Ring main unit group operation state cooperative monitoring and analysis system

Abstract

The invention discloses a ring main unit group operation state cooperative monitoring and analysis system, and relates to the field of power system automatic monitoring. The system comprises a data acquisition module, a local processing module, a collaborative analysis module and an interaction module. The data acquisition module realizes distributed parameter acquisition through multiple sensors and synchronous control; the local processing module executes data preprocessing and dynamic feature extraction; the collaborative analysis module generates a regulation and control strategy through data fusion and state evaluation; and the interaction module supports visual display and remote control. The method breaks through the limitation of single-point monitoring, improves the real-time performance, accuracy and collaboration of the operation state monitoring of the ring main unit group through multi-node collaborative analysis, localization efficient processing and a closed-loop operation and maintenance mechanism, shortens the fault response time, and is suitable for the intelligent operation and maintenance of the distributed ring main unit group.

Description

Technical Field

[0001] The present invention relates to the technical field of power system automation monitoring, and in particular to a collaborative monitoring and analysis system for the operating status of a ring main unit group, which is suitable for real-time status perception, collaborative analysis and intelligent operation and maintenance of a distributed ring main unit cluster. Background Art

[0002] Ring main unit (RMU) is a key device in power distribution networks and is widely used in urban distribution networks, industrial parks, and other scenarios. Its operating status directly affects power supply reliability. Existing RMU monitoring technology has the following limitations:

[0003] Single-point monitoring: Traditional systems primarily monitor a single ring main unit independently, lacking the ability to collaboratively analyze a cluster of ring main units (multiple nodes). This makes it difficult to reflect the overall operating status of the cluster and the correlation between nodes.

[0004] Low data processing efficiency: Raw monitoring data (such as current, temperature, and partial discharge signals) is directly uploaded to the cloud for processing, resulting in high network transmission pressure, poor real-time performance, and susceptibility to communication delays.

[0005] Insufficiently targeted feature extraction: The existing system extracts single-dimensional features of the electrical, environmental, and mechanical features of the ring main unit, and does not dynamically adjust the extraction strategy based on the operating characteristics of the equipment, resulting in low anomaly identification accuracy.

[0006] Disconnection between interaction and control: There is a lack of linkage between the display of monitoring results and the issuance of remote control commands, making it difficult for operation and maintenance personnel to quickly respond to abnormal conditions, thus extending troubleshooting time.

[0007] To this end, the present invention proposes a collaborative monitoring and analysis system for the operating status of a ring main unit group, which solves the above technical problems through distributed data collection, localized processing, multi-node collaborative analysis and interactive control. Summary of the Invention

[0008] The present invention aims to provide a system for collaboratively monitoring and analyzing the operating status of a ring main unit group, achieving the following objectives:

[0009] Realize distributed data collection and time-space synchronization of multiple ring main unit nodes;

[0010] Improve data processing efficiency and reduce redundant data transmission through localized preprocessing;

[0011] Combine the characteristics of the ring main unit to extract multi-dimensional features to improve the accuracy of anomaly identification and risk prediction;

[0012] Build a closed loop of "monitoring-analysis-decision-control" to support remote collaborative operation and maintenance.

[0013] In order to solve the technical defects pointed out in the background technology, the technical solution adopted by the present invention is:

[0014] A ring main unit group operation status collaborative monitoring and analysis system, comprising:

[0015] The data acquisition module is used to collect the operating status parameters of each ring main unit in the ring main unit group and perform distributed data acquisition of multiple ring main unit nodes;

[0016] The local processing module performs local processing on the received raw collected data and extracts characteristic information related to the operating status of the ring main unit;

[0017] The collaborative analysis module receives the characteristic information output by each local processing module and evaluates the overall operating status of the ring main unit group, identifies anomalies, and predicts risks through the collaborative integration and analysis of multi-node data;

[0018] The interactive module is used to display the output results of the collaborative analysis module, support command interaction with the system, and remotely monitor and control the operating status of the ring network cabinet group.

[0019] As a further optional solution of the collaborative monitoring and analysis system for the operation status of the ring main unit group, the data acquisition module includes a variety of sensors, node communication components and synchronization control units deployed in each ring main unit;

[0020] The various sensors are respectively arranged at the electrical connection parts, the interior of the cabinet and the operating mechanism of the ring main unit, and are used to collect current, voltage, partial discharge signal, cabinet temperature, humidity and mechanical operation stroke parameters;

[0021] The synchronization control unit realizes the spatiotemporal alignment of the data collected by the nodes of the multi-ring mainframe through a preset timestamp synchronization mechanism;

[0022] The node communication component transmits the collected data to the local processing module.

[0023] As a further optional solution for the collaborative monitoring and analysis system of the operating status of the ring network cabinet group, the local processing module includes an embedded processing unit, which receives the original data transmitted by the data acquisition module, performs preprocessing operations of noise reduction, filtering and outlier removal on the original data, and extracts feature quantities related to the operating status of the ring network cabinet based on preset feature dimensions, and the feature quantities include timing features, amplitude features and mutation features; the local processing module transmits the extracted feature information to the collaborative analysis module.

[0024] As a further optional solution of the collaborative monitoring and analysis system for the operation status of the ring main unit group, the preset feature dimension extracts feature quantities related to the operation status of the ring main unit, specifically including:

[0025] The electrical characteristic dimension extracts the fluctuation range of the effective current value, the voltage distortion rate, the pulse amplitude and the time domain distribution characteristics of the partial discharge signal;

[0026] Environmental feature dimension: extract the rate of change of cabinet temperature, the correlation coefficient between humidity and temperature, and the distribution uniformity of the cabinet surface temperature field;

[0027] Mechanical feature dimension, extracting the operating mechanism action time, slope change of stroke displacement, and main frequency component characteristics of mechanical vibration signal;

[0028] The extraction of the feature quantity sets a dynamic threshold based on the rated parameters and historical operating data of the ring network cabinet. When the collected data exceeds the threshold range, the feature extraction accuracy of the corresponding dimension is automatically enhanced.

[0029] As a further optional solution of the collaborative monitoring and analysis system for the operation status of the ring main unit group, the collaborative analysis module includes:

[0030] The data fusion unit is used to receive the feature information output by each local processing module, and cross-validate and eliminate redundancy of the feature quantities of multiple ring main unit nodes through the spatiotemporal correlation algorithm to form a joint feature set of the ring main unit group;

[0031] The status assessment unit is used to build an operating status assessment model based on the joint feature set, identify abnormal conditions by comparing with preset health benchmark values, and train a risk prediction sub-model based on historical fault data;

[0032] The decision generation unit is used to generate the corresponding collaborative control strategy according to the status assessment results, and transmit the analysis results and control strategy to the interaction module.

[0033] As a further optional solution of the ring main unit group operation status collaborative monitoring and analysis system, the data fusion unit includes:

[0034] The local fusion submodule performs weighted fusion on the multi-dimensional feature quantities of a single ring main unit and dynamically assigns weight coefficients based on the historical contribution of each feature quantity;

[0035] The global fusion submodule uses a spatiotemporal correlation algorithm to perform correlation analysis on the local fusion results of multiple ring main unit nodes, eliminates redundant features through time series alignment and spatial topology mapping, and uses the 3σ criterion to identify and correct abnormal fusion values.

[0036] The joint feature set output by the data fusion unit includes single-node state features and cross-node correlation features, wherein the cross-node correlation features include load fluctuation correlation and environmental parameter gradient change features of adjacent ring network cabinets.

[0037] As a further optional solution of the ring main unit group operation status collaborative monitoring and analysis system, the status evaluation unit includes:

[0038] The health benchmark library stores the rated operating parameters, historical health status data, and typical fault characteristic maps of the ring main unit group as a reference for status assessment;

[0039] The multi-dimensional evaluation model uses the joint feature set output by the data fusion unit as input. By calculating the difference between the feature quantity and the health baseline value and performing trend fitting, it generates the health index of a single ring main unit and the overall collaborative operation coefficient of the ring main unit group. The abnormality recognition logic sets a dynamic deviation threshold, marks the feature quantity that exceeds the threshold range, and associates it with the corresponding fault mode label.

[0040] The risk prediction model, based on time series feature sequences and historical failure cases, uses a trend extrapolation algorithm to predict the failure risk level within a preset time period in the future and outputs three levels of risk warnings: high, medium, and low.

[0041] As a further optional solution of the ring main unit group operation status collaborative monitoring and analysis system, the interaction module includes:

[0042] The visual display unit uses the RMU group topology diagram as the basic interface, hierarchically displays the health index of a single RMU, the cluster collaborative operation coefficient, and abnormal status marks, and supports correlation query of historical data trend curves and fault cases;

[0043] The command input unit provides a parameter configuration interface and control command options, and receives remote operation commands input by the user through an authority verification mechanism;

[0044] The two-way communication unit establishes a real-time data link with the collaborative analysis module, pushes the collaborative analysis results to the visual display unit, and forwards the control instructions that have been verified to the collaborative analysis module and the local processing module of the corresponding ring network cabinet.

[0045] A method for collaboratively monitoring and analyzing the operating status of a ring main unit group comprises the following steps:

[0046] Data collection step: used to collect the operating status parameters of each ring main unit in the ring main unit group and perform distributed data acquisition of multiple ring main unit nodes;

[0047] Local processing step: Locally process the received raw data and extract feature information related to the operating status of the ring main unit;

[0048] Collaborative analysis step: Receive the feature information output by each local processing module, and through the collaborative integration and analysis of multi-node data, evaluate the overall operating status of the ring main unit group, identify anomalies, and predict risks;

[0049] Interaction step: used to display the output results of the collaborative analysis module, support command interaction with the system, and remotely monitor and control the operating status of the ring network cabinet group.

[0050] As a further optional solution of the method for collaboratively monitoring and analyzing the operating status of a ring main unit group, it 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 method for collaboratively monitoring and analyzing the operating status of a ring main unit group are implemented.

[0051] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the method for collaboratively monitoring and analyzing the operating status of a ring main unit group.

[0052] Compared with the prior art, the present invention has the following beneficial effects:

[0053] Enhanced collaborative monitoring capabilities: Through spatiotemporal synchronization and correlation analysis of multi-node data, the limitations of traditional single-point monitoring can be overcome. This allows for effective identification of systemic risks within ring main units (such as regional load imbalances and other cluster-level issues), enabling an upgrade from single-device monitoring to cluster collaborative awareness.

[0054] Optimizing data processing efficiency: Relying on local preprocessing to reduce redundant data transmission pressure, combined with edge computing technology to improve the real-time performance of feature extraction, avoiding analysis delays caused by remote data transmission delays;

[0055] Improved status assessment accuracy: Through multi-dimensional feature extraction and dynamic threshold adjustment, the pertinence of abnormal status identification and the reliability of risk prediction are enhanced, misjudgments and missed judgments are reduced, and the accuracy of equipment status assessment is improved;

[0056] Accelerated operation and maintenance response speed: Build a "monitoring-analysis-decision-making-control" closed-loop linkage mechanism to promote the transformation of fault handling from passive response to active early warning, shorten the fault handling cycle, reduce the impact of unplanned power outages, and improve overall operation and maintenance efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0058] Figure 1 This is a schematic diagram of the composition of a system for collaborative monitoring and analysis of the operating status of a ring main unit group according to the present invention;

[0059] Figure 2 This is a flow chart of a method for collaboratively monitoring and analyzing the operating status of a ring main unit group according to the present invention. DETAILED DESCRIPTION

[0060] The following is a clear and complete description of the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0061] like Figure 1-2 As shown, it includes data acquisition module, local processing module, collaborative analysis module and interaction module. Each module works together to realize the full life cycle monitoring and intelligent analysis of the ring network cabinet group.

[0062] The data acquisition module is deployed at each ring main unit node and includes various sensors, node communication components, and a synchronization control unit:

[0063] Sensors: Based on the structural characteristics of the ring main unit, current / voltage sensors are installed at the electrical connection points, temperature and humidity sensors and partial discharge sensors (such as UHF sensors) are installed inside the cabinet, and mechanical stroke sensors are installed on the operating mechanism to collect electrical parameters (current, voltage, partial discharge signals), environmental parameters (temperature, humidity), and mechanical parameters (operating stroke, vibration signals).

[0064] Synchronous control unit: Generates a unified timestamp through GPS timing or NTP protocol to ensure the spatiotemporal alignment of data collected by multiple ring network cabinet nodes, avoiding analysis errors caused by collection time deviation;

[0065] Node communication component: transmits the collected raw data to the local processing module and supports short-range wired / wireless communication (such as RS485, LoRa).

[0066] The local processing module implements localized data processing based on an embedded processing unit (such as an ARM architecture chip), including:

[0067] Preprocessing: Perform noise reduction (such as wavelet noise reduction), filtering (such as Kalman filtering), and outlier removal (such as based on boxplot method) on the raw data to remove environmental interference and sensor errors;

[0068] Feature extraction: Based on preset electrical, environmental, and mechanical feature dimensions, it extracts characteristic quantities strongly related to operating status (such as current fluctuation range, temperature change rate, and mechanical operation time). Dynamic thresholds are set based on the rated parameters of the ring main unit and historical data. When the collected data exceeds the threshold, the feature extraction accuracy of the corresponding dimension is automatically improved (for example, by increasing the sampling frequency of partial discharge signals).

[0069] Data transmission: Upload the extracted feature information to the collaborative analysis module to reduce the amount of original data transmission.

[0070] The collaborative analysis module, including the data fusion unit, the state assessment unit and the decision-making unit, realizes the collaborative analysis of multi-node data:

[0071] Data fusion unit: Generates a joint feature set through two-level processing: local fusion and global fusion. Local fusion performs weighted fusion of the multi-dimensional features of a single ring main unit (weights are dynamically assigned based on historical contributions). Global fusion aligns multi-node data through spatiotemporal correlation algorithms (such as dynamic time warping), removes redundant features based on the spatial topology of the ring main unit cluster (such as the location of adjacent nodes), and uses the 3σ criterion to correct outliers.

[0072] Condition Assessment Unit: Builds an assessment model based on a health benchmark library (storing rated parameters, historical health data, and fault maps) to calculate the health index of a single node and the cluster's collaborative operation coefficient. It identifies abnormal conditions using a dynamic deviation threshold (adjusted based on the equipment's age) and associates fault mode labels (e.g., "partial discharge exceeds the limit" or "mechanical jam"). Based on time series characteristics and historical cases, it uses a trend extrapolation algorithm to predict the fault risk level (high / medium / low) for the next 1-7 days.

[0073] Decision generation unit: Generates collaborative control strategies based on the evaluation results, such as fault node isolation instructions, adjacent node load adjustment plans, etc., and transmits the results to the interaction module.

[0074] Interaction module, which realizes human-computer interaction and remote control, including:

[0075] Visual display unit: Based on the ring main unit group topology diagram, it displays the health index of a single node, the cluster operation coefficient, and abnormality marks in layers, and supports the correlation query of historical data curves (such as the temperature trend in the past 30 days) and fault cases;

[0076] Command input unit: provides parameter configuration interface (such as threshold adjustment) and control command options (such as remote opening and closing), and implements authority verification through username and password + digital signature;

[0077] Bidirectional communication unit: establishes a real-time link with the collaborative analysis module, pushes the analysis results to the display unit, and forwards the verified control instructions to the local processing module of the corresponding ring network cabinet.

[0078] A method for collaboratively monitoring and analyzing the operating status of a ring main unit group comprises the following steps:

[0079] Data collection step: used to collect the operating status parameters of each ring main unit in the ring main unit group and perform distributed data acquisition of multiple ring main unit nodes;

[0080] Local processing step: Locally process the received raw data and extract feature information related to the operating status of the ring main unit;

[0081] Collaborative analysis step: Receive the feature information output by each local processing module, and through the collaborative integration and analysis of multi-node data, evaluate the overall operating status of the ring main unit group, identify anomalies, and predict risks;

[0082] Interaction step: used to display the output results of the collaborative analysis module, support command interaction with the system, and remotely monitor and control the operating status of the ring network cabinet group.

[0083] A computer device comprises 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 method for collaboratively monitoring and analyzing the operating status of a ring main unit group are implemented. The memory of the device can be implemented by any type of volatile or non-volatile storage device or a combination thereof. Volatile or non-volatile storage devices include, but are not limited to, magnetic disks, optical disks, EEPROMs, EPROMs, SRAMs, ROMs, magnetic memories, flash memories, and PROMs. The memory of the device provides an environment for the operation of the operating system and computer programs stored therein. The communication interface of the device is a network interface, which is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, the steps of the method for collaboratively monitoring and analyzing the operating status of a ring main unit group are implemented.

[0084] A computer-readable storage medium having a computer program stored thereon, wherein when executed by a processor, the computer program implements the steps of the method for collaboratively monitoring and analyzing the operating status of a ring main unit group. The computer-readable storage medium includes, but is not limited to, ROM, RAM, CD-ROM, magnetic disk, and floppy disk.

[0085] The technical solutions provided by the embodiments of the present invention are introduced in detail above. Specific examples are used herein to illustrate the principles and implementation methods of the embodiments of the present invention. The description of the above embodiments is only applicable to help understand the principles of the embodiments of the present invention. At the same time, for those skilled in the art, according to the embodiments of the present invention, there may be changes in the specific implementation methods and application scopes. In summary, the contents of this specification should not be understood as limiting the present invention.

Claims

1. A ring main unit group operation status collaborative monitoring and analysis system, characterized in that: include: The data acquisition module is used to collect the operating status parameters of each ring main unit in the ring main unit group and perform distributed data acquisition of multiple ring main unit nodes; The local processing module performs local processing on the received raw collected data and extracts characteristic information related to the operating status of the ring main unit; The collaborative analysis module receives the characteristic information output by each local processing module and evaluates the overall operating status of the ring main unit group, identifies anomalies, and predicts risks through the collaborative integration and analysis of multi-node data; The interactive module is used to display the output results of the collaborative analysis module, support command interaction with the system, and remotely monitor and control the operating status of the ring network cabinet group.

2. The system according to claim 1, wherein: The data acquisition module includes a variety of sensors, node communication components and synchronization control units deployed in each ring network cabinet; The various sensors are respectively arranged at the electrical connection parts, the interior of the cabinet and the operating mechanism of the ring main unit, and are used to collect current, voltage, partial discharge signal, cabinet temperature, humidity and mechanical operation stroke parameters; The synchronization control unit realizes the spatiotemporal alignment of the data collected by the nodes of the multi-ring mainframe through a preset timestamp synchronization mechanism; The node communication component transmits the collected data to the local processing module.

3. The system according to claim 1, wherein: The local processing module includes an embedded processing unit, which receives the raw data transmitted by the data acquisition module, performs preprocessing operations such as noise reduction, filtering, and outlier removal on the raw data, and extracts feature quantities related to the operating status of the ring network cabinet based on preset feature dimensions, wherein the feature quantities include time series features, amplitude features, and mutation features; The local processing module transmits the extracted feature information to the collaborative analysis module.

4. The system according to claim 3, characterized in that The preset feature dimension extracts feature quantities related to the operating status of the ring main unit, specifically including: The electrical characteristic dimension extracts the fluctuation range of the effective current value, the voltage distortion rate, the pulse amplitude and the time domain distribution characteristics of the partial discharge signal; Environmental feature dimension: extract the rate of change of cabinet temperature, the correlation coefficient between humidity and temperature, and the distribution uniformity of the cabinet surface temperature field; Mechanical feature dimension, extracting the operating mechanism action time, slope change of stroke displacement, and main frequency component characteristics of mechanical vibration signal; The extraction of the feature quantity sets a dynamic threshold based on the rated parameters and historical operating data of the ring network cabinet. When the collected data exceeds the threshold range, the feature extraction accuracy of the corresponding dimension is automatically enhanced.

5. The system according to claim 1, wherein: The collaborative analysis module includes: The data fusion unit is used to receive the feature information output by each local processing module, and cross-validate and eliminate redundancy of the feature quantities of multiple ring main unit nodes through the spatiotemporal correlation algorithm to form a joint feature set of the ring main unit group; The status assessment unit is used to build an operating status assessment model based on the joint feature set, identify abnormal conditions by comparing with preset health benchmark values, and train a risk prediction sub-model based on historical fault data; The decision generation unit is used to generate the corresponding collaborative control strategy according to the status assessment results, and transmit the analysis results and control strategy to the interaction module.

6. The system according to claim 5, characterized in that The data fusion unit includes: The local fusion submodule performs weighted fusion on the multi-dimensional feature quantities of a single ring main unit and dynamically assigns weight coefficients based on the historical contribution of each feature quantity; The global fusion submodule uses a spatiotemporal correlation algorithm to perform correlation analysis on the local fusion results of multiple ring main unit nodes, eliminates redundant features through time series alignment and spatial topology mapping, and uses the 3σ criterion to identify and correct abnormal fusion values. The joint feature set output by the data fusion unit includes single-node state features and cross-node correlation features, wherein the cross-node correlation features include load fluctuation correlation and environmental parameter gradient change features of adjacent ring network cabinets.

7. The system according to claim 5, characterized in that The state assessment unit comprises: The health benchmark library stores the rated operating parameters, historical health status data, and typical fault characteristic maps of the ring main unit group as a reference for status assessment; The multi-dimensional evaluation model uses the joint feature set output by the data fusion unit as input. By calculating the difference between the feature quantity and the health baseline value and performing trend fitting, it generates the health index of a single ring main unit and the overall collaborative operation coefficient of the ring main unit group. The abnormality recognition logic sets a dynamic deviation threshold, marks the feature quantity that exceeds the threshold range, and associates it with the corresponding fault mode label. The risk prediction model, based on time series feature sequences and historical failure cases, uses a trend extrapolation algorithm to predict the failure risk level within a preset time period in the future and outputs three levels of risk warnings: high, medium, and low.

8. The system according to claim 1, wherein: The interaction module includes: The visual display unit uses the RMU group topology diagram as the basic interface, hierarchically displays the health index of a single RMU, the cluster collaborative operation coefficient, and abnormal status marks, and supports correlation query of historical data trend curves and fault cases; The command input unit provides a parameter configuration interface and control command options, and receives remote operation commands input by the user through an authority verification mechanism; The two-way communication unit establishes a real-time data link with the collaborative analysis module, pushes the collaborative analysis results to the visual display unit, and forwards the control instructions that have been verified to the collaborative analysis module and the local processing module of the corresponding ring network cabinet.

9. A method for collaborative monitoring and analysis of the operating status of a ring main unit group, characterized in that: The specific steps include: Data collection step: used to collect the operating status parameters of each ring main unit in the ring main unit group and perform distributed data acquisition of multiple ring main unit nodes; Local processing step: Locally process the received raw data and extract feature information related to the operating status of the ring main unit; Collaborative analysis step: Receive the feature information output by each local processing module, and through the collaborative integration and analysis of multi-node data, evaluate the overall operating status of the ring main unit group, identify anomalies, and predict risks; Interaction step: used to display the output results of the collaborative analysis module, support command interaction with the system, and remotely monitor and control the operating status of the ring network cabinet group.

10. A computer device, characterized in that: It 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 method for collaborative monitoring and analysis of the operating status of a ring main unit group as claimed in claim 9 are implemented.

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