Off-grid synthetic ammonia park electrolytic bath column level-energy storage-hydrogen storage collaborative optimization method based on rolling optimization

Abstract

The invention provides an off-grid synthetic ammonia park electrolytic bath column level-energy storage-hydrogen storage collaborative optimization method based on rolling optimization, and relates to the technical field of energy storage and hydrogen storage collaboration. The method comprises the following steps: constructing an off-grid system architecture comprising wind-solar power generation, a plurality of rows of electrolytic cells, energy and hydrogen storage equipment and a synthesis ammonia device; a multi-device collaborative optimization strategy based on an eight-hour rolling time domain is designed, the system operation state is divided into high, medium and low working conditions through a working condition recognition mechanism, a current device operation scheme is actively adjusted according to wind and light power information of a next scheduling period, and collaborative regulation and control of energy storage and hydrogen storage are achieved. Compared with a traditional scheduling strategy, the collaborative optimization strategy provided by the invention improves the consumption rate of renewable energy sources of the system, reduces abandoned wind and light, improves the yield of synthetic ammonia, and verifies the effectiveness of the strategy.

Description

Technical Field

[0001] This application relates to the field of electrolyzer stage control technology, and in particular to a method for synergistic optimization of electrolyzer stage, energy storage, and hydrogen storage in off-grid synthetic ammonia industrial parks based on rolling optimization. Background Technology

[0002] The traditional Haber-Bosch ammonia synthesis process heavily relies on fossil fuels, accounting for more than 11% of global industrial carbon emissions annually, and urgently needs to transform to green production. The integrated wind-solar-hydrogen-ammonia system provides a feasible solution for green ammonia production by coupling renewable energy power generation with water electrolysis for hydrogen production and ammonia synthesis. The literature "Deng Zhenyu, Zhou Jiahui, Xu Gang, et al. Capacity-Dispatch Optimization Analysis of On-Grid / Off-Grid Wind-Solar Complementary Hydrogen-Ammonia Synthesis System [J]. Thermal Power Generation, 2024, 53(09):136-146." designed an on-grid / off-grid wind-solar complementary hydrogen-ammonia synthesis system, maximizing the system's annual revenue through capacity configuration and dispatch optimization. The paper "Lin Jin, Yu Zhipeng, Zhang Xinzhen. On-grid / Off-grid Operation Mode and Economic Analysis of Renewable Energy Electric Hydrogen Production to Ammonia Synthesis System [J]. Proceedings of the CSEE, 2024, 44(1): 117-127" compares and analyzes the green ammonia costs of grid-connected, grid-friendly, and off-grid systems, pointing out that grid-friendly systems should be developed in the near future. However, off-grid systems face unique challenges: the strong intermittency of wind and solar resources leads to drastic fluctuations in power supply, while the ammonia synthesis process has strict requirements for operational stability.

[0003] In response to the volatility of renewable energy, scholars both domestically and internationally have conducted in-depth research. The literature "Wang C, Walsh S DC, Longden T, et al. Optimising renewable generation configurations of off-grid green ammonia production systems considering Haber-Bosch flexibility[J]. Energy Conversion and Management, 2023, 280: 116790." shows that a flexible Haber-Bosch operation strategy can significantly reduce energy cuts and storage requirements, thereby improving system economics. The literature "Li Qi, Han Yunbin, Bai Zhang, et al. Coordinated operation strategy and capacity configuration optimization of off-grid wind-solar combined hydrogen production systems[J]. Proceedings of the CSEE, 2024, 44(20):8136-8146." proposes a coordinated operation strategy for off-grid wind-solar combined hydrogen production systems, improving system adaptability through optimized scheduling. The literature "An Guanglu, Liu Yongzhong, Kang Lixia. Optimization Design of Renewable Energy Synthesis Ammonia System Adapted to Seasonal Ammonia Demand [J]. Journal of Chemical Industry and Engineering (China), 2021, 72(03): 1595-1605." constructs a system optimization design model from the perspective of seasonal ammonia demand. These studies mainly focus on the flexibility transformation of single equipment or system capacity optimization, but there is still a lack of systematic solutions for how to achieve deep coordination among multiple equipment. At the scheduling optimization level, the rolling optimization strategy provides a new idea for solving the above problems. The literature "Zhou Buxiang, Zhu Wencong, Zhu Jie, et al. Analysis of Multi-Time Scheduling Domain of Wind-Solar Hydrogen-to-Ammonia Synthesis System [J]. Proceedings of the CSEE, 2024, 44(01): 160-174." analyzes the multi-time scheduling domain of the wind-solar hydrogen-to-ammonia synthesis system and reveals the flexibility boundary of system operation. The paper "Chen R, Gao C, Ming H. Rolling-horizon optimization strategy for wind-storage system in electricity market[J]. IET Renewable Power Generation,2024, 18(5): 825-836" points out that rolling-horizon optimization can effectively cope with the uncertainty of renewable energy by dynamically updating decision information.The paper "Bischi A, Taccari L, Martelli E, et al. A rolling-horizon optimization algorithm for the long-term operational scheduling of cogeneration systems[J]. Energy, 2019, 184: 73-90." successfully applied the rolling-horizon optimization algorithm to the long-term operational scheduling of cogeneration systems. However, these studies have not yet organically combined rolling optimization with multi-device collaborative control, making it difficult to fully realize the overall regulation potential of the system.

[0004] From the equipment perspective, electrolyzer cascade regulation and energy storage-hydrogen synergy have become important means to improve system flexibility. Electrolyzer cascade regulation can achieve fine-grained power adjustment through separate start-up and shutdown. The literature "Sun Huijuan, Que Weixin, Peng Chunhua. Robust planning of confidence gap for electric-hydrogen energy system considering electric-hydrogen coupling and carbon trading [J]. Power System Technology, 2023, 47(11):4477-4490." considers the electric-hydrogen coupling characteristics and establishes a robust planning model for electric-hydrogen energy system. The literature "Han Zijiao, Li Zhengwen, Zhang Wenda, et al. Economic operation strategy of hydrogen integrated energy system considering photovoltaic output uncertainty [J]. Electric Power Automation Equipment, 2021, 41(10):99-106." considers the photovoltaic output uncertainty and proposes an economic operation strategy for hydrogen integrated energy system. Energy storage-hydrogen synergy optimization is a key way to improve system flexibility. The paper "Gao Mingfei, Zhang Ce, Xie Tong, et al. Optimization configuration method of multi-source energy storage for integrated energy systems considering wind and solar consumption [J]. Journal of Power Engineering, 2023, 43(06): 796-804." proposes an optimization configuration method of multi-source energy storage for integrated energy systems considering wind and solar consumption, realizing the complementary advantages of different energy storage forms. The paper "Chen Zhaoyu, Wang Dan, Jia Hongjie, et al. Research on day-ahead optimal economic dispatch strategy of microgrid with multi-source energy storage considering P2G [J]. Proceedings of the CSEE, 2017, 37(11): 3067-3077." studies the dispatch strategy of microgrid with multi-source energy storage considering hydrogen production by electricity, revealing the important role of hydrogen energy storage in mitigating the fluctuations of renewable energy.

[0005] In summary, although existing research has made significant progress in areas such as equipment flexibility modification and scheduling strategies, there are still some shortcomings in the integrated application of key technologies such as multi-equipment collaborative optimization, forward-looking scheduling decision-making, and adaptive control of operating conditions. Summary of the Invention

[0006] This application provides a rolling optimization-based collaborative optimization method for electrolyzer-cell stage, energy storage, and hydrogen storage in off-grid synthetic ammonia parks. Addressing the dual challenges of highly intermittent wind and solar resources and rigid load demand faced by off-grid integrated wind-solar-hydrogen-ammonia systems, this method proposes a rolling optimization-based collaborative optimization strategy for electrolyzer stage, energy storage, and hydrogen storage. By constructing an 8-hour rolling time-domain multi-equipment collaborative optimization model and combining it with a condition identification mechanism, the method proactively adjusts the current equipment operation plan based on the wind and solar power information for the next scheduling cycle, achieving coordinated control of energy storage and hydrogen storage. This provides a new technical path for improving the system's renewable energy absorption rate and synthetic ammonia production.

[0007] This application provides a rolling optimization method for the coordinated optimization of electrolyzer series, energy storage, and hydrogen storage in an off-grid ammonia synthesis park, the method comprising: Construct an off-grid integrated wind-solar-ammonia system; wherein, the off-grid integrated wind-solar-ammonia system includes a power generation module, a hydrogen production module, an ammonia synthesis module and a dispatch module; the power generation module includes wind and solar generator sets and energy storage, the hydrogen production module includes multiple independently operating electrolyzers, hydrogen storage tanks and purification devices, and the ammonia synthesis module includes air separation nitrogen production equipment and ammonia synthesis equipment; Based on the off-grid integrated wind-solar-ammonia system, an off-grid integrated wind-solar-ammonia system model is established. The off-grid integrated wind-solar-ammonia system model includes a wind and solar generator model, an electrolyzer equipment model and constraints, an air separation equipment model and constraints, an ammonia synthesis equipment model and constraints, a hydrogen storage tank model and constraints, and an energy storage equipment model and constraints. Based on the off-grid integrated wind-solar-ammonia system model, a multi-device collaborative optimization strategy based on an n-hour rolling time domain is designed. The system operating status is divided into three types of operating conditions through an operating condition identification mechanism. These three types of operating conditions are high-power operating conditions, medium-power operating conditions, and low-power operating conditions. The operating condition identification mechanism is based on the power supply and demand balance relationship. High-power operating conditions correspond to sufficient renewable energy, low-power operating conditions correspond to severe energy shortage, and medium-power operating conditions correspond to a basic balance between energy supply and demand. Based on the operating condition identification results and combined with the wind and solar power information for the next scheduling cycle, the current equipment operation plan is adjusted to achieve coordinated regulation of electrolyzers and energy storage and hydrogen storage.

[0008] Furthermore, based on the operating condition identification results and combined with the wind and solar power information for the next scheduling cycle, the current equipment operation plan is adjusted to achieve coordinated control of electrolyzer-level regulation and energy storage and hydrogen storage. This includes the following methods: Under high-incidence working conditions, when the first j When the wind and solar power output exceeds the sum of the maximum loads of the synthetic ammonia and electrolytic cells in the +1 scheduling cycle, the first... jEach cycle employs a scheduling strategy of emptying energy storage, releasing hydrogen storage, and increasing load. By adjusting the energy storage and hydrogen storage status in advance to reserve storage capacity, the curtailment of wind and solar power can be avoided in the next cycle. Under low-incidence operating conditions, when the first j When the wind and solar power output is lower than the minimum operating power for ammonia synthesis in +1 scheduling cycle, the first... j Each cycle employs a scheduling strategy of maintaining energy storage, charging hydrogen storage, and reducing load, ensuring stable system operation in the next cycle through energy pre-reservation; Under intermediate operating conditions, when predicting the first j When the wind and solar power is at an intermediate level during +1 scheduling cycle, the first... j Each cycle employs a scheduling strategy that combines balanced optimization, flexible scheduling, and appropriate reserves to achieve optimal energy supply and demand balance, laying the foundation for the long-term efficient operation of the system.

[0009] Furthermore, the wind and solar generator model is represented as follows: (1) In the formula: P wind ( t )express t The output power of wind power equipment at all times; P wind,max Indicates the installed capacity of wind power equipment; P solar ( t )express t The output power of photovoltaic equipment at all times; P solar,max This indicates the installed capacity of photovoltaic equipment.

[0010] Furthermore, the electrolytic cell equipment model and constraints are represented as follows: (2) In the formula: P col,1 ( t ), P col,2 ( t ), P col,i ( t ) are respectively the 1st column, the 2nd column, i Electrolytic cells in t Hydrogen production capacity at any given time; P col ( t )for t Hydrogen production power of the time-sensitive system; M col,1 ( t ), M col,2 (t ), M col,i ( t ) are respectively the 1st column, the 2nd column, i Electrolytic cells in t Hydrogen production at any given time; M col ( t )for t The hydrogen production rate of the electrolyzer at any given time; λ H2 This represents the power consumption coefficient for hydrogen production in the electrolyzer. (3) In the formula: P col,min and P col,max This indicates the lower and upper limits of the operating power of each column of electrolytic cells; u i ( t )and u i ( t -1) are respectively t Time and t The decision variable at time -1 represents... t Time and t -1 moment i Is the electrolytic cell in operation? ystart i ( t )and ystop i ( t ) are respectively t Time of the first i List the start-up and shutdown variables of the electrolytic cell, where 0 represents shutdown and 1 represents start-up.

[0011] Furthermore, the air separation equipment model and constraints are expressed as follows: (4) In the formula: P ASU ( t )for t The power consumption of the air separation unit to generate nitrogen at any given time; λ N2 The power consumption coefficient for nitrogen production in air separation equipment; M N2 ( t )for t The amount of nitrogen produced at any given time; P ASU,max This is the maximum power of the air separation unit.

[0012] Furthermore, the model and constraints of the ammonia synthesis equipment are represented as follows: (5) In the formula: M NH3 ( t For ammonia synthesis equipment t Ammonia production at any given time; P NH3 ( t )for t The power consumption of the ammonia synthesis equipment to produce ammonia gas at all times; λ NH3 The power consumption coefficient for ammonia production in ammonia synthesis equipment; P NH3 , q ( t () represents the power consumption of the ammonia synthesis equipment under different load conditions; q For operating condition index; (6) In the formula: P NH3 ( j , h ) is the first j Within the scheduling cycle, the first h The power consumed by the ammonia synthesis equipment per hour; P NH3 ( j ) is the first j Power consumption of a single-cycle ammonia synthesis unit; ρ NH3 ( j , h ) is the first j Within the scheduling cycle, the first h The load rate of the ammonia synthesis equipment per hour; ρ NH3 ( j ) is the first j Load rate of the ammonia synthesis equipment in each cycle; y NH3 ( t )for t The start / stop variable for the ammonia synthesis equipment is 0, which indicates shutdown and 1 indicates operation.

[0013] Furthermore, the hydrogen storage tank model and constraints are expressed as follows: (7) In the formula: M SOG ( j ), M SOG ( j -1) are respectively the first j The, the j -1 scheduling cycle of hydrogen storage; Eremain ( j ) is the first j Remaining power for each scheduling cycle; E area,H2 ( j This is the upper limit of hydrogen storage capacity for the current scheduling cycle, ensuring that the hydrogen storage process does not exceed the hydrogen storage tank capacity limit or the available power limit; β H2 The electro-hydrogen conversion coefficient; P general ( j ) is the first j Average power generation of wind and solar power over a scheduling cycle; P col ( j ) is the first j Hydrogen production capacity of the electrolyzer per scheduling cycle; M SOG,max The maximum hydrogen filling capacity of the hydrogen storage tank; min is the minimum value function; λ H2 This represents the power consumption coefficient for hydrogen production in the electrolyzer. (8) In the formula: M SOG,in ( t ), M SOG,out ( t These are hydrogen storage tanks. t The amount of hydrogen added and released at any given time; y H2,in ( t ), y H2,out ( t ) represents the charging and discharging state variable of the hydrogen storage tank at time t, where 0 represents stopping and 1 represents running; M SOG (0) represents the initial hydrogen storage capacity of the hydrogen storage tank equipment.

[0014] Furthermore, the energy storage device model and constraints are expressed as follows: (9) In the formula: E SOC ( j ), E SOC ( j -1) are respectively the first j The, the j - The amount of electricity stored in the energy storage device during one scheduling cycle; Δ E SOC ( j ) is the first jThe charge and discharge capacity of the energy storage device in each scheduling cycle; Δ E SOC,in ( j ) for energy storage devices in the first j The amount of charge per scheduling cycle; Δ E SOC,out ( j ) for energy storage devices in the first j Discharge amount per scheduling cycle; E SOC,u ( j Energy storage is the first j Available charging capacity for each scheduling cycle; E SOC,n ( j ) for energy storage j Remaining capacity for each scheduling cycle; E SOC,d ( j Let be the discharge demand of the energy storage in the j-th cycle; max is the maximum value function; min is the minimum value function; (10) In the formula: E SOC,max This represents the maximum charging and discharging power of the energy storage. y in ( t ), y out ( t ) represents the charging and discharging state variables of energy storage, where 0 indicates stop and 1 indicates operation; E SOC (0) represents the initial electrical quantity of the energy storage device.

[0015] Furthermore, the method also includes: Based on the annual wind and solar power output data of the target area, the optimal system scheduling result is obtained by using a mixed integer programming model with the objective function of minimizing the total operating cost of the off-grid wind-solar-hydrogen-ammonia integrated system, and the constraints of power balance and hydrogen power balance.

[0016] Furthermore, the objective function is expressed as: (11) In the formula: P cur ( j ) is the first j The amount of electricity wasted in each scheduling cycle; α This represents the cost coefficient for abandoned electricity. N H2 ( j ) is the first j The number of electrolytic cell operation trains per scheduling cycle; βThis is the single-row start-up and shutdown cost coefficient for the electrolytic cell; P balance ( j ) is the first j The imbalance in each scheduling cycle; δ This is the power imbalance penalty factor; F For system operating costs; The power balance constraint is expressed as follows: (12) In the formula: P balance ( t ) is the first t The imbalance in each time period; P wind ( t )express t The output power of wind power equipment at all times; P solar ( t )express t The output power of photovoltaic equipment at all times; P col ( t )for t Hydrogen production power of the time-sensitive system; P NH3 ( t )for t The power consumption of the ammonia synthesis equipment to produce ammonia gas at all times; P discharge ( t () represents the discharge power of the stored energy at time t; P charge ( t ) represents the charging power of the stored energy at time t; P cur ( t () represents the power wasted by the system at time t; The hydrogen power balance constraint is expressed as follows: (13) In the formula: MNH 3 H 2( t ) is the first t Hydrogen demand for ammonia synthesis in a given period; M SOG,in ( t ), M SOG,out ( t These are hydrogen storage tanks. t The amount of hydrogen added and released at any given time; M col ( t)for t The amount of hydrogen produced by the electrolyzer at any given time.

[0017] The rolling optimization-based synergistic optimization method for electrolyzers, energy storage, and hydrogen storage in off-grid ammonia synthesis parks provided in this application has at least the following beneficial effects: This application focuses on off-grid integrated wind-solar-hydrogen-ammonia systems, addressing the dual challenges of highly intermittent wind and solar resources and rigid load demand. It proposes a rolling optimization strategy for the electrolyzer-energy storage-hydrogen storage co-optimization approach. Through constructing a multi-device collaborative scheduling model and conducting 8760 hours of annual operation simulation, the significant advantages of the proposed strategy in improving the system's renewable energy absorption capacity and operational economy are verified, as detailed below: 1) The proposed collaborative optimization strategy based on an 8-hour rolling time domain effectively improves the system's operating performance. Through the operating condition identification mechanism and forward-looking scheduling, the system can dynamically adjust the current equipment operating status according to the wind and solar power information of the next scheduling cycle, realizing the collaborative control of energy storage and hydrogen storage.

[0018] 2) The electrolyzer cascade control and the synergistic mechanism of energy storage and hydrogen storage significantly improve system flexibility. The electrolyzer is dynamically adjusted based on real-time power margin through fine-grained cascade control. The complementary synergy between energy storage and hydrogen storage in terms of time scale and adjustment depth constructs a three-dimensional energy buffer system.

[0019] 3) Typical daily operation analysis verified the adaptability of the strategy under different operating conditions. Under high wind and solar conditions, the system effectively avoided power curtailment during peak hours through proactive scheduling of "emptying energy storage, releasing hydrogen storage, and increasing load"; under low wind and solar conditions, the system successfully avoided unplanned shutdowns of the ammonia synthesis unit through a pre-reserve strategy of "maintaining energy storage, charging hydrogen storage, and reducing load", reducing downtime from 3520 hours to 1224 hours and ensuring production continuity; under medium wind and solar conditions, the system demonstrated good scheduling flexibility and operational stability. Attached Figure Description

[0020] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0021] Figure 1 A flowchart of a collaborative optimization method for electrolyzer-energy storage-hydrogen storage in an off-grid synthetic ammonia park based on rolling optimization is provided for embodiments of this application; Figure 2 This is a structural diagram of an off-grid integrated wind-solar-hydrogen-ammonia system provided in an embodiment of this application; Figure 3 A flowchart illustrating the analytical criteria based on ammonia synthesis conditions provided in this application embodiment; Figure 4 This is a flowchart illustrating the coordinated scheduling of electrolyzer-energy storage-hydrogen storage provided in an embodiment of this application. Figure 5 The following are the power balance diagrams for traditional and rolling optimized scheduling of an off-grid wind-solar-hydrogen-ammonia system provided in the embodiments of this application; Figure 6 A system operation status diagram of traditional scheduling under a typical daytime high wind and solar power conditions provided in this application embodiment; Figure 7 A system operation status diagram of typical daytime rolling optimization scheduling for high wind and solar power provided in the embodiments of this application.

[0022] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0023] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0024] The collection, storage, use, processing, transmission, provision, and disclosure of financial data or user data involved in the technical solution of this application all comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0025] It should be noted that in the embodiments of this application, certain software, components, models and other existing solutions in the industry may be mentioned. These should be regarded as exemplary and are only intended to illustrate the feasibility of implementing the technical solution of this application. However, they do not mean that the applicant has used or necessarily used the solution.

[0026] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will be described below with reference to the accompanying drawings.

[0027] This application provides a rolling optimization method for the coordinated optimization of electrolyzer series, energy storage, and hydrogen storage in an off-grid synthetic ammonia park. Figure 1A flowchart illustrating a synergistic optimization method for off-grid ammonia synthesis park electrolyzer series-energy storage-hydrogen storage based on rolling optimization, provided in this application embodiment, is shown below. Figure 1 As shown, the multimodal fake news detection method includes the following steps S10 to S40.

[0028] S10: Construct an off-grid integrated wind-solar-ammonia system.

[0029] Based on the different power generation methods, integrated wind-solar-hydrogen-ammonia systems are generally divided into two categories: one is the grid-connected wind-solar-hydrogen-ammonia system, which consists of wind and solar generator sets, electrolytic hydrogen production equipment, ammonia synthesis equipment, and an upstream power grid. The other is the off-grid wind-solar-hydrogen-ammonia system. Unlike the grid-connected system, the off-grid system generates electricity independently from wind and solar power equipment and supplies it to the hydrogen and ammonia production equipment. Because it does not interact with the grid, it requires energy storage and other equipment to cope with the fluctuations and uncertainties of wind and solar power generation, i.e., peak shaving and valley filling of electricity. The advantage of the grid-connected ammonia synthesis system is that it can smooth out the fluctuations of wind and solar power and supply hydrogen and ammonia production equipment through grid power supply, improving the stability of chemical load operation. However, it also has many disadvantages: 1) The large-scale integration of renewable energy sources such as wind and solar can cause fluctuations in grid voltage and frequency; 2) The grid-connected ammonia production system is limited to areas with reliable grid power supply and cannot operate stably in remote areas. 3) While grid-connected ammonia synthesis systems operate stably, their clean energy efficiency is limited by the grid's energy structure. Given that thermal power remains the primary power source, they lack the clean production advantages of off-grid systems. The advantages of off-grid ammonia synthesis systems include: 1) All power generation is from renewable energy sources, ensuring the cleanliness of green ammonia; 2) They can operate independently in remote areas far from the grid; 3) They offer high flexibility, with the scale of production equipment and the capacity configuration of energy storage and hydrogen production units adjustable according to actual needs and resource conditions; 4) They do not require the construction of substations or other grid-connected supporting facilities, resulting in a shorter construction period. However, the disadvantages of off-grid systems lie in their relatively high investment and the need for substantial energy and hydrogen storage to cope with fluctuations in wind and solar power.

[0030] The above comparative analysis shows that the off-grid integrated wind-solar-hydrogen-ammonia system has significant advantages in clean production, regional adaptability, and configuration flexibility, making it particularly suitable for regions with abundant renewable energy but weak grid infrastructure. The structural diagram of the off-grid integrated wind-solar-hydrogen-ammonia system proposed in this embodiment is shown below. Figure 2 As shown. The system includes a power generation module: wind and solar generator sets and electrical energy storage; a hydrogen production module: electrolyzer, hydrogen storage tank, and purification device; and an ammonia synthesis module: air separation nitrogen production equipment, ammonia synthesis equipment, and a scheduling module.

[0031] S20: Based on the off-grid integrated wind-solar-ammonia system, establish an off-grid integrated wind-solar-ammonia system model.

[0032] In this embodiment, the off-grid integrated wind-solar-ammonia system model includes a system equipment model, which includes a wind and solar generator model, an electrolyzer equipment model and constraints, an air separation equipment model and constraints, an ammonia synthesis equipment model and constraints, a hydrogen storage tank model and constraints, and an energy storage equipment model and constraints, as detailed below: (1) Wind and solar generator model The output power of a wind and solar power generator is determined by the installed capacity of the wind and solar power equipment, and its expression is: (1) In the formula: P wind ( t )express t The output power of wind power equipment at all times; P wind,max Indicates the installed capacity of wind power equipment; P solar ( t )express t The output power of photovoltaic equipment at all times; P solar,max This indicates the installed capacity of photovoltaic equipment.

[0033] (2) Electrolytic cell equipment model and constraints In the integrated wind-solar-hydrogen-ammonia system constructed in this paper, the entire electrolyzer system consists of multiple rows of electrolyzers. Each row of electrolyzers operates independently, starting and stopping simultaneously without interference. The specific model expression for the electrolyzer equipment is as follows: (2) In the formula: P col,1 ( t ), P col,2 ( t ), P col,i ( t ) are respectively the 1st column, the 2nd column, i Electrolytic cells in t Hydrogen production capacity at any given time; P col ( t )for t Hydrogen production power of the time-sensitive system; M col,1 ( t ), M col,2 ( t ), M col,i ( t ) are respectively the 1st column, the 2nd column, i Electrolytic cells int Hydrogen production at any given time; M col ( t )for t The hydrogen production rate of the electrolyzer at any given time; λ H2 This represents the power consumption coefficient for hydrogen production in the electrolyzer.

[0034] When multiple electrolytic cells are running, in order to ensure stable system operation, the electrolytic cells should meet corresponding power and start-stop constraints, the specific expressions of which are: (3) In the formula: P col,min , P col,max This indicates the lower and upper limits of the operating power of each column of electrolytic cells; u i ( t ) represents the decision variable for operation. t Time of the first i Is the electrolytic cell in operation? ystart i ( t ), ystop i ( t ) are respectively t Time of the first i List the start-up and shutdown variables of the electrolytic cell, where 0 represents shutdown and 1 represents start-up.

[0035] (3) Air separation equipment model and constraints The air separation equipment employs cryogenic distillation technology, using multi-stage compression, cooling, and distillation separation to extract high-purity nitrogen from the air, providing feedstock for the subsequent ammonia synthesis process. Its expression is: (4) In the formula: P ASU ( t )for t The power consumption of the air separation unit to generate nitrogen at any given time; λ N2 The power consumption coefficient for nitrogen production in air separation equipment; M N2 ( t )for t The amount of nitrogen produced at any given time; P ASU,max This is the maximum power of the air separation unit.

[0036] (4) Ammonia synthesis equipment model and constraints This embodiment employs an ammonia synthesis unit based on the Haber-Bosch process, which is currently the mainstream technology for industrial ammonia synthesis. Under high temperature and high pressure conditions, nitrogen and hydrogen react to produce ammonia in the presence of an iron-based catalyst. The ammonia synthesis unit model is as follows: (5) In the formula: M NH3 ( t For ammonia synthesis equipment t Ammonia production at any given time; P NH3 ( t )for t The power consumption of the ammonia synthesis equipment to produce ammonia gas at all times; λ NH3 The power consumption coefficient for ammonia production in ammonia synthesis equipment; P NH3,q ( t () represents the power consumption of the ammonia synthesis equipment under different load conditions; Operating condition index q The range from 1 to 10 corresponds to power levels of 0 MW (shutdown state), 26 MW (minimum load) to 34 MW (full load operation), with a power step of 1 MW.

[0037] Based on the process characteristics of ammonia synthesis, each load condition range needs to maintain stable operation for 8 hours, and the load power of the unit must remain constant within a single scheduling cycle. The specific expressions and constraints are as follows: (6) In the formula: P NH3 ( j , h ) is the first j Within the scheduling cycle, the first h The power consumed by the ammonia synthesis equipment per hour; P NH3 ( j ) is the first j Power consumption of the ammonia synthesis equipment per cycle; ρ NH3 ( j , h ) is the first j Within the scheduling cycle, the first h The load rate of the ammonia synthesis equipment per hour; ρ NH3 ( j ) is the first j Load rate of the ammonia synthesis equipment in each cycle; y NH3 ( t )for tThe start / stop variable for the ammonia synthesis equipment is 0, which indicates shutdown and 1 indicates operation.

[0038] (5) Hydrogen storage tank model and constraints Hydrogen storage tanks, as the hydrogen supply energy source in the system, play a role in mitigating hydrogen fluctuations. The specific expression is as follows: (7) In the formula: M SOG ( j ), M SOG ( j -1) are respectively the first j The, the j -1 scheduling cycle of hydrogen storage; E remain ( j ) is the first j Remaining power for each scheduling cycle; E area,H2 ( j This is the upper limit of hydrogen storage capacity for the current scheduling cycle, ensuring that the hydrogen storage process does not exceed the hydrogen storage tank capacity limit or the available power limit; β H2 The electro-hydrogen conversion coefficient; P general ( j ) is the first j Average power generation of wind and solar power over a scheduling cycle; P col ( j ) is the first j Hydrogen production capacity of the electrolyzer per scheduling cycle; M SOG,max This is the maximum hydrogen capacity for the hydrogen storage tank.

[0039] The operating constraints of the hydrogen storage tank are: (8) In the formula: M SOG,in ( t ), M SOG,out ( t These are hydrogen storage tanks. t The amount of hydrogen added and released at any given time; y H2,in ( t ), y H2,out ( t ) represents the state variable of the hydrogen storage tank at time t, where 0 represents stopping and 1 represents running; M SOG (0) represents the initial hydrogen storage capacity of the hydrogen storage tank equipment.

[0040] (6) Energy storage device model and constraints Due to the intermittent and fluctuating nature of renewable energy generation, off-grid renewable energy systems must be equipped with energy storage devices to ensure system power balance and operational stability. The device model expression is as follows: (9) In the formula: E SOC ( j ), E SOC ( j -1) are respectively the first j The, the j -The amount of electricity stored within the energy storage device over one scheduling cycle; Δ E SOC ( j ) is the first j The charge and discharge capacity of the energy storage device in each scheduling cycle; Δ E SOC,in ( j ) for energy storage devices in the first j The amount of charge per scheduling cycle; Δ E SOC,out ( j ) for energy storage devices in the first j Discharge amount per scheduling cycle; E SOC,u ( j The energy storage is the available charging capacity for the j-th scheduling cycle; E SOC,n ( j ) represents the remaining capacity of energy storage in the j-th scheduling cycle; E SOC,d ( j ) represents the discharge demand of the energy storage in the j-th cycle.

[0041] The operating state constraints for energy storage are: (10) In the formula: E SOC,max This represents the maximum charging and discharging power of the energy storage. y in ( t ), y out ( t ) represents the charging and discharging state variables of energy storage, where 0 indicates stop and 1 indicates operation; E SOC (0) represents the initial electrical quantity of the energy storage device.

[0042] S30: Based on the off-grid integrated wind-solar-ammonia system model, design a multi-device collaborative optimization strategy based on an n-hour rolling time domain, and divide the system operating status into three types of operating conditions through an operating condition identification mechanism.

[0043] Off-grid synthetic ammonia industrial parks face the dual challenges of highly intermittent wind and solar resources and rigid load demand. Electrolyzers, energy storage devices, and hydrogen storage facilities within the system need to operate efficiently and collaboratively under limited energy supply. Traditional single-equipment optimization strategies often neglect the coupling relationship between equipment, resulting in low overall operating efficiency and insufficient energy utilization.

[0044] To address this issue, this embodiment proposes a multi-device collaborative optimization strategy based on rolling time domain. This strategy employs an 8-hour rolling time domain optimization window, combining actual operating data for the current period with wind and solar power output information for the next period to achieve dynamic coordination of electrolyzer-level control, energy storage power balance, and hydrogen storage capacity management.

[0045] Ammonia synthesis condition identification, as the core judgment step of rolling optimization, directly determines the subsequent equipment scheduling strategy. This embodiment establishes a three-level operating condition classification criterion based on the power supply and demand balance: high-generation conditions correspond to sufficient renewable energy, where the system operates at maximum load and stores excess energy; low-generation conditions correspond to severe energy shortages, requiring the cessation of ammonia synthesis production to protect the equipment; and intermediate conditions achieve cross-time period energy optimization allocation through refined control and rolling prediction mechanisms.

[0046] To clearly demonstrate the logic and decision-making process for assessing operating conditions, Figure 3 This is a flowchart illustrating the complete analytical criteria based on ammonia synthesis operating conditions. Specifically, it sets the scheduling cycle... j =0, execute after entering the loop. j = j +1 signifies entering the [number]th [stage / section]. j The current scheduling cycle. Collect the current data for the [number]th cycle. j The average power output of wind and solar power generation over 8 hours for each scheduling cycle is determined, and the real-time status of energy storage (SOC) and hydrogen storage (SOG) is acquired simultaneously to provide basic data for subsequent condition assessment and scheduling decisions. The determination of the first... j The system roughly calculates the ammonia synthesis operating conditions for each scheduling cycle, updates the ammonia synthesis operating conditions, schedules the electrolyzer, energy storage, and hydrogen storage, and performs energy storage and hydrogen storage status updates. It then determines whether j=1095 is valid; if yes, the analysis process ends; otherwise, it sets... j = j +1. Among them, determine the first... j The general steps of ammonia synthesis operation in a scheduling cycle are as follows: Observe the average power of wind and solar power generation during the (j+1)th scheduling cycle, compare the average power of this cycle with the equipment load value under the ammonia synthesis condition, and determine the operating condition type: If Pgeneral ( j > P sim,max ( j If ), then it is judged as a high wind and solar power condition. P sim,max ( j )≤ P general ( j )≤ P sim,min ( j If ), then it is judged to be a medium wind and solar operating condition. P general ( j )< P sim,min ( j If the wind and solar conditions are low, then it is judged as a low wind and solar operating condition.

[0047] The operating condition assessment considers not only real-time data within the current 8-hour window but also wind and solar information for the next period. This rolling prediction-based operating condition identification mechanism is the foundation for achieving global optimization and can effectively improve the system's adaptability to wind and solar fluctuations.

[0048] S40: Based on the operating condition identification results and combined with the wind and solar power information for the next scheduling cycle, adjust the current equipment operation plan to achieve coordinated control of electrolyzers at the column level and energy storage and hydrogen storage.

[0049] The operating condition assessment considers not only real-time data within the current 8-hour window but also wind and solar power information for the next period. This rolling prediction-based operating condition identification mechanism is the foundation for global optimization and effectively improves the system's adaptability to wind and solar power fluctuations. In off-grid integrated wind-solar-hydrogen-ammonia systems, electrolyzers, energy storage, and hydrogen storage devices are key components for energy conversion and storage, and their coordinated scheduling directly impacts the system's operating efficiency and economy. Step S40, based on the operating condition identification results of S30, proactively adjusts the equipment operation plan for the current period by observing the wind and solar power status for the next scheduling cycle. Figure 4 This is a flowchart of a coordinated scheduling strategy for electrolyzers, energy storage, and hydrogen storage. (Example:) Figure 4 As shown, this embodiment uses an electrolyzer-energy storage-hydrogen storage coordinated scheduling strategy to achieve coordinated control of the electrolyzer series and the coordinated control of energy storage and hydrogen storage. The implementation steps of this electrolyzer-energy storage-hydrogen storage coordinated scheduling strategy are as follows: 1) When the system observes the first j When the wind and solar power output exceeds the combined maximum load of ammonia synthesis and electrolysis in the next scheduling cycle, it indicates that a large amount of surplus renewable energy will need to be absorbed in the next cycle. To maximize the overall absorption capacity of the system, the first... jEach cycle employs a forward-looking dispatch strategy of "emptying energy storage, releasing hydrogen storage, and increasing load." The advantage of this strategy lies in its ability to adjust the energy and hydrogen storage status in advance, thus avoiding wind and solar curtailment due to insufficient storage capacity in the next cycle. This significantly improves the system's adaptability to high-incidence operating conditions and the renewable energy consumption rate.

[0050] 2) When the system predicts the first j If the wind and solar power output falls below the minimum operating power for ammonia synthesis in the next scheduling cycle, it indicates a severe energy shortage in the next cycle, potentially leading to a shutdown risk. To ensure continuous and stable system operation, the first... j Each cycle employs a pre-reserve scheduling strategy of "maintaining energy storage, replenishing hydrogen storage, and reducing load." This pre-reserve strategy improves the reliability of system operation by sacrificing some capacity in the current cycle in exchange for operational stability in the next cycle.

[0051] 3) When the system predicts the first j When wind and solar power are at an intermediate level for one scheduling cycle, it indicates that energy supply and demand are basically balanced in the next cycle, and the system has considerable scheduling flexibility. j Each cycle employs a conventional optimization strategy of "balanced optimization, flexible scheduling, and appropriate reserves." This balanced optimization strategy fully utilizes the scheduling flexibility of the intermediate-cycle operation, laying the foundation for the long-term efficient operation of the system.

[0052] Through the aforementioned collaborative scheduling process based on rolling forecasts, the system can proactively adjust the current operating status of equipment according to future operating conditions, achieve cross-cycle energy optimization configuration, and significantly improve the system's adaptability to renewable energy fluctuations.

[0053] The feasibility and progressiveness of the proposed method will be further illustrated below with specific examples.

[0054] The optimization model for the off-grid integrated wind-solar-hydrogen-ammonia system established in this embodiment aims to minimize the system operating cost. It comprehensively considers the costs of wind and solar curtailment, electrolyzer start-up and shutdown costs, and power imbalance penalty costs. The objective function expression is as follows: (11) In the formula: P cur ( j ) is the first j The amount of electricity wasted in each scheduling cycle; α This represents the cost coefficient for abandoned electricity. N H2 ( j ) for the first j The number of electrolytic cell operation trains per scheduling cycle; β This is the single-row start-up and shutdown cost coefficient for the electrolytic cell; P balance (j ) is the first j The imbalance in each scheduling cycle; δ This is the power imbalance penalty factor; F This refers to the system operating cost.

[0055] The corresponding constraints include: (1) Electric power balance constraint The system must maintain a balance between power supply and demand at every time period to ensure stable operation. (12) In the formula: P balance ( t ) is the first t The imbalance in each time period; P discharge ( t () represents the discharge power of the stored energy at time t; P charge ( t ) represents the charging power of the stored energy at time t; P cur ( t The value t represents the power wasted by the system at time t.

[0056] (2) Hydrogen power balance constraint As a key raw material for ammonia synthesis, the supply and demand balance of gas directly affects the stability of system operation. (13) In the formula: MNH 3 H 2( t ) is the first t The hydrogen demand for ammonia synthesis during a specific period.

[0057] The off-grid integrated wind-solar-hydrogen-ammonia system proposed in this embodiment is based on the annual wind and solar power output data of a certain region in Northeast China. With the objective of minimizing the total system operating cost, a mixed-integer programming model is employed. The optimal system scheduling result is obtained by solving the model using the Guorbi solver in MATLAB. The system's equipment scale and related technical parameters are shown in Tables 1 and 2.

[0058] Table 1 Equipment Scale of Off-Grid Ammonia Synthesis System

[0059] Table 2 Technical Parameters of Key Equipment

[0060] Based on the above system parameter configuration and optimization model, this section analyzes the optimized scheduling results of the off-grid wind-solar-hydrogen-ammonia integrated system over 8760 hours throughout the year. This embodiment sets up two scheduling schemes to compare with the optimized operation strategy proposed in this application: 1) Scheme 1, traditional scheduling strategy (simple rule-based scheduling based on the average wind and solar output over an 8-hour cycle, using a step-by-step trial-and-error decision-making mode). 2) Scheme 2, scheduling strategy based on sliding window rolling optimization. The system optimization results are shown in Table 3.

[0061] Table 3 System Optimization Results

[0062] Comparative analysis results show that, under the same annual wind and solar power generation conditions, the traditional dispatch strategy (Scheme 1), which adopts a simple rule-based dispatch and step-by-step trial-and-error decision-making mode based on the average wind and solar power output over an 8-hour cycle, performs poorly: the amount of abandoned power reaches 670.13 GWh, the abandonment rate reaches 24.2%, the synthetic ammonia production is only 105,000 tons, the synthetic ammonia downtime is as long as 3,520 hours (about 40% of the year), the revenue from ammonia sales is 420 million yuan, and the hydrogen demand for synthetic ammonia is 18,900 tons. However, after adopting the collaborative optimization strategy based on the 8-hour rolling time domain (Scheme 2), the system achieves coordinated control of energy storage and hydrogen storage through multi-equipment collaboration and cross-cycle optimized dispatch. The renewable energy consumption rate is significantly improved, the wind and solar power abandonment rate is significantly reduced to below 15.0%, the synthetic ammonia production increases to 144,500 tons (an increase of 37.6%), the equipment downtime is shortened to 1,224 hours (a decrease of 65.3%), and the revenue from ammonia sales increases to 578 million yuan (an increase of 37.6%).

[0063] Based on 8760 hours of wind and solar data throughout the year, this embodiment selects three typical days—high wind and solar operating conditions, medium wind and solar operating conditions, and low wind and solar operating conditions—for comparative analysis. The operation scheduling analysis for different typical days is as follows: Figure 5 As shown.

[0064] Figure 5This paper presents a comparison of the power balance of an off-grid wind-solar-hydrogen-ammonia (HMA) system under three typical days using traditional and rolling optimization scheduling strategies. From the overall operational performance, the traditional scheduling strategy (left figure) exhibits significant power overflow during peak wind and solar power periods (0-24h), with wind and solar power generation exceeding the system's absorption capacity. Particularly during the 10-20h period, the peak power curtailment exceeds 100MW, indicating a lack of effective forward-looking control measures. In contrast, the rolling optimization scheduling strategy (right figure), through 8-hour rolling forecasting and multi-device coordinated control, significantly improves the power balance, effectively suppressing power overflow during peak wind and solar power periods, and maintaining the system within a reasonable operating range. Under medium wind and solar power conditions (24-48h), the traditional scheduling only operates the ammonia synthesis unit in the last 8-hour cycle, while the rolling optimization strategy allows the ammonia synthesis unit to operate stably in the first scheduling cycle, demonstrating superior coordinated scheduling characteristics. The difference between the two strategies is most evident during low wind and solar power conditions (48-72 hours): traditional dispatching experiences severe power deficits during the 60-70 hour period, forcing the introduction of balancing power sources or even shutdowns; while rolling optimization, through advance reserves and fine-tuning, maintains a relatively stable power balance during the first dispatch cycle. Considering the overall performance of the three conditions, the rolling optimization strategy is significantly superior to the traditional dispatching strategy in improving renewable energy consumption, reducing wind and solar curtailment, and ensuring power supply reliability.

[0065] To more intuitively demonstrate the superiority of rolling optimization, this embodiment selects the typical operating conditions of high wind and solar power under-solar energy storage and hydrogen storage for illustration, such as... Figure 6 and Figure 7 As shown.

[0066] Figure 6 and Figure 7 This study compares the operational differences of energy storage and hydrogen storage systems under two dispatch strategies on a typical day with high wind and solar power. In the traditional dispatch strategy, the energy storage system exhibits a regular, sawtooth-shaped charging and discharging pattern. This mechanical, periodic operation reflects a passive response control logic—simple charging and discharging operations are only performed when power exceeds limits, lacking a comprehensive consideration of the overall system operation. The hydrogen storage system shows a monotonically increasing trend, treating the hydrogen storage tank only as a one-way energy buffer, failing to realize its bidirectional regulation potential. The rolling optimization strategy, however, demonstrates significant synergistic advantages: the energy storage system actively performs deep discharge in the early morning to reserve capacity for daytime peak periods, and then flexibly adjusts the charging and discharging depth based on real-time power; the hydrogen storage system exhibits a dynamic characteristic of "pre-release-rapid charging and storage-flexible adjustment," actively freeing up storage space before peak periods, fully absorbing surplus energy during peak periods, and flexibly allocating power after peak periods according to demand. This multi-timescale synergistic mechanism fully leverages the complementary advantages of rapid energy storage response and large-capacity hydrogen storage, fundamentally improving the off-grid system's adaptability to wind and solar power fluctuations and the level of renewable energy absorption.

[0067] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A method for off-grid ammonia synthesis park cell string- energy storage- hydrogen storage collaborative optimization based on rolling optimization, characterized in that, The method comprises: Constructing an off-grid wind-solar-ammonia-ammonia integrated system; wherein the off-grid wind-solar-ammonia-ammonia integrated system comprises a power generation module, a hydrogen production module, a synthetic ammonia module and a scheduling module; the power generation module comprises a wind-solar generator set and an electric energy storage, the hydrogen production module comprises multiple columns of independently operated electrolytic cells, a hydrogen storage tank and a purification device, and the synthetic ammonia module comprises an air separation nitrogen making device and a synthetic ammonia device; Based on the off-grid wind-solar-ammonia-ammonia integrated system, an off-grid wind-solar-ammonia-ammonia integrated system model is established, which comprises a wind-solar generator set model, an electrolytic cell device model and constraints, an air separation device model and constraints, a synthetic ammonia device model and constraints, a hydrogen storage tank model and constraints, and an energy storage device model and constraints; Based on the off-grid wind-solar-ammonia-ammonia integrated system model, a multi-device collaborative optimization strategy based on n-hour rolling time domain is designed, and the system operating state is divided into three types of working conditions through a working condition identification mechanism; wherein the three types of working conditions are high generation condition, medium generation condition and low generation condition; the working condition identification mechanism is based on the power supply and demand balance relationship, the high generation condition corresponds to the renewable energy sufficient condition, the low generation condition corresponds to the serious energy shortage condition, and the intermediate condition corresponds to the basic balance condition of energy supply and demand. Based on the working condition identification result, the current device operation scheme is adjusted combined with the wind-solar power information of the next scheduling period, to realize the electrolytic cell column level regulation and control, the collaborative regulation and control of energy storage and hydrogen storage.

2. The off-grid synthetic ammonia park electrolyzer train-level energy storage-hydrogen storage co-optimization method based on rolling optimization according to claim 1, characterized in that, The way of adjusting the current device operation scheme based on the working condition identification result and combined with the wind-solar power information of the next scheduling period to realize the electrolytic cell column level regulation and control, the collaborative regulation and control of energy storage and hydrogen storage comprises: Under high load conditions, when the predicted wind and solar power in the first j +1 scheduling period exceeds the sum of the maximum load of the ammonia synthesis and the electrolyzer, the first j period adopts the scheduling strategy of emptying the energy storage, releasing the hydrogen storage, and increasing the load, and by adjusting the state of the energy storage and hydrogen storage in advance to reserve storage capacity, wind and solar power curtailment in the next period is avoided. When the predicted first j +1 scheduling cycle wind-solar power is lower than the minimum ammonia running power, the first j cycle adopts the scheduling strategy of energy storage maintenance, hydrogen storage charging and storage, and load reduction, and the next cycle system stable operation is ensured through energy pre-reserve. Under the intermediate working condition, when the predicted wind-solar power in the next j +1 scheduling period is at the intermediate level, the scheduling strategy of balance optimization, flexible scheduling, and moderate reserve is adopted in the next j period to realize the balance optimization of energy supply and demand and lay the foundation for long-term efficient operation of the system.

3. The off-grid synthetic ammonia park electrolyzer train-level energy storage-hydrogen storage co-optimization method based on rolling optimization according to claim 1, characterized in that, The wind-solar generator set model is represented as: （1） In the formulae: P wind t represents t the output power of the wind power plant at the time instant t; P wind,max represents the installed capacity of the wind power plant; P solar t represents t the output power of the photovoltaic plant at the time instant t; P solar,max represents the installed capacity of the photovoltaic plant.​​ 4. The off-grid synthetic ammonia park electrolyzer train-level energy storage-hydrogen storage co-optimization method based on rolling optimization according to claim 1, wherein, The electrolytic cell device model and constraints are represented as: （2） In the formula: P col,1 t P col,2 t P col,i t are the hydrogen production powers of the 1st column, 2nd column and 3rd column electrolytic cells at the time of t; i t P col t t is the hydrogen production power of the system at the time of t; M col,1 t M col,2 t M col,i t are the hydrogen production amounts of the 1st column, 2nd column and 3rd column electrolytic cells at the time of t; i t M col t t is the hydrogen production amount of the electrolytic cell at the time of t; λ H2 is the electricity consumption coefficient of the hydrogen production of the electrolytic cell;​​​​​​​​​​​​​​​​​​ （3） In the formula: P col,min and P col,max represent the lower limit value and the upper limit value of the operating power of each column of electrolytic cells; u i t ) and u i t -1) are respectively the operating decision variables at the time of t and the time of t -1, indicating whether the t column of electrolytic cells is running at the time of t and the time of i -1; ystart i t ) and ystop i t are respectively the start-up variable and the shutdown variable of the t column of electrolytic cells at the time of i , 0 indicating shutdown and 1 indicating start-up.​​​​ 5. The off-grid synthetic ammonia park electrolyzer train-level energy storage-hydrogen storage co-optimization method based on rolling optimization according to claim 1, wherein, The air separation device model and constraints are represented as: （4） wherein: P ASU t t the power consumption of the air separation unit at the moment of production of nitrogen; λ N2 the power consumption coefficient of the air separation unit for production of nitrogen; M N2 t t the output of nitrogen at the moment; P ASU,max the maximum power of the air separation unit.​​​​ 6. The off-grid synthetic ammonia park electrolyzer train-level energy storage-hydrogen storage co-optimization method based on rolling optimization according to claim 1, wherein, The synthetic ammonia device model and constraints are represented as: （5） In the formula: M NH3 t is the ammonia production of the ammonia synthesis plant at the time instant; t P NH3 t t is the power consumption of the ammonia synthesis plant for producing ammonia at the time instant; λ NH3 is the power consumption coefficient of the ammonia synthesis plant for producing ammonia; P NH3,q t is the power consumption of the ammonia synthesis plant at different load conditions; q is the load condition index;​​​​​ （6） In the formula: P NH3 ( j , h ) is the first j Within the scheduling cycle, the first h The power consumed by the ammonia synthesis equipment per hour; P NH3 ( j ) is the first j Power consumption of a single-cycle ammonia synthesis unit; The hydrogen storage tank model and constraints are represented as: NH3 ( j , h ) is the first j Within the scheduling cycle, the first h The load rate of the ammonia synthesis equipment per hour; λ NH3 ( j ) is the first j Load rate of the ammonia synthesis equipment in each cycle; y NH3 ( t )for t The start / stop variable for the ammonia synthesis equipment is 0, which indicates shutdown and 1 indicates operation.

7. The off-grid synthetic ammonia park electrolyzer train-level energy storage-hydrogen storage co-optimization method based on rolling optimization according to claim 1, characterized in that, The energy storage device model and constraints are represented as: （7） In the formula: M SOG j M SOG j j j E remain j j E area,H2 j β H2 P general j j P col j j M SOG,max min min is the minimum value function; H2 is the hydrogen production power of the electrolyzer in the nth scheduling period;​​​​​​​​​​​​​​​​​​ （8） In the formula: M SOG,in t M SOG,out t are the hydrogen charging amount and hydrogen discharging amount of the hydrogen storage tank at time t, respectively; t y H2,in t y H2,out t are the charging and discharging state variables of the hydrogen storage tank at time t, 0 is stop, and 1 is running; M SOG (0) is the initial state of the hydrogen storage tank equipment.​​​​​​​ 8. The off-grid synthetic ammonia park electrolyzer train-level energy storage-hydrogen storage co-optimization method based on rolling optimization according to claim 1, wherein, The method further comprises: （9） In the formula: E SOC j E SOC j j j E SOC j j E SOC,in j j E SOC,out j j E SOC,u j j E SOC,n j j E SOC,d j max​​​​​​​​​​​​​​​​​​​​​​ Based on the annual wind-solar output data of the target area, the minimum total cost of the off-grid wind-solar-hydrogen-ammonia integrated system is taken as the objective function, the electric power balance constraint and the hydrogen power balance constraint are taken as the constraint conditions, and a mixed integer programming model is used to solve to obtain the optimal result of system scheduling. （10） In the formula: E SOC,max is the maximum charge-discharge power of the energy storage; y in ( t ), y out ( t ) is the charge-discharge state variable of the energy storage, 0 is stopped, and 1 is running; E SOC (0) is the initial state of the energy storage device.

9. The off-grid synthetic ammonia park electrolyzer train-level- energy storage- hydrogen storage collaborative optimization method based on rolling optimization according to any one of claims 1-8, characterized in that, The objective function is represented as: δ 10. The off-grid synthetic ammonia park electrolyzer train-level energy storage-hydrogen storage co-optimization method based on rolling optimization according to claim 9, characterized in that, The electric power balance constraint is represented as: （11） In the formula: P cur j is the power abandonment amount of the first scheduling period; j α is the cost coefficient of power abandonment; N H2 j is the number of electrolytic cell operation lines of the first scheduling period; j β is the single-line start-stop cost coefficient of the electrolytic cell; P balance j is the imbalance amount of the first scheduling period; j The hydrogen power balance constraint is represented as: is the power imbalance penalty coefficient; F is the system operation cost;​​​​​​ MNH （12） In the formula: P balance t is the imbalance of the first time period; t P wind t represents the output power of the wind power equipment at time t; t P solar t represents the output power of the photovoltaic equipment at time t; t P col t is the hydrogen production power of the system at time t; t P NH3 t is the power consumption of the ammonia production equipment for producing ammonia at time t; t P discharge t represents the discharge power of the energy storage at time t; P charge t represents the charge power of the energy storage at time t; P cur t represents the abandoned power of the system at time t;​​​​​​​​​​​​​ ​ （13） In the formula: ​ 3 H 2( t ) is the first t Hydrogen demand for ammonia synthesis in a given period; M SOG,in ( t ), M SOG,out ( t These are hydrogen storage tanks. t The amount of hydrogen added and released at any given time; M col ( t )for t The amount of hydrogen produced by the electrolyzer at any given time.

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