A microgrid group resource optimization allocation method, device, terminal equipment and storage medium

Abstract

The present invention discloses a method, apparatus, terminal device, and storage medium for optimizing and allocating resources in a microgrid group. The method includes: obtaining typhoon basic data, grid line operation data, energy storage operation data, and grid operation costs, and then constructing a grid fault model; solving the constructed microgrid group optimization model under the constraints of the microgrid group with the goal of minimizing the microgrid group dispatching cost, and obtaining the current exchange power and current energy storage configuration; constructing a sub-microgrid optimization model and sub-microgrid constraints based on the grid fault model, the current exchange power, and the current energy storage configuration; solving the constructed sub-microgrid optimization model under the constraints of the sub-microgrid with the goal of minimizing the sub-microgrid dispatching cost, and optimizing and adjusting the microgrid group resources based on the grid line operation data, the solved typhoon basic data, the target exchange power, the target energy storage configuration, and the output of controllable resources. The implementation of the present invention improves the overall security of the distribution network.

Description

Technical Field

[0001] The present invention relates to the field of power systems and automation technologies, and in particular to a method, device, terminal equipment and storage medium for optimizing and allocating resources of a microgrid group. Background Art

[0002] With rapid economic development and increased emphasis on environmental protection, my country is actively promoting the development of sustainable energy. Distributed power generation (DGs) based on renewable energy have become a crucial component of modern power grids. However, the intermittent and random nature of DGs poses challenges to power quality and power system stability. Microgrids have emerged to address this issue. A microgrid is a localized power grid that can operate independently of or connected to the main grid. It typically consists of localized generation resources, energy storage systems, loads, and control systems. A microgrid cluster is a network of multiple microgrids that can be interconnected and operate collaboratively to achieve more efficient resource utilization and improved system stability. In recent years, due to the frequent occurrence of large-scale power outages caused by natural disasters, the power supply reliability of microgrids has been vulnerable to extreme weather events. In particular, when a microgrid cluster is disconnected from the main grid, it can suffer significant losses. Therefore, effectively optimizing resource allocation and improving the overall security of the distribution network have become urgent challenges. Summary of the Invention

[0003] The embodiments of the present invention provide a method, apparatus, terminal device and storage medium for optimizing and allocating resources of a microgrid group, which can effectively solve the problem of how to effectively optimize and allocate resources and improve the overall security of the distribution network.

[0004] An embodiment of the present invention provides a method for optimizing and allocating resources of a microgrid group, comprising:

[0005] Obtain basic typhoon data, power grid line operation data, energy storage operation data, and power grid operation costs;

[0006] Constructing a power grid fault model based on the typhoon basic data and the power grid line operation data;

[0007] Constructing a microgrid group optimization model and microgrid group constraints based on the grid fault model, the grid line operation data, the energy storage operation data, and the grid operation cost;

[0008] According to the grid line operation data, the energy storage operation data and the grid operation cost, with the goal of minimizing the microgrid group dispatching cost, the microgrid group optimization model is solved under the constraints of the microgrid group to obtain the current exchange power and the current energy storage configuration;

[0009] Constructing a sub-microgrid optimization model and sub-microgrid constraints based on the grid fault model, the grid line operation data, the energy storage operation data, the grid operation cost, the current exchange power, and the current energy storage configuration;

[0010] Based on the grid line operation data, the energy storage operation data, the grid operation cost, the current exchange power, and the current energy storage configuration, with the goal of minimizing the sub-microgrid scheduling cost, the sub-microgrid optimization model is solved under the sub-microgrid constraints to obtain the target exchange power, target energy storage configuration, and controllable resource output; and the current exchange power and current energy storage configuration are updated respectively according to the target exchange power and target energy storage configuration;

[0011] The microgrid group resources are optimized and adjusted according to the grid line operation data, typhoon basic data, target exchange power, target energy storage configuration and controllable resource output.

[0012] Furthermore, the microgrid group constraints include: a first power balance constraint, a power exchange constraint, an energy storage constraint, and a diesel generator output constraint;

[0013] The first power balance constraint is:

[0014]

[0015] in, The microgrid group and the upper power grid in the time period The power of electric energy interaction within the For diesel in the period internal effort; Energy storage for microgrids In the period Charging power within Energy storage for microgrids In the period Discharge power within is the load at the microgrid group end; Microgrid group and sub-microgrid In the period The power of electric energy interaction within the Assemble for diesel generators; It is the collection of all energy storage in the microgrid group; is a microgrid cluster;

[0016] The power exchange constraint is:

[0017] ; ;

[0018] in, Microgrid group and sub-microgrid The lower limit of power exchange between Microgrid group and sub-microgrid The upper limit of power exchange between is the lower limit of power exchange between the microgrid cluster and the main grid; is the upper limit of power exchange between the microgrid cluster and the main grid;

[0019] The energy storage constraint is:

[0020]

[0021] ; ;

[0022] ; ;

[0023] in, For time t The amount of energy storage on the node; For time t Minimum energy storage at the node; For time t The maximum energy storage value at the node; is the preset time step; For charging efficiency; is the discharge efficiency; ESS capacity; is the maximum charging power; is the maximum discharge power; is the charging state variable; is the discharge state variable;

[0024] The diesel generator output constraint is:

[0025] ; ;

[0026] in, For diesel generators The lower limit of power output; For diesel generators The upper limit of power output; For diesel generators The total power that can be generated by the stored fuel.

[0027] Furthermore, the sub-microgrid constraints include: a second power balance constraint, a mobile emergency power supply vehicle constraint, a line maintenance constraint, a radial operation constraint, a photovoltaic and wind power output constraint, a controllable load constraint, a sub-microgrid energy storage constraint, and a sub-microgrid power generation constraint;

[0028] The second power balance constraint is:

[0029] ;

[0030] ; ;

[0031] in, Power flows into the bus The branch set of Power outflow bus The branch set of is the active power flowing into or out of node i during period t; is the reactive power flowing into or out of node i during period t; Active power output of distributed energy; Provide reactive power for distributed energy; Active power output for mobile emergency power supply; Reactive power output for mobile emergency power supply; Busbar Active load removed; Busbar Reactive load removed; Energy storage for microgrids In the period Discharge power within For energy storage In the period Charging power within Provides active power for the diesel generators of the microgrid; Provide reactive power for the diesel generators of the microgrid; For nodes Active load; For nodes Reactive load; is the power value of the starting node 1 of the sub-microgrid; It is represented by the exchange power provided by the microgrid group to a certain sub-microgrid during the period t;

[0032] The mobile emergency power supply vehicle is constrained as follows:

[0033] ; ; ; ;

[0034] ; ; ;

[0035] in, A mobile emergency power supply vehicle in the current area; mustering for emergency vehicles; To confirm candidate link nodes Whether to use a mobile emergency power supply vehicle connected variables; The total number of mobile emergency response units in the current region; is the connection state variable between the mobile emergency power supply vehicle and the candidate node; for Active power output of the node mobile emergency power supply vehicle; For the The maximum capacity of a mobile emergency power supply vehicle; is the maximum active power output of MEG; is the maximum reactive power output of MEG;

[0036] The line maintenance constraints are:

[0037] ; ; ;

[0038] in, The maximum number of lines that can be repaired in the same period of time; For maintenance The time taken for each route; For the line exist On / off status within the time period;

[0039] The radial operation constraints are:

[0040] ; ;

[0041] ; ; ; ;

[0042] in, For the current by the branch Flow to branch State variables at time ; For the current by the branch Flow to branch State variables at time ; For the period Inner branch road The state variable of the fault; It is the set of root buses directly connected to the power plant; is the set of root buses directly connected to the DG; It is the set of root buses directly connected to the MEG; For the period Internal busbar There are state variables with power exchange at ; is an infinite value; For the period Inner branch road Active power; For the period Inner branch road Reactive power;

[0043] The photovoltaic and wind power output constraints are:

[0044] ; ;

[0045] in, is the fan output power; is the rated power of the fan; is the cut-in wind speed; is the rated wind speed; To cut out wind speed; is the actual wind speed of the fan; The output power of the photovoltaic power source; is the rated power; is the radiation intensity at the working point; is the battery surface temperature; is the rated temperature; is the rated radiation intensity; is the power temperature coefficient;

[0046] The controllable load constraint is:

[0047]

[0048] in, For nodes Active controllable load; For nodes Reactive controllable load;

[0049] The sub-microgrid energy storage constraints are:

[0050] ; ;

[0051] ; ; ;

[0052] in, For time t The size of the sub-microgrid energy storage at the node; For time t Minimum energy storage value of the sub-microgrid at the node; For time t The maximum energy storage capacity of the sub-microgrid at the node; Charging efficiency for sub-microgrids; is the discharge efficiency of the sub-microgrid; ESS capacity; The maximum charging power of the sub-microgrid; is the maximum discharge power of the sub-microgrid; is the charging state variable; is the discharge state variable;

[0053] The sub-microgrid power generation constraints are:

[0054] ; ;

[0055] in, For diesel generators The lower limit of power output; For diesel generators The upper limit of power output; Diesel generator for microgrid The total power that can be generated by the stored fuel.

[0056] Furthermore, a power grid fault model is constructed based on the typhoon basic data and the power grid line operation data, including:

[0057] Calculating the total wind load per unit length of the power grid conductor based on the typhoon basic data and the conductor operation data in the power grid line operation data;

[0058] Constructing a conductor tensile strength probability model based on the total wind load on the power grid conductor and the power grid line operation data;

[0059] Constructing a probability model of the bending strength of electric poles based on the typhoon basic data and the electric pole operation data in the power grid line operation data;

[0060] The power grid fault model is obtained by connecting the conductor tensile strength probability model and the pole bending strength probability model in series.

[0061] Furthermore, the microgrid group resources are optimized and adjusted according to the grid line operation data, typhoon basic data, target exchange power, target energy storage configuration and controllable resource output, including:

[0062] Determining the importance weight of each load in the microgrid group based on the grid line operation data;

[0063] Determine the loss index of each load in the microgrid group according to the typhoon basic data and the importance weight of each load;

[0064] According to the importance weights and the loss indicators, with the goal of minimizing the supply of important loads in the microgrid group, the microgrid group resources are optimized and adjusted according to the target exchange power, target energy storage configuration and controllable resource output.

[0065] Furthermore, it also includes:

[0066] Based on the grid line operation data, the energy storage operation data, the grid operation cost, the current exchange power, and the current energy storage configuration, with the goal of minimizing the sub-microgrid scheduling cost, the sub-microgrid optimization model is solved under the sub-microgrid constraints to obtain the post-disaster mobile emergency power supply vehicle layout and line maintenance sequence;

[0067] Optimize the load in the microgrid group according to the layout of the post-disaster mobile emergency power supply vehicle;

[0068] According to the line maintenance sequence, maintenance scheduling is performed on the lines in the microgrid group.

[0069] Furthermore, the calculation of the microgrid group dispatching cost includes:

[0070] The dispatching cost of the microgrid group is calculated by adding the power generation cost of the microgrid group, the energy storage operation cost of the microgrid group, the electricity transaction cost between the microgrid group and the upper-level grid, and the electricity transaction cost between the microgrid group and the sub-microgrid.

[0071] As an improvement to the above solution, another embodiment of the present invention provides a device for optimizing and allocating resources of a microgrid group, comprising:

[0072] The power grid data acquisition module is used to obtain typhoon basic data, power grid line operation data, energy storage operation data, and power grid operation costs;

[0073] A fault model building module, configured to build a power grid fault model based on the typhoon basic data and the power grid line operation data;

[0074] A first model and constraint construction module is used to construct a microgrid group optimization model and microgrid group constraints based on the grid fault model, the grid line operation data, the energy storage operation data and the grid operation cost;

[0075] A first model solving module is configured to solve the microgrid group optimization model under the constraints of the microgrid group based on the grid line operation data, the energy storage operation data, and the grid operation cost, with the goal of minimizing the microgrid group scheduling cost, to obtain the current exchange power and the current energy storage configuration;

[0076] A second model and constraint construction module is used to construct a sub-microgrid optimization model and sub-microgrid constraints based on the grid fault model, the grid line operation data, the energy storage operation data, the grid operation cost, the current exchange power and the current energy storage configuration;

[0077] A second model solving module is configured to solve the sub-microgrid optimization model under sub-microgrid constraints based on the grid line operation data, the energy storage operation data, the grid operation cost, the current exchange power, and the current energy storage configuration, with the goal of minimizing the sub-microgrid scheduling cost, to obtain the target exchange power, target energy storage configuration, and controllable resource output; and to update the current exchange power and the current energy storage configuration respectively according to the target exchange power and the target energy storage configuration;

[0078] The microgrid group optimization module is used to optimize and adjust the microgrid group resources according to the grid line operation data, typhoon basic data, target exchange power, target energy storage configuration and controllable resource output.

[0079] Another embodiment of the present invention provides a terminal device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements a microgrid group resource optimization and allocation method as described in the above embodiment.

[0080] Another embodiment of the present invention provides a computer-readable storage medium, which includes a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute a microgrid group resource optimization and allocation method described in the above embodiment.

[0081] By implementing the present invention, at least the following beneficial effects are achieved:

[0082] The present invention provides a method, device, terminal equipment and storage medium for optimizing and allocating resources of a microgrid group, wherein the method can obtain typhoon basic data, grid line operation data, energy storage operation data and grid operation cost; construct a grid fault model based on the typhoon basic data and the grid line operation data; construct a microgrid group optimization model and microgrid group constraints based on the grid fault model, the grid line operation data, the energy storage operation data and the grid operation cost; solve the microgrid group optimization model under the microgrid group constraint with the goal of minimizing the microgrid group dispatching cost based on the grid line operation data, the energy storage operation data and the grid operation cost, and obtain the current exchange power and the current energy storage configuration; solve the microgrid group optimization model based on the grid fault model, The sub-microgrid optimization model and sub-microgrid constraints are constructed based on the grid line operation data, the energy storage operation data, the grid operation cost, the current exchange power and the current energy storage configuration; based on the grid line operation data, the energy storage operation data, the grid operation cost, the current exchange power and the current energy storage configuration, with the goal of minimizing the sub-microgrid scheduling cost, the sub-microgrid optimization model is solved under the sub-microgrid constraints to obtain the target exchange power, the target energy storage configuration and the controllable resource output; and the current exchange power and the current energy storage configuration are updated respectively according to the target exchange power and the target energy storage configuration; the microgrid group resources are optimized and adjusted based on the grid line operation data, typhoon basic data, the target exchange power, the target energy storage configuration and the controllable resource output. By constructing a grid fault model and considering the situation of microgrid group disconnection under the influence of typhoon disasters, with the goal of minimizing the dispatching cost of the microgrid group and the dispatching cost of the sub-microgrid, the constraints of the microgrid group and the sub-microgrid are integrated to solve the microgrid group optimization model and the sub-microgrid optimization model, and obtain the target exchange power, target energy storage configuration and controllable resource output. This makes the dispatch optimization of the microgrid group safer during operation, helps to deal with uncertain factors such as grid failures and energy storage changes caused by typhoons, and improves the overall security of the distribution network. BRIEF DESCRIPTION OF THE DRAWINGS

[0083] Figure 1 This is a flow chart of a method for optimizing and allocating resources of a microgrid group provided by one embodiment of the present invention;

[0084] Figure 2 This is a structural diagram of a microgrid group resource optimization and allocation device provided by one embodiment of the present invention;

[0085] Figure 3 This is a schematic diagram of total load changes in a distribution network provided by an embodiment of the present invention;

[0086] Figure 4 This is a schematic diagram of a two-layer optimization scheduling model for a microgrid group provided by an embodiment of the present invention;

[0087] Figure 5 This is a schematic diagram of a microgrid group scheduling solution process provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0088] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0089] See also Figure 1 , is a flow chart of a method for optimizing and allocating resources of a microgrid group provided by one embodiment of the present invention, comprising:

[0090] S1. Obtain typhoon basic data, power grid line operation data, energy storage operation data, and power grid operation costs;

[0091] S2. Constructing a power grid fault model based on the typhoon basic data and the power grid line operation data;

[0092] S3. Constructing a microgrid group optimization model and microgrid group constraints based on the grid fault model, the grid line operation data, the energy storage operation data, and the grid operation cost;

[0093] S4. Based on the grid line operation data, the energy storage operation data, and the grid operation cost, and with the goal of minimizing the microgrid group dispatching cost, solve the microgrid group optimization model under the microgrid group constraints to obtain the current exchange power and the current energy storage configuration;

[0094] S5. Constructing a sub-microgrid optimization model and sub-microgrid constraints based on the grid fault model, the grid line operation data, the energy storage operation data, the grid operation cost, the current exchange power, and the current energy storage configuration;

[0095] S6. Based on the grid line operation data, the energy storage operation data, the grid operation cost, the current exchange power, and the current energy storage configuration, with the goal of minimizing the sub-microgrid scheduling cost, solve the sub-microgrid optimization model under the sub-microgrid constraints to obtain the target exchange power, target energy storage configuration, and controllable resource output; and update the current exchange power and current energy storage configuration respectively according to the target exchange power and target energy storage configuration;

[0096] S7. Optimize and adjust the microgrid group resources according to the grid line operation data, typhoon basic data, target exchange power, target energy storage configuration, and controllable resource output.

[0097] Specifically, basic typhoon data includes: typhoon center pressure, typhoon center pressure difference, air density, typhoon gradient wind speed, and radius corresponding to maximum wind speed. Power grid line operation data includes conductor operation data, pole operation data, node load weight, conductor self-gravity load, conductor outer diameter, conductor density, conductor cross-sectional area, number of conductors, vertical distance between conductor and pole, pole diameter, pole height, and number of poles. Energy storage operation data includes: energy storage charging power, energy storage discharging power, diesel generator active output, diesel generator reactive output, minimum energy storage value, maximum energy storage value, maximum energy storage discharge power, maximum energy storage charging power, diesel generator power output lower limit, diesel generator power output upper limit, load node outflow power, load node inflow power, distributed energy active output, distributed energy reactive output, mobile emergency power supply active output, mobile emergency power supply reactive output, maximum capacity of mobile emergency power supply, maximum active power output of mobile emergency power supply, maximum reactive power output of mobile emergency power supply, wind turbine rated power, wind turbine output power, photovoltaic power supply rated power, radiation intensity, battery surface temperature, rated radiation temperature, load node active controllable load, load node reactive controllable load, sub-microgrid energy storage minimum value, sub-microgrid energy storage maximum value, sub-microgrid charging efficiency, sub-microgrid discharge efficiency, sub-microgrid maximum charging power, sub-microgrid maximum discharge power, and energy storage quantity. The grid operation costs include: the power generation cost of the microgrid group, the energy storage operation cost of the microgrid group, the electricity transaction cost between the microgrid group and the upper-level grid, and the electricity transaction cost between the microgrid group and the sub-microgrid.

[0098] In a preferred embodiment of the present invention, typhoon basic data, grid line operation data, energy storage operation data and grid operation cost are first obtained; then, a grid fault model is constructed based on the typhoon basic data and the grid line operation data; then, a microgrid group optimization model and a microgrid group constraint are constructed based on the grid fault model, the grid line operation data, the energy storage operation data and the grid operation cost; then, based on the grid line operation data, the energy storage operation data and the grid operation cost, with the goal of minimizing the microgrid group scheduling cost, the microgrid group optimization model is solved under the microgrid group constraint to obtain the current exchange power and the current energy storage configuration; The energy storage operation data, the grid operation cost, the current exchange power and the current energy storage configuration are used to construct a sub-microgrid optimization model and sub-microgrid constraints; then, based on the grid line operation data, the energy storage operation data, the grid operation cost, the current exchange power and the current energy storage configuration, with the goal of minimizing the sub-microgrid scheduling cost, the sub-microgrid optimization model is solved under the sub-microgrid constraints to obtain the target exchange power, the target energy storage configuration and the controllable resource output; and the current exchange power and the current energy storage configuration are updated respectively according to the target exchange power and the target energy storage configuration; finally, the microgrid group resources are optimized and adjusted according to the grid line operation data, the typhoon basic data, the target exchange power, the target energy storage configuration and the controllable resource output.

[0099] Specifically, the microgrid group constraints include: a first power balance constraint, a power exchange constraint, an energy storage constraint, and a diesel generator output constraint;

[0100] The first power balance constraint is: ;in, The microgrid group and the upper power grid in the time period The power of electric energy interaction within the For diesel in the period internal effort; Energy storage for microgrids In the period Charging power within Energy storage for microgrids In the period Discharge power within is the load at the microgrid group end; Microgrid group and sub-microgrid In the period The power of electric energy interaction within the Assemble for diesel generators; It is the collection of all energy storage in the microgrid group; is a microgrid cluster;

[0101] The power exchange constraint is: ; ;in, Microgrid group and sub-microgrid The lower limit of power exchange between Microgrid group and sub-microgrid The upper limit of power exchange between is the lower limit of power exchange between the microgrid cluster and the main grid; is the upper limit of power exchange between the microgrid cluster and the main grid;

[0102] The energy storage constraint is: ; ;

[0103] ; ; ;

[0104] in, For time t The amount of energy storage on the node; For time t Minimum energy storage at the node; For time t The maximum energy storage value at the node; is the preset time step; For charging efficiency; is the discharge efficiency; Energy storage ESS capacity; is the maximum charging power; is the maximum discharge power; is the charging state variable; is the discharge state variable;

[0105] The diesel generator output constraint is: ; ;in, For diesel generators The lower limit of power output; For diesel generators The upper limit of power output; For diesel generators The total power that can be generated by the stored fuel.

[0106] In a preferred embodiment of the present invention, is the charging state variable, which is a binary variable. If ESS When in charging state, is 0, is 1; is the discharge state variable, is a binary variable, if ESS In the discharge state, is 0, When it is 1, it indicates that the ESS cannot be in the charging and discharging states at the same time.

[0107] Specifically, the sub-microgrid constraints include: second power balance constraints, mobile emergency power supply vehicle constraints, line maintenance constraints, radial operation constraints, photovoltaic and wind power output constraints, controllable load constraints, sub-microgrid energy storage constraints, and sub-microgrid power generation constraints;

[0108] The second power balance constraint is:

[0109] ;

[0110] ; in, Power flows into the bus The branch set of Power outflow bus The branch set of is the active power flowing into or out of node i during period t; is the reactive power flowing into or out of node i during period t; Active power output of distributed energy; Provide reactive power for distributed energy; Active power output for mobile emergency power supply; Reactive power output for mobile emergency power supply; Busbar Active load removed; Busbar Reactive load removed; Energy storage for microgrids In the period Discharge power within For energy storage In the period Charging power within Provides active power for the diesel generators of the microgrid; Provide reactive power for the diesel generators of the microgrid; For nodes Active load; For nodes Reactive load; is the power value of the starting node 1 of the sub-microgrid; It is represented by the exchange power provided by the microgrid group to a certain sub-microgrid during the period t;

[0111] The mobile emergency power supply vehicle is constrained as follows: ; ; ; ; ; ; ;in, A mobile emergency power supply vehicle in the current area; mustering for emergency vehicles; To confirm candidate link nodes Whether to use a mobile emergency power supply vehicle connected variables; The total number of mobile emergency response units in the current region; is the connection state variable between the mobile emergency power supply vehicle and the candidate node; for Active power output of the node mobile emergency power supply vehicle; For the The maximum capacity of a mobile emergency power supply vehicle; The maximum active power output of the mobile emergency power supply MEG; It is the maximum reactive power output of the mobile emergency power supply MEG;

[0112] The line maintenance constraints are: ; ;in, The maximum number of lines that can be repaired in the same period of time; For maintenance The time taken for each route; For the line exist On / off status within the time period;

[0113] The radial operation constraints are: ; ; ; ; ; ;in, For the current by the branch Flow to branch State variables at time ; For the current by the branch Flow to branch State variables at time ; For the period Inner branch road The state variable of the fault; It is the set of root buses directly connected to the power plant; is the set of root buses directly connected to the DG; It is the set of root buses directly connected to the MEG; For the period Internal busbar There are state variables with power exchange at ; is an infinite value; For the period Inner branch road Active power; For the period Inner branch road Reactive power;

[0114] The photovoltaic and wind power output constraints are:

[0115] ; ;in, is the fan output power; is the rated power of the fan; is the cut-in wind speed; is the rated wind speed; To cut out wind speed; is the actual wind speed of the fan; The output power of the photovoltaic power source; is the rated power; is the radiation intensity at the working point; is the battery surface temperature; is the rated temperature; is the rated radiation intensity; is the power temperature coefficient;

[0116] The controllable load constraint is: ;in, For nodes Active controllable load; For nodes Reactive controllable load;

[0117] The sub-microgrid energy storage constraints are: ; ; ; ; ;

[0118] in, For time t The size of the sub-microgrid energy storage at the node; For time t Minimum energy storage value of the sub-microgrid at the node; For time t The maximum energy storage capacity of the sub-microgrid at the node; Charging efficiency for sub-microgrids; is the discharge efficiency of the sub-microgrid; ESS capacity; The maximum charging power of the sub-microgrid; is the maximum discharge power of the sub-microgrid; is the charging state variable; is the discharge state variable;

[0119] The sub-microgrid power generation constraints are: ; ;in, For diesel generators The lower limit of power output; For diesel generators The upper limit of power output; Diesel generator for microgrid The total power that can be generated by the stored fuel.

[0120] In a preferred embodiment of the present invention, the diesel generator constraints and energy storage constraints in the sub-microgrid and microgrid cluster are the same, and the scope of consideration is within the sub-microgrid area. The second power balance constraint is the active and reactive power balance constraint, that is, the amount of power flowing into each bus is equal to the amount flowing out. At the same time, it also includes the transmission capacity limits of the line active and reactive power: ;in, and Branch resistance and reactance; is the system reference voltage; and Respectively represent the voltage values ​​on nodes j and i during period t; and They are respectively represented as the active and reactive power transmitted on line ij during period t; Indicates the on / off state of line ij during period t;

[0121] The range of node voltage is limited: ;in, and are the minimum and maximum values ​​of the node voltage, respectively.

[0122] For each power supply station in a region, the number and types of mobile emergency power supply vehicles that can be provided must not exceed the total number and types of mobile emergency power supply vehicles available in the region. In order to ensure that each mobile emergency power supply vehicle can be effectively assigned to the most suitable candidate connection node, we need to consider the mobile emergency power supply vehicle constraints when scheduling these mobile emergency power supply vehicles. When the candidate connection point is connected to the mobile emergency power supply vehicle: ; ;

[0123] The number of MEGs connected to the candidate connection node is less than the total number of mobile emergency units in the area, and each MEG can only be assigned to the candidate connection node once and cannot be assigned repeatedly: ; ;

[0124] No. A car in During the period The energy consumed by the node should be less than or equal to the maximum capacity of the mobile emergency power supply vehicle: ; ; .

[0125] When the fault persists, only repairs can be made within the same period of time. The line maintenance constraints for the on-off state of the model fault are as follows: ; ;Every Time-consuming repairs Lines: Where, For online exist The on-off status within the time period, when When it is 0, the line In disconnected state, when When it is 1, the line In connected state.

[0126] The distribution network is usually a closed-loop design with open-loop operation. When a fault occurs, the load in the power-off area can be restored through dynamic reconstruction of the distribution network and DG scheduling. Regardless of the direction of power flow, the distribution network can ensure the operation of the radial structure. , It is a binary variable, indicating the branch status. Flow to branch hour, is 1, otherwise it is 0; similarly, the flow is from the branch Flow to branch hour is 1 if the value is set, otherwise it is 0. For the period Inner branch road The state variable of the fault occurs, if the period Inner branch road If a fault occurs is 0, otherwise it is 1. To indicate that the distribution network is a radial network, and each sub-busbar cannot be connected to multiple parent lines at the same time, For the period Internal busbar There is a state variable of power exchange at the time Internal busbar There is power exchange at the busbar The load is energized, is 1, otherwise it is 0, because the current can only flow out from the busbar and cannot flow in the reverse direction, so when hour, is zero; strengthen the constraint on branch flow, indicating that when There is no current flow between directly connected buses, that is, branch state , When both are 0, and Also 0, application The method decouples two unconnected buses. The relationship between the output power of the wind turbine and the wind speed in the photovoltaic wind power output constraint can be approximately represented by a piecewise function. In this embodiment, the real-time wind speed is the average wind speed of the current time period at the beginning of each time period. This embodiment approximately assumes that the output of the photovoltaic power source is only related to the light intensity and ambient temperature. , is a binary variable, representing the charge and discharge status respectively. If ESS When in charging state, is 0, is 1; if ESS In the discharge state, is 0, When it is 1, it indicates that the ESS cannot be in the charging and discharging states at the same time.

[0127] Preferably, a power grid fault model is constructed based on the typhoon basic data and the power grid line operation data, including: calculating the total wind load of the power grid conductor per unit length based on the typhoon basic data and the conductor operation data in the power grid line operation data; constructing a conductor tensile strength probability model based on the total wind load of the power grid conductor and the power grid line operation data; constructing a pole bending strength probability model based on the typhoon basic data and the pole operation data in the power grid line operation data; and obtaining a power grid fault model by connecting the conductor tensile strength probability model and the pole bending strength probability model in series.

[0128] In a preferred embodiment of the present invention, the structure of a typhoon includes a typhoon eye, a vortex storm area, and a surrounding strong wind area. According to the Holland model of the gradient wind balance equation, as the typhoon disaster occurs, the number of typhoon duration periods is set to , then the relevant data during the typhoon disaster are: ; ; Where: Distance from the center of the typhoon Gradient wind speed at is the radius corresponding to the maximum wind speed; is the Holland radial pressure distribution parameter; It is the Coriolis parameter related to the Earth's rotational angular velocity and the latitude of the typhoon's center; and are the pressure and pressure difference at the typhoon center respectively; is the air density.

[0129] The total wind load per unit length of the power grid conductor consists of:

[0130] Where: is the actual force on the conductor; is the horizontal wind load; is the gravity load of the conductor itself; is the outer diameter of the wire; is the wind pressure unevenness coefficient; is the wind pressure height variation coefficient; is the angle between the conductor and the wind direction; is the linear density of the conductor; is the acceleration due to gravity.

[0131] The conductor tensile strength probability model analyzes the stress on the conductor cross section at the highest hanging point to determine whether a wire breakage fault will occur. If the stress on the conductor cross section at the highest hanging point is greater than a certain value of the conductor's own tensile strength, it is determined that the conductor has broken. The stress on the conductor cross section at the highest hanging point is: Where: is the cross-sectional area of ​​the reinforced aluminum stranded wire, is the tension at the lowest point of the sag, It is the horizontal distance between the highest suspension point of the conductor and the lowest point of the sag.

[0132] The probability model of the bending strength of the pole can determine whether the pole will fail by analyzing the bending moment generated by the typhoon on the root section of the pole. When the bending moment generated by the typhoon on the root section of the pole is greater than a certain value of the bending strength of the pole itself, it can be determined that the pole has collapsed. It consists of two vector sums, which are the bending moment caused by the horizontal wind load acting on the conductor on the root of the pole and The bending moment generated at the pole root by the wind load on the pole itself , and the calculation formulas are: ; ; Where: For the pole Horizontal wind load on suspended conductors; is the average spacing between conductors; For the The vertical distance between the conductor and the bottom of the pole; is the total number of wires hanging on the pole; is the body shape coefficient; is the pole diameter; is the pole diameter at the base of the pole; is the height of the pole; It is the force arm from the resultant point of wind pressure on the pole to the pole root.

[0133] By simulating the change of wind speed and stress on the components, Time distribution line The distance from the center to the typhoon center is Then: When At this moment, the typhoon is affecting the route The impact is small and there is no risk of failure; when At this moment, the typhoon is affecting the route The impact is large and there is a risk of failure.

[0134] The typhoon disaster intensity can be calculated as When the failure rates of conductors and poles are and :

[0135] Where: and are the mean and standard deviation of the tensile strength of the wire; and are the mean and standard deviation of the bending strength of the poles, respectively. A branch can only operate normally if all conductors and poles between two nodes are in a reliable state. Therefore, the branch failure rate model is a series model of the conductor failure rate and the pole failure rate, as shown in the following formula: Where: For the The branch road is under typhoon intensity Failure rate when and Respectively The number of conductors and poles for each branch line.

[0136] In another preferred embodiment of the present invention, the time-varying wind speed model of the typhoon passing process is combined with the line failure rate model, and the wind speed is used as the intermediate quantity to transmit the correlation relationship to obtain the time-varying failure rate curve of each line. Moment, for the A random number uniformly distributed between [0, 1] is generated for each distribution line , and the line failure rate at this moment In comparison, there are: Where: Indicates the Distribution lines in The operating status at the moment, 0 means failure, 1 means normal operation.

[0137] During a typhoon's passage, the above sampling process is repeated for all lines within the distribution network to identify faulty lines and the corresponding fault occurrence times, generating a distribution network fault scenario. Ultimately, a set of fault scenarios is generated through Monte Carlo simulation. Generating a distribution network fault scenario based on the grid fault model facilitates the subsequent construction of microgrid cluster optimization models and sub-microgrid optimization models.

[0138] Specifically, the resources of the microgrid group are optimized and adjusted according to the grid line operation data, typhoon basic data, target exchange power, target energy storage configuration and controllable resource output, including: determining the importance weight of each load in the microgrid group according to the grid line operation data; determining the loss index of each load in the microgrid group according to the typhoon basic data and the importance weight of each load; based on the importance weight and the loss index, with the goal of minimizing the supply of important loads in the microgrid group, optimizing and adjusting the resources of the microgrid group according to the target exchange power, target energy storage configuration and controllable resource output.

[0139] In a preferred embodiment of the present invention, the typhoon meteorological factors are divided into 6 intervals, and the specific segmentation method is shown in Table 1:

[0140] Table 1

[0141]

[0142] According to the load importance weight ( 、 、 5 levels each) and load capacity A sensitivity analysis was conducted under different typhoon meteorological factors, and various load loss indicators were established, namely: ; Where: For the The capacity of the load, Indicates the sensitivity factor value of typhoon to load, Indicates the weight of the influencing factors (divided into 6 levels), is the segment interval of the influencing factors. Whenever the meteorological factors in the area Change one unit, load Corresponding changes Multiple units. 、 、 For the The life safety, economy and special weight values ​​of each load; It is the sensitive load affected by typhoon factors; For the The loss caused by power outage of each load; Due to the severity of life safety loss, the life safety weight is multiplied by the coefficient .

[0143] Specifically, the calculation of the microgrid group dispatching cost includes: adding the microgrid group power generation cost, the microgrid group energy storage operation cost, the power transaction cost between the microgrid group and the upper grid, and the power transaction cost between the microgrid group and the sub-microgrid in the grid operation cost to calculate the microgrid group dispatching cost.

[0144] In a preferred embodiment of the present invention, after a microgrid group is disconnected from the grid due to a fault, the controllable output is optimized and dispatched through scheduling between microgrid groups, and power interaction is carried out with its sub-microgrid units to minimize the operating cost of the microgrid group during the fault. The load supply status of the microgrid group at each moment is calculated in sequence according to the fault development sequence to obtain its operating cost during the entire typhoon impact process. The formula is as follows: ; ; ; ; Where: The total power generation cost within the microgrid group, including diesel power generation, photovoltaic power generation and wind power generation costs; The operating cost of all energy storage in the microgrid group; The cost of electricity transaction between the microgrid group and the upper power grid; Microgrid group and sub-microgrid The cost of electricity transactions between The time from the occurrence of a fault to normal operation in the microgrid group, For a period of time; Assemble for diesel generators; 、 、 are the cost coefficients of diesel power generation, photovoltaic power generation, and wind power generation respectively; 、 、 Diesel, photovoltaic, and wind power in the time period The output size inside; It is the collection of all energy storage in the microgrid group; Energy storage maintenance cost coefficient; 、 Energy storage In the period The charge and discharge power within the device; 、 The microgrid group and the upper grid and the microgrid group and the sub-microgrid in the time period Internal electricity transaction cost coefficient; 、 The microgrid group and the upper grid and the microgrid group and the sub-microgrid in the time period Internal electrical energy interaction power.

[0145] In another preferred embodiment of the present invention, the sub-microgrid takes into account the location and time of line faults caused by typhoons, and takes into account the role of local photovoltaic, wind power, energy storage, mobile emergency power supply vehicles and other flexible resources to ensure the minimum supply of important loads and minimize the sub-microgrid scheduling cost. The load supply situation of the sub-microgrid at each moment is calculated in sequence according to the fault development sequence to obtain its operating cost during the entire typhoon impact process. The formula is as follows: ; ; Where: For sub-microgrids All power generation costs within the company, including diesel, photovoltaic and wind power generation costs; For sub-microgrids All energy storage operating costs within the 、 The calculation formula of the microgrid group 、 The method is the same, but the scope becomes the sub-microgrid; For sub-microgrids Internal load loss costs; is the set of all nodes in the distribution network; represent Nodes within a time period The load shedding size is the proportion of the load at this point in the period; For nodes The weight corresponding to the load level; is a node exist The load size during the time period; For sub-microgrids Maintenance costs of mobile emergency power supply vehicles; Gather all mobile emergency power supply vehicles in the sub-microgrid; Maintaining cost coefficient for mobile emergency power supply vehicle; Mobile emergency power supply vehicle Capacity size.

[0146] When the power system faces the impact of extreme disasters, a large number of its components fail, causing large-scale power outages. Figure 3As shown, Point is the disaster occurrence point, and They represent the start and end time of the power system derating operation respectively. The first stage is the power system recovery stage. After that, the power system resumes normal operation. For typhoon fault scenarios, according to the corresponding fault line location, fault time and recovery time, considering the role of flexible resources such as photovoltaic, wind power, energy storage, mobile emergency power supply vehicles in the microgrid group and sub-microgrids and the power transactions between sub-microgrids or between microgrid groups and sub-microgrids, the minimum supply of important loads is guaranteed, and the operating cost of the microgrid group and its sub-microgrids is minimized. The two-layer dispatch model of the microgrid group is as follows: Figure 4 shown.

[0147] In a preferred embodiment of the present invention, the Particle Swarm Optimization (PSO) is an optimization algorithm based on the concept of swarm intelligence. It was proposed by British scientists Eberhart and Kennedy in 1995 as a simulation algorithm for simulating the behavior of a large number of particles in a search space for birds or other biological groups. YALMIP is a free optimization solution tool developed by LOFBERG. Its biggest feature is the integration of many external optimization solvers (including CPLEX) to form a unified modeling and solution language. It provides a Matlab calling API to reduce the learning cost of learners. Under the requirements of different optimization objectives at the upper and lower levels, the minimum supply of important loads is guaranteed as a prerequisite, and the scheduling cost of microgrid groups and sub-microgrids throughout the disaster process is minimized as much as possible. The flowchart of the flexible resource emergency optimization scheduling considering the importance of loads in the microgrid group in the off-grid area under specific typhoon weather is as follows. Figure 5 As shown. When the particle swarm algorithm is solving a target, the global optimal solution of a single target can be selected by sorting with a simple particle fitness function. However, the global optimal solution of multiple targets is a set of Pareto solutions that do not dominate each other after each iteration. Therefore, it is necessary to connect these Pareto solutions and select the best one. This embodiment adopts the dynamic dense distance method. After each iterative solution, the non-inferior solution set is updated, and then the dense distance is used to select the best one. Sort the solution, remove the solution with the smallest dense distance, and then select any group in the top 10% of the dense distance as the global optimal solution set under the multi-objective function. The specific formula is as follows: Where: 、 It's distance The two closest particles; For particles No. objective function; For all particles The maximum value of the objective function.

[0148] Schematically, it also includes: based on the grid line operation data, the energy storage operation data, the grid operation cost, the current exchange power and the current energy storage configuration, with the goal of minimizing the sub-microgrid scheduling cost, solving the sub-microgrid optimization model under the sub-microgrid constraints to obtain the post-disaster mobile emergency power supply vehicle layout and line maintenance sequence; according to the post-disaster mobile emergency power supply vehicle layout, optimizing the load in the microgrid group; according to the line maintenance sequence, performing maintenance scheduling on the lines in the microgrid group.

[0149] By implementing this embodiment, typhoon basic data, grid line operation data, energy storage operation data and grid operation cost are obtained; a grid fault model is constructed based on the typhoon basic data and the grid line operation data; a microgrid group optimization model and microgrid group constraints are constructed based on the grid fault model, the grid line operation data, the energy storage operation data and the grid operation cost; based on the grid line operation data, the energy storage operation data and the grid operation cost, the microgrid group optimization model is solved under the microgrid group constraints with the goal of minimizing the microgrid group scheduling cost, and the current exchange power and the current energy storage configuration are obtained; based on the grid fault model, the grid line operation data, the energy storage operation data and the grid operation cost, the microgrid group optimization model is solved under the microgrid group constraints, and the current exchange power and the current energy storage configuration are obtained. The sub-microgrid optimization model and sub-microgrid constraints are constructed based on the power grid line operation data, the energy storage operation data, the power grid operation cost, the current exchange power and the current energy storage configuration; based on the power grid line operation data, the energy storage operation data, the power grid operation cost, the current exchange power and the current energy storage configuration, with the goal of minimizing the sub-microgrid scheduling cost, the sub-microgrid optimization model is solved under the sub-microgrid constraints to obtain the target exchange power, the target energy storage configuration and the controllable resource output; and the current exchange power and the current energy storage configuration are updated respectively according to the target exchange power and the target energy storage configuration; the microgrid group resources are optimized and adjusted according to the power grid line operation data, the typhoon basic data, the target exchange power, the target energy storage configuration and the controllable resource output. By constructing a grid fault model and considering the situation of microgrid group disconnection under the influence of typhoon disasters, with the goal of minimizing the dispatching cost of the microgrid group and the dispatching cost of the sub-microgrid, the constraints of the microgrid group and the sub-microgrid are integrated to solve the microgrid group optimization model and the sub-microgrid optimization model, and obtain the target exchange power, target energy storage configuration and controllable resource output. This makes the dispatch optimization of the microgrid group safer during operation, helps to deal with uncertain factors such as grid failures and energy storage changes caused by typhoons, and improves the overall security of the distribution network.

[0150] See also Figure 2 , is a schematic structural diagram of a microgrid group resource optimization and allocation device provided by one embodiment of the present invention, comprising:

[0151] The power grid data acquisition module is used to obtain typhoon basic data, power grid line operation data, energy storage operation data, and power grid operation costs;

[0152] A fault model building module, configured to build a power grid fault model based on the typhoon basic data and the power grid line operation data;

[0153] A first model and constraint construction module is used to construct a microgrid group optimization model and microgrid group constraints based on the grid fault model, the grid line operation data, the energy storage operation data and the grid operation cost;

[0154] A first model solving module is configured to solve the microgrid group optimization model under the constraints of the microgrid group based on the grid line operation data, the energy storage operation data, and the grid operation cost, with the goal of minimizing the microgrid group scheduling cost, to obtain the current exchange power and the current energy storage configuration;

[0155] A second model and constraint construction module is used to construct a sub-microgrid optimization model and sub-microgrid constraints based on the grid fault model, the grid line operation data, the energy storage operation data, the grid operation cost, the current exchange power and the current energy storage configuration;

[0156] A second model solving module is configured to solve the sub-microgrid optimization model under sub-microgrid constraints based on the grid line operation data, the energy storage operation data, the grid operation cost, the current exchange power, and the current energy storage configuration, with the goal of minimizing the sub-microgrid scheduling cost, to obtain the target exchange power, target energy storage configuration, and controllable resource output; and to update the current exchange power and the current energy storage configuration respectively according to the target exchange power and the target energy storage configuration;

[0157] The microgrid group optimization module is used to optimize and adjust the microgrid group resources according to the grid line operation data, typhoon basic data, target exchange power, target energy storage configuration and controllable resource output.

[0158] The present invention provides a device for optimizing and allocating resources of a microgrid group. By constructing a grid fault model and considering the situation where the microgrid group is disconnected from the grid under the influence of typhoon disasters, the device takes minimizing the dispatching cost of the microgrid group and the dispatching cost of the sub-microgrid as the goal, comprehensively considers the constraints of the microgrid group and the sub-microgrid, solves the microgrid group optimization model and the sub-microgrid optimization model, and obtains the target exchange power, target energy storage configuration and controllable resource output. This makes the dispatching optimization of the microgrid group safer during operation, helps to deal with uncertain factors such as grid failures and energy storage changes caused by typhoons, and improves the overall safety of the distribution network.

[0159] It should be noted that the device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed across multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present embodiment. In addition, in the drawings of the device embodiments provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, which may be specifically implemented as one or more communication buses or signal lines. A person of ordinary skill in the art can understand and implement the present invention without inventive effort.

[0160] Those skilled in the art can clearly understand that, for the sake of convenience and brevity, the specific working process of the device described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0161] Another embodiment of the present invention further provides a terminal device comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the microgrid resource optimization and allocation method described in the above embodiment. The terminal device can be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The terminal device can include, but is not limited to, a processor and a memory.

[0162] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the terminal device, connecting various parts of the entire terminal device using various interfaces and lines.

[0163] The memory can be used to store the computer program. The processor implements the various functions of the terminal device by running or executing the computer program stored in the memory and accessing the data stored in the memory. The memory may primarily include a program storage area and a data storage area. The program storage area may store an operating system, at least one application required for a function, and the data storage area may store data generated based on the use of the mobile phone. Furthermore, the memory may include high-speed random access memory and non-volatile memory, such as a hard disk, internal memory, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, at least one disk storage device, a flash memory device, or other volatile solid-state storage device.

[0164] Another embodiment of the present invention provides a computer-readable storage medium, which includes a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute a microgrid group resource optimization and allocation method described in the above embodiment.

[0165] The storage medium is a computer-readable storage medium, and the computer program is stored in the computer-readable storage medium. When the computer program is executed by the processor, it can implement the steps of each of the above-mentioned method embodiments. The computer program includes computer program code, which can be in source code form, object code form, executable file, or some intermediate form. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium.

[0166] The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A method for optimizing and allocating resources of a microgrid group, characterized in that: include: Obtain basic typhoon data, power grid line operation data, energy storage operation data, and power grid operation costs; Constructing a power grid fault model based on the typhoon basic data and the power grid line operation data; Constructing a microgrid group optimization model and microgrid group constraints based on the grid fault model, the grid line operation data, the energy storage operation data, and the grid operation cost; According to the grid line operation data, the energy storage operation data and the grid operation cost, with the goal of minimizing the microgrid group dispatching cost, the microgrid group optimization model is solved under the constraints of the microgrid group to obtain the current exchange power and the current energy storage configuration; Constructing a sub-microgrid optimization model and sub-microgrid constraints based on the grid fault model, the grid line operation data, the energy storage operation data, the grid operation cost, the current exchange power, and the current energy storage configuration; Based on the grid line operation data, the energy storage operation data, the grid operation cost, the current exchange power, and the current energy storage configuration, with the goal of minimizing the sub-microgrid scheduling cost, the sub-microgrid optimization model is solved under the sub-microgrid constraints to obtain the target exchange power, target energy storage configuration, and controllable resource output; and the current exchange power and current energy storage configuration are updated respectively according to the target exchange power and target energy storage configuration; Optimize and adjust the microgrid group resources based on the grid line operation data, typhoon basic data, target exchange power, target energy storage configuration, and controllable resource output; The step of constructing a power grid fault model based on the typhoon basic data and the power grid line operation data includes: Calculating the total wind load per unit length of the power grid conductor based on the typhoon basic data and the conductor operation data in the power grid line operation data; Constructing a conductor tensile strength probability model based on the total wind load on the power grid conductor and the power grid line operation data; Constructing a probability model of the bending strength of electric poles based on the typhoon basic data and the electric pole operation data in the power grid line operation data; The power grid fault model is obtained by connecting the conductor tensile strength probability model and the pole bending strength probability model in series.

2. A microgrid group resource optimization and allocation method according to claim 1, characterized in that: The microgrid group constraints include: a first power balance constraint, a power exchange constraint, an energy storage constraint, and a diesel generator output constraint; The first power balance constraint is: in, The microgrid group and the upper power grid in the time period The power of electric energy interaction within the For diesel in the period internal effort; Energy storage for microgrids In the period Charging power within Energy storage for microgrids In the period Discharge power within is the load at the microgrid group end; Microgrid group and sub-microgrid In the period The power of electric energy interaction within the Assemble for diesel generators; It is the collection of all energy storage in the microgrid group; is a microgrid cluster; The power exchange constraint is: in, Microgrid group and sub-microgrid The lower limit of power exchange between Microgrid group and sub-microgrid The upper limit of power exchange between is the lower limit of power exchange between the microgrid cluster and the main grid; is the upper limit of power exchange between the microgrid cluster and the main grid; The energy storage constraint is: in, For time t The amount of energy storage on the node; For time t Minimum energy storage at the node; For time t The maximum energy storage value at the node; is the preset time step; For charging efficiency; is the discharge efficiency; Energy storage ESS capacity; is the maximum charging power; is the maximum discharge power; is the charging state variable; is the discharge state variable; The diesel generator output constraint is: in, For diesel generators The lower limit of power output; For diesel generators The upper limit of power output; For diesel generators The total power that can be generated by the stored fuel.

3. A microgrid group resource optimization and allocation method according to claim 1, characterized in that: The sub-microgrid constraints include: second power balance constraints, mobile emergency power supply vehicle constraints, line maintenance constraints, radial operation constraints, photovoltaic and wind power output constraints, controllable load constraints, sub-microgrid energy storage constraints, and sub-microgrid power generation constraints; The second power balance constraint is: in, Power flows into the bus The branch set of Power outflow bus The branch set of is the active power flowing into or out of node i during period t; is the reactive power flowing into or out of node i during period t; Active power output of distributed energy; Provide reactive power for distributed energy; Active power output for mobile emergency power supply; Reactive power output for mobile emergency power supply; Busbar Active load removed; Busbar Reactive load removed; Energy storage for microgrids In the period Discharge power within For energy storage In the period Charging power within Provides active power for the diesel generators of the microgrid; Provide reactive power for the diesel generators of the microgrid; For nodes Active load; For nodes Reactive load; is the power value of the starting node 1 of the sub-microgrid; It is represented by the exchange power provided by the microgrid group to a certain sub-microgrid during the period t; The mobile emergency power supply vehicle is constrained as follows: in, A mobile emergency power supply vehicle in the current area; mustering for emergency vehicles; To confirm candidate link nodes Whether to use a mobile emergency power supply vehicle connected variables; The total number of mobile emergency response units in the current region; is the connection state variable between the mobile emergency power supply vehicle and the candidate node; for Active power output of the node mobile emergency power supply vehicle; For the The maximum capacity of a mobile emergency power supply vehicle; The maximum active power output of the mobile emergency power supply MEG; It is the maximum reactive power output of the mobile emergency power supply MEG; The line maintenance constraints are: in, The maximum number of lines that can be repaired in the same period of time; For maintenance The time taken for each route; For the line exist On / off status within the time period; The radial operation constraints are: in, For the current by the branch Flow to branch State variables at time ; For the current by the branch Flow to branch State variables at time ; For the period Inner branch road The state variable of the fault; It is the set of root buses directly connected to the power plant; is the set of root buses directly connected to the DG; It is the set of root buses directly connected to the MEG; For the period Internal busbar There are state variables with power exchange at ; is an infinite value; For the period Inner branch road Active power; For the period Inner branch road Reactive power; The photovoltaic and wind power output constraints are: in, is the fan output power; is the rated power of the fan; is the cut-in wind speed; is the rated wind speed; To cut out wind speed; is the actual wind speed of the fan; The output power of the photovoltaic power source; is the rated power; is the radiation intensity at the working point; is the battery surface temperature; is the rated temperature; is the rated radiation intensity; is the power temperature coefficient; The controllable load constraint is: in, For nodes Active controllable load; For nodes Reactive controllable load; The sub-microgrid energy storage constraints are: in, For time t The size of the sub-microgrid energy storage at the node; For time t Minimum energy storage value of the sub-microgrid at the node; For time t The maximum energy storage capacity of the sub-microgrid at the node; Charging efficiency for sub-microgrids; is the discharge efficiency of the sub-microgrid; ESS capacity; The maximum charging power of the sub-microgrid; is the maximum discharge power of the sub-microgrid; is the charging state variable; is the discharge state variable; The sub-microgrid power generation constraints are: in, For diesel generators The lower limit of power output; For diesel generators The upper limit of power output; Diesel generator for microgrid The total power that can be generated by the stored fuel.

4. A microgrid group resource optimization and allocation method according to claim 1, characterized in that: Optimize and adjust the microgrid group resources based on the grid line operation data, typhoon basic data, target exchange power, target energy storage configuration, and controllable resource output, including: Determining the importance weight of each load in the microgrid group based on the grid line operation data; Determine the loss index of each load in the microgrid group according to the typhoon basic data and the importance weight of each load; According to the importance weights and the loss indicators, with the goal of minimizing the supply of important loads in the microgrid group, the microgrid group resources are optimized and adjusted according to the target exchange power, target energy storage configuration and controllable resource output.

5. The method for optimizing and allocating resources of a microgrid group according to claim 1, wherein: Also includes: Based on the grid line operation data, the energy storage operation data, the grid operation cost, the current exchange power, and the current energy storage configuration, with the goal of minimizing the sub-microgrid scheduling cost, the sub-microgrid optimization model is solved under the sub-microgrid constraints to obtain the post-disaster mobile emergency power supply vehicle layout and line maintenance sequence; Optimize the load in the microgrid group according to the layout of the post-disaster mobile emergency power supply vehicle; According to the line maintenance sequence, maintenance scheduling is performed on the lines in the microgrid group.

6. A microgrid group resource optimization and allocation method according to claim 1, characterized in that: The calculation of the microgrid group dispatching cost includes: The dispatching cost of the microgrid group is calculated by adding the power generation cost of the microgrid group, the energy storage operation cost of the microgrid group, the electricity transaction cost between the microgrid group and the upper-level grid, and the electricity transaction cost between the microgrid group and the sub-microgrid.

7. A device for optimizing and allocating resources of a microgrid group, characterized in that: include: The power grid data acquisition module is used to obtain typhoon basic data, power grid line operation data, energy storage operation data, and power grid operation costs; A fault model building module, configured to build a power grid fault model based on the typhoon basic data and the power grid line operation data; A first model and constraint construction module is used to construct a microgrid group optimization model and microgrid group constraints based on the grid fault model, the grid line operation data, the energy storage operation data and the grid operation cost; A first model solving module is configured to solve the microgrid group optimization model under the constraints of the microgrid group based on the grid line operation data, the energy storage operation data, and the grid operation cost, with the goal of minimizing the microgrid group scheduling cost, to obtain the current exchange power and the current energy storage configuration; A second model and constraint construction module is used to construct a sub-microgrid optimization model and sub-microgrid constraints based on the grid fault model, the grid line operation data, the energy storage operation data, the grid operation cost, the current exchange power and the current energy storage configuration; A second model solving module is configured to solve the sub-microgrid optimization model under sub-microgrid constraints based on the grid line operation data, the energy storage operation data, the grid operation cost, the current exchange power, and the current energy storage configuration, with the goal of minimizing the sub-microgrid scheduling cost, to obtain the target exchange power, target energy storage configuration, and controllable resource output; and to update the current exchange power and the current energy storage configuration respectively according to the target exchange power and the target energy storage configuration; A microgrid group optimization module is used to optimize and adjust microgrid group resources based on the grid line operation data, typhoon basic data, target exchange power, target energy storage configuration, and controllable resource output; The fault model building module is used to build a power grid fault model based on the typhoon basic data and the power grid line operation data, including: Calculating the total wind load per unit length of the power grid conductor based on the typhoon basic data and the conductor operation data in the power grid line operation data; Constructing a conductor tensile strength probability model based on the total wind load on the power grid conductor and the power grid line operation data; Constructing a probability model of the bending strength of electric poles based on the typhoon basic data and the electric pole operation data in the power grid line operation data; The power grid fault model is obtained by connecting the conductor tensile strength probability model and the pole bending strength probability model in series.

8. A terminal device, characterized in that: The method comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, a microgrid group resource optimization and allocation method according to any one of claims 1 to 6 is implemented.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium includes a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute a microgrid group resource optimization and allocation method according to any one of claims 1 to 6.

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