Carbon market and green certificate market transaction scene evolution simulation analysis method and system

Abstract

The invention relates to the technical field of electricity market transaction, and discloses a carbon market and green certificate market transaction scene evolution simulation analysis method and system, and the method comprises the steps: obtaining economic variables of a plurality of transaction scenes; on the basis of the CGE model, constructing a carbon transaction model according to the total carbon quota, the carbon emission reduction rate, the reference carbon emission, the unit price of the carbon quota, the carbon quota amount of each subject and the free quota amount of each subject, and constructing a green certificate transaction model according to the green certificate transaction price and the renewable energy quota proportion; iterating the carbon transaction model and the green certificate transaction model until a residual value is smaller than a preset threshold value, thereby obtaining an equilibrium solution of the economic variable; according to the equilibrium solution and the variable range of the economic variables corresponding to different transaction scenes, different carbon emission reduction targets are adopted, and the influence of the carbon emission reduction targets on macroeconomy, the carbon emission reduction effect and renewable energy source development under different transaction scenes is evaluated.

Description

Technical Field

[0001] The present invention relates to the field of electricity market transaction technology, and in particular to a method and system for simulating and analyzing the evolution of transaction scenarios in carbon markets and green certificate markets. Background Art

[0002] In the carbon market, current technologies focus on analyzing the allocation of carbon emission quotas and trading supervision and other basic operations; in the green certificate market, trading platforms and related accounting rules have been gradually established, which can carry out green electricity consumption accounting based on green certificate trading, corporate self-generation and self-use of renewable energy electricity, etc., to help companies clarify their own situation and assert their rights. At present, the simulation analysis of the evolution of trading scenarios in the two major markets based on the CGE model mainly focuses on evaluating the economic impact, carbon emission reduction effect and renewable energy development under different policy scenarios.

[0003] Existing simulation methods based on CGE models are often limited to static analysis, which makes it difficult to capture the immediate impact of market dynamics and policy adjustments. In addition, the model lacks an assessment of the synergy between the carbon market and the green certificate market, making it difficult to fully consider the interaction and impact between the two markets, resulting in inaccurate results. Summary of the invention

[0004] The present invention provides a simulation analysis method for the evolution of trading scenarios of the carbon market and the green certificate market, so as to solve the technical problems that the existing CGE model lacks an assessment of the synergy between the carbon market and the green certificate market, and it is difficult to fully consider the interaction and impact between the two markets, resulting in inaccurate results.

[0005] In order to solve the above technical problems, an embodiment of the present invention provides a simulation analysis of the evolution of carbon market and green certificate market trading scenarios, and the method includes:

[0006] Obtain economic variables for multiple trading scenarios, including the total carbon quota, carbon emission reduction rate, benchmark carbon emissions, unit price of carbon quota, carbon quota of each entity, free quota of each entity, green certificate transaction price, and renewable energy quota ratio;

[0007] On the basis of the CGE model, a carbon trading model is constructed according to the total carbon quota, the carbon emission reduction rate, the benchmark carbon emissions, the unit price of the carbon quota, the carbon quota of each entity, and the free quota of each entity; a green certificate trading model is constructed according to the green certificate trading price and the renewable energy quota ratio;

[0008] Iterate the carbon trading model and the green certificate trading model, repeatedly adjust the economic variables, calculate the residual values ​​of the carbon trading model and the green certificate trading model, and solve the Jacobian matrix to update the economic variables until the residual value is less than a preset threshold, thereby obtaining an equilibrium solution of the economic variables;

[0009] According to the variable range of the economic variables corresponding to the equilibrium solution and different trading scenarios, different carbon emission reduction targets are adopted to evaluate the impact of the carbon emission reduction targets under different trading scenarios on the macro-economy, carbon emission reduction effects and renewable energy development.

[0010] Furthermore, when the residual value of the carbon trading model is less than a preset threshold, it means that the carbon trading model has reached equilibrium. The mathematical expression of the carbon trading model in equilibrium is:

[0011] TCO2 t =(1-tcer i )CO2ref i

[0012]

[0013] C i,t =P i,t ·(CR i,t -FP i,t )

[0014] Where, TCO2 t is the total carbon quota of the subject in period t, which is equal to the total supply of carbon quotas. CO2ref is the benchmark carbon emissions of the subject in period t. tcer i is the carbon emission reduction rate of the subject in period t, is the carbon emissions of each entity in period t, COAL i,t 、OIL i,t 、GAS i,t is the energy consumption of coal, oil and natural gas in period t, γ coal , γ oil , γ gas is the carbon emission coefficient of coal, oil and natural gas, C i,t is the carbon trading cost of commodity i in period t; P i,t is the unit price of carbon quota of each entity in period t; CR i,t is the carbon quota of each entity in period t; FP i,t is the free quota of each entity in period t.

[0015] Furthermore, when the residual value of the green certificate trading model is less than a preset threshold, it means that the green certificate trading model has reached equilibrium. The mathematical expression of the green certificate trading model in equilibrium is:

[0016]

[0017] PLC i-ely =Pfine*QRPS

[0018] In the formula, i-nel represents the non-power industry that needs to purchase green certificates, i-ely represents the power industry, Quota represents the proportion of renewable energy power generation to thermal power generation, QSN, QWD, QBS, and QTP represent the production subsidy power synthesis, the commodity needs to be invested in the subsidized photovoltaic power generation, biomass power generation, wind power generation, and thermal power generation, QRPS represents the default power generation when the power generation enterprise fails to complete the renewable energy quota, rps is the exogenously given renewable energy quota ratio, and PLC i-nel represents the cost of purchasing green certificates for the i-nel non-power industry, ptsn, ptbs, ptwd represent the prices of green certificates for photovoltaic power generation, biomass power generation, and wind power generation, respectively, TGCsn i-nel , TGCbs i-nel 、TGCwd i-nel Represents the number of green certificates purchased by the first-tier industry for photovoltaic power generation, biomass power generation and wind power generation, PLC i-ely Represents the cost of purchasing green certificates for the i-th power industry, and Pfine represents the penalty price when the power generation company fails to meet the renewable energy quota.

[0019] Furthermore, when the carbon trading model and the green certificate trading model reach equilibrium, the carbon trading costs and green certificate trading costs of each entity are embedded into the CGE model, and its mathematical expression is:

[0020] X i,t ·PX i,t =OC i,t +PLC i,t +PLC i-nel +PLC i-ely

[0021] PLC i,t =C i,t +P f,t (EM i,t -CR i,t )

[0022] In the formula, X i,t represents the domestic output of commodity i in period t, PX i,t represents the domestic output price of commodity i in period t, OC i,t represents the original production cost of each entity in period t, PLC i,t represents the additional cost that the enterprise pays for carbon emission rights trading in period t, including transaction costs and penalties for excessive emissions. i-nel Represents the cost of purchasing green certificates for the i-nel non-power industry, PLC i-ely represents the cost of purchasing green certificates for the i-th power industry, C i,tis the carbon trading cost of commodity i in period t, P f,t represents the penalty price for excess emissions of each entity in period t, EM i,t represents the carbon emissions of each entity in period t, CR i,t Represents the carbon quota of each entity in period t.

[0023] Furthermore, under market equilibrium conditions, each production activity follows the principle of optimal use of inputs to minimize the cost of existing production technology;

[0024] A multi-level nested structure is used to reflect the complex substitution relationship between multiple inputs. The specific steps include:

[0025] The mathematical expression of total output using the Leontief production function is:

[0026]

[0027] Where, INT i,j represents the intermediate input of commodity i to commodity j; VAE j Represents commodity j energy-factor composite bundle; PSB j Represents commodity j power synthesis bundle; Z j represents the total output of domestic commodity j; represents the intermediate input coefficient; A parameter representing the scale and quantity of inputs required to produce one unit of energy-factor composite bundle goods; A parameter representing the scale quantity of inputs required to produce one unit of the electricity synthesis bundle commodity;

[0028] The mathematical expression of using CES function to represent the second to fourth layer resource input is:

[0029]

[0030] In the formula, QX m represents the total output of each layer of production activity set, represents the scale parameter in the CES production function, K m and L m Represents different types of input, represents the input share coefficient of the CES production function, m represents the set of production activities, Represents the correlation coefficient of substitution elasticity between capital-energy-labor composite input and non-energy intermediate input.

[0031] Furthermore, in the CGE model, the Cobb-Douglas production function is used to explain the utility maximization problem of economic actors. Economic actors achieve equilibrium configuration through market clearing. The mathematical expressions of the behaviors of different economic actors are:

[0032]

[0033] In the formula, PQ i represents the market price of commodity i; QH i Represents the demand of economic actors for commodity i; ω i represents the survival consumption level of product i; i represents the marginal propensity to consume commodity i; YH represents the total income of economic actors.

[0034] Furthermore, the CET function and CES function are used to explain the incomplete substitution relationship between domestic goods and export goods, and between domestic goods and imported goods. For the import and export of domestic goods, the CES / CET utility function is used to determine its domestic demand, and its mathematical expression is:

[0035]

[0036] In the formula, QK i represents the composite supply of the set of goods that are both exported and produced domestically; QQ j represents the composite supply of the set of goods that are both imported and domestically produced; represents the scale parameter, share parameter and utility function index in the CET utility function; Represents the scale parameter, share parameter and utility function index in the CES utility function; QE i The number of export commodities QD that represents the commodity set that is both exported and produced domestically i represents the quantity of domestic goods in the set of goods that are both exported and produced domestically; QM j The quantity of imported goods in the set of goods that are both imported and produced domestically; QD j Represents the quantity of domestic goods in the set of goods that are both imported and domestically produced.

[0037] Furthermore, the CGE model uses a recursive dynamic CGE model.

[0038] The embodiment of the present invention also provides a carbon market and green certificate market transaction scenario evolution simulation analysis system, the system comprising:

[0039] An acquisition module is used to acquire economic variables of multiple transaction scenarios, including the total carbon quota, carbon emission reduction rate, benchmark carbon emissions, unit price of carbon quota, carbon quota of each entity, free quota of each entity, green certificate transaction price, and renewable energy quota ratio;

[0040] A model building module is used to build a carbon trading model based on the CGE model according to the total carbon quota, the carbon emission reduction rate, the benchmark carbon emissions, the unit price of the carbon quota, the carbon quota of each entity, and the free quota of each entity, and to build a green certificate trading model according to the green certificate trading price and the renewable energy quota ratio;

[0041] A model iteration module, used to iterate the carbon trading model and the green certificate trading model, calculate the residual values ​​of the carbon trading model and the green certificate trading model and solve the Jacobian matrix to update the economic variables by repeatedly adjusting the economic variables until the residual value is less than a preset threshold, thereby obtaining an equilibrium solution of the economic variables;

[0042] An evaluation module is used to adopt different carbon emission reduction targets according to the equilibrium solution and the variable range of the economic variables corresponding to different trading scenarios, and to evaluate the impact of the carbon emission reduction targets under different trading scenarios on the macro-economy, carbon emission reduction effects and renewable energy development.

[0043] Beneficial effects of the embodiments of the present invention:

[0044] The method of the present invention obtains the equilibrium solution of the equation group by constructing a carbon trading model and a green certificate trading model, adopts carbon emission reduction measures and policies according to the equilibrium solution to meet the carbon emission reduction target, evaluates the cost-effectiveness of different carbon emission reduction measures and policies and the risks of different carbon emission reduction measures and policies, and evaluates the costs and benefits required to achieve specific emission reduction targets, which helps policymakers to select the most cost-effective carbon emission reduction measures and policies, and formulate a reasonable policy combination; evaluates the impact of policies on economic growth, employment and social equity, and helps policymakers to formulate emission reduction policies with the lowest risk, and formulate corresponding supporting measures. Different carbon emission reduction measures and policies are adopted according to different trading scenarios, so that the equilibrium solutions of the carbon trading model and the green certificate trading model equation group can coordinately evaluate the carbon market and the green certificate market. The present invention can provide policymakers with a scientific decision-making basis, such as evaluating the feasibility, effectiveness and sustainability of different emission reduction policies, which helps policymakers to formulate reasonable emission reduction policies and promote the green transformation of the economy. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 It is a schematic flow chart of an embodiment of the method of the present invention;

[0046] Figure 2 It is a structural schematic diagram of the system of the present invention; DETAILED DESCRIPTION

[0047] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0048] Embodiment 1

[0049] Please refer to Figure 1 , a method for simulating and analyzing the evolution of carbon market and green certificate market transaction scenarios provided by an embodiment of the present invention, the method comprising:

[0050] S10. Obtain economic variables of multiple trading scenarios, including total carbon quota, carbon emission reduction rate, benchmark carbon emission, unit price of carbon quota, carbon quota of each entity, free quota of each entity, green certificate transaction price, and renewable energy quota ratio;

[0051] S20. On the basis of the CGE model, a carbon trading model is constructed based on the total carbon quota, carbon emission reduction rate, benchmark carbon emissions, unit price of carbon quota, carbon quota of each entity, and free quota of each entity. A green certificate trading model is constructed based on the green certificate trading price and renewable energy quota ratio.

[0052] S30, iterating the carbon trading model and the green certificate trading model, repeatedly adjusting the economic variables, calculating the residual values ​​of the carbon trading model and the green certificate trading model and solving the Jacobian matrix to update the economic variables, until the residual value is less than a preset threshold, thereby obtaining an equilibrium solution of the economic variables;

[0053] S40. According to the equilibrium solution and the variable range of economic variables corresponding to different trading scenarios, different carbon emission reduction targets are adopted to evaluate the impact of carbon emission reduction targets under different trading scenarios on the macro-economy, carbon emission reduction effects and renewable energy development.

[0054] Specifically, the carbon market, or greenhouse gas emission rights trading market, is a market mechanism that promotes greenhouse gas emission reduction and promotes green economic transformation by setting a cap on total emissions by the government, allocating emission rights to enterprises, and allowing enterprises to freely buy and sell emission rights in the market.

[0055] Specifically, the green certificate market refers to a market established by government departments to promote the development of environmental protection industries and reduce carbon emissions. It encourages companies to reduce pollution and improve energy efficiency by issuing green certificates (green certificates). Green certificates are electronic certificates issued for green electricity issued by renewable energy power generation projects and can be freely bought and sold on the market.

[0056] Specifically, carbon emission rights refer to the rights allocated by governments or international organizations to enterprises, countries and other entities, allowing them to emit a certain amount of greenhouse gases within a specific period of time. This right has commodity attributes and can be traded in the carbon market. It is the core and foundation of the operation of the carbon market.

[0057] Specifically, the Green Certificate is an electronic certificate with a unique identification code issued by the state to power generation companies for each megawatt-hour of non-hydro renewable energy grid-connected electricity. It is a confirmation and attribute certificate of non-hydro renewable energy power generation and a voucher for consuming green stores. Each MWh = 1 Green Certificate.

[0058] Specifically, the CGE model is a computational general equilibrium model (Computable General Equilibrium), which is an economic mathematical model based on general equilibrium theory, which simulates the relationship between various parts of the economic system by constructing a nonlinear equation group to provide support for policy evaluation and economic analysis. The CGE model of this embodiment uses a recursive dynamic CGE model. In the recursive dynamic CGE model, each behavioral subject does not consider the expectation of future prices, and makes decisions mainly based on specific exogenous assumptions. Compared with the inter-period dynamic CGE model, the recursive dynamic CGE model has relatively low data requirements and is easier to calibrate and calculate.

[0059] Three different emission reduction scenarios are set, including baseline carbon emission reduction, strong carbon emission reduction, and strong-strong carbon emission reduction, and corresponding policy objectives and expected results are set under each scenario.

[0060] When setting the trading evolution scenario, three different emission reduction scenarios can be set in this embodiment, including baseline carbon emission reduction, strong carbon emission reduction, and strong strong carbon emission reduction, and corresponding trading evolution goals and expected effects are set in each scenario. Constraints are set according to the trading evolution goals. The constraints are the variable ranges of economic variables, including setting parameters such as the carbon emission quota cap, carbon trading price range, green certificate trading price range, and renewable energy quota ratio corresponding to different trading evolution goals. Different carbon emission quota caps, carbon trading price ranges, green certificate trading price ranges, and renewable energy quota ratios are set to reflect the policy strength and effect under different trading evolution scenarios.

[0061] After setting the transaction evolution scenario, obtain these economic variables and input them into the CGE model, including the total carbon quota, carbon emission reduction rate, benchmark carbon emissions, unit price of carbon quota, carbon quota of each entity, free quota of each entity, green certificate transaction price, renewable energy quota ratio, and run the model to simulate the transaction evolution. The simulation process includes the following steps:

[0062] The relevant parameters and state variables of the model are set according to the trading evolution scenario, including carbon emission quota, carbon trading price, green certificate trading price, renewable energy quota ratio, etc.

[0063] By setting the initial value, using the iterative algorithm to iterate the carbon trading model and the green certificate trading model, repeatedly adjusting the economic variables under the set constraints, calculating the residuals of the carbon trading model and the green certificate trading model equations and solving the Jacobian matrix to update the economic variables, until the residuals are less than the preset threshold and convergence is achieved, thus obtaining the equilibrium solution of each economic variable in the CGE model equations. Specifically, the official network data can be used as the basic data for iteration, and a standard SAM table matching the dynamic CGE model of the Chinese energy market can be compiled, and the RAS method can be used for leveling.

[0064] The obtained equilibrium solutions are analyzed and compared to evaluate the economic impact, carbon emission reduction effect and renewable energy development under different transaction evolution scenarios.

[0065] Specifically, by comparing the differences between the equilibrium solution and the current economic variables, we can find the abnormal items, take carbon reduction measures based on the abnormal items to make them meet the carbon reduction targets, that is, meet the expected effects. Based on the carbon reduction measures, we can estimate the carbon reduction effects, and based on the carbon reduction targets, we can evaluate the economic impact and the development of renewable energy, provide theoretical support, and promote the transformation of the industry and energy structure. We can simulate and analyze the synergy of the two markets under different trading scenarios and their impact on the macroeconomy and industry output, and achieve accurate simulation and evaluation of the policy effects of the two markets.

[0066] In a specific embodiment, the present invention simulates different carbon emission reduction policy scenarios to predict the growth trend of China's GDP from 2025 to 2030. Under the baseline carbon emission reduction scenario, GDP grows from 139.39 trillion yuan in 2025 to 174.99 trillion yuan in 2030, showing the balance between economic growth and carbon emission reduction policies, which helps policymakers evaluate the impact of different policies on economic growth and set reasonable carbon emission reduction targets.

[0067] The present invention predicts the changes in carbon prices under different emission reduction policies, which can provide a basis for policy makers to adjust and optimize policies. In particular, by implementing different policies to influence market mechanisms, it helps to maximize cost-effectiveness and promote power market structure adjustment and technological innovation.

[0068] The method of the present invention obtains the equilibrium solution of the equation group by constructing a carbon trading model and a green certificate trading model, adopts carbon emission reduction measures and policies according to the equilibrium solution to meet the carbon emission reduction target, evaluates the cost-effectiveness of different carbon emission reduction measures and policies and the risks of different carbon emission reduction measures and policies, and evaluates the costs and benefits required to achieve specific emission reduction targets, which helps policymakers to select the most cost-effective carbon emission reduction measures and policies, and formulate a reasonable policy combination; evaluates the impact of policies on economic growth, employment and social equity, and helps policymakers to formulate emission reduction policies with the lowest risk, and formulate corresponding supporting measures. Different carbon emission reduction measures and policies are adopted according to different trading scenarios, so that the equilibrium solutions of the carbon trading model and the green certificate trading model equation group can coordinately evaluate the carbon market and the green certificate market. The present invention can provide policymakers with a scientific decision-making basis, such as evaluating the feasibility, effectiveness and sustainability of different emission reduction policies, which helps policymakers to formulate reasonable emission reduction policies and promote the green transformation of the economy.

[0069] Furthermore, when the residual value of the carbon trading model is less than the preset threshold, it means that the carbon trading model has reached equilibrium. The mathematical expression of the carbon trading model equilibrium is:

[0070] TCO2 t =(1-tcer i )CO2ref i

[0071]

[0072] C i,t =P i,t ·(CR i,t -FP i,t )

[0073] Where, TCO2 t is the total carbon quota of the subject in period t, which is equal to the total supply of carbon quota; CO2ref is the benchmark carbon emission of the subject in period t; tcer i is the carbon emission reduction rate of the subject in period t; COAL is the carbon emissions of each entity in period t; i,t 、OIL i,t 、GAS i,t is the energy consumption of coal, oil and natural gas in period t; coal , γ oil , γ gas is the carbon emission coefficient of coal, oil and natural gas; C i,t is the carbon trading cost of commodity i in period t; P i,t is the unit price of carbon quota of each entity in period t; CR i,t is the carbon quota of each entity in period t; FP i,t is the free quota of each entity in period t.

[0074] Furthermore, when the residual value of the green certificate trading model is less than the preset threshold, it means that the green certificate trading model has reached equilibrium. The mathematical expression of the green certificate trading model in equilibrium is:

[0075]

[0076]

[0077] PLC i-ely =Pfine*QRPS

[0078] In the formula, i-nel represents the non-power industry that needs to purchase green certificates, i-ely represents the power industry, Quota represents the proportion of renewable energy power generation to thermal power generation, QSN, QWD, QBS, and QTP represent the production subsidy power synthesis, the commodity needs to be invested in the subsidized photovoltaic power generation, biomass power generation, wind power generation, and thermal power generation, QRPS represents the default power generation when the power generation enterprise fails to complete the renewable energy quota, rps is the exogenously given renewable energy quota ratio, and PLC i-nel represents the cost of purchasing green certificates for the i-nel non-power industry, ptsn, ptbs, ptwd represent the prices of green certificates for photovoltaic power generation, biomass power generation, and wind power generation, respectively, TGCsn i-nel , TGCbs i-nel 、TGCwd i-nel Represents the number of green certificates purchased by the first-tier industry for photovoltaic power generation, biomass power generation and wind power generation, PLC i-ely Represents the cost of purchasing green certificates for the i-th power industry, and Pfine represents the penalty price when the power generation company fails to meet the renewable energy quota.

[0079] Taking photovoltaic power generation as an example, the number of green power certificates depends on the amount of photovoltaic power generation traded on the grid, and the unit of green certificates is 1000kWh. Due to the limitations of the CGE model itself, green certificate transactions between power companies are not considered, only green certificate transactions between non-power industries and the power industry are considered.

[0080] Furthermore, when the carbon trading model and the green certificate trading model reach equilibrium, the carbon trading costs and green certificate trading costs of each entity are embedded in the CGE model, and its mathematical expression is:

[0081] X i,t ·PX i,t =OC i,t +PLC i,t +PLC i-nel +PLC i-ely

[0082] PLC i,t =C i,t +P f,t (EM i,t -CR i,t )

[0083] In the formula, X i,t represents the domestic output of commodity i in period t, PX i,t represents the domestic output price of commodity i in period t, OC i,t represents the original production cost of each entity in period t, PLC i,t represents the additional cost that the enterprise pays for carbon emission rights trading in period t, including transaction costs and penalties for excessive emissions. i-nel Represents the cost of purchasing green certificates for the i-nel non-power industry, PLC i-ely represents the cost of purchasing green certificates for the i-th power industry, C i,t is the carbon trading cost of commodity i in period t, P f,t represents the penalty price for excess emissions of each entity in period t, EM i,t represents the carbon emissions of each entity in period t, CR i,t Represents the carbon quota of each entity in period t.

[0084] Furthermore, assuming that the market is perfectly competitive, under the equilibrium conditions of the market, each production activity follows the principle of optimal use of inputs to minimize the cost of existing production technology;

[0085] A multi-level nested structure is used to reflect the complex substitution relationship between multiple inputs, and the nested relationship is solved by the Leontief function and the constant elasticity of substitution function. The specific steps include:

[0086] The mathematical expression of total output using the Leontief production function is:

[0087]

[0088] Where, INT i,j represents the intermediate input of commodity i to commodity j; VAE j Represents commodity j energy-factor composite bundle; PSB j Represents commodity j power synthesis bundle; Z j represents the total output of domestic commodity j; represents the intermediate input coefficient; A parameter representing the scale and quantity of inputs required to produce one unit of energy-factor composite bundle goods; A parameter representing the scale quantity of inputs required to produce one unit of the electricity synthesis bundle commodity;

[0089] The mathematical expression of using CES function to represent the second to fourth layer resource input is:

[0090]

[0091] In the formula, QX m represents the total output of each layer of production activity set, represents the scale parameter in the CES production function, K m and L m Represents different types of input, represents the input share coefficient of the CES production function, m represents the set of production activities, Represents the correlation coefficient of substitution elasticity between capital-energy-labor composite input and non-energy intermediate input.

[0092] Furthermore, in the CGE model, the Cobb-Douglas production function is used to explain the utility maximization problem of economic actors. Economic actors achieve equilibrium configuration through market clearing. The mathematical expression of the behavior of different economic actors is:

[0093]

[0094] In the formula, PQ i represents the market price of commodity i; QH i Represents the demand of economic actors for commodity i; ω i represents the survival consumption level of product i; i represents the marginal propensity to consume commodity i; YH represents the total income of economic actors.

[0095] Furthermore, the CET function and CES function are used to explain the incomplete substitution relationship between domestic goods and export goods, and between domestic goods and imported goods. In addition, the ratio of imports to domestic demand is related to the function of exchange rate, elasticity and CES share parameters. Therefore, for the import and export of domestic goods, the CES / CET utility function is used to determine its domestic demand, and its mathematical expression is:

[0096]

[0097] In the formula, QK i represents the composite supply of the set of goods that are both exported and produced domestically; QQ j represents the composite supply of the set of goods that are both imported and domestically produced; represents the scale parameter, share parameter and utility function index in the CET utility function; Represents the scale parameter, share parameter and utility function index in the CES utility function; QE i The number of export commodities QD that represents the commodity set that is both exported and produced domesticallyi represents the quantity of domestic goods in the set of goods that are both exported and produced domestically; QM j The quantity of imported goods in the set of goods that are both imported and produced domestically; QD j Represents the quantity of domestic goods in the set of goods that are both imported and domestically produced.

[0098] Embodiment 2

[0099] Please refer to Figure 2 The embodiment of the present invention also provides a carbon market and green certificate market transaction scenario evolution simulation analysis system, the system comprising:

[0100] The acquisition module is used to obtain economic variables of multiple trading scenarios, including the total carbon quota, carbon emission reduction rate, benchmark carbon emissions, unit price of carbon quota, carbon quota of each entity, free quota of each entity, green certificate transaction price, and renewable energy quota ratio;

[0101] Model building module, which is used to build a carbon trading model based on the CGE model according to the total carbon quota, carbon emission reduction rate, benchmark carbon emissions, unit price of carbon quota, carbon quota of each entity, and free quota of each entity, and to build a green certificate trading model according to the green certificate trading price and renewable energy quota ratio;

[0102] The model iteration module is used to iterate the carbon trading model and the green certificate trading model by repeatedly adjusting the economic variables, calculating the residual values ​​of the carbon trading model and the green certificate trading model and solving the Jacobian matrix to update the economic variables until the residual value is less than the preset threshold, thereby obtaining the equilibrium solution of the economic variables;

[0103] The evaluation module is used to adopt different carbon emission reduction targets according to the variable range of economic variables corresponding to the equilibrium solution and different trading scenarios, and to evaluate the impact of carbon emission reduction targets under different trading scenarios on the macro-economy, carbon emission reduction effects and renewable energy development.

[0104] The beneficial effects of the system of the embodiment of the present invention are equivalent to the beneficial effects of the above-mentioned carbon market and green certificate market transaction scenario evolution simulation analysis method, which will not be elaborated here.

[0105] The system also includes: a production module, an income and expenditure module, and a market module.

[0106] Furthermore, when the residual value of the carbon trading model is less than the preset threshold, it means that the carbon trading model has reached equilibrium. The mathematical expression of the carbon trading model equilibrium is:

[0107] TCO2 t =(1-tcer i )CO2ref i

[0108]

[0109] C i,t =P i,t ·(CR i,t -FP i,t )

[0110] Where, TCO2 t is the total carbon quota of the subject in period t, which is equal to the total supply of carbon quota; CO2ref is the benchmark carbon emission of the subject in period t; tcer i is the carbon emission reduction rate of the subject in period t; EM i,t COAL is the carbon emissions of each entity in period t; i,t 、OIL i,t 、GAS i,t is the energy consumption of coal, oil and natural gas in period t; coal , γ oil , γ gas is the carbon emission coefficient of coal, oil and natural gas; C i,t is the carbon trading cost of commodity i in period t; P i,t is the unit price of carbon quota of each entity in period t; CR i,t is the carbon quota of each entity in period t; FP i,t is the free quota of each entity in period t.

[0111] Furthermore, when the residual value of the green certificate trading model is less than the preset threshold, it means that the green certificate trading model has reached equilibrium. The mathematical expression of the green certificate trading model in equilibrium is:

[0112]

[0113]

[0114] PLC i-ely =Pfine*QRPS

[0115] In the formula, i-nel represents the non-power industry that needs to purchase green certificates, i-ely represents the power industry, Quota represents the proportion of renewable energy power generation to thermal power generation, QSN, QWD, QBS, and QTP represent the production subsidy power synthesis, the commodity needs to be invested in the subsidized photovoltaic power generation, biomass power generation, wind power generation, and thermal power generation, QRPS represents the default power generation when the power generation enterprise fails to complete the renewable energy quota, rps is the exogenously given renewable energy quota ratio, and PLC i-nel represents the cost of purchasing green certificates for the i-nel non-power industry, ptsn, ptbs, ptwd represent the prices of green certificates for photovoltaic power generation, biomass power generation, and wind power generation, respectively, TGCsni-nel , TGCbs i-nel 、TGCwd i-nel Represents the number of green certificates purchased by the first-tier industry for photovoltaic power generation, biomass power generation and wind power generation, PLC i-ely Represents the cost of purchasing green certificates for the i-th power industry, and Pfine represents the penalty price when the power generation company fails to meet the renewable energy quota.

[0116] Furthermore, when the carbon trading model and the green certificate trading model reach equilibrium, the carbon trading costs and green certificate trading costs of each entity are embedded in the CGE model, and its mathematical expression is:

[0117] X i,t ·PX i,t =OC i,t +PLC i,t +PLC i-nel +PLC i-ely

[0118] PLC i,t =C i,t +P f,t (EM i,t -CR i,t )

[0119] In the formula, X i,t represents the domestic output of commodity i in period t, PX i,t represents the domestic output price of commodity i in period t, OC i,t represents the original production cost of each entity in period t, PLC i,t represents the additional cost that the enterprise pays for carbon emission rights trading in period t, including transaction costs and penalties for excessive emissions. i-nel Represents the cost of purchasing green certificates for the i-nel non-power industry, PLC i-ely represents the cost of purchasing green certificates for the i-th power industry, C i,t is the carbon trading cost of commodity i in period t, P f,t represents the penalty price for excess emissions of each entity in period t, EM i,t represents the carbon emissions of each entity in period t, CR i,t Represents the carbon quota of each entity in period t.

[0120] Furthermore, the production module adopts a multi-level nested structure to reflect the complex substitution relationship between multiple inputs, and solves the nested relationship through the Leontief function and the constant substitution elasticity function. Assuming that the market is perfectly competitive, under the equilibrium conditions of the market, each production activity follows the principle of optimizing the use of inputs to minimize costs with existing production technology.

[0121] A multi-level nested structure is used to reflect the complex substitution relationship between multiple inputs. The specific steps include:

[0122] The mathematical expression of total output using the Leontief production function is:

[0123]

[0124] Where, INT i,j represents the intermediate input of commodity i to commodity j; VAE j Represents commodity j energy-factor composite bundle; PSB j Represents commodity j power synthesis bundle; Z j represents the total output of domestic commodity j; represents the intermediate input coefficient; A parameter representing the scale and quantity of inputs required to produce one unit of energy-factor composite bundle goods; A parameter representing the scale quantity of inputs required to produce one unit of the electricity synthesis bundle commodity;

[0125] The mathematical expression of using CES function to represent the second to fourth layer resource input is:

[0126]

[0127] In the formula, QX m represents the total output of each layer of production activity set, represents the scale parameter in the CES production function, K m and L m Represents different types of input, represents the input share coefficient of the CES production function, m represents the set of production activities, Represents the correlation coefficient of substitution elasticity between capital-energy-labor composite input and non-energy intermediate input.

[0128] Furthermore, the income and expenditure module consists of four economic actors: households, enterprises, governments, and trading partners. In this CGE model, the Cobb-Douglas production function is used to explain the utility maximization problem of economic actors. Economic actors achieve equilibrium allocation through market clearing. The mathematical expression of the behavior of different economic actors is:

[0129]

[0130] In the formula, PQ i represents the market price of commodity i; QH i Represents the demand of economic actors for commodity i; ω i represents the survival consumption level of product i; irepresents the marginal propensity to consume commodity i; YH represents the total income of economic actors.

[0131] Furthermore, the market module uses CET function and CES function to explain the incomplete substitution relationship between domestic goods and export goods, and between domestic goods and imported goods. In addition, the ratio of imports to domestic demand is related to the function of exchange rate, elasticity and CES share parameter. Therefore, for the import and export of domestic goods, the CES / CET utility function is used to determine its domestic demand, and its mathematical expression is:

[0132]

[0133] In the formula, QK i represents the composite supply of the set of goods that are both exported and produced domestically; QQ j represents the composite supply of the set of goods that are both imported and domestically produced; represents the scale parameter, share parameter and utility function index in the CET utility function; Represents the scale parameter, share parameter and utility function index in the CES utility function; QE i The number of export commodities QD that represents the commodity set that is both exported and produced domestically i represents the quantity of domestic goods in the set of goods that are both exported and produced domestically; QM j The quantity of imported goods in the set of goods that are both imported and produced domestically; QD j Represents the quantity of domestic goods in the set of goods that are both imported and domestically produced.

[0134] Furthermore, the CGE model uses a recursive dynamic CGE model.

[0135] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution disclosed in the present invention can be achieved, and this document does not limit this.

[0136] It should be understood that although the steps in the flowchart of the accompanying drawings are shown in sequence according to the instructions of the arrows, these steps are not necessarily performed in the order indicated by the arrows. Unless otherwise clearly stated in this document, the execution of these steps is not strictly limited in order and can be performed in other orders.

[0137] Moreover, at least part of the steps in the flowchart of the accompanying drawings may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The order of execution is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0138] The specific embodiments described above further describe the purpose, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. It is particularly pointed out that for those skilled in the art, any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the scope of protection of the present invention.

Claims

1. The simulation analysis method for the evolution of carbon market and green certificate market trading scenarios is characterized by: The method comprises: Obtain economic variables for multiple trading scenarios, including the total carbon quota, carbon emission reduction rate, benchmark carbon emissions, unit price of carbon quota, carbon quota of each entity, free quota of each entity, green certificate transaction price, and renewable energy quota ratio; On the basis of the CGE model, a carbon trading model is constructed according to the total carbon quota, the carbon emission reduction rate, the benchmark carbon emissions, the unit price of the carbon quota, the carbon quota of each entity, and the free quota of each entity; a green certificate trading model is constructed according to the green certificate trading price and the renewable energy quota ratio; Iterate the carbon trading model and the green certificate trading model, repeatedly adjust the economic variables, calculate the residual values ​​of the carbon trading model and the green certificate trading model, and solve the Jacobian matrix to update the economic variables until the residual value is less than a preset threshold, thereby obtaining an equilibrium solution of the economic variables; According to the variable range of the economic variables corresponding to the equilibrium solution and different trading scenarios, different carbon emission reduction targets are adopted to evaluate the impact of the carbon emission reduction targets under different trading scenarios on the macro-economy, carbon emission reduction effects and renewable energy development.

2. The carbon market and green certificate market transaction scenario evolution simulation analysis method according to claim 1, characterized in that: When the residual value of the carbon trading model is less than a preset threshold, it means that the carbon trading model has reached equilibrium. The mathematical expression of the carbon trading model in equilibrium is: TCO2 t =(1-tcer i )CO2ref i EM i,t =COAL i,t ×γ coal +OIL i,t ×γ oil +GAS i,t ×γ gas C i,t =P i,t ·(CR i,t -FP i,t ) Where, TCO2 t is the total carbon quota of the subject in period t, which is equal to the total supply of carbon quotas. CO2ref is the benchmark carbon emissions of the subject in period t. tcer i is the carbon emission reduction rate of the subject in period t, is the carbon emissions of each entity in period t, COAL i,t 、OIL i,t 、GAS i,t is the energy consumption of coal, oil and natural gas in period t, γ coal , γ oil , γ gas is the carbon emission coefficient of coal, oil and natural gas, C i,t is the carbon trading cost of commodity i in period t, P i,t is the unit price of carbon quota of each entity in period t, CR i,t is the carbon quota of each entity in period t, FP i,t is the free quota of each entity in period t.

3. The carbon market and green certificate market transaction scenario evolution simulation analysis method according to claim 1, characterized in that: When the residual value of the green certificate trading model is less than the preset threshold, it means that the green certificate trading model has reached equilibrium. The mathematical expression of the green certificate trading model in equilibrium is: PLC i-ely =Pfine*QRPS In the formula, i-nel represents the non-power industry that needs to purchase green certificates, i-ely represents the power industry, Quota represents the proportion of renewable energy power generation to thermal power generation, QSN, QWD, QBS, and QTP represent the production subsidy power synthesis, the commodity needs to be invested in the subsidized photovoltaic power generation, biomass power generation, wind power generation, and thermal power generation, QRPS represents the default power generation when the power generation enterprise fails to complete the renewable energy quota, rps is the exogenously given renewable energy quota ratio, and PLC i-nel represents the cost of purchasing green certificates for the i-nel non-power industry, ptsn, ptbs, ptwd represent the prices of green certificates for photovoltaic power generation, biomass power generation, and wind power generation, respectively, TGCsn i-nel , TGCbs i-nel 、TGCwd i-nel Represents the number of green certificates purchased by the first-tier industry for photovoltaic power generation, biomass power generation and wind power generation, PLC i-ely Represents the cost of purchasing green certificates for the i-th power industry, and Pfine represents the penalty price when the power generation company fails to meet the renewable energy quota.

4. The carbon market and green certificate market transaction scenario evolution simulation analysis method according to claim 1, characterized in that: When the carbon trading model and the green certificate trading model reach equilibrium, the carbon trading costs and green certificate trading costs of each entity are embedded into the CGE model, and its mathematical expression is: X i,t ·PX i,t =OC i,t +PLC i,t +PLC i-nel +PLC i-ely PLC i,t =C i,t +P f,t (EM i,t -CR i,t ) In the formula, X i,t represents the domestic output of commodity i in period t, PX i,t represents the domestic output price of commodity i in period t, OC i,t represents the original production cost of each entity in period t, PLC i,t represents the additional cost that the enterprise pays for carbon emission rights trading in period t, including transaction costs and penalties for excessive emissions. i-nel Represents the cost of purchasing green certificates for the i-nel non-power industry, PLC i-ely represents the cost of purchasing green certificates for the i-th power industry, C i,t is the carbon trading cost of commodity i in period t, P f,t represents the penalty price for excess emissions of each entity in period t, represents the carbon emissions of each entity in period t, CR i,t Represents the carbon quota of each entity in period t.

5. The carbon market and green certificate market transaction scenario evolution simulation analysis method according to claim 1, characterized in that: Under market equilibrium conditions, every production activity follows the principle of optimal use of inputs to minimize the cost of existing production technology; A multi-level nested structure is used to reflect the complex substitution relationship between multiple inputs. The specific steps include: The mathematical expression of total output using the Leontief production function is: Where, INT i,j represents the intermediate input of commodity i to commodity j; VAE j Represents commodity j energy-factor composite bundle; PSB j Represents commodity j power synthesis bundle; Z j represents the total output of domestic commodity j; represents the intermediate input coefficient; A parameter representing the scale and quantity of inputs required to produce one unit of energy-factor composite bundle goods; A parameter representing the scale quantity of inputs required to produce one unit of the electricity synthesis bundle commodity; The mathematical expression of using CES function to represent the second to fourth layer resource input is: In the formula, QX m represents the total output of each layer of production activity set, represents the scale parameter in the CES production function, K m and L m Represents different types of input, represents the input share coefficient of the CES production function, m represents the set of production activities, Represents the correlation coefficient of substitution elasticity between capital-energy-labor composite input and non-energy intermediate input.

6. The carbon market and green certificate market transaction scenario evolution simulation analysis method according to claim 1, characterized in that: In the CGE model, the Cobb-Douglas production function is used to explain the utility maximization problem of economic actors. Economic actors achieve equilibrium configuration through market clearing. The mathematical expressions of the behaviors of different economic actors are: In the formula, PQ i represents the market price of commodity i; QH i Represents the demand of economic actors for commodity i; ω i represents the survival consumption level of product i; X i represents the marginal propensity to consume commodity i; YH represents the total income of economic actors.

7. The carbon market and green certificate market transaction scenario evolution simulation analysis method according to claim 1, characterized in that: The CET function and CES function are used to explain the incomplete substitution relationship between domestic goods and export goods, and between domestic goods and imported goods. For the import and export of domestic goods, the CES / CET utility function is used to determine its domestic demand, and its mathematical expression is: In the formula, QK i represents the composite supply of the set of goods that are both exported and produced domestically; QQ j represents the composite supply of the set of goods that are both imported and domestically produced; represents the scale parameter, share parameter and utility function index in the CET utility function; Represents the scale parameter, share parameter and utility function index in the CES utility function; QE i The number of export commodities QD that represents the commodity set that is both exported and produced domestically i represents the quantity of domestic goods in the set of goods that are both exported and produced domestically; QM j The quantity of imported goods in the set of goods that are both imported and produced domestically; QD j Represents the quantity of domestic goods in the set of goods that are both imported and domestically produced.

8. The carbon market and green certificate market transaction scenario evolution simulation analysis method according to claim 1, characterized in that: The CGE model is a recursive dynamic CGE model.

9. Carbon market and green certificate market transaction scenario evolution simulation analysis system, characterized by: include: An acquisition module is used to acquire economic variables of multiple transaction scenarios, including the total carbon quota, carbon emission reduction rate, benchmark carbon emissions, unit price of carbon quota, carbon quota of each entity, free quota of each entity, green certificate transaction price, and renewable energy quota ratio; A model building module is used to build a carbon trading model based on the CGE model according to the total carbon quota, the carbon emission reduction rate, the benchmark carbon emissions, the unit price of the carbon quota, the carbon quota of each entity, and the free quota of each entity, and to build a green certificate trading model according to the green certificate trading price and the renewable energy quota ratio; A model iteration module, used to iterate the carbon trading model and the green certificate trading model, calculate the residual values ​​of the carbon trading model and the green certificate trading model and solve the Jacobian matrix to update the economic variables by repeatedly adjusting the economic variables until the residual value is less than a preset threshold, thereby obtaining an equilibrium solution of the economic variables; An evaluation module is used to adopt different carbon emission reduction targets according to the equilibrium solution and the variable range of the economic variables corresponding to different trading scenarios, and to evaluate the impact of the carbon emission reduction targets under different trading scenarios on the macro-economy, carbon emission reduction effects and renewable energy development.

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