Optimized scheduling method for efficient and stable operation of wind hydrogen storage system integrated with light grid connection strategy

Abstract

The invention provides a wind hydrogen storage system efficient and stable operation optimization scheduling method integrated with a light grid connection strategy, and relates to the technical field of power grids. The method comprises the following steps: S1, generating a multi-element scene model based on historical output data of new energy; s2, based on the load data of the hydrogen production system, determining the operation condition of the electrolytic cell; s3, adapting to a light grid-connected source grid load storage dynamic state, and matching a control strategy; s4, constructing an optimal scheduling model for light grid-connected wind hydrogen storage dynamic matching; s5, generating a multi-element interaction optimal scheduling strategy in a light grid-connected mode based on the optimal scheduling model; and S6, according to the multi-element interaction optimal scheduling strategy, generating an optimal scheduling instruction. By means of the method, efficient utilization of renewable energy sources and efficient operation of a hydrogen production project can be achieved, and meanwhile the hydrogen production cost is reduced.

Description

Technical Field

[0001] The present application relates to the field of power grid technology, and in particular to a method for optimizing the scheduling of efficient and stable operation of a wind hydrogen storage system integrating a light grid-connected strategy. Background Art

[0002] Guided by the "dual carbon" goal, my country is actively promoting the large-scale application of renewable energy, aiming to increase the proportion of clean energy consumption in the energy system to achieve a reduction in greenhouse gas emissions. As the proportion of renewable energy power in the power grid continues to increase, its inherent randomness, volatility and intermittent characteristics make the contradiction of source-load imbalance in time and space increasingly prominent, posing a challenge to the stability and security of the power grid. At the same time, the problem of renewable energy consumption has yet to be solved, which has limited its further development to a certain extent.

[0003] As a key component of the new energy system, hydrogen energy has the properties of clean, low-carbon, flexible and efficient energy, and plays a key role in promoting the replacement of fossil energy in the fields of industry, construction and transportation. At present, provinces across the country have successively issued hydrogen energy development plans, and the multiple renewable energy hydrogen production projects under construction can be divided into two categories: grid-connected and off-grid. The so-called grid-connected renewable energy hydrogen production refers to connecting the renewable energy power generation system to the power grid and taking electricity from the power grid to produce hydrogen. The power grid, as a stable power source, can provide continuous and stable electricity for the hydrogen production system. Off-grid renewable energy hydrogen production refers to the electricity generated by the renewable energy generator set, which is directly provided to the electrolyzer system for hydrogen production without passing through the power grid. It is not restricted by the power grid and capacity, and is more suitable for remote areas or places that cannot access the traditional power grid.

[0004] Regarding the research on off-grid and grid-connected renewable energy hydrogen production technologies, many scholars have achieved a series of results, including research on new energy hydrogen production capacity configuration, research on economic optimization of water electrolysis hydrogen production, research on water electrolysis hydrogen production technology, and research on optimal scheduling of hydrogen production systems considering electricity prices / low carbon.

[0005] However, off-grid renewable energy hydrogen production technology still faces multiple challenges in application. Large-scale, highly volatile new energy power supply will cause the electrolyzer system to start and stop frequently, affecting the efficiency and life of the electrolyzer. When the hydrogen production power is too small, the incomplete water electrolysis process will cause the hydrogen purity to be insufficient, which will increase safety hazards. At the same time, new energy hydrogen production projects often need to be equipped with a certain scale of energy storage, resulting in the project reducing part of the hydrogen production cost in terms of new energy electricity prices, but there are still many problems to be solved in terms of scheduling and overall economy. For grid-connected renewable energy hydrogen production technology, the grid electricity price makes the hydrogen production cost relatively high, and the excessively high proportion of grid electricity hydrogen production will make it difficult to obtain green certification for hydrogen energy. Therefore, it is urgent to explore a light grid-connected hydrogen production technology that can maintain the safe and stable operation of the renewable energy hydrogen production system and meet the downstream production needs and economic requirements. Summary of the invention

[0006] The purpose of the embodiments of the present application is to provide an efficient and stable operation optimization scheduling method for a wind hydrogen storage system integrating a light grid-connected strategy, so as to achieve efficient utilization of renewable energy and efficient operation of hydrogen production projects, while reducing the cost of hydrogen production.

[0007] The present invention provides a method for optimizing the efficient and stable operation of a wind hydrogen storage system integrated with a light grid-connected strategy, the method comprising:

[0008] S1: Generate a multi-scenario model based on historical output data of new energy sources;

[0009] S2: Determine the operating conditions of the electrolyzer based on the load data of the hydrogen production system;

[0010] S3: Adapt to the source-grid-load-storage dynamics of light grid connection and match the control strategy;

[0011] S4: Construct an optimal dispatching model for dynamic matching of light grid-connected wind and hydrogen storage;

[0012] S5: Based on the optimization scheduling model, the optimal scheduling strategy of multi-element interaction in the light grid-connected mode is generated;

[0013] S6: Generate optimized scheduling instructions based on the multi-interaction optimal scheduling strategy.

[0014] In an optional embodiment, in S1, the multivariate scene model is denoted as [p' 1j ,p' 2j ,…,p' ij ] T , p' ij Indicates the wind power output at the jth hour on date i:

[0015] p′ ij =T′ ij ×M′ i

[0016] Where, T' ij represents the forecast result of the future hours of wind power output at the jth hour on the ith date, M' i Indicates the future installed capacity of wind power on date i.

[0017] In an optional embodiment, S1 includes:

[0018] The number of wind power output hours T at the same time on the same date every year in history ij The data set S j Random sampling is performed, 8 samples are selected each time, the maximum and minimum values ​​are removed, and the average value is taken to obtain the forecast result T' of the future hours of wind power output ij .

[0019] In an optional embodiment, S2 includes:

[0020] When the electrolytic cell operating power P el,t In the range of 30% to 110%, no additional start-up and shutdown measures are taken;

[0021] When the electrolytic cell operating power P el,t <30%, stop running immediately until the power returns to the range of 30% to 110%.

[0022] In an optional embodiment, S3 includes:

[0023] Predict p' ij >P el,t , then the remaining electricity in the energy storage is consumed, making the electrolytic cell power P el,t Maintain fluctuations within the range of 30%-110%;

[0024] Predict p' ij <P el,t or p' ij =P el,t , then determine the power fluctuation range of the electrolytic cell: if the electrolytic cell power P el,t Fluctuates within the range of 30%-110%, no additional measures are taken; if p' ij <P el,t And P el,t If the energy storage is less than 30%, the energy storage discharge state is started to maintain the electrolytic cell operating power at 30% of the minimum operating power. If the energy storage cannot maintain the electrolytic cell operating power at 30% of the minimum operating power, the supplementary power G regulated by the energy storage is mobilized. ij Adjust to maintain the electrolytic cell operating power at 30% of the minimum operating power;

[0025] In the preset long time p' ij <Pel,t And P el,t If the power consumption of the electrolytic cell is less than 30%, the electrolytic cell operation will be stopped until the operating power of the electrolytic cell is maintained at 30% of the minimum operating power.

[0026] In an optional embodiment, in S4, the optimization objectives of the optimization scheduling model include maximizing the utilization rate of new energy and minimizing the number of starts and stops of the electrolytic cell.

[0027] In an optional implementation, in S4, the expression for maximizing the utilization rate of new energy is as follows:

[0028]

[0029] Where η is the wind power utilization rate, P el,t is the operating power of the electrolytic cell, G ij is the supplementary power of energy storage regulation, P stc , P std are the charging power and discharging power of the energy storage system at time t, p' ij The wind power output.

[0030] In an optional embodiment, in S4, the expression for the minimum number of starts and stops of the electrolytic cell is as follows:

[0031]

[0032] In the formula, is the number of starts and stops of the electrolytic cell, is the number of electrolytic cell startups, is the number of times the electrolytic cell stops.

[0033] In an optional implementation, in S4, the constraints of the optimization scheduling model include wind turbine output constraints, energy storage device charging and discharging constraints, grid regulation constraints, and hydrogen production system operating power balance constraints.

[0034] In an optional embodiment, S5 includes:

[0035] Based on the optimization scheduling model, multiple scheduling schemes are solved and obtained, and the multi-element interactive optimal scheduling strategy is determined by comparison, wherein the multi-element interactive optimal scheduling strategy includes the energy storage system charging and discharging strategy, the water electrolysis hydrogen production system operation strategy, and the large power grid reactive power regulation strategy.

[0036] The method provided in the embodiment of the present invention is based on the off-grid wind power hydrogen production technology, takes into account a reasonable proportion of energy storage configuration and a small proportion of grid power gap filling or reactive regulation, takes into account the impact of electrolyzer load curve fluctuations on the operating life, and formulates an optimal operation strategy that meets the off-grid water electrolysis hydrogen production load characteristics and safe operation boundaries at different power levels. It can effectively solve the problem of dynamic matching difficulties on both the source and load sides, significantly improve the wind power consumption level, the system hydrogen production efficiency and the safe and stable operation capabilities, and provide technical support for the coordinated green development of the hydrogen energy industry chain. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments of the present application will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0038] Figure 1 A flow chart of a method for optimizing the efficient and stable operation of a wind hydrogen storage system with an integrated light grid-connected strategy provided in an embodiment of the present application;

[0039] Figure 2 Schematic diagram of the technical route of the method for optimizing the efficient and stable operation of a wind hydrogen storage system integrating a light grid-connected strategy provided in an embodiment of the present application. DETAILED DESCRIPTION

[0040] The technical solutions in the embodiments of the present application will be described below in conjunction with the drawings in the embodiments of the present application.

[0041] The embodiment of the present invention proposes an optimized scheduling method for efficient and stable operation of a wind hydrogen storage system that integrates a light grid-connected strategy, aiming to achieve efficient utilization of renewable energy and efficient operation of hydrogen production projects, while reducing the cost of hydrogen production. First, a multivariate scenario model is generated based on the historical output data of new energy, and based on the time characteristics and stability requirements of downstream energy demand, the operating rules of the hydrogen production electrolyzer at different powers are formulated; dynamic interaction characteristics of sources and loads are analyzed, and energy storage device charging and discharging plans and grid regulation plans are formulated, and control ideas for water electrolysis hydrogen production systems under different power boundary conditions are proposed; with the goal of improving the utilization rate of new energy and reducing the loss of electrolyzer operating life, the optimal scheduling plan is formulated by comprehensively considering multiple constraints on system safety, economy, and stable operation.

[0042] Specifically, Figure 1 and Figure 2 The flowcharts and technical route diagrams of the efficient and stable operation optimization scheduling method of the wind hydrogen storage system integrated with the light grid-connected strategy provided in the embodiments of the present application (hereinafter referred to as the method) respectively include the following steps:

[0043] S1: Generate a multi-scenario model based on historical output data of new energy.

[0044] In order to produce "green hydrogen", this embodiment specifies that the main power source in the light grid-connected hydrogen production project is a wind turbine, and the historical output data of the wind turbine is input, which is recorded as the matrix P n×m , that is:

[0045]

[0046] Wherein, n represents the length of time for historical data collection. To ensure the accuracy of subsequent strategy formulation, it is usually required to collect output data for more than 5 years. In this embodiment, n is set to represent the number of days; m represents the time scale within a day. In this embodiment, hourly data is collected every day, that is, m = 1, 2, ..., 24; p ij It represents the wind turbine output power at the jth hour on the i-th date, i=1,2,…,n; j=1,2,…,m.

[0047] Collect the actual installed capacity of wind farms in the same time span to form a data column M = [M 1 ,M 2 ,…,M n ] T , M n represents the actual installed capacity of the wind farm on date n, and solves the number of wind power output hours per day at the hourly level T ij :

[0048]

[0049] Based on T ij Form a data set S j Specifically, the number of wind power output hours T at the same time on the same date every year in history ij The data set S j Random sampling is performed, 8 samples are selected each time, the maximum and minimum values ​​are removed, and the average value is taken to obtain the forecast result T' of the future hours of wind power output ij , T' ij and the future installed capacity of wind power M' i Multiply them to get the wind power output p' ij In this way, multiple samplings can be performed to predict the future hourly wind power output data of the wind farm, forming a multivariate scenario model [p' 1j ,p' 2j ,…,p' ij ] T .

[0050]

[0051] p′ ij =T′ij ×M′ i

[0052] Where, T ij,k Represents each sampling data; T max , T min They represent the maximum and minimum values ​​in 8 samples respectively; k represents the number of samples.

[0053] S2: Determine the operating conditions of the electrolyzer based on the load data of the hydrogen production system.

[0054] The load data of the hydrogen production system includes the energy consumption of hydrogen production by electrolysis of water. The operating conditions of the electrolyzer include that in order to ensure the life and stability of the system, the adaptability of the electrolyzer operating power is limited, and the variation range of the electrolyzer operating power is usually 30%-110%.

[0055] F el，t =Q in，t ×E eq

[0056] Where P el,t represents the operating power of the electrolytic cell at time t; E eq Indicates the energy consumption of hydrogen production by electrolysis of water; Q in,t Indicates the amount of hydrogen entering the hydrogen storage tank at time t.

[0057] The power of hydrogen production by water electrolysis is affected by the downstream hydrogen demand, and the overall performance is:

[0058] Q lan，t =Q tan，t-1 +Q in，t -Q dm，t

[0059] In the formula, Q tan,t Indicates the hydrogen storage capacity of the hydrogen storage tank at time t; Q tan,t-1 Indicates the hydrogen storage capacity of the hydrogen storage tank at time t-1; Q dm,t Represents the hydrogen demand of downstream enterprises at time t.

[0060] Considering that large-scale, highly volatile new energy power supply will cause electrolyzer power fluctuations, which will in turn cause electrolyzer hydrogen production system shutdown and safety hazards, this system is set as follows:

[0061] (1) When the electrolytic cell operating power P el,t In the range of 30% to 110%, no additional start-up and shutdown measures are taken;

[0062] (2) When the electrolytic cell operating power P el,t <30%, stop running immediately until the power returns to within the allowable variation range.

[0063] S3: Adapt to the source-grid-load-storage dynamics of light grid connection and match the control strategy.

[0064] The volatility and randomness of wind power output increase the difficulty of system regulation. A certain scale of energy storage resources in the region has the potential to participate in system regulation and can effectively improve the flexibility of system regulation. The output model of the energy storage system is:

[0065]

[0066] In the formula, SOC t , SOC t-1 are the charge states of the energy storage at time t and t-1 respectively; w 1 、w 2 are the charging efficiency and discharging efficiency of the energy storage device respectively; P stc , P std are the charging power and discharging power of the energy storage system at time t; E sn is the rated capacity of the energy storage device; Δt is the interval time.

[0067] In order to smooth out the volatility and intermittency of renewable energy and ensure the stable and long-term operation requirements of green hydrogen production, the power grid needs to take on a part of the regulation role as a supplementary power for energy storage regulation, denoted as G ij .

[0068] Predict p' ij >P el,t , it is necessary to consume the remaining electricity in the energy storage in advance so that the energy storage charging state can be started when wind power is generated on the same day, so that the power of the electrolyzer can be maintained in the range of 30%-110%.

[0069] Predict p' ij <P el,t or p' ij =P el,t , then determine the power fluctuation range of the electrolytic cell:

[0070] (1) Fluctuation within the range of 30%-110%, no additional measures are taken;

[0071] (2) Within the preset short time p' ij <P el,t And P el,t <30%, start the energy storage discharge state, so that the electrolyzer operating power is maintained at 30% of the minimum operating power (P el,t ×30%, that is, the minimum operating condition of the electrolyzer). If the energy storage cannot meet the minimum operating condition of the electrolyzer, the grid resources (supplementary power G regulated by the energy storage) are mobilized. ij ) to achieve:

[0072] p′ ij +SOCt +C Gj =P el，t ×30%

[0073] (3) Within a preset long time p' ij <P el,t And P el,t <30%, or (2) the minimum operating conditions are still not met, the electrolytic cell operation is stopped until the operating conditions improve.

[0074] S4: Construct an optimized scheduling model for dynamic matching of light grid-connected wind and hydrogen storage.

[0075] The system aims to improve the utilization rate of new energy and reduce the loss of electrolyzer life, so as to achieve efficient and stable operation of wind hydrogen storage system. The maximum utilization rate of new energy means the maximum utilization rate of wind power in wind hydrogen storage projects connected to the light grid, ensuring the production of "green hydrogen". The reduction of electrolyzer life loss is mainly reflected in the minimum number of electrolyzer start-ups and stops, that is, ensuring the stable and efficient operation of the electrolyzer system.

[0076] The wind power utilization rate η refers to the ratio of wind power consumed by the water electrolysis hydrogen production system to the total wind power output. The maximum wind power utilization rate can ensure the lowest hydrogen production cost and the lowest penalty cost for wind and solar power abandonment. The calculation formula is as follows:

[0077]

[0078] Number of electrolytic cell starts and stops The number of electrolytic cell starts and number of stops The sum of the start and stop times can be controlled to be the minimum, which can ensure the lowest start and stop cost of the electrolyzer. The calculation formula is as follows:

[0079]

[0080] Number of electrolytic cell starts and number of stops are all 0-1 variables, that is, if the electrolyzer is switched from the stop state to the start state, the system will Recorded as 1; if the electrolytic cell changes from the start state to the stop state, the system will Recorded as 1.

[0081] To achieve the optimization goal, it is also necessary to consider the output and operation constraints of the light grid-connected wind hydrogen storage system, including wind turbine output constraints, energy storage device charging and discharging constraints, grid regulation constraints, and hydrogen production system operating power balance constraints.

[0082] (1) Wind turbine output constraints

[0083] The output power of the wind turbine is subject to the rated power P W Restrictions: There is an upper limit on wind power output:

[0084] 0≤p' ij ≤P W

[0085] (2) Energy storage device charging and discharging constraints

[0086] The energy storage charge state does not exceed the rated capacity, and charging and discharging are not performed at the same time.

[0087]

[0088] (3) Grid Regulation Constraints

[0089] To ensure the green nature of hydrogen production by water electrolysis, the power grid regulation power does not exceed the maximum value of the capacity design G max , and needs to participate in regulation together with energy storage, and cannot work independently.

[0090]

[0091] (4) Power balance constraints of hydrogen production system operation

[0092] The operation of the water electrolysis hydrogen production system should meet the supply and demand balance and not exceed the maximum daily start and stop times allowed by the design. At the same time, the node voltage must not exceed the limit, that is, the node voltage must not exceed its upper and lower limits.

[0093]

[0094] Where U min , U max , U t They represent the lower limit, upper limit and node voltage at time t respectively; Indicates the maximum number of starts and stops allowed per day for the electrolytic cell.

[0095] (5) Other constraints

[0096] The capacity of the hydrogen storage tank at time t shall not exceed the upper and lower limits specified:

[0097] Q lan，min ≤Q lan，t ≤Q tan，max

[0098] Hydrogen supply reliability constraints:

[0099]

[0100] Where D dm,t Indicates the amount of hydrogen actually supplied to the downstream at time t.

[0101] S5: Based on the optimization scheduling model, the optimal scheduling strategy for multi-element interaction under the light grid-connected mode is generated.

[0102] Combined with the load demand forecast results of the light grid-connected wind turbine with hydrogen storage and the electric hydrogen production system, the operation rules of the water electrolysis hydrogen production system are strictly followed, as well as the system's setting of the energy storage and grid regulation range. Under the multiple constraints of the wind hydrogen storage system, a variety of scheduling schemes are solved. With the ultimate goal of improving the utilization rate of new energy and reducing the loss of electrolyzer operating life, the multi-element interactive optimal scheduling strategy is selected and determined, including the energy storage system charging and discharging strategy, the water electrolysis hydrogen production system operation strategy, and the large power grid reactive power regulation strategy.

[0103] S6: Generate optimized scheduling instructions based on the multi-interaction optimal scheduling strategy.

[0104] Combining the above-mentioned optimal optimization scheduling decision results with the actual operating status of the wind hydrogen storage project, generate optimization scheduling instructions under different operating power conditions, including energy storage charging and discharging control, electrolyzer start and stop control, etc. According to the system feedback mechanism, monitor the execution of instructions in real time and make adjustments when necessary. After all instructions are executed, update the wind turbine output data and the water electrolysis hydrogen production system load data to the database, and start the next day's optimization scheduling plan formulation.

[0105] The beneficial effects of the efficient and stable operation optimization scheduling method of the wind hydrogen storage system integrated with the light grid-connected strategy provided in the embodiment of the present application include:

[0106] This embodiment proposes a light grid-connected mode, which can effectively solve the problems of frequent start and stop of the electrolyzer system, low efficiency of electrolyzer operation, life loss and storage economy caused by the difficulty of dynamic matching between the source and the load in off-grid renewable energy hydrogen production technology, while avoiding the problems of excessive hydrogen production cost and difficulty in green certification of hydrogen energy in grid-connected renewable energy hydrogen production technology. Compared with traditional research, this embodiment comprehensively considers the randomness of wind power output and the actual downstream hydrogen demand, predicts the multi-dimensional output of wind power and the operating power of the electrolyzer, and judges the state and range of energy storage and grid regulation. It proposes the dynamic operation mechanism of the water electrolysis hydrogen production system, formulates a source-grid-load-storage dynamic matching control strategy that is suitable for light grid connection at different power levels, is closer to actual application, and realizes the coordinated operation of source and load under the interaction of multiple subjects such as new energy, energy storage, electrolyzer, and grid. In addition, this embodiment constructs an optimized scheduling model for dynamic matching of light grid-connected wind and hydrogen storage. The optimal operation scheduling scheme solved can not only achieve the highest new energy utilization rate of renewable energy hydrogen production projects, but also achieve the lowest electrolyzer operation life loss, that is, ensure that the electrolyzer system can maintain stable and efficient operation while producing "green hydrogen".

[0107] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0108] In addition, the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0109] Furthermore, the functional modules in the various embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.

[0110] It should be noted that if the function is implemented in the form of a software function module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can essentially be embodied in the form of a software product, or the part that contributes to the prior art or the part of the technical solution. The computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM) random access memory (RAM), disk or optical disk, and other media that can store program codes.

[0111] In this document, relational terms such as first and second, etc. are used merely to distinguish one entity or operation from another entity or operation, but do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0112] The above description is only an embodiment of the present application and is not intended to limit the protection scope of the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for optimizing the efficient and stable operation of a wind hydrogen storage system integrating a light grid-connected strategy, characterized in that: The method comprises: S1: Generate a multi-scenario model based on historical output data of new energy sources; S2: Determine the operating conditions of the electrolyzer based on the load data of the hydrogen production system; S3: Adapt to the source-grid-load-storage dynamics of light grid connection and match the control strategy; S4: Construct an optimal dispatching model for dynamic matching of light grid-connected wind and hydrogen storage; S5: Based on the optimization scheduling model, the optimal scheduling strategy of multi-element interaction in the light grid-connected mode is generated; S6: Generate optimized scheduling instructions based on the multi-interaction optimal scheduling strategy.

2. The method for optimizing the efficient and stable operation of a wind hydrogen storage system with an integrated light grid-connected strategy according to claim 1 is characterized in that: In S1, the multivariate scenario model is denoted as [p' 1j ,p' 2j ,…,p' ij ] T , p' ij Indicates the wind power output at the jth hour on date i: p′ ij =T′ ij ×M′ i Where, T' ij represents the forecast result of the future hours of wind power output at the jth hour on the ith date, M' i Indicates the future installed capacity of wind power on date i.

3. The method for optimizing the efficient and stable operation of a wind hydrogen storage system with an integrated light grid-connected strategy according to claim 2 is characterized in that: S1 includes: The number of wind power output hours T at the same time on the same date every year in history ij The data set S j Random sampling is performed, 8 samples are selected each time, the maximum and minimum values ​​are removed, and the average value is taken to obtain the forecast result T' of the future hours of wind power output ij .

4. The method for optimizing the efficient and stable operation of a wind hydrogen storage system with an integrated light grid-connected strategy according to claim 2 is characterized in that: S2 include: When the electrolytic cell operating power P el,t In the range of 30% to 110%, no additional start-up and shutdown measures are taken; When the electrolytic cell operating power P el,t <30%, stop running immediately until the power returns to the range of 30% to 110%.

5. The method for optimizing the efficient and stable operation of a wind hydrogen storage system with an integrated light grid-connected strategy according to claim 4 is characterized in that S3 include: Predict p' ij >P el,t , then the remaining electricity in the energy storage is consumed, making the electrolytic cell power P el,t Maintain fluctuations within the range of 30%-110%; Predict p' ij <P el,t or p' ij =P el,t , then determine the power fluctuation range of the electrolytic cell: if the electrolytic cell power P el,t Fluctuates within the range of 30%-110%, no additional measures are taken; if p' ij <P el,t And P el,t <30%, the energy storage discharge state is started to maintain the electrolytic cell operating power at 30% of the minimum operating power. If the energy storage cannot maintain the electrolytic cell operating power at 30% of the minimum operating power, the supplementary power G regulated by the energy storage is mobilized. ij Adjust to maintain the electrolytic cell operating power at 30% of the minimum operating power; In the preset long time p' ij <P el,t And P el,t If the power consumption of the electrolytic cell is less than 30%, the electrolytic cell operation will be stopped until the operating power of the electrolytic cell is maintained at 30% of the minimum operating power.

6. The method for optimizing the efficient and stable operation of a wind hydrogen storage system with an integrated light grid-connected strategy according to claim 1 is characterized in that: In S4, the optimization objectives of the optimization scheduling model include maximizing the utilization rate of new energy and minimizing the number of starts and stops of the electrolyzer.

7. The method for optimizing the efficient and stable operation of a wind hydrogen storage system with an integrated light grid-connected strategy according to claim 6 is characterized in that: In S4, the expression for maximum utilization of new energy is as follows: Where η is the wind power utilization rate, P el,t is the operating power of the electrolytic cell, G ij is the supplementary power of energy storage regulation, P stc , P std are the charging power and discharging power of the energy storage system at time t, p' ij The wind power output.

8. The method for optimizing the efficient and stable operation of a wind hydrogen storage system with an integrated light grid-connected strategy according to claim 6 is characterized in that: In S4, the expression for the minimum number of electrolytic cell starts and stops is as follows: In the formula, is the number of starts and stops of the electrolytic cell, is the number of electrolytic cell startups, is the number of times the electrolytic cell stops.

9. The method for optimizing the efficient and stable operation of a wind hydrogen storage system with an integrated light grid-connected strategy according to claim 1 is characterized in that: In S4, the constraints of the optimization scheduling model include wind turbine output constraints, energy storage device charging and discharging constraints, grid regulation constraints, and hydrogen production system operating power balance constraints.

10. The method for optimizing the efficient and stable operation of a wind hydrogen storage system with an integrated light grid-connected strategy according to claim 1, characterized in that S5 include: Based on the optimization scheduling model, multiple scheduling schemes are solved and obtained, and the multi-element interactive optimal scheduling strategy is determined by comparison, wherein the multi-element interactive optimal scheduling strategy includes the energy storage system charging and discharging strategy, the water electrolysis hydrogen production system operation strategy, and the large power grid reactive power regulation strategy.

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