Source positioning method and system for chain instantaneous power utilization abnormity of power distribution network

Abstract

The invention discloses a source positioning method and system for chain instantaneous power utilization abnormity of a power distribution network, and belongs to the technical field of safe and stable power utilization, and the method comprises the steps: obtaining the electrical data and switching value of each monitoring point based on monitoring terminals disposed at a plurality of monitoring points in the power distribution network; sending the electrical data and the switching value to a cloud, so that the cloud constructs and maintains a topological structure diagram of the power distribution network according to the connection relation of the monitoring terminals; and based on the topological structure diagram and the electrical data, identifying an abnormal event and carrying out source positioning. According to the invention, through cooperation of the high-precision monitoring terminal and the cloud, the topological structure chart is constructed based on the position information of the monitoring terminal, abnormal source positioning is completed, the working efficiency of industry power utilization safety inspection is improved, and the power supply service quality is improved; and meanwhile, the industry is promoted to be evolved from the traditional steady-state electric energy quality analysis to a transient-state safety and stability analysis technology.

Description

A method and system for locating the source of interlocking instantaneous power consumption anomalies in a power distribution network Technical Field

[0001] This invention relates to a method and system for locating the source of interlocking instantaneous power consumption anomalies in a power distribution network, belonging to the field of safe and stable power supply technology, especially the field of safe and stable power supply for large industrial users in power distribution networks. Background Technology

[0002] With the advancement of new power system construction, the rapid development of high-proportion renewable energy grid connection and new loads, the frequency and impact of sudden, multi-point, short-term, and cascading anomalies in user electricity consumption are constantly increasing. Sensitive electrical equipment such as frequency converters, PLCs, and precision instruments used by large industrial users may experience operational abnormalities, equipment shutdowns, malfunctions, data loss, or process interruptions due to power supply anomalies. Problems such as power outages causing large equipment to pause, restart, or malfunction are becoming increasingly serious. Simultaneously, the mis-triggering of auxiliary protection devices or insufficient low-voltage ride-through capability leads to disorderly grid disconnection, further disrupting the power grid balance and triggering chain reactions that threaten system stability. These anomalies generally have the following characteristics: they occur frequently, involve multiple industries such as electrolytic aluminum, precision machining, electroplating and oxidation, and electronic manufacturing, and result in significant economic losses. They often have a chain reaction effect; an anomaly at one location often affects other users on the same power supply circuit and at the same voltage level, or even users on different power supply circuits and at different voltage levels, affecting the normal operation of sensitive equipment. The affected area may be within a single industrial park, several industrial parks with power supply coupling, or even cross voltage levels and extend to a wider area. The occurrence and chain reaction of anomalies can take anywhere from milliseconds to seconds from start to finish. They happen instantaneously, spread rapidly, and disappear quickly. The exact source of the anomaly is often impossible to pinpoint, leading to a breakdown in accountability among power companies, large industrial users, and management departments, resulting in escalating conflicts. Summary of the Invention

[0003] The purpose of this invention is to provide a method and system for locating the source of interlocking instantaneous power consumption anomalies in a power distribution network, enabling rapid capture of abnormal events. Through collaboration between monitoring terminals and the cloud, a monitoring terminal topology diagram is constructed to complete the source location of the abnormal events.

[0004] This promotes clear rules among power supply companies, large industrial users, and management departments, while also improving the efficiency of electricity safety inspections and the quality of power supply services in the industry.

[0005] To achieve the above objectives, the present invention is implemented using the following technical solution.

[0006] On the one hand, the present invention provides a method for locating the source of interlocking instantaneous power consumption anomalies in a power distribution network, comprising:

[0007] Based on monitoring terminals deployed at multiple monitoring points in the distribution network, electrical data and switching quantities of each monitoring point are acquired;

[0008] The electrical data and switching signals are sent to the cloud so that the cloud can construct and maintain the topology diagram of the power distribution network based on the connection relationship of each monitoring terminal;

[0009] Based on the topology diagram and electrical data, abnormal events are identified and their sources are located.

[0010] Optionally, the monitoring points include the location of the substation's distribution room feeder cabinet, sectionalizing switch, branch switch, asset demarcation point, distribution transformer, user-side switch with automatic tripping, or user-side power supply inlet.

[0011] Optionally, the monitoring terminal is configured as follows:

[0012] Voltage and current are acquired at a set sampling rate and precision, and switching quantities are acquired via interrupt.

[0013] When a change is detected in the collected voltage, current, or switching quantity, data recording is initiated based on the amount of change.

[0014] Execution time synchronization is performed to ensure the consistency of data collection time across all monitoring terminals.

[0015] It regularly uploads data to the cloud and responds to data query commands issued by the cloud.

[0016] The data information includes file information, event information, and monitoring terminal status information.

[0017] Optionally, the cloud is configured as follows:

[0018] Regularly receive data uploaded by all monitoring terminals and build a monitoring database;

[0019] Automatically construct and update the topology diagram based on the connection relationship of the monitoring terminals;

[0020] Based on the monitoring database and topology diagram, abnormal events are identified by analyzing load equipment alarms and abnormal switch displacements, and a human-machine interface is provided to manually set, confirm or eliminate suspected abnormal events.

[0021] Optionally, constructing the topology diagram of the distribution network includes a probabilistic assessment of the health status of the monitoring terminal nodes, specifically:

[0022] A multi-dimensional state vector is established for each monitoring terminal, and the multi-dimensional state vector includes at least the device state probability, the synchronization state probability, and the connection stability probability.

[0023] The components of the multidimensional state vector are standardized to obtain the standardized state vector.

[0024] The components in the standardized state vector are weighted and fused with preset weights to obtain a comprehensive health score for the monitoring terminal node.

[0025] Based on the comprehensive health score, a first probability coefficient α indicating that the monitoring terminal is in a normal state and a second probability coefficient β indicating that it is in a faulty state are calculated using a preset probability mapping function. The status of the monitoring terminal is indicated as follows: ,in, This indicates that the terminal is in a normal state. This indicates that the terminal is in a faulty state.

[0026] Optionally, the topology graph is further represented by a set of joint probability coefficients. To characterize the connection status of any two monitoring terminals with a direct connection relationship, the joint probability coefficient corresponds to four possible state combinations of the upstream and downstream terminals: both are normal, only the upstream is normal, only the downstream is normal, and both are faulty; the determination of the coefficient includes:

[0027] Extract the topology feature vector of the connecting line, wherein the topology feature vector includes at least: line length, line impedance, number of switches in the path and switch type;

[0028] Based on the topological feature vector, the line status influence factor is calculated using a preset weighting function;

[0029] By combining the first and second probability coefficients of the upstream and downstream terminals and the line status influence factor, the initial probability of the upstream and downstream terminals being in four state combinations is calculated respectively.

[0030] The initial probabilities are normalized to obtain the corresponding final joint probability coefficients, which satisfy... The connection relationship between terminal nodes is represented as follows: ,in, This indicates that both are normal. This indicates that only the upstream is normal. This indicates that only the downstream is normal. This indicates that both are faulty.

[0031] Optionally, based on the topology diagram and electrical data, identifying abnormal events and locating their sources includes:

[0032] Identify the boundary monitoring terminals in the topology diagram and use them as the starting point; calculate the abrupt change in the electrical data of each monitoring terminal and record the corresponding abrupt change time.

[0033] Construct a time chain based on the chronological order of mutation events, following the topological sequence.

[0034] Determine whether the time difference between the sudden changes of two adjacent monitoring terminals is within a preset time window. If it is, compare the difference in the maximum magnitude of the sudden change and determine that the terminal with the largest magnitude of the sudden change is the source of the anomaly.

[0035] If the time difference between the sudden change of two adjacent monitoring terminals is not within the preset time window, the monitoring terminal with the earlier sudden change time is determined to be the source of the anomaly.

[0036] Optionally, the comparison of the differences in mutation magnitude includes:

[0037] If the duration of the anomaly is less than one cycle, the maximum magnitude of the sudden change is calculated based on the instantaneous value of the voltage.

[0038] If the duration of the anomaly is greater than one cycle, the maximum magnitude of the mutation is calculated based on the effective value of the voltage.

[0039] Optionally, the mutation amount is the product of the instantaneous mutation amounts of voltage and current.

[0040] Secondly, the present invention provides a source location system for interlocking instantaneous power consumption anomalies in a power distribution network, comprising:

[0041] The data acquisition module is used to acquire electrical data and switching quantities of each monitoring point based on monitoring terminals deployed at multiple monitoring points in the distribution network;

[0042] The topology construction module is used to send the electrical data and switching quantities to the cloud, so that the cloud can construct and maintain the topology of the power distribution network based on the connection relationship of each monitoring terminal;

[0043] An abnormal event identification and location module is used to identify abnormal events and locate their sources based on the topology diagram and electrical data.

[0044] Compared with the prior art, the beneficial effects achieved by the present invention are as follows:

[0045] This invention acquires electrical-related data and switching quantities through monitoring terminals deployed in the power distribution network, achieving high-speed capture and recording capabilities for instantaneous synchronous abnormal events. Through collaboration between the terminal and the cloud, a topology diagram is constructed based on the connection relationship of each monitoring terminal, thereby completing the source location of the anomaly. This promotes the industry's evolution from traditional steady-state power quality analysis to transient safety and stability analysis technology, while improving the reliability of power supply and consumption. Attached Figure Description

[0046] Figure 1 is a schematic diagram of the source location method for interlocking instantaneous power consumption anomalies in the power distribution network provided in an embodiment of the present invention;

[0047] Figure 2 is a schematic diagram of the topology provided in an embodiment of the present invention;

[0048] Figure 3 is a schematic diagram of the abnormal event source localization process provided in an embodiment of the present invention;

[0049] Figure 4 is a schematic diagram of the source location system for interlocking instantaneous power consumption anomalies in the power distribution network provided in an embodiment of the present invention. Detailed Implementation

[0050] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present invention and the specific features in the embodiments are detailed descriptions of the technical solution of the present invention, rather than limitations thereof. In the absence of conflict, the embodiments of the present invention and the technical features in the embodiments can be combined with each other.

[0051] It should be noted that the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. Additionally, the character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0052] Example 1

[0053] This embodiment introduces a method for locating the source of interlocking instantaneous power consumption anomalies in a power distribution network, as shown in Figure 1, including the following steps:

[0054] Step S1: Based on the monitoring terminals deployed at multiple monitoring points in the distribution network, acquire the electrical data and switching quantities of each monitoring point;

[0055] In this embodiment, the monitoring terminal consists of multiple "wide-area synchronous monitoring terminals" installed in the following locations:

[0056] Feeder cabinets in the 10kV / 35kV distribution room of the substation: Depending on the required physical range, several feeder cabinets on the same busbar can be selected, or multiple feeder cabinets on multiple busbars can be used. This location can be considered the starting point of the distribution network. Installing a wide-area synchronous monitoring terminal can capture instantaneous voltage, current, and switch status changes throughout the entire feeder range.

[0057] Section switches: Section switches are key equipment in power distribution networks that divide the main lines into sections to isolate fault areas and reduce the scope of power outages. In interlocking instantaneous anomaly localization, the monitoring points at the section switches play a crucial role. Installing wide-area synchronous monitoring terminals at the section switches helps determine which power supply section the anomaly occurred in, effectively narrowing down the anomaly's scope.

[0058] Branch switches: Branch switches connect the main line and branch lines, and are used to control the power supply to the branch lines. In the localization of interlocking instantaneous anomalies, the monitoring point at the branch switch is crucial for determining the anomaly propagation path. In areas with a high concentration of large industrial users, the monitoring point at the branch switch is particularly important. Monitoring the branch switch helps identify whether the anomaly is caused by load changes in a specific branch line.

[0059] Asset demarcation point: For dedicated transformer users, it is located on the 10kV / 35kV high-voltage side of the transformer; for public transformer users, it is located on the 380V low-voltage side of the transformer. The asset demarcation point is a key location for clarifying power supply responsibility. Installing a wide-area synchronous monitoring terminal at the asset demarcation point helps to distinguish whether anomalies occur on the power company's side or the user's side.

[0060] Distribution transformers: high-voltage side and low-voltage side. If they coincide with the asset demarcation point, then repeated installation is unnecessary. Distribution transformers are key equipment connecting high-voltage and low-voltage systems. Installing wide-area synchronous monitoring terminals on both the high-voltage and low-voltage sides of the transformer allows for comprehensive monitoring of voltage, current, and switch status changes on both sides of the transformer, helping to determine whether anomalies originate within the transformer or propagate through it.

[0061] The user-side switch with automatic tripping function: This location records the operation of the user-side switch. A monitoring terminal is installed at the user-side switch to record voltage, current and switch status changes, and to determine whether the abnormality is caused by the user-side switch.

[0062] At the power supply inlet of sensitive production equipment or production lines on the user side: For sensitive electrical equipment or production lines such as frequency converters, PLCs, and precision instruments of large industrial users, monitoring terminals are installed at their power supply inlets to directly acquire changes in voltage, current, and switch status at the equipment end. Simultaneously, they communicate with the monitoring and control devices of the load equipment to obtain the current operating status of the load equipment and promptly acquire information on any abnormal operating events of the load equipment.

[0063] The monitoring terminal is configured with the following functions:

[0064] Voltage, current, and switching quantity acquisition: Voltage and current are acquired using a 100kHz sampling rate and a 0.2% amplitude error; switching quantities are acquired using an interrupt-based method. This configuration meets the high-precision requirements of instantaneous anomaly monitoring, and the interrupt-based acquisition of switching quantities ensures microsecond-level response to switch changes, avoiding missed acquisitions due to scanning.

[0065] Data recording based on changes in quantities: This includes changes in current, voltage, and switch positions. When a change is detected, data recording is automatically initiated. The recording duration is 25 cycles (0.5 seconds) before triggering and 3 seconds after triggering, ensuring a complete record of the changes before and after the anomaly occurs.

[0066] Time synchronization based on BeiDou / GPS: The time synchronization error is set to... This ensures the consistency of data collection time across all monitoring terminals.

[0067] Interaction with cloud information includes:

[0068] Scheduled uploads include: file information, event information, and terminal status information. File information includes filename, size, recording start time, and recording end time. Event information includes: voltage surges, current surges, and switch changes. Terminal status information mainly refers to the device's current operating status, with a scheduled upload cycle of 3 minutes. The system receives and responds to cloud-based data query commands. The cloud can retrieve recorded files from the terminal, specifying the time to be retrieved, and the terminal will upload the recorded file containing the specified time. This enables the cloud to comprehensively acquire data from all monitoring points based on the time of abnormal events.

[0069] Step S2: Send the electrical data and switching quantities to the cloud so that the cloud can construct and maintain the topology diagram of the power distribution network based on the connection relationship of each monitoring terminal.

[0070] The main cloud-based functionalities are configured as follows:

[0071] Receiving timed data uploads from terminals: The cloud receives timed data uploads from various terminals and establishes a complete system monitoring database, including basic information such as voltage, current, switch status, and files, providing a foundation for subsequent anomaly identification and location.

[0072] The cloud platform establishes and maintains the current topology of the monitoring terminals, constructing a complete distribution network topology based on installation location information (substation feeder cabinets, sectionalizing switches, branch switches, asset boundary points, distribution transformers, user-side switches, and sensitive equipment inlets). When system structure changes such as switch displacement are detected, the cloud platform automatically updates the topology to ensure that location analysis is based on the latest topology.

[0073] Identification and location of transient abnormal events: Identification methods include load equipment alarms and abnormal switch changes, combined with manual settings and confirmations. Load equipment alarms are determined by the user equipment's own status information to determine if the load equipment has encountered an abnormal power consumption. Abnormal switch changes refer to the tripping of switches with automatic tripping functions on the grid side or user side. The system provides a manual setting and confirmation interface, allowing maintenance personnel to manually set, confirm, and eliminate suspected abnormal events, reducing false alarm and missed alarm rates.

[0074] The aforementioned monitoring terminal establishes data interaction with the cloud via 4G wireless communication.

[0075] In this embodiment, the construction of the topology diagram is specifically as follows:

[0076] First, define the properties of the terminal node:

[0077] Self-information: Location (substation feeder cabinet, sectionalizing switch, branch switch, asset boundary point, distribution transformer, user-side switch and sensitive equipment entrance), terminal status (normal / fault), synchronization status (synchronous / asynchronous), connection status (stable / unstable).

[0078] Upper-level terminal information: connection relationship with this terminal, the length and impedance of the direct connection between the two, switch information in the path. There may be 0 upper-level terminals, or one or more, depending on the actual deployment situation.

[0079] Lower-level terminal information: connection relationship with this terminal, the length and impedance of the direct connection between the two, switch information in the path, the number of upper-level terminals may be 0, or there may be one or more, depending on the actual deployment situation.

[0080] Terminal states are represented using probability coefficients: ;

[0081] in, This indicates that the terminal is in a normal state (device, synchronization, and connection are all normal). This indicates that the terminal is in an abnormal state (any indicator is abnormal); and These are probability coefficients, satisfying... .

[0082] Secondly, calculation and as follows:

[0083] (1) Establishing a three-dimensional state vector: ;

[0084] Where s1 represents the device state probability (0-1, 0=fault, 1=normal);

[0085] s2 represents the probability of synchronous state (0-1, 0=asynchronous, 1=synchronous);

[0086] s3 represents the connection stability probability (0-1, 0 = unstable, 1 = stable);

[0087] (2) Standardization process to eliminate dimensional differences and obtain the standardized state vector:

[0088] Standardized equipment state probability ;

[0089] Standardized synchronization state probability ;

[0090] Standardized connection stability probability ;

[0091] Here, min and max are the minimum and maximum values ​​of each parameter in the historical data.

[0092] (3) Health score is calculated using a weighted fusion method:

[0093] Consider the weight of each dimension's impact on terminal health: ;

[0094] in, For terminal health, the weights must meet the following requirements. w1, w2, and w3 are given by experience and are set to 0.5, 0.4, and 0.1 respectively.

[0095] (4) Calculation of final probability coefficients

[0096] right Further transformation yields:

[0097] ;

[0098] Therefore, we can conclude that: , .

[0099] The topological graph is further analyzed using a set of joint probability coefficients. The joint probability coefficient is used to characterize the connection status of any two monitoring terminals with a direct connection relationship. The joint probability coefficient corresponds to four possible combinations of states for the upstream and downstream terminals: both are normal, only the upstream is normal, only the downstream is normal, and both are faulty. The connection relationship between terminal nodes is represented as follows: ,in, This indicates that both are normal. This indicates that only the upstream is normal. This indicates that only the downstream is normal. This indicates that both are faulty. The determination of the joint probability coefficient is as follows:

[0100] (1) Representing connectivity using topological feature vectors: ;

[0101] Where L represents the line length (km); Z represents the line impedance (km). N represents the number of switches in the path; T represents the switch type (0 = circuit breaker, 1 = disconnector, 2 = load switch).

[0102] (2) Calculation of coefficients:

[0103] Combining the probability coefficients of upstream and downstream terminal nodes , and topological feature weight function .

[0104] The weighting function is defined as: ;

[0105] Where k1 represents the line length influence coefficient (L); k2 represents the line impedance influence coefficient (Z); k3 represents the number of switches influence coefficient (N); k4 represents the switch type influence coefficient (T); k1, k2, k3, and k4 are topology feature weight coefficients, given empirically, and are respectively set to 0.4, 0.35, 0.2, and 0.05.

[0106] Initial coefficient calculation:

[0107] ;

[0108] ;

[0109] ;

[0110] ;

[0111] in, Indicates the upstream terminal. This indicates the downstream terminal.

[0112] To meet the normalization conditions Normalization is performed as follows: The final joint probability coefficients are obtained as follows:

[0113] ;

[0114] ;

[0115] ;

[0116] .

[0117] The topology diagram is shown in Figure 2. It can be automatically updated according to changes in monitoring terminal information. When the switch status changes, the terminal status changes, the terminal installation location changes, a terminal is added or removed, or the line parameters change, the system topology is updated.

[0118] Step S3: Locate the source of the abnormal event, as shown in Figure 3, which specifically includes the following steps:

[0119] Starting with the boundary monitoring terminals in the topology diagram (terminals without upstream or downstream nodes), compare them pairwise with their associated upstream or downstream terminals to determine the order in which abrupt changes occur, identifying which abrupt change of the same magnitude occurs first. Here, the abrupt change refers to the product of the instantaneous changes in voltage and current values.

[0120] Voltage fluctuation: ;

[0121] Current mutation: ;

[0122] The product of voltage change and current change: ;

[0123] The relative magnitude of the product of voltage and current mutations ;

[0124] Where u and i are the instantaneous values ​​of voltage and current, respectively; U and I represent the effective values ​​of voltage and current, respectively; n represents the current instantaneous sampling value number; and T represents a cycle of 20ms.

[0125] The mutation limit is set as follows: , The value is 0.1. and For rated voltage and rated current. The moment when the mutation occurs is the moment when the mutation takes place, because Since the values ​​are discrete, linear interpolation is used to find the specific time of occurrence.

[0126] Establish a timeline based on the chronological order of mutations across all terminals in the system: ,satisfy In the entire system, the earlier the mutation occurs at a terminal, the closer it is to the source of the anomaly, meaning that terminal is identified as the source of the anomaly.

[0127] If the time difference between the two terminal abrupt changes is within 10µs, the difference in the magnitude of the abrupt change is compared. This is divided into two cases: abrupt changes lasting less than one cycle, and abrupt changes lasting one cycle or more. The former is determined based on the instantaneous voltage value, while the latter is determined based on the full-wave Fourier transform value (RMS value) of the voltage.

[0128] Maximum mutation magnitude: ;

[0129] Where: n represents the current sampling time; T is one cycle (20ms); The moment the mutation occurred; This is the abnormal end time, with a maximum value of [value missing]. ;

[0130] When the anomaly lasts for one week, Take the instantaneous voltage value u. When the duration of the anomaly is greater than one cycle, Take the effective value U of the voltage. The terminal with the largest amplitude of the sudden change is closer to the source of the anomaly, and is therefore determined to be the source of the anomaly.

[0131] Example 2

[0132] Based on the same inventive concept as Embodiment 1, this embodiment introduces a source location system for interlocking instantaneous power consumption anomalies in a power distribution network, comprising:

[0133] The data acquisition module is used to acquire electrical data and switching quantities of each monitoring point based on monitoring terminals deployed at multiple monitoring points in the distribution network;

[0134] The topology construction module is used to send the electrical data and switching quantities to the cloud, so that the cloud can construct and maintain the topology of the power distribution network based on the connection relationship of each monitoring terminal;

[0135] An abnormal event identification and location module is used to identify abnormal events and locate their sources based on the topology diagram and electrical data.

[0136] In practical applications, the system is manifested as shown in Figure 4. It uses multiple wide-area synchronous monitoring terminals to monitor anomalies such as load impact (high-power equipment impact), grid-side and load-side faults (such as short-circuit faults) and disturbances (such as induced overvoltage, wind and solar power fluctuations, and switching transients) in the power grid. It interacts with the cloud system for instantaneous anomaly location via 4G to realize real-time judgment and location of the source of abnormal events in the distribution network.

[0137] In summary, this invention, through a high-precision monitoring terminal, achieves high-speed capture and recording of abnormal events at the microsecond level. By collaborating with the cloud, it constructs a topology map based on the monitoring terminal's location information, enabling source localization of anomalies. This improves the efficiency of power safety inspections in the industry and enhances the quality of power supply services. It also drives the industry's evolution from traditional steady-state power quality analysis to transient safety and stability analysis technology.

[0138] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention 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.

[0139] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. 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, create means for implementing the functions specified in one or more blocks of the flowchart illustrations and / or one or more blocks of the block diagrams.

[0140] 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 that implement the functions specified in one or more flowcharts and / or one or more block diagrams.

[0141] These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, such that the instructions, which execute on the computer or other programmable apparatus, provide steps for implementing the functions specified in one or more flowcharts and / or one or more block diagrams.

[0142] The embodiments of the present invention have been described above with reference to the accompanying drawings. However, the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of the present invention without departing from the spirit and scope of the claims. All of these forms are within the protection scope of the present invention.

Claims

1. A method for locating the source of interlocking instantaneous power consumption anomalies in a power distribution network, characterized in that, include: Based on monitoring terminals deployed at multiple monitoring points in the distribution network, electrical data and switching quantities of each monitoring point are acquired; The electrical data and switching signals are sent to the cloud so that the cloud can construct and maintain a topology diagram of the power distribution network based on the connection relationship of each monitoring terminal; based on the topology diagram and electrical data, abnormal events are identified and their sources are located.

2. The method for locating the source of interlocking instantaneous power consumption anomalies in a power distribution network according to claim 1, characterized in that, The monitoring points include the substation's distribution room feeder cabinets, sectionalizing switches, branch switches, asset demarcation points, distribution transformers, user-side switches with automatic tripping, or the location of user-side power supply inlets.

3. The method for locating the source of interlocking instantaneous power consumption anomalies in a power distribution network according to claim 1, characterized in that, The monitoring terminal is configured to: acquire voltage and current at a set sampling rate and precision, and acquire switching quantities in an interrupt manner; when a change in the acquired voltage, current, or switching quantity is detected, data recording is initiated based on the change; perform time synchronization to ensure the time consistency of data acquired by each monitoring terminal; periodically send data information to the cloud and respond to data recording query commands issued by the cloud; wherein, the data information includes file information, event information, and monitoring terminal status information.

4. The method for locating the source of interlocking instantaneous power consumption anomalies in a power distribution network according to claim 3, characterized in that, The cloud is configured to: periodically receive data uploaded by all monitoring terminals and build a monitoring database; automatically build and update a topology diagram based on the connection relationship of the monitoring terminals; and identify abnormal events by analyzing load equipment alarms and abnormal switch displacements based on the monitoring database and topology diagram, and provide a human-machine interface for manually setting, confirming or eliminating suspected abnormal events.

5. The method for locating the source of interlocking instantaneous power consumption anomalies in a power distribution network according to claim 4, characterized in that, Constructing the topology diagram of the distribution network includes a probabilistic assessment of the health status of monitoring terminal nodes. Specifically, a multi-dimensional state vector is established for each monitoring terminal, which includes at least the device state probability, synchronization state probability, and connection stability probability. The components of the multidimensional state vector are standardized to obtain a standardized state vector; the components of the standardized state vector are weighted and fused with preset weights to obtain a comprehensive health score of the monitoring terminal node. Based on the comprehensive health score, a first probability coefficient α indicating that the monitoring terminal is in a normal state and a second probability coefficient β indicating that it is in a faulty state are calculated using a preset probability mapping function. The status of the monitoring terminal is indicated as follows: ,in, This indicates that the terminal is in a normal state. This indicates that the terminal is in a faulty state.

6. The method for locating the source of interlocking instantaneous power consumption anomalies in a power distribution network according to claim 5, characterized in that, The topology graph is further analyzed using a set of joint probability coefficients. The joint probability coefficient is used to characterize the connection status of any two monitoring terminals with a direct connection relationship. The joint probability coefficient corresponds to the four state combination probabilities of the upstream and downstream terminals: both are normal, only the upstream is normal, only the downstream is normal, and both are faulty. The determination of the coefficients includes: extracting the topological feature vector of the connecting line, wherein the topological feature vector includes at least: line length, line impedance, number of switches in the path, and switch type; calculating the line state influence factor based on the topological feature vector using a preset weighting function; calculating the initial probability of the upstream and downstream terminals being in four state combinations by combining the first and second probability coefficients of the upstream and downstream terminals and the line state influence factor; normalizing the initial probabilities to obtain the corresponding final joint probability coefficients, and satisfying the following conditions: The connection relationship between terminal nodes is represented as follows: ,in, This indicates that both are normal. This indicates that only the upstream is normal. This indicates that only the downstream is normal. This indicates that both are faulty.

7. The method for locating the source of interlocking instantaneous power consumption anomalies in a power distribution network according to claim 6, characterized in that, Based on the topology diagram and electrical data, abnormal events are identified and their sources are located, including: identifying the boundary monitoring terminals in the topology diagram as starting points, calculating the mutation amount of the electrical data of each monitoring terminal and recording its corresponding mutation time; constructing a time chain according to the topological order and the chronological relationship of the mutation times; determining whether the mutation time difference between two adjacent monitoring terminals is within a preset time window; if so, comparing the difference in the maximum mutation amount, and determining the terminal with the larger maximum mutation amount as the source of the abnormality; if the mutation time difference between two adjacent monitoring terminals is not within the preset time window, determining the monitoring terminal with the earlier mutation time as the source of the abnormality.

8. The method for locating the source of interlocking instantaneous power consumption anomalies in a power distribution network according to claim 7, characterized in that, The comparison of the maximum magnitude of the mutation includes: if the duration of the abnormality is less than 1 cycle, the maximum magnitude of the mutation is calculated based on the instantaneous value of the voltage; if the duration of the abnormality is greater than 1 cycle, the maximum magnitude of the mutation is calculated based on the effective value of the voltage.

9. The method for locating the source of interlocking instantaneous power consumption anomalies in a power distribution network according to claim 8, characterized in that, The mutation amount is the product of the instantaneous mutation amounts of voltage and current.

10. A source location system for interlocking instantaneous power consumption anomalies in a power distribution network, characterized in that, include: The data acquisition module is used to acquire electrical data and switching quantities of each monitoring point based on monitoring terminals deployed at multiple monitoring points in the distribution network; The topology map construction module is used to send the electrical data and switch quantities to the cloud so that the cloud can construct and maintain the topology map of the distribution network based on the connection relationship of each monitoring terminal; the abnormal event identification and location module is used to identify abnormal events and locate their sources based on the topology map and electrical data.

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