Methods for distributed carbon allocation among multiple entities

Abstract

This invention provides a method for distributed electricity and carbon allocation among multiple entities, characterized by the following steps: Step S1, each entity constructs a corresponding cost function based on its type; Steps S2-S4, combining the cost function and constraints, iteratively solves the multi-entity electricity cooperation and sharing model to obtain the optimal electricity trading volume among the entities; Steps S5-S7, combining the cost function and constraints, iteratively solves the multi-entity bargaining revenue allocation model to obtain the optimal electricity trading price among the entities. In summary, this method can achieve optimal allocation of electricity and carbon quotas among multiple entities.

Description

Technical Field

[0001] This invention belongs to the field of energy conservation, and specifically relates to a method for distributed carbon distribution among multiple entities. Background Technology

[0002] In recent years, with the intensification of global warming, green and low-carbon development has become a focus of attention for countries worldwide. Carbon emission trading, as the main mechanism for carbon emission reduction, is a mandatory market tool to promote emission reduction across society. In recent years, with the rapid expansion of the carbon market, the types of carbon trading products have become more diversified. Industrial parks, as hubs for various enterprises, play a crucial role in industrial upgrading and economic development, but are also major sources of carbon emissions. Furthermore, with the development of distributed energy and new energy sources, the demand-side entities within these parks are transforming from simple energy consumers into integrated producers and consumers, i.e., prosumers. As emerging agents in the electricity market, the role of prosumers cannot be ignored. The uncertainty of distributed renewable energy within individual prosumers places higher demands on the flexibility of the distribution network system. In addition, due to their small scale, individual prosumers often fail to meet the entry threshold for the wholesale electricity market, making it impossible to respond to market price signals and objectively lacking channels to participate in electricity market operations. Therefore, with the increasing number of demand-side prosumers within industrial parks, considering the energy interaction among multiple entities within the park becomes an important means of solving these problems. At the technical level, advanced two-way communication networks and information technology can solve the problems of interaction and intelligent decision-making among multiple stakeholders. At the policy level, against the backdrop of power and energy system reform, market-based trading of distributed generation can incentivize demand-side distributed renewable energy to actively participate in system operation, promoting energy resource sharing. Due to the heterogeneity among different stakeholders within the park in terms of renewable energy output, load demand, and equipment parameters, there is potential for energy interaction among multiple stakeholders.

[0003] However, how to reasonably coordinate and optimize the allocation of electricity and carbon according to the needs of different stakeholders is an urgent problem to be solved. Summary of the Invention

[0004] This invention was made to solve the above-mentioned problems, and its purpose is to provide a method for distributed distribution of electric carbon among multiple entities.

[0005] This invention provides a method for distributed electricity carbon allocation among multiple entities, whereby each entity obtains corresponding electricity allocation data based on its corresponding carbon emission surplus / deficit data and electricity surplus / deficit data. The method includes the following steps: Step S1, each entity constructs a corresponding cost function based on its entity type; Step S2, each entity generates its electricity trading volume with other entities based on its corresponding electricity surplus / deficit data and sends each electricity trading volume to its corresponding entity; Step S3, each entity, based on all received electricity trading volumes, all generated electricity trading volumes, and all carbon emission surplus / deficit data, and in conjunction with the cost function and constraints, solves a multi-entity electricity cooperation and sharing model based on a Nash negotiation model, updates its generated electricity trading volumes based on the solution results, and sends the updated electricity trading volumes to its corresponding entity; Step S4, Step S3 is repeated until a preset first iteration termination condition is reached, resulting in... Step S5: Each entity initializes the electricity trading price corresponding to each optimal electricity trading volume and sends each electricity trading price to the corresponding entity. Step S6: Each entity solves the multi-entity bargaining revenue allocation model based on the Nash negotiation model, based on the corresponding optimal electricity trading volume, all electricity trading prices generated by the entity, all received electricity trading prices, and all carbon emission surplus / deficit data, combined with the cost function and constraints. The entity updates each electricity trading price generated by the entity according to the solution results and sends the updated electricity trading prices to the corresponding entity. Step S7: Step S6 is repeated until the preset second iteration termination condition is reached to obtain the optimal electricity trading price among the entities. The entity types include key emission entities and non-key emission entities, and the entity's electricity allocation data includes all optimal electricity trading volumes and optimal electricity trading prices corresponding to that entity.

[0006] The method for distributed electrocarbon allocation among multiple entities provided by this invention may also have the following feature: wherein the calculation expression of the objective function corresponding to the key emitting entity is: In the formula U i The cost for key emission subject i, where T is the total number of time points. c represents the gas consumption of the equipment of the key emission subject i at time t. gas This refers to the unit price of natural gas. The amount of electricity purchased by the key emission entity i from the upper-level power grid at time t. Let t be the electricity price sold by the upstream power grid at time t. For the amount of electricity sold by the key emission entity i to the upper-level power grid at time t, Let be the repurchase price of the upstream power grid at time t, D be the set of other entities, and λ be the unit cost of transmitting electricity through the grid. Let be the electrical energy interaction between the key emission subject i and the j-th other subject at time t. Let i be the electricity trading volume between the key emission entity i and the jth other entity at time t. The electricity trading price between the key emission entity i and the j-th other entity at time t. The unit average price at time t is the price at which carbon allowances are purchased through a carbon platform and carbon credits are used to offset excess carbon allowances. Let i be the actual carbon emissions of the key emitting entity i at time t. Let represent the carbon allowance for key emission subject i at time t. Let α be the carbon quota trading price in the upper-level carbon market at time t. e,cut The unit price for compensating for reduced electricity load. α represents the reduction in electricity load for key emission source i at time t. e,tran The compensation unit price for electrical load transfer, α represents the electrical load transfer of the key emission subject i at time t. h,cut The unit price is the compensation for the reduction in heat load. α represents the heat load reduction of the primary emission source i at time t. h,tran The unit price for compensation of heat load transfer, The heat load transfer amount of the key emission subject i at time t. The operating costs of equipment for the key emission subject i.

[0007] The method for distributed electric carbon allocation among multiple entities provided by this invention may also have the following feature: wherein the carbon quota of the key emitting entity l The calculation expression is: In the formula ε is the free carbon allowance ratio coefficient for key emission entities l. e Carbon emission limit coefficient per unit of electricity supplied. This refers to the amount of electricity purchased by the key emission entity l from the superior power grid at time t. ε represents the output power of the gas internal combustion engine that the key emission source l purchases electricity from the gas turbine at time t. h Carbon emission limit coefficient per unit of heat supplied. The output power of the waste heat boiler that the main emission source l purchases electricity from the gas turbine at time t. The output power of the gas-fired boiler purchased by the key emission entity l from the gas-fired boiler at time t, and the actual carbon emissions of the key emission entity l. The calculation expression is: In the formula For the gas consumption of the key emission subject l at time t, H g It is the average low calorific value of natural gas. The carbon dioxide emission factor for natural gas based on the lowest calorific value. This is the default value for the electricity emission factor.

[0008] The method for distributed electrocarbon allocation among multiple entities provided by this invention may also have the following feature: wherein the calculation expression of the objective function corresponding to the non-key emission entities is: In the formula U i The cost is for non-priority emission subject i, and T is the total number of time points. The electricity purchased by non-key emission entity i from the superior power grid at time t. Let t be the electricity price sold by the upstream power grid at time t. Let i be the amount of electricity sold by a non-key emission entity i to the upstream power grid at time t. Let be the repurchase price of the upstream power grid at time t, D be the set of other entities, and λ be the unit cost of transmitting electricity through the grid. Let be the electrical energy exchange amount between non-key emission subject i and other subject j at time t. Let be the electricity transaction volume between non-key emission entity i and other entities at time t. Let be the electricity trading price between non-key emission entity i and other entities at time t. Let be the selling price of the internal carbon credits at time t. The combined marginal emission factor of the regional power grid. The renewable energy output of non-key emission subject i at time i.

[0009] The method for distributed electricity carbon allocation among multiple entities provided by this invention may also have the following feature: the constraints include electricity constraints for P2P transactions, cooperative transaction price constraints, demand response constraints, and energy balance constraints. The calculation expression for the electricity constraints of P2P transactions is as follows: In the formula, D is the set of all subjects. Let the electricity trading volume between entity i and entity j at time t be the calculation expression for the cooperative transaction price constraint: In the formula Let t be the on-grid electricity price. Let be the electricity transaction price between subject i and subject j at time t. Let be the time-of-use electricity price at time t. Let t be the carbon inclusive price in the carbon trading market at time t. Let be the internal carbon credit selling price at time t. The average unit price at time t for offsetting excess carbon allowances through carbon platform purchases and carbon credits. Let be the carbon quota trading price in the higher-level carbon market at time t. The expression for calculating the demand response constraint is:

[0010] In the formula The optimized electrical load for the main emission source at time t. The electrical load of the main emission source l at time t is the key emission source l. The electrical power reduced by the main emission source at time t. for, The upper limit of power reduction for key emission entities, β e,tran is the maximum proportionality coefficient for power load transfer, and T is the total number at all times. The optimized heat load for the main emission source at time t. The heat load of the main body l to be emitted at time t. The heat load reduced by the main emission source at time t. To reduce the upper limit of heat load for key emission sources, β h,tran The maximum proportionality coefficient for heat load transfer is given by the following expression for calculating the energy balance constraint: In the formula The output power of the gas-fired internal combustion engine of the main emission source at time t. The power consumption of the electric boiler for the main emission source at time t. To ensure the constant monitoring of the heat production capacity of the main emission source, For renewable energy output from non-critical emission source f at time t, Let f be the on-grid power of the non-key emission source at time t. Let f be the volume of electricity traded between non-key emission entity f and other entity j at time t.

[0011] The method for distributed energy carbon allocation among multiple entities provided by this invention may also have the following feature: the expression for the multi-entity energy cooperation and sharing model is: In the formula Let U be the electricity transaction volume between subject i and subject j at time t, D be the set of subjects, and U be the total electricity transaction volume between subjects i and j at time t. i For the cost function corresponding to subject i, in step S3, the calculation expression for the electricity trading volume of each subject in each iteration is as follows:

[0012] In the formula These are the Lagrange multipliers corresponding to subject i and subject j during the k-th iteration calculation. Let be the amount of electricity traded between entity i and entity j at time t during the k-th iteration. Let be the amount of electricity traded between subject j and subject i at time t during the k-th iteration. Let ρ be the penalty coefficient corresponding to subject i, T be the total number of times, and ρ be the total number of times. P1 The penalty coefficient is used. The termination condition for the first iteration is that the iteration converges or the number of iterations exceeds the preset maximum number of iterations. The expression for calculating the convergence of the iteration in the k-th iteration is: In the formula δ P1 This is the convergence threshold for the original residual.

[0013] The method for distributed carbon allocation among multiple entities provided by this invention may also have the following feature: the expression for the multi-entity bargaining revenue allocation model is as follows: In the formula, D is the set of all subjects. As a point of breakdown in negotiations, The operating cost of subject i under certain circumstances. For the energy interaction cost between subject i and other subjects, in step S6, the calculation expression for the energy transaction price for each subject in each iteration is as follows:

[0014]

[0015] In the formula These are the Lagrange multipliers corresponding to subject i and subject j during the k-th iteration calculation. Let be the electricity trading price between entity i and entity j at time t during the k-th iteration. Let be the electricity trading price between entity j and entity i at time t during the k-th iteration. Let ρ be the penalty coefficient corresponding to subject i, T be the total number of times, and ρ be the total number of times. P2 The penalty coefficient is used. The termination condition for the second iteration is that the iteration converges or the number of iterations exceeds the preset maximum number of iterations. The expression for calculating the convergence of the iteration in the k-th iteration is: In the formula δ P2 This is the convergence threshold for the original residual.

[0016] The method for distributed carbon allocation among multiple entities provided by this invention may also have the following feature: When, based on carbon emission surplus / deficit data, the carbon quota deficit of each key emitting entity is less than the upper limit of voluntary emission reduction offsets, the unit average price... and selling price The calculation expression is:

[0017] In the formula Let t be the carbon quota trading price in the higher-level carbon market. Let X be the carbon inclusive price in the carbon trading market at time t. t For R t The reciprocal of , where F is the set of non-key emission entities. Let f be the carbon inclusive supply from non-critical emitting entities at time t, and L be the set of critical emitting entities. The carbon emission reduction demand of the key emitting entity l at time t. The total carbon inclusive supply at time t represents the amount of carbon credits provided by the cooperative alliance formed by all stakeholders. Let t represent the total carbon allowance demand of the cooperative alliance at time t.

[0018] The method for distributed carbon allocation among multiple entities provided by this invention may also have the following feature: wherein, based on carbon emission surplus / deficit data, the carbon allowance deficit of at least one key emitting entity is greater than the voluntary emission reduction offset limit and the total supply... Less than total demand At that time, the average price per unit and selling price The calculation expression is:

[0019] In the formula Let t be the carbon credit price in the carbon trading market, and β be the carbon credit offset ratio stipulated in the carbon credit rules. Let l be the actual carbon emissions of a key emitting entity at time t. Based on carbon emission surplus / deficit data, at least one key emitting entity has a carbon quota deficit greater than the voluntary emission reduction offset limit and a total supply. Greater than or equal to total demand At that time, the average price per unit and selling price The calculation expression is:

[0020] The role and effect of invention

[0021] According to the method for distributed electricity carbon allocation among multiple entities involved in this invention, on the one hand, the optimal electricity trading volume and optimal electricity trading price are calculated sequentially through a cost function, a multi-entity electricity cooperation and sharing model, and a multi-entity bargaining revenue allocation model, while also considering carbon allowances; on the other hand, the distributed solution is performed using the alternating multiplier direction method, effectively protecting the information privacy of all parties. Therefore, the method for distributed electricity carbon allocation among multiple entities of this invention can achieve optimal allocation of electricity and carbon allowances among multiple entities. Attached Figure Description

[0022] Figure 1 This is a flowchart illustrating a method for distributed carbon allocation among multiple entities in an embodiment of the present invention.

[0023] Figure 2 This is a schematic diagram of a multi-entity energy architecture formed by four entities in an embodiment of the present invention;

[0024] Figure 3 This is a schematic diagram of the results of inter-subject electrical energy interaction in an embodiment of the present invention;

[0025] Figure 4 This is a schematic diagram illustrating the electricity trading prices at various times during the multi-entity cooperative operation in an embodiment of the present invention;

[0026] Figure 5 This is a schematic diagram illustrating the surplus or deficit of carbon emission reduction within the park in an embodiment of the present invention;

[0027] Figure 6 This is a schematic diagram of the carbon trading price within the park in an embodiment of the present invention. Detailed Implementation

[0028] To make the technical means, creative features, objectives and effects of the present invention easy to understand, the following embodiments, in conjunction with the accompanying drawings, specifically illustrate the method of distributed carbon allocation among multiple subjects in the present invention.

[0029] This embodiment provides a method for distributed electricity carbon allocation among multiple entities, allowing each entity to obtain corresponding electricity allocation data based on its carbon emission surplus / deficit data and electricity surplus / deficit data. The entity types include key emitting entities and non-key emitting entities. The electricity allocation data for each entity includes all optimal electricity trading volumes and optimal electricity trading prices corresponding to that entity.

[0030] In this embodiment, all entities are members of a cooperative alliance. Key emitting entities are prosumers, while non-key emitting entities are renewable energy operators. Different entities have different carbon emission surplus / deficit data (i.e., remaining or exceeding carbon allowances) and different electricity surplus / deficit data (i.e., insufficient or excessive electricity). To address this, this embodiment considers a distributed electricity carbon allocation method among multiple entities. This method maximizes the interests of each entity by calculating the optimal electricity trading price and optimal electricity trading volume, and further coordinates the carbon allowances and electricity consumption of each entity to achieve optimal interaction between carbon allowances and electricity consumption.

[0031] Figure 1 This is a flowchart illustrating a method for distributed carbon allocation among multiple entities, as described in an embodiment of the present invention.

[0032] like Figure 1 As shown, the method for distributed electric carbon allocation among multiple entities includes the following steps:

[0033] Step S1: Each entity constructs a corresponding cost function based on its entity type.

[0034] The objective function for the key emission entities is calculated as follows:

[0035]

[0036] In the formula U i The cost for key emission subject i, where T is the total number of time points. c represents the gas consumption of the equipment of the key emission subject i at time t. gas This refers to the unit price of natural gas. The amount of electricity purchased by the key emission entity i from the upper-level power grid at time t. Let t be the electricity price sold by the upstream power grid at time t. For the amount of electricity sold by the key emission entity i to the upper-level power grid at time t, Let be the repurchase price of the upstream power grid at time t, D be the set of other entities, and λ be the unit cost of transmitting electricity through the grid. Let be the electrical energy interaction between the key emission subject i and the j-th other subject at time t. Let i be the electricity trading volume between the key emission entity i and the jth other entity at time t. The electricity trading price between the key emission entity i and the j-th other entity at time t. The unit average price at time t is the price at which carbon allowances are purchased through a carbon platform and carbon credits are used to offset excess carbon allowances. Let i be the actual carbon emissions of the key emitting entity i at time t. Let represent the carbon allowance for key emission subject i at time t. Let α be the carbon quota trading price in the upper-level carbon market at time t. e,cut The unit price for compensating for reduced electricity load. α represents the reduction in electricity load for key emission source i at time t. e,tran The compensation unit price for electrical load transfer, α represents the electrical load transfer of the key emission subject i at time t. h,cut The unit price is the compensation for the reduction in heat load. α represents the heat load reduction of the primary emission source i at time t. h,tran The unit price for compensation of heat load transfer, The heat load transfer amount of the key emission subject i at time t. The operating costs of equipment for the key emission subject i.

[0037] Carbon quotas of key emission entities The calculation expression is:

[0038]

[0039] In the formula ε is the free carbon allowance ratio coefficient for key emission entities l. e Carbon emission limit coefficient per unit of electricity supplied. This refers to the amount of electricity purchased by the key emission entity l from the superior power grid at time t. ε represents the output power of the gas internal combustion engine that the key emission source l purchases electricity from the gas turbine at time t. h Carbon emission limit coefficient per unit of heat supplied. The output power of the waste heat boiler that the main emission source l purchases electricity from the gas turbine at time t. The output power of the gas-fired boiler that the main emission source l purchases electricity from at time t.

[0040] Actual carbon emissions of key emission entities The calculation expression is:

[0041]

[0042] In the formula For the gas consumption of the key emission subject l at time t, H g It is the average low calorific value of natural gas. The carbon dioxide emission factor for natural gas based on the lowest calorific value. This is the default value for the electricity emission factor.

[0043] The objective function for non-key emission entities is calculated as follows:

[0044]

[0045] In the formula U i The cost is for non-priority emission subject i, and T is the total number of time points. The electricity purchased by non-key emission entity i from the superior power grid at time t. Let t be the electricity price sold by the upstream power grid at time t. Let i be the amount of electricity sold by a non-key emission entity i to the upstream power grid at time t. Let be the repurchase price of the upstream power grid at time t, D be the set of other entities, and λ be the unit cost of transmitting electricity through the grid. Let be the electrical energy exchange amount between non-key emission subject i and other subject j at time t. Let be the electricity transaction volume between non-key emission entity i and other entities at time t. Let be the electricity trading price between non-key emission entity i and other entities at time t. Let be the selling price of the internal carbon credits at time t. The combined marginal emission factor of the regional power grid. The renewable energy output of non-key emission subject i at time i.

[0046] In this embodiment, the unit average price and selling price Linked to the carbon emission surplus / deficit data of each entity, specifically:

[0047] Based on carbon emission surplus / deficit data, when the carbon quota deficit of each major emitter is less than the upper limit of voluntary emission reduction offsets, the average unit price... and selling price The calculation expression is:

[0048]

[0049] In the formula Let t be the carbon quota trading price in the higher-level carbon market. Let X be the carbon inclusive price in the carbon trading market at time t. t For R t The reciprocal of , where F is the set of non-key emission entities. Let f be the carbon inclusive supply from non-critical emitting entities at time t, and L be the set of critical emitting entities. The carbon emission reduction demand of the key emitting entity l at time t. The total carbon inclusive supply at time t represents the amount of carbon credits provided by the cooperative alliance formed by all stakeholders. Let t represent the total carbon allowance demand of the cooperative alliance at time t.

[0050] Based on carbon emission surplus / deficit data, at least one major emitting entity has a carbon allowance deficit greater than the voluntary emission reduction offset limit and a total supply greater than the allowance deficit. Less than total demand hour,

[0051] Average unit price and selling price The calculation expression is:

[0052]

[0053] In the formula Let t be the carbon credit price in the carbon trading market, and β be the carbon credit offset ratio stipulated in the carbon credit rules. This represents the actual carbon emissions of the key emitting entity l at time t.

[0054] Based on carbon emission surplus / deficit data, at least one major emitting entity has a carbon allowance deficit greater than the voluntary emission reduction offset limit and a total supply greater than the allowance deficit. Greater than or equal to total demand hour,

[0055] Average unit price and selling price The calculation expression is:

[0056]

[0057]

[0058] In step S2, each entity generates its electricity trading volume with other entities based on the corresponding electricity surplus / deficit data, and sends each electricity trading volume to the corresponding entity.

[0059] Step S3: Each entity, based on all received electricity trading volumes, all electricity trading volumes generated by the entity, and all carbon emission surplus / deficit data, and in conjunction with cost functions and constraints, solves the multi-entity electricity cooperation and sharing model constructed based on the Nash negotiation model. Based on the solution results, the entity updates the electricity trading volumes generated by the entity and sends the updated electricity trading volumes to the corresponding entities.

[0060] The constraints include electricity constraints, cooperative transaction price constraints, demand response constraints, and energy balance constraints for P2P transactions.

[0061] The formula for calculating the electricity constraint in P2P transactions is:

[0062]

[0063] In the formula, D is the set of all subjects. The electricity transaction volume between subject i and subject j at time t.

[0064] The formula for calculating the price constraint in a cooperative transaction is:

[0065]

[0066] In the formula Let t be the on-grid electricity price. Let be the electricity transaction price between subject i and subject j at time t. Let be the time-of-use electricity price at time t. Let t be the carbon inclusive price in the carbon trading market at time t. Let be the internal carbon credit selling price at time t. The average unit price at time t for offsetting excess carbon allowances through carbon platform purchases and carbon credits. Let t be the carbon quota trading price in the higher-level carbon market at time t.

[0067] The expression for calculating the demand response constraint is:

[0068]

[0069] In the formula The optimized electrical load for the main emission source at time t. The electrical load of the main emission source l at time t is the key emission source l. The electrical power reduced by the main emission source at time t. for, The upper limit of power reduction for key emission entities, β e,tran is the maximum proportionality coefficient for power load transfer, and T is the total number at all times. The optimized heat load for the main emission source at time t. The heat load of the main body l to be emitted at time t. The heat load reduced by the main emission source at time t. To reduce the upper limit of heat load for key emission sources, β h,tran This is the maximum proportionality coefficient for heat load transfer.

[0070] The calculation expression for the energy balance constraint is as follows:

[0071]

[0072] In the formula The output power of the gas-fired internal combustion engine of the main emission source at time t. The power consumption of the electric boiler for the main emission source at time t. To ensure the constant monitoring of the heat production capacity of the main emission source, For renewable energy output from non-critical emission source f at time t, Let f be the on-grid power of the non-key emission source at time t. Let f be the volume of electricity traded between non-key emission entity f and other entity j at time t.

[0073] The expression for the multi-entity power cooperation and sharing model in step S3 is as follows:

[0074]

[0075] In the formula Let U be the electricity transaction volume between subject i and subject j at time t, D be the set of subjects, and U be the total electricity transaction volume between subjects i and j at time t. i Let i be the cost function corresponding to subject i.

[0076] In the above multi-entity power cooperation and sharing model Decoupling is achieved by introducing auxiliary variables. And construct the corresponding augmented Lagrange functional. The calculation expression for the electricity trading volume of each entity in each iteration is as follows:

[0077]

[0078] In the formula These are the Lagrange multipliers corresponding to subject i and subject j during the k-th iteration calculation. Let be the amount of electricity traded between entity i and entity j at time t during the k-th iteration. Let be the amount of electricity traded between subject j and subject i at time t during the k-th iteration. Let ρ be the penalty coefficient corresponding to subject i, T be the total number of times, and ρ be the total number of times. P1 This is the penalty coefficient.

[0079] Step S4: Repeat step S3 until the preset first iteration termination condition is met, and obtain the optimal electricity trading volume among the various entities. In this embodiment, the optimal electricity trading volume is the electricity trading volume obtained at the end of the iteration.

[0080] The first iteration termination condition is either iteration convergence or the number of iterations exceeds a preset maximum number of iterations. Therefore, the expression for iteration convergence during the k-th iteration in the first iteration termination condition is:

[0081]

[0082] In the formula δ P1 This is the convergence threshold for the original residual.

[0083] Step S5: Each entity initializes the electricity trading price corresponding to each optimal electricity trading volume and sends each electricity trading price to the corresponding entity.

[0084] Step S6: Each entity, based on its corresponding optimal electricity trading volume, all electricity trading prices generated by the entity, all received electricity trading prices, and all carbon emission surplus / deficit data, and in conjunction with cost functions and constraints, solves the multi-entity bargaining revenue distribution model constructed based on the Nash negotiation model. Based on the solution results, it updates the electricity trading prices generated by the entity and sends the updated electricity trading prices to the corresponding entities.

[0085] The expression for the multi-party bargaining benefit distribution model is as follows:

[0086]

[0087] In the formula, D is the set of all subjects. As a point of breakdown in negotiations, The operating cost of subject i under certain circumstances. The cost of energy interaction between subject i and other subjects. The point of breakdown in negotiation in this embodiment. Operating costs when entity i trades electricity solely with the upstream power grid The operating costs of subject i when trading with other subjects and the upper-level power grid.

[0088] Based on the aforementioned multi-party bargaining benefit distribution model, and through the analysis of... Decoupled construction and augmented Lagrange functionals The calculation expression for the electricity trading price by each entity in each iteration is as follows:

[0089]

[0090] In the formula These are the Lagrange multipliers corresponding to subject i and subject j during the k-th iteration calculation. Let be the electricity trading price between entity i and entity j at time t during the k-th iteration. Let be the electricity trading price between entity j and entity i at time t during the k-th iteration. Let ρ be the penalty coefficient corresponding to subject i, T be the total number of times, and ρ be the total number of times. P2 This is the penalty coefficient.

[0091] Step S7: Repeat step S6 until the preset second iteration termination condition is met, and obtain the optimal electricity trading price among the various entities. In this embodiment, the optimal electricity trading price is the electricity trading price obtained at the end of the iteration.

[0092] The second iteration termination condition is either iteration convergence or the number of iterations exceeds a preset maximum number of iterations. Therefore, the expression for iteration convergence during the k-th iteration in the second iteration termination condition is:

[0093]

[0094] In the formula δ P2 This is the convergence threshold for the original residual.

[0095] In this embodiment, a cooperative alliance consisting of four entities is constructed, meaning there are four entities within the park. The method for distributed carbon allocation among multiple entities in this embodiment is then simulated and tested.

[0096] Figure 2 This is a schematic diagram of a multi-entity energy architecture formed by four entities in an embodiment of the present invention.

[0097] like Figure 2 As shown, the four entities are pharmaceutical companies (prosumers 1), food companies (prosumers 2), electronics companies (prosumers 3), and renewable energy operators (REO). The energy supply equipment involved includes wind turbines (WT), photovoltaics (PV), gas turbines (GT), electric boilers (EB), gas boilers (GB), and electricity storage (ES).

[0098] The equipment parameters of the above-mentioned energy supply equipment are shown in the table below:

[0099]

[0100] The first column of the table above lists the various energy supply devices, while the second and third columns show the energy efficiency and unit operation and maintenance cost of the corresponding devices, respectively. Gas turbines include gas internal combustion engines and waste heat boilers, and electricity storage is provided by batteries. For example, the cell in the fourth row and second column indicates that the energy efficiency of the gas internal combustion engine is 0.4.

[0101] In addition, the energy prices for different energy sources are set as shown in the table below:

[0102]

[0103]

[0104] The first column in the table above shows the price categories for each energy type, while the second and third columns show the corresponding price ranges and prices for each category. For example, the cell in the fifth row and second column indicates that the user's electricity price range covers all time periods.

[0105] In this embodiment, the load data of the four entities were determined based on the typical daily load data of actual enterprises in a certain industrial park in Shanghai during winter, and the carbon quota price and PHCER were 100 CNY / t and 80 CNY / t, respectively, and the offset coefficient of the emission reduction certificate was 10%.

[0106] In this embodiment, the power coordination of the four entities is carried out by considering the distributed distribution of electricity carbon among multiple entities.

[0107] Figure 3 This is a schematic diagram of the results of electrical energy interaction between multiple entities in an embodiment of the present invention.

[0108] like Figure 3 As shown, the horizontal axis represents time in hours (h), and the vertical axis represents power in kilowatts (kW). Positive power represents electricity sold, and negative power represents electricity purchased. It can be seen that the electricity sold and purchased in each time period are symmetrical about the horizontal axis. This demonstrates that the supply and demand of electricity within the park remains balanced in each time period, further verifying the effectiveness of the method considering distributed electricity carbon allocation among multiple entities. Since the distributed wind turbines within the REO operate continuously and have no electricity load demand of their own, the REO is the main supplier in the electricity sharing transaction. During the period from 9:00 to 16:00, the photovoltaic output is relatively large, so producer-consumer 2 has surplus electricity to sell. However, since producer-consumer 2 does not have gas-fired power generation equipment, it needs to purchase electricity from the outside during the non-photovoltaic output period. During the period from 9:00 to 16:00, producer-consumer 1's electricity demand increases dramatically, requiring it to purchase electricity from both the REO and producer-consumer 2. Because producer-consumer 1 experiences a significant increase in heat load between 18:00 and 21:00, its internal combustion engine output increases, thus acting as a supplier in the electricity exchange. Producer-consumer 3, due to its larger overall electricity load, consistently acts as a demander in the transaction.

[0109] Figure 4 This is a schematic diagram of the electricity trading prices at various times during the cooperative operation of multiple entities in an embodiment of the present invention.

[0110] like Figure 4 As shown, the horizontal axis represents time in hours (h), and the vertical axis represents electricity price in yuan / kW·h. It can be seen that when there is zero electricity trading, the electricity price is the grid connection price. When electricity trading exists, due to constraints, the trading price is always higher than the grid connection price. Since the REO grid connection price, the producer-consumer purchase price difference, and the purchase and sale price difference between producers / consumers and the upstream grid are the economic drivers for cooperative sharing (P2P) transactions, the cooperative sharing transaction price is usually higher than the grid connection price but lower than the purchase price from the grid.

[0111] Figure 5 This is a schematic diagram illustrating the surplus or deficit of carbon emission reduction within the park in an embodiment of the present invention.

[0112] like Figure 5 As shown, the horizontal axis represents time in hours (h), and the vertical axis represents the carbon emission reduction surplus or deficit in kilograms.

[0113] Figure 6 This is a schematic diagram of the carbon trading price within the park in an embodiment of the present invention.

[0114] like Figure 6 As shown, the horizontal axis represents time in hours (h), and the vertical axis represents price in yuan / ton.

[0115] according to Figure 5 and Figure 6 It is known that the amount of carbon credits certified by the REO is always greater than the overall carbon quota demand of producers and consumers. Therefore, the supply-demand ratio is always greater than 1, resulting in the carbon trading price within the industrial park, calculated based on the supply-demand ratio pricing mechanism, being close to the carbon credit trading price in the carbon market. When there is no internal demand for carbon quotas, the internal trading price is the same as the carbon credit trading price in the carbon market.

[0116] In summary, the distributed carbon allocation method among multiple entities in this embodiment makes significant contributions to power coordination among entities, carbon quota coordination, and promoting the consumption of renewable energy and reducing carbon emissions in industrial parks.

[0117] (1) Coordinating the power of the main body

[0118] The model used in the multi-entity distributed energy carbon allocation method considers the energy supply and demand of each entity, cost factors, and P2P energy trading constraints, promoting the rational allocation of energy among different entities. For example, in energy sharing and trading analysis, based on the energy production and demand characteristics of each entity, such as producers and consumers acting as energy suppliers or consumers at different times according to their own photovoltaic output, electricity load demand, and equipment operation status. In this way, the balance of power supply and demand within the park is achieved at different times, improving energy utilization efficiency, reducing the dependence of each entity on the upper-level power grid, and enhancing the stability and reliability of the park's energy system.

[0119] (2) Coordinating carbon quotas

[0120] The multi-entity distributed carbon allocation method also designs corresponding carbon trading mechanisms tailored to the different characteristics of prosumers and renewable energy operators, achieving effective coordination of carbon allowances. For prosumers, their carbon allowance allocation is related to the output of their internal gas-fired equipment and the electricity purchased from their upstream suppliers. By rationally arranging energy consumption and participating in carbon trading, they can meet carbon emission requirements and avoid waste or shortage of carbon allowances. For renewable energy operators, participating in carbon trading by selling carbon credits certified by renewable energy power generation not only brings them revenue but also increases the supply of carbon emission reductions within the park. Simultaneously, the carbon asset management platform formulates trading prices within the park based on the carbon emission reduction surplus and shortage information provided by various entities and acts as an agent for trading, further optimizing the allocation and utilization of carbon allowances and promoting the achievement of the park's overall carbon emission reduction targets.

[0121] (3) Promote the consumption of renewable energy and reduce carbon emissions

[0122] The multi-entity distributed energy carbon allocation method significantly promotes the local consumption of distributed renewable energy and reduces the overall carbon emissions of the park. During multi-entity cooperative operation, through energy sharing transactions, each producer and consumer prioritizes the consumption of renewable energy generated by REO (Renewable Energy Organisation), reducing the purchase of high-carbon electricity from the upper-level grid. For example, in the case study analysis, compared with independent operation by each entity, participating in the energy sharing alliance significantly increased the renewable energy consumption rate within the park, while simultaneously reducing carbon emissions. During peak nighttime REO output periods, producers and consumers reduce their purchases from the upper-level grid and utilize REO wind turbines more extensively; during peak daytime photovoltaic output periods, producers and consumers can also effectively share and utilize photovoltaic power. This optimization of the energy consumption structure fundamentally reduces the park's carbon emission level, powerfully promoting the park's development towards a green and low-carbon direction, and has significant practical implications for achieving dual-carbon goals.

[0123] The role and effect of the embodiments

[0124] According to the distributed electricity and carbon allocation method involving multiple entities involved in this embodiment, on the one hand, the optimal electricity trading volume and optimal electricity trading price are calculated sequentially through a cost function, a multi-entity electricity cooperation and sharing model, and a multi-entity bargaining revenue allocation model, while taking carbon allowances into account; on the other hand, a distributed solution is performed using the alternating multiplier direction method, effectively protecting the information privacy of all parties. In summary, this method can achieve optimal allocation of electricity and carbon allowances among multiple entities.

[0125] Those skilled in the art will appreciate that the present invention is not limited to the foregoing embodiments. The foregoing embodiments and descriptions are merely illustrative of the principles of the present invention. Various changes and modifications may be made to the present invention without departing from the spirit and scope of the present invention. Such changes and modifications are intended to fall within the scope of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for distributed electricity carbon allocation among multiple entities, wherein each entity obtains corresponding electricity allocation data based on its corresponding carbon emission surplus / deficit data and electricity surplus / deficit data, characterized in that, Includes the following steps: Step S1: Each of the entities constructs a corresponding cost function based on its entity type; Step S2: Each entity generates its electricity trading volume with other entities based on the corresponding electricity surplus / deficit data, and sends each electricity trading volume to the corresponding entity. Step S3: Each entity, based on all the received electricity trading volumes, all the electricity trading volumes generated by the entity, and all the carbon emission surplus / deficit data, and in conjunction with the cost function and constraints, solves the multi-entity electricity cooperation and sharing model constructed based on the Nash negotiation model, updates each of the electricity trading volumes generated by the entity according to the solution results, and sends the updated electricity trading volumes to the corresponding entity. Step S4: Repeat step S3 until the preset first iteration termination condition is met, and obtain the optimal power trading volume among the various entities. Step S5: Each entity initializes the electricity trading price corresponding to each optimal electricity trading volume, and sends each electricity trading price to the corresponding entity. Step S6: Each entity, based on the corresponding optimal electricity trading volume, all electricity trading prices generated by the entity, all received electricity trading prices, and all carbon emission surplus / deficit data, and in conjunction with the cost function and constraints, solves the multi-entity bargaining revenue allocation model constructed based on the Nash negotiation model, updates each electricity trading price generated by the entity according to the solution results, and sends the updated electricity trading prices to the corresponding entity. Step S7: Repeat step S6 until the preset second iteration termination condition is met, and obtain the optimal electricity trading price among the various entities. The types of entities mentioned include key emitting entities and non-key emitting entities. The power allocation data of the entity includes all the optimal power trading volumes and the optimal power trading prices corresponding to the entity.

2. The method for distributed carbon allocation among multiple entities according to claim 1, characterized in that: in, The calculation expression for the objective function corresponding to the key emission entities is as follows: In the formula U i The cost for key emission subject i, where T is the total number of time points. c represents the gas consumption of the equipment of the key emission subject i at time t. gas This refers to the unit price of natural gas. The amount of electricity purchased by the key emission entity i from the upper-level power grid at time t. Let t be the electricity price sold by the upstream power grid at time t. For the amount of electricity sold by the key emission entity i to the upper-level power grid at time t, Let be the repurchase price of the upstream power grid at time t, D be the set of other entities, and λ be the unit cost of transmitting electricity through the grid. Let be the electrical energy interaction between the key emission subject i and the j-th other subject at time t. Let i be the electricity trading volume between the key emission entity i and the jth other entity at time t. The electricity trading price between the key emission entity i and the j-th other entity at time t. The unit average price at time t is the price at which carbon allowances are purchased through a carbon platform and carbon credits are used to offset excess carbon allowances. Let i be the actual carbon emissions of the key emitting entity i at time t. Let represent the carbon allowance for key emission subject i at time t. Let α be the carbon quota trading price in the upper-level carbon market at time t. e,cut The unit price for compensating for reduced electricity load. α represents the reduction in electricity load for key emission source i at time t. e,tran The compensation unit price for electrical load transfer, α represents the electrical load transfer of the key emission subject i at time t. h,cut The unit price is the compensation for the reduction in heat load. α represents the heat load reduction of the primary emission source i at time t. h,tran The unit price for compensation of heat load transfer, The heat load transfer amount of the key emission subject i at time t. The operating costs of equipment for the key emission subject i.

3. The method for considering distributed electric carbon allocation among multiple entities according to claim 2, characterized in that: in, Carbon quotas of key emission entities The calculation expression is: In the formula ε is the free carbon allowance ratio coefficient for key emission entities l. e Carbon emission limit coefficient per unit of electricity supplied. This refers to the amount of electricity purchased by the key emission entity l from the superior power grid at time t. ε represents the output power of the gas internal combustion engine that the key emission source l purchases electricity from the gas turbine at time t. h Carbon emission limit coefficient per unit of heat supplied. The output power of the waste heat boiler that the main emission source l purchases electricity from the gas turbine at time t. The output power of the gas-fired boiler that the key emission entity l purchases electricity from at time t is given. The actual carbon emissions of the key emission subject l The calculation expression is: In the formula For the gas consumption of the key emission subject l at time t, H g It is the average low calorific value of natural gas. The carbon dioxide emission factor for natural gas based on the lowest calorific value. This is the default value for the electricity emission factor.

4. The method for distributed carbon allocation among multiple entities according to claim 1, characterized in that: in, The calculation expression for the objective function corresponding to the non-key emission entities is as follows: In the formula U i The cost is for non-priority emission subject i, and T is the total number of time points. The electricity purchased by non-key emission entity i from the superior power grid at time t. Let t be the electricity price sold by the upstream power grid at time t. Let i be the amount of electricity sold by a non-key emission entity i to the upstream power grid at time t. Let be the repurchase price of the upstream power grid at time t, D be the set of other entities, and λ be the unit cost of transmitting electricity through the grid. Let be the electrical energy exchange amount between non-key emission subject i and other subject j at time t. Let be the electricity transaction volume between non-key emission entity i and other entities at time t. Let be the electricity trading price between non-key emission entity i and other entities at time t. Let be the selling price of the internal carbon credits at time t. The combined marginal emission factor of the regional power grid. The renewable energy output of non-key emission subject i at time i.

5. The method for distributed carbon allocation among multiple entities according to claim 1, characterized in that: in, The constraints include electricity constraints, cooperative transaction price constraints, demand response constraints, and energy balance constraints for P2P transactions. The calculation expression for the power constraint of the P2P transaction is as follows: In the formula, D is the set of all subjects. Let represent the electricity transaction volume between subject i and subject j at time t. The calculation expression for the cooperative transaction price constraint is as follows: In the formula Let t be the on-grid electricity price. Let be the electricity transaction price between subject i and subject j at time t. Let be the time-of-use electricity price at time t. Let t be the carbon inclusive price in the carbon trading market at time t. Let be the internal carbon credit selling price at time t. The average unit price at time t for offsetting excess carbon allowances through carbon platform purchases and carbon credits. Let t be the carbon quota trading price in the higher-level carbon market at time t. The calculation expression for the demand response constraint is: In the formula The optimized electrical load for the main emission source at time t. The electrical load of the main emission source l at time t is the key emission source l. The electrical power reduced by the main emission source at time t. for, The upper limit of power reduction for key emission entities, β e,tran is the maximum proportionality coefficient for power load transfer, and T is the total number at all times. The optimized heat load for the main emission source at time t. The heat load of the main body l to be emitted at time t. The heat load reduced by the main emission source at time t. To reduce the upper limit of heat load for key emission sources, β h,tran This is the maximum proportionality coefficient for heat load transfer. The calculation expression for the energy balance constraint is as follows: In the formula The output power of the gas-fired internal combustion engine of the main emission source at time t. The power consumption of the electric boiler for the main emission source at time t. To ensure the constant monitoring of the heat production capacity of the main emission source, For renewable energy output from non-critical emission source f at time t, Let f be the on-grid power of the non-key emission source at time t. Let f be the volume of electricity traded between non-key emission entity f and other entity j at time t.

6. The method for distributed electric carbon allocation among multiple entities according to claim 1, characterized in that: in, The expression for the multi-entity power cooperation and sharing model is: In the formula Let U be the electricity transaction volume between subject i and subject j at time t, D be the set of subjects, and U be the total electricity transaction volume between subjects i and j at time t. i The cost function corresponding to subject i. In step S3, the calculation expression for the electricity trading volume by each entity in each iteration is as follows: In the formula These are the Lagrange multipliers corresponding to subject i and subject j during the k-th iteration calculation. Let be the amount of electricity traded between entity i and entity j at time t during the k-th iteration. Let be the amount of electricity traded between subject j and subject i at time t during the k-th iteration. Let ρ be the penalty coefficient corresponding to subject i, T be the total number of times, and ρ be the total number of times. P1 The penalty coefficient is... The first iteration termination condition is that the iteration converges or the number of iterations exceeds a preset maximum number of iterations. The expression for calculating convergence in the k-th iteration is: In the formula δ P1 This is the convergence threshold for the original residual.

7. The method for distributed carbon allocation among multiple entities according to claim 1, characterized in that: in, The expression for the multi-party bargaining benefit distribution model is as follows: In the formula, D is the set of all subjects. As a point of breakdown in negotiations, The operating cost of subject i under certain circumstances. The cost of electrical energy interaction between subject i and other subjects. In step S6, the calculation expression for the electricity trading price is as follows for each entity in each iteration: In the formula These are the Lagrange multipliers corresponding to subject i and subject j during the k-th iteration calculation. Let be the electricity trading price between entity i and entity j at time t during the k-th iteration. Let be the electricity trading price between entity j and entity i at time t during the k-th iteration. Let ρ be the penalty coefficient corresponding to subject i, T be the total number of times, and ρ be the total number of times. P2 The penalty coefficient is... The second iteration termination condition is that the iteration converges or the number of iterations exceeds a preset maximum number of iterations. The expression for calculating convergence in the k-th iteration is: In the formula δ P2 This is the convergence threshold for the original residual.

8. The method for distributed carbon allocation among multiple entities according to claim 1, characterized in that: in, Based on the aforementioned carbon emission surplus / deficit data, when the carbon quota deficit of each of the key emission entities is less than the upper limit of voluntary emission reduction offsets, the average unit price... and selling price The calculation expression is: In the formula Let t be the carbon quota trading price in the higher-level carbon market. Let X be the carbon inclusive price in the carbon trading market at time t. t For R t The reciprocal of , where F is the set of non-key emission entities. Let f be the carbon inclusive supply from non-critical emitting entities at time t, and L be the set of critical emitting entities. The carbon emission reduction demand of the key emitting entity l at time t. The total carbon inclusive supply at time t represents the amount of carbon credits provided by the cooperative alliance formed by all stakeholders. Let t represent the total carbon allowance demand of the cooperative alliance at time t.

9. The method for distributed carbon allocation among multiple entities according to claim 8, characterized in that: in, Based on the aforementioned carbon emission surplus / deficit data, at least one of the key emission entities has a carbon allowance deficit greater than the voluntary emission reduction offset limit and a total supply greater than the allowance deficit. Less than total demand hour, Average unit price and selling price The calculation expression is: In the formula Let t be the carbon credit price in the carbon trading market, and β be the carbon credit offset ratio stipulated in the carbon credit rules. This represents the actual carbon emissions of the key emitting entity l at time t. Based on the aforementioned carbon emission surplus / deficit data, at least one of the key emission entities has a carbon allowance deficit greater than the voluntary emission reduction offset limit and a total supply greater than the allowance deficit. Greater than or equal to total demand hour, Average unit price and selling price The calculation expression is:

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