A multi-to-one electrolytic cell group space-time coordination method and system and computer equipment

Abstract

The application discloses a multi-to-one electrolytic cell group space-time coordination method and system and a computer device, and is applied to a hydrogen production cluster including a multi-to-one electrolytic cell group, and the multi-to-one electrolytic cell group includes electrolytic cells sharing auxiliary systems, and the method comprises the following steps: obtaining operation state data and external environment data of the hydrogen production cluster; based on the two, solving an economic optimal benchmark meeting operation constraints; based on the benchmark and a maximum allowed economic loss ratio, determining an economic benefit lower limit; establishing a space-time coordination index of the multi-to-one electrolytic cell group, the index including a space deviation and a transfer deviation; under the economic benefit lower limit and operation constraint limitation, coordinating and optimizing the space deviation and the transfer deviation to obtain a space-time coordination scheme corresponding to the maximum allowed economic loss ratio; and based on the scheme, generating control instructions of each electrolytic cell. The application can reduce power space differences between running cells in the multi-to-one electrolytic cell group within a loss upper limit, and reduce internal transfer amounts after common variation of the whole group.

Description

Technical Field

[0001] This application relates to the field of renewable energy hydrogen production and multi-electrolyte cluster optimization control, and in particular to a spatiotemporal coordination method, system and computer equipment for many-to-one electrolyzer groups. Background Technology

[0002] As the scale of hydrogen production from renewable energy sources such as wind and solar power continues to expand, hydrogen production plants typically adopt a "many-to-one" configuration structure where multiple electrolyzers share auxiliary systems such as alkali circulation, cooling, and gas-liquid separation to reduce equipment investment and land area. In this structure, the electrolyzers within the same group form a strong coupling relationship through the shared auxiliary systems, and their power allocation is no longer independent. When the power differences between cells within the group are too large, or when power is frequently and significantly transferred between cells, the shared auxiliary systems must simultaneously cope with significant differences in heat, gas production, and material flow rates. This can easily lead to frequent fluctuations in key process parameters such as temperature, pressure, liquid level, and gas purity, posing a challenge to the safe and stable operation of the system. Therefore, when formulating a power allocation strategy, it is necessary to proactively coordinate the spatial distribution differences and temporal power transfers within the group, while ensuring economic control.

[0003] To address the power allocation problem in the aforementioned many-to-one electrolytic cell arrays, existing technologies have solutions involving economic scheduling of electrolytic cell arrays, power command allocation, and lifetime balancing. For example, some solutions focus on achieving power following or start-stop control based on total power commands, but fail to consider power differences among operating cells within the same group as a safety coordination issue requiring proactive optimization. Another type of solution involves inter-cell power adjustment, but fails to clearly distinguish between power changes caused by normal rises and falls in the group's total power and internal transfers that truly alter the distribution relationship within the group, potentially leading to excessive constraints on normal power following. Furthermore, existing multi-objective optimization schemes typically combine economic benefits and power balance indicators with fixed weights, making it difficult to ensure that the economic costs incurred to improve safety coordination are strictly controlled within the upper limit preset by the operator. In summary, existing technologies have not yet been able to effectively solve the comprehensive coordination problem of spatial operating condition differences and internal power transfers within the group under the hard constraint of economic costs.

[0004] Therefore, how to reduce the power space difference between operating cells in a multi-to-one electrolytic cell group and eliminate the internal power transfer after the entire group rises and falls together, while under the hard constraint that economic losses do not exceed the operator's allowable upper limit, is a technical problem that urgently needs to be solved. Summary of the Invention

[0005] In view of this, embodiments of this application provide a spatiotemporal coordination method, system, and computer equipment for a multi-to-one electrolytic cell group, which can simultaneously reduce the power space difference between operating cells in a multi-to-one electrolytic cell group and eliminate the internal power transfer amount after the entire group rises and falls together, under the hard constraint that economic losses do not exceed the operator's allowable upper limit.

[0006] In a first aspect, this application provides a spatiotemporal coordination method for a many-to-one electrolyzer group, applied to a hydrogen production cluster comprising at least one many-to-one electrolyzer group, wherein the many-to-one electrolyzer group includes multiple electrolyzers sharing a common auxiliary system, comprising: The system acquires operational status data and external environment data of the hydrogen production cluster. The operational status data is used to characterize the availability of each electrolyzer in the current scheduling cycle, while the external environment data is used to characterize the available power generation and economic parameters of the hydrogen production cluster in the current scheduling cycle. Based on operational status data and external environment data, the maximum economic benefit that satisfies the operational constraints of the hydrogen production cluster is calculated and used as the economically optimal benchmark. Based on the economically optimal benchmark and the preset maximum allowable economic loss ratio, the lower limit of economic returns is determined. Establish a spatiotemporal coordination index for multiple-to-one electrolyzer groups. The spatiotemporal coordination index includes a spatial deviation index and a transfer deviation index. The spatial deviation index is used to characterize the degree of power difference between electrolyzers within the same multiple-to-one electrolyzer group during the same scheduling period. The transfer deviation index is used to characterize the degree of power transfer between adjacent scheduling periods due to changes in the allocation relationship within the group. Under the combined constraints of the lower limit of economic benefits and the operational constraints of the hydrogen production cluster, the spatial deviation index and the transfer deviation index are coordinated and optimized to obtain the target spatiotemporal coordination scheme corresponding to the maximum allowable economic loss ratio. Based on the target spatiotemporal coordination scheme, control commands for each electrolytic cell are generated.

[0007] Secondly, this application provides a spatiotemporal coordination system for a many-to-one electrolyzer group, applied to a hydrogen production cluster comprising at least one many-to-one electrolyzer group, wherein the many-to-one electrolyzer group includes multiple electrolyzers sharing a common auxiliary system, comprising: The acquisition module is used to acquire the operating status data and external environment data of the hydrogen production cluster. The operating status data is used to characterize the availability status of each electrolyzer in the current scheduling cycle, and the external environment data is used to characterize the available power generation and economic parameters of the hydrogen production cluster in the current scheduling cycle. The calculation module, based on operational status data and external environment data, calculates the maximum economic benefit that satisfies the operational constraints of the hydrogen production cluster, and uses it as the economically optimal benchmark. The determination module is used to determine the lower limit of economic returns based on the economically optimal benchmark and the preset maximum allowable economic loss ratio; The module is used to establish the spatiotemporal coordination index of a multi-to-one electrolytic cell group. The spatiotemporal coordination index includes the spatial deviation index and the transfer deviation index. The spatial deviation index is used to characterize the degree of power difference between electrolytic cells in the same scheduling period within the same multi-to-one electrolytic cell group. The transfer deviation index is used to characterize the degree of power transfer caused by the change in the allocation relationship within the group between adjacent scheduling periods. The optimization module is used to coordinate and optimize the spatial deviation index and the transfer deviation index under the joint constraints of the lower limit of economic benefits and the operation constraints of the hydrogen production cluster, so as to obtain the target spatiotemporal coordination scheme corresponding to the maximum allowable economic loss ratio. The generation module generates control commands for each electrolytic cell based on the target spatiotemporal coordination scheme.

[0008] Thirdly, this application provides a computer device, including a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor, wherein the processor executes the program to implement the above-described many-to-one electrolytic cell group spatiotemporal coordination method.

[0009] By employing the above technical solutions, the spatiotemporal coordination method, system, and computer equipment for a multi-to-one electrolyzer group provided in this application, through coordinated optimization of spatial deviation and transfer deviation indices under the joint constraints of the lower limit of economic benefits and the operational constraints of the hydrogen production cluster, can proactively reduce the power differences between operating cells within the same multi-to-one electrolyzer group during the same scheduling period, while ensuring that economic losses do not exceed the maximum allowable economic loss ratio preset by the operator. This reduces the burden on the shared auxiliary system to handle different chemical conditions simultaneously, and avoids frequent fluctuations in key process parameters such as temperature, pressure, liquid level, and gas purity caused by excessive differences in heat generation, gas production, and material flow rate among cells. Simultaneously, through the transfer deviation index... The power transfer caused by changes in the intra-group allocation relationship between adjacent scheduling periods is quantified, enabling the coordination optimization to accurately suppress the power transfer that truly changes the intra-group allocation relationship, without restricting the common changes in each electrolyzer corresponding to the normal rise and fall of the total power of the group. This reduces the internal operating condition redistribution disturbances borne by the shared auxiliary system while preserving the ability of new energy power to follow. Furthermore, by setting a maximum allowable economic loss ratio to form an economic hard boundary, the economic losses of the schemes participating in the coordination optimization are all controlled within the upper limit stipulated by the operator. Ultimately, the goal of achieving a spatiotemporal coordination scheme with controllable economic losses and coordinated optimization of spatial deviation and transfer deviation is achieved, thereby improving the safe and stable operation level of the multi-to-one electrolyzer group from the source of power command.

[0010] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, specific embodiments of this application are given below. Attached Figure Description

[0011] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings: Figure 1A schematic flowchart of a spatiotemporal coordination method for a many-to-one electrolytic cell group provided in an embodiment of this application is shown. Figure 2 A schematic flowchart of another spatiotemporal coordination method for many-to-one electrolytic cell groups provided in an embodiment of this application is shown; Figure 3 This illustration shows a structural schematic diagram of a multi-to-one electrolytic cell group spatiotemporal coordination system provided in an embodiment of this application; Figure 4 A schematic diagram of the system structure of a computer device provided in an embodiment of this application is shown. Detailed Implementation

[0012] The present application will be described in detail below with reference to the accompanying drawings and embodiments. It should be noted that, unless otherwise specified, the embodiments and features described in the embodiments of the present application can be combined with each other.

[0013] This invention provides a spatiotemporal coordination method for a multi-to-one electrolyzer group, applicable to a hydrogen production cluster comprising at least one multi-to-one electrolyzer group, wherein the multi-to-one electrolyzer group includes multiple electrolyzers sharing a common auxiliary system.

[0014] Among them, a multi-to-one electrolyzer group refers to an electrolyzer combination structure in which multiple electrolyzers share one or more sets of auxiliary equipment such as alkali circulation system, cooling system, gas-liquid separation system or purification system. Each electrolyzer can independently adjust the hydrogen production power, and the electrolyzers in the same multi-to-one electrolyzer group are coupled through the shared auxiliary system.

[0015] For example, such as Figure 1 As shown, the method includes: S101, acquire the operating status data and external environment data of the hydrogen production cluster. The operating status data is used to characterize the availability status of each electrolyzer in the current scheduling cycle, and the external environment data is used to characterize the available power generation and economic parameters of the hydrogen production cluster in the current scheduling cycle.

[0016] In some instances, the hydrogen production cluster also includes at least one independent electrolyzer, which is an electrolyzer with its own auxiliary system and does not share auxiliary equipment with other electrolyzers.

[0017] Operational status data includes the operational status and equipment operating parameters of each electrolyzer during the current scheduling cycle. Operational status refers to the working mode of each electrolyzer during the current scheduling cycle, including hydrogen production operation, hot standby, start-up, and shutdown. Equipment operating parameters refer to the inherent characteristic parameters and operational limitations of each electrolyzer, including the upper limit of single-cell power, the lower limit of single-cell power, and the ramp rate (i.e., the maximum allowable rate of change of single-cell power and rated power during adjacent scheduling periods). Equipment operating parameters are typically provided by the equipment manufacturer's technical documents, project acceptance tests, or site operation procedures.

[0018] External environmental data includes available renewable energy power, electricity purchase price, electricity sales price, and hydrogen revenue parameters. Available renewable energy power comes from wind power and / or photovoltaic power generation. The above data can be obtained in real time through the power station energy management system, renewable energy power prediction system, power trading platform, and local equipment control system.

[0019] S102, based on operational status data and external environment data, solves for the maximum economic benefit that satisfies the operational constraints of the hydrogen production cluster, and uses it as the economically optimal benchmark.

[0020] Specifically, after obtaining operational status data and external environment data, the maximum economic benefit that satisfies the operational constraints of the hydrogen production cluster can be calculated based on the operational status data and external environment data, and this can be used as the economically optimal benchmark.

[0021] S103, based on the economically optimal benchmark and the preset maximum allowable economic loss ratio, determines the lower limit of economic returns.

[0022] The lower bound of economic returns is the minimum allowable economic return value determined based on the economically optimal benchmark and the preset maximum allowable economic loss ratio. It is used to construct the feasible region of economic protection and ensure that the economic losses of all solutions solved within this feasible region do not exceed the upper limit allowed by the operator.

[0023] The maximum permissible economic loss ratio is the maximum economic benefit loss percentage allowed by the operator relative to the economically optimal benchmark. Expressed as a percentage, this ratio limits the upper limit of economic loss for any candidate solution relative to the economically optimal benchmark during the spatiotemporal coordination process, ensuring that the economic cost of improving intra-group spatial deviations and intra-group power transfer does not exceed the operator's acceptable range. This ratio can be set comprehensively based on factors such as the economic operation requirements of the hydrogen production station, the fluctuation range of electricity market prices, the degree of deviation in renewable energy output forecasts, and equipment operation and maintenance budgets.

[0024] S104. Establish a spatiotemporal coordination index for a multi-to-one electrolytic cell group. The spatiotemporal coordination index includes a spatial deviation index and a transfer deviation index. The spatial deviation index is used to characterize the degree of power difference between electrolytic cells within the same multi-to-one electrolytic cell group during the same scheduling period. The transfer deviation index is used to characterize the degree of power transfer caused by changes in the allocation relationship within the group between adjacent scheduling periods.

[0025] The spatial deviation index is used to characterize the degree of power difference among electrolyzers within the same many-to-one electrolyzer group during the same scheduling period. Specifically, it represents the degree of dispersion of the power of each operating cell (i.e., the electrolyzer currently in hydrogen production operation within the many-to-one electrolyzer group) relative to the average power of the group's operating cells during the same scheduling period. A larger index indicates a more uneven power distribution among the operating cells within the group, and a heavier burden on the shared auxiliary system to handle significant differences in heat, gas production, and material flow rates.

[0026] The transfer deviation index characterizes the degree of power transfer caused by changes in the allocation relationship within the group between adjacent scheduling periods. Specifically, it represents the amount of power that alters the relative allocation relationship between the operating cells within the group between adjacent scheduling periods, rather than the power change corresponding to the rise and fall of each electrolyzer along with the total group power. A larger index indicates a more drastic change in the allocation relationship between the operating cells within the group between adjacent scheduling periods, and more frequent internal operating condition redistribution disturbances experienced by the shared auxiliary system.

[0027] S105, under the joint constraints of the lower limit of economic benefits and the operation constraints of the hydrogen production cluster, coordinates and optimizes the spatial deviation index and the transfer deviation index to obtain the target spatiotemporal coordination scheme corresponding to the maximum allowable economic loss ratio.

[0028] The target spatiotemporal coordination scheme is the optimal power allocation scheme that, while ensuring that economic losses do not exceed the operator's allowable limit, can minimize spatial power differences within the group and reduce power transfer within the group as much as possible.

[0029] It should be noted that the spatial deviation index and the transfer deviation index reflect two different dimensions of the safe and stable operation of a many-to-one electrolyzer group. The spatial deviation index reflects the degree of power difference between operating electrolyzers within the same group during the same time period, while the transfer deviation index reflects the degree of power transfer caused by changes in the allocation relationship within the group between adjacent time periods. These two indices often conflict in power allocation. An excessive pursuit of spatial equilibrium may lead to frequent power adjustments between adjacent time periods, increasing the transfer deviation; conversely, an excessive pursuit of smooth transfer may result in excessively large power distribution differences within the same time period, increasing the spatial deviation. The essence of coordinated optimization is to find a set of power allocation schemes within the feasible region defined by a given lower bound of economic benefits and operational constraints, such that both the spatial deviation index and the transfer deviation index are at a relatively optimal level—that is, to seek a reasonable balance between the two. In other words, coordinated optimization refers to the process of jointly weighing and iteratively solving the spatial deviation index and the transfer deviation index under the joint constraints of the lower bound of economic benefits and the operational constraints of the hydrogen production cluster.

[0030] S106 generates control commands for each electrolytic cell based on the target spatiotemporal coordination scheme.

[0031] As can be seen from the above, the spatiotemporal coordination method for a many-to-one electrolyzer group provided in this application, by coordinating and optimizing the spatial deviation index and the transfer deviation index under the joint constraints of the lower limit of economic benefits and the operational constraints of the hydrogen production cluster, can proactively reduce the power difference between operating cells in the same many-to-one electrolyzer group during the same scheduling period, while ensuring that the economic loss does not exceed the maximum allowable economic loss ratio preset by the operator. This reduces the burden on the shared auxiliary system to handle different chemical conditions simultaneously, and avoids frequent fluctuations in key process parameters such as temperature, pressure, liquid level, and gas purity caused by excessive differences in heat generation, gas production, and material flow rate among cells. At the same time, the transfer deviation index is used to coordinate and optimize the spatial deviation index of adjacent scheduling periods. The power transfer caused by changes in the allocation relationship within the group between segments is quantified, enabling the coordination optimization to accurately suppress the power transfer that truly changes the allocation relationship within the group, without restricting the common changes in each electrolyzer corresponding to the normal rise and fall of the total power of the group. This reduces the internal operating condition redistribution disturbances borne by the shared auxiliary system while preserving the ability of new energy power to follow. Furthermore, by setting a maximum allowable economic loss ratio to form an economic hard boundary, the economic losses of the schemes participating in the coordination optimization are all controlled within the upper limit stipulated by the operator. Ultimately, the goal of achieving a spatiotemporal coordination scheme with controllable economic losses and coordinated optimization of spatial deviation and transfer deviation is achieved, thereby improving the safe and stable operation level of the multi-to-one electrolyzer group from the source of power command.

[0032] Furthermore, as a refinement and extension of the specific implementation of the above embodiments, and to fully illustrate the specific implementation process of this embodiment, another method for spatiotemporal coordination of many-to-one electrolytic cell groups is provided, such as... Figure 2 As shown, the method includes: S201 acquires operational status data and external environment data of the hydrogen production cluster.

[0033] The implementation method of S201 is the same as that of S101 in the above embodiment. For details, please refer to the above embodiment, and it will not be repeated here.

[0034] S202, based on operational status data and external environment data, solves for the maximum economic benefit that satisfies the operational constraints of the hydrogen production cluster, and serves as the economically optimal benchmark.

[0035] In this embodiment, the set of electrolyzers currently in hydrogen production operation and the set of electrolyzers currently in hot standby are determined based on the operating status of each electrolyzer in the current scheduling cycle. The additional power consumption of auxiliary equipment is determined based on equipment operating parameters and the set of electrolyzers currently in hot standby. A power balance relationship for the hydrogen production cluster is established within the current scheduling cycle based on available new energy power, purchased electricity power, sold electricity power, the total power of each multi-to-one electrolyzer group, the power of each independent electrolyzer, the additional power consumption of auxiliary equipment, and the power curtailment of the hydrogen production cluster. The comprehensive economic benefit of the hydrogen production cluster in the current scheduling cycle is calculated based on the power balance relationship, the power-hydrogen production characteristics of each electrolyzer, and parameters such as electricity purchase price, electricity sales price, and hydrogen revenue. With the goal of maximizing the comprehensive economic benefit, the solution is obtained under the joint constraints of the power balance relationship, the single-cell power constraint of each electrolyzer, start-stop state constraint, operating mode constraint, ramp-up constraint, and mutual exclusion constraint of electricity purchase and sale. The maximum comprehensive economic benefit obtained is used as the economic optimal benchmark.

[0036] Specifically, after determining the set of electrolyzers currently in hydrogen production operation and the set of electrolyzers currently in hot standby operation based on the operating status of each electrolyzer in the current scheduling cycle, the controller determines the rated power of each electrolyzer in the set currently in hot standby operation. For each electrolyzer in hot standby operation, its rated power is multiplied by a preset hot standby power consumption ratio to obtain the additional hot standby power consumption of each electrolyzer in hot standby operation. Based on the set of electrolyzers currently in startup operation, the rated power of each electrolyzer in the set is determined, and the rated power is multiplied by a preset startup process power consumption ratio to obtain the startup additional power consumption of each startup electrolyzer. The additional power consumption of all hot standby operations and all startup additional power consumption are summed to obtain the additional power consumption of auxiliary equipment. The hot standby power consumption ratio and the startup process power consumption ratio are fixed ratio values ​​pre-calibrated based on the equipment manufacturer's technical documents or on-site operating data; for example, the hot standby power consumption ratio is 3%, and the startup process power consumption ratio is 5%.

[0037] For example, the expression for calculating the additional power consumption of auxiliary devices is as follows: ; in, For the first Additional power consumption of auxiliary equipment during scheduling periods. This refers to the total number of electrolyzers in the hydrogen production cluster. For the first The rated power of each electrolytic cell, and These are the proportion of power consumption for hot standby (e.g., 0.03) and the proportion of power consumption during startup (e.g., 0.05). For the first The electrolytic cell in the first... This is a flag variable indicating whether the scheduling period is in a hot standby state. A value of 1 indicates that it is in a hot standby state, and a value of 0 indicates that it is not in a hot standby state. For the first The electrolytic cell in the first The flag variable indicating whether the scheduling period is in the startup state has a value of 1, which means it is in the startup state (including either cold start or hot start), and a value of 0 means it is not in the startup state.

[0038] Next, the controller establishes the power balance relationship of the hydrogen production cluster within the current scheduling cycle based on the available power of new energy sources, the power purchased, the power sold, the total power of each multi-to-one electrolyzer group, the power of each independent electrolyzer, the additional power consumption of auxiliary equipment, and the power abandoned.

[0039] It should be noted that when a project is allowed to sell electricity to the grid, the power sales power can also be set in the power balance relationship. The three variables of power purchase, power sales and power abandonment are selected and enabled according to the project's grid connection method. The unreasonable simultaneous power purchase and power sales, or simultaneous power purchase and power abandonment, are avoided in the same period by mutual exclusion variables or equivalent constraints.

[0040] In this embodiment, the power balance relationship is as follows: the sum of available new energy power and purchased power equals the sum of the total power of each multi-pair electrolyzer group, the sum of the power of each independent electrolyzer, the additional power consumption of auxiliary equipment, the sum of abandoned power and sold power. Specifically, the total power of each multi-pair electrolyzer group is the sum of the hydrogen production power of all electrolyzers in hydrogen production operation within that group; the power of each independent electrolyzer is the hydrogen production power of an electrolyzer with an independent auxiliary system; and the abandoned power is the portion of available new energy power that is not absorbed by the hydrogen production cluster and is thus abandoned.

[0041] For example, the expression for the power balance relationship is as follows: ; in, For the first Available power of new energy sources during the dispatch period For the first Power purchased during the dispatch period This refers to the total number of multiple-to-one electrolyzer groups in the hydrogen production cluster. For the first The many-to-one electrolytic cell group in the first Total power of the group during the scheduling period This refers to the total number of independent electrolyzers in the hydrogen production cluster. For the first The independent electrolytic cell in the first Hydrogen production capacity during the scheduling period, For the first Additional power consumption of auxiliary equipment during scheduling periods. For the first Power curtailment during dispatch periods For the first Electricity sales volume during the dispatch period.

[0042] Furthermore, based on the power balance relationship, the power-hydrogen production characteristics of each electrolyzer, electricity sales price, electricity purchase price, and hydrogen revenue parameters, the controller calculates the comprehensive economic benefit of the hydrogen production cluster in the current scheduling cycle. Specifically, the comprehensive economic benefit is the hydrogen production revenue of each scheduling period within the current scheduling cycle minus the electricity purchase cost, start-up cost, shutdown cost, depreciation cost, and operation and maintenance cost, plus the electricity sales revenue. The hydrogen production revenue is obtained by converting the hydrogen production power of each electrolyzer into hydrogen production volume through the power-hydrogen production characteristics and then multiplying it by the hydrogen revenue coefficient. If the project allows the sale of electricity to the grid, the electricity sales revenue generated is included in the comprehensive economic benefit, and a corresponding electricity sales power item is set in the power balance relationship.

[0043] For example, calculate the first Hydrogen production during scheduling period The expression is: ; in, For the first Group of multiple-to-one electrolytic cells in the first The set of electrolyzers that are in hydrogen production operation during the scheduling period. For the first Group 1 The electrolytic cell in the first Power-hydrogen production characteristic function during scheduling period, For the first Group 1 The electrolytic cell in the first Hydrogen production capacity during the scheduling period, For scheduling step size, For the first The independent electrolytic cell in the first Power-hydrogen production characteristic function during scheduling period, For the first The independent electrolytic cell in the first Hydrogen production capacity during the scheduling period.

[0044] also, The expression is: ; in, For the first The constant term coefficients of each independent electrolyzer in the power-hydrogen production characteristic function for The coefficients of the first term in the power-hydrogen production characteristic function for each independent electrolyzer. for The quadratic coefficients of each independent electrolyzer in the power-hydrogen production characteristic function.

[0045] The expression for calculating comprehensive economic benefits is: ; in, The overall economic benefits for the current scheduling cycle, For the current scheduling period, The hydrogen profit coefficient, For the first Hydrogen production revenue during the scheduling period, For the first Electricity purchase price during the dispatch period, For the first Electricity prices during the dispatch period , , as well as The first Start-up costs, downtime costs, depreciated degradation costs, and operation and maintenance costs during the scheduling period.

[0046] Finally, the controller constructs a mixed-integer optimization model based on the power balance relationship, the single-cell power constraints of each electrolyzer, start-stop state constraints, operating mode constraints, ramp-up constraints, and mutual exclusion constraints for power purchase and sale. The decision variables include the total power and single-cell power of each many-to-one electrolyzer group, the power of each independent electrolyzer, the power purchased, the power sold, the power abandoned, and the operating state variables of each electrolyzer. The objective function is to maximize the overall economic benefit. Specifically, the single-cell power constraint ensures that the hydrogen production power of each electrolyzer lies between the upper and lower power limits given by the equipment operating parameters; the start-stop state constraints and operating mode constraints are determined based on the operating state of each electrolyzer in the current scheduling cycle, ensuring that the start-stop process of the electrolyzer meets requirements such as the minimum number of operating units, the minimum downtime, and the start-up sequence; the ramp-up constraints are determined based on the executed power in each time period of the previous scheduling cycle and the ramp rate in the equipment operating parameters; and the mutual exclusion constraints for power purchase and sale ensure that power purchase and sale do not occur simultaneously, nor do power purchase and abandonment.

[0047] Then, in the actual solution process, the above model can be constructed into a mixed integer linear programming model, a mixed integer quadratic programming model, or other corresponding mixed integer optimization models, depending on the specific form of the power-hydrogen production characteristic function and the objective function adopted, and solved by solving tools such as Gurobi, CPLEX, or SCIP.

[0048] During the solution process, the solver relaxes the original problem into a series of linear programming subproblems based on the continuity and integer nature of the decision variables. It approximates the integer feasible region by successively adding cutting planes and performs bounding and pruning at branch nodes until the entire feasible region is searched, yielding the global optimum. The optimal solution output by the solver includes the optimal values ​​of each decision variable, with the maximum value corresponding to the overall economic benefit. That is, the economically optimal benchmark. The maximum comprehensive economic benefit obtained from the solution is taken as the economic optimal benchmark. This benchmark represents the maximum economic benefit that the hydrogen production cluster can theoretically obtain in the current scheduling cycle without considering the constraints of spatiotemporal coordination indicators.

[0049] S203, based on the economically optimal benchmark and the maximum allowable economic loss ratio, calculate the allowable economic loss amount; based on the economically optimal benchmark and the allowable economic loss amount, determine the lower limit of economic returns.

[0050] The maximum permissible economic loss ratio is the percentage of economic benefit loss allowed by the operator relative to the economically optimal benchmark. This ratio is expressed as a percentage and can be set by the operator based on factors such as the economic operation requirements of the hydrogen production plant, fluctuations in electricity market prices, the degree of deviation in renewable energy output forecasts, and equipment operation and maintenance budgets.

[0051] Specifically, after obtaining the economically optimal benchmark and the maximum allowable economic loss ratio Then, the economic optimal benchmark will be... Multiply by the maximum permissible economic loss ratio The amount of economic loss allowed ,Right now Then, the economically optimal benchmark will be... Subtract the allowable economic loss amount To obtain the lower limit of economic returns ,Right now This lower limit of economic returns is used to construct an economically protected feasible region, ensuring that the overall economic returns of all candidate solutions solved within this feasible region are not lower than this lower limit, i.e., the economic losses do not exceed the upper limit allowed by the operator.

[0052] S204. Establish spatiotemporal coordination indicators for multiple-to-one electrolytic cell groups. The spatiotemporal coordination indicators include spatial deviation indicators and transfer deviation indicators.

[0053] In some embodiments, the process of constructing the spatial deviation index includes: determining the total power of each multi-pair electrolyzer group in each scheduling period and the number of electrolyzers in hydrogen production operation in each scheduling period within the current scheduling cycle; calculating the average power of the operating cells in each multi-pair electrolyzer group in each scheduling period based on the total power and the number of electrolyzers in hydrogen production operation; calculating the intra-group spatial deviation of each multi-pair electrolyzer group in each scheduling period based on the difference between the hydrogen production power of each electrolyzer and the average power of the operating cells in the same scheduling period, wherein the intra-group spatial deviation is the average absolute deviation of the hydrogen production power of each operating cell in the group relative to the average power of the operating cells; summing the intra-group spatial deviations of all multi-pair electrolyzer groups in all scheduling periods within the current scheduling cycle to obtain the total spatial deviation, and using the total spatial deviation as the spatial deviation index.

[0054] Among them, the operating cell refers to the electrolyzer in the multi-to-one electrolyzer group that is currently in hydrogen production operation. Electrolyzers in cold shutdown, hot standby, and startup processes are not included in the average power calculation.

[0055] For example, calculate the first Group of multiple-to-one electrolytic cells in the first The expression for the average power of the operating slots during the scheduling period is: ; in, For the first Group of multiple-to-one electrolytic cells in the first The average power of the operating slots during the scheduling period. For the first Group of multiple-to-one electrolytic cells in the first The number of electrolyzers in hydrogen production operation during the scheduling period.

[0056] Calculate the first Group of multiple-to-one electrolytic cells in the first The expression for the intra-group spatial deviation during the scheduling period is: ; in, For the first Group of multiple-to-one electrolytic cells in the first The intra-group spatial deviation during the scheduling period, its subscript Representation space ( spatial )property.

[0057] The expression for calculating the total spatial deviation is: ; in, This represents the total spatial deviation.

[0058] In some embodiments, the process of constructing the transfer deviation index includes: within the current scheduling cycle, determining whether the set of operating cells of each many-to-one electrolytic cell group remains consistent in each adjacent scheduling period; taking the many-to-one electrolytic cell group with consistent set of operating cells as the target many-to-one electrolytic cell group, and taking its corresponding adjacent scheduling period as the target adjacent scheduling period; when the total power of the target many-to-one electrolytic cell group in the previous scheduling period of the target adjacent scheduling period is greater than zero, calculating the allocation share of the total power of the group borne by each operating cell in the previous scheduling period based on the actual power of each operating cell in the previous scheduling period and the total power of the group in the previous scheduling period; and based on the allocation share and the total power of the group in the current scheduling period... The following steps are taken: Calculate the common variable reference power that each operating cell should bear in the current scheduling period while maintaining the same allocation share as in the previous scheduling period; determine the intra-group power transfer amount of each operating cell based on the difference between the hydrogen production power of each operating cell in the current scheduling period and the common variable reference power; determine the intra-group transfer deviation of the target multi-to-one electrolyzer group in the current scheduling period based on half of the sum of the absolute values ​​of the intra-group power transfer amounts of all operating cells in the same group; sum the intra-group transfer deviations of all multi-to-one electrolyzer groups that meet the condition of keeping the operating cell set unchanged in the current scheduling cycle in the corresponding adjacent scheduling periods to obtain the total intra-group transfer deviation, and use the total intra-group transfer deviation as the transfer deviation index.

[0059] Specifically, when establishing the transfer deviation index, the controller first determines, within the current scheduling cycle, the performance of each many-to-one electrolytic cell group in each adjacent scheduling period (i.e., the [missing information]). Scheduling period and the Scheduling period, For the current scheduling period, Whether the set of running slots (for the previous scheduling period) remains consistent, i.e., determining... and Are they completely identical, among which For the first Group of multiple-to-one electrolytic cells in the first The scheduling period is for the set of electrolyzers in hydrogen production operation. If the set of operating cells changes, the allocation share before the switchover is not used to calculate the intra-group transfer deviation for that scheduling period. Instead, the controller first completes the mode transition according to the existing equipment constraints such as cold start, hot start, shutdown, minimum start-up power, minimum number of operating cells, minimum restart interval, and single-cell ramp-up. After the set of operating cells stabilizes, the allocation share for the next period is recalculated based on the actual single-cell power. Therefore, the necessary power reallocation caused by start-up, shutdown, or changes in the number of operating cells will not be incorrectly included in the intra-group transfer index during the stable operation phase.

[0060] If the set of operating cells remains consistent across adjacent scheduling periods, the controller designates the many-to-one electrolytic cell group as the target many-to-one electrolytic cell group and its corresponding adjacent scheduling period as the target adjacent scheduling period. When the target many-to-one electrolytic cell group is in the previous scheduling period of the target adjacent scheduling period (i.e., the [missing information]), the controller will determine the target adjacent scheduling period. Total power of groups during scheduling period When the value is greater than zero, the controller bases the hydrogen production power of each operating cell in the target many-to-one electrolyzer group on the hydrogen production power of the previous scheduling period. The total power of the multi-to-one electrolytic cell group in the previous scheduling period Calculate the share of total power allocated to each operating slot in the previous scheduling period. This allocation share represents the proportion of each operating slot in the total power of the group during the previous scheduling period.

[0061] If during this scheduling period, only the total power of the group increases or decreases together while the distribution relationship within the group remains unchanged, then the... The common reference power variation for each electrolytic cell is That is, the allocation share based on the previous scheduling period. Total power of groups during this scheduling period The common variable reference power that each operating slot should bear in the current scheduling period is calculated if the allocated share of the previous scheduling period remains unchanged.

[0062] The deviation of hydrogen production power from the reference power is defined as the power transfer within the group. . For the first Group of multiple-to-one electrolytic cells in the first The power transfer within a group during the scheduling period. Since the sum of the power of all individual tanks in the same group equals the total power of the group, the power transfer q within each tank group during the same scheduling period. g,k,t The sum is zero, meaning that for every power increase in one slot, the same power decrease in another slot. This represents the power transfer within the group. This represents the power component that truly alters the power distribution within the group, rather than the power change corresponding to the rise and fall of each electrolyzer along with the total power of the group.

[0063] To avoid the same power transfer being calculated repeatedly at both the addition and reduction of a cell, the controller determines the intra-group transfer deviation of the target many-to-one electrolytic cell group during the current scheduling period based on half of the sum of the absolute values ​​of the intra-group power transfers of all operating cells within the same group. For example, calculating the... Group of multiple-to-one electrolytic cells in the first The expression for the intra-group transfer bias during the scheduling period is: ; in, Indicates the first Group of multiple-to-one electrolytic cells in the first The intra-group transfer deviation during the scheduling period, its first subscript Indicates time ( time ) attributes, coefficients This is used to eliminate duplicate statistics for positive and negative transfers. For example, if one tank decreases by 1MW and another tank increases by 1MW, the actual transfer within the group is counted as 1MW instead of 2MW.

[0064] Finally, the controller sums the intra-group transfer deviations of all many-to-one electrolytic cell groups that satisfy the condition of keeping the operating cell set unchanged within the current scheduling cycle, in the corresponding adjacent scheduling periods, to obtain the total intra-group transfer deviation. ,in Indicates the first The set of time slots in a group that remains unchanged between adjacent scheduling periods will transfer the total intra-group deviation. As a transfer deviation indicator, the larger the value of this indicator, the more drastic the change in the allocation relationship of each operating electrolyzer within the group between adjacent scheduling periods, and the more frequent the internal operating condition redistribution disturbances experienced by the shared auxiliary system.

[0065] For example, let's take a four-to-one electrolyzer group as an example. Assume that in two consecutive scheduling periods, each of the four electrolyzer groups has four cells in hydrogen production operation, meaning the set of operating cells remains consistent. Furthermore, the total power of the group in the previous scheduling period was 12MW, and the hydrogen production power of the four electrolyzers was 4MW, 4MW, 2MW, and 2MW respectively. Then, the allocation of the total power of the group undertaken by each operating cell in the previous scheduling period is as follows: That is, the allocation share vector is .

[0066] If the total power of the current scheduling period group increases to 15MW, and the internal allocation relationship remains unchanged, the common change reference power that each operating tank should bear after the total power of the group increases is: 15×(1 / 3)=5MW, 15×(1 / 3)=5MW, 15×(1 / 6)=2.5MW, 15×(1 / 6)=2.5MW. If the optimized hydrogen production power of the current scheduling period is 5MW, 4.5MW, 3MW, and 2.5MW respectively, then the internal power transfer amount of each operating tank is 5MW. 5 = 0MW, 4.5 5= 0.5MW, 3 2.5 = +0.5MW, 2.5 2.5 = 0MW. Therefore, the 3MW increase in total power from 12MW to 15MW during the current dispatch period is not included in the intra-group power transfer deviation; only the 0.5MW decrease in the second operating tank relative to the common change reference power and the 0.5MW increase in the third operating tank relative to the common change reference power constitute the same intra-group power transfer. The intra-group transfer deviation for this group during the current dispatch period is... In other words, the actual power transfer within the group during that period was 0.5MW, not 1MW obtained by repeatedly adding the increase and decrease.

[0067] S205, under the joint constraints of the lower limit of economic benefits and the operational constraints of the hydrogen production cluster, coordinates and optimizes the spatial deviation index and the transfer deviation index to obtain the target spatiotemporal coordination scheme corresponding to the maximum allowable economic loss ratio.

[0068] In this embodiment, under the combined constraints of the lower limit of economic returns and operational constraints, the solution is obtained by minimizing the spatial deviation index and the transfer deviation index, respectively, to obtain the first scheme and the second scheme. Multiple boundary position parameters are set between the first and second schemes. Under each boundary position parameter, the solution is obtained by minimizing the transfer deviation index and constraining the spatial deviation index to not exceed the upper limit corresponding to the current boundary position parameter, resulting in multiple boundary schemes. A target boundary scheme is selected from these multiple boundary schemes and used as the inner representative scheme under the current lower limit of economic returns. The target boundary scheme is the one with the largest vertical distance from the normalized index to the line connecting the first and second schemes among the multiple boundary schemes. Multiple candidate economic loss ratios are uniformly selected between zero and the maximum allowable economic loss ratio, and a corresponding candidate economic loss ratio is determined for each candidate economic loss ratio. The process involves selecting a lower bound for economic returns, and then, under each candidate lower bound, returning to the execution steps to solve for the first and second schemes with the objectives of minimizing the spatial deviation index and the transfer deviation index, respectively, under the joint constraints of the lower bound for economic returns and operational constraints. This yields the inner-layer representative schemes corresponding to each candidate economic loss ratio. Based on the economic loss ratio, spatial deviation index, and transfer deviation index of each inner-layer representative scheme, an outer-layer comparison is performed to determine the final economic protection ratio from among the candidate economic loss ratios. Under the joint constraints of the lower bound for economic returns and operational constraints corresponding to the final economic protection ratio, the process returns to the execution steps to solve for the first and second schemes with the objectives of minimizing the spatial deviation index and the transfer deviation index, respectively, under the joint constraints of the lower bound for economic returns and operational constraints. The resulting inner-layer representative schemes are then used as the target spatiotemporal coordination scheme.

[0069] Specifically, the controller first performs single-objective solutions under the combined constraints of the current lower limit of economic returns and operational constraints, with the objectives of minimizing the spatial deviation index and the transfer deviation index respectively, resulting in two endpoint schemes, namely the first scheme. Second Scheme The first option is a spatial deviation index. The minimum acceptable option; the second option is the transfer deviation index. The smallest solution.

[0070] Then, the controller sets multiple boundary position parameters between the first and second schemes. , The value range is from 0 to 1, for example... The possible values ​​are 0, 0.2, 0.4, 0.6, 0.8, or 1.0. For each boundary position parameter, the controller aims to minimize the transfer deviation index, constrained by the spatial deviation index not exceeding the upper limit corresponding to the current boundary position parameter. The upper limit expression is as follows: ,in The spatial deviation index value for the first scheme is... This represents the spatial deviation index value for the second scheme. (Through multiple...) The value is repeatedly solved to obtain multiple boundary schemes.

[0071] After obtaining multiple boundary scenarios, a target boundary scenario needs to be selected as the inner-layer representative scenario under the current economic benefit floor. Specifically, to eliminate the impact of different value ranges of the spatial deviation index and the transfer deviation index, the controller utilizes the first scenario. Second Scheme The index values ​​are then normalized for the spatial deviation index and transfer deviation index of each boundary scheme. The normalization formula is as follows: , ; in, and These are the normalized spatial bias index and the normalized group transfer bias index, respectively. The transfer deviation index for the first scheme. This is the transfer deviation index for the second scheme.

[0072] After normalization, the first scheme corresponds to the normalized coordinates ( The second scheme corresponds to normalized coordinates ( ), ).

[0073] For each boundary scheme, the controller calculates the perpendicular distance from its normalized coordinates to the line connecting the first and second schemes (i.e., the straight line from (0, 1) to (1, 0). The formula for calculating the perpendicular distance is: ; in, The knee index of the boundary point, The boundary position parameters are The corresponding normalized spatial deviation index value at that time, The boundary position parameters are The corresponding normalized transfer deviation index value.

[0074] Then, select The boundary scheme corresponding to the boundary position with the largest value is taken as the target boundary scheme, i.e. When multiple boundary schemes have the same vertical distance, choose the one that is closer to the two-dimensional ideal point (0, 0); if the performance boundary is approximately a straight line, then directly choose the boundary point that is closest to the two-dimensional ideal point (0, 0).

[0075] It should be noted that when the feasible region for economic protection is too narrow, the scheme that minimizes the spatial deviation index and the scheme that minimizes the transfer deviation index may be the same optimal scheme, i.e., the first scheme and the second scheme overlap. In this case, the two endpoint indices are the same, and the denominator of the normalization formula is zero. To avoid the normalization denominator being zero, the controller sets a spatial range tolerance. and transfer range tolerance .when If this indicates that there are no identifiable independent trade-offs for spatial indicators within the current feasible economic protection domain, then they will no longer be calculated. Instead, it selects the option with the smaller transfer deviation index among those that meet the near-optimal space conditions; when When the spatial deviation index is smaller, the controller selects the option with the smaller spatial deviation index. When both ranges degenerate, the ordinary knee point boundary is no longer constructed. The controller selects the option according to preset secondary rules such as lower economic loss, fewer start-stop times, or smaller changes in maximum single-slot power.

[0076] Furthermore, the controller uniformly selects multiple candidate economic loss ratios between zero and the maximum permissible economic loss ratio. It includes at least two endpoints: zero and the maximum permissible economic loss ratio. For example, when the maximum permissible economic loss ratio is 2%, The possible values ​​are 0%, 0.5%, 1.0%, 1.5%, and 2.0%. For each candidate economic loss ratio, the controller determines its corresponding candidate economic benefit lower limit, and returns to execute the above steps of "solving the problem under the common constraints of the current economic benefit lower limit and the operational constraints, with the objectives of minimizing the spatial deviation index and the transfer deviation index respectively, to obtain the first scheme and the second scheme" under each candidate economic benefit lower limit. That is, reconstructing the two-dimensional spatiotemporal performance boundary (i.e., the first scheme and the second scheme) and selecting the target boundary scheme, thereby obtaining the inner representative scheme corresponding to each candidate economic loss ratio.

[0077] Then, the controller performs an outer-layer comparison based on the economic loss ratio, spatial deviation index, and transfer deviation index of each inner-layer representative scheme, determining the final economic protection ratio from among the candidate economic loss ratios. Finally, under the joint constraints of the lower limit of economic benefit corresponding to the final economic protection ratio and the operational constraints, the controller returns to execute the above steps of "solving problems with minimizing the spatial deviation index and the transfer deviation index respectively under the joint constraints of the current lower limit of economic benefit and the operational constraints, thereby obtaining the first and second schemes," that is, reconstructing the two-dimensional spatiotemporal performance boundary and selecting the target boundary scheme, and taking the finally obtained inner-layer representative scheme as the target spatiotemporal coordination scheme. This target spatiotemporal coordination scheme is the optimal power allocation scheme that, while ensuring that the economic loss does not exceed the operator's allowable upper limit, can minimize the spatial power difference within the group and reduce the power transfer within the group as much as possible. Its economic loss ratio does not exceed the final economic protection ratio, and the final economic protection ratio does not exceed the maximum allowable economic loss ratio set by the operator. At this point, the controller has completed the spatiotemporal coordination optimization of the many-to-one electrolytic cell group under economic protection, and obtained a target spatiotemporal coordination scheme that can be directly executed.

[0078] In some embodiments, an outer-layer comparison is performed based on the economic loss ratio, spatial deviation index, and transfer deviation index of each inner-layer representative scheme to determine the final economic protection ratio from the candidate economic loss ratios. This includes: normalizing the spatial deviation index and transfer deviation index of each inner-layer representative scheme, and using the normalized spatial deviation index and normalized transfer deviation index as comprehensive performance indicators; using the minimum economic loss ratio and the minimum comprehensive performance index as the ideal point, selecting the scheme that is not superior to other inner-layer representative schemes in both economic loss ratio and comprehensive performance index from among the inner-layer representative schemes, as candidate schemes; calculating the distance from each candidate scheme to the ideal point, and selecting the candidate scheme with the smallest distance. The economic loss ratio is selected as the current optimal ratio. An intermediate ratio is chosen between the current optimal ratio and adjacent candidate ratios as a new candidate economic loss ratio. For the new candidate economic loss ratio, the process returns to the previous steps, which involve solving for the first and second schemes under the combined constraints of the lower limit of economic returns and operational constraints, with the objectives of minimizing the spatial deviation index and the transfer deviation index, respectively. This yields a new inner-layer representative scheme, which is then included in the candidate schemes. The process returns to the previous steps, which involve calculating the distance from each candidate scheme to the ideal point and selecting the candidate economic loss ratio corresponding to the scheme with the smallest distance as the current optimal ratio. When the preset stopping condition is met, the current optimal ratio is determined as the final economic protection ratio.

[0079] Specifically, after obtaining the inner-layer representative schemes corresponding to the economic loss ratios of each candidate scheme, the controller calculates the economic loss ratio of the inner-layer representative schemes corresponding to the economic loss ratios of each candidate scheme. That is, the proportion of the actual economic loss of the proposed plan relative to the economically optimal benchmark, which usually satisfies .in For the first The proportion of economic protection for each candidate.

[0080] To ensure consistent comparisons across metrics of different dimensions, the controller normalizes the spatial deviation and transfer deviation metrics for each inner-layer representative scheme. Specifically, the maximum value of the spatial deviation metric is determined for each inner-layer representative scheme. and minimum value The maximum value of the transfer deviation index and minimum value Based on the determined maximum and minimum values, the spatial deviation index and transfer deviation index of each inner-layer representative scheme are normalized respectively.

[0081] For example, for the first The normalized expression for each representative scheme is as follows: ; ; ; in, For the first The normalized candidate economic loss ratio of each inner-layer representative scheme. For the first The proportion of economic losses for each inner-layer representative scheme. and These are the minimum and maximum proportions of candidate economic losses among all inner-layer representative schemes, respectively. and The first The normalized spatial deviation index and transfer deviation index of each inner layer representative scheme. and The first The inner layer represents the spatial deviation index and transfer deviation index of the scheme. and These represent the minimum and maximum values ​​of the spatial deviation index among all inner-layer representative schemes, respectively. and These are the minimum and maximum values ​​of the transfer deviation index among all inner-layer representative schemes, respectively.

[0082] After normalization, the values ​​of both indicators are mapped to the interval [0, 1], eliminating the difference in dimensions. Then, the normalized spatial deviation index value and the normalized transfer deviation index are used as the two dimensions of the comprehensive performance index of the corresponding inner representative scheme. That is, the comprehensive performance index is composed of the normalized spatial deviation index value and the normalized transfer deviation index.

[0083] With the first Taking a representative scheme as an example, it constitutes... Comprehensive performance indicators of each inner layer representative scheme The expression is as follows: ; Next, the ideal point is defined as having the minimum economic loss ratio and the minimum comprehensive performance index, with coordinates (0, 0). Among the representative schemes in the inner layer, the controller performs non-dominated screening: if the economic loss ratio of inner layer representative scheme A is no higher than that of inner layer representative scheme B, and its comprehensive performance index is also no higher than that of inner layer representative scheme B, and at least one aspect is strictly superior, then inner layer representative scheme A is said to dominate inner layer representative scheme B. Dominated schemes have no retention advantage in either economic or spatiotemporal performance, so the controller deletes them. The inner layer representative schemes that are not simultaneously superior to other inner layer representative schemes in both economic loss ratio and comprehensive performance index—that is, the retained inner layer representative schemes—are selected as candidate schemes, forming the non-dominated candidate set P.

[0084] For each candidate solution in the non-dominated candidate set P, the controller calculates the distance from each candidate solution to the ideal point and selects the candidate solution with the smallest distance and the corresponding economic loss ratio as the current optimal ratio. When multiple solutions have the same distance to the ideal point, the one with the smaller economic loss ratio or the one with better spatiotemporal comprehensive performance can be selected according to actual needs.

[0085] For example, calculate the first The distances from the candidate solutions to the ideal point are as follows: ; ; in, For the first The distance from each candidate solution to the ideal point For the first Normalized candidate economic loss ratios for each alternative option For the first The overall performance indicators of the candidate solutions This is the index number of the candidate solution with the smallest distance that is ultimately selected.

[0086] To further improve the accuracy of selecting the economic protection ratio, the controller selects an intermediate ratio between the current optimal ratio and adjacent candidate ratios as a new candidate economic loss ratio. For the new candidate economic loss ratio, the controller returns to the step of "solving the problem under the joint constraints of the candidate economic benefit lower limit and operational constraints, with the objectives of minimizing the spatial deviation index and the transfer deviation index respectively, to obtain the first and second schemes," thus obtaining a new inner-layer representative scheme. This new inner-layer representative scheme is included in the candidate schemes, and the controller returns to the step of "calculating the distance from each candidate scheme to the ideal point, and selecting the candidate economic loss ratio corresponding to the candidate scheme with the smallest distance as the current optimal ratio." This process continues the search using binary search or other locally encrypted methods, such as inserting an intermediate ratio between the optimal candidate and its adjacent candidates.

[0087] The controller determines whether the current condition meets the preset stopping criteria. These criteria include at least one of the following: the interval between adjacent ratios is less than the preset minimum resolution; adding a new candidate economic loss ratio no longer changes the final selection; the spatiotemporal performance improvement is below a preset threshold; or the preset maximum number of refinements has been reached. If the stopping criteria are met, outer-layer ratio refinement is stopped, and the current optimal ratio is determined as the final economic protection ratio. If the conditions are not met, the process continues to select an intermediate ratio between the updated current optimal ratio and the adjacent candidate ratios, and repeats the steps of obtaining a new inner-layer representative scheme and reselecting the current optimal ratio until the preset stopping condition is met. Thus, the final economic protection ratio is determined. Within the maximum permissible economic loss ratio given by the operator. Within the range.

[0088] It should be noted that the final economic protection ratio Within the maximum permissible economic loss ratio given by the operator. Within the specified range, a continuous process involving preliminary screening of candidate proportions, outer-layer non-dominated comparison, and local refinement search was employed to determine the optimal economic protection proportion. This process eliminates the need for the operator to pre-specify a single final loss proportion; instead, the operator only needs to set the maximum acceptable economic loss range, and the controller automatically searches and determines the optimal economic protection proportion within this range. The inner-layer spatiotemporal trade-off under candidate proportions ensures a reasonable balance between spatial and transfer deviations for each candidate economic loss proportion. The outer-layer non-dominated screening ensures that the final selected scheme is not simultaneously dominated by other schemes in terms of both economy and spatiotemporal performance. Local refinement further densifies the search in the superior region to improve accuracy. The resulting final economic protection proportion has a clear and traceable selection basis, avoiding incurring economic costs exceeding the operator's requirements to improve spatiotemporal deviations, while ensuring that the economic loss of the final implemented scheme is strictly controlled within the operator's preset maximum allowable economic loss proportion, thus achieving a unity of economic protection and spatiotemporal coordination.

[0089] S206: Extract the operating status and hydrogen production power of each electrolyzer in the hydrogen production cluster during the current scheduling cycle from the target spatiotemporal coordination scheme; based on the operating status and hydrogen production power, generate control instructions for each electrolyzer, including start / stop status instructions and power setpoint instructions.

[0090] Specifically, after obtaining the target spatiotemporal coordination scheme, this scheme includes the optimal operating state and optimal hydrogen production power allocation results for each electrolyzer in the hydrogen production cluster within the current scheduling cycle. The controller extracts the operating state and hydrogen production power of each electrolyzer in the hydrogen production cluster within the current scheduling cycle from the target spatiotemporal coordination scheme. The operating state includes hydrogen production operation state, hot standby state, start-up state, and shutdown state, used to determine whether each electrolyzer needs to be put into operation, whether it is in hot standby, whether it is in the process of starting up, or whether it has been shut down; the hydrogen production power is the electrical power value that each electrolyzer needs to bear within the current scheduling cycle, used to determine the specific load size of each electrolyzer.

[0091] Next, the controller generates corresponding start / stop commands based on the operating status of each electrolyzer: for electrolyzers in hydrogen production or start-up mode, a start command or a maintain-operation command is generated; for electrolyzers in shutdown mode, a shutdown command is generated; for electrolyzers in hot standby mode, a hot standby command is generated to maintain alkali circulation and temperature maintenance for rapid response to subsequent scheduling needs. The controller also generates corresponding power setpoint commands based on the hydrogen production capacity of each electrolyzer, converting the hydrogen production capacity of each electrolyzer into a power setpoint that can be sent to the rectifier unit.

[0092] In this embodiment, the controller employs a rolling optimization execution method, outputting only the start / stop status commands and power setpoint commands for the first scheduling period within the current scheduling cycle, rather than issuing commands for all periods within the entire scheduling cycle at once. This is because external environmental data such as available renewable energy power and electricity purchase prices are time-varying and uncertain, and the prediction accuracy for long-term periods is low. Issuing commands for all future periods at once may cause deviations from the optimal execution. When subsequent periods of the current scheduling cycle arrive, the controller recalculates based on updated operating status data and external environmental data to ensure the timeliness and accuracy of control commands.

[0093] It should be noted that the generated control commands are sent to the rectifiers and auxiliary systems of each electrolyzer via fieldbus or industrial Ethernet for execution. The rectifiers adjust the input power of each electrolyzer according to the power setpoint commands, and the auxiliary systems adjust the operating status of auxiliary equipment such as alkali circulation, cooling, and gas-liquid separation according to the operating status commands. At the start of the next scheduling cycle, the controller re-acquires updated operating status data and external environment data, and repeats all steps from S201 to S206, achieving rolling update execution. Through this rolling optimization execution method, the controller can respond promptly to fluctuations in new energy power and changes in electricity prices, continuously performing spatiotemporal coordinated control of the many-to-one electrolyzer group.

[0094] Furthermore, as Figure 1 In specific implementation, this application provides a spatiotemporal coordination method system for a many-to-one electrolyzer group, applied to a hydrogen production cluster including at least one many-to-one electrolyzer group. The many-to-one electrolyzer group includes multiple electrolyzers sharing a common auxiliary system, such as... Figure 3 As shown, the system includes: The acquisition module 301 is used to acquire the operating status data and external environment data of the hydrogen production cluster. The operating status data is used to characterize the availability status of each electrolyzer in the current scheduling cycle, and the external environment data is used to characterize the available power generation and economic parameters of the hydrogen production cluster in the current scheduling cycle. The calculation module 302, based on the operating status data and external environment data, solves for the maximum economic benefit that satisfies the operating constraints of the hydrogen production cluster, and uses it as the economically optimal benchmark. Module 303 is used to determine the lower limit of economic returns based on the economically optimal benchmark and the preset maximum allowable economic loss ratio. Module 304 is used to establish spatiotemporal coordination indicators for multiple-to-one electrolytic cell groups. The spatiotemporal coordination indicators include spatial deviation indicators and transfer deviation indicators. The spatial deviation indicators are used to characterize the degree of power difference between electrolytic cells in the same scheduling period within the same multiple-to-one electrolytic cell group. The transfer deviation indicators are used to characterize the degree of power transfer caused by changes in the allocation relationship within the group between adjacent scheduling periods. The optimization module 305 is used to coordinate and optimize the spatial deviation index and the transfer deviation index under the joint constraints of the lower limit of economic benefits and the operation constraints of the hydrogen production cluster, so as to obtain the target spatiotemporal coordination scheme corresponding to the maximum allowable economic loss ratio. The generation module 306 generates control commands for each electrolytic cell based on the target spatiotemporal coordination scheme.

[0095] This application also provides a computer device, which may specifically be a personal computer, a server, a network device, etc. Figure 4As shown, the computer device includes a bus, a processor, memory, and a communication interface, and may also include an input / output interface and a display device. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database stores location information. The network interface allows communication with external terminals via a network connection. When the computer program is executed by the processor, it implements the steps in the above-described method embodiments.

[0096] Those skilled in the art will understand that Figure 4 The structure shown is only a part of the structure related to the solution of this application and does not constitute a limitation on the computer device on which the solution of this application is applied. The specific computer device may include more or fewer components, or combine certain components, or have different component arrangements.

[0097] In one embodiment, a computer-readable storage medium is provided, which may be non-volatile or volatile, having stored thereon a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0098] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0099] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, graphics processors, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0100] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0101] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A spatiotemporal coordination method for a many-to-one electrolytic cell group, characterized in that, Applied to hydrogen production clusters comprising at least one many-to-one electrolyzer group, wherein the many-to-one electrolyzer group includes multiple electrolyzers sharing a common auxiliary system, including: The operation status data and external environment data of the hydrogen production cluster are obtained. The operation status data is used to characterize the availability status of each electrolyzer in the current scheduling cycle, and the external environment data is used to characterize the available power generation and economic parameters of the hydrogen production cluster in the current scheduling cycle. Based on the operational status data and the external environment data, the maximum economic benefit that satisfies the operational constraints of the hydrogen production cluster is calculated and used as the economic optimal benchmark. Based on the aforementioned economic optimal benchmark and the preset maximum allowable economic loss ratio, the lower limit of economic returns is determined. Establish a spatiotemporal coordination index for the multiple-to-one electrolytic cell group. The spatiotemporal coordination index includes a spatial deviation index and a transfer deviation index. The spatial deviation index is used to characterize the degree of power difference between electrolytic cells within the same multiple-to-one electrolytic cell group during the same scheduling period. The transfer deviation index is used to characterize the degree of power transfer caused by changes in the allocation relationship within the group between adjacent scheduling periods. Under the combined constraints of the lower limit of economic benefits and the operational constraints of the hydrogen production cluster, the spatial deviation index and the transfer deviation index are coordinated and optimized to obtain a target spatiotemporal coordination scheme corresponding to the maximum allowable economic loss ratio. Based on the target spatiotemporal coordination scheme, control commands for each electrolytic cell are generated.

2. The spatiotemporal coordination method for multiple-to-one electrolytic cell groups according to claim 1, characterized in that, The hydrogen production cluster also includes at least one independent electrolyzer. The operating status data includes the operating status and equipment operating parameters of each electrolyzer in the current scheduling cycle. The external environment data includes available power of new energy sources, electricity purchase price, electricity sales price, and hydrogen revenue parameters. The process of calculating the maximum economic benefit that satisfies the operational constraints of the hydrogen production cluster based on the operational status data and the external environment data, and using this as the economically optimal benchmark, includes: Based on the operating status of each electrolyzer in the current scheduling cycle, determine the set of electrolyzers currently in hydrogen production operation and the set of electrolyzers currently in hot standby operation, and determine the additional power consumption of auxiliary equipment based on the equipment operating parameters and the set of electrolyzers currently in hot standby operation. Based on the available power of the new energy source, the power purchased, the power sold, the total power of each multi-to-one electrolyzer group, the power of each independent electrolyzer, the additional power consumption of the auxiliary equipment, and the power abandoned by the hydrogen production cluster, the power balance relationship of the hydrogen production cluster in the current scheduling cycle is established. Based on the power balance relationship, the power-hydrogen production characteristics of each electrolyzer, and the electricity purchase price, electricity sales price, and hydrogen revenue parameters, the comprehensive economic benefits of the hydrogen production cluster in the current scheduling cycle are calculated. With the goal of maximizing the comprehensive economic benefit, the solution is obtained under the joint constraints of the power balance relationship, the single-cell power constraint of each electrolytic cell, the start-stop state constraint, the operation mode constraint, the ramp constraint, and the mutual exclusion constraint of power purchase and sale. The maximum comprehensive economic benefit obtained is taken as the economic optimal benchmark.

3. The spatiotemporal coordination method for multiple-to-one electrolytic cell groups according to claim 1, characterized in that, The process of constructing the spatial deviation index includes: Determine the total power of each multi-to-one electrolyzer group in each scheduling period and the number of electrolyzers in hydrogen production operation in each scheduling period within the current scheduling cycle. Based on the total power of the group and the number of electrolyzers in hydrogen production operation, the average power of the operating cells in each multiple-to-one electrolyzer group during each scheduling period is calculated. The operating cells refer to the electrolyzers in the multiple-to-one electrolyzer group that are currently in hydrogen production operation. Based on the difference between the hydrogen production power of each electrolyzer and the average power of the operating cells in the same scheduling period, the intra-group spatial deviation of each multi-to-one electrolyzer group in each scheduling period is calculated. The intra-group spatial deviation is the average absolute deviation of the hydrogen production power of each operating cell in the group relative to the average power of the operating cells. The total spatial deviation is obtained by summing the intra-group spatial deviations of all multiple-to-one electrolytic cell groups in all scheduling periods within the current scheduling cycle, and the total spatial deviation is used as the spatial deviation index.

4. The spatiotemporal coordination method for multiple-to-one electrolytic cell groups according to claim 3, characterized in that, The process of constructing the transfer deviation index includes: Within the current scheduling cycle, determine whether the set of operating cells for each many-to-one electrolytic cell group remains consistent in each adjacent scheduling period; The target many-to-one electrolytic cell group with a consistent set of operating slots is taken as the target many-to-one electrolytic cell group, and its corresponding adjacent scheduling time period is taken as the target adjacent scheduling time period. When the total power of the target multi-to-one electrolytic cell group in the previous scheduling period of the adjacent scheduling period of the target is greater than zero, the allocation share of the total power of the group undertaken by each operating cell in the previous scheduling period is calculated based on the actual power of each operating cell in the previous scheduling period and the total power of the group in the previous scheduling period. Based on the allocated share and the total power of the group in the current scheduling period, calculate the common change reference power that each operating slot should bear in the current scheduling period while keeping the allocated share of the previous scheduling period unchanged; Based on the difference between the hydrogen production power of each operating cell during the current scheduling period and the common variable reference power, the intra-group power transfer amount of each operating cell is determined. The intra-group transfer deviation of the target many-to-one electrolytic cell group during the current scheduling period is determined by half the sum of the absolute values ​​of the intra-group power transfer of all operating cells in the same group. The intra-group transfer deviations of all many-to-one electrolytic cell groups that meet the condition of keeping the operating cell set unchanged within the current scheduling cycle are summed in the corresponding adjacent scheduling periods to obtain the total intra-group transfer deviation, which is then used as the transfer deviation index.

5. The spatiotemporal coordination method for multiple-to-one electrolytic cell groups according to claim 1, characterized in that, The determination of the lower limit of economic returns based on the economically optimal benchmark and the preset maximum allowable economic loss ratio includes: Based on the aforementioned economic optimal benchmark and the aforementioned maximum allowable economic loss ratio, the allowable economic loss amount is calculated; Based on the economically optimal benchmark and the allowable economic loss amount, the lower limit of economic returns is determined.

6. The spatiotemporal coordination method for multiple-to-one electrolytic cell groups according to claim 4, characterized in that, Under the combined constraints of the lower limit of economic returns and the operational constraints of the hydrogen production cluster, the spatial deviation index and the transfer deviation index are coordinated and optimized to obtain a target spatiotemporal coordination scheme corresponding to the maximum allowable economic loss ratio, including: Under the combined constraints of the lower limit of economic returns and the operational constraints, the solutions are obtained by minimizing the spatial deviation index and the transfer deviation index, respectively, to obtain the first and second schemes. Multiple boundary position parameters are set between the first scheme and the second scheme. Under each boundary position parameter, the solution is obtained with the goal of minimizing the transfer deviation index and the constraint that the spatial deviation index does not exceed the upper limit corresponding to the current boundary position parameter. Multiple boundary schemes are obtained, and a target boundary scheme is selected from the multiple boundary schemes as the inner representative scheme under the current economic benefit lower limit. The target boundary scheme is the boundary scheme with the largest vertical distance from the normalized index to the line connecting the first scheme and the second scheme among the multiple boundary schemes. Multiple candidate economic loss ratios are uniformly selected between zero and the maximum allowable economic loss ratio. For each candidate economic loss ratio, a corresponding candidate economic benefit lower limit is determined. Under each candidate economic benefit lower limit, the steps of minimizing the spatial deviation index and minimizing the transfer deviation index are performed under the common constraints of the economic benefit lower limit and the operation constraint to obtain the first scheme and the second scheme. In this way, the inner representative scheme corresponding to each candidate economic loss ratio is obtained. Based on the economic loss ratio, spatial deviation index, and transfer deviation index of each inner-layer representative scheme, an outer-layer comparison is made, and the final economic protection ratio is determined from each candidate economic loss ratio. Under the combined constraints of the lower limit of economic benefits corresponding to the final economic protection ratio and the operational constraints, the process returns to the step of solving the problem with the objectives of minimizing the spatial deviation index and the transfer deviation index respectively under the combined constraints of the lower limit of economic benefits and the operational constraints, to obtain the first scheme and the second scheme, and the obtained inner representative scheme is taken as the target spatiotemporal coordination scheme.

7. The spatiotemporal coordination method for multiple-to-one electrolytic cell groups according to claim 6, characterized in that, The outer layer comparison is performed based on the economic loss ratio, spatial deviation index, and transfer deviation index of each inner-layer representative scheme, and the final economic protection ratio is determined from each candidate economic loss ratio, including: The spatial deviation index and transfer deviation index of each inner layer representative scheme are normalized respectively, and the normalized spatial deviation index and normalized transfer deviation index are used as comprehensive performance index. Using the minimum economic loss ratio and the minimum comprehensive performance index as the ideal point, among the representative schemes of each inner layer, the scheme that is not better than other representative schemes in both economic loss ratio and comprehensive performance index is selected as the candidate scheme. Calculate the distance from each candidate solution to the ideal point, and select the candidate economic loss ratio corresponding to the candidate solution with the smallest distance as the current better ratio; Select an intermediate ratio between the current optimal ratio and the adjacent candidate ratios as a new candidate economic loss ratio. For the new candidate economic loss ratio, return to the step of solving the problem under the common constraints of the lower limit of economic benefits and the operational constraints, with the goal of minimizing the spatial deviation index and the transfer deviation index respectively, to obtain the first scheme and the second scheme. This will result in a new inner layer representative scheme. The new inner layer representative scheme will be included in the candidate schemes and return to the step of calculating the distance from each candidate scheme to the ideal point and selecting the candidate economic loss ratio corresponding to the candidate scheme with the smallest distance as the current optimal ratio. When the preset stopping conditions are met, the current optimal ratio is determined as the final economic protection ratio.

8. The spatiotemporal coordination method for multiple-to-one electrolytic cell groups according to claim 1, characterized in that, The generation of control commands for each electrolytic cell based on the target spatiotemporal coordination scheme includes: Extract the operating status and hydrogen production power of each electrolyzer in the hydrogen production cluster during the current scheduling cycle from the target spatiotemporal coordination scheme; Based on the operating status and the hydrogen production power, control instructions are generated for each electrolyzer, including start / stop status instructions and power setpoint instructions.

9. A spatiotemporal coordination system for a many-to-one electrolytic cell group, characterized in that, Applied to hydrogen production clusters comprising at least one many-to-one electrolyzer group, wherein the many-to-one electrolyzer group includes multiple electrolyzers sharing a common auxiliary system, including: The acquisition module is used to acquire the operating status data and external environment data of the hydrogen production cluster. The operating status data is used to characterize the availability status of each electrolyzer in the current scheduling cycle, and the external environment data is used to characterize the available power generation and economic parameters of the hydrogen production cluster in the current scheduling cycle. The calculation module, based on the operating status data and the external environment data, calculates the maximum economic benefit that satisfies the operating constraints of the hydrogen production cluster, and uses it as the economic optimal benchmark. The determination module is used to determine the lower limit of economic returns based on the economic optimal benchmark and the preset maximum allowable economic loss ratio; A construction module is used to establish the spatiotemporal coordination index of the multiple-to-one electrolytic cell group. The spatiotemporal coordination index includes a spatial deviation index and a transfer deviation index. The spatial deviation index is used to characterize the degree of power difference between electrolytic cells in the same scheduling period within the same multiple-to-one electrolytic cell group. The transfer deviation index is used to characterize the degree of power transfer caused by the change in the allocation relationship within the group between adjacent scheduling periods. The optimization module is used to coordinate and optimize the spatial deviation index and the transfer deviation index under the joint constraints of the lower limit of economic benefits and the operation constraints of the hydrogen production cluster, so as to obtain a target spatiotemporal coordination scheme corresponding to the maximum allowable economic loss ratio. The generation module generates control commands for each electrolytic cell based on the target spatiotemporal coordination scheme.

10. A computer device, comprising a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor, characterized in that, When the processor executes the computer program, it implements the spatiotemporal coordination method for a many-to-one electrolytic cell group as described in any one of claims 1 to 8.

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