CN102495858A - Power quality index 95 maximum probability value acquisition method and system - Google Patents
Power quality index 95 maximum probability value acquisition method and system Download PDFInfo
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- CN102495858A CN102495858A CN2011103724567A CN201110372456A CN102495858A CN 102495858 A CN102495858 A CN 102495858A CN 2011103724567 A CN2011103724567 A CN 2011103724567A CN 201110372456 A CN201110372456 A CN 201110372456A CN 102495858 A CN102495858 A CN 102495858A
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- 238000000034 method Methods 0.000 title claims abstract description 28
- 238000012544 monitoring process Methods 0.000 claims description 4
- 230000009466 transformation Effects 0.000 claims 1
- 229910052704 radon Inorganic materials 0.000 abstract 2
- SYUHGPGVQRZVTB-UHFFFAOYSA-N radon atom Chemical compound [Rn] SYUHGPGVQRZVTB-UHFFFAOYSA-N 0.000 abstract 2
- 238000011426 transformation method Methods 0.000 abstract 1
- 238000010586 diagram Methods 0.000 description 4
- 238000012216 screening Methods 0.000 description 4
- 238000013459 approach Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 239000012467 final product Substances 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
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- 238000005315 distribution function Methods 0.000 description 1
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Abstract
The invention discloses a power quality index 95 maximum probability value acquisition method and a system. The method includes steps of selecting power quality indexes which obey normal distribution as radon variables; selecting a time range; selecting raw data within the time range from raw data corresponding to the random variables as radon samples; and computing a 95 maximum probability value, corresponding to the time range, of the random variables according to a formula of X(95%)=Xi(95%)Xsigma+mu. A normal distribution theory and a standard transformation method of the normal distribution theory are introduced into the field of power quality, sorting is omitted, and the problem that sorting time is long when massive data are processed in the prior art is solved.
Description
Technical field
The invention belongs to the Electric automation technology field, relate in particular to a kind of big value-acquiring method of power quality index 95 probability and system.
Background technology
In IEC 61000-4-7 (1991) standard, just mention the big value of 95 probability as the power quality parameter evaluation index, EN50160, IEC 61000-4-30, GB were also mentioned successively and had been enriched the theory of different power quality indexs being assessed with the big value of 95 probability afterwards.In electric energy quality monitoring analysis and assessment system, the big value role of 95 probability ever more important, great majority are got the big value of 95 probability and are weighed foundation as power quality index both at home and abroad now.
At present the big value of 95 probability of main flow obtain the mode that adopts the ordering screening: the raw data of the power quality index that collects is arranged in order by from big to small order; Remove preceding 5% data, get the 95 probability big value of the maximal value of remaining data then as this power quality index.When having the magnanimity raw data in the power quality data storehouse, the mode of above-mentioned ordering screening can expend the more time in ordering.
Summary of the invention
In view of this, the purpose of the embodiment of the invention is to provide a kind of big value-acquiring method of power quality index 95 probability and system, to solve prior art when handling to the magnanimity raw data, the more problem consuming time owing to sort.
For realizing above-mentioned purpose, the embodiment of the invention provides following technical scheme:
The big value-acquiring method of a kind of power quality index 95 probability comprises:
The power quality index of selecting Normal Distribution is as stochastic variable;
The select time scope;
From the corresponding raw data of said stochastic variable, choose and drop on the interior raw data of said time range as random sample;
According to formula X (95%)=ξ (95%) * σ+μ, calculate the big value of 95 probability of said stochastic variable correspondence in said time range;
Wherein:
The big value of 95 probability of the said stochastic variable of said X (95%) expression correspondence in said time range;
95% probability value corresponding in said ξ (95%) the expression standardized normal distribution;
Said μ representes the mean value of said random sample;
Said σ representes the standard deviation of said random sample.
Correspondingly; The embodiment of the invention also provides the big value of a kind of power quality index 95 probability to obtain system; Said system comprises selects module and computing module; Said selection module comprises power quality index selected cell, time range selected cell and data selecting unit, and said computing module comprises the desired value computing unit, wherein:
Said power quality index selected cell, the power quality index that is used to select Normal Distribution is as stochastic variable;
Said time range selected cell is used for the select time scope;
Said data selecting unit is used for from the corresponding raw data of said stochastic variable, chooses and drops on the interior raw data of said time range as random sample;
Said desired value computing unit; Be used for according to formula X (95%)=ξ (95%) * σ+μ; Calculate the corresponding big value of 95 probability of power quality index of the said Normal Distribution of selecting; The corresponding big value of 95 probability of power quality index of the said Normal Distribution of selecting of said X (95%) expression; 95% probability value corresponding in said ξ (95%) the expression standardized normal distribution, said μ representes the mean value of said random sample, said σ representes the standard deviation of said random sample.
Therefore; Compare with the mode that obtains the big value of 95 probability in the prior art; The technical scheme that the embodiment of the invention provided need not sort; Thereby solved prior art when handling mass data because ordering and more problem consuming time, greatly improved the Normal Distribution characteristic power quality index the big value of 95 probability obtain efficient.
Description of drawings
In order to be illustrated more clearly in the embodiment of the invention or technical scheme of the prior art; To do to introduce simply to the accompanying drawing of required use in embodiment or the description of the Prior Art below; Obviously, the accompanying drawing in describing below is some embodiments of the present invention, for those of ordinary skills; Under the prerequisite of not paying creative work, can also obtain other accompanying drawing according to these accompanying drawings.
Fig. 1 is the big value-acquiring method process flow diagram of power quality index 95 probability that the embodiment of the invention provides;
Fig. 2 is another process flow diagram of the big value-acquiring method of power quality index 95 probability that the embodiment of the invention provides;
Fig. 3 is the another process flow diagram of the big value-acquiring method of power quality index 95 probability that the embodiment of the invention provides;
Fig. 4 is that the big value of power quality index 95 probability that the embodiment of the invention provides is obtained the system architecture synoptic diagram;
Fig. 5 is that the big value of power quality index 95 probability that the embodiment of the invention provides is obtained another structural representation of system;
Fig. 6 is that the big value of power quality index 95 probability that the embodiment of the invention provides is obtained the another structural representation of system.
Embodiment
For the purpose, technical scheme and the advantage that make the embodiment of the invention clearer; To combine the accompanying drawing in the embodiment of the invention below; Technical scheme in the embodiment of the invention is carried out clear, intactly description; Obviously, described embodiment is the present invention's part embodiment, rather than whole embodiment.Based on the embodiment among the present invention, those of ordinary skills are not making the every other embodiment that is obtained under the creative work prerequisite, all belong to the scope of the present invention's protection.
Prior art adopts the ordering screening as the main stream approach of obtaining the big value of 95 probability.But when having the magnanimity raw data in the power quality data storehouse, the mode of this kind ordering screening can expend the more time.
Power quality index can comprise voltage deviation, frequency departure, voltage fluctuation and flickering index, relative harmonic content and effective value index, imbalance of three-phase voltage degree index etc.The inventor is through a large amount of research and verify discovery, in power quality index, and the variation tendency Normal Distribution of much electricity quality index.For example voltage deviation and frequency departure, they drop in certain interval major part, and have and approach zero trend, and the probability that drops on the null value both sides is at random, and the probability that more far occurs from null value is more little.And other power quality indexs, for example voltage fluctuation and flickering index, relative harmonic content and effective value index, imbalance of three-phase voltage degree index or the like are also obeyed identical distribution, therefore, can adopt normal distribution and correlation theory thereof to obtain the big value of 95 probability.
In view of this, the invention provides a kind of big value-acquiring method of power quality index 95 probability based on normal distribution and correlation theory thereof, with solve prior art when handling mass data because ordering and more problem consuming time.
See also Fig. 1, said method comprises the steps: at least
S1: the power quality index of selecting Normal Distribution is as stochastic variable X.
Before address; Voltage deviation, frequency departure, voltage fluctuation and flickering index, relative harmonic content and effective value index, imbalance of three-phase voltage degree index etc. be Normal Distribution all; Therefore; The power quality index of above-mentioned Normal Distribution can comprise various conventional power quality indexs, flickering during like phase voltage, frequency, imbalance of three-phase voltage degree, harmonic voltage resultant distortion rate, 2～25 subharmonic voltage containing ratios, 2～25 subharmonic current content, length, flickering in short-term etc.
In addition, in other embodiment of the present invention, can pass through some particular selecting methods,, from power quality index to be selected, select the power quality index of Normal Distribution like W checking, D checking etc.
S2: select time scope T.
Consider accuracy, when selecting above-mentioned time range T, guarantee to comprise in the T 60 raw data at least.
S3: from the corresponding raw data of above-mentioned stochastic variable, choose and drop on the interior raw data of above-mentioned time range as random sample.
To choosing of raw data, can realize through data-interface.Above-mentioned data-interface can obtain raw data from multiple power quality index data source such as electric energy quality monitoring terminal, database, data file, and chooses the raw data that drops in the above-mentioned time range.
Above-mentioned raw data can be a historical data, also can be real time data.In practical application, general if obtain the big value of 95 probability only to the historical data in the database based on electric energy quality monitoring system, and during based on the terminal, generally go to obtain the big value of 95 probability according to real time data.
S4:, calculate the big value of 95 probability of above-mentioned stochastic variable correspondence in above-mentioned time range T according to formula X (95%)=ξ (95%) * σ+μ (formula 1).Wherein:
X (95%) is the stochastic variable selected among the step S1 corresponding big value of 95 probability in above-mentioned time T,
ξ (95%) is 95% a probability value corresponding in the standardized normal distribution,
μ is the mean value of above-mentioned random sample,
σ is the standard deviation of above-mentioned random sample.
Therefore; The method that the above embodiment of the present invention provided is not owing to need sort; Thereby solved prior art when handling mass data because ordering and more problem consuming time, greatly improved the Normal Distribution characteristic power quality index the big value of 95 probability obtain efficient.
To the origin of above-mentioned formula 1 be described in detail below:
Known, if stochastic variable X Normal Distribution N (μ, σ
2), then
Obey standardized normal distribution, promptly
You can use a random real number ξ represents the
ie
(equation 2).Like this, above-mentioned (X-μ)/σ～N (0,1) deformable is ξ～N (0,1).Expression that the distribution function of standardized normal distribution can be used
.
In addition; Known,
(formula 3).
Wherein, P{X≤X (95%) } expression stochastic variable X is smaller or equal to the probability of X (95%).And known, stochastic variable X is 95% smaller or equal to the probability of X (95%) in the present invention.
Get final product with ξ (95%) expression above-mentioned
:
And further distortion obtains above-mentioned formula 1:X (95%)=ξ (95%) * σ+μ.
And can get through formula 3 and 4:
(formula 5);
In the standardized normal distribution table, can find 95% value corresponding ξ (95%) to be specially 1.645 again.
Therefore formula 1 finally can turn to: X (95%)=1.645* σ+μ (formula 6).
Because μ and σ can obtain through calculating, therefore,, just can finally obtain the concrete value of X (95%) as long as with the concrete value substitution formula 6 of μ and σ, also promptly got access to the big value of 95 probability of stochastic variable X correspondence in time range T.
In other embodiment of the present invention, see also Fig. 2, before step S4, also can comprise:
S3 ': average value mu and the standard deviation sigma of asking for above-mentioned random sample.
If random sample comprises X
1, X
2... X
nDeng n sample observations, represent i sample observations with i, then:
Usable samples average
is estimated above-mentioned μ.Asking for of above-mentioned
can be adopted the arithmetic mean algorithm, and its formula is:
Certainly, a said n sample observations is n the raw data that comprises in the time range T.Usable samples variance S
2Estimate above-mentioned σ
2, can ask for through following formula:
Then to above-mentioned S
2Get arithmetic root value and promptly get σ.In other embodiment of the present invention, see also Fig. 3, above-mentioned all embodiment also can comprise:
S5: show the big value of above-mentioned power quality index 95 probability.
Corresponding with it, the embodiment of the invention also provides the big value of power quality index 95 probability to obtain system.
Fig. 4 shows a kind of structure of said system; Comprise: select module 100 and computing module 200; Select module 100 to comprise power quality index selected cell 110, time range selected cell 120 and data selecting unit 130 again; And computing module 200 comprises desired value computing unit 210, wherein:
Power quality index selected cell 110 is used to provide an interface of selecting power quality index, with the power quality index of selecting Normal Distribution as stochastic variable;
Time range selected cell 120, be used to provide one access time scope the interface, with the select time scope;
Desired value computing unit 210 is used for according to formula X (95%)=ξ (95%) * σ+μ, calculates the corresponding big value of 95 probability of power quality index of the above-mentioned Normal Distribution of selecting.
Said system specifically can be passed through realizations such as computing machine, single-chip microcomputer.
Concrete related content sees also aforementioned record, does not give unnecessary details at this.
In other embodiment of the present invention, see also Fig. 5, aforementioned calculation module 200 also can comprise the mean value that calculates above-mentioned random sample and the parameters of formula computing unit 220 of standard deviation.
In other embodiment of the present invention, see also Fig. 6, the system in the foregoing description also can comprise the display unit 300 that shows the big value of above-mentioned power quality index 95 probability.
For the disclosed system of embodiment, because it is corresponding with the embodiment disclosed method, so description is fairly simple, relevant part is partly explained referring to method and is got final product in this instructions.
The above only is a preferred implementation of the present invention; Should be pointed out that for those skilled in the art, under the prerequisite that does not break away from the principle of the invention; Can also make some improvement and retouching, these improvement and retouching also should be regarded as protection scope of the present invention.
Claims (11)
1. the big value-acquiring method of power quality index 95 probability is characterized in that, comprising:
The power quality index of selecting Normal Distribution is as stochastic variable;
The select time scope;
From the corresponding raw data of said stochastic variable, choose and drop on the interior raw data of said time range as random sample;
According to formula X (95%)=ξ (95%) * σ+μ, calculate the big value of 95 probability of said stochastic variable correspondence in said time range;
Wherein:
The big value of 95 probability of the said stochastic variable of said X (95%) expression correspondence in said time range;
95% probability value corresponding in said ξ (95%) the expression standardized normal distribution;
Said μ representes the mean value of said random sample;
Said σ representes the standard deviation of said random sample.
2. method according to claim 1 is characterized in that, also comprises:
Show the big value of said power quality index 95 probability.
3. method according to claim 1; It is characterized in that the acquisition process of said formula X (95%)=ξ (95%) * σ+μ comprises: will obtain said formula X (95%)=ξ (95%) * σ+μ based on formula
distortion of normal distribution and standardization transformation theory thereof.
4. method according to claim 1 is characterized in that,
Said ξ (95%) is specially 1.645.
5. like each described method of claim 1-4, it is characterized in that, according to formula X (95%)=ξ (95%) * σ+μ, calculate before the big value of 95 probability of said stochastic variable correspondence in said time range, also comprise said:
Ask for the mean value and the standard deviation of said random sample.
6. ask 5 described methods according to right, it is characterized in that, the embodiment of the power quality index of said selection Normal Distribution comprises:
Select the power quality index of Normal Distribution according to W checking or D checking system of selection.
7. method according to claim 5 is characterized in that, said raw data comprises: at least a in the historical data in the historical data base and the real time data of monitoring terminal.
8. method according to claim 4 is characterized in that, the value of said ξ (95%) is specifically obtained through searching the standardized normal distribution table.
9. the big value of power quality index 95 probability is obtained system; It is characterized in that comprise and select module and computing module, said selection module comprises power quality index selected cell, time range selected cell and data selecting unit; Said computing module comprises the desired value computing unit, wherein:
Said power quality index selected cell, the power quality index that is used to select Normal Distribution is as stochastic variable;
Said time range selected cell is used for the select time scope;
Said data selecting unit is used for from the corresponding raw data of said stochastic variable, chooses and drops on the interior raw data of said time range as random sample;
Said desired value computing unit; Be used for according to formula X (95%)=ξ (95%) * σ+μ; Calculate the corresponding big value of 95 probability of power quality index of the said Normal Distribution of selecting; The corresponding big value of 95 probability of power quality index of the said Normal Distribution of selecting of said X (95%) expression; 95% probability value corresponding in said ξ (95%) the expression standardized normal distribution, said μ representes the mean value of said random sample, said σ representes the standard deviation of said random sample.
10. system according to claim 9 is characterized in that, also comprises the display unit that shows the big value of said power quality index 95 probability.
11. system according to claim 9 is characterized in that, said computing module also comprises the mean value that calculates said random sample and the parameters of formula computing unit of standard deviation.
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| CN103412867A (en) * | 2013-06-24 | 2013-11-27 | 徐州中矿奥特麦科技有限公司 | Filtering device and filtering algorithm based on 3-sigma rule |
| CN104008310A (en) * | 2014-06-17 | 2014-08-27 | 河北经贸大学 | Electric energy quality steady state index calculation method |
| CN106324344A (en) * | 2016-09-22 | 2017-01-11 | 国家电网公司 | Instantaneously measured waveform-based nonlinear load electricity consumption characteristic analysis system and method |
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| CN108051664A (en) * | 2017-11-15 | 2018-05-18 | 全球能源互联网研究院有限公司 | A kind of equipment for monitoring power quality |
| CN105607029B (en) * | 2016-01-08 | 2018-08-03 | 江苏省电力公司电力科学研究院 | A kind of electric power metering device running quality trend analysis based on standard deviation |
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2011
- 2011-11-21 CN CN2011103724567A patent/CN102495858A/en active Pending
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|---|---|---|---|---|
| CN103412867A (en) * | 2013-06-24 | 2013-11-27 | 徐州中矿奥特麦科技有限公司 | Filtering device and filtering algorithm based on 3-sigma rule |
| CN104008310A (en) * | 2014-06-17 | 2014-08-27 | 河北经贸大学 | Electric energy quality steady state index calculation method |
| CN104008310B (en) * | 2014-06-17 | 2017-01-18 | 河北经贸大学 | Electric energy quality steady state index calculation method |
| CN105607029B (en) * | 2016-01-08 | 2018-08-03 | 江苏省电力公司电力科学研究院 | A kind of electric power metering device running quality trend analysis based on standard deviation |
| CN106324344A (en) * | 2016-09-22 | 2017-01-11 | 国家电网公司 | Instantaneously measured waveform-based nonlinear load electricity consumption characteristic analysis system and method |
| CN107765206A (en) * | 2017-10-12 | 2018-03-06 | 广西电网有限责任公司电力科学研究院 | A kind of appraisal procedure of equipment for monitoring power quality running status |
| CN108051664A (en) * | 2017-11-15 | 2018-05-18 | 全球能源互联网研究院有限公司 | A kind of equipment for monitoring power quality |
| CN110487315A (en) * | 2019-08-28 | 2019-11-22 | 广东核电合营有限公司 | A kind of analysis system and method for instrument drift |
| CN110487315B (en) * | 2019-08-28 | 2021-09-28 | 广东核电合营有限公司 | System and method for analyzing instrument drift |
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