CN116742622B

CN116742622B - Photovoltaic power generation-based power generation amount prediction method and system

Info

Publication number: CN116742622B
Application number: CN202310995182.XA
Authority: CN
Inventors: 陈丹; 王媛媛; 朱宁坦; 胡玉冰
Original assignee: Shandong Polytechnic College
Current assignee: Shandong Polytechnic College
Priority date: 2023-08-09
Filing date: 2023-08-09
Publication date: 2023-11-03
Anticipated expiration: 2043-08-09
Also published as: CN116742622A

Abstract

The invention relates to the technical field of photovoltaic power generation, in particular to a method and a system for predicting the generated energy based on photovoltaic power generation. The method comprises the steps of acquiring meteorological data of a photovoltaic power plant in future preset time; acquiring a plurality of historical meteorological data of a photovoltaic power plant, wherein the historical meteorological data comprise historical sunlight time, historical wind speed, historical evaporation capacity and historical power generation capacity in preset time, and establishing a historical meteorological data model according to the plurality of historical meteorological data; and inquiring whether the historical sunlight time, the historical wind speed and the historical evaporation amount in the data set corresponding to the meteorological data exist or not according to the meteorological data and the historical meteorological data model, and determining the generating capacity of the photovoltaic power plant in the future preset time according to the inquiring result. According to the method, the historical meteorological data model is established, comparison query is carried out with the meteorological data collected in real time, photovoltaic power generation can be rapidly predicted in a short time according to the query result, and the prediction efficiency is improved.

Description

Photovoltaic power generation-based power generation amount prediction method and system

Technical Field

The invention relates to the technical field of photovoltaic power generation, in particular to a method and a system for predicting the generated energy based on photovoltaic power generation.

Background

The photovoltaic power generation output is affected by solar radiation periodic variation, atmospheric temperature, precipitation, cloud cover, humidity and other meteorological factors, and has obvious daily and seasonal variation, discontinuity and uncertainty. However, in the prior art, the prediction of the photovoltaic power generation is based on the obtained real-time meteorological data in a short time, so that the fast prediction cannot be realized, and in order to ensure the accuracy of the prediction, a large amount of relevant meteorological data needs to be adopted before each calculation, a certain time is consumed, and the fast and efficient prediction is not facilitated, so how to provide the power generation prediction method and system based on the photovoltaic power generation is a technical problem which needs to be solved by a person skilled in the art.

Disclosure of Invention

The invention aims to provide a generating capacity prediction method and a generating capacity prediction system based on photovoltaic power generation.

In order to achieve the above object, the present invention provides the following technical solutions:

A generating capacity prediction method based on photovoltaic power generation comprises the following steps:

acquiring meteorological data of a photovoltaic power plant in future preset time, wherein the meteorological data comprise sunlight time t, wind speed V and evaporation capacity R;

acquiring a plurality of historical meteorological data of the photovoltaic power plant, wherein the historical meteorological data comprise historical sunlight time, historical wind speed, historical evaporation capacity and historical power generation capacity in preset time, and establishing a historical meteorological data model according to the plurality of historical meteorological data; wherein,

the historical meteorological data model comprises a plurality of data sets of the historical power generation amount corresponding to the historical sunlight time, the historical wind speed and the historical evaporation amount;

inquiring whether the historical sunlight time, the historical wind speed and the historical evaporation amount in the data set corresponding to the meteorological data exist or not according to the meteorological data and the historical meteorological data model, and determining the generating capacity of the photovoltaic power plant in the future preset time according to an inquiring result; wherein,

when the historical sunlight time, the historical wind speed and the historical evaporation amount in the data set corresponding to the meteorological data exist, correspondingly taking the historical power generation amount as the power generation amount of the photovoltaic power plant in the future preset time;

When the historical sunlight time, the historical wind speed and the historical evaporation amount in the data set corresponding to the meteorological data do not exist, calculating and determining the generated energy of the photovoltaic power plant in the future preset time according to the meteorological data, establishing a set of the calculated generated energy and the meteorological data, and inputting the set into the historical meteorological data model.

In some embodiments of the present application, a preset solar time matrix T0 and a preset predicted power generation amount matrix a are preset, for which a (A1, A2, A3, A4) is set, wherein A1 is a first preset predicted power generation amount, A2 is a second preset predicted power generation amount, A3 is a third preset predicted power generation amount, and A4 is a fourth preset predicted power generation amount;

setting T0 (T01, T02, T03 and T04) for the preset sunshine time matrix T0, wherein T01 is a first preset sunshine time, T02 is a second preset sunshine time, T03 is a third preset sunshine time, T04 is a fourth preset sunshine time, and T01 is less than T02 and less than T03 is less than T04;

when the historical sunlight time, the historical wind speed and the historical evaporation amount in the data set corresponding to the meteorological data do not exist, correspondingly predicting the generated energy as the generated energy of the photovoltaic power plant in the future preset time according to the relation between T and the preset sunlight time matrix T0;

When T is smaller than T01, selecting the first preset predicted power generation amount A1 as the power generation amount of the photovoltaic power plant in the future preset time;

when T01 is less than or equal to T < T02, selecting the second preset predicted power generation amount A2 as the power generation amount of the photovoltaic power plant in the future preset time;

when T02 is less than or equal to T03, selecting the third preset predicted power generation amount A3 as the power generation amount of the photovoltaic power plant in the future preset time;

and when T03 is less than or equal to T04, selecting the fourth preset predicted power generation amount A4 as the power generation amount of the photovoltaic power plant in the future preset time.

In some embodiments of the present application, a preset wind speed matrix N0 and a preset predicted power generation amount correction coefficient matrix B are preset, for which B (B1, B2, B3, B4) is set, wherein B1 is a first preset predicted power generation amount correction coefficient, B2 is a second preset predicted power generation amount correction coefficient, B3 is a third preset predicted power generation amount correction coefficient, B4 is a fourth preset predicted power generation amount correction coefficient, and 0.8 < B1 < B2 < B3 < B4 < 1;

setting N0 (N01, N02, N03, N04) for the preset wind speed matrix N0, wherein N01 is a first preset wind speed, N02 is a second preset wind speed, N03 is a third preset wind speed, N04 is a fourth preset wind speed, and N01 is less than N02 and less than N03 is less than N04;

When the historical sunlight time, the historical wind speed and the historical evaporation amount in the data set corresponding to the meteorological data do not exist, a corresponding predicted generating capacity correction coefficient is selected according to the relation between V and the preset wind speed matrix N0 so as to correct each predicted generating capacity;

when V is smaller than N01, selecting the fourth preset predicted power generation amount correction coefficient B4 to correct the first preset predicted power generation amount A1, wherein the corrected predicted power generation amount is A1 x B4;

when N01 is less than or equal to V and less than N02, selecting the third preset predicted generating capacity correction coefficient B3 to correct the second preset generating capacity A2, wherein the corrected predicted generating capacity is A2 x B3;

when N02 is less than or equal to V and less than N03, selecting the second preset predicted generating capacity correction coefficient B2 to correct the third preset predicted generating capacity A3, wherein the corrected predicted generating capacity is A3 x B2;

when N03 is less than or equal to V and less than N04, the first preset predicted power generation amount correction coefficient B1 is selected to correct the fourth preset power generation amount A4, and the corrected predicted power generation amount is A4 x B1.

In some embodiments of the present application, a preset evaporation capacity matrix W0 and a preset predicted power generation capacity secondary correction coefficient matrix C are preset, for which C (C1, C2, C3, C4) is set, wherein C1 is a first preset predicted power generation capacity secondary correction coefficient, C2 is a second preset predicted power generation capacity secondary correction coefficient, C3 is a third preset predicted power generation capacity secondary correction coefficient, C4 is a fourth preset predicted power generation capacity secondary correction coefficient, and 1 < C2 < C3 < C4 < 1.2;

Setting W0 (W01, W02, W03, W04) for the preset evaporation capacity matrix W0, wherein W01 is a first preset evaporation capacity, W02 is a second preset evaporation capacity, W03 is a third preset evaporation capacity, W04 is a fourth preset evaporation capacity, and W01 is less than W02 and less than W03 is less than W04;

when the historical sunlight time, the historical wind speed and the historical evaporation capacity in the data set corresponding to the meteorological data do not exist, selecting a secondary correction coefficient of the corresponding predicted power generation amount according to the relation between R and the preset evaporation capacity matrix W0 so as to secondarily correct each predicted power generation amount after correction;

when R is smaller than W01, selecting a second correction coefficient C1 of the first preset predicted power generation amount to carry out second correction on the corrected first preset power generation amount A1, wherein the predicted power generation amount after the second correction is A1B 4C 1;

when W01 is less than or equal to R < W02, selecting a second preset predicted power generation amount secondary correction coefficient C2 to carry out secondary correction on the corrected second preset power generation amount A2, wherein the predicted power generation amount after the secondary correction is A2 x B3 x C2;

when W02 is less than or equal to R < W03, selecting a second correction coefficient C3 of the third preset predicted generated energy to carry out second correction on the corrected third preset predicted generated energy A3, wherein the predicted generated energy after the second correction is A3B 2C 3;

When W03 is less than or equal to R < W04, selecting a second correction coefficient C4 of the fourth preset predicted power generation amount to carry out second correction on the corrected fourth preset power generation amount A4, wherein the predicted power generation amount after the second correction is A4B 1C 4.

In some embodiments of the application, when there is the historical solar time, the historical wind speed, and the historical evaporation amount in the data set corresponding to the meteorological data, further comprising:

determining the quantity L of the data sets corresponding to the historical sunlight time, the historical wind speed and the historical evaporation quantity corresponding to the meteorological data, calculating the average value i of the historical power generation quantities in a plurality of data sets corresponding to the meteorological data when L is more than or equal to 2, determining the difference U between each historical power generation quantity and the average value i, determining the final predicted power generation quantity according to the average value i and the difference U, and taking the final predicted power generation quantity as the power generation quantity of the photovoltaic power plant in the future preset time; wherein,

when the difference U between each historical generating capacity and the average value i is 0, determining the average value i as the final predicted generating capacity and using the average value i as the generating capacity of the photovoltaic power plant in the future preset time;

When the difference U between the historical generating capacity and the average value i is 1/2 of the number of positive numbers and is larger than the number L of the data sets, multiplying the average value i by a first preset coefficient g1, determining i x g1 as the final predicted generating capacity, and taking the final predicted generating capacity as the generating capacity of the photovoltaic power plant in the future preset time;

when the difference U between the historical generating capacity and the average value i is positive, and the number of the difference U is equal to 1/2 of the number L of the data sets, multiplying the average value i by a second preset coefficient g2, determining i x g2 as the final predicted generating capacity, and taking the final predicted generating capacity as the generating capacity of the photovoltaic power plant in the future preset time;

when the difference U between the historical generating capacity and the average value i is 1/2 of the number of positive numbers and is smaller than the number L of the data sets, multiplying the average value i by a third preset coefficient g3, determining i x g3 as the final predicted generating capacity, and taking the final predicted generating capacity as the generating capacity of the photovoltaic power plant in the future preset time; and 1 > g2 > g3 > 0.9.

In order to achieve the above object, the present invention further provides a power generation amount prediction system based on photovoltaic power generation, which is applied to the power generation amount prediction method based on photovoltaic power generation, and includes:

The acquisition module is used for acquiring weather data of the photovoltaic power plant in future preset time, wherein the weather data comprise sunlight time t, wind speed V and evaporation capacity R;

the processing module is used for acquiring a plurality of historical meteorological data of the photovoltaic power plant, wherein the historical meteorological data comprise historical sunlight time, historical wind speed, historical evaporation capacity and historical power generation capacity in preset time, and a historical meteorological data model is built according to the plurality of historical meteorological data; wherein,

the prediction module is used for inquiring whether the historical sunlight time, the historical wind speed and the historical evaporation amount in the data set corresponding to the meteorological data exist or not according to the meteorological data and the historical meteorological data model, and determining the generating capacity of the photovoltaic power plant in the future preset time according to an inquiring result; wherein,

In some embodiments of the present application, a preset solar time matrix T0 and a preset predicted power generation amount matrix a are preset in the prediction module, and for the preset predicted power generation amount matrix a, a (A1, A2, A3, A4) is set, where A1 is a first preset predicted power generation amount, A2 is a second preset predicted power generation amount, A3 is a third preset predicted power generation amount, and A4 is a fourth preset predicted power generation amount;

the prediction module is further used for selecting a corresponding predicted power generation amount as the power generation amount of the photovoltaic power plant in the future preset time according to the relation between T and the preset sunlight time matrix T0 when the historical sunlight time, the historical wind speed and the historical evaporation amount in the data set corresponding to the meteorological data do not exist;

In some embodiments of the present application, a preset wind speed matrix N0 and a preset predicted power generation amount correction coefficient matrix B are preset in the prediction module, for the preset predicted power generation amount correction coefficient matrix B, B (B1, B2, B3, B4) is set, wherein B1 is a first preset predicted power generation amount correction coefficient, B2 is a second preset predicted power generation amount correction coefficient, B3 is a third preset predicted power generation amount correction coefficient, B4 is a fourth preset predicted power generation amount correction coefficient, and B1 is more than 0.8 and less than B2 and less than B3 and less than B4 and less than 1;

The prediction module is further used for selecting a corresponding predicted generating capacity correction coefficient according to the relation between V and the preset wind speed matrix N0 to correct each predicted generating capacity when the historical sunlight time, the historical wind speed and the historical evaporation capacity in the data set corresponding to the meteorological data do not exist;

In some embodiments of the present application, a preset evaporation capacity matrix W0 and a preset predicted power generation capacity secondary correction coefficient matrix C are preset in the prediction module, and C (C1, C2, C3, C4) is set for the preset predicted power generation capacity secondary correction coefficient matrix C, where C1 is a first preset predicted power generation capacity secondary correction coefficient, C2 is a second preset predicted power generation capacity secondary correction coefficient, C3 is a third preset predicted power generation capacity secondary correction coefficient, C4 is a fourth preset predicted power generation capacity secondary correction coefficient, and 1 < C2 < C3 < C4 < 1.2;

the prediction module is further used for selecting a secondary correction coefficient of the corresponding predicted power generation amount according to the relation between R and the preset evaporation amount matrix W0 to secondarily correct each predicted power generation amount after correction when the historical sunlight time, the historical wind speed and the historical evaporation amount in the data set corresponding to the meteorological data do not exist;

In some embodiments of the present application, the prediction module is further configured to determine, when there are the historical solar time, the historical wind speed, and the historical evaporation amount in the data set corresponding to the meteorological data, the number L of the data sets corresponding to the historical solar time, the historical wind speed, and the historical evaporation amount corresponding to the meteorological data, calculate, when L is equal to or greater than 2, an average value i of the historical power generation amounts in the plurality of data sets corresponding to the meteorological data, and determine a difference value U between each of the historical power generation amounts and the average value i, determine a final predicted power generation amount according to the average value i and the difference value U, and use the final predicted power generation amount as a power generation amount of the photovoltaic power plant in a future preset time; wherein,

The invention provides a method and a system for predicting the generated energy based on photovoltaic power generation, which have the beneficial effects that compared with the prior art:

According to the application, meteorological data in future time is collected, solar time, wind speed and evaporation amount of the meteorological data are compared with a preset historical meteorological data model, when parameters consistent with comparison results exist, the power generation amount can be rapidly predicted, when the parameters are not present, the power generation amount is rapidly predicted according to the core influence parameters which most influence the photovoltaic power generation, the mode that a large amount of data are required to be collected for function calculation in the traditional mode is changed, thus the photovoltaic power generation prediction is realized more rapidly and accurately, the power dispatching condition is conveniently and timely adjusted by a power system, and the running stability of a power grid is maintained.

Drawings

FIG. 1 is a flow chart of a method for predicting power generation based on photovoltaic power generation in an embodiment of the present application;

fig. 2 is a functional block diagram of a photovoltaic power generation-based power generation amount prediction system in an embodiment of the present application.

Detailed Description

The following describes in further detail the embodiments of the present application with reference to the drawings and examples. The following examples are illustrative of the application and are not intended to limit the scope of the application.

In the description of the present application, it should be understood that the terms "center," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," and the like indicate orientations or positional relationships based on the orientation or positional relationships shown in the drawings, merely to facilitate describing the present application and simplify the description, and do not indicate or imply that the devices or elements referred to must have a specific orientation, be configured and operated in a specific orientation, and thus should not be construed as limiting the present application.

The terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more such feature. In the description of the present application, unless otherwise indicated, the meaning of "a plurality" is two or more.

In the description of the present application, it should be noted that, unless explicitly specified and limited otherwise, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be either fixedly connected, detachably connected, or integrally connected, for example; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be the communication between the inner sides of the two elements. The specific meaning of the above terms in the present application will be understood in specific cases by those of ordinary skill in the art.

In the prior art, the prediction of the photovoltaic power generation amount is based on the acquired real-time meteorological data in a short time, so that the fast prediction cannot be realized, and in order to ensure the accuracy of the prediction, a large amount of relevant meteorological data is required to be adopted before each calculation, so that a certain time is consumed, and the efficient prediction is not facilitated.

According to the invention, gray correlation and stepwise regression analysis of meteorological factors and photovoltaic power generation are carried out according to the power generation data and contemporaneous meteorological observation data. The gray correlation result shows that the consistency of the solar variation trend of sunlight hours, evaporation capacity and wind speed and the daily power generation capacity is highest, and the three parameters can be used as core influence parameters to rapidly and directly predict the power generation capacity. Therefore, the invention provides a method and a system for predicting the generated energy based on photovoltaic power generation.

Referring to fig. 1, a disclosed embodiment of the invention provides a method for predicting power generation capacity based on photovoltaic power generation, which includes:

acquiring a plurality of historical meteorological data of a photovoltaic power plant, wherein the historical meteorological data comprise historical sunlight time, historical wind speed, historical evaporation capacity and historical power generation capacity in preset time, and establishing a historical meteorological data model according to the plurality of historical meteorological data; wherein,

The historical meteorological data model comprises a plurality of data sets of historical power generation capacity corresponding to the historical sunlight time, the historical wind speed and the historical evaporation capacity;

inquiring whether historical sunlight time, historical wind speed and historical evaporation capacity exist in a data set corresponding to the meteorological data according to the meteorological data and historical meteorological data models, and determining the generating capacity of the photovoltaic power plant in the future preset time according to an inquiring result; wherein,

when the historical sunlight time, the historical wind speed and the historical evaporation amount in the data set corresponding to the meteorological data exist, correspondingly historical power generation amount is used as the power generation amount of the photovoltaic power plant in the future preset time;

when the historical sunlight time, the historical wind speed and the historical evaporation amount in the data set corresponding to the meteorological data do not exist, calculating and determining the generated energy of the photovoltaic power plant in the future preset time according to the meteorological data, establishing a set of the calculated generated energy and the meteorological data, and inputting the set into a historical meteorological data model.

It can be understood that the gray correlation degree and stepwise regression analysis of the meteorological factors and the photovoltaic power generation are carried out according to the power generation data and the contemporaneous meteorological observation data. The gray correlation result shows that the solar time, the evaporation capacity, the daily variation trend of the wind speed and the consistency of the daily power generation are the highest, and the three are used as core influence parameters to directly and accurately predict the power generation rapidly, so that the mode that a large amount of data are required to be collected for function calculation in the traditional mode is changed, and the photovoltaic power generation prediction is realized more rapidly and accurately.

In a specific embodiment of the present application, a preset solar time matrix T0 and a preset predicted power generation amount matrix a are preset, and a (A1, A2, A3, A4) is set for the preset predicted power generation amount matrix a, wherein A1 is a first preset predicted power generation amount, A2 is a second preset predicted power generation amount, A3 is a third preset predicted power generation amount, and A4 is a fourth preset predicted power generation amount;

for a preset sunshine duration matrix T0, setting T0 (T01, T02, T03 and T04), wherein T01 is a first preset sunshine duration, T02 is a second preset sunshine duration, T03 is a third preset sunshine duration, T04 is a fourth preset sunshine duration, and T01 is more than T02 and less than T03 is less than T04;

when the historical sunlight time, the historical wind speed and the historical evaporation amount in the data set corresponding to the meteorological data do not exist, correspondingly predicting the generated energy according to the relation between T and a preset sunlight time matrix T0 as the generated energy of the photovoltaic power plant in the future preset time;

when T is less than T01, selecting a first preset predicted power generation amount A1 as the power generation amount of the photovoltaic power plant in the future preset time;

when T01 is less than or equal to T02, selecting a second preset predicted power generation amount A2 as the power generation amount of the photovoltaic power plant in the future preset time;

When T02 is less than or equal to T03, selecting a third preset predicted power generation amount A3 as the power generation amount of the photovoltaic power plant in the future preset time;

In a specific embodiment of the present application, a preset wind speed matrix N0 and a preset predicted power generation amount correction coefficient matrix B are preset, for which B (B1, B2, B3, B4) is set, wherein B1 is a first preset predicted power generation amount correction coefficient, B2 is a second preset predicted power generation amount correction coefficient, B3 is a third preset predicted power generation amount correction coefficient, B4 is a fourth preset predicted power generation amount correction coefficient, and B1 is more than 0.8 and less than B2 and B3 and less than B4 and less than 1;

for a preset wind speed matrix N0, setting N0 (N01, N02, N03, N04), wherein N01 is a first preset wind speed, N02 is a second preset wind speed, N03 is a third preset wind speed, N04 is a fourth preset wind speed, and N01 is more than N02 and less than N03 is less than N04;

when the historical sunlight time, the historical wind speed and the historical evaporation amount in the data set corresponding to the meteorological data do not exist, a corresponding predicted generating capacity correction coefficient is selected according to the relation between V and a preset wind speed matrix N0 so as to correct each predicted generating capacity;

When V is smaller than N01, a fourth preset predicted generating capacity correction coefficient B4 is selected to correct the first preset predicted generating capacity A1, and the corrected predicted generating capacity is A1 x B4;

when N01 is less than or equal to V and less than N02, a third preset predicted generating capacity correction coefficient B3 is selected to correct the second preset predicted generating capacity A2, and the corrected predicted generating capacity is A2 x B3;

when N02 is less than or equal to V and less than N03, selecting a second preset predicted generating capacity correction coefficient B2 to correct the third preset predicted generating capacity A3, wherein the corrected predicted generating capacity is A3 x B2;

when N03 is less than or equal to V and less than N04, a first preset predicted generating capacity correction coefficient B1 is selected to correct the fourth preset predicted generating capacity A4, and the corrected predicted generating capacity is A4 x B1.

In a specific embodiment of the present application, a preset evaporation capacity matrix W0 and a preset predicted power generation capacity secondary correction coefficient matrix C are preset, C (C1, C2, C3, C4) is set for the preset predicted power generation capacity secondary correction coefficient matrix C, wherein C1 is a first preset predicted power generation capacity secondary correction coefficient, C2 is a second preset predicted power generation capacity secondary correction coefficient, C3 is a third preset predicted power generation capacity secondary correction coefficient, C4 is a fourth preset predicted power generation capacity secondary correction coefficient, and 1 < C2 < C3 < C4 < 1.2;

For a preset evaporation amount matrix W0, setting W0 (W01, W02, W03 and W04), wherein W01 is a first preset evaporation amount, W02 is a second preset evaporation amount, W03 is a third preset evaporation amount, W04 is a fourth preset evaporation amount, and W01 is less than W02 and less than W03 is less than W04;

when the historical sunlight time, the historical wind speed and the historical evaporation capacity in the data set corresponding to the meteorological data do not exist, selecting a secondary correction coefficient of the corresponding predicted power generation amount according to the relation between R and a preset evaporation capacity matrix W0 so as to carry out secondary correction on each predicted power generation amount after correction;

when R is less than W01, selecting a second correction coefficient C1 of the first preset predicted power generation amount to carry out second correction on the corrected first preset predicted power generation amount A1, wherein the predicted power generation amount after the second correction is A1 x B4 x C1;

when W01 is less than or equal to R < W02, selecting a second preset power generation amount secondary correction coefficient C2 to carry out secondary correction on the corrected second preset power generation amount A2, wherein the power generation amount predicted after the secondary correction is A2 x B3 x C2;

When W03 is less than or equal to R < W04, selecting a second correction coefficient C4 of the fourth preset predicted generated energy to carry out second correction on the corrected fourth preset predicted generated energy A4, wherein the predicted generated energy after the second correction is A4B 1C 4.

In a specific embodiment of the present application, when there is a historical solar time, a historical wind speed and a historical evaporation amount in the data set corresponding to the meteorological data, the method further comprises:

determining the quantity L of data sets corresponding to the historical sunlight time, the historical wind speed and the historical evaporation quantity corresponding to the meteorological data, calculating the average value i of the historical power generation quantity in a plurality of data sets corresponding to the meteorological data when the quantity L is more than or equal to 2, determining the difference U between each historical power generation quantity and the average value i, determining the final predicted power generation quantity according to the average value i and the difference U, and taking the final predicted power generation quantity as the power generation quantity of the photovoltaic power plant in the future preset time; wherein,

when the difference U between each historical generating capacity and the average value i is 0, determining the average value i as a final predicted generating capacity and using the average value i as the generating capacity of the photovoltaic power plant in the future preset time;

when the difference U between the historical power generation amount and the average value i is positive and the number of the difference U is 1/2 greater than the number L of the data sets, multiplying the average value i by a first preset coefficient g1, determining the i x g1 as the final predicted power generation amount, and taking the i x g1 as the power generation amount of the photovoltaic power plant in the future preset time;

When the difference U between the historical generating capacity and the average value i is positive, and the number of the difference U is equal to 1/2 of the number L of the data sets, multiplying the average value i by a second preset coefficient g2, determining the i x g2 as the final predicted generating capacity, and taking the i x g2 as the generating capacity of the photovoltaic power plant in the future preset time;

when the difference U between the historical power generation amount and the average value i is positive, and the number of the difference U is smaller than 1/2 of the number L of the data sets, multiplying the average value i by a third preset coefficient g3, determining the i x g3 as the final predicted power generation amount, and taking the i x g3 as the power generation amount of the photovoltaic power plant in the future preset time; and 1 > g2 > g3 > 0.9.

It can be understood that, because the weather data presents the discontinuity and the change of randomness in a short time, and only three of sunlight time, wind speed and evaporation capacity are selected as the influence parameters, some same weather data still exist, therefore, the data can be ensured to have more accuracy by carrying out optimization correction calculation according to the generated energy corresponding to a plurality of historical data, and the influence of an irregular data set on a final prediction result is reduced.

Based on the same technical concept, referring to fig. 2, the invention further correspondingly provides a power generation amount prediction system based on photovoltaic power generation, which is applied to a power generation amount prediction method based on photovoltaic power generation, and comprises the following steps:

The acquisition module is used for acquiring meteorological data of the photovoltaic power plant in future preset time, wherein the meteorological data comprise sunlight time t, wind speed V and evaporation capacity R;

the prediction module is used for inquiring whether the historical sunlight time, the historical wind speed and the historical evaporation capacity in the data set corresponding to the meteorological data exist or not according to the meteorological data and the historical meteorological data model, and determining the generating capacity of the photovoltaic power plant in the future preset time according to an inquiring result; wherein,

In a specific embodiment of the present application, a preset solar time matrix T0 and a preset predicted power generation amount matrix a are preset in the prediction module, and a (A1, A2, A3, A4) is set for the preset predicted power generation amount matrix a, where A1 is a first preset predicted power generation amount, A2 is a second preset predicted power generation amount, A3 is a third preset predicted power generation amount, and A4 is a fourth preset predicted power generation amount;

the prediction module is also used for selecting a corresponding predicted power generation amount according to the relation between T and a preset sunlight time matrix T0 as the power generation amount of the photovoltaic power plant in the future preset time when the historical sunlight time, the historical wind speed and the historical evaporation amount in the data set corresponding to the meteorological data do not exist;

In a specific embodiment of the present application, a preset wind speed matrix N0 and a preset predicted power generation amount correction coefficient matrix B are preset in the prediction module, and for the preset predicted power generation amount correction coefficient matrix B, B (B1, B2, B3, B4) is set, wherein B1 is a first preset predicted power generation amount correction coefficient, B2 is a second preset predicted power generation amount correction coefficient, B3 is a third preset predicted power generation amount correction coefficient, B4 is a fourth preset predicted power generation amount correction coefficient, and B1 is more than 0.8 and less than B2 and less than B3 and less than B4 and less than 1;

the prediction module is also used for selecting a corresponding predicted generating capacity correction coefficient according to the relation between V and a preset wind speed matrix N0 to correct each predicted generating capacity when the historical sunlight time, the historical wind speed and the historical evaporation capacity in the data set corresponding to the meteorological data do not exist;

In a specific embodiment of the present application, a preset evaporation capacity matrix W0 and a preset predicted power generation capacity secondary correction coefficient matrix C are preset in the prediction module, and C (C1, C2, C3, C4) is set for the preset predicted power generation capacity secondary correction coefficient matrix C, where C1 is a first preset predicted power generation capacity secondary correction coefficient, C2 is a second preset predicted power generation capacity secondary correction coefficient, C3 is a third preset predicted power generation capacity secondary correction coefficient, C4 is a fourth preset predicted power generation capacity secondary correction coefficient, and 1 < C2 < C3 < C4 < 1.2;

the prediction module is also used for selecting a secondary correction coefficient of the corresponding predicted generated energy according to the relation between R and a preset evaporation capacity matrix W0 to secondarily correct each predicted generated energy after correction when the historical sunlight time, the historical wind speed and the historical evaporation capacity in the data set corresponding to the meteorological data do not exist;

In a specific embodiment of the present application, the prediction module is further configured to determine, when there are a historical sunlight time, a historical wind speed, and a historical evaporation amount in the data sets corresponding to the meteorological data, the number L of the data sets corresponding to the historical sunlight time, the historical wind speed, and the historical evaporation amount corresponding to the meteorological data, calculate an average value i of the historical power generation amounts in the plurality of data sets corresponding to the meteorological data when L is greater than or equal to 2, determine a difference value U between each of the historical power generation amounts and the average value i, determine a final predicted power generation amount according to the average value i and the difference value U, and use the final predicted power generation amount as a power generation amount of the photovoltaic power plant in a preset time in the future; wherein,

In summary, according to the invention, by collecting the weather data in the future time, comparing the sunlight time, the wind speed and the evaporation amount of the weather data with the preset historical weather data model, when the parameters consistent with the comparison result exist, the power generation amount can be rapidly predicted, and when the parameters do not exist, the power generation amount is rapidly predicted according to the core influence parameters which most affect the photovoltaic power generation, and the mode of function calculation which needs to collect a large amount of data in the traditional mode is changed, thereby realizing the photovoltaic power generation prediction more rapidly and accurately, being convenient for a power system to timely adjust the power scheduling condition and maintaining the stability of the operation of the power grid. The invention has the advantages of intelligence, accuracy, high efficiency and the like.

The foregoing is merely an example of the present invention and is not intended to limit the scope of the present invention, and all changes made in the structure according to the present invention should be considered as falling within the scope of the present invention without departing from the gist of the present invention.

It will be clear to those skilled in the art that, for convenience and brevity of description, the specific working process of the system described above and the related description may refer to the corresponding process in the foregoing method embodiment, which is not repeated here.

It should be noted that, in the system provided in the foregoing embodiment, only the division of the foregoing functional modules is illustrated, in practical application, the foregoing functional allocation may be performed by different functional modules, that is, the modules or steps in the embodiment of the present invention are further decomposed or combined, for example, the modules in the foregoing embodiment may be combined into one module, or may be further split into multiple sub-modules, so as to complete all or part of the functions described above. The names of the modules and steps related to the embodiments of the present invention are merely for distinguishing the respective modules or steps, and are not to be construed as unduly limiting the present invention.

Those of skill in the art will appreciate that the various illustrative modules, method steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the program(s) corresponding to the software modules, method steps, may be embodied in Random Access Memory (RAM), memory, read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art. To clearly illustrate this interchangeability of electronic hardware and software, various illustrative components and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as electronic hardware or software depends upon the particular application and design constraints imposed on the solution. Those skilled in the art may implement the described functionality using different approaches for each particular application, but such implementation is not intended to be limiting.

The terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus/apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus/apparatus.

Thus far, the technical solution of the present invention has been described in connection with the preferred embodiments shown in the drawings, but it is easily understood by those skilled in the art that the scope of protection of the present invention is not limited to these specific embodiments. Equivalent modifications and substitutions for related technical features may be made by those skilled in the art without departing from the principles of the present invention, and such modifications and substitutions will fall within the scope of the present invention.

The foregoing description is only of the preferred embodiments of the present invention, and is not intended to limit the scope of the present invention.

Claims

1. The method for predicting the generating capacity based on the photovoltaic power generation is characterized by comprising the following steps of:

when the historical sunlight time, the historical wind speed and the historical evaporation amount in the data set corresponding to the meteorological data do not exist, calculating and determining the generated energy of the photovoltaic power plant in the future preset time according to the meteorological data, establishing a set of the calculated generated energy and the meteorological data, and inputting the set into the historical meteorological data model;

A preset sunlight time matrix T0 and a preset predicted power generation amount matrix A are preset, and for the preset predicted power generation amount matrix A, A (A1, A2, A3 and A4) is set, wherein A1 is a first preset predicted power generation amount, A2 is a second preset predicted power generation amount, A3 is a third preset predicted power generation amount and A4 is a fourth preset predicted power generation amount;

when T03 is less than or equal to T04, selecting the fourth preset predicted power generation amount A4 as the power generation amount of the photovoltaic power plant in the future preset time;

a preset wind speed matrix N0 and a preset predicted generating capacity correction coefficient matrix B are preset, B (B1, B2, B3 and B4) is set for the preset predicted generating capacity correction coefficient matrix B, wherein B1 is a first preset predicted generating capacity correction coefficient, B2 is a second preset predicted generating capacity correction coefficient, B3 is a third preset predicted generating capacity correction coefficient, B4 is a fourth preset predicted generating capacity correction coefficient, and B1 is more than 0.8 and less than B2 and less than B4 and less than 1;

when N03 is less than or equal to V and less than N04, selecting the first preset predicted generating capacity correction coefficient B1 to correct the fourth preset predicted generating capacity A4, wherein the corrected predicted generating capacity is A4 x B1;

a preset evaporation capacity matrix W0 and a preset predicted power generation capacity secondary correction coefficient matrix C are preset, and C (C1, C2, C3 and C4) is set for the preset predicted power generation capacity secondary correction coefficient matrix C, wherein C1 is a first preset predicted power generation capacity secondary correction coefficient, C2 is a second preset predicted power generation capacity secondary correction coefficient, C3 is a third preset predicted power generation capacity secondary correction coefficient, C4 is a fourth preset predicted power generation capacity secondary correction coefficient, and C1 is more than 1 and less than C2 and C3 is more than 1.2;

2. The photovoltaic power generation-based power generation amount prediction method according to claim 1, characterized by further comprising, when there are the historical solar time, the historical wind speed, and the historical evaporation amount in the data set corresponding to the meteorological data:

3. A power generation amount prediction system based on photovoltaic power generation, applied to the power generation amount prediction method based on photovoltaic power generation according to any one of claims 1 to 2, comprising:

4. A photovoltaic power generation-based power generation amount prediction system according to claim 3,

a preset sunlight time matrix T0 and a preset predicted power generation amount matrix A are preset in the prediction module, A (A1, A2, A3 and A4) are set for the preset predicted power generation amount matrix A, wherein A1 is a first preset predicted power generation amount, A2 is a second preset predicted power generation amount, A3 is a third preset predicted power generation amount, and A4 is a fourth preset predicted power generation amount;

5. A photovoltaic power generation-based power generation amount prediction system according to claim 4, characterized in that,

a preset wind speed matrix N0 and a preset predicted generating capacity correction coefficient matrix B are preset in the prediction module, B (B1, B2, B3 and B4) is set for the preset predicted generating capacity correction coefficient matrix B, wherein B1 is a first preset predicted generating capacity correction coefficient, B2 is a second preset predicted generating capacity correction coefficient, B3 is a third preset predicted generating capacity correction coefficient, B4 is a fourth preset predicted generating capacity correction coefficient, and B1 is more than 0.8 and less than B2 and B3 and less than B4 and less than 1;

6. The photovoltaic power generation-based power generation amount prediction system according to claim 5, characterized in that,

the prediction module is internally preset with a preset evaporation capacity matrix W0 and a preset predicted power generation capacity secondary correction coefficient matrix C, and C (C1, C2, C3 and C4) is set for the preset predicted power generation capacity secondary correction coefficient matrix C, wherein C1 is a first preset predicted power generation capacity secondary correction coefficient, C2 is a second preset predicted power generation capacity secondary correction coefficient, C3 is a third preset predicted power generation capacity secondary correction coefficient, C4 is a fourth preset predicted power generation capacity secondary correction coefficient, and C1 is more than 1 and less than C2 and C3 is more than 1.2;

7. A photovoltaic power generation-based power generation amount prediction system according to claim 3,

the prediction module is further used for determining the quantity L of the data sets corresponding to the historical sunlight time, the historical wind speed and the historical evaporation amount in the data sets corresponding to the meteorological data when the historical sunlight time, the historical wind speed and the historical evaporation amount in the data sets corresponding to the meteorological data exist, calculating an average value i of the historical power generation amount in a plurality of data sets corresponding to the meteorological data when the quantity L is more than or equal to 2, determining a difference U between each historical power generation amount and the average value i, determining a final predicted power generation amount according to the average value i and the difference U, and taking the final predicted power generation amount as the power generation amount of the photovoltaic power plant in a future preset time; wherein,