A power line load analysis method, device, equipment and storage medium

Abstract

The application discloses a power supply line load analysis method and device, equipment and a storage medium. The method comprises the following steps: when line overload is detected, total load information of at least one line and load information of at least one user are acquired; for each line, a line load curve of the line is determined according to the total load information of the line; for each user, a user load curve of the user is determined according to the load information of the user; the correlation is calculated according to the line load curves and the user load curves, a target user and a target line are determined; and the line switching is performed according to the target user and the target line. The line load curve and the user load curve are generated according to the collection time. The problem of unreasonable power supply line load switching is solved. The correlation between the user and the line is determined by analyzing the line load curve and the user load curve, and the line switching is performed, so that the heavy overload condition of the line is reduced, resource waste is avoided, and the power supply voltage quality is improved.

Description

Technical Field

[0001] This invention relates to the field of power system technology, and in particular to a method, apparatus, equipment and storage medium for power line load analysis. Background Technology

[0002] With social development, in recent years, with the surge in electricity load during the summer, the problems of line overload and bottlenecks have become increasingly prominent. In order to improve the quality of power supply, ensure reliable power supply, and make the power grid structure more reasonable, power supply companies now often use load switching, which involves transferring part of the load of heavily overloaded lines to lightly overloaded lines.

[0003] Currently, the suitability for line load cutover is determined solely by the overall load rate of the two lines, without accurately analyzing the simultaneity rate of the line loads over time. Therefore, even after a cutover, there may still be periods where the load distribution is unreasonable, such as some lines being heavily overloaded while others are lightly overloaded, resulting in wasted resources. Alternatively, there may be periods where the power supply capacity is sufficient but some heavily overloaded lines have a smaller cross-sectional area, leading to lower voltage and thus affecting voltage quality. Summary of the Invention

[0004] This invention provides a method, apparatus, equipment, and storage medium for power line load analysis to solve the problem of unreasonable load cutover.

[0005] According to one aspect of the present invention, a method for analyzing the load of a power supply line is provided, comprising:

[0006] When a line overload is detected, the total load information of at least one line and the load information of at least one user are obtained.

[0007] For each line, the line load curve is determined based on the total load information of the line;

[0008] For each user, determine the user load curve based on the user's load information;

[0009] Based on the correlation calculated from the load curves of each line and the user load curve, the target users and target lines are determined.

[0010] Perform line cutover based on the target user and target line;

[0011] The line load curve and user load curve are generated based on the data collection time.

[0012] According to another aspect of the present invention, a power line load analysis apparatus is provided, comprising:

[0013] The information acquisition module is used to acquire the total load information of at least one line and the load information of at least one user when a line overload is detected.

[0014] The line curve determination module is used to determine the line load curve of each line based on the total load information of the line.

[0015] The user curve determination module is used to determine the user load curve for each user based on the user's load information.

[0016] The target user and line determination module is used to calculate the correlation between the line load curve and the user load curve to determine the target user and the target line;

[0017] A cutover module is used to perform line cutovers based on the target user and the target line.

[0018] The line load curve and user load curve are generated based on the data collection time.

[0019] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0020] At least one processor; and

[0021] A memory communicatively connected to the at least one processor; wherein,

[0022] The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the power line load analysis method according to any embodiment of the present invention.

[0023] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the power line load analysis method according to any embodiment of the present invention.

[0024] The technical solution of this application embodiment obtains the total load information of at least one line and the load information of at least one user when a line overload is detected; for each line, a line load curve is determined based on the total load information of the line; for each user, a user load curve is determined based on the user's load information; the correlation between the line load curves and the user load curves is calculated to determine the target user and the target line; and line cutover is performed based on the target user and the target line. The line load curves and user load curves are generated based on the acquisition time. This solves the problem of unreasonable power supply line load cutover. When a line overload is detected, the line load curve is determined through the total load information of the line, and the user load curve is determined based on the user's load information. By analyzing the correlation between the line load curves and the user load curves, the target user and the target line are determined, and line cutover is performed based on the target user and the target line. This alleviates the line overload situation, avoids resource waste, and improves the power supply voltage quality. Since the line load curves and user load curves are generated based on the acquisition time, cutover is performed temporally, avoiding unreasonable distribution of loads within a certain time period.

[0025] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0026] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1 This is a flowchart of a power supply line load analysis method provided in Embodiment 1 of the present invention;

[0028] Figure 2 This is a flowchart of a power supply line load analysis method provided in Embodiment 2 of the present invention;

[0029] Figure 3 This is a flowchart illustrating the implementation of determining the target line combination in a power supply line load analysis method according to Embodiment 2 of the present invention.

[0030] Figure 4 This is a flowchart illustrating the process of determining target users and target lines in a power supply line load analysis method according to Embodiment 2 of the present invention.

[0031] Figure 5 This is a schematic diagram of the structure of a power supply line load analysis device according to Embodiment 3 of the present invention;

[0032] Figure 6 This is a schematic diagram of the structure of an electronic device that implements the power line load analysis method of this invention. Detailed Implementation

[0033] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0034] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0035] Example 1

[0036] Figure 1 This invention provides a flowchart of a power supply line load analysis method according to Embodiment 1. This embodiment is applicable to situations where power supply load is analyzed for line cutover. The method can be executed by a power supply line load analysis device, which can be implemented in hardware and / or software and can be configured in electronic devices such as computers. Figure 1 As shown, the method includes:

[0037] S101. When a line overload is detected, obtain the total load information of at least one line and the load information of at least one user.

[0038] In this embodiment, total load information can be specifically understood as the overall load information of all users carried by the line. Total load information may include total load data and the time of data collection. Load information can be specifically understood as the load of a single user when using electricity. Load information may include load data and the time of data collection. Total load information and load information may also include other types of information.

[0039] Specifically, during power system operation, electricity is supplied to users. Each line carries one or more users, supplying electricity to each user. If a line carries too many users, or if users consume excessive amounts of electricity, it can lead to line overload. To ensure reliable power supply, when a line experiences overload, the load on the power supply line is analyzed to facilitate effective line cutover. Therefore, it is necessary to monitor whether each line in the power system is overloaded in real time. When a line is overloaded, a power supply line load analysis is initiated to obtain the total load information of each line in the power system, as well as the load information of each user. The total load information of each line and the load information of each user can be stored in the metering system.

[0040] S102. For each line, determine the line load curve based on the total load information of the line.

[0041] In this embodiment, the line load curve can be specifically understood as a curve describing the load changes of the line. The line load curve in this application is generated based on the data collection time, which is the time of collection for various types of data (e.g., total load data). For example, by describing the load changes of the line through the data collection time and total load data, the power load is correlated with time, thus better describing the relationship between electricity consumption and time.

[0042] Specifically, for each line, its corresponding line load curve is determined. For each line, the line load data at different times is determined based on the total load information of the line, and the line load data at different times is determined based on the data collected at each time point, thereby generating the line load curve.

[0043] S103. For each user, determine the user load curve based on the user's load information.

[0044] In this embodiment, the user load curve can be specifically understood as a curve describing the changes in the user's load. The user load curve in this application is also generated based on the data collection time, which is the time when various types of data (e.g., load data) are collected. By describing the changes in the user's load through the data collection time and load data, the user's load is correlated with time, effectively describing the relationship between the user's electricity consumption and time.

[0045] Specifically, for each user, a corresponding user load curve is determined. For each user, the line data at different times is determined based on the user's load information, and the user's data at different times is determined based on the data collected at each time point, thereby generating the user load curve.

[0046] S104. Calculate the correlation between the load curves of each line and the load curves of the users to determine the target users and target lines.

[0047] In this embodiment, the target user is the user who needs to be cut over, that is, the target user needs to be transferred from one line to another; the target line can be specifically understood as the line that needs to carry the target user, that is, the target user is transferred from the original line to the target line, and the target line provides power.

[0048] Specifically, the correlation between the load curves of each line is calculated, two lines with significant differences are selected, and the electricity consumption of the users on each line is determined based on the user load curve. Based on the correlation between users and lines, users and lines with significant differences are identified, and these users are designated as target users and these lines as target lines, so that the target lines can provide power to the target users and avoid line overload.

[0049] S105. Perform line cutover based on target users and target lines.

[0050] The target users are transferred to the target line, and the target line provides power to the target users, thus completing the line cutover.

[0051] This application provides a power line load analysis method. When a line overload is detected, the method acquires the total load information of at least one line and the load information of at least one user. For each line, a line load curve is determined based on the total load information. For each user, a user load curve is determined based on the user's load information. The correlation between the line load curves and the user load curves is calculated to determine target users and target lines. Line cutover is performed based on the target users and target lines. The line load curves and user load curves are generated based on the data acquisition time. This method solves the problem of unreasonable power line load cutover. When a line overload is detected, the method determines the line load curve using the total load information and the user load curve based on the user's load information. By analyzing the correlation between the line load curves and user load curves, the method identifies target users and target lines. Line cutover is then performed based on the target users and target lines, mitigating line overload, avoiding resource waste, and improving power supply voltage quality. Because the line load curves and user load curves are generated based on the data acquisition time, cutover is performed temporally, avoiding unreasonable load distribution within a specific time period. The power line load analysis method provided in this application can assist power supply companies in analyzing the feasibility of load cut-off based on load simultaneity rate, making the load distribution of lines more reasonable from a temporal perspective, maximizing the utilization of line load capacity, avoiding line waste, and saving line construction costs. Load cut-off based on the relationship between users and loads can reduce the number of lines experiencing instantaneous heavy overloads, thereby improving voltage quality at various time periods, making the power grid operation safer and more stable, and enhancing user experience.

[0052] Example 2

[0053] Figure 2 This is a flowchart of a power line load analysis method provided in Embodiment 2 of the present invention. This embodiment is a refinement based on the above embodiments. Figure 2 As shown, the method includes:

[0054] S201. When a line overload is detected, the target time range is determined based on the previous overload time and the preset time range.

[0055] In this embodiment, the previous overload time can be specifically understood as the time of the last line overload. For example, after a line experiences a heavy overload, the overload time is recorded, and a cutover is performed. The cutover can be a single cutover or multiple cutovers. After the cutover, if the line returns to normal, and a heavy overload occurs again after the line has returned to normal, the overload time is updated based on the time when the heavy overload recurs. The preset time range can be one month, 15 days, etc., and can be set according to the actual engineering situation. The target time range can be specifically understood as the time range between two time points, used to determine the time range of the acquired total load information.

[0056] When a line overload is detected, the time of the previous overload and a preset time range are obtained. The time range is determined based on the current time and the time of the previous overload. It is then determined whether this time range is greater than the preset time range. If the time range is greater than the preset time range, the current time is used as the starting point, and the preset time range is used to determine the ending point. The time range determined by the starting point and the ending point is used as the target time range. If the time range is not greater than the preset time range, this time range is used as the target time range.

[0057] For example, the previous overload time was the 3rd, the current time is the 28th, and the time range is from the 3rd to the 28th, a total of 25 days; if the preset time range is 15 days, and the time range is greater than the preset time range, then the 13th (28th-15th) to the 28th will be used as the target time range; if the preset time range is 30 days, and the time range is not greater than the preset time range, then the 3rd to the 28th will be used as the target time range.

[0058] This application takes into account the impact on the line load when cutting over the previous overload time when determining the target time range.

[0059] S202. Obtain the total load information of each line within the target time range.

[0060] When acquiring the total load information for each line within the target time range, it can be acquired at time intervals, for example, with 15-minute intervals to acquire the total load information within the target time range; alternatively, it can directly acquire all the total load information within the target time range. The target time range is at least one natural day, and the total load information can be stored according to natural days, storing the total load information for each acquisition time within each natural day.

[0061] S203. Obtain load information for at least one user.

[0062] Define a time range and determine the user's load information accordingly. The time range can be preset, for example, one month, or it can be set to be the same as the target time range. User load information can also be stored by calendar day, storing the load information for each collection time within each calendar day.

[0063] In this application, there is no strict order in which the total load information of the line and the load information of the user are obtained. The total load information can be obtained first and then the load information, or the load information can be obtained first and then the total load information, or they can be obtained simultaneously. Figure 2 Taking the example of obtaining total load information first, and then obtaining load information, similarly, there is no strict order in which the line load curve and the user load curve are generated. Figure 2 Take simultaneous execution as an example.

[0064] For each line, the line load curve is determined using the following S204-S207.

[0065] The total load information includes at least one total load data point and the corresponding first acquisition time.

[0066] S204. For each first acquisition time, determine the total load data corresponding to the first acquisition time.

[0067] In this embodiment, the first collection time can be specifically understood as the collection time of the total load data. The total load data corresponding to each first collection time within each calendar day is determined.

[0068] S205. Determine the target total load data based on the total load data.

[0069] In this embodiment, the target total load data can be specifically understood as data that can represent the total load situation of the line. Mathematical operations are performed on each total load data point, such as calculating the average, maximum, minimum, median, and weighted average, to obtain the target total load data. Preferably, this embodiment uses the average value to calculate the target total load data.

[0070] S206. Use the first acquisition time and the target total load data as the coordinates of the line load point.

[0071] In this embodiment, the line load point coordinates can be specifically understood as the coordinates of each point in the line load curve. The first acquisition time is used as the abscissa of the line load point coordinates, and the target total load data is used as the total coordinate of the line load point coordinates.

[0072] S207. Generate line load curves based on the coordinates of each line load point.

[0073] Each initial data collection point corresponds to a line load point coordinate, and a line load curve is generated based on these coordinates. With a data collection interval of 15 minutes, the line load curve consists of (60 / 15)*24 = 96 points.

[0074] For each user, the user load curve is determined using the following steps S208-S211.

[0075] The load information includes at least one load data point and the corresponding second acquisition time.

[0076] S208. For each second acquisition time, determine the corresponding load data for each second acquisition time.

[0077] In this embodiment, the second collection time can be specifically understood as the time when the user's load data is collected. The load data corresponding to each second collection time within each calendar day is determined.

[0078] S209. Determine the target load data based on the load data.

[0079] In this embodiment, the target load data can be specifically understood as data that represents the load situation used by the user. Mathematical operations are performed on each load data point, such as calculating the average, maximum, minimum, median, and weighted average, to obtain the target load data. This embodiment preferably uses the average value to calculate the target load data.

[0080] S210. Use the second acquisition time and the target load data as the coordinates of the user load point.

[0081] In this embodiment, the user load point coordinates can be specifically understood as the coordinates of each point in the user load curve. The second acquisition time is used as the abscissa of the user load point coordinates, and the target load data is used as the total coordinate of the user load point coordinates.

[0082] S211. Generate user load curves based on the coordinates of each user load point.

[0083] Each second data collection moment corresponds to a user load point coordinate, and a user load curve is generated based on the coordinates of each user load point. Again, taking a data collection interval of 15 minutes as an example, the user load curve consists of (60 / 15)*24=96 points.

[0084] S212. Calculate the line correlation between the load curves of each line and determine the target line combination, which includes the first line and the second line.

[0085] In this embodiment, the target line combination can be specifically understood as a line combination that can be used for line cutover. The target line combination includes two lines, namely the first line and the second line. For each line load curve, its line correlation with other line load curves is calculated, and the correlations are compared. The two lines with the largest differences are selected as the target line combination, one of which is designated as the first line and the other as the second line.

[0086] Optional, Figure 3 This invention provides a flowchart of the implementation of a power supply line load analysis method for determining a target line combination. The method involves calculating the line correlation between the load curves of each line and determining the target line combination, including the following steps:

[0087] S2121. Calculate the correlation between the load curves of each line and determine the line correlation coefficient.

[0088] In this embodiment, the line correlation coefficient can be specifically understood as the correlation coefficient between two lines. The correlation between the load curves of each pair of lines is calculated to obtain the line correlation coefficient, for example, using the CORREL function in Excel. For example, the line correlation coefficient between the load curves of line F1 and line F2 is k. 12 The line correlation coefficient between the load curves of line F1 and line F3 is k. 13 And so on. Assuming there are n lines with the possibility of cutover, then there are... combination.

[0089] S2122. Compare the correlation coefficients of each line and determine the minimum correlation coefficient of the line.

[0090] In this embodiment, the minimum line correlation coefficient can be specifically understood as the minimum value among the line correlation coefficients. By comparing the magnitudes of the correlation coefficients of each line, the minimum value is determined and used as the minimum line correlation coefficient.

[0091] S2123. Determine the two lines corresponding to the minimum line correlation coefficient as the target line combination.

[0092] Identify the two lines corresponding to the minimum line correlation coefficient, and use these two lines as the target line combination.

[0093] It is important to know that the correlation coefficient k of the lines ranges from -1 to 1. The closer k is to -1, the greater the negative correlation between the two lines, that is, the greater the load difference at each time point and the lower the load simultaneity rate, and therefore the more suitable it is for cutover.

[0094] S213. Determine the first user corresponding to the first line and the second user corresponding to the second line.

[0095] Identify each first user carried by the first line, and identify each second user carried by the second line.

[0096] S214. Determine the target user and target line based on the correlation between the first line, the second line, each first user, and each second user.

[0097] Determine the line load curve of the first line, the line load curve of the second line, the user load curve of each first user, and the user load curve of each second user. Calculate the correlation between the curves and select the lines and users with poor correlation as target lines and target users.

[0098] Optional, Figure 4 This invention provides a flowchart of the implementation of a power supply line load analysis method for determining target users and target lines. The determination of target users and target lines based on the correlation between a first line, a second line, each first user, and each second user includes the following steps:

[0099] S2141. Calculate the correlation between the user load curve of each first user and the line load curve of the second line to obtain the first correlation coefficient.

[0100] The correlation between the first user and the second line is calculated for all users with cutover potential. Specifically, for each first user, the first correlation coefficient is obtained based on the correlation between the user load curve of the first user and the line load curve of the second line.

[0101] S2142. Calculate the correlation between the user load curve of each second user and the line load curve of the first line to obtain the second correlation coefficient.

[0102] For each second user who is likely to be cut over, the correlation between the user load curve of the second user and the line load curve of the first line is calculated to obtain the second correlation coefficient.

[0103] S2143. Compare the magnitudes of each first correlation coefficient and each second correlation coefficient to determine the minimum user line coefficient.

[0104] In this embodiment, the minimum user line coefficient can be specifically understood as the minimum value of the correlation coefficient between the user and the line. The minimum value is determined by comparing the magnitudes of each first correlation coefficient and each second correlation coefficient, and this minimum value is used as the minimum user line coefficient. The minimum user line coefficient is the correlation coefficient closest to -1, representing the combination of users and lines with the lowest load simultaneity rate and the most suitable for cutover.

[0105] S2144. The user corresponding to the minimum user line coefficient is determined as the target user, and the line corresponding to the minimum user line coefficient is determined as the target line.

[0106] Determine the user and line corresponding to the minimum user line coefficient, and use this user as the target user and this line as the target line.

[0107] S215. Perform line cutover based on target users and target lines.

[0108] S216. Determine whether the cutover termination condition is met. If yes, execute S217; otherwise, return to execute S212.

[0109] In this embodiment, the cutover termination condition can be specifically understood as the condition used to determine whether to end the line cutover. It is determined whether the cutover termination condition is currently met. If yes, S217 is executed; otherwise, the process returns to S212 to continue the cutover.

[0110] When returning to S212 to continue the cutover, the line correlation between the line load curves can be calculated using the results of the previous calculation to obtain a new target line combination. This new combination can be either the previous target line combination or a new target line combination obtained after excluding the previous one (i.e., the line combination corresponding to the second smallest line correlation coefficient). Correspondingly, when determining the new first and second users, the previously determined target users are removed.

[0111] Optionally, the cutover termination condition is that the line is not overloaded or the number of line cutovers exceeds the preset number.

[0112] In this embodiment, the preset number of cutovers can be pre-set according to requirements. When the cutover ends when the line is not overloaded, the cutover is repeated until the overload situation of the line is resolved; when the cutover ends when the preset number of cutovers is reached, the cutover is repeated until the number of cutovers exceeds the preset number, regardless of whether the overload situation of the line has been resolved at this time.

[0113] S217, End cutover.

[0114] This invention provides a power line load analysis method that solves the problem of unreasonable power line load cutover. When a line is detected to be heavily overloaded, the method determines the line load curve based on the total load information of the line and the user load curve based on the user's load information. By analyzing the line load curve and the user load curve, the correlation between users and lines is determined, thereby identifying target users and target lines. Line cutover is then performed based on the target users and target lines to alleviate heavy overload conditions, avoid resource waste, and improve power supply voltage quality. Since the line load curve and user load curve are generated based on the acquisition time, cutover is performed temporally, avoiding unreasonable distribution of loads within a certain time period. The power line load analysis method provided in this application can assist power supply companies in analyzing the feasibility of load cutover based on load simultaneity rate, making line load allocation more reasonable from a temporal distribution perspective, maximizing the utilization of line load capacity, avoiding line waste, and saving line construction costs. Load cutover based on the relationship between users and loads can reduce the number of lines experiencing instantaneous heavy overload, thereby improving voltage quality in various time periods, making the power grid operation safer and more stable, and improving user experience.

[0115] Example 3

[0116] Figure 5 This is a schematic diagram of a power line load analysis device provided in Embodiment 3 of the present invention. Figure 5 As shown, the device includes: an information acquisition module 31, a line curve determination module 32, a user curve determination module 33, a target user and line determination module 34, and a cutover module 35.

[0117] The information acquisition module 31 is used to acquire the total load information of at least one line and the load information of at least one user when a line overload is detected.

[0118] The line curve determination module 32 is used to determine the line load curve of each line based on the total load information of the line.

[0119] User curve determination module 33 is used to determine the user load curve for each user based on the user's load information.

[0120] The target user and line determination module 34 is used to calculate the correlation based on the load curves of each line and the user load curve to determine the target user and the target line;

[0121] Cutover module 35 is used to perform line cutover based on the target user and target line;

[0122] The line load curve and user load curve are generated based on the data collection time.

[0123] This application provides a power line load analysis device that solves the problem of unreasonable power line load cutover. When a line is detected to be heavily overloaded, the device determines the line load curve based on the total load information of the line and the user load curve based on the user's load information. By analyzing the line load curve and the user load curve, the correlation between users and lines is determined, thereby identifying target users and target lines. Line cutover is then performed based on the target users and target lines to alleviate heavy overload conditions, avoid resource waste, and improve power supply voltage quality. Since the line load curve and user load curve are generated based on the acquisition time, cutover is performed temporally, avoiding unreasonable distribution of loads within a certain time period. The power line load analysis method provided in this application can assist power supply companies in analyzing the feasibility of load cutover based on load simultaneity rate, making line load allocation more reasonable from a temporal distribution perspective, maximizing the utilization of line load capacity, avoiding line waste, and saving line construction costs. By performing load cutover based on the relationship between users and loads, the number of lines with instantaneous heavy overload can be reduced, thereby improving voltage quality in various time periods, making the power grid operation safer and more stable, and improving user experience.

[0124] Optionally, the information acquisition module 31 includes:

[0125] The time range determination unit is used to determine the target time range based on the previous overload time and the preset time range.

[0126] The information acquisition unit is used to acquire the total load information of each line within the target time range.

[0127] Optionally, the total load information includes at least one total load data point and a corresponding first acquisition time. The line curve determination module 32 includes:

[0128] The total data determination unit is used to determine the total load data corresponding to each first acquisition time for each first acquisition time;

[0129] The target total load data determination unit is used to determine the target total load data based on each of the total load data;

[0130] The line coordinate determination unit is used to use the first acquisition time and the target total load data as the line load point coordinates;

[0131] The line curve generation unit is used to generate line load curves based on the coordinates of each line load point.

[0132] Optionally, the load information includes at least one load data and a corresponding second acquisition time, and the user curve determination module 33 includes;

[0133] The data determination unit is used to determine the load data corresponding to each second acquisition time for each second acquisition time.

[0134] The target data determination unit is used to determine target load data based on each of the load data;

[0135] The user coordinate determination unit is used to use the second acquisition time and the target load data as the coordinates of the user load point;

[0136] The user curve generation unit is used to generate user load curves based on the coordinates of each user load point.

[0137] Optionally, the target user and route determination module 34 includes:

[0138] A combination determination unit is used to calculate the line correlation between the load curves of each line and determine the target line combination, wherein the target line combination includes a first line and a second line.

[0139] The user determination unit is used to determine the first user corresponding to the first line and the second user corresponding to the second line.

[0140] The target user and line determination unit is used to determine the target user and target line based on the correlation between the first line, the second line, each first user, and each second user.

[0141] Optionally, the combination determination unit is specifically used to: calculate the correlation between the load curves of each line and determine the line correlation coefficient; compare the magnitude of the correlation coefficients of each line and determine the minimum line correlation coefficient; and determine the two lines corresponding to the minimum line correlation coefficient as the target line combination.

[0142] Optionally, the target user and line determination unit is specifically used for: calculating the correlation between the user load curve of each first user and the line load curve of the second line to obtain a first correlation coefficient; calculating the correlation between the user load curve of each second user and the line load curve of the first line to obtain a second correlation coefficient; comparing the magnitudes of each first correlation coefficient and each second correlation coefficient to determine the minimum user line coefficient; determining the user corresponding to the minimum user line coefficient as the target user, and determining the line corresponding to the minimum user line coefficient as the target line.

[0143] Optionally, the device may also include:

[0144] The judgment module is used to determine whether the cutover termination condition is met. If so, the cutover is terminated; otherwise, the operation of calculating the correlation based on the load curves of each line and the load curve of the user to determine the target user and the target line is returned until the cutover termination condition is met.

[0145] The cutover termination condition is that the line is not overloaded or the number of line cutovers exceeds the preset number.

[0146] The power line load analysis device provided in this embodiment of the invention can execute the power line load analysis method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method.

[0147] Example 4

[0148] Figure 6 A schematic diagram of an electronic device 40 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0149] like Figure 6 As shown, the electronic device 40 includes at least one processor 41 and a memory, such as a read-only memory (ROM) 42 or a random access memory (RAM) 43, communicatively connected to the at least one processor 41. The memory stores computer programs executable by the at least one processor. The processor 41 can perform various appropriate actions and processes based on the computer program stored in the ROM 42 or loaded into the RAM 43 from storage unit 48. The RAM 43 may also store various programs and data required for the operation of the electronic device 40. The processor 41, ROM 42, and RAM 43 are interconnected via a bus 44. An input / output (I / O) interface 45 is also connected to the bus 44.

[0150] Multiple components in electronic device 40 are connected to I / O interface 45, including: input unit 46, such as keyboard, mouse, etc.; output unit 47, such as various types of monitors, speakers, etc.; storage unit 48, such as disk, optical disk, etc.; and communication unit 49, such as network card, modem, wireless transceiver, etc. Communication unit 49 allows electronic device 40 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0151] Processor 41 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 41 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 41 performs the various methods and processes described above, such as power line load analysis methods.

[0152] In some embodiments, the power line load analysis method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 48. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 40 via ROM 42 and / or communication unit 49. When the computer program is loaded into RAM 43 and executed by processor 41, one or more steps of the power line load analysis method described above may be performed. Alternatively, in other embodiments, processor 41 may be configured to perform the power line load analysis method by any other suitable means (e.g., by means of firmware).

[0153] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0154] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0155] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0156] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0157] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0158] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0159] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0160] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A power line load analysis method, characterized by, include: When a line overload is detected, the total load information of at least one line and the load information of at least one user are obtained. For each line, the line load curve is determined based on the total load information of the line; For each user, determine the user load curve based on the user's load information; Based on the correlation calculated from the load curves of each line and the user load curve, the target users and target lines are determined. Perform line cutover based on the target user and target line; The line load curve and user load curve are generated based on the data collection time. The step of determining target users and target lines by calculating the correlation based on the load curves of each line and the user load curve includes: Calculate the line correlation between the load curves of each line to determine the target line combination, which includes a first line and a second line. Identify the first user corresponding to the first line and the second user corresponding to the second line; The target user and target line are determined based on the correlation between the first line, the second line, each first user, and each second user. The calculation of the line correlation between the load curves of each line and the determination of the target line combination includes: Calculate the correlation between the load curves of each line and determine the line correlation coefficient; Compare the correlation coefficients of each of the aforementioned lines to determine the minimum correlation coefficient. The two lines corresponding to the minimum line correlation coefficient are identified as the target line combination; The step of determining the target user and target line based on the correlation between the first line, the second line, each first user, and each second user includes: Calculate the correlation between the user load curve of each first user and the line load curve of the second line to obtain the first correlation coefficient; Calculate the correlation between the user load curve of each second user and the line load curve of the first line to obtain the second correlation coefficient; Compare the magnitudes of each of the first correlation coefficients and each of the second correlation coefficients to determine the minimum user line coefficient; The user corresponding to the minimum user line coefficient is identified as the target user, and the line corresponding to the minimum user line coefficient is identified as the target line.

2. The method of claim 1, wherein, The step of obtaining the total load information of at least one line includes: Determine the target time range based on the previous overload time and the preset time range; Obtain the total load information for each line within the target time range.

3. The method of claim 1, wherein, The total load information includes at least one total load data point and a corresponding first acquisition time. Determining the line load curve based on the total load information of the line includes: For each first acquisition time, determine the total load data corresponding to each first acquisition time; Determine the target total load data based on the total load data described above; Use the first acquisition time and the target total load data as the coordinates of the line load point; The line load curve is generated based on the coordinates of each line load point.

4. The method of claim 1, wherein, The load information includes at least one load data point and a corresponding second acquisition time. Determining the user's load curve based on the user's load information includes: For each second acquisition time, determine the corresponding load data for that second acquisition time; Determine the target load data based on the aforementioned load data; Use the second acquisition time and the target load data as the coordinates of the user load point; A user load curve is generated based on the coordinates of each user load point.

5. The method according to any one of claims 1 to 4, characterized in that, Also includes: Determine if the cutover termination condition is met; if so, terminate the cutover. Otherwise, return to the operation of calculating the correlation based on the load curves of each line and the load curve of the user to determine the target user and the target line, until the cutover termination condition is met; The cutover termination condition is that the line is not overloaded or the number of line cutovers exceeds the preset number.

6. A power line load analysis device for performing the power line load analysis method according to any one of claims 1 to 5, characterized by include: The information acquisition module is used to acquire the total load information of at least one line and the load information of at least one user when a line overload is detected. The line curve determination module is used to determine the line load curve of each line based on the total load information of the line. The user curve determination module is used to determine the user load curve for each user based on the user's load information. The target user and line determination module is used to calculate the correlation between the line load curve and the user load curve to determine the target user and the target line; A cutover module is used to perform line cutovers based on the target user and the target line. The line load curve and user load curve are generated based on the data collection time.

7. An electronic device, comprising: The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the power line load analysis method according to any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the power line load analysis method according to any one of claims 1-5.

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