Multi-source intelligent power supply management system and method for meteorological observation instrument

Abstract

The invention relates to the technical field of meteorological observation instrument power supply, and discloses a multi-source intelligent power supply management system and method for a meteorological observation instrument, and the method comprises the steps: obtaining prediction information data which comprises weather prediction data and solar power supply prediction data; according to the prediction information data, analyzing and processing the prediction information data through a weather judgment strategy to form analysis data; according to the analysis data, judging and processing the analysis data through a data adjustment strategy to form an adjustment result; adjusting the power supply module according to the adjustment result; through a weather judgment strategy and a data adjustment strategy, the utilization rate and the power supply quality of a power supply system are effectively improved, and energy waste and cost expenditure are reduced; through comparison of historical prediction data and forecast data, optimization of a scheduling strategy and improvement of stability and reliability of a power supply system are facilitated; the efficiency and economical efficiency of a solar power supply system can be integrally improved, and sustainable energy can be better utilized.

Description

Technical Field

[0001] The present invention relates to the technical field of power supply for meteorological observation instruments, and in particular to a multi-source intelligent power supply management system and method for meteorological observation instruments. Background Art

[0002] The multi-source intelligent power supply of the meteorological observation instrument refers to the use of a variety of different energy sources to provide a stable and lasting power supply for the meteorological observation instrument, and the use of intelligent control technology to optimize the management of energy use. Multi-source intelligent power supply usually includes renewable energy such as solar energy, wind energy, geothermal energy, and traditional power grid power supply. By utilizing a variety of energy sources, the normal operation of the meteorological observation instrument can be guaranteed under different weather conditions, and the dependence on the traditional power grid can be reduced, the power supply cost can be reduced, and the energy utilization efficiency can be improved. The intelligent power supply system can automatically adjust the use and distribution of energy according to the real-time energy situation and the operating status of the equipment, ensure the continuous and stable operation of the meteorological observation instrument, and improve the energy utilization efficiency. Through the multi-source intelligent power supply system, the meteorological observation instrument can achieve a more reliable, environmentally friendly, and energy-saving power supply, and improve the accuracy and stability of the observation data.

[0003] The multi-source intelligent power supply system can also be combined with energy storage technologies, such as battery energy storage, supercapacitors, etc., to achieve energy storage and flexible scheduling, and further improve the reliability and stability of the system. The multi-source intelligent power supply system can also use intelligent control technology to achieve optimal energy distribution and management according to the working requirements and energy supply of the meteorological observation instrument, avoid energy waste and degradation, and ensure that the meteorological observation instrument can operate normally under various circumstances; the multi-source intelligent power supply system is of great significance to the power supply of the meteorological observation instrument, which can not only improve the stability and reliability of the system, but also reduce operating costs, reduce dependence on traditional energy, and promote sustainable energy development. By continuously optimizing and improving the multi-source intelligent power supply technology, the power needs of the meteorological observation instrument can be better met and the quality and reliability of meteorological observation data can be improved.

[0004] Most of the existing meteorological observation instruments are powered by solar energy as the main power supply mode, and are often affected by weather changes during use, which limits the use of the meteorological observation instruments and their practicality. Summary of the invention

[0005] The present invention provides a multi-source intelligent power supply management system and method for a meteorological observation instrument, which has the functions of determining whether a solar energy storage module can supply power normally by predicting weather conditions, making corresponding adjustments according to different weather conditions and energy demands; helping to optimize scheduling strategies and improve the stability and reliability of the power supply system; and improving the efficiency and economy of the solar power supply system as a whole, achieving the beneficial effect of better utilization of sustainable energy, and solving the problem mentioned in the above background technology that most of the existing meteorological observation instruments use solar power supply as the main power supply mode, and are often affected by weather changes when in use, thereby limiting the use of the meteorological observation instrument and limiting its practicality.

[0006] The present invention provides the following technical solution: a multi-source intelligent power supply management method for a meteorological observation instrument, comprising: Acquiring forecast information data, wherein the forecast information data includes weather forecast data and solar power supply forecast data; The weather forecast data includes weather conditions and change time data; The solar power supply prediction data includes solar power storage data and backup power storage data; According to the forecast information data, the forecast information data is analyzed and processed through the weather judgment strategy to form analysis data to analyze weather changes, thereby judging and processing the analysis data to determine whether solar energy can be continuously used for power supply production, and then regulating the power supply module; According to the analysis data, through the data adjustment strategy, the analysis data is judged and processed to form the adjustment result; Adjust the power supply module according to the adjustment result; The weather determination strategy is specifically as follows: Obtain solar power supply needs; The solar power supply demand includes the solar radiation intensity, which is recorded as the radiation demand; Set the radiation threshold range, recorded as (A1, A2), where A1 is the lowest value and A2 is the highest value; Obtain the predicted value of radiation intensity in the target area; determine the weather conditions based on the radiation threshold range; If the radiation prediction value of the target area is ≥ the radiation threshold A1, the weather in the time period corresponding to the radiation prediction value is determined to be the first target weather; If the radiation prediction value of the target area is less than the radiation threshold A1, the weather in the time period corresponding to the radiation prediction value is determined to be the second target weather.

[0007] As an optional solution of the multi-source intelligent power supply management method for a meteorological observation instrument described in the present invention, the data adjustment strategy is specifically: Obtain the change time data of the second target weather; The change time data includes the target start time point, target end time point and target change time length of the weather change; Get solar energy storage data; The solar energy storage data includes a first storage amount and a first power generation duration in the solar energy storage module; Get current time data; Calculate the first time difference, specifically: first time difference = target start time point - current time data; Preset the second storage capacity of the solar energy storage module; Get the second power generation duration; Calculate the third power generation duration, specifically: the third power generation duration = the first power generation duration + the second power generation duration; Calculate the solar energy maintenance time point, specifically: solar energy maintenance time point = current time data + third power generation duration; Compare the target end time point with the solar maintenance time point; If the target end time point ≤ the solar energy maintenance time point, no operation will be performed; If the target end time point is greater than the solar energy maintenance time point, the data adjustment strategy is executed.

[0008] As an optional solution of the multi-source intelligent power supply management method for a meteorological observation instrument described in the present invention, the data adjustment strategy is specifically: Obtain backup power storage data; The backup power storage data is a target first power storage amount and a first power storage duration of the backup power storage module; Calculate the first power storage maintenance time point, specifically: the first power storage maintenance time point = solar energy maintenance time point + first power storage duration; Comparing the target end time point with the first power storage maintenance time point; If the target end time point is ≤ the first power storage maintenance time point, the first change strategy is executed; If the target end time point is greater than the first power storage maintenance time point, the second change strategy is executed.

[0009] As an optional solution of the multi-source intelligent power supply management method for a meteorological observation instrument described in the present invention, the first change strategy specifically includes: Obtaining the battery capacity of the backup power storage module; Calculate the first power percentage, specifically: first power percentage = first power storage ÷ battery capacity; Get expected value; comparing the first stored amount with an expected value; If the first stored amount is ≥ the expected value, the backup power charging device is not charged; If the first stored power is less than the expected value, the expected value is regarded as the first charging value and the first charging strategy is executed; The second change strategy specifically includes: Calculate the first capacitance difference, specifically: first capacitance difference=battery capacity-first storage capacity; Preset the capacitance difference storage time; Calculate the second storage maintenance time, specifically: the second storage maintenance time = the first storage maintenance time point + the capacitance difference storage time; Comparing the target end time point with the second power storage maintenance time point; If the target end time point is less than or equal to the second storage maintenance time point, the expected value is regarded as the first charging value and the first charging strategy is executed; If the target end time point is greater than the first power storage maintenance time point, the first capacitance difference is regarded as the first charging value, and the first charging strategy is executed.

[0010] As an optional solution of the multi-source intelligent power supply management method for a meteorological observation instrument described in the present invention, the first charging strategy specifically includes: Get historical forecast data; The historical forecast data are the predicted second target weather days and the actual second target weather days; Calculate the forecast data ratio, specifically: forecast data ratio = actual second target weather days ÷ predicted second target weather days; Preset a first prediction rate and a second prediction rate; If the forecast data ratio ≥ the first forecast rate, the first electricity price strategy is implemented; If the first prediction rate > forecast data ratio > second prediction rate; Preset judgment threshold percentage; Calculate the second capacitance difference, specifically: second capacitance difference=first capacitance difference×determination threshold percentage; recognizing the second capacitance difference as the first charging value and executing the first electricity price strategy; If the second prediction rate ≥ the forecast data ratio, the planning strategy is executed.

[0011] As an optional solution of the multi-source intelligent power supply management method for a meteorological observation instrument described in the present invention, the first electricity price strategy is specifically: Obtaining a first charging duration, where the first charging duration is the duration required to charge the backup power storage module from a first storage value to a first charging value; Obtain electricity prices, recorded as the first electricity price and the second electricity price, and the first electricity price < the second electricity price; Obtaining time periods corresponding to the first electricity price and the second electricity price, and defining them as the first electricity segment and the second electricity segment; Set duration threshold; Comparing the first power replenishment duration with the duration threshold; If the first power supplement duration is ≤ the duration threshold, the first electricity price strategy is executed; The first electricity price strategy specifically includes: Calculate the first power supplement start time point, specifically: first power supplement start time point = target start time point - first power supplement duration; Charging the backup power storage module according to the first power replenishment start time point until the backup power storage module reaches the first charging value, and performing a planning strategy; If the first power supplement duration is greater than the duration threshold, the second electricity price strategy is executed.

[0012] As an optional solution of the multi-source intelligent power supply management method for a meteorological observation instrument described in the present invention, the second electricity price strategy specifically includes: Obtaining all first electrical segments contained in the first time difference; Compare the time distance values ​​of all the first electrical segments and the target start time point, and sort them in order from small to large according to the values ​​to form the first segment set A, recorded as A1...An; Calculate all durations in the first segment set A, and record them as the first pre-charge duration; Comparing the first pre-charging time and the first charging time; If the first pre-charging time is greater than or equal to the first charging time, the first charging segment in the first set of segments A is selected for charging until the backup power storage module reaches the first charging value, and then the planning strategy is performed; If the first pre-charging duration is less than the first charging duration, the first charging duration is charged according to the time period of the first segment set A; Calculate the remaining charging time, specifically: remaining charging time = first charging time - first pre-charging time; Obtaining all second electrical segments contained in the first time difference; Compare the time distance values ​​of all the second electrical segments with the target start time point, and sort them in order from small to large according to the values ​​to form a second segment set B, recorded as B1...Bn; Select the second power segment with a higher ranking in the second set segment B, match the remaining charging time, and charge until the backup power storage module reaches the first charging value, and then perform the planning strategy.

[0013] As an optional solution of the multi-source intelligent power supply management method for a meteorological observation instrument described in the present invention, the planning strategy is specifically: Get the actual weather conditions at the target start time; If the actual weather condition is the second target weather condition, the solar energy storage data is obtained, and when the amount of electricity in the solar energy storage module cannot sustain power generation, the backup energy storage module is replaced to generate electricity; If the actual weather condition is the first target weather condition, the backup power storage module data is obtained; Obtaining a first power percentage of the backup power storage module; Preset power percentage threshold; Calculate the fixed threshold power, specifically: fixed threshold power = battery capacity × power percentage threshold; The backup power storage module is replaced to generate electricity until the first power in the backup power storage module is used up to a fixed threshold power, and then the solar power storage module is replaced to generate electricity.

[0014] As an optional solution of the multi-source intelligent power supply management system method for a meteorological observation instrument described in the present invention, wherein: the acquisition module is used to obtain prediction information data, and the prediction information data includes weather prediction data and solar power supply prediction data; Analysis module: used to analyze and process the forecast information data according to the forecast information data and the weather determination strategy to form analysis data to analyze weather changes; Adjustment module: used to determine and process the analysis data according to the analysis data and the data adjustment strategy, form the adjustment result, and adjust the power supply module; Solar power supply module: used to provide power by receiving solar radiation; Backup power storage module: used for storing backup power.

[0015] The present invention has the following beneficial effects: 1. A multi-source intelligent power supply management system and method for a meteorological observation instrument determines whether the solar energy storage module can supply power normally by predicting weather conditions, and makes corresponding adjustments according to different weather conditions and energy demands; through weather judgment strategies and data adjustment strategies, the utilization rate and power supply quality of the power supply system can be effectively improved, and energy waste and cost expenditure can be reduced; at the same time, by comparing historical prediction data with forecast data, it can help optimize the scheduling strategy and improve the stability and reliability of the power supply system; as a whole, it can improve the efficiency and economy of the solar power supply system and achieve better utilization of sustainable energy.

[0016] 2. This multi-source intelligent power supply management system and method for meteorological observation instruments, when it is necessary to charge the backup power storage module, selects the most economical and effective charging plan by comparing different electricity price periods and charging durations to ensure that the backup power storage module has sufficient power supply when needed; at the same time, by reasonably managing the charging and use of the backup power storage module, the power supply capacity and reserve capacity of the system can be improved to cope with sudden power supply needs and weather changes.

[0017] 3. A multi-source intelligent power supply management system and method for a meteorological observation instrument determines whether the weather conditions meet the power generation needs of the solar power supply module by determining the solar radiation intensity value. If the weather conditions meet the power generation needs of the solar power supply module, the solar power supply module continues to be used for power generation; if the weather conditions cannot meet the power generation needs of the solar power supply module, the power generation module is adjusted; by obtaining the transition time of the weather conditions, an adjustment strategy for the power supply module is formed more accurately; by estimating the power generation time of the solar energy storage module, the use time of replacing the standby energy storage module is calculated, thereby optimizing the utilization rate and power supply quality of the power supply system and reducing energy waste and cost expenditure.

[0018] 4. This multi-source intelligent power supply management system and method for meteorological observation instruments makes the power supply management more personalized by setting expected values ​​and replenishing power to the backup power storage module according to the expected values; by determining the forecast accuracy, the charging power is more reasonably optimized, and when the forecast accuracy is low, a planning strategy is implemented to reasonably manage the charging and use of the backup power storage module, which can improve the power supply and reserve capacity of the system and respond to sudden power supply needs and weather changes. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 The present invention is a block diagram of a multi-source intelligent power supply management system and method for a meteorological observation instrument. DETAILED DESCRIPTION

[0020] 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.

[0021] Example 1, see Figure 1 , a multi-source intelligent power supply management system and method for a meteorological observation instrument, comprising: obtaining forecast information data, the forecast information data comprising weather forecast data and solar power supply forecast data; the weather forecast data comprising weather conditions and change time data; The solar power supply prediction data includes solar power storage data and backup power storage data; based on the prediction information data, the prediction information data is analyzed and processed through the weather judgment strategy to form analysis data, so as to analyze weather changes, thereby determining and processing the analysis data to determine whether solar energy can be continuously used for power supply production, and then regulating the power supply module; based on the analysis data, the analysis data is determined and processed through the data adjustment strategy to form an adjustment result; based on the adjustment result, the power supply module is adjusted.

[0022] The weather determination strategy is specifically as follows: obtaining the solar power supply demand; the solar power supply demand includes the solar radiation intensity, which is recorded as the radiation demand; setting the radiation threshold range, which is recorded as (A1, A2), where A1 is the lowest value and A2 is the highest value; obtaining the radiation intensity prediction value of the target area; where the radiation intensity prediction of the target area is the predicted value of the solar radiation intensity.

[0023] The weather conditions are determined according to the radiation threshold range; if the radiation prediction value of the target area is ≥ the radiation threshold A1, the weather in the time period corresponding to the radiation prediction value is determined to be the first target weather; the first target weather is: when the weather is clear, the solar radiation intensity is high, and the solar power supply demand is met. If the radiation prediction value of the target area is < the radiation threshold A1, the weather in the time period corresponding to the radiation prediction value is determined to be the second target weather, and the second target weather is: when the weather is cloudy and rainy, the solar radiation intensity is low, and the solar power supply demand cannot be met.

[0024] The data adjustment strategy is specifically as follows: obtaining the change time data of the second target weather; the change time data includes the target start time point, target end time point and target change time length of the weather change; the target start time point is the time point when the weather condition changes to the second target weather; the target change time length is the length of time the second target weather lasts.

[0025] Acquire solar energy storage data; the solar energy storage data includes a first storage capacity and a first power generation duration in the solar energy storage module; the first storage capacity is the existing storage capacity in the solar energy storage module; the first power generation duration is the first storage capacity of the solar energy storage module to maintain power generation.

[0026] Get the current time data, which is the current time point; calculate the first time difference, specifically: first time difference = target start time point - current time data, the first time difference is the time distance between the current time point and the second target weather change start time point.

[0027] Preset a second storage capacity of the solar energy storage module, the second storage capacity is the amount of electricity that the solar module can store under the first time difference; obtain a second power generation duration, the second power generation duration is the usage time of the second storage capacity of the solar energy storage module to maintain power generation; calculate a third power generation duration, specifically: the third power generation duration = the first power generation duration + the second power generation duration, the third power generation duration is the estimated total power generation duration of the solar energy storage module.

[0028] Calculate the solar energy maintenance time point, specifically: solar energy maintenance time point = current time data + third power generation duration; compare the target end time point with the solar energy maintenance time point to determine whether the power of the solar energy storage module can support until the end of the second target weather.

[0029] If the target end time point is ≤ the solar energy maintenance time point, no operation is performed; if the target end time point is > the solar energy maintenance time point, the data adjustment strategy is executed.

[0030] The data adjustment strategy is specifically as follows: Obtain backup power storage data; the backup power storage data is the target first power storage amount and the first storage duration of the backup power storage module, the first power storage amount is the existing power in the backup power storage module; the first storage duration is the usage time of the first power storage amount of the backup power module to maintain power generation.

[0031] Calculate the first power storage maintenance time point, specifically: the first power storage maintenance time point = solar energy maintenance time point + first power storage duration; compare the target end time point with the first power storage maintenance time point to determine whether the existing power of the backup power storage module can support until the end of the second target weather.

[0032] If the target end time point is ≤ the first power storage maintenance time point, the first change strategy is executed; if the target end time point is > the first power storage maintenance time point, the second change strategy is executed.

[0033] The first change strategy specifically includes: obtaining the battery capacity of the backup power storage module; setting an expected value, that is, how much battery power the user expects when using the backup power; calculating the first power ratio, specifically: first power ratio = first storage power ÷ battery capacity; obtaining the expected value, that is, the battery power the user expects when using the backup power.

[0034] Compare the first power storage amount with the expected value; if the first power storage amount ≥ the expected value, do not charge the backup power charging device; if the first power storage amount < the expected value, regard the expected value as the first charging value, and execute the first charging strategy; the second change strategy specifically includes: calculating the first capacitance difference, specifically: the first capacitance difference = battery capacity - the first power storage amount.

[0035] The preset capacitance difference storage time is specifically the time that the backup power storage module can generate electricity under the first capacitance difference; the second storage maintenance time is calculated, specifically: the second storage maintenance time = the first storage maintenance time point + the capacitance difference storage time; and the target end time point is compared with the second storage maintenance time point.

[0036] If the target end time point is less than or equal to the second storage maintenance time point, the expected value is regarded as the first charging value and the first charging strategy is executed; If the target end time point is greater than the first power storage maintenance time point, the first capacitance difference is regarded as the first charging value, and the first charging strategy is executed.

[0037] The first charging strategy specifically includes: Obtain historical forecast data; historical forecast data is the predicted second target weather days and the actual second target weather days; calculate the forecast data ratio, specifically: forecast data ratio = actual second target weather days ÷ predicted second target weather days.

[0038] Preset a first prediction rate and a second prediction rate; if the forecast data ratio ≥ the first prediction rate, execute the first electricity price strategy; if the first prediction rate>forecast data ratio>second prediction rate; preset a determination threshold percentage; calculate the second capacitance difference, specifically: second capacitance difference=first capacitance difference×determination threshold percentage; recognize the second capacitance difference as the first charging value, and execute the first electricity price strategy; if the second prediction rate ≥the forecast data ratio, execute the planning strategy.

[0039] The above scheme determines whether the solar energy storage module can supply power normally by predicting weather conditions, and makes corresponding adjustments according to different weather conditions and energy demands; through weather judgment strategies and data adjustment strategies, the utilization rate and power supply quality of the power supply system can be effectively improved, and energy waste and cost expenditure can be reduced; at the same time, by comparing historical prediction data with forecast data, it can help optimize the scheduling strategy and improve the stability and reliability of the power supply system; as a whole, it can improve the efficiency and economy of the solar power supply system and achieve better utilization of sustainable energy.

[0040] Example 2, see Figure 1 This embodiment is an improvement made on the basis of the first embodiment, wherein the first electricity price strategy is specifically as follows: obtaining a first power replenishment duration, which is the duration required to charge the backup power storage module from the first storage value to the first charging value; obtaining an electricity price, which is recorded as the first electricity price and the second electricity price, and the first electricity price < the second electricity price; obtaining a time period corresponding to the first electricity price and the second electricity price, which is defined as the first electricity segment and the second electricity segment.

[0041] Setting a duration threshold for determining the shortest charging time; comparing the first charging duration with the duration threshold; If the first power supplement duration is ≤ the duration threshold, the first electricity price strategy is executed.

[0042] The first electricity price strategy specifically includes: calculating the first power supplement start time point, specifically: the first power supplement start time point = the target start time point - the first power supplement duration; charging the backup power storage module according to the first power supplement start time point until the backup power storage module reaches the first charging value, and then performing a planning strategy.

[0043] If the first charging time is greater than the time threshold, the second electricity price strategy is executed. Specifically, if the charging time is long, the charging time is calculated, and the most favorable charging time plan is calculated based on the electricity price.

[0044] The second electricity price strategy specifically includes: obtaining all first electricity segments contained in the first time difference; comparing the time distance values ​​of all first electricity segments and the target start time point, and sorting them in order from small to large according to the values ​​to form a first segment set A, recorded as A1...An.

[0045] Calculate all the durations in the first segment set A, recorded as the first pre-charging duration; compare the first pre-charging duration and the first charging duration; if the first pre-charging duration ≥ the first charging duration, select the first charging segment with a higher ranking in the first set segment A for charging until the backup power storage module reaches the first charging value, and then perform the planning strategy.

[0046] If the first pre-charging time is less than the first charging time, the first charging time is charged according to the time period of the first segment set A; the remaining charging time is calculated, specifically: the remaining charging time = the first charging time - the first pre-charging time; all the second charging segments contained in the first time difference are obtained; the time distance values ​​of all the second charging segments and the target start time points are compared, and they are sorted in order from small to large according to the values ​​to form a second segment set B, recorded as B1...Bn; the second charging segment with a higher sorting in the second set segment B is selected to match the remaining charging time, and charging is performed until the backup power storage module is charged to the first charging value, and the planning strategy is performed.

[0047] The planning strategy is specifically as follows: obtaining the actual weather conditions at the target start time; if the actual weather conditions are the second target weather, obtaining the solar energy storage data, and when the power in the solar energy storage module cannot maintain power generation, replacing the backup power storage module for power generation; if the actual weather conditions are the first target weather, obtaining the backup power storage module data.

[0048] Obtain a first power percentage of the backup power storage module; preset a power percentage threshold; calculate a fixed threshold power, specifically: fixed threshold power = battery capacity × power percentage threshold; replace the backup power storage module to generate electricity until the first power in the backup power storage module is used up to the fixed threshold power, and then replace the solar power storage module to generate electricity.

[0049] Acquisition module: used to obtain forecast information data, including weather forecast data and solar power supply forecast data; Analysis module: used to analyze and process the forecast information data according to the forecast information data and the weather determination strategy to form analysis data to analyze weather changes; Adjustment module: used to determine and process the analysis data according to the analysis data and the data adjustment strategy, form the adjustment result, and adjust the power supply module; Solar power supply module: used to provide power by receiving solar radiation; Backup power storage module: used for storing backup power.

[0050] In this embodiment, when the backup power storage module needs to be charged, the most economical and effective charging plan is selected by comparing different electricity price periods and charging durations to ensure that the backup power storage module has sufficient power supply when needed; at the same time, by reasonably managing the charging and use of the backup power storage module, the power supply capacity and reserve capacity of the system can be improved to cope with sudden power supply needs and weather changes.

[0051] The electronic device in the embodiments of the present disclosure may include, but is not limited to, mobile terminals such as laptop computers, PADs (tablet computers), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), and the like, as well as fixed terminals.

[0052] An electronic device may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) or a program loaded from a storage device into a random access memory (RAM). In the RAM, various programs and data required for the operation of the electronic device are also stored. The processing device, ROM, and RAM are connected to each other via a bus. An input / output (I / O) interface is also connected to the bus.

[0053] Typically, the following devices may be connected to the I / O interface: input devices including, for example, a touch screen, a touch pad, an image sensor, a microphone, etc.; output devices including, for example, a liquid crystal display (LCD), a speaker, etc.; storage devices including, for example, a magnetic tape, a hard disk, etc.; and communication devices. The communication devices may allow the electronic device to communicate with other devices wirelessly or by wire to exchange data.

[0054] The embodiment of the present disclosure also provides a non-transitory computer-readable storage medium, which stores computer instructions, and the computer instructions are used to enable the computer to execute a multi-source intelligent power supply management system and method for a meteorological observation instrument in the aforementioned method embodiment.

[0055] It should be noted that more specific examples of computer-readable storage media may include portable computer disks, hard disks, erasable programmable read-only memories (EPROMs or flash memories), optical storage devices, magnetic storage devices, or any suitable combination thereof. In the present disclosure, computer-readable storage media may be any tangible medium that contains or stores a program, which may be used by or in combination with an instruction execution system, apparatus, or device, and the computer-readable medium may be contained in the electronic device; or it may exist independently without being assembled into the electronic device.

[0056] The computer-readable medium carries one or more programs. When the one or more programs are executed by the electronic device, the electronic device can implement the solution provided by the method embodiment.

[0057] Computer program code for performing operations of the present disclosure may be written in one or more programming languages ​​or a combination thereof, and may be executed entirely on a user's computer, partially on a user's computer, as a separate software package, partially on a user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0058] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0059] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A multi-source intelligent power supply management method for a meteorological observation instrument, characterized in that: include: Acquiring forecast information data, wherein the forecast information data includes weather forecast data and solar power supply forecast data; The weather forecast data includes weather conditions and change time data; The solar power supply prediction data includes solar power storage data and backup power storage data; According to the forecast information data, the forecast information data is analyzed and processed through the weather judgment strategy to form analysis data to analyze weather changes, thereby judging and processing the analysis data to determine whether solar energy can be continuously used for power supply production, and then regulating the power supply module; According to the analysis data, through the data adjustment strategy, the analysis data is judged and processed to form the adjustment result; Adjust the power supply module according to the adjustment result; The weather determination strategy is specifically as follows: Obtain solar power supply needs; The solar power supply demand includes the solar radiation intensity, which is recorded as the radiation demand; Set the radiation threshold range, recorded as (A1, A2), where A1 is the lowest value and A2 is the highest value; Obtain the predicted value of radiation intensity in the target area; determine the weather conditions based on the radiation threshold range; If the radiation prediction value of the target area is ≥ the radiation threshold A1, the weather in the time period corresponding to the radiation prediction value is determined to be the first target weather; If the radiation prediction value of the target area is less than the radiation threshold A1, the weather in the time period corresponding to the radiation prediction value is determined to be the second target weather.

2. The multi-source intelligent power supply management method for a meteorological observation instrument according to claim 1, characterized in that: The data adjustment strategy is specifically as follows: Obtain the change time data of the second target weather; The change time data includes the target start time point, target end time point and target change time length of the weather change; Get solar energy storage data; The solar energy storage data includes a first storage amount and a first power generation duration in the solar energy storage module; Get current time data; Calculate the first time difference, specifically: first time difference = target start time point - current time data; Preset the second storage capacity of the solar energy storage module; Get the second power generation duration; Calculate the third power generation duration, specifically: the third power generation duration = the first power generation duration + the second power generation duration; Calculate the solar energy maintenance time point, specifically: solar energy maintenance time point = current time data + third power generation duration; Compare the target end time point with the solar maintenance time point; If the target end time point ≤ the solar energy maintenance time point, no operation will be performed; If the target end time point is greater than the solar energy maintenance time point, the data adjustment strategy is executed.

3. The multi-source intelligent power supply management method for a meteorological observation instrument according to claim 2 is characterized in that: The data adjustment strategy is specifically as follows: Obtain backup power storage data; The backup power storage data is a target first power storage amount and a first power storage duration of the backup power storage module; Calculate the first power storage maintenance time point, specifically: the first power storage maintenance time point = solar energy maintenance time point + first power storage duration; Comparing the target end time point with the first power storage maintenance time point; If the target end time point is ≤ the first power storage maintenance time point, the first change strategy is executed; If the target end time point is greater than the first power storage maintenance time point, the second change strategy is executed.

4. The multi-source intelligent power supply management method for a meteorological observation instrument according to claim 3 is characterized in that: The first change strategy specifically includes: Obtaining the battery capacity of the backup power storage module; Calculate the first power percentage, specifically: first power percentage = first power storage ÷ battery capacity; Get expected value; comparing the first stored amount with an expected value; If the first stored amount is ≥ the expected value, the backup power charging device is not charged; If the first stored power is less than the expected value, the expected value is regarded as the first charging value and the first charging strategy is executed; The second change strategy specifically includes: Calculate the first capacitance difference, specifically: first capacitance difference=battery capacity-first storage capacity; Preset the capacitance difference storage time; Calculate the second storage maintenance time, specifically: the second storage maintenance time = the first storage maintenance time point + the capacitance difference storage time; Comparing the target end time point with the second power storage maintenance time point; If the target end time point is less than or equal to the second storage maintenance time point, the expected value is regarded as the first charging value and the first charging strategy is executed; If the target end time point is greater than the first power storage maintenance time point, the first capacitance difference is regarded as the first charging value, and the first charging strategy is executed.

5. The multi-source intelligent power supply management method for a meteorological observation instrument according to claim 4 is characterized in that: The first charging strategy specifically includes: Get historical forecast data; The historical forecast data are the predicted second target weather days and the actual second target weather days; Calculate the forecast data ratio, specifically: forecast data ratio = actual second target weather days ÷ predicted second target weather days; Preset a first prediction rate and a second prediction rate; If the forecast data ratio is ≥ the first forecast rate, the first electricity price strategy is implemented; If the first prediction rate > forecast data ratio > second prediction rate; Preset judgment threshold percentage; Calculate the second capacitance difference, specifically: second capacitance difference=first capacitance difference×determination threshold percentage; recognizing the second capacitance difference as the first charging value and executing the first electricity price strategy; If the second prediction rate ≥ the forecast data ratio, the planning strategy is executed.

6. The multi-source intelligent power supply management method for a meteorological observation instrument according to claim 5, characterized in that: The first electricity price strategy is specifically: Obtaining a first charging duration, where the first charging duration is the duration required to charge the backup power storage module from a first storage value to a first charging value; Obtain electricity prices, recorded as the first electricity price and the second electricity price, and the first electricity price < the second electricity price; Obtaining time periods corresponding to the first electricity price and the second electricity price, and defining them as the first electricity segment and the second electricity segment; Set duration threshold; Comparing the first power replenishment duration with the duration threshold; If the first power supplement duration is ≤ the duration threshold, the first electricity price strategy is executed; The first electricity price strategy specifically includes: Calculate the first power supplement start time point, specifically: first power supplement start time point = target start time point - first power supplement duration; Charging the backup power storage module according to the first power replenishment start time point until the backup power storage module reaches the first charging value, and performing a planning strategy; If the first power supplement duration is greater than the duration threshold, the second electricity price strategy is executed.

7. A multi-source intelligent power supply management system and method for a meteorological observation instrument according to claim 6, characterized in that: The second electricity price strategy specifically includes: Obtaining all first electrical segments contained in the first time difference; Compare the time distance values ​​of all the first electrical segments and the target start time point, and sort them in order from small to large according to the values ​​to form the first segment set A, recorded as A1...An; Calculate all durations in the first segment set A, and record them as the first pre-charge duration; Comparing the first pre-charging time and the first charging time; If the first pre-charging time is greater than or equal to the first charging time, the first charging segment in the first set of segments A is selected for charging until the backup power storage module reaches the first charging value, and then the planning strategy is performed; If the first pre-charging duration is less than the first charging duration, the first charging duration is charged according to the time period of the first segment set A; Calculate the remaining charging time, specifically: remaining charging time = first charging time - first pre-charging time; Obtaining all second electrical segments contained in the first time difference; Compare the time distance values ​​of all the second electrical segments with the target start time point, and sort them in order from small to large according to the values ​​to form a second segment set B, recorded as B1...Bn; Select the second power segment with a higher ranking in the second set segment B, match the remaining charging time, and charge until the backup power storage module reaches the first charging value, and then perform the planning strategy.

8. A multi-source intelligent power supply management system and method for a meteorological observation instrument according to claim 7, characterized in that: The planning strategy is specifically as follows: Get the actual weather conditions at the target start time; If the actual weather condition is the second target weather condition, the solar energy storage data is obtained, and when the amount of electricity in the solar energy storage module cannot sustain power generation, the backup energy storage module is replaced to generate electricity; If the actual weather condition is the first target weather condition, the backup power storage module data is obtained; Obtaining a first power percentage of the backup power storage module; Preset power percentage threshold; Calculate the fixed threshold power, specifically: fixed threshold power = battery capacity × power percentage threshold; The backup power storage module is replaced to generate electricity until the first power in the backup power storage module is used up to a fixed threshold power, and then the solar power storage module is replaced to generate electricity.

9. A system for executing the multi-source intelligent power supply management method for a meteorological observation instrument according to claim 1, characterized in that: Acquisition module: used to obtain forecast information data, the forecast information data includes weather forecast data and solar power supply forecast data; Analysis module: used to analyze and process the forecast information data according to the forecast information data and the weather determination strategy to form analysis data to analyze weather changes; Adjustment module: used to determine and process the analysis data according to the analysis data and the data adjustment strategy, form the adjustment result, and adjust the power supply module; Solar power supply module: used to provide power by receiving solar radiation; Backup power storage module: used for storing backup power.

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