A regional power grid load forecasting management method and system based on meteorological data

Abstract

The present application discloses a method and system for regional power grid load prediction management based on meteorological data, in the field of regional power grid load prediction. It includes a meteorological data acquisition module, a power information acquisition module, a preliminary analysis module, a power grid load warning module, and a comprehensive evaluation module. By comprehensively analyzing the impact of various meteorological conditions on power generation and power consumption in the target area, and at the same time, based on the meteorological data corresponding to each power consumption time period in the target area and the basic power information corresponding to the target area, the natural power generation deviation coefficient corresponding to various meteorological conditions in the target area at each power consumption time period is obtained. Combining the meteorological data corresponding to the target area and the basic power information corresponding to the target area for comprehensive analysis, the power load warning coefficient corresponding to various meteorological conditions in the target area at each power consumption time period is obtained. Through scientific and effective analysis methods, the accuracy of the regional power grid load prediction results for various meteorological data is improved.

Description

Technical Field

[0001] The present application relates to the field of regional power grid load forecasting, and in particular to a method and system for regional power grid load forecasting management based on meteorological data. Background Art

[0002] The impact of meteorological data on the regional power grid load is a complex and important issue. Considering the global climate change and the increase in extreme weather events, understanding this impact is crucial for the stable operation of the power supply system;

[0003] When analyzing the impact of meteorological data on the regional power grid load, the existing technologies only unilaterally consider the impact of meteorology on power generation or the impact of meteorology on power consumption, and do not comprehensively analyze the two in a scientific and reasonable way, resulting in a large deviation in the results of forecasting the impact of meteorological data on the regional power grid load, which is not conducive to the stable operation of the power supply system. Summary of the Invention

[0004] The purpose of the present invention is to provide a method and system for regional power grid load forecasting management based on meteorological data to solve the problems raised in the above background art.

[0005] To achieve the above purpose, the present invention provides the following technical solutions:

[0006] A regional power grid load forecasting management system based on meteorological data, comprising:

[0007] A meteorological data acquisition module: used to acquire the meteorological conditions of the target area to obtain the meteorological data corresponding to each power consumption time period in the target area;

[0008] A power information acquisition module: used to acquire the basic power conditions of the target area to obtain the basic power information corresponding to the target area;

[0009] A preliminary analysis module: used to obtain the natural power generation deviation coefficient corresponding to each type of meteorology in the target area at each power consumption time period according to the meteorological data corresponding to each power consumption time period in the target area and the basic power information corresponding to the target area;

[0010] A power grid load warning module: used to comprehensively analyze according to the natural power generation deviation coefficient corresponding to each type of meteorology in the target area at each power consumption time period, the meteorological data corresponding to the target area, and the basic power information corresponding to the target area to obtain the power consumption load warning coefficient corresponding to each type of meteorology in the target area at each power consumption time period;

[0011] A comprehensive evaluation module: used to analyze and evaluate the power consumption load warning coefficient corresponding to each type of meteorology in the target area at each power consumption time period to obtain the power grid load forecasting result corresponding to the target area.

[0012] Further, the specific implementation manner of the meteorological data acquisition module is as follows:

[0013] Establish a data extraction relationship between the meteorological data acquisition module and the database, and extract the meteorological data corresponding to each meteorological type stored in the database;

[0014] Obtain the meteorological type corresponding to the target area through the meteorological platform, screen and obtain the meteorological data corresponding to the target area, divide it according to each preset power consumption time period in the target area, and screen and obtain the meteorological data corresponding to each power consumption time period in the target area.

[0015] Further, the specific implementation manner of the power data acquisition module is as follows:

[0016] Establish a data extraction relationship between the power data acquisition module and the database, and extract the basic power information corresponding to the target area stored in the database, where the basic power information includes the natural power generation information and power dispatching information corresponding to the target area;

[0017] The natural power generation information refers to the power generation peak of various natural power generations corresponding to the target area under the standard environment, and the standard environment includes standard air temperature, standard wind speed, standard rainfall, standard air pressure and standard light intensity;

[0018] The power dispatching information refers to the total power generation peak of various natural power generations corresponding to the target area under the standard environment and the power consumption peak of each power consumption time period in the target area under the standard environment. The natural power generation types include wind power generation, hydropower generation and solar power generation.

[0019] Further, the specific implementation manner of the preliminary analysis module is as follows:

[0020] Establish a data extraction relationship between the preliminary analysis module and the database, and extract the meteorological data corresponding to each meteorological type stored in the database, where the meteorological data includes air temperature, wind speed, rainfall, air pressure and light intensity;

[0021] Calculate the wind power generation influence coefficient Wpg of various meteorologies corresponding to the target area through the calculation formula i ;

[0022] Calculate the hydropower generation influence coefficient Hp of various meteorologies corresponding to the target area through the calculation formula i ;

[0023] Calculate the solar power generation influence coefficient Sp of various meteorologies corresponding to the target area through the calculation formula i , where i represents the number of various meteorologies.

[0024] Further, the specific implementation method of the natural power generation deviation coefficient corresponding to various meteorologies in the target area during each power consumption time period in the preliminary analysis module is as follows:

[0025] Divide the lighting time through the power consumption time periods corresponding to various meteorological types in the target area to obtain the lighting time periods and non-lighting time periods corresponding to various meteorological types in the target area;

[0026] When in the lighting time period, obtain the natural power generation deviation coefficient Q i ′ of the target area corresponding to various meteorologies during the lighting time period through calculation formula 1;

[0027] When in the non-lighting time period, obtain the natural power generation deviation coefficient Q i ″ of the target area corresponding to various meteorologies during the non-lighting time period through calculation formula 2, and screen and obtain the natural power generation deviation coefficient corresponding to various meteorologies in the target area during each power consumption time period according to each power consumption time period corresponding to various meteorologies.

[0028] Further, the specific implementation method of the power grid load warning module is as follows:

[0029] Establish a data extraction relationship between the power grid load warning module and the database, and extract the power consumption peak change rate corresponding to each standard meteorological data model stored in the database;

[0030] Among them, the meteorological data model includes meteorological data, population quantity, and per capita GDP;

[0031] Obtain the population quantity and per capita GDP corresponding to the target area through the economic development report and population report corresponding to the target area;

[0032] Establish a meteorological data model corresponding to each power consumption time period in the target area according to the meteorological data corresponding to each power consumption time period in the target area and the population quantity and per capita GDP corresponding to the target area;

[0033] Compare and analyze the meteorological data model corresponding to each power consumption time period in the target area with each standard meteorological data model to obtain the model similarity between the meteorological data model corresponding to each power consumption time period in the target area and each standard meteorological data model, screen the standard meteorological data model with the maximum model similarity corresponding to each power consumption time period in the target area, record it as the comparison meteorological data model corresponding to each power consumption time period in the target area, and record the power consumption peak change rate of the comparison meteorological data model corresponding to each power consumption time period as the power consumption peak change rate corresponding to various meteorologies in the target area during each power consumption time period;

[0034] Extract the total power generation peak change rate corresponding to each natural power generation deviation coefficient stored in the database, which is obtained by screening according to the natural power generation deviation coefficient corresponding to various meteorological conditions in the target area during each power consumption period; the total power generation peak change rate corresponding to various meteorological conditions in the target area during each power consumption period.

[0035] Further, the specific implementation method of the power load warning coefficient corresponding to various meteorological conditions in the target area during each power consumption period in the power grid load warning module is as follows:

[0036] Calculate the power load warning coefficient A corresponding to various meteorological conditions in the target area during each power consumption period through a calculation formula. i～m , where i to m represent the numbers of each power consumption period corresponding to various meteorological conditions.

[0037] Further, the specific implementation method of the power grid load warning module is as follows:

[0038] Compare and analyze the power load warning coefficient corresponding to various meteorological conditions in the target area during each power consumption period with the preset standard power load warning coefficient. If the power load warning coefficient corresponding to various meteorological conditions in the target area during each power consumption period is less than or equal to the preset standard power load warning coefficient, it means that the power consumption status corresponding to each power consumption period of the target area for this type of meteorological condition is safe and does not exceed the power load. If the power load warning coefficient corresponding to a certain meteorological condition in the target area during a certain power consumption period is greater than the preset standard power load warning coefficient, it means that the power consumption status corresponding to this type of meteorological condition during this power consumption period is unsafe and exceeds the power load. Record this power consumption period as the overload period corresponding to this type of meteorological condition. Screen and count the overload periods corresponding to various meteorological conditions in the target area, and record the overload periods corresponding to various meteorological conditions in the target area as the power grid load prediction result corresponding to the target area.

[0039] The present invention also provides a regional power grid load prediction management method based on meteorological data, which is applied to the aforementioned regional power grid load prediction management system based on meteorological data, and includes:

[0040] Obtain the meteorological conditions of the target area to obtain the meteorological data corresponding to each power consumption period of the target area;

[0041] Obtain the basic power status of the target area to obtain the basic power information corresponding to the target area;

[0042] According to the meteorological data corresponding to each power consumption period of the target area and the basic power information corresponding to the target area, obtain the natural power generation deviation coefficient corresponding to various meteorological conditions in the target area during each power consumption period.

[0043] Further, the method for predicting and managing the regional power grid load based on meteorological data further includes:

[0044] Based on the natural power generation deviation coefficients corresponding to various meteorological conditions in the target area during each power consumption time period, the meteorological data corresponding to the target area, and the basic power information corresponding to the target area, comprehensive analysis is carried out to obtain the power load warning coefficients corresponding to various meteorological conditions in the target area during each power consumption time period;

[0045] Analyze and evaluate the power load warning coefficients corresponding to various meteorological conditions in the target area during each power consumption time period to obtain the power grid load prediction result corresponding to the target area.

[0046] Compared with the prior art, the beneficial effects of the present invention are:

[0047] By comprehensively analyzing the influence of power generation and power consumption of the target area corresponding to various meteorological conditions, the present invention is beneficial to improving the accuracy and effectiveness of the meteorological data on the regional power grid load prediction result, and further ensuring the stable operation of the power supply system;

[0048] By obtaining the natural power generation deviation coefficients corresponding to various meteorological conditions in the target area during each power consumption time period according to the meteorological data corresponding to each power consumption time period of the target area and the basic power information corresponding to the target area, and combining the meteorological data corresponding to the target area and the basic power information corresponding to the target area for comprehensive analysis to obtain the power load warning coefficients corresponding to various meteorological conditions in the target area during each power consumption time period, the accuracy of various meteorological data on the regional power grid load prediction result is improved through a scientific and effective analysis method. Description of the Drawings

[0049] The present invention is further described with reference to the accompanying drawings, but the embodiments in the drawings do not constitute any limitation to the present invention. For those of ordinary skill in the art, other drawings can be obtained according to the following drawings without creative efforts.

[0050] Figure 1 It is a schematic structural diagram of a regional power grid load prediction management system based on meteorological data according to an embodiment of the present invention.

[0051] Figure 2 It is a schematic flow diagram of a method for predicting and managing the regional power grid load based on meteorological data according to an embodiment of the present invention. Detailed Embodiments

[0052] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0053] Please refer to Figure 1 , the present invention provides a regional power grid load prediction management system based on meteorological data. The system includes a meteorological data acquisition module, a power information acquisition module, a preliminary analysis module, a power grid load warning module, and a comprehensive evaluation module;

[0054] The meteorological data acquisition module is connected to the preliminary analysis module, the power information acquisition module is connected to the preliminary analysis module, the preliminary analysis module is connected to the power grid load warning module, and the power grid load warning module is connected to the comprehensive evaluation module;

[0055] Furthermore, the specific execution method of the meteorological data acquisition module is as follows:

[0056] Establish a data extraction relationship between the meteorological data acquisition module and the database, and extract the meteorological data corresponding to each meteorological type stored in the database;

[0057] Obtain the meteorological type corresponding to the target area through the meteorological platform, screen to obtain the meteorological data corresponding to the target area, and divide it according to each preset power consumption time period in the target area, and screen to obtain the meteorological data corresponding to each power consumption time period in the target area.

[0058] The meteorological data acquisition module is used to obtain the meteorological conditions of the target area and obtain the meteorological data corresponding to each power consumption time period in the target area;

[0059] Furthermore, the specific execution method of the power data acquisition module is as follows:

[0060] Establish a data extraction relationship between the power data acquisition module and the database, and extract the basic power information corresponding to the target area stored in the database, where the basic power information includes the natural power generation information and power dispatching information corresponding to the target area;

[0061] The natural power generation information refers to the power generation peak of various natural power generations corresponding to the target area under the standard environment, and the standard environment includes standard air temperature, standard wind speed, standard rainfall, standard air pressure, and standard light intensity;

[0062] The power dispatching information refers to the total power generation peak of various natural power generations corresponding to the target area under the standard environment and the power consumption peak of each power consumption time period in the target area under the standard environment. The natural power generation types include wind power generation, hydropower generation, and solar power generation.

[0063] The power information acquisition module is used to acquire the basic power status of the target area and obtain the corresponding basic power information of the target area;

[0064] Furthermore, the specific execution method of the power data acquisition module is as follows:

[0065] Establish a data extraction relationship between the power data acquisition module and the database, and extract the basic power information corresponding to the target area stored in the database, where the basic power information includes the natural power generation information and power dispatching information corresponding to the target area;

[0066] The natural power generation information refers to the power generation peak of various natural power generations corresponding to the target area under the standard environment, and the standard environment includes standard air temperature, standard wind speed, standard rainfall, standard air pressure, and standard light intensity;

[0067] The power dispatching information refers to the total power generation peak of various natural power generations corresponding to the target area under the standard environment and the power consumption peak of each power consumption period in the target area under the standard environment. The types of natural power generation include wind power generation, hydropower generation, and solar power generation.

[0068] The preliminary analysis module is used to obtain the natural power generation deviation coefficient corresponding to each type of meteorology in each power consumption period of the target area according to the meteorological data corresponding to each power consumption period of the target area and the basic power information corresponding to the target area;

[0069] Furthermore, the specific execution method of the preliminary analysis module is as follows:

[0070] Establish a data extraction relationship between the preliminary analysis module and the database, and extract the meteorological data corresponding to each meteorological type stored in the database, where the meteorological data includes air temperature, wind speed, rainfall, air pressure, and light intensity;

[0071] Through the calculation formula

[0072]

[0073] Calculate the wind power generation influence coefficient Wpg corresponding to each type of meteorology in the target area i ;

[0074] It should be noted that: the smaller the difference between the wind speed, air temperature, and air pressure corresponding to each type of meteorological data in the formula and the standard wind speed, standard air temperature, and standard air pressure, the smaller the wind power generation influence coefficient corresponding to each type of meteorology in the target area, which means that the influence of wind power generation corresponding to each type of meteorology in the target area is smaller;

[0075] The wind speed, air temperature, and air pressure corresponding to various meteorological data in the formula will not affect each other with the standard wind speed, standard air temperature, and standard air pressure.

[0076] By calculating the formula

[0077]

[0078] The hydropower generation influence coefficient Hp corresponding to various meteorological conditions in the target area is calculated. i It should be noted that: the smaller the difference between the rainfall and air temperature corresponding to various meteorological data in the formula and the corresponding standard rainfall and standard air temperature, the smaller the hydropower generation influence coefficient corresponding to various meteorological conditions in the target area, indicating that the influence of various meteorological conditions in the target area on hydropower generation is smaller;

[0079] It should be noted that: the rainfall and air temperature corresponding to various meteorological data in the formula will not affect each other with the corresponding standard rainfall and standard air temperature.

[0080] By calculating the formula

[0081]

[0082] The solar power generation influence coefficient Sp corresponding to various meteorological conditions in the target area is calculated. i where ws′, t′, pa′, rf′, li′ represent the standard wind speed, standard air temperature, standard air pressure, standard rainfall, and standard light intensity respectively, and ws i 、t i 、pa i 、rf i 、li i represent the wind speed, air temperature, air pressure, rainfall, and light intensity corresponding to various meteorological data respectively, and α1, α2, α3, α4, α5, α6 represent the wind speed influence factor, wind power generation influence coefficient influence factor, precipitation influence factor, hydropower generation influence coefficient influence factor, light intensity influence factor, and solar power generation influence coefficient influence factor respectively, where i represents the number of various meteorological conditions;

[0083] It should be noted that: the smaller the difference between the light intensity influence factor corresponding to various meteorological data in the formula and the corresponding standard light intensity, the smaller the solar power generation influence coefficient corresponding to various meteorological conditions in the target area, indicating that the influence of various meteorological conditions in the target area on solar power generation is smaller;

[0084] It should be noted that: the light intensity influence factor corresponding to various meteorological data in the formula will not affect each other with the corresponding standard light intensity.

[0085] Divide the lighting time through the power consumption time periods corresponding to each meteorological type in the target area to obtain the lighting time periods and non-lighting time periods corresponding to each meteorological type in the target area;

[0086] When it is in the lighting time period, calculate through calculation formula 1

[0087]

[0088] Calculate and obtain the natural power generation deviation coefficient Q i ′ of each type of meteorology in the target area during the lighting time period;

[0089] When it is in the non-lighting time period, calculate through calculation formula 2

[0090]

[0091] Calculate and obtain the natural power generation deviation coefficient Q i ″ of each type of meteorology in the target area during the non-lighting time period, where β1 and β2 respectively represent the first influence factor of the natural power generation deviation coefficient and the second influence factor of the natural power generation deviation coefficient, and Q represents the total power generation peak of natural power generation in the target area under standard conditions, respectively represent the power generation peak of wind power generation, the power generation peak of hydropower generation, and the power generation peak of solar power generation;

[0092] Screen according to the power consumption time periods corresponding to each type of meteorology to obtain the natural power generation deviation coefficients corresponding to each type of meteorology in the target area during each power consumption time period.

[0093] The power grid load warning module is used to perform comprehensive analysis based on the natural power generation deviation coefficients corresponding to each type of meteorology in the target area during each power consumption time period, the meteorological data corresponding to the target area, and the basic power information corresponding to the target area, and obtain the power load warning coefficients corresponding to each type of meteorology in the target area during each power consumption time period;

[0094] Furthermore, the specific execution method of the power grid load warning module is as follows:

[0095] Establish a data extraction relationship between the power grid load warning module and the database, and extract the power consumption peak change rates corresponding to each standard meteorological data model stored in the database;

[0096] Among them, the meteorological data model includes meteorological data, population quantity, and per capita GDP;

[0097] Obtain the population quantity and per capita GDP corresponding to the target area through the economic development report and population report corresponding to the target area;

[0098] Establish a meteorological data model for each power consumption period in the target area based on the meteorological data corresponding to each power consumption period in the target area, the population quantity and per capita GDP corresponding to the target area;

[0099] Compare and analyze the meteorological data model for each power consumption period in the target area with each standard meteorological data model to obtain the model similarity between the meteorological data model for each power consumption period in the target area and each standard meteorological data model. Screen the standard meteorological data model with the maximum model similarity corresponding to each power consumption period in the target area, denoted as the comparison meteorological data model corresponding to each power consumption period in the target area, and denote the power peak change rate of the comparison meteorological data model corresponding to each power consumption period as the power peak change rate corresponding to each power consumption period for various meteorologies in the target area;

[0100] Extract the total power generation peak change rate corresponding to each natural power generation deviation coefficient stored in the database, and screen and obtain the total power generation peak change rate corresponding to various meteorologies in the target area corresponding to each power consumption period according to the natural power generation deviation coefficient corresponding to various meteorologies in the target area corresponding to each power consumption period;

[0101] Through the calculation formula

[0102]

[0103] Calculate to obtain the power load warning coefficient A corresponding to various meteorologies in the target area corresponding to each power consumption period i～m , where η i～m represents the power peak change rate corresponding to each power consumption period for various meteorologies in the target area, μ i～m represents the total power generation peak change rate corresponding to various meteorologies in the target area corresponding to each power consumption period, pec represents the power peak of the target area in each power consumption period under the standard environment, ψ represents the preset influence factor of the power load warning coefficient, and i~m represent the numbers of each power consumption period corresponding to various meteorologies.

[0104] The comprehensive evaluation module is used to analyze and evaluate the power load warning coefficients corresponding to various meteorologies in the target area corresponding to each power consumption period to obtain the power grid load prediction result corresponding to the target area.

[0105] Furthermore, the specific execution method of the power grid load warning module is as follows:

[0106] Compare and analyze the electricity load warning coefficients corresponding to various meteorological conditions in the target area during each electricity consumption period with the preset standard electricity load warning coefficients. If the electricity load warning coefficients corresponding to various meteorological conditions in the target area during each electricity consumption period are less than or equal to the preset standard electricity load warning coefficients, it indicates that the electricity consumption status corresponding to each electricity consumption period of the target area for each type of meteorology is safe and does not exceed the electricity load. If the electricity load warning coefficient corresponding to a certain type of meteorology in a certain electricity consumption period in the target area is greater than the preset standard electricity load warning coefficient, it indicates that the electricity consumption status corresponding to this type of meteorology in this electricity consumption period is unsafe and exceeds the electricity load. Record this electricity consumption period as the overload period corresponding to this type of meteorology. Screen and count the overload periods corresponding to various meteorological conditions in the target area, and record the overload periods corresponding to various meteorological conditions in the target area as the power grid load prediction results corresponding to the target area.

[0107] Please refer to Figure 2 , to achieve the above object, the present invention also provides the following technical solutions: A regional power grid load prediction management method based on meteorological data, comprising the following steps:

[0108] Obtain the meteorological conditions of the target area to obtain the meteorological data corresponding to each electricity consumption period of the target area;

[0109] Obtain the basic power conditions of the target area to obtain the basic power information corresponding to the target area;

[0110] According to the meteorological data corresponding to each electricity consumption period of the target area and the basic power information corresponding to the target area, obtain the natural power generation deviation coefficients corresponding to various meteorological conditions in the target area during each electricity consumption period;

[0111] Based on the natural power generation deviation coefficients corresponding to various meteorological conditions in the target area during each electricity consumption period, the meteorological data corresponding to the target area, and the basic power information corresponding to the target area, conduct comprehensive analysis to obtain the electricity load warning coefficients corresponding to various meteorological conditions in the target area during each electricity consumption period;

[0112] Analyze and evaluate the electricity load warning coefficients corresponding to various meteorological conditions in the target area during each electricity consumption period to obtain the power grid load prediction results corresponding to the target area.

[0113] The above are all preferred embodiments of this application, and the protection scope of this application is not limited accordingly. Therefore, all equivalent changes made according to the structure, shape, and principle of this application should be covered within the protection scope of this application.

Claims

1. A regional power grid load forecasting and management system based on meteorological data, characterized by: include: Meteorological data acquisition module: used to acquire the meteorological conditions of the target area and obtain the meteorological data corresponding to each power consumption period in the target area; Power information acquisition module: used to acquire the basic power conditions of the target area and obtain the basic power information corresponding to the target area; Preliminary analysis module: used to obtain the natural power generation deviation coefficient corresponding to various types of meteorology in the target area in each power consumption period according to the meteorological data corresponding to each power consumption period in the target area and the basic power information corresponding to the target area, where: The specific implementation method of the preliminary analysis module is as follows: Establishing a data extraction relationship between the preliminary analysis module and the database, extracting meteorological data corresponding to each meteorological type stored in the database, wherein the meteorological data includes air temperature, wind speed, rainfall, air pressure and light intensity; By calculating the formula Calculate the wind power generation impact coefficient of various weather conditions in the target area ; By calculating the formula Calculate the hydropower generation impact coefficients of various meteorological conditions in the target area ; By calculating the formula Calculate the solar power generation impact coefficient of various weather conditions in the target area ,in , , , , They are respectively expressed as standard wind speed, standard air temperature, standard air pressure, standard rainfall and standard light intensity. , , , , They are respectively represented by wind speed, air temperature, air pressure, rainfall and light intensity corresponding to various meteorological data. , , , , , They are respectively expressed as wind speed influence factor, wind power generation influence factor, precipitation influence factor, hydropower generation influence factor, light intensity influence factor, and solar power generation influence factor. Indicates the number of various types of weather; The specific implementation method of the natural power generation deviation coefficient corresponding to various types of weather in the target area in each power consumption period in the preliminary analysis module is as follows: Divide the light time by the electricity consumption time period corresponding to each meteorological type in the target area, and obtain the light time period and no light time period corresponding to each meteorological type in the target area; When there is light during the period, the formula 1 is used to calculate Calculate the natural power generation deviation coefficient of the target area corresponding to various types of weather during the light period ; When there is no light, the formula 2 is used to calculate Calculate the natural power generation deviation coefficient of the target area corresponding to various weather conditions during the no-light period ,in and They are respectively represented as the preset first influencing factor of the natural power generation deviation coefficient and the second influencing factor of the natural power generation deviation coefficient, It is expressed as the total peak value of natural power generation in the target area under standard environment. , , They are respectively represented as peak power generation of wind power, peak power generation of hydropower and peak power generation of solar power; According to the electricity consumption time periods corresponding to various types of meteorology, the natural power generation deviation coefficient corresponding to various types of meteorology in the target area in each electricity consumption time period is obtained; Power grid load warning module: used to conduct a comprehensive analysis based on the natural power generation deviation coefficient corresponding to various types of weather in the target area in each power consumption period, the meteorological data corresponding to the target area, and the basic power information corresponding to the target area, to obtain the power load warning coefficient corresponding to various types of weather in the target area in each power consumption period, where: The specific implementation method of the power load warning coefficient corresponding to each type of weather in the target area in each power consumption time period in the power grid load warning module is as follows: By calculating the formula Calculate the power load warning coefficient corresponding to various weather conditions in the target area during each power consumption period ,in It is expressed as the peak power consumption change rate of each type of weather in the target area corresponding to each power consumption time period. It is expressed as the total peak power generation change rate corresponding to various weather conditions in the target area during each power consumption period. It is expressed as the peak power consumption of each power consumption period in the target area under standard environment. It is expressed as the preset power load warning coefficient influencing factor, Indicates the number of each electricity consumption time period corresponding to each type of weather; Comprehensive evaluation module: used to analyze and evaluate the power load warning coefficient corresponding to various types of meteorological conditions in the target area during each power consumption period, and obtain the power grid load forecast results corresponding to the target area.

2. A regional power grid load forecasting and management system based on meteorological data according to claim 1, characterized in that: The specific implementation method of the meteorological data acquisition module is as follows: Establishing a data extraction relationship between the meteorological data acquisition module and the database, extracting meteorological data corresponding to each meteorological type stored in the database; The meteorological type corresponding to the target area is obtained through the meteorological platform, the meteorological data corresponding to the target area is screened, and the target area is divided according to the preset power consumption time periods, and the meteorological data corresponding to each power consumption time period in the target area is screened.

3. The regional power grid load forecasting and management system based on meteorological data according to claim 1, characterized in that: The specific implementation method of the power information acquisition module is as follows: Establishing a data extraction relationship between the power information acquisition module and the database, extracting the basic power information corresponding to the target area stored in the database, wherein the basic power information includes the natural power generation information and power dispatching information corresponding to the target area; The natural power generation information refers to the power generation peak values ​​of various types of natural power generation in the target area under standard environment, wherein the standard environment includes standard air temperature, standard wind speed, standard rainfall, standard air pressure and standard light intensity; The power dispatch information refers to the total power generation peak value corresponding to various types of natural power generation in the target area under the standard environment and the power consumption peak value in each power consumption time period in the target area under the standard environment. The natural power generation types include wind power generation, hydropower generation and solar power generation.

4. The regional power grid load forecasting and management system based on meteorological data according to claim 1, characterized in that: The specific implementation method of the power grid load early warning module is as follows: Establish a data extraction relationship between the power grid load warning module and the database, and extract the peak power consumption change rate corresponding to each standard meteorological data model stored in the database; The meteorological data model includes meteorological data, population and GDP per capita; Obtain the population and per capita GDP of the target area through the economic development report and population report of the target area; Establish a meteorological data model corresponding to each electricity consumption period in the target area based on the meteorological data corresponding to each electricity consumption period in the target area and the population and per capita GDP corresponding to the target area; Compare and analyze the meteorological data model corresponding to each power consumption time period in the target area with each standard meteorological data model to obtain the model similarity between the meteorological data model corresponding to each power consumption time period in the target area and each standard meteorological data model, select the standard meteorological data model with the maximum model similarity corresponding to each power consumption time period in the target area, and record it as the comparison meteorological data model corresponding to each power consumption time period in the target area, and record the peak power consumption change rate of the comparison meteorological data model corresponding to each power consumption time period as the peak power consumption change rate of each type of meteorology in the target area corresponding to each power consumption time period; The total power generation peak change rate corresponding to each natural power generation deviation coefficient stored in the database is extracted, and the total power generation peak change rate corresponding to each type of meteorological condition in each power consumption period in the target area is obtained by screening according to the natural power generation deviation coefficient corresponding to each type of meteorological condition in each power consumption period in the target area.

5. The regional power grid load forecasting and management system based on meteorological data according to claim 1, characterized in that: The specific implementation method of the power grid load early warning module is as follows: The power load warning coefficient corresponding to each type of meteorological condition in each power consumption time period in the target area is compared and analyzed with the preset standard power load warning coefficient. If the power load warning coefficient corresponding to each type of meteorological condition in each power consumption time period in the target area is less than or equal to the preset standard power load warning coefficient, it means that the power consumption conditions in each power consumption time period in the target area corresponding to each type of meteorological condition are safe and will not exceed the power load. If the power load warning coefficient corresponding to a certain type of meteorological condition in a certain power consumption time period in the target area is greater than the preset standard power load warning coefficient, it means that the power consumption conditions in this power consumption time period in this type of meteorological condition are unsafe and exceed the power load. This power consumption time period is recorded as the overload time period corresponding to this type of meteorological condition. The overload time periods in the target area corresponding to each type of meteorological condition are obtained by screening and statistics. The overload time periods in the target area corresponding to each type of meteorological condition are recorded as the power grid load forecast results corresponding to the target area.

6. A method for regional power grid load forecasting management based on meteorological data, applied to a regional power grid load forecasting management system based on meteorological data as claimed in any one of claims 1 to 5, characterized in that: include: Acquire the meteorological conditions of the target area and obtain the meteorological data corresponding to each power consumption period in the target area; Acquire the basic power conditions of the target area to obtain the basic power information corresponding to the target area; According to the meteorological data corresponding to each power consumption period in the target area and the basic power information corresponding to the target area, the natural power generation deviation coefficient corresponding to each type of meteorology in the target area in each power consumption period is obtained, where: The specific implementation method of the preliminary analysis module is as follows: Establishing a data extraction relationship between the preliminary analysis module and the database, extracting meteorological data corresponding to each meteorological type stored in the database, wherein the meteorological data includes air temperature, wind speed, rainfall, air pressure and light intensity; By calculating the formula Calculate the wind power generation impact coefficient of various weather conditions in the target area ; By calculating the formula Calculate the hydropower generation impact coefficients of various meteorological conditions in the target area ; By calculating the formula Calculate the solar power generation impact coefficient of various weather conditions in the target area ,in , , , , They are respectively expressed as standard wind speed, standard air temperature, standard air pressure, standard rainfall and standard light intensity. , , , , They are respectively represented by wind speed, air temperature, air pressure, rainfall and light intensity corresponding to various meteorological data. , , , , , They are respectively expressed as wind speed influence factor, wind power generation influence factor, precipitation influence factor, hydropower generation influence factor, light intensity influence factor, and solar power generation influence factor. Indicates the number of various types of weather; The specific implementation method of the natural power generation deviation coefficient corresponding to various types of weather in the target area in each power consumption period in the preliminary analysis module is as follows: Divide the light time by the electricity consumption time period corresponding to each meteorological type in the target area, and obtain the light time period and no light time period corresponding to each meteorological type in the target area; When there is light during the period, the formula 1 is used to calculate Calculate the natural power generation deviation coefficient of the target area corresponding to various types of weather during the light period ; When there is no light, the formula 2 is used to calculate Calculate the natural power generation deviation coefficient of the target area corresponding to various weather conditions during the no-light period ,in and They are respectively represented as the preset first influencing factor of the natural power generation deviation coefficient and the second influencing factor of the natural power generation deviation coefficient, It is expressed as the total peak value of natural power generation in the target area under standard environment. , , They are respectively represented as peak power generation of wind power, peak power generation of hydropower and peak power generation of solar power; According to the electricity consumption time periods corresponding to various types of meteorology, the natural power generation deviation coefficient corresponding to various types of meteorology in the target area in each electricity consumption time period is obtained; A comprehensive analysis is conducted based on the natural power generation deviation coefficient corresponding to various types of weather in the target area in each power consumption period, the meteorological data corresponding to the target area, and the basic power information corresponding to the target area to obtain the power load warning coefficient corresponding to various types of weather in the target area in each power consumption period, where: The specific implementation method of the power load warning coefficient corresponding to each type of weather in the target area in each power consumption time period in the power grid load warning module is as follows: By calculating the formula Calculate the power load warning coefficient corresponding to various weather conditions in the target area during each power consumption period ,in It is expressed as the peak power consumption change rate of each type of weather in the target area corresponding to each power consumption time period. It is expressed as the total peak power generation change rate corresponding to various weather conditions in the target area during each power consumption period. It is expressed as the peak power consumption of each power consumption period in the target area under standard environment. It is expressed as the preset power load warning coefficient influencing factor, Indicates the number of each electricity consumption time period corresponding to each type of weather; The power load warning coefficients corresponding to various types of meteorological conditions in the target area during various power consumption time periods are analyzed and evaluated to obtain the power grid load forecast results corresponding to the target area.

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