CN112989632B - Solar energy resource short-term forecasting method based on satellite radiation product - Google Patents
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Abstract
The invention provides a solar resource short-term forecasting method based on a satellite radiation product, which comprises the following steps: acquiring historical solar radiation data corresponding to the current period; establishing a solar radiation value forecasting model based on an averaging function according to the historical solar radiation data corresponding to the current period; outputting an initial solar radiation forecast value in a forecast time period of the current period according to the forecast model; starting from the second period, the solar resource short-forecasting method further comprises: and correcting the initial solar radiation forecast value in the forecast time period of the current cycle by utilizing the ground observation solar radiation value in the forecast time period corresponding to the previous cycle to obtain the final solar radiation forecast value in the forecast time period of the current cycle.
Description
Technical Field
The invention relates to the field of solar resource forecasting, in particular to a solar resource short-term forecasting method based on satellite radiation products, a computer readable storage medium and electronic equipment.
Background
In recent years, photovoltaic power generation has been developed particularly rapidly as a new energy source with the environmental and energy problems becoming more prominent. The surface solar irradiance is the most direct climate factor affecting the photovoltaic power generation, but the surface solar irradiance varies periodically and randomly with seasons and weather, so the photovoltaic power generation has obvious intermittency and fluctuation.
Therefore, how to accurately forecast the solar radiation becomes a technical problem to be solved urgently in the field.
Disclosure of Invention
The invention aims to provide a solar resource short-term forecasting method based on a satellite radiation product, a computer readable storage medium and an electronic device.
As a first aspect of the present disclosure, there is provided a solar resource forecasting method based on a satellite radiation product, the solar resource forecasting method including the following steps performed periodically:
acquiring historical solar radiation data corresponding to a current cycle, wherein the acquisition ending time of the historical solar radiation data corresponding to the current cycle is continuous with the starting time of a forecast time period of the current cycle, when the starting time of the forecast time period of the current cycle is sunrise time and the ending time of the current cycle is predetermined time after sunrise, the historical solar radiation data is acquired according to astronomical observation radiation data in the predetermined time period before sunrise, and when the forecast time period of the current cycle is time after the predetermined time after sunrise, the historical solar radiation data comprises solar radiation values carried in satellite radiation products;
establishing a solar radiation value forecasting model based on an averaging function according to the historical solar radiation data corresponding to the current period;
outputting an initial solar radiation forecast value in a forecast time period of the current period according to the forecast model;
starting from the second period, the solar resource short-forecasting method further comprises:
and correcting the initial solar radiation forecast value in the forecast time period of the current cycle by utilizing the ground observation solar radiation value in the forecast time period corresponding to the previous cycle to obtain the final solar radiation forecast value in the forecast time period of the current cycle.
Optionally, the step of correcting the initial solar radiation forecast value in the forecast time period of the current cycle by using the ground observation solar radiation value of the forecast time period corresponding to the previous cycle to obtain the final solar radiation forecast value in the forecast time period of the current cycle includes:
the first difference is calculated using the following equation (1):
calculating the final solar radiation forecast value for the forecast time period of the current cycle using the following equation (2):
wherein the content of the first and second substances,
、
are all the serial numbers of the periods,
is a positive integer and is a non-zero integer,
=1，2，3……，
is a positive integer and is a non-zero integer,
=1，2，3……；
Optionally, the step of building a solar radiation value forecasting model based on the averaging function according to the historical solar radiation data comprises:
calculating a continuation sequence of sequences from the historical solar radiation data, the sequences representing a set of time-varying arrays constructed from the historical solar radiation data;
selecting a significant period by utilizing the grey correlation degree;
and establishing the solar radiation value forecasting model by utilizing multivariate linear regression.
Optionally, when the forecast time period of the current cycle is a time period after a predetermined time after sunrise, calculating a continuation sequence of the sequence according to the historical solar radiation data includes:
performing linear interpolation on the solar radiation value carried in the satellite radiation product to obtain the solar radiation value in an interpolation time period;
and calculating a continuation sequence of the sequence by using the solar radiation values in each interpolation time period.
Optionally, the solar radiation value carried in the satellite radiation product is hour data, and the interpolation time period is between 10 minutes and 30 minutes.
Optionally, the duration of the forecast time period for each cycle is between 0.5 hours and 4 hours.
Optionally, in each cycle, the method for solar resource forecasting further includes:
and acquiring the ground observation solar radiation value of the forecast time period corresponding to the previous period.
Optionally, for the first cycle, the initial solar radiation forecast value obtained for the first cycle is taken as the final solar radiation forecast value within the forecast time period of the first cycle.
As a second aspect of the present disclosure, there is provided a computer-readable storage medium having stored thereon an executable program, which when called, is capable of implementing the solar resource forecast method according to the first aspect of the present disclosure.
As a third aspect of the present disclosure, there is provided an electronic apparatus, wherein the electronic apparatus includes:
a storage module having an executable program stored thereon;
one or more processors capable of implementing the solar resource forecasting method of the first aspect of the disclosure when the one or more processors invoke the executable program.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
fig. 1 is a flowchart of an embodiment of a method for solar resource forecasting based on satellite radiation products according to the present invention.
Detailed Description
The following detailed description of embodiments of the invention refers to the accompanying drawings. It should be understood that the detailed description and specific examples, while indicating the present invention, are given by way of illustration and explanation only, not limitation.
As a first aspect of the present invention, there is provided a solar resource short forecasting method based on a satellite radiation product, wherein, as shown in fig. 1, the solar resource short forecasting method includes the following steps that are performed periodically:
in step S110, acquiring historical solar radiation data corresponding to a current cycle, where an acquisition end time of the historical solar radiation data corresponding to the current cycle is continuous with a start time of a forecast time period of the current cycle, the historical solar radiation data is acquired according to astronomical observation radiation data within a predetermined time period before sunrise when a start time of the forecast time period of the current cycle is a sunrise time and an end time of the current cycle is a predetermined time after sunrise, and the historical solar radiation data includes a solar radiation value carried in the satellite radiation product when the forecast time period of the current cycle is a time period after the predetermined time after sunrise;
in step S120, a solar radiation value forecasting model based on an averaging function is established according to the historical solar radiation data corresponding to the current period;
in step S130, an initial solar radiation forecast value of the current cycle within a forecast time period of the current cycle is output according to the forecast model.
Starting from the second period, the method for solar resource forecasting may further include, after step S130:
in step S140, the initial solar radiation forecast value in the forecast time period of the current cycle is modified by using the ground observation solar radiation value in the forecast time period corresponding to the previous cycle, so as to obtain the final solar radiation forecast value in the forecast time period of the current cycle.
For the sake of understanding, the three concepts of "current cycle", "forecast time period of current cycle", and "historical solar radiation data corresponding to current cycle" are illustrated.
The "current period" refers to an operation period for performing the solar resource short-term forecasting method. Each cycle can predict the solar radiation value within 0.5 to 4 hours in the future.
In the present disclosure, there is no particular limitation on how to obtain the historical solar radiation data from the astronomical observation radiation data within a predetermined time period before sunrise "when the start time of the forecast time period of the current cycle is the sunrise time and the end time of the current cycle is a predetermined time after sunrise. For example, the historical solar radiation data may be obtained by directly using astronomical observation radiation data within a predetermined time period before sunrise, or may be obtained by multiplying astronomical observation radiation data within a predetermined time period before sunrise by a coefficient greater than 0.5 and less than 1.
In the disclosure, the initial solar radiation forecast value in the first period may not be modified, and the obtained initial solar radiation forecast value may be directly used as the final solar radiation forecast value.
Assuming that each period can predict the solar radiation value within 3 hours in the future, the forecast time period of the current period is 10:00am to 13:00am, and the acquisition end time of the historical solar radiation data corresponding to the current period should be 10:00 am. As an alternative, the historical solar radiation data may be solar radiation data for a period of 7:00am to 10:00am (the forecast time period corresponding to the previous cycle).
In the invention, the "satellite radiation product" is software or an application program for processing data obtained by a meteorological satellite and outputting required data. The satellite radiation product may be used to provide solar radiation values.
The inventor of the present invention has found that the solar radiation value provided by the satellite radiation product is generally higher than the ground-observed solar radiation value obtained by ground observation. Researches show that the cause of the phenomenon mainly lies in that errors exist in the inversion of cloud cover and aerosol by satellites, and therefore corresponding errors also exist in initial radiation prediction values output by a prediction model established by utilizing solar radiation values output in satellite radiation products.
In step S140 of the solar resource short-term forecasting method provided by the present invention, the initial forecast value is corrected by using the solar radiation value obtained by ground observation, so that the satellite inversion error can be eliminated, and the obtained final forecast result is more accurate. In other words, the solar resource short-term forecasting method provided by the invention adopts a rolling forecasting and rolling correcting method to obtain a more accurate forecasting result.
The average generation function is that the time sequence calculates the average value according to different time intervals to generate a group of contemporaneous functions, and then the original time sequence and the group of functions are used for establishing a regression prediction equation, so that the element condition of a certain time period in the future can be predicted by utilizing the self change of historical data. However, in addition to the error in the above-mentioned satellite inversion, the solar energy resource has a characteristic of being present only after sunrise. The solar radiation data output only by the satellite radiation product cannot predict the solar radiation value from the beginning of the sunrise time to the predetermined time period after the sunrise by using the averaging function. To address this issue, a homodyne function model may be built using astronomical radiation within a predetermined time period before sunrise as historical solar radiation data. Through verification, the result of predicting the solar radiation value from the sunrise time to the sunrise within the preset time period by establishing a homodyne function model by using the astronomical radiation within the preset time period before the sunrise as historical solar radiation data is relatively accurate.
In the present invention, the specific type of the satellite radiation product is not particularly limited. As an alternative embodiment, the satellite radiation product can be total radiation data obtained by a wind cloud four-series optical meteorological satellite (FY-4A). The data is lattice data with the resolution of 4km, solar short-term prediction of any point in the coverage range of the Fengyun No. four satellite can be realized, and the space has technical advantages.
In the present invention, how to specifically execute step S140 is not particularly limited, as long as the satellite inversion error can be reduced or even eliminated.
For example, a difference between the ground observed solar radiation value and the initial solar radiation forecast value for the corresponding time period may be calculated, and a function may be established that eliminates the difference using the ground observed solar radiation value and the initial solar radiation forecast value for the corresponding time period. In step S140, the initial solar radiation forecast value is substituted into the function, and the final solar radiation forecast value is automatically generated.
As an alternative embodiment, step S140 may include:
the first difference is calculated using the following equation (1):
calculating the final solar radiation forecast value for the forecast time period of the current cycle using the following equation (2):
wherein the content of the first and second substances,
、
are all the serial numbers of the periods,
is a positive integer and is a non-zero integer,
=1，2，3……，
is a positive integer and is a non-zero integer,
=1，2，3……；
The actual observation of the inventor of the invention shows that the final solar radiation forecast value obtained after the initial solar radiation forecast value is corrected by using the formula (2) has little difference with the actual observation value. Namely, the solar resource short-term forecasting method provided by the invention can be used for accurately forecasting the solar resource short-term.
The ground observation solar radiation value is obtained through ground observation. Accordingly, in each cycle, the solar resource forecasting method further comprises:
and acquiring the ground observation solar radiation value of the forecast time period corresponding to the previous period.
In the present invention, the step of how to establish the averaging function according to the historical solar radiation data is not particularly limited.
Generally, establishing a homodyne function includes the steps of:
calculating a continuation sequence of sequences, the sequences representing a set of time-varying arrays constructed from the historical solar radiation data;
selecting a significant period by utilizing the grey correlation degree;
and (4) establishing a forecasting model by utilizing multivariate linear regression.
For historical solar radiation data, the step S120 of establishing the averaging function may include: calculating a continuation sequence of the sequence according to the historical solar radiation data; selecting a significant period by utilizing the grey correlation degree; and establishing the solar radiation value forecasting model by utilizing multivariate linear regression.
Typically, the solar radiation values output by satellite products are hour data. That is, the solar radiation values in satellite products are data over different hours. For example, a solar radiation value between 10:00am and 11:00 am.
In order to make the prediction result more accurate, in the present invention, the historical solar radiation data may be linearly interpolated. Specifically, the step of calculating a continuation sequence of the sequence from the historical solar radiation data may include: performing linear interpolation on the solar radiation value carried in the satellite radiation product to obtain the solar radiation value in an interpolation time period; and calculating a continuation sequence of the sequence by using the solar radiation values in each interpolation time period.
In the present invention, the duration of the interpolation period is not particularly limited, and for example, the interpolation period is between 10 minutes and 30 minutes.
How to calculate the continuation sequence of the sequence is described below:
setting a time sequence
Has a mean value of
For time series
A homodyne function is defined.
In the formula (I), the compound is shown in the specification,
) And according to applicable circumstances, take
). From equation (3), one can obtain
A averaging function.
It can be seen that the averaging function is derived by calculating the average value of the time series at certain time intervals. Extending the homogeneous function definition domain to the whole number axis, namely performing periodic extension to obtain a homogeneous function extension sequence which is a periodic function and represents various different periodic changes of the original sequence to a certain extent.
It should be noted that, in the above formula,
is the relation between the solar radiation value and the time.
The following describes the steps of picking the saliency period using the grey correlation:
the grey correlation analysis method is used as a method for measuring the correlation degree between the elements according to the similarity or difference degree of development trends between the elements. The grey system theory proposes a concept of grey correlation analysis on each subsystem, seeks a numerical relationship between subsystems (or elements) in the system through a certain method, and is very suitable for dynamic process analysis. The method aims to reveal the strength of the relation between the homogenesis function and the forecast sequence, the operation object is the time sequence of the elements, and the final result is expressed as the degree of association between the homogenesis function and the forecast sequence, namely the degree of association. The method comprises the following basic steps:
and (I) carrying out sequence standardization treatment.
In order to keep the dimension uniformity of different factors, firstly, the elements of each sequence are standardized to eliminate the incommercibility caused by the great difference of the absolute values of different sequences:
in the formula (I), the compound is shown in the specification,
the length of each sequence;
the number of sequences, namely the sum of the factor number and the target amount;
is an original sequence, shows the relation between the solar radiation value and the time,
is the sequence
Is determined by the average value of (a) of (b),
is the standard deviation of the sequence and is,
is the result of the normalization process.
(II) correlation coefficient calculation
For the factor
To the target amount
The correlation coefficient of a point can be calculated by the following formula:
wherein, P is a resolution coefficient, the value of the resolution coefficient is between 0 and 1, different P values correspond to different correlation degrees, and the smaller the P value is, the higher the resolution is, which can be generally 0.5.
And (III) calculating the association degree.
Because each column of data has
Length, and therefore, the correlation coefficient calculated according to equation (5) also has
Information is too scattered. By averaging the management coefficients, the correlation coefficients of each point can be concentrated to a value.
The following steps are introduced to establish the solar radiation value forecasting model by using multiple linear regression:
and after selecting the dominant period through grey correlation analysis, establishing a forecasting model by using a multiple linear regression method. And (3) setting a model to be used as q-step forecasting, and performing q-step extension on the selected homogenesis function to obtain a final homogenesis function forecasting equation:
in the formula (I), the compound is shown in the specification,
and
the coefficients estimated for the multiple regression technique,
is a continuation generating function.
As a second aspect of the present invention, there is provided a computer-readable storage medium having stored thereon an executable program, which when called, is capable of implementing the solar resource forecast method according to the first aspect of the present invention.
As a third aspect of the present invention, there is provided an electronic apparatus, wherein the electronic apparatus includes:
a storage module having an executable program stored thereon;
one or more processors capable of implementing the solar resource forecasting method of the first aspect of the invention when said one or more processors invoke said executable program.
It will be understood by those of ordinary skill in the art that all or some of the steps of the methods, systems, functional modules/units in the devices disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof. In a hardware implementation, the division between functional modules/units mentioned in the above description does not necessarily correspond to the division of physical components; for example, one physical component may have multiple functions, or one function or step may be performed by several physical components in cooperation. Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on computer readable media, which may include computer storage media (or non-transitory media) and communication media (or transitory media). The term computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data, as is well known to those of ordinary skill in the art. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, Digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by a computer. In addition, communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media as known to those skilled in the art.
It will be understood that the above embodiments are merely exemplary embodiments taken to illustrate the principles of the present invention, which is not limited thereto. It will be apparent to those skilled in the art that various modifications and improvements can be made without departing from the spirit and substance of the invention, and these modifications and improvements are also considered to be within the scope of the invention.
Claims (7)
1. A solar energy resource short-term forecasting method based on satellite radiation products is characterized by comprising the following steps of:
acquiring historical solar radiation data corresponding to a current cycle, wherein the acquisition ending time of the historical solar radiation data corresponding to the current cycle is continuous with the starting time of a forecast time period of the current cycle, when the starting time of the forecast time period of the current cycle is sunrise time and the ending time of the current cycle is predetermined time after sunrise, the historical solar radiation data is acquired according to astronomical observation radiation data in the predetermined time period before sunrise, and when the forecast time period of the current cycle is time after the predetermined time after sunrise, the historical solar radiation data comprises solar radiation values carried in satellite radiation products;
establishing a solar radiation value forecasting model based on a homogenesis function according to the historical solar radiation data corresponding to the current period, wherein the solar radiation value forecasting model comprises the following steps: calculating a continuation sequence of sequences from the historical solar radiation data, the sequences representing a set of time-varying arrays constructed from the historical solar radiation data; selecting a significant period by utilizing the grey correlation degree; establishing the solar radiation value forecasting model by utilizing multivariate linear regression, wherein when the forecasting time period of the current period is a time period after a preset time after sunrise, calculating a continuation sequence of the sequence according to the historical solar radiation data comprises the following steps: performing linear interpolation on the solar radiation value carried in the satellite radiation product to obtain the solar radiation value in an interpolation time period; calculating a continuation sequence of the sequence by using the solar radiation values in each interpolation time period;
outputting an initial solar radiation forecast value in a forecast time period of the current period according to the forecast model;
starting from the second period, the solar resource short-forecasting method further comprises:
the method for correcting the initial solar radiation forecast value in the forecast time period of the current cycle by using the ground observation solar radiation value in the forecast time period corresponding to the previous cycle to obtain the final solar radiation forecast value in the forecast time period of the current cycle comprises the following steps:
the first difference is calculated using the following equation (1):
calculating the final solar radiation forecast value for the forecast time period of the current cycle using the following equation (2):
wherein the content of the first and second substances,i、jare all the serial numbers of the periods,iis a positive integer and is a non-zero integer,i=1,2,3……，jis a positive integer and is a non-zero integer,j=1,2,3……；
△ i is as followsiA first difference value required to be used in each period;
△ j is as followsjA first difference value required to be used in each period;
R j is as followsjA final solar radiation forecast value over a forecast time period of the cycle;
R i-1 is as followsi-a final solar radiation forecast value over a forecast period of 1 cycle;
T i-1 is as followsi-astronomical observation radiation data over a forecast time period corresponding to 1 cycle;
R0 j is as followsjAn initial solar radiation forecast value for a forecast time period of a cycle; wherein the content of the first and second substances,
calculating a continuation sequence of the sequence comprises:
let the mean value of a time series x (n) be
；
For the time series
Defining a homogenesis function:
in the formula, nl= INT (n/l) and, as applicable, m = INT (n/3);
obtaining m number of averaging functions according to a formula (3);
extending the m homogenesis function definition domains to the whole number axis to obtain a homogenesis function extension sequence;
the step of selecting the significant period by using the grey correlation degree comprises the following steps:
normalizing the elements of each sequence according to formula (4);
calculating the factor according to equation (5)x i For target amountx 0 In thatkA correlation coefficient of the points;
calculating the correlation coefficient of each point according to the formula (6), and determining the significant period according to the correlation coefficient:
wherein, P is a resolution coefficient, and the value of P is between 0 and 1;
in the step of establishing the solar radiation value prediction model by using multivariate linear regression, the obtained mesogen function prediction equation is shown as formula (7):
wherein the content of the first and second substances,a 0 and a i The coefficients estimated for the multiple regression technique,f i is a continuation generating function.
2. The method according to claim 1, wherein the solar radiation values carried in the satellite radiation products are hour data, and the interpolation time period is between 10 minutes and 30 minutes.
3. A method as claimed in claim 1 or 2, wherein the duration of the forecast time period for each period is between 0.5 and 4 hours.
4. The solar energy resource forecasting method according to claim 1 or 2, wherein in each period, the solar energy resource forecasting method further comprises:
and acquiring the ground observation solar radiation value of the forecast time period corresponding to the previous period.
5. A solar resource short-term forecasting method according to claim 1 or 2, characterized in that, for the first cycle, the initial solar radiation forecast value obtained for the first cycle is taken as the final solar radiation forecast value in the forecast time period of the first cycle.
6. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored thereon an executable program, which when called, can implement the solar resource forecasting method of any one of claims 1 to 5.
7. An electronic device, characterized in that the electronic device comprises:
a storage module having an executable program stored thereon;
one or more processors capable of implementing the solar resource forecasting method of any one of claims 1 to 5 when the executable program is invoked by the one or more processors.
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| CN102281016A (en) * | 2011-06-09 | 2011-12-14 | 国网电力科学研究院 | Clear-sky photovoltaic super-short-term power forecast method based on real-time radiation acquisition technology |
| CN203645341U (en) * | 2013-04-15 | 2014-06-11 | 北京市建筑设计研究院有限公司 | Solar energy large scale utilizing system used for city settlement |
| CN107644416A (en) * | 2017-09-15 | 2018-01-30 | 中国科学院寒区旱区环境与工程研究所 | A kind of real-time dynamic cloud amount inversion method based on ground cloud atlas |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN102281016A (en) * | 2011-06-09 | 2011-12-14 | 国网电力科学研究院 | Clear-sky photovoltaic super-short-term power forecast method based on real-time radiation acquisition technology |
| CN203645341U (en) * | 2013-04-15 | 2014-06-11 | 北京市建筑设计研究院有限公司 | Solar energy large scale utilizing system used for city settlement |
| CN107644416A (en) * | 2017-09-15 | 2018-01-30 | 中国科学院寒区旱区环境与工程研究所 | A kind of real-time dynamic cloud amount inversion method based on ground cloud atlas |
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