CN110544123A - power consumer classification method and device, computer equipment and storage medium - Google Patents

power consumer classification method and device, computer equipment and storage medium Download PDF

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CN110544123A
CN110544123A CN201910808343.3A CN201910808343A CN110544123A CN 110544123 A CN110544123 A CN 110544123A CN 201910808343 A CN201910808343 A CN 201910808343A CN 110544123 A CN110544123 A CN 110544123A
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CN110544123B (en
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王勇
许中
周凯
马智远
郭倩雯
栾乐
饶毅
叶石丰
张群峰
崔晓飞
覃煜
蔡燕春
肖天为
刘田
叶志峰
王荣富
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Guangzhou Power Supply Bureau of Guangdong Power Grid Co Ltd
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Abstract

the application relates to a power consumer classification method, a power consumer classification device, a computer device and a storage medium. The power consumer classification method comprises the following steps: acquiring a lifetime value index, a voltage sag index, a harmonic index, a three-phase voltage unbalance index and a voltage variation index of each power consumer; clustering, namely dividing power users into a plurality of categories, and acquiring a clustering center of each category; determining index weight of each user; and determining the category of each user according to the lifetime value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each user and the index weight of each user. By adopting the method, the accuracy of the classification result of the power consumer can be improved.

Description

Power consumer classification method and device, computer equipment and storage medium
Technical Field
The present application relates to the field of power technologies, and in particular, to a method and an apparatus for classifying power consumers, a computer device, and a storage medium.
background
a competition mechanism is introduced on the electricity selling side instead of a new round of electricity, so that the electricity consumer has the right of autonomously selecting a transaction object like an electricity selling company. Meanwhile, with the continuous development of the high-tech industry, the sensitive load ratio is continuously increased, and the demand of power consumers in the related industry on the quality of electric energy is more and more intense. Therefore, the research on diversified high-quality power requirements of users and the subdivision of different types of users so as to provide differentiated power supply services are a new trend and new requirements for the development of power selling companies under the background of open power selling sides.
At present, user classification is mainly researched aiming at the aspects of power load characteristic clustering, customer value evaluation and the like. According to the form change of the daily power load curve of the user, the similarity of different user load curves is measured, and the user power load data is classified by using a cluster analysis method. In addition, the technology uses different pattern recognition methods to classify daily load curves of large-scale power customers. The traditional scheme does not consider relevant indexes of high-quality power supply requirements of all classes of users, and fails to describe the classes of the users qualitatively and quantitatively, so that the classification result is not accurate enough.
Disclosure of Invention
in view of the above, it is necessary to provide a power consumer classification method, apparatus, computer device and storage medium capable of improving accuracy of classification results.
A power consumer classification method comprises the following steps:
acquiring a lifetime value index, a voltage sag index, a harmonic index, a three-phase voltage unbalance index and a voltage variation index of each power consumer;
After the lifelong value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each power consumer are unified in dimension, clustering the lifelong value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each power consumer so as to divide the power consumers into a plurality of categories and obtain the clustering centers of the categories;
Determining the index weight of each user according to the lifetime value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each power user and the clustering center corresponding to each user;
and determining the category of each user according to the lifetime value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each user and the index weight of each user.
In one embodiment, obtaining the lifetime value index of each power consumer comprises:
acquiring initial lifetime value indexes of each power user, and identifying cost indexes and benefit indexes in the initial lifetime value indexes;
respectively carrying out percent processing on the cost index and the benefit index;
And determining the lifetime value index of each power user according to the index value obtained by the percentile system processing.
as one example, the lifetime value indicators include the value of each indicator within the current value, the value of each indicator within the loyalty, and the value of the credit indicator;
determining the lifetime value index of each power user according to the index parameter obtained by the percentage system processing comprises the following steps:
Substituting the index parameters obtained by the percentage processing of each power consumer into the lifelong value index model to calculate the lifelong value index of each power consumer; the lifelong value index model includes:
wherein Z represents a lifetime value index, Q alpha represents the value of the alpha index in the current value, omega alpha represents the weight corresponding to Q alpha, C beta represents the value of each beta index in the loyalty, omega beta represents the weight corresponding to C beta, H gamma represents the value of the gamma index in the credit, omega gamma represents the weight corresponding to H gamma, and the symbol 'pi' represents multiplication.
In one embodiment, after obtaining the lifetime value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index, and the voltage variation index of each power consumer, the method further includes:
And respectively carrying out normalization processing on the lifetime value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each power consumer so as to unify the lifetime value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each power consumer into dimensions.
As an embodiment, the process of performing normalization processing on the lifetime value index, the voltage sag index, the harmonic index, the three-phase voltage imbalance index, and the voltage variation index of each power consumer includes:
Substituting the lifetime value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each power user into a normalization processing formula respectively to realize normalization processing; the normalization processing formula comprises:
in the formula, μ E represents the index after the normalization process, x represents the index before the normalization process, x1 represents the first reference index, x2 represents the second reference index, x3 represents the third reference index, and x4 represents the fourth reference index.
In one embodiment, determining the index weight of each user according to the lifetime value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index, and the voltage variation index of each power user, and the clustering center corresponding to each user includes:
Establishing a hierarchical structure model by taking a lifetime value index, a voltage sag index, a harmonic index, a three-phase voltage unbalance index and a voltage variation index of each power user as index layers, taking each clustering center as a user layer and taking the index weight of each user as a target layer;
And solving the hierarchical structure model to obtain the index weight of each user.
In one embodiment, determining the category to which each user belongs according to the lifetime value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each user and the index weight of each user comprises:
and multiplying the lifetime value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each user by corresponding index weights respectively to obtain the comprehensive index score of each user, and determining the category of each comprehensive index score as the category of each user.
a power consumer classification device, the device comprising:
The acquisition module is used for acquiring a lifetime value index, a voltage sag index, a harmonic index, a three-phase voltage unbalance index and a voltage variation index of each power consumer;
the clustering module is used for clustering the lifeline value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each power consumer after the lifeline value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each power consumer are unified in dimension, so that the power consumers are divided into a plurality of categories, and a clustering center of each category is obtained;
the first determining module is used for determining the index weight of each user according to the lifetime value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each power user and the clustering centers corresponding to various users;
And the second determining module is used for determining the category of each user according to the lifetime value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each user and the index weight of each user.
A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the power consumer classification method of any of the above embodiments when executing the computer program.
a computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the power consumer classification method of any of the above embodiments.
The power consumer classification method, the device, the computer equipment and the storage medium have the advantages that by acquiring the lifetime value index, the voltage sag index, the harmonic wave index, the three-phase voltage unbalance index and the voltage variation index of each power consumer, after the lifelong value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each power user are unified in dimension, corresponding clustering processing is carried out, so as to divide the power users into a plurality of categories, obtain the clustering centers of the categories, determine the index weight of each user, and the classification process combines the lifelong value index of the user and the electric energy quality index related to the high-quality power supply requirement of the user, comprehensively considers the different requirements of the power selling company and the user, and has higher accuracy.
drawings
FIG. 1 is a flow diagram illustrating a method for classifying power consumers in one embodiment;
FIG. 2 is a power consumer indicator architecture diagram of one embodiment;
FIG. 3 is a block diagram of an electric power consumer classifying device in one embodiment;
FIG. 4 is a diagram illustrating an internal structure of a computer device according to an embodiment.
Detailed Description
in order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
the power consumer classification method can be applied to intelligent terminals for subdividing power consumers with diversified high-quality power demands. The intelligent terminal can obtain a lifetime value index, a voltage sag index, a harmonic index, a three-phase voltage unbalance index and a voltage variation index of each power consumer; after the lifelong value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each power consumer are unified in dimension, clustering the lifelong value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each power consumer so as to divide the power consumers into a plurality of categories and obtain the clustering centers of the categories; determining the index weight of each user according to the lifetime value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each power user and the clustering center corresponding to each user; and determining the category of each user according to the lifetime value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each user and the index weight of each user. So as to realize accurate classification of user categories.
In one embodiment, as shown in fig. 1, there is provided a power consumer classification method, including the steps of:
S210, obtaining a lifetime value index, a voltage sag index, a harmonic index, a three-phase voltage unbalance index and a voltage variation index of each power consumer;
lifetime value indexes, voltage sag indexes, harmonic indexes, three-phase voltage unbalance indexes and voltage variation indexes of power consumers can be obtained from related power management systems. Specifically, the lifetime value index includes a current value and potential value equivalent value parameter. The voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index belong to electric energy quality indexes. The step combines the lifelong value index of the user with the power quality index related to the high-quality power supply requirement of the user, comprehensively considers the different requirements of the power selling company and the user, and can improve the accuracy of the subsequent power user category determination.
S230, after the lifelong value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each power consumer are unified in dimension, clustering the lifelong value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each power consumer so as to divide the power consumers into a plurality of categories and obtain the clustering centers of the categories;
the related intelligent terminals can unify the dimensions of the lifelong value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index in a normalization processing mode and the like so as to ensure the accuracy of the classification basis of the power users.
after the lifeline value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each power consumer are unified in dimension, the intelligent terminal can perform clustering processing on the lifeline value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each power consumer by adopting a clustering algorithm such as a K-means algorithm, so that the power consumers are divided into a plurality of categories to obtain each clustering center. The K-means algorithm can evaluate the similarity and difference between samples by using distance indexes, and the obtained various user index data have obvious similarity.
in an example, the clustering effect may also be comprehensively evaluated by using a mean index equalicity (MIA), a mean of distance between curves (MDC), a classification suitability index (DBI), a contour coefficient index (SC), and the like, and the final clustering parameter k is determined by comprehensively considering the intra-class distance and the inter-class distance, so as to improve the accuracy of the clustering result.
S250, determining the index weight of each user according to the lifetime value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each power user and the clustering center corresponding to each user;
In the process of determining the index weight of each user, the fuzzy analytic hierarchy process based on entropy weight can be used, on the basis of introducing triangular fuzzy numbers, subjective evaluation analysis and objective quantitative results are combined, and meanwhile, the risk preference and the decision confidence degree of a decision maker are considered, so that the corresponding index weight can be determined more accurately.
And S270, determining the category of each user according to the lifetime value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each user and the index weight of each user.
The lifetime value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of a certain power user all have corresponding index weights, and the step can be used for multiplying the lifetime value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of the certain power user by the corresponding index weights respectively to obtain a comprehensive index score so as to determine the category of the power user according to the comprehensive index score.
according to the electric power user classification method, after the lifelong value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each electric power user are unified in dimension, corresponding clustering processing is carried out to divide the electric power users into a plurality of categories, a clustering center of each category is obtained, the index weight of each user is determined, the category to which each user belongs is further determined, and classification of the electric power users is achieved.
In one embodiment, obtaining the lifetime value index of each power consumer comprises:
Acquiring initial lifetime value indexes of each power user, and identifying cost indexes and benefit indexes in the initial lifetime value indexes;
Respectively carrying out percent processing on the cost index and the benefit index;
and determining the lifetime value index of each power user according to the index value obtained by the percentile system processing.
the lifelong value index comprises a current value index and a potential value index, wherein the remaining indexes are benefit indexes except the arrearage amount is a cost index. The percentage processing of the cost index and the benefit index can be separately performed. The formula for performing the percentile processing on the cost index is as follows:
The formula for carrying out the percentile processing on the benefit type index is as follows:
in the formula, d represents the index value after the percentage processing, I represents the original value of the index, Imax represents the maximum value in the original value of the index, and Imin represents the minimum value in the original value of the index.
As one example, the lifetime value indicators include the value of each indicator within the current value, the value of each indicator within the loyalty, and the value of the credit indicator;
Determining the lifetime value index of each power user according to the index parameter obtained by the percentage system processing comprises the following steps:
substituting the index parameters obtained by the percentage processing of each power consumer into the lifelong value index model to calculate the lifelong value index of each power consumer; the lifelong value index model includes:
wherein, A represents the current value, B represents the potential value, Z represents the lifetime value index, Q alpha represents the value of the alpha index in the current value, omega alpha represents the weight corresponding to Q alpha, C beta represents the value of each beta index in the loyalty, omega beta represents the weight corresponding to C beta, H gamma represents the value of the gamma index in the credit, omega gamma represents the weight corresponding to H gamma, and the symbol 'pi' represents the multiplication.
the embodiment can accurately determine the lifetime value index of each power consumer.
as an example, the index system of the power consumer may refer to fig. 2, and the lifetime value index includes the current value and the potential value, and may be obtained in a corresponding statistical period, where the statistical period may include a period of one year. The current value of the user refers to the value of the user brought to the power selling company by the user under the condition that the current behavior mode is kept unchanged, and the value is mainly reflected in the aspects of income contribution, service cost, stability and the like. The income contribution is the most basic standard for measuring the current value of the user and is determined by the annual power consumption and the annual average electricity price; the service cost is different investments of the power selling company on different user services, and can be commonly represented by annual load rate and annual valley power consumption rate. The potential value of the user is the value of the customer which is possibly increased after the electric selling company implements certain marketing strategies, and is mainly reflected in the aspects of loyalty, credit and the like. For power grid enterprises, the loyalty index of a user can select annual electric quantity growth rate and annual capacity change, and the credit index can select electric charge recovery rate and arrearage amount.
in one example, user electrical stability may be represented by the following equation:
In the formula, Is represents the annual power stability, tn represents the current annual power consumption increase rate, and tl represents the last annual power consumption increase rate.
as shown in fig. 2, the user power quality indicators include a voltage sag indicator, a harmonic indicator, a three-phase voltage unbalance indicator, and a voltage variation indicator. The voltage variation indicators include voltage fluctuations and voltage flicker. The voltage sag and the short-time interruption are one of the most important power quality disturbance phenomena, and the economic loss caused by the voltage sag and the short-time interruption accounts for the highest percentage of the power quality loss of users, so the economic loss can be used as an index reflecting the high-quality power supply requirements of the users. With the increase of the impact harmonic source load in the power grid, the influence and harm of the harmonic to the user are increased continuously, wherein the influence and harm include economic losses on a user distribution line and a transformer caused by the harmonic; the annual average voltage total harmonic distortion rate expected by a user and the annual economic loss caused by harmonic distortion at the current power supply level are taken as the sub-indexes of classification. The occurrence of unbalanced three-phase voltage easily causes additional heating of the motor, thereby accelerating the insulation aging of equipment, increasing the electric quantity loss, reducing the efficiency or generating defective products and the like. Therefore, the annual average voltage unbalance degree expected by a user and the annual economic loss caused by three-phase unbalance at the current power supply level are taken as the classification sub-indexes. Voltage fluctuations can affect the normal operation of sensitive loads, and in severe cases, can damage electrical equipment or cause huge economic losses. The voltage flicker is a special reflection of voltage fluctuation and is also an important index for evaluating the quality of electric energy. For voltage fluctuation and flicker, an annual fluctuation value and an annual flicker value expected by a user and annual economic losses caused by the voltage fluctuation and flicker under the current power supply level are selected as the sub-indexes of classification.
in one embodiment, after obtaining the lifetime value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index, and the voltage variation index of each power consumer, the method further includes:
And respectively carrying out normalization processing on the lifetime value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each power consumer so as to unify the lifetime value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each power consumer into dimensions.
As an embodiment, the process of performing normalization processing on the lifetime value index, the voltage sag index, the harmonic index, the three-phase voltage imbalance index, and the voltage variation index of each power consumer includes:
Substituting the lifetime value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each power user into a normalization processing formula respectively to realize normalization processing; the normalization processing formula comprises:
in the formula, μ E represents the index after the normalization process, x represents the index before the normalization process, x1 represents the first reference index, x2 represents the second reference index, x3 represents the third reference index, and x4 represents the fourth reference index. The first reference index, the second reference index, the third reference index and the fourth reference index may be determined according to index value characteristics of the power consumer, for example, may be determined as an optimal value of a corresponding index segment, respectively.
The embodiment introduces the idea of fuzzy theory, establishes membership functions of different classification indexes based on different index data ranges and optimal values of users, and calculates the values of the membership functions according to actual data of the users, so as to obtain normalized data. After the membership function processing, the values of the data are all in the interval of [0,1], so that the purposes of reducing and unifying dimensions are achieved, the subsequent data processing and analysis are facilitated, the convergence is accelerated during the operation of the program, and the clustering result is more meaningful and comparable.
in one embodiment, determining the index weight of each user according to the lifetime value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index, and the voltage variation index of each power user, and the clustering center corresponding to each user includes:
Establishing a hierarchical structure model by taking a lifetime value index, a voltage sag index, a harmonic index, a three-phase voltage unbalance index and a voltage variation index of each power user as index layers, taking each clustering center as a user layer and taking the index weight of each user as a target layer;
and solving the hierarchical structure model to obtain the index weight of each user.
In the embodiment, a fuzzy analytic hierarchy process based on entropy weight is used, on the basis of introducing triangular fuzzy numbers, subjective evaluation analysis and objective quantitative results are combined, and risk preference and decision confidence degree of a decision maker are considered, so that the obtained index weight has higher accuracy.
In one example, the process of building and solving the hierarchy model may include:
(1) and establishing a hierarchical structure model which comprises a target layer, an index layer and a user layer.
(2) The element values in the judgment matrix are represented by symmetrical triangular fuzzy numbers, the triangular fuzzy numbers of the obtained fuzzy judgment matrix are described by three determined numbers, namely, experts participating in evaluation select the fuzzy numbers describing contribution according to professional knowledge and experience, and therefore subjectivity is fully reflected.
(3) Multiplying the fuzzy weight vector of each index by the fuzzy judgment matrix to establish a total fuzzy judgment matrix
(4) by defining the confidence interval under the alpha cut set, it can be expressed as equation (1) for the fuzzy number.
And carrying out fuzzy operation on the fuzzy judgment matrix by using the truncated set alpha and the interval.
In the formula (I), the compound is shown in the specification,
(5) After determining α, the satisfaction of the decision matrix is estimated using α and the optimistic index λ, thereby obtaining a non-ambiguous decision matrix. The optimistic index represents the optimism of the decision maker, the greater the value, the higher the optimism.
In the formula (I), the compound is shown in the specification,
(6) The entropy weight Hi can be calculated from the relative frequency of equation (4) and the entropy weight equation of equation (5).
In the formula
In one embodiment, determining the category to which each user belongs according to the lifetime value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each user and the index weight of each user comprises:
and multiplying the lifetime value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each user by corresponding index weights respectively to obtain the comprehensive index score of each user, and determining the category of each comprehensive index score as the category of each user.
each category has a corresponding value segment of the composite index (e.g., a first value segment of the composite index, a second value segment of the composite index, a third value segment of the composite index, etc.), and the value segment of the composite index can be determined according to the value characteristics of the corresponding cluster center. For a certain power consumer, if the comprehensive index score of the power consumer is in the first comprehensive index value section, the category to which the power consumer belongs is the category corresponding to the first comprehensive index value section.
in one example, after the index weight is determined, the power consumers may be classified into three classes, i.e., I, II, and III power consumers, according to the power consumer classification index system and the classification result, so as to establish a power consumer classification model as shown in table 1.
TABLE 1
In the embodiment, the requirements of the electricity selling company and the user are considered at the same time, the customer value and the electric energy quality requirement are combined to form a new electric power user classification index system, and on the basis, the user is further subdivided by using a fuzzy analytic hierarchy process to achieve the purpose of qualitatively and quantitatively depicting the user classification, so that the obtained result error is smaller, the high-quality electric power requirement of the user is reflected, and the development of differentiated services of the electricity selling company is facilitated.
it should be understood that, although the steps in the flowchart of fig. 1 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a portion of the steps in fig. 1 may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, and the order of performance of the sub-steps or stages is not necessarily sequential, but may be performed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.
in one embodiment, as shown in fig. 3, there is provided a power consumer classification device including:
The obtaining module 210 is configured to obtain a lifetime value index, a voltage sag index, a harmonic index, a three-phase voltage imbalance index, and a voltage variation index of each power consumer;
the clustering module 230 is configured to perform clustering processing on the lifetime value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index, and the voltage variation index of each power consumer after the lifetime value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index, and the voltage variation index of each power consumer are unified in dimension, so as to divide the power consumers into multiple categories and obtain a clustering center of each category;
The first determining module 250 is configured to determine an index weight of each user according to a lifetime value index, a voltage sag index, a harmonic index, a three-phase voltage imbalance index, a voltage variation index of each power user, and a clustering center corresponding to each user;
And a second determining module 270, configured to determine the category to which each user belongs according to the lifetime value index, the voltage sag index, the harmonic index, the three-phase voltage imbalance index, and the voltage variation index of each user, and the index weight of each user.
in one embodiment, the obtaining module is further configured to:
Acquiring initial lifetime value indexes of each power user, and identifying cost indexes and benefit indexes in the initial lifetime value indexes;
respectively carrying out percent processing on the cost index and the benefit index;
and determining the lifetime value index of each power user according to the index value obtained by the percentile system processing.
as one example, the lifetime value indicators include the value of each indicator within the current value, the value of each indicator within the loyalty, and the value of the credit indicator;
the obtaining module is further configured to:
substituting the index parameters obtained by the percentage processing of each power consumer into the lifelong value index model to calculate the lifelong value index of each power consumer; the lifelong value index model includes:
Wherein Z represents a lifetime value index, Q alpha represents the value of the alpha index in the current value, omega alpha represents the weight corresponding to Q alpha, C beta represents the value of each beta index in the loyalty, omega beta represents the weight corresponding to C beta, H gamma represents the value of the gamma index in the credit, omega gamma represents the weight corresponding to H gamma, and the symbol 'pi' represents multiplication.
in one embodiment, the power consumer classifying device further includes:
And the normalization processing module is used for respectively performing normalization processing on the lifetime value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each power consumer so as to enable the lifetime value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each power consumer to be in unified dimension.
as an embodiment, the normalization processing module is further configured to:
substituting the lifetime value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each power user into a normalization processing formula respectively to realize normalization processing; the normalization processing formula comprises:
In the formula, μ E represents the index after the normalization process, x represents the index before the normalization process, x1 represents the first reference index, x2 represents the second reference index, and x3 represents the third reference index.
In one embodiment, the first determining module is further configured to:
Establishing a hierarchical structure model by taking a lifetime value index, a voltage sag index, a harmonic index, a three-phase voltage unbalance index and a voltage variation index of each power user as index layers, taking each clustering center as a user layer and taking the index weight of each user as a target layer;
and solving the hierarchical structure model to obtain the index weight of each user.
in one embodiment, the second determining module is further configured to:
and multiplying the lifetime value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each user by corresponding index weights respectively to obtain the comprehensive index score of each user, and determining the category of each comprehensive index score as the category of each user.
for specific definition of the power consumer classifying device, reference may be made to the above definition of the power consumer classifying method, which is not described herein again. The modules in the power consumer classifying device can be wholly or partially realized by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
in one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as shown in fig. 4. The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a power consumer classification method. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, a key, a track ball or a touch pad arranged on the shell of the computer equipment, an external keyboard, a touch pad or a mouse and the like.
Those skilled in the art will appreciate that the architecture shown in fig. 4 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
based on the above examples, in one embodiment, a computer device is further provided, where the computer device includes a memory, a processor, and a computer program stored on the memory and executable on the processor, and the processor executes the program to implement any one of the power consumer classification methods in the above embodiments.
the computer equipment can realize accurate classification of the power consumers through the computer program running on the processor.
it will be understood by those skilled in the art that all or part of the processes in the method for implementing the above embodiments may be implemented by a computer program to instruct related hardware, and the program may be stored in a non-volatile computer readable storage medium, and in the embodiment of the present invention, the program may be stored in the storage medium of a computer system and executed by at least one processor in the computer system to implement the processes including the embodiments of the power consumer classification method described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), or the like.
Accordingly, in an embodiment, a computer-readable storage medium is also provided, on which a computer program is stored, wherein the program, when executed by a processor, implements any one of the above-described power consumer classification methods in the embodiments.
the computer readable storage medium can combine the lifelong value index of the user with the electric energy quality index related to the high-quality power supply requirement of the user through the stored computer program, comprehensively considers the different requirements of the power selling company and the user, and enables the classification result of the power user to have higher accuracy.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware related to instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
It should be noted that the terms "first \ second \ third" referred to in the embodiments of the present application merely distinguish similar objects, and do not represent a specific ordering for the objects, and it should be understood that "first \ second \ third" may exchange a specific order or sequence when allowed. It should be understood that "first \ second \ third" distinct objects may be interchanged under appropriate circumstances such that the embodiments of the application described herein may be implemented in an order other than those illustrated or described herein.
The terms "comprising" and "having" and any variations thereof in the embodiments of the present application are intended to cover non-exclusive inclusions. For example, a process, method, apparatus, product, or device that comprises a list of steps or modules is not limited to the listed steps or modules but may alternatively include other steps or modules not listed or inherent to such process, method, product, or device.
Reference herein to "a plurality" means two or more. "and/or" describes the association relationship of the associated objects, meaning that there may be three relationships, e.g., a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.

Claims (10)

1. A power consumer classification method, characterized in that the method comprises:
Acquiring a lifetime value index, a voltage sag index, a harmonic index, a three-phase voltage unbalance index and a voltage variation index of each power consumer;
after the lifelong value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each power consumer are unified in dimension, clustering the lifelong value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each power consumer so as to divide the power consumers into a plurality of categories and obtain a clustering center of each category;
determining the index weight of each user according to the lifetime value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each power user and the clustering center corresponding to each user;
And determining the category of each user according to the lifetime value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each user and the index weight of each user.
2. The method of claim 1, wherein the obtaining the lifetime value index of each power consumer comprises:
Acquiring initial lifetime value indexes of each power consumer, and identifying cost indexes and benefit indexes in the initial lifetime value indexes;
respectively carrying out percent processing on the cost index and the benefit index;
And determining the lifetime value index of each power user according to the index value obtained by the percentage processing.
3. The method of claim 2, wherein the lifetime value indicators include the value of each indicator in the current value, the value of each indicator in the loyalty, and the value of the credit indicator;
The determining the lifetime value index of each power consumer according to the index parameter obtained by the percentage processing comprises the following steps:
substituting the index parameters obtained by the percentage processing of each power consumer into a lifetime value index model to calculate the lifetime value index of each power consumer; the lifetime value index model includes:
Wherein Z represents a lifetime value index, Q alpha represents the value of the alpha index in the current value, omega alpha represents the weight corresponding to Q alpha, C beta represents the value of each beta index in the loyalty, omega beta represents the weight corresponding to C beta, H gamma represents the value of the gamma index in the credit, omega gamma represents the weight corresponding to H gamma, and the symbol 'pi' represents multiplication.
4. The method of claim 1, wherein after the obtaining of the lifetime value index, the voltage sag index, the harmonic index, the three-phase voltage imbalance index, and the voltage variation index of each power consumer, the method further comprises:
and respectively carrying out normalization processing on the lifetime value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each power consumer so as to unify the lifetime value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each power consumer into dimensions.
5. The method according to claim 4, wherein the step of normalizing the lifetime value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each power consumer comprises:
Substituting the lifetime value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each power consumer into a normalization processing formula respectively to realize normalization processing; the normalization processing formula comprises:
In the formula, μ E represents the index after the normalization process, x represents the index before the normalization process, x1 represents the first reference index, x2 represents the second reference index, x3 represents the third reference index, and x4 represents the fourth reference index.
6. the method according to any one of claims 1 to 5, wherein the determining the index weight of each power user according to the lifetime value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each power user and the clustering centers corresponding to various users comprises:
establishing a hierarchical structure model by taking the lifetime value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each power user as index layers, each clustering center as a user layer and the index weight of each user as a target layer;
and solving the hierarchical structure model to obtain the index weight of each user.
7. The method according to any one of claims 1 to 5, wherein the determining the category to which the respective user belongs according to the lifetime value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index, and the voltage variation index of the respective user and the index weight of the respective user comprises:
And multiplying the lifetime value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each user by corresponding index weights respectively to obtain the comprehensive index score of each user, and determining the category of each comprehensive index score as the category to which each user belongs.
8. An electrical consumer classification apparatus, the apparatus comprising:
The acquisition module is used for acquiring a lifetime value index, a voltage sag index, a harmonic index, a three-phase voltage unbalance index and a voltage variation index of each power consumer;
The clustering module is used for clustering the lifeline value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each power consumer after the lifeline value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each power consumer are unified in dimension, so as to divide the power consumers into a plurality of categories and obtain the clustering centers of the categories;
the first determining module is used for determining the index weight of each user according to the lifetime value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each power user and the clustering centers corresponding to various users;
and the second determining module is used for determining the category of each user according to the lifetime value index, the voltage sag index, the harmonic index, the three-phase voltage unbalance index and the voltage variation index of each user and the index weight of each user.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the steps of the method of any of claims 1 to 7 are implemented when the computer program is executed by the processor.
10. a computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 7.
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