Method for Generating Capacity Planning System Considering Real-Time Electricity Price and Hydrogen Demand for Vehicles

Abstract

The present invention relates to the technical field of hydrogen energy capacity planning, and specifically relates to a method for generating a capacity planning system considering real-time electricity prices and hydrogen demand for vehicles, comprising the following steps: S1, establishing a capacity scheduling model for a storage device based on the hydrogen produced by an electrolyzer unit, electricity prices, the hydrogen required by an operation department, and the hydrogen consumed by a fuel cell unit; S2, adding a constraint condition for the storage device to store liquid hydrogen on the basis of the capacity scheduling model to obtain a capacity optimization scheduling model; S3, embedding a demand signal from an external power operation market into the capacity optimization scheduling model to obtain a capacity planning system considering real-time electricity prices and hydrogen demand for vehicles. The system obtained by using this method can effectively improve the economic benefits of a hydrogen station, thereby facilitating the popularization of the hydrogen station and increasing the popularization speed of clean energy.

Description

Technical Field

[0001] The present invention relates to the technical field of hydrogen energy capacity planning, and specifically relates to a method for generating a capacity planning system considering real-time electricity prices and hydrogen demand for vehicles. Background Art

[0002] Since the preparation and storage of hydrogen are the basis of the hydrogen energy industry, hydrogen refueling stations with a large demand for hydrogen have also become the focus of research. Liquid hydrogen refueling stations have the advantages of high storage and transportation efficiency, low cost, less investment, high hydrogen purity, low energy consumption, and strong compatibility, and are a very good development direction in the future. The popularization of hydrogen refueling stations is very necessary for the successful implementation of hydrogen-powered vehicles. Hydrogen stations can use electricity to prepare and store hydrogen, and the stored hydrogen can be used to serve the transportation department, bringing profits to the hydrogen stations.

[0003] However, when the transportation department is in a non-peak hydrogen demand period (i.e., the hydrogen refueling demand for hydrogen energy vehicles is not high), the prepared and stored hydrogen energy cannot be effectively utilized. Moreover, since the number of existing hydrogen energy vehicles is not too large and the peak hydrogen demand period in the transportation department is relatively short, the production capacity utilization rate of existing hydrogen stations is at a low level, the economic benefits of hydrogen stations are not high, and there is a relatively large economic benefit resistance to the popularization of hydrogen stations, which in turn leads to a low popularization speed of hydrogen energy. Summary of the Invention

[0004] In view of the above deficiencies of the prior art, the present invention provides a method for generating a capacity planning system considering real-time electricity prices and hydrogen demand for vehicles, which can effectively improve the economic benefits of hydrogen stations, thereby facilitating the popularization of hydrogen stations and increasing the popularization speed of clean energy.

[0005] To solve the above technical problems, the present invention adopts the following technical solutions:

[0006] A method for generating a capacity planning system considering real-time electricity prices and hydrogen demand for vehicles, the method is based on a hydrogen station having an electrolyzer unit, a storage device, and a fuel cell unit; the electrolyzer unit is used to produce hydrogen, the storage device is used to store hydrogen, and the fuel cell unit is used to convert hydrogen into electrical energy to supply power to the external power operation market; the method includes the following steps:

[0007] S1, establish a capacity scheduling model for the storage device according to the hydrogen produced by the electrolyzer unit, the electricity price, the hydrogen required by the operation department, and the hydrogen consumed by the fuel cell unit;

[0008] S2, on the basis of the capacity scheduling model, add the constraint condition of storing liquid hydrogen in the storage device to obtain a capacity optimization scheduling model;

[0009] S3. Embed the demand signal of the external power operation market into the capacity optimization scheduling model to obtain a capacity planning system considering real-time electricity prices and hydrogen demand for vehicles.

[0010] Preferably, in S1, the objective function of the capacity scheduling model is:

[0011] Maximize:

[0012]

[0013] In the formula, t is the time step, Δt is the optimization time interval, s is the hydrogen station index mark, T = {1, 1 + △t,..., optimization length = T} is the set of scheduling time steps, S = {1,..., S} is the set of hydrogen stations, is the output power of the fuel cell unit, is the input power of the electrolyzer unit, is the hydrogen inflow of the fuel cell unit, is the slack variable for the operation of the fuel cell unit, is the slack variable for the operation of the electrolyzer unit, is the electricity price, is the hydrogen price, is the hydrogen demand of the transportation department, is the penalty factor for the slack variable of the fuel cell unit, is the penalty factor for the slack variable of the electrolyzer unit.

[0014] Preferably, in S1, the constraint conditions of the capacity scheduling model include:

[0015]

[0016] In the formula, is the minimum output power of the fuel cell unit, is the maximum output power of the fuel cell unit, is the minimum hydrogen production of the electrolyzer unit, is the hydrogen outflow of the electrolyzer unit, is the maximum hydrogen production of the electrolyzer unit,

[0017] λ FC is the conversion factor for converting hydrogen to electricity, η FC is the efficiency of the fuel cell unit, λ Elz is the conversion factor for converting electricity to hydrogen, η Elz is the efficiency of the electrolyzer unit; is the output power of the fuel cell unit, is the input power of the electrolyzer unit, is the hydrogen inflow of the fuel cell unit.

[0018] Preferably, in S1, the objective function satisfies:

[0019]

[0020] In the formula, is the state of charge of hydrogen at time t, is the state of charge of hydrogen at time t-1, and λ H,Dsp is the hydrogen storage energy dissipation rate.

[0021] Preferably, in S2, the objective function is further subject to the following constraints to provide the lower limit storage of the hydrogen storage device:

[0022]

[0023] In the formula, is the lower limit adjustment factor of the state of charge, is the physically finite minimum state of charge, represents the lower limit reserve margin, is the slack variable of the lower limit reserve, is the signal state of the power operation market, indicates that no demand signal from the external power operation market is received;

[0024] The lower limit storage of the hydrogen storage device also satisfies the following constraint conditions:

[0025]

[0026] Preferably, in S2, the objective function is further subject to the following constraints to provide the upper limit storage of the hydrogen storage device:

[0027]

[0028] In the formula, is the upper limit adjustment factor of the state of charge, is the physically finite maximum state of charge,

[0029] represents the upper limit reserve margin, is the slack variable of the upper limit reserve;

[0030] The upper limit storage of the hydrogen storage device also satisfies the following constraint conditions:

[0031]

[0032] Preferably, in S2, the constraint conditions of the capacity optimization scheduling model further include:

[0033]

[0034] Among them,

[0035]

[0036] Preferably, in S3, the capacity optimization scheduling model further satisfies the following constraint conditions:

[0037]

[0038] In the formula, represents the demand signal received from the external power operation market; P t OR represents the demand reserve of the power operation market, and it is defined that when P t OR is a positive value, it represents the absorption power of the power grid, and when P t OR is a negative value, it represents the injection power of the power grid.

[0039] Preferably, in S3, the objective function further satisfies the following constraint conditions:

[0040]

[0041] Among them, b1 and b2 respectively represent the subscript of the bus and the subscript of the branch in the power system; B1 and B2 respectively represent the set of buses and the set of branches in the power system; Y b1b1' represents the branch admittance from bus b1 to bus b1'; represents the active power supply to bus b1, represents the active power demand of bus b1; represents the reactive power supply to bus b1, represents the reactive power demand of bus b1; P b2,t represents the power flowing through branch b2; P b2.max represents the maximum power flowing through branch b2; V b1,min represents the minimum voltage amplitude at bus b1; V b1,t represents the voltage amplitude at bus b1; V b1',t represents the voltage amplitude at bus b1'; V b1.max represents the maximum voltage amplitude at bus b1; δ b1 represents the voltage phase angle of bus b1; δ b1' represents the voltage phase angle of bus b1'; θ b1b1' represents the voltage phase angle difference between bus b1 and b1'.

[0042] Compared with the prior art, the present invention has the following beneficial effects:

[0043] Since the hydrogen energy in the hydrogen station is obtained through an electrolyzer, that is, by converting electrical energy into hydrogen energy, therefore, in the existing technical solutions for the use of hydrogen energy, no one has considered using the hydrogen energy in the hydrogen station in the power market. Because from the process of "converting electrical energy into hydrogen energy and then outputting it to the power system", the loss of electrical energy will increase unnecessary costs. Therefore, when considering the direction of improving the economic benefits of the hydrogen station, those skilled in the art subconsciously excluded its use in the power market. The applicant, however, broke out of such a thinking inertia. Through research and thinking, the applicant found that although the hydrogen in the hydrogen station is produced by electrical energy, the electrical energy it uses belongs to renewable / cheap electricity (such as unstable electricity generated by photovoltaic). And because this electricity is unstable, its direct use in the power market has a poor effect, so a lot of it is not directly used in the power market and the utilization rate is not high. Although there are existing technologies for converting unstable electricity generated by technologies such as photovoltaic into other forms of energy for storage, there is no way of using the hydrogen station as an intermediate process site to put this electricity into the power market.

[0044] Based on such a premise, the applicant creatively proposed the technical idea of using "hydrogen energy produced by renewable / cheap electricity" in the power market, because the conversion rate of hydrogen energy into electrical energy is very high, and the electrical energy is stable and can be directly used in the power market. Equivalently, through the conversion function of the hydrogen station, the unstable electricity that is difficult to directly use in the power market is converted into stable electricity that can be directly used in the power market, thus enhancing the market application prospect of the hydrogen station.

[0045] In this way, in addition to providing hydrogen energy for the transportation sector, the hydrogen station can also provide energy for the power market. Even if the hydrogen demand in the transportation sector does not increase in the short term, by supplying energy to the power market, the economic benefits of the hydrogen station can still be significantly improved. Thus, it can help promote the hydrogen station and increase the popularization speed of clean energy.

[0046] 2. When using this system, since the hydrogen station will supply energy to the power market, the hydrogen energy it outputs will increase sharply. And the hydrogen it produces comes from the electrolysis of unstable electricity. Naturally, the utilization amount of unstable electricity will also increase sharply, thereby improving the effective utilization rate of unstable electricity and further reducing energy waste.

[0047] 3. When optimizing the hydrogen storage capacity of the hydrogen energy station in this application, the objective function in the system includes the electricity arbitrage period caused by the intertemporal change of electricity price, the profit and cost of supplying the produced hydrogen to the fuel cell units in the transportation department, and the condition of incorporating the external electricity operation market into the optimization problem. Through such settings, the profit and cost of hydrogen energy are fully considered. Not only can the electricity purchase cost be minimized through real-time electricity price fluctuations, but also the profit can be maximized by combining the actual demands of the transportation department and the electricity department, ensuring the economic benefits of the hydrogen station.

[0048] 4. Through the constraint conditions set in this solution, the practical feasibility of maximizing the revenue of the hydrogen station is ensured, which can ensure that the system will not deviate from reality during use. It can carry out hydrogen energy production, storage, and distribution according to the real market demands (transportation department and electricity department) and the actual hydrogen energy preparation and storage capacity of the hydrogen station, thereby ensuring the effectiveness of improving the economic benefits of the hydrogen station. Description of the Drawings

[0049] In order to make the purpose, technical solution, and advantages of the invention clearer, the present invention will be further described in detail below with reference to the drawings, where:

[0050] Figure 1 It is a flowchart of the embodiment. Detailed Description of the Specific Embodiment

[0051] The following will be further described in detail through specific embodiments:

[0052] Since the hydrogen energy of the hydrogen station is obtained through an electrolyzer, that is, by converting electrical energy into hydrogen energy. In the prior art solutions for the use of hydrogen energy, none of them have considered using the hydrogen energy of the hydrogen station in the electricity market. Because from the process of "converting electrical energy into hydrogen energy and then outputting it to the power system", the loss of electrical energy will increase unnecessary costs. Therefore, when those skilled in the art consider the direction of improving the economic benefits of the hydrogen station, they subconsciously rule out using it in the electricity market.

[0053] The applicant of the present invention breaks through such a thinking inertia. Through research and thinking, the applicant finds that although the hydrogen in the hydrogen station is obtained by electrical energy, the electrical energy it uses belongs to renewable / cheap electricity (such as unstable electricity generated by photovoltaic). And because this electricity is unstable, the effect of directly using it in the electricity market is not good, so many of them will not be directly used in the electricity market and the utilization rate is not high. Although there are technologies in the prior art to convert electrical energy such as photovoltaic into other forms of energy for storage, there is no way to use the hydrogen station as an intermediate process site to put this electrical energy into the electricity market.

[0054] Based on such a premise, the applicant creatively proposed the technical idea of "using hydrogen energy generated by renewable / cheap electricity in the electricity market", because the conversion rate of hydrogen energy into electric energy is very high, and the electric energy is stable and can be directly used in the electricity market. Equivalently, through the conversion of the hydrogen station, the unstable electric energy that is difficult to directly use in the electricity market is converted into stable electric energy that can be directly used in the electricity market, thus enhancing the market application prospect of the hydrogen station. Specifically as follows:

[0055] Embodiment

[0056] It should be noted that the implementation of this method is based on a hydrogen station with an electrolyzer unit, a fuel cell unit, and a storage device; the electrolyzer unit is used to produce hydrogen, the storage device is used to store hydrogen, and the fuel cell unit is used to convert hydrogen into electric energy to supply power to the external power operation market. The electrolyzer unit, the storage device, and the fuel cell unit all belong to the prior art, and existing product units can be directly used, so they will not be elaborated here.

[0057] As Figure 1 shown, this embodiment discloses a method for generating a capacity planning system considering real-time electricity prices and hydrogen demand for vehicles, including the following steps:

[0058] S1, establish a capacity scheduling model for the storage device according to the hydrogen produced by the electrolyzer unit, the electricity price, the hydrogen required by the operation department, and the hydrogen consumed by the fuel cell unit;

[0059] Among them, the objective function of the capacity scheduling model is:

[0060] Maximize:

[0061]

[0062] In the formula, t is the time step, Δt is the optimization time interval, s is the hydrogen station index mark, T = {1, 1 + △t,..., optimization length = T} is the set of scheduling time steps, S = {1,..., S} is the set of hydrogen stations, is the output power of the fuel cell unit (MW), is the input power of the electrolyzer unit (MW), is the hydrogen inflow of the fuel cell unit (m3 / h), is the slack variable of the fuel cell unit operation (MW), is the slack variable of the electrolyzer unit operation (MW), is the electricity price ($ / MWh), is the hydrogen price ($ / m3), is the hydrogen demand of the transportation department (m3 / h), is the penalty factor ($ / MWh) for the slack variable of the fuel cell unit, is the penalty factor ($ / MWh) for the slack variable of the electrolyzer unit.

[0063] The capacity scheduling model satisfies the following constraints:

[0064]

[0065]

[0066] where, is the minimum output power (MW) of the fuel cell unit, is the maximum output power (MW) of the fuel cell unit, is the minimum hydrogen production (m3 / h) of the electrolyzer unit, is the hydrogen outflow (m3 / h) of the electrolyzer unit, is the maximum hydrogen production (m3 / h) of the electrolyzer unit, λ FC is the conversion factor (MWh / m3) for converting hydrogen to electricity, η FC is the efficiency (%) of the fuel cell unit, λ Elz is the conversion factor (m3 / MWh) for converting electricity to hydrogen, η Elz is the efficiency (%) of the electrolyzer unit. is the output power (MW) of the fuel cell unit, is the input power (MW) of the electrolyzer unit, is the hydrogen inflow (m3 / h) of the fuel cell unit.

[0067] Among them, constraints (4) and (5) describe the output power and hydrogen production according to the input / output of the fuel cell and electrolyzer units respectively. Among them, constraint (4) describes the output power according to the hydrogen input of the fuel cell; constraint (5) describes the hydrogen production according to the hydrogen output of the electrolyzer unit.

[0068] The objective function also obeys the energy balance equation:

[0069]

[0070] where, is the state of charge of hydrogen (m3) at time t, is the state of charge of hydrogen (m3) at time t-1, λ H,Dsp is the hydrogen storage energy dissipation rate (% / h).

[0071] S2. On the basis of the capacity scheduling model, add the constraint conditions for storing liquid hydrogen in the storage device to obtain the capacity optimization scheduling model.

[0072] Specifically, let the objective function (1) be subject to the following constraints to provide the upper and lower limits of the hydrogen storage:

[0073]

[0074] where is the state of charge of hydrogen at time t (m3), are the upper and lower limit adjustment factors of the state of charge, are the physically finite maximum and minimum states of charge (m3), represents the lower limit reserve margin, are the slack variables of the upper and lower limit reserves (m3); is the signal state of the power operation market, indicates that no demand signal is received from the external power operation market.

[0075] Among them, the following two constraints ensure that the physical limitations of the storage device in constraints (7) and (8) are not violated:

[0076]

[0077] For any greater than 1, Equation (7) increases the lower bound of SOC to provide discharge reserve. When the larger the factor, the larger the lower limit reserve margin, which is optimally determined by the scheduling model and used to change the discharge reserve of each hydrogen station. For any less than 1, Equation (8) decreases the upper bound of SOC to establish charge reserve. When the smaller the factor, the higher the upper limit reserve margin, which is optimally determined by the scheduling model and used to change the charge reserve of the hydrogen station. Since the slack variables are determined by the optimization problem to adapt to the upper and lower limit reserve margins, these variables must be constrained so that the physically finite minimum / maximum SOC is not violated. The constraints represented by Equations (9) and (10) ensure that the physical limitations of the storage device are not violated by the slack variables.

[0078] The following constraints can ensure that the total available SOC is within the upper and lower limit reserves provided to the market at any given time step t, and at the same time meet the following minimum / maximum storage limits:

[0079]

[0080] Among them, the reserve capacity available for all hydrogen stations to provide to the market is expressed as follows:

[0081]

[0082] is the state of charge of hydrogen at time t (m3).

[0083] S3. Embed the demand signal of the external power operation market into the capacity optimization scheduling model to obtain a capacity planning system considering real-time electricity prices and hydrogen demand for vehicles.

[0084] Specifically, when the capacity optimization scheduling model receives a demand signal from the market (i.e., ), it needs to accept and track this signal and incorporate this signal into the optimization problem in the constraint set for implementation.

[0085] The capacity optimization scheduling model also satisfies the following constraint conditions:

[0086]

[0087]

[0088] In the formula, represents receiving a demand signal from the external power operation market; P t OR represents the demand reserve of the power operation market. It is defined that when P t OR is positive, it represents the absorption power of the power network, and when P t OR is negative, it represents the injection power of the power network. The additional slack variables are used to enhance the feasibility of the optimization problem by creating soft constraints. If for any reason, the hydrogen station cannot meet the contribution requirements of the power operation market, these slack variables are optimally assigned non-zero values, thereby using the optimization algorithm to reschedule the reserve P t OR , to achieve the convergence of the optimization problem.

[0089] The objective function also satisfies the following constraint conditions:

[0090]

[0091] Among them, b1 and b2 respectively represent the subscript of the bus and the subscript of the branch in the power system; B1 and B2 respectively represent the set of buses and the set of branches in the power system; Y b1b1' represents the branch admittance from bus b1 to bus b1'; represents supplying active power to bus b1, represents the active power demand of bus b1; represents supplying reactive power to bus b1, represents the reactive power demand of bus b1; P b2,t represents the power flowing through branch b2; P b2.maxRepresents the maximum power flowing through branch b2; V b1,min Represents the minimum voltage magnitude at bus b1; V b1,t Represents the voltage magnitude at bus b1; V b1',t Represents the voltage magnitude at bus b1'; V b1.max Represents the maximum voltage magnitude at bus b1; δ b1 Represents the voltage phase angle of bus b1; δ b1' Represents the voltage phase angle of bus b1'; θ b1b1' Represents the voltage phase angle difference between bus b1 and b1'.

[0092] Using the system obtained by this method, the hydrogen production station can not only provide hydrogen energy for the transportation department, but also provide energy for the electricity market. Even if the hydrogen demand of the transportation department does not increase in the short term, by supplying energy to the electricity market, the economic benefits of the hydrogen production station can still be significantly improved. Thus, it can help promote the hydrogen production station and increase the popularization speed of clean energy. On the other hand, since the hydrogen production station supplies energy to the electricity market, the hydrogen energy output will increase sharply, and the hydrogen it stores comes from the electrolysis of unstable electric energy. Naturally, the utilization of unstable electric energy will also increase sharply, thereby improving the effective utilization rate of unstable electric energy and further reducing energy waste.

[0093] When optimizing the hydrogen storage capacity of the hydrogen energy station in this application, the objective function in the system includes the power arbitrage period caused by the intertemporal change of electricity price, the profit and cost of supplying the produced hydrogen to the fuel cell units of the transportation department, and the condition of incorporating the external power operation market into the optimization problem. Through such settings, the profit and cost of hydrogen energy are fully considered. It can not only minimize the power purchase cost through real-time electricity price fluctuations, but also maximize the profit by combining the actual demands of the transportation department and the power department, ensuring the economic benefits of the hydrogen production station. In addition, through the constraint conditions set in this scheme, the practical feasibility of maximizing the revenue of the hydrogen production station is ensured, which can ensure that the system will not deviate from reality during use and can carry out hydrogen energy production, storage and distribution according to the real market demands (transportation department and power department) and the actual hydrogen energy preparation and storage capacity of the hydrogen production station, thus ensuring the effectiveness of improving the economic benefits of the hydrogen production station.

[0094] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit them. Those of ordinary skill in the art should understand that any modifications or equivalent replacements to the technical solutions of the present invention without departing from the purpose and scope of the present technical solution should be covered within the scope of the claims of the present invention.

Claims

1. Method for generating a capacity planning system considering real-time electricity prices and hydrogen demand for vehicles, Characterized in that: Based on a hydrogen station having an electrolyzer unit, a storage device, and a fuel cell unit; the electrolyzer unit is used to produce hydrogen, the storage device is used to store hydrogen, and the fuel cell unit is used to convert hydrogen into electrical energy to supply power to the external power operation market; Including the following steps: S1. Establish a capacity scheduling model for the storage device according to the hydrogen produced by the electrolyzer unit, the electricity price, the hydrogen required by the operation department, and the hydrogen consumed by the fuel cell unit; S2. On the basis of the capacity scheduling model, add the constraint conditions for the storage device to store liquid hydrogen to obtain a capacity optimization scheduling model; S3. Embed the demand signal of the external power operation market into the capacity optimization scheduling model to obtain a capacity planning system considering real-time electricity prices and hydrogen demand for vehicles; The objective function of the capacity scheduling model is: Where t is the time step, Δt is the optimization time interval, s is the index mark of the hydrogen station, T = {1, 1 + △t, …, optimization length = T} is the set of scheduling time steps, and S = {1, …, S} is the set of hydrogen stations, is the output power of the fuel cell unit, is the input power of the electrolyzer unit, is the hydrogen inflow of the fuel cell unit, is the slack variable for the operation of the fuel cell unit, is the slack variable for the operation of the electrolyzer unit, is the electricity price, is the hydrogen price, is the hydrogen demand of the transportation department, is the penalty factor for the slack variable of the fuel cell unit, is the penalty factor for the slack variable of the electrolyzer unit; The constraint conditions of the capacity scheduling model include: In the formula, is the minimum output power of the fuel cell unit, is the maximum output power of the fuel cell unit, is the minimum hydrogen output of the electrolyzer unit, is the hydrogen outflow of the electrolyzer unit, is the maximum hydrogen output of the electrolyzer unit, λ FC is the conversion factor for converting hydrogen to electrical energy, η FC is the fuel cell unit efficiency, λ Elz is the conversion factor for converting electrical energy to hydrogen, η Elz is the electrolyzer unit efficiency; is the fuel cell unit output power, is the electrolyzer unit input power, is the fuel cell unit hydrogen inflow rate.

2. The method for generating a capacity planning system considering real-time electricity prices and hydrogen demand for vehicles according to claim 1, Characterized in that: In S1, the objective function satisfies: Wherein, is the state of charge of hydrogen at time t, is the state of charge of hydrogen at time t-1, and λ H,Dsp is the hydrogen storage energy dissipation rate.

3. The method for generating a capacity planning system considering real-time electricity prices and hydrogen demand for vehicles according to claim 2, Characterized in that: In S2, the objective function is further subject to the following constraints to provide a lower limit storage capacity for the hydrogen storage device: In the formula, is the lower limit adjustment factor of the state of charge, is the minimum physically finite state of charge, represents the lower limit reserve margin, is the slack variable of the lower limit reserve, is the signal state of the power operation market, indicating that no demand signal from the external power operation market is received; The lower limit storage capacity of the hydrogen storage device also satisfies the following constraint conditions:

4. The method for generating a capacity planning system considering real-time electricity prices and hydrogen demand for vehicles according to claim 3, Characterized in that: In S2, the objective function is further subject to the following constraints to provide an upper limit storage capacity for the hydrogen storage device: In the formula, is the upper limit adjustment factor of the state of charge, is the maximum state of charge that is physically finite, represents the upper limit reserve margin, is the slack variable of the upper limit reserve; The upper limit storage capacity of the hydrogen storage device also satisfies the following constraint conditions:

5. The method for generating a capacity planning system considering real-time electricity prices and hydrogen demand for vehicles according to claim 4, Characterized in that: In S2, the constraint conditions of the capacity optimization scheduling model further include: Wherein, 6. The method for generating a capacity planning system considering real-time electricity prices and hydrogen demand for vehicles according to claim 5, Characterized in that: In S3, the capacity optimization scheduling model also satisfies the following constraint conditions: In the formula, represents the demand signal received from the external power operation market; P t OR represents the demand reserve of the power operation market, and it is defined that when P t OR is positive, it represents the absorption power of the power grid, and when P t OR is negative, it represents the injection power of the power grid.

7. The method for generating a capacity planning system considering real-time electricity prices and hydrogen demand for vehicles according to claim 6, Characterized in that: In S3, the objective function also satisfies the following constraint conditions: Among them, b1 and b2 represent the subscripts of buses and branches in the power system respectively; B1 and B2 represent the sets of buses and branches in the power system respectively; Y b1b1' represents the branch admittance from bus b1 to bus b1'; represents the active power supply to bus b1, represents the active power demand of bus b1; represents the reactive power supply to bus b1, represents the reactive power demand of bus b1; P b2,t represents the power flowing through branch b2; P b2.max represents the maximum power flowing through branch b2; V b1,min represents the minimum voltage amplitude at bus b1; V b1,t represents the voltage amplitude at bus b1; V b1',t represents the voltage amplitude at bus b1'; V b1.max represents the maximum voltage amplitude at bus b1; δ b1 represents the voltage phase angle of bus b1; δ b1' represents the voltage phase angle of bus b1'; θ b1b1' represents the voltage phase angle difference between bus b1 and bus b1'.

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