Method and system for evaluating and forecasting water-wind-solar complementary characteristics based on grading

Abstract

The invention discloses a method and system for evaluating and forecasting water-wind-solar complementary characteristics based on grading. The method comprises the following steps: acquiring historical meteorological data of continuous multiple days in a target area; the meteorological data comprises wind speed, total radiation and precipitation; according to the wind speed, the total radiation and the precipitation of multiple days, the quartile, the average value and the positive and negative two-time standard deviation of the wind speed, the total radiation and the precipitation of multiple days are calculated, and according to the quartile, the average value and the positive and negative two-time standard deviation of the wind speed, the total radiation and the precipitation of multiple days, the average value and the positive and negative two-time standard deviation are calculated. Calculating division intervals of different grades of wind, light and water according to different grades of wind, light and water power generation efficiency; future forecast meteorological data are obtained, and grades corresponding to future wind speed, total radiation and precipitation are calculated according to different grades of divided intervals of wind, light and water; and adding the future forecast wind speed grade, the current day total radiation grade and the future forecast precipitation grade to obtain a complementary characteristic index. According to the invention, the water-wind-light complementary characteristic index can be accurately evaluated and forecasted.

Description

Technical Field

[0001] This application relates to the technical field of power system analysis, and particularly to a method and system for evaluating and forecasting the complementary characteristics of water, wind, and light based on level division. Background Art

[0002] Making full use of and vigorously developing renewable energy sources such as wind, light, and water is an important way for China to achieve the goals of carbon peak and carbon neutrality. In the past decade or more, the installation of new energy in China has achieved unprecedented development. In some regions, sufficient wind, light, and water power generation facilities are configured, and energy generation complementarity is usually achieved through wind, light, and water power generation. However, limited by the inherent intermittency and uncontrollability of wind power and photovoltaic power generation, the problem of their consumption has always been very prominent. In the future, with the continuous expansion of the grid connection scale, the challenges faced by the safe and stable operation of the new power system dominated by new energy are becoming more and more prominent.

[0003] With the acceleration of the energy transformation, the proportion of renewable energy in the power system is increasing continuously, especially clean energy such as wind energy, solar energy, and water energy. Although the multi-energy complementarity of wind, light, and water can alleviate the volatility of energy supply to a certain extent, these energy forms have characteristics such as intermittency, volatility, and uncertainty. Even with the multi-energy complementarity of wind, light, and water, it is difficult to ensure the stable operation of the power system. By evaluating the complementary characteristics of multiple energies such as wind, light, and water, it is possible to deeply understand whether wind, light, and water energy can provide stable high-power generation, so as to provide a scientific basis for optimizing the energy layout, improving energy utilization efficiency, and enhancing the stability and reliability of the power system. Summary of the Invention

[0004] Based on this, in view of the above technical problems, a method for evaluating and forecasting the complementary characteristics of water, wind, and light based on level division is provided to accurately evaluate and forecast the complementary characteristics of water, wind, and light.

[0005] In a first aspect, a method for evaluating the complementary characteristics of water, wind, and light based on multi-energy level division, the method includes:

[0006] Obtain historical meteorological data for consecutive multiple days within a target area; the meteorological data includes wind speed, total radiation, and precipitation;

[0007] Calculate the quartiles, mean, and positive and negative two standard deviations of the wind speed, total radiation, and precipitation for the multiple days respectively according to the wind speed, total radiation, and precipitation of the multiple days;

[0008] Calculate the division intervals of different levels of wind, light, and water according to the quartiles, mean, and positive and negative two standard deviations of the wind speed, total radiation, and precipitation for the multiple days;

[0009] Obtain future forecast meteorological data, and calculate the corresponding levels of future wind speed, total radiation, and precipitation respectively according to the division intervals of different levels of wind, light, and water;

[0010] Add the future wind speed level, future total radiation level, and future precipitation level to obtain a complementary characteristic index to reflect the excellent degree of the complementarity of water, wind, and light.

[0011] In the above solution, optionally, after obtaining the complementary characteristic index, it further includes: judging the excellent degree of the complementarity of water, wind, and light of the complementary characteristic index according to the set interval conditions.

[0012] In the above solution, further optionally, the set interval conditions include:

[0013] When the complementary characteristic index is between 3 and 4, the complementarity is poor, and the overall power generation of water, wind, and light is insufficient; when the complementary characteristic index is between 5 and 6, the complementarity is good, and the overall power generation of water, wind, and light is on the low side; when the complementary characteristic index is between 7 and 8, the complementarity is the best, and the power generation of water, wind, and light can complement each other; when the complementary characteristic index is between 9 and 10, the complementarity is poor, and the power generation of water, wind, and light is on the high side;

[0014] When the complementary characteristic index is between 11 and 12, the complementarity is poor, and the overall power generation of water, wind, and light is excessive.

[0015] In the above solution, optionally, the obtaining of the historical meteorological data of multiple consecutive days in the target area includes:

[0016] Obtain the historical meteorological data of each hour of multiple consecutive days at multiple stations in the target area;

[0017] Calculate the daily average meteorological data according to the meteorological data of each hour in a day;

[0018] Calculate the mean value of the daily average meteorological data of multiple stations, and finally obtain the daily historical meteorological data.

[0019] In the above solution, optionally, according to the quartiles, mean values, and positive and negative two standard deviations of the wind speed, total radiation, and precipitation in multiple days, calculate the division intervals of different grades of wind, light, and water as: (0, mean value - 2 times standard deviation), (mean value - 2 times standard deviation, mean value), (mean value, quartile), (quartile, ∞).

[0020] In the above solution, optionally, after obtaining the historical meteorological data of multiple consecutive days in the target area, preprocess the historical meteorological data to remove abnormal data.

[0021] In the above solution, optionally, after obtaining the complementary characteristic index, it further includes: outputting corresponding adjustment suggestions for wind, light, and water power generation according to the complementary characteristic index.

[0022] In the second aspect, a water-wind-light complementary characteristic evaluation and forecasting system based on grade division, the system includes:

[0023] Meteorological data acquisition module: used to acquire historical meteorological data for consecutive days in the target area; the meteorological data includes wind speed, total radiation, and precipitation;

[0024] Calculation module: used to calculate the quartiles, mean, and positive and negative two standard deviations of the wind speed, total radiation, and precipitation for multiple days respectively based on the wind speed, total radiation, and precipitation for the multiple days;

[0025] Level interval division module: used to calculate the division intervals of different levels of wind, light, and water based on the quartiles, mean, and positive and negative two standard deviations of the wind speed, total radiation, and precipitation for the multiple days;

[0026] Wind speed, total radiation, and precipitation level forecast calculation module: used to acquire future forecast meteorological data, and calculate the corresponding levels of future wind speed, total radiation, and precipitation respectively according to the division intervals of different levels of wind, light, and water;

[0027] Complementary characteristic index calculation module: used to add the future wind speed level, future total radiation level, and future precipitation level to obtain a complementary characteristic index to reflect the excellent degree of water, wind, and light complementarity.

[0028] In a third aspect, a computer device includes a memory and a processor, the memory stores a computer program, and when the processor executes the computer program, it implements the steps of a method for evaluating and forecasting the complementary characteristics of water, wind, and light based on level division described in the first aspect above.

[0029] In a fourth aspect, a computer-readable storage medium stores a computer program thereon, and is characterized in that when the computer program is executed by a processor, it implements the steps of a method for evaluating and forecasting the complementary characteristics of water, wind, and light based on level division described in the first aspect above.

[0030] This application has at least the following beneficial effects:

[0031] This application obtains historical meteorological data for consecutive days within a target area; the meteorological data includes wind speed, total radiation, and precipitation; the quartiles, mean, and positive and negative two standard deviations of the wind speed, total radiation, and precipitation for multiple days are calculated respectively; based on the quartiles, mean, and positive and negative two standard deviations of the wind speed, total radiation, and precipitation for multiple days, the division intervals for different grades of wind, light, and water are calculated; future forecast meteorological data is obtained, and according to the division intervals for different grades of wind, light, and water, the corresponding grades of future forecast wind speed, total radiation, and precipitation are calculated respectively; the future forecast wind speed grade, future total radiation grade, and current day precipitation grade are added together to obtain a complementary characteristic index. Thus, the forecast complementary characteristic index can be accurately calculated, providing a scientific basis for optimizing the energy layout, improving energy utilization efficiency, and enhancing the stability and reliability of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 FIG. is a flowchart of a method for evaluating the complementary characteristics of water, wind, and light based on multi-energy grade division provided by an embodiment of this application;

[0033] Figure 2 FIG. is a distribution diagram of the number of days with different grades of wind speed obtained by dividing the historical wind speed in the Hubei region according to the wind speed grade division interval diagram provided by an embodiment of this application;

[0034] Figure 3 FIG. is a distribution diagram of the number of days with different grades of radiation obtained by dividing the historical radiation data in the Hubei region according to the radiation grade division interval diagram provided by an embodiment of this application;

[0035] Figure 4 FIG. is a distribution diagram of the number of days with different grades of precipitation obtained by dividing the historical precipitation data in the Hubei region according to the precipitation grade division interval diagram provided by an embodiment of this application;

[0036] Figure 5 FIG. is a distribution diagram of the number of days with different grades of the complementary characteristic values of wind, light, and water in the historical data of the Hubei region provided by an embodiment of this application;

[0037] Figure 6 FIG. is a distribution diagram of the number of days with different grades of wind speed obtained by dividing the historical wind speed in the Guangxi region according to the wind speed grade division interval diagram provided by an embodiment of this application;

[0038] Figure 7 FIG. is a distribution diagram of the number of days with different grades of radiation obtained by dividing the historical radiation data in the Guangxi region according to the radiation grade division interval diagram provided by an embodiment of this application;

[0039] Figure 8The distribution diagram of the number of days of different levels of precipitation obtained by dividing the historical precipitation data in Guangxi region provided by an embodiment of this application according to the precipitation level division interval diagram;

[0040] Figure 9 The distribution diagram of the number of days of different levels of the wind-solar-hydro complementary characteristic values in the historical data of Guangxi region provided by an embodiment of this application;

[0041] Figure 10 An interface diagram of a wind-solar-hydro complementary characteristic evaluation system based on multi-energy level division provided by an embodiment of this application;

[0042] Figure 11 Another interface diagram of a wind-solar-hydro complementary characteristic evaluation system based on multi-energy level division provided by an embodiment of this application. Detailed implementation manners

[0043] In order to make the objectives, technical solutions and advantages of this application more clear and understandable, the following further details this application in combination with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not used to limit this application.

[0044] In one embodiment, as Figure 1 shown, a wind-solar-hydro complementary characteristic evaluation method based on multi-energy level division is provided, and the method includes:

[0045] Step S1: Obtain historical meteorological data of consecutive multiple days in the target area; the meteorological data includes wind speed, total radiation and precipitation.

[0046] In step S1, the total precipitation, total radiation and wind speed at 100-meter height in the ERA5 reanalysis data are used as the experimental data for constructing the model in this application. The ERA5 data is the fifth-generation atmospheric reanalysis data of the global climate from January 1979 to the present by the European Centre for Medium-Range Weather Forecasts (ECMWF) using an advanced modeling and data assimilation system to combine a large amount of historical observation data into the global estimation, providing hourly data of many atmospheric, land surface and ocean state parameters. The ERA5 reanalysis data includes elements such as wind speed and surface solar radiation, with a data time resolution of 1h and a spatial resolution of 0.25 degrees × 0.25 degrees. The data time period is 1991 - 2023.

[0047] Process the hourly data of wind speed at 100-meter height, total radiation and precipitation into daily average wind speed, total daily radiation and daily precipitation, and cut out the data of the target area, and then perform regional averaging on these 3 elements to obtain the time series of wind speed at 100-meter height, total radiation and total precipitation respectively.

[0048] Step S2: Calculate the quartiles, mean, and positive and negative two standard deviations of the wind speed, total radiation, and precipitation for multiple days respectively based on the wind speed, total radiation, and precipitation of these multiple days.

[0049] Step S3: Calculate the division intervals of different grades of wind, light, and water based on the quartiles, mean, and positive and negative two standard deviations of the wind speed, total radiation, and precipitation for multiple days.

[0050] In step S3, calculate the quartiles, mean, and positive and negative two standard deviations of these three elements respectively. Considering the power generation efficiency of different grades of wind, light, and water, and combining the power generation grade classification method of the "National Special Report on Meteorological Conditions for Wind and Solar Power Generation" product of the public service center, divide the wind speed, precipitation, and total radiation into 4 grades respectively. In Table 1, the division intervals of the wind speed (ws) grades in the Hubei region obtained from historical meteorological data are as follows:

[0051] Table 1

[0052] Level Classification Standard Level Name Level 1 0 ≤ ws < 3 m / s Zero Wind Power Generation Level 2 3 m / s < Ws < 5 m / s Low Wind Power Generation <![CDATA[Level 3]]> 5 m / s < Ws < 7 m / s Medium Wind Power Generation Level 4 7m / s >= ws High Wind Power Generation

[0053] Step S4: Obtain the future forecast meteorological data, and calculate the corresponding grades of the future wind speed, total radiation, and precipitation respectively according to the division intervals of different grades of wind, light, and water.

[0054] Step S5: Add the future wind speed grade, future total radiation grade, and future precipitation grade to obtain a complementary characteristic index to reflect the excellent degree of water, wind, and light complementarity.

[0055] In steps S4 and S5, based on the grade division of wind speed, total radiation, and total precipitation, judge which grade each day's water, wind, and light resources belong to respectively. And add the 3 resource grades, and then obtain the water, wind, and light complementary index (pWS). pWs is between 3 - 4, that is, the complementarity is poor and the total power generation of water, wind, and light is generally insufficient; between 5 - 6, that is, the complementarity is good and the power generation of water, wind, and light is on the low side; between 7 - 8, the complementarity is the best and the wind, light, and water power generation can complement each other; between 9 - 10, the complementarity is poor and the total power generation of water, wind, and light may be on the high side; between 11 - 12, the complementarity is poor and the total power generation of water, wind, and light is generally excessive. The grade division of the complementary index and the corresponding measures are shown in Table 2 specifically:

[0056] Table 2

[0057]

[0058] According to the obtained division intervals of the wind speed grades in the Hubei region above, in historical data, based on the wind speed grade division standard, the corresponding number of days for each grade is: 2655 days for grade 1, 5928 days for grade 2, 2685 days for grade 3, and 785 days for grade 4, as Figure 2 shown.

[0059] In the historical data of Hubei region, the radiation level classification standard obtained based on the historical data is shown in Table 3. In the historical data, based on the radiation level classification standard, the corresponding number of days for each level is as follows: 1963 days for level 1, 3436 days for level 2, 3959 days for level 3, and 2695 days for level 4. For example, Figure 3 :

[0060] Table 3

[0061]

[0062]

[0063] In the Hubei region, according to the historical data, the classification standard based on precipitation is shown in Table 4. The corresponding number of days for each level is as follows: 4106 days for level 1, 2151 days for level 2, 3097 days for level 3, and 2699 days for level 4. For example, Figure 4 。

[0064] Table 4

[0065]

[0066] Based on the analysis of the ERA5 reanalysis data from 1991 to 2023, the number of days with poor (low incidence) complementarity in Hubei is 346 days, the number of days with good (low - medium incidence) complementarity is 3844 days, the number of days with excellent complementarity is 5794 days, the number of days with relatively good (medium - high incidence) complementarity is 1985 days, and the number of days with poor (high incidence) complementarity is 84. The distribution of each level of the complementarity index belongs to a normal distribution. Specifically, Figure 5 。

[0067] Similarly, the hourly data of wind speed at 100 - meter height, total radiation, and precipitation are processed into daily average wind speed, total daily radiation, and daily precipitation. The data of the Guangxi region are cropped, and the regional average is taken to obtain three time series. The quartiles, mean, and positive and negative two - standard deviations of these three elements are calculated. Considering the power generation efficiency of different levels of wind, light, and water, combined with the power generation level classification method of the "National Meteorological Conditions Forecast Special Report for Wind and Solar Power Generation" product of the public service center, the wind speed, precipitation, and total radiation are respectively divided into 4 levels, and the level division is the same as the above - mentioned division method.

[0068] Analyzing the historical data of the Guangxi region, based on the wind speed level classification standard, the corresponding number of days for each level is as follows: 2268 days for level 1, 5399 days for level 2, 3166 days for level 3, and 1220 days for level 4. For example, Figure 6 。Based on the radiation level classification standard, the corresponding number of days for each level is as follows: 1212 days for level 1, 3831 days for level 2, 4586 days for level 3, and 2424 days for level 4. For example,Figure 7 Based on precipitation, the number of days corresponding to each level is as follows: level 1 has 2231 days, level 2 has 2174 days, level 3 has 4137 days, and level 4 has 3511 days, as follows Figure 8 。

[0069] To analyze the combined complementary characteristics of wind, light, and water in Guangxi, the number of days and proportions corresponding to the simultaneous occurrence of each level of wind speed and radiation were calculated. It can be seen that when the wind speed level is 3 and the radiation level is 2, the number of days is the largest, which is 2110 days, accounting for 17.51%. When the wind speed level is 1 and the radiation level is 1, the number of days is the least, which is 37 days, accounting for 0.31%. Generally, when the overall wind speed levels are 2 and 3, the proportion of each level is the highest. The distribution map of the simultaneous occurrence of each level of wind, light, and water in Guangxi was calculated. It can be seen that when the wind and light are at level 2, the number of days when precipitation is at each level is large, and the maximum number of days is 723 days, accounting for 5.99%. Generally speaking, when the wind speed levels are 2 - 3 and the precipitation levels are 3 - 4, the proportion is the highest. It is also in this level range that the complementarity is relatively good.

[0070] Analysis shows that the number of days with poor complementarity (low power generation) in Guangxi is 51 days, the number of days with good complementarity (slightly low power generation) is 2198 days, the number of days with good complementarity is 6410 days, the number of days with relatively good complementarity (slightly high power generation) is 3229 days, and the number of days with poor complementarity (high power generation) is 165. The distribution of the complementary index at each level belongs to a normal distribution. Specifically as Figure 9 。

[0071] In the above method for evaluating the complementary characteristics of water, wind, and light based on multi - energy level division, historical meteorological data for consecutive multiple days within the target area is obtained; the meteorological data includes wind speed, total radiation, and precipitation; the quartiles, mean, and positive and negative two - standard deviations of the wind speed, total radiation, and precipitation for multiple days are calculated respectively; according to the quartiles, mean, and positive and negative two - standard deviations of the wind speed, total radiation, and precipitation for multiple days, the division intervals of different levels of wind, light, and water are calculated; future forecast meteorological data is obtained, and according to the division intervals of different levels of wind, light, and water, the corresponding levels of future forecast wind speed, total radiation, and precipitation are calculated respectively; the complementary characteristic index is obtained by adding the future forecast wind speed level, future total radiation level, and the current day's precipitation level. Thus, the complementary characteristic index can be accurately calculated, providing a scientific basis for optimizing the energy layout, improving energy utilization efficiency, and enhancing the stability and reliability of the power system.

[0072] In one embodiment, calculating the division intervals of different levels of wind, light, and water according to the quartiles, mean, and positive and negative two - standard deviations of the wind speed, total radiation, and precipitation for multiple days includes: (0, mean - 2 * standard deviation), (mean - 2 * standard deviation, mean), (mean, quartile), (quartile, ∞).

[0073] In one embodiment, after obtaining the historical meteorological data for consecutive days in the target area, preprocess the historical meteorological data to remove abnormal data.

[0074] In one embodiment, after obtaining the complementary characteristic index, it further includes: according to the complementary characteristic index, output the corresponding adjustment suggestions for wind, light, and water power generation.

[0075] In one embodiment, a water-wind-light complementary characteristic evaluation and forecasting system based on grade division, the system includes:

[0076] Meteorological data acquisition module: used to acquire the historical meteorological data for consecutive days in the target area; the meteorological data includes wind speed, total radiation, and precipitation;

[0077] Calculation module: used to calculate the quartiles, mean values, and positive and negative two standard deviations of the wind speed, total radiation, and precipitation for multiple days respectively according to the wind speed, total radiation, and precipitation for multiple days;

[0078] Grade interval division module: used to calculate the division intervals of different grades of wind, light, and water according to the quartiles, mean values, and positive and negative two standard deviations of the wind speed, total radiation, and precipitation for multiple days;

[0079] Wind speed, total radiation, and precipitation grade forecasting and calculation module: used to acquire the future forecast meteorological data, and calculate the corresponding grades of future wind speed, total radiation, and precipitation respectively according to the division intervals of different grades of wind, light, and water;

[0080] Complementary characteristic index calculation module: used to add the future wind speed grade, future total radiation grade, and future precipitation grade to obtain the complementary characteristic index to reflect the excellent degree of water, wind, and light complementarity.

[0081] Due to the limitation of data provided, the forecast data provided by cMA-WSP is not all grid point data, and the proposed forecast data is larger than the grid point average value of ERA5 reanalysis data. Therefore, in actual operations, we need to make corresponding adjustments to the indicators according to the data. In addition, to obtain more accurate results, we need the data of the same period such as the forecast surface rainfall and the measured surface rainfall, as well as the measured data of the wind speed and total radiation at a height of 100 meters in the area to accurately verify the model, and there are certain errors between the results of the reanalysis data and other data. Such as Figure 10 and 11 is an application interface diagram of a water-wind-light complementary characteristic evaluation and forecasting system based on grade division.

[0082] For the specific limitations of a water-wind-solar complementary characteristic evaluation system based on multi-energy level division, reference can be made to the limitations of a water-wind-solar complementary characteristic evaluation method based on multi-energy level division in the above text, which will not be elaborated here. Each module in the above water-wind-solar complementary characteristic evaluation system based on multi-energy level division can be implemented in whole or in part by software, hardware, and their combination. The above modules can be embedded in the processor of the computer device in hardware form or be independent of it, or be stored in the memory of the computer device in software form, so as to facilitate the processor to call and execute the operations corresponding to each of the above modules.

[0083] In one embodiment, a computer device is provided, and this computer device can be a server. The computer device includes a processor, a memory, and a network interface connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, it realizes the above-mentioned water-wind-solar complementary characteristic evaluation method based on multi-energy level division.

[0084] In one embodiment, a computer-readable storage medium is further provided, on which a computer program is stored, and when the computer program is executed by the processor, it involves all or part of the processes in the method of the above embodiment.

[0085] Those of ordinary skill in the art can understand that to implement all or part of the processes in the above embodiment methods, it can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to the memory, storage, database, or other media used in the various embodiments provided in this application can include at least one of non-volatile and volatile memories. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical memory, etc. Volatile memory can include random access memory (RAM) or an external cache memory. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0086] The technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope recorded in this specification.

[0087] The above-described embodiments merely represent several implementation manners of the present application. The description is relatively specific and detailed, but it should not be construed as a limitation on the scope of the invention patent. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the appended claims.

Claims

1. A method for evaluating and predicting the complementary characteristics of water, wind and solar power based on classification, characterized in that: The method comprises: Acquire historical meteorological data for a number of consecutive days in the target area; the meteorological data includes wind speed, total radiation and precipitation; According to the wind speed, total radiation and precipitation of the multiple days, the quartiles, the average values ​​and the plus or minus two standard deviations of the wind speed, total radiation and precipitation of the multiple days are calculated respectively; Calculate the division intervals of different levels of wind, light and water according to the quartiles, average values ​​and plus or minus two times standard deviation of wind speed, total radiation and precipitation of the multiple days; Obtaining future forecast meteorological data, and calculating the levels corresponding to future wind speed, total radiation and precipitation respectively according to the division intervals of different levels of wind, light and water; The future wind speed level, future total radiation level and future precipitation level are added together to obtain a complementary characteristic index to reflect the degree of complementarity among water, wind and light.

2. The method for evaluating and predicting the complementary characteristics of water, wind and solar power based on classification according to claim 1 is characterized in that: The degree of complementarity among water, wind and light of the complementary characteristic index is judged according to the set interval conditions.

3. The method for evaluating and predicting the water-wind-solar complementary characteristics based on classification according to claim 2 is characterized in that: The setting interval conditions include: When the complementary characteristic index is between 3 and 4, the complementarity is poor and the overall power generation of water, wind and solar power is insufficient; When the complementary characteristic index is between 5 and 6, the complementarity is good, and the overall power generation of water, wind and solar power is low; When the complementary characteristic index is between 7 and 8, the complementarity is the best, and hydropower, wind power and solar power can complement each other; When the complementary characteristic index is between 9 and 10, the complementarity is poor, and the hydropower generation is larger than that of wind and solar power; When the complementary characteristic index is between 11 and 12, the complementarity is poor and there is an overall surplus of hydropower, wind power and solar power generation.

4. The method for evaluating and predicting the water-wind-solar complementary characteristics based on classification according to claim 1 is characterized in that: The acquisition of historical meteorological data for consecutive days in the target area includes: Obtain historical hourly meteorological data for multiple stations in the target area for multiple consecutive days; Calculate daily average meteorological data based on meteorological data for each hour of the day; Calculate the mean of the daily average meteorological data of multiple stations and finally obtain the daily historical meteorological data.

5. The method for evaluating and predicting the water-wind-solar complementary characteristics based on classification according to claim 1 is characterized in that: According to the quartiles, average values ​​and positive and negative two times standard deviation of wind speed, total radiation and precipitation of the above multiple days, the division intervals of different levels of wind, light and water are calculated, including: (0, average value - 2 times standard deviation), (average value - 2 times standard deviation, average value), (average value, quartile), (quartile, ∞).

6. The method for evaluating and predicting the water-wind-solar complementary characteristics based on classification according to claim 1 is characterized in that: After obtaining the historical meteorological data of the target area for a plurality of consecutive days, the historical meteorological data is preprocessed to remove abnormal data.

7. The method for evaluating and predicting the water-wind-solar complementary characteristics based on classification according to claim 1 is characterized in that: After obtaining the complementary characteristic index, the method further includes: outputting corresponding wind-solar-hydropower generation adjustment suggestions according to the complementary characteristic index.

8. A water-wind-solar complementary characteristics assessment and forecasting system based on hierarchical classification, characterized in that: The system comprises: Meteorological data acquisition module: used to obtain historical meteorological data of the target area for multiple consecutive days; the meteorological data includes wind speed, total radiation and precipitation; Calculation module: used to calculate the quartile, average and positive and negative two times standard deviation of the wind speed, total radiation and precipitation of the multiple days respectively according to the wind speed, total radiation and precipitation of the multiple days; The level interval division module is used to calculate the division intervals of different levels of wind, light and water according to the quartiles, average values ​​and positive and negative two times standard deviations of the wind speed, total radiation and precipitation of the multiple days; Wind speed, total radiation and precipitation level forecast calculation module: used to obtain future forecast meteorological data, and calculate the corresponding levels of future wind speed, total radiation and precipitation according to the division intervals of different levels of wind, light and water; Complementary characteristic index calculation module: used to add the future wind speed level, future total radiation level and future precipitation level to obtain a complementary characteristic index to reflect the degree of complementarity among water, wind and light.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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