A multi-resource collaborative phase fault self-healing method across voltage levels

Abstract

This invention discloses a multi-resource collaborative phase-by-phase fault self-healing method across voltage levels, belonging to the field of power grid fault self-healing. The invention includes: constructing a power supply and load information database covering the entire power grid based on the power grid's overall structure; wherein the power grid's overall structure includes faulty networks and fault-free networks across voltage levels, with the three phases of the faulty and fault-free networks connected via phase-by-phase converters; evaluating each outage node in the faulty network based on the power supply and load information database, determining the fault self-healing strategy for the current outage node; establishing an optimization model for the phase-by-phase converter switching matrix; solving the optimization model for the phase-by-phase converter switching matrix, and outputting the optimal switching matrix for the phase-by-phase converter. This invention achieves phase-by-phase power mutual assistance across voltage levels, while reducing energy waste caused by wind and solar curtailment, and improving the economic efficiency of power grid operation.

Description

Technical Field

[0001] This invention relates to a multi-resource collaborative phase fault self-healing method across voltage levels, belonging to the field of power grid fault self-healing. Background Technology

[0002] When a power grid fails, if it is not handled promptly and effectively, the fault can easily expand, causing localized or even widespread power outages. This not only results in economic losses but also seriously disrupts normal social order and public life. Therefore, achieving rapid and accurate fault self-healing to minimize power outage time and restore power supply has become an indispensable core function.

[0003] Currently, the commonly used fault self-healing method is mainly based on the "three-phase integrated power transfer" strategy. This strategy treats the three-phase lines as a whole for power dispatch and load transfer. However, this operating mode has increasingly prominent limitations when facing distributed energy sources with high penetration and uneven distribution. First, this strategy is difficult to respond to the actual differences between the output of distributed power sources and load demand in each phase of the line, and cannot achieve fine-grained phase-by-phase power regulation. As a result, a large amount of surplus distributed power is wasted during the fault recovery process because it cannot be consumed locally, and the curtailment rate of wind and solar power remains high. Second, the three-phase integrated power transfer is prone to causing serious voltage imbalance and inter-phase power imbalance, which directly affects power quality and equipment safety. In addition, this strategy lacks flexibility, with limited available integrated power transfer paths, which prolongs the power outage time for users.

[0004] In view of this, the present invention is hereby proposed. Summary of the Invention

[0005] This invention provides a multi-resource collaborative phase fault self-healing method across voltage levels. On the one hand, it constructs a local load demand judgment criterion to determine the fault self-healing strategy of the node in the current power outage area. On the other hand, based on the determined fault self-healing strategy of the node in the current power outage area, it establishes an optimization model of the phase converter switching matrix for solution, so as to achieve phase power mutual assistance across voltage levels, reduce the energy waste caused by wind and solar curtailment, and improve the economic efficiency of grid operation.

[0006] The technical solution of this invention is:

[0007] A multi-resource collaborative phase fault self-healing method across voltage levels includes:

[0008] S101, based on the power grid's overall network structure, constructs a database of power source and load information covering the entire power grid; the power grid's overall network structure includes fault networks and fault-free networks across voltage levels, and the three phases of the fault networks and fault-free networks are connected through phase-separated converters;

[0009] S102, Based on the power supply and load information database covering the entire power grid, evaluate the nodes of each power outage area in the fault network and determine the fault self-healing strategy of the current power outage area node.

[0010] S103, Establish an optimization model for the phase-split converter switching matrix; the optimization model for the phase-split converter switching matrix includes the objective function and constraints.

[0011] S104, solve the optimization model of the phase converter switching matrix, and output the optimal switching matrix of the phase converter.

[0012] Further, S102 includes: obtaining the total active load, total reactive load, maximum reactive power support capacity, and the sum of the maximum active power output of all distributed energy sources and energy storage devices in each power outage area node of each fault network based on a power supply and load information database covering the entire power grid; constructing a local load demand judgment criterion based on the total active load, total reactive load, maximum reactive power support capacity, and the sum of the maximum active power output of all distributed energy sources and energy storage devices; and determining the fault self-healing strategy of the current power outage area node based on the local load demand judgment criterion.

[0013] Furthermore, the criteria for determining local load demand based on total active load, total reactive load, maximum reactive power support capacity, and the sum of the maximum active power output of all distributed energy sources and energy storage devices are as follows:

[0014] First judgment criterion: The sum of the maximum active power output of all distributed energy and energy storage devices within the current power outage area node is greater than the total active load within the current power outage area node;

[0015] The second judgment criterion is that the maximum reactive power support capacity within the current power outage area node is greater than the total reactive power load within the current power outage area node.

[0016] Furthermore, the fault self-healing strategy for the nodes in the current power outage area, determined based on the local load demand judgment criteria, is as follows:

[0017] If both the first and second judgment criteria are true, then the nodes in the current power outage area will start self-organizing network operation;

[0018] Otherwise, the faulty network where the current power outage area node is located and the faultless network connected to the faulty network via the phase converter are taken as the first network, and the process proceeds to step S103.

[0019] Furthermore, the objective function aims to minimize the total amount of abandoned distributed energy resources, and its expression is:

[0020] ;

[0021] in, Let be the curtailment penalty coefficient for the k-th distributed energy source in the first network; This refers to the collection of distributed energy resources in the first network. To determine the maximum active power output of the k-th distributed energy source in the first network, This represents the active power output of the k-th distributed energy source in the first network.

[0022] Furthermore, the constraints include: active power balance constraints, reactive power balance constraints, node voltage constraints, distributed energy output constraints, energy storage power constraints, energy storage state of charge constraints, phase converter capacity constraints, phase converter reactive power transmission constraints, switching logic constraints, phase-to-phase load balancing constraints, linearized power flow constraints, and power direction constraints.

[0023] Furthermore, the optimal switching matrix of the phase-splitting converter is a 3×3 0-1 matrix, representing the switching state of the phase-splitting converter; the rows in the optimal switching matrix correspond to phases A, B, and C of the fault-free network, and the columns correspond to phases A, B, and C of the faulty network; if an element in the optimal switching matrix is ​​1, it means that the phases corresponding to the fault-free network and the faulty network are connected through the phase-splitting converter; if an element is 0, it means that they are not connected.

[0024] The beneficial effects of this invention are as follows: This invention aims to minimize the amount of power curtailment in distributed energy sources. It establishes an optimal switching matrix optimization model for phase-separated converters, achieving power mutual assistance under multi-resource coordinated phase-separated operation across voltage levels, thus overcoming the limitations of traditional three-phase overall power transfer. When a power outage occurs due to a network fault, nodes in the out-of-power area of ​​the faulty network can obtain power from the fault-free network through the phase-separated converters. This phase-separated power mutual assistance avoids the risk of line overload caused by a large load on a certain phase in traditional solutions, significantly improving power supply flexibility and reliability. Simultaneously, this invention helps improve the utilization level of clean energy and reduce wind and solar power curtailment. Attached Figure Description

[0025] Figure 1 This is a flowchart of the present invention.

[0026] Figure 2 This is an example of a global power grid structure provided according to Embodiment 1 of the present invention.

[0027] Figure 3 for Figure 2 A schematic diagram of the optimal switching matrix of the phase converter between the fault-free network N and the faulty network M.

[0028] Figure 4 This is an example of a global power grid structure provided according to Embodiment 2 of the present invention.

[0029] Figure 5This is an example of the solution process using the commercial Gurobi solver in Example 2.

[0030] Figure 6 This is an example of the local resource evaluation results in Example 2.

[0031] Figure 7 This is an example of the optimal switching matrix and power transmission results of the phase-splitting converter obtained by using the Gurobi commercial solver in Example 2.

[0032] Figure 8 This is a schematic diagram of the power transmitted from the fault-free network II to each phase of region 2 in the faulty network I in Example 2. Detailed Implementation

[0033] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. It should be noted that, unless otherwise specified, the embodiments and features in the embodiments of this application can be arbitrarily combined with each other.

[0034] Example 1: As Figures 1-3 As shown, a multi-resource collaborative phase fault self-healing method across voltage levels includes:

[0035] S101, based on the overall power grid structure, constructs a database of power source and load information covering the entire power grid; the overall power grid structure includes fault-prone and fault-free networks across voltage levels, with the three phases of the fault-prone and fault-free networks connected via phase-separated converters; such as Figure 2 As shown, the power grid structure involves two fault networks (network P and network M) and four fault-free networks (network R, network T, network Q, and network N). The voltages involved in the six networks are 35kV, 10kV, and 0.4kV. Region I and Region II in network M and Region III in network P are nodes in the power outage area.

[0036] Furthermore, the power supply and load information database covering the entire power grid includes: the distributed power source type of each node in the faulty network structure of the entire power grid, the maximum active power output and curtailment penalty coefficient of each type of distributed power source, three-phase active load, three-phase reactive load, maximum reactive power support capacity of nodes, initial state of charge of each energy storage device, minimum and maximum state of charge of each energy storage device, maximum charging and discharging power of each energy storage device, charging and discharging efficiency of each energy storage device, and rated capacity of each energy storage device; the distributed power source type in the fault-free network structure of the entire power grid, the maximum active power output and curtailment penalty coefficient of each type of distributed power source, three-phase active load, three-phase reactive load, maximum allowable load rate, line transmission power capacity, initial state of charge of each energy storage device, minimum and maximum state of charge of each energy storage device, maximum charging and discharging power of each energy storage device, charging and discharging efficiency of each energy storage device, and rated capacity of each energy storage device; and the transmission capacity limit per phase of the phase converter connecting any two networks.

[0037] S102, based on the power supply and load information database covering the entire power grid, evaluate each power outage node in the fault network and determine the fault self-healing strategy for the current power outage node.

[0038] Further, S102 includes: obtaining the total active load, total reactive load, maximum reactive power support capacity, and the sum of the maximum active power output of all distributed energy and energy storage devices in each power outage area node in each fault network; constructing a local load demand judgment criterion based on the total active load, total reactive load, maximum reactive power support capacity, and the sum of the maximum active power output of all distributed energy and energy storage devices; and determining the fault self-healing strategy of the current power outage area node based on the local load demand judgment criterion.

[0039] The criteria for determining local load demand, based on total active load, total reactive load, maximum reactive power support capacity, and the sum of the maximum active power output of all distributed energy sources and energy storage devices, are as follows:

[0040] First judgment criterion: The sum of the maximum active power output of all distributed energy and energy storage devices within the current power outage area node is greater than the total active load within the current power outage area node;

[0041] The second judgment criterion is that the maximum reactive power support capacity within the current power outage area node is greater than the total reactive power load within the current power outage area node.

[0042] The fault self-healing strategy for the nodes in the current power outage area is determined based on the local load demand judgment criteria, specifically as follows:

[0043] If both the first and second judgment criteria are true, then the nodes in the current power outage area will start self-organizing network operation;

[0044] Otherwise, the faulty network where the current power outage area node is located and the faultless network connected to the faulty network via the phase converter are taken as the first network, and the process proceeds to step S103.

[0045] in accordance with Figure 2 Regions I and III satisfy both the first and second judgment criteria, thus adopting self-organizing network operation to achieve fault self-healing. For Region II, local resources are insufficient, so proceed to step S103. For Region II, the faulty network where Region II is located and the faultless network connected to the faulty network via a phase-splitter converter are taken as the first network. Further, the first network also includes the power supply network of the faultless network connected to the faulty network via a phase-splitter converter. Specifically, network M and network N are taken as the first network. Considering that network N and network T are connected by a transformer, i.e., network T is the power supply network of network N, network M, network N, and network T can also be taken as the first network.

[0046] Specifically: if the sum of the maximum active power output of all distributed energy and energy storage devices in the current power outage area node is greater than the total active load in the current power outage area node, and the maximum reactive power support capacity is greater than the total reactive power load in the current power outage area node, the current power outage area node will operate in self-organizing mode, that is, without external mutual assistance, it can directly achieve uninterrupted power supply to the power outage area node by controlling the output of local distributed energy and energy storage devices; otherwise, if the conditions are not met, proceed to step S103.

[0047] S103, Establish an optimization model for the phase-splitting converter switching matrix; the optimization model for the phase-splitting converter switching matrix includes the objective function and constraints.

[0048] The phase converter switching matrix optimization model includes:

[0049] The objective function aims to minimize the total amount of abandoned distributed energy resources.

[0050] ;

[0051] in, Let be the curtailment penalty coefficient for the k-th distributed energy source in the first network; This refers to the collection of distributed energy resources in the first network. To determine the maximum active power output of the k-th distributed energy source in the first network, This represents the active power output of the k-th distributed energy source in the first network.

[0052] The constraints include:

[0053] Active power balance constraints: ;

[0054] Reactive power balance constraints: ;

[0055] Node voltage constraints: ;

[0056] Distributed energy output constraints: ;

[0057] Energy storage power constraints: ;

[0058] Energy storage state of charge constraints: ;

[0059] Capacity constraints of phase converters: ;

[0060] Reactive power transmission constraints of phase converters: ;

[0061] Switching logic constraints: ; ; ;

[0062] Interphase load balancing constraints: ;

[0063] Linearized power flow constraints: ;

[0064] Power direction constraint: ;

[0065] in, This refers to the collection of energy storage devices in the first network. This represents the set of fault-free networks in the first network. Let {A,B,C} be the set of three phases of the faulty network in the first network. Let {A,B,C} be the set of three phases of the fault-free network in the first network. For the first network, it is a fault-free network. of Phase to fault network The active power of the phase; This represents the total active load of all power outage nodes in the faulty network within the first network. This represents the total reactive load of all outage nodes in the faulty network within the first network. This represents the maximum reactive power support capacity of all outage nodes in the faulty network within the first network. For the fault-free network w in the first network Phase to fault network The reactive power of the phase; For the first network The node of the first Phase voltage (nodes are either outage nodes or normal nodes in the first network); The reference voltage; The set of all nodes in the first network; Let {A,B,C} be the phases; For the first network The maximum active power output of a distributed energy source; For the first network The active power output of an energy storage device is positive when it indicates discharge and negative when it indicates charging. For the first network The initial state of charge of an energy storage device; For the first network Minimum state of charge of an energy storage device; For the first network The maximum state of charge of an energy storage device; For the first network The maximum charging power of each energy storage device; For the first network The maximum discharge power of each energy storage device; For the first network The charging and discharging efficiency of an energy storage device; For the first network The rated capacity of each energy storage device; For the first network, it is a fault-free network. of Phase to fault network The switching status of the phase-separated converter (0 or 1, where a value of 1 indicates that the corresponding two phases are connected, and a value of 0 indicates that the pair of phases are not connected); To connect a fault-free network The maximum active power transmission capacity of the phase converter in the faulty network; To connect a fault-free network The maximum reactive power transmission capacity of the phase converter in the faulty network; For the first network, it is a fault-free network. of The original phase has active power load; For the fault-free network in the first network Phase line transmission power capacity; For the first network, it is a fault-free network. of Maximum permissible load rate; The node voltage vector in the first network; Let V be the initial voltage vector of the nodes in the first network; This is the voltage sensitivity matrix; Inject power vectors into the nodes of the first network.

[0066] S104, solve the optimization model of the phase converter switching matrix, and output the optimal switching matrix of the phase converter in the first network.

[0067] An optimization model for the phase-split converter switching matrix is ​​solved using a solver or intelligent optimization algorithm, outputting the optimal switching matrix of the phase-split converter. The optimal switching matrix is ​​a 3×3 0-1 matrix representing the switching state of the phase-split converter. Rows in the optimal switching matrix correspond to phases A, B, and C of the fault-free network, and columns correspond to phases A, B, and C of the faulty network. A "1" in the optimal switching matrix indicates that the phases corresponding to the fault-free network and the faulty network are connected through the phase-split converter, while a "0" indicates that they are not connected.

[0068] in accordance with Figure 3 , This represents the optimal switching matrix of the phase converter connecting the fault-free network N and the faulty network M. A N B N C Let M represent phases A, B, and C of the fault-free network N, respectively; A M B M C These represent phases A, B, and C of the faulty network M, respectively. In the first row, "1" indicates that phase A of the fault-free network N is connected to the corresponding phase of the faulty network M through a phase-splitter converter (only phase A of the fault-free network N is connected to phase B of the faulty network M through a phase-splitter converter in the first row, i.e., "1" is selected), and "0" indicates that they are not connected. In the second row, "1" indicates that phase B of the fault-free network N is connected to the corresponding phase of the faulty network M through a phase converter, and "0" indicates that they are not connected. In the third row, "1" indicates that the C phase of the fault-free network N is connected to the corresponding phase of the faulty network M through a phase converter, and "0" indicates that they are not connected.

[0069] S105 controls the switching connection status of the corresponding phase converter based on the optimal switching matrix of the phase converter, so as to realize the fault self-healing of the node in the current power outage area under the multi-resource collaborative phase splitting under cross-voltage level.

[0070] Example 2: As Figure 1 , Figures 4-8 As shown, the following describes an optional specific implementation process of the present invention in conjunction with simulation:

[0071] Step 1: Construct a database of power source and load information covering the entire power grid.

[0072] like Figure 4 As shown, a power grid structure includes network I and network II. Network I and network II are connected by a phase-splitter converter. At a certain moment, network I fails, causing power outages in areas 1 and 2 within network I.

[0073] Network I contains two load locations: Region 1 and Region 2. Region 1 is equipped with distributed resources including solar and wind power, with the maximum active power output of solar power being... =60MW, maximum active power output of wind power =25MW, the three-phase active power loads are P 1A =25MW, P 1B =25MW, P 1C =25MW, Total Active Power Load P in Region 1 1L =83MW, the three-phase reactive power loads are Q 1A =8MVar, Q 1B =10MVar, Q 1C =9MVar, Total reactive load Q in Region 1 1L =27MVar, the maximum reactive power support capacity in Region 1 is 29.7Mvar, the solar curtailment penalty factor in Region 1 is 1, and the wind power curtailment penalty factor is 1.2. The distributed resources in Region 2 include solar and wind power, where the maximum active power output of solar power is... =50MW, maximum active power output of wind power =60MW, the three-phase active power loads are P 2A =45MW, P 2B =40MW, P 2C =42MW, Total Active Power Load P in Region 2 2L =127MW, the three-phase reactive power loads are Q 2A =12MVar, Q 2B =15MVar, Q 2C =13MVar, Total reactive load Q in Region 2 2L =40MVar, the maximum reactive power support capacity in region 2 is 33Mvar, the photovoltaic curtailment penalty coefficient in region 2 is 1, and the wind power curtailment penalty coefficient is 1.2.

[0074] The three-phase active loads in Network II are P ⅡA =60MW, P ⅡB =65MW, P ⅡC =62MW, the three-phase reactive power loads are Q ⅡA =18MVar, Q ⅡB =20MVar, Q ⅡC =19MVar, the distributed resources equipped by Network II include photovoltaic and wind power, with the maximum active power output of photovoltaic power being 19MVar. =120MW, the maximum active power output of wind power is =100MW, the transmission power capacity of each phase line is 150MW, and the maximum allowable load factor is 1.2. The penalty factor for curtailment of photovoltaic power in Network II is 1, and the penalty factor for curtailment of wind power is 1.2.

[0075] Per-phase transmission capacity limits (active and reactive power limits) for phase converters connecting Network I and Network II: , .

[0076] Step 2: Evaluate the nodes in each power outage area of ​​the faulty network:

[0077] As a faulty network, Network I will evaluate Region 1 and Region 2 in Network I as follows:

[0078] Total active load P in region 1 1L =83MW, considering that energy storage devices are not involved, therefore the total maximum active power output of distributed energy resources is calculated. + =60+25=85MW, Total reactive power load of region 1 Q 1L =27MVar, maximum reactive power support capacity is 29.7MVar. In Region 1, the total maximum active power output is greater than the total active power load, and the maximum reactive power support capacity is greater than the total reactive power load. Both the first and second judgment criteria are true, therefore Region 1 is in self-organizing network operation.

[0079] Total active load P in region 2 2L =127MW, considering that energy storage devices are not involved, therefore the total maximum active power output of distributed energy resources is calculated. + =50+60=110MW, active power deficit is 17MW; total reactive power load Q in region 2 2L =40MVar, maximum reactive power support capacity is 33MVar, and reactive power gap is 7MVar.

[0080] If the maximum active power output in region 2 is less than the total active load and the maximum reactive power support capacity is less than the total reactive load in region 2, then both the first and second judgment criteria are false. Therefore, the faulty network I in region 2 and the faultless network II connected to the faulty network I via the phase converter are taken as the first network, and the process proceeds to step S103.

[0081] Step 3: When local resources are insufficient, an optimization model for the phase converter switching matrix is ​​established with the goal of minimizing the amount of electricity wasted from distributed energy sources. Based on the information in Step 1 and Step 2, the optimization model for the phase converter switching matrix is ​​established using the steps in Example 1.

[0082] Step 4: Solve the phase converter switching matrix optimization model to obtain the optimal networking strategy, i.e., the optimal switching matrix of the phase converters in the first network. For example, this embodiment uses the Gurobi commercial solver for solving.

[0083] like Figure 5 This is an example of the solution process using the commercial Gurobi solver; such as... Figure 6 Here is an example of the local resource assessment results for the power outage area in a faulty network; such as... Figure 7 This is an example of the optimal switching matrix and power transfer results for each phase of a split-phase converter, solved using the Gurobi commercial solver; based on Figure 7 Phase A of fault-free network II is connected to phase A of faulty network I through a phase-splitter converter; phase B of fault-free network II is connected to phase C of faulty network I through a phase-splitter converter; phase C of fault-free network II is connected to phase B of faulty network I through a phase-splitter converter.

[0084] Step 5: Based on the optimal switching matrix of the phase converter, control the switching connection state of the corresponding phase converter to achieve fault self-healing of the nodes in the current power outage area under multi-resource collaborative phase switching across voltage levels. Specifically: based on... Figure 7 The optimal switching matrix of the phase converter obtained from the solution is connected to the corresponding phase converter to achieve power mutual assistance and obtain, as shown in the figure. Figure 8 The diagram shows the power transmitted from fault-free network II to each phase of region 2 in faulty network I. Phase IIA transmits 3.3MW of active power and 1.0MVar of reactive power to phase IA. Phase IIB transmits 5.3MW of active power and 2.0MVar of reactive power to phase IC. Phase IIC transmits 8.3MW of active power and 4.0MVar of reactive power to phase IB.

[0085] The specific embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the present invention is not limited to the above embodiments. Within the scope of knowledge possessed by those skilled in the art, various changes can be made without departing from the spirit of the present invention.

Claims

1. A multi-resource collaborative phase fault self-healing method across voltage levels, characterized in that, include: S101, based on the power grid's overall network structure, constructs a database of power source and load information covering the entire power grid; the power grid's overall network structure includes fault networks and fault-free networks across voltage levels, and the three phases of the fault networks and fault-free networks are connected through phase-separated converters; S102, Based on the power supply and load information database covering the entire power grid, evaluate the nodes of each power outage area in the fault network and determine the fault self-healing strategy of the current power outage area node. S103, Establish an optimization model for the phase-split converter switching matrix; the optimization model for the phase-split converter switching matrix includes the objective function and constraints. S104, Solve the optimization model of the phase converter switching matrix and output the optimal switching matrix of the phase converter; The objective function aims to minimize the total amount of abandoned distributed energy resources, and its expression is: ； in, Let be the curtailment penalty coefficient for the k-th distributed energy source in the first network; This refers to the collection of distributed energy resources in the first network. To determine the maximum active power output of the k-th distributed energy source in the first network, The active power output of the k-th distributed energy source in the first network; The constraints include: active power balance constraints, reactive power balance constraints, node voltage constraints, distributed energy output constraints, energy storage power constraints, energy storage state of charge constraints, phase converter capacity constraints, phase converter reactive power transmission constraints, switching logic constraints, phase-to-phase load balancing constraints, linearized power flow constraints, and power direction constraints. The optimal switching matrix of the phase-splitting converter is a 3×3 0-1 matrix, representing the switching state of the phase-splitting converter. The rows in the optimal switching matrix correspond to phases A, B, and C of the fault-free network, and the columns correspond to phases A, B, and C of the faulty network. When an element in the optimal switching matrix is ​​1, it means that the phases corresponding to the fault-free network and the faulty network are connected through the phase-splitting converter; when an element is 0, it means that they are not connected.

2. The multi-resource collaborative phase fault self-healing method across voltage levels according to claim 1, characterized in that, S102 includes: obtaining the total active load, total reactive load, maximum reactive power support capacity, and the sum of the maximum active power output of all distributed energy and energy storage devices in each power outage area node of each fault network based on a power supply and load information database covering the entire power grid; constructing a local load demand judgment criterion based on the total active load, total reactive load, maximum reactive power support capacity, and the sum of the maximum active power output of all distributed energy and energy storage devices; and determining the fault self-healing strategy of the current power outage area node based on the local load demand judgment criterion.

3. The multi-resource collaborative phase fault self-healing method across voltage levels according to claim 2, characterized in that, The criteria for determining local load demand, based on total active load, total reactive load, maximum reactive power support capacity, and the sum of the maximum active power output of all distributed energy sources and energy storage devices, are as follows: First judgment criterion: The sum of the maximum active power output of all distributed energy and energy storage devices within the current power outage area node is greater than the total active load within the current power outage area node; The second judgment criterion is that the maximum reactive power support capacity within the current power outage area node is greater than the total reactive power load within the current power outage area node.

4. The multi-resource collaborative phase fault self-healing method across voltage levels according to claim 3, characterized in that, The fault self-healing strategy for the nodes in the current power outage area is determined based on the local load demand judgment criteria, specifically as follows: If both the first and second judgment criteria are true, then the nodes in the current power outage area will start self-organizing network operation; Otherwise, the faulty network where the current power outage area node is located and the faultless network connected to the faulty network via the phase converter are taken as the first network, and the process proceeds to step S103.

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