based on risk assessment as claimed in claim 1, characterized in that: The indicators that affect carbon market transactions include carbon price fluctuations and quota trading volume indicators, which are specifically expressed as follows: T c =T e -T g +T t +T r ; C t =Q quota ×P c Among them, T c is the total carbon emissions, T e is the carbon emissions of net purchased electricity, T g is the implicit emission of carbon sequestration products, T t is the emission from industrial production process, T r is the fuel combustion emission, C t is the carbon trading cost, Q quota is the quota transaction volume, P c The carbon price.

4. A carbon power market transaction strategy optimization method based on risk assessment as claimed in claim 1, characterized in that: The construction of the carbon quota related constraints is specifically as follows: the entire carbon compliance process is divided into a quota pre-allocation period, a quota issuance period and a compliance window period in chronological order, and carbon quota constraints are formulated respectively; among which, for the quota pre-allocation period, the quota trading volume is predicted based on historical data; for the quota issuance period, the quota trading volume is determined based on the free quota ratio, the carbon emission intensity of the enterprise in the past three years, and the production plan reported by the user this year; for the compliance window period, the quota trading volume is determined based on the actual carbon emissions of the enterprise.

5. The carbon power market transaction strategy optimization method based on risk assessment according to claim 1, characterized in that: The construction of the risk assessment model for users participating in carbon power market transactions is specifically as follows: based on risk theory, a risk indicator system for users participating in carbon power market transactions is constructed; and the weight of each risk indicator is determined by using the hierarchical analysis method; Based on the risk indicators in the indicator system and their weights, the risk assessment results of users participating in carbon power market transactions are obtained through weighted summation, thereby realizing the construction of a risk assessment model for users participating in carbon power market transactions.

6. A carbon power market transaction strategy optimization method based on risk assessment as claimed in claim 1, characterized in that: The simulation analysis process is performed based on the PDCA theory.

7. The carbon power market transaction strategy optimization method based on risk assessment according to claim 1, characterized in that: The optimal carbon-electricity market trading strategy is determined based on the obtained relationship curve, specifically: taking the carbon-electricity trading cost of the park to be optimized as the dependent variable, the free quota issuance ratio and the carbon quota risk control scale as the independent variables, to determine the first relationship curve; taking the carbon-electricity trading risk level of the park to be optimized as the dependent variable, the free quota issuance ratio and the carbon quota risk control scale as the independent variables, to determine the second relationship curve; summing the first relationship curve and the second relationship curve to obtain a fusion relationship curve; Based on the trend of the obtained fusion relationship curve, the carbon power market trading strategy of the park enterprises under the relatively optimal conditions of carbon power trading cost and carbon power trading risk is determined.

8. A carbon power market trading strategy optimization system based on risk assessment, characterized in that: include: An indicator system construction unit, which is used to determine an indicator system affecting carbon-electricity market transactions based on the causal relationship of carbon-electricity market transactions; wherein the indicator system includes indicators affecting electricity market transactions and indicators affecting carbon market transactions; A constraint formulation unit, which is used to construct carbon quota related constraints based on carbon market rules and historical carbon compliance data of enterprises in the park to be optimized; wherein the carbon quota related constraints are formulated by dividing the entire carbon compliance process into a quota pre-allocation period, a quota issuance period and a compliance window period; A simulation model building unit, which is used to build a carbon power market transaction simulation model based on the determined indicator system and carbon quota-related constraints that affect carbon power market transactions, combined with the carbon power price transmission mechanism and a pre-built risk assessment model for users participating in carbon power market transactions, using a system dynamics method; A scenario generation unit is used to construct different carbon power market transaction scenarios based on the historical production data of enterprises in the park to be optimized by adjusting the free quota issuance ratio and the carbon quota risk control scale; A simulation analysis unit, which is used to perform simulation analysis based on different constructed carbon power market transaction scenarios through the constructed carbon power market transaction simulation model, to obtain the carbon power transaction cost and carbon power transaction risk level of the park to be optimized corresponding to different scenarios; The trading strategy optimization unit is used to fit the relationship curves with the carbon power trading cost and carbon power trading risk level of the park to be optimized as dependent variables, and the free quota issuance ratio and the carbon quota risk control scale as independent variables; and determine the optimal carbon power market trading strategy based on the obtained relationship curves.

9. An electronic device comprising a memory, a processor and a computer program stored and running on the memory, characterized in that: When the processor executes the program, it implements a carbon power market trading strategy optimization method based on risk assessment as described in any one of claims 1-7.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, a carbon power market trading strategy optimization method based on risk assessment is implemented as described in any one of claims 1 to 7.

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