Green evidence-carbon-electricity market coupling modeling analysis method based on system dynamics

Abstract

A green evidence-carbon-electricity market coupling modeling analysis method based on system dynamics relates to the field of electricity markets, and comprises the following steps: determining a system boundary, dividing a green evidence-carbon-electricity three-market coupling system into a plurality of sub-modules, and providing a reasonable hypothesis; key elements in each sub-module are extracted, the causal relationship between the key elements is analyzed, and a causal loop diagram of the coupling system is constructed; constructing a stock flow diagram according to the causal loop diagram, establishing an equation, and describing a function relationship between variables; modeling is carried out by utilizing system dynamics simulation software Vensim, parameters are adjusted, and different scenes are set for simulation analysis. According to the method, the interaction among the green certificate market, the carbon market and the electricity market is comprehensively considered, the renewable energy consumption responsibility weight index is concerned, and the influence of the carbon quota tightening coefficient, the carbon quota auction proportion and the renewable energy consumption responsibility weight change on the whole system dynamic state is deeply discussed by establishing the simulation case.

Description

Technical Field

[0001] The present invention relates to the field of electricity market, and in particular to a green certificate-carbon-electricity market coupling modeling and analysis method based on system dynamics. Background Art

[0002] The significant increase in global emissions of greenhouse gases such as carbon dioxide has led to rising global average temperatures, frequent extreme climate events, accelerated glacier melting, rising sea levels, and serious threats to the balance of the ecosystem.

[0003] Green certificate market, carbon market and electricity market are important market mechanisms for realizing my country's energy transformation. The green certificate market is mainly established to promote the development of renewable energy. In this market, renewable energy power generation enterprises obtain green certificates by producing green electricity. These green certificates can be used to meet the government's renewable energy consumption responsibility weight requirements. The existence of the green certificate market effectively alleviates the government's huge subsidy pressure on renewable energy enterprises and attracts more investment into the renewable energy field. The carbon market is established to control greenhouse gas emissions. The government allocates a certain number of carbon emission quotas to each participating enterprise based on the set emission cap. These quotas represent the amount of carbon dioxide that enterprises are allowed to emit. The quota can be allocated free of charge, auctioned, or a combination of the two. If the actual emissions of a company are lower than the quota it holds, it can sell its excess quota to other companies whose emissions exceed the quota, thereby encouraging companies to increase their efforts to reduce emissions and reduce carbon emissions. The electricity market is a broader platform with a variety of trading varieties and many types of transactions. It can be divided into medium- and long-term markets and spot markets according to the time scale, and can be divided into electric energy markets and ancillary service markets according to the trading objects. Among them, the green electricity market refers to the medium- and long-term market with green electricity as the underlying asset. If you buy green electricity, you will also get a corresponding number of green certificates, reflecting the characteristics of "certificate and electricity integration". Different market types have different market rules, but they all play an important role in maintaining the balance of power supply and demand and ensuring power quality.

[0004] However, the green certificate market, carbon market, and electricity market do not exist independently. They are coupled in terms of product attributes, price formation, and accounting system. How to effectively identify the key elements of the coupled system and clarify its interaction mechanism has become an important issue facing current energy policy makers and researchers.

[0005] In the existing technologies, most of them are limited to the interaction between the two markets of green certificate market, carbon market and electricity market, and the research on the trading products of each market is relatively single. For example, the Chinese patent application with application number 202310926928.1 proposes a collaborative modeling method of green certificate market and electricity market based on system dynamics, and the Chinese patent application with application number 202311846577.X proposes a system dynamics analysis method and system for the collaborative system of electricity and green certificate market.

[0006] The Chinese patent application with application number 202311219942.4 proposes a method for constructing a dynamic simulation model of the electricity-carbon-green certificate price transmission system, and constructs an electricity-carbon-green certificate market collaborative operation framework that realizes energy supply and demand through the synergy of electricity, carbon, and green certificate markets. Its initial research on the electricity market only considered the electricity energy market, and did not fully consider the additional benefits that the ancillary service market may bring to those thermal power companies with higher controllability, while also ignoring the possible impact on the revenue of green power companies. In addition, in terms of the carbon market, the application did not take into account the specific impact of the tightening of carbon quotas and the proportion of auctioned carbon quotas on the revenue of thermal power companies. As the carbon market matures, carbon quotas will gradually tighten, and the proportion of paid carbon quotas will increase. Therefore, it is necessary to simulate and analyze these factors to evaluate their impact on thermal power companies. Summary of the invention

[0007] The purpose of the present invention is to provide a system dynamics model construction and analysis method involving the green certificate market, carbon market and electricity market coupling system to address the deficiencies of the prior art.

[0008] In order to achieve the above object, the present invention adopts the following technical solutions: On the one hand, the present invention proposes a green certificate-carbon-electricity market coupling modeling and analysis method based on system dynamics, including: Determine the system boundaries, divide the green certificate-carbon-electricity three-market coupling system into several sub-modules, and propose reasonable assumptions; extract the key elements in each sub-module, analyze the causal relationship between the key elements, and construct a causal loop diagram of the coupling system; construct a stock-flow diagram based on the causal loop diagram, establish equations, and describe the functional relationship between the variables; use the system dynamics simulation software Vensim to build a model, adjust parameters, and set different scenarios for simulation analysis.

[0009] Furthermore, the sub-modules include: a green electricity enterprise module, a thermal power enterprise module, a green certificate market module, a carbon market module, an electric energy market module and ancillary service market module.

[0010] Furthermore, the reasonable assumptions include: 1) Green power enterprises refer to wind power and photovoltaic power generation enterprises that can apply for green certificates; 2) The operation mode of the green electricity market is "certificate and electricity in one", and users can also obtain green certificates when purchasing green electricity; 3) Buyers of green certificates include individual consumers and enterprises responsible for consuming renewable energy; 4) The validity period of the green certificate is 2 years. If the green certificate expires, it cannot be traded on the green certificate market.

[0011] Furthermore, the key elements extracted from each submodule include: In the green electricity enterprise module, the key elements include green electricity installed capacity, green electricity unit power generation, green electricity enterprise profits, and green electricity enterprise flexibility transformation investment.

[0012] In the thermal power enterprise module, the key elements include installed capacity of thermal power units, power generation of thermal power units, profits of thermal power enterprises, and emission reduction investment of thermal power enterprises.

[0013] In the green certificate market module, key elements include green certificate demand, green certificate supply, and green certificate price.

[0014] In the carbon market module, key elements include carbon quota supply, carbon quota demand, and carbon price.

[0015] In the electricity energy market module, the key elements include green electricity demand, green electricity supply, green electricity price, thermal power demand, thermal power supply, and thermal power price.

[0016] In the ancillary service market module, key elements include green electricity penetration rate, ancillary service demand, and ancillary service price.

[0017] Furthermore, the causal relationship between the key elements includes: 1) Increased demand for green electricity → Increased green electricity prices → Increased profits for green electricity companies → Increased installed capacity of green electricity units → Increased power generation of green electricity units → Increased green electricity supply → Falling green electricity prices.

[0018] 2) Increased demand for thermal power → increased thermal power prices → increased profits for thermal power companies → increased installed capacity of thermal power plants → increased power generation from thermal power plants → increased thermal power supply → decreased thermal power prices.

[0019] 3) Increased demand for green certificates → Increased price of green certificates → Increased profits for green electricity companies → Increased installed capacity of green electricity generators → Increased power generation of green electricity generators → Increased supply of green certificates → Decreased price of green certificates.

[0020] 4) Increased demand for carbon quotas → increased carbon prices → reduced profits for thermal power companies → increased investment in emission reductions for thermal power companies → reduced demand for carbon quotas → reduced carbon prices.

[0021] 5) Green electricity penetration rate increases → demand for ancillary services increases → ancillary service prices rise → green electricity companies’ profits decrease → green electricity companies’ flexibility transformation investment increases → demand for ancillary services decreases → ancillary service prices decrease.

[0022] On the other hand, the present invention also proposes a modeling and analysis system for the green certificate-carbon-electricity three-market coupling system based on system dynamics to implement the above method, including: The system division module is used to determine the system boundaries, divide the green certificate-carbon-electricity market coupling system into several sub-modules, and put forward reasonable assumptions.

[0023] The causal loop diagram construction module is used to extract the key elements in each sub-module, analyze the causal relationship and hierarchical relationship between the key elements, and construct the causal loop diagram of the coupled system.

[0024] The stock-flow diagram construction module is used to construct a stock-flow diagram based on the causal loop diagram, establish equations, and describe the functional relationship between variables.

[0025] The simulation analysis module is used to use the system dynamics simulation software Vensim to build models, adjust parameters, and set different scenarios for simulation analysis.

[0026] On the other hand, the present invention further proposes a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above method when executing the computer program.

[0027] On the other hand, the present invention further proposes a computer-readable storage medium, wherein the medium stores a computer program, and when the computer program is executed by a processor, the steps of the above method are implemented.

[0028] The present invention comprehensively considers the interaction between the green certificate market, the carbon market and the electricity market, and pays attention to the renewable energy consumption responsibility weight index. In particular, the present invention distinguishes between the electric energy market and the ancillary service market in the electricity market, reflecting the situation that thermal power companies can realize profits through both the electric energy market and the provision of ancillary services, while taking into account the need for green power companies to purchase ancillary services to stabilize their output fluctuations. In the electric energy market part, the present invention emphasizes the special nature of the green electricity market, which embodies the characteristics of "certificate and electricity integration", that is, the green certificates obtained through green electricity transactions can be used to offset the renewable energy consumption responsibility weight index. In addition, by establishing a simulation case, the present invention deeply explores the impact of the carbon quota tightening coefficient, the carbon quota auction ratio and the changes in the renewable energy consumption responsibility weight on the dynamics of the entire system, which helps decision makers to formulate reasonable policies to promote the coordinated development of the electricity carbon-green certificate market, and can also help operators fully understand market laws and adjust operating strategies. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 is a flow chart of the present invention; Figure 2 It is a causal loop diagram of the green certificate-carbon-electricity three-market coupling system constructed by the present invention; Figure 3 It is the stock-flow diagram of the green power enterprise submodule; Figure 4 It is the stock-flow diagram of the thermal power enterprise submodule; Figure 5 It is the stock-flow diagram of the green certificate market submodule; Figure 6 It is the stock-flow diagram of the carbon market submodule; Figure 7 It is the stock-flow diagram of the electric energy market submodule; Figure 8 It is the stock-flow diagram of the ancillary service market submodule; Fig. 9 It is the trend chart of the cumulative installed capacity of green power and thermal power units; Fig.10 This is the simulation result diagram of green power and thermal power prices; Fig.11 is the cumulative installed capacity of thermal power units under different carbon quota auction ratios; Fig.12 is the change of carbon price under different carbon quota tightening coefficients; Fig.13 It is the change of green certificate price under different growth rates of renewable energy consumption responsibility weight indicators. DETAILED DESCRIPTION

[0030] A coupled system is a system in which two or more subsystems interact with each other through physical or logical connections to jointly complete a specific function. In different fields, coupled systems have different manifestations and application scenarios.

[0031] Regardless of the field, the key to coupled systems is to understand the interaction mechanisms between the various subsystems and how these interactions affect the overall behavior of the system. By optimizing these interactions, the performance, stability and efficiency of the system can be improved.

[0032] In the present invention, the green certificate market, carbon market and electricity market work together to promote the development of renewable energy and reduce greenhouse gas emissions. They are all key mechanisms to promote the transformation of energy structure to green and low-carbon, and there is a coupling relationship at the level of physics, market entities and price mechanism. At the physical level, thermal power generation will produce carbon emissions, while new energy power generation such as wind power and solar energy has significant green environmental value due to its zero emission characteristics, so it needs to be traded in the carbon market and the green certificate market respectively; in terms of market entities, the same enterprise may be active in multiple markets at the same time. For example, traditional thermal power companies obtain income by selling electricity in the electricity market, and at the same time, in order to meet emission standards, they also need to purchase carbon emission quotas in the carbon market to manage their own carbon footprint; in terms of price mechanism, price changes in one market may have an impact on other markets. For example, the rise in carbon prices will increase the cost of using fossil fuels, thereby increasing the relative attractiveness of renewable energy, which may lead to an increase in demand for green electricity and push up the price of green electricity.

[0033] This paper proposes a green certificate-carbon-electricity market coupling modeling and analysis method based on system dynamics, see Figure 1 , including the following steps: Step 1: Determine the system boundaries, divide the green certificate-carbon-electricity market coupling system into several sub-modules, and put forward reasonable assumptions.

[0034] Step 2: Extract the key elements in each sub-module, analyze the causal relationship between the key elements, and construct a causal loop diagram of the coupled system.

[0035] Step 3: Construct a stock-flow diagram based on the causal loop diagram and establish an equation to describe the functional relationship between the variables.

[0036] Step 4: Use the system dynamics simulation software Vensim to build a model, adjust parameters, and set different scenarios for simulation analysis.

[0037] In step 1, the whole process of "generation-transmission-distribution-sale-use" of the power system is considered to straighten out the organizational structure of the three-market coupling system. In order to better analyze the green certificate-carbon-power three-market coupling system, the present invention decomposes this complex system into several sub-modules by determining the system boundary: the system dynamics model constructed by the present invention includes a green power enterprise module, a thermal power enterprise module, a green certificate market module, a carbon market module, an electric energy market module and an ancillary service market module.

[0038] Reasonable assumptions are made for the system, including: 1) Green electricity enterprises refer to wind power and photovoltaic power generation enterprises that can apply for green certificates. In order to avoid the situation of green certificate price flooding, hydropower is not included; 2) The operation mode of the green electricity market is "certificate and electricity in one", and users can obtain green certificates when purchasing green electricity; 3) The buyers of green certificates include individual consumers and renewable energy consumption responsible enterprises. Among them, individual consumers purchase green certificates out of environmental awareness, and their purchase volume meets the demand function. Renewable energy consumption responsible enterprises purchase green certificates in order to meet the renewable energy consumption responsibility indicators; 4) The validity period of a green certificate is 2 years. If a green certificate expires, it cannot be traded on the green certificate market.

[0039] The purpose of making reasonable assumptions is to lay the foundation for the construction of system dynamics models. These assumptions help define the research objectives, clarify the problems to be solved, and help identify the key variables in the system.

[0040] In step 2, the key elements in each submodule are first identified and extracted.

[0041] In this embodiment, the key elements in each submodule include: In the green electricity enterprise module, the key elements include green electricity installed capacity, green electricity unit power generation, green electricity enterprise profits, and green electricity enterprise flexibility transformation investment.

[0042] In the thermal power enterprise module, the key elements include installed capacity of thermal power units, power generation of thermal power units, profits of thermal power enterprises, and emission reduction investment of thermal power enterprises.

[0043] In the green certificate market module, key elements include green certificate demand, green certificate supply, and green certificate price.

[0044] In the carbon market module, key elements include carbon quota supply, carbon quota demand, and carbon price.

[0045] In the electricity energy market module, the key elements include green electricity demand, green electricity supply, green electricity price, thermal power demand, thermal power supply, and thermal power price.

[0046] In the ancillary service market module, key elements include green electricity penetration rate, ancillary service demand, and ancillary service price.

[0047] On this basis, the causal relationship between key elements is analyzed.

[0048] In this embodiment, the causal relationship between the key elements includes: 1) Increased demand for green electricity → Increased green electricity prices → Increased profits for green electricity companies → Increased installed capacity of green electricity units → Increased power generation of green electricity units → Increased green electricity supply → Falling green electricity prices.

[0049] 2) Increased demand for thermal power → increased thermal power prices → increased profits for thermal power companies → increased installed capacity of thermal power plants → increased power generation from thermal power plants → increased thermal power supply → decreased thermal power prices.

[0050] 3) Increased demand for green certificates → Increased price of green certificates → Increased profits for green electricity companies → Increased installed capacity of green electricity generators → Increased power generation of green electricity generators → Increased supply of green certificates → Decreased price of green certificates.

[0051] 4) Increased demand for carbon quotas → increased carbon prices → reduced profits for thermal power companies → increased investment in emission reductions for thermal power companies → reduced demand for carbon quotas → reduced carbon prices.

[0052] 5) Green electricity penetration rate increases → demand for ancillary services increases → ancillary service prices rise → green electricity companies’ profits decrease → green electricity companies’ flexibility transformation investment increases → demand for ancillary services decreases → ancillary service prices decrease.

[0053] After clarifying the causal relationship, a causal loop diagram can be constructed. In this embodiment, a causal loop diagram of six modules of the coupling system is constructed. Figure 2 shown.

[0054] The “+” indicates that there is a positive correlation between the variables, that is, an increase in one variable will lead to an increase in another variable, and the “-” indicates that there is a negative correlation between the variables, that is, an increase in one variable will lead to a decrease in another variable.

[0055] Vensim system dynamics simulation software is based on stock-flow diagrams, so the causal loop diagram must be converted into a stock-flow diagram. The causal loop diagram clarifies the cause-effect relationship in the system, while the stock-flow diagram shows how the variables in the system change over time.

[0056] The mathematical variables (stock, flow, auxiliary variables and constants) extracted from the key factors (physical meaning) in the causal diagram do not have to be the same. For example, the key element "green power unit installed capacity" in the causal loop diagram is converted into "green power unit installed capacity under construction", "green power unit cumulative installed capacity", "green power unit planned installed capacity" and "green power unit new installed capacity" in the stock-flow diagram. These stocks and flows are used to describe the changes in green power unit installed capacity over time.

[0057] In step 3, based on the constructed causal loop diagram, the stocks, flows, auxiliary variables and constants in each submodule are clarified; equations are established, and linear functions, delay functions, smoothing functions, etc. are used to describe the relationship between the variables.

[0058] A stock-flow diagram is a graphical representation method used to show the various stocks in a system and their flow relationships. Stock refers to the cumulative value of any quantity or state in the system at a certain moment, and flow refers to the amount entering or leaving the stock per unit time. Auxiliary variables and constants are also needed to complete the modeling. This kind of diagram shows the direction of flow through arrows. Usually, stocks are represented by rectangles or rounded rectangles, while flows are represented by lines with arrows.

[0059] The following describes the drawing of the stock-flow diagram of each module.

[0060] 1. Construct the stock-flow diagram of the green electricity enterprise module and draw the stock-flow diagram of the green electricity enterprise module, such as Figure 3 shown.

[0061] The stock includes the installed capacity of green power units under construction and the cumulative installed capacity of green power units. The flow includes the planned installed capacity of green power units and the newly installed capacity of green power units. Other variables are auxiliary variables or constants. The planned installed capacity of green power units is a function of the profit of green power enterprises, the average utilization hours of green power units, electricity demand, and the growth rate of electricity demand. The income of green power enterprises includes the income from the green certificate market and the income from the green power enterprise electricity market. The difference between the income and the cost of green electricity is the profit of green power enterprises. The planned installed capacity of green power units can be expressed as: .

[0062] In the formula, Plan to install green power units. k 1 is the adjustment factor 1, D E is the electricity demand, in 100 million kWh, α E is the growth rate of electricity demand, π green is the profit of green power enterprises, in yuan / 100 million kWh, T green is the average utilization hours of green power units, in hours; In the formula, r TGC is the revenue of green electricity enterprises in the green electricity market, in RMB / 100 million kWh. r E green It is the income of green power enterprises in the electric energy market, in RMB / 100 million kWh; c green It is the cost of green electricity enterprises, in Yuan / 100 million kWh.

[0063] New installation of green power units is the delay function of the planned installation of green power units, as shown in the following formula: In the formula, t green is the construction time of the green power unit, in months.

[0064] Green power units under construction Cumulative installed capacity of green power units They can be expressed as: In the formula, and They are respectively the initial values ​​of the green power units under construction and the cumulative installed capacity of green power units, in billion kW.

[0065] Green power generation Q green Green power unit grid-connected power Can be expressed as: In the formula, β green is the power consumption rate of green power units.

[0066] 2. Construct the stock-flow diagram of the thermal power enterprise module and draw the stock-flow diagram of the thermal power enterprise module, such as Figure 4 shown.

[0067] The stock includes the installed capacity of thermal power units under construction and the cumulative installed capacity of thermal power units, and the flow includes the planned installed capacity of thermal power units and the newly installed capacity of thermal power units. Since thermal power companies have to participate in the ancillary service market, thermal power units will reduce part of their power generation to obtain ancillary service benefits.

[0068] In this module, the functional relationships are similar to those in the green electricity enterprise module, as shown below: In the formula, k 2 is the adjustment factor 2; π thermal is the profit of thermal power enterprises, in yuan / 100 million kWh; T thermal is the average utilization hours of thermal power units, in h; , , and They are the planned installed capacity of thermal power units, the newly added installed capacity of thermal power units, the installed capacity of thermal power units under construction and the cumulative installed capacity of thermal power units, in billion kW; r aux It is the income of thermal power enterprises in the auxiliary service market, in RMB / 100 million kWh; It is the income of thermal power enterprises in the electric energy market, in yuan / 100 million kWh; c thermal is the cost of thermal power enterprises, in yuan / 100 million kWh; Q thermal and They are the power generation and grid-connected power of thermal power units, in billion kWh; β thermal is the power consumption rate of thermal power units.

[0069] 3. Construct the stock-flow diagram of the green certificate market module and draw the stock-flow diagram of the green certificate market module, such as Figure 5 shown.

[0070] In the green certificate market module, the stock is the number of valid green certificates held by green power companies, the cumulative number of green certificates sold by green power companies, the change in green certificate prices and the RPS index. The flow is the number of green certificates issued to green power companies, the sales volume of green certificates, the net demand for green certificates and the growth rate of the RPS index. The green certificates issued to green power companies are determined by the power generation of green power units. A part of the green certificates are transferred to electricity users through green power transactions, and the remaining green certificates can be sold in the green certificate market during the validity period. The sales volume of green certificates includes green certificates sold to individual consumers and green certificates sold to RPS responsible companies. The number of green certificates purchased by individual consumers is determined by the demand function, and the number of green certificates purchased by RPS responsible companies is the number of green certificates corresponding to the RPS index. The net demand for green certificates will affect the price of green certificates, and thus affect the revenue of green power companies in the green certificate market. The number of green certificates issued to green power companies G issue It can be expressed as: .

[0071] In the formula, γ It is the electricity-green certificate conversion coefficient, and the unit is per 100 million kWh.

[0072] Number of valid green certificates held by green power companies G valid It can be expressed as: In the formula, G 0 valid It is the initial value of the number of valid green certificates held by green power enterprises, in units; G trans It is the number of green certificates transferred out by green power enterprises through green power trading, in pieces; G invalid The number of expired green certificates, in pieces; G sell The number of green certificates sold, in pieces.

[0073] In the formula, α green is the proportion of green electricity trading.

[0074] In the formula, t valid It is the validity period of the green certificate in months.

[0075] In the formula, p TGC is the price of green certificate, in Yuan / piece; a , b The demand elasticity coefficient for individual consumers to purchase green certificates; I RPS It is the enterprise’s renewable energy consumption responsibility weight indicator.

[0076] Green Certificate Price p TGC Using a smoothing function: In the formula, Δ p TGC The price change of green certificates, in yuan / piece; t TGC is the delay time of the green certificate price relative to the change of the green certificate price, in months; and It is the minimum and maximum price of green certificate, in Yuan per piece.

[0077] Green certificate price change Δ p TGC It is directly related to the net demand for green certificates and can be expressed as: In the formula, Δ p 0 TGC is the initial value of the green certificate price change, in yuan / piece; k 3 is the adjustment factor 3; It represents the excess demand for green certificates, in units of pieces.

[0078] The change in green certificate price can be understood as the expected price of green certificates after the net demand for green certificates changes, but the lag of price changes is taken into account here, so there is a time difference between the green certificate price and the green certificate price change. The initial value of the green certificate price change is the initial price of the green certificate.

[0079] In this article, the following price changes or fluctuations have similar meanings.

[0080] In the formula, I 0 RPS is the initial value of the renewable energy consumption responsibility index, α RPS is the growth rate of the renewable energy consumption responsibility indicator.

[0081] Cumulative sales volume of green certificates G total It can be expressed as: .

[0082] In the formula, G 0 total The initial value of the cumulative sales volume of green certificates, in units; The income of green power enterprises in the green certificate market can be expressed as: .

[0083] 4. Construct the stock-flow diagram of the carbon market module and draw the stock-flow diagram of the carbon market module, such as Figure 6 shown.

[0084] The stock is the carbon quota held by thermal power companies, the total amount of carbon quota transactions of thermal power companies, changes in carbon prices and actual carbon emission intensity, and the flow is the carbon quota supply, carbon quota trading volume, net carbon quota demand and carbon emission intensity reduction rate. Carbon quotas are allocated according to historical carbon emissions based on the grandfather method, of which a part is auctioned carbon quotas. The increase in the auction ratio will increase the cost of thermal power companies, prompting them to strengthen investment in emission reduction and transformation. After the actual carbon emissions are reduced, thermal power companies will have surplus carbon quotas that can be traded in the carbon market, thereby increasing the profits of thermal power companies.

[0085] Supply of carbon quotas C supply It can be expressed as: .

[0086] In the formula, θ is the carbon quota tightening factor; E act is the actual carbon emission intensity of thermal power companies, in tCO 2 / 100 million kWh.

[0087] In the formula, E 0 act is the initial value of carbon emissions, in tCO 2 / 100 million kWh; α c is the carbon emission intensity reduction rate.

[0088] Thermal power companies hold carbon quotas C hold It is expressed as: In the formula, C 0 hold The initial value of thermal power and carbon quota, in tCO 2 ; C trans is the trading volume of carbon quotas, in tCO 2 , expressed as: .

[0089] Total quota trading volume of thermal power enterprises C total It can be expressed as: .

[0090] In the formula, C 0 total is the initial value of the total amount of thermal power enterprise quota trading, in tCO 2 .

[0091] Carbon price p c It can be expressed as: In the formula, Δ p c is the change in carbon price, in yuan; t c is the lag time of carbon price relative to the change of carbon price, in months; p c min p c max and are the minimum and maximum carbon prices, in yuan per piece.

[0092] In the formula, Δ p 0 c is the initial value of carbon price change, in yuan / tCO 2 ; k 4 is the adjustment factor 4; D c ex is the excess demand for carbon quota, in tCO 2 .

[0093] Costs of thermal power companies c thermal It can be expressed as: .

[0094] In the formula, is the fixed cost of thermal power companies, in yuan / 100 million kWh; ε It is the carbon emission reduction transformation intensity coefficient of thermal power enterprises; C auc Auction carbon quota, unit is tCO 2 , which can be expressed as: .

[0095] In the formula, α auc is the carbon quota auction ratio.

[0096] 5. Construct the stock-flow diagram of the electric energy market module and draw the stock-flow diagram of the electric energy market module, such as Figure 7 shown.

[0097] The stock is the change of green power price and thermal power price, and the flow is the excess demand of green power and thermal power. Both thermal power companies and green power companies participate in the electricity market, and their electricity market income is affected by the grid-connected electricity price and grid-connected electricity volume.

[0098] Green electricity price p gp It can be expressed as: In the formula, Δ p gp is the change in green electricity price, in yuan; t gp is the delay time of green electricity price relative to the change of green electricity price, in months; and It is the minimum and maximum value of green electricity price, in Yuan / 100 million kWh.

[0099] In the formula, Δ p 0 gp is the initial value of green electricity price change, in yuan / 100 million kWh; k 5 is the adjustment factor 5; It is the excess demand for green electricity, in 100 million kWh.

[0100] Green power enterprise electricity energy market The benefits can be expressed as: .

[0101] Thermal power price p tp It can be expressed as: In the formula, Δ p tp is the change in thermal power price, in yuan / 100 million kWh; t tp is the delay time of thermal power price relative to the change of thermal power price, in months; and It is the minimum and maximum value of thermal power price, in Yuan / 100 million kWh.

[0102] In the formula, Δ p 0 tp is the initial value of thermal power price change, in yuan / 100 million kWh; k 6 is the adjustment factor 6; It is the excess demand for thermal power, in billion kWh.

[0103] Thermal power enterprise electricity energy market The benefits can be expressed as: .

[0104] 6. Construct the stock-flow diagram of the auxiliary service market module. Draw the stock-flow diagram of the auxiliary service market module, such as Figure 8 shown.

[0105] In the ancillary service market module, green power companies will cause processing deviations due to their volatility, which will affect their income in the electric energy market. Therefore, green power companies act as buyers in the ancillary service market. Relatively speaking, since traditional thermal power companies have higher output controllability, they can provide services in the ancillary service market. When the deviation assessment standards of the power system are more stringent, the demand for ancillary services by green power companies will increase. At the same time, in order to improve their own flexibility to adapt to the needs of the power grid, green power companies may invest in the construction of supporting energy storage facilities or other flexible adjustment methods, which will increase the cost of green power companies.

[0106] Ancillary service prices p aux It can be expressed as: In the formula, Δ p aux is the price change of ancillary services, in Yuan / 100 million kWh; t aux is the delay time of the ancillary service price relative to the change of the ancillary service price, in months; and They are the minimum and maximum prices of ancillary services, in yuan / 100 million kWh.

[0107] In the formula, Δ p 0 aux is the initial value of the ancillary service price change, in yuan / 100 million kWh; k 7 is the adjustment factor 7; It is the excess demand for ancillary services, expressed in 100 million kWh.

[0108] Ancillary service revenue of thermal power companies r aux It can be expressed as: .

[0109] In the formula, T call The number of hours for auxiliary service calls of thermal power units, in hours; C re The auxiliary service capacity reserved for thermal power units, in billion kW.

[0110] In the formula, α re The capacity ratio of thermal power units participating in ancillary services.

[0111] Green power companies’ demand for purchasing ancillary services D aux It can be expressed as: .

[0112] In the formula, k 8 is the adjustment factor 8; θ punish It is the penalty intensity coefficient for deviation assessment; θ mod To improve the flexibility of storage and other transformation factors.

[0113] Green power enterprise costs c green It can be expressed as: .

[0114] In the formula, It is the fixed cost of green power enterprises, in billion / kWh.

[0115] Based on the above, the system dynamics simulation software Vensim is used to model, adjust parameters, and set different scenarios for simulation analysis. In step 4, set the simulation step size, simulation time and various parameters in the model; In this embodiment, the simulation step length is 1 month, the simulation duration is 120 months, and the simulation start time is the end of 2022. The main parameter settings in the model are shown in Table 1.

[0116] Adjust parameters, set different scenarios, and conduct simulation analysis on the cumulative installed capacity of green power and thermal power units.

[0117] In this embodiment, a case study is set up to study the changing trend of the cumulative installed capacity of green power and thermal power units. Fig. 9 As shown in the figure; the green power price and thermal power price were simulated and analyzed, as shown in the figure Fig.10 As shown in Figure 2, three scenarios were set up to analyze the cases where the auction ratio of carbon emission rights quota was 1%, 30% and 80%, as shown in Figure 2. Fig.11 As shown in the figure, the carbon emission quota tightening coefficient is introduced to quantify the country's regulatory strength on carbon emission limits. The smaller the coefficient value, the less initial carbon emission quota allocated to thermal power companies. Three scenarios are set to analyze the changes in carbon prices when the carbon emission quota tightening coefficients are 0.9, 0.7, and 0.5, respectively. Fig.12 As shown in the figure, three scenarios were set with annual growth rates of renewable energy consumption responsibility weight index of 0.012, 0.06 and 0.12 respectively, so as to study the changes in green certificate prices under the three scenarios, as shown in the figure. Fig.13 shown.

[0118] The present invention also proposes a modeling and analysis system for the green certificate-carbon-electricity three-market coupling system based on system dynamics to implement the above method, including: The system division module is used to determine the system boundaries, divide the green certificate-carbon-electricity market coupling system into several sub-modules, and put forward reasonable assumptions.

[0119] The causal loop diagram construction module is used to extract the key elements in each sub-module, analyze the causal relationship and hierarchical relationship between the key elements, and construct the causal loop diagram of the coupled system.

[0120] The stock-flow diagram construction module is used to construct a stock-flow diagram based on the causal loop diagram, establish equations, and describe the functional relationship between variables.

[0121] The simulation analysis module is used to use the system dynamics simulation software Vensim to build models, adjust parameters, and set different scenarios for simulation analysis.

[0122] In addition, the present invention also proposes a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above method when executing the computer program.

[0123] At the same time, the present invention also proposes a computer-readable storage medium, wherein the medium stores a computer program, and when the computer program is executed by a processor, the steps of the above method are implemented.

Claims

1. A green certificate-carbon-electricity market coupling modeling and analysis method based on system dynamics, characterized by: include: Determine the system boundaries, divide the green certificate-carbon-electricity three-market coupling system into several sub-modules, and propose reasonable assumptions; Extract the key elements in each submodule, analyze the causal relationship between the key elements, and construct a causal loop diagram of the coupled system; Construct a stock-flow diagram based on the causal loop diagram and establish equations to describe the functional relationship between variables; Use the system dynamics simulation software Vensim to build a model, adjust parameters, and set different scenarios for simulation analysis.

2. The method according to claim 1, characterized in that The submodules include: Green electricity enterprise module, thermal power enterprise module, green certificate market module, carbon market module, electricity energy market module and ancillary service market module.

3. The method according to claim 2, characterized in that Reasonable assumptions include: 1) Green power enterprises refer to wind power and photovoltaic power generation enterprises that can apply for green certificates; 2) The operation mode of the green electricity market is "certificate and electricity in one", where users can obtain green certificates when purchasing green electricity; 3) Buyers of green certificates include individual consumers and enterprises responsible for consuming renewable energy; 4) The validity period of the green certificate is 2 years. If the green certificate expires, it cannot be traded on the green certificate market.

4. The method according to claim 2, characterized in that: The key elements extracted from each sub-module include: In the green power enterprise module, key elements include green power installed capacity, green power unit power generation, green power enterprise profit, and green power enterprise flexibility transformation investment; In the thermal power enterprise module, key elements include installed capacity of thermal power units, power generation of thermal power units, profits of thermal power enterprises, and emission reduction investment of thermal power enterprises; In the green certificate market module, key elements include green certificate demand, green certificate supply, and green certificate price; In the carbon market module, key elements include carbon quota supply, carbon quota demand, and carbon price; In the electric energy market module, key elements include green power demand, green power supply, green power price, thermal power demand, thermal power supply, and thermal power price; In the ancillary service market module, key elements include green electricity penetration rate, ancillary service demand, and ancillary service price.

5. The method according to claim 4, characterized in that The causal relationships between the key elements include: 1) Green electricity demand increases → green electricity prices rise → green electricity companies increase profits → green electricity installed capacity increases → green electricity units increase power generation → green electricity supply increases → green electricity prices fall; 2) Increased demand for thermal power → increased thermal power prices → increased profits for thermal power companies → increased installed capacity of thermal power plants → increased power generation from thermal power plants → increased thermal power supply → decreased thermal power prices; 3) Increased demand for green certificates → increased prices for green certificates → increased profits for green electricity companies → increased installed capacity for green electricity generators → increased power generation for green electricity generators → increased supply of green certificates → decreased prices for green certificates; 4) Increased demand for carbon quotas → increased carbon prices → reduced profits for thermal power companies → increased investment in emission reduction by thermal power companies → reduced demand for carbon quotas → reduced carbon prices; 5) Green electricity penetration rate increases → demand for ancillary services increases → ancillary service prices rise → green electricity companies’ profits decrease → green electricity companies’ flexibility transformation investment increases → demand for ancillary services decreases → ancillary service prices decrease.

6. The method according to claim 2, characterized in that The stock-flow diagram is constructed based on the causal loop diagram, and an equation is established to describe the functional relationship between the variables, including: On the basis of the causal loop diagram, the stocks, flows, auxiliary variables and constants in each submodule are clarified; equations are established and functions are used to describe the relationship between the variables.

7. The method according to claim 1, characterized in that The method of using system dynamics simulation software Vensim to build a model, adjust parameters, and set different scenarios for simulation analysis includes: setting the simulation step size, simulation duration, and various parameters in the model, adjusting parameters, and setting different scenarios for analysis of key elements.

8. A modeling and analysis system for the green certificate-carbon-electricity market coupling system based on system dynamics, which implements the method described in any one of claims 1 to 7, characterized in that: include: The system division module is used to determine the system boundary, divide the green certificate-carbon-electricity three-market coupling system into several sub-modules, and put forward reasonable assumptions; The causal loop diagram construction module is used to extract the key elements in each submodule, analyze the causal relationship and hierarchical relationship between the key elements, and construct the causal loop diagram of the coupled system; The stock-flow diagram construction module is used to construct the stock-flow diagram based on the causal loop diagram, establish equations, and describe the functional relationship between the variables; The simulation analysis module is used to use the system dynamics simulation software Vensim to build models, adjust parameters, and set different scenarios for simulation analysis.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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