Intelligent distribution network fault warning system based on natural disasters

Abstract

The present invention discloses a fault warning system for an intelligent distribution network under natural disasters. The present invention relates to the technical field of intelligent distribution networks, and solves the problem that when natural disasters occur, the system is often difficult to quickly and accurately identify the fault area, and automatically adjust the grid operation mode to isolate the fault, resulting in the inability to effectively guarantee the stability and reliability of the power supply. The present invention calculates the fault index through a fault judgment module and compares it with a preset threshold. This process ensures the accuracy and real-time nature of the judgment. When a fault occurs, the early warning protection module can respond quickly, and by automatically isolating the fault area and issuing an alarm, the fault spread is effectively avoided, and the rest of the grid is protected from being affected. This fast and accurate fault handling mechanism significantly improves the stability and reliability of the grid operation when facing extreme conditions such as natural disasters, and ensures the continuity and safety of the power supply.

Description

Technical Field

[0001] The present invention relates to the technical field of smart distribution network, and in particular to a smart distribution network fault early warning system based on natural disasters. Background Art

[0002] In the current development of smart distribution networks, fault warning systems have become one of the key technologies, aiming to predict and identify potential grid faults through real-time monitoring and data analysis, so as to take measures in advance to prevent or mitigate the impact of faults. These systems rely on advanced sensor networks, data processing algorithms and communication technologies, and can collect various parameters of grid operation in real time, such as current, voltage, temperature, etc. By analyzing this data, the system can predict possible faults and issue warnings to operators. This early warning system is particularly important for maintaining the stability and reliability of power supply in the face of natural disasters such as storms, earthquakes and other extreme weather conditions.

[0003] However, despite the existence of these fault warning technologies, smart distribution networks still face the challenge of automatically isolating fault areas and reconfiguring grid operation modes in actual operations; especially when natural disasters occur, these systems often find it difficult to quickly and accurately identify fault areas and automatically adjust grid operation modes to isolate faults, resulting in the inability to effectively ensure the stability and reliability of power supply. This may be because the existing systems are not sufficiently automated and intelligent, and cannot fully cope with the complex and unpredictable grid failure scenarios caused by natural disasters. Therefore, there is an urgent need to develop a fault warning system for smart distribution networks under natural disasters. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides an intelligent distribution network fault early warning system based on natural disasters to solve the problem.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: Based on the intelligent distribution network fault early warning system under natural disasters, it includes:

[0006] The data collection module is used to collect information data of the power system in real time and transmit the collected information data to the subsequent data analysis module in real time, wherein the information data includes: current value, voltage value, power factor value and frequency value;

[0007] A data analysis module is used to receive information data, and then determine monitoring information by comparing the real-time information data with preset information, wherein the preset information includes a preset normal operating current value, a preset normal operating voltage value, a preset power factor and a preset standard frequency value, and the monitoring information includes a current mutation value, a voltage mutation value, a power factor change value and a frequency deviation value;

[0008] A fault determination module is used to determine whether a line fault occurs according to monitoring information, and when it is determined that there is a line fault, the line fault is defined as a fault point;

[0009] The early warning protection module is used to quickly locate the fault point by using the fault indicator, issue an alarm message, and automatically isolate the fault area. By controlling the circuit breaker and disconnector equipment in the distribution network, the circuit connection on both sides of the fault point is quickly disconnected to isolate the fault point, and the isolated fault point area is marked as the fault area;

[0010] The impact assessment module, after isolating the fault area, assesses the impact of the isolated fault area on the grid operation by analyzing the grid topology, thereby determining the abnormal area;

[0011] The priority determination module calculates the priority of the determined abnormal areas, and sorts the abnormal areas according to the priority calculation results to determine the abnormal areas with high priority;

[0012] The abnormal area recovery module, after determining the priority of the abnormal area, selects a backup power supply path and a backup power supply according to the order of priority to restore power supply to the abnormal area.

[0013] Preferably, the method for determining monitoring information in the data analysis module is:

[0014] Current mutation value, receiving current value data Gs in real time, and comparing it with the preset normal operating current value Gz, and obtaining the current mutation value ΔI through the formula |Gs-Gz|;

[0015] Voltage mutation value, receiving voltage value data Ds in real time, and comparing it with the preset normal operating voltage value Dz, and obtaining the voltage mutation value ΔV through the formula |Vs-Vz|;

[0016] Power factor change value: the real-time received power factor Ps is compared with the preset power factor Pz, and the power factor change value ΔP is obtained through the formula |Ps-Pz|;

[0017] The frequency deviation value is a comparison between the real-time received frequency value Fs and the preset standard frequency value Fz, and the frequency deviation value ΔF is obtained by the formula |Fs-Fz|.

[0018] Preferably, the method for determining whether a line fault occurs in the fault determination module is:

[0019] Obtain monitoring information and obtain the fault index H through the calculation formula. The specific formula is:

[0020] H=k1×ΔI+k2×ΔV+k3×ΔP+k4×ΔF

[0021] Among them, k1, k2, k3 and k4 are weight coefficients;

[0022] Then, the fault indicator H is compared with the preset threshold value H1. When H>H1, it is determined that a line fault occurs here.

[0023] Preferably, the specific method for determining the abnormal area in the impact assessment module is:

[0024] The first step is to obtain the grid topology structure of the grid operation before the fault, wherein the grid topology structure includes the grid topology structure formed by connecting all power stations, substations, transmission lines, distribution lines and their nodes;

[0025] The second step is to set the corresponding fault point in the power grid topology according to the actual fault point;

[0026] In the third step, after setting the corresponding fault point, the grid topology changes accordingly, and then the fault area caused by the fault point is eliminated in the grid topology to reflect the grid topology after the fault occurs;

[0027] In the fourth step, the network structure of the power grid topology after the fault is calculated through the power system analysis software to obtain the voltage level of each node and the current load of all lines.

[0028] Preferably, after step 4, the method further includes:

[0029] The fifth step is to determine the voltage level of each node, determine the node below a certain threshold as the area that has lost power supply, mark it in the power grid topology, and stop the power supply to the node area;

[0030] Then, the current load of all lines is obtained, and the lines that exceed the safe load are determined as faulty lines. The faulty lines are removed from the grid topology and the power is cut off at the same time.

[0031] In the sixth step, the node area that loses power supply due to the fault point is determined, marked as an abnormal area, and the latest power grid topology is generated.

[0032] Preferably, the priority calculation method of the abnormal area in the priority determination module is:

[0033] Through the following formula:

[0034] CL I=W1×P life +W2×P lnfra +W3×P econ +W4×P res

[0035] Among them, CLI represents the priority index, P lifeExpressed as life safety impact index, P lnfra Expressed as the infrastructure support impact index, P econ Expressed as an economic activity impact indicator, P res It is expressed as the index of impact on residents’ lives. The four indicators are set in advance according to the specific conditions of each area. The weights of indicators W1, W2, W3 and W4 are W1+W2+W3+W4=1;

[0036] Then, the priority index CLI calculated for each abnormal area is compared and sorted from large to small.

[0037] Preferably, the specific way of restoring power supply in the abnormal area recovery module is:

[0038] S1: Obtain the latest grid topology, and then determine the backup power supply path and backup power source;

[0039] S2: judging whether the backup power supply path can be connected to the abnormal area according to the network structure of the power grid topology;

[0040] If it is determined that it can be connected to the fault area, then determine whether the output power of the backup power supply can meet the power demand of the area;

[0041] If it is determined that it is not possible to connect to the faulty area, the next highest priority abnormal area is selected to perform the same judgment;

[0042] S3: When determining whether the output power of the backup power supply meets the power demand of the area, the required power Q1 of the abnormal area is obtained, and a backup power supply with the same output power is selected from the backup power supplies to supply power to the abnormal area.

[0043] Preferably, S3 also includes:

[0044] If there is no backup power supply with the same output power, obtain all backup power supplies with an output power greater than Q1 and record them as available power supplies. Mark the output power Qi of each available power supply, and obtain the calculation result QSi by Qi-Q1. Select the available power supply with the smallest value of QSi as the best backup power supply to supply power to the abnormal area; where i represents the output power of each available power supply, i=1, 2, 3, ..., n, and n is the number of available power supplies;

[0045] When the backup power source with a power greater than the output power Q1 is not available, the power supply is abandoned.

[0046] Preferably, it also includes:

[0047] The fault recovery module is used to dispatch a maintenance team to the site to repair the fault point. After the repair is completed, the operation and maintenance personnel gradually restore the power grid to normal operation and cancel the temporary backup power supply path.

[0048] The present invention provides a smart distribution network fault early warning system based on natural disasters. Compared with the prior art, it has the following beneficial effects:

[0049] (1) The present invention can significantly improve the stability and reliability of the power grid by implementing an intelligent distribution network fault warning system based on natural disasters. Through a highly automated data collection module, key parameters of the power grid, such as current, voltage, power factor and frequency values, are monitored in real time. The system can promptly capture abnormal changes caused by natural disasters. In addition, through an efficient data analysis module, the system can quickly identify the specific location of the power grid fault. Accurate analysis of these monitoring information is the key to achieving rapid response and fault isolation, thereby improving the stability and reliability of the power grid.

[0050] (2) The present invention calculates the fault index through the fault judgment module and compares it with the preset threshold value. This process ensures the accuracy and real-time nature of the judgment. When a fault occurs, the early warning protection module can respond quickly, automatically isolate the fault area and issue an alarm, effectively avoiding the spread of the fault and protecting the rest of the power grid from being affected. This fast and accurate fault handling mechanism significantly improves the stability and reliability of power grid operation in the face of extreme conditions such as natural disasters, and ensures the continuity and safety of power supply.

[0051] (3) The present invention can evaluate the specific impact of the isolated area on the operation of the power grid after the fault is isolated through the impact assessment module and the priority determination module, and sort the abnormal areas according to the priority index CLI. This process not only provides decision support when a fault occurs, but also provides important reference information for power grid operation and management. By analyzing the changes in the power grid topology and current load after the fault, the system can identify the areas that need to be restored first and optimize resource allocation.

[0052] (4) The present invention uses an abnormal area recovery module and a fault recovery module. After determining the priority of the abnormal area, the system can select a backup power supply path and a backup power source according to the priority order, and quickly restore power to the affected area. This not only reduces the duration of the power outage, but also greatly improves the efficiency of restoring power. In emergency situations such as natural disasters, a fast grid recovery speed is crucial in mitigating the impact of long-term power outages. The design of this system quickly identifies the optimal backup power supply path and power source, ensuring that even under the worst natural disaster conditions, power supply to critical areas such as healthcare facilities, emergency services, and critical infrastructure can be restored as quickly as possible. This rapid response capability reduces the economic losses caused by power outages. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] The present invention will be further described below in conjunction with the accompanying drawings.

[0054] Figure 1 This is a system framework diagram of the intelligent distribution network fault early warning system under natural disasters according to the present invention;

[0055] Figure 2 This is a flow chart of determining abnormal areas based on the intelligent distribution network fault early warning system under natural disasters in the present invention. DETAILED DESCRIPTION

[0056] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0057] Embodiment 1

[0058] See also Figure 1-Figure 2 , the present invention provides a smart distribution network fault early warning system based on natural disasters, including;

[0059] The data collection module is used to collect information data of the power system in real time and transmit the collected information data to the subsequent data analysis module in real time, wherein the information data includes: current value, voltage value, power factor value and frequency value;

[0060] It should be noted that: the current value is obtained by using a current sensor, which monitors the current of each part of the power grid in real time and accurately measures the current passing through the wire;

[0061] Voltage value acquisition method: Voltage sensors and voltage transformers are responsible for monitoring the voltage level of the power grid;

[0062] Power factor acquisition method: The measurement of power and power factor is usually completed by power quality analyzers or integrated power monitoring equipment. These devices can simultaneously measure the relationship between current, voltage and phase angle to calculate the power factor;

[0063] Frequency value acquisition method: Frequency measurement is usually carried out through power grid frequency monitoring equipment, which can accurately determine the real-time frequency of the power system;

[0064] The data analysis module is used to analyze and process the received information data to obtain corresponding monitoring information, wherein the monitoring information includes current mutation value, voltage mutation value, power factor change value and frequency deviation value;

[0065] The monitoring information is determined by:

[0066] Current mutation value, receiving current value data Gs in real time, and comparing it with the preset normal operating current value Gz, and obtaining the current mutation value ΔI through the formula |Gs-Gz|;

[0067] Voltage mutation value, receiving voltage value data Ds in real time, and comparing it with the preset normal operating voltage value Dz, and obtaining the voltage mutation value ΔV through the formula |Vs-Vz|;

[0068] Power factor change value: the real-time received power factor Ps is compared with the preset power factor Pz, and the power factor change value ΔP is obtained through the formula |Ps-Pz|;

[0069] Frequency deviation value: compare the real-time received frequency value Fs with the preset standard frequency value Fz, and obtain the frequency deviation value ΔF through the formula |Fs-Fz|;

[0070] The fault determination module is used to determine whether a line fault has occurred in the event of a natural disaster, and define the line fault that has occurred as a fault point;

[0071] The method for determining whether a line fault occurs is:

[0072] Obtain monitoring information and obtain fault indicators through calculation formula. The specific formula is:

[0073] H=k1×ΔI+k2×ΔV+k3×ΔP+k4×ΔF

[0074] Among them, H represents the fault index, k1, k2, k3 and k4 are weight coefficients, which correspond to the importance of current mutation value, voltage mutation value, power factor change value and frequency deviation value respectively. The selection of weights can be adjusted according to historical data and expert experience to improve the accuracy of fault detection;

[0075] Then, the fault index H is compared with the preset threshold value H1. When H>H1, it is determined that a line fault has occurred. The setting of the threshold value H1 needs to be determined according to the specific conditions of the system and historical fault data to balance the risks of false alarms and missed alarms. The specific parameters are set by the staff.

[0076] The early warning protection module is used to quickly locate the fault point by using the fault indicator, issue an alarm message, and automatically isolate the fault area. By controlling the circuit breaker and disconnector equipment in the distribution network, the circuit connection on both sides of the fault point is quickly disconnected to isolate the fault point, and the isolated fault point area is marked as the fault area;

[0077] The above process is designed to prevent the fault from spreading and protect the rest of the grid from being affected;

[0078] The impact assessment module, after isolating the fault area, assesses the impact of the isolated fault area on the grid operation, thereby determining the abnormal area;

[0079] Combination Figure 2 The specific method for determining the abnormal area is:

[0080] The first step is to obtain the grid topology structure of the grid operation before the fault, wherein the grid topology structure includes the grid topology structure formed by connecting all power stations, substations, transmission lines, distribution lines and their connection points (nodes);

[0081] The second step is to set the corresponding fault point in the power grid topology according to the actual fault point;

[0082] In the third step, after setting the corresponding fault point, the grid topology changes accordingly, and then the fault area caused by the fault point is eliminated in the grid topology to reflect the grid topology after the fault occurs;

[0083] The fourth step is to calculate the network structure of the power grid topology after the fault through the power system analysis software to obtain the voltage level of each node and the current load of all lines;

[0084] It should be noted that power system analysis software is a tool designed specifically for the field of power engineering, used to simulate, analyze and optimize the operation and planning of power systems. This type of software can handle complex power grid models and perform various calculations, including power flow analysis (load flow calculation), short circuit analysis, stability analysis, harmonic analysis, etc. Among them, power flow analysis is the most common type of calculation, which is used to determine the voltage level of each node in the power grid and the current load of all lines under given load conditions;

[0085] The fifth step is to determine the voltage level of each node, determine the node below a certain threshold as the area that has lost power supply, mark it in the power grid topology, and stop the power supply to the node area;

[0086] Then, the current load of all lines is obtained, and the lines that exceed the safe load are determined as faulty lines. The faulty lines are removed from the grid topology and the power is cut off at the same time.

[0087] In the sixth step, the node area that loses power supply due to the fault point is determined, marked as an abnormal area, and the latest power grid topology is generated;

[0088] The priority determination module calculates the priority of the determined abnormal areas, and sorts the abnormal areas according to the priority calculation results to determine the abnormal areas with high priority;

[0089] Embodiment 2

[0090] In the specific implementation process, this embodiment is based on the first embodiment, and the difference from the first embodiment is that this embodiment is directed to:

[0091] The priority of the abnormal area is calculated as follows:

[0092] Through the following formula:

[0093] CL I=W1×P life +W2×P lnfra +W3×P econ +W4×P res

[0094] Among them, CLI represents the priority index, P life Expressed as life safety impact index, P lnfra Expressed as the infrastructure support impact index, P econ Expressed as an economic activity impact indicator, P res It is expressed as the impact index of residents' lives. The four indicators are set in advance by relevant personnel according to the specific conditions of each area. The weights of indicators W1, W2, W3 and W4 are determined according to the actual situation, and W1+W2+W3+W4=1;

[0095] Then the priority index CLI calculated for each abnormal area is compared and sorted from large to small;

[0096] Embodiment 3

[0097] In the specific implementation process, this embodiment is based on the first and second embodiments, and the difference from the first and second embodiments is that this embodiment also includes:

[0098] The abnormal area recovery module, after determining the priority of the abnormal area, selects a backup power supply path and a backup power supply according to the order of priority to restore power supply to the abnormal area;

[0099] The specific methods for restoring power supply are as follows:

[0100] S1: Obtain the latest grid topology, and then determine the backup power supply path and backup power source;

[0101] S2: judging whether the backup power supply path can be connected to the abnormal area according to the network structure of the power grid topology;

[0102] If it is determined that it can be connected to the fault area, then determine whether the output power of the backup power supply can meet the power demand of the area;

[0103] If it is determined that it is not possible to connect to the faulty area, the next highest priority abnormal area is selected to perform the same judgment;

[0104] S3: When determining whether the output power of the backup power supply meets the power demand of the area, the required power Q1 of the abnormal area is obtained, and a backup power supply with the same output power is selected from the backup power supplies to supply power to the abnormal area;

[0105] If there is no backup power supply with the same output power, obtain all backup power supplies with an output power greater than Q1 and record them as available power supplies. Mark the output power Qi of each available power supply, and obtain the calculation result QSi by Qi-Q1. Select the available power supply with the smallest value of QSi as the best backup power supply to supply power to the abnormal area; where i represents the output power of each available power supply, i=1, 2, 3, ..., n, and n is the number of available power supplies;

[0106] When no backup power source greater than the output power Q1 is obtained, the power supply is abandoned;

[0107] The fault recovery module dispatches a maintenance team to the site to repair the fault point while ensuring safety. After the repair is completed, the operation and maintenance personnel gradually restore the power grid to normal operation, cancel the temporary backup power supply path, and ensure a smooth transition of the entire process.

[0108] Embodiment 4

[0109] The specific implementation process of this embodiment includes all the implementation processes of the above three groups of embodiments.

[0110] Some of the data in the above formulas are dimensionless and numerically calculated. Meanwhile, the contents not described in detail in this specification belong to the prior art known to those skilled in the art.

[0111] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. Based on the intelligent distribution network fault early warning system under natural disasters, it is characterized by: include: The data collection module is used to collect information data of the power system in real time and transmit the collected information data to the subsequent data analysis module in real time, wherein the information data includes: current value, voltage value, power factor value and frequency value; A data analysis module is used to receive information data, and then determine monitoring information by comparing the real-time information data with preset information, wherein the preset information includes a preset normal operating current value, a preset normal operating voltage value, a preset power factor and a preset standard frequency value, and the monitoring information includes a current mutation value, a voltage mutation value, a power factor change value and a frequency deviation value; A fault determination module is used to determine whether a line fault occurs according to monitoring information, and when it is determined that there is a line fault, the line fault is defined as a fault point; The early warning protection module is used to quickly locate the fault point by using the fault indicator, issue an alarm message, and automatically isolate the fault area. By controlling the circuit breaker and disconnector equipment in the distribution network, the circuit connection on both sides of the fault point is quickly disconnected to isolate the fault point, and the isolated fault point area is marked as the fault area; The impact assessment module, after isolating the fault area, assesses the impact of the isolated fault area on the grid operation by analyzing the grid topology, thereby determining the abnormal area; The priority determination module calculates the priority of the determined abnormal areas, and sorts the abnormal areas according to the priority calculation results to determine the abnormal areas with high priority; The abnormal area recovery module, after determining the priority of the abnormal area, selects a backup power supply path and a backup power supply according to the order of priority to restore power supply to the abnormal area; The way to determine monitoring information in the data analysis module is: Current mutation value, receiving current value data Gs in real time, and comparing it with the preset normal operating current value Gz, and obtaining the current mutation value ΔI through the formula |Gs-Gz|; Voltage mutation value, receiving voltage value data Ds in real time, and comparing it with the preset normal operating voltage value Dz, and obtaining the voltage mutation value ΔV through the formula |Vs-Vz|; Power factor change value: the real-time received power factor Ps is compared with the preset power factor Pz, and the power factor change value ΔP is obtained through the formula |Ps-Pz|; Frequency deviation value: compare the real-time received frequency value Fs with the preset standard frequency value Fz, and obtain the frequency deviation value ΔF through the formula |Fs-Fz|; The way to determine whether a line fault occurs in the fault determination module is as follows: Obtain monitoring information and obtain the fault index H through the calculation formula. The specific formula is: H=k1×ΔI+k2×ΔV+k3×ΔP+k4×ΔF Among them, k1, k2, k3 and k4 are weight coefficients; Then, the fault indicator H is compared with a preset threshold value H1. When H>H1, it is determined that a line fault occurs here.

2. The intelligent distribution network fault early warning system based on natural disasters according to claim 1 is characterized in that: The specific method for determining abnormal areas in the impact assessment module is as follows: The first step is to obtain the grid topology structure of the grid operation before the fault, wherein the grid topology structure includes the grid topology structure formed by connecting all power stations, substations, transmission lines, distribution lines and their nodes; The second step is to set the corresponding fault point in the power grid topology according to the actual fault point; In the third step, after setting the corresponding fault point, the grid topology changes accordingly, and then the fault area caused by the fault point is eliminated in the grid topology to reflect the grid topology after the fault occurs; In the fourth step, the network structure of the power grid topology after the fault is calculated through the power system analysis software to obtain the voltage level of each node and the current load of all lines.

3. The intelligent distribution network fault early warning system based on natural disasters according to claim 2 is characterized in that: After step 4, it also includes: The fifth step is to determine the voltage level of each node, determine the node below a certain threshold as the area that has lost power supply, mark it in the power grid topology, and stop the power supply to the node area; Then, the current load of all lines is obtained, and the lines that exceed the safe load are determined as faulty lines. The faulty lines are removed from the grid topology and the power is cut off at the same time. In the sixth step, the node area that loses power supply due to the fault point is determined, marked as an abnormal area, and the latest power grid topology is generated.

4. The intelligent distribution network fault early warning system based on natural disasters according to claim 1 is characterized in that: The priority calculation method of the abnormal area in the priority determination module is: Through the following formula: CL I=W1×P life +W2×P lnfra +W3×P econ +W4×P res Among them, CLI represents the priority index, P life Expressed as life safety impact index, P lnfra Expressed as the infrastructure support impact index, P econ Expressed as an economic activity impact indicator, P res It is expressed as the index of impact on residents’ lives. The four indicators are set in advance according to the specific conditions of each area. The weights of indicators W1, W2, W3 and W4 are W1+W2+W3+W4=1; Then, the priority index CLI calculated for each abnormal area is compared and sorted from large to small.

5. The intelligent distribution network fault early warning system based on natural disasters according to claim 1 is characterized in that: The specific way to restore power supply in the abnormal area recovery module is as follows: S1: Obtain the latest grid topology, and then determine the backup power supply path and backup power source; S2: judging whether the backup power supply path can be connected to the abnormal area according to the network structure of the power grid topology; If it is determined that it can be connected to the fault area, then determine whether the output power of the backup power supply can meet the power demand of the area; If it is determined that it is not possible to connect to the faulty area, the next highest priority abnormal area is selected to perform the same judgment; S3: When determining whether the output power of the backup power supply meets the power demand of the area, the required power Q1 of the abnormal area is obtained, and a backup power supply with the same output power is selected from the backup power supplies to supply power to the abnormal area.

6. The intelligent distribution network fault early warning system based on natural disasters according to claim 5 is characterized in that: Also included in S3: If there is no backup power supply with the same output power, obtain all backup power supplies with an output power greater than Q1 and record them as available power supplies. Mark the output power Qi of each available power supply, and obtain the calculation result QSi by Qi-Q1. Select the available power supply with the smallest QSi value as the best backup power supply to supply power to the abnormal area; where i represents the output power of each available power supply, i=1, 2, 3, ..., n, and n is the number of available power supplies; When the backup power source with a power greater than the output power Q1 is not available, the power supply is abandoned.

7. The intelligent distribution network fault early warning system based on natural disasters according to claim 1 is characterized in that: Also includes: The fault recovery module is used to dispatch a maintenance team to the site to repair the fault point. After the repair is completed, the operation and maintenance personnel gradually restore the power grid to normal operation and cancel the temporary backup power supply path.

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