Carbon border regulation mechanism-oriented multi-energy collaborative optimization transaction and scheduling system

Abstract

The invention relates to a multi-energy collaborative optimization transaction and scheduling system for a carbon border regulation mechanism, and the system comprises a carbon potential distribution unit which is used for generating a carbon potential curve based on a scheduling period, and distributing green certificate resources on the hour scale according to the carbon potential; the joint transaction unit is used for constructing a carbon transaction and green certificate cooperation mechanism and realizing deduction of the green certificate on the carbon emission; the electricity-to-gas system is used for converting electric energy into hydrogen and methane and generating gas energy capable of being counted into a green certificate; the response control unit is used for adjusting user load behaviors based on the carbon weight parameters and controlling response behaviors of transferable and replaceable loads in the high carbon emission period; and the cooperative scheduling unit comprises a master-slave game model and a cooperative game model which are respectively used for PIES endogenous load interaction and multi-PIES carbon transaction cooperation. The method can solve the problems that the carbon market and the green certificate market are separated and a cooperation mechanism is lacked.

Description

Technical Field

[0001] This invention belongs to the field of modeling technology based on multi-type coupled trading data of "electricity-carbon-green certificates", and relates to a multi-energy collaborative optimization trading and scheduling system, especially a multi-energy collaborative optimization trading and scheduling system for carbon border adjustment mechanism. Background Technology

[0002] Against the backdrop of current international trade and energy transition, the implementation of the Carbon Border Adjustment Mechanism (CBAM) has placed higher carbon compliance requirements on export-oriented industrial parks. To address this pressure, carbon trading markets and green certificate markets have gradually become important avenues for enterprises to achieve emission reductions and lower compliance costs. Currently, carbon trading (CET) and green certificate trading (GCT) operate separately, their role being to support carbon emission reductions through carbon emission allowances and green certificate credits. However, these two types of markets largely operate independently, lacking effective coordination mechanisms, resulting in their potential for fully realizing carbon emission reductions and mitigating CBAM costs.

[0003] Existing green certificate trading mechanisms generally use monthly or annual quotas for offsetting emissions, but this coarse-grained approach is difficult to match hourly carbon emission characteristics. For companies in industrial parks with significant fluctuations in energy consumption, green certificates cannot accurately cover peak hourly carbon emission periods, resulting in low resource utilization efficiency and failing to maximize the value of green electricity.

[0004] Furthermore, while power-to-gas (P2G) technology is considered an effective means to improve renewable energy consumption and achieve carbon emission reduction, it has not yet been systematically incorporated into the carbon and green certificate trading system in existing pathways for addressing CBAM (Consumer-Based Energy Management). Consequently, hydrogen energy utilization strategies are disconnected from carbon compliance measures, failing to create a synergistic effect and limiting their practical application value in the park's energy system.

[0005] In terms of load-side management, existing demand response strategies primarily aim to reduce energy costs, lacking consideration for carbon emission sensitivity. Most optimization models fail to incorporate carbon weight parameters, hindering precise control during periods of high CBAM (Consumer-Based Energy Management) sensitivity. This results in a lack of flexible adjustments to energy consumption behavior under carbon constraints, thus weakening the effectiveness of international carbon compliance policies.

[0006] In summary, existing technologies have shortcomings in the coordination of carbon market and green certificate market, the refinement of green certificate trading, P2G system coupling, and the design of carbon constraint for demand response. There is an urgent need for a multi-energy collaborative optimization trading and scheduling system that can achieve energy and market synergy and is oriented towards carbon border regulation mechanism, so as to improve the carbon compliance capability and energy cost optimization level of enterprises in the park under the CBAM background.

[0007] A search revealed no prior art patents that are identical or similar to this invention. Summary of the Invention

[0008] This invention addresses the shortcomings of existing technologies by proposing a multi-energy collaborative optimization trading and scheduling system oriented towards carbon border regulation mechanisms. This system can solve the problems of the separation between the carbon market and the green certificate market and the lack of a collaborative mechanism.

[0009] The above-mentioned objective of this invention is achieved through the following technical solution: A multi-energy collaborative optimization trading and scheduling system for carbon border regulation mechanisms includes: The carbon potential allocation unit is used to generate carbon potential curves based on the scheduling cycle and allocate green certificate resources on an hourly scale according to carbon potential. The joint trading unit is used to build a collaborative mechanism between carbon trading and green certificates, enabling green certificates to offset carbon emissions. Electricity-to-gas systems are used to convert electrical energy into hydrogen and methane, generating gaseous energy that can be counted for green certificates. The response control unit is used to adjust user load behavior based on carbon weight parameters and control the response behavior of transferable and alternative loads during periods of high carbon emissions. The collaborative scheduling unit includes a master-slave game model and a cooperative game model, which are used for PIES endogenous load interaction and multi-PIES carbon trading collaboration, respectively.

[0010] Moreover, the carbon potential allocation unit includes a carbon potential calculation module and a green certificate time sequence allocation module; The carbon potential calculation module is used to generate hourly carbon potential curves based on energy consumption and emission factors; the green certificate time sequence allocation module is used to prioritize the allocation of green certificates to scheduling periods with high carbon potential. Energy-consuming enterprises follow the green certificate market trading rules and allocate the green electricity corresponding to the purchased green certificates hourly based on the differences in carbon potential at different times. The calculation formula of the carbon potential calculation module is as follows:

[0011] in: Let n be the carbon potential of node n in time period t; Let n be the power of the line (k→n); P represents the carbon potential of the upstream node k; g,t The generating capacity of unit g The source carbon potential of unit g is given; and the carbon potential curve is obtained based on the real-time carbon potential over 24 hours. The calculation formula for the green certificate time-series allocation module is as follows:

[0012] The constraints are:

[0013] The carbon emission credit is:

[0014] in: The number of green certificates allocated for time period t; Let be the carbon potential for time period t; To determine the total number of green certificates to be issued daily; The amount of CO2 deducted per green certificate (0.8042 tCO2 / certificate); The amount of CO2 emissions deducted for each period; high-carbon periods are identified and green certificates are allocated based on a comparison of the real-time number of green certificates and the amount of carbon emission deductions. Furthermore, the joint trading unit includes a green certificate mapping module, which is used to convert the renewable electricity corresponding to the green certificate into deductible carbon emissions according to a unified conversion factor. The processing method is as follows: By using green certificates to offset carbon emissions, the cost of carbon border adjustment mechanisms can be reduced. The formula is as follows:

[0015] in: For the number of green certificates; The amount of CO2 emissions that can be deducted for each green certificate; E c Total carbon emissions; For EU and domestic carbon prices; This is the adjusted CBAM cost.

[0016] Moreover, the electro-gas system includes: an electrolysis unit, a fuel cell unit, and a conversion unit. The electrolysis unit is used to produce hydrogen by electrolyzing water. The fuel cell unit is used to convert hydrogen into electrical energy and heat energy. The conversion unit includes a methane reactor for synthesizing methane from hydrogen and carbon dioxide, and the methane is included in the green certificate through a green gas certification mechanism. The hydrogen production formula of the electrolysis unit is as follows:

[0017] in: This represents the electrical power consumed during time period t. The volume or mass of hydrogen produced during time period t; The electro-hydrogen conversion efficiency of the electrolyzer is given.

[0018] The formula for synthesizing methane in the conversion unit is as follows:

[0019] in: The volume of methane produced during time period t; The amount of hydrogen gas introduced into the methanation reaction during time period t; The efficiency of the methanation reaction.

[0020] The hydrogen power generation formula of the fuel cell unit is as follows:

[0021] in: Let t be the electrical power output of the fuel cell during time period t; The amount of hydrogen consumed by the fuel cell during time period t; This refers to the hydrogen-to-electricity conversion efficiency of a fuel cell.

[0022] Its operational constraints are:

[0023] in: This represents the actual electrical power input to the electrolytic cell during time period t; This indicates the rated maximum input power of the electrolytic cell; This represents the flow rate of hydrogen supplied to the methanation reaction unit during time period t. This indicates the maximum hydrogen flow rate that the methanation unit can handle; This represents the flow rate of hydrogen delivered to the fuel cell during time period t. This indicates the rated maximum hydrogen consumption rate of the fuel cell.

[0024] The hydrogen balance constraint is:

[0025] in: This represents the total hydrogen production of the electrolyzer during time period t; This indicates hydrogen gas destined for the methanation unit; This indicates hydrogen destined for a fuel cell; This indicates the flow rate of hydrogen entering or leaving the hydrogen storage device during time period t. The green gas energy produced by the power-to-gas system is quantified and converted into green certificates that can be traded on the market and are internationally recognized. This provides a basis for enterprises to deduct carbon emissions and reduce CBAM costs. The calculation formula is as follows:

[0026] in: β represents the total energy of green gas produced by the P2G system; β is the gas calorific value conversion coefficient. The number of green certificates available through the P2G system; This represents the CO2 emission reduction corresponding to a single green certificate.

[0027] Furthermore, the response control unit includes a carbon weight analysis module and a load adjustment module. The carbon weight analysis module is used to adjust user load behavior through carbon price; the load adjustment module dynamically adjusts the transferable and reduceable loads according to the load change to avoid high carbon emission periods or realize gas-electricity substitution. The carbon weight analysis module calculates the real-time carbon price based on the changes in the carbon potential curve and the conversion coefficient, thereby affecting the user's load usage. The relationship between carbon price and carbon potential is as follows:

[0028] Where: κ is the conversion coefficient from carbon potential to carbon valence; Carbon potential curves for each time period; The carbon weight parameter is used; the resulting carbon weight is used in the next stage of load adjustment.

[0029] The objective function for minimizing the total cost of the load regulation module's impact on user load based on carbon weight parameters is:

[0030] in: Time-of-use pricing for electricity / gas / heat; , , Initial electrical / gas / heat load values; , , This represents the load variation over different time periods; The optimized total cost of ownership for users; This is due to external carbon cost pressures. (This is the target for load adjustment; the specific adjustment formula is as follows, and the variables below correspond to the above formula.) The formula for adjusting transferable loads in the load adjustment module is as follows:

[0031] in: The maximum transferable proportion of electrical / gas / heat load; , For the amount transferred and the amount reduced.

[0032] The formula for load reduction regulation in the load regulation module is as follows:

[0033] in: , This refers to the amount of load transferred and the amount of load reduced. (Based on the goal of minimizing costs, the above two types of loads are dynamically adjusted.) Moreover, the collaborative scheduling unit includes a master-slave game module and a cooperative game module; The master-slave game module is used to perform optimized scheduling from both sides of a single PIES source load. The specific method is as follows: First, carbon and electricity prices are set and green certificate trading is conducted based on the electricity-carbon-green certificate synergistic coupling mechanism. The trading volume and price are determined through the Nash bargaining model. At the electricity, carbon emission, and green certificate levels, energy operators participate in the day-ahead and real-time market electricity purchase plans, as well as the carbon emission market and green certificate market, in order to meet the assessment requirements for carbon emissions and green certificates.

[0034] Then, with the goal of maximizing returns under multiple market mechanisms, and considering the changes in green certificate transaction costs with supply and demand, the calculation formula is as follows:

[0035] in: Supply and demand of green certificates; The base number of green certificates; Δl is the change. Costs associated with green certificate transactions.

[0036] The goal on the source side is to minimize overall operating costs and influence user behavior by setting electricity prices and carbon prices. The objective function is as follows:

[0037] in: Cost of purchasing electricity from the upper-level power grid; To cover the cost of selling electricity to the higher-level power grid; Carbon penalty costs; For green certificate transaction costs; For PIES-based electricity trading.

[0038] The load side receives energy and carbon prices from the source side and adjusts its load curve to minimize its total energy cost. The objective function is as follows:

[0039] in: In response to the control unit; Cost of CBAM; Cost of green certificates for users.

[0040] Moreover, the cooperative game module is used to process the trading of electricity and carbon quotas between multiple PIES in the form of an alliance, so as to achieve Pareto improvement of the region as a whole. Multiple PIES form a consortium I, which facilitates electricity trading among PIES. Carbon quota trading between PIES The goal is to minimize the total cost of the alliance; the objective function is as follows:

[0041] in, This is the cost PIES incurs after participating in the collaborative transaction, which already includes transaction costs. and .

[0042] The advantages and beneficial effects of this invention are as follows: This invention proposes a multi-energy collaborative optimization trading and scheduling system for carbon border adjustment mechanisms. Addressing the disconnect between the carbon market and the green certificate market and the lack of a collaborative mechanism, it constructs a joint trading model for mutual recognition of carbon and green certificates. This model clarifies that green certificates can be used for carbon emission deductions and establishes a logical connection with the CBAM accounting system, enabling the coordinated management of carbon resources and green electricity resources, thus improving deduction efficiency and system flexibility. Furthermore, it addresses the issue of excessively coarse granularity in green certificate deductions, which cannot cope with hourly carbon emission fluctuations. Existing green certificate mechanisms are mostly based on monthly or annual quota settlements, failing to accurately match enterprises' hourly carbon emission peaks, resulting in low green certificate resource utilization efficiency. A "carbon potential curve" model is introduced to model hourly carbon emission pressure, and green certificates are dynamically allocated hourly according to carbon potential ratios, prioritizing their use during high-carbon emission periods to achieve precise hourly green certificate deductions and maximize their carbon reduction benefits. Addressing the issue of P2G systems not being integrated into the CBAM (Consumer-to-Age Allocation) system and the lack of closed-loop design in hydrogen energy utilization, a three-stage P2G system is constructed, consisting of an electrolyzer (EL), a hydrogen fuel cell (HFC), and a methane reactor (MR). This system achieves a closed-loop conversion of energy and carbon flow, including hydrogen production, hydrogen power generation, and carbon dioxide to methane synthesis, generating green gas energy that can be used for green certificate accounting, while simultaneously enhancing the carbon sequestration capacity within the park. Regarding demand response mechanisms... To address the issues of insufficient consideration of carbon emission sensitivity and a singular strategic objective, a carbon-sensitive demand response mechanism is designed. This mechanism introduces a "carbon weight" parameter to drive the response strategy, combining it with transferable and substitutable load modeling to enable energy users to proactively avoid high-carbon emission periods, release green certificate resources, and enhance carbon compliance capabilities. Furthermore, to address the lack of a unified market and dispatch structure for multi-energy systems at the park level, a two-tier optimization architecture is constructed. The upper layer implements a multi-market pricing linkage strategy combining Nash negotiation and master-slave game theory, while the lower layer executes joint optimization dispatch of multiple energy systems, achieving an integrated "source-load-market-government" response path that balances economic efficiency, carbon emission reduction, and market adaptability. Through the implementation of this invention, the carbon cost of CBAM is significantly reduced. In typical industrial park scenarios, the carbon cost of CBAM can be reduced by up to 70.5%, effectively alleviating the carbon compliance pressure on export enterprises. The efficiency of new energy consumption is significantly improved. With the synergistic effect of demand response and P2G, the wind curtailment rate is reduced by 100%, and the green electricity load utilization rate increases by more than 20%, making full use of renewable energy. The total energy cost is reduced. After coupling the green certificate and carbon market trading strategy, the total energy consumption cost is reduced by 18%, including a reduction in energy purchase cost and operation and maintenance cost. The utilization rate of green certificate resources is improved. The hourly allocation strategy increases the value of the original green certificate by about 1.5 times, achieving the maximum matching of peak carbon prices with the value of green electricity. The carbon sequestration capacity of the system is improved. Through the CH4 synthesis path of P2G, 20.1% of the total internal CO2 emissions can be sequestered, while reducing gas purchase costs and forming a virtuous cycle of energy. Attached Figure Description

[0043] Figure 1 This is a flowchart of the synergistic coupling mechanism of electricity, carbon, and green certificates; Figure 2 This is a flowchart of a multi-energy collaborative optimization trading and scheduling system. Detailed Implementation

[0044] The embodiments of the present invention will be further described in detail below with reference to the accompanying drawings: A multi-energy collaborative optimization trading and scheduling system for carbon border regulation mechanisms includes: The carbon potential allocation unit is used to generate carbon potential curves based on the scheduling cycle and allocate green certificate resources on an hourly scale according to carbon potential. The joint trading unit is used to build a collaborative mechanism between carbon trading and green certificates, enabling green certificates to offset carbon emissions. Electricity-to-gas systems are used to convert electrical energy into hydrogen and methane, generating gaseous energy that can be counted for green certificates. The response control unit is used to adjust user load behavior based on carbon weight parameters and control the response behavior of transferable and alternative loads during periods of high carbon emissions. The collaborative scheduling unit includes a master-slave game model and a cooperative game model, which are used for PIES endogenous load interaction and multi-PIES carbon trading collaboration, respectively.

[0045] In this embodiment, the joint trading unit includes a green certificate mapping module, which is used to convert the renewable electricity corresponding to the green certificate into deductible carbon emissions according to a unified conversion factor; The processing flow is as follows: By using green certificates (GCs) to offset carbon emissions, the cost of the Carbon Border Adjustment Mechanism (CBAM) can be reduced. The formula is as follows:

[0046] in: For the number of green certificates; The amount of CO2 emissions that can be deducted per green certificate (valued at 0.8042 tCO2 / certificate); E c Total carbon emissions; For EU and domestic carbon prices; This is the adjusted CBAM cost.

[0047] Green certificates will be allocated based on carbon intensity for different time periods, with more green certificates allocated to periods of higher carbon intensity, in order to achieve more accurate carbon emission deductions.

[0048] in: The number of green certificates allocated for time period t; Let be the carbon potential for time period t; The number of green certificates allocated for each time period.

[0049] Construct a coordinated trading mechanism for electricity, carbon, and green certificates, using the Nash bargaining model to determine trading volume and price, and considering the changes in green certificate trading costs due to supply and demand:

[0050] in: Supply and demand of green certificates; The base number of green certificates; Δl is the change. Costs associated with green certificate transactions.

[0051] In this embodiment, the carbon potential allocation unit includes a carbon potential calculation module and a green certificate time-series allocation module; the carbon potential calculation module is used to generate an hourly carbon potential curve based on energy consumption and emission factors; the green certificate time-series allocation module is used to prioritize the allocation of green certificates to scheduling periods with high carbon potential. This invention is a user-side green certificate allocation strategy based on carbon potential response, with energy-consuming enterprises as the decision-making body. That is, energy-consuming enterprises follow the green certificate market trading rules and allocate the green electricity corresponding to the purchased green certificates hourly based on the difference in carbon potential at different times.

[0052] The calculation formula of the carbon potential calculation module is as follows:

[0053] in: Let n be the carbon potential of node n in time period t; Let n be the power of the line (k→n); P represents the carbon potential of the upstream node k; g,t The generating capacity of unit g Let g be the source carbon potential of unit g. The carbon potential curve is derived based on the 24-hour real-time carbon potential.

[0054] The calculation formula for the green certificate time-series allocation module is as follows:

[0055] The constraints are:

[0056] The carbon emission credit is:

[0057] in: The number of green certificates allocated for time period t; Let be the carbon potential for time period t; To determine the total number of green certificates to be issued daily; The amount of CO2 deducted per green certificate (0.8042 tCO2 / certificate); This represents the CO2 emissions deducted for each time period.

[0058] On the PIES source side, carbon prices need to be set based on the carbon emission responsibilities that users bear for their energy consumption, in order to guide users to adopt cleaner and more environmentally friendly energy consumption methods. In order to quantify the carbon emissions of each user more precisely, carbon emission flow models of electrical, gas, and heat energy subsystems and energy coupling equipment were established in the previous research work.

[0059] In this embodiment, the joint trading unit includes a green certificate mapping module, which is used to convert the renewable electricity corresponding to the green certificate into deductible carbon emissions according to a unified conversion factor; The processing method is as follows: By using green certificates (GCs) to offset carbon emissions, the cost of the Carbon Border Adjustment Mechanism (CBAM) can be reduced. The formula is as follows:

[0060] in: For the number of green certificates; The amount of CO2 emissions that can be deducted per green certificate (valued at 0.8042 tCO2 / certificate); E c Total carbon emissions; For EU and domestic carbon prices; This is the adjusted CBAM cost.

[0061] In this embodiment, the electro-gas conversion system includes an electrolysis unit, a fuel cell unit, and a conversion unit. The electrolysis unit is used to produce hydrogen by electrolyzing water. The fuel cell unit is used to convert hydrogen into electrical energy and thermal energy. The conversion unit includes a methane reactor for synthesizing methane from hydrogen and carbon dioxide, and the methane is included in the green certificate through a green gas certification mechanism.

[0062] This module, as a key coupling device in PIES, realizes the conversion of electrical energy into gas energy, and the green gas it produces can be used to apply for a green certificate for its owner.

[0063] The formula for the electrolysis unit (hydrogen production) is as follows:

[0064] in: This represents the electrical power consumed during time period t. The volume or mass of hydrogen produced during time period t; The electro-hydrogen conversion efficiency of the electrolyzer is given.

[0065] The formula for the conversion unit (methane synthesis) is as follows:

[0066] in: The volume of methane produced during time period t; The amount of hydrogen gas introduced into the methanation reaction during time period t; The efficiency of the methanation reaction.

[0067] The formula for the fuel cell unit (hydrogen power generation) is as follows:

[0068] in: Let t be the electrical power output of the fuel cell during time period t; The amount of hydrogen consumed by the fuel cell during time period t; This refers to the hydrogen-to-electricity conversion efficiency of a fuel cell.

[0069] Its operational constraints are:

[0070] in: This represents the actual electrical power input to the electrolytic cell during time period t; This indicates the rated maximum input power of the electrolytic cell; This represents the flow rate of hydrogen supplied to the methanation reaction unit during time period t. This indicates the maximum hydrogen flow rate that the methanation unit can handle; This represents the flow rate of hydrogen delivered to the fuel cell during time period t. This indicates the rated maximum hydrogen consumption rate of the fuel cell.

[0071] The hydrogen balance constraint is:

[0072] in: This represents the total hydrogen production of the electrolyzer during time period t; This indicates hydrogen gas destined for the methanation unit; This indicates hydrogen destined for a fuel cell; This indicates the flow rate of hydrogen entering or leaving the hydrogen storage device during time period t.

[0073] The green gas energy produced by the power-to-gas system is quantified and converted into green certificates that can be traded on the market and are internationally recognized. This provides a basis for enterprises to deduct carbon emissions and reduce CBAM costs. The calculation formula is as follows:

[0074] in: β represents the total energy of green gas produced by the P2G system; β is the gas calorific value conversion coefficient. The number of green certificates available through the P2G system; This represents the CO2 emission reduction corresponding to a single green certificate (0.8042 tCO2 / certificate).

[0075] In this embodiment, the response control unit includes a carbon weight analysis module and a load adjustment module. The carbon weight analysis module is used to adjust user load behavior through carbon price. The load adjustment module dynamically adjusts the transferable and reduceable loads according to the load variable to avoid high carbon emission periods or realize gas-electricity substitution. Under the premise of meeting the production plan for export products, the total cost is minimized by adjusting energy consumption behavior, and CBAM cost is incorporated as a key cost into the decision-making process. The carbon weight analysis module calculates the real-time carbon price based on the changes in the carbon potential curve and the conversion coefficient, thereby affecting the user's load usage. The relationship between carbon price and carbon potential is as follows:

[0076] Where: κ is the conversion coefficient from carbon potential to carbon valence; Carbon potential curves for each time period; This is the carbon weighting parameter.

[0077] The objective function for minimizing the total cost of the load regulation module's impact on user load based on carbon weight parameters is:

[0078] in: Time-of-use pricing for electricity / gas / heat; , , Initial electrical / gas / heat load values; , , This represents the load variation over different time periods; The optimized total cost of ownership for users; External carbon cost pressures.

[0079] The formula for adjusting transferable loads in the load adjustment module is as follows:

[0080] in: The maximum transferable proportion of electrical / gas / heat load; , For the amount transferred and the amount reduced.

[0081] The formula for load reduction regulation in the load regulation module is as follows:

[0082] in: , For the amount transferred and the amount reduced.

[0083] In this embodiment, the collaborative scheduling unit includes a master-slave game module and a cooperative game module; The master-slave game module is used to perform optimized scheduling from both sides of a single PIES source load. The specific method is as follows: The coupling mechanism between carbon trading and green certificate markets, such as Figure 1 As shown, carbon and electricity prices are first set according to the electricity-carbon-green certificate synergistic coupling mechanism, and green certificate trading is carried out. The trading volume and price are determined through the Nash bargaining model. At the electricity, carbon emission, and green certificate levels, energy operators participate in the day-ahead and real-time market electricity purchase plans, as well as the carbon emission market and green certificate market, in order to meet the assessment requirements for carbon emissions and green certificates.

[0084] In actual operation, energy operators need to balance carbon emissions and green electricity consumption, aiming to maximize profits under multiple market mechanisms, and considering the calculation formula for green certificate trading costs as supply and demand change:

[0085] in: Supply and demand of green certificates; The base number of green certificates; Δl is the change. Costs associated with green certificate transactions.

[0086] On the source side, price signals guide load behavior, and the load side adjusts its energy consumption plans accordingly. The goal of the source side is to minimize overall operating costs, and this is achieved by influencing user behavior through setting electricity prices and carbon prices. The objective function is as follows:

[0087] in: Cost of purchasing electricity from the upper-level power grid; To cover the cost of selling electricity to the higher-level power grid; Carbon penalty costs; For green certificate transaction costs; For PIES-based electricity trading.

[0088] The load side receives energy and carbon prices from the source side and adjusts its load curve to minimize its total energy cost. The objective function is as follows:

[0089] in: In response to the control unit; Cost of CBAM; Cost of green certificates for users.

[0090] The cooperative game theory module is used to process the trading of electricity and carbon quotas among multiple PIES in the form of an alliance, so as to achieve Pareto improvement for the region as a whole. Multiple PIES form a consortium I, which facilitates electricity trading among PIES. Carbon quota trading between PIES The goal is to minimize the total cost of the alliance; the objective function is as follows:

[0091] in, This is the cost PIES incurs after participating in the collaborative transaction, which already includes transaction costs. and .

[0092] Figure 2 This diagram illustrates the structure of a multi-energy collaborative optimization trading and dispatching system for carbon border regulation mechanisms. The system first sends data on the prices of electricity, carbon, and green certificates, along with forecasts of wind and solar power generation and electricity / heat / gas loads, to the carbon potential allocation unit. This unit then calculates the carbon potential curves for each node over the next 24 hours based on grid structure, generator output, and load data, providing key carbon weight parameters for subsequent optimization. The joint trading unit, based on market prices and internal system resources, conducts collaborative clearing to formulate suggested trading strategies. The electricity-to-gas system, based on electricity prices and carbon potential curves, decides when and at what power to convert surplus renewable energy into hydrogen / methane and calculates the number of available green certificates. The response control unit receives electricity and carbon price signals, optimizes the operating times of transferable / reducible loads, and proactively avoids peak and valley loads, prioritizing low-carbon and high-carbon loads. The collaborative dispatching unit's cooperative game theory provides a broader space for resource optimization, while the optimization results of the master-slave game form the basis for the formation of cooperative game theory and the distribution of benefits. The final output includes detailed scheduling instructions, market transaction lists, and cost and carbon emission reports to guide the actual operation of the park.

[0093] In this embodiment, the joint trading unit achieves dual coordination between carbon reduction costs and clean energy incentives by constructing a carbon trading and green certificate deduction mechanism. According to simulation results from the literature, under the multi-market collaborative trading of electricity, carbon, and green certificates, the total cost and carbon emissions of the park system are significantly reduced (see Table 1), demonstrating superior low-carbon and economic benefits compared to the single-market model.

[0094] Table 1. Comparison of Costs and Carbon Emissions in Multi-Market Integration Scenarios

[0095] As shown in Table 1, the electricity-carbon-green certificate collaborative market (scenario 4) is the best in terms of economic efficiency and carbon emission reduction effect, with an increase of about 12.5% ​​in new energy absorption capacity and a reduction of about 3% in carbon emissions.

[0096] In this embodiment, the joint trading unit is equipped with a green certificate mapping module, which is used to convert the renewable electricity corresponding to the green certificate into deductible carbon emissions according to a unified conversion factor.

[0097] The carbon quota calculation module dynamically calculates carbon emission allowances based on the emission factors and energy consumption of enterprises or industrial parks; the green certificate mapping module converts green certificates corresponding to renewable electricity such as wind and solar power into deductible carbon emissions according to unified conversion rules. Through this mechanism, enterprises can more intuitively compare the quota reduction effects under different market trading models, as shown in Table 1.

[0098] In this embodiment, the conversion factor is dynamically adjusted based on the carbon emission reduction capacity of various renewable energy sources, and is corrected in real time in conjunction with the impact of external carbon border adjustment mechanisms on carbon pricing.

[0099] Dynamic adjustments to the conversion factor ensure that the correspondence between green certificates and carbon allowances remains consistent with the CBAM pricing mechanism. For example, when international carbon prices rise, the system automatically increases the green certificate conversion factor to maintain the compliance of companies' export trade.

[0100] In this embodiment, the carbon potential allocation unit includes a carbon potential calculation module and a green certificate time-series allocation module. The carbon potential calculation module is used to generate an hourly carbon potential curve based on energy consumption forecasts and emission factors, and the green certificate time-series allocation module is used to prioritize the allocation of green certificates to scheduling periods with high carbon potential.

[0101] Simulation results show that when green certificates are prioritized for peak carbon periods, the system’s total carbon emissions can be further reduced by about 5%.

[0102] In this embodiment, the electrolysis unit in the electro-gas system is used to produce hydrogen by electrolyzing water, the fuel cell unit is used to convert hydrogen into electrical and thermal energy, and the conversion unit includes a methane reactor for synthesizing methane from hydrogen and carbon dioxide, and the methane is included in the green certificate through a green gas certification mechanism.

[0103] The output of electrolyzers, hydrogen fuel cells, and methane reactors varies under different trading scenarios. Taking the carbon-green certificate trading coupling scenario as an example, the power of electrolyzers increases by approximately 20.1%, hydrogen fuel cells by approximately 29.1%, and CH4 reactors by 18.6%. This indicates that the power-to-gas system can significantly increase the renewable energy consumption rate under dual market constraints.

[0104] In this embodiment, the response control unit includes a carbon weight analysis module and a load adjustment module. The carbon weight analysis module is used to calculate the carbon emission sensitivity of each time period, and the load adjustment module dynamically adjusts the transferable and alternative loads according to the carbon weight to avoid high carbon emission periods or realize gas-electricity substitution energy use.

[0105] By setting up two demand response modes (Mode1 and Mode2), the CBAM carbon compliance costs of the park can be significantly reduced (see Table 2).

[0106] Table 2. Cost Comparison of the Two Demand Response Models

[0107] As shown in Table 2, the CBAM cost under the Mode2 demand response mechanism is significantly lower than that under Mode1, with a maximum reduction of 70.5%.

[0108] The working principle of this invention is: The carbon market and the green certificate market are isolated and lack a coordination mechanism. Currently, carbon trading (CET) and green certificate trading (GCT) are mostly independent operating mechanisms, failing to consider their potential for synergy in reducing carbon emissions and alleviating CBAM costs. Existing green certificate trading is coarse-grained and cannot match hourly carbon emission characteristics. Most green certificate systems deduct based on monthly / annual quotas, which cannot cover the hourly carbon emission peaks of energy-consuming enterprises, resulting in low efficiency of green certificate resource utilization. P2G technology has not been systematically incorporated into CBAM response strategies. Although P2G (electricity-to-gas) has good potential for new energy consumption and carbon emission reduction, it has not been directly integrated with the carbon-green certificate trading system and CBAM policies, resulting in a fragmented hydrogen energy utilization strategy. Demand response strategies are not designed in sync with carbon emission weights. Most load response optimization models are cost-oriented and fail to incorporate carbon potential into scheduling, making it difficult to accurately control energy consumption behavior during highly sensitive periods of CBAM.

[0109] This invention proposes a multi-energy collaborative optimization trading and scheduling system for carbon border regulation mechanisms, and proposes an integrated "source-load-city-government" park scheduling response path to address CBAM pressure. Specifically, this includes: constructing a joint market model for carbon trading and green certificates, enabling green certificates to be used to offset carbon emissions, and integrating with the CBAM accounting logic to improve offset efficiency; introducing a "carbon potential curve" to model carbon pressure for each time period within a 24-hour scheduling day, and allocating green certificates hourly according to carbon potential ratios to achieve a "priority offset during high carbon emission periods" strategy; finely dividing the P2G system into three units: electrolyzer (EL), hydrogen fuel cell (HFC), and methane reactor (MR), to achieve waste energy hydrogen production, hydrogen power generation, CO2 to CH4 conversion, and other circular paths, while generating green gas energy that can be included in green certificate accounting; proposing a response model that combines transferable and substitutable demand responses, and introducing a "carbon weight" parameter to drive the response strategy, actively avoiding high carbon emission periods and releasing green certificate space on the energy consumption side; and constructing a two-layer model in PIES consisting of upper-layer market participation game and lower-layer energy dispatch optimization, with the upper layer responsible for electricity-carbon-green certificate pricing linkage and the lower layer responsible for load matching and cost-carbon reduction trade-offs.

[0110] This invention can significantly reduce the carbon cost of CBAM (Consumer-Based Energy Management), with a maximum reduction of 70.5% in typical industrial park scenarios, effectively alleviating the carbon compliance pressure on exporting enterprises; it significantly improves the efficiency of new energy consumption, reducing wind curtailment by 100% and increasing green electricity load utilization by more than 20% through the synergistic effect of demand response and P2G (Power-to-Growth) technology, thus fully utilizing renewable energy; it reduces the total cost of energy consumption, with a reduction of up to 18% after coupling green certificates with carbon market trading strategies, including reductions in energy purchase costs and operation and maintenance costs; it improves the utilization rate of green certificate resources, with the hourly allocation strategy increasing the value of original green certificates by about 1.5 times, maximizing the matching of peak carbon prices with the value of green electricity; and it enhances the system's carbon sequestration capacity, sequestering 20.1% of the total internal CO2 emissions through the CH4 synthesis pathway of P2G, while reducing gas purchase costs and forming a virtuous cycle of energy.

[0111] It should be emphasized that the embodiments described in this invention are illustrative rather than limiting. Therefore, this invention includes, but is not limited to, the embodiments described in the specific implementation. Any other implementations derived by those skilled in the art based on the technical solutions of this invention are also within the scope of protection of this invention.

Claims

1. A multi-energy collaborative optimization transaction and scheduling system for carbon border adjustment mechanism, characterized in that: The application relates to a power-to-gas system and a method for reducing the cost of a carbon border adjustment mechanism (CBAM). The application comprises: a carbon potential distribution unit for generating a carbon potential curve based on a scheduling period and distributing green certificate resources on an hourly scale according to carbon potential; a joint transaction unit for constructing a carbon transaction and green certificate coordination mechanism to realize the deduction of green certificates to carbon emissions; a power-to-gas system for converting electric energy into hydrogen and methane and generating a green gas energy that can be counted as a green certificate; a response control unit for adjusting user load behavior based on a carbon weight parameter and controlling the response behavior of transferable and replaceable loads during a high-carbon emission period; 2.The multi-energy collaborative optimization trading and scheduling system for carbon border adjustment mechanism of claim 1, wherein: a coordinated scheduling unit comprising a master-slave game model and a cooperative game model for PIES internal source load interaction and multi-PIES carbon transaction coordination. The carbon potential distribution unit comprises a carbon potential calculation module and a green certificate timing distribution module. The carbon potential calculation module is used for generating an hourly carbon potential curve according to energy consumption and emission factors; and the green certificate timing distribution module is used for preferentially distributing green certificates to scheduling periods with high carbon potential. Energy-consuming enterprises follow the green certificate market trading rules and distribute the green electricity corresponding to the purchased green certificates according to the difference in carbon potential of each period. ; where: is the carbon potential of node n at time period t; is the power of line (k→n); is the carbon potential of upstream node k; P g,t is the power generated by unit g is the source carbon potential of unit g; and carbon potential curves are derived from 24-hour real-time carbon potentials; The calculation formula of the carbon potential calculation module is as follows: ; The calculation formula of the green certificate timing distribution module is as follows: ; The constraint condition is as follows: ; Wherein: The number of green certificates allocated for time period t; The carbon potential for time period t; The total number of green certificates for the dispatch day; The amount of CO2 offset by each green certificate (0.8042 tCO2 per certificate); The amount of CO2 emissions offset for each time period; high-carbon time periods are identified and allocated green certificates based on a comparison of real-time green certificate numbers and carbon emission offset amounts. 3.The multi-energy collaborative optimization trading and scheduling system for carbon border adjustment mechanism of claim 1, wherein: The carbon emission deduction amount is as follows: The joint transaction unit comprises a green certificate mapping module, which is used for converting renewable electricity corresponding to green certificates into deductible carbon emissions according to a unified conversion coefficient. The processing method is as follows: The carbon emission deduction amount is reduced through green certificate deduction, thereby reducing the cost of the carbon border adjustment mechanism. ; Where: is the number of green certificates; is the CO2 emission amount that can be offset per green certificate;E c is the total carbon emissions; is the EU and domestic carbon price; is the adjusted CBAM cost.

4. The multi-energy coordinated optimization transaction and dispatch system for carbon border adjustment mechanism according to claim 1, characterized in that: The formula is as follows: The power-to-gas system comprises an electrolysis unit, a fuel cell unit and a conversion unit. The electrolysis unit is used for preparing hydrogen by electrolyzing water, the fuel cell unit is used for converting hydrogen into electric energy and heat energy, and the conversion unit comprises a methane reactor, which is used for synthesizing methane from hydrogen and carbon dioxide and counting the methane into green certificates through a green gas authentication mechanism. ; wherein: P(t) is the electrical power consumed by the time period t; V(t) is the volume or mass of hydrogen produced by the time period t; η(t) is the electrical-to-hydrogen conversion efficiency of the electrolyzer; The hydrogen production formula of the electrolysis unit is as follows: ; wherein: is the volume of methane produced for time period t; is the amount of hydrogen fed to the methanation reaction for time period t; is the efficiency of the methanation reaction; The methane synthesis formula of the conversion unit is as follows: ; wherein: P(t) is the electrical power output of the fuel cell for the time period t; QH2(t) is the amount of hydrogen consumed by the fuel cell for the time period t; ηH2(t) is the hydrogen-to-electric conversion efficiency of the fuel cell; The hydrogen power generation formula of the fuel cell unit is as follows: ; wherein: represents the actual input power to the electrolyser at time period t; represents the rated maximum input power to the electrolyser; represents the hydrogen flow rate delivered to the methanation reaction unit at time period t; represents the maximum hydrogen flow rate that the methanation unit can process; represents the hydrogen flow rate delivered to the fuel cell for consumption at time period t; represents the rated maximum hydrogen consumption rate of the fuel cell; The operation constraint is as follows: ; wherein: represents the total hydrogen production of the electrolyzer at time period t; represents hydrogen to the methanation unit; represents hydrogen to the fuel cell; represents the hydrogen flow rate stored in the hydrogen storage device at time period t or the hydrogen flow rate taken out from the hydrogen storage device. The hydrogen balance constraint is as follows: ; wherein: is the total energy of green gas generated by the P2G system; β is the gas heat value conversion coefficient; is the number of green certificates available to the P2G system; is the CO2 emission reduction amount corresponding to a single green certificate.

5. The multi-energy coordinated optimization trading and dispatching system for carbon border adjustment mechanism according to claim 1, characterized in that: The green gas energy produced by the power-to-gas system is quantified and converted into green certificates that can be traded in the market and internationally recognized, thereby providing a basis for enterprises to deduct carbon emissions and reduce the cost of the CBAM. The calculation formula is as follows: The response control unit comprises a carbon weight analysis module and a load adjustment module. The carbon weight analysis module is used for adjusting user load behavior through carbon price; and the load adjustment module dynamically adjusts transferable and reducible loads according to load change to avoid high-carbon emission periods or realize gas-electricity substitution energy consumption. The carbon weight analysis module obtains a real-time carbon price through a conversion coefficient according to the change of the carbon potential curve, thereby affecting user load use; ; wherein: k is a conversion factor from carbon potential to carbon value; is the carbon potential curve for each time period; is the carbon weight parameter; the resulting carbon weight participates in load regulation in the next stage; The relationship between the carbon price and the carbon potential is as follows: ; Wherein: is the electric / gas / heat time-sharing price; , , is the initial electric / gas / heat load value; , , is the load change amount of each period; is the total cost of the user after optimization; is the external carbon cost pressure; The total cost minimization objective function of the load adjustment module for affecting user load according to the carbon weight parameter is as follows: ; wherein: is the maximum transferable proportion of the electrical / gas / thermal load; , is the transfer amount and the reduction amount; The transferable load adjustment formula in the load adjustment module is as follows: The reducible load adjustment formula in the load adjustment module is as follows: ; wherein: , is the transfer amount and the reduction amount.

6. The multi-energy coordinated optimization trading and dispatching system for carbon border adjustment mechanism according to claim 1, characterized in that: The cooperative scheduling unit comprises a master-slave game module and a cooperative game module; The master-slave game module is used for optimizing scheduling from both sides of a single PIES source and load, and the specific method is as follows: First, according to the electric-car-green certificate cooperative coupling mechanism, carbon price, electricity price and green certificate transaction are formulated, the transaction volume and price are determined through the Nash bargaining model, on the levels of electricity, carbon emission and green certificate, the energy operator participates in the day-ahead market and real-time market of power purchase plan, and participates in the carbon emission market and green certificate market to meet the assessment requirements of carbon emission and green certificate; Then, taking the realization of maximum income under multiple market mechanisms as the target, and considering the calculation formula of green certificate transaction cost varying with supply and demand, the target function is as follows: ; Wherein: is the green certificate supply and demand; is the benchmark green certificate quantity; ΔI is the change; is the green certificate transaction cost; The target of the source side is to minimize the comprehensive operation cost, and to influence the user behavior by formulating the energy selling price and carbon price, and the target function is as follows: ; wherein: is the cost of purchasing electricity from the superior grid; is the cost of selling electricity to the superior grid; is the carbon penalty cost; is the green certificate trading cost; is the electricity trading between PIESs; The load side receives the energy price and carbon price issued by the source side, takes the minimization of the total energy cost as the target, adjusts the load curve, and the target function is as follows: ; wherein: is the response control unit; is the CBAM cost; is the user-side green certificate cost.

7. The multi-energy coordinated optimization trading and dispatching system for carbon border adjustment mechanism according to claim 6, characterized in that: The cooperative game module is used for processing the transaction of electric energy and carbon quota among multiple PIES through the form of alliance to realize the Pareto improvement of the whole region. A plurality of PIES form a coalition I, through inter-PIES electricity trading and inter-PIES carbon quota trading to minimize the total cost of the coalition; the objective function is as follows: ; wherein, is the cost of PIES after participating in a cooperative transaction, including transaction costs and .

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