Hydrogen energy system modeling method, electronic device and storage medium
By linearizing the dynamic modeling of electrolyzers and hydrogen storage tanks under multiple operating conditions, the problem of insufficient modeling accuracy of hydrogen energy systems was solved, enabling efficient and optimized scheduling and diversified utilization of hydrogen energy systems, thereby improving operational efficiency and economy.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- SHANGHAI ELECTRICGROUP CORP
- Filing Date
- 2026-04-23
- Publication Date
- 2026-06-26
AI Technical Summary
In existing technologies, the modeling accuracy of hydrogen-containing integrated energy systems is insufficient, failing to accurately depict the actual relationship between the volume, density, and pressure of hydrogen during storage, leading to optimization and scheduling deviations and affecting system operating efficiency.
A multi-condition linearization method is adopted to handle the nonlinear operating efficiency of the electrolyzer. A dynamic storage material flow model is established by combining the physical volume, working pressure and ambient temperature parameters of the hydrogen storage tank. The balance constraint between the models is realized through the hydrogen material flow bus, and an overall optimization model of the hydrogen energy system is constructed.
It improves the physical accuracy of hydrogen energy system modeling, generates low-cost, long-life operation strategies, realizes the coupling of multi-utilization models of hydrogen energy systems, and provides a more accurate basis for optimization and scheduling.
Smart Images
Figure CN122287134A_ABST
Abstract
Description
Technical Field
[0001] This application mainly relates to the field of integrated energy system planning technology, specifically to a hydrogen energy system modeling method, electronic equipment, and storage medium. Background Technology
[0002] With the large-scale deployment of renewable energy and the advancement of the low-carbon energy transition, hydrogen energy, as a clean secondary energy source and a highly efficient energy storage medium, is playing an increasingly important role in integrated energy systems. Accurate modeling and optimization of hydrogen-containing systems are key to improving their operational efficiency and economic viability.
[0003] In existing technologies, the optimal scheduling of integrated hydrogen energy systems faces the challenge of insufficient modeling accuracy. Current methods typically simplify the descriptions of hydrogen energy devices, especially hydrogen storage devices, often using fixed energy units to characterize the hydrogen storage state, failing to fully reflect the dynamic impact of actual operating parameters such as temperature and pressure on the physical properties of hydrogen. This simplification results in models that cannot accurately depict the actual relationship between hydrogen volume, density, and pressure during storage, leading to deviations in the physical basis upon which optimal scheduling relies and hindering the improvement of overall system operating efficiency.
[0004] Therefore, there is an urgent need in this field for a modeling method that can more accurately characterize the physical properties of hydrogen, especially the actual working state of hydrogen storage devices, so as to provide a reliable foundation for the efficient and optimized scheduling of hydrogen-containing integrated energy systems. Summary of the Invention
[0005] This application proposes a hydrogen energy system modeling method to solve the above-mentioned technical problems, including: A hydrogen production material flow model for an electrolyzer is established, and the nonlinear operating efficiency of the electrolyzer is handled by a multi-condition linearization method. A material flow model for hydrogen storage tanks is established, which dynamically characterizes the effective capacity of the hydrogen storage tanks based on the physical volume, working pressure and ambient temperature parameters of the hydrogen storage tanks. A hydrogen mass flow bus is constructed. The hydrogen production variable output by the hydrogen production mass flow model of the electrolyzer and the hydrogen charging variable input by the hydrogen storage mass flow model of the hydrogen storage tank are associated with the hydrogen mass flow bus. A hydrogen mass flow balance constraint is established between the models. The balance constraint is used to characterize that at any time, the total amount of hydrogen flowing into the hydrogen mass flow bus is equal to the total amount of hydrogen flowing out of the hydrogen mass flow bus.
[0006] Furthermore, establishing the mass flow model for the hydrogen storage tank includes: Obtain the physical volume parameters, maximum storage pressure parameters, and minimum release pressure parameters of the hydrogen storage tank; Obtain the ambient temperature parameters of the environment in which the hydrogen storage tank is located; Based on the physical volume parameters, the maximum storage pressure parameters, the minimum release pressure parameters, and the ambient temperature parameters, a storage constraint model for the hydrogen storage tank is established based on the physical properties of hydrogen.
[0007] Furthermore, the method for establishing the storage constraint model includes: The first hydrogen density is determined based on the minimum release pressure parameter and the ambient temperature parameter. The second hydrogen density is determined based on the maximum storage pressure parameter and the ambient temperature parameter. Based on the physical volume parameters, the first hydrogen density, and the second hydrogen density, the lower and upper limits of the actual hydrogen storage capacity of the hydrogen storage tank are calculated.
[0008] Furthermore, the storage constraint model is characterized by the following formula:
[0009] in, The physical volume, The first hydrogen density, The second hydrogen density, The conversion factor for converting hydrogen storage capacity from mass units to standard volume units. This represents the actual hydrogen storage capacity, expressed in standard volume units.
[0010] Furthermore, establishing the material flow model for the hydrogen storage tank also includes establishing a dynamic charging and discharging constraint model, which is characterized by the following formula:
[0011] in, and The first Passing the exam Hydrogen storage capacity at any given time and The first The amount of hydrogen added and released at any given time.
[0012] Furthermore, establishing the hydrogen production material flow model of the electrolyzer includes: dividing the operating load rate of the electrolyzer into multiple continuous operating segments, and introducing a discrete variable for each operating segment, transforming the nonlinear hydrogen production power consumption relationship into a piecewise mixed integer linear constraint controlled by the discrete variable.
[0013] Furthermore, establishing the hydrogen production material flow model of the electrolyzer also includes defining start-up and shutdown optimization constraints for the electrolyzer. These start-up and shutdown optimization constraints include: start-up and shutdown frequency constraints and start-up and shutdown penalty cost terms. The start-up and shutdown frequency constraints are used to calculate the number of start-ups and shutdowns based on the change in the number of operating units in adjacent time periods. The start-up and shutdown penalty cost terms are used to associate the number of start-ups and shutdowns with economic costs.
[0014] Furthermore, the start / stop count constraint is characterized by the following inequality:
[0015] in, For the first Time to the The number of electrolytic cells whose state changes constantly. and The first Passing the exam The number of electrolytic cells operating at any given time.
[0016] Furthermore, the start-stop penalty cost is represented by the following formula:
[0017] in, The additional maintenance costs incurred from a single start-up and shutdown of the electrolytic cell. The start-stop penalty cost item represents All additional maintenance costs incurred due to changes in the start-up and shutdown status of the electrolyzer during a given period.
[0018] Furthermore, the hydrogen energy system modeling method also includes: constructing an electric power bus, and associating the power consumption variables in the hydrogen production material flow model of the electrolyzer with the power generation variables or load variables of the power system components through the electric power bus, and establishing power balance constraints between the models; The hydrogen mass flow balance constraints established based on the hydrogen mass flow bus, the power balance constraints established based on the power bus, and the decision variables, constraints, and objective functions defined by each device model in the hydrogen energy system are integrated to form an overall optimization model for the hydrogen energy system.
[0019] This application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method as described in any of the preceding claims.
[0020] This application also provides a computer-readable storage medium storing computer instructions for causing the computer to perform any of the methods described above.
[0021] This application also provides a computer program product comprising computer program instructions that cause the computer to perform any of the methods described above.
[0022] The beneficial effects of this invention are: 1. The technical solution of the present invention, for hydrogen storage equipment, introduces temperature and pressure parameters, and dynamically calculates the actual hydrogen storage capacity through the hydrogen state equation, which can accurately reflect the real impact of temperature and pressure changes on the amount of hydrogen stored, improve the physical accuracy of the model, and make it more in line with engineering practice. 2. The technical solution of the present invention, for electrolytic cells, adopts a multi-condition piecewise linearization model. While ensuring the linearity and efficient solution of the model, it maintains the accuracy of the model. Combined with start-stop optimization constraints, it generates a low-cost operation strategy, achieving an effective balance between the complex characteristics of the electrolytic cell and the optimization solution efficiency. It generates a long-life, low-cost operation strategy, taking into account both the model's realism and engineering solvability.
[0023] 3. The technical solution of this invention significantly improves the modeling accuracy of key equipment in hydrogen energy systems by constructing a material flow model. It couples multiple links such as hydrogen energy production, storage, and diversified utilization through the material flow model, thereby constructing a complete hydrogen energy diversified utilization model, providing a more accurate physical relationship basis and model support for the optimized scheduling of hydrogen-containing integrated energy systems. Attached Figure Description
[0024] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the specific embodiments of this application will be described in detail below with reference to the accompanying drawings, wherein: Figure 1 This is an overall flowchart of a hydrogen energy system modeling method according to an embodiment of this application.
[0025] Figure 2 This is a schematic diagram of the segmented decoupling of the electrolytic cell operation curve according to an embodiment of this application. Detailed Implementation
[0026] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the specific embodiments of this application will be described in detail below with reference to the accompanying drawings.
[0027] Many specific details are set forth in the following description in order to provide a full understanding of this application. However, this application may also be implemented in other ways different from those described herein, and therefore this application is not limited to the specific embodiments disclosed below.
[0028] As indicated in this application and claims, unless the context clearly indicates otherwise, the words "a," "an," "an," and / or "the" plus the plural, not referring to the singular, may also include the plural. Generally speaking, the terms "comprising" and "including" only indicate the inclusion of explicitly identified steps and elements, which do not constitute an exclusive list, and the method or apparatus may also include other steps or elements.
[0029] Flowcharts are used in this application to illustrate the operations performed by the system according to embodiments of this application. It should be understood that the preceding or following operations are not necessarily performed in exact order. Instead, various steps can be processed in reverse order or simultaneously. Furthermore, other operations may be added to these processes, or one or more steps may be removed from these processes.
[0030] Figure 1 This is an overall flowchart of a hydrogen energy system modeling method according to an embodiment of this application. (Reference) Figure 1 As shown, the hydrogen energy system modeling method of this embodiment includes: A hydrogen production material flow model for an electrolyzer is established, and the model uses a multi-condition linearization method to handle the nonlinear operating efficiency of the electrolyzer. A material flow model for hydrogen storage tanks is established, which dynamically characterizes the effective capacity based on the physical volume, working pressure, and ambient temperature parameters of the hydrogen storage tanks. A hydrogen mass flow bus is constructed, linking the hydrogen production variable output from the hydrogen production mass flow model of the electrolyzer and the hydrogen charging variable input from the hydrogen storage mass flow model of the hydrogen storage tank to the hydrogen mass flow bus. This establishes a hydrogen mass flow balance constraint among the models, which characterizes that at any given time, the total amount of hydrogen flowing into the hydrogen mass flow bus equals the total amount of hydrogen flowing out of the hydrogen mass flow bus. In essence, the hydrogen mass flow bus is used to achieve hydrogen mass flow coupling among the models in the system.
[0031] Specifically, a hydrogen mass flow bus is constructed, connecting the hydrogen production outlet of the electrolyzer to the inlet of the hydrogen storage tank. The mass of hydrogen produced on the bus is equal to the mass of hydrogen stored in the storage tank at any given time, as represented by the following formula:
[0032] The hydrogen mass flow bus is used to aggregate all mass flow variables related to the production, storage, and consumption of hydrogen in the system. In one embodiment, the hydrogen production rate of the electrolyzer model is used. Hydrogen filling capacity of the hydrogen storage tank model With hydrogen release and hydrogen load demand variables Associated with the hydrogen mass flow bus.
[0033] When establishing hydrogen mass flow equilibrium constraints, at any given moment The total amount of hydrogen flowing into the hydrogen mass stream is equal to the total amount of hydrogen flowing out of the stream. Its mathematical expression is as follows:
[0034] The above formula indicates that the sum of hydrogen produced by the electrolyzer and hydrogen released from the hydrogen storage tank at any given time in the hydrogen energy system meets the current hydrogen load demand and hydrogen storage tank filling demand, thus achieving real-time material flow balance in the production, storage, and consumption of hydrogen.
[0035] In one embodiment of this application, establishing a mass flow model for a hydrogen storage tank includes: obtaining the physical volume parameters, maximum storage pressure parameters, and minimum release pressure parameters of the hydrogen storage tank; obtaining the ambient temperature parameters of the environment in which the hydrogen storage tank is located; and establishing a storage constraint model for the hydrogen storage tank based on the physical properties of hydrogen, using the physical volume parameters, maximum storage pressure parameters, minimum release pressure parameters, and ambient temperature parameters.
[0036] Understandably, this method aims to establish a physical model that accurately characterizes the impact of temperature and pressure on hydrogen storage capacity. Specifically, it obtains the inherent parameters of the hydrogen storage tank and the parameters of the operating environment, and inputs these parameters into the model. Based on the calculation of hydrogen properties, it determines the upper and lower limits of the actual hydrogen storage capacity of the tank, thus constructing a constraint model for the tank. Modeling based on hydrogen properties means establishing a model based on the physical properties of hydrogen under specific pressure and temperature conditions. The core is to determine the hydrogen density at a given pressure and temperature, thereby converting the physical volume parameters of the hydrogen storage tank into the actual hydrogen storage capacity represented by standard volume units.
[0037] In one embodiment of this application, the method for establishing a storage constraint model includes: calculating a first hydrogen density based on a minimum release pressure parameter and an ambient temperature parameter using the hydrogen equation of state; calculating a second hydrogen density based on a maximum storage pressure parameter and an ambient temperature parameter using the hydrogen equation of state; and calculating the lower and upper limits of the actual hydrogen storage capacity of the hydrogen storage tank based on the physical volume parameter, the first hydrogen density, and the second hydrogen density.
[0038] Specifically, the model parameters input into this method include: the geometric and physical volume of the hydrogen storage tank. The operating pressure range of the hydrogen storage tank, i.e., the maximum storage pressure parameter. and minimum release pressure parameters The ambient temperature of the environment where the hydrogen storage tank is located. This parameter is usually related to the process and design of the hydrogen storage tank and is a property parameter of the hydrogen storage tank equipment.
[0039] Specifically, in practice, the hydrogen density under given conditions is determined by searching a standard hydrogen property library (such as the NIST library) and considering the pressure P and temperature T. The density is then obtained for the minimum release pressure state. The first hydrogen density and maximum storage pressure state The second hydrogen density .
[0040] In one embodiment of this application, the storage constraint model of the hydrogen storage tank model is characterized by the following formula:
[0041] in, For physical volume, The density of hydrogen gas is the first. The second hydrogen density, The conversion factor (approximately 11.2 m³) for converting hydrogen storage capacity from mass units to standard volume units. 3 / kg), To be expressed in standard volume units (e.g., standard cubic meters, m) 3 The actual hydrogen storage capacity is represented by ().
[0042] Understandably, this constraint indicates that, at a specific temperature, the actual effective hydrogen storage capacity of a hydrogen storage tank varies with pressure. arrive It changes with the changes between them.
[0043] In one embodiment of this application, establishing a material flow model for the hydrogen storage tank further includes establishing a dynamic charging and discharging constraint model, which is characterized by the following formula:
[0044] in, and The first Passing the exam Hydrogen storage capacity at any given time and The first The amount of hydrogen added and released at any given time.
[0045] In one embodiment of this application, establishing a hydrogen production material flow model for an electrolyzer includes: dividing the electrolyzer's operating load rate into multiple continuous operating segments, and introducing a discrete variable for each operating segment, thereby transforming the nonlinear hydrogen production power consumption relationship into a piecewise mixed integer linear constraint controlled by the discrete variable. It can be understood that a multi-operating-condition linearization method is used to construct the electrolyzer model to handle the nonlinear relationship between the electrolyzer's operating load rate and the unit hydrogen production power consumption, transforming it into a form suitable for mixed integer programming solutions, and constructing the hydrogen production power consumption constraint.
[0046] Figure 2 This is a schematic diagram of the segmented decoupling of the electrolytic cell operation curve according to an embodiment of this application. (Reference) Figure 2 As shown, the operating load rate of the electrolyzer is divided into multiple continuous operating segments, transforming the nonlinear hydrogen production-power consumption relationship into a piecewise mixed integer linear constraint. When dividing the operating segments and defining variables, the operating load rate range is divided into n continuous operating segments i based on the electrolyzer performance curve. A binary variable is defined for each operating segment i. ,when The time indicates that the electrolytic cell is operating in the i-th operating condition segment at that moment. A continuous time segment i is defined for each operating condition segment. , which represents the amount of hydrogen produced when the electrolyzer is operating in condition i.
[0047] When performing piecewise linearization modeling, within each operating condition segment i, the hydrogen production power consumption is approximately linear, i.e.:
[0048] Among them, the power consumption rate of the electrolytic cell Related to the operating load rate of the electrolytic cell, The hydrogen production power consumption rate of the electrolyzer in operating condition i. This represents the hydrogen production rate of the electrolyzer during operating condition i. This represents the power consumption of the electrolytic cell during operating condition i.
[0049] The following set of constraints is introduced to integrate the piecewise model and ensure physical plausibility: Total hydrogen production related constraints:
[0050] in, This represents the total hydrogen production of the electrolyzer.
[0051] Total power consumption related constraints:
[0052] in, This represents the total power consumption of the electrolytic cell.
[0053] Operating condition mutual exclusion constraints ensure that the electrolytic cell is in at most one operating condition segment at any given time:
[0054] In one embodiment of this application, establishing a hydrogen production material flow model for an electrolyzer further includes defining start-up and shutdown optimization constraints for the electrolyzer. These start-up and shutdown optimization constraints include: a start-up and shutdown frequency constraint for calculating the number of start-ups and shutdowns based on changes in the number of operating units in adjacent time periods, and a start-up and shutdown penalty cost item for associating the number of start-ups and shutdowns with economic costs.
[0055] Specifically, when constructing the start-up, shutdown, and operation constraints for electrolyzers, the start-up and shutdown counts and penalties are characterized. To achieve optimization for different numbers of operating electrolyzers, separate definitions are established. This represents the number of electrolytic cells installed. Representing the number of electrolytic cells operating at time j, it is easy to obtain:
[0056] To incorporate the start-up and shutdown states of the electrolyzer into the conventional optimization, the lifespan loss and maintenance costs resulting from frequent start-ups and shutdowns are first considered. Definition Representative from the first Time to the The number of electrolytic cells whose start-up and shutdown states change at any given time. and The first Passing the exam The number of electrolytic cells operating at any given time. The start-stop frequency constraint is characterized by the following inequality: The additional operation and maintenance costs incurred by a single start-up and shutdown of the electrolytic cell are represented by a start-up and shutdown penalty cost term in the operation and maintenance cost term of the objective function. This penalty cost term is characterized by the following equation:
[0057] in, The start-stop penalty cost item represents all additional maintenance costs incurred due to changes in the start-stop status of the electrolyzer during the 8760 hours of the year.
[0058] For different types of electrolytic cells, a certain period of time needs to be maintained after a start / stop before restarting. Define the start / stop flags for a single electrolytic cell at each moment. For all devices, the following applies:
[0059] Define startup constraint time step Stop time step constraint The following constraints apply:
[0060] The above formula represents the time at startup. The following series Within a certain time period, All values must be 1 to ensure the equipment does not stop immediately.
[0061] The following constraints also exist:
[0062] The above formula represents the time of shutdown. The following series Within a certain time period, All values must be 0 to ensure the device does not restart immediately.
[0063] The goal of system optimization is to minimize the initial investment and operating / maintenance costs of the electrolyzer.
[0064] in, Let be the objective function of the system. For the initial investment in the electrolytic cell, The system's operation and maintenance costs at time j may include the aforementioned start-stop penalty cost item. .
[0065] In one embodiment of this application, the hydrogen energy system modeling method includes: constructing an electrical bus, linking the power consumption variables in the hydrogen production mass flow model of the electrolyzer with the power generation variables or load variables of the power system components through the electrical bus, and establishing power balance constraints among the various models at the system level; it can be understood that the electrical bus is used to realize the coupling of power flow among the various models in the system. The hydrogen mass flow balance constraints established based on the hydrogen mass flow bus, the power balance constraints established based on the electrical bus, and the decision variables, constraints, and objective functions defined by each equipment model in the hydrogen energy system are integrated to form an overall optimization model of the hydrogen energy system; this overall optimization model of the hydrogen energy system is used to optimize and solve the objective function under the condition of satisfying all component internal constraints and system-level balance constraints, and output the optimal values of all decision variables in the system.
[0066] Specifically, an electrical bus is constructed, connecting the output interfaces of associated power generation equipment and the input interfaces of power consumption equipment in the system. The energy flowing into the bus is equal to the energy flowing out at every moment, represented by the following formula:
[0067] The power bus is used to aggregate all energy flow variables related to the supply, conversion, and consumption of electricity in the system. In one embodiment, it aggregates the power consumption of the electrolyzer model. Output variables of photovoltaic power generation model Output variables of wind power generation models Grid interaction variables (electricity purchase) Electricity sold ), and electricity load demand variables It is connected to the power bus.
[0068] When establishing power balance constraints, at any given moment The total generated power flowing into the power bus is equal to the total consumed power flowing out of the bus. Its mathematical expression is as follows:
[0069] The above formula represents the total power provided by all power sources in the hydrogen energy system, including wind power generation and grid power purchase. It is equal in real time to the sum of the total power consumed by all electrical equipment, including electrolyzers and load components, and the power sold by the grid, thus realizing the energy flow coupling between the power subsystem and the hydrogen energy subsystem.
[0070] Based on the defined component models and system balance constraints, this paper integrates all hydrogen mass flow balance constraints, electrical energy balance constraints, and the decision variables, constraints, and objective functions defined for each equipment model to form a holistic optimization model for the hydrogen energy system. This holistic optimization model is a mixed-integer linear programming problem and can be solved using a commercial solver. The solution will output the optimal values of the decision variables in the system, which may include: the optimal configuration capacity and hourly operation strategy of the electrolyzer, the optimal hydrogen charging and discharging strategy of the hydrogen storage tank, the absorption status of wind and solar power generation, and / or the optimal interaction strategy with the power grid, thereby providing a decision-making basis for the planning, design, operation, and scheduling of the hydrogen energy system.
[0071] On the other hand, this application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-described hydrogen energy system modeling method.
[0072] On the other hand, this application provides a computer-readable storage medium that stores computer instructions for causing a computer to execute the above-described hydrogen energy system modeling method.
[0073] On the other hand, this application provides a computer program product including computer program instructions that cause a computer to execute the above-described hydrogen energy system modeling method.
[0074] The basic concepts have been described above. Obviously, for those skilled in the art, the above disclosure is merely illustrative and does not constitute a limitation of this application. Although not explicitly stated herein, those skilled in the art may make various modifications, improvements, and corrections to this application. Such modifications, improvements, and corrections are suggested in this application, and therefore remain within the spirit and scope of the exemplary embodiments of this application.
[0075] Furthermore, this application uses specific terms to describe embodiments of the application. For example, "an embodiment," "one embodiment," and / or "some embodiments" refer to a particular feature, structure, or characteristic related to at least one embodiment of the application. Therefore, it should be emphasized and noted that "an embodiment," "one embodiment," or "an alternative embodiment" mentioned twice or more in different locations in this specification do not necessarily refer to the same embodiment. In addition, certain features, structures, or characteristics in one or more embodiments of the application can be appropriately combined.
[0076] In some embodiments, numbers describing the quantity of components and attributes are used. It should be understood that such numbers used in the description of embodiments are modified in some examples with the terms "approximately," "approximately," or "generally." Unless otherwise stated, "approximately," "approximately," or "generally" indicates that the numbers are allowed to vary by ±20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximate values, which may be changed depending on the characteristics required by individual embodiments. In some embodiments, numerical parameters should take into account specified significant digits and employ a general method of digit reservation. Although the numerical ranges and parameters used to confirm their breadth of scope in some embodiments of this application are approximate values, in specific embodiments, such values are set as precisely as feasible.
Claims
1. A method for modeling a hydrogen energy system, characterized in that, include: A hydrogen production material flow model for an electrolyzer is established, and the nonlinear operating efficiency of the electrolyzer is handled by a multi-condition linearization method. A material flow model for hydrogen storage tanks is established, which dynamically characterizes the effective capacity of the hydrogen storage tanks based on the physical volume, working pressure and ambient temperature parameters of the hydrogen storage tanks. A hydrogen mass flow bus is constructed. The hydrogen production variable output by the hydrogen production mass flow model of the electrolyzer and the hydrogen charging variable input by the hydrogen storage mass flow model of the hydrogen storage tank are associated with the hydrogen mass flow bus. A hydrogen mass flow balance constraint is established between the models. The balance constraint is used to characterize that at any time, the total amount of hydrogen flowing into the hydrogen mass flow bus is equal to the total amount of hydrogen flowing out of the hydrogen mass flow bus.
2. The modeling method as described in claim 1, characterized in that, Establishing the mass flow model for the hydrogen storage tank includes: Obtain the physical volume parameters, maximum storage pressure parameters, and minimum release pressure parameters of the hydrogen storage tank; Obtain the ambient temperature parameters of the environment in which the hydrogen storage tank is located; Based on the physical volume parameters, the maximum storage pressure parameters, the minimum release pressure parameters, and the ambient temperature parameters, a storage constraint model for the hydrogen storage tank is established based on the physical properties of hydrogen.
3. The modeling method as described in claim 2, characterized in that, The method for establishing the storage constraint model includes: The first hydrogen density is determined based on the minimum release pressure parameter and the ambient temperature parameter. The second hydrogen density is determined based on the maximum storage pressure parameter and the ambient temperature parameter. Based on the physical volume parameters, the first hydrogen density, and the second hydrogen density, the lower and upper limits of the actual hydrogen storage capacity of the hydrogen storage tank are calculated.
4. The modeling method as described in claim 3, characterized in that, The storage constraint model is characterized by the following formula: in, The physical volume, The first hydrogen density, The second hydrogen density, The conversion factor for converting hydrogen storage capacity from mass units to standard volume units. This represents the actual hydrogen storage capacity, expressed in standard volume units.
5. The modeling method as described in claim 2, characterized in that, Establishing the material flow model for the hydrogen storage tank also includes establishing a dynamic charge-discharge constraint model, which is characterized by the following formula: in, and The first Passing the exam Hydrogen storage capacity at any given time and The first The amount of hydrogen added and released at any given time.
6. The modeling method as described in claim 1, characterized in that, The hydrogen production material flow model of the electrolyzer includes: dividing the operating load rate of the electrolyzer into multiple continuous operating segments, and introducing a discrete variable for each operating segment, transforming the nonlinear hydrogen production power consumption relationship into a piecewise mixed integer linear constraint controlled by the discrete variable.
7. The modeling method as described in claim 1, characterized in that, Establishing the hydrogen production material flow model of the electrolyzer also includes defining the start-up and shutdown optimization constraints of the electrolyzer. The start-up and shutdown optimization constraints include: start-up and shutdown frequency constraints and start-up and shutdown penalty cost terms. The start-up and shutdown frequency constraints are used to calculate the number of start-ups and shutdowns based on the change in the number of operating units in adjacent time periods. The start-up and shutdown penalty cost terms are used to associate the number of start-ups and shutdowns with economic costs.
8. The modeling method as described in claim 7, characterized in that, The constraint on the number of start / stop cycles is represented by the following inequality: in, For the first Time to the The number of electrolytic cells whose state changes constantly. and The first Passing the exam The number of electrolytic cells operating at any given time.
9. The modeling method as described in claim 8, characterized in that, The start / stop penalty cost is represented by the following formula: in, The additional maintenance costs incurred from a single start-up and shutdown of the electrolytic cell. The start-stop penalty cost item represents All additional maintenance costs incurred due to changes in the start-up and shutdown status of the electrolyzer during a given period.
10. The modeling method as described in claim 1, characterized in that, The method further includes: A power bus is constructed to associate the power consumption variables in the hydrogen production material flow model of the electrolyzer with the power generation variables or load variables of the power system components through the power bus, thereby establishing power balance constraints between the models. Based on the hydrogen mass flow bus established by the hydrogen mass flow balance constraint and the power balance constraint established by the power bus, combined with the decision variables, constraints and objective functions defined by each equipment model in the hydrogen energy system, an overall optimization model of the hydrogen energy system is formed.
11. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method as described in any one of claims 1-10.
12. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to perform the method according to any one of claims 1-10.
13. A computer program product, characterized in that: It includes computer program instructions that cause a computer to perform the method as described in any one of claims 1-10.