Distribution line fault environment adaptive disposal decision architecture and implementation method

Abstract

The invention discloses a distribution line fault environment adaptive disposal decision architecture and an implementation method, and relates to the technical field of distribution network fault detection and protection. The implementation method comprises the following steps: establishing a fault ignition action mechanism according to a fault type, a line channel between a first power distribution main station and a second power distribution main station, a first meteorological element and a second meteorological element, and forming a risk assessment grading model; according to the switch level, the automation level of the power distribution master station and the risk assessment grading model, a decision logic mechanism, switch time delay, alarm and tripping strategies associated with the fault and the environment are constructed; a distribution network fault self-adaptive decision-making framework capable of being integrated into an automatic system is constructed in a low-cost and light-weight mode, a landing solution of engineering application is formed, a traditional direct one-step inherent handling mode of faults is effectively avoided, and compromise balance between effective fault handling and power supply reliability is achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power distribution network fault detection and protection, more particularly, it relates to a power distribution line fault environment adaptive handling decision architecture and implementation method. BACKGROUND

[0002] The possibility of forest and grassland fire caused by distribution network fault mainly depends on the local meteorological environmental conditions, the types and states of vegetation, and the characteristics of the fault itself. These three key factors have great differences in spatial and temporal distribution and have time-varying characteristics. However, the traditional distribution network fault handling method based on fixed logic cannot adapt to such differences and changes, resulting in mismatched fault handling measures and unnecessary tripping. For example, in the mountain fire season, the distribution network generally implements high-sensitivity single-phase ground fault detection and non-delay tripping strategy. If sudden rain occurs, a large number of tripping will occur. From the perspective of preventing forest fires, the risk of forest fires is very low in rainy weather.

[0003] Therefore, to solve the contradiction between power distribution network forest fire prevention and reliable power supply, it is necessary to make the distribution network fault handling measures more accurate and greatly reduce unnecessary tripping events. For this purpose, the current problems are: 1. How to widely monitor the line meteorological environment and vegetation state; 2. How to collect the meteorological quantities associated with the fault based on the widely used distribution automation system; 3. How to realize the environment adaptive distribution network fault handling decision.

[0004] In view of the above, the present application is proposed. SUMMARY

[0005] The purpose of the present application is to provide a power distribution line fault environment adaptive handling decision architecture and implementation method, which can build a distribution network fault adaptive decision architecture that can be integrated into an automation system in a low-cost and lightweight manner, form an engineering application that can be landed solution, and solve the problems in the background art.

[0006] The above technical purpose of the present application is achieved by the following technical scheme: In a first aspect, the present application provides a power distribution line fault environment adaptive handling decision architecture, which comprises: A first Internet of Things terminal is used to collect electrical quantities in real time, and to determine the fault type and fault intensity according to the detection criteria of short circuit and ground fault; it is also used to trigger the collection of first meteorological elements when fault is determined, and to match meteorological data and fault data according to time stamp, and to make immediate handling of corresponding faults through a preset fault adaptive handling decision table; The first power distribution master station is configured to acquire electrical quantity, first meteorological elements and fault processing results according to a fault self-adaptive processing decision table, and transmit the results to the second power distribution master station; and is further configured to receive a strategy table issued by the second power distribution master station, and issue a preset strategy table to the first Internet of Things terminal. The second power distribution master station is configured to acquire second meteorological elements uploaded by the second Internet of Things terminal, and issue a strategy table generated by the second meteorological elements uploaded by the first Internet of Things terminal to the first power distribution master station. The second Internet of Things terminal is configured to acquire second meteorological elements.

[0007] Based on the above technical solutions, the application can be further improved as follows.

[0008] Further, the above-mentioned immediate treatment of the corresponding fault is specifically as follows:

[0009] Switch levels are divided according to the main line and branch line, and the key section cooperation relationship, and the switch distribution position is determined;

[0010] According to the collected electrical quantity and first meteorological elements, the associated risk level and action logic are matched based on the query fault self-adaptive processing decision table, and the fault self-adaptive processing is completed according to the matching result.

[0011] Further, the fault types include single-phase ground fault and short circuit fault; wherein the fault strength of the single-phase ground fault is determined by the following method: , wherein: ; In the formula, represents the fault strength of the single-phase ground fault, which is the absolute value of the zero sequence current sequence of the one cycle after the Fourier decomposition of the fault; represents the n-th sampling value of the one cycle zero sequence current; represents the amplitude of the k-th harmonic component of the zero sequence current; is the cycle sequence length, and when the corresponding sampling rate is 6.4 kHz 128, 12.8 kHz 256; is a virtual part symbol operator; is a frequency operator, .

[0012] Further, the fault strength of the short circuit fault is determined by the following method: , wherein: ; In the formula, representing the electrical strength of short-circuit fault, the maximum value of the absolute value of the Fourier decomposition basis value of the three-phase current one cycle after the fault by Fourier decomposition; , and respectively corresponding to the amplitude of the kth harmonic component of the A, B and C three-phase currents; is the cycle sequence length, corresponding to 128, 12.8 kHz when the sampling rate is 6.4 kHz 128, 12.8 kHz when the sampling rate is 6.4 kHz 256; is the imaginary part symbol operator; is the frequency operator, ; , and respectively corresponding to the nth sampling value of the A, B and C three-phase currents within one cycle.

[0013] In a second aspect, the application provides an implementation method of a power distribution line fault environment adaptive handling decision architecture, which comprises the following specific steps: According to the fault type, the line channel between the first and second power distribution master stations, the first meteorological element, and the second meteorological element, an action mechanism of fault ignition and combustion is established, and a risk assessment grading model is formed. The action mechanism specifically includes: According to the risk level, an alarm or trip strategy is adaptively selected; According to the switch level, a delay is selected based on the principles of reliable power supply and switch characteristics; According to the fire prevention section, the handling is upgraded according to the principle of proximity and height, and there is no delay for high-risk.

[0014] Further, the implementation method further comprises: According to the switch level, the automation level of the power distribution master station, and the risk assessment grading model, a decision logic mechanism associated with the fault and the environment, a switch delay, an alarm and a trip strategy are constructed.

[0015] Further, the risk assessment grading model specifically includes: ; In the formula, corresponding to the fire development probability; corresponding to the short-circuit fault ignition probability; corresponding to the short-circuit fault occurrence probability; corresponding to the grounding fault ignition probability; corresponding to the grounding fault occurrence probability, representing the comprehensive occurrence probability.

[0016] In a third aspect, the application provides an implementation system of a power distribution line fault environment adaptive treatment decision architecture, which is used to execute the implementation method of the power distribution line fault environment adaptive treatment decision architecture in any one of the second aspect, and comprises: A model construction module is configured to establish a fault ignition and combustion mechanism according to the fault type, the line channel between the first power distribution master station and the second power distribution master station, the first meteorological element and the second meteorological element, and form a risk assessment grading model. A strategy construction module is configured to construct a decision logic mechanism associated with the fault and the environment, a switch time delay, an alarm and a tripping strategy according to the switch level, the automation level of the power distribution master station and the risk assessment grading model.

[0017] In a fourth aspect, the application provides an electronic device, which comprises at least one processor, at least one memory and a data bus. The processor and the memory complete mutual communication through the data bus; the memory stores program instructions that can be executed by the processor, and the processor calls the program instructions to execute the implementation method of the power distribution line fault environment adaptive treatment decision architecture in any one of the second aspect.

[0018] In a fifth aspect, the application provides a non-transitory computer readable storage medium, which stores computer instructions, and the computer instructions make the computer execute the implementation method of the power distribution line fault environment adaptive treatment decision architecture in any one of the second aspect.

[0019] Compared with the prior art, the application has at least the following beneficial effects: The application is oriented to environment adaptive power distribution network fault treatment, and according to the global collaborative optimization principles of high-risk immediate export without time delay, switch level optimization adjustment difference and alarm without delay, simultaneously considers a power distribution line topology relationship diagram, establishes a treatment decision mechanism associated with a risk level according to an environment adaptive power distribution line fault cloud edge collaborative architecture, and can effectively avoid the inherent treatment mode of traditional direct “one-size-fits-all” when a fault occurs, and realizes a compromise balance between effective fault treatment and power supply reliability. BRIEF DESCRIPTION OF DRAWINGS

[0020] The accompanying drawings described herein are used to provide a further understanding of the embodiments of the application, constitute a part of the application, and do not constitute a limitation to the embodiments of the application. In the drawings: Figure 1 It is a schematic diagram of the decision architecture in the embodiments of the application; Figure 2 It is a schematic diagram of a low-intensity power distribution network fault fire risk grading decision model in the embodiments of the application; Figure 3A schematic diagram of the fire risk grading decision model caused by the medium-intensity distribution network fault in the embodiment of the present application; Figure 4 A schematic diagram of the fire risk grading decision model caused by the high-intensity distribution network fault in the embodiment of the present application; Figure 5 A schematic diagram of the fault execution principle associated with the risk level in the embodiment of the present application; Figure 6 A schematic diagram of the switch level division, risk level dynamic query and fault adaptive execution strategy in the embodiment of the present application; Figure 7 A schematic diagram of the disposal decision logic under the action of different environments when the ground fault occurs in the third-level switch of the branch line in the embodiment of the present application; Figure 8 A schematic diagram of the single-phase ground fault current and ignition time relationship curve in the embodiment of the present application; Figure 9 A schematic diagram of the wind speed distribution statistical case associated with the historical year forest fire in the embodiment of the present application; Figure 10 A schematic diagram of the grade division mode of the wind speed, moisture content and rainfall discretization in the embodiment of the present application. DETAILED DESCRIPTION

[0021] In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments. The components of the embodiments of the present application described and shown in the drawings can be arranged and designed in various different configurations.

[0022] Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the claimed present application, but only represents selected embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present application without creative labor are within the scope of protection of the present application.

[0023] It should be noted that: similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings.

[0024] In the description of the embodiments of the present application, "a plurality of" represents at least 2.

[0025] To avoid the traditional "one-size-fits-all" approach of directly tripping circuit breakers based on preset logic when power distribution line faults occur, this invention aims for more intelligent and scientific fault decision-making. It innovatively introduces the combined effects of external factors such as line corridor and meteorological environment to achieve adaptive and differentiated fault handling, rather than relying solely on preset fixed logic for a "one-size-fits-all" approach. Ultimately, this makes the adaptive fault decision-making scheme for distribution networks that considers meteorological factors feasible to implement, and also enables accurate, differentiated, and rapid identification and effective handling of different types of faults under the influence of different meteorological factors.

[0026] Example 1: This example provides an adaptive decision-making architecture for handling power distribution line fault environments, such as... Figure 1 As shown, the decision-making framework for handling this situation includes: First Internet of Things Terminal ( Figure 1 The CPU container in Zone I is used to collect electrical quantities in real time and determine the fault type and intensity based on the detection criteria for short circuits and grounding faults; it is also used to trigger the collection of the first meteorological element during fault assessment, and to match meteorological data and fault data according to timestamps, and to perform immediate handling of the corresponding faults through a preset fault adaptive handling decision table; the first distribution master station ( Figure 1 The first distribution master station (located in Zone I) is used to acquire electrical quantities, first meteorological elements, and fault handling results based on the fault adaptive handling decision table, and transmit them to the second distribution master station; it is also used to receive the strategy table issued by the second distribution master station and issue the preset strategy table to the first IoT terminal. The second distribution master station ( Figure 1 The main station of distribution zone IV in the first IoT terminal is used to acquire the second meteorological elements uploaded by the second IoT terminal and send the strategy table generated by the second meteorological elements uploaded by the first IoT terminal to the first distribution main station. The second IoT terminal ( Figure 1 The CPU container in zone IV is used to acquire the second meteorological element.

[0027] Optionally, the above-mentioned fault types include single-phase ground faults and short-circuit faults; among which, the fault intensity of a single-phase ground fault is determined in the following way: ,in: ; In the formula, The fault intensity represents the fault intensity of a single-phase ground fault, which is the absolute value of the zero-sequence current sequence after one cycle of the fault through Fourier decomposition. This represents the nth sampled value of the zero-sequence current of one cycle; The amplitude of the kth harmonic component corresponding to the zero-sequence current; This represents the length of the 1 / 2 Hz sequence, corresponding to a sampling rate of 6.4 kHz. At 128 and 12.8 kHz 256; For the imaginary part of the operator; For frequency operators, .

[0028] The fault intensity of the aforementioned short-circuit fault is determined in the following manner: ,in: ; In the formula, Represents the electrical intensity of a short-circuit fault, which is the maximum absolute value of the three-phase current Fourier decomposition base value after one cycle of the fault through Fourier decomposition. , and These correspond to the amplitudes of the kth harmonic components of the three-phase currents A, B, and C, respectively. This represents the length of the 1 / 2 Hz sequence, corresponding to a sampling rate of 6.4 kHz. At 128 and 12.8 kHz 256; For the imaginary part of the operator; For frequency operators, ; , and These correspond to the nth sampled value of the three-phase currents A, B, and C within one cycle.

[0029] Specifically, the fault type can be determined using current methods, which will not be elaborated here; the fault intensity of the single-phase ground fault and the fault intensity of the short-circuit fault mentioned above are the electrical intensities calculated using the above formula. In practical implementation, the electrical intensities can be divided into low intensity, medium intensity, and high intensity, see [reference needed]. Figure 2 , Figure 3 , Figure 4 The calculated values ​​can be divided into intervals, and the corresponding electrical strength can be obtained randomly. Figure 2 A decision-making model for classifying the risk of fire caused by low-intensity distribution network faults. Figure 3 A decision-making model for classifying the risk of fire caused by medium-intensity distribution network faults. Figure 4 A decision-making model for classifying the risk of fire caused by high-intensity distribution network faults.

[0030] The aforementioned immediate handling of corresponding faults may include: The switch hierarchy is determined based on the main lines, branch lines, and the coordination relationships of key sections, and the switch locations are then determined. The switch hierarchy can be divided according to the following... Figure 6 Perform in the form shown, see Figure 6 The system can be divided into three levels based on the extension of the main line and branch lines. For example, the main line is classified as level one, the main line after its first branch is classified as level two, and the branch line after its second branch is classified as level three.Figure 6 The document also demonstrates the risk level query for corresponding level switches and the adaptive execution strategy for switches.

[0031] Specifically, immediate response may also include:

[0032] Based on the collected electrical quantities and primary meteorological elements, the system matches the associated risk levels and action logic using the fault adaptive handling decision table, and completes the fault adaptive handling based on the matching results.

[0033] The adaptive fault handling decision table is shown in Table 1.

[0034] Table 1 Query Fault Adaptive Handling Decision Table

[0035]

[0036] Based on Table 1 above, with Figure 7 For example, when a fault occurs at the third-level switch of a branch line, the three switches at the branch head 1-2, branch head 1-1, and main trunk section 1 respectively collect electrical signals such as voltage and current, and meteorological elements such as vegetation moisture content, wind speed, and rainfall. Then, based on... Figure 2 , Figure 3 , Figure 4 The fault decision logic for distribution lines under different intensities is implemented to optimize risk classification considering automation level and switch level, match alarm and tripping modes, and set differential delay.

[0037] Example 2: This application provides an implementation method for an adaptive decision-making architecture for handling power distribution line fault environments. The implementation method includes the following specific steps: Based on the fault type, the line corridor between the first and second distribution master stations, the first meteorological element, and the second meteorological element, a fault ignition and combustion mechanism is established, and a risk assessment and grading model is formed; the above risk assessment and grading model is as follows:

[0038] In the formula: The probability of a fire is closely related to wind speed and rainfall. The probability of ignition due to a short circuit fault is affected by the moisture content of combustibles on the vegetation surface. Corresponding to the probability of short-circuit fault occurrence, the three-phase current is collected based on the overcurrent detection algorithm to determine whether multi-phase overcurrent has occurred. If it has occurred, it means that a short-circuit fault has occurred, and this index is set to 1; otherwise, it is set to 0. The probability of a ground fault igniting is mainly affected by the moisture content of trees and vegetation. Corresponding to the probability of ground fault occurrence, the system's zero-sequence voltage and zero-sequence current are collected based on algorithms such as the first half-wave and phase asymmetry to determine the phase polarity. If the directions are opposite, a ground fault has occurred, and this indicator is set to 1; otherwise, it is set to 0. The fault execution principles associated with the risk level are detailed in [link to relevant documentation]. Figure 5 The execution and handling logic associated with risk level is as follows: 1. Adaptively select alarm or tripping strategy according to risk level; 2. Select delay based on the principle of "reliable power supply + switch characteristics" according to switch level; 3. According to fire protection section, upgrade the handling according to the principle of "nearest and highest", with no delay for high risk.

[0039] While the aforementioned model can quantify the risk posed by a failure, it is difficult to use directly in engineering applications. Therefore, this invention provides an engineering modification to the model, see [link to relevant documentation]. Figure 8 , Figure 9 , Figure 10 Specifically, this refers to: fault intensity combined with attached... Figure 8 The fault intensity is divided into three levels: within 0.4A, 0.4-1A, and above 1A; vegetation moisture content is combined with attached... Figure 10 Defined into three levels: [0,30%], (30%,45%], and (45%,100%); wind speed is also combined with the attached... Figure 9 Statistical examples of wind speed distribution associated with wildfires over the years are used to classify wind speeds into three levels: [0, 3.3 m / s], (3.3 m / s, 10.7 m / s], and (10.7 m / s, +00). Based on this, the definitions are as follows (see appendix). Figure 2 Appendix Figure 3 and attached Figure 4 A risk level table for three different fault intensities under the influence of different meteorological factors is provided so that electrical and environmental information can be collected by the power distribution automation terminal and then the table can be consulted for execution.

[0040] Optionally, the above implementation method may further include:

[0041] Based on the switch hierarchy, the automation level of the distribution master station, and the risk assessment and classification model, a decision logic mechanism, switch delay, alarm and tripping strategies related to faults and the environment are constructed.

[0042] The switch hierarchy is shown in the appendix. Figure 6 Automation levels can be distinguished by whether the switch has the ability to detect and exit faults; specifically, the decision logic mechanism, switch delay, alarm and trip strategies associated with faults and environment are shown in Table 2 below.

[0043] Table 2

[0044] Table 2 describes the specific details of the division of each switch level, risk level, action logic, and delay logic. In summary, this embodiment is guided by environmentally adaptive distribution network fault handling. It follows the global collaborative optimization principles of high-risk immediate exit without delay, optimized adjustment of level based on switch level, and alarms without delay. It simultaneously considers the distribution line topology diagram and establishes a risk level-related handling decision mechanism based on the environmentally adaptive distribution line fault cloud-edge collaborative architecture. This can effectively avoid the traditional "one-size-fits-all" handling mode of directly dealing with faults and achieve a compromise between effective fault handling and reliable power supply.

[0045] Example 3: This application provides an implementation system for an adaptive decision-making architecture for handling power distribution line fault environments, used to execute an implementation method for an adaptive decision-making architecture for handling power distribution line fault environments according to Example 2, including: The model building module is used to establish the mechanism of fault ignition and combustion based on fault type, line channel between the first and second distribution master stations, first meteorological element, and second meteorological element, and to form a risk assessment and classification model. The strategy establishment module is used to construct decision logic mechanisms, switch delays, alarms, and tripping strategies related to faults and the environment based on switch levels, the automation level of the distribution master station, and risk assessment and classification models.

[0046] Example 4: This application provides an electronic device, including: at least one processor, at least one memory, and a data bus; In this system, the processor and memory communicate with each other via a data bus; the memory stores program instructions that can be executed by the processor, and the processor calls the program instructions to execute an implementation method of a power distribution line fault environment adaptive handling decision architecture as described in Example 2.

[0047] Example 5: This application provides a non-transitory computer-readable storage medium that stores computer instructions, which cause the computer to execute an implementation method of the adaptive handling decision architecture for power distribution line fault environments according to Example 2.

[0048] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0049] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0050] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0051] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0052] Those skilled in the art will understand that all or part of the steps in the above facts and methods can be implemented by a program instructing related hardware. The program or the program described therein can be stored in a computer-readable storage medium. When the program is executed, it includes the following steps: at this time, the corresponding method steps are introduced. The storage medium can be ROM / RAM, magnetic disk, optical disk, etc.

[0053] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. An adaptive decision-making architecture for handling power distribution line fault environments, characterized in that, The decision-making framework for this action includes: The first IoT terminal is used to collect electrical quantities in real time and to determine the fault type and fault intensity based on the detection criteria of short circuit and ground fault; it is also used to trigger the collection of the first meteorological element during fault assessment, and to match the meteorological data and fault data according to the timestamp, and to handle the corresponding fault in real time through the preset fault adaptive handling decision table. The first power distribution master station is used to acquire electrical quantities, first meteorological elements, and fault handling results based on the fault adaptive handling decision table, and transmit them to the second power distribution master station; it is also used to receive the strategy table issued by the second power distribution master station and issue the preset strategy table to the first Internet of Things terminal. The second power distribution master station is used to acquire the second meteorological elements uploaded by the second IoT terminal and send the strategy table generated by the second meteorological elements uploaded by the first IoT terminal to the first power distribution master station. The second IoT terminal is used to acquire the second meteorological element.

2. The adaptive decision-making architecture for handling power distribution line fault environments according to claim 1, characterized in that, Immediate handling of the corresponding faults, specifically: Based on the main lines and branch lines, as well as the coordination relationship of key sections, the switch hierarchy is divided and the switch locations are determined. Based on the collected electrical quantities and primary meteorological elements, the system matches the associated risk levels and action logic using the fault adaptive handling decision table, and completes the fault adaptive handling based on the matching results.

3. The adaptive decision-making architecture for handling power distribution line fault environments according to claim 1, characterized in that, The fault types include single-phase ground faults and short-circuit faults; wherein, the fault intensity of a single-phase ground fault is determined by the following method: ,in: ； In the formula, The fault intensity represents the fault intensity of a single-phase ground fault, which is the absolute value of the zero-sequence current sequence after one cycle of the fault through Fourier decomposition. This represents the nth sampled value of the zero-sequence current of one cycle; The amplitude of the kth harmonic component corresponding to the zero-sequence current; This represents the length of the 1 / 2 Hz sequence, corresponding to a sampling rate of 6.4 kHz. At 128 and 12.8 kHz 256; For the imaginary part of the operator; For frequency operators, .

4. The adaptive decision-making architecture for handling power distribution line fault environments according to claim 3, characterized in that, The fault strength of the short-circuit fault is determined by the following method: ,in: ； In the formula, Represents the electrical intensity of a short-circuit fault, which is the maximum absolute value of the three-phase current Fourier decomposition base value after one cycle of the fault through Fourier decomposition. , and These correspond to the amplitudes of the kth harmonic components of the three-phase currents A, B, and C, respectively. This represents the length of the 1 / 2 Hz sequence, corresponding to a sampling rate of 6.4 kHz. At 128 and 12.8 kHz 256; For the imaginary part of the operator; For frequency operators, ; , and These correspond to the nth sampled value of the three-phase currents A, B, and C within one cycle.

5. An implementation method of the adaptive decision-making architecture for handling power distribution line fault environments according to any one of claims 1-4, characterized in that, The implementation method includes the following specific steps: Based on the fault type, the line corridor between the first and second distribution master stations, the first meteorological element, and the second meteorological element, a fault ignition and combustion mechanism is established, and a risk assessment and grading model is formed; the mechanism specifically includes: Based on the risk level, adaptively select alarm or tripping strategies; The delay is selected based on the switching level and the principles of reliable power supply and switching characteristics. Based on the fire prevention zone, the response level is raised to the nearest and highest level, with no delays for high-risk areas.

6. The implementation method of the adaptive decision-making architecture for handling power distribution line fault environments according to claim 5, characterized in that, The implementation method further includes: Based on the switch hierarchy, the automation level of the distribution master station, and the risk assessment and classification model, a decision logic mechanism, switch delay, alarm and tripping strategies related to faults and the environment are constructed.

7. The implementation method of the adaptive decision-making architecture for handling power distribution line fault environments according to claim 5, characterized in that, The risk assessment and grading model is as follows: ； In the formula, Corresponding probability of fire development; The probability of ignition corresponding to a short-circuit fault; The probability of a corresponding short-circuit fault occurring; The probability of ignition due to a corresponding ground fault; Corresponding to the probability of grounding fault occurrence, This represents the overall probability of occurrence.

8. An implementation system for an adaptive decision-making architecture for handling power distribution line fault environments, characterized in that, include: The model building module is used to establish the mechanism of fault ignition and combustion based on fault type, line channel between the first and second distribution master stations, first meteorological element, and second meteorological element, and to form a risk assessment and classification model. The strategy establishment module is used to construct decision logic mechanisms, switch delays, alarms, and tripping strategies related to faults and the environment based on switch levels, the automation level of the distribution master station, and risk assessment and classification models.

9. An electronic device, characterized in that, include: At least one processor, at least one memory, and a data bus; The processor and the memory communicate with each other via the data bus. The memory stores program instructions that can be executed by the processor, which calls the program instructions to execute an implementation method of a power distribution line fault environment adaptive handling decision architecture as described in any one of claims 5-7.

10. A non-transitory computer-readable storage medium, characterized in that, The non-transitory computer-readable storage medium stores computer instructions that cause the computer to execute the implementation method of the adaptive handling decision architecture for power distribution line fault environments according to any one of claims 5-7.

Images