Multi-agent benefit allocation method and device based on zero-carbon park green electricity hydrogen production

Abstract

The application relates to the technical field of green electricity hydrogen production, in particular to a multi-subject benefit distribution method and device based on zero-carbon park green electricity hydrogen production, wherein the method comprises the following steps: acquiring source network load storage hydrogen system operation data and multi-subject economic parameters in a zero-carbon park; constructing a source network load storage hydrogen collaborative operation model, solving new energy consumption power and other parameters; establishing a dynamic green electricity attribute label tracking model, marking, decomposing and correcting multi-class hydrogen production electricity, calculating green electricity hydrogen production proportion, green hydrogen yield and carbon emission reduction; forming a distributable income pool based on green electricity consumption income and the like; constructing a multi-subject dynamic contribution degree evaluation model according to the green electricity supply of each subject; correcting marginal contribution distribution results based on the dynamic contribution degree, obtaining each subject benefit distribution result; feeding back the settlement result to the next cycle operation plan, realizing closed-loop collaboration of green electricity hydrogen production operation optimization, green hydrogen identification, carbon income accounting and multi-subject dynamic benefit distribution.

Description

Technical Field

[0001] This application relates to the field of green electricity hydrogen production technology, and in particular to a multi-stakeholder benefit distribution method and apparatus for green electricity hydrogen production in zero-carbon industrial parks. Background Technology

[0002] In practice, green electricity-to-hydrogen projects are typically not completed by a single entity, but rather involve multiple parties, including new energy investment entities, incremental distribution network operators, energy storage operators, hydrogen production operators, hydrogen-consuming enterprises, industrial park management entities, and carbon asset management entities. These different entities differ in their resource input, asset boundaries, cost-bearing, operational responsibilities, revenue demands, and risk exposure. New energy investment entities focus on green electricity consumption prices and generation revenue; incremental distribution network operators focus on network asset utilization rates and transmission and distribution service revenue; energy storage operators focus on regulation service revenue and cycle life losses; hydrogen production operators focus on electrolyzer utilization hours and unit hydrogen production costs; hydrogen-consuming enterprises focus on hydrogen procurement costs, hydrogen supply stability, and gray hydrogen substitution revenue; and industrial park management entities focus on achieving zero-carbon targets, carbon asset certification, and demonstration and promotion effects.

[0003] Existing green electricity-to-hydrogen technologies focus more on electrolyzer capacity configuration, hydrogen production cost calculation, and optimization of new energy consumption or energy storage configuration. They typically treat industrial parks as unified dispatch entities, with less consideration given to revenue distribution and interest coordination among multiple stakeholders. When green electricity-to-hydrogen projects enter the actual operation phase, the lack of a clear revenue distribution mechanism can easily lead to unclear attribution of green electricity revenue, green hydrogen revenue, carbon emission reduction revenue, and transmission and distribution service revenue, thereby affecting the enthusiasm of various stakeholders to participate.

[0004] Furthermore, existing methods are often not precise enough in calculating green electricity and green hydrogen. The actual power consumption of an electrolyzer may come from direct supply from new energy sources, green electricity released from energy storage, and electricity purchased from the external grid. If the sources of power consumption of the electrolyzer cannot be accurately tracked, it is difficult to determine the green hydrogen production, the proportion of green hydrogen, and the corresponding carbon emission reduction, and it is also difficult to generate reliable settlement documents for electricity, hydrogen, carbon, and cash flow.

[0005] The existing revenue distribution methods suffer from insufficient dynamism. Some projects use fixed proportions, fixed electricity prices, or post-negotiation methods for revenue sharing, which fails to reflect changes in renewable energy output, hydrogen demand, electricity prices, carbon prices, energy storage regulation contributions, and the risk-bearing levels of stakeholders across different operating cycles. Fixed distribution methods may result in insufficient incentives for high-contributing stakeholders, excessively high returns for low-contributing stakeholders, or returns for some stakeholders below their minimum participation requirements, thereby affecting the stability of cooperation.

[0006] In summary, existing green electricity-to-hydrogen methods in zero-carbon industrial parks suffer from several problems: operational optimization and revenue distribution are disconnected; the green electricity attribute of energy storage release is difficult to track; green hydrogen production is difficult to accurately determine; carbon emission reduction benefits are difficult to calculate; and the revenue distribution among multiple stakeholders lacks measurable technical basis. Furthermore, operational results cannot be fed back to scheduling strategies, all of which urgently need to be addressed. Summary of the Invention

[0007] This application provides a multi-stakeholder benefit distribution method and apparatus for green electricity hydrogen production in zero-carbon industrial parks, in order to solve the problems in existing green electricity hydrogen production methods in zero-carbon industrial parks, such as the disconnect between green electricity hydrogen production operation optimization and benefit distribution, difficulty in tracking the green electricity attributes of energy storage release, difficulty in accurately identifying green hydrogen production, difficulty in calculating carbon emission reduction benefits, lack of measurable technical basis for multi-stakeholder benefit distribution, and inability to provide feedback on scheduling strategies based on operation results.

[0008] The first aspect of this application provides a multi-stakeholder benefit allocation method for green electricity-to-hydrogen production in a zero-carbon industrial park, comprising the following steps: acquiring operational data of the source-grid-load-storage hydrogen system and multi-stakeholder economic parameters within the target zero-carbon industrial park, and constructing a source-grid-load-storage hydrogen collaborative operation model based on the operational data and economic parameters; solving the source-grid-load-storage hydrogen collaborative operation model to obtain multiple collaborative operation data for each operating period, and establishing a corresponding dynamic green electricity attribute tag tracking model based on the multiple collaborative operation data, and tagging the electricity consumption for hydrogen production of various types through the dynamic green electricity attribute tag tracking model. The data is recorded, decomposed, and corrected to obtain the corresponding green electricity-to-hydrogen ratio, green hydrogen production, and carbon emission reduction. Based on the green electricity-to-hydrogen ratio, green hydrogen production, and carbon emission reduction, an allocable revenue pool for the green electricity-to-hydrogen project is established. A multi-entity dynamic contribution evaluation model is constructed based on the allocable revenue pool and the green hydrogen operation indicators corresponding to each entity. The dynamic comprehensive contribution of each entity is calculated using the multi-entity dynamic contribution evaluation model. The marginal contribution allocation result of each entity is calculated, and the marginal contribution allocation result is corrected using the dynamic comprehensive contribution to obtain the revenue allocation result of each entity.

[0009] Based on the above-mentioned technical means, the embodiments of this application combine the optimization of the coordinated operation of source-grid-load-storage hydrogen, the tracking of green electricity sources, the accounting of green hydrogen and carbon emission reduction, the assessment of the contribution of multiple entities, and the settlement of revenue distribution. This effectively improves the local consumption level of new energy in zero-carbon parks, the accuracy of green hydrogen identification, the credibility of carbon revenue accounting, and the stability of multi-entity coordinated operation, and supports the efficient operation, transparent accounting, and sustainable collaboration of green electricity to hydrogen production projects in zero-carbon parks.

[0010] Optionally, in one embodiment of this application, the step of acquiring the operating data of the source-grid-load-storage hydrogen system and multi-entity economic parameters within the target zero-carbon park, and constructing a source-grid-load-storage hydrogen collaborative operation model based on the operating data and the multi-entity economic parameters, includes: acquiring the operating data of the source-grid-load-storage hydrogen system and multi-entity economic parameters within the target zero-carbon park, wherein the operating data of the source-grid-load-storage hydrogen system includes new energy power generation, park conventional load power, energy storage state of charge, electrolyzer operating status, hydrogen demand, hydrogen storage status, external grid power purchase and sale, power purchase and sale price, and carbon emission factor; the multi-entity economic parameters include new energy power generation cost, transmission and distribution service price, energy storage operating cost, electrolyzer operating cost, hydrogen sales price, gray hydrogen substitution cost, carbon emission reduction revenue unit price, and revenue constraints of each participating entity; and constructing a source-grid-load-storage hydrogen collaborative operation model for the target zero-carbon park based on the operating data and the multi-entity economic parameters. An objective function is defined to maximize the overall operating benefits or minimize the overall operating costs of the target zero-carbon park, and multiple corresponding constraints are determined. Based on the objective function and the multiple constraints, a source-grid-load-storage hydrogen collaborative operation model is constructed. The multiple constraints include new energy output constraints, park power balance constraints, energy storage charging and discharging constraints, electrolyzer operation constraints, hydrogen supply and demand balance constraints, green electricity consumption constraints, carbon emission reduction constraints, and external grid interaction constraints. The park power balance constraint is that the sum of the new energy consumption power, the external grid power purchase power, and the energy storage discharge power in the target zero-carbon park is equal to the sum of the conventional load power, electrolyzer hydrogen production power, energy storage charging power, and external grid power sales power in the target zero-carbon park. The electrolyzer operation constraints include minimum operating power constraints, maximum operating power constraints, start-stop state constraints, ramping constraints, and hydrogen production efficiency constraints. The electrolyzer hydrogen production in each time period is calculated based on the electrolyzer power consumption and the hydrogen production coefficient per unit of power.

[0011] Based on the above technical means, the embodiments of this application construct a source-grid-load-storage hydrogen collaborative operation model to incorporate new energy consumption, energy storage regulation, electrolytic hydrogen production, external grid interaction and hydrogen supply into a unified optimization process, thereby improving the local consumption capacity of new energy in zero-carbon parks and the economic efficiency of green electricity hydrogen production.

[0012] Optionally, in one embodiment of this application, the step of solving the source-grid-load-storage hydrogen collaborative operation model to obtain multiple collaborative operation data for each operating period, and establishing a corresponding dynamic green electricity attribute tag tracking model based on the multiple collaborative operation data, and marking, decomposing, and correcting multiple types of hydrogen production electricity consumption through the dynamic green electricity attribute tag tracking model to obtain the corresponding green electricity hydrogen production ratio, green hydrogen production, and carbon emission reduction, includes: solving the source-grid-load-storage hydrogen collaborative operation model to obtain multiple collaborative operation data for each operating period, wherein the multiple collaborative operation data includes new energy consumption power, green electricity hydrogen production power, energy storage charging and discharging power, external grid power purchase and sale power, hydrogen production of the electrolyzer, hydrogen supply, and abandoned electricity; and based on the new energy consumption power, green electricity hydrogen production power, and green electricity hydrogen production power, the step of establishing a corresponding dynamic green electricity attribute tag tracking model to establish ... A dynamic green electricity attribute tag tracking model is established for the power consumption of the electrolyzer, based on the power, the energy storage charging and discharging power, and the power purchased from the external power grid. This model sets dynamic green electricity attribute tags for the electricity entering the energy storage system and supplied to the electrolyzer. The electrolyzer's power consumption is then decomposed into multiple types of hydrogen production electricity based on these tags. These multiple types of hydrogen production electricity include hydrogen production from direct renewable energy supply, hydrogen production from green electricity released from energy storage, and hydrogen production from electricity purchased from the external power grid. Based on these three types of hydrogen production, the green electricity production ratio and green hydrogen output for each operating period are calculated. Finally, the carbon emission reduction is calculated based on the green hydrogen output, the preset amount of gray hydrogen to be replaced, and the carbon emission factor.

[0013] Based on the aforementioned technical means, this application embodiment establishes a dynamic green electricity attribute tagging and tracking model to mark the source and correct the attributes of the electricity entering the energy storage system and supplying the electrolyzer. This model can distinguish between hydrogen production electricity directly supplied from new energy sources, hydrogen production electricity released from energy storage, and hydrogen production electricity purchased from the external power grid, thereby improving the accuracy of identifying the proportion of green electricity used for hydrogen production and the production of green hydrogen. Furthermore, this application embodiment calculates carbon emission reductions and carbon emission reduction benefits based on the proportion of green electricity used for hydrogen production, green hydrogen production, gray hydrogen substitution, and carbon emission factors, establishing a traceable mapping relationship between electricity, hydrogen, carbon, and cash flow.

[0014] Optionally, in one embodiment of this application, the step of establishing an allocable revenue pool for the green electricity-to-hydrogen project based on the green electricity-to-hydrogen ratio, the green hydrogen production, and the carbon emission reduction, and constructing a multi-entity dynamic contribution evaluation model based on the allocable revenue pool and the corresponding green hydrogen operation indicators of each entity, to calculate the dynamic comprehensive contribution of each entity through the multi-entity dynamic contribution evaluation model, includes: calculating the green electricity consumption revenue, hydrogen sales revenue, energy storage regulation revenue, transmission and distribution service revenue, purchased electricity substitution revenue, and carbon emission reduction revenue of the target zero-carbon park based on the green electricity-to-hydrogen ratio, the green hydrogen production, the carbon emission reduction, the green electricity consumption, energy storage regulation, transmission and distribution service revenue, purchased electricity substitution revenue, and carbon emission reduction revenue, to calculate the green electricity consumption revenue, hydrogen sales revenue, energy storage regulation revenue, transmission and distribution service revenue, and purchased electricity substitution revenue of the target zero-carbon park through the green electricity consumption revenue, hydrogen sales revenue, energy storage regulation revenue, and transmission and distribution service revenue. The revenue from the green electricity-to-hydrogen project, the revenue from the purchase of electricity as a substitute, and the revenue from carbon emission reduction are used to establish an allocable revenue pool. Green hydrogen operation indicators corresponding to each entity are obtained, and based on these indicators, a multi-entity dynamic contribution evaluation model is constructed. The dynamic comprehensive contribution of the new energy investment entity, incremental distribution network operation entity, energy storage operation entity, hydrogen production operation entity, hydrogen-using enterprise, and park management entity is calculated using this model. The green hydrogen operation indicators include green electricity supply, transmission and distribution service electricity, green electricity transferred from energy storage, energy storage regulation electricity, effective hydrogen production from electrolyzers, green hydrogen consumption, carbon emission reduction, and operational risk exposure. The multi-entity dynamic contribution evaluation model includes an electricity contribution sub-model, a hydrogen contribution sub-model, a carbon contribution sub-model, a regulation contribution sub-model, and a risk contribution sub-model.

[0015] Based on the above technical means, the embodiments of this application form an allocable income pool through multi-dimensional income accounting, and combine it with a multi-entity dynamic contribution evaluation model to improve the accuracy, fairness and rationality of income distribution.

[0016] Optionally, in one embodiment of this application, the step of calculating the marginal contribution allocation result of each entity and correcting the marginal contribution allocation result through the dynamic comprehensive contribution degree to obtain the benefit allocation result of each entity includes: calculating the marginal benefit increment of each entity under different cooperation states, and calculating the benefit allocation result of each entity based on the dynamic comprehensive contribution degree, the marginal benefit increment of each entity under the different cooperation states, the minimum benefit constraint and the cooperation stability constraint.

[0017] Based on the above technical means, the embodiments of this application calculate the dynamic comprehensive contribution of each subject based on the contribution of electricity, hydrogen, carbon, regulation and risk, and determine the benefit distribution result by combining the marginal contribution allocation method, thereby improving the rationality, dynamism and incentive compatibility of the benefit distribution of multiple subjects.

[0018] Optionally, in one embodiment of this application, after obtaining the revenue distribution results of each entity, the method further includes: generating settlement results for the electricity, hydrogen, carbon, and cash flow of each entity based on the revenue distribution results, and feeding the settlement results back to the green electricity-to-hydrogen production plan, energy storage regulation plan, hydrogen supply plan, and revenue distribution parameters for the next operating cycle, so as to regenerate new revenue distribution results, so that the rolling optimization operation of the green electricity-to-hydrogen production system of the target zero-carbon park is coordinated with the dynamic revenue of multiple entities. The settlement results include the green electricity consumption revenue of the new energy entity, the transmission and distribution service revenue of the incremental distribution network entity, the regulation service revenue of the energy storage entity, the hydrogen production operation revenue of the hydrogen production entity, the green hydrogen substitution revenue of the hydrogen-using enterprise, the collaborative management revenue of the park management entity, and the corresponding green electricity vouchers, green hydrogen production vouchers, and carbon emission reduction vouchers.

[0019] Based on the aforementioned technical means, this application embodiment feeds back the revenue distribution results to the next cycle's operation plan, enabling the green electricity hydrogen production capacity, energy storage regulation strategy, hydrogen supply plan, dynamic green electricity attribute tags, and revenue distribution parameters to be continuously adjusted in response to changes in new energy output, hydrogen demand, electricity prices, and carbon prices. This achieves integrated and coordinated optimization of green electricity hydrogen production operation, green electricity tracking, green hydrogen identification, carbon emission reduction accounting, multi-entity revenue distribution, and rolling feedback control.

[0020] Optionally, in one embodiment of this application, the step of calculating the dynamic comprehensive contribution of new energy investment entities, incremental distribution network operators, energy storage operators, hydrogen production operators, hydrogen-using enterprises, and park management entities through the multi-entity dynamic contribution evaluation model includes: determining the corresponding dynamic comprehensive contribution based on the green electricity supply, green electricity stability, reduction in curtailment, and new energy investment and operation and maintenance costs of the new energy investment entities; and calculating the corresponding dynamic comprehensive contribution based on the transmission and distribution service volume, network carrying capacity, power supply reliability, and internal green electricity transmission contribution of the incremental distribution network operators. The contribution is determined based on the energy storage operator's charging and discharging capacity, green energy transferred from energy storage, and peak shaving and valley filling contribution. The dynamic comprehensive contribution is also determined based on the hydrogen production operator's effective utilization hours of the electrolyzer, hydrogen production efficiency, green hydrogen production, and hydrogen supply stability. Furthermore, the dynamic comprehensive contribution is determined based on the hydrogen-using enterprise's green hydrogen consumption, gray hydrogen substitution, flexible hydrogen utilization capacity, and carbon emission reduction contribution. Finally, the dynamic comprehensive contribution is determined based on the park management entity's project organization and coordination, carbon asset verification, zero-carbon indicator completion rate, and transaction cost reduction contribution.

[0021] Based on the aforementioned technical means, this application embodiment calculates the electricity contribution, hydrogen contribution, carbon contribution, regulation contribution, and risk contribution for new energy investment entities, incremental distribution network operation entities, energy storage operation entities, hydrogen production operation entities, hydrogen-using enterprises, and park management entities, respectively, and forms a dynamic comprehensive contribution degree for each entity. This allows for multi-dimensional contribution calculation based on the differences between entities, making contribution calculation more accurate and allocation more equitable.

[0022] A second aspect of this application provides a multi-entity benefit-sharing device for green electricity-to-hydrogen production in a zero-carbon industrial park, comprising: a first modeling module, used to acquire operating data of the source-grid-load-storage hydrogen system and multi-entity economic parameters within the target zero-carbon industrial park, and to construct a source-grid-load-storage hydrogen collaborative operation model based on the operating data of the source-grid-load-storage hydrogen system and the multi-entity economic parameters; and a solving module, used to solve the source-grid-load-storage hydrogen collaborative operation model to obtain multiple collaborative operation data for each operating period, and to establish a corresponding dynamic green electricity attribute tag tracking model based on the multiple collaborative operation data, and to mark multiple types of electricity consumption for hydrogen production through the dynamic green electricity attribute tag tracking model. The system is divided and corrected to obtain the corresponding green electricity-to-hydrogen ratio, green hydrogen production, and carbon emission reduction. A second modeling module is used to establish an allocable revenue pool for the green electricity-to-hydrogen project based on the green electricity-to-hydrogen ratio, green hydrogen production, and carbon emission reduction. A multi-entity dynamic contribution evaluation model is constructed based on the allocable revenue pool and the corresponding green hydrogen operation indicators for each entity, so as to calculate the dynamic comprehensive contribution of each entity through the multi-entity dynamic contribution evaluation model. A correction module is used to calculate the marginal contribution allocation result of each entity and correct the marginal contribution allocation result through the dynamic comprehensive contribution to obtain the revenue allocation result of each entity.

[0023] Optionally, in one embodiment of this application, the first modeling module includes: a first acquisition unit, used to acquire the operating data of the source-grid-load-storage hydrogen system and multi-entity economic parameters within the target zero-carbon park, wherein the operating data of the source-grid-load-storage hydrogen system includes new energy power generation, park conventional load power, energy storage state of charge, electrolyzer operating status, hydrogen demand, hydrogen storage status, external grid power purchase and sale, power purchase and sale price, and carbon emission factor; the multi-entity economic parameters include new energy power generation cost, transmission and distribution service price, energy storage operating cost, electrolyzer operating cost, hydrogen sales price, gray hydrogen substitution cost, carbon emission reduction revenue unit price, and revenue constraints of each participating entity; and a construction unit, used to construct an objective function for the source-grid-load-storage hydrogen collaborative operation model of the target zero-carbon park based on the operating data of the source-grid-load-storage hydrogen system and the multi-entity economic parameters, so as to maximize the comprehensive operating benefits of the target zero-carbon park. Alternatively, the overall operating cost can be minimized, and multiple corresponding constraints can be determined to construct the source-grid-load-storage hydrogen collaborative operation model based on the objective function and the multiple constraints. These constraints include constraints on new energy output, park power balance, energy storage charging and discharging, electrolyzer operation, hydrogen supply and demand balance, green electricity consumption, carbon emission reduction, and external grid interaction. The park power balance constraint is defined as the sum of new energy consumption power, external grid power purchase power, and energy storage discharge power within the target zero-carbon park equal to the sum of conventional load power, electrolyzer hydrogen production power, energy storage charging power, and external grid power sales power within the target zero-carbon park. The electrolyzer operation constraints include minimum operating power constraints, maximum operating power constraints, start-stop state constraints, ramping constraints, and hydrogen production efficiency constraints. The electrolyzer hydrogen production volume for each time period is calculated based on the electrolyzer power consumption and the hydrogen production coefficient per unit of electricity.

[0024] Optionally, in one embodiment of this application, the solving module includes: a computation unit, used to solve the source-grid-load-storage hydrogen collaborative operation model to obtain multiple collaborative operation data for each operating segment, wherein the multiple collaborative operation data includes new energy consumption power, green electricity hydrogen production power, energy storage charging and discharging power, external grid power purchase and sale power, the hydrogen production of the electrolyzer, hydrogen supply, and abandoned power; and a building unit, used to build a dynamic green electricity attribute tag tracking model for electrolyzer power consumption based on the new energy consumption power, the green electricity hydrogen production power, the energy storage charging and discharging power, and the external grid power purchase and sale power, so as to obtain multiple collaborative operation data for each operating segment, wherein the multiple collaborative operation data includes new energy consumption power, green electricity hydrogen production power, energy storage charging and discharging power, and ... green electricity hydrogen production power, energy storage charging and discharging power, and external grid power purchase and sale power, so as to obtain multiple collaborative operation data for each operating segment, wherein the multiple collaborative operation data includes new energy consumption power, green electricity hydrogen production power, green electricity hydrogen production power, green electricity hydrogen production power, green electricity hydrogen production power, green electricity hydrogen production power, The attribute tag tracking model sets dynamic green electricity attribute tags for the electricity entering the energy storage system and supplying the electrolyzer, and decomposes the electricity consumption of the electrolyzer into multiple types of hydrogen production electricity based on the dynamic green electricity attribute tags. The multiple types of hydrogen production electricity include hydrogen production electricity directly supplied from new energy sources, hydrogen production electricity released from energy storage, and hydrogen production electricity purchased from the external power grid. The first calculation unit is used to calculate the green electricity hydrogen production ratio and green hydrogen production for each operating period based on the hydrogen production electricity directly supplied from new energy sources, the hydrogen production electricity released from energy storage, and the hydrogen production electricity purchased from the external power grid, and to calculate the carbon emission reduction based on the green hydrogen production, the preset amount of gray hydrogen to be replaced, and the carbon emission factor.

[0025] Optionally, in one embodiment of this application, the second modeling module includes: a second calculation unit, used to calculate the green electricity consumption revenue, hydrogen sales revenue, energy storage regulation revenue, transmission and distribution service revenue, purchased electricity substitution revenue, and carbon emission reduction revenue of the target zero-carbon park based on the green electricity production ratio, the green hydrogen production, the carbon emission reduction, green electricity consumption, energy storage regulation, transmission and distribution service revenue, purchased electricity substitution revenue, and carbon emission reduction revenue, so as to establish an allocable revenue pool for the green electricity production project through the green electricity consumption revenue, the hydrogen sales revenue, the energy storage regulation revenue, the transmission and distribution service revenue, the purchased electricity substitution revenue, and the carbon emission reduction revenue; and a second acquisition unit, used to acquire the corresponding revenue of each entity. The green hydrogen operation indicators are defined, and based on these indicators, a multi-entity dynamic contribution evaluation model is constructed. This model calculates the dynamic comprehensive contribution of new energy investment entities, incremental distribution network operators, energy storage operators, hydrogen production operators, hydrogen-using enterprises, and park management entities. The green hydrogen operation indicators include green electricity supply, transmission and distribution service electricity, green electricity transferred from energy storage, energy storage regulation electricity, effective hydrogen production from electrolyzers, green hydrogen consumption, carbon emission reduction, and operational risk exposure. The multi-entity dynamic contribution evaluation model includes an electricity contribution sub-model, a hydrogen contribution sub-model, a carbon contribution sub-model, a regulation contribution sub-model, and a risk contribution sub-model.

[0026] Optionally, in one embodiment of this application, the correction module includes: a third calculation unit, used to calculate the marginal revenue increment of each entity under different cooperation states, and to calculate the revenue allocation result of each entity based on the dynamic comprehensive contribution, the marginal revenue increment of each entity under the different cooperation states, the minimum revenue constraint and the cooperation stability constraint.

[0027] Optionally, in one embodiment of this application, it further includes: an optimization module, used to generate settlement results for the electricity, hydrogen, carbon, and cash flow of each entity based on the revenue allocation results after obtaining the revenue allocation results of each entity, and to feed the settlement results back to the green electricity-to-hydrogen production plan, energy storage regulation plan, hydrogen supply plan, and revenue allocation parameters for the next operating cycle, so as to regenerate new revenue allocation results, so that the rolling optimization operation of the green electricity-to-hydrogen production system of the target zero-carbon park is coordinated with the dynamic revenue of multiple entities. The settlement results include the green electricity consumption revenue of the new energy entity, the transmission and distribution service revenue of the incremental distribution network entity, the regulation service revenue of the energy storage entity, the hydrogen production operation revenue of the hydrogen production entity, the green hydrogen substitution revenue of the hydrogen-using enterprise, the collaborative management revenue of the park management entity, and the corresponding green electricity vouchers, green hydrogen production vouchers, and carbon emission reduction vouchers.

[0028] Optionally, in one embodiment of this application, the second acquisition unit includes: a first determining subunit, used to determine the corresponding dynamic comprehensive contribution based on the green electricity supply, green electricity stability, reduction in curtailment, and operation and maintenance costs of the new energy investment entity; a second determining subunit, used to calculate the corresponding dynamic comprehensive contribution based on the transmission and distribution service volume, network carrying capacity, power supply reliability, and internal green electricity transmission contribution of the incremental distribution network operator; a third determining subunit, used to determine the corresponding dynamic comprehensive contribution based on the charging and discharging volume, green electricity transferred from energy storage, and peak shaving and valley filling contribution of the energy storage operator; a fourth determining subunit, used to determine the corresponding dynamic comprehensive contribution based on the effective utilization hours of the electrolyzer, hydrogen production efficiency, green hydrogen production, and hydrogen supply stability of the hydrogen production operator; a fifth determining subunit, used to determine the corresponding dynamic comprehensive contribution based on the green hydrogen consumption, gray hydrogen substitution, flexible hydrogen use capacity, and carbon emission reduction contribution of the hydrogen-using enterprise; and a sixth determining subunit, used to determine the corresponding dynamic comprehensive contribution based on the project organization and coordination, carbon asset verification, zero-carbon indicator completion rate, and transaction cost reduction contribution of the park management entity.

[0029] A third aspect of this application provides an electronic device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor. The processor executes the program to implement the multi-stakeholder benefit distribution method for green electricity production in zero-carbon industrial parks as described in the above embodiments.

[0030] A fourth aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described multi-stakeholder benefit allocation method based on green electricity production in zero-carbon industrial parks.

[0031] A fifth aspect of this application provides a computer program product, including a computer program that is executed to implement the above-described method for distributing the benefits of green electricity generation in zero-carbon industrial parks.

[0032] Therefore, the embodiments of this application have the following beneficial effects: The embodiments of this application can obtain the operating data of the source-grid-load-storage hydrogen system and the economic parameters of multiple entities within the target zero-carbon park, and construct a source-grid-load-storage hydrogen collaborative operation model based on the operating data and economic parameters of the source-grid-load-storage hydrogen system; solve the source-grid-load-storage hydrogen collaborative operation model to obtain multiple collaborative operation data for each operating period, and establish a corresponding dynamic green electricity attribute tag tracking model based on the multiple collaborative operation data, and use the dynamic green electricity attribute tag tracking model to mark, decompose and correct multiple types of hydrogen production electricity consumption to obtain the corresponding green electricity hydrogen production ratio, green hydrogen production and carbon emission reduction; based on the green electricity hydrogen production ratio, green hydrogen production and carbon emission reduction, establish a distributable revenue pool for green electricity hydrogen production projects, and construct a multi-entity dynamic contribution evaluation model based on the distributable revenue pool for green electricity hydrogen production projects and the green hydrogen operation indicators corresponding to each entity, so as to calculate the dynamic comprehensive contribution of each entity through the multi-entity dynamic contribution evaluation model; calculate the marginal contribution allocation result of each entity, and correct the marginal contribution allocation result through the dynamic comprehensive contribution to obtain the revenue allocation result of each entity. This application integrates the optimization of hydrogen production through source-grid-load-storage collaborative operation, green electricity source tracking, green hydrogen and carbon emission reduction accounting, multi-entity contribution assessment, and revenue distribution settlement. This effectively improves the local consumption level of new energy in zero-carbon parks, the accuracy of green hydrogen identification, the credibility of carbon revenue accounting, and the stability of multi-entity collaborative operation. It supports the efficient operation, transparent accounting, and sustainable collaboration of green electricity-to-hydrogen projects in zero-carbon parks. Therefore, it solves the problems in existing green electricity-to-hydrogen methods in zero-carbon parks, such as the disconnect between green electricity-to-hydrogen operation optimization and revenue distribution, difficulty in tracking the green electricity attributes of energy storage release, difficulty in accurately identifying green hydrogen production, difficulty in calculating carbon emission reduction revenue, lack of measurable technical basis for multi-entity revenue distribution, and the inability to provide feedback on scheduling strategies based on operational results.

[0033] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0034] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 This is a flowchart illustrating a multi-stakeholder benefit-sharing method for hydrogen production from green electricity in a zero-carbon industrial park, according to an embodiment of this application. Figure 2 A schematic diagram of a zero-carbon industrial park source-grid-load-storage hydrogen collaborative system is provided for embodiments of this application; Figure 3 A schematic diagram of a green electricity source tracing and green hydrogen identification process provided in this application embodiment; Figure 4 A schematic diagram of a multi-stakeholder interest distribution model provided in this application embodiment; Figure 5 A schematic diagram of a rolling optimization and benefit feedback closed loop provided in an embodiment of this application; Figure 6 A schematic diagram of the execution logic of a multi-stakeholder benefit allocation method based on green electricity production in a zero-carbon industrial park, provided for an embodiment of this application; Figure 7 A schematic diagram comparing key operating indicators before and after using the method of this application is provided for an embodiment of this application; Figure 8 This application provides a schematic diagram of a multi-entity revenue distribution result. Figure 9 This is an example diagram of a multi-stakeholder benefit-sharing device based on green electricity production in a zero-carbon industrial park, according to an embodiment of this application. Figure 10 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0035] Among them, 10-a multi-entity benefit distribution device based on green electricity hydrogen production in zero-carbon industrial parks; 100-first modeling module, 200-solution module, 300-second modeling module, 400-correction module; 1001-memory, 1002-processor, 1003-communication interface. Detailed Implementation

[0036] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0037] The following describes, with reference to the accompanying drawings, a method and apparatus for multi-stakeholder benefit allocation based on green electricity production in zero-carbon industrial parks, according to embodiments of this application. Addressing the problems mentioned in the background section, this application provides a method for multi-stakeholder benefit allocation based on green electricity production in zero-carbon industrial parks. This method involves constructing a collaborative operation model for hydrogen production from sources, grid, load, and storage in zero-carbon industrial parks to determine the collaborative operation scheme among new energy consumption, energy storage regulation, electrolyzer hydrogen production, external grid interaction, and hydrogen supply; establishing a dynamic green electricity attribute tag tracking model to determine the amount of hydrogen produced from direct new energy supply, green electricity released from energy storage, and hydrogen produced from electricity purchased from the external grid within the electrolyzer's power consumption; establishing a green hydrogen and carbon emission reduction linkage accounting model to quantify the proportion of green electricity production, green hydrogen output, gray hydrogen substitution, and carbon emission reduction benefits; and establishing... The multi-entity dynamic contribution evaluation model incorporates the electricity, hydrogen, carbon, regulation, and risk contributions of new energy investment entities, incremental distribution network operators, energy storage operators, hydrogen production operators, hydrogen-using enterprises, and park management entities into the revenue distribution process. It also uses settlement results to continuously revise the operating strategy for the next cycle, thereby achieving integrated coordination of green electricity-to-hydrogen production operation optimization, green hydrogen identification, carbon revenue accounting, multi-entity dynamic revenue distribution, and operational feedback control. This model is well-suited for zero-carbon parks with new energy power generation units, incremental distribution networks, energy storage systems, water electrolysis hydrogen production systems, hydrogen storage systems, and industrial hydrogen-using enterprises. This application combines source-grid-load-storage hydrogen collaborative operation optimization, green electricity source tracking, green hydrogen and carbon emission reduction accounting, multi-entity contribution assessment, and revenue distribution settlement, effectively improving the local consumption level of new energy in zero-carbon parks, the accuracy of green hydrogen identification, the credibility of carbon revenue accounting, and the stability of multi-entity collaborative operation. It supports the efficient operation, transparent accounting, and sustainable coordination of green electricity-to-hydrogen projects in zero-carbon parks. This solves the problems in existing zero-carbon park green electricity hydrogen production methods, such as the disconnect between green electricity hydrogen production operation optimization and revenue distribution, difficulty in tracking the green electricity attributes of energy storage release, difficulty in accurately identifying green hydrogen production, difficulty in calculating carbon emission reduction benefits, lack of measurable technical basis for multi-entity revenue distribution, and inability to provide feedback on scheduling strategies based on operation results.

[0038] Specifically, Figure 1 A flowchart illustrating a multi-stakeholder benefit distribution method based on green electricity production in a zero-carbon industrial park, provided as an embodiment of this application.

[0039] like Figure 1 As shown, the multi-stakeholder benefit-sharing method based on green electricity production in zero-carbon industrial parks includes the following steps: In step S101, the operation data of the source-grid-load hydrogen storage system and the economic parameters of multiple entities within the target zero-carbon park are obtained, and a collaborative operation model of source-grid-load hydrogen storage is constructed based on the operation data of the source-grid-load hydrogen storage system and the economic parameters of multiple entities.

[0040] This application embodiment first obtains the operational data of the hydrogen generation, grid, load, and storage system within the zero-carbon park (i.e., the target zero-carbon park), such as the operational data of new energy power generation units, park load, energy storage system, water electrolysis hydrogen production system, hydrogen storage system, hydrogen-using enterprises, and external power grid. Specifically, this includes the power generation capacity of new energy, the conventional load capacity of the park, the state of charge of energy storage, the operating status of electrolyzers, the hydrogen demand, the hydrogen storage status, the power purchased and sold by the external power grid, the power purchase and sale price, and the carbon emission factor. It also obtains the cost, price, revenue, risk, and constraint parameters of each participating entity, i.e., multi-entity economic parameters including the cost of new energy power generation, the price of transmission and distribution services, the operating cost of energy storage, the operating cost of electrolyzers, the hydrogen sales price, the cost of gray hydrogen substitution, the unit price of carbon emission reduction revenue, and the revenue constraints of each participating entity.

[0041] Secondly, the embodiments of this application aim to maximize the comprehensive operating benefits of the park or minimize the comprehensive operating costs, thereby establishing a coupled optimization model between new energy consumption, energy storage regulation, electrolysis hydrogen production, park power supply, external power purchase and sale and hydrogen supply, namely the source-grid-load-storage hydrogen collaborative operation model.

[0042] Optionally, in one embodiment of this application, the operation data of the source-grid-load-storage hydrogen system and multi-entity economic parameters within the target zero-carbon park are obtained, and a collaborative operation model of source-grid-load-storage hydrogen system is constructed based on the operation data and multi-entity economic parameters. This includes: obtaining the operation data of the source-grid-load-storage hydrogen system and multi-entity economic parameters within the target zero-carbon park, wherein the operation data of the source-grid-load-storage hydrogen system includes new energy power generation, park conventional load power, energy storage state of charge, electrolyzer operation status, hydrogen demand, hydrogen storage status, external grid power purchase and sale, power purchase and sale price, and carbon emission factor; and the multi-entity economic parameters include new energy power generation cost, transmission and distribution service price, energy storage operation cost, electrolyzer operation cost, hydrogen sales price, gray hydrogen substitution cost, carbon emission reduction revenue unit price, and revenue constraints of each participating entity; and constructing a collaborative operation model of the source-grid-load-storage hydrogen system for the target zero-carbon park based on the operation data and multi-entity economic parameters. The objective function aims to maximize the overall operational benefits or minimize the overall operational costs of the target zero-carbon park. Multiple constraints are defined to construct a source-grid-load-storage hydrogen collaborative operation model based on the objective function and these constraints. These constraints include constraints on new energy output, park power balance, energy storage charging and discharging, electrolyzer operation, hydrogen supply and demand balance, green electricity consumption, carbon emission reduction, and external grid interaction. The park power balance constraint is defined as the sum of new energy consumption power, external grid power purchase power, and energy storage discharge power within the target zero-carbon park equaling the sum of conventional load power, electrolyzer hydrogen production power, energy storage charging power, and external grid power sales power within the target zero-carbon park. The electrolyzer operation constraints include minimum operating power constraints, maximum operating power constraints, start-stop state constraints, ramping constraints, and hydrogen production efficiency constraints. The hydrogen production capacity of the electrolyzer in each time period is calculated based on the electrolyzer power consumption and the hydrogen production coefficient per unit of electricity.

[0043] like Figure 2 As shown, the new energy power generation units within the zero-carbon park include photovoltaic power generation units and / or wind power generation units. These units supply power to the park's conventional loads, energy storage systems, and water electrolysis hydrogen production systems via an incremental distribution network. The energy storage system smooths out fluctuations in new energy output, transfers green electricity, and supports the continuous operation of the electrolyzers. The water electrolysis hydrogen production system converts green electricity into hydrogen, which is then stored in a hydrogen storage system and further supplied to hydrogen-consuming enterprises. The park's energy management and benefit distribution center collects operational data, performs collaborative optimization, tracks green electricity, calculates carbon emission reduction benefits, calculates the multi-entity benefit distribution results, and outputs settlement instructions.

[0044] Hydrogen-using enterprises have continuous or periodic hydrogen demand. The embodiments of this application can dynamically adjust the electrolyzer operating power and hydrogen storage strategy based on the minimum hydrogen supply demand of the hydrogen-using enterprises, the maximum acceptable green hydrogen price, and the gray hydrogen substitution ratio, thereby balancing green electricity consumption and hydrogen supply stability.

[0045] Specifically, before the start of an operating cycle, the park's Energy Management and Profit Distribution Center collects the data shown in Table 1: Table 1

[0046] It should be noted that the source-grid-load-storage hydrogen collaborative operation model is used to coordinate the consumption of new energy sources, energy storage regulation, electrolysis hydrogen production, and interaction with the external power grid, while meeting the power and hydrogen supply needs of the industrial park. Therefore, the objective of this model can be set to maximize the overall operating benefits or minimize the overall operating costs.

[0047] When the goal is to maximize overall operational benefits, the objective function can be expressed as: (1) Where F represents the overall operating revenue of the park; Indicates the revenue from green electricity consumption; This indicates revenue from hydrogen sales; Indicates the benefits of carbon emission reduction; This indicates revenue from energy storage regulation (i.e., revenue from energy storage regulation services). This indicates revenue from power transmission and distribution services; This indicates the revenue from the substitution of purchased electricity; This indicates the operation and maintenance costs of new energy sources; This indicates the cost of purchasing electricity from the external power grid; This represents the operating cost of energy storage (i.e., the cost of energy storage losses). This indicates the operating cost of the electrolyzer; This indicates the cost of penalties for abandoning electricity; This indicates the penalty cost for hydrogen supply deviation.

[0048] The power balance constraints in the park are: (2) in, Let t be the renewable energy consumption power in time period t; Power purchased from the external power grid; This refers to the energy storage discharge power; This represents the park's standard load power. Hydrogen production power of the electrolyzer; Power for energy storage charging; This refers to the power sold externally.

[0049] The power output constraints for new energy sources are: (3) The electrolyzer operating constraints include minimum operating power constraints, maximum operating power constraints, start-up and shutdown constraints, ramp-up constraints, and hydrogen production efficiency constraints. The hydrogen production rate for each time period is calculated based on the electrolyzer's power consumption and the hydrogen production coefficient per unit of power. The mathematical expression for these electrolyzer operating constraints is as follows: (4) (5) in, These are the start-up and shutdown state variables for the electrolytic cell; and These are the minimum and maximum operating power of the electrolytic cell, respectively. and These are the limits for power reduction and power ramp-up of the electrolytic cell, respectively.

[0050] The constraints for calculating hydrogen production capacity are: (6) in, Let t be the amount of hydrogen produced in time period t; The hydrogen production coefficient per unit of electricity; For time intervals.

[0051] The energy storage state of charge constraints are: (7) (8) The hydrogen supply and demand balance constraint is: (9) in, This is the amount of hydrogen replenished by ash; This is a variable related to the hydrogen supply gap. When the system requires priority supply of green hydrogen, it can be adjusted accordingly. and Set penalty costs.

[0052] Therefore, this application embodiment constructs a source-grid-load-storage hydrogen collaborative operation model to incorporate new energy consumption, energy storage regulation, electrolytic hydrogen production, external grid interaction and hydrogen supply into a unified optimization process, thereby improving the local consumption capacity of new energy in zero-carbon parks and the economic efficiency of green electricity hydrogen production.

[0053] In step S102, the source-grid-load-storage hydrogen collaborative operation model is solved to obtain multiple collaborative operation data for each operating period. Based on the multiple collaborative operation data, a corresponding dynamic green electricity attribute tag tracking model is established. The dynamic green electricity attribute tag tracking model is used to mark, decompose, and correct the electricity consumption of various types of hydrogen production to obtain the corresponding green electricity hydrogen production ratio, green hydrogen production, and carbon emission reduction.

[0054] Furthermore, embodiments of this application can solve the source-grid-load-storage hydrogen collaborative operation model to obtain multiple collaborative operation data such as new energy consumption power, green electricity hydrogen production power, energy storage charging and discharging power, external grid power purchase and sale power, electrolyzer hydrogen production, hydrogen supply, and abandoned electricity during each operating period. Secondly, embodiments of this application can establish a dynamic green electricity attribute tag tracking model for electrolyzer power consumption based on new energy consumption power, green electricity hydrogen production power, energy storage charging and discharging power, and external grid power purchase and sale power. Dynamic green electricity attribute tags are set for the electricity entering the energy storage system and supplied to the electrolyzer, and the electrolyzer power consumption is decomposed into new energy direct supply hydrogen production electricity, energy storage released green electricity hydrogen production electricity, and external grid purchased electricity hydrogen production electricity based on the dynamic green electricity attribute tags.

[0055] Subsequently, embodiments of this application can calculate the green electricity hydrogen production ratio and green hydrogen production for each operating period based on the hydrogen production power from direct supply of new energy sources, the green electricity hydrogen production power from energy storage release, and the hydrogen production power from electricity purchased from external power grids, and calculate the carbon emission reduction based on the green hydrogen production, the amount of gray hydrogen replaced, and the carbon emission factor.

[0056] Optionally, in one embodiment of this application, the source-grid-load-storage hydrogen collaborative operation model is solved to obtain multiple collaborative operation data for each operating period. A corresponding dynamic green electricity attribute tagging tracking model is established based on these multiple collaborative operation data. Furthermore, the dynamic green electricity attribute tagging tracking model is used to label, decompose, and correct various types of hydrogen production electricity consumption to obtain the corresponding green electricity hydrogen production ratio, green hydrogen output, and carbon emission reduction. This includes: solving the source-grid-load-storage hydrogen collaborative operation model to obtain multiple collaborative operation data for each operating period. These multiple collaborative operation data include new energy consumption power, green electricity hydrogen production power, energy storage charging and discharging power, external grid power purchase and sale power, electrolyzer hydrogen production, hydrogen supply, and abandoned electricity. A dynamic green electricity attribute tagging tracking model is established for the electricity consumption of electrolyzers, taking into account hydrogen production power, energy storage charging and discharging power, and external grid power purchase and sale. This model assigns dynamic green electricity attribute tags to the electricity entering the energy storage system and supplied to the electrolyzers. Based on these tags, the electrolyzer power consumption is decomposed into multiple categories of hydrogen production electricity consumption, including hydrogen production electricity directly supplied from new energy sources, hydrogen production electricity released from energy storage, and hydrogen production electricity purchased from the external grid. Based on these categories, the green electricity hydrogen production ratio and green hydrogen output for each operating period are calculated. Finally, carbon emission reductions are calculated based on green hydrogen output, a preset amount of gray hydrogen to be replaced, and a carbon emission factor.

[0057] like Figure 3As shown, to accurately determine green hydrogen production, this application establishes a dynamic green electricity attribute tag tracking model for the power consumption of the electrolyzer. This model sets dynamic green electricity attribute tags for the electricity entering the energy storage system and supplied to the electrolyzer. These dynamic green electricity attribute tags include at least the electricity source, charging period, green electricity attribute ratio, energy storage loss correction coefficient, release period, and release purpose. When the energy storage system discharges to the electrolyzer, the amount of green electricity released from the energy storage system used for hydrogen production is determined based on the dynamic green electricity attribute tags, and the green electricity hydrogen production ratio and green hydrogen production are adjusted accordingly.

[0058] In the embodiments of this application, the dynamic green electricity attribute tag is generated using a time-series electricity marking method. The green electricity attribute is set for the new energy electricity entering the energy storage system, and the proportion of green electricity in the released electricity is determined according to the first-in-first-out, proportional allocation, weighted average or timestamp-based tracking method when the energy storage is discharged.

[0059] The total power consumption of the electrolytic cell in time period t is: (10) Will The hydrogen production capacity can be broken down into three parts: hydrogen production from direct renewable energy supply, hydrogen production from green electricity generated by energy storage, and hydrogen production from electricity purchased from the external power grid. (11) in, To directly supply electricity to the electrolyzers for new energy sources. Electricity released for energy storage and possessing green electricity attributes. Electricity purchased from the external power grid for hydrogen production.

[0060] When the charging power of the energy storage system comes from a combination of new energy sources and the external power grid, this application embodiment can set a green electricity attribute label for the electricity stored in the energy storage. The proportion of green electricity in the energy storage during time period t can be expressed as: (12) The amount of green electricity generated from energy storage discharge for hydrogen production is: (13) The proportion of hydrogen produced from green electricity is: (14) Green hydrogen production is: (15) when When the value equals 1, all hydrogen produced in time period t is considered green hydrogen; when... When the value is between 0 and 1, green hydrogen production is determined proportionally; when... When the value equals 0, the hydrogen produced in time period t is not included in the green hydrogen production. Therefore, the total hydrogen production can be divided into green hydrogen production and non-green electricity hydrogen production, and the carbon emission reduction can be calculated based on the green hydrogen production, the carbon emission intensity per unit of gray hydrogen, and the carbon emission intensity of the green hydrogen production process.

[0061] In addition, the project's distributable revenue pool consists of multiple revenue items, including at least green electricity consumption revenue, hydrogen sales revenue, carbon emission reduction revenue, energy storage regulation revenue, power transmission and distribution service revenue, and purchased electricity substitution revenue.

[0062] (16) The benefits of green electricity consumption are: (17) Revenue from hydrogen sales is: (18) Carbon emission reduction revenue can come from carbon trading, green certificate trading, carbon credits, internal corporate carbon pricing, or zero-carbon credit rewards in industrial parks. It can be calculated based on the amount of carbon emission reduction and the unit price of carbon emission reduction revenue, as shown in the following formula: (19) The benefits of energy storage regulation are: (20) Revenue from power transmission and distribution services is: (twenty one) The benefits of replacing purchased electricity are: (twenty two) In summary, the embodiments of this application set constraints such as power balance, new energy output, energy storage charging and discharging, electrolyzer operation, hydrogen supply and demand, green electricity consumption, carbon emission reduction, and external power grid interaction, and used mixed integer linear programming, model predictive control, second-order cone programming, dynamic programming, nonlinear programming, or heuristic optimization algorithms for solution. Secondly, the embodiments of this application can set dynamic green electricity attribute tags for the electricity entering the energy storage system and supplying the electrolyzer based on the optimized electricity flow, decompose the electricity consumption of the electrolyzer into the electricity for hydrogen production directly supplied by new energy, the electricity for hydrogen production released by energy storage, and the electricity for hydrogen production purchased from the external power grid, and calculate the green electricity hydrogen production ratio and green hydrogen production.

[0063] Therefore, this application embodiment establishes a dynamic green electricity attribute tagging and tracking model to mark the source and correct the attributes of the electricity entering the energy storage system and supplying the electrolyzer. This can distinguish between hydrogen production electricity directly supplied from new energy sources, hydrogen production electricity released from energy storage, and hydrogen production electricity purchased from the external grid, improving the accuracy of identifying the proportion of green electricity used for hydrogen production and the output of green hydrogen. Furthermore, this application embodiment calculates carbon emission reduction and carbon emission reduction benefits based on the proportion of green electricity used for hydrogen production, green hydrogen output, gray hydrogen substitution, and carbon emission factors, establishing a traceable mapping relationship between electricity, hydrogen, carbon, and cash flow.

[0064] In step S103, based on the proportion of green electricity to hydrogen production, green hydrogen production, and carbon emission reduction, an allocable revenue pool for green electricity to hydrogen production projects is established. Based on the allocable revenue pool for green electricity to hydrogen production projects and the green hydrogen operation indicators corresponding to each entity, a multi-entity dynamic contribution evaluation model is constructed to calculate the dynamic comprehensive contribution of each entity through the multi-entity dynamic contribution evaluation model.

[0065] Furthermore, the embodiments of this application calculate the revenue from green electricity consumption, hydrogen sales, energy storage regulation, transmission and distribution service volume, and purchased electricity substitution based on the proportion of green electricity used for hydrogen production, green hydrogen production, carbon emission reduction, green electricity consumption, energy storage regulation, transmission and distribution service volume, purchased electricity substitution, and carbon emission reduction, thus forming an allocable revenue pool for green electricity-to-hydrogen projects. Secondly, the embodiments of this application can construct a multi-entity dynamic contribution evaluation model based on green hydrogen operation indicators such as the green electricity supply, transmission and distribution service volume, green electricity transferred from energy storage, energy storage regulation volume, effective hydrogen production from electrolyzers, green hydrogen consumption, carbon emission reduction, and operational risk exposure of each entity, thereby calculating the dynamic comprehensive contribution of new energy investment entities, incremental distribution network operation entities, energy storage operation entities, hydrogen production operation entities, hydrogen-using enterprises, and park management entities.

[0066] Optionally, in one embodiment of this application, an allocable revenue pool for green electricity-to-hydrogen projects is established based on the proportion of green electricity used for hydrogen production, green hydrogen output, and carbon emission reduction. A multi-entity dynamic contribution evaluation model is constructed based on the allocable revenue pool and the corresponding green hydrogen operation indicators of each entity. This model calculates the dynamic comprehensive contribution of each entity, including: calculating the green electricity consumption revenue, hydrogen sales revenue, energy storage regulation revenue, transmission and distribution service revenue, purchased electricity substitution revenue, and carbon emission reduction revenue of the target zero-carbon park based on the proportion of green electricity used for hydrogen production, green hydrogen output, carbon emission reduction, green electricity consumption, energy storage regulation, transmission and distribution service revenue, purchased electricity substitution revenue, and carbon emission reduction revenue. The revenue is then used to calculate the green electricity consumption revenue, hydrogen sales revenue, energy storage regulation revenue, transmission and distribution service revenue, and purchased electricity substitution revenue. A distributable revenue pool for green electricity-to-hydrogen projects is established based on the revenue from electricity substitution and carbon emission reduction. Green hydrogen operation indicators for each entity are obtained, and a multi-entity dynamic contribution evaluation model is constructed based on these indicators. The dynamic comprehensive contribution of new energy investment entities, incremental distribution network operators, energy storage operators, hydrogen production operators, hydrogen-using enterprises, and park management entities is calculated using this model. Green hydrogen operation indicators include green electricity supply, transmission and distribution service electricity, green electricity transferred from energy storage, energy storage regulation electricity, effective hydrogen production from electrolyzers, green hydrogen consumption, carbon emission reduction, and operational risk exposure. The multi-entity dynamic contribution evaluation model includes sub-models for electricity contribution, hydrogen contribution, carbon contribution, regulation contribution, and risk contribution.

[0067] In actual implementation, after completing the above revenue calculation, the embodiments of this application can calculate the distributable revenue pool of the green electricity hydrogen production project based on the green electricity consumption, green hydrogen production, hydrogen sales price, energy storage regulation, transmission and distribution service electricity, purchased electricity substitution, and carbon emission reduction, and map each revenue to the corresponding electricity voucher, hydrogen voucher, and carbon voucher, providing a basis for subsequent multi-entity settlement.

[0068] Specifically, in this embodiment, the contributions of each entity can be decomposed into cost input contribution, resource supply contribution, operation and regulation contribution, carbon emission reduction contribution, and risk-bearing contribution. For any entity Ai, its comprehensive contribution is: (twenty three) (twenty four) in, This represents the overall contribution of subject Ai; Indicates the contribution of cost input; Indicates contribution to resource supply; Indicates operational adjustment contribution; Z_i represents the contribution to carbon emission reduction; Z_i represents the contribution to risk-taking. to is the weighting coefficient, and the sum of all weights is 1.

[0069] It should be noted that the electricity contribution is used to characterize the green electricity supply, the electricity volume of transmission and distribution services, and the green electricity transferred by energy storage; the hydrogen contribution is used to characterize the effective hydrogen production of electrolyzers, the production of green hydrogen, and the consumption of green hydrogen; the carbon contribution is used to characterize the carbon emission reduction generated by green hydrogen replacing gray hydrogen; the operation regulation contribution is used to characterize the peak shaving and valley filling contribution of energy storage, the flexible operation contribution of electrolyzers, and the flexible consumption contribution of hydrogen-using enterprises; and the risk-bearing contribution is used to characterize the risks of new energy fluctuations, energy storage cycle losses, hydrogen production equipment utilization rates, hydrogen supply deviation risks, and carbon revenue price fluctuation risks.

[0070] The multi-entity dynamic contribution evaluation model includes an electricity contribution sub-model, a hydrogen contribution sub-model, a carbon contribution sub-model, a regulation contribution sub-model, and a risk contribution sub-model. The electricity contribution sub-model is used to characterize the green electricity supply, the electricity volume of transmission and distribution services, and the green electricity transferred by energy storage. The hydrogen contribution sub-model is used to characterize the effective hydrogen production of electrolyzers and the amount of green hydrogen consumed. The carbon contribution sub-model is used to characterize the carbon emission reduction formed by green hydrogen replacing gray hydrogen. The regulation contribution sub-model is used to characterize the regulation contribution of energy storage, the flexible operation contribution of electrolyzers, and the flexible consumption contribution of hydrogen-using enterprises. The risk contribution sub-model is used to characterize the risks of new energy fluctuations, energy storage cycle losses, hydrogen production equipment utilization rates, hydrogen supply deviations, and carbon revenue price fluctuations.

[0071] Therefore, the embodiments of this application form an allocable income pool through multi-dimensional income accounting and combine it with a multi-entity dynamic contribution evaluation model to improve the accuracy, fairness and rationality of income distribution.

[0072] Optionally, in one embodiment of this application, the dynamic comprehensive contribution of new energy investment entities, incremental distribution network operators, energy storage operators, hydrogen production operators, hydrogen-using enterprises, and park management entities is calculated using a multi-entity dynamic contribution evaluation model. This includes: determining the corresponding dynamic comprehensive contribution based on the green electricity supply, green electricity stability, reduction in curtailment, and new energy investment and maintenance costs of new energy investment entities; calculating the corresponding dynamic comprehensive contribution based on the transmission and distribution service volume, network carrying capacity, power supply reliability, and internal green electricity transmission contribution of incremental distribution network operators; determining the corresponding dynamic comprehensive contribution based on the charging and discharging volume, green electricity transferred from energy storage, and peak shaving and valley filling contribution of energy storage operators; determining the corresponding dynamic comprehensive contribution based on the effective utilization hours of electrolyzers, hydrogen production efficiency, green hydrogen production, and hydrogen supply stability of hydrogen production operators; determining the corresponding dynamic comprehensive contribution based on the green hydrogen consumption, gray hydrogen substitution, flexible hydrogen use capacity, and carbon emission reduction contribution of hydrogen-using enterprises; and determining the corresponding dynamic comprehensive contribution based on the project organization and coordination, carbon asset verification, zero-carbon indicator completion rate, and transaction cost reduction contribution of park management entities.

[0073] In the embodiments of this application, each contribution indicator can be processed using range normalization, target value normalization, entropy weighting, analytic hierarchy process (AHP), or a combination of subjective and objective weighting methods. For positive indicators such as green electricity supply, green hydrogen production, and carbon emission reduction, the normalized value increases with the increase of the indicator; for negative indicators such as equipment wear and tear, hydrogen supply deviation, and price fluctuation risk, the normalized value decreases with the increase of the indicator.

[0074] Within an operating cycle, as shown in Table 2, the dynamic comprehensive contribution of new energy investment entities is determined based on their green electricity supply, green electricity stability, reduction in curtailment, and new energy investment and operation and maintenance costs; the dynamic comprehensive contribution of incremental distribution network operators is determined based on their transmission and distribution service volume, network carrying capacity, power supply reliability, and internal green electricity transmission contribution; the dynamic comprehensive contribution of energy storage operators is determined based on their charging and discharging volume, green electricity transferred from energy storage, peak shaving and valley filling contribution, support for the stable operation of electrolyzers, and cycle life cost; the dynamic comprehensive contribution of hydrogen production operators is determined based on the effective utilization hours of electrolyzers, hydrogen production efficiency, green hydrogen production, and hydrogen supply stability; the dynamic comprehensive contribution of hydrogen-using enterprises is determined based on green hydrogen consumption, gray hydrogen substitution, flexible hydrogen use capacity, and carbon emission reduction contribution; and the dynamic comprehensive contribution of park management entities is determined based on project organization and coordination, carbon asset verification, zero-carbon indicator completion rate, and transaction cost reduction contribution.

[0075] Table 2

[0076] Therefore, the embodiments of this application calculate the electricity contribution, hydrogen contribution, carbon contribution, regulation contribution, and risk contribution for new energy investment entities, incremental distribution network operation entities, energy storage operation entities, hydrogen production operation entities, hydrogen consumption enterprises, and park management entities respectively, and form a dynamic comprehensive contribution degree for each entity. This allows for multi-dimensional contribution calculation based on the differences between entities, making the contribution calculation more accurate and the allocation more equitable.

[0077] In step S104, the marginal contribution allocation results of each entity are calculated, and the marginal contribution allocation results are corrected by dynamic comprehensive contribution degree to obtain the benefit allocation results of each entity.

[0078] Subsequently, in this embodiment, the revenue distribution results for each entity can be calculated based on the dynamic comprehensive contribution, the marginal revenue increment of each entity under different cooperation states, the minimum revenue constraint, the cooperation stability constraint, and the fairness constraint. Among them, the marginal revenue increment can be calculated using the Shapley value, Nash bargaining, nucleolus method, TOPSIS comprehensive evaluation, entropy weight method to correct the distribution method, or multi-objective optimization method. The dynamic comprehensive contribution is used to correct the marginal contribution distribution results so that the revenue distribution results are consistent with the green electricity source tracking results, green hydrogen production identification results, and carbon emission reduction accounting results.

[0079] Optionally, in one embodiment of this application, the marginal contribution allocation result of each entity is calculated, and the marginal contribution allocation result is corrected by dynamic comprehensive contribution degree to obtain the benefit allocation result of each entity. This includes: calculating the marginal benefit increment of each entity under different cooperation states, and calculating the benefit allocation result of each entity based on dynamic comprehensive contribution degree, marginal benefit increment of each entity under different cooperation states, minimum benefit constraint and cooperation stability constraint.

[0080] Specifically, such as Figure 4 As shown, this application embodiment can use a marginal contribution allocation method based on dynamic contribution correction to calculate the revenue distribution results of multiple entities. First, this application embodiment can calculate the basic marginal contribution revenue of each entity based on the revenue increment formed by the new energy investment entity, incremental distribution network operation entity, energy storage operation entity, hydrogen production operation entity, hydrogen-using enterprise, and park management entity under different cooperation states.

[0081] Secondly, in this embodiment, the green electricity supply, transmission and distribution service volume, energy storage-transferred green electricity, effective hydrogen production, green hydrogen consumption, carbon emission reduction, and risk-bearing level of each entity within the current operating cycle can be input into a dynamic contribution evaluation model to obtain the dynamic comprehensive contribution of each entity. Thirdly, this embodiment can adjust the basic marginal contribution revenue based on the dynamic comprehensive contribution, ensuring that the final revenue distribution matches the actual contributions of electricity flow, hydrogen flow, carbon flow, and capital flow.

[0082] In one possible implementation, the subject Basic marginal contribution revenue The Shapley value is used for calculation. To reflect the dynamic differences in contributions from different entities within the current operating cycle, a contribution correction factor is introduced. And based on the total distributable revenue of the project Calculation subject Final distribution of income The profit distribution results satisfy the constraints of total profit conservation, individual rationality, cooperative stability, and fairness. If the profit distribution results do not meet the constraints, the system adjusts the dynamic contribution weight, profit distribution parameters, or the next cycle's operating plan, and recalculates the profit distribution results. This embodiment uses the improved Shapley value method to calculate the multi-agent profit distribution results. For the set of agents N, the agents... The basic Shapley yield is: (25) Where S represents the entity that does not contain a subject. The main alliance; This represents the revenue that the main alliance S can obtain when running independently; n is the number of main entities.

[0083] To reflect the differences in cost input, resource contribution, carbon emission reduction contribution, and risk-bearing among different entities, this application's embodiments may introduce a contribution correction coefficient: (26) The final profit distribution result is as follows: (27) in, as the main body The final distribution of profits; Assign a weight to the marginal contribution. When When the value is large, the allocation results place more emphasis on the marginal contribution of the alliance; when When the value is relatively small, the allocation results place more emphasis on the overall contribution.

[0084] The distribution of profits should meet the following constraints.

[0085] (28) (29) (30) (31) The aforementioned constraints represent the constraints of total revenue conservation, individual rationality, cooperative stability, and fairness, respectively. If the revenue distribution does not satisfy any of these constraints, the dynamic contribution weights in this application embodiment need to be adjusted. , to The minimum return parameters for the main entity or the operating plan for the next cycle are determined, and the return distribution results are recalculated.

[0086] Furthermore, this application embodiment can generate a settlement list for each entity based on the revenue distribution results. This settlement list includes not only the fund distribution results but also the corresponding electricity, hydrogen, and carbon certificates, as shown in Table 3: Table 3

[0087] Therefore, the embodiments of this application can calculate the dynamic comprehensive contribution of each entity based on the contribution of electricity, hydrogen, carbon, regulation and risk, and determine the benefit distribution result by combining the marginal contribution allocation method, thereby improving the rationality, dynamism and incentive compatibility of the benefit distribution of multiple entities.

[0088] Optionally, in one embodiment of this application, after obtaining the revenue distribution results of each entity, the method further includes: generating settlement results for the electricity, hydrogen, carbon, and cash flow of each entity based on the revenue distribution results, and feeding the settlement results back to the green electricity hydrogen production plan, energy storage regulation plan, hydrogen supply plan, and revenue distribution parameters for the next operating cycle, so as to regenerate new revenue distribution results, so that the rolling optimization operation of the green electricity hydrogen production system of the target zero-carbon park is coordinated with the dynamic revenue of multiple entities. The settlement results include the green electricity consumption revenue of the new energy entity, the transmission and distribution service revenue of the incremental distribution network entity, the regulation service revenue of the energy storage entity, the hydrogen production operation revenue of the hydrogen production entity, the green hydrogen substitution revenue of the hydrogen-using enterprise, the collaborative management revenue of the park management entity, and the corresponding green electricity vouchers, green hydrogen production vouchers, and carbon emission reduction vouchers.

[0089] As one possible approach, embodiments of this application can generate settlement results for electricity, hydrogen, carbon, and cash flow based on the revenue distribution results, and feed these settlement results back to the next cycle's operational optimization model. This is used to adjust the green electricity hydrogen production plan, energy storage regulation plan, hydrogen supply plan, dynamic green electricity attribute tags, and revenue distribution parameters, thereby achieving rolling optimization operation of the zero-carbon park's green electricity hydrogen production system and dynamic revenue coordination among multiple stakeholders. The settlement results include revenue from green electricity consumption by new energy entities, revenue from transmission and distribution services by incremental distribution network entities, revenue from regulation services by energy storage entities, revenue from hydrogen production operations by hydrogen production entities, revenue from green hydrogen substitution by hydrogen-using enterprises, revenue from collaborative management by park management entities, and corresponding green electricity vouchers, green hydrogen production vouchers, and carbon emission reduction vouchers.

[0090] Specifically, such as Figure 5 As shown, before the start of the next operating cycle, the park's energy management and profit distribution center will make feedback corrections based on the settlement results of the previous cycle and the deviation from the operating target.

[0091] When the curtailment rate of renewable energy exceeds a preset threshold, embodiments of this application can increase the hydrogen production power of the electrolyzer or the charging power of the energy storage in the next cycle to enhance the renewable energy absorption capacity. When the green hydrogen supply is lower than the hydrogen demand target, embodiments of this application can increase the green electricity hydrogen production plan for the next cycle or call upon the hydrogen storage system to supplement the hydrogen supply.

[0092] When the final allocated revenue of any entity is lower than its minimum revenue constraint, embodiments of this application adjust revenue allocation parameters, scheduling priority, or service price parameters to increase its participation incentive. When carbon emission reduction is lower than the target value, embodiments of this application increase the proportion of hydrogen produced from green electricity, or increase the proportion of green hydrogen replacing gray hydrogen for hydrogen-using enterprises.

[0093] In actual implementation, the rolling optimization operation in this application embodiment uses the day-ahead, day-intraday, month-ahead, or year-ahead as the time scale (the rolling optimization cycle can be 15 minutes, 1 hour, 1 day, 1 month, or 1 year, and the specific cycle is determined by the park's scheduling accuracy, settlement cycle, and data collection conditions). It updates the new energy output forecast, park load forecast, hydrogen demand forecast, electricity price parameters, carbon price parameters, main entity revenue constraints, dynamic green electricity attribute labels, and dynamic contribution weights, and regenerates the green electricity hydrogen production operation plan and revenue distribution results.

[0094] Therefore, this application embodiment feeds back the revenue distribution results to the next cycle's operation plan, enabling the green electricity hydrogen production capacity, energy storage regulation strategy, hydrogen supply plan, dynamic green electricity attribute tags, and revenue distribution parameters to be continuously adjusted according to changes in new energy output, hydrogen demand, electricity prices, and carbon prices. This achieves integrated and coordinated optimization of green electricity hydrogen production operation, green electricity tracking, green hydrogen identification, carbon emission reduction accounting, multi-entity revenue distribution, and rolling feedback control.

[0095] The following description, in conjunction with the accompanying drawings, explains the execution logic of the multi-stakeholder benefit allocation method for green electricity production in zero-carbon industrial parks based on this application.

[0096] Figure 6 This is a schematic diagram illustrating the execution logic of the multi-stakeholder benefit-sharing method for green electricity-to-hydrogen production in zero-carbon industrial parks proposed in this application. Figure 6 As shown, the implementation process of the multi-stakeholder benefit-sharing method for green electricity production in zero-carbon industrial parks proposed in this application is as follows: S601: Collects operational data and economic parameters of zero-carbon industrial parks, including data such as new energy output, park load, energy storage status, electrolyzer status, hydrogen demand, electricity price, and carbon price. S602: Construct a coordinated operation model for hydrogen sources, grid, load, and storage; S603: Solving the green electricity hydrogen production operation scheme; S604: Implement green electricity source tracking and green hydrogen certification; S605: Calculate the revenue from green electricity consumption, hydrogen production, energy storage, and carbon emission reduction. S606: Constructing a multi-stakeholder interest distribution model; S607: Calculate the profit distribution results for each entity; S608: Generates electricity, ammonia, carbon and financial settlement results, i.e. outputs green electricity to hydrogen production scheme, green ammonia production, carbon emission reduction, revenue distribution results, settlement instructions and other results; S609: Perform rolling optimization feedback based on the settlement results and then proceed to S602.

[0097] In one embodiment, the method of this application is used to collaboratively optimize and allocate benefits among multiple stakeholders for a green electricity-to-hydrogen system in a zero-carbon industrial park. Before optimization, the operation of green electricity-to-hydrogen in the park was mainly scheduled separately based on new energy output, hydrogen demand, and electricity price parameters, without unified tracking and settlement of the sources of electricity consumption in the electrolyzer, the green electricity released by energy storage, green hydrogen production, and carbon emission reduction benefits. After optimization, this application determines the green electricity-to-hydrogen power and energy storage charging and discharging strategy based on a source-grid-load-storage hydrogen collaborative operation model, and further determines the green electricity-to-hydrogen ratio and green hydrogen production through a green electricity source tracking model. The green electricity source tracking model can adopt a first-in-first-out, proportional allocation, weighted average, or timestamp-based green electricity tag tracking method.

[0098] like Figure 7 As shown, compared with the method described in this application, the adoption of this method has improved the renewable energy consumption rate, reduced the curtailment rate, increased green hydrogen production, and enhanced carbon emission reduction in the zero-carbon industrial park, resulting in improved overall project benefits. These results demonstrate that this application can improve the local renewable energy consumption capacity and the accuracy of green hydrogen identification through green electricity-to-hydrogen load regulation, time-shifted energy storage utilization, and green electricity source tracking.

[0099] Furthermore, this application can calculate the dynamic comprehensive contribution of each entity—new energy investment entity, incremental distribution network operator, energy storage operator, hydrogen production operator, hydrogen-using enterprise, and park management entity—in green electricity supply, transmission and distribution services, energy storage regulation, electrolytic hydrogen production, green hydrogen consumption, and carbon emission reduction, and determine the revenue distribution result based on the marginal contribution allocation method adjusted by the dynamic contribution. For example... Figure 8 As shown, each participating entity receives a benefit distribution result commensurate with its cost input, resource contribution, operational adjustment contribution, carbon emission reduction contribution, and risk-bearing level. Therefore, this application enables closed-loop synergy between green electricity-to-hydrogen operation optimization, green hydrogen certification, carbon emission reduction accounting, and dynamic benefit distribution among multiple entities.

[0100] In another embodiment, hydrogen-using enterprises do not require a continuous 24 / 7 supply of green hydrogen, but rather propose phased or intermittent green hydrogen substitution needs. In this case, this application can classify hydrogen demand into rigid demand, transferable demand, and interruptible demand. Rigid demand is prioritized to be guaranteed by grey hydrogen or green hydrogen, transferable demand is adjusted intraday based on renewable energy output and hydrogen storage status, and interruptible demand participates in green electricity consumption optimization as auxiliary flexible loads.

[0101] For intermittent hydrogen supply needs, this application allows for increased electrolyzer power and hydrogen storage during periods of higher renewable energy output, and reduced electrolyzer power during periods of lower renewable energy output, supplying hydrogen to hydrogen-consuming enterprises through hydrogen storage facilities. If green hydrogen supply cannot meet the needs of hydrogen-consuming enterprises, grey hydrogen is permitted as a backup, and the amount of grey hydrogen supplementation will be included in the green hydrogen substitution gap and the unfulfilled carbon emission reduction targets.

[0102] In the distribution of benefits, providing flexible hydrogen consumption capacity can reduce the start-up and shutdown costs of electrolyzers and the pressure on energy storage regulation. Therefore, this application incorporates flexible hydrogen consumption capacity into the evaluation of the contribution of hydrogen-consuming enterprises, so that they can obtain corresponding synergistic benefits or green hydrogen price discounts.

[0103] In another embodiment, new energy resources in the zero-carbon park are concentrated in the northern area, while hydrogen-using enterprises are concentrated in the southern area. This application can adopt a method of centralized hydrogen production in the northern area and hydrogen transportation to the southern area via dedicated pipelines, or a method of transmitting green electricity from the northern area to the southern area via an incremental distribution network and producing hydrogen on the load side nearby.

[0104] When the centralized hydrogen production method in the northern region is adopted, the source-grid-load-storage hydrogen collaborative operation model further considers the hydrogen pipeline capacity constraints, pipeline hydrogen transportation costs, hydrogen pressure constraints, and safe operation constraints; when the local hydrogen production method in the southern region is adopted, the model further considers the power grid transmission capacity of the northern and southern regions, internal power transmission and distribution prices, and the constraints of hydrogen production land use and safety boundaries in the southern region.

[0105] This application can calculate the comprehensive operating benefits, investment costs, green electricity hydrogen production ratio, hydrogen supply stability, carbon emission reduction benefits, and multi-entity benefit distribution results under the two schemes, and select the scheme that meets the requirements of safety, economy, and benefit coordination.

[0106] Furthermore, this application can also construct a corresponding multi-stakeholder benefit allocation system based on the execution logic of the multi-stakeholder benefit allocation method for green electricity production in zero-carbon parks. This multi-stakeholder benefit allocation system for green electricity production in zero-carbon parks includes a data acquisition module, a dynamic green electricity attribute tracking module, a revenue calculation module, a dynamic contribution evaluation module, a revenue allocation module, and a settlement output and feedback module.

[0107] The data acquisition module is used to collect data related to new energy sources, loads, energy storage, electrolyzers, hydrogen demand, electricity purchase and sale prices, carbon emissions, and economic parameters of multiple entities within the zero-carbon park; the collaborative optimization module is used to construct and solve the source-grid-load-storage hydrogen collaborative operation model to obtain the green electricity-to-hydrogen operation plan. The dynamic green electricity attribute tracking module is used to set dynamic green electricity attribute tags for the electricity entering the energy storage system and supplying the electrolyzer, and to calculate the proportion of green electricity and green hydrogen production in the power consumption of the electrolyzer. The revenue calculation module is used to calculate revenue from green electricity consumption, hydrogen sales, energy storage regulation, power transmission and distribution services, purchased electricity substitution, and carbon emission reduction. The dynamic contribution evaluation module is used to calculate the dynamic comprehensive contribution of each entity based on the contribution of electricity, hydrogen, carbon, regulation, and risk. The revenue distribution module is used to calculate the revenue distribution results of each entity based on dynamic comprehensive contribution, marginal revenue increment, minimum revenue constraint and cooperation stability constraint. The settlement output and feedback module is used to output the settlement results of electricity, hydrogen, carbon and cash flow, and feed the settlement results back to the collaborative optimization module.

[0108] According to the multi-stakeholder benefit allocation method for green electricity-to-hydrogen production in zero-carbon parks proposed in this application, the following steps are taken: First, obtain the output of new energy sources, park load, energy storage status, electrolyzer status, hydrogen demand, electricity price, carbon price, and economic parameters of multiple stakeholders within the zero-carbon park. Second, construct a source-grid-load-storage hydrogen collaborative operation model to solve for the new energy consumption power, energy storage charging and discharging power, electrolyzer hydrogen production power, external grid interaction power, and hydrogen production. Third, establish a dynamic green electricity attribute tagging tracking model for electrolyzer power consumption to mark, decompose, and correct the hydrogen production power directly supplied by new energy sources, the green electricity released from energy storage for hydrogen production, and the hydrogen production power purchased from the external grid, calculating the green electricity-to-hydrogen ratio, green hydrogen production, and carbon emission reduction. Fourth, based on the green electricity consumption revenue, hydrogen sales revenue, energy storage regulation revenue, and transmission and distribution revenue... Revenue from electricity services, revenue from purchased electricity substitution, and carbon emission reduction forms an allocable revenue pool. Based on each entity's corresponding green electricity supply, transmission and distribution service volume, green electricity transferred from energy storage, effective hydrogen production from electrolyzers, green hydrogen consumption, carbon emission reduction, and operational risk exposure, a multi-entity dynamic contribution evaluation model is constructed. The marginal contribution allocation results are corrected based on the dynamic contribution, yielding the revenue allocation results for each entity. The electricity, hydrogen, carbon, and cash flow settlement results are then fed back to the next cycle's operation plan, achieving closed-loop coordination in green electricity-to-hydrogen production operation optimization, green hydrogen identification, carbon revenue accounting, and multi-entity dynamic revenue allocation. This improves the local consumption level of new energy in the zero-carbon park, the accuracy of green hydrogen identification, the credibility of carbon revenue accounting, and the stability of multi-entity collaborative operation.

[0109] Secondly, with reference to the accompanying drawings, a multi-stakeholder benefit-sharing device based on green electricity production in a zero-carbon industrial park, according to an embodiment of this application, is described.

[0110] Figure 9 This is a block diagram of a multi-stakeholder benefit-sharing device based on green electricity production in a zero-carbon industrial park, according to an embodiment of this application.

[0111] like Figure 9 As shown, the multi-stakeholder benefit distribution device 10 based on green electricity production in a zero-carbon industrial park includes: a first modeling module 100, a solution module 200, a second modeling module 300, and a correction module 400.

[0112] The first modeling module 100 is used to acquire the operation data of the source-grid-load hydrogen storage system and the economic parameters of multiple entities in the target zero-carbon park, and to construct a source-grid-load hydrogen storage collaborative operation model based on the operation data of the source-grid-load hydrogen storage system and the economic parameters of multiple entities. The solver module 200 is used to solve the source-grid-load-storage hydrogen collaborative operation model, obtain multiple collaborative operation data for each operating period, and establish a corresponding dynamic green electricity attribute tag tracking model based on multiple collaborative operation data. Furthermore, the dynamic green electricity attribute tag tracking model is used to mark, decompose, and correct multiple types of hydrogen production electricity consumption to obtain the corresponding green electricity hydrogen production ratio, green hydrogen production, and carbon emission reduction. The second modeling module 300 is used to establish an allocable revenue pool for green electricity-to-hydrogen projects based on the proportion of green electricity to hydrogen production, green hydrogen production and carbon emission reduction. Based on the allocable revenue pool for green electricity-to-hydrogen projects and the green hydrogen operation indicators corresponding to each entity, a multi-entity dynamic contribution evaluation model is constructed to calculate the dynamic comprehensive contribution of each entity through the multi-entity dynamic contribution evaluation model. The correction module 400 is used to calculate the marginal contribution allocation results of each entity and correct the marginal contribution allocation results through dynamic comprehensive contribution to obtain the revenue allocation results of each entity.

[0113] Optionally, in one embodiment of this application, the first modeling module 100 includes a first acquisition unit and a construction unit.

[0114] The first acquisition unit is used to acquire the operation data of the hydrogen generation, grid, load, and storage system within the target zero-carbon park and the economic parameters of multiple stakeholders. The operation data of the hydrogen generation, grid, load, and storage system includes the power output of new energy generation, the power output of the park's conventional load, the state of charge of energy storage, the operating status of the electrolyzer, the hydrogen demand, the hydrogen storage status, the power output of the external power grid, the power purchase and sale price, and the carbon emission factor. The economic parameters of multiple stakeholders include the cost of new energy generation, the price of power transmission and distribution services, the operating cost of energy storage, the operating cost of the electrolyzer, the hydrogen sales price, the cost of gray hydrogen substitution, the unit price of carbon emission reduction revenue, and the revenue constraints of each participating stakeholder.

[0115] The construction unit is used to build the objective function of the source-grid-load-storage hydrogen collaborative operation model of the target zero-carbon park based on the operation data of the source-grid-load-storage hydrogen system and the economic parameters of multiple entities. The objective function aims to maximize the comprehensive operation benefits or minimize the comprehensive operation costs of the target zero-carbon park. The unit also determines the corresponding multiple constraints to construct the source-grid-load-storage hydrogen collaborative operation model based on the objective function and multiple constraints. These constraints include new energy output constraints, park power balance constraints, energy storage charging and discharging constraints, electrolyzer operation constraints, hydrogen supply and demand balance constraints, green electricity consumption constraints, carbon emission reduction constraints, and external grid interaction constraints. The park power balance constraint is that the sum of the new energy consumption power, the external grid power purchase power, and the energy storage discharge power in the target zero-carbon park is equal to the sum of the conventional load power, electrolyzer hydrogen production power, energy storage charging power, and external grid power sales power in the target zero-carbon park. The electrolyzer operation constraints include the minimum operating power constraint, the maximum operating power constraint, the start-stop state constraint, the ramping constraint, and the hydrogen production efficiency constraint. The unit also calculates the electrolyzer hydrogen production in each time period based on the electrolyzer power consumption and the hydrogen production coefficient per unit of power.

[0116] Optionally, in one embodiment of this application, the solving module 200 includes: a calculation unit, a setup unit, and a first calculation unit.

[0117] The computing unit is used to solve the source-grid-load-storage hydrogen collaborative operation model to obtain multiple collaborative operation data for each operating segment. These multiple collaborative operation data include new energy consumption power, green electricity hydrogen production power, energy storage charging and discharging power, external grid power purchase and sale power, electrolyzer hydrogen production, hydrogen supply, and abandoned electricity.

[0118] A unit is established to create a dynamic green electricity attribute tag tracking model for electrolyzer power consumption based on the new energy consumption power, green electricity hydrogen production power, energy storage charging and discharging power, and external grid power purchase and sale power. This model sets dynamic green electricity attribute tags for the electricity entering the energy storage system and supplied to the electrolyzer, and decomposes the electrolyzer power consumption into multiple categories of hydrogen production electricity based on the dynamic green electricity attribute tags. These categories include hydrogen production electricity directly supplied from new energy sources, hydrogen production electricity produced from green electricity released from energy storage, and hydrogen production electricity purchased from the external grid.

[0119] The first calculation unit is used to calculate the proportion of green electricity used to produce hydrogen and the output of green hydrogen in each operating period based on the amount of hydrogen produced by direct supply of new energy sources, the amount of green electricity produced by energy storage release, and the amount of hydrogen produced by purchasing electricity from the external power grid. It also calculates the carbon emission reduction based on the output of green hydrogen, the preset amount of gray hydrogen to be replaced, and the carbon emission factor.

[0120] Optionally, in one embodiment of this application, the second modeling module 300 includes: a second calculation unit and a second acquisition unit.

[0121] The second calculation unit is used to calculate the green electricity consumption revenue, hydrogen sales revenue, energy storage regulation revenue, transmission and distribution service revenue, purchased electricity substitution revenue, and carbon emission reduction revenue of the target zero-carbon park based on the green electricity hydrogen production ratio, green hydrogen production, carbon emission reduction, green electricity consumption, energy storage regulation, transmission and distribution service revenue, purchased electricity substitution revenue, and carbon emission reduction revenue. The goal is to establish an allocable revenue pool for the green electricity hydrogen production project through these revenues.

[0122] The second acquisition unit is used to acquire the green hydrogen operation indicators corresponding to each entity, and based on the green hydrogen operation indicators, to construct a multi-entity dynamic contribution evaluation model. The dynamic comprehensive contribution of the new energy investment entity, incremental distribution network operation entity, energy storage operation entity, hydrogen production operation entity, hydrogen-using enterprise, and park management entity is calculated through the multi-entity dynamic contribution evaluation model. Among them, the green hydrogen operation indicators include green electricity supply, transmission and distribution service electricity, energy storage transfer green electricity, energy storage regulation electricity, effective hydrogen production by electrolyzer, green hydrogen consumption, carbon emission reduction, and operation risk exposure. The multi-entity dynamic contribution evaluation model includes an electricity contribution sub-model, a hydrogen contribution sub-model, a carbon contribution sub-model, a regulation contribution sub-model, and a risk contribution sub-model.

[0123] Optionally, in one embodiment of this application, the correction module 400 includes: a third calculation unit, used to calculate the marginal revenue increment of each subject under different cooperative states, and calculate the revenue distribution result of each subject based on the dynamic comprehensive contribution, the marginal revenue increment of each subject under different cooperative states, the minimum revenue constraint and the cooperative stability constraint.

[0124] Optionally, in one embodiment of this application, the multi-entity benefit distribution device 10 based on green electricity production in a zero-carbon park further includes: an optimization module, used to generate settlement results of electricity, hydrogen, carbon and cash flow for each entity based on the revenue distribution results after obtaining the revenue distribution results of each entity, and to feed the settlement results back to the green electricity production plan, energy storage regulation plan, hydrogen supply plan and revenue distribution parameters of the next operating cycle, so as to regenerate new revenue distribution results, so that the rolling optimization operation of the green electricity production system in the target zero-carbon park is coordinated with the dynamic revenue of multiple entities. The settlement results include the green electricity consumption revenue of the new energy entity, the transmission and distribution service revenue of the incremental distribution network entity, the regulation service revenue of the energy storage entity, the hydrogen production operation revenue of the hydrogen production entity, the green hydrogen substitution revenue of the hydrogen-using enterprise, the collaborative management revenue of the park management entity, and the corresponding green electricity vouchers, green hydrogen production vouchers and carbon emission reduction vouchers.

[0125] Optionally, in one embodiment of this application, the second acquisition unit includes: a first determining subunit, a second determining subunit, a third determining subunit, a fourth determining subunit, a fifth determining subunit, and a sixth determining subunit.

[0126] The first determining subunit is used to determine the corresponding dynamic comprehensive contribution based on the green electricity supply, green electricity stability, reduction in curtailment, and operation and maintenance costs of new energy investment entities.

[0127] The second determining sub-unit is used to calculate the corresponding dynamic comprehensive contribution based on the transmission and distribution service volume, network carrying capacity, power supply reliability, and internal green electricity transmission contribution of the incremental distribution network operator.

[0128] The third determination sub-unit is used to determine the corresponding dynamic comprehensive contribution based on the charging and discharging power of the energy storage operator, the green power transferred by energy storage, and the peak shaving and valley filling contribution.

[0129] The fourth sub-unit is determined based on the effective utilization hours of the electrolyzer, hydrogen production efficiency, green hydrogen production, and hydrogen supply stability of the hydrogen production operator to determine the corresponding dynamic comprehensive contribution.

[0130] The fifth sub-unit is used to determine the corresponding dynamic comprehensive contribution based on the green hydrogen consumption, gray hydrogen substitution, flexible hydrogen utilization capacity, and carbon emission reduction contribution of hydrogen-using enterprises.

[0131] The sixth sub-unit is determined based on the project organization and coordination, carbon asset verification, zero-carbon target completion rate, and transaction cost reduction contribution of the park management entity to determine the corresponding dynamic comprehensive contribution.

[0132] It should be noted that the explanation of the above-mentioned embodiment of the multi-stakeholder benefit distribution method for green electricity production in zero-carbon industrial parks also applies to the multi-stakeholder benefit distribution device for green electricity production in zero-carbon industrial parks in this embodiment, and will not be repeated here.

[0133] The multi-stakeholder benefit distribution system for green electricity-to-hydrogen production in a zero-carbon industrial park, as proposed in this application embodiment, includes a first modeling module 100, used to acquire the operation data of the source-grid-load-storage hydrogen system and multi-stakeholder economic parameters within the target zero-carbon industrial park, and to construct a source-grid-load-storage hydrogen collaborative operation model based on the operation data and multi-stakeholder economic parameters; and a solution module 200, used to solve the source-grid-load-storage hydrogen collaborative operation model, obtain multiple collaborative operation data for each operating period, and establish a corresponding dynamic green electricity attribute tag tracking model based on the multiple collaborative operation data, and to tag the electricity consumption for hydrogen production of various types through the dynamic green electricity attribute tag tracking model. The system involves recording, decomposing, and correcting data to obtain the corresponding green electricity-to-hydrogen ratio, green hydrogen production, and carbon emission reduction. A second modeling module 300 establishes an allocable revenue pool for green electricity-to-hydrogen projects based on these data. A multi-entity dynamic contribution evaluation model is constructed based on this pool and the corresponding green hydrogen operation indicators for each entity. This model calculates the dynamic comprehensive contribution of each entity. A correction module 400 calculates the marginal contribution allocation results for each entity and corrects these results using the dynamic comprehensive contribution to obtain the revenue allocation results for each entity. This application combines source-grid-load-storage hydrogen collaborative operation optimization, green electricity source tracking, green hydrogen and carbon emission reduction accounting, multi-entity contribution assessment, and revenue allocation settlement. This effectively improves the local consumption level of new energy in zero-carbon parks, the accuracy of green hydrogen identification, the credibility of carbon revenue accounting, and the stability of multi-entity collaborative operation, supporting the efficient operation, transparent accounting, and sustainable collaboration of green electricity-to-hydrogen projects in zero-carbon parks.

[0134] Figure 10 A schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device may include: The memory 1001, the processor 1002, and the computer program stored on the memory 1001 and capable of running on the processor 1002.

[0135] When the processor 1002 executes the program, it implements the multi-stakeholder benefit distribution method based on zero-carbon park green electricity hydrogen production provided in the above embodiments.

[0136] Furthermore, electronic devices also include: Communication interface 1003 is used for communication between memory 1001 and processor 1002.

[0137] The memory 1001 is used to store computer programs that can run on the processor 1002.

[0138] The memory 1001 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0139] If the memory 1001, processor 1002, and communication interface 1003 are implemented independently, then the communication interface 1003, memory 1001, and processor 1002 can be interconnected via a bus to complete communication between them. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized into address buses, data buses, control buses, etc. For ease of representation, Figure 10 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0140] Optionally, in a specific implementation, if the memory 1001, processor 1002, and communication interface 1003 are integrated on a single chip, then the memory 1001, processor 1002, and communication interface 1003 can communicate with each other through an internal interface.

[0141] The processor 1002 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application.

[0142] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described multi-stakeholder benefit distribution method based on green electricity production for hydrogen production in zero-carbon industrial parks.

[0143] This application also provides a computer program product, including a computer program, which, when executed, is used to implement the above-described multi-stakeholder benefit distribution method based on green electricity production in zero-carbon industrial parks.

[0144] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0145] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0146] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or N executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0147] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0148] It should be understood that the various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0149] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0150] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0151] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A multi-stakeholder benefit-sharing method for hydrogen production from green electricity in zero-carbon industrial parks, characterized in that, Includes the following steps: Obtain the operating data of the source-grid-load hydrogen storage system and the economic parameters of multiple entities within the target zero-carbon park, and construct a source-grid-load hydrogen storage collaborative operation model based on the operating data of the source-grid-load hydrogen storage system and the economic parameters of multiple entities; Solve the source-grid-load-storage hydrogen collaborative operation model to obtain multiple collaborative operation data for each operating period, and establish a corresponding dynamic green electricity attribute tag tracking model based on the multiple collaborative operation data. Furthermore, use the dynamic green electricity attribute tag tracking model to mark, decompose, and correct multiple types of hydrogen production electricity consumption to obtain the corresponding green electricity hydrogen production ratio, green hydrogen production, and carbon emission reduction. Based on the green electricity-to-hydrogen ratio, the green hydrogen production, and the carbon emission reduction, an allocable revenue pool for green electricity-to-hydrogen projects is established. A multi-entity dynamic contribution evaluation model is constructed based on the allocable revenue pool for green electricity-to-hydrogen projects and the green hydrogen operation indicators corresponding to each entity, so as to calculate the dynamic comprehensive contribution of each entity through the multi-entity dynamic contribution evaluation model. The marginal contribution allocation results of each entity are calculated, and the marginal contribution allocation results are corrected by the dynamic comprehensive contribution degree to obtain the revenue allocation results of each entity.

2. The multi-stakeholder benefit distribution method based on zero-carbon industrial park green electricity hydrogen production according to claim 1, characterized in that, The process of acquiring operational data and multi-entity economic parameters of the hydrogen source-grid-load-storage system within the target zero-carbon industrial park, and constructing a collaborative operation model for hydrogen source-grid-load-storage based on the operational data and economic parameters, includes: The system acquires operational data and multi-entity economic parameters of the hydrogen generation, grid, load, and storage system within the target zero-carbon industrial park. The operational data includes renewable energy power generation, park conventional load power, energy storage status of charge, electrolyzer operating status, hydrogen demand, hydrogen storage status, external grid power purchase and sale, electricity purchase and sale price, and carbon emission factor. The multi-entity economic parameters include renewable energy power generation cost, transmission and distribution service price, energy storage operating cost, electrolyzer operating cost, hydrogen sales price, gray hydrogen substitution cost, carbon emission reduction revenue unit price, and revenue constraints for each participating entity. Based on the operational data of the source-grid-load-storage hydrogen system and the multi-entity economic parameters, an objective function is constructed for the source-grid-load-storage hydrogen collaborative operation model of the target zero-carbon park. This function aims to maximize the overall operational benefits or minimize the overall operational costs of the target zero-carbon park. Several corresponding constraints are determined, and the source-grid-load-storage hydrogen collaborative operation model is constructed based on the objective function and these constraints. These constraints include constraints on new energy output, park power balance, energy storage charging and discharging, electrolyzer operation, hydrogen supply and demand balance, and green electricity consumption. The constraints include carbon emission reduction constraints and external power grid interaction constraints. The power balance constraint of the target zero-carbon park is that the sum of the new energy consumption power, the power purchased by the external power grid and the energy storage discharge power in the target zero-carbon park is equal to the sum of the conventional load power, the hydrogen production power of the electrolyzer, the energy storage charging power and the power sold by the external power grid in the target zero-carbon park. The electrolyzer operation constraints include the minimum operating power constraint, the maximum operating power constraint, the start-stop state constraint, the ramping constraint and the hydrogen production efficiency constraint of the electrolyzer. The hydrogen production of the electrolyzer in each time period is calculated based on the power consumption of the electrolyzer and the hydrogen production coefficient per unit power.

3. The multi-stakeholder benefit distribution method based on zero-carbon industrial park green electricity hydrogen production according to claim 2, characterized in that, The process involves solving the source-grid-load-storage hydrogen collaborative operation model to obtain multiple collaborative operation data for each operating period. Based on these multiple collaborative operation data, a corresponding dynamic green electricity attribute tagging and tracking model is established. This model is then used to label, decompose, and correct various types of electricity consumption for hydrogen production to obtain the corresponding green electricity-to-hydrogen ratio, green hydrogen production, and carbon emission reduction, including: Solving the source-grid-load-storage hydrogen collaborative operation model yields multiple collaborative operation data for each operating period. These multiple collaborative operation data include new energy consumption power, green electricity hydrogen production power, energy storage charging and discharging power, external grid power purchase and sale power, hydrogen production of the electrolyzer, hydrogen supply, and abandoned electricity. Based on the new energy consumption power, the green electricity hydrogen production power, the energy storage charging and discharging power, and the external grid power purchased and sold, a dynamic green electricity attribute tag tracking model for electrolyzer power consumption is established. The model sets dynamic green electricity attribute tags for the electricity entering the energy storage system and supplied to the electrolyzer, and decomposes the electrolyzer power consumption into multiple types of hydrogen production electricity based on the dynamic green electricity attribute tags. These multiple types of hydrogen production electricity include hydrogen production electricity directly supplied from new energy sources, hydrogen production electricity produced by releasing green electricity from energy storage, and hydrogen production electricity purchased from the external grid. Based on the hydrogen production power generated directly from new energy sources, the hydrogen production power generated from green electricity released from energy storage, and the hydrogen production power generated from electricity purchased from the external power grid, the green electricity hydrogen production ratio and green hydrogen output for each operating period are calculated, and the carbon emission reduction is calculated based on the green hydrogen output, the preset amount of gray hydrogen to be replaced, and the carbon emission factor.

4. The multi-stakeholder benefit distribution method based on zero-carbon industrial park green electricity hydrogen production according to claim 3, characterized in that, Based on the green electricity-to-hydrogen ratio, the green hydrogen production, and the carbon emission reduction, an allocable revenue pool for the green electricity-to-hydrogen project is established. A multi-entity dynamic contribution evaluation model is constructed based on the allocable revenue pool and the corresponding green hydrogen operation indicators of each entity. This model is used to calculate the dynamic comprehensive contribution of each entity, including: Based on the green electricity-to-hydrogen ratio, green hydrogen production, carbon emission reduction, green electricity consumption, energy storage regulation, power transmission and distribution service volume, and purchased electricity substitution, the green electricity consumption revenue, hydrogen sales revenue, energy storage regulation revenue, power transmission and distribution service revenue, purchased electricity substitution revenue, and carbon emission reduction revenue of the target zero-carbon park are calculated. An allocable revenue pool for the green electricity-to-hydrogen project is then established using the green electricity consumption revenue, hydrogen sales revenue, energy storage regulation revenue, power transmission and distribution service revenue, purchased electricity substitution revenue, and carbon emission reduction revenue. The green hydrogen operation indicators corresponding to each entity are obtained, and based on these indicators, a multi-entity dynamic contribution evaluation model is constructed. The dynamic comprehensive contribution of new energy investment entities, incremental distribution network operation entities, energy storage operation entities, hydrogen production operation entities, hydrogen-using enterprises, and park management entities is calculated using this model. The green hydrogen operation indicators include green electricity supply, transmission and distribution service electricity, green electricity transferred from energy storage, energy storage regulation electricity, effective hydrogen production from electrolyzers, green hydrogen consumption, carbon emission reduction, and operational risk exposure. The multi-entity dynamic contribution evaluation model includes an electricity contribution sub-model, a hydrogen contribution sub-model, a carbon contribution sub-model, a regulation contribution sub-model, and a risk contribution sub-model.

5. The multi-stakeholder benefit distribution method based on zero-carbon industrial park green electricity hydrogen production according to claim 4, characterized in that, The calculation of the marginal contribution allocation results for each entity, and the correction of the marginal contribution allocation results through the dynamic comprehensive contribution degree to obtain the revenue allocation results for each entity, includes: Calculate the marginal revenue increment of each entity under different cooperation states, and calculate the revenue distribution result of each entity based on the dynamic comprehensive contribution, the marginal revenue increment of each entity under different cooperation states, the minimum revenue constraint, and the cooperation stability constraint.

6. The multi-stakeholder benefit distribution method based on zero-carbon industrial park green electricity hydrogen production according to claim 5, characterized in that, After obtaining the profit distribution results for each of the aforementioned entities, the process also includes: Based on the revenue distribution results, settlement results for the electricity, hydrogen, carbon, and cash flow of each entity are generated. These settlement results are then fed back to the green electricity-to-hydrogen production plan, energy storage regulation plan, hydrogen supply plan, and revenue distribution parameters for the next operating cycle to generate new revenue distribution results. This ensures that the rolling optimization operation of the green electricity-to-hydrogen production system in the target zero-carbon park is coordinated with the dynamic revenue of multiple entities. The settlement results include revenue from green electricity consumption by new energy entities, transmission and distribution service revenue by incremental distribution network entities, regulation service revenue by energy storage entities, hydrogen production operation revenue by hydrogen production entities, green hydrogen substitution revenue by hydrogen-using enterprises, collaborative management revenue by park management entities, and corresponding green electricity vouchers, green hydrogen production vouchers, and carbon emission reduction vouchers.

7. The multi-stakeholder benefit distribution method based on zero-carbon industrial park green electricity hydrogen production according to claim 4, characterized in that, The calculation of the dynamic comprehensive contribution of new energy investment entities, incremental distribution network operators, energy storage operators, hydrogen production operators, hydrogen-using enterprises, and park management entities through the multi-entity dynamic contribution evaluation model includes: The corresponding dynamic comprehensive contribution is determined based on the green electricity supply, green electricity stability, reduction in curtailment, and operation and maintenance costs of the new energy investment entities. The corresponding dynamic comprehensive contribution is calculated based on the transmission and distribution service volume, network carrying capacity, power supply reliability, and internal green energy transmission contribution of the incremental distribution network operator. Based on the charging and discharging capacity, green energy transferred from energy storage, and peak shaving and valley filling contribution of the energy storage operator, the corresponding dynamic comprehensive contribution is determined. The dynamic comprehensive contribution is determined based on the effective utilization hours of the electrolyzer, hydrogen production efficiency, green hydrogen production, and hydrogen supply stability of the hydrogen production operator. The dynamic comprehensive contribution rate is determined based on the green hydrogen consumption, gray hydrogen substitution, flexible hydrogen use capacity, and carbon emission reduction contribution of the hydrogen-using enterprises. The dynamic comprehensive contribution is determined based on the project organization and coordination, carbon asset verification, zero-carbon target achievement, and transaction cost reduction contribution of the park management entity.

8. A multi-stakeholder benefit-sharing device for green electricity-to-hydrogen production in a zero-carbon industrial park, characterized in that, include: The first modeling module is used to acquire the operation data of the source-grid-load hydrogen storage system and the economic parameters of multiple entities within the target zero-carbon park, and to construct a source-grid-load hydrogen storage collaborative operation model based on the operation data of the source-grid-load hydrogen storage system and the economic parameters of multiple entities. The solution module is used to solve the source-grid-load-storage hydrogen collaborative operation model, obtain multiple collaborative operation data for each operating period, and establish a corresponding dynamic green electricity attribute tag tracking model based on the multiple collaborative operation data. The dynamic green electricity attribute tag tracking model is used to mark, decompose and correct multiple types of hydrogen production electricity consumption to obtain the corresponding green electricity hydrogen production ratio, green hydrogen production and carbon emission reduction. The second modeling module is used to establish an allocable revenue pool for green electricity-to-hydrogen projects based on the green electricity-to-hydrogen ratio, the green hydrogen production, and the carbon emission reduction. It also constructs a multi-entity dynamic contribution evaluation model based on the allocable revenue pool and the green hydrogen operation indicators corresponding to each entity, so as to calculate the dynamic comprehensive contribution of each entity through the multi-entity dynamic contribution evaluation model. The correction module is used to calculate the marginal contribution allocation result of each entity and correct the marginal contribution allocation result through the dynamic comprehensive contribution degree to obtain the revenue allocation result of each entity.

9. An electronic device, characterized in that, include: The memory, the processor, and the computer program stored in the memory and executable on the processor, the processor executing the program to implement the multi-stakeholder benefit distribution method for green electricity production in zero-carbon industrial parks as described in any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, The program is executed by the processor to implement the multi-stakeholder benefit distribution method based on green electricity production in zero-carbon industrial parks as described in any one of claims 1-7.

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