CN115034927A - Data processing method and device, electronic equipment and storage medium - Google Patents
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Abstract
The invention discloses a data processing method, a data processing device, electronic equipment and a storage medium, wherein the method comprises the following steps: acquiring at least one piece of electricity utilization record data of each power distribution network feeder line associated with a target area; determining abnormal record data in the at least one piece of electricity consumption record data, and performing field filling and/or record deletion on the abnormal record data to obtain at least one piece of electricity consumption record data to be processed, wherein the abnormal record data is data with empty contents of at least one field; determining heavy overload recorded data of corresponding power distribution network feeder lines according to the electricity utilization recorded data to be processed; the heavy overload recording data is data with the power utilization load rate larger than a preset load rate threshold value; and generating a heavy overload record report of the target area based on the heavy overload record data, and analyzing the target area based on the heavy overload record report. According to the technical scheme of the embodiment of the invention, the distribution network dispatching work efficiency is improved, and the effect of the safe operation level of the distribution network is improved.
Description
Technical Field
The invention relates to the technical field of distribution network data analysis, in particular to a data processing method and device, electronic equipment and a storage medium.
Background
With the continuous enlargement of the distribution network scale, the rapid increase of social economy and the continuous improvement of the living standard of residents, the increasing of the power utilization load is caused, and the rapid mastering of the load condition of the distribution network equipment becomes an important means for reducing the faults of the distribution network equipment and the economic loss of users and the complaint work orders.
At present, in order to strengthen the load operation control of distribution network equipment, a distribution network dispatching desk needs to export overload data from a plurality of systems every day, manually screens the data and compiles a distribution network equipment overload detailed list after uniform formats, so that the working efficiency is low, and the normal operation of other dispatching services is influenced.
Disclosure of Invention
The invention provides a data processing method, a data processing device, electronic equipment and a storage medium, which are used for reducing the workload of distribution network scheduling personnel, improving the distribution network scheduling work efficiency and improving the effect of the safe operation level of a distribution network while strengthening the heavy overload management and control of distribution network equipment.
According to an aspect of the present invention, there is provided a data processing method, the method including:
acquiring at least one piece of electricity utilization record data of each power distribution network feeder line associated with a target area;
determining abnormal record data in the at least one piece of electricity consumption record data, and performing field filling and/or record deletion on the abnormal record data to obtain at least one piece of electricity consumption record data to be processed, wherein the abnormal record data is data with empty contents of at least one field;
determining heavy overload recorded data of corresponding power distribution network feeder lines according to the electricity utilization recorded data to be processed; the heavy overload recording data is data with the power utilization load rate larger than a preset load rate threshold value;
and generating a heavy overload record report of the target area based on the heavy overload record data, and analyzing the target area based on the heavy overload record report.
According to another aspect of the present invention, there is provided a data processing apparatus comprising:
the data acquisition module is used for acquiring at least one piece of electricity utilization record data of each power distribution network feeder line associated with the target area;
the data processing module is used for determining abnormal record data in the at least one piece of electricity utilization record data, and performing field filling and/or record deletion on the abnormal record data to obtain at least one piece of electricity utilization record data to be processed, wherein the abnormal record data is data with at least one field with empty content;
the heavy overload record data determining module is used for determining heavy overload record data of a corresponding power distribution network feeder line according to each piece of to-be-processed electricity utilization record data, wherein the heavy overload record data are data with an electricity utilization load rate larger than a preset load rate threshold value;
and the heavy overload record report generation module is used for generating a heavy overload record report of the target area based on the heavy overload record data so as to analyze the target area based on the heavy overload record report.
According to another aspect of the present invention, there is provided an electronic apparatus including:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,
the memory stores a computer program executable by the at least one processor, the computer program being executable by the at least one processor to enable the at least one processor to perform the data processing method according to any of the embodiments of the present invention.
According to another aspect of the present invention, there is provided a computer-readable storage medium storing computer instructions for causing a processor to implement a data processing method according to any one of the embodiments of the present invention when the computer instructions are executed.
The technical scheme of the embodiment of the invention solves the problems that overload data needs to be exported from a plurality of systems every day, overload detailed lists of distribution network equipment are compiled after data are manually screened and in a unified format, the working efficiency is low, the normal operation of other scheduling services is influenced and the like in the prior art by acquiring at least one piece of electricity consumption record data of each distribution network feeder line associated with a target area, then determining abnormal record data in the at least one piece of electricity consumption record data, carrying out field filling and/or record deletion on the abnormal record data to obtain at least one piece of electricity consumption record data to be processed, further determining heavy overload record data of the corresponding distribution network feeder line according to the electricity consumption record data to be processed, finally generating a heavy overload record report form of the target area based on the heavy overload record data, and analyzing the target area based on the heavy overload record report form, the method and the device realize that the workload of distribution network scheduling personnel is reduced while the heavy overload management and control of the distribution network equipment are enhanced, improve the distribution network scheduling work efficiency and improve the effect of the safe operation level of the distribution network.
It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present invention, nor do they necessarily limit the scope of the invention. Other features of the present invention will become apparent from the following description.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the description below are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a flowchart of a data processing method according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a data processing apparatus according to a second embodiment of the present invention;
fig. 3 is a schematic structural diagram of an electronic device implementing the data processing method according to the embodiment of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Moreover, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Example one
Fig. 1 is a flowchart of a data processing method, which is applicable to a situation where a heavy overload condition of a feeder line of a power distribution network is statistically analyzed according to an embodiment of the present invention, and the method may be executed by a data processing device, where the data processing device may be implemented in a form of hardware and/or software, and the data processing device may be configured in a terminal and/or a server. As shown in fig. 1, the method includes:
and S110, acquiring at least one piece of electricity utilization record data of each distribution network feeder line associated with the target area.
In this embodiment, the target area may be any area that needs to be subjected to the electricity usage record statistical analysis. For example, the target area may be a city, a county, or an enterprise with a large demand for electricity. A distribution feeder may be understood as a branch connected to any distribution node, which may be a feed-in branch or a feed-out branch. The feeder line, which may also be referred to as a cable line, is used to efficiently transfer signal energy, power from a transmitter to the input of a transmitting antenna with minimal loss, or signals received by an antenna to the input of a receiver with minimal loss. Illustratively, the distribution feeder may be a 10 kilovolt feeder. The recorded electricity consumption data can be understood as the power load situation of the electricity consumers connected to the corresponding distribution network feeder. The electricity utilization record data can be used for reflecting the transmission power, the transmission current, the transmission time, the safety circuit value, the affiliated operation and maintenance area information and the like of the current power distribution network feeder line. Illustratively, the electricity utilization record data includes a name of a feeder line, a name of a local office to which the feeder line belongs, a name of a service center to which the feeder line belongs, a maximum current value, a safe current value, feeder line alarm information, and the like.
It should be noted that, when operating, each power consumption device may be transmitted to the power distribution automation master station system or the power distribution platform through the corresponding power distribution network feeder, so that the system may perform data processing and analysis on the power consumption load data transmitted by each power distribution network feeder, and generate corresponding power consumption record data, and when acquiring the power consumption record data, the power consumption record data of each power distribution network feeder may be acquired from the power distribution automation master station or the power distribution platform associated with the target area through the data interface.
Specifically, when the power consumption load condition of the power distribution network equipment in the target area is subjected to data analysis, at least one piece of power consumption record data of each distribution network feeder line associated with the target area is acquired, and the power consumption equipment load condition of the target area is determined by performing corresponding data processing analysis on the acquired relevant power consumption record data.
S120, determining abnormal record data in the at least one piece of electricity utilization record data, and performing field filling and/or record deletion on the abnormal record data to obtain at least one piece of electricity utilization record data to be processed.
The abnormal record data is data with at least one field with null value. In general, due to the fact that part of signals of a power distribution network feeder line are lost in the signal transmission process, or due to the fact that part of electric equipment breaks down to cause obvious abnormality of electric data, after all electric record data are obtained, the electric record data need to be screened according to preset screening conditions, and the screened record data can be used as abnormal record data. Field filling may be understood as filling in portions of the exception record data where a field is missing or null with the corresponding field contents. The to-be-processed electricity consumption record data can be understood as data which can be subjected to subsequent data processing after each acquired electricity consumption record data is subjected to preprocessing.
In practical application, due to the fault problem of the power consumption equipment, partial signal loss during signal transmission of a feeder line of a power distribution network, other factors and the like, abnormal record data with a plurality of data fields having lost contents or null values exist in each piece of power consumption record data, so after each piece of power consumption record data is obtained, the abnormal record data needs to be screened, and different data processing is respectively carried out on the abnormal record data according to different fields with null values in the abnormal record data.
Optionally, determining abnormal record data in the electricity consumption record data, and performing field filling and/or deleting on the abnormal record data, including: determining abnormal recorded data lacking non-key fields in the electricity consumption recorded data, comparing the abnormal recorded data with a heavy overload record historical report form of a target area, and performing field filling processing on the abnormal recorded data; and determining abnormal record data lacking the key fields in the electricity utilization record data, and performing record deletion processing on the abnormal record data.
In this embodiment, the non-critical field may be understood as a data field that can be inferred from the contents of other fields in the electricity consumption record data. Illustratively, the non-critical fields may include, but are not limited to, a name of a local office to which the feeder belongs, a name of a service center to which the feeder belongs, and the like. In practical application, the absence of the non-critical fields does not have great influence on the data analysis result of the electricity utilization record data. The heavy overload record history report can be understood as a table for recording the heavy overload condition of each distribution network feeder line in a certain historical time period in a target area. For example, the overload history report may dynamically display data in a table or a chart format. It should be noted that the heavily overloaded historical record report may be obtained in a local database, may also be obtained through an external device, and may also be obtained through other manners, which is not limited in this embodiment.
In the present embodiment, the key field can be understood as a data field whose field content is decisive for the analysis of the electricity consumption record data. Illustratively, the key fields may include, but are not limited to, a feeder name, a maximum current value, a safe current value, and feeder alarm information, among others. In practical application, when the content of a feeder name field in certain electricity consumption record data is a null value, the electricity consumption record data cannot be judged to correspond to the feeder of the power distribution network according to the content of other fields, and further, data analysis cannot be performed on the electricity consumption record data; when the content of the field with the maximum current value in a certain piece of electricity consumption record data is a null value, whether the power distribution network feeder line corresponding to the electricity consumption record data is overloaded or not can not be determined according to the content of other fields, and data analysis can not be performed on the electricity consumption record data.
Specifically, after the electricity consumption record data corresponding to each distribution network feeder line is obtained, abnormal record screening needs to be performed on the electricity consumption record data, the screened abnormal record data are divided into abnormal record data lacking a non-key field and abnormal record data lacking a key field according to different content missing fields, and further, on one hand, the abnormal record data lacking the non-key field can be compared with a heavy overload record historical report form of the target area, the corresponding electricity consumption record data are determined in the heavy overload record historical report form according to the content of other data fields in the abnormal record data, and the abnormal record data are subjected to field filling processing according to the electricity consumption record data; on the other hand, for abnormal recorded data lacking the key field, since the specific content of the missing field cannot be determined by the content of other fields, in order to continue data analysis on the electricity consumption recorded data in the following, it is necessary to perform record deletion processing on the abnormal recorded data to avoid influencing the data analysis result, and after field filling and record deletion processing, each piece of electricity consumption recorded data to be processed can be obtained, so that the electricity consumption condition of the target area can be analyzed according to the electricity consumption recorded data to be processed.
And S130, determining heavy overload recorded data of the corresponding power distribution network feeder line according to the electricity utilization recorded data to be processed.
In this embodiment, the heavy overload record data can be understood as electricity utilization record data used for representing that the feeder line of the power distribution network is overloaded, so that electricity which greatly exceeds the safe current of the line flows on the line. It should be noted that, when the distribution network automation master station collects the electricity consumption record data corresponding to each distribution network feeder, after the maximum value of the transmission current of a certain distribution network feeder continuously exceeds the safe current of the distribution network feeder for a period of time, alarm information corresponding to the distribution network feeder is generated and recorded in the electricity consumption record data in a text form.
Optionally, determining heavy overload record data corresponding to each distribution network feeder line according to each piece of to-be-processed electricity consumption record data includes: determining a maximum current attribute and a safe current attribute in each piece of electricity consumption record data to be processed, and determining electricity consumption load rates corresponding to each distribution network feeder line based on the maximum current attribute and the safe current attribute; and sequencing the electricity utilization record data to be processed according to the electricity utilization load rate, and deleting the electricity utilization record data to be processed, of which the electricity utilization load rate is less than or equal to a preset load rate threshold value, so as to obtain heavy overload record data corresponding to each power distribution network feeder line.
The maximum current property can be understood as the maximum current value transmitted by the feeder of the corresponding distribution network. The safe current property can be understood as the maximum load current corresponding to the feeder of the corresponding distribution network. It should be noted that the safe current attribute is related to the type, specification, ambient temperature and laying mode of the feeder line of the corresponding distribution network. The power consumption rate can be understood as the ratio between the actual transmission current and the rated transmission current of the feeder of the distribution network. The power utilization load rate can be used for representing the load condition of the corresponding distribution network feeder line. The preset load rate threshold may be understood as a lowest value of heavy overload load rates that is preset to determine whether the distribution feeder is heavily overloaded. For example, the preset load rate threshold may be 80%.
Specifically, after obtaining each piece of electricity utilization record data to be processed, the maximum current attribute and the safe current attribute in each piece of electricity utilization record data to be processed are obtained, the ratio between each maximum current attribute and each safe current attribute is respectively determined, the power utilization load rate of the corresponding power distribution network feeder line can be obtained, and further, according to the numerical value of each power utilization load rate, sorting the electricity consumption record data to be processed, deleting the electricity consumption record data to be processed with the electricity load rate less than or equal to the preset load rate threshold value, only keeping the electricity consumption record data to be processed with the electricity load rate greater than the preset load rate threshold value, and the reserved electricity utilization record data is used as heavy overload record data corresponding to the corresponding feeder line of the distribution network, so that the distribution heavy overload analysis can be carried out on the corresponding distribution network feeder and the electric equipment according to the heavy overload record data.
And S140, generating a heavy and overload record report of the target area based on the heavy and overload record data, and analyzing the target area based on the heavy and overload record report.
In the present embodiment, the heavy overload record report may be understood as a specific format of electricity usage record data statistical table for characterizing heavy overload situations of each distribution feeder line associated with the target area. For example, the format of the heavy overload record report may be that each piece of electricity consumption record data is counted according to the local office to which the feeder belongs, the service center to which the feeder belongs, the name of the feeder, the maximum current value, the safe current value, and the electricity consumption load rate.
In practical application, in order to facilitate statistical analysis of the heavy overload condition of the power distribution network feeder line in a target area, the obtained heavy overload recorded data can be sorted out in a chart form, and a report form in a preset format is generated, so that power distribution operation and maintenance personnel can timely master the power consumption load condition of the corresponding power distribution network feeder line according to the data information displayed in the report form.
Optionally, generating a heavy overload record report of the target area based on the heavy overload record data includes: and acquiring a heavy overload record report template in a target format, and mapping heavy overload record data to the heavy overload record report template to obtain a heavy overload record report.
The target format can be understood as a predefined report format. The heavy overload record report form template can be understood as a standardized form according to which the heavy overload record data need to be counted.
Specifically, when generating a corresponding heavy overload record report based on the heavy overload record data, a heavy overload record report template in a target format may be obtained first, and further, each heavy overload record data is imported into the template, so that a corresponding heavy overload record report may be obtained, so that the power distribution load condition of the target area may be analyzed according to the heavy overload record report.
Optionally, analyzing the target area based on the heavy overload record report includes: processing the heavy overload record report according to the statistical function and the sorting function, determining the number of heavy overload records corresponding to at least one power supply area in the target area, and generating heavy overload prompt information based on the number of the heavy overload records; and displaying the heavy overload prompt information on a display interface of the target terminal according to a preset prompt form.
The statistical function may be a function of counting the number of cells in the specified area that meet the specified condition in the data statistical analysis program. Illustratively, the statistical function may be a specified summation (Countif) function. The sorting function may be a function used in a data statistical analysis program to sort a list of numbers in a descending order or an ascending order. Illustratively, the ranking function may be a RANK function. The heavy overload prompting information can be understood as information for prompting the relevant operation and maintenance personnel about the heavy overload condition of each distribution network feeder. The preset prompting mode can be understood as a preset heavy overload warning prompting mode. For example, the preset prompting form may include scrolling display on a website home page, short message prompting, power distribution main station voice prompting and the like. Correspondingly, the target terminal may be a display terminal of the power distribution main station, or may be a fixed terminal of a related operation and maintenance worker, such as a computer, or a mobile terminal, such as a mobile phone, a tablet computer, or the like.
Specifically, after the heavily and overloaded recording report in the target format is generated based on the heavily and overloaded recording data, since the report contains all the heavily and overloaded recording data associated with the target area, in order to accurately analyze the power distribution heavy overload condition of the target area, the heavy overload record report can be optimized, and by adopting a statistical function, calculating the number of the heavy overload records corresponding to each power supply area office in the report, further, sequencing each power supply area office counted by adopting a sequencing function according to the number of the heavy overload records corresponding to the power supply area office, generating heavy overload prompt information comprising the name of the power supply area office and the corresponding number of the heavy overload records, and the prompt information is displayed on a display interface of the target terminal in a preset overload warning mode, so that related personnel can take overload countermeasures in time.
It should be noted that, the distribution network electric equipment is usually in an operating state every day, so that the corresponding distribution network feeder line needs to transmit current every day, and therefore, the heavy overload record report needs to be published on the corresponding display interface every day, so that the heavy overload condition of the distribution network feeder line on the same day can be processed, and in order to perform statistical analysis on the historical heavy overload condition of the corresponding distribution network feeder line in the target area, the heavy overload record report generated every day needs to be stored, so that the heavy overload record report can be extracted at any time later.
On the basis of the technical scheme, the method further comprises the following steps: and correspondingly storing the heavy overload record report and the report generation date, and storing the heavy overload record report and the report generation date into a database.
Specifically, after the heavy overload record report is obtained, the corresponding relationship between the heavy overload record report and the corresponding report generation date is established and is correspondingly stored in the database. For example, the heavy overload record report can be generated into a file named by the report generation date and stored in the database.
On the basis of the technical scheme, the method further comprises the following steps: the data processing method can be realized based on VBA programming.
The VBA (visual Basic for applications) programming is a general automation language of an application program, can be used for expanding functions of the application program, provides an object-oriented programming method and provides a quite complete programming language.
It should be noted that, the intelligent recognition algorithm is realized based on VBA programming, the data processing method can be executed in office software, various power consumption record data derived by the system can be automatically adapted, the method can be used in the batch processing scene of similar reports, and dynamic maintenance of heavy overload record reports is more convenient in the later period.
The technical scheme of the embodiment of the invention solves the problems that overload data needs to be exported from a plurality of systems every day, overload detailed lists of distribution network equipment are compiled after data are manually screened and in a unified format, the working efficiency is low, the normal operation of other scheduling services is influenced and the like in the prior art by acquiring at least one piece of electricity consumption record data of each distribution network feeder line associated with a target area, then determining abnormal record data in the at least one piece of electricity consumption record data, carrying out field filling and/or record deletion on the abnormal record data to obtain at least one piece of electricity consumption record data to be processed, further determining heavy overload record data of the corresponding distribution network feeder line according to the electricity consumption record data to be processed, finally generating a heavy overload record report form of the target area based on the heavy overload record data, and analyzing the target area based on the heavy overload record report form, the method and the device realize that the workload of distribution network scheduling personnel is reduced while the heavy overload management and control of the distribution network equipment are enhanced, improve the distribution network scheduling work efficiency and improve the effect of the safe operation level of the distribution network.
Example two
Fig. 2 is a schematic structural diagram of a data processing apparatus according to a second embodiment of the present invention. As shown in fig. 2, the apparatus includes: the data acquisition module 210, the data processing module 220, the overload record data determination module 230 and the overload record report generation module 240.
The data acquisition module 210 is configured to acquire at least one piece of electricity consumption record data of each distribution network feeder line associated with the target area;
the data processing module 220 is configured to determine abnormal record data in the at least one piece of electricity consumption record data, and perform field filling and/or record deletion on the abnormal record data to obtain at least one piece of electricity consumption record data to be processed, where the abnormal record data is data with at least one field empty;
a heavy overload record data determining module 230, configured to determine heavy overload record data of a corresponding power distribution network feeder according to each piece of to-be-processed power consumption record data, where the heavy overload record data is data in which a power consumption load rate is greater than a preset load rate threshold;
a heavy overload record report generating module 240, configured to generate a heavy overload record report of the target area based on the heavy overload record data, so as to analyze the target area based on the heavy overload record report.
The technical scheme of the embodiment of the invention solves the problems that overload data needs to be exported from a plurality of systems every day, overload detailed lists of distribution network equipment are compiled after data are manually screened and in a unified format, the working efficiency is low, the normal operation of other scheduling services is influenced and the like in the prior art by acquiring at least one piece of electricity consumption record data of each distribution network feeder line associated with a target area, then determining abnormal record data in the at least one piece of electricity consumption record data, carrying out field filling and/or record deletion on the abnormal record data to obtain at least one piece of electricity consumption record data to be processed, further determining heavy overload record data of the corresponding distribution network feeder line according to the electricity consumption record data to be processed, finally generating a heavy overload record report form of the target area based on the heavy overload record data, and analyzing the target area based on the heavy overload record report form, the method and the device realize that the workload of distribution network scheduling personnel is reduced while the heavy overload management and control of the distribution network equipment are enhanced, improve the distribution network scheduling work efficiency and improve the effect of the safe operation level of the distribution network.
Optionally, the data processing module 220 includes a field filling processing unit and a record deleting processing unit.
The field filling processing unit is used for determining abnormal record data lacking non-key fields in each piece of electricity consumption record data, comparing the abnormal record data with a heavy overload record historical report form of a target area, and performing field filling processing on the abnormal record data; and the record deletion processing unit is used for determining abnormal record data which lack key fields in the electricity utilization record data and performing record deletion processing on the abnormal record data.
Optionally, the heavy overload record data determining module 230 includes an electricity utilization load rate determining unit and a heavy overload record data determining unit.
The power consumption load rate determining unit is used for determining the maximum current attribute and the safe current attribute in the power consumption record data to be processed and determining the power consumption load rate corresponding to each power distribution network feeder line based on the maximum current attribute and the safe current attribute; and the heavy overload record data determining unit is used for sequencing the electricity consumption record data to be processed according to the electricity consumption load rate, and deleting the electricity consumption record data to be processed, of which the electricity consumption load rate is less than or equal to a preset load rate threshold value, so as to obtain the heavy overload record data corresponding to the corresponding power distribution network feeder line.
Optionally, the heavy overload record report generating module 240 is further configured to obtain a heavy overload record report template in a target format, and map the heavy overload record data to the heavy overload record report template to obtain a heavy overload record report.
Optionally, the heavy overload record report generating module 240 includes a heavy overload record number determining unit and a heavy overload prompt information displaying unit.
The heavy overload record quantity determining unit is used for processing the heavy overload record report according to the statistical function and the sorting function, determining the heavy overload record quantity corresponding to at least one power supply area in the target area, and generating heavy overload prompt information based on the heavy overload record quantity; and the heavy overload prompt information display unit is used for displaying the heavy overload prompt information on a display interface of the target terminal according to a preset prompt form.
Optionally, the apparatus further comprises: and the heavy overload record report storage module is used for correspondingly storing the heavy overload record report and the report generation date and storing the heavy overload record report and the report generation date into the database.
Optionally, the method is implemented based on VBA programming.
The data processing device provided by the embodiment of the invention can execute the data processing method provided by any embodiment of the invention, and has corresponding functional modules and beneficial effects of the execution method.
EXAMPLE III
FIG. 3 illustrates a block diagram of an electronic device 10 that may be used to implement an embodiment of the invention. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smart phones, 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 meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed herein.
As shown in fig. 3, the electronic device 10 includes at least one processor 11, and a memory communicatively connected to the at least one processor 11, such as a Read Only Memory (ROM)12, a Random Access Memory (RAM)13, and the like, wherein the memory stores a computer program executable by the at least one processor, and the processor 11 can perform various suitable actions and processes according to the computer program stored in the Read Only Memory (ROM)12 or the computer program loaded from a storage unit 18 into the Random Access Memory (RAM) 13. In the RAM 13, various programs and data necessary for the operation of the electronic apparatus 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other via a bus 14. An input/output (I/O) interface 15 is also connected to bus 14.
A number of components in the electronic device 10 are connected to the I/O interface 15, including: an input unit 16 such as a keyboard, a mouse, or the like; an output unit 17 such as various types of displays, speakers, and the like; a storage unit 18 such as a magnetic disk, an optical disk, or the like; and a communication unit 19 such as a network card, modem, wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information/data with other devices via a computer network such as the internet and/or various telecommunication networks.
The processor 11 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various processors running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, or the like. The processor 11 performs the various methods and processes described above, such as data processing methods.
In some embodiments, the data processing method may be implemented as a computer program tangibly embodied in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 10 via the ROM 12 and/or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the data processing method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the data processing method by any other suitable means (e.g. by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, Field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), system on a chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.
A computer program for implementing 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, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions/acts specified in the flowchart and/or block diagram block or blocks to be performed. A computer program can execute entirely on a machine, partly on a machine, as a stand-alone software package partly on a machine and partly on a remote machine or entirely on a remote machine or server.
In the context of the present invention, a computer-readable storage medium may be a tangible medium that can contain, or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. A computer readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, the computer readable storage medium may be a machine readable signal medium. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here 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 a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the electronic device. Other kinds of devices may also be used to provide for interaction with a 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 may be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), blockchain networks, and the internet.
The computing system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical host and VPS service are overcome.
It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present invention may be executed in parallel, sequentially, or in different orders, and are not limited herein as long as the desired results of the technical solution of the present invention can be achieved.
The above-described embodiments should not be construed as limiting the scope of the invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A method of data processing, comprising:
acquiring at least one piece of electricity utilization record data of each power distribution network feeder line associated with a target area;
determining abnormal record data in the at least one piece of electricity consumption record data, and performing field filling and/or record deletion on the abnormal record data to obtain at least one piece of electricity consumption record data to be processed, wherein the abnormal record data is data with at least one field with empty content;
determining heavy overload recorded data of corresponding power distribution network feeder lines according to the to-be-processed electricity consumption recorded data; the heavy overload recording data are data with an electric load rate larger than a preset load rate threshold value;
and generating a heavy overload record report of the target area based on the heavy overload record data, and analyzing the target area based on the heavy overload record report.
2. The method according to claim 1, wherein the determining abnormal record data in the at least one piece of electricity consumption record data and performing field filling and/or deleting on the abnormal record data comprises:
determining abnormal record data lacking non-key fields in the electricity consumption record data, comparing the abnormal record data with a heavy overload record historical report form of the target area, and performing field filling processing on the abnormal record data; and the number of the first and second groups,
and determining abnormal record data lacking key fields in the electricity utilization record data, and performing record deletion processing on the abnormal record data.
3. The method according to claim 1, wherein the determining heavy overload record data of the feeder line of the corresponding distribution network according to the electricity consumption record data to be processed comprises:
determining a maximum current attribute and a safe current attribute in each piece of electricity record data to be processed, and determining electricity load rates corresponding to each distribution network feeder line based on the maximum current attribute and the safe current attribute;
and sequencing each piece of electricity utilization record data to be processed according to the electricity utilization load rate, and deleting the electricity utilization record data to be processed, of which the electricity utilization load rate is smaller than or equal to a preset load rate threshold value, so as to obtain heavy overload record data corresponding to the corresponding power distribution network feeder line.
4. The method according to claim 1, wherein generating a re-overload record report of the target area based on the re-overload record data comprises:
and acquiring a heavy overload record report template in a target format, and mapping the heavy overload record data to the heavy overload record report template to obtain the heavy overload record report.
5. The method of claim 1, wherein analyzing the target area based on the re-overload record report comprises:
processing the heavy overload record report according to a statistical function and a sorting function, determining the number of heavy overload records corresponding to at least one power supply area in the target area, and generating heavy overload prompt information based on the number of heavy overload records;
and displaying the heavy overload prompt information on a display interface of the target terminal according to a preset prompt form.
6. The method of claim 1, further comprising:
and correspondingly storing the heavy overload record report and the report generation date, and storing the heavy overload record report and the report generation date into a database.
7. The method of claim 1, wherein the method is implemented based on VBA programming.
8. A data processing apparatus, comprising:
the data acquisition module is used for acquiring at least one piece of electricity utilization record data of each power distribution network feeder line associated with the target area;
the data processing module is used for determining abnormal record data in the at least one piece of electricity consumption record data, and performing field filling and/or record deletion on the abnormal record data to obtain at least one piece of electricity consumption record data to be processed, wherein the abnormal record data is data with empty content of at least one field;
the heavy overload record data determining module is used for determining heavy overload record data of a corresponding power distribution network feeder line according to the to-be-processed power consumption record data, wherein the heavy overload record data are data of which the power consumption load rate is greater than a preset load rate threshold value;
and the heavy overload record report generation module is used for generating a heavy overload record report of the target area based on the heavy overload record data so as to analyze the target area based on the heavy overload record report.
9. An electronic device, characterized in that the electronic device comprises:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,
the memory stores a computer program executable by the at least one processor, the computer program being executable by the at least one processor to enable the at least one processor to perform the data processing method of any one of claims 1-7.
10. A computer-readable storage medium, characterized in that it stores computer instructions for causing a processor to implement the data processing method of any of claims 1-7 when executed.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117293816A (en) * | 2023-10-10 | 2023-12-26 | 国网浙江省电力有限公司金华供电公司 | High-interconnection high-self-healing intelligent power distribution network construction method |
| CN117874306A (en) * | 2024-03-12 | 2024-04-12 | 北京全路通信信号研究设计院集团有限公司 | Engineering data source processing method and device, electronic equipment and storage medium |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117293816A (en) * | 2023-10-10 | 2023-12-26 | 国网浙江省电力有限公司金华供电公司 | High-interconnection high-self-healing intelligent power distribution network construction method |
| CN117874306A (en) * | 2024-03-12 | 2024-04-12 | 北京全路通信信号研究设计院集团有限公司 | Engineering data source processing method and device, electronic equipment and storage medium |
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