Multidimensional data collection method and system for power distribution communication control

Abstract

The present invention discloses a multidimensional data collection method and system for power distribution communication control, and specifically relates to the field of power communication technology: by formulating a multidimensional data collection scheme, monitoring the real-time operating status of communication equipment during the multidimensional data collection process, obtaining the data transmission efficiency outlier index, communication performance stability ratio and electric energy transmission rate floating value of the communication equipment during the monitoring process and performing comprehensive calculations, and judging whether the operating status of the communication equipment is abnormal based on the calculation results, the system can timely identify and confirm the abnormality, predict potential communication equipment problems in advance, and take measures to reduce the risk of failure. At the same time, when the operating status of the communication equipment is abnormal, the multidimensional data collection scheme can be adjusted, and the adjustment effect of the multi-source data collection scheme can be analyzed to determine the best multidimensional data collection scheme, which not only reduces the burden of manual intervention, but also improves the automation level of the system.

Description

Technical Field

[0001] The present invention relates to the field of power communication technology, and in particular to a multi-dimensional data collection method and system for power distribution communication control. Background Art

[0002] Distribution communication and control refers to the monitoring, management and control of power equipment, power quality and system operating status through communication and control technologies in the power distribution system. The power distribution system helps to improve the reliability and stability of the power grid, optimize power distribution, reduce fault recovery time and improve energy efficiency. However, the communication equipment in some distribution systems may be aging, and when the performance of the communication equipment deteriorates, if the management personnel cannot find it in time, the potential faults may not be monitored in time. At the same time, when the communication equipment cannot transmit the data required for communication to the management personnel in time, the communication control of the distribution system may not be accurate, which will increase the risk of failure and control of the distribution system. Summary of the invention

[0003] The purpose of the present invention is to provide a multi-dimensional data collection method and system for power distribution communication control to solve the deficiencies in the background technology.

[0004] In order to achieve the above object, the present invention provides the following technical solution: a multi-dimensional data collection method for power distribution communication control, comprising the following steps:

[0005] S1: Develop a multi-dimensional data collection plan based on the communication control requirements in the power distribution system, and determine the number of sensors and communication devices for collecting power distribution data in different dimensions;

[0006] S2: monitor the real-time operation status of the communication equipment during the multi-dimensional data collection process, and obtain the data transmission efficiency outlier index, communication performance stability ratio and power transmission rate floating value of the communication equipment during the monitoring process;

[0007] S3: Build a communication equipment operation status prediction model, input the data transmission efficiency outlier index, communication performance stability ratio, and power transmission rate floating value into the model for comprehensive calculation, and judge whether the operation status of the communication equipment is abnormal based on the calculation results;

[0008] S4: When the operation state of the communication device is abnormal, the multi-dimensional data collection scheme is adjusted, and the collection conversion correction index of the multi-dimensional data and the communication error offset ratio during the adjustment process are obtained;

[0009] S5: Analyze the adjustment effect of the multi-source data collection scheme when the communication equipment is in an abnormal operating state by combining the collection conversion correction index and the communication error offset ratio, and determine the best multi-dimensional data collection scheme based on the adjustment effect.

[0010] In a preferred embodiment, in S2, an outlier index of data transmission efficiency, a stable ratio of communication performance, and a floating value of power transmission rate of the communication device during monitoring are obtained;

[0011] The logic for obtaining the data transmission efficiency outlier index is: obtain the data transmission efficiency of the communication equipment during the monitoring process, and the calculation expression is: In the formula, wr k is the data transmission efficiency, wq s is the amount of data transmitted, dh r Total time to transmit data, dh t For transmission delay, calculate the mean value of data transmission efficiency. The calculation expression is: In the formula, μ is the mean value of data transmission efficiency, N is the number of data transmissions; the standard deviation of the data is calculated as follows: In the formula, X i is the value of the ith data point, σ is the standard deviation of the data, Represents the sum of the squares of the differences between each data point in the data set and the mean of the data set, and calculates the outlier index of data transmission efficiency. The calculation expression is: In the formula, qr z is the data transmission efficiency outlier index;

[0012] The logic for obtaining the stable ratio of communication performance is as follows: obtain the number of communication devices H performing data communication during real-time monitoring and label them, H = 1, 2, 3...r, r is a positive integer greater than 0, obtain the continuous effective working time of each communication device in the s time period, and the calculation expression is: st = s-pk, where st is the continuous effective working time, pk is the failure time of the communication device in the s time period, and obtain the preset standard range of the continuous effective working time of each communication device: st min ~st max , obtain the number y of effective working time of communication equipment within the standard range, calculate the stable ratio of communication performance, and the calculation expression is: Where tk s To stabilize the ratio for communication performance;

[0013] The logic for obtaining the floating value of the power transmission rate is as follows: in the real-time monitoring process, the power transmission rate we is obtained each time the power system performs power regulation, and the power transmission rate set we = {we n}={we1,we2,we3...we n}, n is a positive integer, calculate the average power transfer rate we y , calculate the floating value of the power transfer rate, the calculation expression is: In the formula, ky l It is the floating value of power transfer rate.

[0014] In a preferred embodiment, in S3, a communication equipment operation status prediction model is constructed, and the data transmission efficiency outlier index, communication performance stability ratio, and power transmission rate floating value are input into the model for comprehensive calculation;

[0015] The acquired data transmission efficiency outlier index, communication performance stability ratio, and power transmission rate floating value are input into the pre-built communication equipment operation status prediction model for comprehensive calculation, and the operation status coefficient of the communication equipment is calculated. The calculation expression is: In the formula, fr s is the operating state coefficient, qr z is the data transmission efficiency outlier index, tk s is the communication performance stability ratio, ky l is the floating value of the power transmission rate, a1, a2, and a3 are the proportional coefficients of the data transmission efficiency outlier index, the communication performance stability ratio, and the power transmission rate floating value, and a2>a1>a3>0.

[0016] In a preferred embodiment, judging whether the operation state of the communication device is abnormal according to the calculation result;

[0017] If the operating state coefficient is less than or equal to the operating state threshold, a communication abnormality signal is generated at this time, and if the operating state coefficient is greater than the operating state threshold, a communication normal signal is generated at this time.

[0018] In a preferred embodiment, in S4, the acquisition conversion correction index of the multidimensional data during the adjustment process and the communication error offset ratio are obtained;

[0019] The acquisition logic of the acquisition conversion correction index is: the number of data conversions mt in the multidimensional data acquisition process before the acquisition scheme is adjusted g And the number of data corrections gk y , and the number of data conversions in the multidimensional data collection process after the scheme is adjusted g and data correction times ml y , calculate the acquisition conversion correction index, the calculation expression is: In the formula, rh k is the collection conversion correction index, c is the number of matching samples, K is the total number of samples, and j is the number of data matches;

[0020] The logic for obtaining the communication error offset ratio is: obtaining the number of data tp that is correctly transmitted in data transmission due to abnormal operation of the communication device y , and obtain the total amount of data np transmitted by the communication device within w time y , the calculation expression is: In the formula, rkn is the communication error offset ratio.

[0021] In a preferred embodiment, in S5, the adjustment effect of the communication device on the multi-source data acquisition scheme when the operation state is abnormal is analyzed in combination with the acquisition conversion correction index and the communication error offset ratio;

[0022] After comprehensively calculating the acquisition conversion correction index and the communication error offset ratio, a multi-source data acquisition scheme adjustment effect evaluation model is constructed, and the scheme adjustment effect evaluation coefficient is calculated. The calculation expression is: In the formula, gx h To adjust the effect evaluation coefficient, rh k To collect the conversion correction index, rk n is the communication error offset ratio, β1 and β2 are the proportional coefficients of the acquisition conversion correction index and the communication error offset ratio, and β2>β1>0;

[0023] The obtained multi-source data acquisition scheme adjustment effect evaluation coefficient is compared with the standard threshold. If the adjustment effect evaluation coefficient is greater than or equal to the standard threshold, a normal signal is generated; if the adjustment effect evaluation coefficient is less than the standard threshold, an abnormal signal is generated.

[0024] The present invention also provides a multi-dimensional data acquisition system for power distribution communication control, including a program formulation module, a data acquisition module, an abnormality judgment module, a monitoring module and an analysis and adjustment module;

[0025] Solution formulation module: formulates corresponding multi-dimensional data collection schemes according to the communication control requirements in the power distribution system, and determines the number of sensors and communication devices for collecting power distribution data in different dimensions;

[0026] Data acquisition module: monitors the real-time operating status of the communication equipment during the multi-dimensional data collection process, and obtains the data transmission efficiency outlier index, communication performance stability ratio and power transmission rate floating value of the communication equipment during the monitoring process;

[0027] Abnormal judgment module: Build a communication equipment operation status prediction model, input the data transmission efficiency outlier index, communication performance stability ratio, and power transmission rate floating value into the model for comprehensive calculation, and judge whether the operation status of the communication equipment is abnormal based on the calculation results;

[0028] Monitoring module: When the operation status of the communication equipment is abnormal, the multi-dimensional data collection plan is adjusted, and the collection conversion correction index of the multi-dimensional data and the communication error offset ratio are obtained during the adjustment process.

[0029] Analysis and adjustment module: Combined with the acquisition conversion correction index and the communication error offset ratio, it analyzes the adjustment effect of the communication equipment on the multi-source data acquisition plan when the operation status is abnormal, and determines the best multi-dimensional data acquisition plan based on the adjustment effect.

[0030] In the above technical solution, the technical effects and advantages provided by the present invention are:

[0031] 1. The present invention formulates a multi-dimensional data acquisition plan according to the communication control requirements in the power distribution system, determines the number of acquisition sensors and communication equipment for power distribution data of different dimensions, and monitors the real-time operating status of the communication equipment during the multi-dimensional data acquisition process. The data transmission efficiency outlier index, communication performance stability ratio and power transmission rate floating value of the communication equipment during the monitoring process are obtained and input into the prediction model for comprehensive calculation, and judges whether the operating status of the communication equipment is abnormal based on the calculation results. Through real-time monitoring and comprehensive calculation, the system can timely discover the abnormality of the operating status of the communication equipment, predict potential communication equipment problems in advance, take measures to reduce the risk of failure, and improve the stability and reliability of the system.

[0032] 2. The present invention adjusts the multidimensional data collection scheme when the operation state of the communication device is abnormal, obtains the collection conversion correction index of the multidimensional data and the communication error offset ratio during the adjustment process, analyzes the adjustment effect of the communication device on the multi-source data collection scheme when the operation state is abnormal, and determines the optimal multidimensional data collection scheme based on the adjustment effect. By real-time monitoring and analyzing the adjustment effect, the system has adaptability, and can flexibly adjust the multidimensional data collection scheme according to the operation status of the communication device, thereby improving the adaptability of the system. At the same time, the system can automatically judge and adjust the data collection scheme, reducing the burden of manual intervention and improving the automation of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0034] Figure 1 This is a flow chart of the multi-dimensional data collection method for power distribution communication control.

[0035] Figure 2 This is a module diagram of the multi-dimensional data acquisition system for power distribution communication control. DETAILED DESCRIPTION

[0036] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, 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.

[0037] Example 1

[0038] See also Figure 1 , 2 As shown, the multi-dimensional data collection method for power distribution communication control described in this embodiment includes the following steps:

[0039] S1: Develop a multi-dimensional data collection plan based on the communication control requirements in the power distribution system, and determine the number of sensors and communication devices for collecting power distribution data in different dimensions;

[0040] S2: monitor the real-time operation status of the communication equipment during the multi-dimensional data collection process, and obtain the data transmission efficiency outlier index, communication performance stability ratio and power transmission rate floating value of the communication equipment during the monitoring process;

[0041] S3: Build a communication equipment operation status prediction model, input the data transmission efficiency outlier index, communication performance stability ratio, and power transmission rate floating value into the model for comprehensive calculation, and judge whether the operation status of the communication equipment is abnormal based on the calculation results;

[0042] S4: When the operation state of the communication device is abnormal, the multi-dimensional data collection scheme is adjusted, and the collection conversion correction index of the multi-dimensional data and the communication error offset ratio during the adjustment process are obtained;

[0043] S5: Analyze the adjustment effect of the multi-source data collection scheme when the communication equipment is in an abnormal operating state by combining the collection conversion correction index and the communication error offset ratio, and determine the best multi-dimensional data collection scheme based on the adjustment effect.

[0044] Among them, a corresponding multi-dimensional data collection plan is formulated according to the communication control requirements in the power distribution system, and the number of sensors and communication equipment for collecting power distribution data in different dimensions is determined, specifically:

[0045] Multi-dimensional data collection solution:

[0046] Current, voltage, and power data collection, sensor selection: Current sensor: Use a clamp-type current sensor and install one for each cable or device that needs to be monitored. Voltage sensor: Select a voltage transformer or voltage divider and install one for each cable or device that needs to be monitored. Power sensor: Calculated by current and voltage sensors, no additional power sensor is required.

[0047] Communication equipment configuration, PLC or RTU: Each cable or device that needs to be monitored is connected to a PLC or RTU for real-time data acquisition and control. Communication module: Each PLC or RTU is connected to a communication module to achieve communication with the monitoring center. Data collector: The central data collector summarizes the data of all PLCs or RTUs and is responsible for further processing and transmission.

[0048] Power quality data collection, sensor selection: Power quality analyzer: one is installed for each cable or device that needs to be monitored, which is used to monitor power quality parameters such as harmonics, voltage fluctuations, voltage sags, etc. Communication equipment configuration: connected to PLC or RTU, and transmits power quality data to the central data collector through the communication module.

[0049] Temperature and humidity data collection, sensor selection: Temperature and humidity sensors: Install the corresponding number of sensors according to the location and equipment distribution to be monitored. Communication equipment configuration: Connect to PLC or RTU, and transmit temperature and humidity data to the central data collector through the communication module.

[0050] Equipment status data collection, sensor selection: Equipment status sensor: such as switch status sensor, fault detection sensor, installed on each device or switch as needed. Communication device configuration: connected to PLC or RTU, the equipment status data is transmitted to the central data collector through the communication module.

[0051] The number of communication devices, according to the topology of the power distribution system, the number of devices includes: the number of PLCs or RTUs, which matches the number of cables or devices that need to be monitored. The number of communication modules, each PLC or RTU is connected to a communication module. Data collector: a central data collector. Communication protocol: configure the communication protocol used between communication devices, such as Modbus, DNP3, etc., to ensure the effective transmission of data. Security: introduce encryption and authentication mechanisms to ensure the security of communication. Consider using secure communication protocols and network isolation. Redundant design, introduce redundancy on key communication links, such as dual communication modules or dual PLC configurations, to improve the stability and reliability of the system. Data transmission frequency, determine the frequency of data collection and transmission based on monitoring requirements and equipment response speed. It can be adjusted according to real-time requirements.

[0052] Monitor the real-time operating status of communication equipment during multi-dimensional data collection to ensure the real-time operating status of communication equipment during multi-dimensional data collection, and be able to respond to potential problems in a timely manner to ensure stable operation of the system. Specifically:

[0053] SNMP (Simple Network Management Protocol) monitoring: Use SNMP tools to monitor the performance and status of devices. By configuring the SNMP agent, you can obtain real-time information such as CPU utilization, memory usage, network traffic, etc. of communication devices. Common SNMP monitoring tools include Nagios, Cacti, Zabbix, etc.

[0054] Ping and Traceroute to check network connectivity: Use the Ping command regularly to check network connectivity between the communication device and other devices. For connectivity issues, use the Traceroute command to track the network path to help locate the problem.

[0055] Power monitoring equipment: Use professional power monitoring equipment to monitor the power status of communication equipment. These devices can provide information such as voltage, current, and power, and can issue real-time alarms once power problems are detected.

[0056] Device logs and Syslog records: Configure the device to generate detailed log records and use the Syslog service for centralized storage. By analyzing the log files, you can understand the operating status of the device and detect anomalies in a timely manner. ELK Stack (Elasticsearch, Logstash, Kibana) is a commonly used log management tool.

[0057] Equipment self-health check mechanism: Implement a self-health check mechanism in the communication equipment, including periodically executing self-check procedures, checking hardware status, monitoring key processes, etc. If an abnormality is found during the self-check process, the device can automatically issue an alarm and take corresponding measures.

[0058] Remote terminal monitoring: Configure remote terminal monitoring tools, such as SSH or Telnet. By remotely connecting to communication devices, you can monitor the operating status of the device in real time, including system load, connection status, configuration information, etc.

[0059] Containerization and microservice monitoring: If the communication equipment adopts containerization or microservice architecture, you can use specialized monitoring tools such as Prometheus and Grafana. These tools can provide real-time container and service status, performance indicators and other information.

[0060] Obtaining the data transmission efficiency outlier index of the communication device during the monitoring process, obtaining the transmission efficiency of the communication device in real time during the monitoring process, and detecting whether there is an abnormality, the transmission efficiency outlier index of the communication device can be obtained by the following steps;

[0061] The logic for obtaining the data transmission efficiency outlier index is: obtain the data transmission efficiency of the communication equipment during the monitoring process, and the calculation expression is: In the formula, wr k is the data transmission efficiency, wq s is the amount of data transmitted, dh r Total time to transmit data, dh t For transmission delay, calculate the mean value of data transmission efficiency. The calculation expression is: In the formula, μ is the mean value of data transmission efficiency, N is the number of data transmissions; the standard deviation of the data is calculated as follows: In the formula, X i is the value of the ith data point, σ is the standard deviation of the data, Represents the sum of the squares of the differences between each data point in the data set and the mean of the data set, and calculates the outlier index of data transmission efficiency. The calculation expression is: In the formula, qr z is the data transmission efficiency outlier index;

[0062] When the data transmission efficiency outlier index is larger, it indicates that the communication equipment has abnormal data transmission efficiency. A larger outlier index indicates that the data transmission efficiency of one or some aspects is significantly different from the normal situation, and the operation status of the communication equipment is abnormal, which requires further attention and investigation.

[0063] Specifically, a large data transfer efficiency outlier index indicates the following:

[0064] Performance degradation: The performance of the communication equipment has been degraded during the data transmission process. The transmission efficiency may be lower than normal due to network congestion, hardware failure, software problems, etc.

[0065] Network issues: Network communication may be affected, such as increased packet loss, insufficient bandwidth, etc. This may result in decreased data transmission efficiency.

[0066] Increased transmission delay: Increased data transmission delay may cause longer response time of communication equipment, thus affecting overall efficiency.

[0067] Abnormal events: Sudden fluctuations in data transmission efficiency may be associated with abnormal events occurring in the system, such as malicious attacks, equipment failures, or configuration errors.

[0068] It is to be noted that in actual monitoring and management, when the data transmission efficiency outlier index is larger, the system administrator or the monitoring system may receive an alarm notification, indicating that there may be a problem with the operating status of the communication equipment.

[0069] The communication performance stability ratio refers to the ratio of the number of communication devices with stable communication performance during information data transmission to the total number of communication devices. The communication performance stability ratio can be obtained by the ability of communication devices to continuously and stably operate over a long period of time.

[0070] The logic for obtaining the stable ratio of communication performance is as follows: obtain the number of communication devices H performing data communication during real-time monitoring and label them, H = 1, 2, 3...r, r is a positive integer greater than 0, obtain the continuous effective working time of each communication device in the s time period, and the calculation expression is: st = s-pk, where st is the continuous effective working time, pk is the failure time of the communication device in the s time period, and obtain the preset standard range of the continuous effective working time of each communication device: st min ~st max , obtain the number y of effective working time of communication equipment within the standard range, calculate the stable ratio of communication performance, and the calculation expression is: Where tk s To stabilize the ratio for communication performance;

[0071] The communication performance stability ratio reflects the ratio of the communication equipment to maintain a stable state over a period of time. A larger stability ratio means that the communication equipment can maintain good performance most of the time. When the communication performance stability ratio is larger, it has the following main effects on judging whether the operation status of the communication equipment is abnormal:

[0072] Normal operation probability: The communication performance stability ratio roughly reflects the probability that the communication equipment is in normal operation. A higher stability ratio means that the communication equipment is more likely to be in normal operation.

[0073] Predictive maintenance: A high communication performance stability ratio helps implement predictive maintenance strategies. System administrators can predict the operating status of equipment and take preventive measures to prevent potential problems from occurring.

[0074] Reduce fault recovery time: When the stability ratio of communication equipment is high, faults may occur less frequently. Even if a fault occurs, it is easier to quickly restore normal operation and reduce the impact on users.

[0075] The floating value of the power transmission rate reflects the overall stability and reliability of the power system to a certain extent. In the power system, the sharp fluctuation of the power transmission rate may be caused by load changes, fluctuations in renewable energy, system failures, etc. If this fluctuation is serious enough to affect the stability of the power system, it will have some impact on the communication equipment.

[0076] The logic for obtaining the floating value of the power transmission rate is as follows: in the real-time monitoring process, the power transmission rate we is obtained each time the power system performs power regulation, and the power transmission rate set we = {we n}={we1,we2,we3...we n}, n is a positive integer, calculate the average power transfer rate we y , calculate the floating value of the power transfer rate, the calculation expression is: In the formula, ky l It is the floating value of power transmission rate;

[0077] The larger the floating value of the power transmission rate, the more impact it will have on the operating status of the communication equipment. Large fluctuations in the power transmission rate may be accompanied by changes in the current and electromagnetic field in the power system. These changes may cause electromagnetic interference and affect the transmission quality of communication signals. Communication equipment may be subject to electromagnetic interference in such an environment, resulting in a decrease in signal quality.

[0078] Construct a communication equipment operation status prediction model, and input the data transmission efficiency outlier index, communication performance stability ratio, and power transmission rate floating value into the model for comprehensive calculation;

[0079] The acquired data transmission efficiency outlier index, communication performance stability ratio, and power transmission rate floating value are input into the pre-built communication equipment operation status prediction model for comprehensive calculation, and the operation status coefficient of the communication equipment is calculated. The calculation expression is: In the formula, fr s is the operating state coefficient, qr z is the data transmission efficiency outlier index, tk s is the communication performance stability ratio, ky l is the floating value of the power transmission rate, a1, a2, and a3 are the proportional coefficients of the data transmission efficiency outlier index, the communication performance stability ratio, and the power transmission rate floating value, and a2>a1>a3>0.

[0080] It should be noted that the size of the preset proportional coefficient is a specific value obtained by quantifying each parameter. In order to facilitate subsequent comparison, the size of the coefficient depends on the amount of sample data and the preliminary setting of the corresponding preset proportional coefficient for each group of sample data by technical personnel in this field. The coefficient is not unique as long as it does not affect the proportional relationship between the parameter and the quantized value. For example, the data transmission efficiency outlier index is inversely proportional to the operating status coefficient.

[0081] Determine whether the operation state of the communication device is abnormal according to the calculated operation state coefficient of the communication device;

[0082] The acquired operation state coefficient of the communication device is compared with the operation state threshold. If the operation state coefficient is greater than the operation state threshold, it indicates that the communication device is in a stable communication state, and a communication normal signal is generated at this time.

[0083] If the operating status coefficient is less than or equal to the operating status threshold, it means that the communication equipment is in an extremely unstable communication state. In this case, a communication abnormality signal is generated. When the management personnel receives the communication abnormality signal, they can perform remote troubleshooting, configuration modification or system restart through the remote management system to maintain and manage the abnormal communication equipment.

[0084] In this embodiment, a multi-dimensional data collection plan is formulated according to the communication control requirements in the power distribution system, the number of collection sensors and communication equipment for power distribution data of different dimensions is determined, and the real-time operating status of the communication equipment during the multi-dimensional data collection process is monitored. The data transmission efficiency outlier index, communication performance stability ratio and power transmission rate floating value of the communication equipment during the monitoring process are obtained and input into the prediction model for comprehensive calculation, and the operation status of the communication equipment is judged according to the calculation results. Whether there is any abnormality, through real-time monitoring and comprehensive calculation, the system can timely discover the abnormality of the operation status of the communication equipment, predict potential communication equipment problems in advance, take measures to reduce the risk of failure, and improve the stability and reliability of the system. At the same time, the automated monitoring and prediction system can improve the operation and maintenance efficiency, reduce the need for human intervention, and reduce maintenance costs.

[0085] Example 2

[0086] In S4, when the operation state of the communication device is abnormal, the multi-dimensional data collection scheme is adjusted, and the collection conversion correction index of the multi-dimensional data and the communication error offset ratio in the adjustment process are obtained. When the operation state of the communication device is abnormal, the multi-dimensional data collection scheme may need to be adjusted. The specific adjustment scheme will depend on the nature and cause of the abnormality, and the main contents are:

[0087] If the anomaly is related to a fast change in the operating status of the communication equipment, consider increasing the frequency of data collection to monitor the equipment status more frequently and improve the sensitivity of anomaly detection. Move or rearrange sensors to ensure that they better cover the key parts of the communication equipment. It may be necessary to make a reasonable sensor layout based on the physical structure of the equipment and the characteristics of the anomaly.

[0088] Introduce new sensors into existing multi-dimensional data collection schemes to obtain more relevant information. For example, introduce temperature sensors, humidity sensors, etc. to monitor the environmental conditions of communication equipment. Introduce updated data processing algorithms to better adapt to new abnormal patterns. This may involve re-adjusting thresholds, updating outlier detection algorithms, or introducing more complex models to handle new data patterns.

[0089] If the anomaly is related to the mutual interference or layout between communication devices, it may be necessary to optimize the layout of the devices to reduce mutual influence and improve communication quality. Introduce a redundancy mechanism so that a seamless switch to a backup device can be achieved when one communication device fails. This helps improve the stability and reliability of the system.

[0090] If the anomaly may be caused by a security threat, consider strengthening the security measures of communication equipment, including network protection, intrusion detection, etc., to prevent unauthorized access or attacks. Deploy a remote monitoring and management system so that operation and maintenance personnel can monitor the status of equipment in real time remotely, make remote adjustments and management, and reduce dependence on the site.

[0091] It should be noted that the selection of adjustment schemes needs to be determined according to the specific abnormal situation and system requirements. The key is to monitor in real time and adjust the multi-dimensional data collection scheme according to the specific situation to ensure a quick and effective response to the abnormality.

[0092] Acquire the acquisition conversion correction index and communication error offset ratio of multi-dimensional data during the adjustment process. The acquisition conversion correction index is usually used to measure the effect of the conversion and correction operations that occur during the data acquisition process. It can reflect the accuracy and credibility of the data during the acquisition process, especially when it comes to conversion and correction;

[0093] If data is transformed during the collection process (e.g., unit conversion, standardization, etc.), the index can reflect the impact of this transformation. Good transformation operations should make the data easier to understand, compare, and analyze. At the same time, when the collected data are wrong or inaccurate, correction operations may be required to correct these problems. The collection transformation correction index will evaluate the degree of improvement of the data by the correction operation.

[0094] The acquisition logic of the acquisition conversion correction index is: the number of data conversions mt in the multidimensional data acquisition process before the acquisition scheme is adjusted gAnd the number of data corrections gk y , and the number of data conversions in the multidimensional data collection process after the scheme is adjusted g and data correction times ml y , calculate the acquisition conversion correction index, the calculation expression is: In the formula, rh k is the collection conversion correction index, c is the number of matching samples, K is the total number of samples, and j is the number of data matches;

[0095] The larger the acquisition conversion correction index is, the better the adjustment effect of the communication equipment on the multi-source data acquisition scheme is when the operation status is abnormal. It reflects the effect of the conversion and correction operations performed during the data acquisition process. The larger the index is, the more effective the adjustment operation is, and the quality and accuracy of the data have been improved.

[0096] Specifically, a large acquisition conversion correction index may indicate the following:

[0097] Effective data transformation: Data transformation operations performed during the collection process are more successful. The data may have been converted, standardized, or otherwise transformed as expected, making data from different sources more comparable.

[0098] Good correction effect: If there are data errors or inaccuracies, a large collection conversion correction index may indicate that the correction operation is effective. The corrected data is more in line with the actual situation and reduces the errors that may be caused by abnormal conditions.

[0099] Improved data consistency: The increase in the conversion correction index may mean that the consistency of the data in different dimensions has been improved. This is crucial for the effectiveness of multi-source data collection schemes and comprehensive analysis of data.

[0100] Conformance to expected standards and formats: A larger acquisition conversion correction index may also indicate that the data is more conformant to expected standards and formats, helping to improve the interpretability and usability of the data.

[0101] In general, a larger acquisition conversion correction index is a positive signal, indicating that the system makes the data more reliable and in line with expectations by adjusting the multi-source data acquisition scheme under abnormal conditions.

[0102] The communication error offset ratio can quantitatively reflect the degree of influence of the communication equipment on data transmission under abnormal conditions. A lower error offset ratio indicates that the data transmission is relatively stable, while a higher error offset ratio may indicate that the abnormality of the communication equipment affects the accuracy and integrity of the data.

[0103] The logic for obtaining the communication error offset ratio is: obtaining the number of data tp that is correctly transmitted in data transmission due to abnormal operation of the communication devicey , and obtain the total amount of data np transmitted by the communication device within w time y The communication error offset ratio refers to the ratio of the data transmission error caused by abnormal operation of the communication equipment during the communication process to the total data transmission volume. The calculation expression is: In the formula, rk n is the communication error offset ratio;

[0104] The larger the communication error offset ratio, the worse the adjustment effect of the multi-source data acquisition scheme when the communication equipment is in abnormal operation. A larger ratio means that the abnormality interferes with data transmission more significantly. Specifically:

[0105] Unstable communication: A large error offset ratio may mean that the communication device is unable to maintain a stable communication connection under abnormal conditions. This may lead to packet loss, increased transmission delays, or even complete interruption.

[0106] Degraded data transmission quality: A high error offset ratio may lead to increased errors in data transmission, affecting the integrity and accuracy of the data. Data may be damaged or distorted during transmission.

[0107] Data inconsistency: A large error offset ratio may cause data inconsistency between different sources. If the various data sources are subject to different degrees of communication interference, the consistency of the data may be affected.

[0108] Poor Adjustment: A high error offset ratio may indicate poor adaptation and adjustment measures to abnormal conditions. The communication equipment may not be able to effectively respond to the abnormality, resulting in the data collection plan not being adjusted correctly.

[0109] It should be noted here that in practical applications, in order to ensure the stability and accuracy of the multi-source data acquisition solution under abnormal conditions of communication equipment, a series of measures are usually required, such as using redundant data transmission mechanisms, error detection and correction technology, optimizing communication protocols, etc. Large error offset ratios may require further analysis and improvement to improve the robustness of communication equipment under abnormal conditions.

[0110] Combined with the acquisition conversion correction index and the communication error offset ratio, the adjustment effect of the communication equipment on the multi-source data acquisition plan when the operation status is abnormal is analyzed, and the optimal multi-dimensional data acquisition plan is determined based on the adjustment effect;

[0111] After comprehensively calculating the acquisition conversion correction index and the communication error offset ratio, a multi-source data acquisition scheme adjustment effect evaluation model is constructed, and the scheme adjustment effect evaluation coefficient is calculated. The calculation expression is: In the formula, gx h To adjust the effect evaluation coefficient, rh kTo collect the conversion correction index, rk n is the communication error offset ratio, β1 and β2 are the proportional coefficients of the acquisition conversion correction index and the communication error offset ratio, and β2>β1>0.

[0112] The obtained adjustment effect evaluation coefficient of the multi-source data acquisition scheme is compared with the standard threshold. If the adjustment effect evaluation coefficient is greater than or equal to the standard threshold, it means that the adjustment effect of the multi-source data acquisition scheme is better after adjustment, and a normal signal is generated at this time; if the adjustment effect evaluation coefficient is less than the standard threshold, it means that the adjustment effect of the multi-source data acquisition scheme is poor after adjustment, and an abnormal signal is generated at this time.

[0113] After generating a normal or abnormal signal, the system can immediately take corresponding measures. For example, for a normal signal, the system can continue to operate normally; for an abnormal signal, the system can issue an alarm, notify the operation and maintenance personnel, start the backup plan, etc., so as to deal with the problem in time.

[0114] Early warning signals allow managers to promptly detect and address situations where the adjustment of multi-source data collection solutions is ineffective, helping to prevent problems from spreading further and affecting other system components. This also helps maintain system stability and reliability. Real-time monitoring and timely response to abnormal situations help maintain system stability and performance. When the adjustment effect is poor, timely measures can reduce potential data quality issues and ensure system operation. By making timely adjustments to the multi-source data collection solution, the performance and efficiency of the system can be optimized, ensuring that the data collection process proceeds as expected, and improving the accuracy and reliability of the data.

[0115] When determining the best multi-dimensional data collection solution, the system can take the following specific measures:

[0116] Re-adjusting the data collection plan: If the generated signal indicates that the adjustment is not effective, the system can automatically trigger the process of re-adjusting the data collection plan. This may involve reconfiguring sensors, adjusting data sampling frequency, optimizing data transmission protocols, etc. The system can use adaptive algorithms or automation tools to make these adjustments to better adapt to real-time environmental changes.

[0117] Notify relevant personnel to perform manual intervention: If the adjustment effect is poor and manual intervention is required, the system can automatically generate a notification to notify the relevant operation and maintenance personnel or data scientists to perform manual intervention. The notification can include a detailed description of the problem, recommended adjustment measures, and possible impacts. Manual intervention can include manually adjusting configuration parameters, checking device status, and conducting field investigations.

[0118] Record and analyze adjustment history: The system can record the adjustment history of each data collection plan, including the status before adjustment, the effect after adjustment, the measures taken, etc. Such historical records help the system learn and improve, and deal with similar problems more intelligently in future adjustments.

[0119] Implement automated decision-making strategies: Based on historical data and experience of adjustment effects, the system can implement automated decision-making strategies. This can include predefined rules, machine learning algorithms, or expert systems to automatically select the best data collection solution adjustment method based on actual conditions.

[0120] Monitor system performance: After determining the best multi-dimensional data collection solution, the system should continue to monitor system performance to ensure that the adjustment effect can continue to provide the best performance. If the system performance is abnormal again, the corresponding adjustment and intervention process can be triggered.

[0121] In this embodiment, when the operation state of the communication device is abnormal, the multi-dimensional data collection scheme is adjusted, and the collection conversion correction index of the multi-dimensional data and the communication error offset ratio during the adjustment process are obtained. The adjustment effect of the communication device on the multi-source data collection scheme when the operation state is abnormal is analyzed in combination with the collection conversion correction index and the communication error offset ratio, and the optimal multi-dimensional data collection scheme is determined based on the adjustment effect. By real-time monitoring and analysis of the adjustment effect, the system has adaptability and can flexibly adjust the multi-dimensional data collection scheme according to the operation status of the communication device, thereby improving the adaptability of the system. At the same time, the system can automatically judge and adjust the data collection scheme, reducing the burden of manual intervention and improving the automation level of the system.

[0122] Example 3

[0123] The multi-dimensional data acquisition system for power distribution communication control described in this embodiment includes a plan formulation module, a data acquisition module, an abnormality judgment module, a monitoring module and an analysis and adjustment module;

[0124] in,

[0125] Solution formulation module: formulates corresponding multi-dimensional data collection schemes according to the communication control requirements in the power distribution system, and determines the number of sensors and communication devices for collecting power distribution data in different dimensions;

[0126] Data acquisition module: monitors the real-time operating status of the communication equipment during the multi-dimensional data collection process, and obtains the data transmission efficiency outlier index, communication performance stability ratio and power transmission rate floating value of the communication equipment during the monitoring process;

[0127] Abnormal judgment module: Build a communication equipment operation status prediction model, input the data transmission efficiency outlier index, communication performance stability ratio, and power transmission rate floating value into the model for comprehensive calculation, and judge whether the operation status of the communication equipment is abnormal based on the calculation results;

[0128] Monitoring module: When the operation status of the communication equipment is abnormal, the multi-dimensional data collection plan is adjusted, and the collection conversion correction index of the multi-dimensional data and the communication error offset ratio are obtained during the adjustment process.

[0129] Analysis and adjustment module: Combined with the acquisition conversion correction index and the communication error offset ratio, it analyzes the adjustment effect of the communication equipment on the multi-source data acquisition plan when the operation status is abnormal, and determines the best multi-dimensional data acquisition plan based on the adjustment effect.

[0130] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

Claims

1. A multi-dimensional data collection method for power distribution communication control, characterized by: The steps include: S1: Develop a multi-dimensional data collection plan based on the communication control requirements in the power distribution system, and determine the number of sensors and communication devices for collecting power distribution data in different dimensions; S2: monitor the real-time operation status of the communication equipment during the multi-dimensional data collection process, and obtain the data transmission efficiency outlier index, communication performance stability ratio and power transmission rate floating value of the communication equipment during the monitoring process; S3: Build a communication equipment operation status prediction model, input the data transmission efficiency outlier index, communication performance stability ratio, and power transmission rate floating value into the model for comprehensive calculation, and judge whether the operation status of the communication equipment is abnormal based on the calculation results; Step S3 specifically includes: inputting the acquired data transmission efficiency outlier index, communication performance stability ratio, and power transmission rate floating value into a pre-built communication equipment operation status prediction model for comprehensive calculation, and calculating the operation status coefficient of the communication equipment, and the calculation expression is: In the formula, fr s is the operating state coefficient, qr z is the data transmission efficiency outlier index, tk s is the communication performance stability ratio, ky l is the floating value of the power transmission rate, a1, a2, and a3 are the proportional coefficients of the data transmission efficiency outlier index, the communication performance stability ratio, and the floating value of the power transmission rate, and a2>a1>a3>0; according to the calculation result, it is judged whether the operation state of the communication equipment is abnormal; if the operation state coefficient is less than or equal to the operation state threshold, a communication abnormality signal is generated at this time, and if the operation state coefficient is greater than the operation state threshold, a communication normal signal is generated at this time; S4: When the operation state of the communication device is abnormal, the multi-dimensional data collection scheme is adjusted, and the collection conversion correction index of the multi-dimensional data and the communication error offset ratio during the adjustment process are obtained; S5: Analyze the adjustment effect of the communication equipment on the multi-source data collection scheme when the operation status is abnormal by combining the collection conversion correction index and the communication error offset ratio, and determine the best multi-dimensional data collection scheme based on the adjustment effect; Step S5 specifically includes: comprehensively calculating the acquisition conversion correction index and the communication error offset ratio, constructing a multi-source data acquisition scheme adjustment effect evaluation model, and calculating the scheme adjustment effect evaluation coefficient. The calculation expression is: In the formula, gx h To adjust the effect evaluation coefficient, rh k To collect the conversion correction index, rk n is the communication error offset ratio, β1 and β2 are the proportional coefficients of the acquisition conversion correction index and the communication error offset ratio, and β2>β1>0; The obtained multi-source data acquisition scheme adjustment effect evaluation coefficient is compared with the standard threshold. If the adjustment effect evaluation coefficient is greater than or equal to the standard threshold, a normal signal is generated; if the adjustment effect evaluation coefficient is less than the standard threshold, an abnormal signal is generated.

2. The multi-dimensional data collection method for power distribution communication control according to claim 1 is characterized in that: In S2, the data transmission efficiency outlier index, communication performance stability ratio and power transmission rate floating value of the communication equipment during the monitoring process are obtained; The logic for obtaining the data transmission efficiency outlier index is: obtain the data transmission efficiency of the communication equipment during the monitoring process, and the calculation expression is: In the formula, wr k is the data transmission efficiency, wq s is the amount of data transmitted, dh r Total time to transmit data, dh t For transmission delay, calculate the mean value of data transmission efficiency. The calculation expression is: In the formula, μ is the mean value of data transmission efficiency, N is the number of data transmissions; the standard deviation of the data is calculated as follows: Where, X i is the value of the ith data point, σ is the standard deviation of the data, Represents the sum of the squares of the differences between each data point in the data set and the mean of the data set, and calculates the outlier index of data transmission efficiency. The calculation expression is: In the formula, qr z is the data transmission efficiency outlier index; The logic for obtaining the stable ratio of communication performance is as follows: obtain the number of communication devices H performing data communication during real-time monitoring and label them, H = 1, 2, 3...r, r is a positive integer greater than 0, obtain the continuous effective working time of each communication device in the s time period, and the calculation expression is: st = s-pk, where st is the continuous effective working time, pk is the failure time of the communication device in the s time period, and obtain the preset standard range of the continuous effective working time of each communication device: st min ~st max , obtain the number y of effective working time of communication equipment within the standard range, calculate the stable ratio of communication performance, and the calculation expression is: Where tk s To stabilize the ratio for communication performance; The logic for obtaining the floating value of the power transmission rate is as follows: in the real-time monitoring process, the power transmission rate we is obtained each time the power system performs power regulation, and the power transmission rate set we = {we n }=we1,we2,we3...we n }, n is a positive integer, calculate the average power transfer rate we y , calculate the floating value of the power transfer rate, the calculation expression is: In the formula, ky l It is the floating value of power transfer rate.

3. The multi-dimensional data collection method for power distribution communication control according to claim 1 is characterized in that: In S4, the acquisition conversion correction index of the multi-dimensional data during the adjustment process and the communication error offset ratio are obtained; The acquisition logic of the acquisition conversion correction index is: the number of data conversions mt in the multidimensional data acquisition process before the acquisition scheme is adjusted g And the number of data corrections gk y , and the number of data conversions in the multidimensional data collection process after the scheme is adjusted g and data correction times ml y , calculate the acquisition conversion correction index, the calculation expression is: In the formula, rh k is the collection conversion correction index, c is the number of matching samples, K is the total number of samples, and j is the number of data matches; The logic for obtaining the communication error offset ratio is: obtaining the number of data tp that is correctly transmitted in data transmission due to abnormal operation of the communication device y , and obtain the total amount of data np transmitted by the communication device within w time y , the calculation expression is: In the formula, rk n is the communication error offset ratio.

4. A multi-dimensional data acquisition system for power distribution communication control, used to implement the acquisition method according to any one of claims 1 to 3, characterized in that: It includes program formulation module, data acquisition module, abnormality judgment module, monitoring module and analysis and adjustment module; Solution formulation module: formulates corresponding multi-dimensional data collection schemes according to the communication control requirements in the power distribution system, and determines the number of sensors and communication devices for collecting power distribution data in different dimensions; Data acquisition module: monitors the real-time operating status of the communication equipment during the multi-dimensional data collection process, and obtains the data transmission efficiency outlier index, communication performance stability ratio and power transmission rate floating value of the communication equipment during the monitoring process; Abnormal judgment module: Build a communication equipment operation status prediction model, input the data transmission efficiency outlier index, communication performance stability ratio, and power transmission rate floating value into the model for comprehensive calculation, and judge whether the operation status of the communication equipment is abnormal based on the calculation results; Monitoring module: When the operation status of the communication equipment is abnormal, the multi-dimensional data collection plan is adjusted, and the collection conversion correction index of the multi-dimensional data and the communication error offset ratio are obtained during the adjustment process. Analysis and adjustment module: Combined with the acquisition conversion correction index and the communication error offset ratio, it analyzes the adjustment effect of the communication equipment on the multi-source data acquisition plan when the operation status is abnormal, and determines the best multi-dimensional data acquisition plan based on the adjustment effect.

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