CN111539846A - Photovoltaic power prediction method based on weather type subdivision - Google Patents

Photovoltaic power prediction method based on weather type subdivision Download PDF

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CN111539846A
CN111539846A CN202010320966.9A CN202010320966A CN111539846A CN 111539846 A CN111539846 A CN 111539846A CN 202010320966 A CN202010320966 A CN 202010320966A CN 111539846 A CN111539846 A CN 111539846A
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李芬
王悦
刘海风
林逸伦
杨兴武
汤波
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Shanghai University of Electric Power
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Abstract

The invention relates to the field of photovoltaic power generation, and discloses a photovoltaic power prediction method based on weather type subdivision, which is used for predicting direct current off-grid photovoltaic power and alternating current grid-connected photovoltaic power. A photovoltaic power prediction method based on weather type subdivision comprises the following steps: step 1, calculating to obtain corresponding photovoltaic array inclined plane incident total radiation I under different weather types according to a direct scattering separation model and an inclined plane radiation modelt(ii) a Step 2, inclining according to the photovoltaic arraySurface incident total radiation ItEstablishing a photovoltaic cell model according to the plate temperature model, and calculating to obtain direct current off-grid photovoltaic power P according to the photovoltaic cell modeldc(ii) a According to the DC off-grid photovoltaic power PdcAnd calculating the efficiency model of the inverter to obtain the alternating current grid-connected photovoltaic power Pac. The photovoltaic power prediction method based on weather type subdivision provided by the invention has the advantages of high prediction accuracy, wide application range and the like.

Description

Photovoltaic power prediction method based on weather type subdivision
Technical Field
The embodiment of the invention relates to the field of photovoltaic power generation, in particular to a photovoltaic power prediction method based on weather type subdivision.
Background
According to the statistics of the national energy bureau, 19019 ten thousand kilowatts are installed in the national photovoltaic power generation accumulation manner until 2019, the year is 9 months later, the year is increased by 15 percent, and 1599 ten thousand kilowatts are newly added. Wherein 13149 ten thousand kilowatts of the centralized photovoltaic power generation installation are increased by 11 percent on a same scale, and 773 ten thousand kilowatts are newly added; 5870 ten thousand kilowatts of distributed photovoltaic power generation installation, increase 28% on year-on-year basis, newly-increased 826 ten thousand kilowatts.
In the layout of the new installation machines, the installation machines 508.6 million kilowatts are newly added in the northern China three quarters before 2019, and account for 31.8 percent of the whole country; in the northeast region, a machine of 51.2 ten thousand kilowatts is additionally arranged, and accounts for 3.2 percent of the whole country; 332.2 ten thousand kilowatts are additionally arranged in east China and account for 20.8 percent of the whole country; 180.9 million kilowatts are additionally arranged in China and account for 11.3 percent of the whole country; 430.8 ten thousand kilowatts are newly added in northwest region, accounting for 26.9% of the whole country; 95.5 ten thousand kilowatts are additionally installed in the south China, and account for 6 percent of the whole country.
In recent years, with the improvement of grid-connected photovoltaic permeability, the demands for radiation and photovoltaic power are increasing, and researchers at home and abroad begin to accelerate the research on a photovoltaic power generation forecasting method. The photovoltaic power generation forecasting technologies widely adopted at present at home and abroad can be divided into the following categories:
(1) a principle forecasting method based on a solar total radiation forecasting and photoelectric efficiency conversion model;
(2) according to historical data and forecast factor data of the photovoltaic power station and photovoltaic power generation data, adopting statistical algorithms such as multiple regression and support vector machine to carry out analysis modeling, and then inputting numerical model forecast results into a power-statistics forecasting method;
(3) and (3) a simulation forecasting method based on the total solar radiation and photovoltaic I/V curve simulation model.
The inventor of the application finds that the prediction method in the prior art cannot predict different types of photovoltaic power generation power, and the predicted difference is large.
Disclosure of Invention
In order to solve the problems in the prior art, the photovoltaic power prediction method based on weather type subdivision provided by the invention has the advantages of wide application range, high accuracy and the like.
The embodiment of the invention provides a weather type subdivision-based photovoltaic power prediction method, which is used for predicting direct current off-grid photovoltaic power and alternating current grid-connected photovoltaic power and comprises the following steps:
step 1, calculating to obtain corresponding photovoltaic array inclined plane incident total radiation I under different weather types according to a direct scattering separation model and an inclined plane radiation modelt；
Step 2, according to the total incident radiation I of the inclined plane of the photovoltaic arraytEstablishing a photovoltaic cell model according to the plate temperature model, and calculating to obtain direct current off-grid photovoltaic power P according to the photovoltaic cell modeldc，
DC off-grid photovoltaic power PdcThe calculation formula is as follows:
Pdc＝ηPV,STC*[1-α(TC-25℃)]*It*S
in the formula, ηPV,STCPhotoelectric conversion efficiency (standard test conditions), temperature coefficient (α), and TcThe plate temperature is represented, It represents the total incident radiation of the inclined plane of the photovoltaic array, and S represents the effective area of the photovoltaic array for receiving the solar radiation;
wherein, the plate temperature model TCThe calculation formula of (a) is as follows:
Figure RE-GDA0002510559220000031
in the formula, TaIndicating air temperature, NOCT indicating rated photovoltaic cell working temperature, and G indicating inclined plane radiation intensity;
step 3, according to the DC off-grid photovoltaic power PdcAnd calculating the efficiency model of the inverter to obtain the alternating current grid-connected photovoltaic power PacAC grid-connected photovoltaic power PacThe calculation formula of (a) is as follows:
Pac＝Pdc*ηinv*Kc
in the formula, PacRepresenting grid-connected ac power of a photovoltaic array, ηinvRepresenting grid-connected inverter efficiency, KeAnd the loss coefficient of the alternating current loop line is shown.
In the method for predicting photovoltaic power based on weather type subdivision provided by the invention, the method can also have the following characteristics: the method for determining the direct scattering separation model comprises the following steps:
step 1, dividing the weather types of local regions according to the definition indexes;
and 2, comparing the prediction errors of the direct dispersion prediction models under each weather type, and selecting the direct dispersion separation model with the minimum error as the direct dispersion separation model.
In the method for predicting photovoltaic power based on weather type subdivision provided by the invention, the method can also have the following characteristics: wherein, in step 1, the weather types include:
weather type 1 includes: sunny, cloudy-sunny, and cloudy-sunny;
weather type 2 includes: cloudy, cloudy to cloudy, and cloudy to cloudy;
weather type 3 includes: light rain, rain shower, snow, light fog and haze;
weather type 4 includes: rain and snow.
In the method for predicting photovoltaic power based on weather type subdivision provided by the invention, the method can also have the following characteristics: the method for determining the inclined plane radiation model comprises the following steps:
step 1, dividing the weather types of a local area according to a definition index, acquiring the total cloud cover of the area, and performing cross division on the weather types;
and 2, comparing errors of the photovoltaic module in different weather types and different inclination angles in the inclined plane prediction model, and selecting the inclined plane prediction model with the minimum error as an inclined plane radiation model.
In the method for predicting photovoltaic power based on weather type subdivision provided by the invention, the method can also have the following characteristics: wherein, in step 1, the cross-partition of the weather types in the direct segregation model comprises:
k'T≥0.5&When the 2-year-old is more than or equal to C and more than 0-year-old, the weather is fine;
k'T≥0.5&When the 8-year-old is more than or equal to C and more than 2-year-old, the weather is sunny and gradually cloudy;
k'T≥0.5&When the 10 th year is more than or equal to the C > 8 th year, the weather is sunny and gradually cloudy;
when 0.5 > k'TWhen the weather is more than or equal to 0.2, the weather is cloudy and gradually cloudy;
when 0.2 > k'TWhen the weather is more than or equal to 0, the weather is rain, snow and haze,
wherein C represents total cloud number, k'TIndicating the sharpness index.
In the method for predicting photovoltaic power based on weather type subdivision provided by the invention, the method can also have the following characteristics: wherein, the calculation formula of the definition index is as follows:
Figure RE-GDA0002510559220000041
of formula (II) k'TDenotes the sharpness index, kTIndicating clarity, m indicates atmospheric mass;
in the formula, kTThe calculation method of (c) is as follows:
Figure RE-GDA0002510559220000042
wherein I represents the total horizontal radiation, I0Representing solar radiation at the level of the outer layer of the atmosphere.
In the method for predicting photovoltaic power based on weather type subdivision provided by the invention, the method can also have the following characteristics: wherein the inclination angle of the photovoltaic module is within +/-15 degrees of the latitude of the region.
In the method for predicting photovoltaic power based on weather type subdivision provided by the invention, the method can also have the following characteristics: wherein the errors of the prediction model are compared by the mean absolute percentage error, the root mean square error percentage and the correlation coefficient error.
Action and Effect of the invention
According to the weather type subdivision-based photovoltaic power prediction method provided by the invention, when the direct current off-grid photovoltaic power and the alternating current grid-connected photovoltaic power are predicted, the method comprises the following steps: the method comprises the steps of firstly, obtaining a direct scattering separation model and an inclined plane radiation model, and calculating to obtain corresponding total incident radiation I of the inclined plane of the photovoltaic array under different weather typest(ii) a Secondly, according to the total incident radiation I of the inclined plane of the photovoltaic arraytEstablishing a photovoltaic cell model according to the plate temperature model, and calculating and obtaining direct current off-grid photovoltaic power according to the photovoltaic cell model; step 3, according to the DC off-grid photovoltaic power PdcAnd calculating the efficiency model of the inverter to obtain the alternating current grid-connected photovoltaic power PacTherefore, the method has the advantages of wide application range, high accuracy and the like.
Drawings
Fig. 1 is a flowchart of a photovoltaic power prediction method based on weather type subdivision in an embodiment of the present invention.
Detailed Description
In order to make the technical means, the creation features, the achievement purposes and the effects of the invention easy to understand, the invention is specifically described below by combining the embodiment and the attached drawings.
< example 1>
Fig. 1 is a flowchart of a photovoltaic power prediction method based on weather type subdivision in an embodiment of the present invention.
As shown in fig. 1, in the photovoltaic power prediction method based on weather type subdivision provided in this embodiment, when predicting dc off-grid photovoltaic power and ac grid-connected photovoltaic power, the method includes the following steps:
(I) obtaining a direct scattering separation model and obtaining an inclined plane radiation model
The method for obtaining the direct scattering separation model comprises the following steps:
step 1, acquiring data of total horizontal radiation, scattered radiation, direct radiation and reflected radiation in 2010-2011 of the Beijing area, obtaining a definition index according to the corrected definition through the data, and finally classifying weather of the Beijing area through the definition index, wherein the data are shown in Table 1.
Table 1: division of weather types
Figure RE-GDA0002510559220000061
Wherein, the clarity index represents the transparency degree of the atmosphere, is closely related to the weather condition and the solar radiation, and has the formula as follows:
Figure RE-GDA0002510559220000062
solar radiation I on the horizontal plane outside the atmosphere0:
Figure RE-GDA0002510559220000075
Wherein E isscGamma, the correction value and declination angle of solar radiation flux of upper boundary of atmosphere layer caused by solar constant and change of distance between day and ground,
Figure RE-GDA0002510559220000076
and omega is latitude and time angle respectively, and the calculation formula is as follows:
ESC＝1367±7W/m2
Figure RE-GDA0002510559220000071
Figure RE-GDA0002510559220000072
however, the clarity index is not only related to meteorological conditions, but also to the position of the sun in the sky. In order to reduce the influence of the solar altitude on the clarity index, it is modified as follows:
Figure RE-GDA0002510559220000073
wherein k isT' is the clarity index after correction, and m is the atmospheric mass.
And S2, comparing the prediction errors of the direct dispersion prediction models under each weather type, and selecting the direct dispersion prediction model with the minimum error as a direct dispersion separation model. As shown in table 2.
TABLE 2 error analysis of optimal direct and scattered separation model under different weather types
Figure RE-GDA0002510559220000074
The method for obtaining the inclined plane radiation model comprises the following steps:
step 1, dividing the weather types of the local area according to the definition index, acquiring the total cloud cover of the area, and performing cross division on the weather types. As shown in table 3.
Table 3: weather type cross-segmentation
Figure RE-GDA0002510559220000081
And 2, comparing errors of the photovoltaic module in different weather types and different inclination angles in the inclined plane prediction model, and selecting the inclined plane prediction model with the minimum error as an inclined plane radiation model, as shown in tables 4, 5 and 6.
TABLE 4 optimal model for different weather types and different dip angles
Figure RE-GDA0002510559220000082
TABLE 5 optimal model prediction error analysis under better dip angles corresponding to different weather types
Figure RE-GDA0002510559220000091
Wherein: MAPE represents the mean absolute percentage error, NRMSE represents the root mean square error percentage, and CORR represents the correlation coefficient.
As shown in Table 5, according to the error analysis, the Perez model is the inclined plane radiation model with the minimum error under the weather type 1-1; under the weather types of 1-2 and 1-3.3&4, the Liu & Jordan model is an inclined plane radiation model with the minimum error; in weather type 2, the Klucher model is a slant radiation model with the minimum error. Therefore, the above model is selected as the oblique radiation model in this embodiment, as shown in table 6.
TABLE 6 preferred dip angle and model for different weather types
Figure RE-GDA0002510559220000092
(II) oblique incident total radiation I of photovoltaic arraytIs selected from
Calculating to obtain corresponding photovoltaic array inclined plane incident total radiation I under different weather types according to the direct scattering separation model and the inclined plane radiation modelt。ItRepresents the total incident radiation of the inclined plane of the photovoltaic array and has the unit Kw/m2。
(III) obtaining a plate temperature model
The calculation formula of the plate temperature model is as follows:
Figure RE-GDA0002510559220000101
in the formula, TaIndicating air temperature, and the NOCT indicating nominal photovoltaic cell operating temperature, typically 41-48 deg.C, in this example the NOCT is 48 deg., Δ T/Wm2＝0.035℃/Wm2(ii) a G represents the unit of the radiation intensity of the inclined plane W/m2, and the value of G in the embodiment is calculated by the inclined plane radiation model in the step two. In this example, the cell plate temperature Tc is 25 deg.c,zenith angle thetaZ＝48.2°。
(IV) establishing a photovoltaic cell model
According to the total incident radiation I of the inclined plane of the photovoltaic arraytAnd establishing a photovoltaic cell model by using the plate temperature model.
Photovoltaic cell model [1- α (T)C-25℃)]*It
Wherein α represents a temperature coefficient, and in this example, α of the crystalline silicon cell is 0.005, not
The crystal thin film battery α is 0.0035, TcThe plate temperature is indicated.
(V) DC off-grid photovoltaic power PdcAnd AC grid-connected photovoltaic power PacPredicting DC off-grid photovoltaic power PdcThe calculation formula of (a) is as follows:
Pdc＝ηPV,STC*[1-α(TC-25℃)]*It*S
in the formula, ηPV,STCThe photoelectric conversion efficiency of standard test conditions is shown, the crystalline silicon cell accounts for 12% -18%, and the amorphous silicon thin film cell accounts for 5% -8%; STC represents standard test conditions of the ground photovoltaic module, namely the atmospheric mass AM is 1.5; s represents the effective area of the photovoltaic array to receive solar radiation.
AC grid-connected photovoltaic power PacThe calculation formula of (a) is as follows:
Pac＝Pdc*ηinv*Kc
in the formula, PacRepresenting grid-connected ac power of a photovoltaic array, ηinvRepresenting the efficiency of the grid-connected inverter, wherein the efficiency of the inverter from 10:00 to 16:00 is 0.95; taking 0.8 in the rest time period; keWhich represents the ac loop line loss coefficient, is typically 0.95.
Effects and effects of the embodiments
According to the method for predicting the photovoltaic power based on the weather type subdivision, when the direct current off-grid photovoltaic power and the alternating current on-grid photovoltaic power are predicted, the method comprises the following steps: the method comprises the steps of firstly, obtaining a direct scattering separation model and an inclined plane radiation model, and calculating to obtain corresponding inclined planes of the photovoltaic array under different weather typesIncident total radiation It(ii) a Secondly, according to the total incident radiation I of the inclined plane of the photovoltaic arraytEstablishing a photovoltaic cell model according to the plate temperature model, and calculating and obtaining direct current off-grid photovoltaic power according to the photovoltaic cell model; step 3, according to the DC off-grid photovoltaic power PdcAnd calculating the efficiency model of the inverter to obtain the alternating current grid-connected photovoltaic power PacTherefore, the method has the advantages of wide application range, high accuracy and the like.
The above embodiments are preferred examples of the present invention, and are not intended to limit the scope of the present invention.

Claims (8)

1. A photovoltaic power prediction method based on weather type subdivision is used for predicting direct current off-grid photovoltaic power and alternating current grid-connected photovoltaic power and is characterized by comprising the following steps:
step 1, calculating to obtain corresponding photovoltaic array inclined plane incident total radiation I under different weather types according to a direct scattering separation model and an inclined plane radiation modelt；
Step 2, according to the total incident radiation I of the inclined plane of the photovoltaic arraytEstablishing a photovoltaic cell model according to the plate temperature model, and calculating to obtain direct current off-grid photovoltaic power P according to the photovoltaic cell modeldc，
The direct current off-grid photovoltaic power PdcThe calculation formula is as follows:
Pdc＝ηPV,STC*[1-α(TC-25℃)]*It*S
in the formula, ηPV,STCPhotoelectric conversion efficiency (standard test conditions), temperature coefficient (α), and TcThe plate temperature is represented, It represents the total incident radiation of the inclined plane of the photovoltaic array, and S represents the effective area of the photovoltaic array for receiving the solar radiation;
wherein the plate temperature model TCThe calculation formula of (a) is as follows:
Figure FDA0002461371970000011
in the formula, TaIndicating air temperature, NOCT indicating rated photovoltaicThe working temperature of the battery, G represents the radiation intensity of the inclined plane;
step 3, according to the DC off-grid photovoltaic power PdcAnd calculating the efficiency model of the inverter to obtain the alternating current grid-connected photovoltaic power PacSaid AC grid-connected photovoltaic power PacThe calculation formula of (a) is as follows:
Pac＝Pdc*ηinv*Kc
in the formula, PacRepresenting grid-connected ac power of a photovoltaic array, ηinvRepresenting grid-connected inverter efficiency, KeAnd the loss coefficient of the alternating current loop line is shown.
2. The weather-type-subdivision-based photovoltaic power prediction method of claim 1, wherein:
the method for determining the direct scattering separation model comprises the following steps:
step 1, dividing the weather types of local regions according to the definition indexes;
and 2, comparing the prediction errors of the direct and scattered prediction models under each weather type, and selecting the direct and scattered prediction model with the minimum error as the direct and scattered separation model.
3. The weather-type-subdivision-based photovoltaic power prediction method of claim 2, wherein:
wherein, in step 1, the weather types include:
weather type 1 includes: sunny, cloudy-sunny, and cloudy-sunny;
weather type 2 includes: cloudy, cloudy to cloudy, and cloudy to cloudy;
weather type 3 includes: light rain, rain shower, snow, light fog and haze;
weather type 4 includes: rain and snow.
4. The weather-type-subdivision-based photovoltaic power prediction method of claim 1, wherein:
the method for determining the inclined plane radiation model comprises the following steps:
step 1, dividing the weather types of a local area according to a definition index, acquiring the total cloud cover of the area, and performing cross division on the weather types;
and 2, comparing errors of the photovoltaic module in different weather types and different inclination angles in the inclined plane prediction model, and selecting the inclined plane prediction model with the minimum error as the inclined plane radiation model.
5. The weather-type-subdivision-based photovoltaic power prediction method of claim 4, wherein:
wherein, in step 1, the cross-partition of the weather types in the straggling and separating model comprises:
k'T≥0.5&When the 2-year-old is more than or equal to C and more than 0-year-old, the weather is fine;
k'T≥0.5&When the 8-year-old is more than or equal to C and more than 2-year-old, the weather is sunny and gradually cloudy;
k'T≥0.5&When the 10 th year is more than or equal to the C > 8 th year, the weather is sunny and gradually cloudy;
when 0.5 > k'TWhen the weather is more than or equal to 0.2, the weather is cloudy and gradually cloudy;
when 0.2 > k'TWhen the weather is more than or equal to 0, the weather is rain, snow and haze,
wherein C represents the total cloud amount, k'TRepresenting the sharpness index.
6. The weather-type-subdivision-based photovoltaic power prediction method of claim 4, wherein:
wherein, the calculation formula of the definition index is as follows:
Figure FDA0002461371970000031
of formula (II) k'TRepresenting the sharpness index, kTIndicating clarity, m indicates atmospheric mass;
in the formula, kTThe calculation method of (c) is as follows:
Figure FDA0002461371970000032
wherein I represents the total horizontal radiation, I0Representing solar radiation at the level of the outer layer of the atmosphere.
7. The weather-type-subdivision-based photovoltaic power prediction method of claim 4, wherein:
wherein the inclination angle of the photovoltaic module is within +/-15 degrees of the latitude of the region.
8. The weather-type-subdivision-based photovoltaic power prediction method of claim 4, wherein:
and comparing the errors of the slope prediction model through the average absolute percentage error, the root mean square error percentage and the correlation coefficient error.
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