Micro-grid electric-hydrogen hybrid energy storage operation optimization method, system, device and medium

Abstract

The present application relates to the technical field of micro-grid management, and discloses a micro-grid electric-hydrogen hybrid energy storage operation optimization method, system, device and medium, electrolyzer mother array rated power of an electrolyzer mother array of a target micro-grid is acquired; an electric-hydrogen energy storage coupling management strategy is constructed according to the relationship among real-time net power of the target micro-grid, the electrolyzer mother array rated power and current storage power of an electrochemical energy storage device; a hybrid energy storage double-layer optimization model is constructed, the minimum annual total cost of the target micro-grid is taken as an objective function of an upper-layer optimization model, and the minimum hydrogen energy storage device flatized energy storage cost is taken as an objective function of a lower-layer optimization model; the hybrid energy storage double-layer optimization model is solved according to the output result of the electric-hydrogen energy storage coupling management strategy, an electric-hydrogen hybrid energy storage operation optimization strategy is obtained, and the target micro-grid is controlled to execute the electric-hydrogen hybrid energy storage operation optimization strategy. The method improves renewable energy consumption rate, system operation efficiency and stability.

Description

Technical Field

[0001] This invention relates to the field of microgrid management technology, and in particular to a method, system, equipment and medium for optimizing the operation of microgrid hybrid electric-hydrogen energy storage. Background Technology

[0002] The production and consumption of renewable energy exhibit a significant inverse spatial distribution, a structural contradiction that directly leads to severe wind and solar power curtailment, severely hindering the efficient utilization and large-scale development of renewable energy. To address this challenge, microgrids, as small-scale power generation and distribution systems integrating distributed power sources, energy storage systems, and local loads, have emerged. They enable autonomous coordination and optimized management of energy within a local area, providing a crucial system platform for the local consumption of renewable energy. Among these, energy storage systems, as key supporting units for microgrid operation, play an irreplaceable role in mitigating fluctuations in renewable energy output and balancing supply and demand due to their unique bidirectional regulation characteristics, becoming an important means of promoting the efficient utilization of renewable energy.

[0003] Among numerous energy storage technologies, hydrogen energy storage systems demonstrate significant advantages in large-scale, long-term energy storage applications due to their rich diversity in structure, storage methods, and energy conversion and utilization pathways. However, hydrogen energy storage systems still face many limitations in practical applications: relatively low energy conversion efficiency leads to significant energy loss; and slow response speed makes it difficult to meet the rapid adjustment needs of power systems. Therefore, a single hydrogen energy storage technology cannot fully adapt to the diversified operational needs of power systems. To compensate for the shortcomings of a single hydrogen energy storage technology, electro-hydrogen hybrid energy storage technology has gradually attracted attention. This technology aims to combine the advantages of fast response speed of electro-energy storage and long storage time of hydrogen energy storage, improving the overall performance of the system through synergistic operation. However, currently, the synergistic operation relationship between electrochemical energy storage and hydrogen energy storage in electro-hydrogen hybrid energy storage remains at a simple series-sequential adjustment level. That is, after the previous stage completes the initial adjustment, the next stage continues to supplement the adjustment. This extensive coupling mode has obvious defects: due to the unreasonable synergistic scheduling between electrochemical energy storage and hydrogen energy storage, power curtailment is prone to occur, resulting in energy waste, reduced system operating efficiency, and seriously affecting the overall stability and service life of the energy storage system.

[0004] Therefore, optimizing the synergistic operation of electrochemical energy storage and hydrogen energy storage in microgrid hybrid energy storage has become a technical problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0005] This invention provides a method, system, equipment, and medium for optimizing the operation of microgrid electro-hydrogen hybrid energy storage, in order to solve the technical problem of how to optimize the synergistic operation relationship between electrochemical energy storage and hydrogen energy storage in microgrid electro-hydrogen hybrid energy storage, thereby optimizing the synergistic operation mechanism of electrochemical energy storage and hydrogen energy storage in the microgrid electro-hydrogen hybrid energy storage system and improving the renewable energy absorption rate, system operating efficiency, and stability.

[0006] In a first aspect, the present invention provides a method for optimizing the operation of a microgrid with hybrid electro-hydrogen energy storage, applicable to a target microgrid composed of an electrolyzer array, an electrochemical energy storage device, and a hydrogen energy storage device, the method comprising:

[0007] Obtain the rated power of the electrolytic cell array of the target microgrid, wherein the parameters of the electrolytic cell array are matched to the electrical energy processed in different frequency ranges;

[0008] Based on the relationship between the real-time net power of the target microgrid, the rated power of the electrolyzer bus array, and the current storage power of the electrochemical energy storage device, an electro-hydrogen energy storage coupling management strategy is constructed. The electro-hydrogen energy storage coupling management strategy is set to reflect the operating conditions of the electrolyzer bus array, the charging and discharging state of the electrochemical energy storage device, and the combustion state of the hydrogen energy storage device.

[0009] A hybrid energy storage two-layer optimization model is constructed for the target microgrid. The hybrid energy storage two-layer optimization model is set to minimize the annual total cost of the target microgrid as the upper-layer objective function of the upper-layer optimization model, and minimize the levelized cost of the hydrogen energy storage device as the lower-layer objective function of the lower-layer optimization model.

[0010] Based on the output results of the implementation of the electric-hydrogen energy storage coupled management strategy on the target microgrid, the hybrid energy storage two-layer optimization model is solved to obtain the electric-hydrogen hybrid energy storage operation optimization strategy of the target microgrid;

[0011] Control the target microgrid to execute the electric-hydrogen hybrid energy storage operation optimization strategy.

[0012] Secondly, the present invention also provides a microgrid electro-hydrogen hybrid energy storage operation optimization system, which realizes the microgrid electro-hydrogen hybrid energy storage operation optimization method described above, and is applied to a target microgrid composed of an electrolyzer mother array, an electrochemical energy storage device, and a hydrogen energy storage device. The system includes: an electrolyzer mother array data acquisition module, an electro-hydrogen energy storage coupling management strategy construction module, a hybrid energy storage two-layer optimization model construction module, an optimization strategy acquisition module, and an operation optimization module.

[0013] The electrolytic cell mother array data acquisition module is used to obtain the rated power of the electrolytic cell mother array of the target microgrid, and the parameters of the electrolytic cell mother array are matched with the electrical energy processed in different frequency ranges;

[0014] The electro-hydrogen energy storage coupling management strategy construction module is used to construct an electro-hydrogen energy storage coupling management strategy based on the relationship between the real-time net power of the target microgrid, the rated power of the electrolyzer mother array, and the current storage power of the electrochemical energy storage device. The electro-hydrogen energy storage coupling management strategy is set to reflect the operating conditions of the electrolyzer mother array, the charging and discharging state of the electrochemical energy storage device, and the combustion state of the hydrogen energy storage device.

[0015] The hybrid energy storage two-layer optimization model construction module is used to construct the hybrid energy storage two-layer optimization model of the target microgrid. The hybrid energy storage two-layer optimization model is set to take the minimum annual total cost of the target microgrid as the upper-layer objective function of the upper-layer optimization model and the minimum levelized energy storage cost of the hydrogen energy storage device as the lower-layer objective function of the lower-layer optimization model.

[0016] The optimization strategy acquisition module is used to solve the hybrid energy storage two-layer optimization model based on the output result of executing the electric-hydrogen energy storage coupling management strategy on the target microgrid, so as to obtain the electric-hydrogen hybrid energy storage operation optimization strategy of the target microgrid.

[0017] The operation optimization module is used to control the target microgrid to execute the electric-hydrogen hybrid energy storage operation optimization strategy.

[0018] Thirdly, the present invention also provides a computer device, the computer device including a memory, a processor and a transceiver, which are connected to each other via a bus; the memory is used to store a set of computer program instructions and data, and to transmit the stored data to the processor, the processor executing the computer program instructions stored in the memory to execute the above-described microgrid electric-hydrogen hybrid energy storage operation optimization method.

[0019] Fourthly, the present invention also provides a computer-readable storage medium storing a computer program, which, when run, implements the above-described microgrid hydrogen-electric hybrid energy storage operation optimization method.

[0020] This application provides a method, system, equipment, and medium for optimizing the operation of microgrid hybrid electric-hydrogen energy storage. Compared with the prior art, the beneficial effects of the embodiments of this application are as follows:

[0021] This application discloses a method for optimizing the operation of microgrid hybrid electro-hydrogen energy storage, focusing on the coupling relationship between electrochemical energy storage and hydrogen energy storage. It considers an electro-hydrogen energy storage coupling management strategy that integrates electrolyzer arrays and energy management strategies, effectively reducing the impact of fluctuating renewable energy output on electrolyzers and improving economic efficiency and energy management effectiveness. By setting up electrochemical energy storage devices, low-pressure hydrogen storage tanks, and high-pressure hydrogen storage tanks, energy transfer across multiple time scales is achieved, adjusting the system's intraday and cross-seasonal source-load imbalances, reducing wind and solar curtailment, and ensuring load supply. By establishing a hybrid energy storage two-layer optimization model, the annual total cost and LCHS of the microgrid are optimized, enabling the determination of the optimal configuration capacity and operation scheme for hybrid energy storage, balancing high utilization and low cost. The alkaline water electrolyzer subarray and proton exchange membrane electrolyzer subarray used have better hydrogen production effects than single-type electrolyzers and large-capacity electrolyzers. When the capacity ratio of the two types of electrolyzers is 3:1, both green hydrogen production and system economics can be balanced. The energy management strategy proposed in this invention optimizes the complementary mechanism of electrochemical energy storage and hydrogen energy storage, and improves the dynamic operating characteristics of the electrolyzer through the charging and discharging of BT. Attached Figure Description

[0022] Figure 1 This is a schematic diagram of the steps of a microgrid electric-hydrogen hybrid energy storage operation optimization method provided in a preferred embodiment of the present invention;

[0023] Figure 2 This is a preferred embodiment of the present invention showing the relationship between the hydrogen production efficiency and the input power of the electrolyzer.

[0024] Figure 3 This is a schematic diagram of photovoltaic output in a target microgrid provided by a preferred embodiment of the present invention;

[0025] Figure 4 This is a schematic diagram of wind power output in a target microgrid provided by a preferred embodiment of the present invention;

[0026] Figure 5 This is a schematic diagram of the electrical load power in a target microgrid provided by a preferred embodiment of the present invention;

[0027] Figure 6 This is a schematic diagram of the hydrogen load power in a target microgrid provided by a preferred embodiment of the present invention;

[0028] Figure 7 This is a schematic diagram of the result of real-time net power time series decomposition provided in a preferred embodiment of the present invention;

[0029] Figure 8 This is a schematic diagram of low-frequency and high-frequency components provided in a preferred embodiment of the present invention;

[0030] Figure 9This is a schematic diagram of the seasonal component of historical net power provided in a preferred embodiment of the present invention;

[0031] Figure 10 This is a schematic diagram of the net energy output of hydrogen energy storage in a preferred embodiment of the present invention, showing the hybrid energy storage dual-layer optimization model and the single-layer optimization model.

[0032] Figure 11 This is a schematic diagram of the total annual cost (expressed as negative profit) and hydrogen production of a target microgrid under different configuration capacity ratios provided in a preferred embodiment of the present invention;

[0033] Figure 12 This is a schematic diagram comparing the output power of a 1800kW ALK large electrolytic cell and a 600kW PEM large electrolytic cell, which are equivalent to the capacity optimization results, according to a preferred embodiment of the present invention.

[0034] Figure 13 This is a schematic diagram of the operating conditions of a hydrogen energy storage device based on an electro-hydrogen energy storage coupling management strategy provided in a preferred embodiment of the present invention.

[0035] Figure 14 This is a schematic diagram of the operating conditions of a hydrogen energy storage device based on a conventional energy management strategy provided in a preferred embodiment of the present invention;

[0036] Figure 15 This is a schematic diagram of the operating conditions of an electrochemical energy storage device with an electro-hydrogen energy storage coupling management strategy provided in a preferred embodiment of the present invention;

[0037] Figure 16 This is a schematic diagram of the operating conditions of an electrochemical energy storage device based on a conventional energy management strategy provided in a preferred embodiment of the present invention;

[0038] Figure 17 This is a schematic diagram of the structure of a microgrid electric-hydrogen hybrid energy storage operation optimization system provided in a preferred embodiment of the present invention;

[0039] Figure 18 This is an internal structural diagram of the computer device in an embodiment of the present invention;

[0040] Figure label:

[0041] 1-Electrolyzer mother array data acquisition module, 2-Electro-hydrogen energy storage coupling management strategy construction module, 3-Hybrid energy storage dual-layer optimization model construction module, 4-Optimization strategy acquisition module, 5-Operation optimization module. Detailed Implementation

[0042] The embodiments of the present invention are described in detail below with reference to the accompanying drawings. The embodiments are provided for illustrative purposes only and should not be construed as limiting the scope of the invention. The accompanying drawings are for reference and illustration only and do not constitute a limitation on the scope of protection of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of this invention.

[0043] Please see Figure 1 The diagram illustrates the steps of a microgrid electro-hydrogen hybrid energy storage operation optimization method. In an embodiment of the present invention, a microgrid electro-hydrogen hybrid energy storage operation optimization method is provided, applied to a target microgrid composed of an electrolyzer bus array, an electrochemical energy storage device, and a hydrogen storage device. The method includes:

[0044] S1. Obtain the rated power of the electrolyzer array of the target microgrid, wherein the parameters of the electrolyzer array are matched to the electrical energy processed in different frequency ranges; In a preferred embodiment of this application, the electro-hydrogen hybrid energy storage of the microgrid involves an electrochemical energy storage device and a hydrogen energy storage device. The electrochemical energy storage device uses a battery to store energy, and the hydrogen energy storage device includes an electrolyzer, a hydrogen storage unit, and a hydrogen fuel cell. In the target microgrid, for electrolyzers, an electrolyzer master array is constructed based on the requirements of different types of electrolyzers for input power, amplitude range, and fluctuation range. The parameters of the electrolyzer master array are matched to the power processed in different frequency ranges. In a preferred embodiment of this application, it includes at least: an alkaline water electrolyzer subarray (ALK subarray) and a proton exchange membrane electrolyzer subarray (PEM subarray). The alkaline water electrolyzers in the alkaline water electrolyzer subarray are inexpensive, but have a narrow power range, poor fluctuation adaptability, and high power quality requirements, making them suitable for processing low-frequency power. The proton exchange membrane electrolyzers in the proton exchange membrane electrolyzer subarray have fast response capabilities and a wide power range, enabling efficient processing of high-frequency power, but they are expensive. Combining the low-frequency processing capability of the alkaline water electrolyzer subarray with the high-frequency response characteristics of the proton exchange membrane electrolyzer subarray enables efficient utilization of renewable energy fluctuations.

[0045] The target microgrid of this application includes renewable energy, electrical load, and hydrogen load. Renewable energy includes photovoltaic power generation systems, wind power generation systems, biomass power generation systems, and hydropower generation systems. In this application, photovoltaic power generation systems and wind power generation systems are used as examples for illustration. Since the electrolyzer mother array includes alkaline water electrolyzer sub-arrays and proton exchange membrane electrolyzer sub-arrays, different frequency ranges include at least a first power range and a second frequency range. The VMD algorithm (variable mode decomposition) is used to decompose the power to be processed by the electrolyzer mother array into a time series. The first power is decomposed into a trend component, a periodic component, and two fluctuation components. The trend component and periodic component are low-frequency components, and the fluctuation components are high-frequency components. The power of the low-frequency component changes slowly but has a large amplitude, while the power of the high-frequency component fluctuates greatly but has a small amplitude. The low-frequency component is suitable for alkaline water electrolyzer sub-array processing, and the high-frequency component is suitable for proton exchange membrane electrolyzer array processing. Therefore, this application inputs the electrical energy of the first power range obtained by superimposing and merging the trend component and the periodic component into the alkaline water electrolyzer subarray, and inputs the electrical energy of the second power range obtained by superimposing and merging the two fluctuation components into the proton exchange membrane electrolyzer subarray, so as to electrolyze the low-frequency component and the high-frequency component respectively, convert the electrical energy into hydrogen energy for storage, and realize the efficient utilization of the fluctuation power of renewable energy.

[0046] In a preferred embodiment of this application, the mathematical expression for the operation of the electrolytic cell mother array is as follows:

[0047]

[0048] in, express The input power of the electrolytic cell mother array at any given time. express The input power of the alkaline water electrolysis cell subarray at any given time. express The input power of the proton exchange membrane electrolyzer subarray at any given time. This indicates the hydrogen production efficiency of the alkaline water electrolyzer subarray. This indicates the hydrogen production efficiency of the proton exchange membrane electrolyzer subarray. express The total amount of hydrogen produced by the electrolyzer array at any given time. This represents the lower heating value of hydrogen, taken as 0.033 MWh / kg.

[0049] like Figure 2 The figure shows the relationship between hydrogen production efficiency and input power for alkaline water electrolyzer subarrays and proton exchange membrane electrolyzer subarrays. Figure 2It is known that the hydrogen production efficiency and input power of both the alkaline water electrolyzer subarray and the proton exchange membrane electrolyzer subarray exhibit a nonlinear relationship. To simplify the calculation, in the preferred embodiment of this application, the relationship between the hydrogen production efficiency and input power of the alkaline water electrolyzer subarray and the proton exchange membrane electrolyzer subarray is fitted using the piecewise linear function shown below:

[0050]

[0051]

[0052] in, This indicates the rated power of the alkaline water electrolysis cell subarray. This indicates the rated power of the proton exchange membrane electrolyzer subarray.

[0053] In a preferred embodiment of this application, a long- and short-term collaborative cascaded hydrogen storage tank model based on typical seasonal scenarios is proposed. The renewable energy, electrical load, and hydrogen load of a microgrid system exhibit significant fluctuations, and these fluctuations are seasonal. Therefore, this application divides the target microgrid into a high-energy season, a low-energy season, and a normal-energy season based on the historical power data corresponding to the renewable energy, electrical load, and hydrogen load obtained from the target microgrid. The historical power data includes historical photovoltaic power generation, historical wind power generation, and historical electrical load power, with a time granularity of daily. The VMD algorithm is used to perform time series decomposition on the historical photovoltaic power generation, historical wind power generation, and historical electrical load power respectively. The historical net power data is obtained by subtracting the trend component of the historical electrical load power from the sum of the trend components of the historical photovoltaic power generation and historical wind power generation. The historical net power data is statistically calculated based on the monthly average net power to obtain the monthly average net power. The monthly average net power is then sorted by size, and the historical net power is divided into high, medium, and low intervals using quantiles, corresponding to the high-energy season, low-energy season, and normal-energy season of the target microgrid, respectively. Considering the long time spans of the abundant energy season, the dry energy season, and the normal energy season, and the difficulty in directly and efficiently solving the long-short-term collaborative cascade hydrogen storage tank model, the K-centroid clustering algorithm is used to aggregate the historical net power of the abundant energy season, the dry energy season, and the normal energy season according to the proportion of the duration, corresponding to several typical energy state days. The typical energy state days include at least: typical days of the abundant energy season, typical days of the dry energy season, and typical days of the normal energy season.

[0054] In a preferred embodiment of this application, the hydrogen storage unit includes a low-pressure hydrogen storage tank and a high-pressure hydrogen storage tank, respectively addressing storage needs on short-term and long-term timescales. Furthermore, a long-term hydrogen energy storage operation model is constructed based on the high-energy season, low-energy season, and normal-energy season. The high-pressure hydrogen storage tank employs an operation strategy of "filling hydrogen during the high-energy season, releasing hydrogen during the low-energy season, and storing hydrogen during the normal-energy season" to achieve cross-quarter energy transfer. A short-term hydrogen energy storage operation model is constructed by employing the collaborative operation relationship between the low-pressure hydrogen storage tank and the electrochemical energy storage device. This model controls the operating status of the low-pressure hydrogen storage tank. The short-term hydrogen energy storage operation model utilizes efficient electricity-hydrogen-electricity conversion to smooth out intraday fluctuations in renewable energy and improve the energy utilization rate of the target microgrid. The long- and short-term collaborative cascaded hydrogen storage tank models with different timescales can effectively solve the time mismatch problem of renewable energy supply and demand.

[0055] The low-pressure hydrogen storage tank in the short-term hydrogen energy storage operation model is used for intraday hydrogen storage. It can perform rapid hydrogen charging and discharging on an hourly basis to cope with the uncertain output of renewable energy. When the target microgrid has surplus power, the excess electricity is used to produce hydrogen by electrolyzing water through the electrolyzer array and then stored. When the target microgrid experiences a power deficit, the hydrogen in the low-pressure hydrogen storage tank is converted into electricity through a hydrogen fuel cell to supplement the energy gap. The mathematical expression equation for the low-pressure hydrogen storage tank in the short-term hydrogen energy storage operation model is as follows:

[0056]

[0057]

[0058]

[0059] in, express The hydrogen storage capacity of the low-pressure hydrogen storage tank at all times. express The hydrogen storage capacity of the low-pressure hydrogen storage tank at all times. express The amount of hydrogen input to the low-pressure hydrogen storage tank at all times. express The amount of hydrogen output from the low-pressure hydrogen storage tank at all times. express The charging status of the low-pressure hydrogen storage tank at all times. express The discharge state of the low-pressure hydrogen storage tank is displayed at all times; 1 indicates the presence of the state, and 0 indicates its absence. This indicates the charging efficiency of the low-pressure hydrogen storage tank. This indicates the discharge efficiency of the low-pressure hydrogen storage tank.

[0060] The high-pressure hydrogen storage tank in the long-term hydrogen energy storage operation model is used for seasonal hydrogen storage on a monthly cycle, with few cycles per year. To simplify calculations, the high-pressure hydrogen storage tank is designed to be filled with hydrogen during the high-energy season and released during the low-energy season to address the supply and demand imbalance of renewable energy between seasons. The mathematical equation for the high-pressure hydrogen storage tank in the long-term hydrogen energy storage operation model is as follows:

[0061]

[0062]

[0063]

[0064] in, express The hydrogen storage capacity of the high-pressure hydrogen storage tank at all times. express The hydrogen storage capacity of the high-pressure hydrogen storage tank at all times. express The amount of hydrogen input to the high-pressure hydrogen storage tank at all times. express The amount of hydrogen output from the high-pressure hydrogen storage tank at all times. express Monitor the charging status of the high-pressure hydrogen storage tank at all times. express The discharge state of the high-pressure hydrogen storage tank is recorded at all times; 1 indicates the presence of the state, and 0 indicates its absence. This indicates the charging efficiency of the high-pressure hydrogen storage tank. This indicates the discharge efficiency of the high-pressure hydrogen storage tank.

[0065] The mathematical equations for the operation of a hydrogen fuel cell are as follows:

[0066]

[0067] in, express The output power of the hydrogen fuel cell at all times This indicates the conversion efficiency of the hydrogen fuel cell. express The amount of hydrogen input to the hydrogen fuel cell at any given time.

[0068] For electrochemical energy storage devices that use batteries to store electrical energy, the mathematical equation for battery operation is as follows:

[0069]

[0070]

[0071]

[0072] in, express The battery's stored capacity is constantly monitored. express The battery's stored capacity is constantly monitored. This indicates the battery's self-loss rate. express The charging power of the battery at all times. express The discharge power of the storage battery at all times. express Monitor the battery's charging status at all times. express The battery's discharge state is constantly monitored; a value of 1 indicates the presence of the state, while a value of 0 indicates its absence. Indicates the charging efficiency of the battery. This indicates the discharge efficiency of the battery.

[0073] S2. Based on the relationship between the real-time net power of the target microgrid, the rated power of the electrolyzer bus array, and the current storage power of the electrochemical energy storage device, an electro-hydrogen energy storage coupling management strategy is constructed. The electro-hydrogen energy storage coupling management strategy is set to reflect the operating conditions of the electrolyzer bus array, the charging and discharging state of the electrochemical energy storage device, and the combustion state of the hydrogen energy storage device. In a preferred embodiment of this application, based on the real-time operating power and the rated operating power of the electrolyzer bus array, the operating conditions of the electrolyzer bus array are divided into overload operating conditions, stable operating conditions, low-power operating conditions, and rotating operating conditions. The operating conditions include: overload operation, where the alkaline water electrolyzer subarray and the proton exchange membrane electrolyzer subarray can operate at 100%~120% of their rated power for a short period; stable operation, where the alkaline water electrolyzer subarray operates stably at 30%~100% of its rated power and the proton exchange membrane electrolyzer subarray operates stably at 10%~100% of its rated power; low power operation, where the alkaline water electrolyzer subarray operates at 30% of its rated power and the proton exchange membrane electrolyzer subarray operates at 10% of its rated power; and rotating operation, where only a preset number of electrolyzers in either the alkaline water electrolyzer subarray or the proton exchange membrane electrolyzer subarray are in operation at any given time. After every preset time period, the electrolyzers in operation are numbered and rotated in an orderly manner, allowing the electrolyzers to exchange their operating states sequentially, thus ensuring that the operating time of each electrolyzer is as balanced as possible. The preset time period is the minimum allowable downtime and continuous unstable operation time of the electrolyzer. Specifically, the alkaline water electrolyzer subarray and the proton exchange membrane electrolyzer subarray are numbered sequentially from 1 to n. In low-power operation, only the electrolyzers numbered 1 to m are in operation. After every preset time period, the numbers of the electrolyzers in operation are shifted to the next position, so that the electrolyzers exchange their working states sequentially. This avoids a single electrolyzer operating in an unstable state for a long time and extends the service life of the electrolyzer array.

[0074] In a preferred embodiment of this application, real-time power data of the target microgrid is obtained. This real-time power data includes real-time renewable energy input power, real-time electrical load power, and real-time hydrogen load power, with a time granularity of daily. Further, based on the real-time power data, real-time net power is obtained. Real-time net power is the difference between real-time renewable energy input power and real-time electrical load power. The expression for real-time net power is:

[0075]

[0076] in, express Real-time net power express Real-time power generation of photovoltaic power generation equipment express Real-time power generation of wind power generation equipment express Real-time electrical load power.

[0077] Real-time net power is used to initially determine the supply and demand balance of the system, identify the operating conditions of the electrolyzer main array, the charging and discharging status of the electrochemical energy storage device, and the combustion status of the hydrogen fuel cell in the hydrogen energy storage device. Based on the relationship between the real-time net power of the target microgrid, the rated power of the electrolyzer main array, and the current storage power of the electrochemical energy storage device, an electro-hydrogen energy storage coupling management strategy is constructed. This strategy prioritizes hydrogen energy storage, supplemented by electrochemical energy storage, while also considering increasing green hydrogen production and achieving unbalanced energy transfer. Specifically, when the real-time net power is greater than or equal to a first preset multiple of the rated power of the electrolyzer main array, the target microgrid is in a first electro-hydrogen energy storage coupling state. This first state is defined as the electrolyzer main array operating under overload conditions and the electrochemical energy storage device charging. The charging amount of the electrochemical energy storage device is the remaining real-time net power after electrolysis by the electrolyzer main array.

[0078] Right now

[0079] in, This indicates the first preset multiple.

[0080] At this point, the real-time net power is very high. Even if all electrolyzers operate at their rated power, some power will still remain unconsumed. Although the electrolyzers can operate under overload conditions for a short period, this will lead to problems such as shortened equipment lifespan, decreased operating efficiency, and increased safety risks. In this situation, the first electro-hydrogen energy storage coupling state puts all electrolyzers under overload operation while operating at their rated power. The excess power is stored by the electrochemical energy storage device. The operation of the electrolyzer mother array and the electrochemical energy storage device is represented as follows:

[0081]

[0082] in, express The input power of the alkaline water electrolyzer at time 1. express The input power of the alkaline water electrolyzer at time number 2. express Time number is The input power of the alkaline water electrolyzer, express The input power of the proton exchange membrane electrolyzer at time number 1. express The input power of the proton exchange membrane electrolyzer at time number 2. express Time number is The input power of the proton exchange membrane electrolyzer. Indicates the first number of alkaline water electrolysis cells. This indicates the second number of proton exchange membrane electrolyzers.

[0083] When the real-time net power is greater than or equal to the rated power of the electrolyzer mother array by a second preset multiple and less than the rated power of the electrolyzer mother array by a first preset multiple, a second electro-hydrogen energy storage coupling state is established. The second electro-hydrogen energy storage coupling state is set so that the electrolyzer mother array is in a stable operating condition and the electrochemical energy storage device is in a storage capacity maintenance state. Specifically:

[0084] Right now

[0085] in, Indicates the second preset multiple, and .

[0086] At this point, the real-time net power is relatively high, sufficient to maintain all electrolyzers in stable operating conditions. To balance the operating status and duration of the electrolyzers, the net power is evenly distributed based on the number of electrolyzers, while the storage capacity of the electrochemical energy storage device remains unchanged. The operation of the electrolyzer array and the electrochemical energy storage device is represented as follows:

[0087]

[0088] in, express Low-voltage component of net power at all times express The high-voltage component of the net power at all times.

[0089] When the real-time net power is greater than or equal to zero and less than the rated power of the electrolyzer mother array by a second preset multiple, a third electro-hydrogen energy storage coupling state is established. This third electro-hydrogen energy storage coupling state is defined as the operating condition of the electrolyzer mother array and the charging / discharging state of the electrochemical energy storage device being jointly determined by the real-time net power and the current storage power of the electrochemical energy storage device. Specifically:

[0090] Right now

[0091] At this point, the real-time net power is low and cannot support all electrolyzers to operate under stable conditions. In order to keep as many electrolyzers as possible running continuously, the operating conditions of the electrolyzers are changed by utilizing the power stored in the electrochemical energy storage device. It is necessary to determine the operating conditions of the electrolyzer mother array and the charging and discharging state of the electrochemical energy storage device based on the sum of the real-time net power and the current stored power of the electrochemical energy storage device, including the following three situations:

[0092] ① When the sum of the real-time net power and the current storage power of the electrochemical energy storage device is greater than the rated power of the electrolytic cell array by a second preset multiple, the electrolytic cell array is in a low-power operating condition and the electrochemical energy storage device is in a discharging state. Specifically:

[0093] Right now

[0094] At this time, the electrochemical energy storage device has a large amount of stored power. When the electrochemical energy storage device discharges, the sum of its power and the real-time net power can ensure that each electrolyzer operates at low power, avoiding shutdown. The operation of the electrolyzer mother array and the electrochemical energy storage device at this time is represented as follows:

[0095]

[0096] ② When the sum of the real-time net power and the current storage power of the electrochemical energy storage device is less than the rated power of the electrolytic cell array by a second preset multiple but greater than or equal to the minimum operating power of the electrolytic cell array, the electrolytic cell array is in a rotating operation mode and the electrochemical energy storage device is in a discharging state. Specifically:

[0097] Right now

[0098] At this point, the sum of the current stored power and real-time net power of the electrochemical energy storage device only supports the continuous operation of a portion of the electrolyzers. Therefore, the electrolyzer mother array is in a rotating operation mode and the electrochemical energy storage device is in a discharging state. Hydrogen production power is input sequentially according to the electrolyzer numbers; electrolyzers with later numbers will shut down. Assume that the final number of alkaline water electrolyzers in operation is... The number of proton exchange membrane electrolyzers in operation is Then, the operation of the electrolytic cell array and the electrochemical energy storage device at this time can be represented as follows:

[0099]

[0100] in, express Time number is The input power of the alkaline water electrolyzer, express Time number is The input power of the alkaline water electrolyzer, express Time number is The input power of the proton exchange membrane electrolyzer. express Time number is Input power of the proton exchange membrane electrolyzer.

[0101] ③ When the sum of the real-time net power and the electrochemical storage power of the electrochemical energy storage device is less than the minimum operating power, the electrolytic cell array is in a shutdown state and the electrochemical energy storage device is in a charging state. Specifically:

[0102] Right now

[0103] At this time, the current storage power of the electrochemical energy storage device is also relatively low. The sum of the current storage power and the real-time net power of the electrochemical energy storage device is insufficient to support the continuous operation of some electrolyzers. Therefore, all electrolyzers are in a shutdown state, and the real-time net power is absorbed by the electrochemical energy storage device. The operation of the electrolyzer mother array and the electrochemical energy storage device at this time is represented as follows:

[0104]

[0105] When the real-time net power is less than zero, a fourth electro-hydrogen energy storage coupling state is constructed. This fourth electro-hydrogen energy storage coupling state is set so that the charge / discharge state of the electrochemical energy storage device and the combustion state of the hydrogen fuel cell in the hydrogen energy storage device are jointly determined by the current storage power of the electrochemical energy storage device and the distribution network electricity price. Based on the current storage power of the electrochemical energy storage device and the distribution network electricity price, the charge / discharge state of the electrochemical energy storage device and the combustion state of the hydrogen fuel cell in the hydrogen energy storage device are determined, including the following three cases:

[0106] ①In

[0107] At this time, the electrochemical energy storage device has stored electrochemical energy that can be used to regulate power. The device preferentially uses its current stored power for discharge. The discharge of the electrochemical energy storage device at this time is represented as follows:

[0108]

[0109] ②In

[0110] At this point, since the electrochemical energy storage device has no adjustable power, it is considered to use hydrogen fuel cells to burn hydrogen from the hydrogen storage tank or to purchase electricity from the distribution network to ensure the power supply of the target microgrid.

[0111] When the corresponding time-of-use electricity price is a non-peak price, there is a lot of energy waste in converting hydrogen from the hydrogen storage tank into electricity by burning hydrogen fuel cells. Therefore, electricity is directly purchased from the distribution network to supply the target microgrid, and the hydrogen fuel cells of the hydrogen energy storage device are in an open circuit state.

[0112] When the corresponding time-of-use electricity price is the peak price, hydrogen from the hydrogen storage tank in the hydrogen fuel cell is used to power the target microgrid first. Among them, the low-pressure hydrogen storage tank is discharged first, followed by the high-pressure hydrogen storage tank.

[0113] This application proposes a coupled management strategy for electro-hydrogen energy storage with different real-time net power, setting appropriate operating conditions for the electrolyzer array, appropriate charge and discharge states for the electrochemical energy storage device, and appropriate combustion states for the hydrogen fuel cell. This effectively enhances the complementarity between the electrochemical energy storage device and the hydrogen storage device, improves the consumption of renewable energy, and increases the production of green hydrogen.

[0114] S3. Construct a hybrid energy storage two-layer optimization model for the target microgrid. The hybrid energy storage two-layer optimization model is set with the minimum annual total cost of the target microgrid as the upper-layer objective function of the upper-layer optimization model, and the minimum levelized cost of the hydrogen energy storage device as the lower-layer objective function of the lower-layer optimization model. In a preferred embodiment of this application, considering the mutual influence between the hydrogen energy storage device and the electrochemical energy storage device, a hybrid energy storage two-layer optimization model is constructed. The hybrid energy storage two-layer optimization model includes an upper-layer optimization model and a lower-layer optimization model. The minimum annual total cost of the target microgrid is used as the upper-layer objective function of the upper-layer optimization model. The annual total cost includes equipment investment cost, operation and maintenance cost, electricity purchase cost, hydrogen purchase cost, and curtailment penalty cost. The annual total cost is then expressed as:

[0115]

[0116]

[0117]

[0118]

[0119]

[0120]

[0121]

[0122]

[0123]

[0124]

[0125] in, This represents the total annual cost of the target microgrid. This represents the total annual cost of the electrolytic cell array. This represents the total annual cost of a hydrogen fuel cell. This indicates the total annual cost of the low-pressure hydrogen storage tank. This represents the total annual cost of the high-pressure hydrogen storage tank. This represents the total annual cost of an electrochemical energy storage device. This represents the electricity purchase cost of the target microgrid. This represents the hydrogen purchase cost of the target microgrid. This represents the cost of curtailment penalty for the target microgrid. This indicates the capacity configuration of the electrolytic cell array. Indicates the investment recovery factor. This represents the unit investment cost of the electrolytic cell array. This represents the unit operation and maintenance cost of the electrolytic cell array. Indicates the capacity configuration of the hydrogen fuel cell. This indicates the unit investment cost of hydrogen fuel cells. This indicates the unit operation and maintenance cost of hydrogen fuel cells. This indicates the capacity configuration of the low-pressure hydrogen storage tank. This indicates the unit investment cost of the low-pressure hydrogen storage tank. This indicates the unit operation and maintenance cost of the low-pressure hydrogen storage tank. This indicates the capacity configuration of the high-pressure hydrogen storage tank. This indicates the unit investment cost of the high-pressure hydrogen storage tank. This indicates the unit operation and maintenance cost of the high-pressure hydrogen storage tank. Indicates the capacity configuration of the electrochemical energy storage device. This indicates the unit investment cost of an electrochemical energy storage device. This indicates the unit operation and maintenance cost of electrochemical energy storage devices. Indicates the discount rate. Indicates equipment Service life of equipment This includes electrolyzer arrays, hydrogen fuel cells, low-pressure hydrogen storage tanks, high-pressure hydrogen storage tanks, and electrochemical energy storage devices. Indicates the system operating cycle. express The power purchased from the distribution network at all times express Electricity purchase price at all times express The amount of hydrogen purchased at any given time. express The price of hydrogen purchased at any time express The amount of wind and solar power curtailed at any given time. express Price of penalties for abandoning electricity at any time.

[0126] In the preferred embodiment of this application, the minimum levelized cost of hydrogen energy storage is taken as the lower-level objective function of the lower-level optimization model. The levelized cost of hydrogen energy storage refers to the ratio of the total cost of the hydrogen energy storage device to the cumulative energy transmitted over its entire life cycle. The levelized cost of hydrogen energy storage can quantify the discounted cost per unit discharge of hydrogen energy storage technology and is a standardized basis for evaluating the economics of hydrogen energy storage technology. The levelized cost of hydrogen energy storage is expressed as:

[0127]

[0128]

[0129] in, This represents the levelized cost of hydrogen energy storage. This indicates the actual energy released by the hydrogen energy storage device. This represents the hydrogen load power of the target microgrid.

[0130] For the lower-level optimization model, the following constraints apply:

[0131] The device input / output constraints are as follows:

[0132]

[0133] in, Indicates equipment exist Input / output power at any given time Indicates equipment The actual installed capacity.

[0134] The equipment ramping power constraint is:

[0135]

[0136] in, For equipment climbing power, For equipment The lower limit of climbing power. For equipment The upper limit of climbing power.

[0137] The power balance constraint is:

[0138]

[0139] The hydrogen power balance constraint is:

[0140]

[0141] Electricity purchase constraints are:

[0142]

[0143] in, The maximum power purchase capacity of the target microgrid.

[0144] Hydrogen purchase constraints are:

[0145]

[0146] in, The maximum amount of externally purchased hydrogen for the target microgrid.

[0147] S4 solves the hybrid energy storage bilayer optimization model based on the output results of the electro-hydrogen energy storage coupling management strategy applied to the target microgrid to obtain the electro-hydrogen hybrid energy storage operation optimization strategy for the target microgrid. In a preferred embodiment of this application, based on the electro-hydrogen energy storage coupling management strategy, the output results are obtained, including the operating conditions of the electrolyzer mother array, the charge / discharge status of the electrochemical energy storage device, and the combustion status of the hydrogen fuel cell. Based on the operating conditions, charge / discharge status, and combustion status, the upper-level optimization model of the hybrid energy storage bilayer optimization model is solved to obtain the capacity configuration of the electrolyzer mother array, the capacity configuration of the electrochemical energy storage device, and the capacity configuration of the hydrogen fuel cell. Based on the capacity configuration of the electrolyzer mother array, the capacity configuration of the electrochemical energy storage device, and the capacity configuration of the hydrogen fuel cell, the lower-level optimization model of the hybrid energy storage bilayer optimization model is solved to obtain the electro-hydrogen hybrid energy storage operation optimization strategy, which includes: the operating power of the electrolyzer mother array, the charge / discharge power of the electrochemical energy storage device, and the combustion power of the hydrogen fuel cell.

[0148] In the simulation environment of this application, Figure 3 The diagram shows the photovoltaic output in the target microgrid. Figure 4 The diagram shows the wind power output in the target microgrid. Figure 5 The diagram shows the electrical load power in the target microgrid. Figure 6 The diagram shows the hydrogen load power in the target microgrid. The parameters of the target microgrid are shown in Tables 1 and 2.

[0149] The single-unit capacity of the alkaline water electrolyzer subarray and the proton exchange membrane electrolyzer subarray is 0.2MW, and the time-of-use electricity price is shown in Table 3.

[0150] Table 1

[0151]

[0152] Table 2

[0153]

[0154] Table 3

[0155]

[0156] Taking the real-time net power of the first week as an example, Figure 7 The diagram shows the results of real-time net power time series decomposition. IMF1 represents the trend component, IMF2 represents the periodic component, IMF3 represents the first fluctuation component, and IMF4 represents the second fluctuation component. Based on the characteristics of different decomposed signals, low-frequency and high-frequency components are reconstructed and used as subarrays for alkaline water electrolyzers and proton exchange membrane electrolyzers, respectively. Figure 8 The diagram shows the low-frequency and high-frequency components.

[0157] Figure 9 The diagram shows the seasonal components of historical net power. Figure 9 It can be seen that the seasonal fluctuations in wind power, photovoltaic power and electricity load caused by seasonal changes result in a positive total net power of the system from March to October, and a negative total net power from January to February and November to December. Therefore, March and July to November are the normal energy seasons, April to June are the high energy seasons, and January to February and December are the low energy seasons.

[0158] Based on this classification, the three types of seasons are proportionally grouped into four typical days. Typical day 1 and typical day 3 are the average energy season, typical day 2 is the high energy season, and typical day 4 is the low energy season.

[0159] The microgrid electricity-hydrogen hybrid energy storage operation optimization method of this application is compared and analyzed with different schemes, and the following 5 schemes are set:

[0160] Case 1: The microgrid electro-hydrogen hybrid energy storage operation optimization method of this application includes an electrochemical energy storage device, a low-pressure hydrogen storage tank and a high-pressure hydrogen storage tank.

[0161] Case 2: The energy storage device only includes electrochemical energy storage devices and does not include low-pressure hydrogen storage tanks and high-pressure hydrogen storage tanks.

[0162] Case 3: The energy storage device includes an electrochemical energy storage device and a low-pressure hydrogen storage tank, but does not include a high-pressure hydrogen storage tank. The total capacity of the low-pressure hydrogen storage tank is the same as in Case 1.

[0163] Case 4: The energy storage device includes an electrochemical energy storage device and a high-pressure hydrogen storage tank, but does not include a low-pressure hydrogen storage tank. The total capacity of the high-pressure hydrogen storage tank is the same as in Case 1.

[0164] Case 5: A single-layer optimization model similar to the upper-layer optimization model of this invention, the energy storage device includes an electrochemical energy storage device, a low-pressure hydrogen storage tank and a high-pressure hydrogen storage tank, and the optimization objective is to minimize the total annual cost of the target microgrid.

[0165] The above five schemes were solved, and the capacity configuration and operation results of different schemes are shown in Table 4.

[0166] Table 4

[0167]

[0168] As shown in Table 4, the microgrid electro-hydrogen hybrid energy storage operation optimization method of this application allows the electrochemical energy storage device to charge and discharge rapidly, achieving real-time power balance. The low-pressure hydrogen storage tank ensures the daily hydrogen load supply, while the high-pressure hydrogen storage tank stores hydrogen during the high-energy season and releases hydrogen during the low-energy season, solving the problem of cross-seasonal energy mismatch and balancing low curtailment rate with economic efficiency. Case 2 uses single electrochemical energy storage, which has a cost advantage but lacks seasonal adjustment capabilities. During the high-energy season, excess energy cannot be stored for a long time, resulting in an annual curtailment rate as high as 12.24%. During the low-energy season, the output of renewable energy and the battery of the electrochemical energy storage device is insufficient, resulting in a large power supply gap and reliance on purchasing electricity from the upstream grid. Since there is no hydrogen energy storage equipment, the system is completely dependent on external hydrogen purchases. Case 3, with its electrochemical energy storage device and low-pressure hydrogen storage tank working in tandem, can mitigate intraday wind and solar power fluctuations. Compared to Case 2, it addresses the hydrogen load supply issue to some extent and reduces the system's hydrogen purchase volume. However, Case 3 lacks long-term energy storage and cannot address the energy balance issue between the peak and off-peak seasons. During the peak season, it experiences power curtailment, with a curtailment rate 5.26% higher than Case 1. Furthermore, during the off-peak season, it relies on external energy purchases, resulting in a LCHS (Low-Low Power Consumption Rate) 0.08 higher than Case 1. Case 4, with its high-pressure hydrogen storage tank, can alleviate seasonal supply and demand imbalances and improve the annual utilization rate of renewable energy, resulting in a curtailment rate 1.29% lower than Case 3. However, the high-pressure hydrogen storage tank only adds hydrogen during the peak season and releases it during the off-peak season, failing to achieve intraday hydrogen transfer. This leads to power curtailment during the off-peak season and intraday hydrogen load supply issues, requiring external hydrogen purchases. The LCHS is 0.03 higher than Case 1. Case 1: Compared to the single-layer optimization model in Case 5, the microgrid electricity-hydrogen hybrid energy storage operation optimization method of this application increases the total cost by 0.97%, while reducing LCHS by 2.2% and the curtailment rate by 0.65%. For example... Figure 10 The diagram shows the net energy output of hydrogen energy storage in a hybrid energy storage two-layer optimization model and a single-layer optimization model. Because the calculation only considers the energy actually released and does not include stored energy, negative values ​​may occur at certain times. Figure 10 It can be seen that, based on calculations, the present invention The figure is 7.4% higher than Case 5, indicating that the energy storage utilization rate of the hybrid energy storage two-layer optimization model is higher, the energy storage system frequently participates in energy dispatch, and the renewable energy absorption capacity is strong.

[0169] Furthermore, the optimization effects of different electrolyzer configurations were compared and analyzed. To verify the performance advantages of the electrolyzer mother array in this application, the annual total cost and hydrogen production of the target microgrid under different configuration capacity ratios were obtained by adjusting the configuration capacity ratio of proton exchange membrane electrolyzers in the electrolyzer mother array. Figure 11The diagram illustrates the total annual cost (represented by negative profit) and hydrogen production of the target microgrid under different capacity configurations. Figure 11 It is evident that as the proportion of proton exchange membrane (PEM) electrolyzers increases, hydrogen production increases, but the total cost also rises, while the opposite is true for alkaline water electrolyzers. An optimal balance between cost and capacity is achieved when the capacity ratio of alkaline water electrolyzers to PEM electrolyzers is approximately 3:1. Compared to a single PEM electrolyzer, using a hybrid electrolyzer can reduce the total annual cost by 46.39%, while compared to a single alkaline water electrolyzer, it can increase annual hydrogen production by 20.60%, fully demonstrating the advantages of hybrid electrolyzers.

[0170] To compare the operating performance of electrolyzers with different capacities, Case 1 and Case 6 were set based on data from four typical days. The hydrogen production power of the large-capacity electrolyzer and the electrolyzer array of this invention were compared and analyzed. Case 6 is shown below:

[0171] Case 6: A large-capacity electrolytic cell array is used, and the capacity of the electrochemical energy storage device is the same as that in Case 1.

[0172] like Figure 12 The diagram shows a comparison of the output power of a 1800kW ALK large electrolyzer and a 600kW PEM large electrolyzer, both with the same capacity optimization results. Because large-capacity electrolyzers require higher start-up power, the ALK large electrolyzer only achieves high hydrogen production power during the peak energy season; at other times, it often fails to operate normally due to insufficient minimum input power. In contrast, the PEM electrolyzer has a relatively low start-up power and can stably produce hydrogen year-round, with the system's hydrogen load relying on the PEM electrolyzer's supply. Compared to the large electrolyzer, the electrolyzer array in this application, due to its lower minimum hydrogen production power, is easier to start, can operate stably over a wider power range, and has less downtime. Calculations show that the total hydrogen production power is increased by 5.2% and the total hydrogen production is increased by 5.7% compared to the large electrolyzer.

[0173] To verify the optimization effect of the electro-hydrogen energy storage coupling management strategy of this application, Case 1 and Case 7 were set up. The operating conditions of hydrogen energy storage and electrochemical energy storage corresponding to the electro-hydrogen energy storage coupling management strategy of this application and the traditional energy management strategy were compared and analyzed. Case 7 is shown below:

[0174] Case 7: Using a traditional energy management strategy, the capacity of the electrochemical energy storage device, low-pressure hydrogen storage tank, and high-pressure hydrogen storage tank is the same as in Case 1.

[0175] like Figure 13 The diagram shows the operating conditions of a hydrogen energy storage device using a coupled management strategy for electricity and hydrogen energy storage. Figure 14The diagram shows the operating conditions of a hydrogen energy storage device using a traditional energy management strategy. In this diagram, ALK+ represents hydrogen production via alkaline water electrolysis subarray, PEM+ represents hydrogen production via proton exchange membrane electrolysis subarray, HS+ represents hydrogen storage in a low-pressure hydrogen storage tank, SHS+ represents hydrogen storage in a high-pressure hydrogen storage tank, BUY+ represents hydrogen purchase, HFC- represents hydrogen combustion in a hydrogen fuel cell, HS- represents hydrogen release from a low-pressure hydrogen storage tank, SHS- represents hydrogen release from a high-pressure hydrogen storage tank, and LAOD- represents the amount of hydrogen converted from electrical load. Figure 15 The diagram shows the operating conditions of an electrochemical energy storage device using a coupled electro-hydrogen energy storage management strategy. In this diagram, BT+ represents battery charging, BT- represents battery discharging, and SOC represents the battery's state of charge. Figure 16 The diagram shown illustrates the operating conditions of an electrochemical energy storage device based on a traditional energy management strategy. Figure 13 , Figure 14 , Figure 15 and Figure 16 It is known that under traditional energy management strategies, hybrid electro-hydrogen energy storage does not fully consider the operational optimization of electrolyzers. Its output is greatly affected by fluctuations in renewable energy sources. When renewable energy power input is insufficient, many electrolyzers, especially ALK electrolyzers, are forced to shut down, forcing the target microgrid to rely on large-scale external hydrogen purchases to meet its hydrogen load demand. In contrast, the strategy proposed in this invention reduces hydrogen production by 4.35% for ALK electrolyzers, increases hydrogen production by 1.51% for PEM electrolyzers, and reduces the total hydrogen production of the target microgrid by 2.73%.

[0176] By 13, Figure 14 , Figure 15 and Figure 16 As can be seen, by adopting the electro-hydrogen energy storage coupling management strategy proposed in this invention, the hydrogen purchase amount of the target microgrid was reduced by 23.35%, while the charging and discharging frequency of the battery of the electrochemical energy storage device was reduced by 16.98%. This is because the electro-hydrogen energy storage coupling management strategy of this application effectively smooths out the fluctuations of renewable energy through the rapid response of the electrochemical energy storage device, enabling the electrolyzer in the target microgrid to operate under more stable conditions. This not only improves the overall hydrogen production efficiency of the target microgrid and reduces the dependence on external hydrogen sources, but also optimizes the synergistic interaction between electrochemical energy storage and hydrogen energy storage, significantly improving the comprehensive operating performance of the hybrid energy storage system.

[0177] In a preferred embodiment of the present invention, the rated power of the electrolyzer bus array of the target microgrid is obtained, and the parameters of the electrolyzer bus array are matched with the power processed in different frequency ranges. Based on the relationship between the real-time net power of the target microgrid, the rated power of the electrolyzer bus array, and the current storage power of the electrochemical energy storage device, an electro-hydrogen energy storage coupling management strategy is constructed. The electro-hydrogen energy storage coupling management strategy is set to reflect the operating conditions of the electrolyzer bus array, the charging and discharging state of the electrochemical energy storage device, and the combustion state of the hydrogen energy storage device. A hybrid energy storage two-layer optimization model of the target microgrid is constructed. The hybrid energy storage two-layer optimization model is set to minimize the annual total cost of the target microgrid as the upper-layer objective function of the upper-layer optimization model, and minimize the levelized cost of the hydrogen energy storage device as the lower-layer objective function of the lower-layer optimization model. Based on the output results of the electro-hydrogen energy storage coupling management strategy implemented on the target microgrid, the hybrid energy storage two-layer optimization model is solved to obtain the electro-hydrogen hybrid energy storage operation optimization strategy of the target microgrid. The target microgrid is then controlled to implement the electro-hydrogen hybrid energy storage operation optimization strategy. This application discloses a method for optimizing the operation of microgrid hybrid electro-hydrogen energy storage, focusing on the coupling relationship between electrochemical energy storage and hydrogen energy storage. It considers an electro-hydrogen energy storage coupling management strategy that integrates electrolyzer arrays and energy management strategies, effectively reducing the impact of fluctuating renewable energy output on electrolyzers and improving economic efficiency and energy management effectiveness. By setting up electrochemical energy storage devices, low-pressure hydrogen storage tanks, and high-pressure hydrogen storage tanks, energy transfer across multiple time scales is achieved, adjusting the system's intraday and cross-seasonal source-load imbalances, reducing wind and solar curtailment, and ensuring load supply. By establishing a hybrid energy storage two-layer optimization model, the annual total cost and LCHS of the microgrid are optimized, enabling the determination of the optimal configuration capacity and operation scheme for hybrid energy storage, balancing high utilization and low cost. The alkaline water electrolyzer subarray and proton exchange membrane electrolyzer subarray used have better hydrogen production effects than single-type electrolyzers and large-capacity electrolyzers. When the capacity ratio of the two types of electrolyzers is 3:1, both green hydrogen production and system economics can be balanced. The energy management strategy proposed in this invention optimizes the complementary mechanism of electrochemical energy storage and hydrogen energy storage, and improves the dynamic operating characteristics of the electrolyzer through the charging and discharging of BT.

[0178] Accordingly, such as Figure 17 The diagram shows the structure of a microgrid electro-hydrogen hybrid energy storage operation optimization system. Based on a microgrid electro-hydrogen hybrid energy storage operation optimization method, this embodiment of the invention also provides a microgrid electro-hydrogen hybrid energy storage operation optimization system. This system implements the microgrid electro-hydrogen hybrid energy storage operation optimization method disclosed in this embodiment of the invention and is applied to a target microgrid composed of an electrolyzer mother array, an electrochemical energy storage device, and a hydrogen energy storage device. The system includes: an electrolyzer mother array data acquisition module 1, an electro-hydrogen energy storage coupling management strategy construction module 2, a hybrid energy storage two-layer optimization model construction module 3, an optimization strategy acquisition module 4, and an operation optimization module 5.

[0179] The electrolytic cell mother array data acquisition module 1 is used to obtain the rated power of the electrolytic cell mother array of the target microgrid, and the parameters of the electrolytic cell mother array are matched with the electrical energy processed in different frequency ranges.

[0180] The electro-hydrogen energy storage coupling management strategy construction module 2 is used to construct an electro-hydrogen energy storage coupling management strategy based on the relationship between the real-time net power of the target microgrid, the rated power of the electrolyzer mother array, and the current storage power of the electrochemical energy storage device. The electro-hydrogen energy storage coupling management strategy is set to reflect the operating conditions of the electrolyzer mother array, the charging and discharging state of the electrochemical energy storage device, and the combustion state of the hydrogen energy storage device.

[0181] The hybrid energy storage dual-layer optimization model construction module 3 is used to construct the hybrid energy storage dual-layer optimization model of the target microgrid. The hybrid energy storage dual-layer optimization model is set to take the minimum annual total cost of the target microgrid as the upper-layer objective function of the upper-layer optimization model and the minimum levelized energy storage cost of the hydrogen energy storage device as the lower-layer objective function of the lower-layer optimization model.

[0182] The optimization strategy acquisition module 4 is used to solve the hybrid energy storage two-layer optimization model based on the output result of the execution of the electric-hydrogen energy storage coupling management strategy on the target microgrid, so as to obtain the electric-hydrogen hybrid energy storage operation optimization strategy of the target microgrid.

[0183] The operation optimization module 5 is used to control the target microgrid to execute the electric-hydrogen hybrid energy storage operation optimization strategy.

[0184] Specific limitations regarding a microgrid-based hybrid electric-hydrogen energy storage operation optimization system can be found in the above-described limitations regarding a microgrid-based hybrid electric-hydrogen energy storage operation optimization method, and will not be repeated here. Those skilled in the art will recognize that the various modules and steps described in conjunction with the embodiments disclosed in this invention can be implemented in hardware, software, or a combination of both. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this invention.

[0185] like Figure 18 The diagram shows the internal structure of a computer device. An embodiment of the present invention provides a computer device including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the steps described in the embodiment of the microgrid hydrogen-electric hybrid energy storage operation optimization method, for example... Figure 1 Steps S1 to S5 as described above.

[0186] Those skilled in the art will understand that the illustrations Figure 18 This is merely an example of a computer device and does not constitute a limitation on the computer device. It may include more or fewer components than shown, or combine certain components, or different components. For example, the computer device may also include input / output devices, network access devices, buses, etc.

[0187] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor. The processor is the control center of the computer device, connecting various parts of the computer device via various interfaces and lines.

[0188] The memory can be used to store the computer programs and / or modules. The processor implements various functions of the computer device by running or executing the computer programs and / or modules stored in the memory and by calling data stored in the memory. The memory may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the mobile phone (such as audio data, phonebook, etc.). In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0189] If the modules integrated into the computer device are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

[0190] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0191] Accordingly, embodiments of the present invention provide a computer-readable storage medium, the computer-readable storage medium including a stored computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to perform the steps described in the embodiments of the microgrid electric-hydrogen hybrid energy storage operation optimization method, for example... Figure 1 Steps S1 to S5 as described above.

[0192] In summary, the embodiments of this application provide a method, system, equipment, and medium for optimizing the operation of microgrid electro-hydrogen hybrid energy storage, addressing the technical problem of how to optimize the synergistic operation relationship between electrochemical energy storage and hydrogen energy storage in microgrid electro-hydrogen hybrid energy storage. The method includes: obtaining the rated power of the electrolyzer mother array of the target microgrid, with the parameters of the electrolyzer mother array matched to the processing of electrical energy in different frequency ranges; and constructing an electro-hydrogen energy storage coupling management strategy based on the relationship between the real-time net power of the target microgrid, the rated power of the electrolyzer mother array, and the current storage power of the electrochemical energy storage device. This electro-hydrogen energy storage coupling management strategy is set to reflect the relationship between the real-time net power of the target microgrid, the rated power of the electrolyzer mother array, and the current storage power of the electrochemical energy storage device. The operating conditions of the electrochemical energy storage array, the charging and discharging states of the electrochemical energy storage device, and the combustion state of the hydrogen energy storage device are analyzed. A hybrid energy storage two-layer optimization model for the target microgrid is constructed. The hybrid energy storage two-layer optimization model is set with the minimum annual total cost of the target microgrid as the upper-layer objective function and the minimum levelized cost of the hydrogen energy storage device as the lower-layer objective function. Based on the output results of the electro-hydrogen energy storage coupled management strategy implemented on the target microgrid, the hybrid energy storage two-layer optimization model is solved to obtain the electro-hydrogen hybrid energy storage operation optimization strategy for the target microgrid. The target microgrid is then controlled to implement the electro-hydrogen hybrid energy storage operation optimization strategy. This application discloses a method for optimizing the operation of microgrid hybrid electro-hydrogen energy storage, focusing on the coupling relationship between electrochemical energy storage and hydrogen energy storage. It considers an electro-hydrogen energy storage coupling management strategy that integrates electrolyzer arrays and energy management strategies, effectively reducing the impact of fluctuating renewable energy output on electrolyzers and improving economic efficiency and energy management effectiveness. By setting up electrochemical energy storage devices, low-pressure hydrogen storage tanks, and high-pressure hydrogen storage tanks, energy transfer across multiple time scales is achieved, adjusting the system's intraday and cross-seasonal source-load imbalances, reducing wind and solar curtailment, and ensuring load supply. By establishing a hybrid energy storage two-layer optimization model, the annual total cost and LCHS of the microgrid are optimized, enabling the determination of the optimal configuration capacity and operation scheme for hybrid energy storage, balancing high utilization and low cost. The alkaline water electrolyzer subarray and proton exchange membrane electrolyzer subarray used have better hydrogen production effects than single-type electrolyzers and large-capacity electrolyzers. When the capacity ratio of the two types of electrolyzers is 3:1, both green hydrogen production and system economics can be balanced. The energy management strategy proposed in this invention optimizes the complementary mechanism of electrochemical energy storage and hydrogen energy storage, and improves the dynamic operating characteristics of the electrolyzer through the charging and discharging of BT.

[0193] The various embodiments in this specification are described in a progressive manner. For directly identical or similar parts of the embodiments, refer to each other. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments. It should be noted that the technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as the combination of these technical features does not contradict each other, it should be considered within the scope of this specification.

[0194] The embodiments described above are merely preferred embodiments of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the patent application. It should be noted that those skilled in the art can make various improvements and substitutions without departing from the technical principles of this application, and these improvements and substitutions should also be considered within the scope of protection of this application. Therefore, the scope of protection of this patent application should be determined by the scope of the claims.

Claims

1. A micro-grid electric-hydrogen hybrid energy storage operation optimization method, characterized in that, The method is applied to a target micro-grid composed of an electrolytic cell mother array, an electrochemical energy storage device and a hydrogen energy storage device, and comprises the following steps: obtaining an electrolytic cell mother array rated power of the electrolytic cell mother array of the target micro-grid, the parameters of the electrolytic cell mother array being matched with processing electric energy of different frequency ranges; constructing an electricity-hydrogen energy storage coupling management strategy according to a relationship among a real-time net power of the target micro-grid, the electrolytic cell mother array rated power and a current storage power of the electrochemical energy storage device, the electricity-hydrogen energy storage coupling management strategy being set to reflect an operating condition of the electrolytic cell mother array, a charging and discharging state of the electrochemical energy storage device and a combustion state of the hydrogen energy storage device, and specifically comprising: when the real-time net power of the target micro-grid is greater than or equal to a first preset multiple of the electrolytic cell mother array rated power, the target micro-grid is in a first electricity-hydrogen energy storage coupling state, the first electricity-hydrogen energy storage coupling state being set to an overload operating condition of the electrolytic cell mother array and a charging state of the electrochemical energy storage device; when the real-time net power is greater than or equal to a second preset multiple of the electrolytic cell mother array rated power and less than the first preset multiple of the electrolytic cell mother array rated power, the target micro-grid is in a second electricity-hydrogen energy storage coupling state, the second electricity-hydrogen energy storage coupling state being set to a stable operating condition of the electrolytic cell mother array and a storage amount keeping state of the electrochemical energy storage device; when the real-time net power is greater than or equal to zero and less than the second preset multiple of the electrolytic cell mother array rated power, the target micro-grid is in a third electricity-hydrogen energy storage coupling state, the third electricity-hydrogen energy storage coupling state being set to that the operating condition of the electrolytic cell mother array and the charging and discharging state of the electrochemical energy storage device are determined by the real-time net power and the current storage power of the electrochemical energy storage device; when the real-time net power is less than zero, the target micro-grid is in a fourth electricity-hydrogen energy storage coupling state, the fourth electricity-hydrogen energy storage coupling state being set to that the charging and discharging state of the electrochemical energy storage device and the combustion state of a hydrogen fuel cell of the hydrogen energy storage device are determined by the current storage power of the electrochemical energy storage device and a power grid price; constructing an electricity-hydrogen energy storage coupling management strategy according to the first electricity-hydrogen energy storage coupling state, the second electricity-hydrogen energy storage coupling state, the third electricity-hydrogen energy storage coupling state and the fourth electricity-hydrogen energy storage coupling state; constructing a hybrid energy storage double-layer optimization model of the target micro-grid, the hybrid energy storage double-layer optimization model being set to have a minimum annual total cost of the target micro-grid as an upper layer objective function of an upper layer optimization model and a minimum levelized energy storage cost of the hydrogen energy storage device as a lower layer objective function of a lower layer optimization model; solving the hybrid energy storage double-layer optimization model according to an output result of executing the electricity-hydrogen energy storage coupling management strategy on the target micro-grid to obtain an electricity-hydrogen hybrid energy storage operation optimization strategy of the target micro-grid; controlling the target micro-grid to execute the electricity-hydrogen hybrid energy storage operation optimization strategy; the method further comprises: According to the obtained historical net power data of the target micro-grid, the target micro-grid is divided into a rich energy season, a dry energy season and a flat energy season; According to the rich energy season, the dry energy season and the flat energy season, a long-term hydrogen energy storage operation model is constructed, which is used to control the operation state of the high-pressure hydrogen storage tank of the hydrogen energy storage device; According to the cooperative operation relationship between the electrochemical energy storage device and the low-pressure hydrogen storage tank of the hydrogen energy storage device, a short-term hydrogen energy storage operation model is constructed, which is used to control the operation state of the low-pressure hydrogen storage tank.

2. The micro-grid hydrogen hybrid energy storage operation optimization method of claim 1, wherein, The different frequency ranges at least include a first power range and a second frequency range; The first power range is a trend component and a periodic component obtained by time series decomposition of the to-be-processed power to be electrolyzed by the electrolyzer mother array; The second frequency range is a fluctuation component obtained by time series decomposition of the to-be-processed power.

3. The micro-grid hydrogen hybrid energy storage operation optimization method of claim 1, wherein, When the real-time net power is greater than or equal to zero and less than the second preset multiple of the electrolyzer mother array rated power, the target micro-grid is in a third electro-hydrogen energy storage coupling state, which includes: When the sum of the real-time net power and the current storage power of the electrochemical energy storage device is greater than or equal to the second preset multiple of the electrolyzer mother array rated power, the electrolyzer mother array is in a low-power operation condition and the electrochemical energy storage device is in a discharging state; When the sum of the real-time net power and the current storage power of the electrochemical energy storage device is less than the second preset multiple of the electrolyzer mother array rated power and greater than or equal to the minimum operating power of the electrolyzer mother array, the electrolyzer mother array is in a shift operation condition and the electrochemical energy storage device is in the discharging state; When the sum of the real-time net power and the current storage power of the electrochemical energy storage device is less than the minimum operating power, the electrolyzer mother array is in a shutdown state and the electrochemical energy storage device is in the charging state.

4. The micro-grid hydrogen hybrid energy storage operation optimization method of claim 1, wherein, When the real-time net power is less than zero, the target micro-grid is in a fourth electro-hydrogen energy storage coupling state, which includes: When the current storage power of the electrochemical energy storage device is greater than zero, the electrochemical energy storage device is in a discharging state; When the current storage power of the electrochemical energy storage device is equal to zero and the time-of-use electricity price is a non-peak electricity price, the target micro-grid purchases electricity from the power distribution network and the hydrogen fuel cell of the hydrogen energy storage device is in an open circuit state; When the current storage power of the electrochemical energy storage device is equal to zero and the time-of-use electricity price is a peak electricity price, the hydrogen fuel cell is in a discharging and burning state.

5. The micro-grid hydrogen hybrid energy storage operation optimization method of claim 1, wherein, According to the output result of the electro-hydrogen energy storage coupling management strategy executed on the target micro-grid, the mixed energy storage double-layer optimization model is solved to obtain an electro-hydrogen mixed energy storage operation optimization strategy of the target micro-grid, which includes: The electro-hydrogen energy storage coupling management strategy is executed on the target micro-grid to obtain an output result, which includes the operation condition of the electrolyzer mother array, the charging and discharging state of the electrochemical energy storage device and the burning state of the hydrogen fuel cell; Solve the mixed energy storage double-layer optimization model based on the operating condition, the charging and discharging state and the combustion state, to obtain an electricity-hydrogen mixed energy storage operation optimization strategy of the target microgrid, which includes electrolyzer mother array capacity configuration, electrochemical energy storage device capacity configuration, hydrogen fuel cell capacity configuration, operating power of the electrolyzer mother array, charging and discharging power of the electrochemical energy storage device and combustion power of the hydrogen fuel cell.

6. A micro-grid electric-hydrogen hybrid energy storage operation optimization system for implementing the micro-grid electric-hydrogen hybrid energy storage operation optimization method of any one of claims 1-5, characterized in that, The system is applied to a target microgrid composed of an electrolyzer mother array, an electrochemical energy storage device and a hydrogen energy storage device, and includes an electrolyzer mother array data acquisition module, an electricity-hydrogen energy storage coupling management strategy construction module, a mixed energy storage double-layer optimization model construction module, an optimization strategy acquisition module and an operation optimization module. The electrolyzer mother array data acquisition module is configured to acquire electrolyzer mother array rated power of the electrolyzer mother array of the target microgrid, and parameters of the electrolyzer mother array are matched with processing electric energy of different frequency ranges. The electricity-hydrogen energy storage coupling management strategy construction module is configured to construct an electricity-hydrogen energy storage coupling management strategy according to a relationship among real-time net power of the target microgrid, the electrolyzer mother array rated power and current storage power of the electrochemical energy storage device, and the electricity-hydrogen energy storage coupling management strategy is set to reflect operating condition of the electrolyzer mother array, charging and discharging state of the electrochemical energy storage device and combustion state of the hydrogen energy storage device. The mixed energy storage double-layer optimization model construction module is configured to construct a mixed energy storage double-layer optimization model of the target microgrid, and the mixed energy storage double-layer optimization model is set to have minimum annual total cost of the target microgrid as an upper layer target function of an upper layer optimization model and minimum levelized energy storage cost of the hydrogen energy storage device as a lower layer target function of a lower layer optimization model. The optimization strategy acquisition module is configured to solve the mixed energy storage double-layer optimization model according to an output result of executing the electricity-hydrogen energy storage coupling management strategy on the target microgrid, to obtain an electricity-hydrogen mixed energy storage operation optimization strategy of the target microgrid. The operation optimization module is configured to control the target microgrid to execute the electricity-hydrogen mixed energy storage operation optimization strategy.

7. A computer device, characterized by: The computer device includes a memory, a processor and a transceiver connected through a bus, the memory is configured to store a set of computer program instructions and data, and transmit the stored data to the processor, the processor executes the computer program instructions stored in the memory to execute the microgrid electricity-hydrogen mixed energy storage operation optimization method in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that: The computer readable storage medium stores a computer program, when the computer program is executed, the microgrid electricity-hydrogen mixed energy storage operation optimization method in any one of claims 1 to 5 is implemented.

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