Distribution network risk tracing method, system, equipment and medium

Abstract

The invention discloses a distribution network risk traceability method, system and device and a medium. The method comprises the steps of obtaining measurement data of a distribution network before and after a risk; encoding the measurement data of the power distribution network before and after the risk to obtain encoded data; and matching the coded data with the data in the classifier to obtain factors causing the risk, and the method, the system, the equipment and the medium can realize risk traceability of the power distribution network.

Description

Technical Field

[0001] The present invention belongs to the technical field of distribution network operation risk analysis, and relates to a distribution network risk tracing method, system, equipment and medium. Background Art

[0002] Under the background of new power systems, the topology of distribution networks is becoming more and more complex with the growth of system scale, and the operation modes are becoming more and more diverse. With the large-scale access of high-proportion distributed generation, new electric vehicle loads, power electronic equipment, etc., the randomness, fragility and complexity of distribution systems are more prominent. Relying solely on data-driven methods inevitably leads to unexplainable problems, which makes the confidence of prediction and decision-making consequences insufficient. How to ensure the safe operation level of distribution networks, enhance the safety and robustness of decision-making, and realize risk discovery and traceability, and the operation risk analysis of knowledge participation verification, and improve the confidence of risk discovery and traceability are the research hotspots. At the same time, in the distribution network operation verification scenario, prior knowledge data such as operation plan arrangement, control procedures, control history records and operation plans, organize and utilize this knowledge, introduce human-machine collaborative knowledge enhancement technology in the distribution network operation decision-making machine intelligence, and use human knowledge to guide the training-decision-making process of machine intelligence, which can not only realize the analysis and prediction of the operation status of the distribution network by machine intelligence, but also ensure the reliability of power supply, and realize the traceability of risks, provide support for auxiliary decision-making to quickly respond to power grid emergencies and unplanned maintenance, and ensure the safe and stable operation of the power grid. Summary of the invention

[0003] The purpose of the present invention is to overcome the shortcomings of the above-mentioned prior art and provide a distribution network risk tracing method, system, equipment and medium, which can realize the risk tracing of the distribution network.

[0004] In order to achieve the above object, the present invention adopts the following technical scheme:

[0005] In one aspect of the present invention, the distribution network risk tracing method of the present invention comprises:

[0006] Obtain measurement data of the distribution network before and after the risk;

[0007] Encoding the measured data of the distribution network before and after the risk to obtain encoded data;

[0008] The encoded data is matched with the data in the classifier to obtain the factors causing the risk.

[0009] The distribution network risk tracing method described in the present invention is further improved in that:

[0010] Furthermore, before matching the encoded data with the data in the classifier, the method also includes: constructing the classifier based on historical data of the distribution network.

[0011] Furthermore, the process of constructing the classifier based on the historical data of the distribution network is:

[0012] Build an initial classifier;

[0013] Acquire historical data of the distribution network, classify the historical data of the distribution network according to the operation risk classification of the distribution network, take the highest level risk obtained by classification as a primary risk, and take the primary risk as basic historical data;

[0014] Encoding the basic historical data to obtain encoded basic historical data;

[0015] The consequences caused by the risk are used as the primary index, and the factors causing the risk are used as the secondary index. The encoded basic historical data are filled into the preliminary classifier to obtain the final classifier.

[0016] Furthermore, the process of constructing the initial classifier is:

[0017] Obtain the operational risk classification of the distribution network;

[0018] Conduct mechanism analysis on the operation risk classification of distribution network and obtain the consequences of mechanism analysis;

[0019] Analyze the consequences according to the mechanism, and obtain the consequences caused by the risk and the factors that lead to the risk;

[0020] The consequences of risks are used as the first-level classification, and the factors that lead to risks are used as the second-level classification. The factors that lead to risks are ranked according to their importance, and the initial classifier is constructed based on this.

[0021] In a second aspect of the present invention, the distribution network risk tracing system of the present invention comprises:

[0022] An acquisition module is used to obtain the measurement data of the distribution network before and after the risk;

[0023] A first encoding module, used for encoding the measurement data of the distribution network before and after the risk to obtain encoded data;

[0024] The matching module is used to match the encoded data with the data in the classifier to obtain the factors causing the risk.

[0025] The distribution network risk tracing system of the present invention is further improved in that:

[0026] Furthermore, it also includes:

[0027] The first building module is used to build the classifier based on historical data of the power distribution network.

[0028] Furthermore, the first building block includes:

[0029] The second building module is used to build an initial classifier;

[0030] A grading module is used to obtain historical data of the distribution network, grade the historical data of the distribution network according to the operation risk classification of the distribution network, take the highest level risk obtained by grading as a primary risk, and take the primary risk as basic historical data;

[0031] A second encoding module, used for encoding the basic historical data to obtain encoded basic historical data;

[0032] The filling module is used to fill the encoded basic historical data into the preliminary classifier with the consequences caused by the risk as the primary index and the factors causing the risk as the secondary index to obtain the final classifier.

[0033] Furthermore, the second building block includes:

[0034] The third acquisition module is used to obtain the operation risk classification of the distribution network;

[0035] The analysis module is used to analyze the mechanism of the distribution network operation risk classification and obtain the mechanism analysis consequences;

[0036] A fourth acquisition module is used to analyze the consequences according to the mechanism to obtain the consequences caused by the risk and the factors causing the risk;

[0037] The third building block is used to classify the consequences of risks as the first level and the factors causing risks as the second level. The factors causing risks are ranked according to their importance and an initial classifier is constructed based on them.

[0038] In a third aspect of the present invention, the computer device described in the present invention includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the steps of the distribution network risk tracing method when executing the computer program.

[0039] In a fourth aspect of the present invention, the computer-readable storage medium of the present invention stores a computer program, and when the computer program is executed by a processor, the steps of the distribution network risk tracing method are implemented.

[0040] The present invention has the following beneficial effects:

[0041] During specific operation, the distribution network risk tracing method, system, equipment and medium described in the present invention use a classifier to obtain the factors causing the risk based on the measured data of the distribution network before and after the risk, thereby tracing the operation risk, providing theoretical and technical support for emergency plan formulation, improving the safe operation level of the distribution network, and enhancing the safety and robustness of the decision-making process. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The accompanying drawings constituting a part of the present invention are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the accompanying drawings:

[0043] Figure 1 Flowchart built for the classifier;

[0044] Figure 2 is a flow chart of the method of the present invention;

[0045] Figure 3 It is a system structure diagram of the present invention. DETAILED DESCRIPTION

[0046] 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 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.

[0047] In the description of the present invention, it should be understood that the terms “include” and “comprises” indicate the presence of described features, wholes, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or collections thereof.

[0048] It should also be understood that the terms used in the present specification are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the present specification and the appended claims, the singular forms "a", "an" and "the" are intended to include plural forms unless the context clearly indicates otherwise.

[0049] It should be further understood that the term "and / or" used in the present specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes these combinations. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in the present invention generally indicates that the associated objects are in an "or" relationship.

[0050] It should be understood that, although the terms first, second, third, etc. may be used to describe preset ranges, etc. in the embodiments of the present invention, these preset ranges should not be limited to these terms. These terms are only used to distinguish preset ranges from each other. For example, without departing from the scope of the embodiments of the present invention, the first preset range may also be referred to as the second preset range, and similarly, the second preset range may also be referred to as the first preset range.

[0051] The word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrases "if it is determined" or "if (stated condition or event) is detected" may be interpreted as "when it is determined" or "in response to determining" or "when detecting (stated condition or event)" or "in response to detecting (stated condition or event)", depending on the context.

[0052] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. The components of the embodiments of the present invention described and shown in the drawings here can usually be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0053] Various structural schematic diagrams of the embodiments disclosed in the present invention are shown in the accompanying drawings. These figures are not drawn to scale, and some details are magnified and some details may be omitted for the purpose of clear expression. The shapes of various regions and layers shown in the figures and the relative sizes and positional relationships therebetween are only exemplary, and may deviate in practice due to manufacturing tolerances or technical limitations, and those skilled in the art may additionally design regions / layers with different shapes, sizes, and relative positions according to actual needs.

[0054] Embodiment 1

[0055] refer to Figure 1 and Figure 2 The distribution network risk tracing method of the present invention comprises the following steps:

[0056] 1) Build a classifier;

[0057] 11) According to the given distribution network operation risk classification, select the first-level risk for mechanism analysis and obtain the consequences of the mechanism analysis;

[0058] 12) Based on the mechanism analysis, classify the primary risks according to the consequences caused by the risks and the factors that lead to the consequences;

[0059] 13) Classify the consequences of risks. Specifically, classify them by equipment, for example, a certain line + overload, a certain load + removal, etc.;

[0060] 14) After the equipment is classified, the consequences caused by the risk are classified according to the stability indicators. Specifically, the specific indicators are listed first and then the consequences, for example, voltage at a certain node + over-line (low), grid frequency + over-limit;

[0061] 15) Classify the consequences of risks as the first-level classification, classify the factors that cause risks as the second-level classification, and then rank the factors that cause risks according to their importance;

[0062] 16) Check whether the classification of all mechanism analysis consequences is completed. If not, go to step 13), otherwise, go to step 17) to obtain an initial classifier;

[0063] 17) Obtaining historical data, and grading the historical data according to a given distribution network operation risk, wherein the highest level of risk obtained is taken as the first-level risk, and this is used as the basic historical data for analysis;

[0064] 18) For basic historical data, according to the topology of the distribution network, obtain the measurement data before the risk and the measurement data after the risk, wherein the measurement data includes node voltage, line flow, generator output and load size;

[0065] 19) Encode the measurement data before and after the risk;

[0066] The specific numbering process is:

[0067] 191) For node voltage, node + is coded from 1 to 7, from -3% to +7%, with two percentage intervals + upper and lower limits;

[0068] 192) For line load, the line + is coded from 1 to 7, from 0% to +100%, with an interval of 20% + upper and lower limits;

[0069] 193) For generator output, the generator + is coded from 1 to 7, from 0% to +100%, with an interval of 20% + upper and lower limits;

[0070] 194) For load power, the load + is coded from 0 to 9, from -100% to +100%, with an interval of 20%;

[0071] 110) Taking the consequences caused by risks as the primary index, and the factors causing risks as the secondary index according to the risk consequences of historical data, the basic historical data are classified, and the encoded basic historical data are placed in the corresponding category in the initial classifier to obtain the final classifier.

[0072] 2) Obtain measurement data of the distribution network before and after the risk;

[0073] 3) Encode the collected measurement data before and after the risk, and then match the encoded data with the classifier to obtain the factors that cause the risk.

[0074] The process of step 3) is:

[0075] It should be noted that the present invention encodes the measurement data collected before and after the risk occurs, matches the encoded data with the historical data, finds the factors causing the risk through the secondary index, and finally verifies through mechanism analysis to achieve risk tracing. The corresponding block diagram is shown in Figure 2 As shown, the specific steps of step 3) include:

[0076] 31) Encode the data before and after the risk occurs to complete the coding of the collected data.

[0077] 32) Using the consequences of risk as an index, select historical data determined by the first-level classification and match it with the collected data.

[0078] 33) When the collected data does not match the historical data, go to step 32), otherwise, go to step 34)

[0079] 34) Use the corresponding secondary index and the risk-causing factors as the initial value of risk tracing, and use the data collected before the risk as the basis to analyze the risk consequences using the mechanism;

[0080] 35) When the risk consequence of the mechanism analysis is consistent with the measured data, it is completed, otherwise, go to step 32).

[0081] It should be noted that, based on the risk classification of distribution network operation, the present invention selects the highest risk level as the research object, sorts out the causes of the risk through mechanism analysis, and classifies according to the consequences of the risk, risk influencing factors, etc., and on this basis, brings in historical data and classifies them. When the actual risk occurs, if the highest level of risk occurs, the consequences of the risk and the collected data are matched with the historical data, which will be used as the consequences of the preliminary analysis, and finally further confirmed through mechanism analysis, so as to achieve the traceability of the risk.

[0082] Embodiment 2

[0083] refer to Figure 3 The distribution network risk tracing system of the present invention comprises:

[0084] An acquisition module is used to obtain the measurement data of the distribution network before and after the risk;

[0085] A first encoding module, used for encoding the measurement data of the distribution network before and after the risk to obtain encoded data;

[0086] The matching module is used to match the encoded data with the data in the classifier to obtain the factors causing the risk.

[0087] As an embodiment of the present invention, it also includes:

[0088] The first building module is used to build the classifier based on historical data of the power distribution network.

[0089] As an embodiment of the present invention, the first building block includes:

[0090] The second building module is used to build an initial classifier;

[0091] A grading module is used to obtain historical data of the distribution network, grade the historical data of the distribution network according to the operation risk classification of the distribution network, take the highest level risk obtained by grading as a primary risk, and take the primary risk as basic historical data;

[0092] A second encoding module, used for encoding the basic historical data to obtain encoded basic historical data;

[0093] The filling module is used to fill the encoded basic historical data into the preliminary classifier with the consequences caused by the risk as the primary index and the factors causing the risk as the secondary index to obtain the final classifier.

[0094] As an embodiment of the present invention, the second building block includes:

[0095] The third acquisition module is used to obtain the operation risk classification of the distribution network;

[0096] The analysis module is used to analyze the mechanism of the distribution network operation risk classification and obtain the mechanism analysis consequences;

[0097] A fourth acquisition module is used to analyze the consequences according to the mechanism to obtain the consequences caused by the risk and the factors causing the risk;

[0098] The third building block is used to classify the consequences of risks as the first level and the factors causing risks as the second level. The factors causing risks are ranked according to their importance and an initial classifier is constructed based on them.

[0099] The division of modules in the embodiments of the present application is schematic and is only a logical function division. There may be other division methods in actual implementation. In addition, each functional module in each embodiment of the present application may be integrated into a processor, or may exist physically separately, or two or more modules may be integrated into one module. The above-mentioned integrated modules may be implemented in the form of hardware or in the form of software functional modules.

[0100] Embodiment 3

[0101] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the distribution network risk tracing method are implemented, for example, including: obtaining the measurement data of the distribution network before and after the risk; encoding the measurement data of the distribution network before and after the risk to obtain the encoded data; matching the encoded data with the data in the classifier to obtain the factors causing the risk. Among them, the memory may include a memory, such as a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk memory, etc. The processor, the network interface, and the memory are interconnected through an internal bus, and the internal bus may be an industrial standard architecture bus, a peripheral component interconnection standard bus, an extended industrial standard architecture bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. The memory is used to store programs. Specifically, the program may include a program code, and the program code includes computer operation instructions. The memory may include a memory and a non-volatile memory, and provide instructions and data to the processor.

[0102] Embodiment 4

[0103] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the distribution network risk tracing method are implemented, for example, including: obtaining the measurement data of the distribution network before and after the risk; encoding the measurement data of the distribution network before and after the risk to obtain the encoded data; matching the encoded data with the data in the classifier to obtain the factors causing the risk. Specifically, the computer-readable storage medium includes, but is not limited to, for example, volatile memory and / or non-volatile memory. The volatile memory may include random access memory (RAM) and / or cache memory (cache), etc. The non-volatile memory may include read-only memory (ROM), hard disk, flash memory, optical disk, magnetic disk, etc.

[0104] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0105] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0106] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0107] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0108] Those skilled in the art will readily appreciate other embodiments of the present invention after considering the specification and disclosure of the invention. This application is intended to cover any variations, uses or adaptations of the present invention that follow the general principles of the present invention and include common knowledge or customary techniques in the art that are not disclosed by the present invention. The specification and examples are to be considered exemplary only, and the true scope and spirit of the present invention are indicated by the following claims.

[0109] It should be understood that the present invention is not limited to the exact construction that has been described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

[0110] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any way. Any simple modification, change and equivalent structural change made to the above embodiment based on the technical essence of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. A distribution network risk tracing method, characterized in that: include: Obtain measurement data of the distribution network before and after the risk; Encoding the measured data of the distribution network before and after the risk to obtain encoded data; The encoded data is matched with the data in the classifier to obtain the factors causing the risk.

2. The distribution network risk tracing method according to claim 1 is characterized in that: Before matching the encoded data with the data in the classifier, the method further includes: constructing the classifier based on historical data of the power distribution network.

3. The distribution network risk tracing method according to claim 2 is characterized in that: The process of constructing the classifier based on the historical data of the distribution network is as follows: Build an initial classifier; Acquire historical data of the distribution network, classify the historical data of the distribution network according to the operation risk classification of the distribution network, take the highest level risk obtained by classification as a primary risk, and take the primary risk as basic historical data; Encoding the basic historical data to obtain encoded basic historical data; The consequences caused by the risk are used as the primary index, and the factors causing the risk are used as the secondary index. The encoded basic historical data are filled into the preliminary classifier to obtain the final classifier.

4. The distribution network risk tracing method according to claim 3 is characterized in that: The process of constructing the initial classifier is as follows: Obtain the operational risk classification of the distribution network; Conduct mechanism analysis on the operation risk classification of distribution network and obtain the consequences of mechanism analysis; Analyze the consequences according to the mechanism, and obtain the consequences caused by the risk and the factors that lead to the risk; The consequences of risks are used as the first-level classification, and the factors that lead to risks are used as the second-level classification. The factors that lead to risks are ranked according to their importance, and the initial classifier is constructed based on this.

5. A distribution network risk tracing system, characterized in that: include: An acquisition module is used to obtain the measurement data of the distribution network before and after the risk; A first encoding module, used for encoding the measurement data of the distribution network before and after the risk to obtain encoded data; The matching module is used to match the encoded data with the data in the classifier to obtain the factors causing the risk.

6. The distribution network risk tracing system according to claim 5, characterized in that: Also includes: The first building module is used to build the classifier based on historical data of the power distribution network.

7. The distribution network risk tracing system according to claim 6, characterized in that: The first building block comprises: The second building module is used to build an initial classifier; A grading module is used to obtain historical data of the distribution network, grade the historical data of the distribution network according to the operation risk classification of the distribution network, take the highest level risk obtained by grading as a primary risk, and take the primary risk as basic historical data; A second encoding module, used for encoding the basic historical data to obtain encoded basic historical data; The filling module is used to fill the encoded basic historical data into the preliminary classifier with the consequences caused by the risk as the primary index and the factors causing the risk as the secondary index to obtain the final classifier.

8. The distribution network risk tracing system according to claim 7, characterized in that: The second building block comprises: The third acquisition module is used to obtain the operation risk classification of the distribution network; The analysis module is used to analyze the mechanism of the distribution network operation risk classification and obtain the mechanism analysis consequences; A fourth acquisition module is used to analyze the consequences according to the mechanism to obtain the consequences caused by the risk and the factors causing the risk; The third building block is used to classify the consequences of risks as the first level and the factors causing risks as the second level. The factors causing risks are ranked according to their importance and an initial classifier is constructed based on them.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the distribution network risk tracing method as described in any one of claims 1 to 4 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the distribution network risk tracing method as described in any one of claims 1 to 4 are implemented.

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