CN111596384A - Inclined plane radiation prediction method based on weather type effective identification - Google Patents
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Abstract
The invention discloses an inclined plane radiation prediction method based on weather type effective identification. The method of the invention comprises the following steps: s1: acquiring historical data of weather and radiation; s2: calculating a direct incidence ratio and a corrected definition index, and calculating a weather type index SCF and a solar altitude; s3: judging whether the solar altitude is greater than 10 degrees, if so, entering the next step, and otherwise, returning to the previous step; s4: classifying weather, namely classifying the weather type index SCF by using a K-means clustering algorithm; s5: acquiring actually measured data, calculating a weather type index SCF and judging the weather type of the index SCF; s6: and selecting different direct and scattered separation models according to different weather types. According to the invention, the accuracy reduction phenomenon of a single model under a specific weather type is avoided through calculation, and the most suitable weather condition of each model is selected, so that the accuracy of the prediction model is obviously improved.
Description
Technical Field
The invention relates to the field of photovoltaic systems, in particular to an inclined plane radiation prediction method based on weather type effective identification.
Background
The main source of greenhouse gases is traditional fossil fuels, and the exploitation and application of renewable energy sources provides a viable solution for reducing greenhouse gas emissions. Among them, solar energy resources have great development potential, and thus are receiving more and more attention. At present, the photovoltaic power generation technology is the most mature in the solar energy resource development technology. According to the photovoltaic review and prospect report prediction of 2019-2023 published by the European photovoltaic industry association, the photovoltaic new installation can realize 26% of growth in 2020, and the growth reaches 20-21 GW; the new photovoltaic installation in 2021 will reach 21.9GW, close to the highest historical value of annual photovoltaic installation capacity. According to the statistical data of the national energy agency, the total installed capacity of the national photovoltaic power generation is about 1.9 hundred million kilowatt hours by 2019, and the national photovoltaic power generation 1715 hundred million kilowatt hours three quarters before 2019 is increased by 28% on a same scale.
The incident total radiation directly determines the output power of the photovoltaic array. Whereas the incident total radiation is mainly composed of three parts, direct radiation, scattered radiation and reflected radiation, respectively. To maximize the received energy, the photovoltaic array of the northern hemisphere is usually chosen to be placed obliquely to the south (optimal tilt angle). The radiation data measured in the weather station is generally on a horizontal plane, which requires the model to convert the radiation data from the horizontal plane to an inclined plane.
The literature: s Armstrong, W G Hurley.A new method to optimal solar Energy extraction arrangement [ J ] Renewable Energy,2010,35: 780-. Aiming at the characteristic that the scattered radiation accounts for a large amount under the condition of overcast days, two parameters of sunshine percentage (namely the ratio of sunshine hours to illuminable hours) and total cloud amount are introduced, and the average accounts for different weather types are obtained through calculation of historical data, so that the radiation amount is calculated, but the calculated value is lower than the actual value.
The literature: demain C, journal e M, Bertrand C, et al, evaluation of differential to estimate the global radio on included surfaces [ J ]. Renewable Energy,2013,50: 710-. The concept of correcting the definition index is introduced, and the influence of the solar altitude on the definition index is reduced. The corrected definition index is divided into segments according to weather, the inclined plane radiation model with the highest precision in the segments is selected, and combined prediction is carried out, so that the result shows that the precision of the combined model is obviously improved compared with that of a single model.
The literature: lefen, Hu Chao, horse-year-Jun et al direct separation model study on PM2.5 under different weather types [ J ]. solar energy bulletin, 2017,38(12): 3339-3347. The method combines three parameters of PM2.5, definition index and sunshine percentage, establishes a BP neural network model for predicting direct and scattered separation in Beijing area, and tests the optimal parameter combination under different weather conditions.
The literature: li F, Li C, Shi J, et al, an evaluation index system for photonic systems and devices of static characteristics in central China [ J ]. IET reusable Power Generation,2017,11(14): 1794-.
In the national weather industry standard, the ground weather observation standard and the service operation weather forecast, a single index is usually used, such as total cloud cover or sunshine hours and the like, to divide weather. The observation of the total cloud amount mainly depends on manual observation, human errors exist, a single index is adopted, and the accuracy of weather type division is deficient.
The existing solar radiation models are mainly proposed by foreigners, the data for establishing the models mainly come from the United states and European regions, and the models can have larger errors when being directly used in China.
Different inclined plane radiation models are suitable for different weather types, and some models are higher in accuracy under the condition of multiple clouds, and some models are opposite. If a single usage model is used, the accuracy is necessarily reduced.
Disclosure of Invention
The invention aims to overcome the defects in the prior art, provides a comprehensive weather type index according to horizontal plane and inclined plane radiation data and meteorological environment data and combines with meteorological environment factors such as a correction definition index, a direct incidence ratio, total cloud amount and the like, effectively divides weather types into five categories, analyzes corresponding optimal models aiming at different weather types, and accordingly provides an inclined plane radiation prediction method based on weather type effective identification with high precision.
Therefore, the invention adopts the following technical scheme: a method for predicting inclined plane radiation based on effective identification of weather types comprises the following steps:
s1: acquiring historical data of weather and radiation;
s2: calculating a direct incidence ratio and a corrected definition index, and calculating a weather type index SCF and a solar altitude;
s3: judging whether the solar altitude is greater than 10 degrees, if so, entering the next step, and otherwise, returning to the previous step;
s4: classifying weather, namely classifying the weather type index SCF by using a K-means clustering algorithm;
s5: acquiring actually measured data, calculating a weather type index SCF and judging the weather type of the index SCF;
s6: and selecting different direct and scattered separation models according to different weather types.
Further, in step S1, the radiation data includes total horizontal radiation, scattered radiation, direct radiation, reflected radiation, and total oblique radiation data with a normal south orientation and an inclination angle of beijing latitude; the meteorological data comprises total cloud cover and visibility; the total cloud cover is defined as the number of cloud-covered sky views, and represents the percentage of the range covered by the cloud cover in the sky to the total sky range.
Further, in step S2, the data is screened and quality controlled, and the sharpness index and the corrected sharpness index are calculated based on the horizontal plane radiation observation and the astronomical factors (such as latitude, solar altitude, etc.).
Further, in step S2, the clarity index is the total solar radiation I on the horizontal plane and the solar radiation I on the horizontal plane outside the atmosphereoThe ratio of the components is as follows:
the clarity index is not only related to meteorological conditions but also to the position of the sun in the sky, and is modified as follows in order to reduce the influence of the solar altitude on the clarity index:
wherein, k'TIs the sharpness index after correction, and m is the atmospheric mass.
The definition index can be used for representing the attenuation of the atmosphere to solar radiation and is a priority weather type classification index. The greater the clarity index, the greater the transparency of the atmosphere, the less the atmospheric attenuation of the solar radiation, and the greater the solar radiation reaching the ground.
Further, in step S2, the corrected three data, that is, the sharpness index, the direct incidence ratio, and the total cloud amount, are respectively normalized and weighted to obtain a comprehensive index factor, which is named scf (sky conditioning factor), that is, a weather type index, and the specific calculation formula is as follows:
SCF＝w1Bd+w2k'T+w3(1-C)，
wherein the weight w1，w2And w3The sum of (1) is calculated according to the local geographic position and the radiation data; c represents total cloud cover; bd represents the direct ratio, i.e., the proportion of the horizontal plane direct radiation exposure in the total radiation exposure.
Further, in step S4, the weather type index SCF is classified into 5 categories by K-means clustering algorithm: type I, SCF <1 > is more than or equal to 0.58; type II, SCF is more than or equal to 0.44 and less than 0.58; type III, SCF value is more than or equal to 0.3 and less than 0.44; IV type, SCF is more than or equal to 0.15 and less than 0.3; form v, 0< SCF <0.15, with successively less richness of the direct radiation component of solar radiation.
The weather type I condition is best, namely sunny days; weather type II is from sunny to cloudy; weather type III is from sunny to cloudy; the weather type IV mainly comprises cloudy, cloudy-cloudy, etc.; the weather type V belongs to severe weather, and comprises the crossed weather conditions of light rain, gust rain, light snow, light fog, haze, middle rain and the like, or middle snow and the like.
Further, the specific content of step S6 is:
s61) if the current weather type obtained in the step S5 is I type, selecting a Hay model for calculation;
s62) if the current weather type obtained in the step S5 is II, III or IV, selecting a Perez model for calculation;
s63) if the current weather type obtained in the step S5 is V type, selecting a Liu & Jordan model for calculation.
Further, in step S1, the time of the history data is two years.
The invention has the following beneficial effects: 1) the weather type can be accurately and effectively classified. Compared with the existing mode of singly adopting the total cloud amount or adopting the combination of the definition index and the cloud amount, the method is more accurate.
2) The weather type index has the advantages of simple calculation formula, easy quantification, small calculation amount and easy discrimination.
3) Compared with a single model, the comprehensive model avoids the precision reduction phenomenon of the single model under a specific weather type through calculation, and selects the most suitable weather condition of each model, so that the precision of the prediction model is remarkably improved.
The method of the invention uses observation data of Beijing area for verification, which shows that the method is more suitable for the geographical climate characteristics of China.
Drawings
FIG. 1 is a comparison of the various models of the present invention under weather type I;
FIG. 2 is a comparison of the models of the present invention under weather type II;
FIG. 3 is a comparison of the models of the present invention under weather type III;
FIG. 4 is a comparison of the various models of the present invention under weather type IV;
FIG. 5 is a comparison of the models for weather type V of the present invention.
Detailed Description
In order that those skilled in the art will better understand the present invention, the following detailed description will be given to illustrate the present invention, but the scope of the present invention is not limited to the following examples. Any modification and variation made within the spirit of the present invention and the scope of the claims fall within the scope of the present invention.
The embodiment provides a method for predicting inclined plane radiation based on effective identification of weather types, which comprises the following steps:
s1: acquiring historical data of weather and radiation, wherein the time of the historical data is two years.
S2: calculating a direct incidence ratio and a corrected definition index, and calculating a weather type index SCF and a solar altitude;
s3: judging whether the solar altitude is greater than 10 degrees, if so, entering the next step, and otherwise, returning to the previous step;
s4: classifying weather, namely classifying the weather type index SCF by using a K-means clustering algorithm;
s5: acquiring actually measured data, calculating a weather type index SCF and judging the weather type of the index SCF;
s6: and selecting different direct and scattered separation models according to different weather types.
In step S1, the radiation data includes total horizontal plane radiation, scattered radiation, direct radiation, and reflected radiation data; the meteorological data comprises total cloud cover and visibility; the total cloud cover is defined as the number of cloud-covered sky views, and represents the percentage of the range covered by the cloud cover in the sky to the total sky range.
In step S2, the data are screened and quality controlled, and the sharpness index and the corrected sharpness index are calculated according to the horizontal plane radiation observation value and the astronomical geographic factor (such as latitude, solar altitude angle, etc.).
In step S2, the definition index is the total solar radiation I on the horizontal plane and the solar radiation I on the horizontal plane outside the atmosphereoThe ratio of the components is as follows:
the clarity index is not only related to meteorological conditions but also to the position of the sun in the sky, and is modified as follows in order to reduce the influence of the solar altitude on the clarity index:
wherein, k'TIs the sharpness index after correction, and m is the atmospheric mass.
In step S2, the corrected three data, i.e., the sharpness index, the direct incidence ratio, and the total cloud amount, are respectively normalized and weighted to obtain a comprehensive index factor, which is named as SCF, i.e., a weather type index, and the specific calculation formula is as follows:
SCF＝w1Bd+w2k'T+w3(1-C)，
wherein the weight w1，w2And w3The sum of (1) is calculated according to the local geographic position and the radiation data; c represents total cloud cover; bd represents the direct ratio.
In step S4, the weather type index SCF is divided into 5 types by a K-means clustering algorithm: type I, SCF <1 > is more than or equal to 0.58; type II, SCF is more than or equal to 0.44 and less than 0.58; type III, SCF value is more than or equal to 0.3 and less than 0.44; IV type, SCF is more than or equal to 0.15 and less than 0.3; form v, 0< SCF <0.15, with successively less richness of the direct radiation component of solar radiation.
The specific content of step S6 is:
s61) if the current weather type obtained in the step S5 is I type, selecting a Hay model for calculation;
s62) if the current weather type obtained in the step S5 is II, III or IV, selecting a Perez model for calculation;
s63) if the current weather type obtained in the step S5 is V type, selecting a Liu & Jordan model for calculation.
Comparison of several representative models:
in the invention, representative models are selected, namely an isotropic Liu & Jordan model, an anisotropic Temps & Clouson model, a Perez model, a Kulcher model, a Hay model and a Reindl model. And performing calculation analysis and inspection through actually measured data of total radiation of the inclined plane with the normal south orientation of the Beijing south suburb and the inclination angle equal to the latitude of the Beijing. Under the weather type I, the calculated values of the isotropic model and most of the anisotropic models are lower than the measured values, and the Hay model is the closest to the calculated values, mainly because the radiation component of the weather type I is mainly direct radiation; in weather types II, III and IV, the error between the Perez model and the measured value is minimum, and the calculated values of other models are all low; in the weather type V, the calculated values of the anisotropic models are slightly larger than the measured values, and only the isotropic Liu & Jordan model is closest to the measured values, mainly because the weather condition is very poor in the weather type V, and the solar radiation is mainly scattered radiation and is uniformly distributed in the sky, and approaches to isotropy.
The pair of models for different weather conditions is shown below.
Wherein the standard deviation, also commonly referred to as mean square error, is the square root of the arithmetic mean of the squared deviations of the samples from their means; the coefficient of variation is the ratio of the standard deviation of the original data to the average of the original data, and the discrete degree of the two groups of data can be compared; the square root of the ratio of the square of the deviation between the root mean square error predicted value and the true value to the observation times n (or the number of samples) is commonly used for measuring the deviation between the observation value and the true value; the average absolute error is the average of the absolute values of the deviations of all the single observed values and the arithmetic mean value, so that the problem of mutual offset of the errors can be avoided, and the actual prediction error can be accurately reflected.
Claims (8)
1. A method for predicting inclined plane radiation based on weather type effective identification is characterized by comprising the following steps:
s1: acquiring historical data of weather and radiation;
s2: calculating a direct incidence ratio and a corrected definition index, and calculating a weather type index SCF and a solar altitude;
s3: judging whether the solar altitude is greater than 10 degrees, if so, entering the next step, and otherwise, returning to the previous step;
s4: classifying weather, namely classifying the weather type index SCF by using a K-means clustering algorithm;
s5: acquiring actually measured data, calculating a weather type index SCF and judging the weather type of the index SCF;
s6: and selecting different direct and scattered separation models according to different weather types.
2. The method for predicting inclined plane radiation based on weather type effective recognition of claim 1, wherein in step S1, the radiation data comprises horizontal plane total radiation, scattered radiation, direct radiation and reflected radiation data; the meteorological data comprises total cloud cover and visibility; the total cloud cover is defined as the number of cloud-covered sky views, and represents the percentage of the range covered by the cloud cover in the sky to the total sky range.
3. The method for predicting the inclined plane radiation based on the effective weather type identification as claimed in claim 1, wherein in step S2, the data are screened and quality controlled, and the clarity index and the corrected clarity index are calculated according to the horizontal plane radiation observation value and the astronomical geographic factor.
4. The method for predicting solar radiation on an inclined plane based on weather type effective recognition of claim 3, wherein in step S2, the definition indexes are total solar radiation I on a horizontal plane and solar radiation I on a horizontal plane outside the atmosphereoThe ratio of the components is as follows:
the clarity index is not only related to meteorological conditions but also to the position of the sun in the sky, and is modified as follows in order to reduce the influence of the solar altitude on the clarity index:
wherein, k'TIs the sharpness index after correction, and m is the atmospheric mass.
5. The method for predicting the inclined plane radiation based on the effective weather type identification as claimed in claim 4, wherein in step S2, the corrected three data of the sharpness index, the direct incidence ratio and the total cloud amount are respectively normalized and weighted to obtain a comprehensive index factor, which is named as SCF, namely the weather type index, and the specific calculation formula is as follows:
SCF＝w1Bd+w2k'T+w3(1-C)，
wherein the weight w1，w2And w3The sum of (1) is calculated according to the local geographic position and the radiation data; c represents total cloud cover; bd represents the direct ratio.
6. The method for predicting the inclined plane radiation based on the effective identification of the weather types as claimed in claim 1, wherein in the step S4, the weather type index SCF is classified into 5 categories by a K-means clustering algorithm: type I, SCF <1 > is more than or equal to 0.58; type II, SCF is more than or equal to 0.44 and less than 0.58; type III, SCF value is more than or equal to 0.3 and less than 0.44; IV type, SCF is more than or equal to 0.15 and less than 0.3; form v, 0< SCF <0.15, with successively less richness of the direct radiation component of solar radiation.
7. The method for predicting the radiation of the inclined plane based on the effective identification of the weather types as claimed in claim 6, wherein the specific content of the step S6 is as follows:
s61) if the current weather type obtained in the step S5 is I type, selecting a Hay model for calculation;
s62) if the current weather type obtained in the step S5 is II, III or IV, selecting a Perez model for calculation;
s63) if the current weather type obtained in the step S5 is V type, selecting a Liu & Jordan model for calculation.
8. The method for predicting the radiation of the inclined plane based on the effective identification of the weather type as claimed in claim 1, wherein the time of the historical data is two years in step S1.
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