CN110008443A - A kind of optimal quantile of the wind power probability based on EMD determines method - Google Patents
A kind of optimal quantile of the wind power probability based on EMD determines method Download PDFInfo
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- CN110008443A CN110008443A CN201910336865.8A CN201910336865A CN110008443A CN 110008443 A CN110008443 A CN 110008443A CN 201910336865 A CN201910336865 A CN 201910336865A CN 110008443 A CN110008443 A CN 110008443A
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- probability
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/06—Electricity, gas or water supply
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
- Y02E40/70—Smart grids as climate change mitigation technology in the energy generation sector
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
Abstract
The present invention relates to a kind of optimal quantiles of wind power probability based on EMD to determine method, comprising steps of obtaining the optimal quantile of wind power probability by minimizing EMD, continuous probability density function is separated into several probability density points；Solve the corresponding probability of each optimal quantile.The approximation accuracy of discrete distribution and former distribution that the method for the present invention acquires is high, and error is small, can construct the high quality scene collection for approaching practical wind power distribution.
Description
Technical field
The present invention relates to field of power systems, more particularly to a kind of optimal quartile of wind power probability based on EMD
Point determines method.
Background technique
In recent years, the permeability of the renewable energy power generations such as wind-powered electricity generation is continuously improved, and it is uncertain with weight to study its power output
Want meaning.Scene analysis method is one of probabilistic main method of processing power output, it passes through with continuous probability distribution
Random vector is separated into scene set, and stochastic optimization problems are converted to certain problem processing.
Scene collection how to be improved to the approximation accuracy of former problem, and generates the computational efficiency of high quality scene collection, is to answer
With the probabilistic difficult point of scene analytic approach processing renewable energy power output.
Summary of the invention
The present invention solves the technical problem of EMD index is used, a kind of wind power probability based on EMD is provided
Optimal quantile determines method.
The following technical solution is employed by the present invention:
Input distance measure order, the form parameter of wind power probability density function；Incision, specified, cut-out wind speed；Wind
Fast parameter；
The optimal quantile that wind power probability is obtained by minimizing EMD, continuous probability density function is separated into
Several probability density points；
Solve the corresponding probability of each optimal quantile.
Specifically, comprising steps of
Input distance measure order, the form parameter of wind power probability density function；Incision, specified, cut-out wind speed；Wind
Fast parameter；
The optimal quantile for obtaining wind power probability is minimized by EMD, and continuous probability density function is separated into
Several probability density points, comprising:
EMD is to be denoted as Es to the integral of the r rank distance measure of two probability density functions:
Es(p1,p2；D)=∫ d [p1(x),p2(x)]rdx
In formula, p1And p2For two probability density functions, d (p1,p2) it is distance measure；R is that distance is surveyed
The order of degree.
In Power System Planning and operation, under the premise of reducing error as far as possible, usually with discrete probability distribution
Continuous probability distribution is replaced to be simplified.It is sought in this regard, can use in the case that the above problem is converted to minimum Es by EMD
M optimal quantile problems.Assuming that optimal quantile is denoted as Lm(m=1,2 ..., M).The continuous probability density function of variable x is remembered
For h (x), L can be acquired by following formulam:
The uncertainty of usual single point in time wind speed can be described with Weibull distribution function, be defined as follows:
In formula, v is wind speed；C is wind speed parameter；K is the form factor of probability distribution.
Wind power is denoted as p, Weibull distribution is based on, wind power can be derived in section (0, Pwn) probability density
Function is denoted as f (p):
As p=0 and p=PwnWhen, have:
In formula, vn、vi、voRespectively specified, incision, cut-out wind speed；PwnFor the rated power of Wind turbines；H=vn/vi-
1。
Enable c1=vi/ c, c2=(hvi)/(cPwn), b=c2p+c1, can incite somebody to action
Right-hand vector conversion are as follows:
It enablesAbove formula is substituted into obtain:
It enablesAbove formula is substituted into obtain:
It enablesIncomplete gamma functions are defined as simultaneouslyIt can incite somebody to action
Above formula conversion are as follows:
Similarly, it can incite somebody to actionLeft end abbreviation are as follows:
Arrangement can obtain:
To sum up, optimal quantile L can be acquired by solving above formulam。
Solve the corresponding probability of each optimal quantile, comprising: corresponding optimal quantile LmDiscrete probabilistic pmAre as follows:
In formula, L0、LM+1The respectively lower and upper limit of variable x, are usually taken as-∞ ,+∞ respectively.Solving above formula can ask
Obtain optimal quantile LmCorresponding Probability pm。
Technical solution provided by the invention the utility model has the advantages that
The method of the present invention obtains optimal quantile and its corresponding general using EMD index under the premise of minimizing error
Rate, it is continuously distributed with discrete wind power probability density distribution substitution.The discrete distribution and former distribution that the method for the present invention acquires
Approximation accuracy it is high, error is small, can construct the high quality scene collection for approaching practical wind power distribution.
Detailed description of the invention
Fig. 1 determines method flow diagram for the optimal quantile of the wind power probability based on EMD.
Specific embodiment
Purpose, technical solution and technical effect for a better understanding of the present invention, below in conjunction with attached drawing to the present invention
Carry out further explaining illustration.
The invention proposes a kind of optimal quantiles of wind power probability based on EMD to determine method, implementing procedure
Including following detailed step:
Step 1, the distance measure order for inputting wind power probability density function, form parameter；It cuts, is specified, cutting out
Wind speed；Wind speed parameter；
Step 2, the optimal quantile that wind power probability is obtained by minimizing EMD, by continuous probability density function
It is separated into several probability density points.Wherein, EMD is denoted as Es:
Es(p1,p2；D)=∫ d [p1(x),p2(x)]rdx
In formula, p1And p2For two probability density functions, d (p1,p2) it is distance measure；R is the order of distance measure.
Optimal quantile L can be acquired by following formulam:
In formula, c1=vi/ c, c2=(hvi)/(cPwn),K is probability distribution
Form factor.
Step 3 solves the corresponding probability of each optimal quantile.Corresponding quantile LmDiscrete probabilistic pmAre as follows:
In formula, L0、LM+1The respectively lower and upper limit of variable x, are usually taken as-∞ ,+∞ respectively.
For a further understanding of the present invention, below with the typical wind-powered electricity generation data instance in Chinese somewhere, to explain the present invention
Practical application.
The mean wind speed predicted value of this area is as shown in table 1.
1 mean wind speed data of table
Assuming that in section (0, Pwn) in take 4 scenes, then plus power output for 0 and power output be rated power 2 scenes
Afterwards, total scene number of single moment is equal to 6.
The optimal quantile of each moment wind-powered electricity generation probability density curve of table 2
The probability of 3 each moment of table optimal quantile
Based on EMD minimize criterion, can acquire respectively probability density function each moment 6 optimal quantiles and
Corresponding discretization probability, numerical value is respectively as shown in table 2, table 3.
Claims (6)
1. a kind of optimal quantile of the wind power probability based on EMD determines method, which is characterized in that comprising steps of
Input distance measure order, the form parameter of wind power probability density function；Incision, specified, cut-out wind speed；Wind speed ginseng
Number；
The optimal quantile that EMD obtains wind power probability is minimized, it is general that continuous probability density function is separated into several
Rate density points；
Solve the corresponding probability of each optimal quantile.
2. the optimal quantile of the wind power probability according to claim 1 based on EMD determines that method, feature exist
In, by EMD minimize obtain wind power probability optimal quantile, continuous probability density function is separated into several
Probability density point, comprising:
EMD is to be denoted as E to the integral of the r rank distance measure of two probability density functionss:
Es(p1,p2；D)=∫ d [p1(x),p2(x)]rdx
In formula, p1And p2For two probability density functions, d (p1,p2) it is distance measure；R is the order of distance measure；
In Power System Planning and operation, under the premise of reducing error as far as possible, usually replaced with discrete probability distribution
Continuous probability distribution is simplified；E is minimized in this regard, can use EMD and be converted to the above problemsIn the case where seek M
Optimal quantile problem；Assuming that optimal quantile is denoted as Lm(m=1,2 ..., M)；The continuous probability density function of variable x is denoted as h
(x), L can be acquired by following formulam:
The uncertainty of usual single point in time wind speed can be described with Weibull distribution function, be defined as follows:
In formula, v is wind speed；C is wind speed parameter；K is the form factor of probability distribution；
Wind power is denoted as p, Weibull distribution is based on, wind power can be derived in section (0, Pwn) probability density letter
Number, is denoted as f (p):
As p=0 and p=PwnWhen, have:
In formula, vn、vi、voRespectively specified, incision, cut-out wind speed；PwnFor the rated power of Wind turbines；H=vn/vi-1；
Enable c1=vi/ c, c2=(hvi)/(cPwn), b=c2p+c1, can incite somebody to actionRight end
Item conversion are as follows:
It enablesAbove formula is substituted into obtain:
It enablesAbove formula is substituted into obtain:
It enablesIncomplete gamma functions are defined as simultaneouslyIt can be by above formula
Conversion are as follows:
Similarly, it can incite somebody to actionLeft end abbreviation are as follows:
Arrangement can obtain:
To sum up, optimal quantile L can be acquired by solving above formulam。
3. the optimal quantile of the wind power probability according to claim 1 based on EMD determines that method, feature exist
In solving the corresponding probability of each optimal quantile, comprising:
Corresponding optimal quantile LmDiscrete probabilistic pmAre as follows:
In formula, L0、LM+1The respectively lower and upper limit of variable x, are usually taken as-∞ ,+∞ respectively；Solving above formula can acquire most
Optimal sorting site LmCorresponding Probability pm。
4. the optimal quantile of the wind power probability according to claim 1 based on EMD determines that method, feature exist
In, by EMD minimize obtain wind power probability optimal quantile, continuous probability density function is separated into several
Probability density point.
5. the optimal quantile of the wind power probability according to claim 1 based on EMD determines that method, feature exist
In usually replacing continuous probability distribution to be simplified with discrete probability distribution under the premise of reducing error as far as possible.
6. the optimal quantile of the wind power probability according to claim 1 based on EMD determines that method, feature exist
In minimum EMD obtains the optimal quantile of wind power probability, and continuous probability density function is separated into several probability
Density points.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110929399A (en) * | 2019-11-21 | 2020-03-27 | 国网江苏省电力有限公司南通供电分公司 | Wind power output typical scene generation method based on BIRCH clustering and Wasserstein distance |
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2019
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110929399A (en) * | 2019-11-21 | 2020-03-27 | 国网江苏省电力有限公司南通供电分公司 | Wind power output typical scene generation method based on BIRCH clustering and Wasserstein distance |
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Application publication date: 20190712 |