Multi-region power optimization method, control device and storage medium in electric hydrogen system

Abstract

The present application relates to a multi-region power optimization method in an electric hydrogen system, a control device and a storage medium. The electric hydrogen system comprises an electric energy system and a hydrogen energy system, wherein the electric hydrogen system is connected with the hydrogen energy system, the electric hydrogen system model comprises a hydrogen energy system model, and the method comprises: obtaining electric hydrogen system data; obtaining a pending hydrogen load based on the hydrogen energy system model, wherein the pending hydrogen load reflects the hydrogen consumption of the hydrogen energy system in a first preset time period; inputting the pending hydrogen load and the electric hydrogen system data into the electric hydrogen system model to optimize the electric hydrogen system, and obtaining the power scheduling result between the electric hydrogen system and the hydrogen energy system. The present application optimizes the utilization of renewable energy, ensures the accurate matching between energy production and demand, and realizes the efficient consumption of the hydrogen energy system through accurate regulation. The overall energy management performance and economy of the system are greatly improved.

Description

Technical Field

[0001] This invention relates to the field of power grid optimization technology, specifically providing a method, control device, and storage medium for multi-region power optimization in an electric hydrogen system. Background Technology

[0002] In traditional energy networks combining electricity and hydrogen (electric-hydrogen systems), a major technical challenge is low energy efficiency. This problem stems from the coordination and optimization difficulties between electricity and hydrogen production, storage, and consumption. The energy conversion, distribution, and storage processes in these systems often fail to precisely match energy supply and demand, leading to losses in renewable energy generation, underutilization of energy storage facilities, and inconsistencies between hydrogen production and demand.

[0003] In existing technologies, energy allocation is usually based on experience, which is not precise enough.

[0004] Accordingly, there is a need in this field for a new power optimization scheme to address the above problems. Summary of the Invention

[0005] In order to overcome the above-mentioned defects, the present invention is proposed to provide a solution or at least a partial solution to the technical problem that the use experience in the prior art is not precise enough in the preparation of the hydrogen-electric system, which easily leads to consumption and waste.

[0006] In a first aspect, the present invention provides a multi-region power optimization method for an electric hydrogen system, the electric hydrogen system comprising: an electric energy system and a hydrogen energy system, wherein the electric hydrogen system and the hydrogen energy system are connected, and the electric hydrogen system model includes a hydrogen energy system model. The method comprises: acquiring electric hydrogen system data; obtaining a pending hydrogen load based on the hydrogen energy system model, wherein the pending hydrogen load reflects the hydrogen consumption of the hydrogen energy system within a first preset time period; inputting the pending hydrogen load and the electric hydrogen system data into the electric hydrogen system model to optimize the electric hydrogen system, thereby obtaining power scheduling results within the electric hydrogen system and between the electric hydrogen system and the hydrogen energy system.

[0007] As an alternative or supplement to the above solutions, in a method according to an embodiment of the present invention, the hydrogen energy system includes a hydrogen production station, and the electric energy system includes at least two regions connected by a power electronic conversion device, wherein at least one region is connected to the hydrogen production station to provide power to the hydrogen production station; "inputting the undetermined hydrogen load and the electric-hydrogen system data into the electric-hydrogen system model to optimize the electric-hydrogen system and obtain power scheduling results within the electric-hydrogen system and between the electric-hydrogen system and the hydrogen energy system" includes: obtaining the objective function, constraints, and energy management strategy; optimizing the electric-hydrogen system based on the undetermined hydrogen load, the electric-hydrogen system data, the energy management strategy, the objective function, and the constraints to obtain power scheduling results within the electric-hydrogen system and between the electric-hydrogen system and the hydrogen energy system.

[0008] As an alternative or supplement to the above solutions, in a method according to an embodiment of the present invention, "optimizing the electric hydrogen system based on the undetermined hydrogen load, the electric hydrogen system data, energy management strategy, objective function, and constraints" includes: wherein the parameters of the region to be optimized include the electric load of the region in each time period, the amount of electrical energy input to the region through the green energy input device, and the state of charge of the energy storage device corresponding to the region; for one time period, different energy dispatch strategies are selectively executed based on the state of charge of the energy storage device, the electric load of the region, and the amount of electrical energy input by the green energy input device.

[0009] As an alternative or supplement to the above solutions, in a method according to an embodiment of the present invention, the power system includes a first region, wherein the first region is connected to a hydrogen production station and a green energy input device, and the parameters for optimizing the first region also include the hydrogen production capacity of the hydrogen production station and the amount of electricity transferred to the first region through a power electronic conversion device. "For one period of time, different energy dispatch strategies are selectively executed based on the state of charge of the energy storage device, the electrical load of the targeted region, and the amount of electrical energy input by the green energy input device," including: for one period of time, different first energy dispatch strategies are selectively executed based on the state of charge of the energy storage device, the electrical load of the first region, the amount of electrical energy input by the green energy input device, the hydrogen production capacity of the hydrogen production station, and the amount of electricity transferred to the first region through a power electronic conversion device.

[0010] As an alternative or supplement to the above solutions, in a method according to an embodiment of the present invention, the power system further includes a second region, wherein the second region is connected to a green energy input device, and the parameters for optimizing the second region further include the amount of electricity transferred to the second region through a power electronic conversion device, wherein the second region is connected to a first region through a power electronic conversion device; "for one time period, selectively executing different energy dispatch strategies based on the state of charge of the energy storage device, the electrical load of the targeted region, and the amount of electrical energy input by the green energy input device" includes: for one time period, selectively executing different energy dispatch strategies based on the state of charge of the energy storage device, the electrical load of the second region, the amount of electricity transferred to the second region through the power electronic conversion device, and the amount of electrical energy input by the green energy input device.

[0011] As an alternative or supplement to the above solutions, in a method according to an embodiment of the present invention, the power system further includes a third region, wherein the third region is connected to a green energy input device, wherein the first region and the third region are both AC regions, and the second region is a DC region, wherein the third region is connected to the second region through a power electronic conversion device; "for one time period, selectively executing different energy dispatch strategies based on the state of charge of the energy storage device, the electrical load of the targeted region, and the amount of electrical energy input by the green energy input device" includes: for one time period, selectively executing different energy dispatch strategies based on the state of charge of the energy storage device, the electrical load of the third region, and the amount of electrical energy input by the green energy input device.

[0012] As an alternative or supplement to the above solutions, in a method according to an embodiment of the present invention, "obtaining the undetermined hydrogen load based on a hydrogen energy system model" includes: the hydrogen energy system model includes a mobile hydrogen power device module and a stationary hydrogen power device module; and the undetermined hydrogen load is obtained based on the mobile hydrogen power device module and the stationary hydrogen power device module.

[0013] As an alternative or supplement to the above solutions, in a method according to an embodiment of the present invention, the hydrogen-powered machinery module includes: a mobile hydrogen-powered crane, a hydrogen-powered forklift, and a hydrogen-powered truck module, wherein the mobile hydrogen-powered crane module is modeled as follows: in m RTG These represent the upper and lower limits of the onboard hydrogen storage capacity for mobile hydrogen-powered cranes, Δm. RTG (t) represents the amount of hydrogen consumed during time period t; For time period t, the i-th mobile hydrogen-powered crane in the hydrogen-electric system can adjust the hydrogen load. The initial hydrogen storage capacity is T; the total system scheduling period is T, and the current time period is t within the total system scheduling period.

[0014] The hydrogen-powered forklift module is modeled as follows:

[0015] in These represent the upper and lower limits of the onboard hydrogen storage capacity of the hydrogen-electric forklift, Δm. forklift (t) represents the amount of hydrogen consumed during time period t. For the time period t, the adjustable hydrogen load of the i-th hydrogen-electric forklift in the hydrogen-electric system is... Its initial hydrogen storage capacity;

[0016] The hydrogen-powered truck module is modeled as follows:

[0017] in These are its unloaded distance and loaded distance, respectively, v unloaded v loaded Let be the no-load speed and the loaded speed of the hydrogen-powered truck, respectively. When the i-th hydrogen-powered truck operates for Ni cycles, the hydrogen consumption of the i-th hydrogen-powered truck is: Where Δm unloaded Δm loaded These figures represent the hydrogen consumption per 100 kilometers for hydrogen-powered trucks under both unloaded and loaded conditions.

[0018] In a second aspect, a control device is provided, comprising a processor and a storage device, the storage device being adapted to store a plurality of computer programs, the computer programs being adapted to be loaded and run by the processor to execute the power optimization method for a multi-regional electric hydrogen system as described in any of the above-described technical solutions.

[0019] In a third aspect, a computer-readable storage medium is provided, wherein a plurality of computer programs are stored therein, the computer programs being adapted to be loaded and run by a processor to perform the power optimization method for a multi-regional electric hydrogen system as described in any of the above-described technical solutions.

[0020] The present invention comprises one or more of the following technical solutions: Beneficial effects:

[0021] In implementing the technical solution of this invention, by integrating data from the electro-hydrogen system and the hydrogen energy system model, efficient energy conversion and precise power scheduling are achieved, effectively improving the synergistic utilization efficiency of electrical and hydrogen energy. Utilizing refined data acquisition and model optimization, this solution optimizes the utilization of renewable energy, ensures precise matching between energy production and demand, and achieves efficient consumption of the hydrogen energy system through precise control. As a result, energy flow within and between the electro-hydrogen system and the hydrogen energy system is optimized, significantly improving the overall energy management performance and economy of the system. Attached Figure Description

[0022] The disclosure of this invention will become more readily understood with reference to the accompanying drawings. It will be readily understood by those skilled in the art that these drawings are for illustrative purposes only and are not intended to limit the scope of protection of this invention. Furthermore, similar numbers in the drawings are used to denote similar components, wherein:

[0023] Figure 1 This is a schematic flowchart of the main steps of a multi-region power optimization method in an electro-hydrogen system according to an embodiment of the present invention;

[0024] Figure 2 This is a flowchart illustrating the minor steps of a multi-region power optimization method in an electro-hydrogen system according to an embodiment of the present invention.

[0025] Figure 3 This is a flowchart illustrating the minor steps of a multi-region power optimization method in an electro-hydrogen system according to an embodiment of the present invention.

[0026] Figure 4 This is a flowchart illustrating the minor steps of a multi-region power optimization method in an electro-hydrogen system according to an embodiment of the present invention.

[0027] Figure 5 This is a schematic diagram of the secondary steps of a power optimization method for a multi-regional system according to an embodiment of the present invention. Detailed Implementation

[0028] Some embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0029] See appendix Figure 1 , Figure 1 This is a schematic flowchart illustrating the main steps of a multi-region power optimization method in an electro-hydrogen system according to an embodiment of the present invention. Figure 1 As shown, the power optimization method for multiple regions in the electro-hydrogen system in this embodiment of the invention mainly includes the following steps S10-S30.

[0030] Step S10: Obtain data from the electro-hydrogen system.

[0031] In this embodiment, the data of the electro-hydrogen system are some known data, parameter data collected for the region where the electro-hydrogen system is located, and the specific values ​​of these electro-hydrogen system data are regional and time-sensitive.

[0032] In one implementation, the data for the hydrogen-electric system includes simulation parameters of the hydrogen-electric system model and a time-of-use electricity price list for the region where the hydrogen-electric system is located.

[0033] In this embodiment, the electro-hydrogen system model is a simulation model. Preferably, in one embodiment, the electro-hydrogen system model includes a hydrogen energy system model. The hydrogen energy system model is a part of the electro-hydrogen system model and is also a simulation model; that is, the hydrogen energy system model is a sub-model within the electro-hydrogen system model.

[0034] In this embodiment, the electro-hydrogen system includes an electrical energy system and a hydrogen energy system. The electrical energy system includes at least two regions connected by a power electronic conversion device. At least one region is connected to a hydrogen production station and is used to provide power to the hydrogen production station.

[0035] In this embodiment, the regions included in the power system are connected by power electronic conversion devices, including direct and indirect connections. For example, in one scenario provided in this embodiment, the power system includes three regions, denoted as region 1, region 2, and region 3. It is assumed that region 1 and region 2 are directly connected by power electronic conversion devices, region 2 and region 3 are directly connected by power electronic conversion devices, and region 1 and region 3 are not directly connected. Therefore, region 1 and region 2, region 2 and region 3 are directly connected, and region 1 and region 3 are indirectly connected. Preferably, in one embodiment, the power electronic conversion device is a flexible multi-state switch.

[0036] In this embodiment, the first area is connected to the hydrogen production station and is used to provide power to the hydrogen production station.

[0037] In this embodiment, specific data for the electro-hydrogen system are provided, as shown in Tables 1 and 2: Table 1. Time-of-use electricity rates for industrial use in the region where the hydrogen-electric system is located. Table 2 shows the simulation parameters of the hydrogen-electric system model.

[0038] The symbols for the simulation parameters of the electro-hydrogen system model in Table 2 will be explained in the following sections.

[0039] Step S20: Obtain the undetermined hydrogen load based on the hydrogen energy system model.

[0040] In this embodiment, the undetermined hydrogen load reflects the hydrogen consumption of the hydrogen energy system during the first preset time period.

[0041] In one implementation, the undetermined hydrogen load is not a fixed value, but rather an expression derived from a hydrogen energy system model, used for subsequent optimization of the electro-hydrogen system. In this implementation, the undetermined hydrogen load is represented by an expression.

[0042] In this embodiment, the hydrogen energy system model includes at least a hydrogen-powered device module, which comprises a stationary hydrogen-powered device module and a mobile hydrogen-powered device module. A hydrogen-powered device is a power device that uses hydrogen power as its energy source at least partially. The hydrogen-powered device module is a simulation model of the hydrogen-powered device. Preferably, in this embodiment, the hydrogen-powered device is a power device that uses hydrogen power as its entire energy source.

[0043] Fixed hydrogen-powered devices refer to those that are permanently installed and typically use hydrogen pipelines to supply hydrogen for operation. Mobile hydrogen-powered devices refer to those that are mobile and typically store hydrogen in internal storage tanks or other hydrogen storage devices, converting hydrogen energy into their own power during use. In this embodiment, the fixed hydrogen-powered device module is a simulation model built based on a fixed hydrogen-powered device, and the mobile hydrogen-powered device module is a simulation model built based on a mobile hydrogen-powered device. In this embodiment, any module or model refers to a simulation model built upon it, and will not be described further hereafter.

[0044] In this embodiment, the stationary hydrogen-powered machinery module includes at least a large hydrogen-powered crane module. The model of the large hydrogen-powered crane module in this embodiment is as follows:

[0045]

[0046] Where m crane (t) represents the adjustable hydrogen load of the large hydrogen-powered crane in the hydrogen-electric system during time period t. The actual hydrogen load of this type of equipment during time period t.

[0047] In this embodiment, the hydrogen supply to the stationary hydrogen-powered device can be interrupted at any time, thereby stopping the hydrogen supply to the stationary hydrogen-powered device. This is achieved by interrupting the hydrogen supply pipeline. It should be noted that the hydrogen pipeline is connected to the city's pipeline network and can use hydrogen produced from renewable energy sources in the electric hydrogen system, or it can use hydrogen from the city's pipeline network where the electric hydrogen system is located. A detailed description will follow.

[0048] In this embodiment, the mobile hydrogen-powered equipment includes: a mobile hydrogen-powered crane, a hydrogen-powered forklift, and a hydrogen-powered truck.

[0049] In this embodiment, the mobile hydrogen-powered crane module is modeled as follows:

[0050]

[0051]

[0052] In the formula m RTG These represent the upper and lower limits of the onboard hydrogen storage capacity for mobile hydrogen-powered cranes, Δm. RTG (t) represents the amount of hydrogen consumed during time period t. For time period t, the i-th mobile hydrogen-powered crane in the hydrogen-electric system can adjust the hydrogen load. This represents its initial hydrogen storage capacity. T is the total system scheduling period.

[0053] In this embodiment, the total system scheduling cycle T and the unit scheduling cycle Δt have the following relationship: T*Δt is the length of the minimum cycle calculated by the electric hydrogen system model in this embodiment. For example, in a scenario provided in this embodiment, the length of the minimum cycle calculated by the electric hydrogen system is one day, then the total duration of one day is T*Δt. In a scenario provided in this embodiment, Δt is defaulted to 1 hour. It should be noted that in this embodiment, mobile hydrogen-powered vehicles are assumed to be in working (endurance) state and refueling state. Since most mobile hydrogen-powered vehicles generally require short refueling times and have long driving ranges and times, for the sake of easier description of this technology, the hydrogen load, except for hydrogen-powered trucks, is assumed to have a scheduling cycle of Δt.

[0054] In this embodiment, the hydrogen-powered forklift module is modeled as follows:

[0055]

[0056]

[0057] In the formula m forklift These represent the upper and lower limits of the onboard hydrogen storage capacity of the hydrogen-electric forklift, Δm. forklift (t) represents the amount of hydrogen consumed during time period t. For the time period t, the adjustable hydrogen load of the i-th hydrogen-electric forklift in the hydrogen-electric system is... Its initial hydrogen storage capacity.

[0058] In this embodiment, the hydrogen-powered truck module is modeled as follows:

[0059]

[0060] in These are its unloaded distance and loaded distance, respectively, v unloaded v loaded These represent the unloaded speed and the loaded speed of the hydrogen-powered truck, respectively. When the i-th hydrogen-powered truck cycles through N... i At this time, the hydrogen consumption of the i-th hydrogen-powered truck is:

[0061]

[0062] In the formula Δm unloaded Δm loaded These represent the hydrogen consumption per 100 kilometers for a hydrogen-powered truck under no-load and loaded conditions, respectively. The flexibility model for the hydrogen-powered truck upon arrival at a hydrogen refueling station is as follows:

[0063]

[0064]

[0065] In the formula N i Δt truck This indicates the time when the hydrogen-powered truck arrives at the hydrogen refueling station. The time constraint implicitly includes the following:

[0066] 0 < N i Δt truck ≤T,

[0067] remember Let be the number of times the i-th hydrogen-powered truck cycles within the system scheduling period t. Then, the load of the hydrogen-powered truck can be rewritten as:

[0068]

[0069] As can be seen from the modeling of the hydrogen-powered truck, the truck in this embodiment has its own unique cycle. This is due to its special transportation patterns. In this embodiment, the hydrogen-powered truck has a relatively fixed transportation route, and one round trip along the transportation route is called a cycle. Only after completing one cycle can it refuel with hydrogen.

[0070] In this embodiment, the hydrogen power device is the physical component that primarily provides the hydrogen load in the hydrogen-generating system. Therefore, the undetermined hydrogen load is obtained through the aforementioned four specific hydrogen power devices. It is expressed as follows:

[0071]

[0072] In this embodiment, the undetermined hydrogen load integrates both the stationary hydrogen power equipment module and the mobile hydrogen power equipment module, which better reflects the hydrogen load situation in the hydrogen energy system and is more conducive to subsequent optimization.

[0073] Step S30: Input the undetermined hydrogen load and the data of the electric hydrogen system into the electric hydrogen system model to optimize the electric hydrogen system and obtain the power scheduling results within the electric hydrogen system and between the electric hydrogen system and the hydrogen energy system.

[0074] In this embodiment, the power scheduling result is the same as the energy scheduling result.

[0075] In one embodiment, within a scenario provided by this embodiment, the first region is an AC region, the second region is a DC region, and the third region is an AC region. The first region and the second region are connected via a flexible multi-state switch, and the second region and the third region are also connected via a flexible multi-state switch. In this embodiment, each of the first, second, and third regions is independently connected to a green energy input device, which supplies power to the corresponding connected region. It should be noted that in this embodiment, AC region and DC region refer to whether the main power grid used for power transmission in the region is AC or DC.

[0076] In this embodiment, although the first, second, and third regions each have independent green energy input devices connected to their respective regions, the composition of the electrical energy input to these devices may differ. In this embodiment, the electrical energy input to the green energy input device refers to the electrical energy input by the green energy input device to the corresponding region.

[0077] In one scenario provided in this embodiment, the green energy input device in the first area inputs electricity converted from solar energy and electricity converted from wind energy; the green energy input device in the second area inputs only electricity converted from solar energy; and the green energy input device in the third area inputs only electricity converted from wind energy. Therefore, the composition of the electricity input to the green energy input devices in the first, second, and third areas may differ. It is easy to imagine that the electricity input to the green energy input device may selectively include one or both of wind and solar energy. For example, when the electricity input to the green energy input device is converted from solar energy, the green energy input device may be a solar panel; when the electricity input to the green energy input device is converted from wind energy, the green energy input device may be a wind power generation device. In this embodiment, the green energy input device converts green energy into electrical energy and inputs it to the corresponding area.

[0078] In this embodiment, each region is connected to a corresponding energy storage device. The first region is connected to a first energy storage device, the second region to a second energy storage device, and the third region to a third energy storage device. The energy storage devices are used to collect and store electrical energy. In this embodiment, the energy storage device can be a battery, a supercapacitor, or other power storage device. In this embodiment, the energy storage device is used to collect energy, especially when there is a large amount of electricity generated within the region, to store excess electrical energy for discharge to power the region when needed.

[0079] In one scenario provided in this embodiment, the first, second, and third regions each have their own corresponding loads. These loads consume electrical energy within their respective regions and are directly or indirectly connected to the external power grid. When the energy supplied by the internal electro-hydrogen system is insufficient to meet the load's needs, the load will utilize power from the external power grid.

[0080] In this embodiment, an energy management strategy for a region is also included, wherein the energy management strategy is applied to at least one region of the electric power system. That is, in a scenario provided in this embodiment, the energy management strategy will be applied to at least one of the first region, the second region, or the third region. Preferably, in this embodiment, the energy management strategy will be applied to the first region, the second region, and the third region. From another perspective, the energy management strategy is a constraint used in the optimization of this application. The operation of the electric hydrogen system follows the framework of the energy management strategy. In this embodiment, preferably, a more detailed energy management strategy can be applied to each region. In summary, step S30 also includes: optimizing the electric hydrogen system based on the undetermined hydrogen load, electric hydrogen system data, energy management strategy, objective function, and constraints to obtain power scheduling results within the electric hydrogen system and between the electric hydrogen system and the hydrogen energy system.

[0081] In this embodiment, the energy management strategy is a management strategy that makes judgments within a unit scheduling cycle. In other words, during the optimization process of the electric hydrogen system, the optimization result will necessarily meet the requirements of the energy management strategy. In this embodiment, the relationship between time period, unit scheduling cycle, and total system scheduling cycle is explained. Within a total system scheduling cycle, the smallest scheduling cycle is a unit scheduling cycle. In this embodiment, the smallest time unit during the optimization of the electric hydrogen system is a time period. Preferably, in one embodiment, the unit of time period and the size of the unit scheduling cycle are consistent, and the duration of one cycle during the optimization of the electric hydrogen system is consistent with the duration of the total system scheduling cycle. In a scenario provided in this embodiment, the unit of time period is 1 hour, and the duration of one cycle during the optimization of the electric hydrogen system is 24 hours.

[0082] In this embodiment, an energy management strategy is used to optimize the target area, including steps S301-S302, such as... Figure 2 As shown, the details are as follows:

[0083] Step S301: Based on the data of the electric hydrogen system and the energy management strategy, optimize the region targeted by the energy management strategy to obtain the power scheduling results within the electric hydrogen system and between the electric hydrogen system and the hydrogen energy system that meet the energy management strategy. The parameters involved in the optimization of the region include the electrical load of the region, the amount of electrical energy input to the region through the green energy input device, and the state of charge of the energy storage device corresponding to the region at each time period.

[0084] Step S302: For one time period, different energy dispatch strategies are selectively executed based on the state of charge of the energy storage device, the electrical load of the targeted area, and the amount of electrical energy input by the green energy input device.

[0085] In this embodiment, the state of charge (SBC) of the energy storage device indicates whether the corresponding energy storage device has sufficient space for energy collection. The SBC of the energy storage device can be represented by a percentage value. When the value is 0%, it means that the energy storage device has not yet stored any electricity and can receive and store electrical energy. When the value is 100%, it means that the energy storage device has reached its maximum capacity and can no longer receive additional electrical energy.

[0086] In this embodiment, different, more detailed energy management strategies are applied to different regions. That is, when step S302 is executed, a more detailed scheduling strategy will be applied based on the characteristics of different regions, as detailed in steps S302-1 to S302-3.

[0087] When the target area is the first area, step S302-1 is used, such as... Figure 3 As shown. When the target region is the first region, the parameters for optimization involving the target region also include the hydrogen production capacity of the hydrogen production station and the electricity transferred through the power electronic conversion device. If the hydrogen production capacity reaches its upper limit, excess electricity cannot be input to the hydrogen production station for hydrogen production. The electricity transferred by the power electronic conversion device is a numerical value. In the scenario provided in this embodiment, a positive value indicates that electricity is being supplied to this region from other regions; a negative value indicates that the first region is supplying electricity to other regions.

[0088] Step S302-1: For one of the time periods, different first energy dispatch strategies are selectively executed based on the state of charge of the first energy storage device, the electrical load of the first region, the amount of electrical energy input by the green energy input device, the amount of hydrogen produced by the hydrogen production station, and the amount of electricity transferred to the first region through the power electronic conversion device.

[0089] In this embodiment, the first energy dispatch strategy prioritizes maximizing the absorption rate (100%). Afterward, internal power is allocated to supply the local electrical load, and any surplus power is supplied according to the priority order of hydrogen production station and energy storage device. If internal power is insufficient to meet the local electrical load, the energy storage device discharges to supply power to the first region. If the first energy storage device's state of charge (SOC1) is low, power is obtained from the external power grid to supply the load of the first region. The internal power consists of the sum of the electrical energy input from the green energy input device and the power transferred through the power electronic conversion device.

[0090] In one implementation, described in detail, the primary principle of power management in the optimization of the first region is to meet the immediate electrical load demand within the region. This is achieved by monitoring and adjusting the power supply within the region, including the electrical energy input from green energy input devices and the power transfer via flexible multi-state switches. Ensuring a sufficient power supply to the load is the primary task of system operation during any given scheduling cycle.

[0091] If the electricity received from the green energy input device and the flexible multi-state switch exceeds the electricity required by the regional load, the system will transfer this excess electricity to the hydrogen production station to produce hydrogen through the water electrolysis process. Simultaneously, the excess electricity will be stored in the energy storage device. If the state of charge (SBC) of the energy storage device is below its maximum value, this indicates that the device still has capacity to receive additional electricity. Conversely, if the SBC of the energy storage device has reached or exceeded its maximum value, the system cannot store any more electricity in the device.

[0092] When the power supplied by the green energy input device and the flexible multi-state switch is insufficient to meet load demand, the system will dispatch the stored energy in the energy storage device. If the state of charge of the energy storage device is higher than the minimum value, the energy storage device will release energy to support the electrical load in the area. If the state of charge of the energy storage device is lower than the minimum value, power will be obtained from the external power grid to supply the load of the first area.

[0093] In certain situations, such as when the energy storage device has reached its maximum state of charge and the hydrogen production station has reached its maximum hydrogen production capacity, the system will be unable to utilize the excess electrical energy. In such cases, the optimization result is deemed invalid.

[0094] In the operation of the electric hydrogen system, this optimization process is continuous. The system adjusts power distribution based on real-time data in each scheduling cycle. Through this dynamic adjustment, the electric hydrogen system can optimize power production and consumption while ensuring basic electrical load, improving energy efficiency and ensuring the economic and sustainable operation of the system.

[0095] When the target area is the second area, step S302-2 is used, such as... Figure 4 As shown. When the target region is the second region, the parameters involved in the optimization of the target region are those in step S30.

[0096] Step S302-2: For one of the time periods, different energy dispatch strategies are selectively executed based on the state of charge of the second energy storage device, the electrical load of the second region, the amount of electricity transferred to the second region through the power electronic conversion device, and the amount of electrical energy input by the green energy input device.

[0097] In this embodiment, the energy scheduling strategy in this step still aims to maximize the absorption rate, and the same applies to the third region thereafter, which will not be elaborated here.

[0098] In one implementation, in the energy management strategy for the second region, photovoltaic DC power, as a green energy input device, along with electricity transferred to the second region via power electronic conversion devices, serves as the primary source of power supply. This region is specific to DC power supply and is not connected to a hydrogen production station.

[0099] At the start of each scheduling period, the system assesses whether the internal power of the second region is sufficient to meet the current period's electrical load demand. If the internal power of the second region exceeds its electrical load demand, the system will consider storing the excess energy and / or transferring it to the first region. The state of charge (SOC2) of the second energy storage device is a key indicator for determining whether energy storage is feasible.

[0100] If the energy storage device's state of charge (SOC) is below its maximum SOC, it means the device still has capacity to receive excess energy, and the system will instruct the device to store this extra energy. When the SOC reaches its maximum SOC, it means the device is full and can no longer store any more energy.

[0101] If the electricity generated by the photovoltaic DC power source is insufficient to meet the electrical load demand of the second region, this will trigger the discharge process of the energy storage device. The discharge of the energy storage device will be based on its current state of charge and will not fall below the minimum state of charge to prevent damage that may be caused by over-discharge. During the discharge process, the energy storage device provides the required electrical energy to meet the electrical load, ensuring energy stability in the region. If the energy storage device's state of charge falls below the minimum state of charge or the energy storage device cannot provide sufficient electrical energy to meet the load demand, the second region will request electricity from the third region. This strategy ensures the continuity and reliability of the regional power supply even when the capacity of the green energy input device is insufficient.

[0102] Through this energy management strategy, the second region can maximize the utilization of photovoltaic power, improve energy efficiency, and ensure a balanced and sustainable energy supply under different supply and demand conditions.

[0103] When the target area is the third area, step S302-3 is used, such as... Figure 5 As shown. When the target region is the third region, the parameters involved in the optimization of the target region are those in step S30.

[0104] Step S302-3: For one of the time periods, different energy dispatch strategies are selectively executed based on the state of charge of the third energy storage device, the electrical load of the third region, and the amount of electrical energy input by the green energy input device.

[0105] In this embodiment, when the internal power of the third region is higher than the electrical load of the third region, the excess power will be supplied to the energy storage device and / or the excess power will be transferred to the second region, wherein the state of charge of the third energy storage device is denoted as S0C3.

[0106] In this embodiment, optimization also includes using an objective function and constraints, wherein the objective function is as follows:

[0107] maxf = 365 * (E1 + E2 + E3) - (C bat +C el +C sto ),

[0108] Where C bat C el C sto These represent the annual costs of the energy storage device, the annual cost of hydrogen production at the hydrogen production station, and the annual cost of the hydrogen storage device, respectively. E1 and E2 represent the revenue from hydrogen production and the revenue from supplying local loads of renewable energy, respectively. The specific formulas for the revenues are as follows.

[0109]

[0110] In the formula R H Rgrid These represent the hydrogen price and the time-of-use electricity price, respectively. α is a binary variable, where a value of 1 indicates that renewable energy generation exceeds the load. P bat,dis m el These represent the energy storage discharge power and hydrogen production during time period t, respectively. This represents the load capacity that can be met by local renewable energy sources. The specific formula for cost is as follows:

[0111]

[0112] In the formula I PV I el I bat I sto These represent the prices per unit capacity of photovoltaic power, hydrogen production at hydrogen production stations, energy storage in energy storage devices, and hydrogen storage tanks, respectively. V PV V el V bat V sto These represent the capacities of photovoltaic power generation, hydrogen production at the hydrogen production station, energy storage in the energy storage device, and hydrogen storage tank, respectively. r0 is the discount rate, which is set to 5% in this embodiment, and m is the system operating period, which is set to 20 years in this paper. uPV, uel, ubat, and usto are the annual operation and maintenance costs of photovoltaic power generation, hydrogen production at the hydrogen production station, energy storage in the energy storage device, and hydrogen storage tank, respectively.

[0113] This embodiment also includes constraints, which are as follows:

[0114] Before detailing the constraints, let's explain the hydrogen production capacity of the hydrogen production station. The formula for calculating the hydrogen production capacity of the hydrogen production station is as follows:

[0115] m el (t)=η el · el ()·Δt,

[0116] Where m is el (t) represents the mass of hydrogen produced by the hydrogen production station during time period t, and η el P represents the hydrogen production efficiency of a hydrogen production station. el (t) represents the hydrogen production capacity of the hydrogen production station during time period t. First, the constraints that the hydrogen energy system must meet for operation are as follows:

[0117] The total hydrogen production per day needs to meet the hydrogen load demand:

[0118]

[0119] N t N represents the total number of scheduling cycles in a day. j Let t0 represent the number of hydrogen load types and t0 represent any time period during the day. The system's net hydrogen production per day is less than the upper limit of hydrogen storage, and the hydrogen storage tank capacity constraints are as follows:

[0120]

[0121]

[0122] in ρ represents the maximum mass of hydrogen that the hydrogen storage tank can hold. sto V represents hydrogen storage density. sto This indicates the capacity of the hydrogen storage tank.

[0123] To ensure the normal operation of the hydrogenation process, the following constraints are imposed on the total hydrogenation time of the hydrogen-using equipment within time period t:

[0124]

[0125] The pressure inside the hydrogen storage tank is directly proportional to the amount of hydrogen stored. The hydrogen storage conditions in the tank are as follows:

[0126]

[0127]

[0128] In the formula p t,sto p t-1,sto These represent the hydrogen storage tank pressures during time period t and time period t-1, respectively, where R is the ideal gas constant and T is the pressure of the hydrogen storage tank during time period t-1. H2 It is the temperature of the gas inside the tank, C. sto β is the volume of the hydrogen storage tank, and β is the conversion factor between different units. The hydrogen storage tank must meet the following constraints:

[0129] LOH min ≤LOH≤LOH max ,

[0130] In the formula LOH min LOH max These represent the minimum and maximum hydrogen storage capacities, respectively. Furthermore, the constraints that the power system must satisfy are as follows:

[0131] For ease of subsequent description, the variables are simplified. The net power of the line is defined as:

[0132]

[0133] Define the actual power of the battery as:

[0134] P bat,i (t)=P bat,i,ch (t)-P bat,i,dis (t)| i＝Ⅰ,Ⅱ,DC ,

[0135] The power balance constraints for the first, second, and third regions are set as follows:

[0136]

[0137]

[0138]

[0139] In the formula P PV P wind These are the photovoltaic and wind power generation systems connected to each busbar, P grid P represents the interaction power between the bus and the power grid. load For the electrical load of each busbar, P bat,ch P bat,dis These represent the energy storage charging and discharging power, respectively.

[0140] The power of each unit must meet the following constraints:

[0141]

[0142] In the formula P el,max P el,min P bat,max P bat,min These are the upper and lower limits of hydrogen production capacity for hydrogen production stations, as well as the upper and lower limits of energy storage capacity. Additionally, there is the load capacity that can be met by local renewable energy sources. In this regard, the following constraints must be met:

[0143]

[0144] The equipment capacity needs to meet the following constraints:

[0145]

[0146] P el (t)≤V el ,t∈[1,T],

[0147] To ensure the safe and efficient operation of the batteries, the state of charge of the energy storage devices in the three areas is as follows:

[0148]

[0149] SOC min ≤SOC i ≤SOC max | i＝Ⅰ,Ⅱ,DC

[0150] In addition, to maintain operational sustainability, the state of charge at the end of the day is set to be the same as at the beginning, as shown in the following formula:

[0151]

[0152] In the formula, SOC min SOC max η represents the minimum and maximum states of charge, respectively. bat This refers to the energy storage charging and discharging efficiency.

[0153] By defining regional energy management strategies, objective functions, and constraints, the power scheduling results within the electric hydrogen system and between the electric hydrogen system and the hydrogen energy system are ultimately obtained.

[0154] In this embodiment, the amount of electricity transmitted by the first and second regions through the power electronic conversion device, the amount of electricity transmitted by the second and third regions through the power electronic conversion device, the amount of electricity obtained by each region through the green energy transmission device, the amount of electricity stored by each region to the energy storage device, and the amount of electricity transmitted by the first region to the hydrogen production station are obtained in each time period of a cycle during optimization.

[0155] Furthermore, in this embodiment, after obtaining the above data, the optimal hydrogen storage capacity of the hydrogen storage station, the optimal capacity of the energy storage devices in each area, and the optimal hydrogen production rate of the hydrogen production station can be obtained. Based on this data, the actual equipment can be designed accordingly.

[0156] Furthermore, in this embodiment, after obtaining the above data, the annual revenue of the electric hydrogen system can be obtained based on the data of the electric hydrogen system. Specifically, the daily revenue is obtained by multiplying it by the number of days in the year, which will not be elaborated here.

[0157] It should be noted that although the steps in the above embodiments are described in a specific order, those skilled in the art will understand that in order to achieve the effects of the present invention, different steps do not necessarily have to be executed in such an order. They can be executed simultaneously (in parallel) or in other orders, and these variations are all within the scope of protection of the present invention.

[0158] Those skilled in the art will understand that all or part of the processes in the method of the above-described embodiment of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes other computer programs, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable storage medium can include any entity or device capable of carrying a computer program, media, USB flash drive, portable hard drive, magnetic disk, optical disk, computer memory, read-only memory, random access memory, electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in the computer-readable storage medium can be appropriately added to or subtracted according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable storage medium does not include electrical carrier signals and telecommunication signals.

[0159] Furthermore, the present invention also provides a control device. In one embodiment of the control device according to the present invention, the control device includes a processor and a storage device. The storage device can be configured to store a program for executing the power optimization method for multiple regions in the electric hydrogen system described in the above-described method embodiments. The processor can be configured to execute the program in the storage device, which includes, but is not limited to, a program for executing the power optimization method for multiple regions in the electric hydrogen system described in the above-described method embodiments. For ease of explanation, only the parts related to the embodiments of the present invention are shown; for specific technical details not disclosed, please refer to the method section of the embodiments of the present invention. This control device can be a control device device comprising various electronic devices.

[0160] Furthermore, the present invention also provides a computer-readable storage medium. In one embodiment of the computer-readable storage medium according to the present invention, the computer-readable storage medium can be configured to store a program for executing a multi-region power optimization method in an electric hydrogen system according to the above-described method embodiments. This program can be loaded and run by a processor to implement the multi-region power optimization method in the above-described electric hydrogen system. For ease of explanation, only the parts related to the embodiments of the present invention are shown; for specific technical details not disclosed, please refer to the method section of the embodiments of the present invention. The computer-readable storage medium can be a storage device comprising various electronic devices. Optionally, in the embodiments of the present invention, the computer-readable storage medium is a non-transitory computer-readable storage medium.

[0161] Furthermore, it should be understood that since the various modules are only provided to illustrate the functional units of the device of the present invention, the physical devices corresponding to these modules may be the processor itself, or a part of the processor's software, hardware, or a combination of software and hardware. Therefore, the number of modules shown in the figures is merely illustrative.

[0162] Those skilled in the art will understand that the various modules in the device can be adaptively split or combined. Such splitting or combining of specific modules will not cause the technical solution to deviate from the principles of the present invention; therefore, the technical solutions after splitting or combining will fall within the protection scope of the present invention.

[0163] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after such changes or substitutions will all fall within the scope of protection of the present invention.

Claims

1. A method for optimizing power consumption in multiple regions of an electro-hydrogen system, characterized in that, The electro-hydrogen system includes an electrical energy system and a hydrogen energy system, wherein the electrical energy system and the hydrogen energy system are connected, the electro-hydrogen system model includes a hydrogen energy system model, and the method includes: Acquire data from the electro-hydrogen system; The undetermined hydrogen load is obtained based on the hydrogen energy system model, wherein the undetermined hydrogen load reflects the hydrogen consumption of the hydrogen energy system during a first preset time period. The undetermined hydrogen load and the data of the electric hydrogen system are input into the electric hydrogen system model to optimize the electric hydrogen system and obtain the power scheduling results within the electric energy system and between the electric energy system and the hydrogen energy system. "Obtaining the undetermined hydrogen load based on a hydrogen energy system model" includes: The hydrogen energy system model includes a mobile hydrogen-powered device module and a stationary hydrogen-powered device module; The determined hydrogen load is obtained based on the mobile hydrogen power device module and the stationary hydrogen power device module; The mobile hydrogen-powered equipment module includes: a mobile hydrogen-powered crane, a hydrogen-powered forklift, and a hydrogen-powered truck module. The mobile hydrogen-powered crane module is modeled as follows: ， ， in , These are the upper and lower limits of the onboard hydrogen storage capacity for mobile hydrogen-powered cranes. The amount of hydrogen consumed during period t; For time period t, the i-th mobile hydrogen-powered crane in the hydrogen-electric system can adjust the hydrogen load. The initial hydrogen storage capacity is T; the total system scheduling period is T, and the current time period is t within the total system scheduling period. The hydrogen-powered forklift module is modeled as follows: ， ， in , These represent the upper and lower limits of the onboard hydrogen storage capacity of hydrogen-electric forklifts. The amount of hydrogen consumed during period t; For the time period t, the adjustable hydrogen load of the i-th hydrogen-electric forklift in the hydrogen-electric system is... Its initial hydrogen storage capacity; The hydrogen-powered truck module is modeled as follows: ， in These are its unloaded distance and loaded distance, respectively. , These represent the unloaded speed and the loaded speed of the hydrogen-powered truck, respectively; when the i-th hydrogen-powered truck cycles through N... i At this time, the hydrogen consumption of the i-th hydrogen-powered truck for: ， in , These figures represent the hydrogen consumption per 100 kilometers for hydrogen-powered trucks under no-load and loaded conditions, respectively.

2. The multi-region power optimization method in the electro-hydrogen system according to claim 1, characterized in that, The hydrogen energy system includes a hydrogen production station, and the electrical energy system includes a first region, a second region, and a third region. The second region is connected to the first region via a power electronic converter, and the third region is connected to the second region via a power electronic converter. The first region is connected to the hydrogen production station, a green energy input device, and a first energy storage device, and is used to provide power to the hydrogen production station. The second region is connected to the green energy input device and the second energy storage device, and the third region is connected to both the green energy input device and the third energy storage device. The first and third regions are AC regions, and the second region is a DC region. "Inputting the undetermined hydrogen load and the data of the electric-hydrogen system into the electric-hydrogen system model to optimize the electric-hydrogen system, and obtaining the power dispatch results within the electric energy system and between the electric energy system and the hydrogen energy system," including: Obtain the objective function, constraints, and energy management strategy; Based on the undetermined hydrogen load, the data of the electric-hydrogen system, the energy management strategy, the objective function, and the constraints, the electric-hydrogen system is optimized to obtain the power scheduling results within the electric energy system and between the electric energy system and the hydrogen energy system.

3. The multi-region power optimization method in the electro-hydrogen system according to claim 2, characterized in that, "Optimizing the electric hydrogen system based on the undetermined hydrogen load, the data of the electric hydrogen system, the energy management strategy, the objective function, and the constraints" includes: The parameters for the targeted region to be optimized include the electrical load of the targeted region at each time period, the amount of electrical energy input to the targeted region through the green energy input device, and the state of charge of the corresponding energy storage device in the targeted region. For any given time period, different energy dispatch strategies are selectively executed based on the state of charge of the energy storage device, the electrical load of the target area, and the amount of electrical energy input from the green energy input device. Optimizing the parameters of the first region also includes the hydrogen production capacity of the hydrogen production station and the amount of electricity transferred to the first region through the power electronic conversion device. "For a given time period, different energy dispatch strategies are selectively executed based on the state of charge of the energy storage devices, the electrical load of the targeted area, and the amount of electrical energy input from the green energy input devices," including: For one of the time periods, different first energy dispatch strategies are selectively executed based on the state of charge of the first energy storage device, the electrical load of the first region, the amount of electrical energy input by the green energy input device, the amount of hydrogen produced by the hydrogen production station, and the amount of electricity transferred to the first region through the power electronic conversion device. Optimizing the parameters of the second region also includes the amount of electricity transferred to the second region through a power electronic conversion device, wherein the second region is connected to the first region through the power electronic conversion device; "For a given time period, different energy dispatch strategies are selectively executed based on the state of charge of the energy storage devices, the electrical load of the targeted area, and the amount of electrical energy input from the green energy input devices," including: For one time period, different energy dispatch strategies are selectively executed based on the state of charge of the second energy storage device, the electrical load of the second region, the amount of electricity transferred to the second region through the power electronic conversion device, and the amount of electrical energy input by the green energy input device. "For a given time period, different energy dispatch strategies are selectively executed based on the state of charge of the energy storage devices, the electrical load of the targeted area, and the amount of electrical energy input from the green energy input devices," including: For any given time period, different energy dispatch strategies are selectively executed based on the state of charge of the third energy storage device, the electrical load of the third region, and the amount of electrical energy input from the green energy input device.

4. The multi-region power optimization method in the electro-hydrogen system according to claim 1, characterized in that, The undetermined hydrogen load It is expressed as follows: ； in, The hydrogen load of the fixed hydrogen-powered device module is defined for time period t.

5. The multi-region power optimization method in the electro-hydrogen system according to claim 3, characterized in that, "Based on the state of charge of the first energy storage device, the electrical load of the first region, the amount of electrical energy input by the green energy input device, the hydrogen production capacity of the hydrogen production station, and the amount of electricity transferred to the first region through the power electronic conversion device, different first energy dispatch strategies are selectively executed," including: If the internal power of the first area exceeds the power required by the electrical load of the first area, the excess power will be supplied according to the priority order of hydrogen production station and energy storage device; wherein the internal power is the sum of the amount of electrical energy input by the green energy input device and the amount of power transferred through the power electronic conversion device; When the internal power of the first region is insufficient to meet the electrical load demand of the first region and the state of charge of the first energy storage device is higher than the minimum value, the first energy storage device will release electrical energy to support the electrical load of the first region; if the state of charge of the first energy storage device is lower than the minimum value, it will request power from the external power grid to supply the electrical load of the first region.

6. The multi-region power optimization method in the electro-hydrogen system according to claim 3, characterized in that, "Selectively executing different energy dispatch strategies based on the state of charge of the second energy storage device, the electrical load of the second region, the amount of electricity transferred to the second region through the power electronic conversion device, and the amount of electrical energy input by the green energy input device," including: If the internal power of the second region exceeds the power load demand of the second region and the state of charge of the second energy storage device is lower than the maximum state of charge, the second energy storage device is instructed to store the excess power; if the state of charge of the second energy storage device reaches the maximum state of charge, the excess power is transferred to the first region. If the electrical energy input from the green energy input device fails to meet the electrical load demand of the second region and the state of charge of the second energy storage device is not lower than the minimum state of charge, the second energy storage device is triggered to discharge to support the electrical load of the second region; if the state of charge of the second energy storage device is lower than the minimum state of charge or the second energy storage device cannot provide enough electrical energy to meet the electrical load demand of the second region, the second region requests electricity from the third region.

7. The multi-region power optimization method in the electro-hydrogen system according to claim 2, characterized in that, It also includes the following constraints: The total hydrogen production per day must meet the hydrogen load demand: ; in, The mass of hydrogen produced by the hydrogen production station during time period t; To meet hydrogen load demand; The system's daily net hydrogen production is less than the upper limit of hydrogen storage, and the hydrogen storage tank capacity is constrained as follows: , , in ρ represents the maximum mass of hydrogen that the hydrogen storage tank can hold. sto V represents hydrogen storage density. sto Indicates the capacity of the hydrogen storage tank; The hydrogen storage status of the hydrogen storage tank is as follows: ; Where, p sto (t) represents the pressure of the hydrogen storage tank during time period t, p sto (t-1) represents the pressure of the hydrogen storage tank during time period t-1, R is the ideal gas constant, and T is the pressure of the storage tank. H2 β is the temperature of the gas inside the tank, and β is the conversion factor between different units; The hydrogen storage tank satisfies the following constraints: , Among them, LOH min The minimum hydrogen storage capacity, LOH max This represents the maximum amount of hydrogen stored.

8. A control device comprising a processor and a storage device, said storage device being adapted to store a plurality of computer programs, characterized in that, The computer program is adapted to be loaded and run by the processor to perform a multi-region power optimization method in the electric hydrogen system according to any one of claims 1 to 7.

9. A computer-readable storage medium storing a plurality of computer programs, characterized in that, The computer program is adapted to be loaded and run by a processor to perform a multi-region power optimization method in an electric hydrogen system as described in any one of claims 1 to 7.

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