AC / DC power supply system monitoring method, device and system

Abstract

The present application relates to the technical field of AC / DC power supply monitoring, and specifically to a method, device, and system for monitoring an AC / DC power supply system, specifically comprising: quantifying the influence of aging and environmental factors through changes in insulation resistance and the relationship between changes in insulation resistance and environmental changes, and calculating an environmental impact coefficient and an aging trend coefficient; calculating the expected insulation resistance of each node at each moment based on changes between data points at adjacent moments in the fitting curve, combined with the insulation resistance of each node at the previous moment; correlation between positive and negative pole-to-ground voltages; constructing a grounding fault coefficient at each moment based on the above parameters; detecting DC grounding faults in the AC / DC power supply system based on the grounding fault coefficients at consecutive moments; enhancing the sensitivity and accuracy of DC grounding fault diagnosis using the grounding fault coefficient, reducing the probability of misjudgment and missed judgment, and improving the monitoring quality of the AC / DC power supply system.

Description

Technical Field

[0001] The present application relates to the technical field of AC / DC power supply monitoring, and in particular to a method, device, and system for monitoring an AC / DC power supply system. Background Art

[0002] With the continuous development of smart grids, AC / DC power systems have been widely used in fields such as power generation, communications, rail transit, and data centers. These systems are characterized by complex structures, diverse operating modes, and strong load sensitivity. To ensure the safe and stable operation of the system, real-time monitoring of its operating status is particularly important. DC ground faults are one of the common faults in AC / DC power systems. Once they occur, they can have serious consequences. It is generally believed that normal operation can still be achieved in the event of a single-point ground fault. However, if another ground fault is created on this basis, a short circuit is formed, which can ultimately cause the circuit where the system protection device is located to malfunction or fail to operate due to erroneous information. This can even cause fuses to blow, equipment to burn out, and disrupt the stable operation of the power grid. Therefore, timely detection of DC ground faults is crucial.

[0003] Currently, mainstream DC ground fault detection methods rely primarily on insulation resistance monitoring. This method determines whether a DC ground fault exists based on the insulation resistance level in the system. This often requires setting a fixed insulation resistance threshold. However, this threshold setting method has significant limitations. It only considers instantaneous changes in insulation resistance and fails to account for its susceptibility to environmental and aging factors, making it prone to misjudgment or missed detections. Summary of the Invention

[0004] In order to solve the above technical problems, the purpose of this application is to provide an AC / DC power system monitoring method, device and system. The technical solutions adopted are as follows:

[0005] In a first aspect, an embodiment of the present application provides a method for monitoring an AC / DC power supply system, the method comprising the following steps:

[0006] Collect monitoring data of the AC and DC power systems at all times, including the insulation resistance of the main bus, branches, and key equipment, the positive and negative ground voltages of the main bus and branches, and ambient temperature and humidity. The main bus, branches, and key equipment are considered nodes.

[0007] The acquisition time is clustered by temperature and humidity at all times, and an insulation series of each cluster is constructed for each node based on the insulation resistance of each node at the corresponding time in each cluster. A fitting curve for each cluster insulation series is obtained. Based on the data change trend and data mutation characteristics in all cluster insulation series of each node, as well as the differences between all corresponding fitting curves, an aging trend coefficient for the insulation resistance data change of each node is constructed.

[0008] Calculating the correlation between the insulation resistance of each node in the same time period and the temperature and humidity, respectively; calculating the aging degree metric of each node in each time period based on the function values ​​of all the fitting curves of each node at the same time; constructing the environmental impact coefficient of the insulation resistance data change of each node based on the difference in the correlation and the difference in the aging degree metric of each node in adjacent time periods;

[0009] Based on the changes between the data points at adjacent moments in the fitting curve and in combination with the insulation resistance of each node at the previous moment, the expected insulation resistance of each node at each moment is calculated; based on the correlation between the positive and negative pole-to-ground voltages at the same acquisition location, the aging trend coefficient and the environmental impact coefficient of each node, and the difference between the insulation resistance of each node at each moment and the expected insulation resistance, the ground fault coefficient at each moment is constructed;

[0010] DC ground fault detection in AC / DC power systems is performed based on the ground fault coefficient at consecutive moments.

[0011] In one embodiment, the process of obtaining the aging trend coefficient of the insulation resistance data change of each node is as follows:

[0012] Calculate the mean of the integrated area difference of the fitting curves of the pairwise combinations of all cluster insulation sequences of each node, and record it as the first area mean;

[0013] Calculating the proportion of positive numbers in the first-order difference sequence of each cluster insulation sequence of each node; calculating the ratio of the goodness of fit of the fitting curve function of each cluster insulation sequence of each node to the proportion of positive numbers, recorded as a first ratio;

[0014] The ratio of the sum of the first ratios of all cluster insulation sequences of each node to the first area mean is used as the aging trend coefficient of the insulation resistance data change of each node.

[0015] In one embodiment, the process of obtaining the aging degree metric of each node in each time period is as follows:

[0016] Calculate the sum of the function values ​​at any same time in the fitting curve functions of all cluster isolation sequences of each node, and record it as the first sum value at any same time of each node;

[0017] The average of the first sum values ​​of each node at all moments in each time period is used as the aging degree measurement of each node in each time period.

[0018] In one embodiment, the process of obtaining the environmental impact coefficient of the insulation resistance data change of each node is as follows:

[0019] Based on the correlation between the insulation resistance data of each node and the temperature and humidity data, respectively, the correlation between the insulation resistance data of each node and the environmental parameter data in each time period is calculated, and recorded as resistance-environment correlation;

[0020] Calculate the resistance environment correlation difference of each node between the i+1th time period and the ith time period; calculate the sign function value of the aging degree metric difference of each node between the i+1th time period and the ith time period;

[0021] An average value of the ratio of the resistance environment correlation difference value to the sign function value of each node in all time periods is used as the environmental impact coefficient of the insulation resistance data change of each node.

[0022] In one embodiment, the process of obtaining the resistance environment correlation is:

[0023] The correlation measures between the time series of the insulation resistance of each node in the i-th time period and the time series of the temperature and humidity in the i-th time period are calculated respectively, and recorded as the first correlation and the second correlation respectively. The average of the first correlation and the second correlation is taken as the resistance environment correlation of each node in the i-th time period.

[0024] In one embodiment, the expression of the expected insulation resistance is:

[0025] , where yes The expected insulation resistance of the current node at the moment; yes The actual insulation resistance data collected by the current node at the moment; yes Moment and The aging rate of the insulation resistance between moments, The calculation process is: calculate the fitting curve of each cluster insulation sequence Time data points and The slope of the line connecting the data points at the moment is recorded as the rate of change, and the mean of the rate of change of all cluster isolation sequences of the current node is taken as .

[0026] In one embodiment, the expression of the ground fault coefficient at each moment is:

[0027] , where yes The ground fault coefficient at the moment; The mean value of the correlation measure between the positive pole-to-ground voltage time series and the negative pole-to-ground voltage time series at the same position of the main busbar and all branches; is the number of nodes in the AC / DC power system that perform insulation resistance monitoring; 、 They are The normalized value of the environmental impact coefficient and the normalized value of the aging trend coefficient of each node; For the Nodes in The difference between the actual insulation resistance collected at a certain moment and the expected insulation resistance.

[0028] In one embodiment, the DC grounding fault detection of the AC / DC power supply system based on the grounding fault coefficient at consecutive moments is specifically performed as follows:

[0029] The ground fault coefficient at any moment and a preset number of moments before it is divided by threshold value;

[0030] If the grounding fault coefficient at any moment is greater than the segmentation threshold, and the grounding fault coefficients at a preset number of moments after the any moment are also greater than the segmentation threshold, it is determined that a DC grounding fault exists in the AC / DC power supply system.

[0031] In a second aspect, an embodiment of the present application further provides an AC / DC power supply system monitoring device, wherein a computer program is stored in the device, and when the computer program is executed by a processor, the steps of the method described in the first aspect are implemented.

[0032] In a third aspect, an embodiment of the present application further provides an AC / DC power supply system monitoring system, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor implements the steps of the method described in the first aspect above when executing the computer program.

[0033] The embodiments of the present application have at least the following beneficial effects:

[0034] The present application first calculates the environmental impact coefficient and the aging trend coefficient based on the change of insulation resistance and the relationship between it and environmental changes. These two indicators improve the accuracy of quantifying the relationship between the change of insulation resistance of AC / DC power supply systems and the influence of environmental factors and aging, which helps to improve the accuracy of subsequent DC ground fault identification and correction; then, the ground fault coefficient is calculated in combination with the positive and negative ground voltages, and the DC ground fault detection is corrected according to the influence of environmental and aging factors on the insulation resistance, thereby enhancing the sensitivity and accuracy of DC ground fault diagnosis using the ground fault coefficient and reducing the probability of misjudgment and missed judgment. Through this method, the influence of aging and environmental factors is first quantified, and the quantified results are used to correct the DC ground fault detection, thereby reducing the influence of aging and environmental factors as much as possible, thereby enhancing the accuracy of DC ground fault diagnosis, improving the monitoring quality of AC / DC power supply systems, and helping to ensure the safe and stable operation of AC / DC power supply systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present application or the prior art, the following is a brief introduction to 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 application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0036] Figure 1 A flowchart of a method for monitoring an AC / DC power supply system according to an embodiment of the present application is provided;

[0037] Figure 2 Schematic diagram of the process of obtaining the aging trend coefficient. DETAILED DESCRIPTION

[0038] To further illustrate the technical means and effectiveness of this application to achieve the intended invention objectives, the following, in conjunction with the accompanying drawings and preferred embodiments, describes in detail the AC / DC power system monitoring method, device, and system proposed in this application, including its specific implementation, structure, features, and effectiveness. In the following description, different references to "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0039] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0040] The following describes in detail a method, device and system for monitoring an AC / DC power supply system provided by the present application with reference to the accompanying drawings.

[0041] See also Figure 1 , which shows a flowchart of a method for monitoring an AC / DC power supply system provided by an embodiment of the present application, the method comprising the following steps:

[0042] Step S1, collecting monitoring data of the AC and DC power supply systems at each moment, including: the insulation resistance of the main bus, each branch and each key equipment, the positive and negative voltages of the main bus and each branch to ground, and the ambient temperature and humidity; the main bus, each branch and each key equipment are regarded as nodes.

[0043] Install insulation resistance monitors on the AC / DC power system's main busbar, branch feeders, and key equipment to collect insulation resistance data. Key equipment here includes transformers, circuit breakers, and cable connectors. The main busbar, branches, and key equipment are considered nodes.

[0044] The temperature and humidity sensors in the AC / DC power supply monitoring system are used to collect the ambient temperature and humidity of the AC / DC power supply system.

[0045] At the positive and negative poles of the main bus and each branch feeder, the positive and negative poles to ground voltages at the corresponding positions are measured using Hall voltage sensors.

[0046] It should be noted that, for the data collection frequency of insulation resistance, ambient temperature, and ambient humidity, preferably, in the embodiment of the present application, the data collection frequency is set to once per hour; for the data collection frequency of voltage data, preferably, in the embodiment of the present application, the data collection frequency is set to once per second. As other embodiments of the present application, the implementer can set the collection frequency of various types of data according to actual conditions.

[0047] The insulation resistance data collected at each node are sequenced in ascending order of collection time as the insulation resistance sequence of each node; the temperature data and humidity data of the operating environment of the AC / DC power supply system are sequenced in ascending order of collection time, and the obtained sequences are recorded as temperature sequence and humidity sequence respectively; the positive and negative pole-to-ground voltages of the main busbar and each branch feeder are sequenced in ascending order of collection time, thereby obtaining the positive pole-to-ground voltage sequence and negative pole-to-ground voltage sequence of the main busbar and each branch feeder.

[0048] Then, each data sequence is normalized using a normalization method to eliminate the effects of units and dimensions. This application uses the maximum normalization method to normalize each data sequence.

[0049] It should be noted that there are many existing normalization methods, and implementers can also use other normalization methods to normalize each data sequence. This application does not impose specific restrictions.

[0050] Step S2: cluster the collection moments by the temperature and humidity at all moments, and construct an insulation sequence for each cluster of each node based on the insulation resistance of each node at the corresponding moment in each cluster; obtain a fitting curve for the insulation sequence of each cluster; and construct an aging trend coefficient for the insulation resistance data change of each node based on the data change trend and data mutation characteristics in the insulation sequences of all clusters of each node, as well as the differences between all corresponding fitting curves.

[0051] In AC / DC power systems, DC ground faults are one of the most common faults. When a single-point DC ground fault occurs, it is generally assumed that the system can still operate normally. If a ground fault occurs at another point, a short circuit will be formed, which will have a negative impact on the AC / DC power system. Therefore, accurate identification of DC ground faults is key to ensuring the safe and stable operation of AC / DC power systems. In existing methods, DC ground faults are often diagnosed based on changes in insulation resistance. When the insulation resistance exceeds a set threshold, a fault is considered to exist. However, since insulation resistance is easily affected by various factors other than the fault, and AC / DC power systems also have complex fault scenarios such as multi-point grounding, existing DC ground fault diagnosis methods have a high probability of missed detection and false detection. Therefore, it is necessary to further improve the accuracy of DC ground faults.

[0052] When a DC ground fault occurs in an AC / DC power system, it can cause a change in insulation resistance. This high sensitivity of insulation resistance helps reduce missed DC ground fault detections. However, precisely because of this high sensitivity, insulation resistance is easily affected by the state and environment of the AC / DC power system. These various influencing factors, when coupled together, significantly increase the probability of misdiagnosis when using insulation resistance to diagnose DC ground faults, thereby increasing the probability of malfunction in the AC / DC power system and impacting its safe and stable operation. Therefore, improving the recognition of fluctuations in insulation resistance due to aging and environmental influences is key to improving the accuracy of measuring abnormal insulation resistance fluctuations and the precision of DC ground fault identification.

[0053] When identifying the effects of aging and environmental impacts, it is necessary to first decouple the two influencing factors. Aging in AC and DC power systems is characterized by stability and trend. Trend refers to the fact that aging is an irreversible damage that reduces insulation resistance. Due to the irreversibility of aging, aging causes the insulation resistance to show a strict and continuous decreasing trend. Stability refers to the gradual change trend of aging. Normal aging does not cause major mutations and strictly follows a functional curve.

[0054] Based on the above analysis, we first obtain insulation resistance data under the same environmental conditions to eliminate environmental influences, so as to analyze the degree to which insulation resistance changes are affected by aging. Specifically:

[0055] The temperature series and humidity series are used as inputs to the K-means clustering algorithm, where the number of clusters is determined by the elbow rule. Using the temperature and humidity data at the same collection time as the feature data at that collection time, all collection times are clustered and output as clusters. The K-means clustering algorithm and the elbow rule are both well-known technologies, and the specific process will not be repeated here.

[0056] It should be noted that for the clustering of collection moments, this application only provides one clustering method. There are many existing clustering methods, and implementers can also use other clustering algorithms to cluster the collection moments. This application does not make specific restrictions.

[0057] Furthermore, within each node's insulation resistance sequence, the insulation resistance data from all acquisition moments within a cluster are arranged in chronological order to form a cluster insulation sequence. For each cluster insulation sequence at each node, a polynomial fitting algorithm is used to perform curve fitting, with each element in the cluster insulation sequence as the ordinate and the corresponding data acquisition moment as the abscissa, to obtain a fitted curve function for the cluster insulation sequence. Polynomial fitting is a well-known technique, and the specific process is not described in detail here. In this manner, a fitted curve function for each cluster insulation sequence at each node is obtained.

[0058] It should be noted that for the curve fitting of clustered cluster insulation sequences, this application only provides a curve fitting method. There are many existing curve fitting methods, and implementers can also use other curve fitting algorithms to perform curve fitting on clustered cluster insulation sequences. This application does not make specific restrictions.

[0059] Then, any node is taken as the current node. Taking the current node as an example, the aging trend coefficient of the insulation resistance data change of each node is calculated through the fitting characteristics and data change characteristics of all cluster insulation sequences of each node. The expression is:

[0060] , where is the aging trend coefficient of the insulation resistance data change of the current node; The mean of the integrated area differences of the fitting curves of all pairwise combinations of cluster insulation sequences of the current node is recorded as the first area mean, where the integration interval for the area integration of the fitting curve of each cluster insulation sequence is from the first acquisition moment to the last acquisition moment; is the number of cluster isolation sequences of the current node, which is the number of clusters mentioned above; The current node The goodness of fit of the fitting curve function of the cluster insulation sequence; The current node The proportion of positive numbers in the first-order difference sequence of the cluster isolation sequence is the ratio of the number of positive numbers in the first-order difference sequence to the total number of elements. The calculation of the goodness of fit is a well-known technology and the specific process will not be repeated here. is the first ratio.

[0061] Under normal circumstances, as the AC and DC power systems age, the insulation resistance shows a stricter decrease, i.e. The value should be small; and under normal circumstances, the insulation resistance fluctuation mutation caused by aging is relatively rare, so there are fewer mutation data in the insulation resistance data. After fitting, the fitting curve function has a higher fitting goodness. At the same time, since the decreasing trend of the insulation resistance caused by aging is also relatively regular, the insulation resistance fluctuation curve caused by aging is also relatively consistent, that is, The value of should be smaller; thus, the aging trend coefficient is larger, and the insulation resistance change is more consistent with the data change caused by aging, and less consistent with the data characteristics of DC grounding fault.

[0062] Step S3, calculate the correlation between the insulation resistance of each node in the same time period and the temperature and humidity respectively, and calculate the aging degree measurement of each node in each time period based on the function value at the same moment in all the fitting curves of each node in each time period; based on the difference in the correlation and the difference in the aging degree measurement of adjacent time periods of each node, construct the environmental impact coefficient of the insulation resistance data change of each node.

[0063] As for environmental influences, ambient temperature and humidity will affect the insulation resistance of AC and DC power supply systems. Therefore, under normal circumstances, there is a high correlation between changes in insulation resistance and changes in environmental parameters. As the degree of aging becomes more serious, the influence of environmental factors on insulation resistance becomes more and more obvious. Therefore, the correlation between insulation resistance and changes in environmental parameters becomes stronger with the degree of aging. When a DC grounding fault exists, the insulation resistance is affected by the DC grounding fault, which weakens the correlation between the insulation resistance and the environmental parameters and the degree of aging.

[0064] As the AC and DC power systems age, the impact of environmental factors on insulation resistance becomes increasingly significant. To measure the impact of environmental factors, it is necessary to first divide the environmental parameters into periodic groups, specifically:

[0065] Set the cycle length. A period is obtained by collecting the data at each time. Taking temperature data as an example, the temperature sequence is divided into periods. Each temperature subsequence contains elements, where the last temperature subsequence is insufficient. The elements are no longer replenished. Among them, because it is affected by environmental factors and also by aging, and the aging effect takes a long time to show a difference, in this embodiment, The value of is set to 168, meaning that each segment contains one week of monitoring data. Based on the humidity sequence and the insulation resistance sequence of each node, the same period division method as the temperature sequence is used to divide the sequence into subsequences of humidity and insulation resistance at each node.

[0066] Then, the correlation between the insulation resistance subsequence of each node and the corresponding environmental data is calculated. Specifically, the correlation measures between the i-th insulation resistance subsequence of each node and the i-th temperature subsequence and the i-th humidity subsequence are calculated, which are recorded as the first correlation and the second correlation respectively. The average of the first correlation and the second correlation is taken as the correlation between the i-th insulation resistance subsequence of each node and the corresponding environmental data, which is recorded as the resistance environment correlation.

[0067] It should be noted that, for the correlation measurement, the specific one in the embodiment of the present application is the Pearson correlation coefficient; the present application only proposes a correlation measurement method, and there are many existing correlation measurement methods. The implementer may also use other correlation measurement algorithms such as the Spearman correlation coefficient and cosine similarity to measure the correlation between the insulation resistance subsequence and the temperature and humidity subsequences respectively. The present application does not impose any specific restrictions.

[0068] Afterwards, the aging degree measure of each segment of the insulation resistance subsequence is calculated by taking the mean of the function values ​​of the fitting curve functions of all cluster insulation sequences of each node at the same time. The expression is: , where is the aging degree measure of the ith insulation resistance subsequence of the current node; is the number of elements in the insulation resistance subsequence of the current node i; is the number of cluster isolation sequences of the current node; The current node In the fitting curve function of the cluster insulation sequence, the The function value of the nth element of the insulation resistance subsequence at the acquisition moment. is the first sum value.

[0069] Finally, taking the current node as an example, the environmental impact coefficient of the insulation resistance change of each node is calculated to measure the degree to which the insulation resistance data change in the AC / DC power supply system is affected by the environment. The expression is:

[0070] , where is the environmental impact coefficient of the insulation resistance data change of the current node; is the number of insulation resistance subsequences of the current node; 、 They are the current node Paragraph and Section Correlation between segment insulation resistance subsequences and corresponding environmental data; 、 They are the current node Paragraph and Section Aging degree measurement of segment insulation resistance subsequence; is a sign function.

[0071] Under normal circumstances, there is a high correlation between the change in insulation resistance and the environmental parameters, and with the increase of aging, the correlation becomes stronger, resulting in a larger environmental impact coefficient; conversely, when a DC grounding fault may exist, the fault has a greater impact on the insulation resistance, thereby destroying the correlation between the change in insulation resistance and the environmental parameters, and thus making the environmental impact coefficient smaller; and as the DC grounding fault becomes more and more serious, it gradually dominates the impact on the insulation resistance, and the environmental impact can be almost ignored, so the smaller the environmental impact coefficient, the more likely the DC grounding fault exists.

[0072] It should be noted that although the environmental impact coefficient and aging trend coefficient can reflect DC grounding faults to a certain extent, they are only more accurate when the fault is more serious, so they can only be used as an auxiliary adjustment method.

[0073] Step S4: Calculate the expected insulation resistance of each node at each moment based on the changes between adjacent data points in the fitting curve and the insulation resistance of each node at the previous moment; and construct the ground fault coefficient at each moment based on the correlation between the positive and negative pole-to-ground voltages at the same acquisition location, the aging trend coefficient and the environmental impact coefficient of each node, and the difference between the insulation resistance of each node at each moment and the expected insulation resistance.

[0074] Changes in insulation resistance due to aging are normal fluctuations in AC / DC power systems. They only become dangerous to AC / DC power systems after the insulation resistance due to aging has decreased to a certain level. However, in existing insulation resistance testing, the detected insulation resistance is often the result of a combination of aging, environmental factors, and faults. Due to the combined influence of these factors, existing technologies, when detecting DC ground faults, use the insulation resistance due to this combined effect to detect faults. This significantly reduces the sensitivity of DC ground fault detection, especially in the early stages of a fault, and increases the probability of false or missed faults, thereby affecting the safety and stability of the AC / DC power systems. Therefore, it is necessary to consider the effects of aging and environmental factors in the changes in insulation resistance, and to enhance the sensitivity and accuracy of identifying insulation resistance changes due to faults.

[0075] (1) Taking the current node as an example, based on the insulation resistance data actually collected at each node at the previous moment and the aging rate between these two moments, the expected insulation resistance of each node at each moment is calculated. The expression is:

[0076] , where yes The expected insulation resistance of the current node at the moment; yes The actual insulation resistance data collected by the current node at the moment; yes Moment and The aging rate of the insulation resistance between moments, The calculation process is: calculate the fitting curve of each cluster insulation sequence Time data points and The slope of the line connecting the data points at each moment is recorded as the rate of change, and the mean of the rate of change of all cluster isolation sequences is taken as .

[0077] It is understandable that the change trend of the insulation resistance due to aging should be strictly consistent with the change trend of the fitting curve. Therefore, the fitting curve can be used to quantify the aging rate, and at the same time, the actual insulation resistance can be combined to quantify the expected insulation resistance at the next moment.

[0078] (2) The ground fault coefficient at each moment is calculated by combining the expected insulation resistance of all nodes at each moment, the correlation between the positive and negative poles of the main bus and each branch line to the ground, the environmental impact coefficient and the aging trend coefficient. This is used to measure the degree of insulation resistance abnormality caused by the DC ground fault in the AC / DC power supply system. The expression is:

[0079] , where yes The ground fault coefficient at the moment; The mean value of the correlation measure between the positive pole-to-ground voltage series and the negative pole-to-ground voltage series at the same position of the main busbar and all branches; is the number of nodes in the AC / DC power system that perform insulation resistance monitoring; 、 They are The normalized value of the environmental impact coefficient and the normalized value of the aging trend coefficient of each node; For the Nodes in The difference between the actual insulation resistance collected at a certain moment and the expected insulation resistance.

[0080] It should be noted that, for the correlation measurement between the positive pole-to-ground voltage sequence and the negative pole-to-ground voltage sequence at the same position, in the embodiment of the present application, it is specifically the Pearson correlation coefficient between the positive pole-to-ground voltage sequence and the negative pole-to-ground voltage sequence at the same position; the present application only proposes a correlation measurement method, and there are many existing correlation measurement methods. Implementers can also use other correlation measurement algorithms such as Spearman correlation coefficient and cosine similarity to measure the correlation between the positive pole-to-ground voltage sequence and the negative pole-to-ground voltage sequence at the same position. This application does not make specific restrictions.

[0081] It is understandable that when a DC ground fault occurs, the voltage at the ground point will decrease, causing the voltage at the other pole to increase, resulting in a negative correlation between the positive and negative poles in the AC / DC power supply system and the ground voltage. Secondly, due to the influence of the DC ground fault, the insulation resistance exhibits fluctuations that are completely inconsistent with the aging situation, and the corresponding environmental impact coefficient and aging trend coefficient are small, resulting in a corresponding ground fault coefficient that is large.

[0082] Step S5: performing DC grounding fault detection on the AC / DC power supply system based on the grounding fault coefficients at consecutive moments.

[0083] Since DC ground faults are irreversible, when the insulation resistance and positive and negative voltages to ground are abnormal during the monitoring of AC / DC power systems, these abnormalities are also irreversible. Taking the moment monitoring as an example, according to the above method, calculate The ground fault coefficient at the moment; then Time and before The ground fault coefficient at each moment is used as input, and the Otsu threshold segmentation method is used to output the segmentation threshold. The Otsu threshold segmentation is a well-known technology, and the specific process will not be repeated here.

[0084] It should be noted that for the threshold segmentation of the ground fault coefficient, this application only proposes a threshold segmentation method. There are many existing threshold segmentation methods. Implementers can also use threshold segmentation algorithms to perform threshold segmentation of the ground fault coefficient. This application does not make specific restrictions.

[0085] if Not enough before the moment At this moment, according to the previous The ground fault coefficient at the moment is used to obtain the segmentation threshold. Before the moment The reason for the time is to avoid the problem of excessive data volume caused by long-term monitoring. The value of is set to 720, which is the monitoring data within one month. As other embodiments of this application, the implementer can set it according to the actual situation. The value of .

[0086] if The ground fault coefficient at the moment is greater than the segmentation threshold, and After the moment If the ground fault coefficient at the moment is also greater than the segmentation threshold, it means that there is a DC ground fault in the AC / DC power supply system. The value range is [12,48]. Preferably, in the embodiment of this application, The value of is set to 24. As other embodiments of this application, the implementer can set it according to the actual situation. The value of .

[0087] The schematic diagram of the process of obtaining the aging trend coefficient is as follows: Figure 2 shown.

[0088] Based on the same inventive concept as the above method, an embodiment of the present application further provides an AC / DC power system monitoring device, wherein a computer program is stored in the device, and when the computer program is executed by a processor, the steps of any one of the above-mentioned AC / DC power system monitoring methods are implemented.

[0089] Based on the same inventive concept as the above method, an embodiment of the present application also provides an AC / DC power supply system monitoring system, comprising a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, the steps of any one of the above-mentioned AC / DC power supply system monitoring methods are implemented.

[0090] In summary, the embodiment of the present application provides a method for monitoring an AC / DC power supply system. First, the environmental impact coefficient and the aging trend coefficient are calculated based on the change in insulation resistance and the relationship between the change in insulation resistance and the environmental factors. These two indicators improve the accuracy of quantifying the relationship between the change in insulation resistance of the AC / DC power supply system and the influence of environmental factors and aging, which helps to improve the accuracy of subsequent DC ground fault identification and correction. Then, the ground fault coefficient is calculated in combination with the positive and negative ground voltages. The DC ground fault detection is corrected according to the influence of environmental and aging factors on the insulation resistance, which enhances the sensitivity and accuracy of DC ground fault diagnosis using the ground fault coefficient and reduces the probability of misjudgment and missed judgment. Through this method, the influence of aging and environmental factors is first quantified, and the quantified results are used to correct the DC ground fault detection, thereby reducing the influence of aging and environmental factors as much as possible, thereby enhancing the accuracy of DC ground fault diagnosis, improving the monitoring quality of the AC / DC power supply system, and helping to ensure the safe and stable operation of the AC / DC power supply system.

[0091] It should be noted that the order in which the embodiments of the present application are presented is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. Furthermore, the above descriptions are of specific embodiments of the present application. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the specific order or sequential sequence shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0092] The various embodiments in this application are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

[0093] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A method for monitoring an AC / DC power supply system, characterized in that: The method comprises the following steps: Collect monitoring data of the AC and DC power systems at all times, including the insulation resistance of the main bus, branches, and key equipment, the positive and negative ground voltages of the main bus and branches, and ambient temperature and humidity. The main bus, branches, and key equipment are considered nodes. The acquisition time is clustered by temperature and humidity at all times, and an insulation series of each cluster is constructed for each node based on the insulation resistance of each node at the corresponding time in each cluster. A fitting curve for each cluster insulation series is obtained. Based on the data change trend and data mutation characteristics in all cluster insulation series of each node, as well as the differences between all corresponding fitting curves, an aging trend coefficient for the insulation resistance data change of each node is constructed. Calculating the correlation between the insulation resistance of each node in the same time period and the temperature and humidity, respectively; calculating the aging degree metric of each node in each time period based on the function values ​​of all the fitting curves of each node at the same time; constructing the environmental impact coefficient of the insulation resistance data change of each node based on the difference in the correlation and the difference in the aging degree metric of each node in adjacent time periods; Based on the changes between the data points at adjacent moments in the fitting curve and in combination with the insulation resistance of each node at the previous moment, the expected insulation resistance of each node at each moment is calculated; based on the correlation between the positive and negative pole-to-ground voltages at the same acquisition location, the aging trend coefficient and the environmental impact coefficient of each node, and the difference between the insulation resistance of each node at each moment and the expected insulation resistance, the ground fault coefficient at each moment is constructed; DC ground fault detection in AC / DC power systems is performed based on the ground fault coefficient at consecutive moments.

2. The AC / DC power system monitoring method according to claim 1, wherein: The process of obtaining the aging trend coefficient of the insulation resistance data change of each node is as follows: Calculate the mean of the integrated area difference of the fitting curves of the pairwise combinations of all cluster insulation sequences of each node, and record it as the first area mean; Calculate the proportion of positive numbers in the first-order difference sequence of each cluster insulation sequence of each node; Calculate the ratio of the goodness of fit of the fitting curve function of each cluster insulation sequence of each node to the proportion of positive numbers, and record it as the first ratio; The ratio of the sum of the first ratios of all cluster insulation sequences of each node to the first area mean is used as the aging trend coefficient of the insulation resistance data change of each node.

3. The AC / DC power system monitoring method according to claim 1, wherein: The process of obtaining the aging degree measurement of each node in each time period is as follows: Calculate the sum of the function values ​​at any same time in the fitting curve functions of all cluster isolation sequences of each node, and record it as the first sum value at any same time of each node; The average of the first sum values ​​of each node at all moments in each time period is used as the aging degree measurement of each node in each time period.

4. The AC / DC power system monitoring method according to claim 1, wherein: The process of obtaining the environmental impact coefficient of the insulation resistance data change of each node is as follows: Based on the correlation between the insulation resistance data of each node and the temperature and humidity data, respectively, the correlation between the insulation resistance data of each node and the environmental parameter data in each time period is calculated, and recorded as resistance-environment correlation; Calculate the resistance environment correlation difference between each node in the i+1th time period and the ith time period; Calculate the sign function value of the difference between the aging degree measurement of each node in the i+1th time period and the ith time period; An average value of the ratio of the resistance environment correlation difference value to the sign function value of each node in all time periods is used as the environmental impact coefficient of the insulation resistance data change of each node.

5. The AC / DC power system monitoring method according to claim 4, wherein: The process of obtaining the resistance environment correlation is as follows: The correlation measures between the time series of the insulation resistance of each node in the i-th time period and the time series of the temperature and humidity in the i-th time period are calculated respectively, and recorded as the first correlation and the second correlation respectively. The average of the first correlation and the second correlation is taken as the resistance environment correlation of each node in the i-th time period.

6. The AC / DC power system monitoring method according to claim 1, wherein: The expression of the expected insulation resistance is: , where yes The expected insulation resistance of the current node at the moment; yes The actual insulation resistance data collected by the current node at the moment; yes Moment and The aging rate of the insulation resistance between moments, The calculation process is: calculate the fitting curve of each cluster insulation sequence Time data points and The slope of the line connecting the data points at the moment is recorded as the rate of change, and the mean of the rate of change of all cluster isolation sequences of the current node is taken as .

7. The AC / DC power system monitoring method according to claim 1, wherein: The expression of the ground fault coefficient at each moment is: , where yes The ground fault coefficient at the moment; The mean value of the correlation measure between the positive pole-to-ground voltage time series and the negative pole-to-ground voltage time series at the same position of the main busbar and all branches; is the number of nodes in the AC / DC power system that perform insulation resistance monitoring; 、 They are The normalized value of the environmental impact coefficient and the normalized value of the aging trend coefficient of each node; For the Nodes in The difference between the actual insulation resistance collected at a certain moment and the expected insulation resistance.

8. The AC / DC power system monitoring method according to claim 1, wherein: The DC grounding fault detection of the AC / DC power supply system based on the grounding fault coefficient at consecutive moments is specifically as follows: The ground fault coefficient at any moment and a preset number of moments before it is divided by threshold value; If the grounding fault coefficient at any moment is greater than the segmentation threshold, and the grounding fault coefficients at a preset number of moments after the any moment are also greater than the segmentation threshold, it is determined that a DC grounding fault exists in the AC / DC power supply system.

9. A device for monitoring an AC / DC power supply system, wherein a computer program is stored in the device, characterized in that: When the computer program is executed by a processor, the steps of the AC / DC power system monitoring method according to any one of claims 1 to 8 are implemented.

10. An AC / DC power system monitoring system, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the steps of the AC / DC power system monitoring method according to any one of claims 1 to 8 are implemented.

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