A method, apparatus, and medium for load scheduling of hydrogen production unit clusters that takes into account the flexibility and backup of electro-hydrogen production.

Abstract

This invention discloses a method, apparatus, and medium for load scheduling of hydrogen production unit clusters that considers the flexibility and standby of electro-hydrogen production. The method includes the following steps: S100: Constructing a state switching logic model for a single hydrogen production unit, the state switching logic model including the standby state of a single hydrogen production unit; S200: Based on the state switching logic model, constructing a comprehensive hydrogen production unit cluster load model; S300: By relaxing the comprehensive hydrogen production unit cluster load model, constructing a hydrogen production unit cluster load model that considers the flexibility and standby of electro-hydrogen production, based on the state switching logic model; S400: Based on the hydrogen production unit cluster load model that considers the flexibility and standby of electro-hydrogen production, under the condition of wind power uncertainty, establishing a two-layer optimized scheduling model for the hydrogen production unit and energy storage system, including an upper-layer scheduling model and a lower-layer scheduling model. This invention can achieve economic efficiency in hydrogen production systems.

Description

Technical Field

[0001] This invention belongs to the field of comprehensive energy optimization and scheduling technology, and particularly relates to a method, device and medium for load scheduling of hydrogen production unit clusters that takes into account the flexibility of hydrogen production in electro-hydrogen production. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] With the increasing prominence of the global energy crisis and environmental problems, energy systems face the development tasks of improving quality and efficiency while conserving energy and reducing emissions. Concepts such as Integrated Energy Systems (IES) have been proposed and studied by scholars at home and abroad. With their optimization of energy utilization and the achievement of complementary advantages and efficient utilization through the conversion between different energy sources, they are gradually becoming an inevitable element of energy sector transformation.

[0004] Hydrogen is green and pollution-free during combustion, making it an important carrier for promoting the clean and low-carbon development of energy systems. Electro-hydrogen technology is regarded as an important means to promote multi-energy coupling and new energy consumption, and has great potential in promoting the low-carbon economic operation of integrated energy systems and the efficient utilization of internal renewable energy.

[0005] However, the power generated by renewable energy sources such as wind and solar power as input to the hydrogen production system is volatile and uncertain. This can lead to frequent start-ups and shutdowns of the electrolyzer during operation, which will not only reduce its own service life, but also reduce its hydrogen production, and may even affect the purity of the product hydrogen and the concentration of hydrogen in oxygen, thereby affecting the safety of the entire electrolytic hydrogen production system.

[0006] On the one hand, the volatility of wind power exacerbates the volatility of electrical energy, making the efficient and stable operation of the energy conversion process crucial to the electrolytic hydrogen production equipment. On the other hand, fluctuations in hydrogen production power significantly impact the lifespan of the hydrogen production unit and the purity of the hydrogen, placing higher demands on the electrolyzer. Optimizing the materials of the electrodes and catalysts in the electrolyzer can reduce electrolysis costs and improve hydrogen production efficiency. Optimizing the performance of the separator membrane can enhance its performance. Adjusting process parameters can improve the electrolyzer's resistance to power fluctuations and ensure safe system operation. However, modifying the electromagnetic power supply load configuration and cluster control strategy of the electrolytic hydrogen production equipment is worth considering in the short term.

[0007] In existing technologies, wind-storage hydrogen production systems and traditional hydrogen generator cluster control methods struggle to flexibly address fluctuations in wind power supply and changes in hydrogen generator status, lacking flexibility and stability, and lacking a comprehensive system model. Current electric hydrogen production load configurations are not suitable for scenarios involving large-scale intermittent renewable energy sources, nor have they considered research on hydrogen load configuration under electric-hydrogen technology; the load configurations obtained through traditional optimization methods are not optimal solutions. Furthermore, the lack of effective strategies for coordinated control of hydrogen generator clusters and energy storage systems limits the overall system performance and economic benefits. Therefore, a new hydrogen generator cluster load scheduling method is urgently needed, capable of flexibly responding to fluctuations in wind power supply and changes in hydrogen generator status, and modifying the electric-hydrogen electromagnetic power supply load configuration and cluster control strategy. This is of great significance for the optimal low-carbon economic operation of integrated energy systems. Summary of the Invention

[0008] To address the shortcomings of the existing technology, this invention aims to provide a method for load scheduling of hydrogen production unit clusters that takes into account the flexibility and backup of electro-hydrogen production.

[0009] The purpose of this invention is to provide a load scheduling method for hydrogen generator clusters that takes into account the flexibility and reserve of electric hydrogen production, thereby improving the economy and flexibility of wind power hydrogen production systems and effectively coping with fluctuations in wind power supply; to design and modify the load configuration and cluster control strategy of electric hydrogen production electromagnetic power supply, effectively managing and scheduling the start-up and shutdown status of hydrogen generators, and promoting the low-carbon and economically optimized operation of the integrated energy system; to design an optimized scheduling model that can formulate real-time scheduling strategies based on the uncertainty of wind power, thereby improving the overall efficiency of the hydrogen generator cluster; and to propose an effective coordinated control strategy that achieves optimized system scheduling by comprehensively considering the flexibility constraints and economic objectives of the hydrogen generator cluster and the energy storage system.

[0010] To achieve the above objectives, the present invention provides a method for load scheduling of hydrogen production unit clusters that takes into account the flexibility and backup of electro-hydrogen production, characterized by comprising the following steps:

[0011] S100: Construct a state switching logic model for a single hydrogen generator. The state switching logic model includes the shutdown state, standby state, production state, start-up action, and shutdown action of a single hydrogen generator. The state switching logic model includes switching logic, which includes the single hydrogen generator switching from any one of the shutdown state, standby state, and production state to any other state.

[0012] S200: Based on the state switching logic model, a comprehensive hydrogen production unit cluster load model is constructed according to the wind power forecast, the power load of a single hydrogen production unit, and the hydrogen production loss; according to the comprehensive hydrogen production unit cluster load model, the optimal state of each hydrogen production unit is scheduled so that the wind power hydrogen production system can dynamically respond to fluctuations in wind power supply.

[0013] S300: By relaxing the load model of the integrated hydrogen production unit cluster, a hydrogen production unit cluster load model that takes into account the flexibility of the electro-hydrogen production process is constructed based on the state switching logic model.

[0014] S400: Based on the hydrogen generator cluster load model that takes into account the flexibility of hydrogen production in electro-hydrogen production, under the condition of wind power uncertainty, a two-layer hydrogen generator cluster optimization scheduling model including an upper-layer scheduling model and a lower-layer scheduling model is established for hydrogen generators and energy storage systems.

[0015] The upper-level scheduling model generates start-stop commands and load allocation schemes for the hydrogen generator cluster based on wind power output. The lower-level scheduling model, based on the state switching logic model, adjusts the regulation commands in real time according to the wind power prediction deviation to coordinate and control the hydrogen generator cluster and energy storage system.

[0016] To achieve the above objectives, the present invention also provides a grid dispatching device that considers the electromagnetic power supply load of electric hydrogen and wind power consumption, comprising a memory, a processor, and a computer program, wherein the memory is connected to the processor:

[0017] A memory configured to store the computer program;

[0018] The processor is configured to run the computer program;

[0019] When the computer program is run by the processor, it executes the hydrogen production unit cluster load scheduling method that takes into account the flexibility of the electro-hydrogen production process.

[0020] To achieve the above objectives, the present invention also provides a non-transitory computer-readable storage medium configured to store computer-readable instructions, wherein, when the computer-readable instructions are executed by a processor, the aforementioned hydrogen production unit cluster load scheduling method considering the flexibility of electro-hydrogen production is executed.

[0021] Compared with the prior art, the present invention has the following beneficial technical effects:

[0022] This invention proposes a load scheduling method for hydrogen generator clusters that considers the flexibility and reserve requirements of electro-hydrogen production. The method includes constructing a state switching logic model for a single hydrogen generator, a comprehensive hydrogen generator cluster load model, and a hydrogen generator cluster load model that considers the flexibility and reserve requirements of electro-hydrogen production. By constructing a comprehensive hydrogen generator cluster load scheduling model, this invention enables the system to dynamically respond to power supply fluctuations and flexibly manage the status of hydrogen production equipment. Through the construction of a two-layer scheduling model, it can dynamically respond to fluctuations in wind power supply, improving the system's flexibility and stability and reducing the impact of wind power fluctuations. Furthermore, it improves the accuracy of lower-level regulation demand assessment by introducing a scenario-based approach to model the uncertainty of wind power and considering flexibility reserves to accurately assess the regulation power demand of the lower-level scheduling model. This allows the system to more effectively cope with real-time fluctuations in wind power, reduce wind curtailment, and optimize energy storage and release. This invention effectively solves the problems of insufficient real-time performance and flexibility in traditional hydrogen generator cluster control methods by sending real-time scheduling strategies and regulation commands, improving the overall efficiency and stability of the hydrogen generator cluster. This invention achieves optimized scheduling of the hydrogen generator cluster and energy storage system through a coordinated control strategy. At the same time, it reduced wind curtailment and optimized energy storage and release. Attached Figure Description

[0023] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0024] Figure 1A A flowchart of a hydrogen production unit cluster load scheduling method considering the flexibility of electric hydrogen production as a specific embodiment of the present invention is provided.

[0025] Figure 1B This is a schematic diagram of a wind power hydrogen production system provided in a specific embodiment of the present invention;

[0026] Figure 2 This is a schematic diagram of cluster load stratification optimization control provided in a specific embodiment of the present invention;

[0027] Figure 3 This is a schematic diagram of the flexible adjustment space of cluster load under uncertain wind power conditions provided by a specific embodiment of the present invention;

[0028] Figure 4 This is a performance comparison chart of a specific embodiment of the present invention, showing the operating conditions that take into account hydrogen production flexibility and reserve versus those that do not.

[0029] Figure 5A This is a specific embodiment of the present invention, providing a hydrogen production unit assembly diagram under operating condition I, taking into account the flexibility of hydrogen production.

[0030] Figure 5B This is a specific embodiment of the present invention, showing a hydrogen production unit assembly diagram under operating condition II without taking into account hydrogen production flexibility and backup.

[0031] Figure 6 This is a specific embodiment of the present invention providing an output curve of a hydrogen generator and energy storage system synergistically absorbing wind power fluctuations; and,

[0032] Figure 7 A schematic diagram of a load cluster scheduling device that takes into account the flexibility of electric hydrogen production in a specific embodiment of the present invention. Detailed Implementation

[0033] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0034] It should be noted that the following detailed description is illustrative and intended to provide further explanation of the invention. Unless otherwise specified, all technical and scientific terms used in these embodiments have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0035] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms include and / or encompass are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0036] Figure 1A A flowchart illustrating a method for load scheduling of a hydrogen production unit cluster, taking into account the flexibility of electric hydrogen production, is provided as a specific embodiment of the present invention. Figure 1A As shown, in a specific embodiment of the present invention, the present invention provides a method for load scheduling of hydrogen production unit clusters that takes into account the flexibility of electric hydrogen production, including the following steps:

[0037] S100: Construct a state switching logic model for a single hydrogen generator. The state switching logic model includes the shutdown state, standby state, production state, start-up action, and shutdown action of a single hydrogen generator. The state switching logic model includes switching logic, which includes the single hydrogen generator switching from any one of the shutdown state, standby state, and production state to any other state.

[0038] S200: Based on the state switching logic model, a comprehensive hydrogen production unit cluster load model is constructed according to the wind power forecast, the power load of a single hydrogen production unit, and the hydrogen production loss; according to the comprehensive hydrogen production unit cluster load model, the optimal state of each hydrogen production unit is scheduled so that the wind power hydrogen production system can dynamically respond to fluctuations in wind power supply.

[0039] S300: By relaxing the load model of the integrated hydrogen production unit cluster, a hydrogen production unit cluster load model that takes into account the flexibility of the electro-hydrogen production process is constructed based on the state switching logic model.

[0040] S400: Based on the hydrogen generator cluster load model that takes into account the flexibility of hydrogen production in electro-hydrogen production, under the condition of wind power uncertainty, a two-layer hydrogen generator cluster optimization scheduling model including an upper-layer scheduling model and a lower-layer scheduling model is established for hydrogen generators and energy storage systems.

[0041] The upper-level scheduling model generates start-stop commands and load allocation schemes for the hydrogen generator cluster based on wind power output. The lower-level scheduling model, based on the state switching logic model, adjusts the regulation commands in real time according to the wind power prediction deviation to coordinate and control the hydrogen generator cluster and energy storage system.

[0042] Figure 1B This is a schematic diagram of a wind power-to-hydrogen system provided in a specific embodiment of the present invention. A typical structure of a wind power-storage-hydrogen system is shown below. Figure 1B As shown, the wind-powered hydrogen production system includes components such as solar panels, inverters, a combined heat and power (CHP) system, an electrolyzer, a hydrogen storage tank, and a fuel cell. The solar panels convert sunlight into electricity, which is then converted to alternating current by the inverter and fed into the CHP system. The CHP system uses a portion of the electricity to drive a generator and fuel cell, with excess electricity and heat used for power supply and heating / cooling, respectively. Simultaneously, a portion of the electricity is fed into the electrolyzer to produce hydrogen, which is stored in the hydrogen storage tank for use by the fuel cell. All components are tightly connected via electrical and hydrogen pipelines, forming a complete wind-powered hydrogen production system.

[0043] Hydrogen production operates in three states: shutdown, standby, and production. State adjustments are made to adapt to power fluctuations.

[0044] The hydrogen production unit cluster system is modeled as follows:

[0045]

[0046] In the formula: These are 0-1 variables, representing the production, standby, and shutdown status of the nth hydrogen generator at time t, respectively. The hydrogen generator is represented by 0-1 variables for start-up and shutdown actions. The transition from standby to production status does not require a start-up action, while the transition from production to standby requires a shutdown action; hence the above constraints.

[0047] In a specific embodiment of the present invention, in the scheduling method, in step S100, the shutdown state, standby state, production state, start-up action, and shutdown action of a single hydrogen generator are treated as variables of 0 or 1.

[0048] In a specific embodiment of the present invention, in the scheduling method, step S100, the switching logic further includes:

[0049] In step S100, the switching logic includes: when a single hydrogen generator switches from standby to production, the start action is 0; when a single hydrogen generator switches from production to standby, the shutdown action is 1.

[0050] In a specific embodiment of the present invention, in the scheduling method, step S100, the switching logic further includes:

[0051] When a single hydrogen generator switches from standby to shutdown, the shutdown mechanism is set to 1;

[0052] When a single hydrogen generator switches from shutdown to standby mode, the startup action is 1;

[0053] When a single hydrogen generator switches from production to shutdown, the shutdown mechanism is set to 1;

[0054] When a single hydrogen generator switches from a shutdown state to a production state, the start-up action is 1.

[0055] In a specific embodiment of the present invention, the scheduling method, wherein the integrated hydrogen production unit cluster load model includes load range constraints, yield constraints, and ramp-up constraints of the hydrogen production unit cluster.

[0056] The load range constraint of the hydrogen production unit cluster is

[0057]

[0058] In the formula: P n,t P is the power of the nth hydrogen generator at time t; t W Forecast wind power output; P SB For hydrogen production losses; P max and P min These are the upper and lower limits of single-machine load, respectively.

[0059] The hydrogen production capacity of a single unit is expressed as follows:

[0060]

[0061] η cell =(I n / A) 2 / [f1+(I n / A) 2 ]×f2 (5)

[0062] In the formula: Hydrogen flow rate; N cell η is the number of cells in the electrolytic cell; F is the Faraday constant; η is the number of cells in the electrolytic cell. cell For Faraday efficiency; I n Indicates the electrolysis current; Electrolysis power; This refers to the cell voltage; The power consumed by the hydrogen generator consists of electrolysis power and auxiliary equipment power consumption. Where: U rev The voltage is reversible; T is the tank temperature; A is the electrode area; r1, r2, s t1, t2, and t3 are constant coefficients; f1 and f2 are temperature-dependent coefficients.

[0063] The above model is severely non-convex, so a relaxation process is performed:

[0064]

[0065] In the formula, A, B, and C are coefficient matrices. By linearizing the coefficient matrices A, B, and C, the severely non-convex hydrogen production model is relaxed, transforming it into a solvable load scheduling model.

[0066] In a specific embodiment of the present invention, the scheduling method, step S300 further includes linearizing the severely non-convex integrated hydrogen production unit cluster load model to construct a hydrogen production unit cluster load model that takes into account the flexibility of electric hydrogen production.

[0067] Hydrogen production typically requires compression and buffering to meet user pressure and stable production requirements. The hydrogen compression and buffer tank model is as follows:

[0068]

[0069] In the formula: S t Indicates hydrogen storage capacity; and S For upper and lower limits of storage; F t out The hydrogen flow rate at the back end; Δt is the scheduling step size; P t buffer The compressor power is represented by p1 and p2, respectively, which are the pressures of hydrogen before and after compression; T is the pressure of the hydrogen gas before and after compression. bufferIndicates compressor temperature; η b For compression efficiency; Let be the gas constant of hydrogen, where R is the ideal gas constant; denoted as , where is the molar mass of hydrogen gas.

[0070] The impact of hydrogen stability constraints on hydrogen production scheduling is considered. The yield and ramp-up constraints of the hydrogen generator cluster load model can be expressed as hydrogen flow rate constraints, specifically...

[0071]

[0072] In the formula: This indicates the ramp-up rate of hydrogen supply. Indicates the maximum hydrogen flow rate; η + and η - These represent the upper and lower limits of the hydrogen load ramp rate.

[0073] To achieve flexible control of hydrogen generator clusters, this invention proposes a two-layer scheduling model method that takes into account the flexibility of hydrogen production in wind power hydrogen production, based on the established hydrogen production model. This method is used for the active power balance of wind power hydrogen production systems to achieve flexible control of hydrogen generator clusters.

[0074] Figure 2 This is a schematic diagram of the cluster load stratification optimization control principle provided in a specific embodiment of the present invention. The structural diagram of this method is shown below. Figure 2 As shown, the upper and lower layers use different optimization control cycles and control step sizes.

[0075] The upper-level scheduling model optimizes the control cycle with a resolution of 15 minutes and is responsible for formulating the daily production plan. To accurately assess the power adjustment requirements of the lower-level scheduling model, a scenario-based approach is introduced to model the uncertainty of wind power. Then, under the constraints of hydrogen production, storage, and consumption, the "flexibility reserve" required for real-time fluctuations in wind power is considered. With the goal of maximizing operational benefits, start-up and shutdown instructions and load allocation schemes for the hydrogen production unit cluster are generated.

[0076] Given the short timescale of hydrogen production, the lower-level scheduling model achieves energy balance on a second-level timescale. Within each control interval, the flexibility constraints of the hydrogen generator cluster and energy storage system are fully considered to formulate an economically optimal control strategy, maximizing the absorption of wind power and eliminating the impact of real-time wind power fluctuations. The lower-level scheduling model maintains the internal power balance of the system by issuing real-time power adjustment commands to the hydrogen generators and energy storage system.

[0077] The lower-level scheduling model executes in a rolling manner. After the current optimization control cycle ends, the power state of the hydrogen generator and energy storage system will be used as initial values ​​for the next round of upper-level scheduling, thereby achieving a closed-loop feedback control system. In the two-level scheduling model method, the lower-level scheduling model maintains the internal power balance of the system by issuing real-time power adjustment commands to the hydrogen generator and energy storage system.

[0078] In the upper-level scheduling model, production plans are formulated based on wind power predictions with the goal of achieving optimal economic efficiency.

[0079] For a single hydrogen generator, its flexibility is measured by its current operating status (operating / shutdown / standby), power level, and allowable up / down adjustment range and ramp rate.

[0080] For the entire hydrogen generator cluster, the adjustable power and ramping capability are equal to the sum of the total adjustable power range and ramping rate that all the equipment can provide in non-shutdown conditions.

[0081] Given that the response speed of hydrogen generators differs from that of electrical equipment, the upper-level scheduling model should retain real-time adjustment capabilities as much as possible to fully absorb wind power fluctuations. Therefore, upper and lower limits for "flexibility reserve" were established, namely power constraints and ramp-up constraints.

[0082] The upper-level scheduling model in the two-level scheduling model aims to achieve optimal economic efficiency by considering the flexibility and backup of the hydrogen generator and maximizing the system's operational benefits.

[0083] In one specific embodiment of the present invention, the scheduling method wherein the upper-level scheduling model has an optimized control cycle with a resolution of 15 minutes.

[0084] In a specific embodiment of the present invention, the scheduling method, wherein the upper-level scheduling model generates start-stop instructions and load allocation schemes for the hydrogen production unit cluster based on wind power, includes: the upper-level scheduling model modeling the uncertainty of wind power by introducing a scenario method and taking into account the flexibility of electric hydrogen production; and generating start-stop instructions and load allocation schemes for the hydrogen production unit cluster based on the upper-level objective function of the upper-level scheduling model according to wind power.

[0085] Figure 3 This is a schematic diagram illustrating the flexible adjustment space of cluster load under uncertain wind power conditions, provided by a specific embodiment of the present invention. Figure 3 For example, this is a schematic diagram of the adjustable power range of a hydrogen generator cluster within a time window. This range is determined by the single-unit capacity, ramp rate, and current operating status of each hydrogen generator in the cluster. Figure 3The study demonstrates the power adjustment potential of hydrogen production clusters at different points in time, particularly the flexibility and reserve constraints of hydrogen production ramp-up, and the limitations of hydrogen production ramp-up capabilities. This is of great significance to power system operators and hydrogen production cluster managers, as it helps to formulate more reasonable energy management strategies, optimize resource allocation, and thereby improve the flexibility and reliability of the entire power system.

[0086] like Figure 3 As shown, in a specific embodiment of the present invention, the scheduling method establishes the upper-level scheduling model based on the hydrogen production up-adjustment flexibility reserve constraint, the hydrogen production up-adjustment flexibility reserve constraint, and the hydrogen production ramp-up capability limitation of the hydrogen generator.

[0087] In one specific embodiment of the present invention, the scheduling method wherein the lower-level scheduling model has an optimized control cycle with a resolution of seconds.

[0088] In a specific embodiment of the present invention, the scheduling method, wherein the lower-level scheduling model, based on the state switching logic model, adjusts the regulation command in real time according to the wind power prediction deviation to coordinate and control the hydrogen production cluster and the energy storage system, includes: considering the state switching logic model and taking into account the flexibility of electric hydrogen production for reserve, and adjusting the power regulation command in real time based on the lower-level objective function of the lower-level scheduling model according to the wind power prediction deviation to coordinate and control the hydrogen production cluster and the energy storage system.

[0089] When formulating a production plan for a higher-level scheduling model, two aspects need to be considered simultaneously:

[0090] First, the adjustable range provided by the hydrogen production cluster should adjust for the fluctuations of wind power as much as possible to ensure that it can effectively cope with the uncertainty of wind energy.

[0091] Secondly, the ramp rate of the hydrogen generator cluster should be able to meet the ramp requirements of the maximum wind power within the corresponding time period, thereby reducing the requirements on the power response speed of the hydrogen generator and energy storage system.

[0092] When the "flexibility reserve" of the hydrogen production cluster in the lower-level scheduling model is insufficient, the wind power fluctuations will be borne by the energy storage system.

[0093] If the energy storage system's regulation capacity is also insufficient, it will lead to power curtailment.

[0094] Therefore, in order to assess the regulation power demand in the lower-level scheduling model, the flexibility reserve constraint of the electro-hydrogen production process needs to be considered in the upper-level scheduling model. In the upper-level scheduling model, the uncertainty of wind power is modeled by the scenario method, and "flexibility reserve" is considered to accurately assess the regulation power demand of the lower-level scheduling model.

[0095] The expression for the flexibility and reserve constraint of electro-olefin hydrogen production is as follows:

[0096]

[0097] In the formula: P t enve These represent the upper and lower limits of wind power on a short timescale, respectively, r AEL The rated ramp rate of the hydrogen generator; r t w+ r t W- They are respectively t The upper and lower limits of power ramp-up within a given time period. The objective of the upper-level scheduling model is to maximize the system's operational benefits, considering the start-up and shutdown of hydrogen generators, energy costs, and hydrogen production revenue, while taking into account the flexibility and reserve of hydrogen generators. The upper-level objective function of the upper-level scheduling model is:

[0098]

[0099] In the formula: C WT For wind power prices; C su C sd The cost of starting and stopping the hydrogen generator; denoted as the price of hydrogen; β is the non-negative penalty coefficient.

[0100] In a specific embodiment of the present invention, the scheduling method wherein the upper-level objective function of the upper-level scheduling model includes a function of wind power price, hydrogen generator start-up and shutdown cost, hydrogen price, and non-negative penalty coefficient.

[0101] The upper-level scheduling model is summarized as follows:

[0102]

[0103] The lower-level scheduling model maintains internal power balance by issuing real-time power regulation commands to the hydrogen generators and energy storage systems, taking into account the regulation capacity constraints of the hydrogen generator cluster and energy storage system. The lower-level scheduling model aims for optimal economic efficiency, fully considering the flexibility constraints of the hydrogen generator cluster and energy storage system to formulate control strategies. The lower-level objective function of the lower-level scheduling model is:

[0104]

[0105] Where: ΔP t W This refers to the deviation in wind power prediction. The change in hydrogen production; β b (s T -s0) 2 This is a penalty for the energy storage system deviating from its initial state.

[0106] In one specific embodiment of the present invention, the scheduling method wherein the lower-level objective function of the lower-level scheduling model includes functions for wind power prediction deviation, hydrogen production variation, and penalties for deviation of the energy storage system from its initial state.

[0107] The active power balance constraint of the lower-level scheduling model is:

[0108]

[0109] Where: ΔP n,t This represents the regulated power allocated to each hydrogen generator; ΔP t b The regulation power allocated to the energy storage system is determined based on wind power forecast deviations, establishing the regulation ranges for both the energy storage system and the hydrogen generator to ensure system power balance.

[0110] In a specific embodiment of the present invention, the active power balance constraint of the lower-level scheduling model in the scheduling method is related to the adjustment power allocated to each hydrogen generator.

[0111] In one specific embodiment of the present invention, the scheduling method wherein the active power balance constraint of the lower-level scheduling model includes a function of the regulating power allocated to each hydrogen generator and the regulating power allocated to the energy storage system.

[0112] The power regulation constraint of the hydrogen generator is determined based on the upper-level scheduling results to fully utilize its flexibility for backup.

[0113]

[0114] -η AEL P max ≤(ΔP n,t -ΔP n,t-1 ) / Δt≤η AEL P max (twenty two)

[0115] Where: ΔP n,t This indicates the regulated power allocated to each hydrogen generator; the status of the hydrogen generator unit. and reference load All of these have been obtained through the upper-level scheduling model.

[0116] In one specific embodiment of the present invention, the scheduling method determines the adjustment power allocated to each hydrogen generator in the lower-level scheduling model based on the optimized state of the hydrogen generator units and the baseline load of the upper-level scheduling model.

[0117] In addition, it is necessary to consider the situation where insufficient wind power leads to the energy storage system supplying electricity for hydrogen production. The specific modeling method is shown in the following formula:

[0118]

[0119] After summarizing, the lower-level real-time control model can be represented as:

[0120]

[0121] This embodiment is based on the previous 24-hour period and considers whether hydrogen production provides "flexibility backup," and is divided into two operating conditions. Operating condition I takes into account hydrogen production flexibility backup; operating condition II does not take hydrogen production flexibility backup into account.

[0122] The flexibility of a hydrogen generator is measured by its current operating status, power level, and permissible up / down adjustment range and ramp rate.

[0123] Figure 4 This is a performance comparison chart of a specific embodiment of the present invention, showing the operation condition that takes into account the flexibility of hydrogen production and the operation condition that does not take into account the flexibility of hydrogen production and the backup. Figure 4 Planned power output of the hydrogen production cluster. To maximize the utilization of new energy sources for hydrogen production,

[0124] right Figure 4 The interpretation is that, on the one hand, the present invention requires that the hydrogen production cluster, while providing basic load, also has backup capacity and ramp-up capability to cope with real-time fluctuations in wind power; on the other hand, the state switching logic model established by the present invention can flexibly switch to production state or standby state according to the amount of new energy generated, so that the lower-level scheduling model has greater adjustment space.

[0125] Figure 5A This is a specific embodiment of the present invention, showing a hydrogen production unit assembly diagram under operating condition I, which takes into account the flexibility of hydrogen production. Figure 5B This is a specific embodiment of the present invention, showing a hydrogen production unit assembly diagram under operating condition II without considering hydrogen production flexibility.

[0126] right Figures 5A-5B The interpretation is that, Figures 5A-5B The demonstration showcased the unit combination of the hydrogen production cluster, and the control strategy that takes into account the flexibility and backup of the electro-hydrogen production process. This strategy can better adapt to the fluctuations in new energy sources to adjust its own state and maximize benefits.

[0127] From an economic perspective, if the flexibility of the electric hydrogen production process (condition II) is not taken into account, the profit from hydrogen production is 23,704 yuan. The profit from hydrogen production is relatively high, but the amount of wind power not absorbed is relatively large, and the number of start-ups and shutdowns is also relatively high, which exacerbates the operating costs.

[0128] From an economic perspective, if the flexibility of the electrolytic hydrogen production (condition I) is taken into account, the profit of hydrogen production is 22,185 yuan. Although the profit of hydrogen production is relatively low, the electrolyzer combination has the least amount of unused wind power and relatively controls the start-up and shutdown of the unit, which effectively improves the total operating income.

[0129] The reduced revenue from hydrogen production under Condition I is mainly due to the allocation of some wind power to maintain the operation of more hydrogen production units in order to increase "flexibility reserves".

[0130] The increase in operating costs is due to the fact that, without taking into account the flexibility of the electric hydrogen production system, it is only necessary to ensure that the total power of the hydrogen production units that are already in operation can absorb the wind power; while when taking into account the flexibility of the electric hydrogen production system, it is also necessary to ensure that the adjustable power range of the hydrogen production units can cover the fluctuations of wind power, which leads to an increase in the number of hydrogen production units that need to be in operation.

[0131] like Figures 5A-5B As shown, during the scheduling time t from 20:00 to 24:00, compared with the operating condition II which does not take into account the flexibility of the electric olefin hydrogen production, operating condition I, which takes into account the flexibility of the electric olefin hydrogen production, requires the startup of 1 to 2 additional hydrogen generators. The cost of each startup leads to an increase in the operating cost of the upper-level scheduling.

[0132] From a flexibility perspective, both operating conditions can fully cover the range of wind power variation in terms of the ability to reduce hydrogen production load.

[0133] However, in terms of upscaling capacity, the hydrogen generator cluster in Operating Condition I has sufficient load response capability to cope with the upscaling demand of wind power. This is because the lower-level scheduling model of the two-layer scheduling model adjusts commands in real time (on the order of seconds), ensuring that the power response of the hydrogen generator cluster can match the fluctuations in wind power.

[0134] In Operating Condition II, due to the limited number of hydrogen generators operating during certain periods, the single-unit load is large, and the adjustable backup is insufficient, making it impossible to fully cope with the real-time fluctuations in wind power.

[0135] This situation will lead to a decrease in the regulation capability of hydrogen production in the lower-level scheduling model, requiring the energy storage system to bear a greater regulation load, which will in turn have an adverse impact on the overall economic efficiency of operation.

[0136] Table 1 Results of Optimized Operation of Hydrogen Generator Cluster

[0137] Operating conditions Hydrogen production profit / yuan Unabsorbed wind power / kW Start-stop count Operating Condition I 22185 213 10 Operating Condition II 23704 1443 7

[0138] Operating Condition II offers higher hydrogen production profits compared to Operating Condition I, but with increased unused wind power and slightly lower start-up and shutdown costs; however, the regulation load on the energy storage system decreases, ultimately increasing total revenue. Therefore, Operating Condition I demonstrates its superiority in considering the flexibility of hydrogen production reserves.

[0139] Figure 6 This is a specific embodiment of the present invention, showing the output curve of a hydrogen generator and an energy storage system working together to absorb wind power fluctuations. Figure 6 The results of wind power consumption in a two-level dispatch model for a Park Integrated Energy System (PIES) obtained through computer simulation are presented.

[0140] from Figure 6 The simulation results show that the proposed two-layer scheduling model has the advantage of fully absorbing wind power. Specifically, the designed lower-layer scheduling model can dynamically allocate electrical energy and hydrogen energy according to the wind power output deviation, thereby more effectively tracking and absorbing fluctuating wind power output.

[0141] In one specific embodiment of the present invention, the present invention also provides a grid dispatching device that considers the electromagnetic power supply load of electric hydrogen and wind power consumption, including a memory, a processor and a computer program, wherein the memory is connected to the processor:

[0142] A memory configured to store the computer program;

[0143] The processor is configured to run the computer program;

[0144] When the computer program is run by the processor, it executes the hydrogen production unit cluster load scheduling method that takes into account the flexibility of the electro-hydrogen production process.

[0145] Please refer to Figure 7 The diagram below illustrates a load cluster scheduling device for flexible backup in electro-hydrogen production, as provided in a specific embodiment of the present invention. This load cluster scheduling device for flexible backup in electro-hydrogen production is preferably a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable by the processor. When the processor executes the computer program, it implements any of the methods described above.

[0146] In one specific embodiment of the present invention, the present invention also provides a non-transitory computer-readable storage medium configured to store computer-readable instructions, wherein, when the computer-readable instructions are executed by a processor, the hydrogen production unit cluster load scheduling method considering the flexibility of electro-hydrogen production is executed.

[0147] Compared with the prior art, the present invention has the following beneficial technical effects:

[0148] This invention proposes a load scheduling method for hydrogen generator clusters that considers the flexibility and reserve requirements of electro-hydrogen production. The method includes constructing a state switching logic model for a single hydrogen generator, a comprehensive hydrogen generator cluster load model, and a hydrogen generator cluster load model that considers the flexibility and reserve requirements of electro-hydrogen production. By constructing a comprehensive hydrogen generator cluster load scheduling model, this invention enables the system to dynamically respond to power supply fluctuations and flexibly manage the status of hydrogen production equipment. Through the construction of a two-layer scheduling model, it can dynamically respond to fluctuations in wind power supply, improving the system's flexibility and stability and reducing the impact of wind power fluctuations. Furthermore, it improves the accuracy of assessing the adjustment demand of the lower-level scheduling model. By introducing a scenario-based approach to model the uncertainty of wind power and considering flexibility reserves, it accurately assesses the adjustment power demand of the lower-level scheduling model, enabling the system to more effectively cope with real-time fluctuations in wind power, reduce wind curtailment, and optimize energy storage and release. This invention effectively solves the problems of insufficient real-time performance and flexibility in traditional hydrogen generator cluster control methods by sending real-time scheduling strategies and adjustment commands, improving the overall efficiency and stability of the hydrogen generator cluster. This invention achieves optimized scheduling of the hydrogen generator cluster and energy storage system through a coordinated control strategy. At the same time, it reduced wind curtailment and optimized energy storage and release.

[0149] The above embodiments are merely illustrative examples and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations. However, obvious variations or modifications derived therefrom are still within the scope of protection of this invention.

Claims

1. A load scheduling method for a hydrogen production machine cluster with flexible reserve of electricity-to-hydrogen production, characterized in that, The method comprises the following steps: S100: constructing a state switching logic model of a single hydrogen generator, the state switching logic model comprising a shutdown state, a standby state, a production state, a start-up action and a shutdown action of the single hydrogen generator, the state switching logic model comprising switching logic, the switching logic comprising switching of the single hydrogen generator from any one of the shutdown state, the standby state and the production state to any other state; S200: based on the state switching logic model, constructing a comprehensive hydrogen generator cluster load model according to wind power prediction, power load of the single hydrogen generator and hydrogen production loss; and scheduling the optimal state of each hydrogen generator according to the comprehensive hydrogen generator cluster load model, so that the wind power hydrogen production system can dynamically respond to fluctuations in wind power supply; S300: based on the state switching logic model, constructing a hydrogen generator cluster load model considering flexible standby of the electrolytic hydrogen production by relaxing the comprehensive hydrogen generator cluster load model; S400: based on the hydrogen generator cluster load model considering flexible standby of the electrolytic hydrogen production, establishing a two-level hydrogen generator cluster optimization scheduling model comprising an upper-level scheduling model and a lower-level scheduling model for the hydrogen generator and the energy storage system under wind power uncertainty; wherein the upper-level scheduling model generates start-stop instructions and load distribution schemes of the hydrogen generator cluster according to wind power; and the lower-level scheduling model adjusts the instructions in real time according to wind power prediction deviation based on the state switching logic model, so as to coordinately control the hydrogen generator cluster and the energy storage system.

2. The scheduling method according to claim 1, wherein: in the step S100, the shutdown state, the standby state, the production state, the start-up action and the shutdown action of the single hydrogen generator are variables of 0 or 1.

3. The scheduling method of claim 1, wherein, in the step S100, the switching logic further comprises: in the step S100, the switching logic comprises: when the single hydrogen generator switches from the standby state to the production state, the start-up action is 0; and when the single hydrogen generator switches from the production state to the standby state, the shutdown action is 1.

4. The scheduling method of claim 3, wherein, in the step S100, the switching logic further comprises: when the single hydrogen generator switches from the standby state to the shutdown state, the shutdown action is 1; when the single hydrogen generator switches from the shutdown state to the standby state, the start-up action is 1; when the single hydrogen generator switches from the production state to the shutdown state, the shutdown action is 1; when the single hydrogen generator switches from the shutdown state to the production state, the start-up action is 1.

5. The scheduling method according to claim 1, wherein: the comprehensive hydrogen generator cluster load model comprises load range constraints, yield constraints and ramping constraints of the hydrogen generator cluster.

6. The scheduling method according to claim 1, wherein: in the step S300, the relaxation processing is performed by linearizing the severely non-convex comprehensive hydrogen generator cluster load model to construct the hydrogen generator cluster load model considering flexible standby of the electrolytic hydrogen production.

7. The scheduling method according to claim 1, wherein: the upper-level scheduling model has an optimization control period with a resolution of 15 minutes.

8. The scheduling method of claim 1, wherein: the upper-layer scheduling model generates the start-stop instruction and the load distribution scheme of the hydrogen production machine cluster according to the wind power, including: the upper-layer scheduling model, by introducing a scenario method to model the uncertainty of wind power, and taking into account the flexible reserve of the electrolytic hydrogen production, generates the start-stop instruction and the load distribution scheme of the hydrogen production machine cluster according to the wind power based on an upper-layer objective function of the upper-layer scheduling model.

9. The scheduling method of claim 1, wherein: the upper-layer scheduling model is established based on the hydrogen production upper regulation flexible reserve constraint of the hydrogen production machine, the hydrogen production upper regulation flexible reserve constraint, and the hydrogen production ramping capability limit.

10. The scheduling method of claim 1, wherein: the upper-layer objective function of the upper-layer scheduling model includes a function of the wind power price, the hydrogen production machine start-stop cost, the hydrogen price, and a non-negative penalty coefficient.

11. The scheduling method of claim 1, wherein: the lower-layer scheduling model has an optimization control period with a resolution of seconds.

12. The scheduling method of claim 1, wherein: the lower-layer scheduling model adjusts the regulation instruction in real time based on the wind power prediction power deviation to coordinate control of the hydrogen production machine cluster and the energy storage system based on the state switching logic model, including: considering the state switching logic model and taking into account the flexible reserve of the electrolytic hydrogen production, the lower-layer scheduling model adjusts the power regulation instruction in real time based on a lower-layer objective function of the lower-layer scheduling model according to the wind power prediction deviation to coordinate control of the hydrogen production machine cluster and the energy storage system.

13. The scheduling method of claim 1, wherein: the lower-layer objective function of the lower-layer scheduling model includes a function of the wind power prediction deviation, the hydrogen production change amount, and the penalty for the energy storage system deviating from the initial state.

14. The scheduling method of claim 1, wherein: the active power balance constraint of the lower-layer scheduling model is related to the regulation power allocated to each hydrogen production machine.

15. The scheduling method of claim 1, wherein: the regulation power allocated to each hydrogen production machine in the lower-layer scheduling model is determined according to the hydrogen production machine group state and the reference load optimized by the upper-layer scheduling model.

16. A load cluster scheduling device considering the flexibility of hydrogen production by electric dehydrogenation, characterized in that, a memory, a processor, and a computer program, the memory being connected to the processor: the memory is configured to store the computer program; the processor is configured to run the computer program; wherein the computer program, when executed by the processor, performs the hydrogen production machine cluster load scheduling method considering the flexible reserve of the electrolytic hydrogen production according to any one of claims 1-15.

17. A non-transitory computer-readable storage medium, comprising: the non-transitory computer readable storage medium is configured to store computer readable instructions, wherein when the computer readable instructions are executed by the processor, the hydrogen production machine cluster load scheduling method considering the flexible reserve of the electrolytic hydrogen production according to any one of claims 1-15 is performed.

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