Resource scheduling method and system based on power information communication

Abstract

The application provides a resource scheduling method and system based on power information communication, relates to the technical field of power grid management, is applied to a server and comprises the following steps: receiving a first electric meter reading of a first power grid area and first power consumption record data of a first measuring switch; acquiring a first power transmission loss quantity; performing consistency verification on the first electric meter reading and the first power consumption record data, acquiring a first verification result; when the verification fails, analyzing the first measuring switch and acquiring a first abnormality analysis result; when the communication is normal, acquiring first identification information according to the first electric meter; when the communication is abnormal, acquiring second identification information according to the first measuring switch; and performing resource scheduling management according to the first identification information or the second identification information. The application solves the technical problem of low resource scheduling efficiency caused by a long scheduling management path of maintenance resources in the prior art.

Description

Technical Field

[0001] This invention relates to the field of power grid management technology, and more specifically to a resource scheduling method and system based on power information communication. Background Technology

[0002] The maintenance of various equipment in the power grid is a crucial foundation for ensuring the stable operation of the power grid. Traditional power grid equipment maintenance mainly involves periodically inspecting the equipment at each power grid node, and then scheduling and managing maintenance resources according to the type of faulty equipment after a fault is detected.

[0003] In existing technologies, maintenance resources are scheduled by periodically detecting anomalies in the equipment at each power grid node. However, the scheduling and management path for maintenance resources is relatively long, resulting in low efficiency in resource scheduling. Summary of the Invention

[0004] This application provides a resource scheduling method and system based on power information communication, which addresses the technical problem of low efficiency in the prior art, which relies on periodic anomaly detection of equipment at each power grid node to schedule maintenance resources, resulting in a long scheduling and management path for maintenance resources.

[0005] In view of the above problems, this application provides a resource scheduling method and system based on power information communication.

[0006] The first aspect of this application provides a resource scheduling method based on power information communication, applied to a server, comprising: receiving a first meter reading and first electricity consumption record data from a first measuring switch in a first power grid area, wherein the first measuring switch is the power supply switch for the first meter reading; acquiring the transmission topology from the first measuring switch to the first meter and performing transmission loss analysis to obtain a first transmission loss amount; performing a consistency check on the first meter reading and the first electricity consumption record data based on the first transmission loss amount to obtain a first check result; when the first check result is a check failure signal, performing abnormal communication analysis on the first measuring switch to obtain a first abnormal analysis result; when the first abnormal analysis result includes a normal communication signal, marking the first meter as having a communication abnormality and obtaining first identification information; when the first abnormal analysis result includes a communication abnormal signal, marking the first measuring switch as having an abnormal communication and obtaining second identification information; and performing resource scheduling management based on the first identification information or the second identification information.

[0007] A second aspect of this application provides a resource scheduling system based on power information communication, applied to a server, comprising: a first receiving unit, configured to receive a first meter reading and a first electricity consumption record data from a first measuring switch in a first power grid area, wherein the first measuring switch is a power supply switch for the first meter reading; a first acquiring unit, configured to acquire the transmission topology from the first measuring switch to the first meter, perform transmission loss analysis, and acquire a first transmission loss amount; a first verification unit, configured to perform consistency verification on the first meter reading and the first electricity consumption record data based on the first transmission loss amount, and acquire a first verification result; a first execution unit, configured to perform abnormal communication analysis on the first measuring switch and acquire a first abnormal analysis result when the first verification result is a verification failure signal; a first identification unit, configured to identify a communication abnormality on the first meter and acquire first identification information when the first abnormal analysis result includes a communication normal signal; a second identification unit, configured to identify an abnormal communication on the first measuring switch and acquire second identification information when the first abnormal analysis result includes a communication abnormal signal; and a second execution unit, configured to perform resource scheduling management based on the first identification information or the second identification information.

[0008] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0009] The resource scheduling method and system based on power information communication provided in this application first performs consistency verification on the meter readings and measurement switch readings in a preset area. If the two are inconsistent, a communication anomaly exists. By performing anomaly analysis on the measurement switches, the abnormal state of the meters and measurement switches is determined, thereby realizing the anomaly identification of the measurement switches and meters. Based on the identification results, maintenance resource scheduling can be carried out, which can achieve highly targeted resource scheduling and eliminates the need for detection before resource scheduling, shortening the maintenance resource scheduling path and achieving the technical effect of improving the efficiency of power grid maintenance resource scheduling. Attached Figure Description

[0010] Figure 1 A schematic diagram of the resource scheduling method based on power information communication provided for this application;

[0011] Figure 2 A flowchart illustrating the transmission loss analysis process in the power information communication-based resource scheduling method provided in this application;

[0012] Figure 3 A flowchart illustrating the discreteness analysis in the resource scheduling method based on power information communication provided in this application;

[0013] Figure 4 A schematic diagram of the structure of the resource scheduling system based on power information communication provided in this application.

[0014] Explanation of reference numerals in the attached drawings: First receiving unit 11, first acquiring unit 12, first verification unit 13, first execution unit 14, first identification unit 15, second identification unit 16, second execution unit 17. Detailed Implementation

[0015] This application provides a resource scheduling method and system based on power information communication. First, it verifies the consistency of meter readings and measurement switch records in a preset area. If they are inconsistent, a communication anomaly exists. By analyzing the anomalies of the measurement switches, the abnormal states of the meters and switches are determined, thus identifying the anomalies. Maintenance resource scheduling is then performed based on the identification results. This allows for highly targeted resource scheduling without requiring prior detection, shortening the maintenance resource scheduling path and improving the efficiency of power grid maintenance resource scheduling. This addresses the technical problem of low efficiency in existing technologies that rely on periodic anomaly detection of equipment at each power grid node for maintenance resource scheduling, resulting in a long scheduling management path.

[0016] Example 1

[0017] like Figure 1 As shown, this application provides a resource scheduling method based on power information communication, applied to the server side, including the following steps:

[0018] In a preferred embodiment, the resource scheduling method based on power information communication is applied to a server. The server can be a physical device or a virtual processor, and can be deployed on a power grid maintenance and management terminal or a cloud computing center, without further restrictions. Preferably, the instructions and code corresponding to any step of the resource scheduling method based on power information communication are stored in the server's memory. When any step of the resource scheduling method is executed, the server's processor retrieves the instructions and code corresponding to that step stored in memory to realize the process of the resource scheduling method based on power information communication. Furthermore, the server's memory and processor can be conventional computer memory and processor, and can be physical or virtual.

[0019] S100: Receive the first electricity meter reading and the first electricity consumption record data of the first measuring switch in the first power grid area, wherein the first measuring switch is the power supply switch for the first electricity meter reading;

[0020] In a preferred embodiment, the first power grid area refers to any preset area where abnormal meters and measuring switches need to be verified in real time. The first meter reading refers to the real-time meter reading information of the first meter in the first power grid area; based on the meter readings at different times, the electricity consumption of the first power grid area over a set period can be determined. The first electricity consumption record data refers to the electricity consumption record data transmitted to the first power grid area recorded by the first measuring switch. Here, the first meter refers to a device used to count the electricity consumption of the first power grid area, and the first measuring switch refers to a device used to control the transmission of electricity to the first power grid area, capable of recording the amount of electricity transmitted to the first power grid area.

[0021] By collecting the readings of the first electricity meter and the first electricity consumption record data, it is convenient to judge their consistency in the next step. If they are consistent, it means that there is no abnormality in the transmission process of electricity information. If they are inconsistent, it means that there is an abnormality in the transmission process of electricity information. In this case, it is necessary to conduct an anomaly analysis on the first electricity meter and the first measuring switch to determine the party with the greater possibility of an anomaly, so as to provide a reference for the scheduling of maintenance resources.

[0022] S200: Obtain the power transmission topology from the first measuring switch to the first meter, perform power transmission loss analysis, and obtain the first power transmission loss amount;

[0023] In a preferred embodiment, when electrical energy is transmitted from the first measuring switch to the first power grid area, there will be power loss along the transmission path. Therefore, it is necessary to analyze the transmission loss and then determine the actual electrical energy transmitted to the first power grid area, so as to facilitate consistency verification with the reading of the first meter.

[0024] Furthermore, transmission loss is closely related to the length of the transmission path and the type of load along the path. Therefore, the transmission topology data collected should include at least both of these factors, representing the composition of the power transmission circuit from the first measuring switch to the first power grid region. Then, based on large-scale data collection of transmission loss records under the same transmission topology, statistical analysis is performed to determine the average of the most frequently occurring transmission loss records, which is set as the first transmission loss value. Here, the transmission loss value refers to the loss per unit of transmitted power per unit time. This provides a data fitting basis for subsequent consistency verification, improving the accuracy of the consistency verification.

[0025] S300: Perform a consistency check on the first meter reading and the first electricity consumption record data based on the first power transmission loss, and obtain the first check result;

[0026] In a preferred embodiment, the electricity consumption of a first power grid area within a preset time period is determined by the reading of a first electricity meter, and the electricity transmission capacity of the first power grid area within the preset time period is determined by the first electricity consumption record data. Then, the total transmission loss is calculated according to the formula: total loss = first transmission loss * preset time * transmission capacity. Finally, the actual transmission capacity delivered to the first power grid area is obtained by subtracting the total loss from the transmission capacity.

[0027] Furthermore, the deviation between the actual electricity supply and consumption is compared. If the deviation is greater than or equal to the consistency deviation threshold, a verification failure message is generated. This indicates either an anomaly in the first meter causing information transmission errors, an anomaly in the first measuring switch causing information transmission errors, or noise during communication causing data loss and resulting in data anomalies. These situations need to be investigated to determine the specific content of the anomaly, providing a reference benchmark for subsequent maintenance resource allocation. When the deviation is less than the consistency deviation threshold, a verification pass message is generated, indicating no abnormal communication data and no need to activate subsequent processes. The consistency deviation threshold refers to a fault-tolerant electricity consumption deviation value defined by the management personnel.

[0028] S400: When the first verification result is a verification failure signal, perform abnormal communication analysis on the first measurement switch and obtain the first abnormal analysis result;

[0029] S500: When the first anomaly analysis result includes a normal communication signal, mark the first meter as having a communication anomaly and obtain the first identification information;

[0030] S600: When the first anomaly analysis result includes a communication anomaly signal, mark the first measuring switch for abnormal communication and obtain the second identification information;

[0031] In a preferred embodiment, when the first verification result is a verification failure signal, an abnormal communication analysis is performed on the first measuring switch. Since the first measuring switch also supplies power to other areas, a consistency analysis is performed between the first measuring switch and the electricity meters in other areas. If the data transmitted with the electricity meters in other areas is consistent, a normal communication signal is generated and added to the first abnormal analysis result for storage, representing the abnormal state of the first measuring switch. At this time, it is considered that the electricity meter communication is abnormal, and the first electricity meter is marked with a communication abnormality, the first identification information is obtained, and the signal of the electricity meter communication abnormality is stored.

[0032] If the data transmitted by the meters in other areas is inconsistent, a communication error signal is generated. At this time, the probability of the first measuring switch being abnormal is relatively high. Therefore, the first measuring switch is marked with an abnormal communication identifier, the second identifier information is obtained, and the signal representing the abnormality of the first measuring switch is stored.

[0033] S700: Perform resource scheduling management based on the first identification information or the second identification information.

[0034] In a preferred embodiment, based on the first identification information or the second identification information, the abnormal device type, such as an electricity meter or a measuring switch, can be determined. Therefore, corresponding resources can be prepared for targeted resource scheduling according to the abnormal device type, eliminating the need for a second scheduling after a first detection, resulting in high resource scheduling efficiency.

[0035] Preferably, the resource allocation process is as follows, taking the first identifier information as an example:

[0036] Step 1: Determine the resource distribution locations. Based on the first identifier information, it can be determined that the first electricity meter is highly likely to be faulty. Data transmission anomalies are ruled out here because the server-received measurement switch data is consistent with that of other electricity meters, indicating that the first electricity meter is likely faulty. The resources needed at this point are the relevant spare parts for the electricity meter. Obtain the distribution information of maintenance and repair inventory points to determine the locations where the relevant spare parts for the electricity meter have redundancy, as well as the locations of maintenance personnel with available redundancy time.

[0037] Step 2: Filter schedulable resources. Based on the distribution location of parts, determine the first set of delivery times for parts; based on the distribution location of maintenance personnel, determine the second set of movement durations for maintenance personnel; clean the distribution locations of parts whose first delivery time set is greater than or equal to the delivery duration threshold to obtain the schedulable distribution locations of parts; clean the distribution locations of maintenance personnel whose second movement duration set is greater than or equal to the delivery duration threshold to obtain the schedulable distribution locations of personnel.

[0038] Step 3: Optimizing the Scheduling Scheme: Place overlapping locations of available spare parts and available staff into first-priority scheduling locations; place non-overlapping locations into second-priority scheduling locations. Sort the first-priority scheduling locations according to transport time to obtain a ranking result. Based on the number of damaged meters, determine the required number of personnel and spare parts, and allocate resources to the first-priority scheduling locations sequentially according to the ranking result. If the resource allocation for the first-priority scheduling locations is insufficient to meet the required number of personnel and spare parts, sort the non-overlapping locations from smallest to largest according to travel time or transport duration, and allocate resources to the non-overlapping locations sequentially according to the ranking result to obtain the final scheduling scheme.

[0039] Furthermore, if the resource scheduling scheme cannot be met even if the non-overlapping locations are not selected, a resource replenishment instruction needs to be generated and sent to the management terminal to replenish the resource inventory in a timely manner.

[0040] Furthermore, such as Figure 2As shown, based on the obtained transmission topology from the first measuring switch to the first meter, transmission loss analysis is performed to obtain the first transmission loss. Step S200 includes:

[0041] S210: Based on the power transmission topology, obtain the power transmission distance characteristics and load distribution characteristics;

[0042] S220: Based on the transmission distance characteristics and the load distribution characteristics, perform data mining to determine the transmission loss record data of the same family of transmission topologies;

[0043] S230: Perform transmission loss analysis based on the transmission loss record data to obtain the first transmission loss amount.

[0044] In a preferred embodiment, the detailed process for transmission loss analysis is as follows:

[0045] The transmission distance feature, representing the distance from the first measuring switch to the first power grid region, and the load distribution feature, representing the load distribution location along the transmission path from the first measuring switch to the first power grid region, are extracted from the transmission topology. Using the transmission distance feature and load distribution feature as scenario constraint data, data is collected based on big data to determine transmission loss records representing the unit transmission power loss value per unit time under the same transmission distance and load distribution features. Based on the transmission loss records, discrete values ​​are removed, and the mean of the non-discrete transmission loss records is calculated and set as the first transmission loss.

[0046] Furthermore, based on the transmission loss analysis performed according to the recorded transmission loss data, the first transmission loss amount is obtained. Step S230 includes:

[0047] S231: The power transmission loss recording data includes first recording data, second recording data, up to the Nth recording data, where N≥50 and N is an integer;

[0048] S232: Perform discrete analysis on the first recorded data, the second recorded data up to the Nth recorded data, and obtain N discrete coefficients;

[0049] S233: Clean the first record data, the second record data and up to the Nth record data whose N discrete coefficients are greater than or equal to the discrete coefficient threshold, and obtain the cleaning result of the loss record data;

[0050] S234: Perform statistical analysis on the cleaning results of the loss record data to obtain the average transmission loss, the maximum transmission loss, and the minimum transmission loss, and add them to the first transmission loss amount.

[0051] In a preferred embodiment, the first record data, the second record data, and so on up to the Nth record data refer to N transmission loss record values ​​filtered based on big data, where N ≥ 50 and N is an integer. Discreteness analysis is performed on the first record data, the second record data, and so on up to the Nth record data to determine the degree of dispersion of each record value, denoted as the dispersion coefficient. The N records with dispersion coefficients greater than or equal to the dispersion coefficient threshold are then cleaned to obtain the remaining cleaned loss record data.

[0052] Furthermore, the maximum value of the remaining loss record data cleaning result is determined and set as the maximum transmission loss; the minimum value of the remaining loss record data cleaning result is determined and set as the minimum transmission loss; the mean value of the remaining loss record data cleaning result is determined and set as the mean transmission loss. The mean transmission loss, the maximum transmission loss, and the minimum transmission loss are added to the first transmission loss.

[0053] Furthermore, when fitting the power transmission volume of the first power consumption record data in the subsequent step, it is necessary to use the power transmission volume minus (average transmission loss * time * power transmission volume) to obtain the average actual power transmission volume, use the power transmission volume minus (maximum transmission loss * time * power transmission volume) to obtain the maximum actual power transmission volume, and use the power transmission volume minus (minimum transmission loss * time * power transmission volume) to obtain the minimum actual power transmission volume.

[0054] First, a consistency check is performed between the average actual power delivery and the reading data. If the check fails, a consistency check is performed based on the interval constructed by the maximum and minimum actual power delivery values. If the meter reading information falls within the interval constructed by the maximum and minimum actual power delivery values, it is considered consistent; otherwise, it is considered inconsistent, and a check failure signal is generated.

[0055] Furthermore, such as Figure 3 As shown, based on the discrete analysis of the first record data, the second record data, up to the Nth record data, N discrete coefficients are obtained. Step S232 includes:

[0056] S232-1: Set the loss threshold;

[0057] S232-2: Perform cluster analysis on the first recorded data, the second recorded data up to the Nth recorded data according to the loss threshold to obtain the recorded data clustering result, wherein the recorded data clustering result has a clustering frequency parameter;

[0058] S232-3: Iterate through the clustering frequency parameters to obtain the N discrete coefficients.

[0059] In a preferred embodiment, the discreteness analysis process is as follows:

[0060] A loss threshold is preset by the management terminal, representing the minimum loss amount considered as a deviation in the recorded value. Cluster analysis is performed on the first, second, and up to the Nth recorded data based on this loss threshold to obtain the clustering results. Record values ​​less than or equal to the loss threshold are grouped into one class, and their mean is calculated as the new record value. Record values ​​greater than the loss threshold are grouped into multiple classes. This clustering process is repeated to obtain the final clustering result. The number of recorded values ​​clustered within each class is denoted as the clustering frequency parameter. The reciprocal of the clustering frequency parameter is calculated to obtain N discrete coefficients. Higher frequencies indicate greater concentration; therefore, their reciprocals represent the degree of dispersion.

[0061] Furthermore, based on the condition that the first verification result is a verification failure signal, abnormal communication analysis is performed on the first measuring switch to obtain the first abnormal analysis result. Step S400 includes:

[0062] S410: Acquire the second power consumption record data, the third power consumption record data, up to the Mth power consumption record data from the first measuring switch;

[0063] S420: Obtain the readings of the second electricity meter, the third electricity meter, and up to the Mth electricity meter, wherein the second electricity meter reading uniquely corresponds to the second electricity consumption record data, and the third electricity consumption record data uniquely corresponds to the third electricity meter reading until the Mth electricity consumption record data uniquely corresponds to the Mth electricity meter reading;

[0064] S430: Perform a consistency check on the second electricity consumption record data and the second electricity meter reading, and obtain a second check result;

[0065] S440: Perform a consistency check on the Mth electricity consumption record data and the Mth meter reading, and obtain the Mth check result;

[0066] S450: Count the number of verification failure signals from the second verification result up to the Mth verification result, and set it as the first count result;

[0067] S460: When the first counting result is greater than or equal to the counting threshold, the communication abnormality signal is generated;

[0068] S470: When the first counting result is less than the counting threshold, the normal communication signal is generated.

[0069] In a preferred embodiment, the process of performing abnormal communication analysis on the first measuring switch and obtaining the first abnormal analysis result is as follows:

[0070] The second, third, and up to the Mth power consumption record data of the first measuring switch refer to the power supply record data within the preset time zones of the second, third, and up to the Mth power grid regions. The second, third, and up to the Mth meter readings refer to the readings of the second meter in the second power grid region, the third meter in the third power grid region, and up to the Mth meter in the Mth power grid region. Specifically, the second meter reading uniquely corresponds to the second power consumption record data, and the third power consumption record data uniquely corresponds to the third meter reading, and so on, until the Mth power consumption record data uniquely corresponds to the Mth meter reading. The second, third, and up to the Mth power grid regions are the areas where the first measuring switch distributes power, and are different from the first power grid region. The second to the Mth meters refer to the meters within the second, third, and up to the Mth power grid regions.

[0071] Using the exact same consistency verification method, the second electricity consumption record data and the second meter reading are verified for consistency, and the second verification result is obtained. ... The Mth electricity consumption record data and the Mth meter reading are verified for consistency, and the Mth verification result is obtained. Preferably, a successful verification is recorded as 0, and a failed verification is recorded as 1.

[0072] The number of failed verification signals up to the Mth verification result is counted. Preferably, the sum of the 1 values ​​of the failed verifications is used to obtain a first count result. When the first count result is less than a counting threshold, a normal communication signal is generated. The counting threshold is the maximum allowable number of failed verifications set based on the M value. Therefore, a first count result less than the counting threshold is considered a normal communication signal, and a first count result greater than or equal to the counting threshold is considered a communication anomaly signal.

[0073] Furthermore, when the first anomaly analysis result includes a communication anomaly signal, the first measuring switch is marked with an abnormal communication identifier, and second identifier information is obtained. This also includes step S480, which includes the following steps:

[0074] S481: When the first anomaly analysis result includes the communication anomaly signal, the first meter reading is fitted according to the first power transmission loss to obtain the first meter reading fitting result.

[0075] S482: Obtain the first deviation between the fitting result of the first electricity meter reading and the first electricity consumption record data;

[0076] S483: Obtain the second deviation between the fitting result of the second electricity meter reading and the second electricity consumption record data;

[0077] S484: Obtain the Mth deviation between the fitting result of the Mth meter reading and the Mth electricity consumption record data;

[0078] S485: Based on the first deviation, the second deviation, and the Mth deviation, perform abnormal meter analysis to obtain a set of quasi-abnormal meters;

[0079] S486: Identify the abnormal communication of the quasi-abnormal meter set and obtain third identification information;

[0080] S487: Perform resource scheduling management based on the third identification information.

[0081] In a preferred embodiment, when the first anomaly analysis result includes a communication anomaly signal, the deviation between the meter reading and the electricity consumption record should tend to be consistent based on the same first measuring switch. Therefore, the first transmission loss is fitted to the first meter reading, that is, the electricity consumption in a preset time zone is determined based on the first meter reading, plus the first transmission loss, and stored as the first meter reading fitting result. The same calculation method is used to determine the second meter reading fitting result up to the Mth meter reading fitting result.

[0082] Then, based on the first electricity consumption record data, the power supply amount for the preset time zone is determined. The absolute value of the difference between this value and the fitted result of the first meter reading is calculated and set as the first deviation. Using the same calculation method, the fitted results of the second meter readings are iterated until the fitted result of the Mth meter reading is obtained, yielding the second and Mth deviations. Meters with discrete deviation distributions are selected from the first, second, and Mth deviations and designated as abnormal meters, added to the quasi-abnormal meter set. Abnormal communication identification is applied to the quasi-abnormal meter set, and third identification information is obtained for resource scheduling management. Abnormal meters are further identified by the consistency of data deviations from the same measuring switches, facilitating targeted resource scheduling in subsequent steps.

[0083] Furthermore, based on the first deviation, the second deviation, and the Mth deviation, abnormal meter analysis is performed to obtain a set of quasi-abnormal meters. Step S485 includes the following steps:

[0084] S485-1: Based on the first deviation, iterate through the second deviation until the Mth deviation to obtain the distance parameter set;

[0085] S485-2: Based on the distance parameter set, select k second deviation quantities from near to far until the Mth deviation quantity, and construct the particle neighborhood of the first deviation quantity k;

[0086] S485-3: Calculate the average of the sum of the first deviation and the reciprocal of the particle distances in the neighborhood of the first deviation k particle, and set it as the distribution density of the first deviation.

[0087] S485-4: Calculate the second deviation amount and the second deviation amount distribution density of the Mth deviation amount up to the Mth deviation amount distribution density;

[0088] S485-5: Obtain the mean distribution density based on the first deviation distribution density, the second deviation distribution density, and up to the Mth deviation distribution density;

[0089] S485-6: Based on the mean distribution density, traverse the first deviation distribution density, the second deviation distribution density up to the Mth deviation distribution density and compare them to obtain the first anomaly coefficient, the second anomaly coefficient up to the Mth anomaly coefficient;

[0090] S485-7: Select the meters whose first abnormal coefficient, second abnormal coefficient, up to the Mth abnormal coefficient are greater than or equal to the abnormal coefficient threshold, and set them as the quasi-abnormal meter set.

[0091] In a preferred embodiment, the anomaly analysis process is as follows:

[0092] Based on the first deviation, the absolute value of the difference between the second deviations up to the Mth deviation is calculated to obtain the distance parameter set. Then, k second deviations up to the Mth deviation are selected from the nearest to the farthest based on the distance parameter set to construct the k-particle neighborhood of the first deviation, where k is a preset number of neighborhood distances used to evaluate the anomaly coefficient. The reciprocal of the distance between the first deviation and any particle in the k-particle neighborhood of the first deviation is calculated, and then summed to obtain the mean, which is set as the distribution density of the first deviation.

[0093] Calculate the second deviation distribution density up to the Mth deviation distribution density using the same method. Calculate the mean of the first deviation distribution density, the second deviation distribution density up to the Mth deviation distribution density, and set it as the distribution density mean.

[0094] Based on the mean distribution density, the distribution densities of the first deviation, second deviation, and up to the Mth deviation are compared to obtain the first anomaly coefficient, the second anomaly coefficient, and so on up to the Mth anomaly coefficient. That is, the mean distribution density is divided by the first deviation distribution density, the second deviation distribution density, and so on up to the Mth deviation distribution density to obtain the first anomaly coefficient, the second anomaly coefficient, and so on up to the Mth anomaly coefficient. Meters with the first anomaly coefficient, the second anomaly coefficient, and so on up to the Mth anomaly coefficient greater than or equal to the anomaly coefficient threshold are selected and set as the quasi-abnormal meter set, where the anomaly coefficient threshold is the maximum allowable anomaly level preset by the management terminal. This method is not limited to the case of an abnormal first measuring switch; it can also verify meters when the measuring switch is normal, improving the efficiency of power grid anomaly detection and providing a data foundation for power grid maintenance.

[0095] In summary, the embodiments of this application have at least the following technical effects:

[0096] This application's embodiment of a resource scheduling method and system based on power information communication first performs a consistency check on the meter readings and measurement switch readings in a preset area. If the two are inconsistent, a communication anomaly exists. By performing anomaly analysis on the measurement switches, the abnormal states of the meters and measurement switches are determined, thereby enabling anomaly identification of the measurement switches and meters. Based on the identification results, maintenance resource scheduling is performed, which can achieve highly targeted resource scheduling without the need for detection before resource scheduling, shortening the maintenance resource scheduling path and achieving the technical effect of improving the efficiency of power grid maintenance resource scheduling.

[0097] Example 2

[0098] Based on the same inventive concept as the resource scheduling method based on power information communication in the foregoing embodiments, such as Figure 4 As shown, this application provides a resource scheduling system based on power information communication, applied to the server side, including:

[0099] The first receiving unit 11 is used to receive the first electricity meter reading of the first power grid area and the first electricity consumption record data of the first measuring switch, wherein the first measuring switch is the power supply switch for the first electricity meter reading.

[0100] The first acquisition unit 12 is used to acquire the power transmission topology from the first measuring switch to the first meter, perform power transmission loss analysis, and acquire the first power transmission loss amount.

[0101] The first verification unit 13 is used to perform consistency verification on the first meter reading and the first electricity consumption record data based on the first power transmission loss, and obtain the first verification result.

[0102] The first execution unit 14 is used to perform abnormal communication analysis on the first measurement switch and obtain the first abnormal analysis result when the first verification result is a verification failure signal.

[0103] The first identification unit 15 is used to identify the first meter as having a communication anomaly when the first anomaly analysis result includes a normal communication signal, and to obtain the first identification information.

[0104] The second identification unit 16 is used to identify the first measurement switch as having abnormal communication when the first anomaly analysis result includes a communication anomaly signal, and to obtain the second identification information.

[0105] The second execution unit 17 is used to perform resource scheduling management based on the first identification information or the second identification information.

[0106] Furthermore, the first acquisition unit 12 performs the following steps:

[0107] Based on the power transmission topology, the power transmission distance characteristics and load distribution characteristics are obtained;

[0108] Data mining is performed based on the transmission distance characteristics and the load distribution characteristics to determine the transmission loss record data of the same family of transmission topologies;

[0109] Based on the recorded transmission loss data, transmission loss analysis is performed to obtain the first transmission loss amount.

[0110] Furthermore, the first acquisition unit 12 further includes the following steps:

[0111] The power transmission loss recording data includes first recording data, second recording data, up to the Nth recording data, where N≥50 and N is an integer;

[0112] Perform discrete analysis on the first record data, the second record data, up to the Nth record data, to obtain N discrete coefficients;

[0113] The first record data, the second record data, and up to the Nth record data with N discrete coefficients greater than or equal to the discrete coefficient threshold are cleaned to obtain the loss record data cleaning result.

[0114] Statistical analysis is performed on the cleaning results of the loss record data to obtain the average transmission loss, the maximum transmission loss, and the minimum transmission loss, which are then added to the first transmission loss amount.

[0115] Furthermore, the first acquisition unit 12 further includes the following steps:

[0116] Set a loss threshold;

[0117] Cluster analysis is performed on the first recorded data, the second recorded data, up to the Nth recorded data according to the loss threshold to obtain the recorded data clustering result, wherein the recorded data clustering result has a clustering frequency parameter;

[0118] The clustering frequency parameters are iterated through and inverted to obtain the N discrete coefficients.

[0119] Furthermore, the first execution unit 14 performs the following steps:

[0120] Acquire the second power consumption record data, the third power consumption record data, up to the Mth power consumption record data from the first measuring switch;

[0121] Acquire the readings of the second electricity meter, the third electricity meter, and so on up to the Mth electricity meter, wherein the second electricity meter reading uniquely corresponds to the second electricity consumption record data, and the third electricity consumption record data uniquely corresponds to the third electricity meter reading, up to the Mth electricity consumption record data uniquely corresponding to the Mth electricity meter reading;

[0122] Perform a consistency check on the second electricity consumption record data and the second electricity meter reading, and obtain a second check result;

[0123] Perform a consistency check on the Mth electricity consumption record data and the Mth meter reading, and obtain the Mth check result;

[0124] The number of failed verification signals up to the Mth verification result is counted and set as the first count result;

[0125] When the first counting result is greater than or equal to the counting threshold, the communication abnormality signal is generated;

[0126] When the first counting result is less than the counting threshold, the normal communication signal is generated.

[0127] Furthermore, the execution steps of the first execution unit 14 also include:

[0128] When the first anomaly analysis result includes the communication anomaly signal, the first meter reading is fitted according to the first power transmission loss to obtain the first meter reading fitting result.

[0129] Obtain the first deviation between the fitting result of the first electricity meter reading and the first electricity consumption record data;

[0130] Obtain the second deviation between the fitting result of the second electricity meter reading and the second electricity consumption record data;

[0131] Obtain the Mth deviation between the fitted result of the Mth meter reading and the Mth electricity consumption record data;

[0132] Based on the first deviation, the second deviation, and the Mth deviation, abnormal electricity meter analysis is performed to obtain a set of quasi-abnormal electricity meters.

[0133] The quasi-abnormal meter set is identified by abnormal communication, and third identification information is obtained;

[0134] Resource scheduling and management are performed based on the third identification information.

[0135] Furthermore, the first execution unit 14 performs the following steps:

[0136] Based on the first deviation, the second deviation is iterated up to the Mth deviation to obtain the distance parameter set;

[0137] Based on the distance parameter set, select k second deviation quantities from near to far up to the Mth deviation quantity, and construct the particle neighborhood of the first deviation quantity k;

[0138] Calculate the average of the sum of the first deviation and the reciprocal of the particle distances in the neighborhood of the first deviation k particle, and set it as the distribution density of the first deviation.

[0139] Calculate the second deviation and the second deviation distribution density of the Mth deviation until the Mth deviation distribution density is calculated;

[0140] The mean distribution density is obtained based on the first deviation distribution density, the second deviation distribution density, and up to the Mth deviation distribution density.

[0141] Based on the mean distribution density, the first deviation distribution density, the second deviation distribution density, and up to the Mth deviation distribution density are compared to obtain the first anomaly coefficient, the second anomaly coefficient, and up to the Mth anomaly coefficient.

[0142] Meters whose first abnormal coefficient, second abnormal coefficient, up to the Mth abnormal coefficient are greater than or equal to the abnormal coefficient threshold are selected and set as the quasi-abnormal meter set.

[0143] This specification and accompanying drawings are merely illustrative examples of this application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Clearly, those skilled in the art can make various alterations and modifications to this application without departing from its scope. Therefore, if such modifications and modifications fall within the scope of this application and its equivalents, this application intends to include such modifications and modifications.

Claims

1. A resource scheduling method based on power information communication, characterized in that, Applied to the server side, including: Receive the first electricity meter reading and the first electricity consumption record data of the first measuring switch in the first power grid area, wherein the first measuring switch is the power supply switch for the first electricity meter reading; The power transmission topology from the first measuring switch to the first meter is obtained to perform power transmission loss analysis and obtain the first power transmission loss. Based on the first power transmission loss, the consistency of the first meter reading and the first electricity consumption record data is verified to obtain the first verification result; When the first verification result is a verification failure signal, perform abnormal communication analysis on the first measurement switch to obtain the first abnormal analysis result. When the first anomaly analysis result includes a normal communication signal, the first meter is marked as having a communication anomaly, and the first marking information is obtained. When the first anomaly analysis result includes a communication anomaly signal, the first measuring switch is marked with an abnormal communication identifier, and the second identifier information is obtained. Resource scheduling and management are performed based on the first or second identification information; The resource scheduling management based on the first identification information or the second identification information includes: Based on the first identification information, the first meter is identified as abnormal. The distribution information of maintenance and repair inventory points is obtained to determine the locations where meter parts have redundancy, as well as the locations of maintenance personnel with redundancy time. Based on the distribution location of the parts, determine the first set of delivery time for the parts. Based on the distribution location of the maintenance personnel, determine the second set of movement time for the maintenance personnel. Clean the distribution locations of the parts whose first delivery time set is greater than or equal to the delivery time threshold to obtain the schedulable distribution locations of the parts. Clean the distribution locations of the maintenance personnel whose second movement time set is greater than or equal to the delivery time threshold to obtain the schedulable distribution locations of the personnel. The overlapping locations of the dispatchable parts distribution locations and the dispatchable employee distribution locations are set as the first priority dispatch locations, and the non-overlapping locations are set as the second priority dispatch locations. The first priority dispatch locations are sorted according to the delivery time to obtain the sorting results. Based on the number of damaged electricity meters, determine the required number of personnel and spare parts, and allocate resources to the first priority scheduling positions in order of ranking. If the resources at the first priority scheduling location are configured but still cannot meet the required number of personnel and parts, then the non-overlapping locations are sorted from smallest to largest according to their movement duration or delivery time. Resources are then configured for the non-overlapping locations in sequence according to the sorting results to obtain the final scheduling scheme.

2. The method as described in claim 1, characterized in that, The transmission topology from the first measuring switch to the first meter is obtained to perform transmission loss analysis, and the first transmission loss is obtained, including: Based on the power transmission topology, the power transmission distance characteristics and load distribution characteristics are obtained; Data mining is performed based on the transmission distance characteristics and the load distribution characteristics to determine the transmission loss record data of the same family of transmission topologies; Based on the recorded transmission loss data, transmission loss analysis is performed to obtain the first transmission loss amount.

3. The method as described in claim 2, characterized in that, Based on the recorded transmission loss data, transmission loss analysis is performed to obtain the first transmission loss amount, including: The power transmission loss recording data includes first recording data, second recording data, up to the Nth recording data, where N≥50 and N is an integer; Perform discrete analysis on the first record data, the second record data, up to the Nth record data, to obtain N discrete coefficients; The first record data, the second record data, and up to the Nth record data with N discrete coefficients greater than or equal to the discrete coefficient threshold are cleaned to obtain the loss record data cleaning result. Statistical analysis is performed on the cleaning results of the loss record data to obtain the average transmission loss, the maximum transmission loss, and the minimum transmission loss, which are then added to the first transmission loss amount.

4. The method as described in claim 3, characterized in that, Discreteness analysis is performed on the first record data, the second record data, and up to the Nth record data to obtain N discrete coefficients, including: Set a loss threshold; Cluster analysis is performed on the first recorded data, the second recorded data, up to the Nth recorded data according to the loss threshold to obtain the recorded data clustering result, wherein the recorded data clustering result has a clustering frequency parameter; The clustering frequency parameters are iterated through and inverted to obtain the N discrete coefficients.

5. The method as described in claim 1, characterized in that, When the first verification result is a verification failure signal, an abnormal communication analysis is performed on the first measuring switch to obtain the first abnormal analysis result, including: Acquire the second power consumption record data, the third power consumption record data, up to the Mth power consumption record data from the first measuring switch; Acquire the readings of the second electricity meter, the third electricity meter, and so on up to the Mth electricity meter, wherein the second electricity meter reading uniquely corresponds to the second electricity consumption record data, and the third electricity consumption record data uniquely corresponds to the third electricity meter reading, up to the Mth electricity consumption record data uniquely corresponding to the Mth electricity meter reading; Perform a consistency check on the second electricity consumption record data and the second electricity meter reading, and obtain a second check result; Perform a consistency check on the Mth electricity consumption record data and the Mth meter reading, and obtain the Mth check result; The number of failed verification signals up to the Mth verification result is counted and set as the first count result; When the first counting result is greater than or equal to the counting threshold, the communication abnormality signal is generated; When the first counting result is less than the counting threshold, the normal communication signal is generated.

6. The method as described in claim 5, characterized in that, When the first anomaly analysis result includes a communication anomaly signal, the first measuring switch is marked with an abnormal communication identifier, and second identifier information is obtained. The method also includes: When the first anomaly analysis result includes the communication anomaly signal, the first meter reading is fitted according to the first power transmission loss to obtain the first meter reading fitting result. Obtain the first deviation between the fitting result of the first electricity meter reading and the first electricity consumption record data; Obtain the second deviation between the fitting result of the second electricity meter reading and the second electricity consumption record data; Obtain the Mth deviation between the fitted result of the Mth meter reading and the Mth electricity consumption record data; Based on the first deviation, the second deviation, and the Mth deviation, abnormal electricity meter analysis is performed to obtain a set of quasi-abnormal electricity meters. The quasi-abnormal meter set is identified by abnormal communication, and third identification information is obtained; Resource scheduling and management are performed based on the third identification information.

7. The method as described in claim 6, characterized in that, Based on the first deviation, the second deviation, and the Mth deviation, abnormal meter analysis is performed to obtain a set of quasi-abnormal meters, including: Based on the first deviation, the second deviation is iterated up to the Mth deviation to obtain the distance parameter set; Based on the distance parameter set, select k second deviation quantities from near to far up to the Mth deviation quantity, and construct the particle neighborhood of the first deviation quantity k; Calculate the average of the sum of the first deviation and the reciprocal of the particle distances in the neighborhood of the first deviation k particle, and set it as the distribution density of the first deviation. Calculate the second deviation and the second deviation distribution density of the Mth deviation until the Mth deviation distribution density is calculated; The mean distribution density is obtained based on the first deviation distribution density, the second deviation distribution density, and up to the Mth deviation distribution density. Based on the mean distribution density, the first deviation distribution density, the second deviation distribution density, and up to the Mth deviation distribution density are compared to obtain the first anomaly coefficient, the second anomaly coefficient, and up to the Mth anomaly coefficient. Meters whose first abnormal coefficient, second abnormal coefficient, up to the Mth abnormal coefficient are greater than or equal to the abnormal coefficient threshold are selected and set as the quasi-abnormal meter set.

8. A resource scheduling system based on power information communication, characterized in that, Applied to the server side, including: The first receiving unit is used to receive the first electricity meter reading and the first electricity consumption record data of the first measuring switch in the first power grid area, wherein the first measuring switch is the power supply switch for the first electricity meter reading. The first acquisition unit is used to acquire the power transmission topology from the first measuring switch to the first meter, perform power transmission loss analysis, and acquire the first power transmission loss amount. The first verification unit is used to perform consistency verification on the first meter reading and the first electricity consumption record data based on the first power transmission loss, and obtain the first verification result. The first execution unit is configured to perform abnormal communication analysis on the first measurement switch and obtain the first abnormal analysis result when the first verification result is a verification failure signal. The first identification unit is used to identify the first meter as having a communication anomaly when the first anomaly analysis result includes a normal communication signal, and to obtain the first identification information. The second identification unit is used to identify the first measurement switch as having abnormal communication when the first anomaly analysis result includes a communication anomaly signal, and to obtain the second identification information. The second execution unit is used to perform resource scheduling management based on the first identification information or the second identification information; The resource scheduling management based on the first identification information or the second identification information includes: Based on the first identification information, the first meter is identified as abnormal. The distribution information of maintenance and repair inventory points is obtained to determine the locations where meter parts have redundancy, as well as the locations of maintenance personnel with redundancy time. Based on the distribution location of the parts, determine the first set of delivery time for the parts. Based on the distribution location of the maintenance personnel, determine the second set of movement time for the maintenance personnel. Clean the distribution locations of the parts whose first delivery time set is greater than or equal to the delivery time threshold to obtain the schedulable distribution locations of the parts. Clean the distribution locations of the maintenance personnel whose second movement time set is greater than or equal to the delivery time threshold to obtain the schedulable distribution locations of the personnel. The overlapping locations of the dispatchable parts distribution locations and the dispatchable employee distribution locations are set as the first priority dispatch locations, and the non-overlapping locations are set as the second priority dispatch locations. The first priority dispatch locations are sorted according to the delivery time to obtain the sorting results. Based on the number of damaged electricity meters, determine the required number of personnel and spare parts, and allocate resources to the first priority scheduling positions in order of ranking. If the resources at the first priority scheduling location are configured but still cannot meet the required number of personnel and parts, then the non-overlapping locations are sorted from smallest to largest according to their movement duration or delivery time. Resources are then configured for the non-overlapping locations in sequence according to the sorting results to obtain the final scheduling scheme.

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