Multi-timescale scheduling method and system for electricity-hydrogen coupled integrated energy, device, and medium

Abstract

The present invention relates to the technical field of electricity-hydrogen coupled integrated regulation, and provides a multi-timescale scheduling method and system for electricity-hydrogen coupled integrated energy, a device, and a medium. The method comprises: constructing an electricity-hydrogen coupled integrated energy subsystem to convert electrical energy into hydrogen energy; establishing a power balance model for electricity, heat, and gas; configuring photovoltaic, purchased electricity, and natural gas constraint conditions, and electric vehicle power constraint conditions; establishing a carbon trading model and a reserve capacity bidding model mechanism, and collecting, in real time, operating data of various devices in the electricity-hydrogen coupled integrated energy subsystem, energy supply-demand data, and external environment data; and storing and displaying comparison results on the basis of real-time detected data. In the present invention, an electricity-hydrogen coupled integrated energy system can be dynamically scheduled on the basis of energy supply and demand conditions at different times, thereby achieving efficient storage, conversion, and utilization of energy. In addition, the performance and constraints of different devices are taken into account to ensure stable and economical operation of the system.

Description

A method, system, device, and medium for multi-timescale scheduling of an integrated energy source coupled with hydrogen. Technical Field

[0001] This invention belongs to the field of integrated regulation technology of electro-hydrogen coupling, and particularly relates to a multi-timescale scheduling method, system, equipment and medium for integrated electro-hydrogen coupling energy. Background Technology

[0002] Electro-hydrogen coupled integrated energy is a new type of energy that interconnects an electric power system with a hydrogen energy system to achieve efficient conversion and synergistic utilization of electrical and hydrogen energy. Electro-hydrogen coupled integrated energy refers to the deep integration of an electric power system and a hydrogen energy system through electro-hydrogen coupling technology, enabling the mutual conversion and efficient utilization of electrical and hydrogen energy. Technical issues

[0003] In related technologies, systems often only dispatch photovoltaic, purchased electricity, or natural gas, failing to utilize the coupled use of electricity and hydrogen. These technologies lack effective configuration of energy constraints and optimization coordination mechanisms for energy sources such as photovoltaic, purchased electricity, and natural gas, resulting in the inability to coordinate the use of different energy sources. Insufficient optimization and coordination during energy dispatch impacts energy demand for production and daily life. Technical solutions

[0004] This invention provides a multi-timescale scheduling method for integrated energy with electro-hydrogen coupling, which effectively improves energy utilization efficiency, meets energy demand at different times through multi-energy synergistic optimization, reduces energy costs, and improves the stability and reliability of energy supply.

[0005] The methods include:

[0006] Construct an integrated energy subsystem that couples electricity and hydrogen to convert electrical energy into hydrogen energy. The integrated energy subsystem includes: an electrolyzer model, a hydrogen fuel cell model, a hydrogen storage tank model, and an electrical energy storage model.

[0007] Set up a power balance model for electricity, heat, and gas. Through the power balance model for electricity, heat, and gas, calculate the amount of electricity, heat, and gas required in each time period and coordinate the production and distribution of different energy sources.

[0008] Configure constraints for photovoltaic, purchased electricity and natural gas, as well as electric vehicle power constraints;

[0009] Establish carbon trading models and reserve capacity bidding models, and combine them with multi-timescale low-carbon economic dispatch models to collect real-time operational data, energy supply and demand data, and external environmental data of each device in the integrated energy subsystem of the electric-hydrogen coupling system.

[0010] Based on real-time monitoring data, the data is compared with constraints imposed by photovoltaic, purchased electricity, and natural gas, as well as electric vehicle power constraints. The comparison results are then stored and displayed.

[0011] It should be further noted that the electrolytic cell model is as follows:

[0012]

[0013] in, , This indicates the output power and input power of the electrolytic cell; Indicates the energy conversion efficiency of the electrolytic cell; , These represent the minimum and maximum input power of the electrolytic cell, respectively. Indicates the operating status of the electrolytic cell; This indicates the output fluctuation power of the electrolytic cell;

[0014] The hydrogen fuel cell model is as follows:

[0015] , This indicates the output electrical and thermal power of the hydrogen fuel cell; This indicates the overall conversion efficiency of the hydrogen fuel cell. This indicates the input power of the hydrogen fuel cell; , These represent the lower and upper limits of the thermoelectric ratio of hydrogen fuel cells, respectively.

[0016] The hydrogen storage tank model is as follows:

[0017]

[0018] This indicates the hydrogen storage level of the hydrogen storage tank. , This indicates the hydrogen storage and release efficiency of the hydrogen storage tank. , This indicates the hydrogen storage and release capacity of the hydrogen storage tank. , This indicates the upper limit of the hydrogen storage and release capacity of the hydrogen storage tank. , This indicates the upper and lower limits of the hydrogen storage tank capacity. , This indicates the hydrogen storage tank's charging and discharging status, and is a binary variable, meaning the hydrogen storage tank cannot be charged and discharged simultaneously. , The initial and final hydrogen storage capacities of the hydrogen storage tank are T, and the scheduling period is T.

[0019] The energy storage model is

[0020]

[0021] Indicates the storage level of electrical energy; , This indicates the energy storage and release efficiency of the energy storage system (ES). , Indicates the charging and discharging power of energy storage; , Indicates the upper limit of energy storage charging and discharging power; , Indicates the upper and lower limits of energy storage capacity; , indicates the energy storage charging and discharging state; This indicates that the storage device cannot be charged and discharged simultaneously; , This indicates the starting and ending amounts of energy storage.

[0022] It should be further noted that the power balance model for electricity, heat, and gas is as follows:

[0023]

[0024] , , These represent the power, heat, and gas loads of the electro-hydrogen coupled integrated energy system, respectively. , Represents the output electrical and thermal power of a combined heat and power (CHP) system; , Represents the energy storage capacity and the released capacity; Represents the output power of an electric vehicle; , Represents the heat storage capacity and release capacity of the thermal storage tank; , This represents the output power and input power of the gas-fired boiler.

[0025] It should be further noted that the constraints for photovoltaic power, purchased electricity, and natural gas are as follows:

[0026]

[0027] , , These represent the upper limits of photovoltaic output power, purchased electricity power, and purchased natural gas power, respectively.

[0028] , , These represent photovoltaic output power, purchased electricity power, and purchased natural gas power, respectively.

[0029] , This refers to the purchased electricity and photovoltaic output power that supply the load of the electro-hydrogen coupled integrated energy system, excluding electric vehicles.

[0030] , This represents the purchased electrical power and photovoltaic output power used to power electric vehicles;

[0031] The power constraint for electric vehicles is:

[0032]

[0033] Indicates the charging power of electric vehicles; This indicates the electricity consumption of an electric vehicle per 100 kilometers. This represents the expected charging state when the i-th electric vehicle finishes charging; This represents the mileage traveled by the i-th electric vehicle. This indicates the charging status of the i-th electric vehicle; , This represents the charging and discharging power of the i-th electric vehicle; , This represents the upper limit of the charging and discharging power of the i-th electric vehicle; , This indicates the charging and discharging efficiency of an electric vehicle. , Let represent the charging / discharging state of the i-th electric vehicle, and let represent the state of the i-th electric vehicle, indicating that the i-th electric vehicle cannot be charged / discharged simultaneously; C represents the battery capacity of the electric vehicle. , Let represent the upper limits of the charging and discharging power fluctuations of the i-th electric vehicle, respectively; , Indicate the maximum and minimum charging states of the i-th electric vehicle: , This indicates the start and end charging states of the i-th electric vehicle; , Indicates the times when the electric vehicle starts and ends charging; This indicates the amount of electric vehicles collected.

[0034] It should be further explained that the established carbon trading model and reserve capacity bidding model mechanism include: carbon trading model;

[0035] The carbon trading model includes: a carbon emission quota module for purchased electric and gas-fired boilers and combined heat and power, an actual carbon emission module, a carbon trading cost module, and a low-carbon treatment module for electric vehicles;

[0036] The carbon emission quota module for purchased electric and gas-fired boilers and combined heat and power is represented as follows:

[0037]

[0038] in, , , , These represent the carbon emission allowances for an integrated energy system with electro-hydrogen coupling, purchased electricity, combined heat and power, and gas-fired boilers, respectively. , This indicates the carbon emission allowance per unit of energy consumption for coal-fired and natural gas-fired power units;

[0039] The actual carbon emissions module is calculated as follows:

[0040]

[0041] in, , , , These represent the actual carbon emissions of an integrated electric-hydrogen coupled energy system, purchased electricity, combined heat and power (CHP), and gas-fired boilers, respectively. The carbon emission coefficient representing the electricity generated by the upper-level power grid; Carbon content, representing the unit calorific value of natural gas; Represents the carbon oxidation rate of natural gas; Represents the thermoelectric conversion coefficient; Represents the relative molecular mass of carbon;

[0042] The calculation method for the carbon trading cost module is as follows:

[0043]

[0044] in, Represents carbon trading costs; The trading price representing the carbon emissions of a unit;

[0045] The calculation method for the low-carbon processing module of electric vehicles is as follows:

[0046]

[0047] in, Represents the total cost of charging an electric vehicle; This represents the price of time-sharing charging for electric vehicles; Represents revenue from the sale of carbon allowances; The selling price representing carbon allowances for electric vehicles; Represents the carbon allowances obtained by electric vehicles; This represents the carbon emissions generated by charging electric vehicles; This represents the carbon emissions of a gasoline-powered car when it travels 1 kilometer. The distance traveled by electric power is represented by the unit of measurement. This represents the marginal carbon emission coefficient of gasoline-powered vehicles.

[0048] It should be further noted that the carbon trading model and the reserve capacity bidding model mechanism also include: a reserve capacity bidding module;

[0049] The reserve capacity bidding module includes: a reserve capacity bidding model for hydrogen fuel cells, a reserve capacity bidding model for electric vehicles, a reserve capacity bidding benefit model, and reserve capacity constraints for an integrated energy system with electro-hydrogen coupling.

[0050] The bidding model for hydrogen fuel cell reserve capacity is as follows:

[0051]

[0052] in, This indicates the operating status of the hydrogen fuel cell. Indicates the standby service time; This indicates the backup capacity that the hydrogen fuel cell provides to the upstream power grid; This indicates the fluctuating output power of the hydrogen fuel cell;

[0053] The bidding model for reserve capacity of electric vehicles is as follows:

[0054]

[0055] in, This indicates the reserve capacity that electric vehicles provide to the upper-level power grid; , These represent the upper-level and lower-level reserve capacity provided by electric vehicles to the upper-level power grid, respectively. Indicates the charging and discharging status of the electric vehicle. This indicates that electric vehicles cannot be charged and discharged simultaneously. This indicates the total power of the electric vehicle; , This indicates the maximum fluctuating power during the charging and discharging of an electric vehicle; , This indicates the maximum charging and discharging power of an electric vehicle;

[0056] The benefit model for reserve capacity bidding is as follows

[0057]

[0058] This represents the total reserve capacity provided by the electro-hydrogen coupled integrated energy system to the upper-level power grid. This represents the reserve capacity provided by combined heat and power (CHP) to the upper-level power grid. Represents the total revenue of the spinning reserve market; Bidding price representing spare capacity;

[0059] The reserve capacity constraint of the electro-hydrogen coupled integrated energy system is

[0060]

[0061] , This represents the maximum output power of hydrogen fuel cells and combined heat and power (CHP). This represents the required reserve capacity for an integrated electro-hydrogen coupled energy system.

[0062] It should be further noted that the multi-timescale low-carbon economic scheduling model includes the following scheduling objective function:

[0063]

[0064] in, Represents the cost of purchasing energy; Represents electricity price; Represents natural gas prices; This represents low-calorific-value natural gas.

[0065] This application also provides a multi-timescale scheduling system for an integrated energy system coupled with hydrogen, the system comprising: a subsystem for constructing an integrated energy system coupled with hydrogen, a power balance model for electricity, heat and gas, a constraint configuration module, a carbon trading processing module, and a monitoring and comparison module;

[0066] Construct an integrated energy subsystem that couples electricity and hydrogen to convert electrical energy into hydrogen energy;

[0067] Power balance models for electricity, heat, and gas are used to calculate the amount of electricity, heat, and gas required at different times, and to coordinate the production and distribution of different energy sources.

[0068] The constraint configuration module is used to configure constraints for photovoltaic, purchased electricity and natural gas, as well as electric vehicle power constraints.

[0069] The carbon trading processing module is used to establish carbon trading models and reserve capacity bidding models, combined with multi-timescale low-carbon economic dispatch models, to collect real-time operating data, energy supply and demand data, and external environmental data of various equipment in the electric-hydrogen coupled integrated energy subsystem.

[0070] The monitoring and comparison module is used to compare real-time monitoring data with constraints of photovoltaic, purchased electricity and natural gas, as well as electric vehicle power constraints, and to store and display the comparison results.

[0071] According to another embodiment of this application, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of the multi-timescale scheduling method for the electro-hydrogen coupled integrated energy.

[0072] According to another embodiment of this application, a storage medium is also provided, on which a computer program is stored, wherein the computer program, when executed by a processor, implements the steps of the multi-timescale scheduling method for the electro-hydrogen coupled integrated energy. Beneficial effects

[0073] As can be seen from the above technical solutions, the present invention has the following advantages:

[0074] The multi-timescale scheduling method for integrated energy with electro-hydrogen coupling provided in this application achieves flexible conversion and storage of electrical and hydrogen energy through electro-hydrogen coupling, effectively balancing energy supply and demand and improving the overall energy utilization efficiency.

[0075] This application, combined with a carbon trading model, can generate economic benefits in the carbon trading market by rationally allocating the use of low-carbon energy while meeting energy demand. A reserve capacity bidding model mechanism enables the system to participate in reserve capacity services in the electricity market. Multi-timescale scheduling considers energy price fluctuations at different times, such as storing electricity or producing hydrogen during periods of low electricity prices, and using stored electricity or generating electricity through hydrogen fuel cells during periods of high electricity prices, thereby reducing energy costs.

[0076] The application of hydrogen storage tank models and electrical energy storage models can smooth out fluctuations in energy supply. Hydrogen storage tanks can regulate when there is a surplus or shortage of hydrogen, while electrical energy storage devices can buffer changes in electricity supply and demand, ensuring a stable supply of electricity, heat, and fuel gas.

[0077] This application also includes various constraints and power balance models, as well as real-time data monitoring and processing, which enable the system to promptly detect abnormal problems and issue alarm information, thereby enhancing the stability and reliability of energy supply. Attached Figure Description

[0078] To more clearly illustrate the technical solution of the present invention, the accompanying drawings used in the description will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0079] Figure 1 is a flowchart of the multi-timescale scheduling method for integrated energy with electro-hydrogen coupling.

[0080] Figure 2 is a schematic diagram of a multi-timescale scheduling system for an integrated energy system with coupled electro-hydrogen energy.

[0081] Figure 3 is a schematic diagram of an electronic device. The best embodiment of the present invention

[0082] The multi-timescale scheduling method for integrated electro-hydrogen coupled energy provided in this application is based on the multi-timescale scheduling of integrated electro-hydrogen coupled energy. It achieves the conversion and storage of electrical and hydrogen energy by constructing subsystems including models of electrolyzers and hydrogen fuel cells. A power balance model is set up to coordinate the allocation of electricity, heat, and gas, and various energy constraints are configured. Combined with carbon trading and reserve capacity bidding models, various types of data are collected in real time and compared with the constraints for storage.

[0083] This application effectively improves energy utilization efficiency, meets energy demand at different times through multi-energy synergy optimization, reduces energy costs, and improves the stability and reliability of energy supply.

[0084] Various embodiments of this disclosure will be described more fully below. This disclosure may have various embodiments, and adjustments and changes may be made therein. However, it should be understood that there is no intention to limit the various embodiments of this disclosure to the specific embodiments disclosed herein, but rather this disclosure should be understood to cover all adjustments, equivalents, and / or alternatives falling within the spirit and scope of the various embodiments of this disclosure.

[0085] In the following, the terms “comprising” or “may include”, which may be used in various embodiments of this disclosure, indicate the presence of the disclosed functions, operations, or elements, and do not limit the addition of one or more functions, operations, or elements. Furthermore, as used in various embodiments of this disclosure, the terms “comprising,” “having,” and their cognates are intended only to indicate a particular feature, number, step, operation, element, component, or combination of the foregoing, and should not be construed as primarily excluding the presence of one or more other features, numbers, steps, operations, elements, components, or combinations of the foregoing, or the possibility of adding one or more combinations of the foregoing.

[0086] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0087] Please refer to Figure 1, which is a flowchart of a multi-timescale scheduling method for an integrated electro-hydrogen coupled energy system in a specific embodiment. The method includes:

[0088] S101: Construct an integrated energy subsystem of electro-hydrogen coupling to convert electrical energy into hydrogen energy; the integrated energy subsystem of electro-hydrogen coupling includes: an electrolyzer model, a hydrogen fuel cell model, a hydrogen storage tank model, and an electrical energy storage model.

[0089] In this embodiment, an integrated energy subsystem with electro-hydrogen coupling is constructed to convert electrical energy into hydrogen energy, thus realizing the conversion process of electrical energy into hydrogen energy.

[0090] Among them, the hydrogen fuel cell model can convert hydrogen energy back into electrical energy, allowing hydrogen energy to be put back into the power supply. This establishes a two-way coupling and conversion relationship between the two energy forms of electricity and hydrogen, effectively improving the efficiency and flexibility of energy utilization.

[0091] The hydrogen storage tank model in this embodiment can store excess hydrogen energy. When there is a surplus of electricity and high hydrogen production, the excess hydrogen can be stored. When the system experiences peak electricity demand or insufficient hydrogen supply, the stored hydrogen can be released for power generation or other purposes.

[0092] The energy storage model in this embodiment can store electrical energy and release it during peak electricity demand periods. This effectively smooths out fluctuations in the supply and demand of electricity and hydrogen, improving the stability and reliability of energy supply.

[0093] This application constructs an integrated energy subsystem with electro-hydrogen coupling, which enables optimized energy allocation and efficient utilization, reducing energy procurement and operating costs. For example, when electricity prices are low, hydrogen can be produced and stored using an electrolyzer; when electricity prices are high, electricity can be generated through hydrogen fuel cells, thereby reducing overall energy costs and improving the economics of the energy system.

[0094] S102: Set up a power balance model for electricity, heat, and gas. Calculate the required amounts of electricity, heat, and gas for each time period using the power balance model, and coordinate the production and distribution of different energy sources.

[0095] In this embodiment, setting a power balance model can ensure that the supply and demand of these energy sources are balanced at all times.

[0096] For example, in a work area containing an electro-hydrogen coupling system, the production equipment in the work area obtains electricity to operate, and heat is supplied to the living area. By setting up a power balance model, the amount of electricity, heat, and gas required at each time period can be calculated, coordinating the production and distribution of different energy sources and avoiding situations of insufficient or excessive energy supply.

[0097] The power balance model for electricity, heat, and gas in this embodiment calculates the amount of electricity, heat, and gas required at each time period, and coordinates the production and distribution of different energy sources.

[0098] It should be noted that when photovoltaic power generation fluctuates due to weather changes, or when the operating status of equipment such as electrolyzers and hydrogen fuel cells changes, the power balance model can promptly adjust the input from other power supply channels, such as purchased electricity, to ensure the stability of the entire system's power supply. The power balance model in this embodiment can comprehensively consider the mutual conversion and coupling relationships between different energy forms.

[0099] As one implementation of this embodiment, the power balance model for electricity, heat, and gas is as follows:

[0100]

[0101] , , These represent the power, heat, and gas loads of the electro-hydrogen coupled integrated energy system, respectively. , Represents the output electrical and thermal power of a combined heat and power (CHP) system; , Represents the energy storage capacity and the released capacity; Represents the output power of an electric vehicle; , Represents the heat storage capacity and release capacity of the thermal storage tank; , This represents the output power and input power of the gas-fired boiler.

[0102] This embodiment can use the upper-level power grid and photovoltaic power generation to power electric vehicles.

[0103] In an integrated electro-hydrogen coupled energy system, an electrolyzer consumes electrical energy to produce hydrogen, and a hydrogen fuel cell can then convert hydrogen into electrical energy. A power balance model can optimize both the hydrogen production process and the conversion process, allowing excess hydrogen to be stored for future power generation or for storing electrical energy to meet future electricity demands and improve the overall efficiency of the energy system.

[0104] It should be noted that when electricity prices are low and the energy storage devices in the system are fully charged, the power balance model can rationally arrange the operation of the electrolyzer based on the current heat and gas demand, converting excess electricity into hydrogen for storage. When electricity demand peaks or electricity prices are high, the hydrogen fuel cell can then generate electricity, thus effectively utilizing the price difference and improving system operating efficiency.

[0105] Furthermore, this embodiment involves the coordinated operation of three different energy forms—electricity, heat, and natural gas—in a comprehensive energy system. In actual operation, these three energy sources are interconnected and mutually restrictive. For example, natural gas can be used for power generation or heating; electricity can drive an electrolyzer to produce hydrogen, and hydrogen can then be used to generate electricity and provide heating through fuel cells. The power balance model can coordinate the production and distribution of electricity, heat, and natural gas based on the operating data of various devices in the system, energy supply and demand data, and external environmental data such as temperature and light intensity. This achieves synergistic optimization of multiple energy sources, maximizing the benefits of the entire comprehensive energy system.

[0106] S103: Configure constraints for photovoltaic, purchased electricity and natural gas, as well as electric vehicle power constraints.

[0107] As one implementation of this embodiment, the constraints for photovoltaic power, purchased electricity, and natural gas are as follows:

[0108]

[0109] , , These represent the upper limits of photovoltaic output power, purchased electricity power, and purchased natural gas power, respectively. , , These represent photovoltaic output power, purchased electricity power, and purchased natural gas power, respectively. , This refers to the purchased electricity and photovoltaic output power that supply the load of the electro-hydrogen coupled integrated energy system, excluding electric vehicles. , This represents the purchased electrical power and photovoltaic output power used to power electric vehicles.

[0110] The power constraint for electric vehicles is:

[0111]

[0112] in, Indicates the charging power of electric vehicles; This indicates the electricity consumption of an electric vehicle per 100 kilometers. This represents the expected charging state when the i-th electric vehicle finishes charging, and can generally be set to 0.95.

[0113] This represents the mileage traveled by the i-th electric vehicle. This indicates the charging status of the i-th electric vehicle; , This represents the charging and discharging power of the i-th electric vehicle; , This represents the upper limit of the charging and discharging power of the i-th electric vehicle; , This indicates the charging and discharging efficiency of an electric vehicle. The charging / discharging state of the i-th electric vehicle is represented by a binary variable. This indicates that the i-th electric vehicle cannot be charged and discharged simultaneously; C represents the battery capacity of the electric vehicle. , Let represent the upper limits of the charging and discharging power fluctuations of the i-th electric vehicle, respectively; , Indicate the maximum and minimum charging states of the i-th electric vehicle: , This indicates the start and end charging states of the i-th electric vehicle; , Indicates the times when electric vehicles begin and end charging (grid-connected and off-grid); This indicates the amount of electric vehicles collected.

[0114] This embodiment configures photovoltaic (PV) constraints based on factors such as local solar resources and the performance of PV equipment to reasonably estimate the maximum power generation capacity of PV. The PV constraints prioritize the use of PV energy within the permissible range of PV power generation capacity. By rationally utilizing these constraints, such as maximizing the use of PV power for hydrogen production in electrolyzers or direct power supply when sunlight is abundant, reliance on other relatively high-cost energy sources like purchased electricity is reduced, thereby lowering energy costs.

[0115] This embodiment configures external power purchase constraints to clearly define the limits of external power supply. By using external power purchase constraints, it ensures that the maximum power supply that the power grid can provide is not exceeded, allowing for reasonable scheduling of electricity consumption and guaranteeing the stability of energy supply.

[0116] The external power purchase constraint in this embodiment allows for the purchase of an appropriate amount of external power at suitable times. During periods of low electricity prices, the purchased power can be increased for hydrogen storage or charging of energy storage devices; during periods of high electricity prices, the purchased power can be reduced, thus effectively lowering energy procurement costs.

[0117] The natural gas constraint takes into account factors such as pipeline transportation capacity and storage facility capacity that limit the supply of natural gas. The electric vehicle power constraint in this embodiment is configured based on factors such as electric vehicle model and charging infrastructure. Setting electric vehicle power constraints can prevent excessive impact on the power grid during the charging process.

[0118] Within the constraints of natural gas supply, and considering fluctuations in natural gas prices, the use of natural gas can be optimized. When natural gas prices are low and supply is ample, the use of natural gas for power generation or heating can be appropriately increased, while considering storing excess electricity or heat. When natural gas prices rise or supply is tight, the use of natural gas should be reduced, and it can be replaced by photovoltaic power or hydrogen fuel cell power generation, thereby optimizing energy utilization and controlling costs.

[0119] The electric vehicle power constraint condition in this embodiment combines electric vehicle charging with grid load conditions by constraining the electric vehicle's power. During periods of low grid load, the electric vehicle is allowed to charge at a higher power, while during periods of high grid load, the charging power is reduced through the constraint condition. This allows the electric vehicle's battery to discharge into the grid as an energy storage device, achieving bidirectional energy utilization and improving overall energy efficiency.

[0120] S104: Establish a carbon trading model and a reserve capacity bidding model mechanism, combined with a multi-timescale low-carbon economic dispatch model, to collect real-time operating data, energy supply and demand data, and external environmental data of each device in the integrated energy subsystem of the electric-hydrogen coupling system.

[0121] As one embodiment of this application, the principle of carbon emission reduction is to construct carbon emission rights and incentivize the assessed entity to reduce carbon emissions through cost. When the actual carbon emissions exceed the quota, carbon emission rights need to be purchased; conversely, carbon emission rights can be sold to obtain carbon emission revenue.

[0122] The carbon trading model and reserve capacity bidding model mechanism established in this embodiment include: carbon trading model and reserve capacity bidding model, reserve capacity bidding benefit model, and reserve capacity constraints of the electric-hydrogen coupled integrated energy system.

[0123] The carbon trading model includes: a carbon emission quota module for purchased electric and gas-fired boilers and combined heat and power, an actual carbon emission module, a carbon trading cost module, and a low-carbon treatment module for electric vehicles;

[0124] The carbon emission quota module for purchased electric and gas-fired boilers and combined heat and power is represented as follows:

[0125]

[0126] in, , , , These represent the carbon emission allowances for an integrated energy system with electro-hydrogen coupling, purchased electricity, combined heat and power, and gas-fired boilers, respectively. , This indicates the carbon emission allowance per unit of energy consumption for coal-fired and natural gas-fired power units.

[0127] The actual carbon emissions module is calculated as follows:

[0128]

[0129] in, , , , These represent the actual carbon emissions of an integrated electric-hydrogen coupled energy system, purchased electricity, combined heat and power (CHP), and gas-fired boilers, respectively. The carbon emission coefficient representing the electricity generated by the upper-level power grid; Carbon content, representing the unit calorific value of natural gas; Represents the carbon oxidation rate of natural gas; This represents the thermoelectric conversion coefficient, with a value of 3600 MJ / MWh; Represents the relative molecular mass of carbon.

[0130] The calculation method for the carbon trading cost module is as follows:

[0131]

[0132] in, Represents carbon trading costs; The trading price representing the carbon emissions of a unit;

[0133] The calculation method for the low-carbon processing module of electric vehicles is as follows:

[0134]

[0135] in, Represents the total cost of charging an electric vehicle; This represents the price of time-sharing charging for electric vehicles; Represents revenue from the sale of carbon allowances; The selling price representing carbon allowances for electric vehicles; Represents the carbon allowances obtained by electric vehicles; This represents the carbon emissions generated by charging electric vehicles; This represents the carbon emissions of a gasoline-powered car when it travels 1 kilometer. The distance traveled by electric power is represented by the unit of measurement. This represents the marginal carbon emission factor for gasoline-powered vehicles. If... A negative value indicates that the price of selling carbon allowances is higher than the price of charging.

[0136] The carbon trading model and reserve capacity bidding model mechanism in this embodiment also include: a reserve capacity bidding module.

[0137] The reserve capacity bidding module includes: a reserve capacity bidding model for hydrogen fuel cells, a reserve capacity bidding model for electric vehicles, a reserve capacity bidding benefit model, and reserve capacity constraints for an integrated energy system with electro-hydrogen coupling.

[0138] The bidding model for hydrogen fuel cell reserve capacity is as follows:

[0139]

[0140] in, This represents the operating status of the hydrogen fuel cell. It is a binary optimization variable, with a value of 1 indicating that the electrolyzer is in operation and a value of 0 indicating the opposite. Indicates the standby service time; This indicates the backup capacity that the hydrogen fuel cell provides to the upstream power grid; This represents the fluctuating electrical power output of the hydrogen fuel cell. Both combined heat and power (CHP) and hydrogen fuel cells are CHP devices, so the constraints in this part are basically the same.

[0141] The bidding model for reserve capacity of electric vehicles is as follows:

[0142]

[0143] in, This indicates the reserve capacity that electric vehicles provide to the upper-level power grid; , These represent the upper-level and lower-level reserve capacity provided by electric vehicles to the upper-level power grid, respectively. , This represents the charging and discharging status of an electric vehicle. It is a binary variable, indicating that the electric vehicle cannot be charged and discharged simultaneously. This represents the total power of the electric vehicle; it is positive when the electric vehicle is charging and negative when the electric vehicle is discharging. , This indicates the maximum fluctuating power during the charging and discharging of an electric vehicle; , This indicates the maximum power output of an electric vehicle during charging and discharging.

[0144] The benefit model for reserve capacity bidding is as follows

[0145]

[0146] This represents the total reserve capacity provided by the electro-hydrogen coupled integrated energy system to the upper-level power grid. This represents the reserve capacity provided by combined heat and power (CHP) to the upper-level power grid. Represents the total revenue of the spinning reserve market; Bidding price representing spare capacity;

[0147] The reserve capacity constraint of the electro-hydrogen coupled integrated energy system is

[0148]

[0149] , This represents the maximum output power of hydrogen fuel cells and combined heat and power (CHP). This represents the required reserve capacity for the electro-hydrogen coupled integrated energy system. In this embodiment, the minimum required reserve capacity is 10% of the total photovoltaic power generation and load.

[0150] It can be seen that, regarding the establishment of carbon trading models and reserve capacity bidding mechanisms, the system can calculate the cost of carbon emissions through carbon trading models. This guides the system to choose low-carbon or zero-carbon energy production and conversion methods while meeting energy demand. For example, using electrolyzers to convert excess renewable electricity into hydrogen for storage, instead of relying on natural gas for power generation, promotes the energy system's transition to a low-carbon model. This method selection can be made clear to users through information displays or operational guidance, allowing them to understand which method is preferred for power generation or consumption, thereby improving overall energy efficiency.

[0151] The standby capacity bidding model mechanism in this embodiment enables integrated energy systems to participate in the electricity market's standby capacity service. When the system has surplus electrical energy storage or can quickly start hydrogen fuel cells to provide standby power, the system can obtain additional economic benefits by participating in standby capacity bidding.

[0152] For example, during peak electricity demand or when other power generation facilities fail, the system can supply the grid with stored electricity or electricity rapidly generated by hydrogen fuel cells.

[0153] This embodiment can also collect real-time operating data, energy supply and demand data, and external environmental data of each device in the electro-hydrogen coupled integrated energy subsystem, providing a basis for the optimized operation of the entire system.

[0154] This embodiment combines a multi-timescale low-carbon economic dispatch model, which can optimize energy dispatch at different time scales, such as by day, by week, or by month, comprehensively considering energy costs, carbon emissions, and energy supply and demand balance.

[0155] In some specific embodiments, considering that the prediction accuracy of sources and loads decreases as the time scale decreases, in order to reduce the impact of load forecasting and renewable energy on the optimal scheduling of the system, the multi-time-scale low-carbon economic scheduling model involved in this embodiment can consider optimal scheduling models for both weekly and daily time scales.

[0156] Weekly optimization scheduling uses a 1-hour scheduling interval and a 168-hour scheduling cycle, providing scheduling schemes for each unit for day-ahead optimization.

[0157] Day-ahead optimization is based on weekly optimization, using a 1-hour scheduling interval and a 24-hour scheduling cycle for optimized scheduling. In this paper, the day-ahead optimization model and the weekly optimization model for low-carbon economic scheduling differ only in the scheduling cycle; their objective functions and constraints are the same, therefore their scheduling models are consistent.

[0158] Multi-timescale low-carbon economic scheduling models include the following scheduling objective functions:

[0159]

[0160] in, Represents the cost of purchasing energy; Represents electricity price; Represents natural gas prices; This represents low-calorific-value natural gas, specifically 9.97 kWh / m³. 3 .

[0161] It can be seen that by combining a multi-timescale low-carbon economic dispatch model, we can address changes in energy demand and the environment at different times and seasons. In winter, heat demand may increase. By utilizing stored hydrogen or natural gas through combined heat and power (CHP) equipment, we can meet the heat demand while considering carbon emissions and costs. Optimized dispatching ensures a stable and economical energy supply.

[0162] S105: Based on real-time monitoring data, compare the results with constraints of photovoltaic, purchased electricity and natural gas, as well as electric vehicle power constraints, and store and display the comparison results.

[0163] In some embodiments, real-time data can be monitored based on the comparison results, and the system can automatically adjust the operating parameters of the corresponding equipment when constraints arise that exceed or fall below the power of photovoltaic, purchased electricity, natural gas, or electric vehicles.

[0164] For example, when the photovoltaic power generation exceeds the constraints, the system can adjust the inverter's power output or the power connected to the grid to guide excess electricity to the electrolyzer for hydrogen production or store it in an energy storage device. When purchased electricity approaches its constraints, the system can reduce the power demand of certain non-critical loads or start hydrogen fuel cell power generation to reduce reliance on purchased electricity. This automatic adjustment ensures stable system operation and avoids safety issues and performance degradation caused by equipment overload or insufficient energy supply. It optimizes the system's energy distribution, ensuring the system is always in its optimal operating state.

[0165] Based on the comparison results, the system can generate quotation information and notify the user through the integrated energy display interface of the electro-hydrogen coupling system.

[0166] For example, when the charging power of an electric vehicle continues to approach the constraint condition, an alarm is displayed through the integrated energy display interface of the electric-hydrogen coupling to inform the user of the potential overload risk; or when the natural gas supply approaches the lower limit constraint, an early warning is issued to the energy dispatch personnel so that alternative energy sources can be arranged in advance or corresponding emergency measures can be taken.

[0167] Based on the comparison results, combined with the current power balance models for electricity, heat, and gas, as well as carbon trading and reserve capacity bidding models, this embodiment can optimize energy dispatch decisions for different time periods.

[0168] For example, when real-time monitoring data shows that the price of purchased electricity is low and within constraints, while other energy supplies are unstable, the use of purchased electricity can be increased, and the storage strategies of hydrogen storage tanks and energy storage devices can be adjusted, provided that system demand is met. When a peak in electricity demand is detected and existing energy reserves are close to constraints, hydrogen fuel cells and energy storage devices can be prepared in advance to ensure energy supply during peak periods.

[0169] For the above-described implementation of this application, a PLC (Programmable Logic Controller) can be used to control the operation of the equipment. When the photovoltaic power generation exceeds its constraints, the PLC will send a start signal to the electrolyzer according to the preset control logic, start the electrolyzer, calculate the required hydrogen production based on the excess power, and adjust the current and voltage of the electrolyzer to convert the excess electrical energy into hydrogen and store it in the hydrogen storage tank.

[0170] For energy storage devices, when the comparison results indicate that energy needs to be stored, the PLC programmable logic controller sends a charging command to the battery management system to store the excess energy; when energy needs to be released, it sends a discharging command to release the energy to the grid or to supply power to a specific load. For electric vehicle charging stations, when the charging power is detected to be too high, the charging station's control system automatically adjusts the charging power and reduces the charging speed to ensure that the power limit is not exceeded.

[0171] In one embodiment of the present invention, based on step S101, a possible embodiment will be given below, and its specific implementation will be described in a non-limiting manner.

[0172] The electrolyzer model for the electro-hydrogen coupled integrated energy subsystem is as follows:

[0173]

[0174] in, , This indicates the output power and input power of the electrolytic cell; Indicates the energy conversion efficiency of the electrolytic cell; , These represent the minimum and maximum input power of the electrolytic cell, respectively. This represents the operating status of the electrolytic cell and is a binary optimization variable. A value of 1 indicates that the electrolytic cell is in working condition, and a value of 0 indicates the opposite. This indicates the output fluctuation power of the electrolytic cell.

[0175] As can be seen, the electrolyzer model achieves precise modeling and control of the electrolyzer's operating state by describing the relationship between its input power, output power, energy conversion efficiency, operating status, and output power fluctuations. By defining minimum and maximum input power, the operating range of the electrolyzer can be limited, ensuring it operates within a safe and efficient power range. Binary optimization variables can conveniently represent the electrolyzer's operating state, optimizing scheduling decisions and determining when to start or shut down the electrolyzer. For example, when there is a power surplus, based on the electrolyzer's minimum input power and energy conversion efficiency, it can be determined whether to start the electrolyzer to convert excess electrical energy into hydrogen for storage, thereby balancing power supply and demand and achieving energy storage and conversion.

[0176] The hydrogen fuel cell model in this embodiment is as follows:

[0177] , This indicates the output electrical and thermal power of the hydrogen fuel cell; This represents the overall conversion efficiency of a hydrogen fuel cell, which is the sum of its power generation efficiency and its heating efficiency, and its value is a constant. This indicates the input power of the hydrogen fuel cell; , These represent the lower and upper limits of the heat-to-power ratio of hydrogen fuel cells, respectively. Both combined heat and power (CHP) and hydrogen fuel cells are CHP devices, therefore these constraints are essentially the same.

[0178] The hydrogen fuel cell model illustrates the relationship between the input power and the output electrical and thermal power of a hydrogen fuel cell, and achieves performance evaluation of the hydrogen fuel cell through comprehensive conversion efficiency. In the system, when electricity and heat supply are required, based on the current hydrogen supply and the performance parameters of the hydrogen fuel cell, the hydrogen fuel cell model can be used to calculate the electrical and thermal power that can be generated, achieving efficient energy utilization and energy form conversion.

[0179] The hydrogen storage tank model in this embodiment is as follows:

[0180]

[0181] This indicates the hydrogen storage level of the hydrogen storage tank. , This indicates the hydrogen storage and release efficiency of the hydrogen storage tank. , This indicates the hydrogen storage and release capacity of the hydrogen storage tank. , This indicates the upper limit of the hydrogen storage and release capacity of the hydrogen storage tank. , This indicates the upper and lower limits of the hydrogen storage tank capacity. , This indicates the hydrogen storage tank's charging and discharging status, and is a binary variable, meaning the hydrogen storage tank cannot be charged and discharged simultaneously. , Let T represent the initial and final hydrogen storage capacity of the hydrogen storage tank, and T be the scheduling period. However, considering the advantages of hydrogen in long-term energy storage, the hydrogen storage tank is balanced at the beginning and end of a week of energy storage.

[0182] The hydrogen storage tank model is based on the change in hydrogen storage level over time, taking into account hydrogen storage and release efficiencies, storage and release capacities and states, as well as the tank's capacity limitations. The binary variable model ensures that the tank cannot be simultaneously filled and released, avoiding logical errors and operational risks. When there is excess hydrogen, it can be stored based on storage efficiency and capacity. When hydrogen is needed for electricity or heat, it is released based on release efficiency and capacity. Furthermore, by considering the upper and lower limits of the tank's capacity, the safe operation and rational utilization of the hydrogen storage tank can be ensured.

[0183] The energy storage model in this embodiment is as follows:

[0184]

[0185] in, Indicates the storage level of electrical energy; , This indicates the energy storage and release efficiency of the energy storage system (ES). , Indicates the charging and discharging power of energy storage; , Indicates the upper limit of energy storage charging and discharging power; , Indicates the upper and lower limits of energy storage capacity; , This represents the charging and discharging state of the energy storage device. It is a binary variable and indicates that the energy storage device cannot charge and discharge simultaneously. , This indicates the starting and ending amounts of energy storage.

[0186] Similar to the hydrogen storage tank model, the electrical energy storage model describes the change in the storage level of electrical energy over time, considering energy storage and release efficiency, charging and discharging power and capacity limitations, and charging and discharging states. This helps the system store electrical energy when there is a power surplus and release it when there is a power shortage, ensuring the stability and reliability of the power supply. Binary variables ensure that the energy storage device does not perform simultaneous charging and discharging operations, avoiding damage to the device.

[0187] The above model can dynamically schedule the integrated energy system of electric-hydrogen coupling based on the energy supply and demand situation and equipment status at different times, so as to achieve efficient energy storage, conversion and utilization. At the same time, it takes into account the performance and constraints of different equipment to ensure the stable and economical operation of the system.

[0188] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0189] The following are embodiments of the multi-timescale scheduling system for integrated electric-hydrogen coupled energy provided in this disclosure. This system and the multi-timescale scheduling method for integrated electric-hydrogen coupled energy in the above embodiments belong to the same inventive concept. For details not described in detail in the embodiments of the multi-timescale scheduling system for integrated electric-hydrogen coupled energy, please refer to the embodiments of the multi-timescale scheduling method for integrated electric-hydrogen coupled energy described above.

[0190] As shown in Figure 2, the system includes: a construction of an integrated energy subsystem for electricity-hydrogen coupling, a power balance model for electricity, heat and gas, a constraint configuration module, a carbon trading processing module, and a monitoring and comparison module.

[0191] An integrated energy subsystem coupled with hydrogen energy was constructed to convert electrical energy into hydrogen energy.

[0192] Power balance models for electricity, heat, and gas are used to calculate the amount of electricity, heat, and gas required at different times, and to coordinate the production and distribution of different energy sources.

[0193] The constraint configuration module is used to configure constraints for photovoltaic, purchased electricity and natural gas, as well as electric vehicle power constraints.

[0194] The carbon trading processing module is used to establish carbon trading models and reserve capacity bidding models. Combined with multi-timescale low-carbon economic dispatch models, it collects real-time operating data, energy supply and demand data, and external environmental data of various devices in the electric-hydrogen coupled integrated energy subsystem.

[0195] The monitoring and comparison module is used to compare real-time monitoring data with constraints of photovoltaic, purchased electricity and natural gas, as well as electric vehicle power constraints, and to store and display the comparison results.

[0196] As shown in Figure 3, this application also provides an electronic device, including a display module 103, a memory 102, a processor 101, and a computer program stored in the memory and executable on the processor 101. When the processor 101 executes the program, it implements the steps of a multi-timescale scheduling method for electro-hydrogen coupled integrated energy.

[0197] In embodiments of the present invention, electronic devices include, but are not limited to, laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. Electronic devices may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the embodiments described and / or claimed herein.

[0198] In this embodiment, processor 101 may be implemented using at least one of an Application Specific Integrated Circuit (ASIC), a Programmable Logic Device (PLD), a Field Programmable Gate Array (FPGA), a processor, a controller, a microcontroller, a microprocessor, or an electronic unit designed to perform the functions described herein. In some cases, such implementations may be implemented within a controller. For software implementations, implementations such as processes or functions may be implemented with separate software modules that allow the performance of at least one function or operation. The software code may be implemented by a software application (or program) written in any suitable programming language, and the software code may be stored in memory and executed by the controller.

[0199] The display module 103 is used to display information input by the user or information provided to the user. The display module 103 may include a display panel, which may be configured in the form of a liquid crystal display (LCD), an organic light-emitting diode (OLED), or the like.

[0200] The memory 102 can be used to store software programs and various data. The memory 102 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0201] This application also provides a storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the multi-timescale scheduling method for the electro-hydrogen coupled integrated energy source.

[0202] The storage medium may be any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example,, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of readable storage media include: electrical connections having one or more wires, portable disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0203] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A multi-timescale scheduling method for an integrated energy source coupled with hydrogen, characterized in that, The methods include: Construct an integrated energy subsystem that couples electricity and hydrogen to convert electrical energy into hydrogen energy. The integrated energy subsystem includes: an electrolyzer model, a hydrogen fuel cell model, a hydrogen storage tank model, and an electrical energy storage model. Set up a power balance model for electricity, heat, and gas. Using the power balance model for electricity, heat, and gas, calculate the amount of electricity, heat, and gas required at each time period and coordinate the production and distribution of different energy sources. Configure constraints for photovoltaic, purchased electricity and natural gas, as well as electric vehicle power constraints; Establish carbon trading models and reserve capacity bidding models, and combine them with multi-timescale low-carbon economic dispatch models to collect real-time operational data, energy supply and demand data, and external environmental data of each device in the integrated energy subsystem of the electric-hydrogen coupling system. Based on real-time monitoring data, the data is compared with constraints imposed by photovoltaic, purchased electricity, and natural gas, as well as electric vehicle power constraints. The comparison results are then stored and displayed.

2. The multi-timescale scheduling method for electro-hydrogen coupled integrated energy according to claim 1, characterized in that, The electrolytic cell model is as follows: ； in, 、 This indicates the output power and input power of the electrolytic cell; Indicates the energy conversion efficiency of the electrolytic cell; 、 These represent the minimum and maximum input power of the electrolytic cell, respectively. Indicates the operating status of the electrolytic cell; This indicates the output fluctuation power of the electrolytic cell; The hydrogen fuel cell model is as follows: ； 、 This indicates the output electrical and thermal power of the hydrogen fuel cell; This indicates the overall conversion efficiency of the hydrogen fuel cell. This indicates the input power of the hydrogen fuel cell; 、 These represent the lower and upper limits of the thermoelectric ratio of hydrogen fuel cells, respectively. The hydrogen storage tank model is as follows: ； This indicates the hydrogen storage level of the hydrogen storage tank. 、 This indicates the hydrogen storage and release efficiency of the hydrogen storage tank. 、 This indicates the hydrogen storage and release capacity of the hydrogen storage tank. 、 This indicates the upper limit of the hydrogen storage and release capacity of the hydrogen storage tank. 、 This indicates the upper and lower limits of the hydrogen storage tank capacity. 、 This indicates the hydrogen storage tank's charging and discharging status, and is a binary variable, meaning the hydrogen storage tank cannot be charged and discharged simultaneously. 、 The initial and final hydrogen storage capacities of the hydrogen storage tank are T, and the scheduling period is T. The energy storage model is ； Indicates the storage level of electrical energy; 、 This indicates the energy storage and release efficiency of the energy storage system (ES). 、 Indicates the charging and discharging power of energy storage; 、 Indicates the upper limit of energy storage charging and discharging power; 、 Indicates the upper and lower limits of energy storage capacity; , indicates the energy storage charging and discharging state; This indicates that the storage device cannot be charged and discharged simultaneously; 、 This indicates the starting and ending amounts of energy storage.

3. The multi-timescale scheduling method for electro-hydrogen coupled integrated energy according to claim 1, characterized in that, The power balance model for electricity, heat, and gas is as follows: ； 、 、 These represent the power, heat, and gas loads of the electro-hydrogen coupled integrated energy system, respectively. 、 This represents the output electrical and thermal power of a combined heat and power (CHP) system. 、 Represents the energy storage capacity and the released capacity; Represents the output power of an electric vehicle; 、 Represents the heat storage capacity and release capacity of the thermal storage tank; 、 This represents the output power and input power of the gas-fired boiler.

4. The multi-timescale scheduling method for electro-hydrogen coupled integrated energy according to claim 1, characterized in that, The constraints for photovoltaic power, purchased electricity, and natural gas are as follows: ； 、 、 These represent the upper limits of photovoltaic output power, purchased electricity power, and purchased natural gas power, respectively. 、 、 These represent photovoltaic output power, purchased electricity power, and purchased natural gas power, respectively. 、 This refers to the purchased electricity and photovoltaic output power that supply the load of the electro-hydrogen coupled integrated energy system, excluding electric vehicles. 、 This represents the purchased electrical power and photovoltaic output power used to power electric vehicles; The power constraint for electric vehicles is: ； Indicates the charging power of electric vehicles; This indicates the electricity consumption of an electric vehicle per 100 kilometers. This represents the expected charging state when the i-th electric vehicle finishes charging; This represents the mileage traveled by the i-th electric vehicle. This indicates the charging status of the i-th electric vehicle; 、 This represents the charging and discharging power of the i-th electric vehicle; 、 This represents the upper limit of the charging and discharging power of the i-th electric vehicle; 、 This indicates the charging and discharging efficiency of an electric vehicle. 、 Let represent the charging / discharging state of the i-th electric vehicle, and let represent the state of the i-th electric vehicle, indicating that the i-th electric vehicle cannot be charged / discharged simultaneously; C represents the battery capacity of the electric vehicle. 、 Let represent the upper limits of the charging and discharging power fluctuations of the i-th electric vehicle, respectively; 、 Indicate the maximum and minimum charging states of the i-th electric vehicle: 、 This indicates the start and end charging states of the i-th electric vehicle; 、 Indicates the times when the electric vehicle starts and ends charging; This indicates the amount of electric vehicles collected.

5. The multi-timescale scheduling method for electro-hydrogen coupled integrated energy according to claim 1, characterized in that, The established carbon trading model and reserve capacity bidding model mechanism include: carbon trading model; The carbon trading model includes: a carbon emission quota module for purchased electric and gas-fired boilers and combined heat and power, an actual carbon emission module, a carbon trading cost module, and a low-carbon treatment module for electric vehicles; The carbon emission quota module for purchased electric and gas-fired boilers and combined heat and power is represented as follows: ； in, 、 、 、 These represent the carbon emission allowances for an integrated energy system with electro-hydrogen coupling, purchased electricity, combined heat and power, and gas-fired boilers, respectively. 、 This indicates the carbon emission allowance per unit of energy consumption for coal-fired and natural gas-fired power units; The actual carbon emissions module is calculated as follows: ； in, 、 、 、 These represent the actual carbon emissions of an integrated electric-hydrogen coupled energy system, purchased electricity, combined heat and power (CHP), and gas-fired boilers, respectively. The carbon emission coefficient representing the electricity generated by the upper-level power grid; Carbon content, representing the unit calorific value of natural gas; Represents the carbon oxidation rate of natural gas; Represents the thermoelectric conversion coefficient; Represents the relative molecular mass of carbon; The carbon trading cost module is calculated as follows: ； in, Represents carbon trading costs; The trading price representing the carbon emissions of a unit; The calculation method for the low-carbon processing module of electric vehicles is as follows: ； in, Represents the total cost of charging an electric vehicle; This represents the price of time-sharing charging for electric vehicles; Represents revenue from the sale of carbon allowances; The selling price representing carbon allowances for electric vehicles; Represents the carbon allowances obtained by electric vehicles; This represents the carbon emissions generated by charging electric vehicles; This represents the carbon emissions of a gasoline-powered vehicle when it travels 1 kilometer. The distance traveled by electric power is represented by the unit of measurement. This represents the marginal carbon emission coefficient of gasoline-powered vehicles.

6. The multi-timescale scheduling method for electro-hydrogen coupled integrated energy according to claim 5, characterized in that, The carbon trading model and the reserve capacity bidding model mechanism also include: a reserve capacity bidding module; The reserve capacity bidding module includes: a reserve capacity bidding model for hydrogen fuel cells, a reserve capacity bidding model for electric vehicles, a reserve capacity bidding benefit model, and reserve capacity constraints for an integrated energy system with electro-hydrogen coupling. The bidding model for hydrogen fuel cell reserve capacity is as follows: ； in, This indicates the operating status of the hydrogen fuel cell. Indicates the standby service time; This indicates the backup capacity that the hydrogen fuel cell provides to the upstream power grid; This indicates the fluctuating output power of the hydrogen fuel cell; The bidding model for reserve capacity of electric vehicles is as follows: ； in, This indicates the reserve capacity that electric vehicles provide to the upper-level power grid; 、 These represent the upper-level and lower-level reserve capacity provided by electric vehicles to the upper-level power grid, respectively. Indicates the charging and discharging status of the electric vehicle. This indicates that electric vehicles cannot be charged and discharged simultaneously. This indicates the total power of the electric vehicle; 、 This indicates the maximum fluctuating power during the charging and discharging of an electric vehicle; 、 This indicates the maximum charging and discharging power of an electric vehicle; The benefit model for reserve capacity bidding is as follows ； This represents the total reserve capacity provided by the electro-hydrogen coupled integrated energy system to the upper-level power grid. This represents the reserve capacity provided by combined heat and power (CHP) to the upper-level power grid. Represents the total revenue of the spinning reserve market; Bidding price representing spare capacity; The reserve capacity constraint of the electro-hydrogen coupled integrated energy system is ； 、 This represents the maximum output power of hydrogen fuel cells and combined heat and power (CHP). This represents the required reserve capacity for an integrated electro-hydrogen coupled energy system.

7. The multi-timescale scheduling method for electro-hydrogen coupled integrated energy according to claim 1, characterized in that, Multi-timescale low-carbon economic scheduling models include the following scheduling objective functions: ； in, Represents the cost of purchasing energy; Represents electricity price; Represents natural gas prices; This represents low-calorific-value natural gas.

8. A multi-timescale scheduling system for an integrated electro-hydrogen coupled energy system, characterized in that, The system is used to implement the multi-timescale scheduling method for electro-hydrogen coupled integrated energy as described in any one of claims 1 to 7; The system includes: a construction of an integrated energy subsystem for electricity and hydrogen coupling, a power balance model for electricity, heat and gas, a constraint configuration module, a carbon trading processing module, and a monitoring and comparison module; Construct an integrated energy subsystem that couples electricity and hydrogen to convert electrical energy into hydrogen energy; Power balance models for electricity, heat, and gas are used to calculate the amount of electricity, heat, and gas required at different times, and to coordinate the production and distribution of different energy sources. The constraint configuration module is used to configure constraints for photovoltaic, purchased electricity and natural gas, as well as electric vehicle power constraints. The carbon trading processing module is used to establish carbon trading models and reserve capacity bidding models, combined with multi-timescale low-carbon economic dispatch models, to collect real-time operating data, energy supply and demand data, and external environmental data of various equipment in the electric-hydrogen coupled integrated energy subsystem. The monitoring and comparison module is used to compare real-time monitoring data with constraints of photovoltaic, purchased electricity and natural gas, as well as electric vehicle power constraints, and to store and display the comparison results.

9. 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 program, it implements the steps of the multi-timescale scheduling method for electro-hydrogen coupled integrated energy as described in any one of claims 1 to 7.

10. A storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the multi-timescale scheduling method for the electro-hydrogen coupled integrated energy as described in any one of claims 1 to 7.

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