CN114091948A - Electric energy quality comprehensive evaluation method based on multidimensional space volume and storage medium - Google Patents
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Abstract
The invention discloses a comprehensive evaluation method for electric energy quality based on a multidimensional space volume, which comprises the following steps: step S10, collecting the electric energy monitoring data with a preset collection frequency; step S11, calculating the numerical deviation proportion of each evaluation index according to the electric energy monitoring data; step S12, obtaining a grade value corresponding to each evaluation index deviation proportion according to a preset mapping table corresponding to each evaluation index deviation and grade, and obtaining the vertex coordinates of the corresponding multidimensional space cube; step S13, obtaining the electric energy quality comprehensive value of the electric energy monitoring data corresponding to the sampling time of the sampling period; and step S14, storing the electric energy quality comprehensive value and the vertex coordinate of the electric energy monitoring data into a mass database. The invention also discloses a storage medium. The implementation of the invention can improve the certainty and the intelligibility of the comprehensive evaluation of the electric energy quality.
Description
Technical Field
The invention relates to the technical field of quality monitoring and evaluation, in particular to a comprehensive evaluation method and a storage medium for electric energy quality based on a multidimensional space volume.
Background
In order to achieve the carbon neutralization goal, a large number of wind power generation plants and photovoltaic power generation plant projects need to be built, and more distributed wind power generation and photovoltaic projects can appear in a power distribution network. Due to the fact that wind power and photovoltaic project power generation are intermittent, the influence on the power quality of a regional power grid is large, and monitoring and evaluation on the power quality of the regional power grid need to be enhanced. Aiming at the problem of power quality, a series of national standards of power quality are issued by each country in turn, and national technical supervision authorities in China also issue national standards relating to five aspects of power quality, namely: the allowable deviation of the power supply voltage, the allowable fluctuation and flicker of the power supply voltage, the allowable unbalance degree of the power supply three-phase voltage, the harmonic waves of a public power grid, the allowable deviation of the power supply frequency and the like.
Because the evaluation of the power quality relates to a plurality of indexes, a power quality comprehensive evaluation index is difficult to provide so as to guide the implementation of power bidding internet surfing, pricing according to quality and high-quality optimal price. Therefore, the comprehensive evaluation of the power quality in the power market environment has important significance. The method needs to weight and merge a plurality of electric energy quality evaluation indexes into one-dimensional comprehensive evaluation indexes, various different methods can be adopted for merging, the electric energy quality evaluation methods have many research results at home and abroad, and the method mainly comprises two main objective and intelligent evaluation methods, such as an evidence theory method, a rank and ratio method, a vector algebra method, a method based on a probability distance method, a fuzzy comprehensive evaluation method, a method combining probability statistics and fuzzy numbers, an analytic hierarchy process, a matter element analysis method, a method based on genetic projection pursuit, an artificial neural network method and the like.
However, because of the objective irrelevance of each single index of the power quality, the relative weight is difficult to determine, the existing various power quality comprehensive assessment methods consider the mutual influence among the indexes when data fusion is carried out, meanwhile, uncertain factors such as subjective fuzzy evaluation and the like are added, and most of the indexes are fused by giving different authorities, so the assessment result has subjective randomness, is not intuitive enough and is difficult to understand.
Disclosure of Invention
The invention aims to provide a comprehensive evaluation method and a storage medium for electric energy quality based on a multidimensional space volume, which can combine the comprehensive evaluation result of the electric energy quality with a multidimensional space and can better improve the certainty and the understandability of the comprehensive evaluation of the electric energy quality.
In order to solve the above technical problems, an aspect of the present invention provides a comprehensive evaluation method for power quality based on a multidimensional space volume, which includes the following steps:
step S10, collecting the electric energy monitoring data with a preset collection frequency;
step S11, calculating the numerical deviation proportion of each corresponding evaluation index according to the collected electric energy monitoring data each time; the evaluation index includes a plurality of the following indices: voltage deviation, voltage flicker, frequency deviation, three-phase unbalance and total harmonic distortion rate indexes;
step S12, obtaining a grade value corresponding to each evaluation index deviation proportion according to a preset mapping table corresponding to each evaluation index deviation and grade, establishing a multidimensional space cube according to the quantity of the evaluation indexes and the grade values, and obtaining the vertex coordinates of the multidimensional space cube;
step S13, calculating according to the vertex coordinates of the multidimensional space cube to obtain the electric energy quality comprehensive value of the electric energy monitoring data corresponding to the sampling time of the sampling period;
and step S14, storing the electric energy quality comprehensive value and the vertex coordinate of the electric energy monitoring data into a mass database.
Preferably, further comprising:
generating a mapping table of the deviation of each evaluation index and the corresponding level in advance, wherein each evaluation index is divided into a preset number of levels in the mapping table, each level corresponds to the numerical value deviation proportion range of the evaluation index, each level corresponds to a level value, and the level values of the levels corresponding to different evaluation indexes are the same.
Preferably, the vertex coordinates P obtained in step S12 are expressed as: (P)1，P2，P3，...，Pn) Wherein P isnAnd the grade value corresponding to each selected evaluation index.
Preferably, in the step S13, the following formula is adoptedCalculating to obtain the electric energy quality comprehensive value P of the electric energy monitoring data corresponding to the sampling time t of the sampling periodt:
Pt＝(P1*P2*P3*...*Pn)/(K*n)；
Wherein, K is the total number of grades of each evaluation index, and n is the total number of selected evaluation indexes.
Preferably, further comprising:
accessing a mass database, and finding out the comprehensive value P of the electric energy quality at all sampling moments in a period of timetAnd calculating to obtain the electric energy quality comprehensive index P in the time period by the following formula:
wherein t1 and t2 are the beginning and the end of the time period; and T is the acquisition frequency of the electric energy monitoring data.
Preferably, further comprising:
accessing a mass database, selecting a vertex coordinate of a multidimensional space cube at a sampling moment, mapping the vertex coordinate to the multidimensional space cube, and displaying the multidimensional space cube;
selecting the comprehensive value P of the electric energy quality at each sampling moment in a period of timetAnd forming a distribution curve for displaying; or
And selecting the comprehensive indexes P of the electric energy quality in a plurality of time periods, and forming a distribution curve for displaying.
Accordingly, in another aspect of the present invention, there is also provided a computer-readable storage medium having stored thereon a series of computer-executable instructions that, when executed by one or more computing devices, cause the one or more computing devices to implement a method as described above.
The embodiment of the invention has the following beneficial effects:
the invention provides a comprehensive evaluation method of electric energy quality based on a multidimensional space volume and a storage medium. In the embodiment of the invention, each evaluation index is used as a vector, and the index vectors construct an N-dimensional space, so that the irrelevance among the evaluation indexes can be reflected, meanwhile, the judgment value of the index is mapped to the numerical value of the N-dimensional space coordinate, and a group of measurement values of the index are mapped to one surface in the N-dimensional space; the volume of the space formed by the plane, the origin and each coordinate plane is evaluated.
In the embodiment of the invention, the comprehensive value of the electric energy quality is calculated by timing monitoring and synchronization and is recorded into a mass database. Related personnel can form a distribution curve chart of the comprehensive evaluation value of the power quality by searching the mass database, and can also check the multidimensional space cube corresponding to each sampling point, so that the understandability of the power quality change is improved.
In conclusion, the method and the system have the advantages that the same authority is given to a plurality of different evaluation indexes for fusion, so that the subjective randomness of weighting the indexes in an evaluation system can be overcome; meanwhile, a power quality comprehensive evaluation curve can be given instead of a single power quality comprehensive numerical value, so that a specific power quality comprehensive numerical value can be obtained from curve distribution, and understandability of power quality change is improved by observing the graphic change of power quality comprehensive numerical value distribution by a user.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is within the scope of the present invention for those skilled in the art to obtain other drawings based on the drawings without inventive exercise.
Fig. 1 is a schematic main flow chart of an embodiment of a comprehensive evaluation method for power quality based on a multidimensional space volume provided by the invention;
fig. 2 is a schematic view of a multi-dimensional spatial volume according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments.
As shown in fig. 1, a main flow diagram of an embodiment of a comprehensive evaluation method for power quality based on a multidimensional space volume provided by the present invention is shown; referring to fig. 2 together, in this embodiment, the method includes the following steps:
step S10, collecting the electric energy monitoring data with a preset collection frequency; in a specific example, considering that the collection frequency of the power quality monitoring data is very high, generally two minutes is taken as a sampling period, so that the accumulation of the power quality monitoring data is increasing with time, and a mass storage mechanism is required to store the power quality monitoring data.
Step S11, calculating the numerical deviation ratio of each corresponding evaluation index (the percentage of the normal value of the index) according to the collected electric energy monitoring data each time; the evaluation index includes a plurality of the following indices: voltage deviation, voltage flicker, frequency deviation, three-phase unbalance and total harmonic distortion rate indexes;
step S12, obtaining a grade value corresponding to each evaluation index deviation proportion according to a preset mapping table corresponding to each evaluation index deviation and grade, establishing a multidimensional space cube according to the quantity of the evaluation indexes and the grade values, and obtaining the vertex coordinates of the multidimensional space cube;
it can be understood that, in the present invention, a mapping table for mapping the deviation of each evaluation index to a level needs to be generated in advance, in the mapping table, each evaluation index is divided into a predetermined number of levels, each level corresponds to a numerical deviation proportion range of the evaluation index, each level corresponds to a level value, and the level values of the levels corresponding to different evaluation indexes are the same.
More specifically, in one example, the subdivision may be performed according to the electric energy quality index evaluation value range specified according to the country; generally, the voltage deviation is less than or equal to 10 percent, which is qualified; the voltage flicker is less than or equal to 10 percent, and the product is qualified; the frequency deviation is less than or equal to 10 percent, and the product is qualified; the three-phase unbalance degree is less than or equal to 10 percent and is qualified; the total harmonic distortion rate is less than or equal to 10 percent, and the product is qualified. In the present invention, the comprehensive evaluation weights of the respective indexes of the power quality are subjected to an equal normalization process, and as shown in the following table, a classification table showing the grades of the respective evaluation indexes (the proportions of the range values are all calculated in%:
table 1 evaluation index deviation and grade correspondence mapping table
From the table above, it can be seen that the levels corresponding to the deviations of the indexes of the power quality are divided into 8 levels, wherein the acceptable levels include 4 levels (respectively corresponding to the optimal level, the good level and the acceptable level), and the unacceptable levels include 4 levels (respectively corresponding to the unacceptable level, the poor level, the very poor level and the worst level), and the deviation ranges of the indexes are converted into uniform values according to the proportion and correspond to the points (0, 8) on the coordinate axes of the indexes.
Considering the irrelevancy of indexes, each index is taken as a vector, and the group of vectors are linearly independent. Taking the above table as an example, the 5 power quality indicators form a 5-dimensional space, and the coordinate of each dimension is the above-mentioned rank value of the coordinate. Obviously, if there are N indices, one N-dimensional space can be constructed, and when N is 3, the constructed 3-dimensional space is as shown in fig. 2. Wherein, under a coordinate system (voltage deviation, frequency deviation and voltage flicker), the corresponding vertex value P of the large cube is (8,8, 8); and the blue cube represents a primary power quality measurement with vertex PtIs (4,3, 2).
Therefore, in this step, the obtained vertex coordinates P are expressed as: (P)1，P2，P3，...，Pn) Wherein P isnAnd the grade value corresponding to each selected evaluation index.
Step S13, calculating according to the vertex coordinates of the multidimensional space cube to obtain the electric energy quality comprehensive value of the electric energy monitoring data corresponding to the sampling time of the sampling period;
in a specific example, in the step S13, the following formula is adopted to perform calculation, and the power quality comprehensive value P of the power monitoring data corresponding to the sampling time t of the sampling period is obtainedt:
Pt＝(P1*P2*P3*...*Pn)/(K*n)；
Where K is the total number of ranks per evaluation index (8 in the example shown in the above table), and n is the total number of evaluation indexes selected (5 or less).
And step S14, storing the electric energy quality comprehensive value and the vertex coordinate of the electric energy monitoring data into a mass database.
It is understood that in the embodiment of the present invention, the mass database may be further accessed to obtain more data or to display the corresponding data.
In a specific example, the method further comprises:
accessing a mass database, and finding out the comprehensive value P of the electric energy quality at all sampling moments in a period of timetAnd calculating to obtain the electric energy quality comprehensive index P in the time period by the following formula:
wherein t1 and t2 are the beginning and the end of the time period; and T is the acquisition frequency of the electric energy monitoring data.
In a specific example, the method further comprises:
accessing a mass database, selecting a vertex coordinate of a multidimensional space cube at a sampling moment, mapping the vertex coordinate to the multidimensional space cube, and displaying the multidimensional space cube;
selecting the comprehensive value P of the electric energy quality at each sampling moment in a period of timetAnd forming a distribution curve for exhibitionShown in the specification; or
And selecting the comprehensive indexes P of the electric energy quality in a plurality of time periods, and forming a distribution curve for displaying.
It can be understood that the method adopted by the invention overcomes the subjective randomness of weighting the indexes in the evaluation system, and endows the indexes with the same authority for fusion; meanwhile, an electric energy quality comprehensive evaluation curve (or multi-dimensional space display of each sampling point) can be given instead of a single electric energy quality comprehensive numerical value, so that a specific electric energy quality comprehensive numerical value can be obtained from curve distribution, and understandability of electric energy quality change is improved by observing the pattern change of the electric energy quality comprehensive numerical value distribution by a user.
Accordingly, in another aspect of the present invention, a computer-readable storage medium is further provided, on which a series of computer-executable instructions are stored, which when executed by one or more computing devices, cause the one or more computing devices to implement the method as described in the foregoing fig. 1 and fig. 2. For more details, reference may be made to and combined with the foregoing description of fig. 1 and fig. 2, which are not repeated herein.
The embodiment of the invention has the following beneficial effects:
the invention provides a comprehensive evaluation method of electric energy quality based on a multidimensional space volume and a storage medium. In the embodiment of the invention, each evaluation index is used as a vector, and the index vectors construct an N-dimensional space, so that the irrelevance among the evaluation indexes can be reflected, meanwhile, the judgment value of the index is mapped to the numerical value of the N-dimensional space coordinate, and a group of measurement values of the index are mapped to one surface in the N-dimensional space; the volume of the space formed by the plane, the origin and each coordinate plane is evaluated.
In the embodiment of the invention, the comprehensive value of the electric energy quality is calculated by timing monitoring and synchronization and is recorded into a mass database. Related personnel can form a distribution curve chart of the comprehensive evaluation value of the power quality by searching the mass database, and can also check the multidimensional space cube corresponding to each sampling point, so that the understandability of the power quality change is improved.
In conclusion, the method and the system have the advantages that the same authority is given to a plurality of different evaluation indexes for fusion, so that the subjective randomness of weighting the indexes in an evaluation system can be overcome; meanwhile, a power quality comprehensive evaluation curve can be given instead of a single power quality comprehensive numerical value, so that a specific power quality comprehensive numerical value can be obtained from curve distribution, and understandability of power quality change is improved by observing the graphic change of power quality comprehensive numerical value distribution by a user.
While the invention has been described in connection with what is presently considered to be the most practical and preferred embodiment, it is to be understood that the invention is not to be limited to the disclosed embodiment, but on the contrary, is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims.
Claims (7)
1. A comprehensive electric energy quality evaluation method based on a multidimensional space volume is characterized by comprising the following steps:
step S10, collecting the electric energy monitoring data with a preset collection frequency;
step S11, calculating the numerical deviation proportion of each corresponding evaluation index according to the collected electric energy monitoring data each time; the evaluation index includes a plurality of the following indices: voltage deviation, voltage flicker, frequency deviation, three-phase unbalance and total harmonic distortion rate indexes;
step S12, obtaining a grade value corresponding to each evaluation index deviation proportion according to a preset mapping table corresponding to each evaluation index deviation and grade, establishing a multidimensional space cube according to the quantity of the evaluation indexes and the grade values, and obtaining the vertex coordinates of the multidimensional space cube;
step S13, calculating according to the vertex coordinates of the multidimensional space cube to obtain the electric energy quality comprehensive value of the electric energy monitoring data corresponding to the sampling time of the sampling period;
and step S14, storing the electric energy quality comprehensive value and the vertex coordinate of the electric energy monitoring data into a mass database.
2. The method of claim 1, further comprising:
generating a mapping table of the deviation of each evaluation index and the corresponding level in advance, wherein each evaluation index is divided into a preset number of levels in the mapping table, each level corresponds to the numerical value deviation proportion range of the evaluation index, each level corresponds to a level value, and the level values of the levels corresponding to different evaluation indexes are the same.
3. The method according to claim 2, wherein the vertex coordinate P obtained in step S12 is expressed as: (P)1，P2，P3，...，Pn) Wherein P isnAnd the grade value corresponding to each selected evaluation index.
4. The method according to claim 3, wherein in step S13, the following formula is used to calculate the integrated power quality value P of the power monitoring data corresponding to the sampling time t of the sampling periodt:
Pt＝(P1*P2*P3*...*Pn)/(K*n)；
Wherein, K is the total number of grades of each evaluation index, and n is the total number of selected evaluation indexes.
5. The method of claim 4, further comprising:
accessing a mass database, and finding out the comprehensive value P of the electric energy quality at all sampling moments in a period of timetAnd calculating to obtain the electric energy quality comprehensive index P in the time period by the following formula:
wherein t1 and t2 are the beginning and the end of the time period; and T is the acquisition frequency of the electric energy monitoring data.
6. The method of any of claims 1 to 5, further comprising:
accessing a mass database, selecting a vertex coordinate of a multidimensional space cube at a sampling moment, mapping the vertex coordinate to the multidimensional space cube, and displaying the multidimensional space cube;
selecting the comprehensive value P of the electric energy quality at each sampling moment in a period of timetAnd forming a distribution curve for displaying; or
And selecting the comprehensive indexes P of the electric energy quality in a plurality of time periods, and forming a distribution curve for displaying.
7. A computer-readable storage medium having stored thereon a series of computer-executable instructions that, when executed by one or more computing devices, cause the one or more computing devices to implement the method of any of claims 1-6.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101726678A (en) * | 2008-10-30 | 2010-06-09 | 华北电力科学研究院有限责任公司 | Electricity quality evaluation system and method |
| CN107491832A (en) * | 2017-07-12 | 2017-12-19 | 国网上海市电力公司 | Energy quality steady-state index prediction method based on chaology |
| CN110909983A (en) * | 2019-10-25 | 2020-03-24 | 浙江工业大学 | Multidimensional assessment method for electric energy quality of active power distribution network |
| CN112288293A (en) * | 2020-11-03 | 2021-01-29 | 浙江华电器材检测研究所有限公司 | Comprehensive evaluation method for electric energy quality of large charging station |
-
2021
- 2021-11-29 CN CN202111429917.XA patent/CN114091948A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101726678A (en) * | 2008-10-30 | 2010-06-09 | 华北电力科学研究院有限责任公司 | Electricity quality evaluation system and method |
| CN107491832A (en) * | 2017-07-12 | 2017-12-19 | 国网上海市电力公司 | Energy quality steady-state index prediction method based on chaology |
| CN110909983A (en) * | 2019-10-25 | 2020-03-24 | 浙江工业大学 | Multidimensional assessment method for electric energy quality of active power distribution network |
| CN112288293A (en) * | 2020-11-03 | 2021-01-29 | 浙江华电器材检测研究所有限公司 | Comprehensive evaluation method for electric energy quality of large charging station |
Non-Patent Citations (5)
| Title |
|---|
| T. MARTINS 等: "Detection of Power Quality Disturbance Using a Multidimensional Approach in an Embedded System", IEEE LATIN AMERICA TRANSACTIONS, vol. 17, no. 7, 31 July 2019 (2019-07-31), pages 1102 - 1108, XP011761064, DOI: 10.1109/TLA.2019.8931197 * |
| 中国电源学会: "团体标准-公用交流电网稳态电能质量综合指标评估方法", vol. 1007, 1 September 2021, pages: 1 - 17 * |
| 刘颖英;戴平;徐永海;刘云峰;: "电能质量综合评估方法比较", 电力自动化设备, vol. 28, no. 12, 10 December 2008 (2008-12-10), pages 93 - 100 * |
| 李如琦;苏浩益;曲振旭;: "核向量空间模型在电能质量综合评估中的应用", 电力系统保护与控制, vol. 40, no. 1, 1 January 2012 (2012-01-01), pages 72 - 76 * |
| 阴艳超;吴仁杰;常斌磊;: "复杂电网电能质量知识云评价服务模型与方法", 电力自动化设备, vol. 38, no. 05, 4 May 2018 (2018-05-04), pages 241 - 247 * |
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