A method and terminal for power grid post-disaster recovery

Abstract

The application discloses a power grid post-disaster recovery method and a terminal. After natural disasters occur in a power grid, a load recovery task is determined, and a post-disaster topology change constraint containing a flexible soft switch is established based on the load recovery task. A pre-disaster and post-disaster multi-type electric vehicle cluster regulation and control model and a post-disaster recovery optimization decision model are established based on the determined load recovery task and the priority thereof, so as to generate a post-disaster recovery optimization decision model considering the flexible soft switch and the multi-type electric vehicle. The model is solved to obtain a line reconfiguration result for the load recovery task and a charging and discharging strategy of the electric vehicle. In this way, the flexible soft switch technology is used to quickly isolate the affected area when a natural disaster causes a fault, the risk of fault diffusion is reduced, the power grid can quickly make necessary topology adjustment after a disaster, and the efficient distribution of post-disaster power support is realized in combination with the electric vehicle cluster, so that the resilience and sustainability of the power grid after a disaster are effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power supply grid restoration, and in particular to a power supply grid post-disaster restoration method and terminal. Background Art

[0002] The power grid is the power supply unit of an urban distribution network, and its stable operation is crucial to supporting users' production and daily lives. However, natural disasters, especially typhoons, can cause severe damage to the power grid. The strong winds and heavy rains brought by typhoons can not only cause power lines to break and transmission towers to collapse, but can also cause flooding, further exacerbating damage to related power equipment, leading to large-scale power outages, affecting the lives and safety of tens of thousands of people, and causing significant economic losses. Therefore, designing and implementing effective power system post-disaster recovery strategies to restore the normal operation of the power grid as soon as possible and enhance the distribution network's response and recovery capabilities during typhoon disasters are of great significance to ensuring the security and stability of the power supply. Summary of the Invention

[0003] The technical problem to be solved by the present invention is to provide a power grid post-disaster recovery method and terminal, which can effectively improve the resilience and sustainability of the power grid after a disaster.

[0004] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0005] A power grid post-disaster recovery method comprising the steps of:

[0006] Determine whether a natural disaster has occurred in the power grid. If so, determine a load restoration task and establish a post-disaster topology change constraint including flexible soft switching based on the load restoration task.

[0007] Obtaining disaster data and load importance information, and determining the priority of the load restoration task based on the disaster data and the load importance information;

[0008] Establishing a pre-disaster and post-disaster multi-type electric vehicle cluster control model and a post-disaster recovery optimization decision model based on the load recovery task and the priority;

[0009] According to the post-disaster topology change constraints containing flexible soft switches, the pre-disaster and post-disaster multi-type electric vehicle cluster control model, and the post-disaster recovery optimization decision model, a post-disaster recovery optimization decision model considering flexible soft switches and multi-type electric vehicles is generated, and the post-disaster recovery optimization decision model considering flexible soft switches and multi-type electric vehicles is solved to obtain the line reconstruction results for the load recovery task and the charging and discharging strategies of electric vehicles.

[0010] In order to solve the above technical problems, another technical solution adopted by the present invention is:

[0011] A power grid post-disaster recovery terminal includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the following steps are implemented:

[0012] Determine whether a natural disaster has occurred in the power grid. If so, determine a load restoration task and establish a post-disaster topology change constraint including flexible soft switching based on the load restoration task.

[0013] Obtaining disaster data and load importance information, and determining the priority of the load restoration task based on the disaster data and the load importance information;

[0014] Establishing a pre-disaster and post-disaster multi-type electric vehicle cluster control model and a post-disaster recovery optimization decision model based on the load recovery task and the priority;

[0015] According to the post-disaster topology change constraints containing flexible soft switches, the pre-disaster and post-disaster multi-type electric vehicle cluster control model, and the post-disaster recovery optimization decision model, a post-disaster recovery optimization decision model considering flexible soft switches and multi-type electric vehicles is generated, and the post-disaster recovery optimization decision model considering flexible soft switches and multi-type electric vehicles is solved to obtain the line reconstruction results for the load recovery task and the charging and discharging strategies of electric vehicles.

[0016] The beneficial effects of the present invention are: when a natural disaster occurs in the power supply grid, the load recovery task is determined, and based on the load recovery task, the topology change constraints containing flexible soft switches are established after the disaster. Based on the determined load recovery task and its priority, a pre-disaster and post-disaster multi-type electric vehicle cluster control model and a post-disaster recovery optimization decision model are established, thereby generating a post-disaster recovery optimization decision model considering flexible soft switches and multi-type electric vehicles. The model is solved to obtain the line reconstruction results for the load recovery task and the charging and discharging strategy of the electric vehicle. In this way, the flexible soft switching technology is used to quickly isolate the affected area when a natural disaster causes a fault, reduce the risk of fault spread, and enable the power supply grid to quickly make necessary topology adjustments after the disaster. Combined with the electric vehicle cluster, efficient distribution of post-disaster power support is achieved, thereby effectively improving the resilience and sustainability of the power supply grid after the disaster. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 A flowchart of a method for post-disaster recovery of a power grid according to an embodiment of the present invention;

[0018] Figure 2 This is a schematic structural diagram of a power grid post-disaster recovery terminal according to an embodiment of the present invention;

[0019] Figure 3 A schematic diagram of a power supply grid topology after a typhoon disaster occurs in a power supply grid post-disaster recovery method according to an embodiment of the present invention;

[0020] Figure 4 This is a schematic diagram of line restoration after a typhoon disaster occurs in a power grid post-disaster recovery method for a power grid according to an embodiment of the present invention;

[0021] Figure 5 This is a schematic diagram of the voltage conditions of each node in each period after a disaster in the power grid post-disaster recovery method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0022] To illustrate the technical content, achieved objectives and effects of the present invention in detail, the following description is given in conjunction with the embodiments and accompanying drawings.

[0023] Please refer to Figure 1 A method for post-disaster recovery of a power grid comprises the following steps:

[0024] Determine whether a natural disaster has occurred in the power grid. If so, determine a load restoration task and establish a post-disaster topology change constraint including flexible soft switching based on the load restoration task.

[0025] Obtaining disaster data and load importance information, and determining the priority of the load restoration task based on the disaster data and the load importance information;

[0026] Establishing a pre-disaster and post-disaster multi-type electric vehicle cluster control model and a post-disaster recovery optimization decision model based on the load recovery task and the priority;

[0027] According to the post-disaster topology change constraints containing flexible soft switches, the pre-disaster and post-disaster multi-type electric vehicle cluster control model, and the post-disaster recovery optimization decision model, a post-disaster recovery optimization decision model considering flexible soft switches and multi-type electric vehicles is generated, and the post-disaster recovery optimization decision model considering flexible soft switches and multi-type electric vehicles is solved to obtain the line reconstruction results for the load recovery task and the charging and discharging strategies of electric vehicles.

[0028] From the above description, it can be seen that the beneficial effects of the present invention are: when a natural disaster occurs in the power supply grid, the load recovery task is determined, and based on the load recovery task, the topology change constraints containing flexible soft switches are established after the disaster. Based on the determined load recovery task and its priority, a pre-disaster and post-disaster multi-type electric vehicle cluster control model and a post-disaster recovery optimization decision model are established, thereby generating a post-disaster recovery optimization decision model considering flexible soft switches and multi-type electric vehicles. The model is solved to obtain the line reconstruction results for the load recovery task and the charging and discharging strategy of the electric vehicle. In this way, the flexible soft switching technology is used to quickly isolate the affected area when a natural disaster causes a fault, reduce the risk of fault spread, and enable the power supply grid to quickly make necessary topology adjustments after the disaster. Combined with the electric vehicle cluster, efficient distribution of post-disaster power support is achieved, thereby effectively improving the resilience and sustainability of the power supply grid after the disaster.

[0029] Furthermore, the establishment of post-disaster topology change constraints containing flexible soft switches based on the load recovery task includes:

[0030] Establish radial and connected constraints on distribution network operation, line virtual power flow constraints, the relationship between line on / off status and virtual power flow constraints, virtual power state and output constraints, and constraints on the number of restored lines in the power grid;

[0031] Post-disaster topology change constraints containing flexible soft switches are generated based on the distribution network operation radial and connectivity constraints, the line virtual power flow constraints, the relationship constraints between the line on-off status and the virtual power flow, the virtual power supply status and output constraints, and the constraint on the number of restored lines in the power supply grid.

[0032] From the above description, it can be seen that flexible soft switches can not only replace traditional tie switches and provide safer and more reliable power control, but also effectively isolate fault currents in the event of a fault and protect the system from further damage. In addition, during the power restoration phase, they can provide the necessary voltage support for the fault side, thereby helping to expand the scope of power restoration. The reactive power supply function of the flexible soft switch can provide reactive support for the system, enhancing the operational flexibility and controllability of the distribution system, and effectively solving the problems of active power balance and reactive voltage control during the power restoration process. Therefore, flexible soft switches are used to reconstruct the power supply grid and establish topology change constraints containing flexible soft switches after the disaster to ensure system stability and safety during fault isolation and power restoration.

[0033] Furthermore, the radial and connected operation constraints of the distribution network are as follows:

[0034]

[0035] Where, α ij，trepresents the open and closed state of the switch on line ij at time t, n represents the number of all nodes in the network, n f represents the number of line root nodes, W represents the set of all lines, β ij，t A variable indicating whether node i is the parent node of node j, β ji,t A variable indicating whether node j is the parent node of node i, N(j) represents the set of nodes connected to node j, N represents all nodes in the network, and N f Indicates the line root node, N / N f Represents all nodes except the root node, N e Indicates the nodes involved in the fault line, a i，t represents the power-on status of node i at time t;

[0036] The line virtual power flow constraint is:

[0037]

[0038] Where N1(i) represents the node set of the branch terminal starting from node i, and F ij,t represents the virtual power flow of line ij, N2(i) represents the node set at the head end of the branch with node i as the terminal, and F ki,t represents the virtual power flow of line ki, D i,t represents the virtual power emitted by node i with power supply;

[0039] The relationship between the line on-off state and the virtual power flow is constrained as follows:

[0040]

[0041] Where, M represents a constant;

[0042] The virtual power state and output constraints are:

[0043]

[0044] Where, Indicates the on-state of the distributed power supply at node i;

[0045] The number of restored lines in the power grid is constrained to:

[0046]

[0047] Where N DG Represents the set of nodes connected to the black start distributed generation.

[0048] From the above description, it can be seen that when a disaster occurs, due to the change of the network topology, it is necessary to improve the relevant constraints to ensure that the lines can still meet the radial topology requirements of the distribution network after the disaster occurs.

[0049] Furthermore, before determining whether a natural disaster has occurred in the power grid, the method further includes:

[0050] Establish a tower and line fault prediction model for the power grid;

[0051] Calculating a failure probability curve based on the tower and line fault prediction model;

[0052] Based on the fault probability curve, the Monte Carlo method is used to sample the state of each line when a natural disaster occurs, and a pre-disaster disaster simulation result is obtained;

[0053] Based on the load recovery tasks and their priorities, a pre-disaster and post-disaster multi-type electric vehicle cluster control model is established, including:

[0054] Determining a charging and dispatching plan for public transportation electric vehicles and a charging strategy and an emergency response strategy for private electric vehicles based on the pre-disaster disaster simulation results;

[0055] Generating a pre-disaster preparedness strategy for a multi-type electric vehicle cluster based on the charging and dispatching plan for the public transportation electric vehicles and the charging strategy and emergency response strategy for the private electric vehicles;

[0056] Establishing a public transportation electric vehicle post-disaster scheduling model and a private electric vehicle post-disaster scheduling model based on the load recovery tasks and their priorities;

[0057] A pre-disaster and post-disaster multi-type electric vehicle cluster control model is obtained according to the pre-disaster preparation strategy of the multi-type electric vehicle cluster, the post-disaster scheduling model of the public transportation electric vehicle and the post-disaster scheduling model of the private electric vehicle.

[0058] From the above description, it can be seen that pre-disaster disaster simulation can help to reasonably pre-allocate resources before the disaster and ensure more reasonable resource allocation and deployment in the future. The pre-disaster and post-disaster multi-type electric vehicle cluster control model includes a pre-disaster preparation strategy for multi-type electric vehicle clusters, a post-disaster scheduling model for public transportation electric vehicles, and a post-disaster scheduling model for private electric vehicles. In this way, backup power can be provided to the power supply grid after the disaster, which not only improves the flexibility and efficiency of post-disaster recovery, but also promotes the development of smart grid technology.

[0059] Furthermore, a post-disaster dispatch model for electric vehicles for public transportation is established based on the load recovery tasks and their priorities, including:

[0060] Establishing a first objective function and its corresponding supply constraints, demand constraints and non-negative constraints based on the load restoration tasks and their priorities to minimize costs;

[0061] A post-disaster scheduling model for electric vehicles of the public transportation type is generated according to the first objective function, the supply constraint, the demand constraint and the non-negative constraint.

[0062] From the above description, it can be seen that the post-disaster scheduling model of electric vehicles for public transportation establishes the first objective function and its corresponding supply constraints, demand constraints and non-negative constraints by minimizing costs, which can ensure that key areas can obtain sufficient transportation support in emergency situations while taking into account cost and efficiency.

[0063] Furthermore, the first objective function is:

[0064]

[0065] In the formula, S represents the set of all sites, D represents the set of demand points, c ij represents the cost from site i to site j, r j represents the degree of damage to the route near station j, w j represents the importance weight of site j, x ij represents the number of electric vehicles of the public transportation type dispatched from station i to station j.

[0066] From the above description, it can be seen that the first objective function is established by minimizing the cost, which ensures the economic feasibility of electric vehicles for public transportation supporting power grid restoration.

[0067] Furthermore, a post-disaster dispatch model for private electric vehicles is established based on the load restoration tasks and their priorities, including:

[0068] Quantify the total travel intention of private electric vehicles;

[0069] Determining the remaining power requirement for the private electric vehicle;

[0070] Determining the discharge power of the private electric vehicle;

[0071] A post-disaster dispatch model for private electric vehicles is generated according to the total travel intention, the remaining power requirement, and the discharge power.

[0072] As can be seen from the above description, the post-disaster scheduling model for private electric vehicles is generated based on total travel intention, remaining power requirements, and discharge power. It takes into account the impact of disasters on users' travel intentions and ensures that only private electric vehicles with sufficient power are included in the power-supported electric vehicle cluster, ensuring the reliability of private electric vehicles in supporting power grid restoration.

[0073] Furthermore, establishing a post-disaster recovery optimization decision model based on the load recovery tasks and their priorities includes:

[0074] Establishing a second objective function and its corresponding flexible soft switching constraints, node voltage constraints, branch current constraints, and network power flow constraints based on the load restoration tasks and their priorities to minimize the weighted sum of load losses at each node;

[0075] A post-disaster recovery optimization decision model is generated according to the second objective function, the flexible soft switch constraint, the node voltage constraint, the branch current constraint, and the network power flow constraint.

[0076] From the above description, it can be seen that the second objective function and its corresponding flexible soft switching constraints, node voltage constraints, branch current constraints and network flow constraints are established based on the load recovery task and its priority to minimize the weighted sum of the load losses of each node. The flexibility of the grid-load (power supply network and load) is taken into account to improve the resilience and recovery efficiency of the power system, thereby reducing power outage time and reducing economic losses.

[0077] Furthermore, the second objective function is:

[0078]

[0079] Where F represents the weighted sum of load losses at each node, T represents the recovery period, I represents the set of all load nodes, and κ i represents the priority of the load at node i during post-disaster recovery, represents the load loss of node i at time t.

[0080] From the above description, it can be seen that the second objective function is established by minimizing the weighted sum of load losses at each node, so that the remaining dispatchable load resources can be used to participate in the post-disaster load recovery process, improve the recovery efficiency, and effectively improve the resilience and sustainability of the power supply grid after the disaster.

[0081] Please refer to Figure 2 Another embodiment of the present invention provides a power grid post-disaster recovery terminal, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, each step in the above-mentioned power grid post-disaster recovery method is implemented.

[0082] The power grid post-disaster recovery method and terminal of the present invention are applicable to power grid post-disaster recovery scenarios, and are described below through specific implementation methods:

[0083] Please refer to Figure 1 、 Figure 3-Figure 5 , embodiment 1 of the present invention is:

[0084] A power grid post-disaster recovery method comprising the steps of:

[0085] S1. Establish a tower and line fault prediction model for the power grid.

[0086] Specifically, power grid failures caused by natural disasters (such as typhoons) are generally caused by overhead line collapse and line disconnection. The specific prediction model for tower and line failures in the power grid is as follows:

[0087]

[0088]

[0089] In the formula, p(v) represents the failure rate of the tower, v represents the maximum wind speed predicted by the typhoon, represents the failure rate of tower components, v p represents the design wind speed of the tower, η represents the angle between the typhoon wind direction and the line direction, λ p represents the tower's sensitivity to typhoons, v l Indicates the ultimate wind speed of the tower, p line represents the probability of normal operation of the line, K represents the number of towers contained in the line, and p k (v) represents the probability of failure of the kth tower in the line at wind speed v.

[0090] S2. Calculate a fault probability curve based on the tower and line fault prediction model.

[0091] The horizontal axis of the failure probability curve is wind stress, and the vertical axis is failure rate. The curve quantifies the relationship between the stress of the tower subjected to wind and the failure rate, so as to reflect the impact of typhoons on distribution network components.

[0092] S3. Based on the fault probability curve, a Monte Carlo method is used to sample the state of each line when a natural disaster occurs, to obtain a pre-disaster disaster simulation result.

[0093] S4. Determine whether a natural disaster has occurred in the power grid. If so, determine a load restoration task and establish a post-disaster topology change constraint including flexible soft switches based on the load restoration task. Specifically, S41-S43 are included:

[0094] S41. Determine whether a natural disaster has occurred in the power grid. If so, determine a load restoration task.

[0095] For example, suppose a typhoon occurs. Figure 3 As shown, if lines 1-2 and 8-9 fail, the power supply grid may lose the support of the upper power grid, and the load recovery task is determined based on lines 1-2 and 8-9.

[0096] S42. Establish radial and connectivity constraints for distribution network operation, line virtual flow constraints, constraints on the relationship between line on / off status and virtual flow, virtual power supply status and output constraints, and constraints on the number of restored lines in the power supply grid.

[0097] Among them, with the help of distributed power sources with black start capability in the power grid to restore power supply, the distribution network exhibits radial constraints under normal operation. However, after a line failure caused by a disaster, the radial requirements of the line may no longer be met. Flexible soft switches and tie switches are needed to reconfigure the network so that the power grid lines meet the radial and connectivity constraints. Therefore, the radial and connectivity constraints of the distribution network operation are:

[0098]

[0099] Where, α ij，t It represents the open and closed state of the switch on line ij at time t, which is a Boolean variable. n represents the number of all nodes in the network. f represents the number of line root nodes, W represents the set of all lines, β ij，t A variable indicating whether node i is the parent node of node j. It is a Boolean auxiliary variable. If node i is the parent node of node j, then β ij，t is equal to 1, otherwise equal to 0, β ji,t A variable indicating whether node j is the parent node of node i, N(j) represents the set of nodes connected to node j, N represents all nodes in the network, and N f Indicates the line root node, N / N f Represents all nodes except the root node, N e represents the nodes involved in the fault line, α i，t Indicates the power-on status of node i at time t, which is a Boolean variable;

[0100] After a disaster occurs, due to changes in the network topology, it is necessary to improve the relevant constraints to ensure that the line can still meet the radial requirements of the distribution network after restoration. Here, the single commodity flow method is used to further improve the network topology constraints. Therefore, the line virtual power flow constraint is:

[0101]

[0102] Where N1(i) represents the node set of the branch terminal starting from node i, and F ij,t represents the virtual power flow of line ij, N2(i) represents the node set at the head end of the branch with node i as the terminal, and F ki,t represents the virtual power flow of line ki, D i,t represents the virtual power emitted by node i with power supply;

[0103] The relationship between the line on-off state and the virtual power flow is constrained as follows:

[0104]

[0105] Where, M represents a constant;

[0106] The virtual power state and output constraints are:

[0107]

[0108] Where, Indicates the on-state of the distributed power supply at node i;

[0109] The number of restored lines in the power grid is constrained to:

[0110]

[0111] Where N DG Represents the set of nodes connected to the black start distributed generation.

[0112] The above constraints can ensure that the line can still meet the radial topology requirements of the distribution network after the disaster occurs, such as Figure 4 shown.

[0113] S43. Generate post-disaster topology change constraints containing flexible soft switches based on the radial and connected operation constraints of the distribution network, the line virtual power flow constraints, the relationship constraints between the line on-off status and the virtual power flow, the virtual power supply status and output constraints, and the constraint on the number of restored lines in the power supply grid.

[0114] S2. Obtain disaster data and load importance information, and determine the priority of the load restoration task based on the disaster data and the load importance information, ensuring that the most critical load is restored first.

[0115] S3. Establishing a pre-disaster and post-disaster multi-type electric vehicle cluster control model and a post-disaster recovery optimization decision model based on the load recovery task and the priority, specifically including S31-S36:

[0116] S31. Determine a charging and dispatching plan for public transportation electric vehicles and a charging strategy and emergency response strategy for private electric vehicles based on the pre-disaster disaster simulation results.

[0117] Specifically, the charging plan for electric vehicles used in public transportation is determined based on historical data and predicted electricity demand, and the travel routes and times of electric vehicles used in public transportation are determined based on traffic flow forecasts and the pre-disaster disaster simulation results, to ensure that there are enough vehicles on standby at critical moments before a disaster; real-time information on charging stations and charging recommendations are provided to private electric vehicles to encourage private car owners to maintain a high charge state before a disaster and avoid charging peaks during emergency periods; an information sharing platform is established to enable private car owners to obtain emergency information in a timely manner and make emergency responses.

[0118] It can also provide real-time scheduling and route planning suggestions for private electric vehicles through smartphone applications or in-car navigation systems.

[0119] S32: Generate a pre-disaster preparedness strategy for a multi-type electric vehicle cluster based on the charging and dispatching plan for the public transportation electric vehicles and the charging strategy and emergency response strategy for the private electric vehicles.

[0120] Electric vehicles can be regarded as mobile distributed small-scale energy storage, providing emergency power support for rescue equipment or disaster areas. The characteristics of electric vehicles enable them to travel to weak nodes in the distribution network, providing flexible scheduling capabilities for the distribution network and improving the post-disaster recovery efficiency of the power supply grid.

[0121] S33: establishing a public transportation electric vehicle post-disaster scheduling model and a private electric vehicle post-disaster scheduling model based on the load recovery tasks and their priorities, specifically including S331-S336:

[0122] S331. Based on the load recovery task and its priority, a first objective function and its corresponding supply constraint, demand constraint and non-negative constraint are established to minimize cost.

[0123] Among them, for electric vehicles used in public transportation, reasonable arrangements must be made before the disaster based on the predicted damaged line locations. Since public transportation vehicles are centrally dispatched by relevant transportation departments and have strong compliance and regularity, electric vehicles used in public transportation should be reasonably distributed based on the importance of the load and the distribution location of the predicted fault lines to ensure that key areas can receive sufficient transportation support in an emergency. At the same time, considering cost efficiency, the first objective function is:

[0124]

[0125] In the formula, S represents the set of all sites, D represents the set of demand points, c ij represents the cost from site i to site j, including factors such as time and energy consumption, r j represents the degree of damage to the route near station j, w jrepresents the importance weight of site j, x ij represents the number of electric vehicles of the public transportation type dispatched from station i to station j.

[0126] The supply constraint is:

[0127]

[0128] Where s i represents the number of electric vehicles supplied for public transportation at station i;

[0129] The requirement constraints are:

[0130]

[0131] Where, d i represents the number of electric vehicles required for public transportation at station i;

[0132] The non-negativity constraints are:

[0133]

[0134] S332. Generate a post-disaster dispatch model for electric vehicles for public transportation based on the first objective function, the supply constraint, the demand constraint, and the non-negative constraint.

[0135] S333. Quantify the total travel intention of private electric vehicles, specifically:

[0136] N res =ρN all ;

[0137] Where N res Indicates the number of private electric vehicles willing to participate in post-disaster support, N all represents the number of all private electric vehicles, and ρ represents the travel ratio coefficient.

[0138] For private electric vehicles, natural disasters will affect the travel behavior of electric vehicle users to a certain extent. In order to reflect the impact of disasters on users' travel intentions, a travel proportion coefficient is introduced to quantify the changes in the total travel intentions of private electric vehicle user groups.

[0139] S334: Determine the remaining power requirement for the private electric vehicle.

[0140] Specifically, to estimate the discharge potential of electric vehicles after a disaster, it is necessary to analyze the SOC (state of charge) of electric vehicles when they are connected to V2G (electric vehicle access network technology). The SOC of electric vehicle batteries is mainly affected by the daily mileage. Therefore, assuming that the power consumption of private electric vehicles is proportional to their daily mileage, the final remaining power of private electric vehicles can be calculated from the initial power and mileage as follows:

[0141]

[0142] Where, Indicates the SOC of the electric vehicle when it leaves the charging period after charging. represents the initial SOC of the electric vehicle during the charging period, d represents the mileage of the electric vehicle outside the charging period, and D represents the cruising range of the electric vehicle.

[0143] The Monte Carlo method is used to sample the daily mileage of private electric vehicles based on probability characteristics, and the remaining power of multiple private electric vehicle loads is obtained as follows:

[0144]

[0145] Where, f D (d) represents the remaining power of multiple private electric vehicle loads, σ D represents the standard deviation of the corresponding driving distance, μ D represents the mean of the corresponding travel distances.

[0146] Only vehicles with sufficient power can support the post-disaster recovery of the power grid. Therefore, only private electric vehicles that meet the relevant power requirements will be included in the power-supported electric vehicle load cluster, specifically:

[0147]

[0148] Where, represents the maximum power of the i-th private electric vehicle, and γ represents the power threshold ratio set to allow participation in post-disaster support.

[0149] S335: Determine the discharge power of the private electric vehicle, specifically:

[0150]

[0151] Where, Indicates the aggregate power of private electric vehicles, N res Indicates the number of private electric vehicles participating in the support. Indicates the power of a single electric vehicle, represents the power of a private electric vehicle at time t, Represents the electric car's power at time t-1, P i EV Indicates the discharge power of private electric vehicles, represents the discharge efficiency, P represents the state of charge of a private electric vehicle at time t. i max represents the maximum discharge power of the i-th private electric vehicle.

[0152] S336: Generate a post-disaster dispatch model for private electric vehicles based on the total travel intention, the remaining power requirement, and the discharge power.

[0153] S34. Obtain a pre-disaster and post-disaster multi-type electric vehicle cluster control model based on the pre-disaster preparation strategy of the multi-type electric vehicle cluster, the public transportation electric vehicle post-disaster scheduling model, and the private electric vehicle post-disaster scheduling model.

[0154] S35. Establish a second objective function and its corresponding flexible soft switching constraints, node voltage constraints, branch current constraints, and network power flow constraints based on the load recovery tasks and their priorities to minimize the weighted sum of load losses at each node.

[0155] Among them, the second objective function is:

[0156]

[0157] Where F represents the weighted sum of load losses at each node, T represents the recovery period, I represents the set of all load nodes, and κ i represents the priority of the load at node i during post-disaster recovery, represents the load loss of node i at time t.

[0158] The flexible soft switching constraints are:

[0159]

[0160] Where, represents the active power of node i on both sides of the flexible soft switch at time t, represents the active power of node j on both sides of the flexible soft switch at time t, represents the reactive power of node i on both sides of the flexible soft switch at time t, represents the reactive power of node j on both sides of the flexible soft switch at time t, P mini represents the lower limit of active power of node i on both sides of the flexible soft switch, P maxi represents the upper limit of active power of node i on both sides of the flexible soft switch, Qminj represents the lower limit of reactive power at node j on both sides of the flexible soft switch, Q maxj represents the upper limit of reactive power of node j on both sides of the flexible soft switch, represents the access capacity of node i on both sides of the flexible soft switch, represents the access capacity of node j on both sides of the flexible soft switch.

[0161] The node voltage constraint is:

[0162] U min ≤U i,t ≤U max ;

[0163] Where U min Indicates the lower limit of the node voltage, U i,t represents the node voltage value of node i at time t, U max Indicates the upper limit of the node voltage.

[0164] The branch current constraint is:

[0165] I ij,t ≤I ij,max ;

[0166] Where, I ij,t It represents the current amplitude flowing from node i to node j at time t, I ij,max Indicates the upper limit of the current amplitude flowing from node i to node j.

[0167] The network power flow constraint is:

[0168]

[0169] Where, Φ i represents the set of branch head nodes with node i as the terminal node, Ψ i represents the set of branch end nodes with node i as the head node, α ik Indicates the switch status of line ik, P ik,t represents the active power flowing from node i to node k at time t, α ji Indicates the switch status of line ji, P ij，t represents the active power flowing from node j to node i at time t, R ji Indicates the resistance of branch ji, I ji，t represents the current amplitude from node j to node i at time t, P t,i represents the active power of node i at time t, Q ik,t represents the reactive power flowing from node i to node k at time t, Q ji，t represents the reactive power flowing from node j to node i at time t, X ji Indicates the reactance of branch ji, Qt,i represents the reactive power of node i at time t, U j,t represents the voltage amplitude of node j at time t, U t,i represents the voltage amplitude of node i at time t, r ji represents the resistance of line ji, x ji Indicates the reactance of line ji;

[0170] The above power flow equation is non-convex, and the large M method is used to introduce inequality constraints to relax it. At this time, for the open branch, its active power, reactive power and branch current are 0, while for the closed branch, this constraint does not apply. Specifically:

[0171]

[0172] Where, M1 represents the first constant, M2 represents the second constant, M3 represents the third constant, and P ij,t Indicates the active power of branch ij, Q ij,t represents the reactive power of branch ij, α ij Indicates the switch state of line ij;

[0173] So the above power flow equation is transformed into:

[0174]

[0175] Where, P i，t represents the sum of the net active power injected into node i at time t, Q i，t represents the sum of the net reactive power injected into node i at time t, represents the active power injected by the distributed generation on node i at time t, represents the reactive power injected by the distributed generation on node i at time t, represents the reactive power injected into node i by the flexible soft switch, represents the reactive power injected into node i by the flexible soft switch, represents the active power of the load on node i at time t, It represents the reactive power of the load on node i at time t, U i,t represents the voltage amplitude of node i at time t, M4 represents the fourth constant, α ji,t represents the switch state of line ji at time t, P t loss represents the load of node i at time t;

[0176] There are many non-convex constraints in the above formula, which need to be transformed. The node voltage constraint also does not meet the requirements of SOCP (quadratic cone programming) for the constraint form. and Replace the quadratic term (It，ji ) 2 and(U t，ij ) 2 The node voltage constraint and the above power flow equation are transformed into a second-order cone in the form of , and the upper and lower limits are transformed and the related constraints are relaxed. The network power flow constraint and the node voltage constraint can be expressed as follows in the mixed integer second-order cone programming model:

[0177]

[0178] Finally Further relaxation and equivalent deformation into a second-order cone form is:

[0179]

[0180] S36. Generate a post-disaster recovery optimization decision model according to the second objective function, the flexible soft switch constraint, the node voltage constraint, the branch current constraint, and the network power flow constraint.

[0181] S4. Generate a post-disaster recovery optimization decision model considering flexible soft switches and multiple types of electric vehicles based on the post-disaster topology change constraints containing flexible soft switches, the pre-disaster and post-disaster multi-type electric vehicle cluster control model, and the post-disaster recovery optimization decision model. Solve the post-disaster recovery optimization decision model considering flexible soft switches and multiple types of electric vehicles to obtain the line reconstruction results for the load recovery task and the charging and discharging strategy of the electric vehicle.

[0182] Specifically, after inputting the boundary conditions according to the actual situation, the solver is used to solve the post-disaster recovery optimization decision model considering flexible soft switches and multiple types of electric vehicles, and the line reconstruction results for the load recovery task and the charging and discharging strategies of electric vehicles are obtained.

[0183] In an optional embodiment, the method further includes:

[0184] S5. Determine whether the load has recovered to the expected level. If not, return to S3. If so, end.

[0185] like Figure 5 As shown, after the per-unit values ​​of the voltages of the nodes in the power grid in various periods after the disaster are implemented through the above-described strategy of the present invention, the voltages have returned to a relatively stable level.

[0186] Please refer to Figure 2 , the second embodiment of the present invention is:

[0187] A power grid post-disaster recovery terminal includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the processor implements the various steps of the power grid post-disaster recovery method in the first embodiment.

[0188] In summary, the present invention provides a power grid post-disaster recovery method and terminal. When a natural disaster occurs in the power grid, the load recovery task is determined, and based on the load recovery task, a post-disaster topology change constraint containing flexible soft switches is established. Based on the determined load recovery tasks and their priorities, a pre-disaster and post-disaster multi-type electric vehicle cluster control model and a post-disaster recovery optimization decision model are established. In this way, a post-disaster recovery optimization decision model considering flexible soft switches and multi-type electric vehicles is generated. The model is solved to obtain the line reconstruction results for the load recovery task and the charging and discharging strategy of the electric vehicle. In this way, the flexible soft switching technology is used to quickly isolate the affected area when a fault is caused by a natural disaster, thereby reducing the spread of the fault. The risk of disaster can be reduced, so that the power supply grid can quickly make necessary topological adjustments after the disaster. Combined with the electric vehicle cluster, efficient distribution of post-disaster power support is achieved, thereby effectively improving the resilience and sustainability of the power supply grid after the disaster. In addition, pre-disaster disaster simulation can help to reasonably pre-allocate pre-disaster resources to ensure more reasonable resource allocation and deployment in the future. The pre-disaster and post-disaster multi-type electric vehicle cluster control model includes pre-disaster preparation strategies for multi-type electric vehicle clusters, post-disaster scheduling models for public transportation electric vehicles, and post-disaster scheduling models for private electric vehicles, so as to provide backup power to the power supply grid after the disaster, which not only improves the flexibility and efficiency of post-disaster recovery, but also promotes the development of smart grid technology.

[0189] The above descriptions are merely embodiments of the present invention and are not intended to limit the scope of the present invention. Any equivalent transformations made using the contents of the present invention's description and drawings, or directly or indirectly applied in related technical fields, are also included in the scope of the present invention's patent protection.

Claims

1. A power grid post-disaster recovery method, characterized in that: Including steps: Determine whether a natural disaster has occurred in the power grid. If so, determine a load restoration task and establish a post-disaster topology change constraint including flexible soft switching based on the load restoration task. Obtaining disaster data and load importance information, and determining the priority of the load restoration task based on the disaster data and the load importance information; Establishing a pre-disaster and post-disaster multi-type electric vehicle cluster control model and a post-disaster recovery optimization decision model based on the load recovery task and the priority; A post-disaster recovery optimization decision model considering flexible soft switches and multiple types of electric vehicles is generated based on the post-disaster topology change constraints containing flexible soft switches, the pre-disaster and post-disaster multi-type electric vehicle cluster control model, and the post-disaster recovery optimization decision model. The post-disaster recovery optimization decision model considering flexible soft switches and multiple types of electric vehicles is solved to obtain a line reconstruction result for the load recovery task and a charging and discharging strategy for the electric vehicle; Based on the load recovery tasks and their priorities, a pre-disaster and post-disaster multi-type electric vehicle cluster control model is established, including: Determine charging and dispatch plans for electric vehicles used in public transportation, as well as charging strategies and emergency response strategies for private electric vehicles, based on pre-disaster simulation results; Generating a pre-disaster preparedness strategy for a multi-type electric vehicle cluster based on the charging and dispatching plan for the public transportation electric vehicles and the charging strategy and emergency response strategy for the private electric vehicles; Establishing a public transportation electric vehicle post-disaster scheduling model and a private electric vehicle post-disaster scheduling model based on the load recovery tasks and their priorities; Obtaining a pre-disaster and post-disaster multi-type electric vehicle cluster control model based on the pre-disaster preparation strategy of the multi-type electric vehicle cluster, the post-disaster dispatch model of the public transportation electric vehicle, and the post-disaster dispatch model of the private electric vehicle; The post-disaster dispatch model for electric vehicles for public transportation based on the load recovery tasks and their priorities includes: Establishing a first objective function and its corresponding supply constraints, demand constraints and non-negative constraints based on the load restoration tasks and their priorities to minimize costs; Generate a post-disaster dispatch model for electric vehicles for public transportation according to the first objective function, the supply constraint, the demand constraint, and the non-negative constraint; The establishment of a post-disaster recovery optimization decision model based on the load recovery tasks and their priorities includes: Establishing a second objective function and its corresponding flexible soft switching constraints, node voltage constraints, branch current constraints, and network power flow constraints based on the load restoration tasks and their priorities to minimize the weighted sum of load losses at each node; A post-disaster recovery optimization decision model is generated according to the second objective function, the flexible soft switch constraint, the node voltage constraint, the branch current constraint, and the network power flow constraint.

2. A power grid post-disaster recovery method according to claim 1, characterized in that: The establishment of a post-disaster topology change constraint including a flexible soft switch based on the load restoration task includes: Establish radial and connected constraints on distribution network operation, line virtual power flow constraints, the relationship between line on / off status and virtual power flow constraints, virtual power state and output constraints, and constraints on the number of restored lines in the power grid; Post-disaster topology change constraints containing flexible soft switches are generated based on the distribution network operation radial and connectivity constraints, the line virtual power flow constraints, the relationship constraints between the line on-off status and the virtual power flow, the virtual power supply status and output constraints, and the constraint on the number of restored lines in the power supply grid.

3. A power grid post-disaster recovery method according to claim 2, characterized in that: The radial and connected operation constraints of the distribution network are: Where, represents the open and closed state of the switch on line ij at time t, n represents the number of all nodes in the network, n f represents the number of line root nodes, W represents the set of all lines, A variable indicating whether node i is the parent node of node j, A variable indicating whether node j is the parent node of node i, N(j) represents the set of nodes connected to node j, N represents all nodes in the network, and N f Indicates the line root node, N / N f Represents all nodes except the root node, N e Indicates the nodes involved in the fault line, represents the power-on status of node i at time t; The line virtual power flow constraint is: ； Where N1(i) represents the node set of the branch terminal starting from node i, represents the virtual power flow of line ij, N2(i) represents the node set at the head end of the branch with node i as the terminal, represents the virtual power flow of line ki, represents the virtual power emitted by node i with power supply; The relationship between the line on-off state and the virtual power flow is constrained as follows: ； Where, M represents a constant; The virtual power state and output constraints are: ； Where, Indicates the on-state of the distributed power supply at node i; The number of restored lines in the power grid is constrained to: ； Where N DG Represents the set of nodes connected to the black start distributed generation.

4. A power grid post-disaster recovery method according to claim 1, characterized in that: Before determining whether a natural disaster has occurred in the power grid, the method further includes: Establish a tower and line fault prediction model for the power grid; Calculating a failure probability curve based on the tower and line fault prediction model; Based on the fault probability curve, the Monte Carlo method is used to sample the state of each line when a natural disaster occurs, and a pre-disaster disaster simulation result is obtained.

5. The power grid post-disaster recovery method according to claim 1, characterized in that: The first objective function is: ； In the formula, S represents the set of all sites, D represents the set of demand points, c ij represents the cost from site i to site j, r j represents the degree of damage to the route near station j, w j represents the importance weight of site j, x ij represents the number of electric vehicles of the public transportation type dispatched from station i to station j.

6. A power grid post-disaster recovery method according to claim 4, characterized in that: The post-disaster dispatch model for private electric vehicles based on the load restoration tasks and their priorities includes: Quantify the total travel intention of private electric vehicles; Determining the remaining power requirement for the private electric vehicle; Determining the discharge power of the private electric vehicle; A post-disaster dispatch model for private electric vehicles is generated according to the total travel intention, the remaining power requirement, and the discharge power.

7. A power grid post-disaster recovery method according to claim 1, characterized in that: The second objective function is: ； Where F represents the weighted sum of load losses at each node, T represents the recovery period, and I represents the set of all load nodes. represents the priority of the load at node i during post-disaster recovery, represents the load loss of node i at time t.

8. A power grid post-disaster recovery terminal, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, each step of the power grid post-disaster recovery method according to any one of claims 1 to 7 is implemented.

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