Intelligent visualization system and method for operation and maintenance of transformer substation

Abstract

The invention discloses an intelligent visualization system and method for operation and maintenance of a transformer substation, and relates to the technical field of intelligent operation and maintenance of transformer equipment.The system is connected with a sensor set installed on a transformer through a wireless network, collects equipment operation data, obtains a risk data set through preprocessing, calculates a comprehensive risk index sfx through an algorithm, and stores the comprehensive risk index sfx. And comparing with an equipment safe operation threshold A to evaluate the equipment operation health condition. And when an anomaly is detected, generating a dynamic optimization adjustment coefficient yht, correcting an abnormal parameter, and further calculating a risk fault assessment index tzy to deeply analyze an anomaly reason. The device state, the historical data trend and the alarm record in the area are displayed in a layered view mode, interactive operation is supported, and rapid device positioning, running log query and problem tracking are achieved. Through intelligent data analysis and visual presentation, the system provides all-around decision support for operation and maintenance personnel, and the operation and maintenance efficiency, accuracy and safety of the transformer substation are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent operation and maintenance of substation equipment, and specifically to an intelligent visualization system and method for substation operation and maintenance. Background Art

[0002] With the rapid development of social economy, the continuous advancement of industrialization and urbanization, the demand for electricity has shown a trend of sustained growth. As the infrastructure of modern society, the stability and security of the power system are crucial to economic development and people's lives. Especially in the era of informatization and intelligence, society's dependence on power supply is increasing, and the demand for power supply quality and reliability is becoming more and more stringent. At the same time, with the increase in the proportion of new energy access and the diversification of power loads, the complexity of power grid operation has increased significantly, and the traditional power grid operation and maintenance mode can no longer meet the efficiency and safety requirements of modern power system operation. Therefore, promoting the intelligent transformation of power grids and realizing the digital and intelligent management of substations have become an important direction to ensure social and economic development and energy security.

[0003] Although traditional substation operation and maintenance methods can ensure the safe operation of equipment to a certain extent, there are still many limitations. For example, data processing methods are relatively scattered, making it difficult to form a systematic risk assessment; fault warning time is delayed, often relying on manual diagnosis and maintenance after the fault occurs, and lacking active prevention capabilities. In addition, insufficient visualization capabilities are another important shortcoming. Existing systems are mainly based on decentralized charts and static data presentations, lacking comprehensive dynamic analysis and prediction functions. For multi-parameter comprehensive evaluation, traditional methods have difficulty modeling complex relationships, resulting in limited risk analysis accuracy. At the same time, due to the existence of the data island effect, the linkage analysis capabilities between different devices and regions are weak, and it is not easy to meet the needs of rapid positioning and efficient troubleshooting. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides an intelligent visualization system and method for substation operation and maintenance, which solves the problems in the above-mentioned background technology.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: an intelligent visualization system for substation operation and maintenance, including a data acquisition module, a data integration module, an abnormality analysis module, an optimization and adjustment module and a visualization module;

[0006] The data acquisition module is used to construct a central processing server, and establish a communication connection between the sensor group installed on the transformer and the central processing server through a wireless network, and then transmit the substation equipment operation data collected in real time by the sensor group to the central processing server;

[0007] The data integration module pre-processes the substation operation data through the central processor, obtains the risk data group, builds a time series repository, and stores the risk data group in the time series repository;

[0008] The abnormal analysis module is used to perform summary calculations based on the acquired risk data group to obtain the thermal stability index rwd, the insulation state index jyz and the insulation gas tightness index qmz, and then summarize the thermal stability index rwd, the insulation state index jyz and the insulation gas tightness index qmz to obtain the comprehensive risk index sfx, and perform substation equipment operation risk assessment with the preset equipment safety operation threshold A;

[0009] The optimization and adjustment module is used to construct a dynamic optimization adjustment coefficient yht formula through a central processing server when the risk assessment of substation operation is abnormal, adjust the parameters according to historical normal data, and summarize and calculate with the comprehensive risk index sfx to obtain the risk fault assessment index tzy, and then conduct substation equipment fault assessment with the preset equipment safety operation threshold A;

[0010] The visualization module is used to collect risk data groups and evaluate alarm information, build a hierarchical status display view, display the operating status and alarm information of the substation equipment in the area, and transmit it to the user end of the operation and maintenance personnel through the wireless network.

[0011] Preferably, the data acquisition module includes a data acquisition unit and a communication connection unit;

[0012] The data acquisition unit collects the transformer substation equipment operation data of the transformer in real time through the sensor group installed on the transformer, sets the collection frequency of the sensor group to 5 minutes, and records the collection timestamp;

[0013] The sensor group includes a temperature sensor, a viscosity sensor, a current sensor, a gas purity analyzer, a flow sensor, an electric field sensor, a pressure sensor and a laser leak monitor;

[0014] The communication connection unit is used to construct a central processing server, establish a communication connection between the sensor group and the central processing server through a wireless network, and transmit the substation equipment operation data collected by the sensor group to the central processing server in real time.

[0015] Preferably, the data integration module includes a data integration unit and a data storage unit;

[0016] The data integration unit is used to pre-process the substation operation data transmitted to the central processing server. The pre-processing includes forming a change sequence set Q for the periodically collected equipment temperature wd, insulating oil viscosity nd and insulating gas purity cd, where Q = {wd, nd, cd}, and differential calculation to obtain the temperature gradient Δwd, the insulating oil viscosity gradient Δnd and the insulating gas purity gradient Δcd respectively. The specific algorithm formula is: Among them, Q i represents the i-th parameter in the change sequence set;

[0017] Then, the substation equipment operation data is subjected to denoising, outlier detection and dimensionless processing to obtain a risk data group;

[0018] The risk data group includes a thermal stability data group, an insulation factor data group and an airtight factor data group;

[0019] The thermal stability data group includes the equipment temperature gradient ΔT, the cooling medium flow rate ll, the cooling medium inlet and outlet temperature difference wc and the actual load current sf;

[0020] The insulation factor data set includes the partial discharge intensity fd, the insulating oil viscosity gradient Δnd and the leakage current value ld;

[0021] The airtight factor data group includes the leakage rate xl, the insulating gas purity change gradient Δcd and the sealing pressure difference yc;

[0022] The data storage unit is used to construct a time series repository, store the risk data group in the time series repository, and perform information marking on the parameters in the risk data group, wherein the information marking includes a sensor ID, a sensor location, and a data type.

[0023] Preferably, the abnormality analysis module includes an abnormality analysis unit and a comprehensive risk analysis unit;

[0024] The abnormality analysis unit is used to perform summary calculations based on the acquired thermal stability data group, insulation factor data group and airtight factor data group to obtain a thermal stability index rwd, an insulation state index jyz and an insulation gas airtight index qmz;

[0025] The thermal stability index rwd, insulation state index jyz and insulation gas tightness index qmz are calculated and obtained by the following formulas respectively;

[0026]

[0027]

[0028]

[0029] Where I represents the rated current of the substation equipment, cp represents the specific heat capacity of the cooling medium, Δt represents the time interval between two samplings, and ln represents the logarithmic function.

[0030] Preferably, the comprehensive risk analysis unit includes a comprehensive risk calculation unit and a comprehensive risk warning unit;

[0031] The comprehensive risk calculation unit is used to perform summary calculation based on the obtained thermal stability index rwd, insulation state index jyz and insulation gas airtightness index qmz to obtain a comprehensive risk index sfx;

[0032] The comprehensive risk index sfx is calculated by the following formula:

[0033]

[0034] Wherein, ln represents the logarithmic function.

[0035] Preferably, the comprehensive risk alarm unit is used to extract the historical substation equipment operation data in the time series storage library, divide the historical data into normal data and abnormal data by cluster analysis, and then use the statistical method to calculate the peak value of the comprehensive risk index of normal data and the valley value of the comprehensive risk index of abnormal data, and extract the average value, and perform the preset equipment safety operation threshold value A, and then perform the substation equipment failure assessment with the obtained comprehensive risk index sfx. The specific assessment scheme is as follows;

[0036] When the comprehensive risk index sfx>equipment safe operation threshold A, it indicates that there is an abnormality in the operation of the substation equipment, triggering the adjustment mechanism;

[0037] When the comprehensive risk index sfx ≤ the equipment safe operation threshold A, it means that the substation equipment operates normally and maintains normal monitoring.

[0038] Preferably, the optimization and adjustment module includes an optimization and adjustment unit and a fault assessment and analysis unit;

[0039] The optimization and adjustment unit is used for the central processing server to analyze the causes of the abnormal parameters when the risk assessment of the operation of the substation equipment shows that there is an abnormality. The abnormal causes include parameter fluctuations and substation equipment failures caused by external emergencies. The central processing server corrects the abnormal parameters based on historical safety operation data and constructs a dynamic optimization adjustment coefficient yht;

[0040] The dynamic optimization adjustment coefficient yht is calculated and obtained by the following formula:

[0041]

[0042] In the formula, sj i represents the actual measured value of the ith parameter, zci Represents the safe value of the i-th parameter, a i It represents the optimization constant of the impact of the ith parameter on the overall risk, and n represents the number of abnormal parameters currently occurring.

[0043] Preferably, the fault assessment and analysis unit includes a risk fault calculation unit and a risk fault assessment unit;

[0044] The risk failure calculation unit is used to summarize and calculate the dynamic optimization adjustment coefficient yht and the comprehensive risk index sfx to obtain the risk failure evaluation index tzy;

[0045] The risk failure assessment index tzy is calculated and obtained by the following formula:

[0046] tzy=yht+k*sfx;

[0047] In the formula, k represents the adjustment coefficient of the comprehensive risk index;

[0048] The risk failure assessment unit is used to perform a substation equipment failure assessment based on the acquired risk failure assessment index tzy and the equipment safe operation threshold A, and deeply assess the cause of the substation equipment failure. The specific assessment scheme is as follows;

[0049] When the risk fault assessment index tzy>equipment safe operation threshold A, it indicates that the adjustment is invalid and it is a hardware fault of the substation equipment. The serial number, specific location and fault cause of the substation equipment are marked, and risk information is generated. The risk information is transmitted to the user end of the operation and maintenance personnel through the wireless network to remind the operation and maintenance personnel to conduct substation equipment inspection;

[0050] When the risk fault assessment index tzy≤equipment safe operation threshold A, it means that the substation equipment operation fault has returned to normal after adjustment. At this time, it is an abnormal fault of substation equipment parameters and normal monitoring is maintained.

[0051] Preferably, the visualization module includes a chart display unit and an interactive visualization unit;

[0052] The chart display unit constructs a hierarchical status display view in the central processing server, imports the risk data group and assessment alarm information collected in real time into the hierarchical status display view, and displays the operating status and alarm information of the substation equipment in the area. The hierarchical status display view includes a top view, a middle view and a bottom view;

[0053] The top-level view displays the health status of the overall substation equipment through a partitioned color block diagram based on the risk data group and the assessment alarm information, and marks the healthy area in green, the area with abnormal data fluctuation in yellow, and the abnormalities that cannot be controlled by the central processing server in red, providing a global operation overview;

[0054] The middle-level view is used to display the operating status and alarm information of the substation equipment in this area.

[0055] The bottom-level view generates a line chart by combining the data acquisition timestamp to display the parameter change trend and current alarm record of a single substation equipment, and supports trend analysis and problem location;

[0056] The interactive visualization unit is used to transmit the chart information of the chart display unit to the user end of the operation and maintenance personnel through the wireless network. The operation and maintenance personnel select the substation equipment, specific area and alarm level of concern through the screening panel, dynamically update the view, and quickly locate the target substation equipment by entering the substation equipment number and alarm ID, and display the complete operation log, historical alarm record and alarm cause of the substation equipment.

[0057] An intelligent visualization method for substation operation and maintenance includes the following steps:

[0058] S1, build a central processing server, and establish a communication connection between the sensor group installed on the transformer and the central processing server through a wireless network, and then transmit the substation equipment operation data collected in real time by the sensor group to the central processing server;

[0059] S2. Preprocessing the substation operation data through the central processor to obtain the risk data group, and constructing a time series repository, and storing the risk data group in the time series repository;

[0060] S3. Summarize and calculate the acquired risk data group to obtain the thermal stability index rwd, the insulation state index jyz and the insulation gas tightness index qmz, then summarize and calculate the thermal stability index rwd, the insulation state index jyz and the insulation gas tightness index qmz to obtain the comprehensive risk index sfx, and perform the substation equipment operation risk assessment with the preset equipment safety operation threshold A;

[0061] S4. When the risk assessment of substation operation shows abnormality, the central processing server constructs a dynamic optimization adjustment coefficient yht formula, adjusts the parameters according to historical normal data, and calculates and summarizes the comprehensive risk index sfx to obtain the risk fault assessment index tzy, and then conducts substation fault assessment with the preset equipment safety operation threshold A;

[0062] S5. Collect risk data groups and evaluate alarm information, build a hierarchical status display view, display the operating status and alarm information of the substation equipment in the area, and transmit it to the user end of the operation and maintenance personnel through the wireless network.

[0063] The present invention provides an intelligent visualization system and method for substation operation and maintenance, which has the following beneficial effects:

[0064] (1) The system monitors the operation data of substation equipment in real time through the sensor group and records the equipment operation status at a high frequency of 5 minutes. The communication connection unit transmits information to the central processing server through the wireless communication network to ensure real-time and efficient data aggregation, and marks the collection timestamp and sensor location to achieve accurate tracking of equipment operation data. This real-time and comprehensive monitoring method effectively improves the information level of substation operation and maintenance, and provides a solid foundation for subsequent data analysis.

[0065] (2) The system pre-processes the substation equipment operation data, removes noise, detects outliers, and non-dimensionalizes them to form three risk data groups: thermal stability data group, insulation factor data group, and airtightness factor data group. It also constructs temperature gradient ΔT, insulation oil viscosity gradient Δnd, and insulation gas purity change gradient Δcd through a unique gradient algorithm to provide diverse data support for status assessment. In abnormal analysis, the system calculates the thermal stability index rwd, insulation status index jyz, and insulation gas airtightness index qmz based on the three dimensions of thermal stability data group, insulation factor data group, and airtightness factor data group, and summarizes and calculates them to obtain the comprehensive risk index sfx. By comparing the comprehensive risk index sfx with the preset equipment safety operation threshold A, a comprehensive assessment of the equipment operation status is performed. When the operation status is abnormal, the optimization and adjustment module dynamically optimizes and corrects the abnormal parameters in combination with historical data, constructs the dynamic optimization adjustment coefficient yht, and summarizes and calculates it with the comprehensive risk index sfx to obtain the risk fault assessment index tzy, which is then compared with the preset equipment safety operation threshold A to perform substation equipment fault assessment to achieve fault assessment and risk control. This multi-level analysis and optimization mechanism not only ensures the accuracy of fault detection, but also provides a scientific basis for subsequent operation and maintenance.

[0066] (3) The system visualization module constructs a hierarchical status view to present the operating status and alarm information of the substation equipment to the operation and maintenance personnel in an intuitive way. The top-level view provides a global overview of the equipment operation in the area, and abnormal areas are marked with colors for quick identification; the middle and bottom-level views further display the local equipment operation status and detailed data, and support problem location and trend analysis in combination with historical trend charts. The interactive function allows operation and maintenance personnel to customize queries on the areas, equipment and alarm levels of interest through the filtering panel, and quickly locate the target equipment by entering the number, and view its historical records and operation logs. This system design, which integrates global monitoring, problem diagnosis, fault tracing and interactive functions, has significantly improved the efficiency and accuracy of operation and maintenance work, reduced safety hazards in equipment operation, and laid a solid technical foundation for ensuring the stable operation of the power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] Figure 1 This is a schematic diagram of the process of an intelligent visualization system for substation operation and maintenance according to the present invention;

[0068] Figure 2 The figure is a schematic diagram of the steps of an intelligent visualization method for substation operation and maintenance according to the present invention. DETAILED DESCRIPTION

[0069] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0070] Example 1

[0071] See also Figure 1 , the present invention provides an intelligent visualization system for substation operation and maintenance. To achieve the above purpose, the present invention is implemented through the following technical solutions: including a data acquisition module, a data integration module, an abnormality analysis module, an optimization and adjustment module and a visualization module;

[0072] The data acquisition module is used to construct a central processing server, and establish a communication connection between the sensor group installed on the transformer and the central processing server through a wireless network, and then transmit the substation equipment operation data collected in real time by the sensor group to the central processing server;

[0073] The data integration module pre-processes the substation operation data through the central processor, obtains the risk data group, builds a time series repository, and stores the risk data group in the time series repository;

[0074] The abnormal analysis module is used to perform summary calculations based on the acquired risk data group to obtain the thermal stability index rwd, the insulation state index jyz and the insulation gas tightness index qmz, and then summarize the thermal stability index rwd, the insulation state index jyz and the insulation gas tightness index qmz to obtain the comprehensive risk index sfx, and perform substation equipment operation risk assessment with the preset equipment safety operation threshold A;

[0075] The optimization and adjustment module is used to construct a dynamic optimization adjustment coefficient yht formula through a central processing server when the risk assessment of substation operation is abnormal, adjust the parameters according to historical normal data, and summarize and calculate with the comprehensive risk index sfx to obtain the risk fault assessment index tzy, and then conduct substation equipment fault assessment with the preset equipment safety operation threshold A;

[0076] The visualization module is used to collect risk data groups and evaluate alarm information, build a hierarchical status display view, display the operating status and alarm information of the substation equipment in the area, and transmit it to the user end of the operation and maintenance personnel through the wireless network.

[0077] In this embodiment, the data acquisition module collects equipment operation data through real-time monitoring of the sensor group and transmits it to the central processing server, realizing efficient and stable data acquisition and transmission functions. This combination of distributed perception and centralized processing solves the problem of untimely and incomplete information collection in traditional operation and maintenance methods, and lays a solid foundation for subsequent data processing and analysis. The data integration module and the abnormality analysis module form a comprehensive risk data group through preprocessing, grouping and indexing of the collected data, and use the thermal stability index rwd, insulation state index jyz and insulation gas airtightness index qmz to construct a comprehensive risk index sfx, and the preset equipment safety operation threshold A to complete the risk assessment of the equipment operation status. This multi-dimensional data processing and analysis method effectively improves the accuracy and comprehensiveness of equipment abnormality detection, and overcomes the limitations of relying on single parameter monitoring in traditional operation and maintenance methods. The optimization and adjustment module and the visualization module further improve the intelligence level of the system. The optimization and adjustment module constructs a dynamic optimization adjustment coefficient yht based on historical operation data and abnormal parameters, corrects the abnormal operation status, and summarizes and calculates it with the comprehensive risk index sfx to obtain the risk fault assessment index tzy, and then evaluates the substation equipment fault with the preset equipment safety operation threshold A, filling the gap in the traditional operation and maintenance methods in the lack of abnormal state processing capabilities. The visualization module displays the equipment operation health status through a hierarchical status view, and combines real-time alarms and historical data trends to improve the intuitiveness and operational efficiency of operation and maintenance work. Compared with traditional technical means, the system has achieved significant improvements in data real-time, analysis depth, early warning capabilities and operation and maintenance efficiency, providing reliable support for the safe operation of substations and efficient decision-making of operation and maintenance personnel.

[0078] Example 2

[0079] This embodiment is explained in Example 1, please refer to Figure 1 ,Specifically: the data acquisition module includes a data acquisition unit and a communication connection unit;

[0080] The data acquisition unit collects the transformer substation equipment operation data of the transformer in real time through the sensor group installed on the transformer, sets the collection frequency of the sensor group to 5 minutes, and records the collection timestamp;

[0081] The sensor group includes a temperature sensor, a viscosity sensor, a current sensor, a gas purity analyzer, a flow sensor, an electric field sensor, a pressure sensor and a laser leak monitor;

[0082] The actual load current sf is monitored in real time by the current sensor installed on the low voltage side of the transformer;

[0083] The temperature difference wc between the inlet and outlet temperature of the cooling medium and the flow rate ll of the cooling medium are obtained by installing a temperature sensor and a flow rate sensor at the inlet and outlet of the cooling medium respectively;

[0084] By arranging current sensors on the surface of insulators, the leakage current value ld of the insulation layer of the substation equipment can be monitored in real time;

[0085] Obtain the local discharge intensity fd through the electric field sensor;

[0086] The internal and external pressures are obtained in real time by installing pressure sensors inside and outside the insulating gas sealed tank, and the sealing pressure difference yc is obtained by the internal and external pressure difference;

[0087] By arranging a laser leakage monitor outside the airtight insulating gas sealed tank, the gas leakage is monitored in real time, and the leakage rate xl is calculated by combining the leakage time and the total leakage;

[0088] The equipment temperature wd, insulating oil viscosity nd and insulating gas purity cd are collected by temperature sensor, viscosity sensor and gas purity analyzer respectively;

[0089] The communication connection unit is used to construct a central processing server, establish a communication connection between the sensor group and the central processing server through a wireless network, and transmit the substation equipment operation data collected by the sensor group to the central processing server in real time.

[0090] In this embodiment, the data acquisition module constructs a set of refined real-time monitoring systems through a highly integrated sensor group and communication connection unit, providing technical support for the comprehensive perception of the operating status of the substation equipment. Various sensor types include temperature sensors, viscosity sensors, current sensors, gas purity analyzers, flow sensors, electric field sensors, pressure sensors and laser leakage monitors. The acquisition frequency is accurate to 5 minutes, and the timestamp is recorded, realizing high-frequency and multi-dimensional substation equipment operation data acquisition. Through the synchronous acquisition of different data in the substation equipment operation data group, the complex dynamic characteristics of the equipment operation can be captured. The communication connection unit realizes real-time communication between the sensor group and the central processing server through a wireless network, ensuring the rapid convergence and reliable transmission of data. This modular design solves the problems of single parameter collection and delayed information update in traditional systems, provides an accurate and rich real-time data foundation for equipment abnormality detection and operation optimization, and significantly improves the intelligence and reliability level of substation operation and maintenance.

[0091] Example 3

[0092] This embodiment is explained in Example 2. Please refer to Figure 1 ,Specifically: the data integration module includes a data integration unit and a data storage unit;

[0093] The data integration unit is used to pre-process the substation operation data transmitted to the central processing server. The pre-processing includes forming a change sequence set Q for the periodically collected equipment temperature wd, insulating oil viscosity nd and insulating gas purity cd, where Q = {wd, nd, cd}, and differential calculation to obtain the temperature gradient Δwd, the insulating oil viscosity gradient Δnd and the insulating gas purity gradient Δcd respectively. The specific algorithm formula is: Among them, Q i represents the i-th parameter in the change sequence set;

[0094] Then, the substation equipment operation data is subjected to denoising, outlier detection and dimensionless processing to obtain a risk data group;

[0095] The risk data group includes a thermal stability data group, an insulation factor data group and an airtight factor data group;

[0096] The thermal stability data group includes the equipment temperature gradient ΔT, the cooling medium flow rate ll, the cooling medium inlet and outlet temperature difference wc and the actual load current sf;

[0097] The insulation factor data set includes the partial discharge intensity fd, the insulating oil viscosity gradient Δnd and the leakage current value ld;

[0098] The airtight factor data group includes the leakage rate xl, the insulating gas purity change gradient Δcd and the sealing pressure difference yc;

[0099] The data storage unit is used to construct a time series repository, store the risk data group in the time series repository, and perform information marking on the parameters in the risk data group, wherein the information marking includes a sensor ID, a sensor location, and a data type.

[0100] In this embodiment, the data integration module provides efficient and accurate data processing and storage capabilities for substation operation and maintenance through the synergy of the data integration unit and the data storage unit. The data integration unit is based on multi-dimensional parameter acquisition, and through differential calculation of the change sequence of equipment temperature wd, insulating oil viscosity nd and insulating gas purity cd, the temperature gradient ΔT, insulating oil viscosity gradient Δnd and insulating gas purity change gradient Δcd indicators are extracted, thereby realizing efficient transformation of data from original acquisition to risk assessment. At the same time, through pre-processing steps such as denoising, outlier detection and dimensionless conversion, the accuracy and standardization of the data are improved. The uniqueness of the module lies in that by dividing the three risk data groups of thermal stability data group, insulation factor data group and airtight factor data group, the complex equipment operation data is structured and layered, providing multi-dimensional information support for subsequent fault diagnosis and status assessment. In addition, the time series repository constructed by the data storage unit not only realizes efficient data storage, but also ensures the traceability and accurate positioning capability of the data through the information tagging function. This full-process optimized processing and storage method solves the problems of inefficient data management and insufficient information relevance in traditional systems, and lays a solid data foundation for subsequent intelligent analysis and decision support.

[0101] Example 4

[0102] This embodiment is explained in Example 3, please refer to Figure 1 ,Specifically: the abnormality analysis module includes an abnormality analysis unit and a comprehensive risk analysis unit;

[0103] The abnormality analysis unit is used to perform summary calculations based on the acquired thermal stability data group, insulation factor data group and airtight factor data group to obtain a thermal stability index rwd, an insulation state index jyz and an insulation gas airtight index qmz;

[0104] The thermal stability index rwd, insulation state index jyz and insulation gas tightness index qmz are calculated and obtained by the following formulas respectively;

[0105]

[0106]

[0107]

[0108] Where I represents the rated current of the substation equipment, cp represents the specific heat capacity of the cooling medium, Δt represents the time interval between two samplings, and ln represents the logarithmic function.

[0109] The comprehensive risk analysis unit includes a comprehensive risk calculation unit and a comprehensive risk warning unit;

[0110] The comprehensive risk calculation unit is used to perform summary calculation based on the obtained thermal stability index rwd, insulation state index jyz and insulation gas airtightness index qmz to obtain a comprehensive risk index sfx;

[0111] The comprehensive risk index sfx is calculated by the following formula:

[0112]

[0113] Wherein, ln represents the logarithmic function.

[0114] The comprehensive risk alarm unit is used to extract the historical substation equipment operation data in the time series storage library, divide the historical data into normal data and abnormal data by cluster analysis, and then use the statistical method to calculate the peak value of the comprehensive risk index of normal data and the valley value of the comprehensive risk index of abnormal data, and extract the average value, and perform the preset equipment safety operation threshold value A, and then perform the substation equipment failure assessment with the obtained comprehensive risk index sfx. The specific assessment scheme is as follows;

[0115] When the comprehensive risk index sfx>equipment safe operation threshold A, it indicates that there is an abnormality in the operation of the substation equipment, triggering the adjustment mechanism;

[0116] When the comprehensive risk index sfx ≤ the equipment safe operation threshold A, it means that the substation equipment operates normally and maintains normal monitoring.

[0117] In this embodiment, the abnormal analysis module and the comprehensive risk analysis unit form a multi-dimensional and multi-level risk assessment system by calculating the thermal stability index rwd, the insulation state index jyz and the insulating gas airtightness index qmz. This method effectively solves the limitation that traditional single parameter monitoring is difficult to capture complex operating problems, and ensures comprehensive control of the equipment status. At the same time, the system combines the historical operating data in the time series storage library, and uses the cluster analysis method to divide the historical data into two groups: normal data and abnormal data. By performing statistical analysis on the peak value of normal data and the valley value of abnormal data, the key characteristic values ​​are extracted, and the safe operation threshold A adapted to the current state and operating environment of the equipment is dynamically generated. This dynamically adjusted threshold adaptation mechanism overcomes the shortcomings of the traditional fixed threshold method and responds more flexibly to changes in different operating conditions and external environments. On this basis, the comprehensive risk analysis unit quickly determines the equipment operation status by calculating the real-time comprehensive risk index sfx and comparing it with the dynamically generated equipment safety operation threshold A. When the comprehensive risk index sfx is greater than the equipment safe operation threshold A, the system immediately triggers the abnormal adjustment mechanism, prompting the operation and maintenance personnel to intervene; when the comprehensive risk index sfx is less than or equal to the equipment safe operation threshold A, the equipment is judged to be operating normally and the system maintains normal monitoring. This mechanism significantly improves the accuracy and sensitivity of abnormal detection, effectively reduces the probability of false alarms and missed alarms, enhances the system's adaptability in complex and changing environments, and provides more reliable, intelligent, and efficient technical support for substation operation and maintenance.

[0118] Example 5

[0119] This embodiment is explained in Example 4. Please refer to Figure 1 ,Specifically: the optimization and adjustment module includes an optimization and adjustment unit and a fault assessment and analysis unit;

[0120] The optimization and adjustment unit is used for the central processing server to analyze the causes of the abnormal parameters when the risk assessment of the operation of the substation equipment shows that there is an abnormality. The abnormal causes include parameter fluctuations and substation equipment failures caused by external emergencies. The central processing server corrects the abnormal parameters based on historical safety operation data and constructs a dynamic optimization adjustment coefficient yht;

[0121] The dynamic optimization adjustment coefficient yht is calculated and obtained by the following formula:

[0122]

[0123] In the formula, sj i represents the actual measured value of the ith parameter, zc i Represents the safe value of the i-th parameter, a iThe optimization constant representing the impact of the ith parameter on the overall risk is a fixed dimensionless value obtained under the same environmental experiment. n represents the number of abnormal parameters currently occurring.

[0124] The fault assessment and analysis unit includes a risk fault calculation unit and a risk fault assessment unit;

[0125] The risk failure calculation unit is used to summarize and calculate the dynamic optimization adjustment coefficient yht and the comprehensive risk index sfx to obtain the risk failure evaluation index tzy;

[0126] The risk failure assessment index tzy is calculated and obtained by the following formula:

[0127] tzy=yht+k*sfx;

[0128] In the formula, k represents the adjustment coefficient of the comprehensive risk index;

[0129] The risk failure assessment unit is used to perform a substation equipment failure assessment based on the acquired risk failure assessment index tzy and the equipment safe operation threshold A, and deeply assess the cause of the substation equipment failure. The specific assessment scheme is as follows;

[0130] When the risk fault assessment index tzy>equipment safe operation threshold A, it indicates that the adjustment is invalid and it is a hardware fault of the substation equipment. The serial number, specific location and fault cause of the substation equipment are marked, and risk information is generated. The risk information is transmitted to the user end of the operation and maintenance personnel through the wireless network to remind the operation and maintenance personnel to conduct substation equipment inspection;

[0131] When the risk fault assessment index tzy≤equipment safe operation threshold A, it means that the substation equipment operation fault has returned to normal after adjustment. At this time, it is an abnormal fault of substation equipment parameters and normal monitoring is maintained.

[0132] In this embodiment, the optimization and adjustment module not only realizes the intelligent correction of abnormal parameters through the linkage of the optimization and adjustment unit and the fault assessment and analysis unit, but also shows unique advantages in deeply evaluating the causes of equipment failures. When the equipment operation is abnormal, the specific causes of external emergencies and internal equipment failures are distinguished, and the abnormal parameters are dynamically adjusted using historical safety data to ensure that the system adjustment process is targeted and scientific. The introduction of the dynamic optimization adjustment coefficient yht makes risk assessment more flexible and effective. The adjustment effect is further comprehensively analyzed through the risk fault assessment index tzy to clarify whether the equipment operation has returned to normal. This closed-loop evaluation and optimization mechanism not only improves the efficiency of abnormal handling, but also significantly reduces the misjudgment rate. By marking hardware fault information and informing the operation and maintenance personnel immediately, the system ensures the accuracy and timeliness of fault handling, while maintaining continuous monitoring of the equipment after the parameter abnormality is corrected, and establishing a reliable equipment status tracking mechanism. Compared with traditional fault management methods, these characteristics greatly improve the controllability of operation risks and the intelligent level of decision support, and provide a strong guarantee for the efficiency and safety of substation operation and maintenance.

[0133] Example 6

[0134] This embodiment is explained in Example 5. Please refer to Figure 1 ,Specifically: the visualization module includes a chart display unit and an interactive visualization unit;

[0135] The chart display unit constructs a hierarchical status display view in the central processing server, imports the risk data group and assessment alarm information collected in real time into the hierarchical status display view, and displays the operating status and alarm information of the substation equipment in the area. The hierarchical status display view includes a top view, a middle view and a bottom view;

[0136] The top-level view displays the health status of the overall substation equipment through a partitioned color block diagram based on the risk data group and the assessment alarm information, and marks the healthy area in green, the data fluctuation abnormal area in yellow, and the abnormalities that cannot be controlled by the central processing server in red, providing a global operation overview. By clicking on any area of ​​the partitioned color block diagram, you can enter the middle-level view of this area;

[0137] The middle-level view is used to display the operating status and alarm information of the substation equipment in this area. By clicking on any substation equipment in the middle-level view, you can enter the bottom-level view and the detailed status page of this substation equipment.

[0138] The bottom-level view generates a line chart by combining the data acquisition timestamp to display the parameter change trend and current alarm record of a single substation equipment, and supports trend analysis and problem location;

[0139] The interactive visualization unit is used to transmit the chart information of the chart display unit to the user end of the operation and maintenance personnel through the wireless network. The operation and maintenance personnel select the substation equipment, specific area and alarm level of concern through the screening panel, dynamically update the view, and quickly locate the target substation equipment by entering the substation equipment number and alarm ID, and display the complete operation log, historical alarm record and alarm cause of the substation equipment.

[0140] In this embodiment, the visualization module realizes global monitoring, local in-depth analysis and real-time interactive decision support of the substation operation status through the combination of the chart display unit and the interactive visualization unit. The hierarchical status display view is centered on the top, middle and bottom layers, and displays the operation information and alarm data of the equipment layer by layer, from the global view of the overall health status to the detailed status of a single device. Among them, the top view uses partition color blocks to intuitively mark healthy areas and abnormal areas, helping operation and maintenance personnel to quickly identify problem areas; the middle and bottom views provide more specific equipment status and trend analysis, making problem location and cause investigation more accurate. This hierarchical structure design enables complex operation data to be presented in an intuitive and clear manner, significantly improving the judgment efficiency of operation and maintenance personnel. The interactive visualization unit further expands the operational flexibility and convenience of operation and maintenance personnel. Through the screening panel, operation and maintenance personnel can dynamically update the view according to needs and quickly focus on specific areas, equipment and alarm information. In addition, the function of entering the device number and alarm ID greatly speeds up the location of the target device, and supports in-depth analysis and problem review in combination with the display of complete operation logs and historical alarm records. This interactivity and dynamism not only significantly improves operation and maintenance efficiency, but also avoids the problem of information lag in traditional static monitoring methods, ensuring that operation and maintenance personnel can respond quickly and make accurate decisions in complex situations, ultimately improving the safety and management efficiency of substation operations.

[0141] Example 7

[0142] Please refer to Figure 1 and Figure 2 , an intelligent visualization method for substation operation and maintenance, comprising the following steps:

[0143] S1, build a central processing server, and establish a communication connection between the sensor group installed on the transformer and the central processing server through a wireless network, and then transmit the substation equipment operation data collected in real time by the sensor group to the central processing server;

[0144] S2. Preprocessing the substation operation data through the central processor to obtain the risk data group, and constructing a time series repository, and storing the risk data group in the time series repository;

[0145] S3. Summarize and calculate the acquired risk data group to obtain the thermal stability index rwd, the insulation state index jyz and the insulation gas tightness index qmz, then summarize and calculate the thermal stability index rwd, the insulation state index jyz and the insulation gas tightness index qmz to obtain the comprehensive risk index sfx, and perform the substation equipment operation risk assessment with the preset equipment safety operation threshold A;

[0146] S4. When the risk assessment of substation operation shows abnormality, the central processing server constructs a dynamic optimization adjustment coefficient yht formula, adjusts the parameters according to historical normal data, and calculates and summarizes the comprehensive risk index sfx to obtain the risk fault assessment index tzy, and then conducts substation fault assessment with the preset equipment safety operation threshold A;

[0147] S5. Collect risk data groups and evaluate alarm information, build a hierarchical status display view, display the operating status and alarm information of the substation equipment in the area, and transmit it to the user end of the operation and maintenance personnel through the wireless network.

[0148] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An intelligent visualization system for substation operation and maintenance, characterized by: It includes data collection module, data integration module, abnormal analysis module, optimization and adjustment module and visualization module; The data acquisition module is used to construct a central processing server, and establish a communication connection between the sensor group installed on the transformer and the central processing server through a wireless network, and then transmit the substation equipment operation data collected in real time by the sensor group to the central processing server; The data integration module pre-processes the substation operation data through the central processor, obtains the risk data group, builds a time series repository, and stores the risk data group in the time series repository; The abnormal analysis module is used to perform summary calculations based on the acquired risk data group to obtain the thermal stability index rwd, the insulation state index jyz and the insulation gas tightness index qmz, and then summarize the thermal stability index rwd, the insulation state index jyz and the insulation gas tightness index qmz to obtain the comprehensive risk index sfx, and perform substation equipment operation risk assessment with the preset equipment safety operation threshold A; The optimization and adjustment module is used to construct a dynamic optimization adjustment coefficient yht formula through a central processing server when the risk assessment of substation operation is abnormal, adjust the parameters according to historical normal data, and summarize and calculate with the comprehensive risk index sfx to obtain the risk fault assessment index tzy, and then conduct substation equipment fault assessment with the preset equipment safety operation threshold A; The visualization module is used to collect risk data groups and evaluate alarm information, build a hierarchical status display view, display the operating status and alarm information of the substation equipment in the area, and transmit it to the user end of the operation and maintenance personnel through the wireless network.

2. The intelligent visualization system for substation operation and maintenance according to claim 1 is characterized by: The data acquisition module includes a data acquisition unit and a communication connection unit; The data acquisition unit collects the transformer substation equipment operation data of the transformer in real time through the sensor group installed on the transformer, sets the collection frequency of the sensor group to 5 minutes, and records the collection timestamp; The sensor group includes a temperature sensor, a viscosity sensor, a current sensor, a gas purity analyzer, a flow sensor, an electric field sensor, a pressure sensor and a laser leak monitor; The communication connection unit is used to construct a central processing server, establish a communication connection between the sensor group and the central processing server through a wireless network, and transmit the substation equipment operation data collected by the sensor group to the central processing server in real time.

3. The intelligent visualization system for substation operation and maintenance according to claim 2 is characterized by: The data integration module includes a data integration unit and a data storage unit; The data integration unit is used to pre-process the substation operation data transmitted to the central processing server. The pre-processing includes forming a change sequence set Q for the periodically collected equipment temperature wd, insulating oil viscosity nd and insulating gas purity cd, where Q = {wd, nd, cd}, and differential calculation to obtain the temperature gradient Δwd, the insulating oil viscosity gradient Δnd and the insulating gas purity gradient Δcd respectively. The specific algorithm formula is: Among them, Q i represents the i-th parameter in the change sequence set; Then, the substation equipment operation data is subjected to denoising, outlier detection and dimensionless processing to obtain a risk data group; The risk data group includes a thermal stability data group, an insulation factor data group and an airtight factor data group; The thermal stability data group includes the equipment temperature gradient ΔT, the cooling medium flow rate ll, the cooling medium inlet and outlet temperature difference wc and the actual load current sf; The insulation factor data set includes the partial discharge intensity fd, the insulating oil viscosity gradient Δnd and the leakage current value ld; The airtight factor data group includes the leakage rate xl, the insulating gas purity change gradient Δcd and the sealing pressure difference yc; The data storage unit is used to construct a time series repository, store the risk data group in the time series repository, and perform information marking on the parameters in the risk data group, wherein the information marking includes a sensor ID, a sensor location, and a data type.

4. The intelligent visualization system for substation operation and maintenance according to claim 3 is characterized by: The abnormality analysis module includes an abnormality analysis unit and a comprehensive risk analysis unit; The abnormality analysis unit is used to perform summary calculations based on the acquired thermal stability data group, insulation factor data group and airtight factor data group to obtain a thermal stability index rwd, an insulation state index jyz and an insulation gas airtight index qmz; The thermal stability index rwd, insulation state index jyz and insulation gas tightness index qmz are calculated and obtained by the following formulas respectively; Where I represents the rated current of the substation equipment, cp represents the specific heat capacity of the cooling medium, Δt represents the time interval between two samplings, and ln represents the logarithmic function.

5. The intelligent visualization system for substation operation and maintenance according to claim 4 is characterized by: The comprehensive risk analysis unit includes a comprehensive risk calculation unit and a comprehensive risk warning unit; The comprehensive risk calculation unit is used to perform summary calculation based on the obtained thermal stability index rwd, insulation state index jyz and insulation gas airtightness index qmz to obtain a comprehensive risk index sfx; The comprehensive risk index sfx is calculated by the following formula: Wherein, ln represents the logarithmic function.

6. The intelligent visualization system for substation operation and maintenance according to claim 5 is characterized by: The comprehensive risk alarm unit is used to extract the historical substation equipment operation data in the time series storage library, divide the historical data into normal data and abnormal data by cluster analysis, and then use the statistical method to calculate the peak value of the comprehensive risk index of normal data and the valley value of the comprehensive risk index of abnormal data, and extract the average value, and perform the preset equipment safety operation threshold value A, and then perform the substation equipment failure assessment with the obtained comprehensive risk index sfx. The specific assessment scheme is as follows; When the comprehensive risk index sfx>equipment safe operation threshold A, it indicates that there is an abnormality in the operation of the substation equipment, triggering the adjustment mechanism; When the comprehensive risk index sfx ≤ the equipment safe operation threshold A, it means that the substation equipment operates normally and maintains normal monitoring.

7. The intelligent visualization system for substation operation and maintenance according to claim 6 is characterized by: The optimization and adjustment module includes an optimization and adjustment unit and a fault assessment and analysis unit; The optimization and adjustment unit is used for the central processing server to analyze the causes of the abnormal parameters when the risk assessment of the operation of the substation equipment shows that there is an abnormality. The abnormal causes include parameter fluctuations and substation equipment failures caused by external emergencies. The central processing server corrects the abnormal parameters based on historical safety operation data and constructs a dynamic optimization adjustment coefficient yht; The dynamic optimization adjustment coefficient yht is calculated and obtained by the following formula: In the formula, sj i represents the actual measured value of the ith parameter, zc i Represents the safe value of the i-th parameter, a i It represents the optimization constant of the impact of the ith parameter on the overall risk, and n represents the number of abnormal parameters currently occurring.

8. The intelligent visualization system for substation operation and maintenance according to claim 7 is characterized by: The fault assessment and analysis unit includes a risk fault calculation unit and a risk fault assessment unit; The risk failure calculation unit is used to summarize and calculate the dynamic optimization adjustment coefficient yht and the comprehensive risk index sfx to obtain the risk failure evaluation index tzy; The risk failure assessment index tzy is calculated and obtained by the following formula: tzy=yht+k*sfx; In the formula, k represents the adjustment coefficient of the comprehensive risk index; The risk failure assessment unit is used to perform a substation equipment failure assessment based on the acquired risk failure assessment index tzy and the equipment safe operation threshold A, and deeply assess the cause of the substation equipment failure. The specific assessment scheme is as follows; When the risk fault assessment index tzy>equipment safe operation threshold A, it indicates that the adjustment is invalid and it is a hardware fault of the substation equipment. The serial number, specific location and fault cause of the substation equipment are marked, and risk information is generated. The risk information is transmitted to the user end of the operation and maintenance personnel through the wireless network to remind the operation and maintenance personnel to conduct substation equipment inspection; When the risk fault assessment index tzy≤equipment safe operation threshold A, it means that the substation equipment operation fault has returned to normal after adjustment. At this time, it is an abnormal fault of substation equipment parameters and normal monitoring is maintained.

9. The intelligent visualization system for substation operation and maintenance according to claim 1 is characterized by: The visualization module includes a chart display unit and an interactive visualization unit; The chart display unit constructs a hierarchical status display view in the central processing server, imports the risk data group and assessment alarm information collected in real time into the hierarchical status display view, and displays the operating status and alarm information of the substation equipment in the area. The hierarchical status display view includes a top view, a middle view and a bottom view; The top-level view displays the health status of the overall substation equipment through a partitioned color block diagram based on the risk data group and the assessment alarm information, and marks the healthy area in green, the area with abnormal data fluctuation in yellow, and the abnormalities that cannot be controlled by the central processing server in red, providing a global operation overview; The middle-level view is used to display the operating status and alarm information of the substation equipment in this area; The bottom-level view generates a line chart by combining the data acquisition timestamp to display the parameter change trend and current alarm record of a single substation equipment, and supports trend analysis and problem location; The interactive visualization unit is used to transmit the chart information of the chart display unit to the user end of the operation and maintenance personnel through the wireless network. The operation and maintenance personnel select the substation equipment, specific area and alarm level of concern through the screening panel, dynamically update the view, and quickly locate the target substation equipment by entering the substation equipment number and alarm ID, and display the complete operation log, historical alarm record and alarm cause of the substation equipment.

10. An intelligent visualization method for substation operation and maintenance, applied to an intelligent visualization system for substation operation and maintenance as claimed in any one of claims 1 to 9, characterized in that: The following steps are involved: S1, build a central processing server, and establish a communication connection between the sensor group installed on the transformer and the central processing server through a wireless network, and then transmit the substation equipment operation data collected in real time by the sensor group to the central processing server; S2. Preprocessing the substation operation data through the central processor to obtain the risk data group, and constructing a time series repository, and storing the risk data group in the time series repository; S3. Summarize and calculate the acquired risk data group to obtain the thermal stability index rwd, the insulation state index jyz and the insulation gas tightness index qmz, then summarize and calculate the thermal stability index rwd, the insulation state index jyz and the insulation gas tightness index qmz to obtain the comprehensive risk index sfx, and perform the substation equipment operation risk assessment with the preset equipment safety operation threshold A; S4. When the risk assessment of substation operation shows abnormality, the central processing server constructs a dynamic optimization adjustment coefficient yht formula, adjusts the parameters according to historical normal data, and calculates and summarizes the comprehensive risk index sfx to obtain the risk fault assessment index tzy, and then conducts substation fault assessment with the preset equipment safety operation threshold A; S5. Collect risk data groups and evaluate alarm information, build a hierarchical status display view, display the operating status and alarm information of the substation equipment in the area, and transmit it to the user end of the operation and maintenance personnel through the wireless network.

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