Shared game benefit allocation method and system for multi-stage utilization of clean energy and carbon resources

Abstract

The invention discloses a shared game benefit allocation method and system for clean energy and carbon resource multistage utilization, and the method provided by the invention forms a cooperative game through the mutual connection of a plurality of IESs through energy sharing and carbon transfer, achieves the mutual benefit and win-win of resource sharing and benefit allocation, and achieves the mutual benefit and win-win of a micro-grid operator. The MGO can supply energy to each IES and form a Stackelberg game, and analysis and verification are carried out by taking a certain industrial park as an example, so that the advancement of the method is shown, the carbon emission of the system can be reduced for the problems of indirect promotion of increasingly prominent low-carbon importance by a market mechanism, multi-stage utilization of carbon resources and the like, and the effects of flexible management of the carbon resources and the like are achieved.

Description

Technical Field

[0001] The present invention relates to the field of power systems, and more specifically, to a method and system for allocating benefits of a shared game for multi-level utilization of clean energy and carbon resources. Background Art

[0002] In order to promote low-carbon energy transformation and promote the efficient development of renewable energy, it is urgent to efficiently tap into flexible resources such as clean energy in the integrated energy system (IES) and encourage the optimal supply of integrated energy and low-carbon economic operation through market-based means.

[0003] However, existing studies rarely consider the interaction between the green certificate trading (GCT) market and the carbon emissions trading (CET) market, and the multi-level utilization of carbon resources such as carbon capture and storage, carbon transfer and utilization, carbon trading and carbon offset, resulting in poor carbon resource management and allocation effects. Summary of the invention

[0004] In view of the fact that the existing technologies rarely consider the interaction between the Green certificate trading (GCT) market and the carbon emissions trading (CET) market, and at the same time consider the multi-level utilization of carbon resources such as carbon capture and carbon storage, carbon transfer and carbon utilization, carbon trading and carbon offset, in order to dispatch the carbon emission reduction enthusiasm of IES, it is necessary to consider the time-sharing energy price and carry out a two-stage mixed game study of non-cooperative game and cooperative game to achieve the benefits of different class subjects at the same time. Therefore, it is necessary to invent a shared game benefit sharing strategy for the multi-level utilization of clean energy and carbon resources, so that multiple IES can be connected to each other through energy sharing and carbon transfer to form a cooperative game, and achieve mutual benefit and win-win results of resource sharing and benefit sharing, and the micro-grid operator (MGO) can supply energy to each IES and form a Stackelberg game.

[0005] To achieve the above-mentioned purpose, the first aspect of the present invention provides a method for allocating benefits of a shared game for multi-level utilization of clean energy and carbon resources, comprising:

[0006] S1: Establish a multi-level carbon resource utilization mechanism, which realizes the management of carbon resources through carbon capture and storage, carbon transfer and utilization, carbon trading, and carbon offset;

[0007] S2: Taking into account the benefits of MGO and each IES, an IES trading method based on asymmetric Nash cooperation two-stage mixed game is set. In the Stackelberg game stage, the transaction between MGO and each IES is a master-slave game. MGO sets differential prices for each IES according to its energy purchase demand to maximize its own interests. MGO's differential pricing will affect the energy purchase demand and unit output of the IES. In the cooperative game stage, each IES forms an IES alliance through energy sharing and carbon transfer to increase its own benefits. They respond to MGO's decision through cooperative games to ensure that their own benefits are maximized while maximizing the total benefits of the IES alliance. MGO is a microgrid operator and IES is an integrated energy system.

[0008] S3: IES energy trading price and energy sharing are carried out based on the IES trading method based on the multi-level utilization mechanism of carbon resources and the two-stage mixed game of asymmetric Nash cooperation.

[0009] In one embodiment, the multi-level carbon resource utilization mechanism includes:

[0010] S1.1: Use post-combustion capture system to capture CO2 generated by natural gas combustion in CCHP and GB;

[0011] S1.2: Pipeline transportation is used between IES, ignoring the transmission distance between carbon transfers;

[0012] S1.3: Adopt a carbon trading mechanism and allocate carbon allowances in a free allocation manner;

[0013] S1.4: Adopting a carbon offset mechanism, when calculating carbon emissions, each IES can consume a certain amount of green certificates to offset part of the system's carbon emissions.

[0014] In one embodiment, the conditions in S1.1 include:

[0015] (1) The energy efficiency of carbon capture and storage technology meets the following requirements:

[0016]

[0017] Where: are the carbon emissions of CCHP, GB and in the i-th IES at time t; CO2 not captured by carbon capture, utilization and storage technologies 2 ;μ CCHP , μ GB are the carbon emission intensity coefficients of CCHP and GB respectively; is the output electric power of GT; is the output thermal power of GB; is the carbon capture efficiency of CCUS; Carbon emissions captured for CCUS; is the CO transferred between the i-th IES and the j-th IES at time t 2 ; CO2 for carbon storage in carbon capture 2 ; c and s represent carbon capture and carbon storage, respectively;

[0018] (2) The energy effect of carbon capture and storage energy consumption meets the following requirements:

[0019]

[0020] Where: and They are total energy consumption of CCUS, energy consumption of carbon capture and energy consumption of carbon storage; is the unit carbon capture power consumption coefficient; is the unit carbon sequestration power consumption coefficient; They are the upper and lower limits of CCUS operating power respectively; They are the upper and lower limits of CCUS ramp rate respectively;

[0021] (3) The energy effect of carbon capture and storage costs meets the following requirements:

[0022]

[0023] Where: is the cost of carbon capture and carbon storage; c , k s is the unit carbon capture cost and carbon storage cost coefficient;

[0024] The conditions in S1.2 include:

[0025] (1) The carbon transferor bears the transfer cost, the carbon recipient obtains the transfer income, and the carbon transfer constraints and costs are met:

[0026]

[0027] Where: Transfer CO between IES 2 Upper and lower limits; is the carbon transfer cost; k trans is the unit carbon transfer cost coefficient;

[0028] (2) Carbon utilization constraints are met:

[0029]

[0030] Where: For the preparation of CH 4 CO 2 ; Preparation of CH for MR 4 Carbon consumption coefficient; is the hydrogen output power of EL at time t; To store backup hydrogen power in carbon storage tanks; Power input for hydrogen used to produce natural gas; is the hydrogen input power used to produce natural gas at time t+1; is the amount of natural gas produced by MR; η MR For MR operation efficiency; GT has low calorific value; are the upper and lower limits of MR hydrogen input power; is the MR hydrogen input power in the i-th IES at time t; The upper and lower limits of MR climbing rate;

[0031] (3) Carbon emission flow balance constraints are satisfied:

[0032]

[0033] Where: are MR and stored CO 2 ; For the purchased CO 2 ; To transfer from other systems for the preparation of CH 4 CO 2 ; CO for carbon storage 2 ;

[0034] S1.3 includes:

[0035] (1) Carbon quotas are allocated by free allocation. The carbon emission sources of IES include CCHP and GB. The initial carbon quota of the i-th IES meets the following requirements:

[0036]

[0037] Where: Q e,i The carbon quota allocated to the i-th IES; Carbon quotas of CCHP and GB in the i-th IES; The carbon quota benchmark value for CCHP’s electricity and heating supply; is the CCHP energy supply correction factor; The electricity generated by CCHP; It is the heat energy generated by CCHP and GB; is the GB heating carbon quota benchmark value; e and h represent electricity supply and heating supply respectively;

[0038] (2) The carbon emissions calculated by each IES include CO2 not captured by CCUS 2 The carbon emissions equivalent to electricity purchases meet the following requirements:

[0039]

[0040] Where: Calculate carbon emissions for IES; B is the equivalent carbon emission intensity coefficient of purchased electricity; The equivalent carbon emission power of purchased electricity; Equivalent carbon emissions for electricity purchase;

[0041] (3) The established carbon trading prices and costs meet the following requirements:

[0042]

[0043] Where: is the IES carbon trading price; k 1 , k 2 are carbon price growth and compensation coefficient respectively; c is the carbon trading base price; d is the ladder price range; Carbon quotas for participating in carbon trading; is the IES carbon trading cost; Q e,i Carbon allowances allocated to IES;

[0044] The conditions in S1.4 include:

[0045] (1) The carbon emissions offset by green certificates meet the following requirements:

[0046]

[0047] Where: Carbon emissions offset by green certificates; γ offset is the carbon emission quota correction coefficient; θ is the new energy output emission reduction coefficient; τ trans , shar is the weight coefficient; The proportion of new energy output; is the ratio of actual carbon emissions to carbon quota; is the actual carbon emissions; and are the output power of photovoltaic and wind turbine respectively; is the electrical output power of HFC;

[0048] (2) The quantitative competition Cournot model in game theory is used to describe the price of green certificates, which satisfies the following formula:

[0049]

[0050] Where: p GCT G is the unit green certificate transaction price; GCT The green certificate quota difference; It is the basic price of green certificate transaction; is the inverse price function parameter of the Cournot model, all of which are positive; ζ is the green certificate transaction price ratio coefficient; G e The number of green certificates that must be held;

[0051] (3) GCT benefit calculation meets the following requirements:

[0052] I GCT =G GCT p GCT =(G r -G e ) GCT

[0053] Where: I GCT G is the income from green certificate trading; r Number of green certificates obtained for IES;

[0054] (4) The regulatory authorities allocate the green certificate quota required for each IES, and the green certificate certification and quota coefficients satisfy the following formula:

[0055]

[0056] Where: α, β are the green certificate conversion and green certificate quota coefficients; δ r ,δ e , are the error incentive weight coefficients obtained and held respectively; P t PV , P t WT are the actual output power of photovoltaic and wind turbine at time t; e MMAPE,r is the mean absolute percentage error; e CVRMSE,r is the root mean square error coefficient of variation; L t is the total user load; N is the total number of load samples; y q ,y q is the actual value and predicted value of sample q;

[0057] (5) After IES uses green certificates to offset system carbon emissions, CET costs and GCT benefits will be affected, respectively:

[0058]

[0059] In one embodiment, in the IES trading method based on the asymmetric Nash cooperation two-stage mixed game in step S2, the conditions satisfied in the Stackelberg game stage include:

[0060] (1) As the leader of the Stackelberg game, MGO has the priority to set prices and can set differential prices according to the electricity and gas demand of each IES to maximize its own interests. Its objective function satisfies:

[0061]

[0062] Where: F MGO Energy supply income for MGO; are the electricity and gas supply revenues of the i-th IES at time t respectively; are the electricity selling and purchasing prices from MGO by IES at the moment; and are the gas selling and purchasing prices of the i-th IES to MGO at time t, respectively; and They are the electricity and gas volumes sold and purchased by the i-th IES at time t; T is the upper limit of the transaction time;

[0063] (2) The energy prices set by the MGO cannot exceed the price ceiling set by the regulatory agency, and must meet the following requirements:

[0064]

[0065] Where: and They are the upper and lower limits of electricity and gas trading prices respectively; is the average price of electricity transactions; is the average natural gas transaction price;

[0066] (3) The energy transaction between MGO and each IES must satisfy the exchange power constraints:

[0067]

[0068] Where: They are the upper and lower limits of electricity and gas trading power respectively;

[0069] (4) As a follower of the Stackelberg game, IES conducts energy sharing and multi-level utilization of carbon resources based on the demand for energy consumption, green certificates, and carbon emissions. Each IES aims to maximize its own interests. Its energy supply and demand balance, energy sharing balance, energy sharing price, CCHP operating power, and HFC operating power constraints are satisfied respectively:

[0070]

[0071] Where: is the heat output power; The hydrogen output power used to meet the hydrogen energy supply; for natural gas transmission capacity; for energy prices; are the purchase and sale prices of energy respectively; are the power of GT and AC respectively; and They are the upper and lower limits of GT and AC power respectively; They are the upper and lower limits of GT climbing rate respectively; Power input for HFC hydrogen; The upper limit of HFC hydrogen input power; is the HFC electrical input power; are the upper and lower limits of the thermoelectric ratio, respectively; is the HFC ramp rate; They are the upper and lower limits of HFC ramp rate respectively;

[0072] An asymmetric Nash bargaining model is constructed in the cooperative game stage. The asymmetric Nash bargaining model satisfies:

[0073]

[0074] Where: U i The benefit obtained by the ith IES participating in Nash bargaining; is the benefit of the ith IES when it operates independently, i.e., the negotiation breakdown point; It is an indicator of contribution to energy sharing.

[0075] In one embodiment, the method further includes solving the asymmetric Nash bargaining model, specifically converting the model into three sub-problems: IES alliance benefit maximization Q1, resource sharing contribution quantification Q2, and cooperative benefit distribution Q3, and solving them in sequence.

[0076] (1) Q1: IES Alliance benefits maximization meets:

[0077]

[0078] (2) Q2: Resource sharing contribution measurement satisfies:

[0079]

[0080] Where: Contribution to IES resource sharing;

[0081] (3)Q3: The distribution of cooperative benefits satisfies:

[0082]

[0083] Where: is the energy sharing benefit and carbon transfer cost at the optimal transaction volume in Q1; is the revenue of IES i in Q1.

[0084] In one embodiment, S3 includes:

[0085] S3.1: Analyze the typical daily load of an industrial park and form the energy transaction prices of various IES based on Stackelberg game and asymmetric Nash cooperation game;

[0086] S3.2: Energy sharing strategies for each IES for typical daily loads include sharing of electricity, heat, hydrogen, cold and natural gas.

[0087] In one embodiment, the method further includes establishing four strategies for comparative analysis to perform an economic analysis on the energy sharing strategy of step S3.

[0088] Based on the same inventive concept, the second aspect of the present invention provides a shared game benefit sharing system for multi-level utilization of clean energy and carbon resources, comprising:

[0089] A carbon resource multi-level utilization mechanism setting module is used to set a carbon resource multi-level utilization mechanism, wherein the carbon resource multi-level utilization mechanism realizes the management of carbon resources through carbon capture and carbon storage, carbon transfer and carbon utilization, carbon trading, and carbon offset;

[0090] The IES transaction method setting module is used to take into account the benefits of MGO and each IES, and set up an IES transaction method based on an asymmetric Nash cooperation two-stage mixed game. In the Stackelberg game stage, the transaction between MGO and each IES is a master-slave game. MGO sets differential prices for each IES according to its energy purchase demand to maximize its own interests. MGO's differential pricing will affect the energy purchase demand and unit output of the IES. In the cooperative game stage, in order to increase its own benefits, each IES forms an IES alliance through energy sharing and carbon transfer. They respond to MGO's decision through cooperative games to ensure that their own benefits are maximized while maximizing the total benefits of the IES alliance. MGO is a microgrid operator and IES is an integrated energy system.

[0091] The shared game benefit sharing module is used to carry out IES energy trading prices and energy sharing based on the IES trading method based on the multi-level utilization mechanism of carbon resources and the two-stage mixed game of asymmetric Nash cooperation.

[0092] Based on the same inventive concept, the third aspect of the present invention provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, it implements the shared game benefit sharing method for multi-level utilization of clean energy and carbon resources described in the first aspect.

[0093] Based on the same inventive concept, the fourth aspect of the present invention provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the shared game benefit sharing method for multi-level utilization of clean energy and carbon resources described in the first aspect is implemented.

[0094] Compared with the prior art, the advantages and beneficial technical effects of the present invention are as follows:

[0095] The present invention provides a shared game benefit-sharing strategy for the multi-level utilization of clean energy and carbon resources. In view of the increasing importance of indirect promotion of low carbon by market mechanisms and the multi-level utilization of carbon resources, carbon capture and storage, carbon transfer and utilization, carbon trading, carbon offset and other methods are used to reduce system carbon emissions and achieve flexible management of carbon resources. In addition, considering time-sharing energy prices and energy management plans, an IES trading method based on Stackelberg-asymmetric Nash cooperation two-stage mixed game is proposed. It can reduce system carbon emissions and achieve flexible management of carbon resources for the market mechanism to indirectly promote the increasing importance of low carbon and the multi-level utilization of carbon resources. In addition, an industrial park is used as an example for analysis and verification, which shows the advanced nature of the proposed method. BRIEF DESCRIPTION OF THE DRAWINGS

[0096] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0097] Figure 1 A framework diagram of a shared game benefit allocation strategy for multi-level utilization of clean energy and carbon resources in an embodiment of the present invention;

[0098] Figure 2 The differential electricity price of MGO to IES and the energy sharing electricity price of IES alliance in the embodiment of the present invention;

[0099] Figure 3 The differential gas price between MGO and IES and the IES alliance energy sharing gas price in the embodiment of the present invention;

[0100] Figure 4 is the energy price among IES alliances under the cooperative game in the embodiment of the present invention;

[0101] Figure 5 This is a diagram showing the optimization results of IES power supply in an embodiment of the present invention;

[0102] Figure 6This is a diagram showing the optimization results of IES heat supply in an embodiment of the present invention;

[0103] Figure 7 This is a diagram showing the optimization results of IES hydrogen energy supply in an embodiment of the present invention;

[0104] Figure 8 This is a diagram showing the optimization results of IES cooling energy supply in an embodiment of the present invention;

[0105] Fig. 9 This is a diagram of IES natural gas supply optimization results in an embodiment of the present invention. DETAILED DESCRIPTION

[0106] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0107] Embodiment 1

[0108] This embodiment discloses a method for allocating benefits of shared games for multi-level utilization of clean energy and carbon resources, including:

[0109] S1: Establish a multi-level carbon resource utilization mechanism, which realizes the management of carbon resources through carbon capture and storage, carbon transfer and utilization, carbon trading, and carbon offset;

[0110] S2: Taking into account the benefits of MGO and each IES, an IES trading method based on asymmetric Nash cooperation two-stage mixed game is set. In the Stackelberg game stage, the transaction between MGO and each IES is a master-slave game. MGO sets differential prices for each IES according to its energy purchase demand to maximize its own interests. MGO's differential pricing will affect the energy purchase demand and unit output of the IES. In the cooperative game stage, each IES forms an IES alliance through energy sharing and carbon transfer to increase its own benefits. They respond to MGO's decision through cooperative games to ensure that their own benefits are maximized while maximizing the total benefits of the IES alliance. MGO is a microgrid operator and IES is an integrated energy system.

[0111] S3: IES energy trading price and energy sharing are carried out based on the IES trading method based on the multi-level utilization mechanism of carbon resources and the two-stage mixed game of asymmetric Nash cooperation.

[0112] See also Figure 1 , which is a framework diagram of the shared game benefit sharing strategy for multi-level utilization of clean energy and carbon resources in an embodiment of the present invention.

[0113] In one embodiment, in step S1, a multi-level carbon resource utilization mechanism is proposed to improve the flexibility of clean energy in IES and reduce system carbon emissions, and the flexible management of carbon resources is achieved through carbon capture and storage, carbon transfer and utilization, carbon trading, carbon offset, etc. The specific details are as follows:

[0114] Step S1.1: A post-combustion capture system is used to capture CO2 generated by the combustion of natural gas in CCHP (Combined Cooling, Heating and Power) and GB (Gas Boiler).

[0115] (1) The energy efficiency of carbon capture and storage technology meets the following requirements:

[0116]

[0117] Where: are the carbon emissions of CCHP, GB and in the i-th IES at time t; CO2 not captured by carbon capture utilization and storage (CCUS) 2 ;μ CCHP , μ GB are the carbon emission intensity coefficients of CCHP and GB respectively; is the output electric power of GT; is the output thermal power of GB; is the carbon capture efficiency of CCUS; Carbon emissions captured for CCUS; is the CO transferred between the i-th IES and the j-th IES at time t 2 ; CO2 for carbon storage in carbon capture 2 ; c and s represent carbon capture and carbon storage, respectively.

[0118] (2) The energy effect of carbon capture and storage energy consumption meets the following requirements:

[0119]

[0120] Where: and They are total energy consumption of CCUS, energy consumption of carbon capture and energy consumption of carbon storage; is the unit carbon capture power consumption coefficient; is the unit carbon sequestration power consumption coefficient; They are the upper and lower limits of CCUS operating power respectively; They are the upper and lower limits of CCUS ramp rate respectively.

[0121] (3) The energy effect of carbon capture and storage costs meets the following requirements:

[0122]

[0123] Where: is the cost of carbon capture and carbon storage; c , k s is the unit carbon capture cost and carbon storage cost coefficient.

[0124] Step S1.2: Assume that pipeline transportation is used between IES and ignore the transmission distance between carbon transfers.

[0125] (1) The carbon transferor bears the transfer cost, the carbon recipient obtains the transfer income, and the carbon transfer constraints and costs are met:

[0126]

[0127] Where: Transfer CO between IES 2 Upper and lower limits; is the carbon transfer cost; k trans is the unit carbon transfer cost coefficient.

[0128] (2) The transferred CO2 can be directly stored underground, or part of it can be reacted with H2 in the MR system to produce CH4 for gas load supply, and the other part can be stored in a carbon storage tank for backup. Carbon utilization constraints meet:

[0129]

[0130] Where: For the preparation of CH 4 CO 2 ; Preparation of CH for MR 4 Carbon consumption coefficient; is the hydrogen output power of EL at time t; To store backup hydrogen power in carbon storage tanks; Power input for hydrogen used to produce natural gas; is the hydrogen input power used to produce natural gas at time t+1; is the amount of natural gas produced by MR; η MR For MR operation efficiency; GT has low calorific value; are the upper and lower limits of MR hydrogen input power; is the MR hydrogen input power in the i-th IES at time t; It is the upper and lower limits of MR climbing rate.

[0131] (3) Carbon emission flow balance constraints are satisfied:

[0132]

[0133] Where: are MR and stored CO 2 ; For the purchased CO 2 ; To transfer from other systems for the preparation of CH 4 CO 2 ; CO for carbon storage 2 .

[0134] Step S1.3: A CET mechanism is proposed to address the problem that fixed prices cannot motivate operators to participate in the CET market.

[0135] (1) Carbon quotas are allocated by free allocation. The carbon emission sources of IES are mainly CCHP and GB. The initial carbon quota of IES i meets the following requirements:

[0136]

[0137] Where: Q e,i The carbon quota allocated to the i-th IES; The carbon quota of the i-th CCHP, GB; The carbon quota benchmark value for CCHP’s electricity and heating supply; is the CCHP energy supply correction factor; The electricity generated by CCHP; It is the heat energy generated by CCHP and GB; is the benchmark value of GB heating carbon quota; e and h represent electricity supply and heating respectively.

[0138] (2) The carbon emissions calculated by each IES include CO2 not captured by CCUS 2 The carbon emissions equivalent to electricity purchases meet the following requirements:

[0139]

[0140] Where: Calculate carbon emissions for IES; B is the carbon emission intensity coefficient of electricity purchase equivalent; P t B The equivalent carbon emission power of purchased electricity; It is the equivalent carbon emissions of purchased electricity.

[0141] (3) The established carbon trading prices and costs meet the following requirements:

[0142]

[0143] Where: is the IES carbon trading price; k 1 , k 2 are carbon price growth and compensation coefficient respectively; c is the carbon trading base price; d is the ladder price range; Carbon quotas for participating in carbon trading; is the IES carbon trading cost; Q e,i Carbon allowances allocated to IES.

[0144] Step S1.4: The traditional carbon trading market cannot use green certificates to obtain carbon emission rights. In order to further improve the flexibility of system operation and market transactions, a carbon offset mechanism is designed. When calculating carbon emissions, each IES can consume a certain amount of green certificates to offset part of the system's carbon emissions.

[0145] (1) The higher the carbon transfer output ratio and energy sharing ratio, the more carbon emissions can be offset. The carbon emissions offset by green certificates meet the following requirements:

[0146]

[0147] Where: Carbon emissions offset by green certificates; γ offset is the carbon emission quota correction coefficient; θ is the new energy output emission reduction coefficient; τ trans , shar is the weight coefficient; The proportion of new energy output; is the ratio of actual carbon emissions to carbon quota; is the actual carbon emissions; and are the output power of photovoltaic and wind turbine respectively; is the electrical output power of HFC.

[0148] (2) IES carbon offset willingness is affected by the price of green certificates and carbon trading prices. The quantity competition Cournot model in game theory is used to describe the price of green certificates, which satisfies the following equation. The IES carbon offset trading market is stimulated by the demand signal of green certificate purchase and sale.

[0149]

[0150] Where: p GCT G is the unit green certificate transaction price; GCT The green certificate quota difference; It is the basic price of green certificate transaction; is the inverse price function parameter of the Cournot model, all of which are positive; ζ is the green certificate transaction price ratio coefficient; G eThe number of green certificates that must be held.

[0151] (3) Using the data from the “China Green Power Certificate Subscription and Trading Platform” as a reference, assuming that the GCT prices of wind power and photovoltaic power are equal, Yuan / capital, then the GCT income calculation satisfies:

[0152] I GCT =G GCT p GCT =(G r -G e ) GCT

[0153] Where: I GCT G is the income from green certificate trading; r The number of green certificates obtained for IES.

[0154] (4) The regulatory authorities allocate the number of green certificate quotas required by each IES. Each IES obtains green certificates based on renewable energy and participates in the GCT market to purchase or sell green certificates to meet the demand for holding green certificate quotas. In the green certificate certification and quota, two dimensionless prediction error evaluation indicators are selected to evaluate the new energy output and load prediction errors. The coefficient of variation of the mean absolute percentage error and the root mean square error is combined to determine the green certificate certification and quota coefficient to meet the following formula, thereby encouraging IES operators to improve prediction accuracy and system operation stability.

[0155]

[0156] Where: α, β are the green certificate conversion and green certificate quota coefficients; δ r ,δ e , are the error incentive weight coefficients obtained and held respectively; P t PV , P t WT are the actual output power of photovoltaic and wind turbine at time t; e MMAPE,r is the mean absolute percentage error; e CVRMSE,r is the root mean square error coefficient of variation; L t is the total user load; N is the total number of load samples, which is 24; y q ,y q is the actual value and predicted value of sample q.

[0157] (5) After IES uses green certificates to offset system carbon emissions, CET costs and GCT benefits will be affected and should meet the following requirements respectively:

[0158]

[0159] In one embodiment, in order to take into account the benefits of MGO and each IES in step S2, an IES trading method based on Stackelberg-asymmetric Nash cooperation two-stage mixed game is proposed as follows:

[0160] Step S2.1: Stackelberg game stage: The transaction between MGO and each IES is a master-slave game. MGO sets different prices for each IES according to their energy purchase demand to maximize its own interests. MGO's differential pricing will affect the energy purchase demand and unit output of the IES.

[0161] (1) As the leader of the Stackelberg game, MGO has the priority pricing power and can set differential prices according to the electricity and gas demand of each IES to maximize its own interests. Its objective function satisfies:

[0162]

[0163] Where: F MGO Energy supply income for MGO; are the electricity and gas supply revenues of the i-th IES at time t respectively; are the electricity selling and purchasing prices from MGO by IES at the moment; and are the gas selling and purchasing prices of the i-th IES to MGO at time t, respectively; and are the electricity and gas volumes sold and purchased by the i-th IES at time t respectively; T is the upper limit of the transaction time.

[0164] (2) The energy prices set by the MGO cannot exceed the price ceiling set by the regulatory agency and must meet the following requirements:

[0165]

[0166] Where: and They are the upper and lower limits of electricity and gas trading prices respectively; is the average price of electricity transactions; The average price of natural gas transactions.

[0167] (3) The energy transaction between MGO and each IES must meet the exchange power constraints:

[0168]

[0169] Where: They are the upper and lower limits of electricity and gas trading power respectively.

[0170] (4) IES, as a follower of the Stackelberg game, conducts energy sharing and multi-level utilization of carbon resources based on energy consumption, green certificates, and carbon emissions. Each IES aims to maximize its own interests, and its energy supply and demand balance, energy sharing balance, energy sharing price, CCHP operating power, and HFC operating power constraints are respectively satisfied:

[0171]

[0172] Where: is the heat output power; The hydrogen output power used to meet the hydrogen energy supply; for natural gas transmission capacity; for energy prices; are the purchase and sale prices of energy respectively; are the power of GT and AC respectively; and They are the upper and lower limits of GT and AC power respectively; They are the upper and lower limits of GT climbing rate respectively; Power input for HFC hydrogen; The upper limit of HFC hydrogen input power; is the HFC electrical input power; are the upper and lower limits of the thermoelectric ratio, respectively; is the HFC ramp rate; They are the upper and lower limits of HFC ramp rate respectively.

[0173] Step S2.2: In the cooperative game stage, each IES forms an IES alliance through energy sharing and carbon transfer to increase its own benefits, and responds to the decision of MGO through cooperative games. The IESs cooperate with each other and are independent of each other, ensuring their own benefits while maximizing the total benefits of the IES alliance.

[0174] The asymmetric Nash bargaining theory is introduced to describe the cooperative game within the IES alliance. The asymmetric Nash bargaining model satisfies:

[0175]

[0176] Where: U i The benefit obtained by the ith IES participating in Nash bargaining; is the benefit of the ith IES when it operates independently, i.e., the negotiation breakdown point; It is an indicator of contribution to energy sharing.

[0177] This implementation also proposes a solution method for the asymmetric Nash bargaining model. This model is a non-convex nonlinear optimization problem and is often difficult to solve directly. It is converted into three easy-to-solve sub-problems: IES alliance profit maximization (Q1), resource sharing contribution quantification (Q2), and cooperation profit distribution (Q3), and these sub-problems are solved in turn.

[0178] (1) Q1: IES Alliance benefits maximization meets:

[0179]

[0180] (2) Q2: Resource sharing contribution measurement satisfies:

[0181]

[0182] Where: Contribution to IES resource sharing.

[0183] (3)Q3: The distribution of cooperative benefits satisfies:

[0184]

[0185] Where: is the energy sharing benefit and carbon transfer cost at the optimal transaction volume in Q1; is the revenue of IES i in Q1.

[0186] See also Figure 2 to Figure 4 ,in, Figure 2 Differential electricity prices for MGO to IES and energy sharing electricity prices for IES alliance; Figure 3 The differential gas price between MGO and IES and the gas price shared by IES alliance energy, Figure 4 is the energy price among IES alliances under cooperative game. Figures 5 to 9 ,in, Figure 5 This is the IES power supply optimization result diagram; Figure 6 Optimization result diagram for IES heat supply; Figure 7 IES hydrogen supply optimization results diagram; Figure 8 This is the result diagram of IES cooling energy supply optimization; Fig. 9 Optimization results for IES natural gas supply.

[0187] In one implementation mode, in step S3, according to the shared game benefit allocation strategy for the multi-level utilization of clean energy and carbon resources obtained in step 1 and step 2, the energy transaction prices and energy sharing strategies of each IES are formed by using the typical daily load of a certain industrial park as follows:

[0188] Step 3.1: Take the typical daily load of an industrial park as an example for case analysis, and form the energy transaction prices of various IES based on Stackelberg game and asymmetric Nash cooperation game.

[0189] Step 3.2: Energy sharing strategies for each IES for typical daily loads include electricity, heat, hydrogen, cold and natural gas.

[0190] In one embodiment, the method further includes step S4: establishing four strategies for comparative analysis to conduct an economic analysis of the energy sharing strategy of step S3, which is specifically implemented as follows:

[0191] Step 4.1: Four strategies are set up for comparative analysis. Different factors are considered in each strategy, as shown in Table 1. The economic benefits of MGO and IES operators under different cases are shown in Table 2.

[0192] Table 1 Different case settings

[0193]

[0194] Table 2 Economic benefits of MGO and IES operators under different cases

[0195]

[0196]

[0197] Embodiment 2

[0198] Based on the same inventive concept, this embodiment discloses a shared game benefit sharing system for multi-level utilization of clean energy and carbon resources, including:

[0199] A carbon resource multi-level utilization mechanism setting module is used to set a carbon resource multi-level utilization mechanism, wherein the carbon resource multi-level utilization mechanism realizes the management of carbon resources through carbon capture and carbon storage, carbon transfer and carbon utilization, carbon trading, and carbon offset;

[0200] The IES transaction method setting module is used to take into account the benefits of MGO and each IES, and set up an IES transaction method based on an asymmetric Nash cooperation two-stage mixed game. In the Stackelberg game stage, the transaction between MGO and each IES is a master-slave game. MGO sets differential prices for each IES according to its energy purchase demand to maximize its own interests. MGO's differential pricing will affect the energy purchase demand and unit output of the IES. In the cooperative game stage, in order to increase its own benefits, each IES forms an IES alliance through energy sharing and carbon transfer. They respond to MGO's decision through cooperative games to ensure that their own benefits are maximized while maximizing the total benefits of the IES alliance. MGO is a microgrid operator and IES is an integrated energy system.

[0201] The shared game benefit sharing module is used to carry out IES energy trading prices and energy sharing based on the IES trading method based on the multi-level utilization mechanism of carbon resources and the two-stage mixed game of asymmetric Nash cooperation.

[0202] Since the system introduced in the second embodiment of the present invention is a system used to implement the shared game benefit allocation method for multi-level utilization of clean energy and carbon resources in the first embodiment of the present invention, based on the method introduced in the first embodiment of the present invention, the person skilled in the art can understand the specific structure and deformation of the system, so it is not repeated here. All systems used in the method in the first embodiment of the present invention belong to the scope of protection of the present invention.

[0203] Embodiment 3

[0204] Based on the same inventive concept, the present invention further provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the method described in the first embodiment is implemented.

[0205] Since the computer-readable storage medium introduced in the third embodiment of the present invention is a computer-readable storage medium used to implement the shared game benefit allocation method for multi-level utilization of clean energy and carbon resources in the first embodiment of the present invention, based on the method introduced in the first embodiment of the present invention, the person skilled in the art can understand the specific structure and deformation of the computer-readable storage medium, so it is not repeated here. All computer-readable storage media used in the method of the first embodiment of the present invention belong to the scope of protection of the present invention.

[0206] Embodiment 4

[0207] The present invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method described in Embodiment 1 when executing the program.

[0208] Since the computer device introduced in the fourth embodiment of the present invention is a computer device used to implement the shared game benefit allocation method for multi-level utilization of clean energy and carbon resources in the first embodiment of the present invention, based on the method introduced in the first embodiment of the present invention, the person skilled in the art can understand the specific structure and deformation of the computer device, so it is not repeated here. All computer devices used in the method of the first embodiment of the present invention belong to the scope of protection of the present invention.

[0209] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0210] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0211] Although preferred embodiments of the present invention have been described, additional changes and modifications may be made to these embodiments by those skilled in the art once the basic creative concepts are known. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention. Obviously, those skilled in the art may make various changes and modifications to the embodiments of the present invention without departing from the spirit and scope of the embodiments of the present invention. Thus, if these modifications and variations of the embodiments of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A shared game benefit allocation method for multi-level utilization of clean energy and carbon resources, characterized in that: include: S1: Establish a multi-level carbon resource utilization mechanism, which realizes the management of carbon resources through carbon capture and storage, carbon transfer and utilization, carbon trading, and carbon offset; S2: Taking into account the benefits of MGO and each IES, an IES trading method based on asymmetric Nash cooperation two-stage mixed game is set. In the Stackelberg game stage, the transaction between MGO and each IES is a master-slave game. MGO sets differential prices for each IES according to its energy purchase demand to maximize its own interests. MGO's differential pricing will affect the energy purchase demand and unit output of the IES. In the cooperative game stage, each IES forms an IES alliance through energy sharing and carbon transfer to increase its own benefits. They respond to MGO's decision through cooperative games to ensure that their own benefits are maximized while maximizing the total benefits of the IES alliance. MGO is a microgrid operator and IES is an integrated energy system. S3: IES energy trading price and energy sharing are carried out based on the IES trading method based on the multi-level utilization mechanism of carbon resources and the two-stage mixed game of asymmetric Nash cooperation.

2. The method for sharing game benefits of multi-level utilization of clean energy and carbon resources as claimed in claim 1, characterized in that: Multi-level carbon resource utilization mechanism, including: S1.1: Use post-combustion capture system to capture CO2 generated by natural gas combustion in CCHP and GB; S1.2: Pipeline transportation is used between IES, ignoring the transmission distance between carbon transfers; S1.3: Adopt a carbon trading mechanism and allocate carbon allowances in a free allocation manner; S1.4: Adopting a carbon offset mechanism, when calculating carbon emissions, each IES can consume a certain amount of green certificates to offset part of the system's carbon emissions.

3. The shared game benefit allocation method for multi-level utilization of clean energy and carbon resources as claimed in claim 2, characterized in that: The conditions in S1.1 include: (1) The energy efficiency of carbon capture and storage technology meets the following requirements: Where: are the carbon emissions of CCHP, GB and in the i-th IES at time t; CO2 not captured by carbon capture, utilization and storage technologies; μ CCHP , μ GB are the carbon emission intensity coefficients of CCHP and GB respectively; is the output electric power of GT; is the output thermal power of GB; is the carbon capture efficiency of CCUS; Carbon emissions captured for CCUS; is the CO2 transferred between the i-th IES and the j-th IES at time t; is the CO2 used for carbon storage in carbon capture; c and s represent carbon capture and carbon storage, respectively; (2) The energy effect of carbon capture and storage energy consumption meets the following requirements: Where: and They are total energy consumption of CCUS, energy consumption of carbon capture and energy consumption of carbon storage; is the unit carbon capture power consumption coefficient; is the unit carbon sequestration power consumption coefficient; They are the upper and lower limits of CCUS operating power respectively; They are the upper and lower limits of CCUS ramp rate respectively; (3) The energy effect of carbon capture and storage costs meets the following requirements: Where: is the cost of carbon capture and carbon storage; c , k s is the unit carbon capture cost and carbon storage cost coefficient; The conditions in S1.2 include: (1) The carbon transferor bears the transfer cost, the carbon recipient obtains the transfer income, and the carbon transfer constraints and costs are met: Where: The upper and lower limits for transferring CO2 between IES; is the carbon transfer cost; k trans is the unit carbon transfer cost coefficient; (2) Carbon utilization constraints are met: Where: CO2 for producing CH4; is the carbon consumption coefficient for preparing CH4 for MR; is the hydrogen output power of EL at time t; To store backup hydrogen power in carbon storage tanks; Power input for hydrogen used to produce natural gas; is the hydrogen input power used to produce natural gas at time t+1; is the amount of natural gas produced by MR; η MR For MR operation efficiency; GT has low calorific value; are the upper and lower limits of MR hydrogen input power; is the MR hydrogen input power in the i-th IES at time t; The upper and lower limits of MR climbing rate; (3) Carbon emission flow balance constraints are satisfied: Where: are MR and stored CO2, respectively; For the purchased CO2; To transfer CO2 from other systems for CH4 production; for CO2 used for carbon sequestration; S1.3 includes: (1) Carbon quotas are allocated by free allocation. The carbon emission sources of IES include CCHP and GB. The initial carbon quota of the i-th IES meets the following requirements: Where: Q e,i The carbon quota allocated to the i-th IES; Carbon quotas of CCHP and GB in the i-th IES; The carbon quota benchmark value for CCHP’s electricity and heating supply; is the CCHP energy supply correction factor; The electricity generated by CCHP; It is the heat energy generated by CCHP and GB; is the GB heating carbon quota benchmark value; e and h represent electricity supply and heating supply respectively; (2) The carbon emissions calculated by each IES include the CO2 not captured by CCUS and the carbon emissions equivalent to purchased electricity that meet the following requirements: Where: Calculate carbon emissions for IES; B is the carbon emission intensity coefficient of electricity purchase equivalent; P t B The equivalent carbon emission power of purchased electricity; Equivalent carbon emissions for electricity purchase; (3) The established carbon trading prices and costs meet the following requirements: Where: is the IES carbon trading price; k1 and k2 are the carbon price growth and compensation coefficient respectively; c is the carbon trading base price; d is the ladder price range; Carbon quotas for participating in carbon trading; is the IES carbon trading cost; Q e,i Carbon allowances allocated to IES; The conditions in S1.4 include: (1) The carbon emissions offset by green certificates meet the following requirements: Where: Carbon emissions offset by green certificates; γ offset is the carbon emission quota correction coefficient; θ is the new energy output emission reduction coefficient; τ trans , shar is the weight coefficient; The proportion of new energy output; is the ratio of actual carbon emissions to carbon quotas; is the actual carbon emissions; and are the output power of photovoltaic and wind turbine respectively; is the electrical output power of HFC; (2) The quantitative competition Cournot model in game theory is used to describe the price of green certificates, which satisfies the following formula: Where: p GCT G is the unit green certificate transaction price; GCT The green certificate quota difference; is the basic price of green certificate transaction; l1 and 2 are the parameters of the inverse price function of the Cournot model, both of which are positive values; ζ is the proportional coefficient of the green certificate transaction price; G e The number of green certificates that must be held; (3) GCT benefit calculation meets the following requirements: I GCT =G GCT p GCT =(G r -G e )p GCT Where: I GCT G is the income from green certificate trading; r Number of green certificates obtained for IES; (4) The regulatory authorities allocate the green certificate quota required for each IES, and the green certificate certification and quota coefficients satisfy the following formula: Where: α, β are the green certificate conversion and green certificate quota coefficients; δ r , δ e , are the error incentive weight coefficients obtained and held respectively; P t PV , P t WT are the actual output power of photovoltaic and wind turbine at time t; e MMAPE,r is the mean absolute percentage error; e CVRMSE,r is the root mean square error coefficient of variation; L t is the total user load; N is the total number of load samples; y q ,y q is the actual value and predicted value of sample q; (5) After IES uses green certificates to offset system carbon emissions, CET costs and GCT benefits will be affected, respectively: The carbon emissions offset by green certificates.

4. The method for sharing game benefits of multi-level utilization of clean energy and carbon resources as claimed in claim 1, characterized in that: In the IES trading method based on the asymmetric Nash cooperation two-stage mixed game in step S2, the conditions satisfied in the Stackelberg game stage include: (1) As the leader of the Stackelberg game, MGO has the priority to set prices and can set differential prices according to the electricity and gas demand of each IES to maximize its own interests. Its objective function satisfies: Where: F MGO Energy supply income for MGO; are the electricity and gas supply revenues of the i-th IES at time t respectively; are the electricity selling and purchasing prices from MGO by IES at the moment; and are the gas selling and purchasing prices of the i-th IES to MGO at time t, respectively; and They are the electricity and gas volumes sold and purchased by the i-th IES at time t; T is the upper limit of the transaction time; (2) The energy prices set by the MGO cannot exceed the price ceiling set by the regulatory agency, and must meet the following requirements: Where: and They are the upper and lower limits of electricity and gas trading prices respectively; is the average price of electricity trading; is the average natural gas transaction price; (3) The energy transaction between MGO and each IES must satisfy the exchange power constraints: Where: They are the upper and lower limits of electricity and gas trading power respectively; (4) As a follower of the Stackelberg game, IES conducts energy sharing and multi-level utilization of carbon resources based on the demand for energy consumption, green certificates, and carbon emissions. Each IES aims to maximize its own interests. Its energy supply and demand balance, energy sharing balance, energy sharing price, CCHP operating power, and HFC operating power constraints are satisfied respectively: Where: is the heat output power; The hydrogen output power used to meet the hydrogen energy supply; for natural gas transmission capacity; for energy prices; are the purchase and sale prices of energy respectively; are the power of GT and AC respectively; and They are the upper and lower limits of GT and AC power respectively; They are the upper and lower limits of GT climbing rate respectively; Power input for HFC hydrogen; The upper limit of HFC hydrogen input power; is the HFC electrical input power; are the upper and lower limits of the thermoelectric ratio, respectively; is the HFC ramp rate; They are the upper and lower limits of HFC ramp rate respectively; An asymmetric Nash bargaining model is constructed in the cooperative game stage. The asymmetric Nash bargaining model satisfies: Where: U i The benefit obtained by the ith IES participating in Nash bargaining; is the benefit of the ith IES when it operates independently, i.e., the negotiation breakdown point; It is an indicator of contribution to energy sharing.

5. The shared game benefit allocation method for multi-level utilization of clean energy and carbon resources as claimed in claim 4, characterized in that: The method also includes solving the asymmetric Nash bargaining model, specifically converting the model into three sub-problems: IES alliance benefit maximization Q1, resource sharing contribution quantification Q2, and cooperative benefit distribution Q3, and solving them in turn. (1) Q1: IES Alliance benefits maximization meets: (2) Q2: Resource sharing contribution measurement satisfies: Where: Contribution to IES resource sharing; (3)Q3: The distribution of cooperative benefits satisfies: Where: is the energy sharing benefit and carbon transfer cost at the optimal transaction volume in Q1; This is the revenue of IESi in Q1.

6. The method for sharing game benefits of multi-level utilization of clean energy and carbon resources as claimed in claim 1, characterized in that S3 include: S3.1: Analyze the typical daily load of an industrial park and form the energy transaction prices of various IES based on Stackelberg game and asymmetric Nash cooperation game; S3.2: Energy sharing strategies for each IES for typical daily loads include sharing of electricity, heat, hydrogen, cold and natural gas.

7. The method for sharing game benefits of multi-level utilization of clean energy and carbon resources as claimed in claim 6, characterized in that: The method further includes establishing four strategies for comparative analysis to conduct an economic analysis on the energy sharing strategy of step S3.

8. A shared game benefit sharing system for multi-level utilization of clean energy and carbon resources, characterized in that: include: A carbon resource multi-level utilization mechanism setting module is used to set a carbon resource multi-level utilization mechanism, wherein the carbon resource multi-level utilization mechanism realizes the management of carbon resources through carbon capture and carbon storage, carbon transfer and carbon utilization, carbon trading, and carbon offset; The IES transaction method setting module is used to take into account the benefits of MGO and each IES, and set up an IES transaction method based on an asymmetric Nash cooperation two-stage mixed game. In the Stackelberg game stage, the transaction between MGO and each IES is a master-slave game. MGO sets differential prices for each IES according to its energy purchase demand to maximize its own interests. MGO's differential pricing will affect the energy purchase demand and unit output of the IES. In the cooperative game stage, in order to increase its own benefits, each IES forms an IES alliance through energy sharing and carbon transfer. They respond to MGO's decision through cooperative games to ensure that their own benefits are maximized while maximizing the total benefits of the IES alliance. MGO is a microgrid operator and IES is an integrated energy system. The shared game benefit sharing module is used to carry out IES energy trading prices and energy sharing based on the IES trading method based on the multi-level utilization mechanism of carbon resources and the two-stage mixed game of asymmetric Nash cooperation.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, it implements the shared game benefit allocation method for multi-level utilization of clean energy and carbon resources as described in any one of claims 1 to 7.

10. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the shared game benefit sharing method for multi-level utilization of clean energy and carbon resources as described in any one of claims 1 to 7 is implemented.

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