Transformer area power utilization data analysis method and device, electronic equipment and storage medium

Abstract

The embodiment of the invention relates to a transformer area power consumption data analysis method and device, electronic equipment and a storage medium. The method comprises the following steps: determining a power consumption data statistical rule for a transformer area; according to the electricity consumption data statistical rule, performing statistics on to-be-analyzed electricity consumption data; obtaining a target data analysis parameter, and determining a target data analysis rule corresponding to the target data analysis parameter from a preset data analysis library; according to the target data analysis rule, analyzing and calculating the to-be-analyzed power consumption data to obtain target power consumption data; and generating a data analysis chart according to the target power consumption data. Therefore, the data analysis efficiency and accuracy of the power utilization data of the transformer area can be improved, and the user experience is improved.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of power system technology, and in particular to a method, apparatus, electronic device and storage medium for analyzing power consumption data of distribution transformer areas. Background Technology

[0002] With the development of technology, people's electricity demand is gradually increasing. For example, in addition to daily electricity use, with the development of electric vehicles, the number of charging stations is also gradually increasing.

[0003] As transformers in the distribution area are used over time, their capacity will gradually decrease due to aging, resulting in a contradiction between insufficient transformer capacity and surging electricity demand. To solve the above problems, it is necessary to continuously optimize the power consumption strategy for the distribution area.

[0004] However, in the process of continuously optimizing the electricity consumption strategy within a transformer substation, various electricity consumption data are typically acquired manually and then analyzed manually to optimize the strategy. This manual analysis of substation electricity consumption data is not only inefficient but also prone to errors due to significant human intervention, negatively impacting user experience. Summary of the Invention

[0005] In view of this, in order to solve the technical problems mentioned above, which are that the analysis of power consumption data of transformer substations is not only inefficient, but also prone to errors due to the large number of human factors involved, thus affecting the user experience, the present invention provides a method, device, electronic device and storage medium for analyzing power consumption data of transformer substations.

[0006] In a first aspect, embodiments of the present invention provide a method for analyzing electricity consumption data in a distribution area, the method comprising:

[0007] Define the statistical rules for electricity consumption data for each transformer substation;

[0008] According to the aforementioned electricity consumption data statistics rules, statistically analyze the electricity consumption data to be analyzed.

[0009] Obtain the target data analysis parameters, and determine the target data analysis rules corresponding to the target data analysis parameters from the preset data analysis library;

[0010] According to the target data analysis rules, the electricity consumption data to be analyzed and calculated is performed to obtain the target electricity consumption data.

[0011] Data analysis charts are generated based on the target electricity consumption data.

[0012] As one possible implementation, the determination of electricity consumption data statistics rules for the transformer area includes:

[0013] Output a first visualization interface so that the user can select multiple statistical parameters included in the electricity data statistics rules through the first visualization interface. The statistical parameters include at least: target transformer area, target equipment in the target transformer area, target distribution box in the target transformer area, load line in the target transformer area, and target time period.

[0014] In response to a click operation of a preset button in the first visualization interface, multiple statistical parameters are obtained from the first visualization interface;

[0015] Based on the aforementioned statistical parameters, statistical rules for electricity consumption data of the transformer area are generated.

[0016] As one possible implementation, obtaining the target data analysis parameters includes:

[0017] Output a second visualization interface, which includes multiple data analysis parameters;

[0018] Receives user selection operation for any one of the multiple data analysis parameters;

[0019] The data analysis parameters corresponding to the selection operation are determined as the target data analysis parameters;

[0020] After generating data analysis charts based on the target electricity consumption data, the method further includes:

[0021] A third visualization interface is output, which includes the data analysis charts.

[0022] As one possible implementation, the data analysis library includes multiple data analysis parameters, data analysis rules corresponding to each data analysis parameter, and the correspondence between the two. The step of determining the target data analysis rule corresponding to the target data analysis parameter from the preset data analysis library includes:

[0023] The target data analysis parameter is matched with each data analysis parameter in the data analysis library to obtain the first data analysis parameter;

[0024] Based on the correspondence, determine the first data analysis rule corresponding to the first data analysis parameter;

[0025] The first data analysis rule is determined as the target data analysis rule corresponding to the target data analysis parameter.

[0026] As one possible implementation, the target data analysis rules include year-on-year analysis rules. The electricity consumption data to be analyzed includes electricity consumption data of load lines within the target distribution area in different sub-time periods within the target time period. The step of analyzing and calculating the electricity consumption data to be analyzed according to the target data analysis rules to obtain the target electricity consumption data includes:

[0027] For the first electricity consumption data of each sub-time period in the electricity consumption data to be analyzed, obtain the second electricity consumption data of the sub-time period in the time period preceding the target time period;

[0028] Divide the first electricity consumption data by the second electricity consumption data to obtain the year-on-year rate corresponding to the sub-time period;

[0029] The target electricity consumption data are determined by the different sub-time periods within the target time period, the first electricity consumption data and the second electricity consumption data corresponding to each sub-time period, and the year-on-year rate corresponding to each sub-time period.

[0030] As one possible implementation, the target data analysis rules include month-on-month analysis rules. The electricity consumption data to be analyzed includes the electricity consumption data of the load lines within the target distribution area in different sub-time periods within the target time period. The step of analyzing and calculating the electricity consumption data to be analyzed according to the target data analysis rules to obtain the target electricity consumption data includes:

[0031] For the third electricity consumption data in each sub-time period of the electricity consumption data to be analyzed, obtain the fourth electricity consumption data corresponding to the previous sub-time period;

[0032] Subtract the fourth electricity consumption data from the third electricity consumption data to obtain the difference corresponding to the sub-time period;

[0033] Divide the difference by the fourth electricity consumption data to obtain the month-on-month growth rate corresponding to the sub-time period;

[0034] The target electricity consumption data are determined by the different sub-time periods within the target time period, the third and fourth electricity consumption data corresponding to each sub-time period, and the month-on-month growth rate corresponding to each sub-time period.

[0035] As one possible implementation, the target data analysis rules include electrical safety analysis rules. The power consumption data to be analyzed includes a set of temperature values ​​and a set of residual current values ​​for multiple load lines within the target transformer area during a target time period. The step of analyzing and calculating the power consumption data to be analyzed according to the target data analysis rules to obtain the target power consumption data includes:

[0036] For each load line, determine whether there is a high temperature value greater than a preset temperature threshold in the set of temperature values ​​of the load line within the target time period, and whether there is a high residual current value greater than a preset current threshold in the set of residual current values.

[0037] If the high temperature value and / or the high residual current value are determined to exist, an alarm message is output and / or the transformer in the target area is controlled to stop supplying power to the load line;

[0038] The set of temperature values ​​and the set of residual current values ​​for each load line within the target time period are determined as the target electricity consumption data.

[0039] As one possible implementation, the target data analysis rules include utilization rate analysis rules. The electricity consumption data to be analyzed includes the electricity consumption duration of multiple load lines within the target distribution area during a target time period. The step of analyzing and calculating the electricity consumption data to be analyzed according to the target data analysis rules to obtain target electricity consumption data includes:

[0040] For each load line, the electricity consumption duration corresponding to the load line is divided by the target time period to obtain the utilization rate of the load line.

[0041] The usage duration and usage rate of each load line within the target distribution area are determined as the target electricity consumption data.

[0042] As one possible implementation, the target data analysis rules include transformer area capacity analysis rules. The electricity consumption data to be analyzed includes the transformer load and energy storage system load corresponding to each sub-time period of the target transformer area within the target time period. The step of analyzing and calculating the electricity consumption data to be analyzed according to the target data analysis rules to obtain the target electricity consumption data includes:

[0043] For each sub-time period, the load of the transformer and the load of the energy storage system are added together to obtain the total load of the target distribution area in the sub-time period;

[0044] Divide the transformer load by a preset transformer load threshold to obtain the transformer load rate of the target area in the sub-time period.

[0045] Divide the load of the energy storage system by the preset load threshold of the energy storage system to obtain the load rate of the energy storage system in the target area during the sub-time period.

[0046] The total load, transformer load, energy storage system load, transformer load rate, and energy storage system load rate for each sub-time period are determined as the target electricity consumption data.

[0047] As one possible implementation, the target data analysis rules include transformer area load prediction analysis rules. The electricity consumption data to be analyzed includes the transformer area load at each sub-time point within the target time period, the first transformer area load set in the first time period before the sub-time point, the second transformer area load set in the second time period before the first time period, and the third transformer area load set in the third time period before the time point. The step of analyzing and calculating the electricity consumption data to be analyzed according to the target data analysis rules to obtain the target electricity consumption data includes:

[0048] Sum the loads of all first transformer areas in the first transformer area load set and divide by the first time period to obtain the first average load of the target transformer area during the first time period.

[0049] Sum the loads of all second transformer areas in the second transformer area load set, and divide by the second time period to obtain the second average load of the target transformer area during the second time period.

[0050] The summation of all loads in the third distribution area load set is divided by the third time period to obtain the third average load of the target distribution area during the third time period.

[0051] The first average load is multiplied by a preset first weight to obtain the first load.

[0052] The second average load is multiplied by a preset second weight to obtain the second load.

[0053] The third average load is obtained by multiplying the third average load by a preset third weight.

[0054] The first load, the second load, and the third load are added together to obtain the predicted load of the transformer area in the sub-time period.

[0055] The load of the target transformer area at each sub-time point within the target time period and the predicted load are determined as the target electricity consumption data.

[0056] As one possible implementation, the target data analysis rules include district benefit analysis rules. The electricity consumption data to be analyzed includes the transformer capacity of the target district, the load set of the transformers in the target district during the target time period, and the operating time of the transformers operating at full load or overload. The step of analyzing and calculating the electricity consumption data to be analyzed according to the target data analysis rules to obtain the target electricity consumption data includes:

[0057] The total load of the transformer during the target time period is obtained by adding up all the loads in the load set.

[0058] Divide the total load by the target time period to obtain the average load of the transformer during the target time period;

[0059] Determine the maximum load from the set of load amounts;

[0060] Subtracting the transformer capacity from the maximum load yields the transformer capacity saving.

[0061] Divide the average load by a preset load threshold to obtain the average load rate of the transformer during the target time period;

[0062] Divide the operating time by the target time period to obtain the percentage of time the transformer operates at full load or overload.

[0063] The transformer capacity, the average load rate, the maximum load, the capacity savings, the average load rate, and the time percentage are determined as the target electricity consumption data.

[0064] Secondly, embodiments of the present invention provide a power consumption data analysis device for a distribution area, the device comprising:

[0065] The first determining module is used to determine the statistical rules for electricity consumption data of the transformer area;

[0066] The statistics module is used to statistically analyze the electricity consumption data according to the aforementioned electricity consumption data statistics rules.

[0067] The acquisition module is used to acquire target data analysis parameters;

[0068] The second determining module is used to determine the target data analysis rule corresponding to the target data analysis parameter from a preset data analysis library;

[0069] The analysis module is used to analyze and calculate the electricity consumption data to be analyzed according to the target data analysis rules to obtain the target electricity consumption data;

[0070] The generation module is used to generate data analysis charts based on the target electricity consumption data.

[0071] Thirdly, embodiments of the present invention provide an electronic device, including: a processor and a memory, wherein the processor is configured to execute a transformer area power consumption data analysis program stored in the memory to implement the transformer area power consumption data analysis method described in any one of the first aspects.

[0072] Fourthly, embodiments of the present invention provide a storage medium storing one or more programs, which can be executed by one or more processors to implement the power consumption data analysis method for transformer substations as described in the first aspect.

[0073] The technical solution provided by this invention determines statistical rules for electricity consumption data in a transformer substation, statistically analyzes the electricity consumption data to be analyzed according to these rules, obtains target data analysis parameters, determines the target data analysis rules corresponding to the target data analysis parameters from a preset data analysis library, analyzes and calculates the electricity consumption data to be analyzed according to these target data analysis rules, obtains target electricity consumption data, and generates data analysis charts based on the target electricity consumption data. This technical solution, by statistically analyzing the electricity consumption data to be analyzed according to the determined statistical rules and then analyzing and calculating the electricity consumption data to be analyzed according to the determined target data analysis rules, obtains target electricity consumption data and generates data analysis charts corresponding to the target electricity consumption data, enabling users to more easily and intuitively understand the electricity consumption situation in the transformer substation, thereby improving the efficiency and accuracy of electricity consumption data analysis in the transformer substation and enhancing the user experience. Attached Figure Description

[0074] Figure 1 A flowchart illustrating an embodiment of a method for analyzing electricity consumption data in a distribution area, provided by an embodiment of the present invention;

[0075] Figure 2 A schematic diagram of a first visual interface provided in an embodiment of the present invention;

[0076] Figure 3 This is a schematic diagram of a data chart corresponding to a year-on-year analysis provided in an embodiment of the present invention;

[0077] Figure 4 This invention provides a schematic diagram of a data analysis chart corresponding to a month-on-month analysis.

[0078] Figure 5 This invention provides a schematic diagram of a data analysis chart corresponding to electrical safety analysis.

[0079] Figure 6 This invention provides a schematic diagram of a data analysis chart corresponding to a usage rate analysis.

[0080] Figure 7 This invention provides a schematic diagram of a data analysis chart corresponding to the capacity analysis of a transformer substation.

[0081] Figure 8 This is a schematic diagram of a data analysis chart corresponding to the load forecasting and analysis of a transformer substation, provided in an embodiment of the present invention.

[0082] Figure 9 This invention provides a schematic diagram of a data analysis chart corresponding to the analysis of the benefits of a transformer substation.

[0083] Figure 10 This is a schematic diagram of a data analysis chart corresponding to power data collection and analysis provided in an embodiment of the present invention;

[0084] Figure 11 A schematic diagram of rule grouping provided in an embodiment of the present invention;

[0085] Figure 12 A block diagram illustrating an embodiment of a power consumption data analysis device for a distribution area provided by this invention;

[0086] Figure 13 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0087] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0088] The method for analyzing power consumption data in transformer substations provided by the present invention will be further explained and described below with reference to the accompanying drawings and specific embodiments. These embodiments do not constitute a limitation on the embodiments of the present invention.

[0089] See Figure 1 This is a flowchart illustrating an embodiment of a method for analyzing electricity consumption data in a distribution area, provided by an embodiment of the present invention. Figure 1 As shown, the process may include the following steps:

[0090] Step 101: Determine the statistical rules for electricity consumption data for the transformer area.

[0091] The aforementioned electricity consumption data statistics rules refer to the rules used to statistically analyze various electricity consumption data within the transformer area. These rules can be default rules or generated by the execution entity of this invention based on user operations. This invention does not impose any restrictions on these rules.

[0092] In one embodiment, the executing entity of this invention may pre-store an electricity consumption data statistics rule, which can count all electricity consumption data within the transformer area.

[0093] In another embodiment, the executing entity of this invention can output a visual interface (hereinafter referred to as the first visual interface for ease of description), through which the user can select multiple statistical parameters included in the electricity consumption data statistical rules. These statistical parameters may include, but are not limited to, the following parameters: target transformer area (the transformer area where electricity consumption data is to be statistically analyzed), target equipment in the target transformer area (the equipment where electricity consumption data is to be statistically analyzed, which may be one or multiple), target distribution box within the target transformer area (the distribution box where electricity consumption data is to be statistically analyzed), load line within the target transformer area (the load line where electricity consumption data is to be statistically analyzed), and target time period (the time period corresponding to the electricity consumption data to be statistically analyzed).

[0094] For example, see Figure 2 This is a schematic diagram of a first visual interface provided in an embodiment of the present invention. Figure 2 As shown, the first visualization interface may include the following parameters: rule name, rule description, selected transformer area, statistical method, distribution box, line, and statistical time.

[0095] The rule name can be the name of a user-defined electricity consumption data statistics rule.

[0096] Rule descriptions can be used to describe the content and function of rules for electricity consumption data statistics;

[0097] Selecting a transformer area allows you to choose the target transformer area for which electricity consumption data is to be collected.

[0098] The statistical method can be used to select the target equipment for which electricity consumption data is to be statistically analyzed;

[0099] Distribution boxes can be used to select the distribution boxes within the target transformer area where the electricity consumption data is to be collected;

[0100] The line can be used to select the load line within the target transformer area where the electricity consumption data is to be statistically analyzed;

[0101] The statistical time period can be used to select the target time period for the electricity consumption data to be statistically analyzed. It can be a day, a month, or a year. When the target time period is "day", it can be divided into multiple sub-time periods (segments) for statistical analysis. When the target time period is "month", it can be analyzed with each day as a sub-time period. When the target time period is "year", it can be analyzed with each month as a sub-time period.

[0102] Afterwards, users can set the above statistical parameters through the first visualization interface, and click the preset button in the first visualization interface (e.g., ...) after setting. Figure 2(e.g., the "Execute" or "Save" button in the interface). Based on this, the execution entity of this embodiment of the invention can receive a user's click operation on a preset button in the first visual interface, and in response to the received click operation on the preset button in the first visual interface, obtain multiple statistical parameters from the first visual interface.

[0103] Finally, based on the above statistical parameters, statistical rules for electricity consumption data of the transformer area can be generated.

[0104] Step 102: According to the electricity consumption data statistics rules, collect the electricity consumption data to be analyzed.

[0105] The electricity consumption data to be analyzed refers to the electricity consumption data within the target distribution area obtained according to the above-mentioned electricity consumption data statistical rules. It may include, but is not limited to: the electricity consumption data of transformers within the target distribution area, the electricity consumption data of distribution boxes within the target distribution area, or the electricity consumption data of at least one load line within the target distribution area.

[0106] In one embodiment, after determining the electricity consumption data statistics rules, the executing entity of this embodiment can count the electricity consumption data to be analyzed in the target transformer area according to the electricity consumption data statistics rules.

[0107] As one possible implementation, the executing entity of this embodiment of the invention can be connected to a smart transformer substation monitoring system, which can monitor and acquire electricity consumption data within the target substation in real time. Based on this, the executing entity of this embodiment of the invention can acquire the electricity consumption data monitored in real time by the aforementioned smart transformer substation monitoring system, and perform statistical analysis on the acquired electricity consumption data within the target substation according to the aforementioned electricity consumption data statistical rules, thereby obtaining the aforementioned electricity consumption data to be analyzed.

[0108] As another possible implementation, the executing entity of this embodiment of the invention can directly monitor and acquire all electricity consumption data within the target transformer area, and save the electricity consumption data to a preset database. Based on this, after determining the electricity consumption data statistical rules, the executing entity of this embodiment of the invention can statistically analyze the electricity consumption data from the aforementioned database according to the electricity consumption data statistical rules to obtain the electricity consumption data to be analyzed.

[0109] Step 103: Obtain the target data analysis parameters and determine the target data analysis rules corresponding to the above target data analysis parameters from the preset data analysis library.

[0110] The aforementioned target data analysis parameters refer to the analysis parameters corresponding to the electricity consumption data to be analyzed. They can be used to indicate the analysis objectives of the electricity consumption data to be analyzed, such as analyzing the year-on-year rate and month-on-month rate of the electricity consumption data to be analyzed, or analyzing the electricity consumption data to be analyzed to determine the gas safety, capacity, or load forecast of the target distribution area.

[0111] The aforementioned data analysis library is used to store multiple data analysis parameters, the data analysis rules corresponding to each data analysis parameter, and the correspondence between the two.

[0112] The aforementioned target data analysis rules refer to the rules for analyzing the electricity consumption data to be analyzed, which may include, but are not limited to: year-on-year analysis rules, month-on-month analysis rules, electrical safety analysis rules, utilization rate analysis rules, transformer area capacity analysis rules, transformer area load forecast analysis rules, and transformer area benefit analysis rules, etc.

[0113] In one embodiment, the executing entity of this invention may be equipped with a voice acquisition and voice recognition device. Based on this, the executing entity of this invention can acquire user-inputted voice and recognize the voice. If data analysis parameters are identified based on the recognition results, the identified data analysis parameters can be determined as target data analysis parameters.

[0114] In another embodiment, the executing entity of this invention may output a visualization interface (hereinafter referred to as the second visualization interface for ease of description). This second visualization interface may include multiple data analysis parameters, such as year-on-year analysis, month-on-month analysis, electrical safety analysis, utilization rate analysis, transformer area capacity analysis, transformer area load forecast analysis, and benefit analysis. Users can select the data analysis parameters they need through this second visualization interface.

[0115] Based on this, the execution entity of this embodiment of the invention can receive a user's selection operation for any one of multiple data analysis parameters, and determine the data analysis parameter corresponding to the selection operation as the target data analysis parameter.

[0116] Subsequently, after determining the target data analysis parameters, the executing entity of this embodiment of the invention can determine the target data analysis rules corresponding to the target data analysis parameters, and generate analysis charts corresponding to the target data analysis parameters using the following steps 104 and 105.

[0117] Finally, the executing entity of this embodiment of the invention can output a visualization interface (hereinafter referred to as the third visualization interface for ease of description), which may include analysis charts corresponding to the target data analysis parameters.

[0118] In one embodiment, the aforementioned data analysis library may include multiple data analysis parameters, data analysis rules corresponding to each data analysis parameter, and the correspondence between the two. Based on this, when the execution subject of this embodiment determines the target data analysis rule corresponding to the target data analysis parameter from the preset data analysis library, it may match the aforementioned target data analysis parameter with each data analysis parameter in the data analysis library to obtain a data analysis parameter that matches the target data analysis parameter (hereinafter referred to as the first data analysis parameter).

[0119] Then, based on the above correspondence, the data analysis rule corresponding to the first data analysis parameter (hereinafter referred to as the first data analysis rule for ease of description) can be determined, and the first data analysis rule can be determined as the target data analysis rule corresponding to the target data analysis parameter.

[0120] Step 104: Analyze and calculate the electricity consumption data to be analyzed according to the above target data analysis rules to obtain the target electricity consumption data.

[0121] Step 105: Generate data analysis charts based on the target electricity consumption data mentioned above.

[0122] The following provides a unified explanation of steps 104 and 105:

[0123] The aforementioned target electricity consumption data refers to the electricity consumption data obtained after analyzing and calculating the electricity consumption data to be analyzed according to the determined target data analysis rules.

[0124] The above data analysis charts are data charts generated from the above target electricity consumption data. They may include graphs and reports corresponding to the target electricity consumption data. The graphs may be bar charts, line charts, or pie charts. This embodiment of the invention does not limit the types of graphs.

[0125] In one embodiment, the executing entity of this invention may analyze and calculate the determined electricity consumption data to be analyzed according to the target data analysis rules determined in step 103, and obtain the target electricity consumption data after analysis and calculation.

[0126] Optionally, the above target data analysis rules may include year-on-year analysis rules (year-on-year analysis is a comparative analysis of the electricity consumption of the same or a group of monitoring devices during the same period), and the above-mentioned electricity consumption data to be analyzed may include the electricity consumption data of the load lines in the target area in different sub-time periods within the target time period.

[0127] Based on this, when the executing entity of this embodiment analyzes and calculates the electricity consumption data to be analyzed according to the target data analysis rules, it can obtain the electricity consumption data of the corresponding sub-time period in the time period preceding the target time period (hereinafter referred to as the second electricity consumption data) for each sub-time period of the electricity consumption data to be analyzed (hereinafter referred to as the first electricity consumption data). The time period preceding the target time period can be a time period of the same length as the target time period. For example, if the target time period is a specific day, then the time period preceding the target time period is the previous day; if the target time period is a specific month, then the time period preceding the target time period is the previous month; if the target time period is a specific year, then the time period preceding the target time period is the previous year. Correspondingly, the sub-time periods of the target time period are the same as the sub-time periods of the time period preceding the target time period, for example, both are 12:00 to 14:00, or both are the 11th, or both are in April.

[0128] Then, by dividing the first electricity consumption data by the second electricity consumption data, the year-on-year rate corresponding to the above sub-time period can be obtained.

[0129] Then, the target electricity consumption data can be determined by the different sub-time periods within the target time period, the first and second electricity consumption data corresponding to each sub-time period, and the year-on-year rate corresponding to each sub-time period.

[0130] Finally, based on the target electricity consumption data mentioned above, corresponding data analysis charts can be generated.

[0131] For example, taking the target time period mentioned above as an example for today, see [link to example]. Figure 3 This is a schematic diagram of a data chart corresponding to a year-on-year analysis provided in an embodiment of the present invention. For example... Figure 3 As shown, the electricity consumption data to be analyzed is the electricity consumption of line XX in area XX, with a target time period of YYYY-MM-DD, which is divided into 12 sub-time periods (each sub-time period is two hours). After the executing entity of this embodiment analyzes and calculates the above-mentioned electricity consumption data according to the target data analysis rules, it can obtain the corresponding target electricity consumption data and generate data as shown below. Figure 3 The bar charts and reports shown are provided. It should be noted that the data statistics rules can be modified; that is, the power consumption of load lines in other transformer areas can be statistically analyzed.

[0132] Optionally, the above target data analysis rules may include month-on-month analysis rules (month-on-month analysis is a comparison and analysis of the electricity consumption of the same or a group of monitoring devices with the previous period), and the above-mentioned electricity consumption data to be analyzed may include the electricity consumption data of the load lines in the target area in different sub-time periods within the target time period.

[0133] Based on this, when the executing entity of this embodiment of the invention analyzes and calculates the electricity consumption data to be analyzed according to the target data analysis rules, it can obtain the electricity consumption data corresponding to the previous sub-time period (hereinafter referred to as the fourth electricity consumption data) for each sub-time period of the electricity consumption data to be analyzed (for ease of description, it is referred to as the third electricity consumption data). The aforementioned sub-time period and the previous sub-time period can both be target time periods, or they can belong to different target time periods. For example, if the target time period is the current day and the sub-time period is from 0:00 to 2:00 on the current day, then the previous sub-time period is the last sub-time period in the previous time period of the target time period, that is, from 22:00 to 24:00 yesterday.

[0134] Next, the third electricity consumption data is subtracted from the fourth electricity consumption data to obtain the difference for that sub-period. This difference is then divided by the fourth electricity consumption data to obtain the month-on-month growth rate for that sub-period.

[0135] Then, the target electricity consumption data can be determined by the different sub-time periods within the target time period, the third and fourth electricity consumption data corresponding to each sub-time period, and the month-on-month growth rate corresponding to each sub-time period.

[0136] Finally, based on the target electricity consumption data, corresponding data analysis charts can be generated.

[0137] For example, taking a target period of one year as an example, the sub-periods of this target period can be each month of the year. See also Figure 4 This is a schematic diagram of a data analysis chart corresponding to a month-on-month analysis provided in an embodiment of the present invention. For example... Figure 4 As shown, the electricity consumption data to be analyzed is the electricity consumption of line XX in area XX, with a target time period of year YYYY. This target time period is divided into 12 sub-time periods (each month is a sub-time period). After the executing entity of this embodiment of the invention analyzes and calculates the above-mentioned electricity consumption data according to the target data analysis rules, it can obtain the corresponding target electricity consumption data and generate data as shown below. Figure 4 The bar charts and reports shown are provided. It should be noted that the data statistics rules can be modified; that is, the power consumption of load lines in other transformer areas can be statistically analyzed.

[0138] Optionally, the aforementioned target data analysis rules may include electrical safety analysis rules, and the aforementioned power consumption data to be analyzed may include the set of temperature values ​​and the set of residual current values ​​of multiple load lines within the target transformer area within the target time period.

[0139] Based on this, when the execution subject of the present invention analyzes and calculates the power consumption data to be analyzed in accordance with the target data analysis rules, it can determine for each load line whether there is a high temperature value greater than a preset temperature threshold in the set of temperature values ​​of the load line within the target time period, and whether there is a high residual current value greater than a preset circuit threshold in the set of residual current values.

[0140] Optionally, if the aforementioned high temperature and / or high residual current values ​​are confirmed, it indicates that the temperature of the current load line is too high or the residual current value is abnormal, posing a safety hazard. An alarm message can be output, and / or the transformer within the target distribution area can be controlled to stop supplying power to the load line.

[0141] Then, the set of temperature values ​​and the set of residual current values ​​for each load line within the target time period can be determined as the target power consumption data.

[0142] Finally, based on the target electricity consumption data, corresponding data analysis charts can be generated.

[0143] For example, taking the target time period as the current day as an example, see [link to example]. Figure 5 This is a schematic diagram of a data analysis chart corresponding to an electrical safety analysis provided in an embodiment of the present invention. For example... Figure 5 As shown, the electricity consumption data to be analyzed consists of the electricity consumption of multiple lines (A1, A2, B1, B2, C1, C2) in the XX distribution area, with the target time period being 0:00 to 4:00 on the current day. After analyzing and calculating the aforementioned electricity consumption data according to the target data analysis rules, the executing entity of this embodiment of the invention can obtain the corresponding target electricity consumption data and generate data as shown below. Figure 5 The bar charts and reports shown are provided. It should be noted that the data statistics rules can be modified; that is, the power consumption of load lines in other transformer areas can be statistically analyzed.

[0144] Optionally, the above target data analysis rules may include utilization analysis rules, and the above-mentioned electricity consumption data to be analyzed may include the electricity consumption duration of multiple load lines in the target area within the target time period.

[0145] Based on this, when the executing entity of this invention analyzes and calculates the electricity consumption data to be analyzed in accordance with the target data analysis rules, it can divide the electricity consumption duration corresponding to each load line by the target time period to obtain the utilization rate of the load line.

[0146] Then, the usage duration and utilization rate of each load line in the target distribution area can be determined as the target power consumption data.

[0147] Finally, based on the target electricity consumption data, corresponding data analysis charts can be generated.

[0148] For example, taking the target time period as the current day as an example, see [link to example]. Figure 6 This is a schematic diagram of a data analysis chart corresponding to a usage rate analysis provided in an embodiment of the present invention. For example... Figure 6 As shown, the electricity consumption data to be analyzed is the electricity consumption of multiple lines in the XX distribution area, and the target time period is YYYY-MM-DD. After the executing entity of this embodiment analyzes and calculates the above-mentioned electricity consumption data according to the target data analysis rules, it can obtain the corresponding target electricity consumption data and generate the following... Figure 6 The bar charts and reports shown are provided. It should be noted that the data statistics rules can be modified; that is, the power consumption of load lines in other transformer areas can be statistically analyzed.

[0149] Optionally, the aforementioned target data analysis rules may include transformer area capacity analysis rules, and the aforementioned electricity consumption data to be analyzed may include the transformer load and energy storage system load corresponding to each sub-time period of the target transformer area within the target time period. The aforementioned energy storage system can be used to supply power to the load lines within the target transformer area when the transformers within the target transformer area are operating under overload conditions.

[0150] Based on this, when the executing entity of this embodiment analyzes and calculates the electricity consumption data to be analyzed according to the target data analysis rules, it can add the corresponding transformer load and energy storage system load for each sub-time period to obtain the total load of the target area in that sub-time period. Then, the transformer load is divided by a preset transformer load threshold to obtain the transformer load rate of the target area in that sub-time period. Next, the energy storage system load is divided by a preset energy storage system load threshold to obtain the energy storage system load rate of the target area in that sub-time period.

[0151] Then, the total load, transformer load, energy storage system load, transformer load rate, and energy storage system load rate for each sub-time period can be determined as the target electricity consumption data.

[0152] Finally, based on the target electricity consumption data, corresponding data analysis charts can be generated.

[0153] For example, taking the target time period as the current day as an example, see [link to example]. Figure 7 This is a schematic diagram of a data analysis chart corresponding to a transformer area capacity analysis provided in an embodiment of the present invention. Figure 7 As shown, the electricity consumption data to be analyzed is the electricity consumption situation of the XX distribution area, and the target time period is YYYY-MM-DD. After the executing entity of this embodiment analyzes and calculates the above-mentioned electricity consumption data according to the target data analysis rules, it can obtain the corresponding target electricity consumption data and generate the following... Figure 7 The bar charts and reports shown.

[0154] Optionally, the aforementioned target data analysis rules may include transformer area load forecasting analysis rules, and the aforementioned electricity consumption data to be analyzed may include the transformer area load corresponding to each sub-time point within the target time period, the first transformer area load set in the first time period before the sub-time point, the second transformer area load set in the second time period before the first time period, and the third transformer area load set in the third time period before the time point. Optionally, the duration of the aforementioned first time period, second time period, and third time period may increase sequentially; for example, the aforementioned first time period may be one week, the aforementioned second time period may be one month, and the aforementioned third time period may be one year.

[0155] Based on this, when the executing entity of this invention analyzes and calculates the electricity consumption data to be analyzed according to the target data analysis rules, it can determine the target electricity consumption data through the following steps:

[0156] Step 1: Sum all the loads of the first transformer area in the first transformer area load set, and divide by the first time period mentioned above to obtain the average load of the target transformer area in the first time period (hereinafter referred to as the first average load for ease of description).

[0157] Step 2: Sum all the loads of the second transformer area in the second transformer area load set, and divide by the second time period to obtain the average load of the target transformer area in the second time period (hereinafter referred to as the second average load for ease of description).

[0158] Step 3: Sum all the loads of the third transformer area in the load set of the third transformer area, and divide by the third time period to obtain the average load of the target transformer area in the third time period (hereinafter referred to as the third average load for ease of description).

[0159] Step 4: Multiply the above first average load amount by the preset first weight value to obtain the first load amount.

[0160] Step 5: Multiply the above-mentioned second average load amount by the preset second weight to obtain the second load amount.

[0161] Step 6: Multiply the above third average load amount by the preset third weight to obtain the third load amount.

[0162] Step 7: Add the first load, the second load, and the third load together to obtain the predicted load of the transformer area in that sub-time period.

[0163] Finally, the load and predicted load of the target transformer area at each sub-time point within the target time period can be determined as the target electricity consumption data, and corresponding data analysis charts can be generated based on the target electricity consumption data.

[0164] For example, let's take the target time period as one day in the future as an example. See [link / reference]. Figure 8 This is a schematic diagram of a data analysis chart corresponding to a transformer area load forecasting analysis provided in an embodiment of the present invention. For example... Figure 8 As shown, the electricity consumption data to be analyzed is the predicted electricity consumption situation in the XX distribution area, and the target time period is YYYY-MM-DD.

[0165] Subsequently, when forecasting load at each time point, the following rules can be used: 50% for the average load of the same period one week (7 days) prior to today; 10% for the average load of the same period one month (30 days) prior to today; and 40% for the average load of the same period in the same month of the previous year. The weighted sum of these three data points is then the predicted load value for the current time point. Based on the above target electricity consumption data, a forecast can be generated as follows: Figure 8 The bar charts and reports shown.

[0166] Optionally, the above target data analysis rules may include distribution area benefit analysis rules, and the above-mentioned electricity consumption data to be analyzed may include the transformer capacity of the target distribution area, the load set of the transformers in the target distribution area during the target time period, and the operating time of the transformers operating at full load or overload.

[0167] Based on this, when the executing entity of this invention analyzes and calculates the electricity consumption data to be analyzed according to the target data analysis rules, it can determine the target electricity consumption data through the following steps:

[0168] Step 1: Add up all the loads in the load set to get the total load of the transformer during the target time period.

[0169] Step 2: Divide the total load by the target time period to obtain the average load of the transformer during the target time period.

[0170] Step 3: Determine the maximum load from the load set.

[0171] Step 4: Subtract the transformer capacity from the maximum load to obtain the transformer capacity saving.

[0172] Step 5: Divide the average load by the preset load rate threshold to obtain the average load rate of the transformer during the target time period.

[0173] Step 6: Divide the running time by the target time period to obtain the percentage of time the transformer operates at full load or overload.

[0174] Subsequently, the aforementioned transformer capacity, average load rate, maximum load, capacity savings, average load rate, and time percentage can be determined as the target electricity consumption data.

[0175] Finally, based on the target electricity consumption data, corresponding data analysis charts can be generated.

[0176] For example, taking a target period of one year as an illustration, see [link to example]. Figure 9 This is a schematic diagram of a data analysis chart corresponding to a transformer area benefit analysis provided in an embodiment of the present invention. For example... Figure 9 As shown, the electricity consumption data to be analyzed is the electricity consumption situation of area XX. After the executing entity of this embodiment analyzes and calculates the above-mentioned electricity consumption data according to the target data analysis rules, it can obtain the corresponding target electricity consumption data and generate data as shown below. Figure 9 The report shown.

[0177] Furthermore, the aforementioned target data analysis rules may include district-level power consumption data collection and analysis rules, and the aforementioned power consumption data to be analyzed may include the power consumption status of multiple load lines corresponding to the target district. When performing district-level power consumption data collection and analysis on the aforementioned power consumption data, the executing entity of this embodiment can directly generate data analysis charts based on the aforementioned power consumption data to be analyzed, so that users can easily and intuitively understand the power consumption status of multiple load lines in the target district.

[0178] For example, taking the target time period as the current day as an example, see [link to example]. Figure 10 This is a schematic diagram of a data analysis chart corresponding to power data collection and analysis provided in an embodiment of the present invention. For example... Figure 10 As shown, the electricity consumption data to be analyzed is the electricity consumption of line XX in area XX. The executing entity of this embodiment can directly generate data such as... Figure 10 The chart shown.

[0179] Furthermore, the executing entity of this embodiment of the invention can perform grouped statistics on the above-mentioned electricity consumption data statistics rules, wherein each electricity consumption data statistics rule also includes data analysis rules, for example... Figure 11 The diagram shown is a schematic representation of a rule-based grouping method provided in an embodiment of the present invention. Figure 11 As can be seen, users can view, edit, and delete each rule in the above rule groups, and can also create new rules.

[0180] The technical solution provided by this invention determines statistical rules for electricity consumption data in a transformer substation, statistically analyzes the electricity consumption data to be analyzed according to these rules, obtains target data analysis parameters, determines the target data analysis rules corresponding to the target data analysis parameters from a preset data analysis library, analyzes and calculates the electricity consumption data to be analyzed according to these target data analysis rules, obtains target electricity consumption data, and generates data analysis charts based on the target electricity consumption data. This technical solution, by statistically analyzing the electricity consumption data to be analyzed according to the determined statistical rules and then analyzing and calculating the electricity consumption data to be analyzed according to the determined target data analysis rules, obtains target electricity consumption data and generates data analysis charts corresponding to the target electricity consumption data, enabling users to more easily and intuitively understand the electricity consumption situation in the transformer substation, thereby improving the efficiency and accuracy of electricity consumption data analysis in the transformer substation and enhancing the user experience.

[0181] See Figure 12 This is a block diagram illustrating an embodiment of a power consumption data analysis device for a distribution area provided by an embodiment of the present invention. Figure 12 As shown, the device may include:

[0182] The first determining module 1201 is used to determine the statistical rules for electricity consumption data of the transformer area;

[0183] The statistics module 1202 is used to statistically analyze the electricity consumption data according to the electricity consumption data statistics rules.

[0184] Module 1203 is used to acquire target data analysis parameters;

[0185] The second determining module 1204 is used to determine the target data analysis rule corresponding to the target data analysis parameter from a preset data analysis library;

[0186] The analysis module 1205 is used to analyze and calculate the electricity consumption data to be analyzed according to the target data analysis rules to obtain the target electricity consumption data.

[0187] The generation module 1206 is used to generate data analysis charts based on the target electricity consumption data.

[0188] Figure 13 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Figure 13The illustrated electronic device 1300 includes at least one processor 1301, a memory 1302, at least one network interface 1304, and a user interface 1303. The various components in the electronic device 1300 are coupled together via a bus system 1305. It is understood that the bus system 1305 is used to implement communication between these components. In addition to a data bus, the bus system 1305 also includes a power bus, a control bus, and a status signal bus. However, for clarity, ... Figure 13 The general designated all buses as Bus System 1305.

[0189] The user interface 1303 may include a display, keyboard, or clicking device (e.g., mouse, trackball, touchpad, or touchscreen).

[0190] It is understood that the memory 1302 in this embodiment of the invention can be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), Synchronous DRAM (SDRAM), Double Data Rate Synchronous DRAM (DDRSDRAM), Enhanced Synchronous DRAM (ESDRAM), Synchlink DRAM (SLDRAM), and Direct Rambus RAM (DRRAM). The memory 1302 described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0191] In some implementations, memory 1302 stores elements, executable units or data structures, or subsets thereof, or extended sets thereof: operating system 13021 and application program 13022.

[0192] The operating system 13021 includes various system programs, such as the framework layer, core library layer, and driver layer, used to implement various basic business functions and handle hardware-based tasks. The application program 13022 includes various applications, such as a media player and a browser, used to implement various application functions. The program implementing the method of this embodiment can be included in the application program 13022.

[0193] In this embodiment of the invention, by calling the program or instructions stored in memory 1302, specifically the program or instructions stored in application program 13022, processor 1301 executes the method steps provided in each method embodiment, including, for example:

[0194] Define the statistical rules for electricity consumption data for each transformer substation;

[0195] According to the aforementioned electricity consumption data statistics rules, statistically analyze the electricity consumption data to be analyzed.

[0196] Obtain the target data analysis parameters, and determine the target data analysis rules corresponding to the target data analysis parameters from the preset data analysis library;

[0197] According to the target data analysis rules, the electricity consumption data to be analyzed and calculated is performed to obtain the target electricity consumption data.

[0198] Data analysis charts are generated based on the target electricity consumption data.

[0199] The methods disclosed in the above embodiments of the present invention can be applied to processor 1301, or implemented by processor 1301. Processor 1301 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the integrated logic circuit of the hardware in processor 1301 or by instructions in the form of software. The processor 1301 may be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of the present invention. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of the present invention can be directly embodied in the execution of a hardware decoding processor, or executed by a combination of hardware and software units in the decoding processor. The software units may be located in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. The storage medium is located in memory 1302. Processor 1301 reads the information in memory 1302 and completes the steps of the above method in conjunction with its hardware.

[0200] It is understood that the embodiments described herein can be implemented in hardware, software, firmware, middleware, microcode, or a combination thereof. For hardware implementation, the processing unit can be implemented in one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), general-purpose processors, controllers, microcontrollers, microprocessors, other electronic units for performing the functions described herein, or combinations thereof.

[0201] For software implementation, the techniques described herein can be implemented by units that perform the functions described herein. The software code can be stored in memory and executed by a processor. The memory can be implemented in the processor or external to the processor.

[0202] The electronic device provided in this embodiment may be as follows: Figure 13 The electronic device shown can perform the following: Figure 1 All steps of the electricity consumption data analysis method in the central distribution area, thereby achieving... Figure 1 For details on the technical effectiveness of the power consumption data analysis method for the transformer substations shown in the diagram, please refer to [link / reference]. Figure 1 The relevant descriptions are presented concisely and will not be elaborated upon here.

[0203] This invention also provides a storage medium (computer-readable storage medium). This storage medium stores one or more programs. The storage medium may include volatile memory, such as random access memory; it may also include non-volatile memory, such as read-only memory, flash memory, hard disk, or solid-state drive; and it may also include combinations of the above types of memory.

[0204] One or more programs in the storage medium can be executed by one or more processors to implement the above-mentioned method for analyzing power consumption data of the distribution area executed on the electronic device side.

[0205] The processor is used to execute the power consumption data analysis program for the transformer substation stored in the memory to implement the following steps of the power consumption data analysis method for the transformer substation executed on the electronic device side:

[0206] Define the statistical rules for electricity consumption data for each transformer substation;

[0207] According to the aforementioned electricity consumption data statistics rules, statistically analyze the electricity consumption data to be analyzed.

[0208] Obtain the target data analysis parameters, and determine the target data analysis rules corresponding to the target data analysis parameters from the preset data analysis library;

[0209] According to the target data analysis rules, the electricity consumption data to be analyzed and calculated is performed to obtain the target electricity consumption data.

[0210] Data analysis charts are generated based on the target electricity consumption data.

[0211] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0212] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented in hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0213] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for analyzing electric power data of a district, characterized by, The method comprises: determining power consumption data statistical rules for a power distribution area; statistically analyzing power consumption data to be analyzed according to the power consumption data statistical rules; obtaining target data analysis parameters and determining target data analysis rules corresponding to the target data analysis parameters from a preset data analysis library; analyzing and calculating the power consumption data to be analyzed according to the target data analysis rules to obtain target power consumption data; generating a data analysis chart according to the target power consumption data.

2. The method of claim 1, wherein, The determination of the power consumption data statistical rules for the power distribution area comprises: outputting a first visual interface to enable a user to select a plurality of statistical parameters included in the power consumption data statistical rules through the first visual interface, the statistical parameters at least including a target power distribution area, a target device in the target power distribution area, a target distribution box in the target power distribution area, a target load line in the target power distribution area, and a target time period; in response to a received click operation of a preset button in the first visual interface, obtaining a plurality of the statistical parameters from the first visual interface; generating power consumption data statistical rules for the power distribution area according to a plurality of the statistical parameters.

3. The method of claim 1, wherein, The obtaining of the target data analysis parameters comprises: outputting a second visual interface, the second visual interface including a plurality of data analysis parameters; receiving a selection operation of any data analysis parameter in the plurality of data analysis parameters by a user; determining the data analysis parameter corresponding to the selection operation as a target data analysis parameter; after the generation of the data analysis chart according to the target power consumption data, the method further comprises: outputting a third visual interface, the third visual interface including the data analysis chart.

4. The method of claim 1, wherein, The data analysis library includes a plurality of data analysis parameters, a data analysis rule corresponding to each data analysis parameter, and a corresponding relationship therebetween, and the determination of the target data analysis rule corresponding to the target data analysis parameter from the preset data analysis library comprises: matching the target data analysis parameter with each data analysis parameter in the data analysis library to obtain a first data analysis parameter; determining a first data analysis rule corresponding to the first data analysis parameter according to the corresponding relationship; determining the first data analysis rule as a target data analysis rule corresponding to the target data analysis parameter.

5. The method of claim 2, wherein, The target data analysis rule includes a same-period analysis rule, the power consumption data to be analyzed includes power consumption data of different sub-time periods of a load line in a target time period in a target power distribution area, and the analysis and calculation of the power consumption data to be analyzed according to the target data analysis rule to obtain target power consumption data comprises: for first power consumption data of each sub-time period in the power consumption data to be analyzed, obtaining second power consumption data of the sub-time period in a previous time period of the target time period; dividing the first power consumption data by the second power consumption data to obtain a same-period ratio corresponding to the sub-time period; and The different sub-time periods in the target time period, the first power consumption data and the second power consumption data corresponding to each sub-time period, and the same ratio corresponding to each sub-time period are determined as target power consumption data.

6. The method of claim 2, wherein, The target data analysis rule includes a same-period analysis rule, the to-be-analyzed power consumption data includes power consumption data of different sub-time periods of a load line in the target area in a target time period, and the target power consumption data is obtained by performing analysis and calculation on the to-be-analyzed power consumption data according to the target data analysis rule. For third power consumption data of each sub-time period in the to-be-analyzed power consumption data, fourth power consumption data corresponding to a previous sub-time period of the sub-time period is obtained. The third power consumption data is subtracted from the fourth power consumption data to obtain a difference value corresponding to the sub-time period. The difference value is divided by the fourth power consumption data to obtain a same-period growth rate corresponding to the sub-time period. The different sub-time periods in the target time period, the third power consumption data and the fourth power consumption data corresponding to each sub-time period, and the same-period growth rate corresponding to each sub-time period are determined as target power consumption data.

7. The method of claim 2, wherein, The target data analysis rule includes an electrical safety analysis rule, the to-be-analyzed power consumption data includes a temperature value set and a residual current value set of a plurality of load lines in the target area in a target time period, and the target power consumption data is obtained by performing analysis and calculation on the to-be-analyzed power consumption data according to the target data analysis rule. For each load line, it is determined whether there is a high temperature value greater than a preset temperature threshold in the temperature value set of the load line in the target time period, and whether there is a high residual current value greater than a preset current threshold in the residual current value set. If the high temperature value and / or the high residual current value is determined to exist, an alarm information is output and / or a transformer in the target area is controlled to stop power supply to the load line. The temperature value set and the residual current value set of each load line in the target time period are determined as target power consumption data.

8. The method of claim 2, wherein, The target data analysis rule includes a usage rate analysis rule, the to-be-analyzed power consumption data includes power consumption duration of a plurality of load lines in the target area in a target time period, and the target power consumption data is obtained by performing analysis and calculation on the to-be-analyzed power consumption data according to the target data analysis rule. For each load line, the power consumption duration corresponding to the load line is divided by the target time period to obtain a usage rate corresponding to the load line. The usage duration and the usage rate corresponding to each load line in the target area are determined as the target power consumption data.

9. The method of claim 2, wherein, The target data analysis rule includes an area capacity analysis rule, the to-be-analyzed power consumption data includes transformer load and energy storage system load corresponding to each sub-time period of the target area in a target time period, and the target power consumption data is obtained by performing analysis and calculation on the to-be-analyzed power consumption data according to the target data analysis rule. add the transformer load and the energy storage system load for each sub-time period to obtain total load of the target transformer area in the sub-time period; divide the transformer load by a preset transformer load threshold to obtain a transformer load rate of the target transformer area in the sub-time period; divide the energy storage system load by a preset energy storage system load threshold to obtain an energy storage system load rate of the target transformer area in the sub-time period; determine the total load, the transformer load, the energy storage system load, the transformer load rate, and the energy storage system load rate in each sub-time period as target power consumption data.

10. The method of claim 2, wherein, The target data analysis rule includes a transformer area load prediction analysis rule, the power consumption data to be analyzed includes transformer area load at each sub-time point in a target time period, a first transformer area load set before the sub-time point, a second transformer area load set before a first time period, a third transformer area load set before a second time period, and the target power consumption data is obtained by analyzing and calculating the power consumption data to be analyzed according to the target data analysis rule, including: summing all first transformer area loads in the first transformer area load set and dividing by the first time period to obtain a first average load of the target transformer area in the first time period; summing all second transformer area loads in the second transformer area load set and dividing by the second time period to obtain a second average load of the target transformer area in the second time period; summing all third transformer area loads in the third transformer area load set and dividing by the third time period to obtain a third average load of the target transformer area in the third time period; multiplying the first average load by a preset first weight to obtain a first load; multiplying the second average load by a preset second weight to obtain a second load; multiplying the third average load by a preset third weight to obtain a third load; adding the first load, the second load, and the third load to obtain a predicted load of the transformer area in the sub-time period; determining the transformer area load at each sub-time point in the target time period and the predicted load as target power consumption data.

11. The method of claim 2, wherein, The target data analysis rule includes a transformer area benefit analysis rule, the power consumption data to be analyzed includes transformer capacity of the target transformer area, a load set of the transformer of the target transformer area in the target time period, and running time of the transformer running at full load or overload, and the target power consumption data is obtained by analyzing and calculating the power consumption data to be analyzed according to the target data analysis rule, including: adding all loads in the load set to obtain total load of the transformer in the target time period; dividing the total load by the target time period to obtain an average load of the transformer in the target time period; determining a maximum load from the load set; Subtracting the transformer capacity from the maximum load capacity, a capacity saving of the transformer is obtained; Dividing the average load capacity by a preset load capacity threshold, an average load rate of the transformer in the target time period is obtained; Dividing the running time by the target time period, a time proportion of full load or overload operation of the transformer is obtained; The transformer capacity, the average load rate, the maximum load capacity, the capacity saving, the average load rate, and the time proportion are determined as the target power consumption data.

12. A power consumption data analysis device for a district, characterized by comprising: The device comprises: A first determination module configured to determine power consumption data statistical rules for a transformer area; A statistics module configured to statistically analyze power consumption data to be analyzed according to the power consumption data statistical rules; An acquisition module configured to acquire target data analysis parameters; A second determination module configured to determine target data analysis rules corresponding to the target data analysis parameters from a preset data analysis library; An analysis module configured to analyze and calculate the power consumption data to be analyzed according to the target data analysis rules to obtain target power consumption data; A generation module configured to generate a data analysis chart according to the target power consumption data.

13. An electronic device, comprising: Comprise: A processor and a memory, the processor is used for executing the transformer area power consumption data analysis program stored in the memory, to realize the transformer area power consumption data analysis method in any one of claims 1-11.

14. A storage medium, characterized by The storage medium stores one or more programs, which can be executed by one or more processors to realize the transformer area power consumption data analysis method in any one of claims 1-11.

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