CN114024302A - Method and device for evaluating distribution room - Google Patents
Method and device for evaluating distribution room Download PDFInfo
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- CN114024302A CN114024302A CN202111123893.5A CN202111123893A CN114024302A CN 114024302 A CN114024302 A CN 114024302A CN 202111123893 A CN202111123893 A CN 202111123893A CN 114024302 A CN114024302 A CN 114024302A
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
Abstract
The embodiment of the invention provides a method and a device for evaluating a transformer area, and belongs to the technical field of electric power. The method for evaluating the station area comprises the following steps: acquiring original power data of a distribution room in a preset evaluation period; obtaining the potential attributes of the transformer area according to the original power data; determining a label type corresponding to the potential attribute of the platform area, wherein the label type comprises a positive label and a negative label; and obtaining an image of the platform area according to the proportion of the potential attributes of the platform area and the frequency of the label type so as to evaluate the platform area. By adopting the scheme of the invention, the evaluation accuracy of the transformer area can be improved.
Description
Technical Field
The invention relates to the technical field of electric power, in particular to a method and a device for evaluating a transformer area.
Background
With the deepening of power reform and the continuous improvement of informatization level, the lean level of the transformer area management is increased day by day, and the comprehensive evaluation of the transformer area guides the comprehensive management of the transformer area to a certain extent. The comprehensive evaluation of the transformer area involves a plurality of directions and dimensions, the index selection is complex, the existing comprehensive evaluation system of the transformer area is difficult to objectively and comprehensively evaluate the comprehensive state of the transformer area, the comprehensive condition of the transformer area cannot be accurately evaluated, and the problem of inaccurate evaluation exists.
Disclosure of Invention
The invention aims to provide a method and a device for evaluating a transformer area, which aim to solve the problem that the conventional transformer area evaluation is not accurate enough.
In order to achieve the above object, a first aspect of the present invention provides a method for evaluating a station area, the method comprising:
acquiring original power data of a distribution room in a preset evaluation period;
obtaining the potential attributes of the transformer area according to the original power data;
determining a label type corresponding to the potential attribute of the platform area, wherein the label type comprises a positive label and a negative label;
and obtaining an image of the platform area according to the proportion of the potential attributes of the platform area and the frequency of the label type so as to evaluate the platform area.
In an embodiment of the invention, the platform zone potential attribute comprises at least one of the following: the system comprises a line loss rate, a platform area load, a platform area power supply reliability, a power failure time, a power restoration time, a three-phase imbalance, a voltage qualification rate, electric energy quality, an electric charge recovery rate and customer satisfaction.
In the embodiment of the present invention, obtaining the platform area potential attribute according to the raw power data includes: and determining the potential attributes of the transformer area according to the original power data and the pre-stored service rule.
In the embodiment of the present invention, determining a tag type corresponding to a platform area potential attribute includes: and comparing the potential attributes of the transformer area with a preset threshold value to determine the type of the label corresponding to the potential attributes of the transformer area.
In the embodiment of the present invention, comparing the platform area potential attribute with a preset threshold to determine a tag type corresponding to the platform area potential attribute includes: determining the label type corresponding to the platform area potential attribute as a front label under the condition that the platform area potential attribute is greater than or equal to a preset threshold value; and under the condition that the potential attribute of the transformer area is smaller than a preset threshold value, determining that the type of the label corresponding to the potential attribute of the transformer area is a negative label.
In an embodiment of the present invention, obtaining an image of the platform area according to the weight of the platform area potential attribute and the frequency of the tag type includes: determining the multiplying power of the label type according to the frequency of the label type; determining the weight of the label type according to the proportion of the platform area potential attribute, the preset basic score of the platform area potential attribute and the multiplying power of the label type; and obtaining the image of the platform area according to the weight of the label type.
In the embodiment of the present invention, determining the multiplying power of the tag type according to the frequency of the tag type includes: and determining the multiplying power of the label type according to the frequency of the label type and a preset evaluation period.
In this embodiment of the present invention, before obtaining the platform area potential attribute according to the raw power data, the method further includes: and cleaning the original power data.
In the embodiment of the present invention, determining the weight of the tag type according to the specific gravity of the platform area potential attribute, the preset base score, and the multiplying power of the tag type includes: and determining the product of the specific gravity of the platform potential attribute, the preset basic score of the platform potential attribute and the multiplying power of the label type to determine the weight of the label type.
A second aspect of the present invention provides an apparatus for evaluating a station area, the apparatus comprising:
the system comprises an original data acquisition module, a data processing module and a data processing module, wherein the original data acquisition module is used for acquiring original power data of a distribution room in a preset evaluation period;
the station area potential attribute determining module is used for obtaining station area potential attributes according to the original power data;
the system comprises a tag type determining module, a tag identification module and a tag identification module, wherein the tag type determining module is used for determining a tag type corresponding to a potential attribute of a platform area, and the tag type comprises a positive tag and a negative tag;
and the platform area evaluation module is used for obtaining an image of the platform area according to the specific gravity of the potential attributes of the platform area and the frequency of the label type so as to evaluate the platform area.
According to the technical scheme, the original power data of the transformer area in the preset evaluation period are obtained, the potential attribute of the transformer area is obtained according to the original power data, the label type corresponding to the potential attribute of the transformer area is further determined, the portrait of the transformer area is obtained according to the proportion of the potential attribute of the transformer area and the frequency of the label type, and the transformer area is evaluated. According to the technical scheme, the potential attributes of the transformer area are mined through comprehensive analysis of transformer area data, the characteristics of the potential attributes of the transformer area are extracted, the label types corresponding to the potential attributes of the transformer area are obtained, accurate transformer area portrait is constructed according to the proportion of the potential attributes of the transformer area and the frequency of the label types, accurate evaluation of the comprehensive state of the transformer area can be achieved through the accurate transformer area portrait, and the accuracy of transformer area evaluation is improved.
Additional features and advantages of embodiments of the invention will be set forth in the detailed description which follows.
Drawings
The accompanying drawings, which are included to provide a further understanding of the embodiments of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the embodiments of the invention without limiting the embodiments of the invention. In the drawings:
FIG. 1 schematically illustrates a flow diagram of a method for evaluating a distribution area in one embodiment of the invention;
FIG. 2 is a flow chart schematically illustrating the steps of obtaining a representation of a distribution area in one embodiment of the present invention;
fig. 3 schematically shows a block diagram of an apparatus for evaluating a station area according to an embodiment of the present invention.
Detailed Description
The following detailed description of embodiments of the invention refers to the accompanying drawings. It should be understood that the detailed description and specific examples, while indicating embodiments of the invention, are given by way of illustration and explanation only, not limitation.
Fig. 1 schematically shows a flow diagram of a method for evaluating a distribution room in an embodiment of the invention. As shown in fig. 1, in the embodiment of the present invention, a method for evaluating a cell is provided, which is described by taking a processor of a terminal as an example, and may include the following steps:
step S102, acquiring original power data of the distribution room in a preset evaluation period.
It is understood that the preset evaluation period is a preset evaluation time period, for example, 7 days or 30 days. The original power data are acquired by the transformer area acquisition equipment and comprise acquired table codes, voltage, current, power failure events and other original data. The region acquisition device may include, but is not limited to, an electric meter or a power terminal device.
Specifically, the processor may obtain raw power data (e.g., codes, voltages, currents, power failure events, etc.) of the distribution room in a preset evaluation period through a detection device such as an electric meter or a power terminal device.
And step S104, obtaining the potential attributes of the transformer area according to the original power data.
It can be understood that the potential attributes of the cell are attribute features of the cell, which need to be obtained through a certain calculation process, in addition to the basic attributes of the cell, for example, a line loss rate, which is a percentage of electric energy (line loss load) lost in the power network to electric energy (power supply load) supplied to the power network, and further, the number of the potential attributes of the cell may be multiple. The basic property of the transformer area is a property characteristic of the transformer area which is stored in advance and is not changed normally, and may include, but is not limited to, a type of the transformer area, a running time, a manufacturer of the transformer, an address of the transformer area, a type of the transformer area, and a unit of the transformer area. Understandably, the basic attribute can be only used for feature classification, and does not participate in the calculation of the station area image score.
Specifically, the processor may calculate, based on a corresponding algorithm, a corresponding platform potential attribute according to the acquired raw power data.
In one embodiment, the platform zone potential attributes may include at least one of: the system comprises a line loss rate, a platform area load, a platform area power supply reliability, a power failure time, a power restoration time, a three-phase imbalance, a voltage qualification rate, electric energy quality, an electric charge recovery rate and customer satisfaction.
In one embodiment, deriving the zone potential attributes from the raw power data comprises: and determining the potential attributes of the transformer area according to the original power data and the pre-stored service rule.
It can be understood that the pre-stored service rule is a preset and stored algorithm rule for calculating potential attributes of the distribution area according to the original power data, for example, an algorithm rule for calculating the power outage duration according to the power outage event, and an algorithm rule for calculating the voltage qualification rate according to the voltage data.
And step S106, determining the label type corresponding to the potential attribute of the platform area, wherein the label type comprises a positive label and a negative label.
It is understood that different platform zone potential attributes correspond to different tag types, including positive tags and negative tags, and the tag types of the line loss rate may include a high line loss rate and a low line loss rate, taking the line loss rate as an example. Further, in some embodiments, the tag type may also include a neutral tag, e.g., a tag type of line loss rate may also include a normal line loss rate.
Specifically, the processor may determine a tag type corresponding to the platform area potential attribute based on a preset algorithm.
In one embodiment, determining the type of the tag corresponding to the potential attribute of the platform area includes: and comparing the potential attributes of the transformer area with a preset threshold value to determine the type of the label corresponding to the potential attributes of the transformer area.
It is understood that the preset threshold is a preset reference value corresponding to each potential attribute of the station area, and the tag type may be determined based on the reference value.
Specifically, the processor may compare the platform area potential attribute with a pre-stored preset threshold to determine a tag type corresponding to the platform area potential attribute.
In one embodiment, comparing the platform area potential attribute with a preset threshold to determine a tag type corresponding to the platform area potential attribute includes: determining the label type corresponding to the platform area potential attribute as a front label under the condition that the platform area potential attribute is greater than or equal to a preset threshold value; and under the condition that the potential attribute of the transformer area is smaller than a preset threshold value, determining that the type of the label corresponding to the potential attribute of the transformer area is a negative label.
Specifically, the processor compares a platform potential attribute (e.g., a line loss rate) with a preset threshold, and if the platform potential attribute is greater than or equal to the preset threshold, the processor may determine that a tag type corresponding to the platform potential attribute is a positive tag (e.g., a low line loss rate); and determining that the type of the label corresponding to the platform area potential attribute is a negative label (for example, a high loss rate) when the platform area potential attribute is smaller than a preset threshold value.
And step S108, obtaining an image of the platform area according to the proportion of the platform area potential attribute and the frequency of the label type so as to evaluate the platform area.
It can be understood that the specific gravity of the potential attributes of the cell may be set according to actual service requirements, that is, different weights are given to the potential attributes of different cells according to the actual service requirements, for example, the specific gravity of the line loss rate is 1.5. Further, in some embodiments, the value range of the specific gravity of the potential property of the platform area may be 1-1.5. The frequency of the tag type is the number of times or days that the tag type appears in a preset evaluation period. The image of the platform area is used for showing the label characteristics of the platform area so as to comprehensively evaluate the platform area through the image of the platform area.
Specifically, the processor may obtain a representation of the platform area based on a weight of the platform area potential attribute and a frequency of the tag type to evaluate the platform area from the representation of the platform area.
According to the method for evaluating the transformer area, the original power data of the transformer area in the preset evaluation period are obtained, the potential attribute of the transformer area is obtained according to the original power data, the label type corresponding to the potential attribute of the transformer area is further determined, the image of the transformer area is obtained according to the proportion of the potential attribute of the transformer area and the frequency of the label type, and the transformer area is evaluated. According to the method, the station area data are comprehensively analyzed, the potential attributes of the station area are mined, the characteristic extraction is carried out on the potential attributes of the station area, the label type corresponding to the potential attributes of the station area is obtained, and then the accurate image of the station area is constructed according to the proportion of the potential attributes of the station area and the frequency of the label type, so that the accurate evaluation on the comprehensive state of the station area can be realized through the accurate image of the station area, and the accuracy of the evaluation on the station area is improved.
FIG. 2 is a flow chart schematically illustrating the steps of obtaining a typhoon area image according to an embodiment of the present invention. As shown in FIG. 2, in one embodiment, obtaining a representation of the plateau based on the specific gravity of the potential attribute of the plateau and the frequency of the tag type may include the steps of:
step S202, determining the multiplying power of the label type according to the frequency of the label type.
It can be understood that the multiplying power of the tag type is a relation coefficient determined according to the frequency of the tag type and a preset evaluation period.
In one embodiment, determining the multiplying power of the tag type according to the frequency of the tag type includes: and determining the multiplying power of the label type according to the frequency of the label type and a preset evaluation period.
Specifically, in the case that the type of the label is a front label, the magnification of the front label may be determined according to the frequency of the front label and a preset evaluation period, and specifically, the magnification of the front label may be determined with reference to the following formula:
multiplying power of the positive label is 1+ frequency of the positive label/preset evaluation period is 100%
The frequency of the front label may be the number of days of appearance of the front label in a preset evaluation period, and the preset evaluation period may be the number of days of the preset evaluation period.
When the type of the tag is a negative tag, the multiplying power of the negative tag can be determined according to the frequency of the negative tag and a preset evaluation period, and specifically, the multiplying power of the negative tag can be determined by referring to the following formula:
multiplying power of negative label (preset evaluation period-frequency of negative label)/preset evaluation period 100%
Wherein the frequency of the negative label may be the number of days in which the negative label appears within a preset evaluation period, and the preset evaluation period may be the number of days of the preset evaluation period.
And step S204, determining the weight of the label type according to the proportion of the platform potential attribute, the preset basic score of the platform potential attribute and the multiplying power of the label type.
It is understood that the preset base score of the platform potential attribute is a preset base score of the platform potential attribute, for example, 5 points. The weight of a label type is the fractional value of the label type in the representation.
In one embodiment, determining the weight of the tag type according to the specific gravity of the platform area potential attribute, the preset basic score and the multiplying power of the tag type comprises the following steps: and determining the product of the specific gravity of the platform potential attribute, the preset basic score of the platform potential attribute and the multiplying power of the label type to determine the weight of the label type.
Specifically, the weight of the tag type can be calculated with reference to the following formula:
weight of tag type ═ preset base score · weight of plateau potential attribute · magnification of tag type
The preset basic score of the potential attribute of the transformer area is, for example, 5 points, the specific gravity of the potential attribute of the transformer area can be set according to actual service requirements, for example, the specific gravity of the line loss rate is 1.5, and the multiplying power of the tag type is a relation coefficient determined according to the frequency of the tag type and a preset evaluation period, for example, 120%.
Step S206, obtaining the image of the platform area according to the weight of the label type.
Specifically, the processor may obtain the representation of the platform region according to the weight of the tag type, and further may perform cumulative summation on the weights of the tag types (i.e., the scores of the tags), thereby obtaining the representation score of the platform region.
In the embodiment of the invention, all the label score values of the potential attributes of the transformer area are calculated according to the algorithm formula, and the scores are obtained according to the multidimensional labels of the transformer area, so that the accurate evaluation of the transformer area can be obtained according to the final scores, and the accuracy of the comprehensive evaluation of the transformer area is improved.
In some embodiments, for the problem that the current relational data storage structure cannot meet the storage requirement of the growing mass data of the distribution area, the data can be stored by using a distributed scheme based on the access of a big data message middleware component to the archive data and the collected data of the distribution area to form a data source. Specifically, a combination scheme of NoSQL data + Hive may be adopted to implement data storage, where the NoSQL database is responsible for storing hotspot data (the collection period is data in the last 2 years), Hive is responsible for storing the whole amount of data, data in the NoSQL database is periodically synchronized into Hive for storage, and the synchronization time may be in the morning every day.
In one embodiment, before obtaining the potential property of the station area according to the raw power data, the method further comprises: and cleaning the original power data.
Understandably, the processor may also perform a cleaning of the raw power data before deriving the potential attributes of the station area from the raw power data. Aiming at the problem that the current data cleaning mode is difficult to meet the requirement of high-efficiency cleaning of data under the massive data scene, a large data batch processing technology can be used for cleaning a data source, a Spark + Impala scheme can be specifically adopted, data in NoSQL storage is loaded into a memory, a corresponding structured memory table is generated, and the data are cleaned, for example: and (3) aiming at the table code data, judging whether the table code is backward walking, flying or uneven in indicating value according to an abnormity diagnosis rule, and repairing the data under the load abnormal condition by adopting a completion rule, for example, using the average value of the table codes of the last seven days as the indicating value of the repaired table code.
In an embodiment, obtaining the platform area potential attribute according to the raw power data may specifically include: based on the collected table codes, voltage, current, power failure events and other original data, the data are calculated by utilizing big data calculation capacity, and the result data obtained after calculation are clustered by utilizing unsupervised learning algorithm model data to obtain the potential attributes of the transformer area.
In another embodiment of the present invention, a method for evaluating a station area is provided, which may include the steps of:
1. and accessing the file data and the collected data in the platform area based on the big data message middleware component, and storing the data by using a distributed scheme to form a data source.
Specifically, a combination scheme of NoSQL data + Hive may be adopted to implement data storage, where the NoSQL database is responsible for storing hotspot data (the collection period is data in the last 2 years), Hive is responsible for storing the whole amount of data, data in the NoSQL database is periodically synchronized into Hive for storage, and the synchronization time may be in the morning every day.
2. Cleaning a data source by using a big data batch processing technology; and comprehensively analyzing the data of the transformer area by utilizing a deep learning technology, mining potential attributes of the transformer area, and generating specific gravity for the attributes according to business requirements.
Specifically, a Spark + Impala scheme may be adopted to load data in the NoSQL storage into the memory, generate a corresponding structured memory table, and clean the data, for example: and (3) aiming at the table code data, judging whether the table code is backward walking, flying or uneven in indicating value according to an abnormity diagnosis rule, and repairing the data under the load abnormal condition by adopting a completion rule, for example, using the average value of the table codes of the last seven days as the indicating value of the repaired table code.
Based on the collected table codes, voltage, current, power failure events and other original data, the data are calculated by utilizing big data calculation capacity, and the result data obtained after calculation are clustered by utilizing unsupervised learning algorithm model data to obtain the potential attributes of the transformer area.
The station area attributes are divided into two categories, which are:
1) basic properties of the platform area: the type of the transformer area, the running time, the manufacturer of the transformer, the address of the transformer area, the type of the transformer area and the unit of the transformer area.
2) Station zone potential attributes: the system comprises a line loss rate, a platform area load, a platform area power supply reliability, a power failure time, a power restoration time, three-phase imbalance, a voltage qualification rate, electric energy quality, an electric charge recovery rate and customer satisfaction.
3. Performing feature extraction by using a big data technology, converting the station area attribute into a label, and giving weight to the label according to the frequency and the proportion of the label; and constructing a platform area accurate picture based on the label.
The characteristic extraction is based on the distribution area attribute, the distribution area attribute is processed by utilizing a big data technology, wherein the distribution area basic attribute can be directly converted into a corresponding label, when the distribution area potential attribute is converted into the label, the data obtained by calculating each attribute is compared with a public agreed threshold value, for example, for the distribution area line loss rate attribute, a numerical value can be calculated according to the line loss rate, and the conversion is carried out: high loss, negative loss or normal three kinds of labels. After the classification of the labels of the station area is completed, the station area is represented as a combined description of all the labels of the station area, for example: station a has the following labels: high line loss rate, low customer satisfaction, long average power failure time, long average power restoration time and the like, and the combination of all the labels is the A-station area portrait.
4. And (4) constructing a platform area comprehensive evaluation model by utilizing the platform area portrait label weight, and realizing accurate evaluation of the platform area comprehensive state.
An example of a method for weighting tags is as follows: for the basic labels of the platform area, such as the affiliated units, the addresses and the like, label weight assignment is carried out according to a fixed score part, for example: in a remote area, considering the influence of the current technical capability, the weight score of the label is higher than that of a normal area; the labels of the potential attribute conversion of the station areas are classified according to the true calculation results and the appointed threshold, for example: the line loss rate of the transformer area can be divided into three categories of normal, high loss and negative loss, the negative loss is taken as an example, the line loss rate can be divided into abnormal negative loss of a metering device, information input negative loss and the like according to actual conditions, and label weight assignment is respectively carried out on the size of the influence of normal operation under different conditions. The line loss evaluation model is specifically a set of data formula, namely mathematical operation is carried out according to all label score values of the transformer area, and as the scores are obtained according to the multidimensional labels of the transformer area, accurate evaluation on the transformer area is obtained according to the final scores.
In the embodiment of the invention, based on the advantages of large data distributed storage and cluster transverse expansion, the storage requirement of the current mass data can be met, and the requirement of future data storage can be ensured; the data processing technology based on big data can efficiently finish the cleaning of mass data and ensure the validity of result data; by adopting data mining technologies such as association analysis, statistical analysis, deep learning and cluster analysis, and adopting different algorithm models for different transformer areas, hidden attributes and association relations of transformer area data can be mined from multiple dimensions, transformer area labels can be comprehensively and finely extracted, and accurate construction of transformer area portraits is realized.
Fig. 3 schematically shows a block diagram of an apparatus for evaluating a station area according to an embodiment of the present invention. As shown in fig. 3, in an embodiment of the present invention, there is provided an apparatus 300 for evaluating a station area, including: a raw data acquisition module 310, a platform potential attribute determination module 320, a tag type determination module 330, and a platform evaluation module 340, wherein:
the raw data obtaining module 310 is configured to obtain raw power data of the distribution room within a preset evaluation period.
And a platform potential attribute determining module 320, configured to obtain a platform potential attribute according to the raw power data.
And the tag type determining module 330 is configured to determine a tag type corresponding to the potential attribute of the platform area, where the tag type includes a positive tag and a negative tag.
And the platform area evaluation module 340 is used for obtaining an image of the platform area according to the proportion of the platform area potential attribute and the frequency of the label type so as to evaluate the platform area.
The device 300 for evaluating the transformer area obtains the potential property of the transformer area according to the original power data by obtaining the original power data of the transformer area in the preset evaluation period, further determines the label type corresponding to the potential property of the transformer area, and obtains the portrait of the transformer area according to the specific gravity of the potential property of the transformer area and the frequency of the label type so as to evaluate the transformer area. The device excavates the latent attribute of platform district through the analysis of synthesis platform district data to through carrying out the feature extraction to the latent attribute of platform district, obtain the label type that the latent attribute of platform district corresponds, and then construct the accurate portrait of platform district according to the proportion of the latent attribute of platform district and the frequency of label type, thereby can realize the accurate evaluation to the comprehensive state of platform district through the accurate portrait of this platform district, improved the precision of platform district evaluation.
In one embodiment, the platform zone potential attributes include at least one of: the system comprises a line loss rate, a platform area load, a platform area power supply reliability, a power failure time, a power restoration time, a three-phase imbalance, a voltage qualification rate, electric energy quality, an electric charge recovery rate and customer satisfaction.
In one embodiment, the platform potential attribute determination module 320 is further configured to: and determining the potential attributes of the transformer area according to the original power data and the pre-stored service rule.
In one embodiment, the tag type determination module 330 is further configured to: and comparing the potential attributes of the transformer area with a preset threshold value to determine the type of the label corresponding to the potential attributes of the transformer area.
In one embodiment, the tag type determination module 330 is further configured to: determining the label type corresponding to the platform area potential attribute as a front label under the condition that the platform area potential attribute is greater than or equal to a preset threshold value; and under the condition that the potential attribute of the transformer area is smaller than a preset threshold value, determining that the type of the label corresponding to the potential attribute of the transformer area is a negative label.
In one embodiment, the block evaluation module 340 is further configured to: determining the multiplying power of the label type according to the frequency of the label type; determining the weight of the label type according to the proportion of the platform area potential attribute, the preset basic score of the platform area potential attribute and the multiplying power of the label type; and obtaining the image of the platform area according to the weight of the label type.
In one embodiment, the block evaluation module 340 is further configured to: and determining the multiplying power of the label type according to the frequency of the label type and a preset evaluation period.
In one embodiment, the apparatus 300 for evaluating a distribution area further includes a data cleansing module for cleansing the raw power data before obtaining the potential property of the distribution area from the raw power data.
In one embodiment, the block evaluation module 340 is further configured to: and determining the product of the specific gravity of the platform potential attribute, the preset basic score of the platform potential attribute and the multiplying power of the label type to determine the weight of the label type.
The device for evaluating the transformer area comprises a processor and a memory, wherein the original data acquisition module, the transformer area potential attribute determination module, the tag type determination module, the transformer area evaluation module, the data cleaning module and the like are stored in the memory as program modules, and the processor executes the program modules stored in the memory to realize corresponding functions.
The processor comprises a kernel, and the kernel calls the corresponding program unit from the memory. One or more than one kernel can be set, and the evaluation accuracy of the transformer area is improved by adjusting kernel parameters.
The memory may include volatile memory in a computer readable medium, Random Access Memory (RAM) and/or nonvolatile memory such as Read Only Memory (ROM) or flash memory (flash RAM), and the memory includes at least one memory chip.
An embodiment of the present invention provides a storage medium having a program stored thereon, which when executed by a processor implements the above-described method for evaluating a station area.
The embodiment of the invention provides a processor, wherein the processor is used for running a program, and the method for evaluating the transformer area is executed when the program runs.
An embodiment of the present invention provides an apparatus, where the apparatus includes a processor, a memory, and a program stored in the memory and capable of running on the processor, and when the processor executes the program, the method for evaluating a station area is implemented. The device herein may be a server, a PC, a PAD, a mobile phone, etc.
The present application also provides a computer program product adapted to perform a program initialized with the above-described method for evaluating a station area when executed on a data processing device.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). The memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in the process, method, article, or apparatus that comprises the element.
The above are merely examples of the present application and are not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (10)
1. A method for evaluating a station area, the method comprising:
acquiring original power data of a distribution room in a preset evaluation period;
obtaining a platform area potential attribute according to the original power data;
determining a label type corresponding to the platform area potential attribute, wherein the label type comprises a positive label and a negative label;
and obtaining an image of the platform area according to the proportion of the potential attributes of the platform area and the frequency of the tag type so as to evaluate the platform area.
2. The method of claim 1, wherein the platform zone potential attributes comprise at least one of: the system comprises a line loss rate, a platform area load, a platform area power supply reliability, a power failure time, a power restoration time, a three-phase imbalance, a voltage qualification rate, electric energy quality, an electric charge recovery rate and customer satisfaction.
3. The method of claim 1, wherein deriving the zone potential attributes from the raw power data comprises:
and determining the potential attributes of the distribution area according to the original power data and a pre-stored service rule.
4. The method of claim 1, wherein the determining the type of the tag corresponding to the platform zone potential attribute comprises:
and comparing the platform area potential attribute with a preset threshold value to determine a label type corresponding to the platform area potential attribute.
5. The method of claim 4, wherein comparing the platform potential attribute with a preset threshold to determine a tag type corresponding to the platform potential attribute comprises:
determining that the label type corresponding to the platform area potential attribute is a front label under the condition that the platform area potential attribute is larger than or equal to the preset threshold value;
and under the condition that the platform area potential attribute is smaller than the preset threshold value, determining that the label type corresponding to the platform area potential attribute is a negative label.
6. The method of claim 1, wherein said deriving a representation of the platform area based on the specific gravity of the platform area potential attribute and the frequency of the tag type comprises:
determining the multiplying power of the label type according to the frequency of the label type;
determining the weight of the label type according to the proportion of the platform area potential attribute, the preset basic score of the platform area potential attribute and the multiplying power of the label type;
and obtaining the portrait of the platform area according to the weight of the label type.
7. The method of claim 6, wherein determining the multiplying power of the tag type according to the frequency of the tag type comprises:
and determining the multiplying power of the label type according to the frequency of the label type and a preset evaluation period.
8. The method of claim 1, further comprising, prior to said deriving a zone potential attribute from said raw power data:
and cleaning the original power data.
9. The method of claim 6, wherein determining the weight of the tag type according to the specific gravity of the platform area potential attribute, a preset base score and the multiplying power of the tag type comprises:
and determining the product of the specific gravity of the platform potential attribute, the preset basic score of the platform potential attribute and the multiplying power of the label type so as to determine the weight of the label type.
10. An apparatus for evaluating a platen, the apparatus comprising:
the system comprises an original data acquisition module, a data processing module and a data processing module, wherein the original data acquisition module is used for acquiring original power data of a distribution room in a preset evaluation period;
the transformer area potential attribute determining module is used for obtaining transformer area potential attributes according to the original power data;
the tag type determining module is used for determining tag types corresponding to the platform area potential attributes, wherein the tag types comprise positive tags and negative tags;
and the platform area evaluation module is used for obtaining the representation of the platform area according to the specific gravity of the potential attributes of the platform area and the frequency of the tag type so as to evaluate the platform area.
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