CN111160404B - Analysis method and device for reasonable value of line loss marker post of power distribution network - Google Patents
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Abstract
The invention discloses a method and a device for analyzing reasonable values of a line loss marker post of a power distribution network. Wherein the method comprises the following steps: determining a line loss data sample set of a plurality of analysis dimensions based on equipment parameter information required by theoretical line loss of the power distribution network and theoretical line loss result data; performing systematic cluster analysis on line loss data sample sets under different analysis dimensions to form a reference cluster value scale; based on a reference cluster value scale, adopting a preset cluster algorithm to analyze line loss data sample sets under different analysis dimensions so as to select a target cluster value; determining a plurality of line loss reference domains based on the target cluster value, wherein each line loss reference domain comprises a plurality of sub-analysis factors; and determining a reasonable value of the line loss marker post corresponding to each analysis dimension by utilizing the data analysis decision tree and the plurality of line loss reference fields.
Description
Technical Field
The invention relates to the technical field of power distribution network line loss evaluation, in particular to a method and a device for analyzing reasonable values of power distribution network line loss benchmarks.
Background
In the related technology, along with the development of economy, the dependence on electric power energy is continuously improved, the line loss management of a power distribution network is a very complex problem in the field of power distribution networks, and as a result, the line loss rate is influenced by a plurality of factors, when the line loss of the power distribution network is calculated, the conditions of different use environments, line trend, voltage and the like need to be comprehensively considered, but no reasonable line loss marker post analysis mode is available in the aspect of selecting the line loss of the power distribution network at present, so that the problem of the line loss of the power distribution network cannot provide a reasonable calculation mode, and quantitative management cannot be realized.
In view of the above problems, no effective solution has been proposed at present.
Disclosure of Invention
The embodiment of the invention provides a method and a device for analyzing reasonable values of a power distribution network line loss marker post, which at least solve the technical problems that the power distribution network line loss cannot be quantitatively managed and the power distribution network line loss management efficiency is affected due to the fact that the power distribution network line loss marker post parameters cannot be reasonably provided in the related technology.
According to one aspect of the embodiment of the invention, an analysis method for reasonable values of a line loss marker post of a power distribution network is provided, which comprises the following steps: determining a line loss data sample set of a plurality of analysis dimensions based on equipment parameter information required by theoretical line loss of the power distribution network and theoretical line loss result data; performing systematic cluster analysis on the line loss data sample sets under different analysis dimensions to form a reference cluster value scale; based on the reference cluster value scale, adopting a preset clustering algorithm to analyze line loss data sample sets under different analysis dimensions so as to select a target cluster value; determining a plurality of line loss reference domains based on the target cluster value, wherein each line loss reference domain comprises a plurality of sub-analysis factors; and determining a reasonable value of the line loss marker post corresponding to each analysis dimension by utilizing the data analysis decision tree and the line loss reference fields.
Optionally, the step of determining a line loss data sample set for a plurality of analysis dimensions includes: acquiring equipment parameter information and theoretical line loss result data required by theoretical line loss of a power distribution network, wherein the equipment parameter information comprises at least one of the following: basic wiring parameter information and wiring hanging-up distribution transformer parameter information, wherein the theoretical line loss result data comprises at least one of the following: reporting a historical theoretical line loss value, a line loss planning reference value, a line loss experience estimated value and contemporaneous line loss daily loss data; screening the multidimensional sample data by using a data analysis tool, and outputting standardized sample data; performing initial inspection on the standardized sample data to obtain an initial line loss data sample set; and screening the initial line loss data sample set by adopting a preset data screening formula to obtain line loss data sample sets with a plurality of analysis dimensions.
Optionally, performing systematic cluster analysis on the line loss data sample sets under different analysis dimensions to form a reference cluster value scale, including: determining a plurality of analysis dimensions, wherein the plurality of analysis dimensions includes at least one of: the power distribution network comprises an area, power supply quantity and line length, wherein the line length comprises a total line length and a main line length; determining the total number of clustered variables based on the plurality of analysis dimensions, and clustering variables adjacent to each other by using a preset variable distance formula; circulating clustering operation to make the clustering quantity reach the target clustering quantity and complete the clustering work; after the clustering work is completed, the line loss data sample sets in different analysis dimensions are analyzed by using a data analysis tool, and a reference cluster value scale is formed.
Optionally, based on the reference cluster value scale, a preset clustering algorithm is adopted to analyze line loss data sample sets under different analysis dimensions, so as to select a target cluster value, which includes: based on the reference cluster value scale, arbitrarily selecting k data objects from n data objects as initial cluster centers; calculating the distance value between each line loss data object and the initial clustering center to obtain a plurality of clustering distance values; selecting a clustering distance value with the smallest numerical value as a clustering dividing reference, and dividing all line loss data objects to obtain a divided line loss aggregation set; and calculating the clustering convergence of the line loss cluster set by using a standard measure function so as to determine a target cluster value.
Optionally, the plurality of line loss reference fields includes at least one of: a reference field based on a line loss planning standard pole value, a reference field based on a historical theoretical line loss value, a reference field based on an empirical line loss estimation value and a reference field based on a synchronous line loss daily loss value.
Optionally, the plurality of sub-analysis factors includes at least one of: line loss marker post value, number of samples, and duty cycle.
Optionally, after determining the line loss marker post reasonable value corresponding to each of the analysis dimensions, the analysis method further includes: constructing a line loss scatter diagram by using a data analysis tool; performing multiple linear regression curve fitting based on the line loss scatter diagram to obtain a linear regression model; and displaying the reasonable line loss marker post values corresponding to each analysis dimension and the reference interval of the reasonable multi-dimensional line loss marker post values by using the linear regression model.
According to another aspect of the embodiment of the present invention, there is also provided an analysis device for reasonable values of line loss benchmarks of a power distribution network, including: the first determining unit is used for determining line loss data sample sets of a plurality of analysis dimensions based on equipment parameter information required by theoretical line loss of the power distribution network and theoretical line loss result data; the cluster analysis unit is used for performing systematic cluster analysis on the line loss data sample sets under different analysis dimensions to form a reference cluster value scale; the selecting unit is used for analyzing line loss data sample sets under different analysis dimensions by adopting a preset clustering algorithm based on the reference cluster value scale so as to select a target cluster value; a second determining unit, configured to determine a plurality of line loss reference domains based on the target cluster value, where each line loss reference domain includes a plurality of sub-analysis factors; and the third determining unit is used for determining a reasonable value of the line loss marker post corresponding to each analysis dimension by utilizing the data analysis decision tree and the plurality of line loss reference fields.
Optionally, the first determining unit includes: the first acquisition module is used for acquiring equipment parameter information and theoretical line loss result data required by theoretical line loss of the power distribution network, wherein the equipment parameter information comprises at least one of the following: basic wiring parameter information and wiring hanging-up distribution transformer parameter information, wherein the theoretical line loss result data comprises at least one of the following: reporting a historical theoretical line loss value, a line loss planning reference value, a line loss experience estimated value and contemporaneous line loss daily loss data; the first screening module is used for screening the multidimensional sample data by using a data analysis tool and outputting standardized sample data; the initialization checking module is used for carrying out initial checking on the standardized sample data to obtain an initial line loss data sample set; and the second screening module is used for screening the initial line loss data sample set by adopting a preset data screening formula to obtain line loss data sample sets with a plurality of analysis dimensions.
Optionally, the cluster analysis unit includes: a first determination module for determining a plurality of analysis dimensions, wherein the plurality of analysis dimensions includes at least one of: the power distribution network comprises an area, power supply quantity and line length, wherein the line length comprises a total line length and a main line length; the clustering module is used for determining the total number of clustered variables based on the plurality of analysis dimensions and clustering variables adjacent to each other by utilizing a preset variable distance formula; the cyclic clustering module is used for cyclic clustering operation so that the clustering quantity reaches the target clustering quantity and clustering work is completed; and the first analysis module is used for analyzing the line loss data sample sets under different analysis dimensions by using a data analysis tool after the clustering work is completed to form a reference cluster value scale.
Optionally, the selecting unit includes: the first selecting module is used for randomly selecting k data objects from n data objects as initial clustering centers based on the reference cluster value scale; the first calculation module is used for calculating the distance value between each line loss data object and the initial clustering center to obtain a plurality of clustering distance values; the second selecting module is used for selecting the clustering distance value with the smallest numerical value as a clustering dividing reference, dividing all line loss data objects and obtaining a divided line loss aggregation set; and the first calculation module is used for calculating the cluster convergence of the line loss cluster set by using a standard measure function so as to determine a target cluster value.
Optionally, the plurality of line loss reference fields includes at least one of: a reference field based on a line loss planning standard pole value, a reference field based on a historical theoretical line loss value, a reference field based on an empirical line loss estimation value and a reference field based on a synchronous line loss daily loss value.
Optionally, the plurality of sub-analysis factors includes at least one of: line loss marker post value, number of samples, and duty cycle.
Optionally, the analysis device for reasonable values of the line loss marker post of the power distribution network further comprises: a construction unit, configured to construct a line loss scatter plot using a data analysis tool after determining a reasonable value of the line loss marker post corresponding to each of the analysis dimensions; the fitting unit is used for performing multiple linear regression curve fitting based on the line loss scatter diagram to obtain a linear regression model; and the display unit is used for displaying the reasonable value of the line loss marker post corresponding to each analysis dimension and the reference interval of the reasonable value of the multidimensional line loss marker post by using the linear regression model.
According to another aspect of the embodiment of the present invention, there is also provided an electronic device, including: a processor; and a memory for storing executable instructions of the processor; the processor is configured to execute the analysis method of the reasonable value of the line loss marker post of the power distribution network through executing the executable instructions.
According to another aspect of the embodiment of the present invention, there is further provided a storage medium, where the storage medium includes a stored program, and when the program runs, the device where the storage medium is controlled to execute the method for analyzing the reasonable value of the line loss marker post of the power distribution network according to any one of the above.
In the embodiment of the invention, equipment parameter information and theoretical line loss result data required by theoretical line loss of a power distribution network are adopted to determine line loss data sample sets of a plurality of analysis dimensions, then systematic cluster analysis is carried out on the line loss data sample sets of different analysis dimensions to form a reference cluster value scale, then the line loss data sample sets of different analysis dimensions can be analyzed by a preset cluster algorithm based on the reference cluster value scale to select a target cluster value, and a plurality of line loss reference fields are determined based on the target cluster value, wherein each line loss reference field comprises a plurality of sub-analysis factors, and finally a reasonable value of a line loss marker post corresponding to each analysis dimension can be determined by utilizing a data analysis decision tree and the plurality of line loss reference fields. In the embodiment, the line loss data sample can be analyzed to obtain a reasonable value reference interval value of the multi-dimensional line loss marker post, so that line loss data visualization is realized, and the technical problems that the line loss of the power distribution network cannot be quantitatively managed and the management efficiency of the line loss of the power distribution network is affected due to the fact that the line loss marker post parameters of the power distribution network cannot be reasonably provided in the related technology are solved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiments of the invention and together with the description serve to explain the invention and do not constitute a limitation on the invention. In the drawings:
FIG. 1 is a flow chart of an alternative method of analyzing a reasonable value of a line loss marker post for a power distribution network in accordance with an embodiment of the present invention;
fig. 2 is a schematic diagram of an alternative analysis device for reasonable values of line loss benchmarks for power distribution networks according to embodiments of the present invention.
Detailed Description
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
To facilitate understanding of the invention by those skilled in the art, some terms or nouns involved in embodiments of the invention are explained below:
SPSS data mining tool: IBM SPSS Statistics makes full use of the valuable information provided by the data by utilizing a powerful set of statistical functions. In addition to general summary Statistics and line calculations, SPSS Statistics also provides a broad range of basic statistical analysis functions such as data summarization, counting, cross analysis, classification, descriptive statistical analysis, factor analysis, regression, and cluster analysis.
And (3) cluster analysis: the method is a multivariate statistical analysis method for establishing classification, can automatically classify a batch of sample (or variable) data according to a plurality of characteristics of the sample (or variable) data and the degree of relativity of the characteristics under the condition of no priori knowledge, and generates a plurality of classification results, wherein the results are that individual characteristics in the same class have similarity, and the individual characteristics of different classes have larger differences. Two cluster analysis methods are adopted in the embodiment of the invention: systematic clustering and K-Means clustering methods.
Decision tree algorithm: the method is an important method in data mining, and the algorithm is used for classifying the objects by learning the existing data and identifying a plurality of factors influencing object classification and constructing a decision tree classification model. The architecture of a decision tree is composed of three parts: leaf nodes, decision nodes, and branches. The basic principle of the decision tree is as follows: the overall data is classified by the classification conditions specified in the algorithm, a decision node is generated, and classification according to algorithm rules is continued until the data cannot be reclassified.
z-score normalization: this method performs normalization of data based on the mean (mean) and standard deviation (standard deviation) of the raw data. The original value x of a is normalized to x' using z-score. The z-score normalization method is applicable to the case where the maximum value and the minimum value of the attribute a are unknown, or the case where there is outlier data out of the range of values. Wherein:
new data = (raw data-mean)/standard deviation.
In the embodiment of the invention, a data mining tool (for example SPSS) can be utilized to carry out sample screening, cluster analysis, decision tree analysis and the like on theoretical line loss and contemporaneous line loss data, so that an analysis method for reasonable line loss rate standard pole values based on the SPSS is realized, multi-dimensional analysis is carried out on the reasonable line loss standard pole values by utilizing multi-source theoretical line loss big data, a multi-dimensional line loss reference domain list is provided, and line loss visualization is realized.
According to an embodiment of the present invention, there is provided an embodiment of a method for analyzing a reasonable value of a line loss marker post of a power distribution network, and it should be noted that, the steps illustrated in the flowchart of the drawings may be performed in a computer system such as a set of computer executable instructions, and, although a logical order is illustrated in the flowchart, in some cases, the steps illustrated or described may be performed in an order different from that herein.
Fig. 1 is a flowchart of an alternative analysis method for reasonable values of line loss benchmarks for power distribution networks according to embodiments of the present invention, as shown in fig. 1, the method including the steps of:
step S102, determining a line loss data sample set of a plurality of analysis dimensions based on equipment parameter information required by theoretical line loss of a power distribution network and theoretical line loss result data;
step S104, performing systematic cluster analysis on line loss data sample sets under different analysis dimensions to form a reference cluster value scale;
step S106, analyzing line loss data sample sets under different analysis dimensions by adopting a preset clustering algorithm based on a reference cluster value scale so as to select a target cluster value;
step S108, determining a plurality of line loss reference domains based on the target cluster value, wherein each line loss reference domain comprises a plurality of sub-analysis factors;
and step S110, determining a reasonable value of the line loss marker post corresponding to each analysis dimension by utilizing the data analysis decision tree and the plurality of line loss reference fields.
Through the steps, equipment parameter information and theoretical line loss result data required by theoretical line loss of a power distribution network can be adopted to determine line loss data sample sets of a plurality of analysis dimensions, then systematic cluster analysis is carried out on the line loss data sample sets of different analysis dimensions to form a reference cluster value scale, then a preset cluster algorithm can be adopted to analyze the line loss data sample sets of different analysis dimensions on the basis of the reference cluster value scale so as to select a target cluster value, and a plurality of line loss reference fields are determined on the basis of the target cluster value, wherein each line loss reference field comprises a plurality of sub-analysis factors, and finally a reasonable value of a line loss marker corresponding to each analysis dimension can be determined by utilizing a data analysis decision tree and the plurality of line loss reference fields. In the embodiment, the line loss data sample can be analyzed to obtain a reasonable value reference interval value of the multi-dimensional line loss marker post, so that line loss data visualization is realized, and the technical problems that the line loss of the power distribution network cannot be quantitatively managed and the management efficiency of the line loss of the power distribution network is affected due to the fact that the line loss marker post parameters of the power distribution network cannot be reasonably provided in the related technology are solved.
The embodiment of the invention can be applied to the use environments such as the line loss of a power distribution network, the loss of a power grid line and the like.
Embodiments of the present invention will be described in detail with reference to the following steps.
Step S102, a line loss data sample set of a plurality of analysis dimensions is determined based on equipment parameter information required by theoretical line loss of the power distribution network and theoretical line loss result data.
Optionally, the step of determining a line loss data sample set for a plurality of analysis dimensions includes: acquiring equipment parameter information and theoretical line loss result data required by theoretical line loss of a power distribution network, wherein the equipment parameter information comprises at least one of the following: basic wiring parameter information and wiring hanging-on distribution transformer parameter information, and theoretical line loss result data comprise at least one of the following: reporting a historical theoretical line loss value, a line loss planning reference value, a line loss experience estimated value and contemporaneous line loss daily loss data; screening the multidimensional sample data by using a data analysis tool, and outputting standardized sample data; carrying out initial test on the standardized sample data to obtain an initial line loss data sample set; and screening the initial line loss data sample set by adopting a preset data screening formula to obtain line loss data sample sets with a plurality of analysis dimensions.
The basic wiring parameter information can be information of a machine account of access and screening equipment managed by wiring basic equipment, and mainly comprises the following steps: wiring line information, distribution transformer account information, etc. And theoretical line loss result data including: the method comprises the steps of connecting theoretical line loss data of the calendar year and daily loss big data of the contemporaneous line loss, screening unqualified data, screening abnormal data based on a data mining tool, and outputting standardized data to form an effective data sample. And (3) the large data information of the contemporaneous line loss and daily loss is accessed and screened, unqualified data is accessed and screened, abnormal data screening is realized based on a data mining tool, standardized data is output, and a line loss data sample set with multiple analysis dimensions is formed.
And step S104, performing systematic cluster analysis on the line loss data sample sets under different analysis dimensions to form a reference cluster value scale.
As an optional embodiment of the invention, the step of performing systematic cluster analysis on the line loss data sample sets under different analysis dimensions to form a reference cluster value scale comprises the following steps: determining a plurality of analysis dimensions, wherein the plurality of analysis dimensions includes at least one of: the power distribution network comprises an area, power supply quantity and line length, wherein the line length comprises the total length of lines and the length of a main line; determining the total number of clustered variables based on a plurality of analysis dimensions, and clustering variables adjacent to each other by using a preset variable distance formula; circulating clustering operation to make the clustering quantity reach the target clustering quantity and complete the clustering work; after the clustering work is completed, a data analysis tool is used for analyzing line loss data sample sets under different analysis dimensions to form a reference cluster value scale.
Wherein, the distance proximity means that the distance between the variables is the shortest.
Systematic cluster analysis is a method adopting traditional statistical cluster analysis, and determining cluster influence mainly comprises the following steps: the area of the distribution network is line loss rate, power supply quantity-line loss rate, line length-line loss rate and the like. The line length is distributed by considering the influence of the total line length and the main line length on the line loss rate.
The systematic clustering process is as follows:
(1) assuming a total of n variables, each variable is individually grouped into one class, with n classes in total.
(2) According to the variable distance formula, two variables with relatively close distances are aggregated into one type, and the other variables are still aggregated into one type respectively and copolymerized into n-1 type.
(3) The two nearest classes are further gathered into one class and copolymerized into n-2 class.
The above steps are continued until the number of polymerizations reaches a predetermined number.
According to the embodiment of the invention, automatic analysis can be automatically carried out on the line loss effective data sample sets under different dimensions based on SPSS system cluster analysis, so that a reasonable reference cluster value scale is formed.
Step S106, based on the reference cluster value scale, adopting a preset clustering algorithm to analyze line loss data sample sets under different analysis dimensions so as to select a target cluster value.
In the embodiment of the invention, based on a reference cluster value scale, a preset clustering algorithm is adopted to analyze line loss data sample sets under different analysis dimensions so as to select a target cluster value, and the method comprises the following steps: based on a reference cluster value scale, arbitrarily selecting k data objects from n data objects as initial cluster centers; calculating the distance value between each line loss data object and the initial clustering center to obtain a plurality of clustering distance values; selecting a clustering distance value with the smallest numerical value as a clustering dividing reference, and dividing all line loss data objects to obtain a divided line loss aggregation set; and calculating the clustering convergence of the line loss aggregation class set by using the standard measure function to determine a target clustering value.
Optionally, the preset clustering algorithm may select a K-Means clustering algorithm, and the correlation coefficient method is used to analyze the correlation influence of the user on the area and the wiring. Aiming at high-loss lines and areas, solving a correlation coefficient k: the goal of k-means is to divide the data points into k object groups, find the center of each object group, and utilize a minimization function
Where is the center of the ith object group.
The above equation requires that each data point be as close as possible to the center of the object group to which they belong.
The method comprises the following specific steps:
(1) arbitrarily selecting k objects from n data objects as initial clustering centers;
(2) calculating the distance between each object and the center objects according to the average value (center object) of each clustered object; dividing the corresponding objects again according to the clustering distance value with the minimum numerical value;
(3) recalculating the mean (center object) of each (changed) cluster;
(4) calculating a standard measure function, and terminating the algorithm when a certain condition is met, such as function convergence; and (5) returning to the step (2) if the condition is not satisfied.
According to a reference cluster value scale provided by systematic clustering, line loss data sample sets under different analysis dimensions are analyzed, line loss sample sets under different dimensions can be respectively analyzed by adopting a preset clustering algorithm, an optimal cluster value is selected, and further reasonable reference values of line loss under different dimensions are obtained.
Step S108, determining a plurality of line loss reference domains based on the target cluster value, wherein each line loss reference domain comprises a plurality of sub-analysis factors.
As an alternative embodiment of the present invention, the plurality of line loss reference fields includes at least one of: a reference field based on a line loss planning standard pole value, a reference field based on a historical theoretical line loss value, a reference field based on an empirical line loss estimation value and a reference field based on a synchronous line loss daily loss value.
In an embodiment of the present invention, the plurality of sub-analysis factors includes at least one of: line loss marker post value, number of samples, and duty cycle.
And step S110, determining a reasonable value of the line loss marker post corresponding to each analysis dimension by utilizing the data analysis decision tree and the plurality of line loss reference fields.
In the embodiment of the invention, after determining the reasonable value of the line loss marker post corresponding to each analysis dimension, the analysis method further comprises the following steps: constructing a line loss scatter diagram by using a data analysis tool; performing multiple linear regression curve fitting based on the line loss scatter diagram to obtain a linear regression model; and (3) using a linear regression model to display a reasonable value of the line loss marker post corresponding to each analysis dimension and a reasonable value reference interval of the multi-dimensional line loss marker post.
Optionally, the reasonable value reference interval of each dimension line loss marker post has a corresponding reference boundary value, and a reasonable selection mode of the line loss of the power distribution network is realized through the reference boundary value.
In the embodiment of the invention, a data mining tool can be used for forming a multidimensional line loss reference field, wherein the multidimensional line loss reference field comprises a line loss planning standard pole value reference field, a line loss value reference field based on a calendar theory, an experience line loss estimation value reference field and a synchronous line loss daily loss value reference field, and each reference field comprises auxiliary analysis factors such as a line loss standard pole value, a sample number, a duty ratio and the like. And based on decision tree analysis, reasonable values of the line loss marker post in different areas, different power supply amounts, different wiring lengths and other dimensions are analyzed. Multiple linear regression curve fitting is carried out based on the line loss scatter diagram, a linear regression model is obtained, line loss visual reference is achieved, and a novel big data analysis reference method is provided for service personnel to carry out loss reduction analysis.
The invention is illustrated by the following alternative embodiments.
Fig. 2 is a schematic diagram of an alternative analysis device for reasonable values of line loss benchmarks for power distribution networks according to embodiments of the present invention, as shown in fig. 2, the analysis device may include:
a first determining unit 21, configured to determine a line loss data sample set of multiple analysis dimensions based on device parameter information required by a theoretical line loss of the power distribution network and theoretical line loss result data;
the cluster analysis unit 22 is used for performing systematic cluster analysis on the line loss data sample sets under different analysis dimensions to form a reference cluster value scale;
a selecting unit 23, configured to analyze line loss data sample sets under different analysis dimensions by using a preset clustering algorithm based on a reference cluster value scale, so as to select a target cluster value;
a second determining unit 24, configured to determine a plurality of line loss reference domains based on the target cluster value, where each line loss reference domain includes a plurality of sub-analysis factors;
a third determining unit 25, configured to determine a reasonable value of the line loss marker post corresponding to each analysis dimension by using the data analysis decision tree and the plurality of line loss reference fields.
The above analysis device for reasonable values of line loss targets of a power distribution network can determine line loss data sample sets of multiple analysis dimensions based on equipment parameter information and theoretical line loss result data required by theoretical line loss of the power distribution network through a first determination unit 21, then perform systematic cluster analysis on the line loss data sample sets of different analysis dimensions through a cluster analysis unit 22 to form a reference cluster value scale, then analyze the line loss data sample sets of different analysis dimensions through a selection unit 23 based on the reference cluster value scale by adopting a preset cluster algorithm to select target cluster values, and determine multiple line loss reference fields based on the target cluster values through a second determination unit 24, wherein each line loss reference field comprises multiple sub-analysis factors, and finally determine reasonable values of the line loss targets corresponding to each analysis dimension through a third determination unit 25 by utilizing a data analysis decision tree and multiple line loss reference fields. In the embodiment, the line loss data sample can be analyzed to obtain a reasonable value reference interval value of the multi-dimensional line loss marker post, so that line loss data visualization is realized, and the technical problems that the line loss of the power distribution network cannot be quantitatively managed and the management efficiency of the line loss of the power distribution network is affected due to the fact that the line loss marker post parameters of the power distribution network cannot be reasonably provided in the related technology are solved.
Optionally, the first determining unit includes: the first acquisition module is used for acquiring equipment parameter information and theoretical line loss result data required by theoretical line loss of the power distribution network, wherein the equipment parameter information comprises at least one of the following: basic wiring parameter information and wiring hanging-on distribution transformer parameter information, and theoretical line loss result data comprise at least one of the following: reporting a historical theoretical line loss value, a line loss planning reference value, a line loss experience estimated value and contemporaneous line loss daily loss data; the first screening module is used for screening the multidimensional sample data by using a data analysis tool and outputting standardized sample data; the initialization checking module is used for carrying out initial checking on the standardized sample data to obtain an initial line loss data sample set; and the second screening module is used for screening the initial line loss data sample set by adopting a preset data screening formula to obtain line loss data sample sets with a plurality of analysis dimensions.
In an embodiment of the present invention, the cluster analysis unit includes: a first determination module for determining a plurality of analysis dimensions, wherein the plurality of analysis dimensions includes at least one of: the power distribution network comprises an area, power supply quantity and line length, wherein the line length comprises the total length of lines and the length of a main line; the clustering module is used for determining the total number of clustered variables based on a plurality of analysis dimensions and clustering variables adjacent to each other by utilizing a preset variable distance formula; the cyclic clustering module is used for cyclic clustering operation so that the clustering quantity reaches the target clustering quantity and clustering work is completed; and the first analysis module is used for analyzing the line loss data sample sets under different analysis dimensions by using a data analysis tool after the clustering work is completed to form a reference cluster value scale.
As an alternative embodiment of the present invention, the selecting unit includes: the first selecting module is used for randomly selecting k data objects from n data objects as initial clustering centers based on a reference cluster value scale; the first calculation module is used for calculating the distance value between each line loss data object and the initial clustering center to obtain a plurality of clustering distance values; the second selecting module is used for selecting the clustering distance value with the smallest numerical value as a clustering dividing reference, dividing all line loss data objects and obtaining a divided line loss aggregation set; and the first calculation module is used for calculating the cluster convergence of the line loss aggregation set by using the standard measure function so as to determine a target cluster value.
In an embodiment of the present invention, the plurality of line loss reference domains includes at least one of: a reference field based on a line loss planning standard pole value, a reference field based on a historical theoretical line loss value, a reference field based on an empirical line loss estimation value and a reference field based on a synchronous line loss daily loss value.
Optionally, the plurality of sub-analysis factors includes at least one of: line loss marker post value, number of samples, and duty cycle.
Alternatively, the analysis device for reasonable values of the line loss marker post of the power distribution network further comprises: the construction unit is used for constructing a line loss scatter diagram by using a data analysis tool after determining the reasonable value of the line loss marker post corresponding to each analysis dimension; the fitting unit is used for performing multiple linear regression curve fitting based on the line loss scatter diagram to obtain a linear regression model; and the display unit is used for displaying the reasonable value of the line loss marker post corresponding to each analysis dimension and the reference interval of the reasonable value of the multidimensional line loss marker post by using a linear regression model.
The analysis device for the reasonable value of the line loss marker post of the power distribution network may further include a processor and a memory, where the first determining unit 21, the cluster analyzing unit 22, the selecting unit 23, the second determining unit 24, the third determining unit 25 and the like are stored as program units in the memory, and the processor executes the program units stored in the memory to implement corresponding functions.
The processor includes a kernel, and the kernel fetches a corresponding program unit from the memory. The kernel may be configured with one or more kernel parameters to determine a reasonable value for the line loss marker post corresponding to each analysis dimension.
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), which includes at least one memory chip.
According to another aspect of the embodiment of the present invention, there is also provided an electronic device, including: a processor; and a memory for storing executable instructions of the processor; the processor is configured to execute the analysis method of the reasonable value of the line loss marker post of the power distribution network according to any one of the above through executing the executable instructions.
According to another aspect of the embodiment of the invention, a storage medium is provided, the storage medium comprises a stored program, and the equipment where the storage medium is located is controlled to execute the analysis method of the reasonable value of the line loss marker post of the power distribution network according to any one of the above steps when the program runs.
The present application also provides a computer program product adapted to perform, when executed on a data processing device, a program initialized with the method steps of: determining a line loss data sample set of a plurality of analysis dimensions based on equipment parameter information required by theoretical line loss of the power distribution network and theoretical line loss result data; performing systematic cluster analysis on line loss data sample sets under different analysis dimensions to form a reference cluster value scale; based on a reference cluster value scale, adopting a preset cluster algorithm to analyze line loss data sample sets under different analysis dimensions so as to select a target cluster value; determining a plurality of line loss reference domains based on the target cluster value, wherein each line loss reference domain comprises a plurality of sub-analysis factors; and determining a reasonable value of the line loss marker post corresponding to each analysis dimension by utilizing the data analysis decision tree and the plurality of line loss reference fields.
The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
In the foregoing embodiments of the present invention, the descriptions of the embodiments are emphasized, and for a portion of this disclosure that is not described in detail in this embodiment, reference is made to the related descriptions of other embodiments.
In the several embodiments provided in the present application, it should be understood that the disclosed technology content may be implemented in other manners. The above-described embodiments of the apparatus are merely exemplary, and the division of the units, for example, may be a logic function division, and may be implemented in another manner, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some interfaces, units or modules, or may be in electrical or other forms.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied essentially or in part or all of the technical solution or in part in the form of a software product stored in a storage medium, including instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a removable hard disk, a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The foregoing is merely a preferred embodiment of the present invention and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present invention, which are intended to be comprehended within the scope of the present invention.
Claims (7)
1. The analysis method of the reasonable value of the line loss marker post of the power distribution network is characterized by comprising the following steps:
determining a line loss data sample set of a plurality of analysis dimensions based on equipment parameter information required by theoretical line loss of the power distribution network and theoretical line loss result data;
performing systematic cluster analysis on the line loss data sample sets under different analysis dimensions to form a reference cluster value scale, including: determining a plurality of analysis dimensions, wherein the plurality of analysis dimensions comprises: the power distribution network comprises an area, power supply quantity and line length, wherein the line length comprises a total line length and a main line length; determining the total number of clustered variables based on the plurality of analysis dimensions, and clustering variables adjacent to each other by using a preset variable distance formula; circulating clustering operation to make the clustering quantity reach the target clustering quantity and complete the clustering work; after the clustering work is completed, the line loss data sample sets under different analysis dimensions are analyzed by using a data analysis tool to form a reference cluster value scale;
based on the reference cluster value scale, adopting a preset clustering algorithm to analyze line loss data sample sets under different analysis dimensions so as to select a target cluster value;
determining a plurality of line loss reference domains based on the target cluster value, wherein each line loss reference domain comprises a plurality of sub-analysis factors, and the plurality of line loss reference domains comprise: a reference domain based on a line loss planning standard pole value, a reference domain based on a historical theoretical line loss value, a reference domain based on an empirical line loss estimation value and a reference domain based on a synchronous line loss daily loss value;
determining reasonable values of the line loss marker post corresponding to each analysis dimension by utilizing a data analysis decision tree and the plurality of line loss reference fields, carrying out multidimensional analysis on the reasonable values of the line loss marker post by utilizing multi-source theoretical line loss big data, providing a multidimensional line loss reference field list,
after the reasonable value of the line loss marker post corresponding to each analysis dimension is determined, a data analysis tool is used for constructing a line loss scatter diagram; performing multiple linear regression curve fitting based on the line loss scatter diagram to obtain a linear regression model; and displaying a reasonable line loss marker post value corresponding to each analysis dimension and a multi-dimensional line loss marker post reasonable value reference interval by using the linear regression model, wherein each dimension of the line loss marker post reasonable value reference interval corresponds to a reference boundary value.
2. The method of analysis of claim 1, wherein the step of determining a line loss data sample set for a plurality of analysis dimensions comprises:
acquiring equipment parameter information and theoretical line loss result data required by theoretical line loss of a power distribution network, wherein the equipment parameter information comprises at least one of the following: basic wiring parameter information and wiring hanging-up distribution transformer parameter information, wherein the theoretical line loss result data comprises at least one of the following: reporting a historical theoretical line loss value, a line loss planning reference value, a line loss experience estimated value and contemporaneous line loss daily loss data;
screening the multidimensional sample data by using a data analysis tool, and outputting standardized sample data;
performing initial inspection on the standardized sample data to obtain an initial line loss data sample set;
and screening the initial line loss data sample set by adopting a preset data screening formula to obtain line loss data sample sets with a plurality of analysis dimensions.
3. The method according to claim 1, wherein the step of analyzing the line loss data sample set in different analysis dimensions to select the target cluster value by using a preset clustering algorithm based on the reference cluster value scale comprises:
based on the reference cluster value scale, arbitrarily selecting k data objects from n data objects as initial cluster centers;
calculating the distance value between each line loss data object and the initial clustering center to obtain a plurality of clustering distance values;
selecting a clustering distance value with the smallest numerical value as a clustering dividing reference, and dividing all line loss data objects to obtain a divided line loss aggregation set;
and calculating the clustering convergence of the line loss cluster set by using a standard measure function so as to determine a target cluster value.
4. The method of any one of claims 1 to 3, wherein the plurality of sub-analysis factors comprises at least one of: line loss marker post value, number of samples, and duty cycle.
5. An analysis device for reasonable values of line loss marker posts of a power distribution network, which is characterized by comprising:
the first determining unit is used for determining line loss data sample sets of a plurality of analysis dimensions based on equipment parameter information required by theoretical line loss of the power distribution network and theoretical line loss result data;
the cluster analysis unit is used for performing systematic cluster analysis on the line loss data sample sets under different analysis dimensions to form a reference cluster value scale, and comprises: a first determination module configured to determine a plurality of analysis dimensions, wherein the plurality of analysis dimensions includes: the power distribution network comprises an area, power supply quantity and line length, wherein the line length comprises a total line length and a main line length; the clustering module is used for determining the total number of clustered variables based on the plurality of analysis dimensions and clustering variables adjacent to each other by utilizing a preset variable distance formula; the cyclic clustering module is used for cyclic clustering operation so that the clustering quantity reaches the target clustering quantity and clustering work is completed; the first analysis module is used for analyzing the line loss data sample sets under different analysis dimensions by using a data analysis tool after the clustering work is completed to form a reference cluster value scale;
the selecting unit is used for analyzing line loss data sample sets under different analysis dimensions by adopting a preset clustering algorithm based on the reference cluster value scale so as to select a target cluster value;
a second determining unit, configured to determine a plurality of line loss reference domains based on the target cluster value, where each line loss reference domain includes a plurality of sub-analysis factors, and the plurality of line loss reference domains includes: a reference domain based on a line loss planning standard pole value, a reference domain based on a historical theoretical line loss value, a reference domain based on an empirical line loss estimation value and a reference domain based on a synchronous line loss daily loss value;
a third determining unit, configured to determine a reasonable value of the line loss marker post corresponding to each of the analysis dimensions by using a data analysis decision tree and the plurality of line loss reference fields, perform multidimensional analysis on the reasonable value of the line loss marker post by using multi-source theoretical line loss big data, provide a multidimensional line loss reference field list,
a construction unit, configured to construct a line loss scatter plot using a data analysis tool after determining a reasonable value of the line loss marker post corresponding to each of the analysis dimensions; the fitting unit is used for performing multiple linear regression curve fitting based on the line loss scatter diagram to obtain a linear regression model; the display unit is used for displaying the reasonable line loss marker post values corresponding to each analysis dimension and the multi-dimensional line loss marker post reasonable value reference intervals by using the linear regression model, and the reference boundary values corresponding to the line loss marker post reasonable value reference intervals in each dimension.
6. An electronic device, comprising:
a processor; and
a memory for storing executable instructions of the processor;
wherein the processor is configured to perform the method of analyzing the line loss marker post reasonable value of the power distribution network of any one of claims 1 to 4 via execution of the executable instructions.
7. A storage medium, characterized in that the storage medium comprises a stored program, wherein the program, when run, controls a device in which the storage medium is located to perform the method for analyzing the reasonable value of the line loss marker post of the power distribution network according to any one of claims 1 to 4.
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| CN112163370A (en) * | 2020-09-18 | 2021-01-01 | 国网冀北电力有限公司承德供电公司 | Power distribution network line loss calculation method based on improved ASMDE algorithm |
| CN112684398B (en) * | 2020-11-23 | 2024-01-23 | 国网江苏省电力有限公司营销服务中心 | Electric energy meter operation error monitoring method and system based on dynamic line loss |
| CN113435609B (en) * | 2021-06-08 | 2022-11-22 | 国网河北省电力有限公司临漳县供电分公司 | Line loss abnormity detection method and device and terminal equipment |
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