Power distribution network post-disaster recovery method fusing electric vehicle V2G and electricity-hydrogen coupling

Abstract

A power distribution network post-disaster recovery method integrating electric vehicle V2G and electricity-hydrogen coupling comprises the following steps that S1, before a disaster occurs, an economic compensation strategy is made, and electric vehicles in an area are guided to a V2G charging station or a centralized refuge station, and hydrogen fuel cell vehicles in the area are guided to a hydrogen refuge station or a centralized refuge station; s2, after a disaster occurs, integrating a dispatchable vehicle cluster, dispatching an electric vehicle of a refuge station to a target V2G charging station, dispatching a hydrogen fuel cell vehicle of the refuge station to the target V2G charging station or a hydrogen refuge station, and exciting the vehicle to perform reverse power supply on a power distribution network through an economic compensation strategy; and S3, carrying out topology reconstruction on the power distribution network, establishing a power supply recovery model of the power distribution network, and forming a micro-grid system containing the V2G charging station and / or hydrogen refueling station as a power supply so as to recover emergency load power supply. According to the invention, a cooperative scheduling system of two energy forms is constructed, stable operation duration of the post-disaster power distribution network can be realized, and the method has obvious advantages.

Description

Technical Field

[0001] This invention relates to the field of power distribution network post-disaster recovery technology, specifically to a power distribution network post-disaster recovery method that integrates electric vehicle V2G and electric-hydrogen coupling. Background Technology

[0002] Against the backdrop of global energy transition and climate change response, disaster recovery technologies for power distribution networks are evolving towards multi-energy complementarity and coordinated dispatch. Vehicle-to-Grid (V2G) technology utilizes large-scale electric vehicles (EVs) as distributed energy storage units, enabling rapid response during power distribution network failures and providing reverse power to critical loads, thus shortening recovery time and representing a crucial pathway to enhancing grid resilience. Meanwhile, hydrogen energy, as a key clean energy carrier, achieves spatiotemporal decoupling and long-term energy balance through its electro-hydrogen coupling system (including hydrogen production, storage, transportation, and power generation). In particular, hydrogen fuel cell vehicles (HVs) and their hydrogen refueling station hubs possess bidirectional "electricity-hydrogen-electricity" conversion capabilities, serving as virtual power plant resources to provide regulatory capacity.

[0003] However, existing technologies have the following limitations: First, the disaster recovery model relying solely on V2G is constrained by the driving range of electric vehicles and user behavior, making it difficult to support long-term power supply needs after a disaster, resulting in insufficient recovery sustainability; Second, the inherent long-term energy storage characteristics and emergency power generation capabilities of hydrogen energy systems have not yet been fully explored and utilized in the disaster recovery scenario of power distribution networks; Third, there is currently a lack of mechanisms for effectively coordinating the scheduling of V2G resources and hydrogen-electric systems, failing to explore the complementary characteristics of the two in disaster scenarios, especially lacking a joint optimization scheduling strategy for electric vehicles and hydrogen fuel cell vehicles to achieve efficient power distribution network recovery.

[0004] In summary, there is an urgent need for a disaster recovery method for power distribution networks that integrates electric vehicle V2G and electric-hydrogen coupling to overcome the limitations of single technologies and achieve rapid and continuous power supply after a disaster.

[0005] It is understood that the above statements only provide background information related to the present invention and do not necessarily constitute prior art. Summary of the Invention

[0006] The purpose of this invention is to provide a method for disaster recovery of power distribution networks that integrates electric vehicle V2G and electric-hydrogen coupling, breaking through the limitations of single technology and realizing rapid and continuous power supply after a disaster.

[0007] To achieve the above objectives, this invention provides a method for post-disaster recovery of power distribution networks that integrates electric vehicle V2G and hydrogen fuel cell vehicle coupling, comprising the following steps: S1, Pre-disaster scheduling stage: Before a disaster occurs, an economic compensation strategy is formulated, and electric vehicles in the area are guided to V2G charging stations or centralized refuge stations, and hydrogen fuel cell vehicles are guided to hydrogen refueling stations or centralized refuge stations; S2, Post-disaster coordinated scheduling stage: After a disaster occurs, the dispatchable vehicle cluster is integrated, and electric vehicles in refuge stations are dispatched to target V2G charging stations, and hydrogen fuel cell vehicles in refuge stations are dispatched to target V2G charging stations or hydrogen refueling stations, and the vehicles are incentivized to provide reverse power to the power distribution network through an economic compensation strategy; S3, Power distribution network recovery stage: The power distribution network is topologically reconstructed, a power distribution network power supply recovery model is established, and a microgrid system containing the V2G charging stations and / or hydrogen refueling stations as power sources is formed to restore emergency load power supply.

[0008] Preferably, the guidance is implemented based on a road network topology model and a travel chain model, and the optimal path from the vehicle to its corresponding target station is calculated using the Floyd shortest path algorithm.

[0009] Preferably, the road network topology model abstracts the urban road network as an undirected graph G. R Using a node set N R Representing the key region, using edge set G R The formula for calculating a road that allows two-way traffic is:

[0010] G R =(N R C R );

[0011] The road modeling is undirected, reflecting the bidirectional driving capability of vehicles; it is only necessary to ensure that V2G charging stations and hydrogen refueling stations have corresponding nodes in the road network, without the need for one-to-one mapping of all nodes in the entire domain; through virtual node insertion technology, roads of unequal length are unified into equal-length edges.

[0012] Preferably, the travel chain model generates paths based on the activity patterns of key area nodes and key areas in the road network topology model, and each travel chain L is defined as:

[0013] L={T start ,T end ,t stay ,t 0f ,L start ,L end ,L path ,l lenth};

[0014] In the formula, T start ,T end These represent the departure and arrival times of the travel chain, respectively; t0f ,t stay L represents travel time and dwell time, respectively. start ,L end These represent the starting and ending points of the travel chain, respectively; L path ,l lenth This indicates the travel route and route length.

[0015] Preferably, the economic compensation strategy is an incentive-discharge response model constructed based on consumer psychology:

[0016]

[0017] Where, ρ v2g Indicates the actual percentage of users participating in the V2G response; X v2g This indicates the compensation price offered to users who participated in the V2G response; and These represent the theoretical lower limit and theoretical upper limit of the proportion of users participating in V2G responses, respectively; The response function representing the V2G response; This represents the minimum compensation price when the proportion of users participating in V2G response reaches the theoretical lower limit. This represents the maximum compensation price when the proportion of users participating in the V2G response reaches the theoretical lower limit. This represents the minimum compensation price when the proportion of users participating in V2G responses reaches the theoretical upper limit. This represents the maximum compensation price when the proportion of users participating in the V2G response reaches the theoretical upper limit.

[0018] Preferably, electric vehicles can be charged and powered in reverse via V2G stations, while hydrogen fuel cell vehicles can be powered in reverse via V2G stations or hydrogen refueling stations. However, hydrogen fuel cell vehicles can only be refueled using equipment at hydrogen refueling stations. Therefore, it is necessary to construct hydrogen refueling station facilities and impose relevant constraints on hydrogen fuel cell vehicles, including:

[0019] Electrolytic cell constraints:

[0020]

[0021] in, Indicates the operating status of the electrolytic cell; P elt.min and P elt.max These represent the lower and upper limits of the electrolytic cell's operating power, respectively; P t elt η represents the power consumption of the electrolytic cell in the t-th time period; elt Indicates the energy consumption ratio of the electrolytic cell; m hyg.t This represents the total amount of hydrogen produced by the electrolyzer during the t-th time period;

[0022] Fuel cell constraints:

[0023]

[0024] Where, μ t fc Indicates the operating status of the fuel cell; P fc.min and P fc.max These represent the lower and upper limits of fuel cell operating power, respectively; P t fc η represents the power consumption of the fuel cell in the t-th time period; fc Indicates the fuel cell energy efficiency ratio; m hyc.t This represents the total amount of hydrogen consumed in the t-th time period;

[0025] Hydrogen storage tank constraints:

[0026]

[0027] Where, m hy,t+1 This represents the change in hydrogen storage capacity in the hydrogen storage tank during the (t+1)th time period; m hyg,t This represents the amount of hydrogen flowing into the hydrogen storage tank during the t-th time period; m hyc,t This represents the hydrogen flow rate from the hydrogen storage tank during the t-th time period; m hy.t This indicates the real-time hydrogen storage capacity of the hydrogen storage tank; Δm hy,t This represents the change in hydrogen storage capacity in the hydrogen storage tank during the t-th time period; m hy.max Indicates the upper limit of the equipment's hydrogen storage capacity;

[0028]

[0029] Where, ρ hy,t ρ represents the internal air pressure of the equipment during the t-th time period; hy,t-1 R0 represents the internal air pressure of the equipment during the (t-1)th time period; R0 represents the coefficients of the gas equation. Indicates the internal temperature of the equipment; V hy Indicates the upper limit of the hydrogen storage volume of the equipment; ρ represents the molar mass of hydrogen gas. hy,min and ρ hy,max These represent the lowest and highest air pressures inside the equipment, respectively.

[0030]

[0031] Among them, P t comp This represents the power consumption of the compressor in the t-th time period; T represents the specific heat capacity of hydrogen. in Indicates the temperature at which hydrogen is introduced; η comp Indicates compressor efficiency; H in and H outThe internal gas pressure at the compressor input and output indicates the pressure at the compressor input and output; κ represents the isentropic exponent of hydrogen. This indicates the compressor's maximum power consumption;

[0032] Constraints on hydrogen fuel cell vehicles:

[0033]

[0034] Indicates the operating status of a hydrogen fuel cell vehicle; P HV.min and P HV.max These represent the minimum and maximum operating power of a hydrogen fuel cell vehicle, respectively; P t HV η represents the real-time power of the hydrogen fuel cell vehicle during the t-th time period; HV Indicates the energy efficiency ratio of hydrogen fuel cell vehicles; Δm hv.t m represents the total amount of hydrogen consumed by the hydrogen fuel cell vehicle in the t-th time period; HV,t This indicates the real-time hydrogen storage capacity of a hydrogen fuel cell vehicle; m HV.max This indicates the upper limit of hydrogen storage capacity for hydrogen fuel cell vehicles.

[0035] Preferably, the specific calculation for reverse power supply is as follows:

[0036]

[0037] in, This represents the total number of electric vehicles and hydrogen fuel cell vehicles parked at the charging station in the h-th hour. This represents the total number of electric vehicles and hydrogen fuel cell vehicles that actually participate in reverse power transmission at the h-th charging station. ρ represents the sum of active power generated by the reverse power supply from electric vehicles and hydrogen fuel cell vehicles at the i-th charging station; ρ represents the impact coefficient of natural disasters on the willingness of electric vehicle and hydrogen fuel cell vehicle users to respond; P i,n,t This represents the active power of the nth electric vehicle or hydrogen fuel cell vehicle supplying power in reverse at time t. This indicates the reverse power supply state of the nth electric vehicle or hydrogen fuel cell vehicle at time t.

[0038] Preferably, the following constraints must be met when performing coordinated scheduling:

[0039]

[0040] Among them, S i,n,t and M l,n,t θ(k) represents the stationary state of the i-th electric vehicle or hydrogen fuel cell vehicle at the t-th time and the driving state on the branch road of the road network, respectively; θ(k) indicates whether the node is a charging station; E represents the maximum reverse power supply of an electric vehicle or hydrogen fuel cell vehicle at node i; n,t E represents the remaining electricity or hydrogen storage of the nth electric vehicle or hydrogen fuel cell vehicle at time t; move This indicates the amount of electricity or hydrogen stored when an electric vehicle or hydrogen fuel cell vehicle is driving on a branch road of the road network.

[0041] Preferably, the power distribution network restoration model includes:

[0042]

[0043]

[0044] in, This represents the real-time active power output of clean energy at node i at time t. P represents the real-time active power output of node i in reverse V2G at time t; DG,i,t PL represents the real-time active power output of the distributed power source at time t of node i; i,t This represents the active power demand of node i at time t. This refers to the power rationing during that time period; H i,j,t H represents the active power flow through line (i,j) at time t; σ(i) and ε(i) represent the set of child nodes and the set of parent nodes of node i, respectively; m,i,t This represents the active power flow through line (m,i) at time t;

[0045] Q DG,i,t This represents the real-time reactive power output of the distributed power source at node i at time t; QL i,t G represents the reactive power demand of node i at time t; PF represents the power factor; G i,j,t G represents the reactive power flow through line (i,j); m,i,t This represents the reactive power flow through line (m,i) at time t;

[0046] c i,j,t The switching status of line (i,j); x i,j and r i,j Represents the power grid topology parameters; M is any positive number; S max This is the upper limit of the branch transmission power;

[0047] U i,t U represents the voltage at node i at time t; imax and U imin These represent the upper and lower limits of the node voltage, respectively.

[0048] P DGimax P DGimin and QDGimax Q DGimin These represent the upper and lower limits of the active and reactive power outputs of the distributed generation, respectively. This indicates the upper limit of active power output of clean energy.

[0049] Preferably, when performing distribution network topology reconfiguration, the topology radial constraint must be followed, specifically:

[0050]

[0051] -Mc i,j,t ≤F i,j ≤Mc i,j,t ;

[0052]

[0053] Where, N E The number of nodes in a power system, δ i,DG Refers to the distributed power supply deployment status, μ refers to the number of system islands, and F i,j The flow rate W refers to the flow rate in a single-product flow model. i This represents the supply of goods in the virtual root node;

[0054] Furthermore, when performing distribution network topology reconfiguration, an objective function also needs to be set, specifically:

[0055]

[0056] Among them, T all It optimizes the total number of time periods.

[0057] In summary, compared with existing technologies, this invention provides a disaster recovery method for power distribution networks that integrates electric vehicle V2G and electric-hydrogen coupling. This method deeply integrates electric vehicle V2G technology with electric-hydrogen coupling technology, constructing a collaborative scheduling system for the two energy forms. It overcomes the limitations of traditional single-technology paths, achieving a significant increase in the resilience of the post-disaster power distribution network through the rapid response capability of electric vehicles and the continuous power supply capability of hydrogen fuel cell vehicles. Furthermore, it increases the stable operating time of the post-disaster power distribution network, enabling long-term power supply needs. In addition, a power distribution network recovery model is constructed, achieving multi-energy complementarity and collaborative optimization. The feasibility and effectiveness of the model are verified through practical examples, providing strong support for subsequent large-scale promotion. Attached Figure Description

[0058] Figure 1 This is a flowchart of the post-disaster recovery method for power distribution networks that integrates electric vehicle V2G and electric-hydrogen coupling according to the present invention. Detailed Implementation

[0059] The following is in conjunction with the appendix Figure 1The present invention will be further illustrated by describing a preferred embodiment in detail.

[0060] It should be noted that the accompanying drawings are in a very simplified form and use non-precise proportions. They are only used to facilitate and clarify the purpose of illustrating the embodiments of the present invention, and are not intended to limit the implementation conditions of the present invention. Therefore, they have no substantial technical significance. Any modifications to the structure, changes in the proportional relationship, or adjustments to the size should still fall within the scope of the technical content disclosed in the present invention, provided that they do not affect the effects and objectives that the present invention can produce.

[0061] It should be noted that, in this invention, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only the expressly listed elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus.

[0062] like Figure 1 As shown, this invention provides a method for disaster recovery of power distribution networks that integrates electric vehicle V2G and electric-hydrogen coupling, specifically including the following steps:

[0063] S1. Pre-disaster dispatch phase: Before a disaster occurs, formulate economic compensation strategies and guide electric vehicles in the region to V2G charging stations or centralized shelters, and hydrogen fuel cell vehicles to hydrogen refueling stations or centralized shelters.

[0064] S2, Post-disaster Coordinated Dispatch Phase: After a disaster occurs, integrate the dispatchable vehicle cluster, dispatch electric vehicles from the shelter to the target V2G charging station, dispatch hydrogen fuel cell vehicles from the shelter to the target V2G charging station or hydrogen refueling station, and incentivize vehicles to provide reverse power to the power distribution network through economic compensation strategies.

[0065] S3. Distribution Network Restoration Phase: The distribution network is topologically reconstructed, a distribution network power supply restoration model is established, and a microgrid system containing the V2G charging station and / or hydrogen refueling station as power sources is formed to restore power supply to emergency loads.

[0066] Specifically, in step S1, before the disaster occurs, based on disaster prediction information, electric vehicles in the area are guided to the nearest charging station or centralized shelter that can perform vehicle-to-grid (V2G) interaction at their current location through information media, and hydrogen fuel cell vehicles in the area are guided to the nearest hydrogen refueling station or centralized shelter at their current location, so that electric vehicles and hydrogen fuel cell vehicles can gather at the charging station, hydrogen refueling station or centralized shelter when the disaster occurs.

[0067] Furthermore, the information medium includes, but is not limited to, broadcasting, the internet, text messaging, and telephone.

[0068] Furthermore, the guidance is based on a road network topology model and a travel chain model, and the optimal path from the vehicle to its corresponding target station is calculated using the Floyd shortest path algorithm.

[0069] The road network topology model is used to guide route planning for electric vehicles and hydrogen fuel cell vehicles. This model abstracts the urban road network as an undirected graph G. R Using a node set N R Representing intersections or key areas (such as residential areas, work areas, and commercial areas), the edge set G is used. R The expression for a road that allows two-way traffic is as follows:

[0070] G R =(N R C R (1)

[0071] Regarding this formula, it should be noted that: firstly, the road model is undirected, reflecting the actual bidirectional traffic capacity of vehicles; secondly, it is only necessary to ensure that V2G charging stations and hydrogen refueling stations have corresponding nodes in the road network, without the need for one-to-one mapping of all nodes in the entire region; and thirdly, by using virtual node insertion technology, roads of unequal length are unified into equal-length edges, simplifying the calculation process of travel time. Specifically, when the actual road lengths differ significantly, virtual nodes can be inserted between the original nodes to transform the model into a directed graph model with equal edge lengths for calculation.

[0072] The travel chain model is used to simulate and guide the movement of electric vehicles and hydrogen fuel cell vehicles. Key nodes are defined in the road network topology model. The travel chain model generates paths based on the activity patterns of these key areas, and each travel chain includes departure / arrival times, travel duration, and dwell time. Each travel chain L is defined as follows:

[0073] L={T start ,T end ,t stay ,t 0f ,L start ,L end ,Lpath ,l lenth} (2)

[0074] In the formula, T start ,T end These represent the departure and arrival times of the travel chain, respectively; t 0f ,t stay L represents travel time and dwell time, respectively. start ,L end These represent the starting and ending points of the travel chain, respectively; L path ,l lenth This indicates the travel route and route length.

[0075] The above state variables are calculated as follows:

[0076] T end,n =T start,n +t 0f,n (3)

[0077] T start,n+1 =T end,n +T stay,n (4)

[0078]

[0079] EV state ={C rem,t ,S t} (7)

[0080] Equation (3) indicates that in the nth travel chain, the arrival time is the departure time plus the travel time; Equation (4) indicates that in the (n+1)th travel chain, the departure time is the arrival time of the nth travel chain plus the dwell time; Equation (5) This represents the remaining energy when the nth travel chain arrives, and the remaining energy at the start. Subtract the energy consumed during travel, i.e., the path length l lenth,n Multiply by the electricity consumption of the electric vehicle or the hydrogen consumption of the hydrogen fuel cell vehicle, where the consumption of the electric vehicle's electricity or the hydrogen storage of the hydrogen fuel cell vehicle is proportional to the driving distance; Equation (6) indicates that the energy at the arrival of the nth travel chain remains unchanged from the energy at the departure time of the (n+1)th travel chain, that is, the energy remains unchanged during the parking period; In Equation (7), EV state Represents the vehicle state at time t; where C rem,t S represents the amount of electricity in an electric vehicle or the amount of hydrogen in a hydrogen fuel cell vehicle at time t. t This indicates the vehicle's position at time t, whether it is an electric vehicle or a hydrogen fuel cell vehicle.

[0081] The travel time t is fixed and follows a normal distribution:

[0082]

[0083] In equation (8), μ and σ represent the mean and standard deviation of the user's travel time, respectively.

[0084] Furthermore, based on the aforementioned road network topology model and travel chain model, the shortest path is calculated using the Floyd algorithm, and a time-battery coupling relationship is established. That is, the arrival time of the path equals the departure time plus the travel time, and the departure time of the next road segment needs to be superimposed with the dwell time. The battery power decreases linearly with travel time and remains constant during dwell time. This enables electric vehicles to be guided to the nearest V2G charging station or centralized shelter, and hydrogen fuel cell vehicles to the nearest hydrogen refueling station or centralized shelter, based on their real-time location during a disaster.

[0085] Furthermore, before a disaster occurs, power companies need to assess the scale of the disaster's impact (such as typhoon intensity, earthquake magnitude, or the extent of power grid damage) to formulate differentiated economic compensation strategies, thereby increasing the emergency power supply participation of electric vehicle and hydrogen fuel cell vehicle users. Therefore, an incentive-discharge response model is constructed based on consumer psychology:

[0086]

[0087] In equations (9), (10), and (11), ρ v2g Indicates the actual percentage of users participating in the V2G response; X v2g This indicates the compensation price offered to users who participated in the V2G response; and These represent the theoretical lower limit and theoretical upper limit of the proportion of users participating in V2G responses, respectively; The response function representing the V2G response; This represents the minimum compensation price when the proportion of users participating in V2G responses reaches the theoretical lower limit. This represents the maximum compensation price when the proportion of users participating in the V2G response reaches the theoretical lower limit. This represents the minimum compensation price when the proportion of users participating in V2G responses reaches the theoretical upper limit. This represents the maximum compensation price when the proportion of users participating in the V2G response reaches the theoretical upper limit.

[0088] It should be noted that in step S2, electric vehicles that were already at a V2G charging station or hydrogen fuel cell vehicles that were already at a V2G charging station or hydrogen refueling station at the time of the disaster will remain in their original positions, and the vehicles will be incentivized to supply power to the power grid in reverse through an economic compensation strategy.

[0089] Specifically, it is worth noting that electric vehicles can be charged and powered back via V2G stations, while hydrogen fuel cell vehicles can be powered back via V2G stations or hydrogen refueling stations, but can only be refueled at hydrogen refueling stations. Therefore, in addition to meeting the same road network and travel chain models as electric vehicles, hydrogen fuel cell vehicles also require the construction of hydrogen refueling station facilities and related constraints.

[0090] (1) Electrolytic cell constraint:

[0091]

[0092] In equation (12): Indicates the operating status of the electrolytic cell; P elt.min and P elt.max These represent the lower and upper limits of the electrolytic cell's operating power, respectively. η represents the power consumption of the electrolytic cell in the t-th time period; elt This indicates the energy consumption ratio of the electrolyzer, i.e., the amount of electricity required to produce 1 kg of hydrogen; m hyg.t This represents the total amount of hydrogen produced by the electrolyzer during the t-th time period.

[0093] (2) Fuel cell constraints

[0094]

[0095] In equation (13): Indicates the operating status of the fuel cell; P fc.min and P fc.max These represent the lower and upper limits of fuel cell operating power, respectively; P t fc η represents the power consumption of the fuel cell in the t-th time period; fc Indicates the fuel cell energy efficiency ratio; m hyc.t This represents the total amount of hydrogen consumed in the t-th time period.

[0096] (3) Hydrogen storage tank constraints

[0097]

[0098] In equation (14): m hy,t+1 This represents the change in hydrogen storage capacity in the hydrogen storage tank during the (t+1)th time period; m hyg,t This represents the amount of hydrogen flowing into the hydrogen storage tank during the t-th time period; m hyc,t This represents the hydrogen flow rate from the hydrogen storage tank during the t-th time period; m hy.t Indicates the real-time hydrogen storage capacity of the hydrogen storage tank; Δm hy,t This represents the change in hydrogen storage capacity in the hydrogen storage tank during the t-th time period; m hy.max This indicates the upper limit of the equipment's hydrogen storage capacity.

[0099]

[0100] In equation (15): ρ hy,t ρ represents the internal air pressure of the equipment during the t-th time period; hy,t-1 R0 represents the internal air pressure of the equipment during the (t-1)th time period; R0 represents the coefficients of the gas equation. Indicates the internal temperature of the equipment; V hy Indicates the upper limit of the hydrogen storage volume of the equipment; ρ represents the molar mass of hydrogen gas. hy,min and ρ hy,max These represent the lowest and highest air pressure inside the equipment, respectively.

[0101]

[0102] In equation (16): P t comp This represents the power consumption of the compressor in the t-th time period; T represents the specific heat capacity of hydrogen. in Indicates the temperature at which hydrogen is introduced; η comp Indicates compressor efficiency; H in and H out The internal gas pressure at the compressor input and output indicates the pressure at the compressor input and output; κ represents the isentropic exponent of hydrogen. This indicates the compressor's maximum power consumption.

[0103] (4) Constraints on hydrogen fuel cell vehicles

[0104]

[0105] In the formula: Indicates the operating status of a hydrogen fuel cell vehicle; P HV.min and P HV.max These represent the minimum and maximum operating power of a hydrogen fuel cell vehicle, respectively; P t HV η represents the real-time power of the hydrogen fuel cell vehicle during the t-th time period; HV The energy efficiency ratio (Δm) of a hydrogen fuel cell vehicle is the electrical energy that can be converted from 1 unit of hydrogen gas. hv.t m represents the total amount of hydrogen consumed by the hydrogen fuel cell vehicle in the t-th time period; HV,t This indicates the real-time hydrogen storage capacity of a hydrogen fuel cell vehicle; m HV.max This indicates the upper limit of hydrogen storage capacity for hydrogen fuel cell vehicles.

[0106] Furthermore, the specific calculations for reverse power supply are as follows:

[0107]

[0108] In equations (18), (19), and (20): This represents the total number of electric vehicles and hydrogen fuel cell vehicles parked at the charging station in the h-th hour. This represents the total number of electric vehicles and hydrogen fuel cell vehicles that actually participate in reverse power transmission at the h-th charging station. ρ represents the sum of active power generated by the reverse power supply from electric vehicles and hydrogen fuel cell vehicles at the i-th charging station; ρ represents the impact coefficient of natural disasters on the willingness of electric vehicle and hydrogen fuel cell vehicle users to respond; P i,n,t This represents the active power of the nth electric vehicle or hydrogen fuel cell vehicle supplying power in reverse at time t. This indicates the reverse power supply state of the nth electric vehicle or hydrogen fuel cell vehicle at time t.

[0109] Furthermore, the following constraints must be met when performing coordinated scheduling:

[0110]

[0111] In equations (21), (22), (23), (24) and (25), S i,n,t and M l,n,t θ(k) represents the stationary state of the i-th electric vehicle or hydrogen fuel cell vehicle at the t-th time and the driving state on the branch road of the road network, respectively; θ(k) indicates whether the node is a charging station; E represents the maximum reverse power supply of an electric vehicle or hydrogen fuel cell vehicle at node i; n,t E represents the remaining electricity or hydrogen storage of the nth electric vehicle or hydrogen fuel cell vehicle at time t; move This represents the amount of electricity or hydrogen stored when an electric vehicle or hydrogen fuel cell vehicle is traveling on a branch road of the road network. Equation (21) requires that an electric vehicle or hydrogen fuel cell vehicle can only be in one state at the same scheduling time, that is, parked at a node or traveling on a branch road of the road network; Equation (25) is the capacity change constraint of the electric vehicle or hydrogen fuel cell vehicle, reflecting the dynamic consumption process of mobile resource capacity.

[0112] Furthermore, in step S3, it is understood that after a disaster, the main power grid is damaged, making it difficult to supply power to the distribution network normally, and often resulting in damage to multiple distribution lines. At this time, the faulty area can be isolated, and the distribution network can be reconstructed using remote switches, thereby forming multiple independent microgrid systems, that is, forming an islanded operation network containing the V2G charging station and / or hydrogen refueling station as power sources, for restoring emergency load power supply.

[0113] The power supply restoration model for the distribution network includes the following formulas:

[0114]

[0115] Uimin ≤U i,t ≤U imax (29)

[0116]

[0117] In equation (26), This represents the real-time active power output of clean energy at node i at time t. P represents the real-time active power output of node i in reverse V2G at time t; DG,i,t PL represents the real-time active power output of the distributed power source at time t of node i; i,t This represents the active power demand of node i at time t. This refers to the power rationing during that time period; H i,j,t H represents the active power flow through line (i,j) at time t; σ(i) and ε(i) represent the set of child nodes and the set of parent nodes of node i, respectively; m,i,t This represents the active power flow through line (m,i) at time t.

[0118] In equation (27), Q DG,i,t This represents the real-time reactive power output of the distributed power source at node i at time t; QL i,t G represents the reactive power demand of node i at time t; PF represents the power factor; G i,j,t G represents the reactive power flow through line (i,j); m,i,t This represents the reactive power flow through line (m,i) at time t.

[0119] In equation (28), c i,j,t This represents the switching status of line (i,j), where 0 indicates the line is out of service, and 1 indicates the line is in service; x i,j and r i,j Represents the power grid topology parameters; M is any positive number; S max This represents the upper limit of the transmission power of the branch.

[0120] In equation (29), U i,t U represents the voltage at node i at time t; imax and U imin These represent the upper and lower limits of the node voltage, respectively.

[0121] In equation (30), P DGimax P DGimin and Q DGimax Q DGimin These represent the upper and lower limits of the active and reactive power outputs of the distributed power source, respectively.

[0122] In equation (32), This indicates the upper limit of active power output of clean energy.

[0123] Furthermore, when performing distribution network topology reconfiguration, topology radial constraints must also be followed, specifically:

[0124]

[0125] Where: N E The number of nodes in a power system, δ i,DG Refers to the distributed power supply deployment status, μ refers to the number of system islands, and F i,j The flow rate W refers to the flow rate in a single-product flow model. i This represents the supply of goods at the virtual root node. Equation (33) constrains the relationship between the number of nodes and branches in the radial system; Equation (34) is the flow balance constraint for the virtual root node; Equation (35) requires that the virtual flow when the line is disconnected be 0, corresponding to c. i,j,t In the case of taking 1; Equation (36) restricts the range of goods supply for the virtual root node, that is, the virtual root node can only supply within the island it is located on.

[0126] Furthermore, establishing a power supply restoration model for the distribution network also requires setting an objective function to optimize the distribution network and minimize its weighted total loss. This objective function is specifically:

[0127]

[0128] In the formula: T all It optimizes the total number of time periods.

[0129] In summary, this invention presents a disaster recovery method for power distribution networks that integrates electric vehicle V2G and hydrogen-electric coupling technologies. It deeply integrates electric vehicle V2G technology with hydrogen-electric coupling technology, constructing a collaborative scheduling system for these two energy forms. This overcomes the limitations of traditional single-technology paths. By leveraging the rapid response capability of electric vehicles and the continuous power supply capability of hydrogen fuel cell vehicles, it achieves a significant increase in the resilience of the post-disaster power distribution network and extends its stable operating time, enabling long-term power supply. Furthermore, a power distribution network recovery model is constructed, achieving multi-energy complementarity and collaborative optimization. The feasibility and effectiveness of the model are verified through practical examples, providing strong support for its subsequent large-scale promotion.

[0130] Although the present invention has been described in detail through the preferred embodiments above, it should be understood that the above description should not be considered as a limitation of the present invention. Various modifications and substitutions to the present invention will be apparent to those skilled in the art after reading the above description. Therefore, the scope of protection of the present invention should be defined by the appended claims.

Claims

1. A method for disaster recovery of power distribution networks integrating electric vehicle V2G and electric-hydrogen coupling, characterized in that, Includes the following steps: S1. Pre-disaster dispatch phase: Before a disaster occurs, formulate economic compensation strategies and guide electric vehicles in the region to V2G charging stations or centralized shelters, and hydrogen fuel cell vehicles to hydrogen refueling stations or centralized shelters. S2, Post-disaster Coordinated Dispatch Phase: After a disaster occurs, integrate the dispatchable vehicle cluster, dispatch electric vehicles from the shelter to the target V2G charging station, dispatch hydrogen fuel cell vehicles from the shelter to the target V2G charging station or hydrogen refueling station, and incentivize vehicles to provide reverse power to the power distribution network through economic compensation strategies. S3. Distribution Network Restoration Phase: The distribution network is topologically reconstructed, a distribution network power supply restoration model is established, and a microgrid system containing the V2G charging station and / or hydrogen refueling station as power sources is formed to restore power supply to emergency loads.

2. The method for disaster recovery of power distribution networks integrating electric vehicle V2G and electric-hydrogen coupling as described in claim 1, characterized in that, The guidance is based on a road network topology model and a travel chain model, and the optimal path from the vehicle to its corresponding target station is calculated using the Floyd shortest path algorithm.

3. The method for disaster recovery of power distribution networks integrating electric vehicle V2G and electro-hydrogen coupling as described in claim 2, characterized in that, The road network topology model abstracts the urban road network as an undirected graph G. R Using a node set N R Representing the key region, using edge set G R The formula for calculating a road that allows two-way traffic is: G R =(N R ,C R ); The road modeling is undirected, reflecting the bidirectional driving capability of vehicles; it is only necessary to ensure that V2G charging stations and hydrogen refueling stations have corresponding nodes in the road network, without the need for one-to-one mapping of all nodes in the entire domain; through virtual node insertion technology, roads of unequal length are unified into equal-length edges.

4. The method for disaster recovery of power distribution networks integrating electric vehicle V2G and electric-hydrogen coupling as described in claim 3, characterized in that, The travel chain model generates paths based on the activity patterns of key area nodes and key areas in the road network topology model. Each travel chain L is defined as follows: L={T start ,T end ,t stay ,t 0f ,L start ,L end ,L path ,l lenth }; In the formula, T start ,T end These represent the departure and arrival times of the travel chain, respectively; t 0f ,t stay L represents travel time and dwell time, respectively. start ,L end These represent the starting and ending points of the travel chain, respectively; L path ,l lenth This indicates the travel route and route length.

5. The method for disaster recovery of power distribution networks integrating electric vehicle V2G and electric-hydrogen coupling as described in claim 1, characterized in that, The economic compensation strategy is based on an incentive-discharge response model constructed from consumer psychology: Where, ρ v2g Indicates the actual percentage of users participating in the V2G response; X v2g This indicates the compensation price offered to users who participated in the V2G response; and These represent the theoretical lower limit and theoretical upper limit of the proportion of users participating in V2G responses, respectively; The response function representing the V2G response; This represents the minimum compensation price when the proportion of users participating in V2G responses reaches the theoretical lower limit. This represents the maximum compensation price when the proportion of users participating in the V2G response reaches the theoretical lower limit. This represents the minimum compensation price when the proportion of users participating in V2G responses reaches the theoretical upper limit. This represents the maximum compensation price when the proportion of users participating in the V2G response reaches the theoretical upper limit.

6. The method for disaster recovery of power distribution networks integrating electric vehicle V2G and electric-hydrogen coupling as described in claim 5, characterized in that, Electric vehicles can be charged and powered back via V2G stations, while hydrogen fuel cell vehicles can power back via V2G stations or hydrogen refueling stations. However, hydrogen fuel cell vehicles can only be refueled at hydrogen refueling stations. Therefore, it is necessary to construct hydrogen refueling station facilities and impose relevant constraints on hydrogen fuel cell vehicles, including: Electrolytic cell constraints: in, Indicates the operating status of the electrolytic cell; P elt.min and P elt.max These represent the lower and upper limits of the electrolytic cell's operating power, respectively; P t elt η represents the electrical power consumed by the electrolytic cell in the t-th time period; elt Indicates the energy consumption ratio of the electrolytic cell; m hyg.t This represents the total amount of hydrogen produced by the electrolyzer during the t-th time period; Fuel cell constraints: Where, μ t fc Indicates the operating status of the fuel cell; P fc.min and P fc.max These represent the lower and upper limits of fuel cell operating power, respectively; P t fc η represents the power consumption of the fuel cell in the t-th time period; fc Indicates the fuel cell energy efficiency ratio; m hyc.t This represents the total amount of hydrogen consumed in the t-th time period; Hydrogen storage tank constraints: Where, m hy,t+1 This represents the change in hydrogen storage capacity in the hydrogen storage tank during the (t+1)th time period; m hyg,t This represents the amount of hydrogen flowing into the hydrogen storage tank during the t-th time period; m hyc,t This represents the hydrogen flow rate from the hydrogen storage tank during the t-th time period; m hy.t This indicates the real-time hydrogen storage capacity of the hydrogen storage tank; Δm hy,t This represents the change in hydrogen storage capacity in the hydrogen storage tank during the t-th time period; m hy.max Indicates the upper limit of the equipment's hydrogen storage capacity; Where, ρ hy,t ρ represents the internal air pressure of the equipment during the t-th time period; hy,t-1 R represents the internal air pressure of the equipment during the (t-1)th time period; R0 represents the coefficients of the gas equation; T H2 Indicates the internal temperature of the equipment; V hy Indicates the upper limit of the hydrogen storage volume of the equipment; ρ represents the molar mass of hydrogen gas. hy,min and ρ hy,max These represent the lowest and highest air pressures inside the equipment, respectively. Among them, P t comp This represents the power consumption of the compressor in the t-th time period; T represents the specific heat capacity of hydrogen. in Indicates the temperature at which hydrogen is introduced; η comp Indicates compressor efficiency; H in and H out The internal gas pressure at the compressor input and output indicates the pressure at the compressor input and output; κ represents the isentropic exponent of hydrogen. This indicates the compressor's maximum power consumption; Constraints on hydrogen fuel cell vehicles: μ t HV Indicates the operating status of a hydrogen fuel cell vehicle; P HV.min and P HV.max These represent the minimum and maximum operating power of a hydrogen fuel cell vehicle, respectively; P t HV η represents the real-time power of the hydrogen fuel cell vehicle during the t-th time period; HV Indicates the energy efficiency ratio of hydrogen fuel cell vehicles; Δm hv.t m represents the total amount of hydrogen consumed by the hydrogen fuel cell vehicle in the t-th time period; HV,t This indicates the real-time hydrogen storage capacity of a hydrogen fuel cell vehicle; m HV.max This indicates the upper limit of hydrogen storage capacity for hydrogen fuel cell vehicles.

7. The method for disaster recovery of power distribution networks integrating electric vehicle V2G and electric-hydrogen coupling as described in claim 6, characterized in that, The specific calculation for reverse power supply is as follows: in, This represents the total number of electric vehicles and hydrogen fuel cell vehicles parked at the charging station in the h-th hour. This represents the total number of electric vehicles and hydrogen fuel cell vehicles that actually participate in reverse power transmission at the h-th charging station. ρ represents the sum of active power generated by the reverse power supply from electric vehicles and hydrogen fuel cell vehicles at the i-th charging station; ρ represents the impact coefficient of natural disasters on the willingness of electric vehicle and hydrogen fuel cell vehicle users to respond; P i,n,t This represents the active power of the nth electric vehicle or hydrogen fuel cell vehicle supplying power in reverse at time t. This indicates the reverse power supply state of the nth electric vehicle or hydrogen fuel cell vehicle at time t.

8. The method for disaster recovery of power distribution networks integrating electric vehicle V2G and electric-hydrogen coupling as described in claim 7, characterized in that, The following constraints must be met when performing coordinated scheduling: Among them, S i,n,t and M l,n,t θ(k) represents the stationary state of the i-th electric vehicle or hydrogen fuel cell vehicle at time t and the driving state on the branch road of the road network, respectively; θ(k) indicates whether the node is a charging station; E represents the maximum reverse power supply of an electric vehicle or hydrogen fuel cell vehicle at node i; n,t E represents the remaining electricity or hydrogen storage of the nth electric vehicle or hydrogen fuel cell vehicle at time t; move This indicates the amount of electricity or hydrogen stored when an electric vehicle or hydrogen fuel cell vehicle is driving on a branch road of the road network.

9. The method for disaster recovery of power distribution networks integrating electric vehicle V2G and electric-hydrogen coupling as described in claim 1, characterized in that, The power distribution network restoration model includes: IN imin ≤U i,t ≤U imax ; in, This represents the real-time active power output of clean energy at node i at time t. P represents the real-time active power output of node i in reverse V2G at time t; DG,i,t PL represents the real-time active power output of the distributed power source at time t of node i; i,t This represents the active power demand of node i at time t. This refers to the power rationing at certain nodes during this period; H i,j,t H represents the active power flow through line (i,j) at time t; σ(i) and ε(i) represent the sets of child nodes and parent nodes of node i, respectively; m,i,t This represents the active power flow through line (m,i) at time t; Q DG,i,t This represents the real-time reactive power output of the distributed power source at node i at time t; QL i,t G represents the reactive power demand of node i at time t; PF represents the power factor; G i,j,t G represents the reactive power flow through line (i,j); m,i,t This represents the reactive power flow through line (m,i) at time t; c i,j,t The switching status of line (i,j); x i,j and r i,j Represents the power grid topology parameters; M is any positive number; S max This is the upper limit of the branch transmission power; U i,t U represents the voltage at node i at time t; imax and U imin These represent the upper and lower limits of the node voltage, respectively. P DGimax P DGimin and Q DGimax Q DGimin These represent the upper and lower limits of the active and reactive power outputs of the distributed generation, respectively. This indicates the upper limit of active power output of clean energy.

10. The method for disaster recovery of power distribution networks integrating electric vehicle V2G and electric-hydrogen coupling as described in claim 9, characterized in that, When performing distribution network topology reconfiguration, topology radial constraints must be followed, specifically: -Mc i,j,t ≤F i,j ≤Mc i,j,t ; Where, N E The number of nodes in a power system, δ i,DG Refers to the distributed power supply deployment status, μ refers to the number of system islands, and F i,j The flow rate W refers to the flow rate in a single-product flow model. i This represents the supply of goods in the virtual root node; Furthermore, when performing distribution network topology reconfiguration, an objective function also needs to be set, specifically: Among them, T all It optimizes the total number of time periods.

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