Electricity certificate carbon market price analysis method and system based on system dynamics

Abstract

The invention relates to the technical field of system dynamics, and discloses an electricity certificate carbon market price analysis method and system based on system dynamics, and the method comprises the steps: S1, determining the main body of a green certificate transaction market and the main body of a carbon emission permit transaction market, and determining a renewable energy power generation mode; s2, constructing a TCC cost control mechanism; s3, TCC cost is calculated according to a TCC cost control mechanism; s4, establishing stock flow dynamic model frames of the green certificate market and the electricity market and the carbon emission permit trading market and the electricity market, and combining the two dynamic model frames to generate an electricity certificate carbon market stock flow dynamic model frame; and S5, analyzing the electricity evidence carbon market price. The system comprises an information input unit, a mechanism construction unit, a calculation and analysis unit and a system dynamics model framework construction unit. According to the method, the system dynamics and the method for controlling and optimizing the TCC cost are combined, and the analysis accuracy and reliability are improved.

Description

Technical Field

[0001] This invention relates to the field of system dynamics technology, and in particular to a method and system for analyzing the price of electric carbon (TCC) market based on system dynamics. It combines system dynamics with methods for controlling and optimizing TCC costs to improve the accuracy and reliability of the analysis, while also paying attention to new market dynamics to adapt to the ever-changing market environment. Background Technology

[0002] The price of carbon certificates in the market constitutes a key pathway for us to deeply understand the dynamic evolution of the carbon market, and is also an important benchmark for measuring its effectiveness. The core objective of the carbon market is to promote emission reduction and lower carbon emissions through market mechanisms. As the core manifestation of market mechanism operation, market prices, with their fluctuations and changes, directly reflect the operational efficiency and achievements of the carbon market. Therefore, in-depth analysis of market prices can objectively assess the actual effectiveness of the carbon market in promoting emission reduction and accelerating green transformation. The analysis of carbon certificate prices in the market plays a crucial role in promoting the sound development of my country's carbon market.

[0003] Common methods for analyzing the relationship between electricity and carbon market prices include comparative analysis, time series analysis, multiple regression analysis, and artificial intelligence (AI) forecasting. Each method has its own characteristics and drawbacks. Comparative analysis compares historical price data from the electricity and carbon markets to find correlations. However, this method is limited by the completeness and accuracy of historical data and may not fully reflect the current situation. Time series analysis uses statistical methods to analyze time-series price data from the electricity and carbon markets to predict future price trends. However, this method lacks sensitivity to sudden market events and policy changes. Multiple regression analysis incorporates multiple influencing factors from both the electricity and carbon markets into the analytical model to explore the degree of influence of each factor on prices. However, in practice, this method may become overly complex due to too many variables, making the model difficult to interpret and apply. AI forecasting uses artificial intelligence algorithms, such as neural networks and support vector machines, to predict electricity and carbon market prices. While this method has advantages in forecasting accuracy and flexibility, it requires substantial data support and computational resources, and the model construction and parameter tuning process is quite complex.

[0004] In summary, the methods described above all have certain limitations in analyzing the relationship between electricity market and carbon market prices. To more accurately predict and analyze this relationship, this invention provides a system and method for analyzing electricity and carbon market prices based on system dynamics. This method combines system dynamics with methods for controlling and optimizing TCC costs, improving the accuracy and reliability of the analysis. It also pays attention to new market dynamics and policy changes to adapt to the ever-changing market environment. Summary of the Invention

[0005] This invention provides a method and system for analyzing the price of electric carbon certificates (TCCs) based on system dynamics. It combines system dynamics with methods for controlling and optimizing TCC costs to improve the accuracy and reliability of the analysis, while also paying attention to new market dynamics and policy changes to adapt to the ever-changing market environment.

[0006] This invention is achieved through the following technical solution: a method for analyzing the price of carbon certificates based on system dynamics, comprising the following steps: Step S1: Confirm the main players in the green certificate trading market and the carbon emission rights trading market, and at the same time confirm the renewable energy power generation methods; Step S2: Construct a TCC cost control mechanism; Step S3: Calculate the TCC cost according to the TCC cost control mechanism; Step S4: In Vensim-PLE, build stock flow dynamic model frameworks for the green certificate market and the electricity market, and carbon emission trading market and the electricity market respectively, and combine the two dynamic model frameworks to generate the stock flow dynamic model framework for the electricity certificate carbon market. Step S5: Analyze the carbon market price based on the established stock-flow dynamics model framework of the carbon certificate market and the TCC cost control mechanism. To better realize this invention, it is further confirmed that green electricity manufacturers are the main players in the green certificate trading market, and traditional energy power generation manufacturers are the main players in the carbon emission rights trading market; renewable energy power generation methods include wind power generation.

[0007] To better realize the present invention, the quota ratio is further confirmed, and when the actual renewable energy power generation ratio is greater than the prescribed quota ratio, the electricity generated by renewable energy is sold; When the actual proportion of renewable energy generation is less than the prescribed quota, but still within the penalty margin, the insufficient renewable energy generation can be purchased in the form of green certificates. When the actual proportion of renewable energy generation is insufficient and exceeds the penalty margin, it is necessary not only to purchase renewable energy electricity but also to accept the penalty mechanism.

[0008] To better realize the present invention, step S3 further includes: Step S3.1, calculate the TGC cost and express it as: ; in, denoted as TGC cost; k is the quota ratio of renewable energy generation to total grid-connected electricity, satisfying k≥15%; u is the actual proportion of renewable energy to grid-connected electricity; s is the penalty margin, expressed in the model as the margin percentage of renewable energy to total grid-connected electricity. c represents the penalty price; c represents the trading price of wind power green certificates. , These represent the on-grid electricity generated by power plants and the on-grid electricity generated by wind power within a unit of time period; Step S3.2: Calculate the on-grid electricity generated by the power plant and the on-grid electricity generated by wind power within a unit time period. , And expressed as: ; ;in, The amount of thermal power generated by a power plant and fed into the grid within a unit of time period; The reduction in CO2 emissions for each portion of renewable energy generation is a fixed value determined by the thermal power units, expressed as... , The amount of CO2 emissions indirectly reduced by renewable energy generation; Z' is the emission intensity per unit of electricity supplied, in kg / MWh; Step S3.3: Use the baseline method to initially allocate carbon allocation quotas to construct a carbon allocation quota model and obtain the allocated carbon allocation quota at time t. ; Step S3.4, calculate the carbon trading cost and express it as: ; ; in, The carbon trading cost of the system at time t; Let t be the actual carbon emissions of the system at time t; The amount of carbon offset at time t; The carbon emission intensity of the i-th unit; and These are the selling prices of the carbon allocation and carbon offset at time t, respectively. The selling price of the carbon offset for the i-th conventional unit within time period t; The purchase price of the carbon offset at time t; The planned output of the i-th conventional unit within time period t; This is the number of conventional generating units; The measurement period is 1 hour. Step S3.5, calculate the system carbon trading cost and express it as: ,in, The system's carbon trading cost is represented by T, which is the scheduling period, taken as 24 hours. Step S3.6, calculate the TCC cost, expressed as: ,in For TGC cost, For CT cost, For TCC cost.

[0009] To better realize the present invention, step S3.6 further includes: The objective function for obtaining the final TCC cost control mechanism is the function that minimizes the sum of TCC cost and other costs.

[0010] To better realize the present invention, step S4 further includes: Identify the boundaries of the dynamic model and define the assumptions. Based on the stock flow dynamics model framework of the green certificate market and the electricity market, and the carbon emission trading market and the electricity market, the main functional relationships between the two markets, namely the green certificate market and the electricity market, and the carbon emission trading market and the electricity interaction market, are obtained. Based on the main functional relationships, system boundaries, and prescribed assumptions of the two markets, the stock flow dynamics model frameworks of the green certificate market and the electricity market, and the carbon emission trading market and the electricity market are combined to form the stock flow dynamics model framework of the electricity certificate carbon market.

[0011] To better realize the present invention, step S5 further includes: By combining the TCC cost control mechanism, we analyze the market price of electric carbon certificates through data collection methods, simulation calculation methods, authenticity verification methods, and market comparison methods.

[0012] This invention also provides a system for analyzing carbon market prices based on system dynamics, comprising an information input unit, a mechanism construction unit, a calculation and analysis unit, and a system dynamics model framework construction unit, wherein: The information input unit is used to confirm the main participants in the green certificate trading market and the carbon emission rights trading market, and at the same time, to confirm the renewable energy power generation method. Mechanism building unit, used to build TCC cost control mechanism; The system dynamics model framework building unit is used to build stock flow dynamics model frameworks for the green certificate market and the electricity market, and the carbon emission trading market and the electricity market in Vensim-PLE, respectively, and combine the two dynamics model frameworks to generate the stock flow dynamics model framework for the electricity certificate carbon market. The calculation and analysis unit is used to calculate TCC costs based on the TCC cost control mechanism; and to analyze and calculate the market price of electric carbon certificates based on the established electric carbon certificate stock flow dynamics model framework combined with the TCC cost control mechanism.

[0013] The present invention also provides an electronic device comprising a processor and a memory; the processor includes the system dynamics-based carbon market price analysis system described in the second aspect above.

[0014] The present invention also provides a computer-readable storage medium comprising instructions that, when executed on an electronic device described in the third aspect, cause the electronic device to perform the method described in the first aspect.

[0015] Compared with the prior art, the present invention has the following advantages and beneficial effects: (1) This invention provides a method and system for analyzing the price of electric carbon market based on system dynamics, which combines system dynamics with the method of controlling and optimizing TCC costs to improve the accuracy and reliability of the analysis, while paying attention to new dynamics in the market to adapt to the ever-changing market environment; (2) This invention provides a method and system for analyzing the price of electricity and carbon markets based on system dynamics. It can not only deeply understand and reveal the complex dynamic relationship between the electricity market and the carbon market, but also effectively guide power companies on how to reduce overall carbon emission costs by optimizing their carbon trading strategies. It can help power companies better formulate market entry and exit strategies and optimize their carbon trading plans. Through model analysis and optimization, companies can achieve cost optimization and improve their competitiveness in the carbon market. Attached Figure Description

[0016] The present invention will be further described in conjunction with the following drawings and embodiments. All inventive concepts of the present invention should be considered as disclosed content and within the scope of protection of the present invention.

[0017] Figure 1 A flowchart of a method for analyzing carbon market prices based on system dynamics, and a method within the system, provided for embodiments of this application; Figure 2 This application provides a method for analyzing carbon market prices based on system dynamics, and a dynamic model framework for the green certificate market and the electricity market within the system. Figure 3 This application provides a method for analyzing carbon market prices based on system dynamics, and a dynamic model framework for the carbon emission rights trading market and the electricity market within the system. Figure 4 This application provides a method for analyzing the price of carbon market using electronic certificates based on system dynamics, as well as a framework for a dynamic model of the stock flow of carbon market using electronic certificates within the system. Detailed Implementation

[0018] To more clearly illustrate the technical solutions of the embodiments of the present invention, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments, and therefore should not be regarded as a limitation on the scope of protection. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "set up," "connected," and "linked" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0020] Example 1: This embodiment presents a method and system for analyzing carbon market prices based on system dynamics. The green certificate trading mechanism is a significant driving force for the development of renewable energy. It not only promotes the production and consumption of renewable energy electricity but also incentivizes the widespread application of clean energy through market mechanisms. This mechanism securitizes renewable energy generation by issuing green electricity certificates (referred to as green certificates), forming a tradable commodity certificate with unique financial attributes and environmental value.

[0021] In the green certificate trading market, supply and demand forces jointly drive its operation. When renewable energy power generation companies generate more electricity than the nationally mandated quota, they can apply for and obtain green certificates, which they can then sell on the market. Electricity consumers or companies obligated to consume renewable energy can then purchase these green certificates to meet their renewable energy consumption requirements. This trading mechanism not only provides renewable energy power generation companies with an additional source of revenue but also reduces the cost for electricity consumers to achieve their green consumption goals.

[0022] The green certificate trading market operates on the principle of market competition, with prices determined jointly by buyers and sellers. When the supply of green certificates exceeds demand, prices naturally decrease to attract more buyers; conversely, when demand exceeds supply, prices rise to encourage more power generation companies to increase renewable energy generation. This pricing mechanism effectively regulates the market's supply and demand balance, promoting the sustainable development of renewable energy.

[0023] This invention takes green electricity producers as the main players in the green certificate trading market and traditional energy power producers as the main players in the carbon emission trading market, and considers the relationship between green certificate prices, carbon prices, and the power supply and demand of each power producer.

[0024] To analyze the carbon market price for electricity certificates, this invention considers renewable energy as wind power generation, taking 24 points per day for wind power output forecasting. The forecast output value at each point, as well as the thermal power output value at each point, are defined as the average of the wind and thermal power output within that 1 hour. For example... Figure 1 The diagram shown is a flowchart of the method in this embodiment.

[0025] Example 2: This embodiment further optimizes upon embodiment 1. TCC cost, as a key manifestation of the new electricity reform energy policy on the generation side, is jointly constructed by two core elements: TGC (Green Certificate Cost) and CT (Carbon Trading) cost. The establishment of this cost structure aims to achieve seamless integration and unified operation of the TGC and CT systems through precise management of CO2 emission intensity per unit of electricity supply.

[0026] Within this framework, TGC (Total Gas Cost) not only reflects support and incentives for renewable energy power generation projects but also emphasizes the importance of environmental protection and sustainable development. CT (Constant Carbon Cost), on the other hand, directly constrains the carbon emission behavior of power generation companies, prompting them to actively adopt emission reduction measures and lower carbon intensity. Through the organic combination of TGC and CT, the TCC (Total Gas Cost) system not only provides a clear cost orientation for the power generation side but also lays a solid foundation for promoting my country's energy structure transformation and achieving green and low-carbon development. As an important component of the new electricity reform policy, TCC is ingeniously designed and rich in content, reflecting both the policymakers' profound insights into energy transformation and demonstrating the firm determination and practical actions of my country's power industry in addressing climate change and promoting sustainable development.

[0027] TCC (Total Controlled Conversion) costs consist of two main parts. The first is TGC (Tradable Green Certificate) cost, which covers all expenses incurred by power generation companies during the power production process, including fuel costs, operation and maintenance costs, and equipment depreciation. The second is CT (Connection Cost), which refers to the costs incurred by power generation companies in transmitting electricity to the grid, including the construction and maintenance costs of transmission lines and grid connection fees. TCC cost is the sum of TGC cost and CT cost.

[0028] By calculating and analyzing TCC costs, comprehensive cost control can be achieved for power generation companies, thereby promoting the power industry towards greater efficiency, cleaner emissions, and sustainability. Simultaneously, the integrated connection between TCC and CT also signifies optimization of the power generation and transmission process, helping to reduce CO2 emission intensity per unit of electricity supplied.

[0029] Under the guidance of new energy policies, my country's power industry is gradually transforming from traditional thermal power generation to clean energy power generation. The establishment of a TCC cost control mechanism and the reasonable control and optimization of TCC costs will provide strong support for this transformation.

[0030] The first stage is when the actual proportion of renewable energy generation exceeds the prescribed quota, and the electricity generated from selling renewable energy (reflected in the model as the sale of green certificates) generates profit. The second stage is when the actual proportion of renewable energy generation is less than the prescribed quota, but still within the penalty margin. At this time, it is only necessary to purchase the insufficient renewable energy generation in the form of green certificates. The third stage is when the actual proportion of renewable energy generation is seriously insufficient, exceeding the penalty margin. At this time, it is necessary not only to purchase renewable energy electricity, but also to accept the penalty mechanism.

[0031] ; In the formula: denoted as TGC cost; k is the quota ratio of renewable energy generation to total grid-connected electricity, satisfying k≥15%; u is the actual proportion of renewable energy to grid-connected electricity; s is the penalty margin, expressed in the model as the margin percentage of renewable energy to total grid-connected electricity. c represents the penalty price; c represents the trading price of wind power green certificates. , These represent the on-grid electricity generated by power plants and the on-grid electricity generated by wind power within a given time period.

[0032] , The expression is: ; ;in, This represents the amount of thermal power generated by a power plant and fed into the grid within a given time period. The CO2 emission reduction for each portion of renewable energy generation is a fixed value determined by the thermal power units, expressed as... , Z' represents the CO2 emissions indirectly reduced by renewable energy generation; Z' is the emission intensity per unit of electricity supplied, in kg / MWh. Renewable energy generation directly affects TGC costs. The unit output value considering the TGC mechanism alone is calculated using the example parameters and compared with the unit output value of traditional dispatching. The value of Z' is determined by the unit with the largest output change during the measurement period.

[0033] The carbon allocation model uses a baseline method to initially allocate carbon allocations. Taking a power generation company with a wind farm as an example, the carbon allocation at time t is... ,in: The carbon allocation obtained by the system at time t, in kg; η is the load forecast value at time t, in MW; η is the national regional carbon allocation coefficient per unit of electricity, in kg / MW.

[0034] The other parts of this embodiment are the same as those in Embodiment 1, so they will not be described again.

[0035] Example 3: This embodiment further optimizes the above embodiment 1 or 2, and calculates the carbon trading cost using the following formula: ; ; ; in, The carbon trading cost of the system at time t; Let t be the actual carbon emissions of the system at time t; The carbon emission intensity of the i-th unit; and These are the selling prices of the carbon allocation and carbon offset at time t, respectively. The purchase price of the carbon offset at time t; The planned output of the i-th conventional unit within time period t; This is the number of conventional generating units; The system's carbon trading cost is represented by T, which is the scheduling period, taken as 24 hours. The measurement period is 1 hour.

[0036] The TCC cost is the sum of the TGC cost and the CT cost, expressed as: ,in For TGC cost, For CT cost, For TCC cost.

[0037] In addition, this embodiment also considers the power generation and operation costs of thermal power units, wind curtailment costs, and the cost of purchasing reserves. Taking these costs into account, the final scheduling objective function used is the function that minimizes the sum of the TCC cost and these other costs.

[0038] The other parts of this embodiment are the same as any one of the embodiments 1-2 above, so they will not be described again.

[0039] Example 4: This embodiment further optimizes any one of embodiments 1-3 above. System dynamics is a method for studying the behavior of complex systems. Analyzing the price of the carbon market based on system dynamics requires first establishing a framework for a stock-flow dynamics model, which is then built in Vensim-PLE as follows: Figure 2 and Figure 3 The model framework shown is used to predict the impact of introducing green certificates into the electricity certificate carbon market trading mechanism on power system dispatch, and then combined with the reasonable control and optimization mechanism of the added TCC cost to analyze the electricity certificate carbon market price.

[0040] The main functional relationships between the green certificate market and the electricity market, and between the carbon emission trading market and the electricity market, are expressed as follows: ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; In the formula: For changes in the price of green certificates; The price of green certificates (RMB / MWh); This represents the initial value of the green certificate price. For green certificate requirements; The number of green certificates owned by power generation companies; Power generation companies possess initial green certificate values; Supply of green certificates; For the sale of green certificates; For the sale of carbon allowances. Carbon allowances are required for the power grid; The number of green certificates owned by the power grid; Initial values ​​for green certificates for the power grid; Submit the green certificate; For wind and solar installed capacity; This represents the initial value for wind and solar installed capacity. The construction of wind and solar power capacity has been completed; The proportion of wind and solar power generation; The quota ratio is constrained by green certificates; For electricity demand; For wind and solar energy profits; This represents the average number of hours of wind and solar power utilization. Cost of wind and solar energy; For grid connection electricity price; For wind and solar power generation; For power supply; I represents the proportion of wind and solar power installed capacity; I represents the total installed capacity. Carbon price (yuan / ton); For changes in carbon prices; This is the initial value of the carbon price; The initial value of the carbon quota required for thermal power plants by the buyer; The seller's thermal power plant needs to purchase carbon quotas; This represents the initial value of the carbon quota required for the seller's thermal power plants. For the profits of thermal power companies; This refers to the number of thermal power plants currently in operation. For carbon quota supply; This represents the initial value of the installed capacity of thermal power plants under construction. The construction of thermal power installed capacity has been completed; Net demand for carbon allowances; This refers to the amount of electricity generated by thermal power plants. For real GDP; The proportion of thermal power generation; This refers to the installed capacity of thermal power plants under construction. For thermal power installed capacity; The proportion of thermal power installed capacity; This refers to the amount of electricity generated by thermal power plants. Average utilization hours of thermal power plants (hours / year); This refers to the growth rate of electricity demand. M represents the auction quota; σ represents the total quota; and M represents the auction ratio. Carbon emission intensity; β represents the initial value of carbon emission intensity; β represents the rate of reduction in carbon emission intensity.

[0041] In the green certificate trading market, the units for variables are as follows: green certificate price is in yuan / MWh; variables related to the quantity of green certificates, electricity demand and supply, and power generation are in 100 million kWh; installed capacity is in 100 million kW; electricity price, cost, and profit settings are in yuan / kWh; average utilization time of wind and solar power is in hours; and the remaining variables are dimensionless. Carbon price is in yuan / ton; variables related to the quantity of carbon allowances are in 100 million tons; GDP is in trillions of yuan; installed capacity is in 100 million kW; thermal power generation is in 100 million kWh, and cost and profit settings are in yuan / kWh; average utilization time of thermal power is in hours; and the remaining variables are dimensionless.

[0042] To regulate green certificate prices and carbon prices, we should first establish a clear initial price setting and its fluctuation range. After setting the initial value of the green certificate price, we should define its reasonable fluctuation range. Similarly, an initial price and its fluctuation range should also be set for the carbon price. If the market price fluctuates freely within this range, the actual transaction price should be used directly; if the market price exceeds the upper limit, it should be automatically adjusted to the upper limit price; if it falls below the lower limit, it should be adjusted to the lower limit price. When constructing these constraints, we need to assume that the green certificate price is not only closely related to its own price changes and initial value, but also always remains within the preset upper and lower limits. Similarly, the carbon price should also follow this principle, always fluctuating within its specific upper and lower limit range. Furthermore, carbon price changes are not only affected by its own price changes, but also by the combined effects of multiple factors such as electricity price fluctuations, auction quota allocation, and the initial carbon price. In the initial stage of renewable energy policy implementation, wind power and photovoltaic power generation account for a relatively small proportion; therefore, we can temporarily ignore the direct impact of electricity price fluctuations on them. However, thermal power generation, as the main source of current electricity supply, is significantly affected by fluctuations in the market prices of raw materials such as coal. Therefore, fully considering electricity price fluctuations when formulating the carbon price formula will be closer to reality.

[0043] The other parts of this embodiment are the same as any one of the embodiments 1-3 above, so they will not be described again.

[0044] Example 5: This embodiment is a further optimization based on any one of embodiments 1-4 above, and... Figure 2 and Figure 3 The model is integrated based on the main functional relationships, boundaries, and specified assumptions to generate, as shown below. Figure 4 The above illustrates the framework of the stock-flow dynamics model for the electric carbon market. The main functional relationships within this framework are expressed as follows: ; ; ; ; ; ; ; ; ; ; ; ; ; in, For grid connection electricity price; This is the initial value of the grid connection electricity price; For price changes; For actual power supply; This refers to the installed capacity of hydropower projects under construction. For hydropower profits; This refers to the average number of hours of hydropower utilization. The construction of hydropower installed capacity has been completed; The proportion of hydropower generation; The proportion of hydropower installed capacity; The proportion of renewable energy generation; The proportion of installed capacity for renewable energy power generation; Hydropower generation; γ represents the installed capacity of hydropower; γ represents the transmission power loss. ε represents the initial value of GDP; ε is the annual GDP growth rate. The units of variables not mentioned in the energy certificate carbon market stock flow dynamics model framework are as follows: hydropower installed capacity is in 100 million kW; hydropower generation is in kWh; profit is set in yuan / kWh; the remaining variables are dimensionless.

[0045] Ultimately, we comprehensively applied the TCC cost control mechanism, relying on data collection, precise calculation, rigorous verification of authenticity, and extensive market comparison to conduct a comprehensive and in-depth analysis of the carbon market price for electric carbon certificates.

[0046] The other parts of this embodiment are the same as any one of the embodiments 1-4 above, so they will not be described again.

[0047] Example 6: This invention also provides a system dynamics-based carbon market price analysis system that matches the method, including an information input unit, a mechanism construction unit, a calculation and analysis unit, and a system dynamics model framework construction unit.

[0048] The present invention also provides an electronic device comprising a processor and a memory; the processor includes the aforementioned system dynamics-based carbon market price analysis system described above.

[0049] Example 7: The present invention also provides a computer-readable storage medium comprising instructions; when the instructions are executed on the electronic device described in the above embodiments, the electronic device causes the electronic device to perform the methods described in the above embodiments. Optionally, the computer-readable storage medium may be a memory.

[0050] The processor involved in the embodiments of this application can be a chip. For example, it can be a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), a system on chip (SoC), a central processor unit (CPU), a network processor (NP), a digital signal processor (DSP), a microcontroller unit (MCU), a programmable logic device (PLD), or other integrated chips.

[0051] The memory involved in the embodiments of this application can be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous linked dynamic random access memory (SLDRAM), and direct memory bus RAM (DR RAM). It should be noted that the memory used in the systems and methods described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0052] It should be understood that in the various embodiments of this application, the order of the above-mentioned processes does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0053] Those skilled in the art will recognize that the modules and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0054] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and modules described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0055] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or modules may be electrical, mechanical, or other forms.

[0056] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; that is, they may be located on one device or distributed across multiple devices. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0057] In addition, the functional modules in the various embodiments of this application can be integrated into one device, or each module can exist physically separately, or two or more modules can be integrated into one device.

[0058] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented using software programs, implementation can be, in whole or in part, in the form of a computer program product. This computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium accessible to a computer or a data storage device containing one or more servers, data centers, etc., that can be integrated with the medium. The available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media (e.g., solid-state drives (SSDs)).

[0059] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Any simple modifications or equivalent changes made to the above embodiments based on the technical essence of the present invention shall fall within the protection scope of the present invention.

Claims

1. A method for analyzing the market price of carbon certificates based on system dynamics, characterized in that, Includes the following steps: Step S1: Confirm the main players in the green certificate trading market and the carbon emission rights trading market, and at the same time confirm the renewable energy power generation methods; Step S2: Construct a TCC cost control mechanism; Step S3: Calculate the TCC cost according to the TCC cost control mechanism; Step S4: In Vensim-PLE, build stock flow dynamic model frameworks for the green certificate market and the electricity market, and carbon emission trading market and the electricity market respectively, and combine the two dynamic model frameworks to generate the stock flow dynamic model framework for the electricity certificate carbon market. Step S5: Analyze the carbon market price based on the established carbon market stock flow dynamics model framework and the TCC cost control mechanism.

2. The method for analyzing carbon market prices based on system dynamics according to claim 1, characterized in that, Step S1 includes: Green energy producers are confirmed as the main players in the green certificate trading market, while traditional energy power generation producers are confirmed as the main players in the carbon emission trading market. The renewable energy generation methods include wind power generation.

3. The method for analyzing carbon market prices based on system dynamics according to claim 1, characterized in that, Step S2 includes: Confirm the quota ratio; when the actual renewable energy power generation ratio exceeds the prescribed quota ratio, sell the electricity generated by renewable energy. When the actual proportion of renewable energy generation is less than the prescribed quota, but still within the penalty margin, the insufficient renewable energy generation can be purchased in the form of green certificates. When the actual proportion of renewable energy generation is insufficient and exceeds the penalty margin, it is necessary not only to purchase renewable energy electricity but also to accept the penalty mechanism.

4. The method for analyzing carbon market prices based on system dynamics according to claim 1, characterized in that, Step S3 includes: Step S3.1, calculate the TGC cost and express it as: in, denoted as TGC cost; k is the quota ratio of renewable energy generation to total grid-connected electricity, satisfying k≥15%; u is the actual proportion of renewable energy to grid-connected electricity; s is the penalty margin, expressed in the model as the margin percentage of renewable energy to total grid-connected electricity. c represents the penalty price; c represents the trading price of wind power green certificates. , These represent the on-grid electricity generated by power plants and the on-grid electricity generated by wind power within a unit of time period; Step S3.2: Calculate the on-grid electricity generated by the power plant and the on-grid electricity generated by wind power within a unit time period. , And expressed as: ; ;in, The amount of thermal power generated by a power plant and fed into the grid within a unit of time period; The reduction in CO2 emissions for each portion of renewable energy generation is a fixed value determined by the thermal power units, expressed as... , The amount of CO2 emissions indirectly reduced by renewable energy generation; Z' is the emission intensity per unit of electricity supplied, in kg / MWh; Step S3.3: Use the baseline method to initially allocate carbon allocation quotas to construct a carbon allocation quota model and obtain the allocated carbon allocation quota at time t. ; Step S3.4, calculate the carbon trading cost and express it as: ； in, The carbon trading cost of the system at time t; Let t be the actual carbon emissions of the system at time t; The carbon offset amount at time t; The carbon emission intensity of the i-th unit; and These are the selling prices of the carbon allocation and carbon offset at time t, respectively. The selling price of the carbon offset for the i-th conventional unit within time period t; The purchase price of the carbon offset at time t; The planned output of the i-th conventional unit within time period t; This is the number of conventional generating units; The measurement period is 1 hour. Step S3.5, calculate the system carbon trading cost and express it as: ,in, The system's carbon trading cost is represented by T, which is the scheduling period, taken as 24 hours. Step S3.6, calculate the TCC cost, expressed as: ,in For TGC cost, For CT cost, For TCC cost.

5. The method for analyzing carbon market prices based on system dynamics according to claim 4, characterized in that, Step S3.6 includes: The objective function for obtaining the final TCC cost control mechanism is the function that minimizes the sum of TCC cost and other costs.

6. The method for analyzing carbon market prices based on system dynamics according to claim 1, characterized in that, Step S4 includes: Identify the boundaries of the dynamic model and define the assumptions. Based on the stock flow dynamics model framework of the green certificate market and the electricity market, and the carbon emission trading market and the electricity market, the main functional relationships between the two markets, namely the green certificate market and the electricity market, and the carbon emission trading market and the electricity interaction market, are obtained. Based on the main functional relationships of the two markets, the system boundaries, and the prescribed assumptions, the stock flow dynamics model frameworks of the green certificate market and the electricity market, and the carbon emission trading market and the electricity market are combined to form the stock flow dynamics model framework of the electricity certificate carbon market.

7. The method for analyzing carbon market prices based on system dynamics according to claim 1, characterized in that, Step S5 includes: The TCC cost control mechanism is combined with data collection methods, simulation calculation methods, authenticity verification methods, and market comparison methods to analyze the market price of electric carbon certificates.

8. A system for analyzing carbon market prices based on system dynamics, characterized in that, It includes an information input unit, a mechanism construction unit, a computational analysis unit, and a system dynamics model framework construction unit, among which: The information input unit is used to confirm the main participants in the green certificate trading market and the carbon emission rights trading market, and at the same time, to confirm the renewable energy power generation method. Mechanism building unit, used to build TCC cost control mechanism; The system dynamics model framework building unit is used to build stock flow dynamics model frameworks for the green certificate market and the electricity market, and the carbon emission trading market and the electricity market in Vensim-PLE, respectively, and combine the two dynamics model frameworks to generate the stock flow dynamics model framework for the electricity certificate carbon market. The calculation and analysis unit is used to calculate the TCC cost according to the TCC cost control mechanism; and to analyze and calculate the carbon market price of the electric carbon certificate based on the established carbon market stock flow dynamics model framework combined with the TCC cost control mechanism.

9. An electronic device, characterized in that, It includes a processor and a memory; the processor includes the electronic carbon market price analysis system based on system dynamics as described in claim 8.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes instructions that, when executed on the electronic device as claimed in claim 9, cause the electronic device to perform the method as claimed in any one of claims 1-7.

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