Wind and light load probabilistic balance method considering hydrogen energy two-stage planning

Abstract

The invention belongs to the technical field of wind and light load probability prediction, and particularly discloses a wind and light load probabilistic balance method considering hydrogen energy two-stage planning, comprising the following steps: constructing a joint probability distribution model of wind power, photovoltaic output and load demand, and defining a feasible region; based on a joint probability distribution model of wind power, photovoltaic output and load demand and a feasible region, first-stage hydrogen energy monthly planning is carried out with the goal of minimizing wind-abandoning, light-abandoning and electricity-abandoning quantity; and with minimization of the total cost of the system as a target and with the monthly planning total amount of the first-stage hydrogen energy as a constraint condition, second-stage hydrogen energy hourly scheduling is carried out, and wind and light load probabilistic balance is realized. The problems that the randomness and volatility of wind and light output are not fully considered in an existing method, the wind and light abandoning rate is high, energy waste is serious, system planning and real-time scheduling are usually separated in an existing planning and scheduling method, and dynamic association cannot be established between monthly energy storage configuration and hourly output optimization are solved.

Description

Technical Field

[0001] The present invention belongs to the technical field of wind and solar load probability prediction, and specifically relates to a wind and solar load probabilistic balancing method considering two-stage hydrogen energy planning. Background Art

[0002] With the large-scale grid integration of renewable energy sources such as wind power and photovoltaics, the volatility and intermittency of their output make it difficult to accurately assess system risk using traditional fixed reserve capacity methods. Renewable energy output is significantly affected by weather, and even with advanced forecasting technologies, significant errors can still occur. At the same time, China is strongly advocating for the use of hydrogen energy. As a highly efficient and high-capacity energy storage system, hydrogen energy is an excellent way to balance supply and demand. Traditional deterministic planning can no longer meet the needs of multi-energy complementarity, cross-regional coordination, and extreme event prevention. These factors are collectively driving the power system's transition from deterministic to probabilistic balance, optimizing reserve configuration, scheduling strategies, and investment decisions by quantifying uncertainty.

[0003] However, the existing technology mainly has the following problems: (1) Traditional wind and solar power consumption methods do not fully consider the randomness and volatility of wind and solar power output, resulting in a high wind and solar power abandonment rate and serious energy waste.

[0004] (2) There are different criteria for determining probabilistic equilibrium. Traditional methods include expectation consistency and entropy maximization, but there is a lack of a systematic method to characterize probabilistic equilibrium.

[0005] (3) Existing planning and scheduling methods usually separate system planning from real-time scheduling, and are unable to establish a dynamic relationship between monthly energy storage configuration and hourly output optimization. Summary of the Invention

[0006] The purpose of this invention is to solve the problems that existing methods do not fully consider the randomness and volatility of wind and solar power output, resulting in high wind and solar power curtailment rates and serious energy waste, and that existing planning and scheduling methods usually separate system planning from real-time scheduling and cannot establish a dynamic relationship between monthly energy storage configuration and hourly output optimization. A probabilistic balancing method for wind and solar power loads considering two-stage hydrogen energy planning is proposed.

[0007] The technical solution of the present invention is: a probabilistic balancing method for wind and solar loads considering two-stage planning of hydrogen energy, comprising the following steps: Based on the joint probability distribution model of wind power and photovoltaic power output, the first phase of monthly hydrogen energy planning is carried out with the goal of minimizing the amount of wind, solar and electricity curtailed; With the goal of minimizing the total system cost, the total monthly amount of hydrogen energy obtained from the first-phase monthly hydrogen energy planning will be used as a constraint condition to carry out hourly hydrogen energy scheduling in the second phase to achieve a probabilistic balance of wind and solar loads.

[0008] Preferably, the objective function of the first-stage monthly hydrogen energy planning is to minimize the amount of wind, solar and electricity curtailed throughout the year. The specific formula is:

[0009] in, represents the objective function of the one-stage hydrogen energy monthly planning, represents minimization, Indicates the amount of wind and solar power curtailment at each hour, Represents a unit time interval, Indicates the amount of load shedding hourly, Indicates the month number, Indicates the number of hours in the month, Represents a unit time node.

[0010] Preferably, the constraints of the first-stage monthly hydrogen energy planning include seasonal hydrogen storage model constraints, thermal power model constraints, wind-solar combined output model constraints, and first balance equation constraints; The seasonal hydrogen storage model constraints include the charge change state constraints of each hydrogen energy storage station, the initial storage state constraints of the hydrogen energy storage station, the seasonal energy storage constraints of the hydrogen energy storage station, the limited charging and discharging capacity constraints, and the total cumulative charging and discharging capacity constraints of the hydrogen energy storage station throughout the year.

[0011] Preferably, the charge change state constraints of each hydrogen energy storage station are:

[0012] in, and Respectively expressed in Moment Hydrogen Energy Storage Station State of charge in winter and summer; and Respectively expressed in Moment Hydrogen Energy Storage Station State of charge in winter and summer; and Respectively expressed in Moment Hydrogen Energy Storage Station Changes in energy storage between winter and summer; Indicates the charging and discharging efficiency of energy storage; the number of hydrogen storage stations to be built; The initial storage capacity state constraint of the hydrogen energy storage station is specifically formulated as follows:

[0013] in, and Respectively represent the hydrogen energy storage station at time 0 State of charge in winter and summer; Indicates the maximum value; Indicates the amount of hydrogen stored at the last moment of winter; The specific formula for seasonal energy storage constraints of hydrogen energy storage stations is:

[0014] in, Indicates the total length of the month; The charge and discharge capacity limit constraint is:

[0015] in, Indicates the storage limit of a single energy storage site; The total cumulative charge and discharge volume of the hydrogen energy storage station throughout the year is constrained as follows: ; The thermal power model constraints are:

[0016]

[0017]

[0018]

[0019] in, and It is a thermal power unit The minimum and maximum output values, Indicates thermal power Always make an effort, It is the hourly output of thermal power. Indicates thermal power unit exist The effort of each moment, For thermal power units The ratio of the maximum uphill and downhill climbs; It is a thermal power unit The maximum installed capacity of and It is a thermal power unit Uptime and downtime, and It is a thermal power unit Minimum startup time and minimum downtime, is the spare capacity of each thermal power unit, is the total spare capacity; The constraints of the wind-solar combined output model are:

[0020]

[0021] in, and yes The planned output dispatch values ​​of wind power and photovoltaic power at the moment; and yes Real-time wind power and photovoltaic power output forecast; The first equilibrium equation constraint is:

[0022] in, express Load demand at any moment.

[0023] Preferably, the Wind power and photovoltaic power forecast at the moment and Together they conform to the joint probability distribution:

[0024] in, represents the probability, Represents wind power, Represents photovoltaic, represents the differential symbol, Indicates the feasible region. When the actual output of wind power and photovoltaic power falls into the feasible region When the system is balanced, Indicates the upper and lower limits of other flexibility resources. Denote the probability density function by, Indicates the actual output of wind power. Indicates the actual photovoltaic output.

[0025] Preferably, the objective function of the second stage hydrogen energy hourly scheduling is to minimize the overall system operating cost, which includes operating cost, investment cost, wind and solar power curtailment cost, and load loss cost; The expression of the objective function of the second stage hydrogen energy hourly scheduling is:

[0026] in, represents the objective function of the second-stage hydrogen energy hourly scheduling, represents the investment cost, represents the operating cost, represents the cost of curtailed wind and solar power generation, Represents the load loss cost.

[0027] As a preference, the investment cost for:

[0028]

[0029] Where, 、 、 、 and They are the unit capacity investment costs of thermal power, renewable energy, water electrolysis device, energy storage device and fuel cell device; represents the capital recovery coefficient, represents the annual interest rate, is the average lifetime of the system, 、 、 、 and Represent the installed capacity of thermal power, renewable energy, water electrolysis device, energy storage device and fuel cell device respectively; The running costs Including fuel costs , unit operating depreciation cost and startup costs , specifically:

[0030]

[0031]

[0032]

[0033] in, is the fuel cost of thermal power units, Indicates the total time, Indicates the number of thermal power units, Indicates the unit; 、 、 、 、 They are the unit capacity operating costs of thermal power, renewable energy, water electrolysis device, energy storage device and fuel cell device; represents the startup cost of thermal power units, is a 0-1 variable corresponding to the startup state; The cost of curtailing wind and solar power Specifically:

[0034]

[0035] in, represents the unit curtailment cost of wind and solar power, Indicates unit time wind turbines The amount of abandoned wind, Indicates unit time Photovoltaic units The amount of abandoned light, Indicates the amount of wind and solar power curtailment at each hour; The load loss cost Specifically:

[0036] in, Represents the unit loss of load cost.

[0037] Preferably, the constraints for hourly scheduling of hydrogen energy in the second stage include the monthly planned total amount of hydrogen energy in the first stage, water electrolysis model constraints, hydrogen storage tank constraints, hydrogen fuel cell constraints and second balance equation constraints.

[0038] Preferably, the water electrolysis model constraints are specifically:

[0039]

[0040]

[0041] in, 、 Respectively The power consumption and hydrogen production capacity of hydrogen production at each moment; represents the efficiency of hydrogen production from electricity; Indicates the electricity-hydrogen unit conversion factor; Indicates the lower calorific value of hydrogen combustion; represents the conversion coefficient, Indicates the maximum hydrogen production capacity; The hydrogen storage tank constraints are specifically:

[0042]

[0043]

[0044]

[0045] in, and Respectively represent the charging and discharging power of the hydrogen storage tank; and 0-1 state variables representing the charging and discharging of the hydrogen storage tank respectively; Indicates the maximum power of the hydrogen storage tank; Indicates the capacity of the hydrogen storage tank; Indicates the maximum capacity of the hydrogen storage tank; Indicates the initial capacity of the hydrogen storage tank; and are the charging and discharging efficiency of the hydrogen storage tank respectively; Represents unit interval time; The hydrogen fuel cell constraints are specifically:

[0046]

[0047] in, Indicates the discharge power of hydrogen fuel cells; is the efficiency of hydrogen-to-electricity; is the electricity-hydrogen unit conversion factor; is the hydrogen consumption; is the maximum output power of the hydrogen fuel cell; The second equilibrium equation constraint is specifically:

[0048] in, Indicates thermal power output value, and yes The planned output dispatch value of wind power and photovoltaic power at the moment, Indicates the amount of wind and solar power curtailment at each hour, express The load demand at any moment, Indicates the hourly load shedding amount.

[0049] The beneficial effects of the present invention are: 1. By adopting a two-stage planning method combined with probabilistic modeling, the present invention can effectively reduce the wind and solar power curtailment rate, maximize the absorption capacity of wind and solar energy, and achieve optimal management of these uncertain energy sources, thereby significantly improving the stability and reliability of the system.

[0050] 2. This invention innovatively establishes a tight coupling relationship between monthly planning and hourly scheduling, ensuring the spatiotemporal consistency of hydrogen energy storage and real-time output strategies, while also enhancing the power system's ability to cope with short-term fluctuations and long-term changes.

[0051] 3. The present invention adopts a method that combines probabilistic load forecasting with dynamic hydrogen energy scheduling, pursuing optimal economic benefits throughout the entire life cycle while ensuring system stability, thereby promoting the effective use of clean energy and the efficient operation of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 The figure shows a flow chart of a probabilistic balancing method for wind and solar loads considering two-stage planning of hydrogen energy. DETAILED DESCRIPTION

[0053] The exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be understood that the embodiments shown and described in the accompanying drawings are merely exemplary and are intended to illustrate the principles and spirit of the present invention, rather than to limit the scope of the present invention.

[0054] Example 1: like Figure 1 As shown, a probabilistic balancing method for wind and solar loads considering two-stage hydrogen energy planning includes the following steps: S1. Based on the joint probability distribution model of wind power and photovoltaic power output, the first phase of monthly hydrogen energy planning is carried out with the goal of minimizing the amount of wind, solar and electricity curtailed; S2. With the goal of minimizing the total system cost, the total monthly amount of hydrogen energy obtained from the first-phase monthly hydrogen energy planning is used as a constraint condition to carry out hourly hydrogen energy scheduling in the second phase to achieve a probabilistic balance between wind and solar loads.

[0055] In the first phase, based on a probabilistic forecast model for wind power, photovoltaic power, and load demand, monthly hydrogen storage capacity was optimized with the goal of minimizing wind, photovoltaic, and power curtailment. This phase, through precise probabilistic analysis, ensured that the energy storage system's capacity could effectively cope with the volatility of wind and solar power output, thereby maximizing the utilization of renewable energy.

[0056] In the second phase, the present invention focuses on optimizing the economics of system operation. Specifically, it develops an hourly hydrogen output strategy with the goal of minimizing overall system operating costs. This phase fully considers real-time changes in wind speed, light intensity, and load fluctuations, and combines the dynamic response characteristics of the hydrogen storage system to achieve efficient energy management and allocation. Furthermore, by establishing a coupling relationship between monthly planning and hourly scheduling, this approach addresses the disconnect between long-term planning and short-term scheduling in traditional approaches.

[0057] In this embodiment, the source load uncertainty in the new energy power system usually includes wind and solar loads and electricity loads. Wind and solar loads are usually related to weather factors, and electricity loads are usually related to the electricity usage habits of different users. On a certain basis, electricity loads can be intervened by human factors, while the output of wind and solar loads cannot be intervened by humans and can be predicted based on past historical data. However, no matter how many data sets are used in this prediction, there will always be a deviation value between the predicted output and the actual output, depending on the specific prediction method used.

[0058] Wind power output conforms to the Weibull distribution, and photovoltaic output conforms to Distribution, electricity demand can be stabilized under intervention, so the net load can be expressed as:

[0059] Where, is the net load, The electricity demand, and are the outputs of wind power and photovoltaic power respectively, and their outputs have load-specific probability distributions.

[0060] Therefore, the net load can also be represented by a probability distribution to represent its output characteristics. However, under this method, the probability distribution of the net load output at each moment is independent of each other, resulting in the probability distribution function at each moment being discontinuous. Therefore, this method is less feasible.

[0061] Therefore, it is necessary to establish a joint probability distribution function of wind and light. The joint probability distribution function is a mathematical tool that describes the probability distribution of multiple random variables taking values ​​at the same time. It can characterize the probability of multiple random events occurring together. Its joint probability distribution function can be expressed as:

[0062] in, Indicates the A random event, represents the probability density of the nth random event; The joint probability density function is calculated The probability of falling within a certain region R, Indicates the value of the x-axis, Represents the value on the y-axis, and the joint probability density function needs to be integrated over this area:

[0063]

[0064] The feasible region of the joint probability density is defined as D. When the output falls within region D, the power can be balanced. When it falls outside region D, it is considered unbalanced. Therefore, the probability of power imbalance can be expressed as:

[0065] At the same time, the imbalance probability It consists of two parts: the probability of wind and solar power abandonment , and the probability of power abandonment , and It can also be expressed as:

[0066]

[0067]

[0068] Therefore, to determine whether the system can meet the power and electricity balance, it is only necessary to observe whether the output falls within the feasible domain D. The integral of the feasible domain can reflect the probability of power and electricity balance.

[0069] In this embodiment, since the present invention involves a wind and solar system, combined with the theory of probability balance of electric power in the above part, the first phase of monthly hydrogen energy planning is started for hydrogen energy. The present invention treats hydrogen energy as hydropower, utilizes its good liquid storage characteristics, and uses seasonal hydrogen storage to realize the transfer of electric energy. Hydrogen energy is regarded as an energy that can be adjusted across seasons. Therefore, the planning result that needs to be obtained in the first phase is the total monthly storage capacity of hydrogen energy.

[0070] The objective function of the first phase of hydrogen energy monthly planning is to minimize the amount of wind, solar and electricity curtailment throughout the year. The specific formula is:

[0071] in, represents the objective function of the one-stage hydrogen energy monthly planning, represents minimization, Indicates the amount of wind and solar power curtailment at each hour, Represents a unit time interval, Indicates the amount of load shedding hourly, Indicates the month number, Indicates the number of hours in the month, Represents a unit time node.

[0072] The constraints of the objective function of the first phase of hydrogen energy monthly planning include: Seasonal hydrogen storage model constraints: The charge change state constraints of each hydrogen energy storage station are:

[0073] in, and Respectively expressed in Moment Hydrogen Energy Storage Station State of charge in winter and summer; and Respectively expressed in Moment Hydrogen Energy Storage Station State of charge in winter and summer; and Respectively expressed in Moment Hydrogen Energy Storage Station Changes in energy storage between winter and summer; Indicates the charging and discharging efficiency of energy storage; the number of hydrogen storage stations to be built; The initial storage capacity state constraint of the hydrogen energy storage station is the initial storage capacity of the hydrogen energy storage station. At the beginning of winter, the storage capacity is 0. At the beginning of summer, the storage capacity is equal to the storage capacity of the last month of winter. The specific formula is:

[0074] in, and Respectively represent the hydrogen energy storage station at time 0 State of charge in winter and summer; Indicates the maximum value; Indicates the amount of hydrogen stored at the last moment of winter; The seasonal energy storage constraint of the hydrogen energy storage station is to charge in winter and discharge in summer. The specific formula is:

[0075] in, Indicates the total length of the month; The charge and discharge capacity constraints are:

[0076] in, Indicates the storage limit of a single energy storage site; The total annual charge and discharge volume of the hydrogen energy storage station is constrained to 0: ; The constraints of the thermal power model are:

[0077]

[0078]

[0079]

[0080] in, and It is a thermal power unit The minimum and maximum output values, Indicates thermal power Always make an effort, It is the hourly output of thermal power. Indicates thermal power unit exist The effort of each moment, For thermal power units The ratio of the maximum uphill and downhill climbs; It is a thermal power unit The maximum installed capacity of and It is a thermal power unit Uptime and downtime, and It is a thermal power unit Minimum startup time and minimum downtime, is the spare capacity of each thermal power unit, is the total spare capacity.

[0081] Constraints of the wind and solar combined output model Conventional wind and solar power output models usually determine the maximum installed capacity of wind and solar power with reference to the historical wind and solar power curve. The output of wind and solar power usually fluctuates around the historical curve and has strong uncertainty.

[0082]

[0083]

[0084] in, and yes The planned output dispatch values ​​of wind and solar power at the current moment; and yes Always downwind, only predict output.

[0085] at this time, and Together they conform to a joint probability distribution, which is a variable value, and its probability density function is expressed as To express it, its probability can be expressed as:

[0086] in, represents the probability, Represents wind power, Represents photovoltaic, represents the differential symbol, Indicates the feasible region. When the actual output of wind power and photovoltaic power falls into the feasible region When the system is balanced, Denote the probability density function by, Indicates the actual output of wind power. Represents the actual output of photovoltaic power, based on which the backup capacity of other flexible resources is considered It can affect the wind and solar power output, and its probability can be expressed as:

[0087] in, It is the upper and lower limits for adjusting other flexibility resources.

[0088] The predicted output values ​​of wind power and photovoltaic power can be expressed as expectations:

[0089]

[0090] in, and Represent the predicted output values ​​of wind power and photovoltaic power respectively.

[0091] The first equilibrium equation constraint is:

[0092] in, express Load demand at any moment.

[0093] In this embodiment, the monthly planned total hydrogen energy volume is solved in the first phase, which serves as the constraint for the second phase. The hourly hydrogen energy scheduling in the second phase will carefully characterize the hydrogen energy model. The objective function of the second phase is the total cost of the entire new energy system.

[0094] The objective function of the second stage is expressed as operating cost + investment cost + wind and solar curtailment cost + load loss cost, and the expression is:

[0095] in, represents the objective function of the second-stage hydrogen energy hourly scheduling, represents the investment cost, represents the operating cost, represents the cost of curtailed wind and solar power generation, Represents the load loss cost.

[0096] The investment cost for:

[0097]

[0098] Where, 、 、 、 and They are the unit capacity investment costs of thermal power, renewable energy, water electrolysis device, energy storage device and fuel cell device; represents the capital recovery coefficient, represents the annual interest rate, is the average life of the system, which is about 20 years, 、 、 、 and They represent the installed capacity of thermal power, renewable energy, water electrolysis equipment, energy storage equipment and fuel cell equipment respectively.

[0099] The running costs Including fuel costs , unit operating depreciation cost and startup costs , specifically:

[0100]

[0101]

[0102]

[0103] in, is the fuel cost of thermal power units, Indicates the total time, Indicates the number of thermal power units, Indicates the unit; 、 、 、 、 They are the unit capacity operating costs of thermal power, renewable energy, water electrolysis device, energy storage device and fuel cell device; represents the startup cost of thermal power units, is a 0-1 variable corresponding to the startup state; The cost of curtailing wind and solar power Specifically:

[0104]

[0105] in, represents the unit curtailment cost of wind and solar power, Indicates unit time wind turbines The amount of abandoned wind, Indicates unit time Photovoltaic units The amount of abandoned light, Indicates the amount of wind and solar power curtailment at each hour; The load loss cost Specifically:

[0106] in, Represents the unit loss of load cost.

[0107] In the same phase as the other equipment models in the second phase, the constraints of the hydrogen energy storage system model were re-characterized. The constraints for the hourly hydrogen scheduling in the second phase included the monthly planned total hydrogen energy in the first phase, the constraints of the water electrolysis model, the constraints of the hydrogen storage tank, the constraints of the hydrogen fuel cell, and the constraints of the second equilibrium equation.

[0108] Water electrolysis model constraints: The most common method for producing hydrogen through electricity is proton exchange membrane electrolysis (PEM). Of course, there are other solutions, but the principles are the same. The specific constraints of the water electrolysis model are:

[0109]

[0110]

[0111] in, 、 Respectively The power consumption and hydrogen production capacity of hydrogen production at each moment; represents the efficiency of hydrogen production from electricity; Indicates the electricity-hydrogen unit conversion factor; Indicates the lower calorific value of hydrogen combustion; represents the conversion coefficient, Indicates the maximum hydrogen production capacity; Hydrogen storage tank constraints: The hydrogen storage system is similar to a conventional energy storage system. It has only one charging or discharging state at a time. Its constraints are expressed as:

[0112]

[0113]

[0114]

[0115] in, and Respectively represent the charging and discharging power of the hydrogen storage tank; and 0-1 state variables representing the charging and discharging of the hydrogen storage tank respectively; Indicates the maximum power of the hydrogen storage tank; Indicates the capacity of the hydrogen storage tank; Indicates the maximum capacity of the hydrogen storage tank; Indicates the initial capacity of the hydrogen storage tank; and are the charging and discharging efficiency of the hydrogen storage tank respectively; Represents unit interval time; Hydrogen fuel cell constraints: Hydrogen fuel cells are the same as traditional fuel cells, except for the internal medium. Their constraints are:

[0116]

[0117] in, Indicates the discharge power of hydrogen fuel cells; is the efficiency of hydrogen-to-electricity; is the electricity-hydrogen unit conversion factor; is the hydrogen consumption; is the maximum output power of the hydrogen fuel cell; The second equilibrium equation constraint is specifically:

[0118] in, Indicates thermal power output value, and yes The planned output dispatch value of wind power and photovoltaic power at the moment, Indicates the amount of wind and solar power curtailment at each hour, express The load demand at any moment, Indicates the hourly load shedding amount.

[0119] Those skilled in the art will appreciate that the embodiments described herein are intended to help readers understand the principles of the present invention, and it should be understood that the scope of protection of the present invention is not limited to such specific descriptions and embodiments. Those skilled in the art can make various other specific variations and combinations based on the technical teachings disclosed in the present invention without departing from the essence of the present invention, and such variations and combinations are still within the scope of protection of the present invention.

Claims

1. A probabilistic balancing method for wind and solar loads considering two-stage planning of hydrogen energy, characterized by: The following steps are involved: Based on the joint probability distribution model of wind power and photovoltaic power output, the first phase of monthly hydrogen energy planning is carried out with the goal of minimizing the amount of wind, solar and electricity curtailed; With the goal of minimizing the total system cost, the total monthly amount of hydrogen energy obtained from the first-phase monthly hydrogen energy planning will be used as a constraint condition to carry out hourly hydrogen energy scheduling in the second phase to achieve a probabilistic balance of wind and solar loads.

2. The wind and solar load probabilistic balancing method considering two-stage hydrogen energy planning according to claim 1 is characterized in that: The objective function of the first phase of hydrogen energy monthly planning is to minimize the amount of wind, solar and electricity curtailment throughout the year. The specific formula is: in, represents the objective function of the one-stage hydrogen energy monthly planning, represents minimization, Indicates the amount of wind and solar power curtailment at each hour, Represents a unit time interval, Indicates the amount of load shedding hourly, Indicates the month number, Indicates the number of hours in the month, Represents a unit time node.

3. The wind and solar load probabilistic balancing method considering two-stage hydrogen energy planning according to claim 1 is characterized in that: The constraints of the first phase of hydrogen energy monthly planning include seasonal hydrogen storage model constraints, thermal power model constraints, wind and solar combined output model constraints, and the first balance equation constraints; The seasonal hydrogen storage model constraints include the charge change state constraints of each hydrogen energy storage station, the initial storage state constraints of the hydrogen energy storage station, the seasonal energy storage constraints of the hydrogen energy storage station, the limited charging and discharging capacity constraints, and the total cumulative charging and discharging capacity constraints of the hydrogen energy storage station throughout the year.

4. The wind and solar load probabilistic balancing method considering two-stage hydrogen energy planning according to claim 3 is characterized in that: The charge change state constraints of each hydrogen energy storage station are: in, and Respectively expressed in Moment Hydrogen Energy Storage Station State of charge in winter and summer; and Respectively expressed in Moment Hydrogen Energy Storage Station State of charge in winter and summer; and Respectively expressed in Moment Hydrogen Energy Storage Station Changes in energy storage between winter and summer; Indicates the charging and discharging efficiency of energy storage; the number of hydrogen storage stations to be built; The initial storage capacity state constraint of the hydrogen energy storage station is specifically formulated as follows: in, and Respectively represent the hydrogen energy storage station at time 0 State of charge in winter and summer; Indicates the maximum value; Indicates the amount of hydrogen stored at the last moment of winter; The specific formula for seasonal energy storage constraints of hydrogen energy storage stations is: in, Indicates the total length of the month; The charge and discharge capacity limit constraint is: in, Indicates the storage limit of a single energy storage site; The total cumulative charge and discharge volume of the hydrogen energy storage station throughout the year is constrained as follows: ； The thermal power model constraints are: in, and It is a thermal power unit The minimum and maximum output values, Indicates thermal power Always make an effort, It is the hourly output of thermal power. Indicates thermal power unit exist The effort of each moment, For thermal power units The ratio of the maximum uphill and downhill climbs; It is a thermal power unit The maximum installed capacity of and It is a thermal power unit Uptime and downtime, and It is a thermal power unit Minimum startup time and minimum downtime, is the spare capacity of each thermal power unit, is the total spare capacity; The constraints of the wind-solar combined output model are: in, and yes The planned output dispatch values ​​of wind power and photovoltaic power at the moment; and yes Real-time wind power and photovoltaic power output forecast; The first equilibrium equation constraint is: in, express Load demand at any moment.

5. The wind and solar load probabilistic balancing method considering two-stage hydrogen energy planning according to claim 4 is characterized in that: described Wind power and photovoltaic power forecast at the moment and Together they conform to the joint probability distribution: in, represents the probability, Represents wind power, Represents photovoltaic, represents the differential symbol, Indicates the feasible region. When the actual output of wind power and photovoltaic power falls into the feasible region When the system is balanced, Indicates the upper and lower limits of other flexibility resources. Denote the probability density function by, Indicates the actual output of wind power. Indicates the actual photovoltaic output.

6. The wind and solar load probabilistic balancing method considering two-stage hydrogen energy planning according to claim 1 is characterized in that: The objective function of the second-stage hourly hydrogen energy scheduling is to minimize the overall system operating cost, which includes operating cost, investment cost, wind and solar power curtailment cost, and load loss cost; The expression of the objective function of the second stage hydrogen energy hourly scheduling is: in, represents the objective function of the second-stage hydrogen energy hourly scheduling, represents the investment cost, represents the operating cost, represents the cost of curtailed wind and solar power generation, Represents the load loss cost.

7. The wind and solar load probabilistic balancing method considering two-stage hydrogen energy planning according to claim 6 is characterized in that: The investment cost for: Where, 、 、 、 and They are the unit capacity investment costs of thermal power, renewable energy, water electrolysis device, energy storage device and fuel cell device; represents the capital recovery coefficient, represents the annual interest rate, is the average lifetime of the system, 、 、 、 and Represent the installed capacity of thermal power, renewable energy, water electrolysis device, energy storage device and fuel cell device respectively; The running costs Including fuel costs , unit operating depreciation cost and startup costs , specifically: in, is the fuel cost of thermal power units, Indicates the total time, Indicates the number of thermal power units, Indicates the unit; 、 、 、 、 They are the unit capacity operating costs of thermal power, renewable energy, water electrolysis device, energy storage device and fuel cell device; represents the startup cost of thermal power units, is a 0-1 variable corresponding to the startup state; The cost of curtailing wind and solar power Specifically: in, represents the unit curtailment cost of wind and solar power, Indicates unit time wind turbines The amount of abandoned wind, Indicates unit time Photovoltaic units The amount of abandoned light, Indicates the amount of wind and solar power curtailment at each hour; The load loss cost Specifically: in, Represents the unit loss of load cost.

8. The wind and solar load probabilistic balancing method considering two-stage hydrogen energy planning according to claim 1 is characterized in that: The constraints for the hourly scheduling of hydrogen energy in the second phase include the monthly planned total amount of hydrogen energy in the first phase, water electrolysis model constraints, hydrogen storage tank constraints, hydrogen fuel cell constraints and the second balance equation constraints.

9. The wind and solar load probabilistic balancing method considering two-stage hydrogen energy planning according to claim 8 is characterized in that: The constraints of the water electrolysis model are specifically: in, 、 Respectively The power consumption and hydrogen production capacity of hydrogen production at each moment; represents the efficiency of hydrogen production from electricity; Indicates the electricity-hydrogen unit conversion factor; Indicates the lower calorific value of hydrogen combustion; represents the conversion coefficient, Indicates the maximum hydrogen production capacity; The hydrogen storage tank constraints are specifically: in, and Respectively represent the charging and discharging power of the hydrogen storage tank; and 0-1 state variables representing the charging and discharging of the hydrogen storage tank respectively; Indicates the maximum power of the hydrogen storage tank; Indicates the capacity of the hydrogen storage tank; Indicates the maximum capacity of the hydrogen storage tank; Indicates the initial capacity of the hydrogen storage tank; and are the charging and discharging efficiency of the hydrogen storage tank respectively; Represents unit interval time; The hydrogen fuel cell constraints are specifically: in, Indicates the discharge power of hydrogen fuel cells; is the efficiency of hydrogen-to-electricity; is the electricity-hydrogen unit conversion factor; is the hydrogen consumption; is the maximum output power of the hydrogen fuel cell; The second equilibrium equation constraint is specifically: in, Indicates thermal power output value, and yes The planned output dispatch value of wind power and photovoltaic power at the moment, Indicates the amount of wind and solar power curtailment at each hour, express The load demand at any moment, Indicates the hourly load shedding amount.

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