A multi-energy flow coupling-based comprehensive energy system fault simulation method and system

Abstract

This application discloses a fault simulation method and system for integrated energy systems based on multi-energy flow coupling, belonging to the field of integrated energy system technology. The system fault simulation method disclosed in this invention models the hydrogen fuel cell and electrolyzer, which are coupled components of a hydrogen-electric integrated energy system, taking into account the bidirectional coupling characteristics of the system. This fills the gap in existing technologies, which typically focus on single energy systems (such as electric or hydrogen systems) and lack in-depth research on the mutual influence of faults within multi-energy coupled systems. Furthermore, through dynamic simulation technology, it simulates the real fault propagation process of the integrated energy system to the greatest extent possible, which is more intuitive and efficient than traditional static analysis. It can dynamically capture the fault propagation patterns in complex systems, helping researchers and operators to identify potential risks in a timely manner.

Description

Technical Field

[0001] This invention belongs to the field of integrated energy system technology, specifically relating to a fault simulation method and system for integrated energy systems based on multi-energy flow coupling. Background Technology

[0002] With the continuous optimization of the global energy structure and the rapid development of clean energy technologies, integrated energy systems are demonstrating increasingly significant advantages in energy efficiency and clean energy consumption. Hydrogen, as a clean and efficient secondary energy source, has applications spanning industry, transportation, and the power sector, and is gradually becoming an important component of the energy field. Against this backdrop, integrated energy systems deeply coupled with electricity have emerged. These systems achieve optimized allocation and improved utilization efficiency of energy resources through efficient conversion and complementary synergy between hydrogen and electricity, providing a new approach to addressing energy security, environmental protection, and energy transition. However, the operational complexity of multi-energy coupled integrated energy systems is significantly increased, especially in the coordinated operation of hydrogen and electricity systems, where various potential operational risks exist. These risks include, but are not limited to, equipment aging or failure, system operational errors, and accidents caused by external environmental factors such as extreme weather. These problems can lead to localized failures and create a chain reaction within the system, ultimately causing widespread failure propagation or system collapse. For example, failures in hydrogen production, storage, and transportation equipment can affect the power supply system; conversely, grid failures can also affect the normal operation of hydrogen production and storage equipment. This bidirectional coupling characteristic makes the propagation and evolution of faults more complex and difficult to predict.

[0003] Currently, the application of simulation technology in the energy field mostly focuses on single energy systems, such as pure electric systems or single hydrogen energy systems, while few studies have comprehensively and deeply explored the complex and subtle coupling relationships between multiple energy systems. This limitation makes it difficult to accurately understand and predict the behavior patterns of multiple energy systems in actual operation. Furthermore, traditional simulation techniques mostly rely on static models or quasi-static analysis methods. While these methods may be sufficient for simple, stable energy systems, they often fail to accurately reproduce the dynamic evolution processes of complex and variable energy systems, especially under fault conditions. Therefore, simulation results often deviate significantly from reality, failing to provide strong support for the optimal design and safe operation of energy systems. To overcome these challenges, we need to explore more advanced and comprehensive simulation technologies to more accurately simulate and predict the behavior of multiple energy systems under various conditions, providing strong guarantees for the sustainable development of energy systems. Summary of the Invention

[0004] The purpose of this invention is to provide a method and system for simulating faults in integrated energy systems based on multi-energy flow coupling, in order to solve the technical problem that existing prediction methods are difficult to simulate faults in multi-energy coupled systems.

[0005] To achieve the above objectives, the present invention employs the following technical solution:

[0006] This invention discloses a fault simulation method for integrated energy systems based on multi-energy flow coupling, comprising the following steps:

[0007] The hydrogen-electric integrated energy system includes a coupled hydrogen energy subsystem and an electric power subsystem.

[0008] When a fault occurs in the hydrogen energy subsystem, an initial fault is randomly injected into the hydrogen energy subsystem. Then, based on whether the gas supply of the hydrogen energy subsystem, as fed back by the injected initial fault, meets the requirements of the power subsystem, the fault evolution process is simulated.

[0009] When a fault occurs in the power subsystem, an initial fault is randomly injected into the power subsystem. Then, the fault evolution process is simulated based on whether the power of the electrolyzer in the power subsystem is affected by the feedback from the injected initial fault.

[0010] Furthermore, when a fault occurs in the hydrogen energy subsystem, the fault evolution process simulation method includes the following steps:

[0011] S1: Collect and initialize the parameters of the hydrogen-electric integrated energy system, set the simulation time interval and format it, then proceed to S2;

[0012] S2: Randomly inject an initial fault into the hydrogen energy subsystem, then proceed to S3;

[0013] S3: Collect the influence trend of the fault side on the gas delivery volume after the initial fault of the hydrogen energy subsystem is injected, draw the gas delivery volume change curve of the hydrogen energy subsystem based on the influence trend, and then proceed to S4.

[0014] S4: At the number of simulation time intervals, according to the gas delivery rate change curve, increase the gas delivery rate on the non-fault side. After the simulation time interval, determine whether a normal operating device and pipeline in the hydrogen energy subsystem has reached the maximum load. If yes, proceed to S3; otherwise, proceed to S5.

[0015] S5: The fault is transferred to the power subsystem. The power of the hydrogen fuel cell in the power subsystem is affected. The power subsystem starts power flow scheduling to reduce the load until the power subsystem reaches a balanced state and then transfers to S6.

[0016] S6: Check if each transmission line of the power subsystem exceeds the maximum load. If so, update the power subsystem topology and proceed to S5; otherwise, proceed to S7. If the power of the electrolytic cell of the coupling element in the system is affected, proceed to S3 after the power subsystem is restored to balance.

[0017] S7: If the gas supply of the hydrogen energy subsystem after the current time node meets the gas supply required by the power subsystem and reaches a balanced state, then proceed to S8; otherwise, as the time node advances, proceed to S4.

[0018] S8: Calculate the load loss of the hydrogen-electric integrated energy system and record the cascading failure evolution process of the hydrogen-electric integrated energy system.

[0019] Furthermore, in S1, the simulation time interval and formatting include the following steps:

[0020] The simulation time interval is set as ΔT; ΔT satisfies the following relationship:

[0021] △T p <△T;

[0022] Among them, △T p This indicates the time required for the power subsystem to complete power flow scheduling;

[0023] In S3, the specific process of collecting the impact trend of the fault side on the gas delivery volume after the initial fault injection of the hydrogen energy subsystem, and plotting the gas delivery volume change curve of the hydrogen energy subsystem based on the impact trend, includes:

[0024] The influence trend of the fault side on the gas delivery volume after the initial fault is injected into the hydrogen energy subsystem is collected, and compared with the maximum gas delivery volume of the non-fault side to determine the power flow scheduling strategy and fault evolution strategy of the hydrogen energy subsystem. The gas delivery volume change curve of the hydrogen energy subsystem is plotted based on the power flow scheduling strategy and fault evolution strategy. Whenever a new fault propagates to the hydrogen energy subsystem, the gas delivery volume change curve is corrected in a timely manner.

[0025] Furthermore, when a fault occurs in a power subsystem, the fault evolution process simulation method includes the following steps:

[0026] S11: Collect and initialize the parameters of the hydrogen-electric integrated energy system, then proceed to S22;

[0027] S22: Randomly inject an initial fault into the power subsystem, then proceed to S33;

[0028] S33: The power subsystem begins power flow scheduling to reduce load until the power subsystem reaches a balanced state, then proceeds to S44.

[0029] S44: Check if each transmission line of the power subsystem exceeds the maximum load. If so, update the power subsystem topology and proceed to S33; otherwise, proceed to S55.

[0030] S55: If the hydrogen production of the electrolyzer in the coupling element of the power subsystem is affected during the power flow scheduling process, then proceed to S66; otherwise, proceed to S77.

[0031] S66: The fault propagates to the hydrogen energy subsystem through the electrolyzer. The hydrogen energy subsystem adjusts the gas supply to determine whether the hydrogen fuel cell, the coupling element in the system, is affected. If so, proceed to S33; otherwise, proceed to S77.

[0032] S77: Balance of hydrogen-electric integrated energy system, calculate the load loss of hydrogen-electric integrated energy system, and construct the cascading fault propagation process.

[0033] Furthermore, the parameters collected from the hydrogen-electric integrated energy system include hydrogen subsystem datasets, electric subsystem datasets, and coupling node data;

[0034] The hydrogen energy subsystem dataset includes the topology of the hydrogen energy subsystem, node gas transmission capacity, pipeline gas flow rate, and gas network node parameters.

[0035] The power subsystem dataset includes the power subsystem topology, node injected power, line power flow, and transmission line parameters.

[0036] The coupling node data includes the location and energy conversion efficiency of the coupling nodes in the hydrogen-electric integrated energy system.

[0037] Furthermore, in S2 and S22, the initial fault injection satisfies the condition that causes the hydrogen-electric integrated energy system to experience an Nk cascading fault; the types of the initial fault include extreme weather, equipment failure, or human error.

[0038] Furthermore, the model for the hydrogen fuel cell in the power subsystem is as follows:

[0039] P w,m (t)=β w Q w,m (t)·HHV,w∈Ω HT ,m∈Ω BUS ;

[0040] Among them, Ω HT —The set of all hydrogen power generation nodes in the power subsystem; Ω BUS —The set of all nodes in the power subsystem; P w,m (t)——Power output of hydrogen fuel cell node w / MW; β w—Energy conversion coefficient of hydrogen fuel cell node w; Q w,m (t)——Gas consumption of hydrogen fuel cell node w / m 3 ·s -1 HHV—Highest calorific value of hydrogen (J·kg) -1 .

[0041] Furthermore, the objective function of the optimal power flow model for power subsystem power flow scheduling is:

[0042]

[0043] Among them, Ω Load —The set of all load nodes in the power subsystem; P L,m —Load demand at node L / MW; C m —Weighting coefficient for load shedding costs in power subsystems; Ω BUS —The set of all nodes in the power subsystem;

[0044] The constraint equations are:

[0045]

[0046] P l =(θ m -θ n ) / X l ;

[0047]

[0048] Among them, Ω HT —The set of all hydrogen power generation nodes in the power subsystem; Ω BUS —The set of all nodes in the power subsystem; P w,m — Output of hydrogen fuel cell node w in MW; P L,m —Load demand at node L / MW; θ m θ n —The phase angle (°) at both ends m and n of line l; and —Minimum and maximum power flow of transmission line l (MW); and —Minimum and maximum output of hydrogen fuel cell node w in MW; — Maximum power flow load at node L / MW.

[0049] Furthermore, the electrolytic cell model is as follows:

[0050]

[0051] Among them, Ω P2G—The collection of all coupling elements and electrolytic cell nodes; Ω NODE —The set of all nodes in the hydrogen energy subsystem; Q d,i (t)——Gas production at node d of the electrolyzer / m 3 ·s -1 ;ω d —Energy conversion coefficient at node d of the electrolyzer; HHV —High calorific value of hydrogen / J·kg -1 ;P d,i (t)——Electric energy input to node d of the electrolyzer / MW;

[0052] The model for load loss is as follows:

[0053]

[0054] in, —Load of power node m at the initial moment / MW; —Load capacity of power m at the end of fault evolution / MW; Ω BUS —The set of all nodes in the power subsystem; Ω Load —The set of all load nodes in the power subsystem; —Total load shedding of hydrogen-electric integrated energy system under cascading failures / MW.

[0055] The present invention also discloses a fault simulation system based on the above method.

[0056] Compared with the prior art, the present invention has the following beneficial effects:

[0057] This invention discloses a fault simulation method for integrated energy systems based on multi-energy flow coupling. Targeting the bidirectional coupling characteristics of hydrogen-electric integrated energy systems, it models the coupling elements, hydrogen fuel cells and electrolyzers. This fills the gap in existing technologies, which typically focus on single energy systems (such as electric or hydrogen systems) and lack in-depth research on the mutual influence of faults within multi-energy coupled systems. From the perspective of the overall system, it provides an innovative solution for fault analysis of multi-energy coupled systems.

[0058] Furthermore, the method of this invention employs dynamic simulation technology, which simulates the fault evolution and self-regulation processes within the system in real time, maximizing the simulation of the actual fault propagation process in a comprehensive energy system. This enables more accurate prediction of the fault propagation path and scope. Compared to traditional static analysis, this method is more intuitive and efficient, allowing for the dynamic capture of fault propagation patterns in complex systems and helping researchers and operators identify potential risks in a timely manner. Attached Figure Description

[0059] Figure 1The flowchart shows a comprehensive energy system fault simulation method based on multi-energy flow coupling.

[0060] Figure 2 A flowchart of a fault simulation method when a fault occurs in a hydrogen energy subsystem;

[0061] Figure 3 This is a flowchart of a fault simulation method when a fault occurs in a power subsystem. Detailed Implementation

[0062] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0063] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0064] The present invention will now be described in further detail with reference to the accompanying drawings:

[0065] like Figure 1 As shown, this invention discloses a comprehensive energy system fault simulation method based on multi-energy flow coupling, including two simulation scenarios: the initial fault occurs in the hydrogen energy subsystem and the initial fault occurs in the power subsystem.

[0066] When a fault occurs in the hydrogen energy subsystem, such as Figure 2 As shown, it includes the following steps:

[0067] S1: Initialize the parameters of the hydrogen-electric integrated energy system and set the simulation time interval, then proceed to S2;

[0068] S2: Randomly inject an initial fault into the hydrogen energy subsystem. This initial fault can cause an Nk cascade fault in the hydrogen-electric integrated energy system, and then proceed to S3.

[0069] S3: Collect the impact trend of the fault side on the gas transmission volume after the initial fault injection in the hydrogen-electric integrated energy system, draw the gas transmission volume change curve of the hydrogen subsystem based on the impact trend, and then proceed to S4.

[0070] S4: In T n When (n=1, 3, 5…), that is, within n simulation time intervals, according to the gas supply change curve, increase the gas supply on the non-fault side. After the simulation time interval, determine whether a normal operating component or pipeline in the hydrogen energy subsystem has reached the maximum load. If yes, proceed to S3; otherwise, proceed to S5.

[0071] S5: In T 2n When (n=1, 3, 5…), as the gas supply changes, the power of the hydrogen fuel cell in the hydrogen-electric integrated energy system is affected, and the power subsystem begins power flow scheduling, reducing the load in order of load importance from low to high until the power subsystem reaches a balanced state and enters S6.

[0072] S6: Check whether each transmission line of the power subsystem exceeds the power limit. If a line reaches the power limit, trip the line and update the power subsystem topology, then proceed to S5; otherwise, proceed to S7. If the power of the electrolyzer is affected during the power flow scheduling of the power subsystem, proceed to S3 after the subsystem is restored to balance.

[0073] S7: If the gas supply of the hydrogen energy subsystem meets the gas supply required by the power subsystem after the current time node and reaches a balanced state, then proceed to S8; otherwise, as the time node advances, proceed to S4.

[0074] S8: Calculate the load loss of the hydrogen-electric integrated energy system; record the evolution process of cascading failures in the hydrogen-electric integrated energy system.

[0075] When a fault occurs in a power subsystem, such as Figure 3 As shown, it includes the following steps:

[0076] S11: Collect and initialize the parameters of the hydrogen-electric integrated energy system, then proceed to S22;

[0077] S22: Randomly inject an initial fault into the power subsystem, then proceed to S33;

[0078] S33: The power subsystem begins power flow dispatching, and load reduction is carried out in order of load importance from low to high until the power subsystem reaches a balanced state, then proceeds to S44.

[0079] S44: Detect whether each transmission line of the power subsystem exceeds the power limit. If a line reaches the power limit, trip the line and update the power system topology, then proceed to S33; otherwise, proceed to S55.

[0080] S55: If the hydrogen production of the electrolyzer in the power subsystem is affected during power flow scheduling, proceed to S66; otherwise, proceed to S77.

[0081] S66: The fault propagates to the hydrogen energy subsystem through the electrolyzer. The hydrogen energy subsystem maintains the subsystem balance by adjusting the gas delivery of other components and proceeds to S77. If the gas delivery of the fuel cell is affected during the adjustment process, it immediately proceeds to S33.

[0082] S77: Balance of hydrogen-electric integrated energy system, calculate the load loss of hydrogen-electric integrated energy system, and construct the cascading fault propagation process.

[0083] Preferably, in S1 and S11, the data acquisition and initialization content is as follows:

[0084] The system collects data including power subsystem datasets, hydrogen energy subsystem datasets, and coupled node data. The power subsystem dataset includes information such as the power subsystem topology, node injection power, line power flow, and transmission line parameters. The hydrogen energy subsystem dataset contains information such as the system topology, node gas delivery volume, pipeline gas flow rate, and gas network node parameters. The coupled node data includes information such as the location of coupled nodes in the system and their energy conversion efficiency.

[0085] Preferably, in S1, the simulation time interval formatting content is as follows:

[0086] Set the simulation time interval to a unit time ΔT, where ΔT is required to be:

[0087] △T p ≤△T;

[0088] Among them, △T p This indicates the time required for the power subsystem to complete power flow scheduling.

[0089] Preferably, in S2 and S22, the initial fault content is set as follows:

[0090] The simulation simulated initial system failures caused by sudden events such as extreme weather, equipment failure, and human error, including issues such as pipeline icing, pipeline shutdown, and hydrogen storage tank failure; these initial failures can cause Nk cascading failures in the hydrogen-electric integrated energy system.

[0091] Preferably, in S3, the impact of the initial fault on the components and gas pipeline of the hydrogen energy subsystem is collected, and the power flow scheduling strategy and fault evolution strategy of the hydrogen energy subsystem are determined based on the maximum gas delivery of the normally operating components. The gas delivery change curve of the hydrogen energy subsystem is plotted, and the change curve is corrected in a timely manner whenever a new fault propagates to the hydrogen energy subsystem.

[0092] Preferably, in S5 and S66, the hydrogen fuel cell model is:

[0093] P w,m (t)=β w Q w,m (t)·HHV,w∈Ω HT ,m∈Ω BUS ;

[0094] Among them, Ω HT —The set of all hydrogen power generation nodes in the power subsystem; Ω BUS —The set of all nodes in the power subsystem; P w,m (t)——Power output of hydrogen fuel cell node w / MW; β w —Energy conversion coefficient of hydrogen fuel cell node w; Q w,m (t)——Gas consumption of hydrogen fuel cell node w / m 3 ·s -1 HHV—Highest calorific value of hydrogen (J·kg) -1 .

[0095] Preferably, in S5 and S33, the objective function of the optimal power flow model for power subsystem power flow scheduling is:

[0096]

[0097] Among them, Ω Load —The set of all load nodes in the power subsystem; P L,m —Load demand at node L / MW; C m —Weighting coefficient for load shedding costs in power subsystems; Ω BUS —The set of all nodes in the power subsystem;

[0098] The constraint equations are:

[0099]

[0100] P l =(θ m -θ n ) / X l ;

[0101]

[0102] Among them, Ω HT —The set of all hydrogen power generation nodes in the power subsystem; Ω BUS —The set of all nodes in the power subsystem; P w,m — Output of hydrogen fuel cell node w in MW; P L,m —Load demand at node L / MW; θ m θ n —The phase angle (°) at both ends m and n of line l; and —Minimum and maximum power flow of transmission line l (MW); and —Minimum and maximum output of hydrogen fuel cell node w in MW; —Maximum power flow load at node L / MW.

[0103] Preferably, in S6 and S55, the electrolytic cell model is as follows:

[0104]

[0105] Among them, Ω P2G —The collection of all coupling elements and electrolytic cell nodes; Ω NODE —The set of all nodes in the hydrogen energy subsystem; Q d,i (t)——Gas production at node d of the electrolyzer / m 3 ·s -1 ;ω d —Energy conversion coefficient at node d of the electrolyzer; HHV —High calorific value of hydrogen / J·kg -1 ;P d,i (t)——Electric energy input to node d of the electrolyzer / MW.

[0106] Preferably, the model for load loss is as follows:

[0107]

[0108] in, —Load of power node m at the initial moment / MW; —Load capacity of power m at the end of fault evolution / MW; Ω BUS —The set of all nodes in the power subsystem; Ω Load —The set of all load nodes in the power subsystem; —Total load shedding of hydrogen-electric integrated energy system under cascading failures / MW.

[0109] The above content is only for illustrating the technical concept of the present invention and should not be construed as limiting the scope of protection of the present invention. Any modifications made to the technical solution based on the technical concept proposed in this invention shall fall within the scope of protection of the claims of this invention.

Claims

1. A fault simulation method for a comprehensive energy system based on multi-energy flow coupling, characterized in that, The hydrogen-electric integrated energy system includes a coupled hydrogen energy subsystem and an electric power subsystem; Includes the following steps: When a fault occurs in the hydrogen energy subsystem, an initial fault is randomly injected into the hydrogen energy subsystem. Then, based on whether the gas supply of the hydrogen energy subsystem, as fed back by the injected initial fault, meets the requirements of the power subsystem, the fault evolution process is simulated. When a fault occurs in the power subsystem, an initial fault is randomly injected into the power subsystem. Then, the fault evolution process is simulated based on whether the output power of the electrolyzer in the power subsystem is affected by the feedback from the injected initial fault. When a fault occurs in a hydrogen energy subsystem, the fault evolution process simulation method includes the following steps: S1: Collect and initialize the parameters of the hydrogen-electric integrated energy system, set the simulation time interval and format it, then proceed to S2; S2: Randomly inject an initial fault into the hydrogen energy subsystem, then proceed to S3; S3: Collect the influence trend of the fault side on the gas delivery volume after the initial fault of the hydrogen energy subsystem is injected, draw the gas delivery volume change curve of the hydrogen energy subsystem based on the influence trend, and then proceed to S4. S4: At the number of simulation time intervals, increase the gas supply on the non-fault side according to the gas supply change curve. After the simulation time interval, determine whether a normal working device or pipeline in the hydrogen energy subsystem has reached the maximum load. If yes, proceed to S3; otherwise, proceed to S5. S5: The fault is transferred to the power subsystem. The power of the hydrogen fuel cell in the power subsystem is affected. The power subsystem starts power flow scheduling to reduce the load until the power subsystem reaches a balanced state and then transfers to S6. S6: Check if each transmission line of the power subsystem exceeds the maximum load. If so, update the power subsystem topology and proceed to S5; otherwise, proceed to S7. If the power of the electrolytic cell of the coupling element in the system is affected, proceed to S3 after the power subsystem is restored to balance. S7: If the gas supply of the hydrogen energy subsystem after the current time node meets the gas supply required by the power subsystem and reaches a balanced state, then proceed to S8; otherwise, as the time node advances, proceed to S4. S8: Calculate the load loss of the hydrogen-electric integrated energy system and record the cascading failure evolution process of the hydrogen-electric integrated energy system; When a fault occurs in a power subsystem, the fault evolution process simulation method includes the following steps: S11: Collect and initialize the parameters of the hydrogen-electric integrated energy system, then proceed to S22; S22: Randomly inject an initial fault into the power subsystem, then proceed to S33; S33: The power subsystem begins power flow scheduling to reduce load until the power subsystem reaches a balanced state, then proceeds to S44. S44: Check if each transmission line of the power subsystem exceeds the maximum load. If so, update the power subsystem topology and proceed to S33; otherwise, proceed to S55. S55: If the hydrogen production of the electrolyzer in the coupling element of the power subsystem is affected during the power flow scheduling process, proceed to S66; otherwise, proceed to S77. S66: The fault propagates to the hydrogen energy subsystem through the electrolyzer. The hydrogen energy subsystem adjusts the gas supply to determine whether the hydrogen fuel cell, the coupling element in the system, is affected. If so, proceed to S33; otherwise, proceed to S77. S77: Balance of hydrogen-electric integrated energy system, calculate the load loss of hydrogen-electric integrated energy system, and construct the cascading fault propagation process.

2. The integrated energy system fault simulation method based on multi-energy flow coupling according to claim 1, characterized in that, In S1, the simulation time interval and formatting include the following steps: The simulation time interval is set as ΔT; ΔT satisfies the following relationship: ； in, This indicates the time required for the power subsystem to complete power flow scheduling; In S3, the specific process of collecting the impact trend of the fault side on the gas delivery volume after the initial fault injection of the hydrogen energy subsystem, and plotting the gas delivery volume change curve of the hydrogen energy subsystem based on the impact trend, includes: The influence trend of the fault side on the gas delivery volume after the initial fault is injected into the hydrogen energy subsystem is collected, and compared with the maximum gas delivery volume of the non-fault side to determine the power flow scheduling strategy and fault evolution strategy of the hydrogen energy subsystem. The gas delivery volume change curve of the hydrogen energy subsystem is plotted based on the power flow scheduling strategy and fault evolution strategy. Whenever a new fault occurs in the hydrogen energy subsystem, the gas delivery volume change curve is corrected in a timely manner.

3. The integrated energy system fault simulation method based on multi-energy flow coupling according to claim 1, characterized in that, The parameters collected from the hydrogen-electric integrated energy system include hydrogen energy subsystem dataset, electric subsystem dataset, and coupling node data. The hydrogen energy subsystem dataset includes the topology of the hydrogen energy subsystem, node gas transmission capacity, pipeline gas flow rate, and gas network node parameters. The power subsystem dataset includes the power subsystem topology, node injected power, line power flow, and transmission line parameters. The coupling node data includes the location and energy conversion efficiency of the coupling nodes in the hydrogen-electric integrated energy system.

4. The integrated energy system fault simulation method based on multi-energy flow coupling according to claim 1, characterized in that, In S2 and S22, the initial fault injection satisfies the condition that causes the hydrogen-electric integrated energy system to experience N- k Conditions for cascading failures; the types of initial failures include extreme weather, equipment malfunction, or human error.

5. The integrated energy system fault simulation method based on multi-energy flow coupling according to claim 1, characterized in that, The model for the hydrogen fuel cell in the power subsystem is as follows: ； in, —The set of all hydrogen power generation nodes in the power subsystem; —The set of all nodes in the power subsystem; — Hydrogen fuel cell node contribution ; — Hydrogen fuel cell node Energy conversion coefficient; — Hydrogen fuel cell node gas consumption ; —High calorific value of hydrogen .

6. The integrated energy system fault simulation method based on multi-energy flow coupling according to claim 1, characterized in that, The objective function of the optimal power flow model for power subsystem power flow scheduling is: ； in, —The set of all load nodes in the power subsystem; --node L load demand ; —Weighting coefficient for load shedding costs in power subsystems; —The set of all nodes in the power subsystem; The constraint equations are: ； ； ； ； ； in, —The set of all hydrogen power generation nodes in the power subsystem; —The set of all nodes in the power subsystem; — Hydrogen fuel cell node contribution ; --node L load demand ; --line Both ends phase angle ; and ——Transmission lines Minimum Current and Maximum Current ; and — Hydrogen fuel cell node Minimum output and maximum output ; --node Maximum Flow Load .

7. The integrated energy system fault simulation method based on multi-energy flow coupling according to claim 1, characterized in that, The electrolytic cell model is as follows: ； in, —The collection of all coupling element electrolytic cell nodes; —The set of all nodes in the hydrogen energy subsystem; —Electrolyzer node d Gas production ; —Electrolyzer node d Energy conversion coefficient; —High calorific value of hydrogen ; — Input to electrolytic cell node d electrical energy ; The model for load loss is as follows: ； in, —Power Node Load at the initial moment ; --electricity Load at the end of the fault evolution ; —The set of all nodes in the power subsystem; —The set of all load nodes in the power subsystem; —Total load shedding of a hydrogen-electric integrated energy system under cascading failures .

8. A fault simulation system for a comprehensive energy system based on multi-energy flow coupling, characterized in that, Used to perform the simulation method described in any one of claims 1 to 7.

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