An electricity-hydrogen-ammonia multi-scale grid-connected peak shaving method

Abstract

The application discloses a kind of electric hydrogen ammonia multiscale grid-connected peak shaving methods, it is related to new energy grid-connected scheduling and electric hydrogen ammonia coupling optimization operation technical field.The method obtains wind power, photovoltaic predicted output, grid peak shaving demand, grid-connected power constraint and system operating state, establishes the multi-time scale model of electrolytic hydrogen production fast response, hydrogen storage intermediate buffer and slow dynamic continuous operation of ammonia synthesis;In day-ahead stage, the benchmark plan of hydrogen production power, hydrogen storage state, ammonia synthesis load and peak shaving capacity is generated;In the day stage, according to the actual output of new energy and real-time peak shaving instruction is carried out rolling correction;And combined with peak shaving contribution and dynamic operation cost feedback updates scheduling strategy.The application can improve new energy consumption capacity, grid-connected power smoothness and system operation economy.

Description

Technical Field

[0001] This invention relates to the fields of new energy grid-connected dispatching, power system peak-shaving control, and optimized operation of electric-hydrogen-ammonia coupled systems. Specifically, it relates to a grid-connected peak-shaving dispatching method for an electric-hydrogen-ammonia system that takes into account the rapid response of electrolytic hydrogen production, the buffer regulation of hydrogen storage, and the slow dynamic constraints of synthetic ammonia. Background Technology

[0002] With the large-scale integration of new energy sources such as wind power and photovoltaics into the power system, the randomness and volatility of their output are causing the peak-to-valley difference in the system's net load to continuously increase, placing higher demands on flexible peak-shaving resources. The electricity-hydrogen-ammonia coupling pathway can convert surplus new energy power into hydrogen and further synthesize ammonia, combining the value of new energy consumption, long-term energy storage, and green chemical substitution. Therefore, it is considered an important technical path to support a high proportion of new energy grid connection.

[0003] Existing dispatching methods often simplify the electricity-hydrogen-ammonia system into a single energy conversion load, focusing primarily on hydrogen production costs, ammonia production revenue, or renewable energy consumption, without fully considering the significant differences in dynamic response speeds between electrolytic hydrogen production, hydrogen storage buffering, and ammonia synthesis processes. Electrolytic hydrogen production can adjust power output in a relatively short time, making it suitable for responding to grid peak-shaving commands; however, the ammonia synthesis process is limited by temperature, pressure, catalytic reactions, and continuous production conditions, exhibiting slow inertia and strong constraints, making frequent and rapid adjustments difficult.

[0004] Therefore, when the grid's peak-shaving demand changes rapidly or when there are short-term deviations in renewable energy output, the lack of a multi-timescale coordination mechanism can easily lead to a mismatch between hydrogen production power regulation and stable ammonia synthesis operation, thereby affecting the peak-shaving response effect and system economy. There is an urgent need for a grid-connected peak-shaving scheduling method that can coordinate fast and slow dynamic processes, take into account both day-ahead planning and intraday corrections, and quantify peak-shaving contributions and dynamic operating costs. Summary of the Invention

[0005] To address the shortcomings in existing power-hydrogen-ammonia (HHM) systems' grid-connected peak-shaving scheduling, such as insufficient consideration of differences in dynamic response speed, weak integration between day-ahead planning and intraday corrections, and difficulty in quantifying peak-shaving contributions and operating costs, this invention proposes a multi-scale grid-connected peak-shaving method for HHM. This invention constructs a multi-timescale scheduling model for the electrolysis hydrogen production, hydrogen storage buffer, and ammonia synthesis processes, forming a closed-loop scheduling mechanism that combines day-ahead economic scheduling with intraday rolling corrections. This achieves a coordinated improvement in renewable energy consumption, grid peak-shaving response, and system operational economy.

[0006] To achieve the above objectives, the present invention proposes the following technical solution: A multi-scale grid-connected peak-shaving method for electro-hydrogen ammonia, the method comprising the following steps: 1) Obtain grid-connected peak-shaving dispatch information: Obtain wind power forecast output, photovoltaic power forecast output, grid load forecast, grid-connected power constraints, grid peak-shaving demand, electricity price, peak-shaving compensation price, and the operating status of the electricity-hydrogen-ammonia system within the dispatch period; the operating status of the electricity-hydrogen-ammonia system includes electrolysis hydrogen production power, hydrogen storage capacity, hydrogen supply and demand balance, synthetic ammonia load, ammonia production plan, and system adjustability margin; 2) Establish a fast and slow dynamic response difference model: Based on the operating characteristics of the electrolytic hydrogen production, hydrogen storage buffer and ammonia synthesis processes, establish a multi-time scale scheduling model; among them, the electrolytic hydrogen production link participates in grid peak regulation as a fast adjustable load, the hydrogen storage link serves as a buffer variable between electrolytic hydrogen production and ammonia synthesis, and the ammonia synthesis link serves as a slow dynamic load constrained by continuous operation, safety boundary and load change rate. 3) Generate day-ahead baseline dispatch plan: Under the day-ahead dispatch scale, with the goal of maximizing the overall system benefits, comprehensively consider the revenue from ammonia sales, peak shaving compensation revenue, green electricity consumption revenue, electricity cost, operating cost, wind and solar curtailment penalty cost and peak shaving deviation penalty cost to determine the baseline power for electrolytic hydrogen production, the baseline state for hydrogen storage, the baseline load for synthetic ammonia and the peak shaving capacity that can be provided to the grid. 4) Implement intraday rolling adjustments: Under the intraday dispatch scale, the day-ahead baseline dispatch plan is rolled over based on the actual output of new energy sources, forecast errors, hydrogen storage status, and real-time peak-shaving instructions from the power grid. When the actual output of new energy sources is higher than the forecast value or the power grid requires a reduction in grid-connected power, the electrolysis hydrogen production power is increased and the hydrogen storage capacity is increased. When the actual output of new energy sources is lower than the forecast value or the power grid requires a increase in grid-connected power, the electrolysis hydrogen production power is reduced and the hydrogen storage buffer is activated, while simultaneously constraining the synthetic ammonia load to be smoothly adjusted within the allowable range. 5) Peak shaving contribution and dynamic cost feedback: Based on the scheduling execution results, calculate the peak shaving command tracking deviation, new energy consumption, wind and solar curtailment reduction, hydrogen storage safety margin, ammonia production plan completion rate and dynamic operating cost, and update the electrolytic hydrogen production power boundary, hydrogen storage safety range, synthetic ammonia load plan and optimization weight for subsequent scheduling cycles, forming a closed-loop scheduling process of day-ahead planning, intraday correction, execution feedback and re-optimization.

[0007] Furthermore, the difference in fast and slow dynamic response includes the minute-level power regulation characteristics of hydrogen electrolysis, the intermediate-scale buffer characteristics of hydrogen storage, and the hour-level slow inertial regulation characteristics of ammonia synthesis.

[0008] Furthermore, the day-ahead scheduling metric is used to determine the system's baseline operating plan and peak-shaving capacity in the next scheduling cycle, while the intraday scheduling metric is used to respond to short-term forecast errors of new energy sources and real-time peak-shaving instructions from the power grid.

[0009] Furthermore, the dynamic operating costs include the cost of fluctuations in hydrogen production power due to electrolysis, the cost of hydrogen storage deviating from the safe range, the cost of ammonia synthesis load shift, the cost of peak shaving response deviation, and the cost of penalties for wind and solar power curtailment.

[0010] Furthermore, the hydrogen storage component is used to decouple the contradiction between the rapid power regulation of electrolytic hydrogen production and the slow dynamic stability of ammonia synthesis, enabling the electrolytic hydrogen production power to change rapidly in accordance with peak shaving commands, while ensuring the stable operation of the ammonia synthesis process under continuous production constraints.

[0011] Compared with existing technologies, the technical effects of this invention are as follows: This invention introduces the difference in fast and slow dynamic response within the electricity-hydrogen-ammonia system into the grid-connected peak-shaving scheduling process, avoiding the simplistic equivalent of the system to a single electricity-ammonia conversion load; it improves the system's planning for participating in grid peak shaving by determining the baseline operating plan and available peak-shaving capacity through day-ahead economic scheduling; it responds to new energy fluctuations and real-time peak-shaving commands by utilizing the rapid adjustment capability of electrolytic hydrogen production and the buffering capability of hydrogen storage through intraday rolling correction; and it achieves synergistic optimization of peak-shaving effect and operational economy through feedback of peak-shaving contribution and dynamic operating costs, thereby improving the new energy absorption capacity, grid peak-shaving efficiency, and the comprehensive benefits of the electricity-hydrogen-ammonia system. Attached Figure Description

[0012] To more clearly present the relevant technical solutions of the present invention, the accompanying drawings used in the description of the implementation methods are briefly introduced below. These drawings represent only part of the content of the present invention, and not all of it. Wherein: Figure 1 This is a schematic diagram of the grid-connected peak-shaving scheduling method for an electric-hydrogen-ammonia system that takes into account the difference in fast and slow dynamic response in an embodiment of the present invention; Figure 2 This is a schematic diagram of the fast-slow dynamic decoupling and day-to-day coordinated peak-shaving logic of the electricity-hydrogen-ammonia system in an embodiment of the present invention; Detailed Implementation

[0013] The present invention will be further described below with reference to the accompanying drawings and specific application scenarios. It should be understood that the specific embodiments described herein are only for explaining the present invention and are not intended to limit the scope of protection of the present invention.

[0014] This embodiment focuses on a grid-connected wind-solar-hydrogen-ammonia synthesis demonstration park in Northwest China. The park is connected to the regional power grid and includes a wind farm, a photovoltaic power station, an electrolysis hydrogen production unit, a hydrogen storage unit, an ammonia synthesis section, and an ammonia storage and transmission facility. Due to fluctuations in renewable energy output and constraints on grid transmission channels, the park is prone to grid-connected power limitations and wind / solar curtailment during peak photovoltaic power generation at midday, peak wind power generation at night, and off-peak load periods. Simultaneously, the grid dispatching agency requires the park to submit its available peak-shaving capacity before the day's deadline and respond to peak-shaving instructions based on actual operating conditions within the day. Therefore, this embodiment adopts... Figure 1The method for grid-connected peak-shaving scheduling of the electricity-hydrogen-ammonia system shown is combined with... Figure 2 The fast and slow dynamic decoupling logic shown enables the coordinated operation of daily planning, intraday correction, and execution feedback.

[0015] Step 1: Obtain grid connection peak shaving and scheduling information In this embodiment, a scheduling information collection and status aggregation process is first established. The scheduling cycle is 24 hours, the day-ahead scheduling interval is 1 hour, and the intraday rolling correction interval is 15 minutes. Before scheduling begins, the predicted wind power output, predicted photovoltaic power output, grid load forecast, regional grid allowable grid-connected power limit, peak-shaving demand curve, electricity price curve, and peak-shaving compensation price for the next 24 hours are obtained. Simultaneously, the current operating status of the electricity-hydrogen-ammonia system is obtained, including the electrolysis hydrogen production power, hydrogen storage capacity, hydrogen storage safety upper and lower limits, current load of the ammonia synthesis section, minimum continuous operating load, upper limit of load change rate, ammonia production plan, and peak-shaving deviation of the previous scheduling cycle.

[0016] Let the scheduling time be t The predicted output of wind power is P w ( t The predicted output of photovoltaic power is P pv ( t The local load is P L ( t The maximum allowable grid-connected power is... P g,max ( t The peak-shaving demand of the power grid is P peak ( t The total predicted output of local renewable energy is: ; After considering local load and grid capacity, the surplus renewable energy power available for electrolytic hydrogen production or peak shaving absorption is as follows: ; The actual grid-connected power can be expressed as: ; In the formula, P RE ( t )for t Real-time forecast of total new energy output; P w ( t (Forecast wind power output;) P pv ( t (This will contribute to photovoltaic forecasting;) PL ( t This represents the local load. P g,max ( t This represents the upper limit of the grid-connected power capacity allowed by the power grid. P sur ( t This represents surplus power from new energy sources; P g ( t (This refers to the actual grid-connected power.) P el ( t () represents the hydrogen production power through electrolysis; P cur ( t () represents the power of wind and solar power curtailment.

[0017] In this step, the scheduling information is not directly used to generate a hydrogen production maximization plan, but rather to determine the park's ability to support grid peak shaving at different times. P sur ( t Larger or P peak ( t When the grid connection power is required to be reduced, the system tends to increase the electrolysis hydrogen production power to absorb the surplus new energy; when the output of new energy decreases or the grid requires an increase in grid connection power, the system tends to reduce the electrolysis hydrogen production power and use the hydrogen storage unit to maintain the stable operation of the subsequent ammonia synthesis section.

[0018] To facilitate subsequent scheduling modeling, this embodiment organizes the collected information into a scheduling input vector: ; Step 2: Establish a fast and slow dynamic response difference model After completing the acquisition of grid connection and peak shaving information, this embodiment is based on Figure 2 The fast and slow dynamic decoupling relationship is shown, and a multi-timescale scheduling model is established for the electrolysis hydrogen production, hydrogen storage buffer, and ammonia synthesis sections. This model does not simply equate the electro-hydrogen-ammonia system to a single electrical load, but rather characterizes the dynamic response characteristics of each link separately, so that the hydrogen production link undertakes the task of rapid peak shaving, the hydrogen storage link undertakes the task of process buffering, and the ammonia synthesis section maintains slow dynamic stable operation.

[0019] In this embodiment, the time scale and scheduling function of each stage are shown in the table below.

[0020] Table 1. Time Scale and Scheduling Role of Each Stage ; For the electrolysis hydrogen production process, its operating power must meet the upper and lower power limits and ramp-up constraints: ; ; In the formula, P el,min and P el,max These are the minimum stable power and maximum power for hydrogen production by electrolysis, respectively. R el,up and R el,down These are the limits on the rate of increase and decrease of the electrolytic hydrogen production power.

[0021] For the hydrogen storage stage, the state changes are jointly determined by the amount of hydrogen produced and the amount of hydrogen consumed in ammonia synthesis: ; ; In the formula, H ( t )for t Hydrogen storage capacity at all times; η el The conversion coefficient for hydrogen production via electrolysis; q NH3 ( t ) represents the hydrogen consumption rate in the ammonia synthesis section; Δ t The scheduling time interval; H min and H max These represent the lower and upper limits of safe hydrogen storage, respectively. Hydrogen storage capacity. H ( t It is used to connect the rapidly changing electrolytic hydrogen production power with the relatively stable hydrogen consumption demand for ammonia synthesis.

[0022] For the ammonia synthesis section, load changes must meet the constraints of continuous operation and slow dynamics: ; ; In the formula, P NH3,min and P NH3,max These are the minimum and maximum continuous operating loads for the ammonia synthesis section, respectively. R NH3,up and R NH3,down These are the limits on the rate of increase and decrease of the ammonia synthesis load. Because the ammonia synthesis process has continuous requirements for temperature, pressure, and catalytic reaction conditions, this embodiment limits it to only small, smooth adjustments during daily rolling corrections to avoid affecting production stability due to frequent follow-up to grid peak-shaving commands.

[0023] Through the above modeling, the electrolytic hydrogen production process can rapidly absorb new energy fluctuations within a 15-minute timescale, the hydrogen storage process can balance hydrogen supply and demand on an hourly timescale, and the ammonia synthesis process can maintain continuous operation over a longer timescale. This forms a multi-timescale coordination basis for rapid hydrogen production response, intermediate buffering of hydrogen storage, and slow adjustment of ammonia synthesis, providing constraints for day-ahead baseline scheduling and intraday rolling correction in subsequent steps.

[0024] Step 3: Generate the day-ahead baseline scheduling plan After completing the fast and slow dynamic response difference modeling in step two, this embodiment follows... Figure 1 The process shown enters the day-ahead baseline scheduling phase. Day-ahead scheduling uses a 24-hour scheduling cycle with 1-hour time intervals. Its main task is to determine the baseline power for electrolytic hydrogen production, the baseline state for hydrogen storage, the baseline load for synthetic ammonia, and the peak-shaving capacity that can be reported to the grid for each time period of the next day, based on the predicted output of wind power and photovoltaic power, the grid peak-shaving demand, market prices, and the operating status of the electricity-hydrogen-ammonia system.

[0025] In this embodiment, day-ahead scheduling does not solely aim to increase ammonia production or reduce hydrogen production costs. Instead, it integrates ammonia sales revenue, peak-shaving compensation revenue, renewable energy consumption revenue, electricity costs, system operating costs, and deviation penalty costs into a comprehensive revenue function. Its day-ahead optimization objective can be expressed as: ; In the formula, R day This represents the overall system revenue within the current scheduling cycle. T This represents the total number of scheduling periods in the previous day; R NH3 ( t ) is the first t Revenue from ammonia sales during specific time periods; R peak ( t (This is for peak-shaving compensation revenue;) R re ( t (This refers to revenue generated from the consumption of new energy sources.) C e ( t The cost of electricity; C op ( t The system operating cost is [not specified]. C pen ( t The penalty costs incurred due to wind and solar power curtailment, peak shaving deviations, or deviations from ammonia production plans.

[0026] The revenue from peak shaving compensation can be determined based on the peak shaving capacity and peak shaving compensation price declared previously: ; In the formula, c peak ( t The price is the peak-shaving compensation price. P cap ( t ) for the system in the first t Peak-shaving capacity that can be provided to the power grid during a given period; Δ t This is the day-ahead scheduling time interval.

[0027] In determining the peak-shaving capacity, this embodiment comprehensively considers the remaining upscaling capacity of electrolytic hydrogen production, the safety margin of hydrogen storage, and the hydrogen consumption requirements for ammonia synthesis. If the hydrogen storage is close to the upper limit, the ability of electrolytic hydrogen production to further increase the capacity is limited; if the hydrogen storage is close to the lower limit, the system should not significantly reduce the hydrogen production power to avoid affecting the continuous operation of ammonia synthesis. Therefore, the peak-shaving capacity satisfies: ; Meanwhile, to ensure the continuous and stable production of the ammonia synthesis section, the day-ahead scheduling phase only arranges the ammonia load gradually, ensuring it meets the upper and lower limit constraints and ramp-up constraints described in step two. In this way, the day-ahead planning layer primarily determines the baseline operating trajectory of the electricity-hydrogen-ammonia system and provides the power grid with relatively reliable peak-shaving capacity declaration results.

[0028] Step 4: Perform intraday rolling correction After the baseline scheduling plan was formed, this embodiment follows... Figure 2 The fast and slow dynamic decoupling logic shown employs a 15-minute rolling cycle to revise the day-ahead plan during the intraday phase. The main function of the intraday rolling revision is to address the deviation between the actual output of new energy sources and the day-ahead forecast, as well as real-time peak-shaving instructions temporarily issued by the power grid dispatching agency.

[0029] Let the first k Within a rolling cycle of one day, the actual output of new energy is P RE act ( k The predicted output is... P RE pre ( k If the new energy prediction error is: ; The intraday rolling correction aims to minimize the tracking deviation of peak-shaving instructions, the curtailment of renewable energy, the stable regulation of electrolytic hydrogen production power, and the load shift of synthetic ammonia. Its optimization objectives can be expressed as: ; In the formula, J in The objective function is adjusted for intraday rolling correction; KTo optimize the number of time periods within the scrolling window; P g ( k (This refers to the actual grid-connected power.) P g,ref ( k () represents the expected grid-connected power. P cur ( k ) represents the power of wind and solar power curtailment; Δ P el ( k ) represents the change in hydrogen production power via electrolysis; Δ P NH3 ( k () represents the change in ammonia synthesis load; α , β , γ , δ These are the weighting coefficients.

[0030] In practice, when the actual output of new energy sources is higher than the predicted value, or when the power grid requires a reduction in grid-connected power, the system prioritizes increasing the electrolysis hydrogen production power to convert surplus electricity into hydrogen and send it to the hydrogen storage stage. When the actual output of new energy sources is lower than the predicted value, or when the power grid requires an increase in grid-connected power, the system reduces the electrolysis hydrogen production power to reduce local electricity consumption and provides hydrogen to the ammonia synthesis stage through the hydrogen storage stage to maintain the stability of the downstream ammonia synthesis load.

[0031] The power correction for hydrogen production via electrolysis can be expressed as: ; In the formula, P elnew ( k This represents the intraday revised electrolytic hydrogen production power. P el day ( k ) represents the electrolysis hydrogen production capacity in the current day-to-date baseline plan; Δ P el ( k () represents the intraday rolling correction amount.

[0032] For the ammonia synthesis section, rapid response to grid peak-shaving commands is not required during the daytime phase; instead, buffering is provided through hydrogen storage. When hydrogen storage is within a safe range, the ammonia synthesis load prioritizes maintaining the daytime plan; only when hydrogen storage continuously deviates from the safe range is a small adjustment of the ammonia synthesis load allowed within slow dynamic constraints. This avoids disrupting the continuous and stable operation of the ammonia synthesis process due to frequent changes in real-time grid peak-shaving demands.

[0033] Step 5: Perform peak shaving contribution and dynamic cost feedback After completing intraday rolling adjustments and executing corresponding scheduling instructions, this embodiment further performs peak-shaving contribution and dynamic operating cost feedback based on actual operating results. This step corresponds to... Figure 1 The closed-loop feedback loop is used to correct the power boundary, hydrogen storage safety margin, and optimization weights in the next rolling cycle or the next day-ahead scheduling cycle.

[0034] First, the calculation system's tracking deviation of the power grid peak-shaving command: ; In the formula, E peak This is the cumulative value of the tracking deviation for peak shaving commands. The smaller this value, the better the system's response to power grid peak shaving commands.

[0035] Secondly, calculate the dynamic operating cost of the system. This dynamic operating cost includes the cost of fluctuations in hydrogen production power due to electrolysis, the cost of hydrogen storage deviating from the safe range, the cost of ammonia synthesis load shifts, and the cost of peak shaving deviations, which can be expressed as: ; In the formula, C dyn For dynamic operating costs; H ref This is a reference value for hydrogen storage; a 1 to a 4 represents the cost weighting coefficient.

[0036] When the peak-shaving deviation is large, it indicates that the electrolytic hydrogen production power regulation capability or hydrogen storage buffer capability is insufficient, and the peak-shaving tracking weight needs to be increased in subsequent cycles. When the hydrogen storage volume is close to the upper or lower limit for a long period of time, it indicates that the day-ahead baseline hydrogen production plan and the synthetic ammonia hydrogen consumption plan are mismatched, and the hydrogen storage safety range or synthetic ammonia quasi-load needs to be adjusted. When the synthetic ammonia load frequently deviates from the planned value, the adjustment range of synthetic ammonia load during the intraday correction process should be reduced, so that it can undertake more slow dynamic stable operation functions.

[0037] This embodiment updates and optimizes the weights in the following way: ; In the formula, ω i ( k ) is the first k Within the first cycle i Optimization weights for class objectives; μ This is the weighting adjustment factor; e i ( k ) represents the normalized deviation of the corresponding target, including peak shaving tracking deviation, hydrogen storage status deviation, or ammonia production plan deviation.

[0038] Through the aforementioned feedback mechanism, the system can continuously adjust its scheduling strategy based on actual operational results, forming a closed-loop optimization process of "day-ahead baseline plan – intraday rolling adjustment – ​​scheduling execution – feedback update". This method leverages the rapid response capability of electrolytic hydrogen production to grid peak-shaving commands while utilizing hydrogen storage to isolate front-end power fluctuations from the slow dynamic process of downstream ammonia synthesis. This ensures continuous ammonia synthesis while improving the level of new energy consumption, grid peak-shaving response capability, and the overall economic efficiency of the electricity-hydrogen-ammonia system.

Claims

1. A multi-scale grid-connected peak-shaving method for electro-hydrogen and ammonia, characterized in that, Includes the following steps: 1) Obtain the predicted output of wind power and photovoltaic power, the predicted grid load, the grid-connected power constraints, the peak-shaving demand, the peak-shaving compensation price, the electricity price, and the operating status of the electricity-hydrogen-ammonia system within the scheduling period. The operating status includes the electrolysis hydrogen production power, hydrogen storage capacity, hydrogen supply and demand balance status, synthetic ammonia load, and ammonia production plan. 2) Establish a multi-timescale scheduling model that takes into account the difference between fast and slow dynamic responses, treat the electrolysis hydrogen production process as a fast and adjustable load, the hydrogen storage process as a buffer variable between the electrolysis hydrogen and ammonia processes, and the ammonia synthesis process as a slow dynamic load constrained by continuous operation. 3) Under the day-ahead dispatch scale, with the goal of maximizing the overall system benefits, determine the baseline power for electrolytic hydrogen production, the baseline state for hydrogen storage, the quasi-load for synthetic ammonia, and the peak-shaving capacity that can be provided to the grid; 4) On an intraday rolling scale, based on the actual output of new energy sources, forecast errors, and real-time peak-shaving instructions from the power grid, the electrolysis hydrogen production power and hydrogen storage charging and discharging plan are revised, and the synthetic ammonia load is constrained to be smoothly adjusted within the allowable range; 5) Update the power boundary and optimization weights for subsequent scheduling cycles based on peak shaving command tracking deviation, renewable energy consumption, hydrogen storage safety margin, ammonia production plan completion rate, and dynamic operating costs.

2. The multi-scale grid-connected peak-shaving method for electro-hydrogen ammonia according to claim 1, characterized in that, The multi-timescale scheduling model includes a day-ahead planning layer and an intraday rolling correction layer. The day-ahead planning layer is used to determine the system's baseline operating plan and peak-shaving capacity, while the intraday rolling correction layer is used to respond to short-term fluctuations in new energy sources and real-time peak-shaving commands from the power grid.

3. The multi-scale grid-connected peak-shaving method for electro-hydrogen ammonia according to claim 1, characterized in that, The differences in fast and slow dynamic responses include the minute-level power regulation characteristics of hydrogen electrolysis, the intermediate buffer characteristics of hydrogen storage, and the hour-level slow inertia characteristics of ammonia synthesis.

4. The multi-scale grid-connected peak-shaving method for electro-hydrogen ammonia according to claim 1, characterized in that, The system's comprehensive revenue includes revenue from ammonia sales, peak-shaving compensation, green electricity consumption, electricity costs, operating costs, wind and solar curtailment penalties, and peak-shaving deviation penalties.

5. The multi-scale grid-connected peak shaving method for electro-hydrogen ammonia according to claim 1, characterized in that, The electrolytic hydrogen production power is constrained by the maximum power, minimum stable power, ramp rate, and number of start-stop cycles; the ammonia synthesis load is constrained by continuous operation, safety boundary, and load change rate.

6. The multi-scale grid-connected peak-shaving method for electro-hydrogen ammonia according to claim 1, characterized in that, When the actual output of new energy sources is higher than the day-ahead forecast or the grid requires a reduction in grid-connected power, priority should be given to increasing the electrolysis hydrogen production power and increasing hydrogen storage capacity; when the actual output of new energy sources is lower than the day-ahead forecast or the grid requires a reduction in grid-connected power, the electrolysis hydrogen production power should be reduced and the hydrogen storage buffer should be utilized.

7. The multi-scale grid-connected peak-shaving method for electro-hydrogen ammonia according to claim 1, characterized in that, The dynamic operating costs include the cost of fluctuations in hydrogen production power due to electrolysis, the cost of ammonia synthesis load shifts, the cost of hydrogen storage deviating from the safe range, and the cost of deviations due to failure to complete peak shaving orders.

8. The multi-scale grid-connected peak-shaving method for electro-hydrogen ammonia according to claim 1, characterized in that, The optimization weights are updated based on the peak-shaving response deviation, hydrogen storage status deviation, and ammonia production plan deviation of the previous rolling cycle, to form a closed-loop scheduling process of day-ahead planning, intraday correction, execution feedback, and re-optimization.

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