CN113255985B - Method and system for predicting generating capacity of photovoltaic power station - Google Patents
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Abstract
The invention provides a method and a system for predicting the power generation capacity of a photovoltaic power station, comprising the following steps: collecting the current illumination intensity of a photovoltaic power station; setting a general relation of solar radiation quantity, illumination parameters and illumination intensity; calculating future illumination intensity according to a general relation by utilizing the characteristic that the total solar radiation quantity is certain but basically changes with the solar altitude in a regular manner; fitting the future illumination intensity into a curve of illumination intensity changing along with time, and calculating the future power generation amount according to the fitted curve. According to the principle that the total solar radiation is certain but basically changes with the solar altitude, the invention simplifies the illumination intensity prediction method and obtains a reasonable power generation amount prediction method.
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 popularization of new energy in China, the popularization rate and development potential of photovoltaic and wind power are fastest, photovoltaic power generation is usually used as standby energy to be overlapped on thermal power generation, if the photovoltaic power generation capacity is too high, a great burden is caused on a power grid, potential safety hazards are formed, and the waste of the power generation capacity is caused, so that the prediction of the power generation power and the power generation capacity of a power station in actual work is also significant. In the power generation process, the photovoltaic power generation is greatly influenced by illumination, so that the photovoltaic power generation is generated by influencing the generated energy by illumination intensity, the generated energy is predicted by the traditional illuminance value acquisition method, the total radiation amount of sunlight is required to be considered, the calculation is quite troublesome, and the error is larger; and the weather data on the network is collected, the server sends back a response by sending a request to the server, and the weather data is extracted by using a get command after processing, so that the request program needs to be rewritten again once the website is changed and upgraded, and the stability is poor.
Disclosure of Invention
The invention provides a method and a system for predicting the power generation capacity of a photovoltaic power station to solve the technical problems.
In a first aspect, the present invention provides a method of predicting the power generation of a photovoltaic power plant, comprising:
collecting the current illumination intensity of a photovoltaic power station;
setting a general relation of solar radiation quantity, illumination parameters and illumination intensity;
calculating future illumination intensity according to a general relation by utilizing the principle that the solar radiation quantity is certain but changes regularly with the sun altitude;
fitting the future illumination intensity into a curve of 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) docking with an API interface of a weather forecast website, and automatically acquiring illumination parameters through the forecast website, wherein the illumination parameters comprise cloud cover and visibility.
Further, the general relation is: solar radiation amount x [ (1-cloud amount) ×cloud amount weight ] × (visibility×visibility weight) =illumination intensity.
Further, the calculating the future illumination intensity by using the general relation includes:
calculating a current solar radiation amount of the upper atmosphere, wherein the current solar radiation amount=total solar radiation amount x (ground day nearest distance/current ground day distance) × (current solar altitude angle/current annual maximum solar altitude angle);
calculating a future solar radiation amount of the atmosphere upper bound, future solar radiation amount=total solar radiation amount× (ground day closest distance/future ground day distance) × (future solar altitude angle/future annual maximum solar altitude angle);
substituting the illumination parameter and the current solar radiation quantity of the current time into the general relation to obtain a current illumination intensity calculation formula of the atmosphere lower boundary,
current solar radiation amount x [ (1-current cloud amount) ×current cloud amount weight ] × (current visibility×current visibility weight) =current illumination intensity;
substituting the illumination parameter and the future solar radiation quantity of the future time into the general relation to obtain a future illumination intensity calculation formula of the atmosphere lower boundary,
future solar radiation amount x [ (1-future cloud amount) ×future cloud amount weight ] × (future visibility×future visibility weight) =future illumination intensity;
integrating the current illumination intensity calculation formula and the future illumination intensity calculation formula to obtain the final illumination intensity of the future,
future illumination 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 utilizing a k-means clustering algorithm according to the final type of the future illumination intensity.
Further, the establishing a prediction model of the illumination intensity by using a k-means clustering algorithm according to the final type of the future illumination intensity comprises the following steps:
dividing the light into a plurality of clusters according to illumination parameters according to the final type of future illumination intensity;
randomly taking a plurality of future illumination intensities under each cluster as an initial cluster center;
future illumination intensity samples are input and assigned to the nearest cluster center, and the cluster center is recalculated every time a sample is input.
Further, the method further comprises:
and training the prediction model by using a neural network to obtain the current cloud amount weight, the future cloud amount weight, the current visibility weight and the future visibility weight.
Further, the fitting the future illumination intensity to a curve of illumination intensity changing with time, calculating a predicted power generation amount according to the fitted curve, including:
collecting 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 load value of unit illumination intensity;
calculating the product of the future illumination intensity and the unit illumination intensity load value to obtain the future power generation=unit illumination intensity load value multiplied by the future illumination intensity;
and forming a fitting curve with the ordinate as future power generation and the abscissa as time aiming at the prediction model of the illumination intensity.
Further, the calculating the predicted power generation amount according to the fitting curve includes:
acquiring prediction time for predicting the generated energy;
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:
obtaining the high-temperature influence rate of a photovoltaic module of a photovoltaic power station, wherein the high-temperature influence rate is the reduction percentage of the power generation power of the photovoltaic module when the air temperature rises by one degree;
automatically acquiring the current air temperature and the predicted air temperature through a forecast website;
when the predicted air temperature is greater than the current air temperature, calculating a difference between the predicted air temperature and the current air temperature, wherein the difference is used as the rising temperature;
updating future power generation according to the high temperature influence rate and the elevated temperature to obtain accurate future power generation=elevated temperature× (1-high temperature influence rate) ×future power generation;
and updating the predicted power generation amount according to the accurate future power generation power.
In a second aspect, the present invention provides a system for predicting the power generation of a photovoltaic power plant, comprising:
the information acquisition unit is configured to acquire the current illumination intensity of the photovoltaic power station;
the formula setting unit is configured to set a general relation of solar radiation quantity, illumination parameters and illumination intensity;
the light intensity calculating unit is configured to calculate future illumination intensity according to a general relation by utilizing the principle that the solar radiation amount is fixed but changes regularly with the solar altitude;
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 fitted curve.
The invention has the advantages that,
according to the method and the system for predicting the power generation capacity of the photovoltaic power station, provided by the invention, according to the principle that the total solar radiation is certain but regularly changes along with time, the illumination intensity prediction method is simplified; directly interfacing with an API of the network weather forecast, ensuring accuracy and data stability; and the influence of cloud cover and visibility is considered, so that a reasonable power generation amount prediction method is obtained, the influence of temperature factors and age decay factors on the power generation 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.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required to be used in the description of the embodiments or the prior art will be briefly described below, and it will be obvious to those skilled in the art that other drawings can be obtained from these drawings without inventive effort.
FIG. 1 is a schematic flow chart 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 the technical solution of the present invention better understood by those skilled in the art, the technical solution of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
FIG. 1 is a schematic flow chart of a method of one embodiment of the invention. The execution subject of fig. 1 may 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 illumination intensity changing along with time, and calculating the future power generation amount according to the fitted curve.
The method can predict the power generation power and the power generation quantity of the photovoltaic power station which are durable to one month at maximum in the future of a plurality of hours or days. In order to facilitate understanding of the present invention, a method for predicting the power generation capacity of a photovoltaic power station provided by the present invention is further described below.
Specifically, the method for predicting the power generation amount of the photovoltaic power station comprises the following steps:
1. collecting current illumination intensity of a place where the photovoltaic power station is located by using an illumination intensity collector, collecting 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 load value of unit illumination intensity;
2. the API interface of the network weather forecast is docked, illumination parameters are automatically obtained, the data are stable and high in accuracy, in the embodiment, the illumination parameters are cloud quantity and visibility, the cloud quantity is the total number shielded by all cloud during solar radiation, and the visibility is the total number which is shielded from passing through by dust particles in the air during solar radiation; in this embodiment, the cloud cover and visibility are in percent form;
calculating the solar radiation amount through radiation parameters of the photovoltaic power station, wherein the radiation parameters comprise: longitude and latitude, solar altitude angle and time of the region where the photovoltaic power station is located; the solar radiation amount is calculated as follows:
3. the general relation means that the sunlight irradiates from the sky, and the illumination intensity of the photovoltaic module irradiated on the photovoltaic power station is obtained after the influence of cloud quantity and visibility, namely
Solar radiation amount x [ (1-cloud amount) ×cloud amount weight ] × (visibility x visibility weight) =illumination intensity (1),
in this embodiment, the solar radiation amount is the change of the total solar radiation amount in the upper atmosphere, the total solar radiation amount refers to the total energy transmitted by the sun in the form of electromagnetic waves, the solar radiation amount refers to the solar energy in the upper atmosphere of the photovoltaic power station at this time, and the solar radiation amount is attenuated by weather factors such as cloud amount and visibility in the lower atmosphere to obtain the illumination intensity of the photovoltaic power station.
Substituting the illumination parameter and the solar radiation quantity of the current time into the general relation to obtain a current illumination intensity calculation formula,
current solar radiation amount x [ (1-current cloud amount) ×current cloud amount weight ] × (current visibility×current visibility weight) =current illumination intensity (2);
substituting the illumination parameters and the solar radiation quantity of the future time into the general relation to obtain a future illumination intensity calculation formula,
future solar radiation amount x [ (1-future cloud amount) ×future cloud amount weight ] × (future visibility×future visibility weight) =future illumination intensity (3);
integrating the current illumination intensity calculation formula and the future illumination intensity calculation formula to obtain the final illumination intensity of the future,
future illumination 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) } (4), wherein the relationship of the future solar radiation amount and the current solar radiation amount is determined by the principle that the total solar radiation amount in the atmosphere is unchanged but changes regularly in the years;
wherein, the current solar radiation amount of the atmosphere upper limit is calculated, the current solar radiation amount = total solar radiation amount x (ground day nearest distance/current ground day distance) × (current solar altitude angle/current annual maximum solar altitude angle),
calculating a future solar radiation amount of the atmosphere upper bound, future solar radiation amount=total solar radiation amount× (ground day closest distance/future ground day distance) × (future solar altitude angle/future annual maximum solar altitude angle);
in this embodiment, the solar radiation amount is related to the solar altitude angle of the region where the photovoltaic power station is located, the larger the solar altitude angle is, the shorter the path passing through the atmosphere is, the smaller the attenuation effect of the atmosphere on the solar radiation is, the more the solar radiation amount reaching the ground is, the altitude directly affects the size of the solar altitude angle, the solar altitude angle is related to the time of the present year, the solar altitude angles at different times are certain, the solar altitude angles in one day are different, so the change of the solar radiation amount is related to the time, so in the ratio of the equation (2) and the equation (3) is calculated, the future solar radiation amount/the current solar radiation amount can be obtained by the calculation formula of the solar radiation amount at the upper boundary 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 the formula related to the time;
4. according to different time and illumination parameters, applying influence factor data influencing the power generation or the power generation to a clustering algorithm, establishing a prediction model of illumination intensity by using a k-means clustering algorithm according to the final type of 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 illumination intensity samples are input and assigned to the nearest cluster center, and the cluster center is recalculated every time a sample is input.
5. Training a prediction model by utilizing a neural network to obtain a current cloud amount weight, a future cloud amount weight, a current visibility weight and a future visibility weight, substituting the current cloud amount weight, the future cloud amount weight, the current visibility weight and the future visibility weight into (4),
6. calculating the product of the predicted illumination intensity and the unit illumination intensity load value to obtain future generation power = unit illumination intensity load value x { future solar radiation amount [ (1-future cloud amount): future cloud amount weight ] × (future visibility x future visibility weight) }/{ current solar radiation amount× [ (1-cloud amount): current cloud amount weight ] × (visibility x current visibility weight) } (5);
the future cloud amount and the future visibility are cloud amounts and visibility of a plurality of future prediction time points, in the embodiment, the current time point is 9 points, the plurality of future prediction time points are 10 points, 11 points and 12 points … …, the future cloud amounts and the future visibility of the plurality of prediction time points are substituted into (5), and a fitting curve with an ordinate being the future power generation and an abscissa being the time point is formed by fitting; calculating the area of the fitting curve and the abscissa as the predicted power generation amount according to an integral calculation method;
7. acquiring a prediction time point for predicting the power generation amount, wherein in the embodiment, the current time is 9 points, the prediction time point is 12 points, the curve area of a fitting curve between 9 points and 12 points is calculated, and the curve area between 9 points and 12 points is used as the predicted power generation amount;
8. obtaining a high-temperature influence rate of a photovoltaic power station photovoltaic module, wherein the high-temperature influence rate is a reduction percentage of the power generation of the photovoltaic module when the temperature is increased by one degree, in the embodiment, the power generation is reduced by 0.44% when the temperature is increased by one degree, and the accurate future power generation=the increased temperature× (1-high-temperature influence rate) × (1-annual attenuation rate) ×unit illuminance load value× { future solar radiation amount [ (1-future cloud amount) ×future cloud amount weight ] × (future visibility) x (future visibility weight) }/{ current solar radiation amount× [ (1-cloud amount) × (current cloud amount weight) };
in this embodiment, to calculate the predicted power generation amount in units of years, it is necessary to consider an annual attenuation rate, where the annual attenuation rate is a percentage of decrease in power generation of the photovoltaic module due to its own factors, for example, an annual average attenuation rate of crystalline silicon in the photovoltaic module is 0.5%, and 0.5% is taken as an annual attenuation rate, so as to obtain an increase period of the predicted time compared with the current time; accurate prediction of generated power = elevated temperature x (1-high temperature influence rate) x growth period x (1-period decay rate) x unit illuminance load value x { 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-cloud amount) × current cloud amount weight ] × (visibility x current visibility weight) };
and 4, updating the predicted generated energy according to the accurate predicted generated power, and carrying out the same process as 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 relation of the solar radiation amount, the illumination parameter, and the illumination intensity;
the light intensity calculating unit 230 is configured to calculate future illumination intensity according to a general relation by using a principle that the solar radiation amount is constant but changes regularly with the solar altitude;
the fitting calculation unit 240 is configured to fit the future illumination intensity to a curve of the illumination intensity over time, and calculate the future power generation amount based on the fitted curve.
The same or similar parts between the various embodiments in this specification are referred to each other. In particular, for the terminal embodiment, since it is substantially similar to the method embodiment, the description is relatively simple, and reference should be made to the description in the method embodiment for relevant points.
In the several embodiments provided by the present invention, it should be understood that the disclosed systems, and methods may be implemented in other ways. For example, the system embodiments described above are merely illustrative, e.g., the division of the elements is merely a logical functional division, and there may be additional divisions when actually implemented, e.g., multiple elements or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some interface, system or unit indirect coupling or communication connection, which may be in electrical, mechanical or other form.
The units described as separate units may or may not be physically separate, and units shown 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 may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.
Although the present invention has been described in detail by way of preferred embodiments with reference to the accompanying drawings, the present invention is not limited thereto. Various equivalent modifications and substitutions may be made in the embodiments of the present invention by those skilled in the art without departing from the spirit and scope of the present invention, and it is intended that all such modifications and substitutions be within the scope of the present invention/be within the scope of the present invention as defined by the appended claims. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (6)
1. A method of predicting power generation in a photovoltaic power plant, comprising:
collecting the current illumination intensity of a photovoltaic power station;
setting a general relation of solar radiation quantity, illumination parameters and illumination intensity;
calculating future illumination intensity according to a general relation by utilizing the principle that the total solar radiation quantity is certain but changes regularly with the sun altitude;
fitting the future illumination intensity into a curve of illumination intensity changing along with time, and calculating the future power generation amount according to the fitted curve;
the method further comprises the steps of:
the method comprises the steps of docking an API interface of a weather forecast website, and automatically obtaining illumination parameters through the forecast website, wherein the illumination parameters comprise cloud cover and visibility;
the general relation is: solar radiation amount x [ (1-cloud amount) ×cloud amount weight ] × (visibility×visibility weight) =illumination intensity;
the method for calculating future illumination intensity according to the principle that the total solar radiation amount is certain but changes regularly with the sun altitude angle comprises the following steps:
calculating a current solar radiation amount of the upper atmosphere, wherein the current solar radiation amount=total solar radiation amount x (ground day nearest distance/current ground day distance) × (current solar altitude angle/current annual maximum solar altitude angle);
calculating a future solar radiation amount of the atmosphere upper bound, future solar radiation amount=total solar radiation amount× (ground day closest distance/future ground day distance) × (future solar altitude angle/future annual maximum solar altitude angle);
substituting the illumination parameter and the current solar radiation quantity of the current time into the general relation to obtain a current illumination intensity calculation formula of the atmosphere lower boundary,
current solar radiation amount x [ (1-current cloud amount) ×current cloud amount weight ] × (current visibility×current visibility weight) =current illumination intensity;
substituting the illumination parameter and the future solar radiation quantity of the future time into the general relation to obtain a future illumination intensity calculation formula of the atmosphere lower boundary,
future solar radiation amount x [ (1-future cloud amount) ×future cloud amount weight ] × (future visibility×future visibility weight) =future illumination intensity;
integrating the current illumination intensity calculation formula and the future illumination intensity calculation formula to obtain the final illumination intensity of the future,
future illumination 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) };
establishing a prediction model of the illumination intensity by utilizing a k-means clustering algorithm according to the final type of the future illumination intensity;
further comprises:
obtaining the high-temperature influence rate of a photovoltaic module of a photovoltaic power station, wherein the high-temperature influence rate is the reduction percentage of the power generation power of the photovoltaic module when the air temperature rises by one degree;
automatically acquiring the current air temperature and the predicted air temperature through a forecast website;
when the predicted air temperature is greater than the current air temperature, calculating a difference between the predicted air temperature and the current air temperature, wherein the difference is used as the rising temperature;
updating future power generation according to the high temperature influence rate and the elevated temperature to obtain accurate future power generation=elevated temperature× (1-high temperature influence rate) ×future power generation;
and updating the predicted power generation amount according to the accurate future power generation power.
2. The method of claim 1, wherein the establishing a predictive model of the illumination intensity using a k-means clustering algorithm based on the final future illumination intensity comprises:
dividing the light into a plurality of clusters according to illumination parameters according to the final type of future illumination intensity;
randomly taking a plurality of future illumination intensities under each cluster as an initial cluster center;
future illumination intensity samples are input and assigned to the nearest cluster center, and the cluster center is recalculated every time a sample is input.
3. The method according to claim 1, wherein the method further comprises:
and training the prediction model by using a neural network to obtain the current cloud amount weight, the future cloud amount weight, the current visibility weight and the future visibility weight.
4. The method of claim 1, wherein fitting the future illumination intensity to a curve of illumination intensity over time, calculating a predicted power generation amount from the fitted curve, comprises:
collecting 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 load value of unit illumination intensity;
calculating the product of the future illumination intensity and the unit illumination intensity load value to obtain the future power generation=unit illumination intensity load value multiplied by the future illumination intensity;
and forming a fitting curve with the ordinate as future power generation and the abscissa as time aiming at the prediction model of the illumination intensity.
5. The method of claim 4, wherein said calculating a predicted power generation amount from said fitted curve comprises:
acquiring prediction time for predicting the generated energy;
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.
6. A system for predicting power generation in a photovoltaic power plant, the system performing a method for predicting power generation in a photovoltaic power plant as claimed in any one of claims 1 to 5, the system comprising:
the information acquisition unit is configured to acquire the current illumination intensity of the photovoltaic power station;
the formula setting unit is configured to set a general relation of solar radiation quantity, illumination parameters and illumination intensity;
the light intensity calculating unit is configured to calculate future illumination intensity according to a general relation by utilizing the principle that the solar radiation amount is fixed but changes regularly with the solar altitude;
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 fitted curve.
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