CN113255985A - Method and system for predicting power generation capacity of photovoltaic power station - Google Patents
Method and system for predicting power generation capacity of photovoltaic power station Download PDFInfo
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Abstract
The invention provides a method and a system for predicting the power generation capacity of a photovoltaic power station, which comprises the following steps: collecting the current illumination intensity of a photovoltaic power station; setting a general relational expression of the solar radiation quantity, the illumination parameters and the illumination intensity; calculating the future illumination intensity according to a general relational expression by utilizing the characteristic that the total solar radiation quantity is certain but basically shows the annual regular change along with the solar altitude; and fitting the future illumination intensity into a curve of the illumination intensity changing along with time, and calculating the future power generation amount according to the fitted curve. According to the invention, the illumination intensity prediction method is simplified according to the principle that the total solar radiation amount is certain but basically shows the annual regular change along with the solar altitude angle, and a reasonable generating capacity prediction method is obtained.
Description
Technical Field
The invention belongs to the technical field of photovoltaic power generation, and particularly relates to a method and a system for predicting the power generation capacity of a photovoltaic power station.
Background
With the rapid popularization of new energy in China, the popularization rate and the development potential of photovoltaic and wind power are the fastest, photovoltaic power generation is generally used as standby energy to be superposed on thermal power generation, if the photovoltaic power generation capacity is too high, a large burden is caused on a power grid, potential safety hazards are formed, waste of the power generation capacity is caused, and therefore the prediction of the power generation power and the power generation capacity of a power station in actual work is of great significance. In the power generation process, the photovoltaic power generation is greatly influenced by illumination, so that the photovoltaic power generation influences the power generation amount by the illumination intensity, the power generation amount is predicted by the traditional illumination value collection method, the total radiation amount of sunlight needs to be considered, the calculation is quite troublesome, and the error is large; and the server sends back a response to the acquisition of the weather data on the network by sending a request to the server, extracts the weather data by using a get command after processing, and rewrites the request program once the website is changed and upgraded, so that the stability is poor.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a method and a system for predicting the power generation capacity of a photovoltaic power station, so as to solve the technical problems.
In a first aspect, the present invention provides a method for predicting power generation of a photovoltaic power station, comprising:
collecting the current illumination intensity of a photovoltaic power station;
setting a general relational expression of the solar radiation quantity, the illumination parameters and the illumination intensity;
calculating the future illumination intensity according to a general relational expression by utilizing the principle that the solar radiation quantity is certain but shows the annual regular change along with the solar altitude angle;
and fitting the future illumination intensity into a curve of the illumination intensity changing along with time, and calculating the future power generation amount according to the fitted curve.
Further, the method further comprises:
and (3) connecting an API (application programming interface) of a weather forecast website, and automatically acquiring illumination parameters including cloud cover and visibility through the forecast website.
Further, the general relation is as follows: solar radiation amount × [ (1-cloud amount) × cloud amount weight ] × (visibility ×) visibility weight) × (light intensity).
Further, the calculating the future illumination intensity by using the general relation includes:
calculating the current solar radiation amount of the upper air bound, wherein the current solar radiation amount is the total solar radiation amount x (the nearest distance to the earth day/the current distance to the earth day) x (the current solar altitude/the maximum solar altitude of the current year);
calculating the future solar radiation amount of the upper air bound, wherein the future solar radiation amount is the total solar radiation amount x (the nearest distance to the earth day/the distance to the earth day in the future) x (the future solar altitude/the maximum solar altitude in the future);
substituting the illumination parameter of the current time and the current solar radiation amount into the general relational expression to obtain a current illumination intensity calculation formula of the atmospheric lower bound,
current solar radiation amount × [ (1-current cloudiness) × (current cloudiness weight ] × (current visibility × current visibility weight) × (current visibility weight) ═ current illumination intensity;
substituting the general relational expression into the illumination parameter of future time and future solar radiation quantity to obtain a future illumination intensity calculation formula of the atmospheric lower bound,
future solar radiation amount × [ (1-future cloudiness) × (future cloudiness weight ] × (future visibility × future visibility weight) ═ future light intensity;
integrating the current illumination intensity calculation formula and the future illumination intensity calculation formula to obtain a final formula of the future illumination intensity,
future light intensity ═ future solar radiation amount × [ (1-future cloud amount) × future cloud amount weight ] × (future visibility × future visibility weight) }/{ current solar radiation amount × [ (1-current cloud amount) × current cloud amount weight ] × (current visibility × current visibility weight) };
and establishing a prediction model of the illumination intensity by using a k-means clustering algorithm according to a final formula of the future illumination intensity.
Further, the establishing of the prediction model of the illumination intensity by using the k-means clustering algorithm according to the final formula of the future illumination intensity includes:
dividing the light into a plurality of clusters according to the final formula of the future light intensity and the light parameters;
randomly taking a plurality of future illumination intensities under each cluster as an initial cluster center;
future light intensity samples are input and assigned to the nearest cluster center, and the cluster center is recalculated each time a sample is input.
Further, the method further comprises:
and training the prediction model by utilizing a neural network to obtain the current cloud cover weight, the future cloud cover weight, the current visibility weight and the future visibility weight.
Further, the fitting the future illumination intensity into a curve of the illumination intensity changing with time, and calculating the predicted power generation amount according to the fitted curve includes:
acquiring the current power generation power of a photovoltaic power station, and calculating the ratio of the current power generation power to the current illumination intensity to obtain a unit illumination intensity load value;
calculating the product of the future illumination intensity and the unit illumination load value to obtain the future power generation power which is the unit illumination load value multiplied by the future illumination intensity;
and aiming at the prediction model of the illumination intensity, forming a fitting curve with the ordinate as future generating power and the abscissa as time.
Further, the calculating the predicted power generation amount according to the fitted curve includes:
acquiring a prediction time at which power generation amount prediction is to be performed;
and calculating the curve area of a fitting curve between the current time and the predicted time, wherein the curve area is used as the predicted power generation amount.
Further, the method further comprises:
acquiring a high-temperature influence rate of a photovoltaic module of a photovoltaic power station, wherein the high-temperature influence rate is the percentage of reduction of the generated power of the photovoltaic module when the air temperature is higher by one degree per liter;
automatically acquiring the current air temperature and the predicted air temperature through a forecast website;
when the predicted air temperature is larger than the current air temperature, calculating a difference value between the predicted air temperature and the current air temperature, wherein the difference value is used as an elevated temperature;
updating the future generated power according to the high-temperature influence rate and the rising temperature to obtain the accurate future generated power which is the rising temperature x (1-high-temperature influence rate) x the future generated power;
and updating the predicted generating capacity according to the accurate future generating power.
In a second aspect, the present invention provides a system for predicting power generation of a photovoltaic power station, comprising:
the information acquisition unit is configured for acquiring the current illumination intensity of the photovoltaic power station;
the formula setting unit is used for setting a general relational expression of the solar radiation quantity, the illumination parameters and the illumination intensity;
the light intensity calculating unit is configured for calculating the future illumination intensity according to the general relational expression by utilizing the principle that the solar radiation quantity is certain but shows annual regular change along with the solar altitude angle;
and the fitting calculation unit is configured to fit the future illumination intensity into a curve of the illumination intensity changing along with time, and calculate the future power generation amount according to the fitting curve.
The beneficial effect of the invention is that,
according to the method and the system for predicting the power generation capacity of the photovoltaic power station, provided by the invention, the method for predicting the illumination intensity is simplified according to the principle that the total solar radiation is constant but regularly changes along with time; directly connecting an API of the network weather forecast, and ensuring the accuracy and the data stability; the influence of cloud cover and visibility is considered to obtain a reasonable power generation amount prediction method, the influence of temperature factors and age decay factors on power generation power and power generation amount is considered, and the accuracy of the prediction method is improved.
In addition, the invention has reliable design principle, simple structure and very wide application prospect.
Drawings
In order to more clearly illustrate the embodiments or technical solutions in the prior art of the present invention, the drawings used in the description of the embodiments or prior art will be briefly described below, and it is obvious for those skilled in the art that other drawings can be obtained based on these drawings without creative efforts.
FIG. 1 is a schematic flow diagram of a method of one embodiment of the invention.
FIG. 2 is a schematic block diagram of a system of one embodiment of the present invention.
Detailed Description
In order to make those skilled in the art better understand the technical solution of the present invention, the technical solution in the embodiment of the present invention will be clearly and completely described below with reference to the drawings in the embodiment of the present invention, and it is obvious that the described embodiment is only a part of the embodiment of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
FIG. 1 is a schematic flow diagram of a method of one embodiment of the invention. The implementation subject of fig. 1 can be a system for predicting the power generation of a photovoltaic power station.
As shown in fig. 1, the method includes:
and 140, fitting the future illumination intensity into a curve of the illumination intensity changing along with time, and calculating the future power generation amount according to the fitted curve.
The method can predict the generated power and generated energy of the photovoltaic power station within several hours or days in the future and can be maximally endured to one month. In order to facilitate understanding of the present invention, a method for predicting the power generation of a photovoltaic power plant provided by the present invention is further described below.
Specifically, the method for predicting the power generation capacity of the photovoltaic power station comprises the following steps:
1. acquiring the current illumination intensity of the location of the photovoltaic power station by using an illumination intensity collector, acquiring the current power generation power of the photovoltaic power station by using an ammeter, and calculating the ratio of the current power generation power to the current illumination intensity to obtain a unit illumination intensity load value;
2. the method comprises the steps of connecting an API (application programming interface) of a network weather forecast, automatically acquiring illumination parameters, and enabling data to be stable and high in accuracy, wherein in the embodiment, the illumination parameters are cloud cover and visibility, the cloud cover refers to the number of assemblies shielded by all clouds when the sun irradiates, and the visibility refers to the number of assemblies which are blocked by dust particles in the air to irradiate and penetrate when the sun irradiates; in this embodiment, the cloud cover and visibility are in percent form;
calculating the solar radiation amount through radiation parameters of a photovoltaic power station, wherein the radiation parameters comprise: latitude and longitude of the area where the photovoltaic power station is located, solar altitude and time; the solar radiation amount is calculated by the following method:
3. the general relation is that the sunlight is irradiated from the sky, and the illumination intensity of the photovoltaic module irradiated on the photovoltaic power station is obtained after the influence of cloud cover and visibility, namely
Solar radiation amount × [ (1-cloud amount) × cloud amount weight ] × (visibility ×) visibility weight) ═ light intensity (1),
in this embodiment, the solar radiation amount is a change of a total solar radiation amount of an upper atmospheric boundary, the total solar radiation amount refers to a total energy of the sun transmitted outwards in the form of electromagnetic waves, the solar radiation amount refers to a solar energy of the upper atmospheric boundary of the photovoltaic power station at this time, and in a lower atmospheric boundary, the solar radiation amount is attenuated by weather factors such as cloud cover and visibility to obtain an illumination intensity of the photovoltaic power station.
Substituting the illumination parameter and the solar radiation amount of the current time into the general relational expression to obtain a current illumination intensity calculation formula,
current solar radiation amount × [ (1-current cloudiness) × (current cloudiness weight ] × (current visibility × current visibility weight) ═ current illumination intensity (2);
substituting the illumination parameters and the solar radiation amount of the future time into the general relational expression to obtain a future illumination intensity calculation formula,
future solar radiation amount × [ (1-future cloudiness) × (future cloudiness weight ] × (future visibility × future visibility weight) ═ future light intensity (3);
integrating the current illumination intensity calculation formula and the future illumination intensity calculation formula to obtain a final formula of the future illumination intensity,
the future illumination intensity is { future solar radiation amount x [ (1-future cloud amount) x future cloud amount weight ] × (future visibility x future visibility weight) }/{ current solar radiation amount x [ (1-current cloud amount) x current cloud amount weight ] × (current visibility x current visibility weight) } (4), wherein the relation between the future solar radiation amount and the current solar radiation amount is determined by the principle that the total solar radiation amount of the upper air boundary is constant but changes in a regular year;
wherein, the current solar radiation amount of the upper air bound is calculated, the current solar radiation amount is the total solar radiation amount x (the nearest distance of the earth day/the distance of the current earth day) x (the current solar altitude/the maximum solar altitude of the current year),
calculating the future solar radiation amount of the upper air bound, wherein the future solar radiation amount is the total solar radiation amount x (the nearest distance to the earth day/the distance to the earth day in the future) x (the future solar altitude/the maximum solar altitude in the future);
in this embodiment, the solar radiation amount is related to the solar altitude of the area where the photovoltaic power station is located, the larger the solar altitude is, the shorter the path through the atmosphere is, the smaller the attenuation effect of the atmosphere on the solar radiation is, the more the solar radiation amount reaches the ground, the latitude directly affects the size of the solar altitude, the solar altitude is related to the time of the year, the solar altitude at different times is fixed, the solar altitude in one day is different, so the change of the solar radiation amount is related to the time, in calculating the ratio of the above equations (2) and (3), the future solar radiation amount/the current solar radiation amount can be obtained by a calculation formula of the solar radiation amount of the upper bound of the atmosphere, the cloud amount and the visibility can be obtained by the input time, and finally the whole equation (4) can be converted into a formula related to the time;
4. according to different time and illumination parameters, applying influence factor data influencing the power generation power or the power generation capacity to a clustering algorithm, establishing a prediction model of the illumination intensity by using a k-means clustering algorithm according to a final formula of the future illumination intensity, and dividing the prediction model into a plurality of clusters according to the illumination parameters; randomly taking a plurality of future illumination intensities under each cluster as an initial cluster center; future light intensity samples are input and assigned to the nearest cluster center, and the cluster center is recalculated each time a sample is input.
5. Training the prediction model by using a neural network to obtain the current cloud cover weight, the future cloud cover weight, the current visibility weight and the future visibility weight, substituting the weights into the step (4),
6. calculating the product of the predicted illumination intensity and the unit illumination load value to obtain future generated power which is the unit illumination load value x { future solar radiation amount [ (1-future cloud amount) future cloud amount weight ] × (future visibility weight) }/{ current solar radiation amount x [ (1-cloud amount) current cloud amount weight ] × (visibility current visibility weight) } (5);
in the embodiment, the current time point is 9 points, the future time points are 10 points, 11 points and 12 points … …, the future cloud cover and the future visibility of the prediction time points are substituted into the step (5), and a fitting curve with the ordinate as future power generation power and the abscissa as time points is formed by fitting; calculating the area of the fitting curve and the abscissa according to an integral calculation method to serve as predicted power generation amount;
7. acquiring a prediction time point at which power generation amount prediction is to be performed, in the embodiment, to predict power generation amount in three hours in the future, the current time is 9 points, the prediction time point is 12 points, the curve area of a fitting curve between the 9 points and the 12 points is calculated, and the curve area between the 9 points and the 12 points is used as the predicted power generation amount;
8. obtaining a high-temperature influence rate of a photovoltaic module of a photovoltaic power station, wherein the high-temperature influence rate is a percentage of reduction in power generation power of the photovoltaic module when an air temperature is higher by one degree per liter, and in this embodiment, when the temperature is higher by one degree, power generation amount is reduced by 0.44%, an accurate future power generation power is obtained, wherein the accurate future power generation power is increased by 0.44%, and the accurate future power generation power is increased by 0.1-high-temperature influence rate, x (1-year attenuation rate) x unit illuminance load value, and the accurate future solar radiation amount is [ (1-future cloud amount) }/{ future cloud amount weight (future visibility) x (visibility x current weight) };
in this embodiment, if the predicted power generation amount is calculated in units of years, an age-related decay rate, which is a percentage of reduction in power generation power of the photovoltaic module per year due to its own factors, needs to be considered, for example, an average annual decay rate of crystalline silicon in the photovoltaic module is 0.5%, and 0.5% is used as the age-related decay rate, so as to obtain the growth age of the predicted time compared with the current time; accurately predicting generated power, namely, rising temperature x (1-high temperature influence rate) x growth period x (1-period attenuation rate) x unit illuminance load value x { future solar radiation quantity [ (1-future cloud quantity) future cloud quantity weight ] × (future visibility weight) }/{ current solar radiation quantity x [ (1-cloud quantity) current cloud quantity weight ] × (visibility current visibility weight) };
and updating the predicted power generation capacity according to the accurately predicted power generation power, and similarly in the concrete process, and the step 4.
As shown in fig. 2, the system 200 includes:
an information acquisition unit 210 configured to acquire a current illumination intensity of the photovoltaic power station;
a formula setting unit 220 configured to set a general relational expression of the amount of solar radiation, the illumination parameter, and the illumination intensity;
the light intensity calculating unit 230 is configured to calculate the future illumination intensity according to the general relational expression by using the principle that the solar radiation amount is certain but shows the annual regular change along with the solar altitude angle;
and the fitting calculation unit 240 is configured to fit the future illumination intensity into a curve of illumination intensity changing along with time, and calculate the future power generation amount according to the fitted curve.
The same and similar parts in the various embodiments in this specification may be referred to each other. Especially, for the terminal embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant points can be referred to the description in the method embodiment.
In the embodiments provided by the present invention, it should be understood that the disclosed system, system and method can be implemented in other ways. For example, the above-described system embodiments are merely illustrative, and for example, the division of the units is only one logical functional division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, systems or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
Although the present invention has been described in detail by referring to the drawings in connection with the preferred embodiments, the present invention is not limited thereto. Various equivalent modifications or substitutions can be made on the embodiments of the present invention by those skilled in the art without departing from the spirit and scope of the present invention, and these modifications or substitutions are within the scope of the present invention/any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A method for predicting power generation capacity of a photovoltaic power station is characterized by comprising the following steps:
collecting the current illumination intensity of a photovoltaic power station;
setting a general relational expression of the solar radiation quantity, the illumination parameters and the illumination intensity;
calculating the future illumination intensity according to a general relational expression by utilizing the principle that the total solar radiation amount is constant but shows annual regular change along with the solar altitude angle;
and fitting the future illumination intensity into a curve of the illumination intensity changing along with time, and calculating the future power generation amount according to the fitted curve.
2. The method of claim 1, further comprising:
and (3) connecting an API (application programming interface) of a weather forecast website, and automatically acquiring illumination parameters including cloud cover and visibility through the forecast website.
3. The method of claim 2, wherein the general relationship is: solar radiation amount × [ (1-cloud amount) × cloud amount weight ] × (visibility ×) visibility weight) × (light intensity).
4. The method of claim 3, wherein calculating the future illumination intensity according to the general relationship using the principle that the total solar irradiance varies with the solar altitude but with the annual regularity, comprises:
calculating the current solar radiation amount of the upper air bound, wherein the current solar radiation amount is the total solar radiation amount x (the nearest distance to the earth day/the current distance to the earth day) x (the current solar altitude/the maximum solar altitude of the current year);
calculating the future solar radiation amount of the upper air bound, wherein the future solar radiation amount is the total solar radiation amount x (the nearest distance to the earth day/the distance to the earth day in the future) x (the future solar altitude/the maximum solar altitude in the future);
substituting the illumination parameter of the current time and the current solar radiation amount into the general relational expression to obtain a current illumination intensity calculation formula of the atmospheric lower bound,
current solar radiation amount × [ (1-current cloudiness) × (current cloudiness weight ] × (current visibility × current visibility weight) × (current visibility weight) ═ current illumination intensity;
substituting the general relational expression into the illumination parameter of future time and future solar radiation quantity to obtain a future illumination intensity calculation formula of the atmospheric lower bound,
future solar radiation amount × [ (1-future cloudiness) × (future cloudiness weight ] × (future visibility × future visibility weight) ═ future light intensity;
integrating the current illumination intensity calculation formula and the future illumination intensity calculation formula to obtain a final formula of the future illumination intensity,
future light intensity ═ future solar radiation amount × [ (1-future cloud amount) × future cloud amount weight ] × (future visibility × future visibility weight) }/{ current solar radiation amount × [ (1-current cloud amount) × current cloud amount weight ] × (current visibility × current visibility weight) };
and establishing a prediction model of the illumination intensity by using a k-means clustering algorithm according to a final formula of the future illumination intensity.
5. The method according to claim 4, wherein the establishing a prediction model of the illumination intensity by using a k-means clustering algorithm according to the final formula of the future illumination intensity comprises:
dividing the light into a plurality of clusters according to the final formula of the future light intensity and the light parameters;
randomly taking a plurality of future illumination intensities under each cluster as an initial cluster center;
future light intensity samples are input and assigned to the nearest cluster center, and the cluster center is recalculated each time a sample is input.
6. The method of claim 4, further comprising:
and training the prediction model by utilizing a neural network to obtain the current cloud cover weight, the future cloud cover weight, the current visibility weight and the future visibility weight.
7. The method of claim 4, wherein fitting the future illumination intensity to a curve of illumination intensity over time, and calculating the predicted power generation from the fitted curve comprises:
acquiring the current power generation power of a photovoltaic power station, and calculating the ratio of the current power generation power to the current illumination intensity to obtain a unit illumination intensity load value;
calculating the product of the future illumination intensity and the unit illumination load value to obtain the future power generation power which is the unit illumination load value multiplied by the future illumination intensity;
and aiming at the prediction model of the illumination intensity, forming a fitting curve with the ordinate as future generating power and the abscissa as time.
8. The method of claim 7, wherein said calculating a predicted power generation from said fitted curve comprises:
acquiring a prediction time at which power generation amount prediction is to be performed;
and calculating the curve area of a fitting curve between the current time and the predicted time, wherein the curve area is used as the predicted power generation amount.
9. The method of claim 4, further comprising:
acquiring a high-temperature influence rate of a photovoltaic module of a photovoltaic power station, wherein the high-temperature influence rate is the percentage of reduction of the generated power of the photovoltaic module when the air temperature is higher by one degree per liter;
automatically acquiring the current air temperature and the predicted air temperature through a forecast website;
when the predicted air temperature is larger than the current air temperature, calculating a difference value between the predicted air temperature and the current air temperature, wherein the difference value is used as an elevated temperature;
updating the future generated power according to the high-temperature influence rate and the rising temperature to obtain the accurate future generated power which is the rising temperature x (1-high-temperature influence rate) x the future generated power;
and updating the predicted generating capacity according to the accurate future generating power.
10. A system for predicting power generation from a photovoltaic power plant, comprising:
the information acquisition unit is configured for acquiring the current illumination intensity of the photovoltaic power station;
the formula setting unit is used for setting a general relational expression of the solar radiation quantity, the illumination parameters and the illumination intensity;
the light intensity calculating unit is configured for calculating the future illumination intensity according to the general relational expression by utilizing the principle that the solar radiation quantity is certain but shows annual regular change along with the solar altitude angle;
and the fitting calculation unit is configured to fit the future illumination intensity into a curve of the illumination intensity changing along with time, and calculate the future power generation amount according to the fitting curve.
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