Regional power grid load prediction management method and system based on meteorological data

Abstract

The invention discloses a regional power grid load prediction management method and system based on meteorological data, and relates to the field of regional power grid load prediction, and the system comprises a meteorological data acquisition module, an electric power information acquisition module, a preliminary analysis module, a power grid load early warning module, and a comprehensive evaluation module. The method comprises the following steps: comprehensively analyzing the generating capacity influence and the power consumption influence of a target area corresponding to various types of meteorology, and obtaining a natural generating deviation coefficient corresponding to each type of meteorology in each power consumption time period of the target area according to meteorological data corresponding to each power consumption time period of the target area and basic power information corresponding to the target area; and comprehensive analysis is carried out in combination with the meteorological data corresponding to the target region and the basic power information corresponding to the target region to obtain the electrical load early warning coefficients corresponding to the various types of meteorology corresponding to the target region in the various power consumption time periods, and the accuracy of the regional power grid load prediction result by the various types of meteorological data is improved through a scientific and effective analysis mode.

Description

Technical Field

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

[0002] The impact of meteorological data on regional power grid load is a complex and important issue. Considering 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 regional power grid load, existing technologies only unilaterally consider the impact of meteorology on power generation or the impact of meteorology on electricity consumption, and fail to conduct a comprehensive analysis of the two in a scientific and reasonable manner, resulting in an increased deviation in the results of meteorological data forecasting 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 technology.

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

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

[0007] 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;

[0008] 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;

[0009] Preliminary analysis module: used to obtain the natural power generation deviation coefficient corresponding to various types of meteorology in each power consumption period in 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;

[0010] 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;

[0011] 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.

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

[0013] 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;

[0014] 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.

[0015] Furthermore, the specific execution method 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, wherein 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 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;

[0018] 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.

[0019] Furthermore, the specific execution mode of the preliminary analysis module is as follows:

[0020] 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;

[0021] The wind power generation influence coefficient Wpg corresponding to various types of weather in the target area is calculated by the calculation formula i ;

[0022] The hydropower generation influence coefficient Hp corresponding to various types of meteorological conditions in the target area is calculated by the calculation formula i ;

[0023] The solar power generation impact coefficient Sp corresponding to various types of weather in the target area is calculated by the calculation formula i , where i represents the number of each type of meteorology.

[0024] Furthermore, 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 time period in the preliminary analysis module is as follows:

[0025] 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;

[0026] When there is sunlight, the natural power generation deviation coefficient Q of the target area corresponding to various types of weather in the sunlight period is calculated by formula 1. i ′;

[0027] When there is no sunlight, the natural power generation deviation coefficient Q corresponding to various types of weather in the target area during the no sunlight period is calculated by calculation formula 2. i ″, 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.

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

[0029] 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;

[0030] The meteorological data model includes meteorological data, population and GDP per capita;

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

[0032] 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;

[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, 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;

[0034] Extract the total power generation peak change rate corresponding to each natural power generation deviation coefficient stored in the database, and filter and obtain the total power generation peak change rate corresponding to each type of meteorology in each power consumption period in the target area according to the natural power generation deviation coefficient corresponding to each type of meteorology in the target area;

[0035] Furthermore, 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:

[0036] The power load warning coefficient A corresponding to each type of weather in each power consumption period in the target area is calculated by the calculation formula i～m , i~m represent the numbers of the power consumption time periods corresponding to various types of weather.

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

[0038] 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.

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

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

[0041] Acquire the basic power conditions 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 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.

[0043] Furthermore, the regional power grid load forecasting management method based on meteorological data also includes:

[0044] A comprehensive analysis is performed 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;

[0045] 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.

[0046] Compared with the prior art, the present invention has the following beneficial effects:

[0047] The present invention comprehensively analyzes the impact of various types of weather on the target area's power generation and power consumption, which is conducive to improving the accuracy and effectiveness of meteorological data on regional power grid load forecasting results, and further ensures the stable operation of the power supply system;

[0048] The present invention obtains the natural power generation deviation coefficient corresponding to each type of meteorological weather in 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 basic power information corresponding to the target area, and performs a comprehensive analysis in combination with 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 each type of meteorological weather in each power consumption time period in the target area. Through a scientific and effective analysis method, the accuracy of the regional power grid load prediction results of various meteorological data is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The present invention is further described using the accompanying drawings, but the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without creative work.

[0050] Figure 1 The present invention is a schematic diagram of the structure of a regional power grid load forecasting management system based on meteorological data according to an implementation example of the present invention.

[0051] Figure 2 The present invention is a flowchart of a method for regional power grid load forecasting and management based on meteorological data according to an implementation example of the present invention. DETAILED DESCRIPTION

[0052] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0053] See also Figure 1 , the present invention provides a regional power grid load forecasting and 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 early 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 early warning module, and the power grid load early warning module is connected to the comprehensive evaluation module;

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

[0056] 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;

[0057] 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.

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

[0059] Furthermore, the specific implementation 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, wherein 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 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;

[0062] 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.

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

[0064] Furthermore, the specific implementation 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, wherein 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 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;

[0067] 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.

[0068] The preliminary analysis module is used to obtain the natural power generation deviation coefficient corresponding to various types of meteorological conditions in each power consumption period in 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;

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

[0070] 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;

[0071] By calculating the formula

[0072]

[0073] Calculate the wind power generation influence coefficient Wpg corresponding to various weather conditions in the target area i ;

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

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

[0076] By calculating the formula

[0077]

[0078] Calculate the hydropower generation impact coefficient Hp of the target area corresponding to various types of meteorological conditions i ; It should be noted that: the smaller the difference between the rainfall and air temperature corresponding to each type of meteorological data in the formula and the corresponding standard rainfall and standard air temperature, the smaller the impact coefficient of hydropower generation corresponding to each type of meteorological data in the target area, which means that the impact of each type of meteorological data in the target area on hydropower generation is smaller;

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

[0080] By calculating the formula

[0081]

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

[0083] It should be noted that: the smaller the difference between the light intensity impact factor corresponding to each type of meteorological data in the formula and the corresponding standard light intensity, the smaller the solar power generation impact coefficient corresponding to each type of meteorological data in the target area, which means that the impact of each type of meteorological data in the target area on solar power generation is smaller;

[0084] It should be noted that the light intensity influencing factors corresponding to various meteorological data in the formula and the corresponding standard light intensity will not affect each other.

[0085] 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;

[0086] When there is light during the period, the formula 1 is used to calculate

[0087]

[0088] Calculate the natural power generation deviation coefficient Q of the target area corresponding to various types of weather during the illumination period i ′;

[0089] When there is no light, the formula 2 is used to calculate

[0090]

[0091] Calculate the natural power generation deviation coefficient Q of the target area corresponding to various weather conditions during the no-light period i ″, where β1 and β2 represent the preset first influencing factor of natural power generation deviation coefficient and the second influencing factor of natural power generation deviation coefficient respectively, and Q represents the total peak value of natural power generation in the target area under the 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;

[0092] 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 during various electricity consumption time periods is obtained.

[0093] The power grid load warning module is 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;

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

[0095] 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;

[0096] The meteorological data model includes meteorological data, population and GDP per capita;

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

[0098] 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;

[0099] 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;

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

[0101] By calculating the formula

[0102]

[0103] Calculate the power load warning coefficient A corresponding to each type of weather in the target area during each power consumption period i～m , where η i～m 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, μ i～m It is represented by the total power generation peak change rate corresponding to each type of meteorological condition in each power consumption time period in the target area, pec is represented by the peak power consumption in each power consumption time period in the target area under the standard environment, ψ is represented by the preset power load warning coefficient influencing factor, and i~m are represented by the numbers of each power consumption time period corresponding to each type of meteorological condition.

[0104] The comprehensive evaluation module is used to analyze and evaluate the power load warning coefficients corresponding to various types of meteorological conditions in the target area during various power consumption time periods, and obtain the power grid load forecast results corresponding to the target area.

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

[0106] 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.

[0107] See also Figure 2 To achieve the above purpose, the present invention also provides the following technical solution: a method for regional power grid load forecasting management based on meteorological data, comprising the following steps:

[0108] Acquire the meteorological conditions of the target area and obtain the meteorological data corresponding to each power consumption period in the target area;

[0109] Acquire 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 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 meteorological condition in each power consumption period in the target area is obtained;

[0111] A comprehensive analysis is performed 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;

[0112] 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.

[0113] The above are all preferred embodiments of the present application, and the protection scope of the present application is not limited thereto. Therefore, any equivalent changes made according to the structure, shape, and principle of the present application should be included in the protection scope of the present 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 each power consumption period in 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; 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; 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 data acquisition module is as follows: 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, 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. A regional power grid load forecasting and management system based on meteorological data according to claim 3, characterized in that: 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; The wind power generation influence coefficient Wpg corresponding to various types of weather in the target area is calculated by the calculation formula i ; The hydropower generation influence coefficient Hp corresponding to various types of meteorological conditions in the target area is calculated by the calculation formula i ; The solar power generation impact coefficient Sp corresponding to various types of weather in the target area is calculated by the calculation formula i , where i represents the number of each type of meteorology.

5. A regional power grid load forecasting and management system based on meteorological data according to claim 4, characterized in that: 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 sunlight, the natural power generation deviation coefficient Q of the target area corresponding to various types of weather in the sunlight period is calculated by formula 1. i ′; When there is no sunlight, the natural power generation deviation coefficient Q corresponding to various types of weather in the target area during the no sunlight period is calculated by calculation formula 2. i ″, 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.

6. A regional power grid load forecasting and management system based on meteorological data according to claim 5, 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.

7. A regional power grid load forecasting and management system based on meteorological data according to claim 6, characterized in that: 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: The power load warning coefficient A corresponding to each type of weather in each power consumption period in the target area is calculated by the calculation formula i～m , i~m represent the numbers of the power consumption time periods corresponding to various types of weather.

8. A regional power grid load forecasting and management system based on meteorological data according to claim 7, 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.

9. 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 8, 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.

10. A method for regional power grid load forecasting and management based on meteorological data according to claim 9, characterized in that: Also includes: Comprehensive analysis is performed 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; 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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