Low-voltage transformer area health degree assessment method, system, equipment, medium and product

Abstract

The invention discloses a low-voltage transformer area health degree assessment method, system, device, medium and product, and the method comprises the steps: obtaining the historical operation data, historical environment data, historical fault case data, current operation data and current environment data of a low-voltage transformer area, and obtaining the health degree of the low-voltage transformer area through the historical operation data and the historical environment data; determining the number of historical fault cases under each fault type, determining first health degree scores corresponding to historical operation data and historical environment data according to the number of historical fault cases under each fault type and fault hazard weights, and determining first health degree scores corresponding to the historical environment data according to the abnormal conditions of the current operation data and the current environment data. And determining a second health degree score corresponding to the current operation data and the current environment data according to the first health degree score and the second health degree score, and determining a total health degree score of the low-voltage transformer area by integrating the first health degree score and the second health degree score, so that the health state of the low-voltage transformer area is comprehensively and accurately evaluated by using the total health degree score.

Description

Technical Field

[0001] The present invention relates to the technical field of power systems, and in particular to a method, system, equipment, medium and product for evaluating the health of a low-voltage substation. Background Art

[0002] With the continuous growth of electricity demand and the continued expansion of distribution networks, the stability and reliability of low-voltage substations, the key link between the power system and users, are crucial to ensuring power supply quality. Accurately assessing the health of low-voltage substations, promptly identifying potential problems, and implementing targeted measures are key requirements for improving power supply reliability and optimizing operations and maintenance management.

[0003] At present, although the operating parameters of low-voltage substations, such as voltage, current, and load rate, can be obtained, there are still deficiencies in the overall statistics and health portraits of low-voltage substations, and there is a lack of comprehensive, systematic and accurate health assessment methods.

[0004] However, the existing low-voltage substation health evaluation methods are not accurate and comprehensive enough, making it difficult to effectively guide operation and maintenance management and ensure power supply reliability. Summary of the Invention

[0005] In view of this, the present invention provides a low-voltage substation health assessment method, system, equipment, medium and product, which solves the technical problems that the existing low-voltage substation health assessment methods are not accurate and comprehensive enough, making it difficult to effectively guide operation and maintenance management and ensure power supply reliability.

[0006] A first aspect of the present invention provides a method for assessing the health of a low-voltage substation, comprising:

[0007] Obtain historical operating data, historical environmental data, and historical fault case data of the low-voltage area within the same time window, and obtain current operating data and current environmental data of the low-voltage area within the current time window;

[0008] Classifying the historical fault case data according to fault types to obtain historical fault case data under multiple fault types;

[0009] Determining the number of historical fault cases for each fault type based on the historical operating data and the historical environmental data; wherein the number of historical fault cases is obtained by counting the number of historical fault cases corresponding to the fault type that occurred due to abnormalities in the historical operating data or the historical environmental data;

[0010] Determining first health scores corresponding to the historical operation data and the historical environment data, respectively, according to the number of historical fault cases under each fault type and a preset fault hazard weight;

[0011] Determining abnormal conditions of the current operating data and the current environmental data respectively, and determining second health scores corresponding to the current operating data and the current environmental data respectively according to the abnormal conditions;

[0012] The total health score of the low-voltage station area is determined according to the first health score and the second health score.

[0013] Preferably, the number of historical failure cases includes the number of first historical failure cases and the number of second historical failure cases;

[0014] Determining the number of historical fault cases for each fault type based on the historical operation data and the historical environment data includes:

[0015] For each of the fault types, determining, in the historical fault case data, the number of historical fault cases corresponding to the fault type caused by the abnormality of the historical operating data as a first number of historical fault cases;

[0016] For each of the fault types, in the historical fault case data, the number of historical fault cases corresponding to the fault type caused by the abnormality of the historical environmental data is determined as a second number of historical fault cases.

[0017] Preferably, determining the first health scores corresponding to the historical operation data and the historical environment data respectively according to the number of historical fault cases under each fault type and a preset fault hazard weight includes:

[0018] Normalizing the first number of historical failure cases and the second number of historical failure cases under each of the failure types to obtain a normalized number of first historical failure cases and a normalized number of second historical failure cases;

[0019] Determine, based on the normalized number of first historical fault cases under each fault type and the preset fault hazard weight, a first sub-health score of the historical operation data under each fault type, and then perform an average operation on all first sub-health scores of the historical operation data to obtain a second sub-health score;

[0020] Determining a third sub-health score of the historical environment data under each fault type according to the normalized second number of historical fault cases under each fault type and the preset fault hazard weight, and then performing an average operation on all third sub-health scores of the historical environment data to obtain a fourth sub-health score;

[0021] Based on the second sub-health score and the fourth sub-health score, determine the first health scores corresponding to the historical operation data and the historical environment data respectively; wherein the first health score is obtained by subtracting the second sub-health score and the fourth sub-health score from the value 1.

[0022] Preferably, the determining of abnormal conditions of the current operating data and the current environmental data respectively, and determining, based on the abnormal conditions, second health scores corresponding to the current operating data and the current environmental data respectively, includes:

[0023] Comparing the current operating data with a preset operating data threshold to obtain the number of categories of abnormal operating data; and comparing the current environmental data with a preset environmental data threshold to obtain the number of categories of abnormal environmental data;

[0024] Performing a multi-threshold range comparison based on the number of categories of the abnormal operation data and the number of categories of the abnormal environment data, and determining the threshold ranges into which the abnormal operation data and the abnormal environment data fall respectively;

[0025] According to the threshold ranges into which the abnormal operation data and the abnormal environment data respectively fall, second health scores corresponding to the current operation data and the current environment data are determined.

[0026] Preferably, determining the total health score of the low-voltage station area according to the first health score and the second health score includes:

[0027] Obtaining a fifth sub-health score corresponding to the current running data according to the second health score corresponding to the current running data and the second sub-health score;

[0028] Obtaining a sixth sub-health score corresponding to the current environment data according to the second health score corresponding to the current environment data and the fourth sub-health score;

[0029] The total health score of the low-voltage station area is obtained according to the sum of the fifth sub-health score and the sixth sub-health score.

[0030] Preferably, the method further comprises:

[0031] The total health score of the low-voltage area in each time window is periodically updated, and the total health score of the low-voltage area is visualized.

[0032] In a second aspect, the present invention further provides a low voltage area health assessment system, comprising:

[0033] A data acquisition module is used to acquire historical operating data, historical environmental data, and historical fault case data of the low-voltage area within the same time window, and to acquire current operating data and current environmental data of the low-voltage area within the current time window;

[0034] A fault case classification module is used to classify the historical fault case data according to the fault type to obtain historical fault case data under multiple fault types;

[0035] a fault case statistics module, configured to determine the number of historical fault cases for each fault type based on the historical operating data and the historical environmental data; wherein the number of historical fault cases is obtained by counting the number of historical fault cases corresponding to the fault type that occurred due to abnormalities in the historical operating data or the historical environmental data;

[0036] A first health evaluation module is configured to determine first health scores corresponding to the historical operation data and the historical environment data, respectively, based on the number of historical fault cases under each fault type and a preset fault hazard weight;

[0037] a second health evaluation module, configured to determine abnormal conditions of the current operating data and the current environmental data, respectively, and determine second health scores corresponding to the current operating data and the current environmental data, respectively, based on the abnormal conditions;

[0038] The total health evaluation module is used to determine the total health score of the low-voltage substation according to the first health score and the second health score.

[0039] In a third aspect, the present invention further provides an electronic device comprising a memory and a processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the processor executes the steps of the low-voltage substation health assessment method as described in the first aspect.

[0040] In a fourth aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed, implements the steps of the low-voltage substation health assessment method as described in the first aspect.

[0041] In a fifth aspect, the present invention also provides a computer program product, comprising a computer program stored on a non-transitory computer-readable storage medium, wherein the computer program comprises program instructions, wherein when the program instructions are executed by a computer, the computer executes the steps of the low-voltage substation health assessment method as described in the first aspect.

[0042] It can be seen from the above technical solutions that the present invention obtains historical operation data, historical environmental data, historical fault case data, current operation data and current environmental data of the low-voltage substation, thereby collecting data from multiple data type dimensions and multiple time dimensions, and determines the number of historical fault cases under each fault type through historical operation data and historical environmental data, and determines the first health score corresponding to the historical operation data and historical environmental data respectively according to the number of historical fault cases and the fault hazard weight under each fault type, and also determines the second health score corresponding to the current operation data and the current environmental data respectively according to the abnormal conditions of the current operation data and the current environmental data, and determines the total health score of the low-voltage substation by combining the first health score and the second health score, so as to use the total health score to comprehensively and accurately evaluate the health status of the low-voltage substation, timely discover potential operation risks, so as to improve the stability and reliability of the low-voltage substation and ensure the safe operation of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0044] Figure 1 An application environment diagram of a low-voltage substation health assessment method provided by an embodiment of the present invention;

[0045] Figure 2 A flowchart of a method for evaluating the health of a low-voltage transformer area provided by an embodiment of the present invention;

[0046] Figure 3 A schematic diagram of the structure of a low-voltage substation health assessment system provided by an embodiment of the present invention;

[0047] Figure 4 A schematic structural diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0048] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0049] The low voltage area health assessment method provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown, the terminal 101 communicates with the server 102 via a network. The data storage system can store data that the server 102 needs to process. The data storage system can be integrated on the server 102 or placed on the cloud or other network servers. The terminal 101 or the server 102 obtains the historical operation data, historical environmental data and historical fault case data of the low-voltage substation in the same time window, and obtains the current operation data and current environmental data of the low-voltage substation in the current time window; classifies the historical fault case data according to the fault type to obtain historical fault case data under multiple fault types; determines the number of historical fault cases under each fault type based on the historical operation data and the historical environmental data; wherein the number of historical fault cases is obtained by counting the number of historical fault cases corresponding to the fault type caused by abnormal historical operation data or abnormal historical environmental data; determines the first health score corresponding to the historical operation data and the historical environmental data respectively according to the number of historical fault cases under each fault type and the preset fault hazard weight; determines the abnormal conditions of the current operation data and the current environmental data respectively, and determines the second health score corresponding to the current operation data and the current environmental data respectively based on the abnormal conditions; determines the total health score of the low-voltage substation based on the first health score and the second health score.

[0050] The terminal 101 may be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, and the like.

[0051] The server 102 may be an independent physical server, a server cluster or a distributed system composed of multiple physical servers, or a cloud server that provides cloud computing services.

[0052] like Figure 2 As shown, the embodiment of the present application provides a method for evaluating the health of a low-voltage station area. Figure 1 The terminal 101 or the server 102 is taken as an example to illustrate, including the following steps S1 to S6.

[0053] Step S1: Obtain historical operation data, historical environmental data, and historical fault case data of the low-voltage area within the same time window, and obtain current operation data and current environmental data of the low-voltage area within the current time window.

[0054] Among them, data acquisition equipment (such as smart meters, harmonic detection instruments, line loss monitoring devices) and environmental monitoring sensors (such as temperature and humidity sensors, electromagnetic interference monitors) are deployed in each low-voltage substation to collect multi-dimensional data of the low-voltage substation within the same time window, including historical operation data and historical environmental data, and retrieve historical fault case data within the same time window from the production system of each low-voltage substation.

[0055] Among them, historical operation data includes but is not limited to parameters such as voltage, current, power factor, load rate, etc. that reflect the operating status of the low-voltage substation. Historical environmental data includes but is not limited to external environmental factors such as temperature, humidity, wind speed, rainfall, etc. that may affect the operating status of the low-voltage substation. Historical fault case data is various fault cases that occurred in each low-voltage substation in the past, including but not limited to detailed information such as the time, location, type, cause, and scope of impact of the fault. Generally speaking, historical fault case data is recorded because of historical operation data or historical environmental data, thus

[0056] It can fully reflect the operating status of low-voltage substations in different time periods and under different environmental conditions.

[0057] For example, a data collection cycle is set for data acquisition equipment and environmental monitoring sensors. The data collection cycle for the data acquisition equipment includes: smart meters collect voltage, current, and power factor data every 15 minutes; harmonic detection instruments test the harmonic content of the substation every hour; and line loss monitoring devices calculate line loss data every other day by measuring the power difference between the two ends of the line. The data collection cycle for environmental monitoring sensors includes: electromagnetic interference monitors collect electromagnetic radiation intensity data every 15 minutes; and temperature and humidity sensors collect temperature and humidity data from low-voltage substations in real time. After completing each data collection cycle, the data acquisition equipment and environmental monitoring sensors transmit and summarize the collected parameters in real time. They also collect historical data for each low-voltage substation, including historical fault cases, historical operating parameters, and historical environmental parameters.

[0058] Step S2: classify the historical fault case data according to the fault type to obtain historical fault case data under multiple fault types.

[0059] Fault types are categorized into multiple fault types based on the fault information recorded in the historical fault case data, such as the cause of the fault, the characteristics of the fault manifestation, and the method of fault resolution. For example, fault types can be categorized into overload faults, short circuit faults, ground faults, equipment aging faults, and faults caused by environmental factors. For each fault type, the number of cases in the historical fault case data for that fault type is counted to generate historical fault case data for multiple fault types.

[0060] Step S3: Determine the number of historical fault cases under each fault type based on the historical operation data and the historical environmental data; wherein the number of historical fault cases is obtained by counting the number of historical fault cases corresponding to the fault type caused by abnormal historical operation data or abnormal historical environmental data.

[0061] This step analyzes the correlation between historical operating and environmental data and fault cases. By deeply analyzing historical data, we can identify abnormal changes in historical operating or environmental data that are directly associated with specific fault types. For example, an overload fault might be associated with an abnormal increase in voltage or current, while a fault caused by environmental factors might be related to extreme changes in temperature or humidity.

[0062] After determining the association, the fault case statistics module traverses historical fault case data and, for each fault type, counts the number of historical fault cases resulting from abnormal historical operating data or environmental data. The number of historical fault cases indicates the historical frequency of that fault type and its potential risk. A greater number of fault cases indicates a greater threat to the stable operation of the low-voltage substation, and therefore warrants greater attention and weighting when assessing the health of the low-voltage substation.

[0063] Step S4: Determine the first health scores corresponding to the historical operation data and the historical environment data respectively according to the number of historical fault cases under each fault type and the preset fault hazard weight.

[0064] The fault hazard weight is assigned to each fault type based on historical experience and expert assessment. The fault hazard weight reflects the impact and potential risk of the fault type on the stable operation of the low-voltage substation.

[0065] For example, overload faults and short circuit faults may pose a serious threat to the safe operation of the low-voltage substation, so the assigned fault hazard weight is higher; although equipment aging faults will also affect the performance of the low-voltage substation, their degree of hazard is relatively low, so the assigned fault hazard weight is also correspondingly lower.

[0066] After determining the fault hazard weight of each fault type, the terminal or server will calculate the product of the number of historical fault cases under each fault type and its corresponding fault hazard weight, and then add up the product results under all fault types. The higher the result, the worse the operating condition of the low-voltage substation in the past time window, the greater the potential risk, and corresponding measures need to be taken to improve and optimize in order to improve the stability and reliability of the low-voltage substation.

[0067] To obtain the first health score, the aforementioned results must be normalized and then subtracted from 1 to obtain the first health score. This ensures that the first health score ranges from 0 to 1, with higher scores indicating healthier historical operating conditions for the low-voltage substation. Normalization can employ a maximum-minimum normalization method to map the calculated results to a range of 0 to 1, facilitating horizontal comparison and evaluation of the health scores of different low-voltage substations.

[0068] Step S5: Determine abnormal conditions of the current operating data and the current environmental data respectively, and determine second health scores corresponding to the current operating data and the current environmental data respectively according to the abnormal conditions.

[0069] Among them, by detecting data anomalies of the current operating data and the current environmental data, such as voltage fluctuations beyond the normal range, excessive humidity or abnormal electromagnetic interference intensity, and marking these abnormal data and the number of abnormal data, the second health scores corresponding to the current operating data and the current environmental data are calculated.

[0070] Step S6: Determine the total health score of the low-voltage substation based on the first health score and the second health score.

[0071] Among them, the first health score and the second health score are weighted and summed to obtain the total health score of the low-voltage substation. Among them, the weighted weights can be set according to actual conditions to reflect the importance of historical operating data, historical environmental data and current operating data, and current environmental data in evaluating the health of the low-voltage substation. For example, if it is believed that historical data can better reflect the long-term operating status and potential risks of the low-voltage substation, the weight of the first health score can be set higher; and if it is believed that current data can better reflect the real-time operating status and immediate risks of the low-voltage substation, the weight of the second health score can be set higher. The higher the final total health score, the healthier the overall operating status of the low-voltage substation and the smaller the potential risks; conversely, the lower the total health score, the worse the operating status of the low-voltage substation, and corresponding measures need to be taken to improve and optimize it.

[0072] It should be noted that the embodiment of the present application obtains historical operation data, historical environmental data, historical fault case data, current operation data and current environmental data of the low-voltage substation, thereby collecting data from multiple data type dimensions and multiple time dimensions, and determines the number of historical fault cases under each fault type through historical operation data and historical environmental data. According to the number of historical fault cases under each fault type and the fault hazard weight, the first health score corresponding to the historical operation data and historical environmental data is determined. According to the abnormal conditions of the current operation data and current environmental data, the second health score corresponding to the current operation data and current environmental data is determined. The first health score and the second health score are combined to determine the total health score of the low-voltage substation, so as to use the total health score to comprehensively and accurately evaluate the health status of the low-voltage substation, timely discover potential operation risks, so as to improve the stability and reliability of the low-voltage substation and ensure the safe operation of the power system.

[0073] In some embodiments, the number of historical failure cases includes a first number of historical failure cases and a second number of historical failure cases;

[0074] Based on historical operating data and historical environmental data, determine the number of historical failure cases for each failure type, including:

[0075] Step S301: For each fault type, determine the number of historical fault cases corresponding to the fault type caused by abnormal historical operating data in the historical fault case data as a first number of historical fault cases.

[0076] Among them, the first number of historical fault cases is in the historical fault case data, and the historical operation data with data abnormalities when the fault occurs is counted. The number of fault cases associated with the historical operation data when data abnormalities occur in different fault types is counted. Historical operation data abnormalities refer to historical operation data deviating from the normal range, such as the current exceeding the rated current carrying capacity of the line.

[0077] Step S302: For each fault type, determine the number of historical fault cases corresponding to the fault type caused by abnormal historical environmental data in the historical fault case data as a second number of historical fault cases.

[0078] Among them, by checking whether the operating data at the time of the fault is abnormal due to the fluctuation of environmental data, if such a situation exists, the environmental data that causes the abnormal operating data and the number of historical fault cases under different fault types associated with this situation are counted. Environmental data fluctuations refer to fluctuations in environmental parameters, such as precipitation of more than 100 mm in a low-pressure area within 2-3 hours.

[0079] In some embodiments, determining the first health scores corresponding to the historical operation data and the historical environment data respectively based on the number of historical failure cases under each failure type and a preset failure hazard weight includes:

[0080] Step S401: Normalize the number of first historical fault cases and the number of second historical fault cases under each fault type to obtain the normalized number of first historical fault cases and the normalized number of second historical fault cases.

[0081] Step S402: Determine the first sub-health score of the historical operation data for each fault type based on the normalized number of first historical fault cases for each fault type and the preset fault hazard weight. Then, perform an average operation on all first sub-health scores of the historical operation data to obtain a second sub-health score.

[0082] Among them, the fault types are weighted according to their degree of hazard to obtain the fault hazard weight. The fault type with a high degree of hazard has a high fault hazard weight, and the fault type with a low degree of hazard has a low fault hazard weight. In addition, the fault hazard weight should be between 0 and 1.

[0083] Among them, when the historical operation data involves multiple fault types, the health score of the historical operation data under a single fault type is calculated separately according to the fault type, and then the calculated health scores of all fault types are added together, and the result of the addition is divided by the number of fault types, and the average value is taken as the second sub-health score.

[0084] Step S403: Determine the third sub-health score of the historical environmental data for each fault type based on the normalized number of second historical fault cases for each fault type and the preset fault hazard weight. Then, perform an average operation on all third sub-health scores of the historical environmental data to obtain the fourth sub-health score.

[0085] Among them, when the historical environmental data involves multiple fault types, the health score of the historical environmental data under a single fault type is calculated separately according to the fault type, and then the calculated health scores of all fault types are added together, and the result of the addition is divided by the number of fault types, and the average value is taken as the fourth sub-health score.

[0086] Step S404: Determine the first health scores corresponding to the historical operation data and the historical environment data, respectively, based on the second sub-health score and the fourth sub-health score; wherein the first health score is obtained by subtracting the second sub-health score and the fourth sub-health score from the value 1.

[0087] Among them, the second sub-health score is the first health score corresponding to the historical operation data, and the fourth sub-health score is the first health score corresponding to the historical environment data. Since in historical data analysis and health assessment, it is hoped that the higher the score, the better the health status, that is, the closer the historical operation data or historical environment data is to the ideal state, the higher the corresponding health score should be. However, after normalization, what is obtained is a quantitative representation of the degree to which the data deviates from the normal range. The higher the value, the greater the degree of deviation, that is, the worse the health status. Therefore, in order to obtain a health score that meets the expectations, the result of the normalization process needs to be reversed, that is, the value 1 is subtracted, so that the value originally representing the degree of deviation is converted into a score representing the health level. In this way, the second sub-health score and the fourth sub-health score can accurately reflect the health status corresponding to the historical operation data and historical environment data.

[0088] In some embodiments, determining abnormalities of the current operating data and the current environmental data, and determining second health scores corresponding to the current operating data and the current environmental data, respectively, based on the abnormalities, includes:

[0089] Step S501: compare the current operating data with a preset operating data threshold to obtain the number of categories of abnormal operating data; and compare the current environmental data with a preset environmental data threshold to obtain the number of categories of abnormal environmental data.

[0090] Step S502: performing a multi-threshold range comparison based on the number of categories of abnormal operation data and the number of categories of abnormal environment data, and determining the threshold ranges into which the abnormal operation data and the abnormal environment data fall respectively;

[0091] Step S503: Determine the second health scores corresponding to the current operation data and the current environment data, respectively, according to the threshold ranges into which the abnormal operation data and the abnormal environment data fall.

[0092] For example, the equipment data of the low-voltage substation is retrieved, and the operating data of different equipment are divided into three stages according to the equipment data, namely poor, medium, and excellent. The poor stage refers to the operating parameters completely deviating from the ideal numerical range for normal operation of the equipment, the medium stage refers to the operating parameters partially deviating from the ideal numerical range for normal operation of the equipment, and the excellent stage refers to the operating parameters being completely within the ideal numerical range for normal operation of the equipment. The health scores corresponding to the three stages are set to be higher and higher, such as 0.3, 0.5, and 0.8 respectively.

[0093] Similarly, based on the criterion of suitability for equipment operation, the environmental data is divided into three stages, namely poor, medium, and excellent. The poor stage refers to the environmental parameters completely deviating from the ideal numerical range for normal operation of the equipment, the medium stage refers to the environmental parameters partially deviating from the ideal numerical range for normal operation of the equipment, and the excellent stage refers to the environmental parameters completely within the ideal numerical range for normal operation of the equipment. The health scores corresponding to the three stages are set to be higher and higher, such as 0.2, 0.4, and 0.7 respectively. Among them, the second health score of the environmental data can be lower than the second health score of the operation data to reflect the importance of the operation data.

[0094] When the current operating data and current environmental data of the low-voltage substation are collected, the number of categories of abnormal data is counted by comparing the current operating data with the preset operating data threshold, and by comparing the current environmental data with the preset environmental data threshold, such as the number of categories such as voltage anomaly and current anomaly. Then, based on the number of categories of these abnormal data, a multi-threshold range comparison is performed. For example, the number of categories of abnormal data can be compared with different preset thresholds to determine the threshold range in which the abnormal data falls. For example, if the number of abnormal operating data counted is 10, the threshold ranges corresponding to poor, medium, and excellent are set to {10, 10 or above}, {5, 10}, and {0, 5}, respectively. By comparison, it is found that the abnormal operating data falls into the medium range, so the second health score of the current operating data is set to 0.5.

[0095] Among them, different threshold ranges correspond to different health scores, and the closer the threshold range is to the ideal state, the higher the score. For example, if the number of categories of abnormal data is small, and they are all just some anomalies that deviate slightly from the normal range, then these abnormal data may fall into a threshold range with a higher score; conversely, if the number of categories of abnormal data is large, and they are all anomalies that deviate seriously from the normal range, then these abnormal data may fall into a threshold range with a lower score. In this way, the health status of the current operating data and the current environmental data can be quantitatively evaluated to obtain the corresponding second health score. The higher the score, the healthier the current operating status and environmental status of the low-voltage substation, and the smaller the immediate risk; conversely, the lower the score, the worse the current operating status and environmental status of the low-voltage substation.

[0096] In some embodiments, determining the total health score of the low-voltage station area based on the first health score and the second health score includes:

[0097] Step S601: Obtain a fifth sub-health score corresponding to the current operating data based on the second health score and the second sub-health score corresponding to the current operating data;

[0098] Step S602: Obtain a sixth sub-health score corresponding to the current environment data based on the second health score and the fourth sub-health score corresponding to the current environment data;

[0099] Step S603: Obtain the total health score of the low voltage substation based on the sum of the fifth sub-health score and the sixth sub-health score.

[0100] The fifth sub-health score corresponding to the current and historical operating data, and the sixth sub-health score corresponding to the current and historical environmental data, are derived by weighting the first health score corresponding to historical operating data and historical environmental data, and the second health score corresponding to current operating data and current environmental data, based on the time dimension. This weighting allows for the allocation of weights based on the importance of historical and current data in the assessment, comprehensively reflecting the historical and current operating conditions of the low-voltage substation.

[0101] For example, if historical data is considered more important in the assessment, the weight of the first health score corresponding to historical data can be set higher. If current data is considered to better reflect the real-time status of the low-voltage substation, the weight of the second health score corresponding to current data can be set higher. Finally, the fifth and sixth sub-health scores are added together to obtain the total health score of the low-voltage substation. This total health score combines information from historical and current data to more comprehensively reflect the health of the low-voltage substation.

[0102] In some embodiments, the method further comprises:

[0103] The total health score of the low-voltage area in each time window is updated periodically, and the total health score of the low-voltage area is visualized.

[0104] Among them, by constructing a visual interface, the total health score of the low-voltage substation in each time window is displayed in the form of a chart or curve, so that the operation and maintenance personnel can intuitively understand the changing trend of the health status of the low-voltage substation. For example, a bar chart can be used to display the total health scores of different time windows, and the height changes of the bar chart can be used to reflect the pros and cons of the health status of the low-voltage substation; or a line chart can be used to display the trend of changes in the total health score over time, and the stability of the health status of the low-voltage substation can be judged by the fluctuations of the line chart. In addition, an early warning mechanism can be set in the visual interface. When the total health score is lower than the preset threshold, an early warning signal is automatically triggered to remind the operation and maintenance personnel to take timely measures to intervene, thereby effectively avoiding the occurrence of potential risks and improving the operating efficiency and safety of the low-voltage substation.

[0105] For example, according to the stage results of the total health score of the low-voltage substation, different low-voltage substations are represented by filled blocks of different colors on the control center screen and displayed on the map. Low-voltage substations in the excellent stage, medium stage, and poor stage are represented by green filled blocks, yellow filled blocks, and red filled blocks respectively. Set the chart option in the lower right corner of the map. After clicking the chart option, a total health score table of each low-voltage substation will pop up on the page. Click a single low-voltage substation in the table, and a trend chart of the total health score of the low-voltage substation within one month will pop up on the page. You can select the time on the pop-up page on the control center screen to view the historical trend chart of the total health score of the low-voltage substation.

[0106] Click on the filled color block of a single low-voltage area, and a detailed table of the health score of the area will pop up. The detailed table contains the total health score of the low-voltage area and the health score of each parameter of the low-voltage area. Click on a single parameter, and a health score trend chart of the parameter within one month will pop up. You can select a time on the pop-up page to view the historical health score trend chart of the parameter.

[0107] Based on the same inventive concept, an embodiment of the present application also provides a low-voltage substation health assessment system for implementing the above-mentioned low-voltage substation health assessment method.

[0108] The implementation solution provided by this system to solve the problem is similar to the implementation solution described in the above method. Therefore, the specific limitations in one or more low-voltage substation health assessment system embodiments provided below can be found in the above limitations on the low-voltage substation health assessment method and will not be repeated here.

[0109] like Figure 3 As shown, the embodiment of the present application provides a low voltage area health assessment system, including:

[0110] The data acquisition module 100 is used to acquire the historical operation data, historical environmental data and historical fault case data of the low-voltage area in the same time window, and to acquire the current operation data and current environmental data of the low-voltage area in the current time window;

[0111] The fault case classification module 200 is used to classify the historical fault case data according to the fault type, and obtain the historical fault case data under multiple fault types;

[0112] The fault case statistics module 300 is used to determine the number of historical fault cases for each fault type based on historical operating data and historical environmental data. The number of historical fault cases is obtained by counting the number of historical fault cases corresponding to the fault type caused by abnormal historical operating data or abnormal historical environmental data.

[0113] A first health evaluation module 400 is configured to determine first health scores corresponding to the historical operating data and the historical environmental data, respectively, based on the number of historical fault cases under each fault type and a preset fault hazard weight;

[0114] The second health evaluation module 500 is used to determine abnormal conditions of the current operating data and the current environmental data, and determine second health scores corresponding to the current operating data and the current environmental data respectively according to the abnormal conditions;

[0115] The overall health evaluation module 600 is configured to determine an overall health score of the low voltage substation area based on the first health score and the second health score.

[0116] In some embodiments, the number of historical failure cases includes a first number of historical failure cases and a second number of historical failure cases;

[0117] The fault case statistics module 300 is used to:

[0118] For each fault type, in the historical fault case data, determine the number of historical fault cases corresponding to the fault type caused by abnormal historical operating data as the first number of historical fault cases;

[0119] For each fault type, in the historical fault case data, the number of historical fault cases corresponding to the fault type caused by abnormal historical environmental data is determined as the second number of historical fault cases.

[0120] In some embodiments, the first health assessment module 400 is configured to:

[0121] Normalizing the number of first historical fault cases and the number of second historical fault cases under each fault type to obtain a normalized number of first historical fault cases and a normalized number of second historical fault cases;

[0122] Based on the normalized number of first historical fault cases under each fault type and the preset fault hazard weight, the first sub-health score of the historical operation data under each fault type is determined. Then, the average operation is performed on all the first sub-health scores of the historical operation data to obtain the second sub-health score.

[0123] Based on the normalized number of second historical fault cases under each fault type and the preset fault hazard weight, the third sub-health score of the historical environmental data under each fault type is determined. Then, all the third sub-health scores of the historical environmental data are averaged to obtain the fourth sub-health score.

[0124] Based on the second sub-health score and the fourth sub-health score, the first health scores corresponding to the historical operation data and the historical environment data are determined respectively; wherein the first health score is obtained by subtracting the second sub-health score and the fourth sub-health score from the value 1 respectively.

[0125] In some embodiments, the second health assessment module 500 is configured to:

[0126] Comparing the current operating data with a preset operating data threshold to obtain the number of categories of abnormal operating data; and comparing the current environmental data with a preset environmental data threshold to obtain the number of categories of abnormal environmental data;

[0127] Performing a multi-threshold range comparison based on the number of categories of abnormal operation data and the number of categories of abnormal environment data, and determining the threshold ranges into which the abnormal operation data and the abnormal environment data fall respectively;

[0128] According to the threshold ranges into which the abnormal operation data and the abnormal environment data respectively fall, second health scores corresponding to the current operation data and the current environment data are determined.

[0129] In some embodiments, the overall health assessment module 600 is configured to:

[0130] Obtaining a fifth sub-health score corresponding to the current running data based on the second health score and the second sub-health score corresponding to the current running data;

[0131] Obtaining a sixth sub-health score corresponding to the current environmental data based on the second health score and the fourth sub-health score corresponding to the current environmental data;

[0132] The total health score of the low-voltage substation is obtained by adding the fifth sub-health score and the sixth sub-health score.

[0133] In some embodiments, the system further comprises:

[0134] The visualization module is used to periodically update the total health score of the low-voltage area in each time window and visualize the total health score of the low-voltage area.

[0135] like Figure 4 As shown, an embodiment of the present application provides an electronic device, the electronic device 10 includes a memory 20 and a processor 30, the memory 20 stores a computer program, and when the computer program is executed by the processor 30, the processor 30 executes the steps of the low-voltage substation health assessment method in the above embodiment.

[0136] An embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed, the steps of the low-voltage substation health assessment method in the above embodiment are implemented.

[0137] An embodiment of the present application provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium, and the computer program includes program instructions. When the program instructions are executed by a computer, the computer executes the steps of the low-voltage substation health assessment method described in the above embodiment.

[0138] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described systems, electronic devices, and computer storage media can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0139] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0140] It should be understood that, although the various steps in the flowcharts involved in the above embodiments are shown in sequence as indicated by the arrows, these steps are not necessarily performed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be performed in other orders. Moreover, at least a portion of the steps in the flowcharts involved in the above embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily performed at the same time, but can be performed at different times, and the execution order of these steps or stages is not necessarily performed in sequence, but can be performed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0141] In the several embodiments provided by the present invention, it should be understood that the disclosed systems, electronic devices, computer storage media and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0142] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0143] In addition, the functional units in the various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0144] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for executing all or part of the steps of the method described in each embodiment of the present invention via a computer device (which can be a personal computer, server, or network device, etc.). The aforementioned storage medium includes various media that can store program code, such as a USB flash drive, a mobile hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0145] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A method for assessing the health of a low-voltage substation, characterized in that: include: Obtain historical operating data, historical environmental data, and historical fault case data of the low-voltage area within the same time window, and obtain current operating data and current environmental data of the low-voltage area within the current time window; Classifying the historical fault case data according to fault types to obtain historical fault case data under multiple fault types; Determining the number of historical fault cases for each fault type based on the historical operating data and the historical environmental data; wherein the number of historical fault cases is obtained by counting the number of historical fault cases corresponding to the fault type that occurred due to abnormalities in the historical operating data or the historical environmental data; Determining first health scores corresponding to the historical operation data and the historical environment data, respectively, according to the number of historical fault cases under each fault type and a preset fault hazard weight; Determining abnormal conditions of the current operating data and the current environmental data respectively, and determining second health scores corresponding to the current operating data and the current environmental data respectively according to the abnormal conditions; The total health score of the low-voltage station area is determined according to the first health score and the second health score.

2. The low voltage area health assessment method according to claim 1, characterized in that: The number of historical failure cases includes the number of first historical failure cases and the number of second historical failure cases; Determining the number of historical fault cases for each fault type based on the historical operation data and the historical environment data includes: For each of the fault types, determining, in the historical fault case data, the number of historical fault cases corresponding to the fault type caused by the abnormality of the historical operating data as a first number of historical fault cases; For each of the fault types, in the historical fault case data, the number of historical fault cases corresponding to the fault type caused by the abnormality of the historical environmental data is determined as a second number of historical fault cases.

3. The low voltage area health assessment method according to claim 2, characterized in that: The determining, based on the number of historical fault cases under each fault type and a preset fault hazard weight, first health scores corresponding to the historical operation data and the historical environment data, respectively, includes: Normalizing the first number of historical failure cases and the second number of historical failure cases under each of the failure types to obtain a normalized number of first historical failure cases and a normalized number of second historical failure cases; Determine, based on the normalized number of first historical fault cases under each fault type and the preset fault hazard weight, a first sub-health score of the historical operation data under each fault type, and then perform an average operation on all first sub-health scores of the historical operation data to obtain a second sub-health score; Determining a third sub-health score of the historical environment data under each fault type according to the normalized second number of historical fault cases under each fault type and the preset fault hazard weight, and then performing an average operation on all third sub-health scores of the historical environment data to obtain a fourth sub-health score; Based on the second sub-health score and the fourth sub-health score, determine the first health scores corresponding to the historical operation data and the historical environment data respectively; wherein the first health score is obtained by subtracting the second sub-health score and the fourth sub-health score from the value 1.

4. The low voltage area health assessment method according to claim 3, characterized in that: The determining of abnormal conditions of the current operating data and the current environmental data respectively, and determining second health scores corresponding to the current operating data and the current environmental data respectively according to the abnormal conditions, includes: Comparing the current operating data with a preset operating data threshold to obtain the number of categories of abnormal operating data; and comparing the current environmental data with a preset environmental data threshold to obtain the number of categories of abnormal environmental data; Performing a multi-threshold range comparison based on the number of categories of the abnormal operation data and the number of categories of the abnormal environment data, and determining the threshold ranges into which the abnormal operation data and the abnormal environment data fall respectively; According to the threshold ranges into which the abnormal operation data and the abnormal environment data respectively fall, second health scores corresponding to the current operation data and the current environment data are determined.

5. The low voltage area health assessment method according to claim 4 is characterized in that: Determining the total health score of the low-voltage station area according to the first health score and the second health score includes: Obtaining a fifth sub-health score corresponding to the current running data according to the second health score corresponding to the current running data and the second sub-health score; Obtaining a sixth sub-health score corresponding to the current environment data according to the second health score corresponding to the current environment data and the fourth sub-health score; The total health score of the low-voltage station area is obtained according to the sum of the fifth sub-health score and the sixth sub-health score.

6. The low voltage substation health assessment method according to any one of claims 1 to 5, characterized in that: Also includes: The total health score of the low-voltage area in each time window is periodically updated, and the total health score of the low-voltage area is visualized.

7. A low voltage substation health assessment system, characterized in that: include: A data acquisition module is used to acquire historical operating data, historical environmental data, and historical fault case data of the low-voltage area within the same time window, and to acquire current operating data and current environmental data of the low-voltage area within the current time window; A fault case classification module is used to classify the historical fault case data according to the fault type to obtain historical fault case data under multiple fault types; a fault case statistics module, configured to determine the number of historical fault cases for each fault type based on the historical operating data and the historical environmental data; wherein the number of historical fault cases is obtained by counting the number of historical fault cases corresponding to the fault type that occurred due to abnormalities in the historical operating data or the historical environmental data; A first health evaluation module is configured to determine first health scores corresponding to the historical operation data and the historical environment data, respectively, based on the number of historical fault cases under each fault type and a preset fault hazard weight; a second health evaluation module, configured to determine abnormal conditions of the current operating data and the current environmental data, respectively, and determine second health scores corresponding to the current operating data and the current environmental data, respectively, based on the abnormal conditions; The total health evaluation module is used to determine the total health score of the low-voltage substation according to the first health score and the second health score.

8. An electronic device, characterized in that: The electronic device includes a memory and a processor, wherein a computer program is stored in the memory. When the computer program is executed by the processor, the processor executes the steps of the low-voltage substation health assessment method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed, the steps of the low-voltage substation health assessment method according to any one of claims 1 to 6 are implemented.

10. A computer program product, characterized in that The computer program product includes a computer program stored on a non-transitory computer-readable storage medium, wherein the computer program includes program instructions, wherein when the program instructions are executed by a computer, the computer is caused to perform the steps of the low-voltage substation health assessment method according to any one of claims 1 to 6.

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