CN103336995A - Method for constructing real-time light metering network of million kilowatt level photovoltaic power generation base - Google Patents
Method for constructing real-time light metering network of million kilowatt level photovoltaic power generation base Download PDFInfo
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Abstract
The invention discloses a method for constructing a real-time light metering network of a million kilowatt level photovoltaic power generation base. The method mainly comprises the steps of analyzing spatial and temporal distribution characteristics of the radiation quantity of an area where the million kilowatt level photovoltaic power generation base is located according to observation data of the radiation quantity; dividing typical areas in which the distributions of the radiation quantity are consistent, and carrying out macroscopic site selection for light metering stations; carrying out microscopic site selection for the light metering stations by using the location distribution of a photovoltaic power station group clustering center; and building the light metering station at the candidate locations so as to form the light metering network. The method for construction the real-time light metering network of the million kilowatt level photovoltaic power generation base can overcome the defects existing in the prior art such as poor real-time performance, large monitoring time granularity, and incapability of being applied to photovoltaic generated power short-term and ultrashort-term forecasting of the photovoltaic power station and the like, and has the advantages of good real-time performance, small monitoring time granularity, and capability of ensuring the timeliness of photovoltaic generated power forecasting.
Description
Technical field
The present invention relates to wind-force and be transported to electro-technical field, particularly, relate to the construction method of the real-time photometry network in a kind of million kilowatt photovoltaic generation base.
Background technology
The structure of photometry network is all significant for the assessment of million kilowatt photo-voltaic power generation station light resources, raising photovoltaic generation power prediction precision and the calculating of photovoltaic generation theoretical power etc. in real time.
Structure is at the light resources real time monitoring network of million kilowatt photo-voltaic power generation station, can assess the light resources distribution situation in an area accurately, for a long time, the real-time meteorological element data in microclimate of living in zone, million kilowatt photovoltaic generation base can also be provided for photovoltaic generation power prediction system.
The photometry station is as a conventional forecast point of numerical weather forecast, its measured data can provide important evidence for numerical weather prediction model revision and parameter adjusting, thereby promote the accuracy of radiation forecast, and then photovoltaic generation power prediction precision is provided, reduce and abandon optical quantum.
At present, light resources monitoring less application except meteorological department, and the monitoring of the light resources of meteorological department mostly is the non real-time monitoring, and the monitoring time granularity is bigger, and be not suitable for photovoltaic plant photovoltaic generation power short-term and the ultrashort phase is predicted.
In realizing process of the present invention, the inventor finds to exist at least in the prior art that real-time is poor, the monitoring time granularity big, be not suitable for defectives such as photovoltaic plant photovoltaic generation power short-term and the prediction of ultrashort phase.
Summary of the invention
The objective of the invention is to, at the problems referred to above, propose the construction method of the real-time photometry network in a kind of million kilowatt photovoltaic generation base, to realize that real-time is good, the monitoring time granularity is little, can guarantee the advantage that the photovoltaic generation power prediction is ageing.
For achieving the above object, the technical solution used in the present invention is: the construction method of the real-time photometry network in a kind of million kilowatt photovoltaic generation base mainly comprises:
A, according to the radiant quantity observation data, analyze region, million kilowatt photovoltaic generation base radiant quantity and get spatial-temporal distribution characteristic;
B, get spatial-temporal distribution characteristic according to region, above-mentioned analysis gained million kilowatt photovoltaic generation base radiant quantity, divide the radiant quantity consistent representative region that distributes, carry out macroscopical addressing at photometry station;
C, according to macroscopical addressing result at the above-mentioned photometry station that obtains, utilize the position distribution at photovoltaic plant field clustering class center, carry out the microcosmic addressing at photometry station;
D, according to the microcosmic addressing result at the above-mentioned photometry station that obtains, in each position candidate, build the photometry station, form the photometry network.
Further, described step b specifically comprises:
B1, the radiation data cumulative length is reached near all regions, million kilowatt photovoltaic generation base about 30 years weather station radiant quantity observational data, average, analyze this area's annual radiant quantity distribution characteristics;
B2, with each observation station gained observation data, be that the longitudinal axis, time shaft are that transverse axis constitutes the area radiation amount and describes matrix with the spatial axes, utilize the PCA analytical approach, radiant quantity is described matrix carries out principal component analysis (PCA), obtain influencing the dimension ordering that radiant quantity distributes.
Further, in step b2, the described PCA analytical approach of utilizing is described matrix to radiant quantity and is carried out principal component analysis (PCA), obtains influencing the operation of the dimension ordering that radiant quantity distributes, and specifically comprises:
B21, the data decomposition that will be mutually related are the mode component that is independent of each other, and each pattern is analyzed separately, carry out the decorrelation processing;
After b22, the process PCA, by the ordering to its eigenwert and proper vector, obtain each mode component by the ordering of its degree of influence descending order, this ordering reflection respectively influences the main lesser extent of dimension;
B23, the bigger major component PC of selection eigenwert are rotated principal factor analysis (PFA), by appropriate thresholds is set, divides radiant quantity and change close zone, as macroscopical addressing at photometry station.
Further, described step b22 specifically comprises:
1. the primary radiation data are arranged by time and space and constitute the radiant quantity observing matrix:
Wherein, m represents to have m photometry station, and n represents to have n time point;
2. at first matrix T is carried out the square graduation and handles, be about to matrix T and deduct equal value matrix,
Wherein,
,
3. calculate the intersectionproduct of T and its transposed matrix, after T was through the square graduation, the intersectionproduct that obtains was covariance matrix:
4. calculate covariance matrix C eigenwert (
) and proper vector
, its eigen vector satisfies:
Wherein,
Be the diagonal matrix that is constituted by proper vector,
And proper vector is arranged by order from big to small, namely
, because matrix T is the concept of reality measured value, so characteristic root should be more than or equal to 0, the corresponding row proper vector of each non-zero characteristics root;
5. calculate the PCA component, on the source book matrix T, the PCA component that just obtains all spatial signature vectors correspondences is space vector time corresponding coefficient with the eigenvector projection that calculates:
Calculating P is the capable n row of m time coefficient matrix, and each line data of P is exactly the time coefficient of corresponding each proper vector;
6. said process is the PCA component of corresponding each proper vector of projection properties vector sum that the observation data matrix T is calculated, by computation process as can be known, utilize proper vector and PCA component can reconstruct the original observed data matrix T, utilize several major component PC of front maximum, just can simulate the principal character of original observed data matrix T.
Further, described step b23 specifically comprises:
7. according to the reconstruction nature of PCA as can be known, a standardized observation data matrix that contains n observation sample of m observation website can be decomposed into the product by proper vector and proper vector weight coefficient:
Wherein,
Each row be that PCA analyzes the normalized proper vector obtain, matrix
Be the proper vector weight coefficient, i.e. the time coefficient;
8. by very big variance rotation eigenvectors matrix and weight coefficient matrix are rotated, get preceding p major component component, make the variance of element in the new weight coefficient matrix:
Reach maximum;
9. each proper vector that obtains after the rotation principal factor analysis (PFA) has represented the spatial coherence distributed architecture of radiant quantity, the zone of space correlation significantly can be reduced after advancing overwinding alternation of hosts factorial analysis, the time coefficient of radiant quantity changes to be concentrated on preceding several major component components, and projection coefficient is zero on all the other most of directions;
If a certain vector is in each minute in a certain zone quantity symbol unanimity, then it represents the consistance that this regional climate changes; Choose appropriate threshold value and can obtain the consistent dividing region of radiant quantity, the zone of radiant quantity unanimity can be built a photometry station and carry out the light resources monitoring.
Further, in step c, the described operation of carrying out the microcosmic addressing at photometry station specifically comprises:
C1, by four jiaos of GPS latitude and longitude coordinates in photo-voltaic power generation station planning zone, obtain the GPS latitude and longitude coordinates of photovoltaic plant central point, represent the position coordinates of photovoltaic plant with the gps coordinate of central point;
C2, the macroscopic view that obtains the photometry station by the clustering method position of layouting:
C3, obtain cluster being carried out in the photovoltaic plant present position, called after by above-mentioned iteration: photovoltaic plant field group 1, photovoltaic plant field group 2 ..., photovoltaic plant field group n; N is natural number;
C4, each photovoltaic plant field group's cluster centre is the microcosmic addressing position at photometry station; If group's radius is bigger, by increasing distance center to reduce group's radius;
Macroscopical addressing position by taking all factors into consideration the photometry station and the microcosmic addressing position at photometry station finally obtain the photometry station and optimize the addressing scheme.
Further, described step c2 specifically comprises:
1. from the position coordinates of n photovoltaic plant, select k position coordinates as initial cluster center arbitrarily;
2. according to the gps coordinate of each cluster centre, calculate each photovoltaic plant position coordinates to each distances of clustering centers, and according to minor increment the residing distance of each object is divided;
3. recomputate the centre coordinate of each vicissitudinous cluster;
4. when the variable quantity of cluster centre position in each iterative process during less than pre-set threshold, iteration stopping, otherwise get back to step 2..
Further, in steps d, the operation at described construction photometry station specifically comprises:
D1, complete photometry station of construction mainly are made up of sensor, data acquisition unit, communication facilities, electric power system and other utility appliance;
The breath key element that d2, photometry station need be monitored comprises wind speed, wind direction, temperature, humidity, air pressure, total radiation, reflected radiation and assembly temperature etc.; Field environment at the Gobi desert, desert requires the operating ambient temperature of all devices all should reach-40 ℃～+ 60 ℃;
D3, for realizing the real-time monitoring to the light resources data, need install additional at each photometry station the real-time data acquisition device; The real-time data acquisition device is as the core of light resources real time monitoring network, and the quality of its type selecting is directly connected to the performance of photometry station data acquisition.
Further, in steps d 3, the performance of described photometry station data acquisition comprises:
1. the unimpeded rate of system transmissions: 〉=98%;
2. system is all the time according to stream time: 〉=15 days;
3. should be able to the data volume of complete preservation more than 3 months;
4. place in anti-dust storm, rainproof, the corrosion resistant guard box;
5. can realize that the image data of minute level is in real time from newspaper.
The construction method of the real-time photometry network in million kilowatt photovoltaic generation base of various embodiments of the present invention is owing to mainly comprise: according to the radiant quantity observation data, analyze region, million kilowatt photovoltaic generation base radiant quantity and get spatial-temporal distribution characteristic; Divide the consistent representative region of radiant quantity distribution, carry out macroscopical addressing at photometry station; Utilize the position distribution at photovoltaic plant field clustering class center, carry out the microcosmic addressing at photometry station; In each position candidate, build the photometry station, form the photometry network; Can provide the real-time meteorological element data in photovoltaic plant microclimate of living in zone for photovoltaic generation power prediction system for assessment of the light resources situation of region, million kilowatt photovoltaic generation base; Thereby can overcome that real-time in the prior art is poor, the monitoring time granularity big, not be suitable for the defective of photovoltaic plant photovoltaic generation power short-term and the prediction of ultrashort phase, to realize that real-time is good, the monitoring time granularity is little, can guarantee the advantage that the photovoltaic generation power prediction is ageing.
Other features and advantages of the present invention will be set forth in the following description, and, partly from instructions, become apparent, perhaps understand by implementing the present invention.
Below by drawings and Examples, technical scheme of the present invention is described in further detail.
Description of drawings
Accompanying drawing is used to provide further understanding of the present invention, and constitutes the part of instructions, is used from explanation the present invention with embodiments of the invention one, is not construed as limiting the invention.In the accompanying drawings:
Fig. 1 is the schematic flow sheet of the construction method of the real-time photometry network in million kilowatt photovoltaic generation of the present invention base;
Fig. 2 a, Fig. 2 b, Fig. 2 c and Fig. 2 d are the cluster result synoptic diagram of photovoltaic plant field group 1,2,3, n.
Embodiment
Below in conjunction with accompanying drawing the preferred embodiments of the present invention are described, should be appreciated that preferred embodiment described herein only is used for description and interpretation the present invention, and be not used in restriction the present invention.
(or claim: photovoltaic generation base group) floor area is wide, and physical environment is abominable, and many places are in area, Gobi desert, desert in some million kilowatt photovoltaic generations base.It carries out the monitoring of real-time light resources and should set up a plurality of photometries station to a plurality of million kilowatt photovoltaic generations base, forms the photometry network, could guarantee all standing of light resources is monitored, thus the accuracy that can improve the photovoltaic generation power prediction.Simultaneously, for guaranteeing the ageing of photovoltaic generation power prediction, need to adopt cover the region wide, at Gobi desert, open-air desert environment, possess the real-time Communication for Power ability, safeguard simple and convenient and lower-cost a kind of million kilowatt photovoltaic generation base photometry networking method.The present invention is directed to above-mentioned feature, proposed the construction method of the real-time photometry network in a kind of million kilowatt photovoltaic generation base.
According to the embodiment of the invention, shown in Fig. 1, Fig. 2 a, Fig. 2 b, Fig. 2 c and Fig. 2 d, the construction method of the real-time photometry network in a kind of million kilowatt photovoltaic generation base is provided, light resources situation for assessment of region, million kilowatt photovoltaic generation base, for photovoltaic generation power prediction system provides the real-time meteorological element data in photovoltaic plant microclimate of living in zone, be applied to photovoltaic generation capability evaluation, base planning, photovoltaic generation power prediction and the analysis of photovoltaic generation theoretical power.
Referring to Fig. 1, the construction method of the real-time photometry network in million kilowatt photovoltaic generation base of present embodiment mainly may further comprise the steps:
Step 100: according to the radiant quantity observation data, analyze region, million kilowatt photovoltaic generation base radiant quantity and get spatial-temporal distribution characteristic, execution in step 101;
Step 101: analyze region, gained million kilowatt photovoltaic generation base radiant quantity according to step 100 and get spatial-temporal distribution characteristic, divide the consistent representative region of radiant quantity distribution, obtain macroscopical addressing result at photometry station, execution in step 102;
Step 102: utilize the position distribution at photovoltaic plant field clustering class center, carry out the microcosmic addressing at photometry station, execution in step 104;
Step 104: in each position candidate, build light measurer, form the photometry network.
In above-mentioned steps 101, the operation to macroscopical addressing at photometry station specifically comprises:
⑴ average near the weather station radiant quantity observational data all regions, million kilowatt photovoltaic generation base, analyzes this area's annual radiant quantity distribution characteristics (suggestion radiation data cumulative length reached about 30 years);
⑵ be that the longitudinal axis, time shaft are transverse axis with the spatial axes with each observation station gained observation data, constitute the area radiation amount and describe matrix, radiant quantity is described matrix carry out principal component analysis (PCA) (Principal Component Analysis is called for short PCA), obtain influencing the dimension ordering that radiant quantity distributes.
The PCA analytical approach is a kind of analysis matrix data structure feature, extracts a kind of method of general data characteristic quantity, and Lorenz is introduced into meteorology and climatic study first in generation nineteen fifty, has obtained using very widely now in ground and other subjects.Common proper vector correspondence is space sample in the earth science data analysis, so be called spatial signature vectors, what carry out major component correspondence after the PCA is to change the time, is also referred to as time coefficient, therefore the radiant quantity data is carried out PCA and analyzes the space-time that also can be called the radiant quantity data and decompose.
The PCA analytical approach is with in relevant mutually Conversion of Spatial Data to the new coordinate system, and each coordinate axis of new coordinate system is the linear combination of raw data, and separate between each coordinate axis.
The PCA analytical approach has following feature:
⑴ the data decomposition that will be mutually related is the mode component that is independent of each other, and can analyze separately each pattern, and this step also becomes decorrelationization;
⑵ by the ordering to its eigenwert and proper vector, can obtain each mode component by the ordering of its degree of influence descending order through after the PCA, and this ordering reflection respectively influences the main lesser extent of dimension.
PCA process formulism is described below:
1. the primary radiation data are arranged by time and space and constitute the radiant quantity observing matrix:
Wherein, m represents to have m photometry station, and n represents to have n time point.
2. at first matrix T is carried out the square graduation and handles, be about to matrix T and deduct equal value matrix,
（2）
Wherein,
,
3. calculate the intersectionproduct of T and its transposed matrix, after T was through the square graduation, the intersectionproduct that obtains was covariance matrix,
4. calculate covariance matrix C eigenwert (
) and proper vector
, its eigen vector satisfies
Wherein,
Be the diagonal matrix that is constituted by proper vector,
And proper vector is arranged by order from big to small, namely
, because matrix T is the concept of reality measured value, so characteristic root should be more than or equal to 0, the corresponding row proper vector of each non-zero characteristics root.
5. calculate the PCA component, the eigenvector projection that calculates on the source book matrix T, is just obtained the PCA component (being space vector time corresponding coefficient) of all spatial signature vectors correspondences
Calculating P is the capable n row of m time coefficient matrix, and each line data of P is exactly the time coefficient of corresponding each proper vector.
6. said process is the PCA component of corresponding each proper vector of projection properties vector sum that the observation data matrix T is calculated, by computation process as can be known, utilize proper vector and PCA component can reconstruct the original observed data matrix T, can utilize several major components (PC) of front maximum just can simulate the principal character of original observed data matrix T sometimes.
⑶ select the bigger major component (PC) of eigenwert, is rotated principal factor analysis (PFA), by appropriate thresholds is set, divides radiant quantity and change close zone, as macroscopical addressing at photometry station.
According to the reconstruction nature of PCA as can be known, the observation data matrix of n observation sample of one the standardized m of containing an observation website can be decomposed into the product by proper vector and proper vector weight coefficient
Wherein,
Each row be that PCA analyzes the normalized proper vector obtain, matrix
Be the proper vector weight coefficient, i.e. the time coefficient.
By very big variance rotation eigenvectors matrix and weight coefficient matrix are rotated, get preceding p major component component, make the variance of element in the new weight coefficient matrix
Reach maximum.
Each proper vector that obtains after the rotation principal factor analysis (PFA) has represented the spatial coherence distributed architecture of radiant quantity, the zone of space correlation significantly can be reduced after advancing overwinding alternation of hosts factorial analysis, the time coefficient of radiant quantity changes to be concentrated on preceding several major component components, and projection coefficient is zero on all the other most of directions.If a certain vector is in each minute in a certain zone quantity symbol unanimity, then it represents the consistance that this regional climate changes.Choose appropriate threshold value (as 0.6) and can obtain the consistent dividing region of radiant quantity.The zone of radiant quantity unanimity can be built a photometry station and carry out the light resources monitoring.
In above-mentioned steps 103, the operation to the microcosmic addressing at photometry station specifically comprises:
Can only obtain macroscopical addressing at photometry station by said method, if will carry out the microcosmic addressing, need consider that also other are all multifactor, whether satisfy construction condition etc. as the distance between photometry station and the photovoltaic plant, region, photometry station.Consider emphatically that below the photovoltaic plant position is to the influence of photometry station addressing:
⑴ obtain the GPS latitude and longitude coordinates of photovoltaic plant central point by four jiaos of GPS latitude and longitude coordinates in photo-voltaic power generation station planning zone, represents the position coordinates of photovoltaic plant with the gps coordinate of central point.
⑵ the macroscopic view that obtain the photometry station by the clustering method position of layouting:
1. from the position coordinates of n photovoltaic plant, select k position coordinates as initial cluster center arbitrarily;
2. according to the gps coordinate of each cluster centre, calculate each photovoltaic plant position coordinates to each distances of clustering centers, and according to minor increment the residing distance of each object is divided;
3. recomputate the centre coordinate of each (vicissitudinous) cluster;
4. when the variable quantity of cluster centre position in each iterative process during less than pre-set threshold, iteration stopping, otherwise get back to step 2.2;
By step 3., 4. iteration obtains cluster being carried out in the photovoltaic plant present position, called after: photovoltaic plant field group 1, photovoltaic plant field group 2 ..., photovoltaic plant field group n(cluster result can be referring to Fig. 2 a, Fig. 2 b, Fig. 2 c and Fig. 2 d).
⑷ each photovoltaic plant field group cluster centre is the microcosmic addressing position (if group's radius is bigger, suggestion is by increasing distance center to reduce group's radius) at photometry station.
Macroscopical addressing position by taking all factors into consideration the photometry station and the microcosmic addressing position at photometry station finally obtain the photometry station and optimize the addressing scheme.
In above-mentioned steps 104, build the operation of light measurer (being the construction at photometry station), specifically comprise:
⑴ complete photometry station owner will be made up of sensor, data acquisition unit, communication facilities, electric power system and other utility appliance.
⑵ the breath key element that photometry station need be monitored comprises wind speed, wind direction, temperature, humidity, air pressure, total radiation, reflected radiation and assembly temperature etc.Field environment at the Gobi desert, desert requires the operating ambient temperature of all devices all should reach-40 ℃～+ 60 ℃.
⑶ need to install the real-time data acquisition device additional at each photometry station for realizing the real-time monitoring to the light resources data.The real-time data acquisition device is as the core of light resources real time monitoring network, and the quality of its type selecting is directly connected to stability, reliability and the accuracy of photometry station data acquisition.Need its Specifeca tion speeification is done following requirement:
1. the unimpeded rate of system transmissions: 〉=98%;
2. system is all the time according to stream time: 〉=15 days;
3. should be able to the data volume of complete preservation more than 3 months;
4. place in anti-dust storm, rainproof, the corrosion resistant guard box;
5. realize that the image data of minute level is in real time from reporting low-power consumption, being fit to open-air unmanned operation.
The construction method of the real-time photometry network in million kilowatt photovoltaic generation base of the various embodiments described above of the present invention, both considered to have considered again that at the influence to the photometry station location of the large scale weather attitude feature in some million kilowatt photovoltaic generations base the feature of microcosmic photovoltaic plant position distribution is to the influence of photometry station location; Under the consistent regional location of macroscopical radiant quantity, utilize the distance factor of photometry station and photovoltaic plant to carry out the microcosmic addressing.The construction method of this real-time photometry network in million kilowatt photovoltaic generation base has following characteristics at least:
⑴ average with near each the weather station annual radiation data the region, million kilowatt photovoltaic base, analyzes the distribution characteristics of annual radiation in this zone;
⑵ be processed into standardization anomaly matrix with the observational data matrix, by principal component analysis (PCA) (PCA), and disengaging time field and spatial field, the spatial-temporal characteristics of analysis region, photovoltaic generation base radiant quantity;
⑶ select the bigger major component (PC) of eigenwert, is rotated principal factor analysis (PFA), by appropriate thresholds is set, divides radiant quantity and change close zone;
⑷ utilize clustering method to obtain group's position distribution center, some photovoltaic plants field, utilizes the distance factor at photometry station and group's position distribution center, photovoltaic plant field to obtain microcosmic optimization addressing.
It should be noted that at last: the above only is the preferred embodiments of the present invention, be not limited to the present invention, although with reference to previous embodiment the present invention is had been described in detail, for a person skilled in the art, it still can be made amendment to the technical scheme that aforementioned each embodiment puts down in writing, and perhaps part technical characterictic wherein is equal to replacement.Within the spirit and principles in the present invention all, any modification of doing, be equal to replacement, improvement etc., all should be included within protection scope of the present invention.
Claims (9)
1. the construction method of the real-time photometry network in million kilowatt photovoltaic generation base is characterized in that, mainly comprises:
A, according to the radiant quantity observation data, analyze region, million kilowatt photovoltaic generation base radiant quantity and get spatial-temporal distribution characteristic;
B, get spatial-temporal distribution characteristic according to region, above-mentioned analysis gained million kilowatt photovoltaic generation base radiant quantity, divide the radiant quantity consistent representative region that distributes, carry out macroscopical addressing at photometry station;
C, according to macroscopical addressing result at the above-mentioned photometry station that obtains, utilize the position distribution at photovoltaic plant field clustering class center, carry out the microcosmic addressing at photometry station;
D, according to the microcosmic addressing result at the above-mentioned photometry station that obtains, in each position candidate, build the photometry station, form the photometry network.
2. the construction method of the real-time photometry network in million kilowatt photovoltaic generation base according to claim 1 is characterized in that described step b specifically comprises:
B1, the radiation data cumulative length is reached near all regions, million kilowatt photovoltaic generation base about 30 years weather station radiant quantity observational data, average, analyze this area's annual radiant quantity distribution characteristics;
B2, with each observation station gained observation data, be that the longitudinal axis, time shaft are that transverse axis constitutes the area radiation amount and describes matrix with the spatial axes, utilize the PCA analytical approach, radiant quantity is described matrix carries out principal component analysis (PCA), obtain influencing the dimension ordering that radiant quantity distributes.
3. the construction method of the real-time photometry network in million kilowatt photovoltaic generation base according to claim 2, it is characterized in that, in step b2, the described PCA analytical approach of utilizing, radiant quantity is described matrix carry out principal component analysis (PCA), obtain influencing the operation of the dimension ordering that radiant quantity distributes, specifically comprise:
B21, the data decomposition that will be mutually related are the mode component that is independent of each other, and each pattern is analyzed separately, carry out the decorrelation processing;
After b22, the process PCA, by the ordering to its eigenwert and proper vector, obtain each mode component by the ordering of its degree of influence descending order, this ordering reflection respectively influences the main lesser extent of dimension;
B23, the bigger major component PC of selection eigenwert are rotated principal factor analysis (PFA), by appropriate thresholds is set, divides radiant quantity and change close zone, as macroscopical addressing at photometry station.
4. the construction method of the real-time photometry network in million kilowatt photovoltaic generation base according to claim 3 is characterized in that described step b22 specifically comprises:
1. the primary radiation data are arranged by time and space and constitute the radiant quantity observing matrix:
Wherein, m represents to have m photometry station, and n represents to have n time point;
2. at first matrix T is carried out the square graduation and handles, be about to matrix T and deduct equal value matrix,
Wherein,
,
3. calculate the intersectionproduct of T and its transposed matrix, after T was through the square graduation, the intersectionproduct that obtains was covariance matrix:
4. calculate covariance matrix C eigenwert (
) and proper vector
, its eigen vector satisfies:
Wherein,
Be the diagonal matrix that is constituted by proper vector,
And proper vector is arranged by order from big to small, namely
, because matrix T is the concept of reality measured value, so characteristic root should be more than or equal to 0, the corresponding row proper vector of each non-zero characteristics root;
5. calculate the PCA component, on the source book matrix T, the PCA component that just obtains all spatial signature vectors correspondences is space vector time corresponding coefficient with the eigenvector projection that calculates:
Calculating P is the capable n row of m time coefficient matrix, and each line data of P is exactly the time coefficient of corresponding each proper vector;
6. said process is the PCA component of corresponding each proper vector of projection properties vector sum that the observation data matrix T is calculated, by computation process as can be known, utilize proper vector and PCA component can reconstruct the original observed data matrix T, utilize several major component PC of front maximum, just can simulate the principal character of original observed data matrix T.
5. according to the construction method of the real-time photometry network of claim 3 or 4 described million kilowatt photovoltaic generation bases, it is characterized in that described step b23 specifically comprises:
7. according to the reconstruction nature of PCA as can be known, a standardized observation data matrix that contains n observation sample of m observation website can be decomposed into the product by proper vector and proper vector weight coefficient:
Wherein,
Each row be that PCA analyzes the normalized proper vector obtain, matrix
Be the proper vector weight coefficient, i.e. the time coefficient;
8. by very big variance rotation eigenvectors matrix and weight coefficient matrix are rotated, get preceding p major component component, make the variance of element in the new weight coefficient matrix:
Reach maximum;
9. each proper vector that obtains after the rotation principal factor analysis (PFA) has represented the spatial coherence distributed architecture of radiant quantity, the zone of space correlation significantly can be reduced after advancing overwinding alternation of hosts factorial analysis, the time coefficient of radiant quantity changes to be concentrated on preceding several major component components, and projection coefficient is zero on all the other most of directions;
If a certain vector is in each minute in a certain zone quantity symbol unanimity, then it represents the consistance that this regional climate changes; Choose appropriate threshold value and can obtain the consistent dividing region of radiant quantity, the zone of radiant quantity unanimity can be built a photometry station and carry out the light resources monitoring.
6. the construction method of the real-time photometry network in million kilowatt photovoltaic generation base according to claim 1 is characterized in that, in step c, the described operation of carrying out the microcosmic addressing at photometry station specifically comprises:
C1, by four jiaos of GPS latitude and longitude coordinates in photo-voltaic power generation station planning zone, obtain the GPS latitude and longitude coordinates of photovoltaic plant central point, represent the position coordinates of photovoltaic plant with the gps coordinate of central point;
C2, the macroscopic view that obtains the photometry station by the clustering method position of layouting:
C3, obtain cluster being carried out in the photovoltaic plant present position, called after by above-mentioned iteration: photovoltaic plant field group 1, photovoltaic plant field group 2 ..., photovoltaic plant field group n; N is natural number;
C4, each photovoltaic plant field group's cluster centre is the microcosmic addressing position at photometry station; If group's radius is bigger, by increasing distance center to reduce group's radius;
Macroscopical addressing position by taking all factors into consideration the photometry station and the microcosmic addressing position at photometry station finally obtain the photometry station and optimize the addressing scheme.
7. the construction method of the real-time photometry network in million kilowatt photovoltaic generation base according to claim 6 is characterized in that described step c2 specifically comprises:
1. from the position coordinates of n photovoltaic plant, select k position coordinates as initial cluster center arbitrarily;
2. according to the gps coordinate of each cluster centre, calculate each photovoltaic plant position coordinates to each distances of clustering centers, and according to minor increment the residing distance of each object is divided;
3. recomputate the centre coordinate of each vicissitudinous cluster;
4. when the variable quantity of cluster centre position in each iterative process during less than pre-set threshold, iteration stopping, otherwise get back to step 2..
8. the construction method of the real-time photometry network in million kilowatt photovoltaic generation base according to claim 1 is characterized in that, in steps d, the operation at described construction photometry station specifically comprises:
D1, complete photometry station of construction mainly are made up of sensor, data acquisition unit, communication facilities, electric power system and other utility appliance;
The breath key element that d2, photometry station need be monitored comprises wind speed, wind direction, temperature, humidity, air pressure, total radiation, reflected radiation and assembly temperature etc.; Field environment at the Gobi desert, desert requires the operating ambient temperature of all devices all should reach-40 ℃～+ 60 ℃;
D3, for realizing the real-time monitoring to the light resources data, need install additional at each photometry station the real-time data acquisition device; The real-time data acquisition device is as the core of light resources real time monitoring network, and the quality of its type selecting is directly connected to the performance of photometry station data acquisition.
9. the construction method of the real-time photometry network in million kilowatt photovoltaic generation base according to claim 8 is characterized in that, in steps d 3, the performance of described photometry station data acquisition comprises:
1. the unimpeded rate of system transmissions: 〉=98%;
2. system is all the time according to stream time: 〉=15 days;
3. should be able to the data volume of complete preservation more than 3 months;
4. place in anti-dust storm, rainproof, the corrosion resistant guard box;
5. can realize that the image data of minute level is in real time from newspaper.
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103870999A (en) * | 2014-02-25 | 2014-06-18 | 国家电网公司 | Rotated empirical orthogonal decomposition-based irradiance area division method |
| CN103929129A (en) * | 2014-05-08 | 2014-07-16 | 国家电网公司 | Method and system for predicting distributed photovoltaic power |
| CN105718721A (en) * | 2016-01-15 | 2016-06-29 | 中国电力科学研究院 | Regional solar energy resource calculation method |
| CN104050345B (en) * | 2014-02-25 | 2017-09-05 | 国家电网公司 | A kind of light-metering station coverage analysis method for lattice point classification of being formatted based on regional network |
| CN110390287A (en) * | 2019-07-17 | 2019-10-29 | 中科光启空间信息技术有限公司 | A kind of crop maturity phase prediction technique based on satellite remote sensing |
| CN111161443A (en) * | 2019-01-17 | 2020-05-15 | 浙江诸暨美数信息科技有限公司 | Patrol path setting method based on historical data |
| CN114139448A (en) * | 2021-11-29 | 2022-03-04 | 自然资源部第一海洋研究所 | Method, system, medium, terminal and application for optimizing sea-based observation network station layout |
| CN117217376A (en) * | 2023-09-12 | 2023-12-12 | 陕西丝路创城建设有限公司 | Site selection method and system for photovoltaic power station construction |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2006215919A (en) * | 2005-02-04 | 2006-08-17 | Chugoku Electric Power Co Inc:The | Green power generation facility investment system |
| CN102142103A (en) * | 2011-04-15 | 2011-08-03 | 河海大学 | Real-coded genetic algorithm-based optimizing method for micrositing of wind power station |
| CN102945507A (en) * | 2012-10-09 | 2013-02-27 | 东北大学 | Optimal site selection method and device for distributed wind power plant based on fuzzy analytic hierarchy process |
-
2013
- 2013-04-19 CN CN201310139149.3A patent/CN103336995B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2006215919A (en) * | 2005-02-04 | 2006-08-17 | Chugoku Electric Power Co Inc:The | Green power generation facility investment system |
| CN102142103A (en) * | 2011-04-15 | 2011-08-03 | 河海大学 | Real-coded genetic algorithm-based optimizing method for micrositing of wind power station |
| CN102945507A (en) * | 2012-10-09 | 2013-02-27 | 东北大学 | Optimal site selection method and device for distributed wind power plant based on fuzzy analytic hierarchy process |
Non-Patent Citations (3)
| Title |
|---|
| 赵明智: "槽式太阳能热发电站微观选址的方法研究", 《中国博士学位论文全文数据库 工程科技Ⅱ辑》 * |
| 赵龙等: "风能资源测量网络建设初探", 《风能》 * |
| 龚强等: "辽宁省风能、太阳能资源时空分布特征及其初步区划", 《资源科学》 * |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103870999A (en) * | 2014-02-25 | 2014-06-18 | 国家电网公司 | Rotated empirical orthogonal decomposition-based irradiance area division method |
| CN104050345B (en) * | 2014-02-25 | 2017-09-05 | 国家电网公司 | A kind of light-metering station coverage analysis method for lattice point classification of being formatted based on regional network |
| CN103929129A (en) * | 2014-05-08 | 2014-07-16 | 国家电网公司 | Method and system for predicting distributed photovoltaic power |
| CN105718721A (en) * | 2016-01-15 | 2016-06-29 | 中国电力科学研究院 | Regional solar energy resource calculation method |
| CN111161443A (en) * | 2019-01-17 | 2020-05-15 | 浙江诸暨美数信息科技有限公司 | Patrol path setting method based on historical data |
| CN110390287A (en) * | 2019-07-17 | 2019-10-29 | 中科光启空间信息技术有限公司 | A kind of crop maturity phase prediction technique based on satellite remote sensing |
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| CN117217376B (en) * | 2023-09-12 | 2024-03-08 | 陕西丝路创城建设有限公司 | Site selection method and system for photovoltaic power station construction |
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