An intelligent monitoring method and system based on power supply and distribution system

Abstract

The present application relates to an intelligent monitoring method and system based on a power supply and distribution system, and to the field of power grid monitoring technology. The method includes obtaining detection power parameters; establishing a detection interval and determining interval change parameters; determining interval change combinations based on all interval change parameters; establishing a historical interval, and randomly defining a comparison interval with a width of the detection duration in the historical interval, and determining a comparison change combination in each comparison interval; determining a combination similarity value based on the interval change combination and the comparison change combination, and determining the combination similarity value with the largest value based on a sorting rule, and defining the comparison interval corresponding to the combination similarity value as a similar interval; establishing a prediction interval based on the similar interval, and defining the detection power parameters in the prediction interval as predicted power parameters; and outputting an aging warning signal when there is a situation where the predicted power parameter is greater than the preset warning power parameter. The present application has the effect of improving the overall operation effect of the power supply and distribution system.

Description

Technical Field

[0001] The present application relates to the field of power grid monitoring technology, and in particular to an intelligent monitoring method and system based on a power supply and distribution system. Background Art

[0002] The power supply and distribution system is a system for supplying and distributing electric energy. Its main function is to obtain electric energy from the power grid and transmit it to various types of power loads safely, reliably, economically and with high quality through reasonable line and equipment configuration to meet the power needs of different users. Among them, the distribution cabinet is an important part of the power supply and distribution system, which mainly plays the role of distributing electric energy, controlling circuit on and off, and protecting circuits.

[0003] In the related art, when the power distribution cabinet is used, the circuit will be affected by the current because the current is constantly passing through it. The circuit will age after a period of use. Once the circuit is aged seriously, the transmitted current will change, resulting in abnormal power transmission. Therefore, in order to better monitor the aging of the circuit inside the power distribution cabinet, a sensor for detecting power data will be installed inside the power distribution cabinet to determine whether the circuit is aged by analyzing the power data.

[0004] In the above-mentioned related technologies, when aging of the circuit is detected, it takes a certain amount of time for the staff to repair the circuit, which will cause the distribution cabinet to have a certain period of poor operating performance, resulting in poor overall operating performance of the power supply and distribution system. There is still room for improvement. Summary of the invention

[0005] In order to improve the overall operation effect of a power supply and distribution system, the present application provides an intelligent monitoring method and system based on a power supply and distribution system.

[0006] In a first aspect, the present application provides an intelligent monitoring method based on a power supply and distribution system, which adopts the following technical solution:

[0007] An intelligent monitoring method based on a power supply and distribution system, comprising:

[0008] Obtaining detection power parameters of distribution nodes;

[0009] When the detected power parameter is greater than the preset demand analysis parameter, the preset demand maintenance time is controlled to count down, wherein when the detected power parameter is not greater than the demand analysis parameter, the demand maintenance time is reset;

[0010] When the required maintenance timer returns to zero, a detection interval with the current time point as the rear end point and a width of the preset detection time length is established on the preset time axis;

[0011] In the detection interval, performing difference calculation according to adjacent detection power parameters to determine the interval change parameter, and combining all the interval change parameters to determine the interval change combination;

[0012] A historical interval with a width of a preset historical duration is established on the time axis with the current time point as the rear end point, and a comparison interval with a width of the detection duration is randomly defined in the historical interval, and a comparison change combination is determined in each comparison interval;

[0013] Analyze the interval change combination and the comparison change combination to determine the combination similarity value, and determine the combination similarity value with the largest value according to the preset sorting rules, and define the comparison interval corresponding to the combination similarity value as the similar interval;

[0014] A prediction interval having a width equal to a preset prediction time length is established with the rear end point of the similar interval as the front end point, and the detected power parameter in the prediction interval is defined as the predicted power parameter;

[0015] When the predicted power parameter is greater than the preset warning power parameter, an aging warning signal is output.

[0016] Optionally, after the combined similarity value is determined, the intelligent monitoring method based on the power supply and distribution system further includes:

[0017] Determine whether there are at least two comparison intervals with the same and largest combined similarity values;

[0018] If there are not at least two comparison intervals with the same and largest combined similarity values, the comparison interval corresponding to the largest combined similarity value is determined as the similar interval;

[0019] If there are at least two comparison intervals with the same and largest combined similarity values, the comparison interval corresponding to the largest combined similarity value is determined as the candidate interval;

[0020] Determine whether the predicted intervals determined by the candidate intervals all have a situation where the predicted power parameter is greater than the warning power parameter;

[0021] If the predicted power parameters in all the prediction intervals determined by the candidate intervals are greater than the warning power parameters, an aging warning signal is output;

[0022] If the predicted intervals determined by the candidate intervals do not all have the situation where the predicted power parameter is greater than the warning power parameter, the candidate intervals where the predicted power parameter is greater than the warning power parameter are defined as valid intervals, and the remaining candidate intervals are defined as invalid intervals;

[0023] Counting is performed according to a valid interval to determine a valid quantity, and counting is performed according to an invalid interval to determine an invalid quantity;

[0024] When the valid number is greater than the invalid number, an aging warning signal is output.

[0025] Optionally, after the valid quantity and the invalid quantity are determined, the intelligent monitoring method based on the power supply and distribution system further includes:

[0026] When the valid quantity is not greater than the invalid quantity, the difference between the invalid quantity and the valid quantity is calculated to determine the deviation quantity, and the deviation ratio is calculated based on the deviation quantity, the invalid quantity and the valid quantity;

[0027] Determine whether the deviation ratio is greater than the preset benchmark demand ratio;

[0028] If the deviation ratio is greater than the benchmark demand ratio, a normal operation signal is output;

[0029] If the deviation ratio is not greater than the benchmark demand ratio, the detection time is shortened according to the preset unit time, and the detection interval and comparison interval are constructed according to the new detection time until a normal operation signal or an aging warning signal is output.

[0030] Optionally, if the deviation ratio is not greater than the benchmark demand ratio, the intelligent monitoring method based on the power supply and distribution system further includes:

[0031] Determine whether the current detection duration is less than the preset lower limit required duration;

[0032] If the current detection duration is not less than the lower limit required duration, the current detection duration is updated according to the unit duration;

[0033] If the current detection duration is less than the lower limit required duration, the adjacent nodes of the current distribution node are determined according to the preset power supply and distribution topology;

[0034] Determine adjacent change combinations according to adjacent nodes in the detection interval, and determine adjacent candidate combinations according to adjacent nodes in each candidate interval;

[0035] Adjacent similarity values ​​are determined according to adjacent variation combinations and adjacent candidate combinations, and adjacent similarity values ​​with the largest values ​​are determined according to sorting rules, and candidate intervals corresponding to the adjacent similarity values ​​are determined as similar intervals.

[0036] Optionally, after the combined similarity value is determined, the intelligent monitoring method based on the power supply and distribution system further includes:

[0037] Determine whether the maximum combined similarity value is greater than the preset benchmark requirement value;

[0038] If the maximum combined similarity value is greater than the benchmark demand value, a similar interval or alternative interval is determined;

[0039] If the maximum combination similarity value is not greater than the reference demand value, the interval change parameter in the interval change combination that belongs to the demand maintenance duration is defined as the most recent change parameter, and the mean change parameter is determined by calculation based on each most recent change parameter;

[0040] Perform difference calculation based on the early warning power parameters and the current detection power parameters to determine the demand increase parameters;

[0041] The demand increase times are determined by calculation based on the demand increase parameter and the mean change parameter, and an aging warning signal is output when the demand increase times are less than a preset benchmark warning times.

[0042] Optionally, after the demand increase parameter is determined, the intelligent monitoring method based on the power supply and distribution system further includes:

[0043] On the time axis, a high point maintenance interval with a width equal to the required maintenance time is established with the current time point as the rear end point, and the detection gas parameters are obtained at each time point in the high point maintenance interval;

[0044] Performing mean calculation based on each detected gas parameter to determine a mean gas parameter;

[0045] The compensation increase parameter corresponding to the mean gas parameter is determined according to the preset compensation matching relationship, and the demand increase parameter is corrected according to the compensation increase parameter.

[0046] In a second aspect, the present application provides an intelligent monitoring system based on a power supply and distribution system, which adopts the following technical solutions:

[0047] An intelligent monitoring system based on a power supply and distribution system, comprising:

[0048] An acquisition module, used to acquire detection power parameters of a power distribution node;

[0049] A processing module, connected to the acquisition module and the judgment module, for storing and processing information;

[0050] A judgment module, connected with the acquisition module and the processing module, for judging the information;

[0051] When the judging module judges that the detected power parameter is greater than the preset demand analysis parameter, the processing module controls the preset demand maintenance time to count down, wherein, when the detected power parameter is not greater than the demand analysis parameter, the demand maintenance time is reset;

[0052] When the required maintenance timer returns to zero, the processing module establishes a detection interval with the current time point as the rear end point and a width of the preset detection time on the preset time axis;

[0053] The processing module performs difference calculation according to adjacent detection power parameters in the detection interval to determine the interval change parameter, and combines all the interval change parameters to determine the interval change combination;

[0054] The processing module establishes a historical interval with a width of a preset historical duration on the time axis with the current time point as the rear end point, and randomly defines a comparison interval with a width of the detection duration in the historical interval, and determines a comparison change combination in each comparison interval;

[0055] The processing module analyzes the interval change combination and the comparison change combination to determine the combination similarity value, and determines the combination similarity value with the largest value according to the preset sorting rule, and defines the comparison interval corresponding to the combination similarity value as the similar interval;

[0056] The processing module establishes a prediction interval with a width of a preset prediction time length using the rear end point of the similar interval as the front end point, and defines the detected power parameter in the prediction interval as the predicted power parameter;

[0057] When the judging module judges that the predicted power parameter is greater than the preset warning power parameter, the processing module outputs an aging warning signal.

[0058] In a third aspect, the present application provides a computer storage medium capable of storing corresponding programs, which has the characteristics of improving the overall operation effect of the power supply and distribution system, and adopts the following technical solutions:

[0059] A computer-readable storage medium stores a computer program that can be loaded by a processor and execute any of the above-mentioned intelligent monitoring methods based on a power supply and distribution system.

[0060] In summary, the present application includes at least one of the following beneficial technical effects:

[0061] When performing daily monitoring of the power distribution cabinet, the changes in power data can be analyzed to predict the subsequent power data, so that early warning can be given before the circuit ages and causes abnormal operation of the power distribution cabinet, so that the staff can know the situation in advance and take corresponding countermeasures, thereby improving the overall operation effect of the power supply and distribution system;

[0062] When analyzing the power parameters of the distribution cabinet, the distribution cabinet conditions of adjacent nodes are analyzed to determine the data with reference significance, thereby improving the accuracy of data analysis;

[0063] Combined with the analysis of the gas conditions in the distribution cabinet, it is possible to further determine whether the internal circuit of the distribution cabinet is aging. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 It is a flow chart of an intelligent monitoring method based on a power supply and distribution system.

[0065] Figure 2 It is a module flow chart of an intelligent monitoring method based on a power supply and distribution system. DETAILED DESCRIPTION

[0066] In order to make the purpose, technical solutions and advantages of this application more clear, the following Figure 1-Figure 2 It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0067] The embodiments of the present application are further described in detail below in conjunction with the drawings in the specification.

[0068] The present application embodiment discloses an intelligent monitoring method based on a power supply and distribution system, referring to Figure 1 The method flow of the intelligent monitoring method based on the power supply and distribution system includes the following steps:

[0069] Step S100: Acquire detection power parameters of a power distribution node.

[0070] The power distribution node is the power distribution cabinet, and the power parameters detected are the parameters in the power distribution cabinet that can reflect whether the circuit transmission of the power distribution cabinet is abnormal, including current parameters, voltage parameters, etc.

[0071] Step S101: when the detected power parameter is greater than the preset demand analysis parameter, the preset demand maintenance time is controlled to count down, wherein when the detected power parameter is not greater than the demand analysis parameter, the demand maintenance time is reset.

[0072] The demand analysis parameter is the minimum detection power parameter set by the staff to determine that the current detection power parameter is too large and there may be abnormal conditions such as circuit aging. The demand maintenance time is a fixed time set by the staff. The countdown of the demand maintenance time is controlled to determine the time when the detection power parameter is greater than the demand analysis parameter, thereby eliminating abnormal conditions caused by some power fluctuations and facilitating a more accurate analysis of circuit aging.

[0073] Step S102: When the required maintenance timer returns to zero, a detection interval with the current time point as the rear end point and a width of the preset detection time length is established on the preset time axis.

[0074] The time axis is a coordinate axis formed by the combination of various time points, and the coordinate axis points from the time points that have passed to the time points that have not yet arrived, wherein the time points that have passed are on the left side of the coordinate axis and the left side of the designated coordinate axis is the front; the detection duration is a fixed duration set by the staff, and the fixed duration is greater than the demand maintenance duration. Under normal circumstances, the detection duration is 10 times the demand maintenance duration; by establishing a detection interval, the detection power parameters within the detection duration can be obtained and analyzed.

[0075] Step S103: performing difference calculation according to adjacent detection power parameters in the detection interval to determine an interval variation parameter, and combining all the interval variation parameters to determine an interval variation combination.

[0076] The interval change parameter is the difference between the detection power parameters obtained at adjacent time points in the detection interval, and the difference is determined by subtracting the detection power parameter at the previous time point from the detection power parameter at the next time point; the interval change combination is a combination obtained by combining the interval change parameters according to the chronological order.

[0077] Step S104: Establish a historical interval with a width of a preset historical duration on the time axis with the current time point as the rear end point, randomly define a comparison interval with a width of the detection duration in the historical interval, and determine a comparison change combination in each comparison interval.

[0078] The historical duration is the duration set by the staff to obtain data from the historical use of each distribution cabinet, for example 3 years. By establishing a historical interval, it is convenient to obtain and analyze the data within the historical duration; by determining the comparison interval, it is convenient to compare with the detection interval. The method for determining the comparison change combination is the same as the interval change combination, which will not be repeated here.

[0079] Step S105: Analyze the interval change combination and the comparison change combination to determine the combination similarity value, determine the combination similarity value with the largest value according to the preset sorting rule, and define the comparison interval corresponding to the combination similarity value as the similar interval.

[0080] The combination similarity value is a value that reflects the similarity between the interval change combination and the comparison change combination. The larger the value, the more similar the two combinations are. In other words, the more similar the power usage of the distribution cabinet is in different time intervals, the more reference value it has. The calculation formula of the combination similarity value is: ,in is the combined similarity value, is the interval change combination from front to back interval variation parameters, To compare the first to the last in the change combination interval variation parameters, is the total number of interval change parameters in the interval change combination; the sorting rule is a method set by the staff to sort the values. The sorting rule can be used to determine the combination similarity value with the largest value, that is, the corresponding comparison interval is similar to the current detection interval. At this time, it is defined as a similar interval to distinguish different comparison intervals, which is convenient for subsequent analysis.

[0081] Step S106: establishing a prediction interval with a width of a preset prediction time length with the rear end point of the similar interval as the front end point, and defining the detected power parameters in the prediction interval as predicted power parameters.

[0082] The prediction duration is the duration set by the staff to predict the power data of the distribution cabinet for a subsequent period of time. By constructing a prediction interval, data on the subsequent power conditions in a similar interval can be obtained to facilitate subsequent analysis; prediction power parameters are defined to distinguish different detection power parameters for subsequent analysis.

[0083] Step S107: outputting an aging warning signal when the predicted power parameter is greater than the preset warning power parameter.

[0084] The early warning power parameter is the minimum predicted power parameter set by the staff to determine that there is circuit aging and other conditions inside the distribution cabinet. When the predicted power parameter is greater than the early warning power parameter, it means that the corresponding distribution cabinet in the prediction interval has circuit aging and other conditions, and the current detection interval is similar to the power data in the similar interval, that is, there is a high possibility that circuit aging will occur in the future to affect the power parameters. At this time, an aging warning signal is output so that the staff can be informed of the situation in time, so that they can intervene in advance to reduce the situation where the staff can only intervene after the circuit data is completely abnormal, thereby improving the overall operation effect of the power supply and distribution system.

[0085] After the combined similarity value is determined, the intelligent monitoring method based on the power supply and distribution system also includes:

[0086] Step S200: Determine whether there are at least two comparison intervals with the same and maximum combined similarity values.

[0087] The purpose of the judgment is to find out whether there are multiple relatively similar comparison intervals to facilitate subsequent analysis.

[0088] Step S2001: If there are not at least two comparison intervals with the same and largest combined similarity values, the comparison interval corresponding to the largest combined similarity value is determined as the similar interval.

[0089] When there are not at least two comparison intervals with the same and largest combined similarity values, it means that there is only one comparison interval that meets the requirements, and it can be determined as a similar interval.

[0090] Step S2002: If there are at least two comparison intervals with the same and largest combined similarity values, the comparison interval corresponding to the largest combined similarity value is determined as a candidate interval.

[0091] When there are at least two comparison intervals with the same and largest combined similarity values, it means that there are multiple similar comparison intervals. At this time, they are defined as candidate intervals to distinguish different comparison intervals, which is convenient for subsequent screening of comparison intervals that meet the requirements.

[0092] Step S201: determining whether the predicted intervals determined by the candidate intervals all have a situation where the predicted power parameter is greater than the warning power parameter.

[0093] The purpose of the judgment is to find out whether circuit aging is detected under the current power parameter changes.

[0094] Step S2011: If the predicted intervals determined by the candidate intervals all have the situation where the predicted power parameters are greater than the warning power parameters, an aging warning signal is output.

[0095] When the predicted power parameters in the prediction intervals determined by the candidate intervals are all greater than the warning power parameters, it means that the circuits are aging. In this case, an aging warning signal can be directly output.

[0096] Step S2012: If the predicted intervals determined by the candidate intervals do not all have the situation where the predicted power parameter is greater than the warning power parameter, the candidate intervals where the predicted power parameter is greater than the warning power parameter are defined as valid intervals, and the remaining candidate intervals are defined as invalid intervals.

[0097] When the predicted intervals determined by the alternative intervals do not all have the situation where the predicted power parameters are greater than the warning power parameters, it means that circuit aging exists in some cases, but not in some cases, so further analysis is needed; valid intervals and invalid intervals are defined to distinguish different situations for subsequent analysis.

[0098] Step S202: Counting is performed according to the valid interval to determine the valid number, and counting is performed according to the invalid interval to determine the invalid number.

[0099] The valid number is the total number of valid intervals, and the invalid number is the total number of invalid intervals.

[0100] Step S203: outputting an aging warning signal when the valid number is greater than the invalid number.

[0101] When the valid number is greater than the invalid number, it means that in most cases the current power data indicates circuit aging. In this case, the aging warning signal can be output normally.

[0102] After the effective quantity and the invalid quantity are determined, the intelligent monitoring method based on the power supply and distribution system also includes:

[0103] Step S300: When the valid number is not greater than the invalid number, a difference calculation is performed based on the invalid number and the valid number to determine the deviation number, and a calculation is performed based on the deviation number, the invalid number and the valid number to determine the deviation ratio.

[0104] When the valid number is not greater than the invalid number, it means that the circuit aging situation does not occur in the vast majority of cases, and further analysis is needed; the deviation number is the value obtained by subtracting the valid number from the invalid number, and the deviation proportion is the ratio of the deviation number to the corresponding situations of all alternative intervals, that is, the deviation number divided by the sum of the invalid number and the valid number.

[0105] Step S301: Determine whether the deviation ratio is greater than a preset reference demand ratio.

[0106] The benchmark demand ratio is the minimum deviation ratio set by the staff to determine that in most cases there is no circuit aging. The purpose of the judgment is to find out whether there is circuit aging under the current power data.

[0107] Step S3011: If the deviation ratio is greater than the reference requirement ratio, a normal operation signal is output.

[0108] When the deviation ratio is greater than the baseline demand ratio, it means that circuit aging will basically not occur under the current power data. At this time, a normal operation signal can be output to record the situation.

[0109] Step S3012: If the deviation ratio is not greater than the benchmark demand ratio, the detection time is shortened according to the preset unit time, and a detection interval and a comparison interval are constructed according to the new detection time until a normal operation signal or an aging warning signal is output.

[0110] When the deviation ratio is not greater than the benchmark demand ratio, it means that it is impossible to effectively distinguish whether the circuit will age. Therefore, the detection time is updated by subtracting the unit time from the original detection time, thereby realizing the update of the detection interval and the comparison interval, so as to be able to re-analyze similar situations; among which, the unit time is a fixed time set by the staff that is much smaller than the detection time.

[0111] If the deviation ratio is not greater than the benchmark demand ratio, the intelligent monitoring method based on the power supply and distribution system also includes:

[0112] Step S400: Determine whether the current detection duration is less than a preset lower limit required duration.

[0113] The lower limit required time is the minimum detection time required for a comparison interval with good reference significance in historical situations. The purpose of the judgment is to find out whether the detection time can be further shortened.

[0114] Step S4001: If the current detection duration is not less than the lower limit required duration, the current detection duration is updated according to the unit duration.

[0115] When the current detection time is not less than the lower limit required time, it means that the detection time can be shortened. At this time, the detection time can be updated normally using the unit time.

[0116] Step S4002: If the current detection duration is less than the lower limit required duration, the adjacent nodes of the current power distribution node are determined according to a preset power supply and distribution topology.

[0117] When the current detection time is less than the lower limit required time, it means that it is impossible to determine a reference value by shortening the detection time, and further analysis is needed; the power supply and distribution topology structure is the connection distribution structure of each distribution cabinet, and the adjacent nodes are the remaining distribution cabinet nodes that are connected to the current distribution node for direct current transmission.

[0118] Step S401: Determine adjacent variation combinations according to adjacent nodes in a detection interval, and determine adjacent candidate combinations according to adjacent nodes in each candidate interval.

[0119] The adjacent change combination is a combination of interval change parameters of adjacent nodes in the detection interval, and the adjacent candidate combination is a combination of interval change parameters of adjacent nodes in the candidate interval. The method for determining the combination is the same as the interval change combination, which will not be repeated here.

[0120] Step S402: Determine adjacent similarity values ​​according to adjacent variation combinations and adjacent candidate combinations, determine the adjacent similarity value with the largest value according to a sorting rule, and determine the candidate interval corresponding to the adjacent similarity value as a similar interval.

[0121] The adjacent similarity value is the combined similarity value between adjacent change combinations and adjacent alternative combinations. The determination method is the same as the combined similarity value and will not be repeated here. The adjacent similarity value with the largest value can be determined through the sorting rule, that is, the power data of adjacent nodes in the alternative interval corresponding to the adjacent similarity value is the most similar. At this time, the alternative interval can be used to analyze the power parameters of the current distribution node, so it can be determined as a similar interval.

[0122] After the combined similarity value is determined, the intelligent monitoring method based on the power supply and distribution system also includes:

[0123] Step S500: Determine whether the maximum combined similarity value is greater than a preset reference requirement value.

[0124] The benchmark requirement value is the minimum combined similarity value set by the staff to determine whether two intervals are relatively similar. The purpose of the judgment is to find out whether the closest comparison interval currently determined can be used as a reference for the current situation.

[0125] Step S5001: If the maximum combined similarity value is greater than the reference requirement value, a similar interval or an alternative interval is determined.

[0126] When the maximum combined similarity value is greater than the benchmark demand value, it means that the currently determined comparison interval has a good reference significance, and the analysis can be carried out normally.

[0127] Step S5002: If the maximum combined similarity value is not greater than the reference demand value, the interval change parameters in the interval change combination that belong to the demand maintenance duration are defined as recent change parameters, and the mean change parameter is determined by calculation based on each recent change parameter.

[0128] When the maximum combined similarity value is not greater than the benchmark demand value, it means that there is no comparison interval with reference significance and further analysis is needed. The most recent change parameter is defined to distinguish the interval change parameters of the distribution node within the demand maintenance time, which is convenient for subsequent analysis. The mean change parameter is the average value of all the most recent change parameters, that is, the change parameter value that will appear per unit time under the current circumstances.

[0129] Step S501: performing difference calculation based on the warning power parameter and the current detection power parameter to determine the demand increase parameter.

[0130] The demand increase parameter is the parameter value that needs to be increased from the current detection power parameter to the power parameter that needs to trigger the early warning signal, and is determined by subtracting the current detection power parameter from the early warning power parameter.

[0131] Step S502: Calculate the demand increase times according to the demand increase parameter and the mean change parameter, and output an aging warning signal when the demand increase times are less than a preset benchmark warning times.

[0132] The number of demand increases is the number of changes required when an early warning is theoretically required based on the current power changes. It is determined by dividing the demand increase parameter by the mean change parameter and rounding up. The benchmark early warning number is the maximum number of demand increases set by the staff to determine that circuit aging will occur in a short period of time. When the number of demand increases is less than the benchmark early warning number, it means that circuit aging will basically occur in the subsequent period. At this time, the aging early warning signal can be output normally to mark the situation.

[0133] After the demand increase parameters are determined, the intelligent monitoring method based on the power supply and distribution system also includes:

[0134] Step S600: establishing a high point maintenance interval with a width equal to the required maintenance time on the time axis with the current time point as the rear end point, and obtaining the detection gas parameters at each time point in the high point maintenance interval.

[0135] A high point maintenance interval is established to facilitate the acquisition and analysis of data within the demand maintenance time. The detected gas parameters are the gas parameters detected by the gas sensor installed at the ventilation port inside the distribution cabinet at each time point in the high point maintenance interval. The gas includes ozone, nitrogen oxides and other gases generated by circuit aging.

[0136] Step S601: performing mean calculation according to each detected gas parameter to determine the mean gas parameter.

[0137] The mean gas parameter is the average value of all detected gas parameters.

[0138] Step S602: Determine a compensation increase parameter corresponding to the mean gas parameter according to a preset compensation matching relationship, and modify the demand increase parameter according to the compensation increase parameter.

[0139] The compensation increase parameter is a correction parameter for the demand increase parameter. Different mean gas parameters indicate different possibilities of current circuit aging. When the mean gas parameter is larger, the possibility and degree of circuit aging are greater, and the compensation increase parameter is also larger. The compensation matching relationship between the two is determined by the staff through multiple tests in advance. It is only necessary to ensure that the mean gas parameter and the compensation increase parameter are in direct proportion. The demand increase parameter can be corrected by subtracting the compensation increase parameter from the demand increase parameter, which is convenient for analyzing and determining the actual aging of the circuit.

[0140] Reference Figure 2Based on the same inventive concept, an embodiment of the present invention provides an intelligent monitoring system based on a power supply and distribution system, comprising:

[0141] An acquisition module, used to acquire detection power parameters of a power distribution node;

[0142] A processing module, connected to the acquisition module and the judgment module, for storing and processing information;

[0143] A judgment module, connected with the acquisition module and the processing module, for judging the information;

[0144] When the judging module judges that the detected power parameter is greater than the preset demand analysis parameter, the processing module controls the preset demand maintenance time to count down, wherein, when the detected power parameter is not greater than the demand analysis parameter, the demand maintenance time is reset;

[0145] When the required maintenance timer returns to zero, the processing module establishes a detection interval with the current time point as the rear end point and a width of the preset detection time on the preset time axis;

[0146] The processing module performs difference calculation according to adjacent detection power parameters in the detection interval to determine the interval change parameter, and combines all the interval change parameters to determine the interval change combination;

[0147] The processing module establishes a historical interval with a width of a preset historical duration on the time axis with the current time point as the rear end point, and randomly defines a comparison interval with a width of the detection duration in the historical interval, and determines a comparison change combination in each comparison interval;

[0148] The processing module analyzes the interval change combination and the comparison change combination to determine the combination similarity value, and determines the combination similarity value with the largest value according to the preset sorting rule, and defines the comparison interval corresponding to the combination similarity value as the similar interval;

[0149] The processing module establishes a prediction interval with a width of a preset prediction time length using the rear end point of the similar interval as the front end point, and defines the detected power parameter in the prediction interval as the predicted power parameter;

[0150] When the judging module judges that the predicted power parameter is greater than the preset warning power parameter, the processing module outputs an aging warning signal;

[0151] A comparison interval screening module is used to screen multiple comparison intervals that meet the combination similarity;

[0152] A detection time adjustment module is used to adjust the detection time;

[0153] An adjacent node analysis module is used to analyze adjacent nodes so as to select and process candidate intervals;

[0154] The change trend analysis module analyzes and processes the change trend of power data in the absence of reference data;

[0155] The demand increase parameter correction module is used to correct the demand increase parameters.

[0156] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device and unit described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0157] An embodiment of the present invention provides a computer-readable storage medium storing a computer program that can be loaded by a processor and executed based on an intelligent monitoring method for a power supply and distribution system.

[0158] Computer storage media include, for example, various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks or optical disks.

Claims

1. An intelligent monitoring method based on a power supply and distribution system, characterized in that: include: Obtaining detection power parameters of the power distribution node; When the detected power parameter is greater than the preset demand analysis parameter, the preset demand maintenance time is controlled to count down, wherein when the detected power parameter is not greater than the demand analysis parameter, the demand maintenance time is reset; When the required maintenance timer returns to zero, a detection interval with the current time point as the rear end point and a width of the preset detection time length is established on the preset time axis; In the detection interval, performing difference calculation according to adjacent detection power parameters to determine the interval change parameter, and combining all the interval change parameters to determine the interval change combination; A historical interval with a width of a preset historical duration is established on the time axis with the current time point as the rear end point, and a comparison interval with a width of the detection duration is randomly defined in the historical interval, and a comparison change combination is determined in each comparison interval; Analyze the interval change combination and the comparison change combination to determine the combination similarity value, and determine the combination similarity value with the largest value according to the preset sorting rules, and define the comparison interval corresponding to the combination similarity value as the similar interval; A prediction interval having a width equal to a preset prediction time length is established with the rear end point of the similar interval as the front end point, and the detected power parameter in the prediction interval is defined as the predicted power parameter; Outputting an aging warning signal when the predicted power parameter is greater than the preset warning power parameter; After the combined similarity value is determined, the intelligent monitoring method based on the power supply and distribution system also includes: Determine whether there are at least two comparison intervals with the same and largest combined similarity values; If there are not at least two comparison intervals with the same and largest combined similarity values, the comparison interval corresponding to the largest combined similarity value is determined as the similar interval; If there are at least two comparison intervals with the same and largest combined similarity values, the comparison interval corresponding to the largest combined similarity value is determined as the candidate interval; Determine whether the predicted intervals determined by the candidate intervals all have a situation where the predicted power parameter is greater than the warning power parameter; If the predicted power parameters in all the prediction intervals determined by the candidate intervals are greater than the warning power parameters, an aging warning signal is output; If the predicted intervals determined by the candidate intervals do not all have the situation where the predicted power parameter is greater than the warning power parameter, the candidate intervals where the predicted power parameter is greater than the warning power parameter are defined as valid intervals, and the remaining candidate intervals are defined as invalid intervals; Counting is performed according to a valid interval to determine a valid quantity, and counting is performed according to an invalid interval to determine an invalid quantity; When the valid number is greater than the invalid number, an aging warning signal is output.

2. The intelligent monitoring method based on the power supply and distribution system according to claim 1 is characterized in that: After the effective quantity and the invalid quantity are determined, the intelligent monitoring method based on the power supply and distribution system also includes: When the valid quantity is not greater than the invalid quantity, the difference between the invalid quantity and the valid quantity is calculated to determine the deviation quantity, and the deviation ratio is calculated based on the deviation quantity, the invalid quantity and the valid quantity; Determine whether the deviation ratio is greater than the preset benchmark demand ratio; If the deviation ratio is greater than the benchmark demand ratio, a normal operation signal is output; If the deviation ratio is not greater than the benchmark demand ratio, the detection time is shortened according to the preset unit time, and the detection interval and comparison interval are constructed according to the new detection time until a normal operation signal or an aging warning signal is output.

3. The intelligent monitoring method based on the power supply and distribution system according to claim 2 is characterized in that: If the deviation ratio is not greater than the benchmark demand ratio, the intelligent monitoring method based on the power supply and distribution system also includes: Determine whether the current detection duration is less than the preset lower limit required duration; If the current detection duration is not less than the lower limit required duration, the current detection duration is updated according to the unit duration; If the current detection duration is less than the lower limit required duration, the adjacent nodes of the current distribution node are determined according to the preset power supply and distribution topology; Determine adjacent change combinations according to adjacent nodes in the detection interval, and determine adjacent candidate combinations according to adjacent nodes in each candidate interval; Adjacent similarity values ​​are determined according to adjacent variation combinations and adjacent candidate combinations, and adjacent similarity values ​​with the largest values ​​are determined according to sorting rules, and candidate intervals corresponding to the adjacent similarity values ​​are determined as similar intervals.

4. The intelligent monitoring method based on the power supply and distribution system according to claim 1 is characterized in that: After the combined similarity value is determined, the intelligent monitoring method based on the power supply and distribution system also includes: Determine whether the maximum combined similarity value is greater than the preset benchmark requirement value; If the maximum combined similarity value is greater than the benchmark demand value, a similar interval or alternative interval is determined; If the maximum combined similarity value is not greater than the reference demand value, the interval change parameter in the interval change combination that belongs to the demand maintenance duration is defined as the most recent change parameter, and the mean change parameter is determined by calculation based on each most recent change parameter; Perform difference calculation based on the early warning power parameters and the current detection power parameters to determine the demand increase parameters; The demand increase times are determined by calculation based on the demand increase parameter and the mean change parameter, and an aging warning signal is output when the demand increase times are less than a preset benchmark warning times.

5. The intelligent monitoring method based on the power supply and distribution system according to claim 4 is characterized in that: After the demand increase parameters are determined, the intelligent monitoring method based on the power supply and distribution system also includes: On the time axis, a high point maintenance interval with a width equal to the required maintenance time is established with the current time point as the rear end point, and the detection gas parameters are obtained at each time point in the high point maintenance interval; Performing mean calculation based on each detected gas parameter to determine a mean gas parameter; The compensation increase parameter corresponding to the mean gas parameter is determined according to the preset compensation matching relationship, and the demand increase parameter is corrected according to the compensation increase parameter.

6. An intelligent monitoring system based on a power supply and distribution system, characterized in that: include: An acquisition module, used to acquire detection power parameters of a power distribution node; A processing module, connected to the acquisition module and the judgment module, for storing and processing information; A judgment module, connected with the acquisition module and the processing module, for judging the information; When the judging module judges that the detected power parameter is greater than the preset demand analysis parameter, the processing module controls the preset demand maintenance time to count down, wherein, when the detected power parameter is not greater than the demand analysis parameter, the demand maintenance time is reset; When the required maintenance timer returns to zero, the processing module establishes a detection interval with the current time point as the rear end point and a width of the preset detection time on the preset time axis; The processing module performs difference calculation according to adjacent detection power parameters in the detection interval to determine the interval change parameter, and combines all the interval change parameters to determine the interval change combination; The processing module establishes a historical interval with a width of a preset historical duration on the time axis with the current time point as the rear end point, and randomly defines a comparison interval with a width of the detection duration in the historical interval, and determines a comparison change combination in each comparison interval; The processing module analyzes the interval change combination and the comparison change combination to determine the combination similarity value, and determines the combination similarity value with the largest value according to the preset sorting rule, and defines the comparison interval corresponding to the combination similarity value as the similar interval; The processing module establishes a prediction interval with a width of a preset prediction time length using the rear end point of the similar interval as the front end point, and defines the detected power parameter in the prediction interval as the predicted power parameter; When the judging module judges that the predicted power parameter is greater than the preset warning power parameter, the processing module outputs an aging warning signal; After the combined similarity value is determined, the judging module judges whether there are at least two comparison intervals with the same and largest combined similarity values; If the judging module judges that there are not at least two comparison intervals with the same and largest combined similarity values, the processing module determines the comparison interval corresponding to the largest combined similarity value as the similar interval; If the judging module judges that there are at least two comparison intervals with the same and largest combined similarity values, the processing module determines the comparison interval corresponding to the largest combined similarity value as the candidate interval; The judgment module judges whether the prediction intervals determined by each candidate interval all have a situation where the predicted power parameter is greater than the warning power parameter; If the judgment module determines that the predicted intervals determined by the candidate intervals all have the situation where the predicted power parameters are greater than the warning power parameters, the processing module outputs an aging warning signal; If the judging module judges that the predicted intervals determined by the candidate intervals do not all have the situation where the predicted power parameter is greater than the warning power parameter, the processing module defines the candidate intervals where the predicted power parameter is greater than the warning power parameter as valid intervals, and defines the remaining candidate intervals as invalid intervals; The processing module counts according to the valid interval to determine the valid quantity, and counts according to the invalid interval to determine the invalid quantity; The processing module outputs an aging warning signal when the valid number is greater than the invalid number.

7. A computer-readable storage medium, characterized in that: The computer program is stored which can be loaded by a processor and execute the intelligent monitoring method based on the power supply and distribution system as claimed in any one of claims 1 to 5.

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