Irrigation and fertilization management method and system based on photovoltaic driving

Abstract

The invention relates to the technical field of agricultural management systems, and discloses an irrigation and fertilization management method and system based on photovoltaic driving, and the system comprises an execution unit and a processing unit. The execution unit comprises a photovoltaic energy storage module, a water taking module, a spraying module and a chemical adding module; the processing unit comprises an acquisition module which is configured to acquire the illumination intensity, the residual electric quantity stored by the energy storage device and the corresponding acquisition time; the storage database stores initial irrigation and fertilization strategies of different crops; the prediction module is configured to calculate natural power consumption and predicted remaining power, compare the predicted remaining power with the corresponding total power consumption and judge whether the initial irrigation and fertilization strategy is adjusted or not; the adjusting module is configured to adjust the initial irrigation and fertilization strategy; and the early warning module is configured to judge whether a system shutdown early warning is sent out or not. According to the system, when the electric quantity is insufficient, the strategy can be intelligently regulated and controlled, and irrigation and fertilization tasks can be completed.

Description

Technical Field

[0001] The present invention relates to the technical field of agricultural management systems, and in particular to an irrigation and fertilization management method and system based on photovoltaic drive. Background Art

[0002] As the world pays more and more attention to sustainable agricultural development, modern agriculture is gradually developing towards automation and intelligence. In this context, photovoltaic-driven irrigation and fertilization management systems have emerged, aiming to provide power for agricultural irrigation and fertilization through clean and renewable solar energy, thereby overcoming dependence on municipal power supply and improving energy utilization.

[0003] However, in practical applications, systems based on photovoltaic power generation face some technical problems, especially photovoltaic power generation cannot always stably support irrigation or fertilization strategies, affecting the stability and reliability of the system. Specifically, the output power of the photovoltaic power generation system depends on the light intensity, which is greatly affected by the weather, season and sunshine time. In rainy weather, cloud cover or short sunshine time, solar power generation may drop significantly, which will cause the battery energy storage system to be unable to charge in time, or the stored power is insufficient to support the continuous operation of the system. At this time, if the original irrigation or fertilization strategy is not adjusted, especially when agricultural equipment that requires high power support (such as water pumps, sprinklers, etc.) is running, the lack of photovoltaic power may directly cause the system to shut down or fail to complete the irrigation and fertilization tasks as planned.

[0004] In view of the above problems, it is particularly important to design an intelligent photovoltaic-driven irrigation and fertilization management method or system. Summary of the invention

[0005] In view of this, the present invention proposes a photovoltaic-driven irrigation and fertilization management method and system, aiming to solve the problem in the current technology that when the photovoltaic-driven irrigation and fertilization management method or system is insufficient in power, the system may shut down or fail to complete the irrigation and fertilization tasks as planned due to the lack of intelligent control strategies.

[0006] On the one hand, the present invention proposes a photovoltaic-driven irrigation and fertilization management system, comprising an execution unit and a processing unit; The execution unit comprises: A photovoltaic energy storage module is provided with a photovoltaic panel and an energy storage device, wherein the photovoltaic energy storage module is configured to convert solar energy into electrical energy through the photovoltaic panel and store or provide electrical energy through the energy storage device; A water intake module is configured to extract water from a source through a water pump; A spraying module, provided with a lifting pole and a spray head mounted on the lifting pole, the spraying module is connected to the water intake module, and the spraying module is configured to perform a spraying operation; A dosing module is provided with a control valve and a flow sensor for controlling the start and stop of the dosing process, the dosing module is connected to the spray head, and the dosing module is configured to deliver medicine or fertilizer to the spraying module; The processing unit comprises: A collection module, configured to obtain light intensity, the remaining power stored in the energy storage device and the corresponding acquisition time; A storage database storing initial fertigation strategies for different crops, wherein the storage database is further configured to store the remaining power, light intensity and acquisition time as first historical data, and store the total irrigation water volume, total fertilizer volume and total power consumption for each fertigation in the initial fertigation strategy as second historical data; a prediction module configured to determine the type of crop and obtain the initial fertigation strategy for the crop, calculate the natural power consumption and predicted remaining power of the energy storage device from the current time to a preset time point according to the first historical data, compare the predicted remaining power with the corresponding total power consumption, and determine whether the initial fertigation strategy is adjusted; The adjustment module is configured to calculate the difference between the total power consumption and the predicted remaining power when adjusting the initial fertigation strategy, and record it as the power gap; adjust the initial fertigation strategy according to the power gap, and at the same time, determine whether to issue a system shutdown warning.

[0007] Further, when the natural power consumption of the energy storage device from the current time to the preset time point is calculated according to the first historical data, it includes: The light intensity is obtained and compared with the minimum light intensity for the photovoltaic panel to generate electricity. When the light intensity is less than or equal to the minimum light intensity, n groups of the first historical data are intercepted; when the light intensity is greater than the minimum light intensity, interception is stopped, and the first natural power consumption is calculated based on the intercepted first historical data, and the calculation is repeated to obtain x groups of natural power consumption data; The natural power consumption satisfies the following relationship: ; ; in, represents the i-th natural power consumption, i is a positive integer; n represents the number of groups of the first historical data intercepted when the light intensity is less than or equal to the minimum light intensity; Indicates the remaining power of the i-th group of the first historical data; represents the acquisition time of the first historical data of the i-th group; represents natural power consumption; k represents a floating coefficient, k is (1,1.1]; x represents the number of repeated calculations.

[0008] Further, when the predicted remaining power of the energy storage device from the current time to the preset time point is calculated according to the first historical data, it also includes: The predicted remaining power satisfies the following relationship: ; in, Indicates the estimated remaining power. Indicates the current time point. Indicates a preset time point.

[0009] Furthermore, when the predicted remaining power is compared with the corresponding total power consumption to determine whether the initial fertigation strategy is to be adjusted, it includes: If the predicted remaining power is greater than the total power consumption, it is determined that the initial fertigation strategy does not need to be adjusted; If the predicted remaining power is less than or equal to the total power consumption, the stored power of the energy storage device from the current time to the preset time point is predicted based on the light intensity; when the sum of the predicted remaining power and the stored power is greater than the total power consumption, it is determined that the initial fertilization strategy does not need to be adjusted; when the sum of the predicted remaining power and the stored power is lower than or equal to the total power consumption, it is determined that the initial fertilization strategy needs to be adjusted.

[0010] Furthermore, the stored electrical energy is obtained by the following method: ; in, represents the stored electric energy from time t to the preset time point, represents the light intensity at time t, represents the area of ​​the photovoltaic panel, represents the conversion efficiency of the photovoltaic panel, represents the charging efficiency of the energy storage device, represents the maximum capacity of the energy storage device, It means taking the smaller value of a and b. represents the security factor, Take [0.8,1).

[0011] Furthermore, when the initial fertigation strategy is adjusted according to the power shortage, it includes: Obtain the power gap and the predicted light intensity after a preset time point, obtain the predicted daily stored electric energy based on the predicted light intensity, and determine whether to divide the initial fertilization strategy completed at one time into several batches based on the power gap and the predicted daily stored electric energy, and determine the number of batches when it is determined that division is required; The daily detection period of stored electric energy is 24 hours.

[0012] Further, based on the power gap and the predicted daily stored power, determining whether to divide the initial fertigation strategy completed once into several batches and determining the number of batches when it is determined that division is required includes: S1: Compare the current power gap with the predicted daily stored power. When the predicted daily stored power is greater than or equal to the power gap, do not divide the initial irrigation and fertilization strategy. When the predicted daily stored power is less than the power gap, calculate the difference between the power gap and the daily stored power and record it as the Yth power difference, and obtain the daily stored power again. S2: Compare the daily stored electric energy with the Yth electric energy difference. When the daily stored electric energy is greater than or equal to the Yth electric energy difference, determine to divide the batches into Y+1 times; when the daily stored electric energy is less than the Yth electric energy difference, obtain the daily stored electric energy again and repeat step S2 until the daily stored electric energy is greater than or equal to the Yth electric energy difference.

[0013] Furthermore, when the initial fertigation strategy is adjusted according to the power shortage, it also includes: Determine the time point of irrigation and fertilization according to the predicted light intensity; The predicted light intensity and the corresponding predicted time are obtained, and a predicted light intensity-predicted time curve is established. When the slope of the predicted light intensity-predicted time curve is greater than zero, the predicted time is used as the time point for irrigation and fertilization.

[0014] Furthermore, the processing unit further includes: The early warning module is configured to send out an early warning signal when the number of repetitions of step S2 is greater than 7.

[0015] Compared with the prior art, the present invention has the following beneficial effects: By introducing intelligent control strategies, the system can adjust the irrigation and fertilization strategies in real time according to the actual situation of photovoltaic power generation, ensuring that the system can flexibly respond and continue to operate in the case of insufficient power, avoiding downtime caused by insufficient power. The volatility of photovoltaic power generation is a challenge for traditional photovoltaic-driven systems. Through the intelligent adjustment mechanism of the invention, the system can monitor the light intensity and energy storage status in real time, and dynamically adjust the irrigation and fertilization strategies, thereby effectively solving the impact of photovoltaic power generation fluctuations on the completion of irrigation and fertilization tasks. By calculating natural power consumption, predicting the remaining power, and comparing the total power consumption with the predicted remaining power, the system can evaluate in advance whether it is necessary to adjust the irrigation and fertilization strategy to ensure efficient use of energy. At the same time, the system reasonably allocates and utilizes limited power resources by adjusting strategies to avoid power waste. Through intelligent power gap calculation and prediction of daily stored power judgment, the system can optimize the execution mode of irrigation and fertilization when photovoltaic power generation is insufficient, maximize the utilization of power resources, avoid over-reliance on energy storage systems, and reduce waste. The system can optimize the irrigation and fertilization tasks according to the needs and growth environment of different crops and improve the intelligent level of agricultural production by storing the initial irrigation and fertilization strategies of different crops and making dynamic adjustments according to factors such as the types of crops, light intensity, and weather conditions. Through precise adjustment of irrigation and fertilization strategies, it is ensured that each crop can obtain the most suitable water and nutrients during its growth process, thereby improving the efficiency of water and fertilizer utilization, reducing resource waste, and contributing to the healthy growth of crops and increasing agricultural output. When the system finds that the power gap is large or that the strategy needs to be adjusted multiple times, the built-in early warning module will send out an early warning signal to remind the operator or relevant management personnel to take corresponding measures in time to avoid system failure or inability to complete the task, and ensure the smooth operation of the entire irrigation and fertilization system. The system of the present invention has intelligent prediction and adjustment functions, and can autonomously optimize the irrigation and fertilization plan according to environmental changes, reduce manual intervention, and improve the autonomy, intelligence and operation efficiency of the system. This not only improves the convenience of system operation, but also reduces labor costs.

[0016] On the other hand, the present invention also proposes a method for implementing the above-mentioned photovoltaic-driven irrigation and fertilization management system, the method comprising: Convert solar energy into electrical energy through photovoltaic panels, and store or provide electrical energy through energy storage devices; extract water through water pumps; spray through lifting poles and nozzles installed on the lifting poles; transport medicines or fertilizers; Acquire light intensity, remaining power stored in the energy storage device, and corresponding acquisition time; The remaining power, light intensity and acquisition time are stored as first historical data, and the total irrigation water volume, total fertilizer volume and total power consumption of each irrigation and fertilization in the initial fertigation strategy are stored as second historical data; Determine the type of crop and obtain the initial fertilization strategy for the crop, calculate the natural power consumption and predicted remaining power of the energy storage device from the current time to the preset time point according to the first historical data, compare the predicted remaining power with the corresponding total power consumption, and determine whether the initial fertilization strategy should be adjusted; When the initial fertigation strategy is adjusted, the difference between the total power consumption and the predicted remaining power is calculated and recorded as the power gap; the initial fertigation strategy is adjusted according to the power gap, and at the same time, it is determined whether to issue a system shutdown warning.

[0017] It is understandable that the above-mentioned irrigation and fertigation management method and system have the same beneficial effects, which will not be described in detail here. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings: Figure 1 This is a functional block diagram of a photovoltaic-driven irrigation and fertilization management system according to an embodiment of the present invention; Figure 2 The present invention is a flowchart of a photovoltaic-driven irrigation and fertilization management method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0019] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art. It should be noted that, in the absence of conflict, the embodiments of the present invention and the features described in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0020] See also Figure 1 As shown, an embodiment of the present invention provides an irrigation and fertilization management system based on photovoltaic drive, including an execution unit and a processing unit; The execution units include: A photovoltaic energy storage module is provided with a photovoltaic panel and an energy storage device, and the photovoltaic energy storage module is configured to convert solar energy into electrical energy through the photovoltaic panel and store or provide electrical energy through the energy storage device; A water intake module is configured to extract water from a source through a water pump; A spraying module is provided with a lifting pole and a spray head installed on the lifting pole, the spraying module is connected to the water intake module, and the spraying module is configured to perform a spraying operation; A dosing module is provided with a control valve and a flow sensor for controlling the start and stop of the dosing process. The dosing module is connected to the spray head and is configured to deliver medicine or fertilizer to the spraying module; The processing unit includes: A collection module is configured to obtain light intensity, remaining power stored in the energy storage device, and corresponding acquisition time; A storage database storing initial fertigation strategies for different crops, the storage database being further configured to store the remaining power, light intensity and acquisition time as first historical data, and the total irrigation water volume, total fertilizer dosage and total power consumption for each fertigation in the initial fertigation strategy as second historical data; The prediction module is configured to determine the type of crop and obtain the initial fertilization and irrigation strategy of the crop, calculate the natural power consumption and the predicted remaining power of the energy storage device from the current time to the preset time point according to the first historical data, compare the predicted remaining power with the corresponding total power consumption, and determine whether the initial fertilization and irrigation strategy should be adjusted; The adjustment module is configured to calculate the difference between the total power consumption and the predicted remaining power when adjusting the initial irrigation and fertilization strategy, and record it as the power gap; adjust the initial irrigation and fertilization strategy according to the power gap, and at the same time, determine whether to issue a system shutdown warning.

[0021] It should be noted that the execution unit mainly includes four modules, namely photovoltaic energy storage module, water intake module, spraying module and dosing module. These modules work together to complete the irrigation and fertilization tasks.

[0022] The core function of the photovoltaic energy storage module is to convert solar energy into electrical energy. Photovoltaic panels absorb sunlight through the photovoltaic effect and convert it into electrical energy. Energy storage devices (such as batteries) store the electrical energy and provide power to the system when needed. This module ensures that the energy source of the entire irrigation and fertilization system is independent and clean, reducing dependence on the municipal power grid.

[0023] The water intake module draws water from the water source through a water pump and provides water for the irrigation system. The operation of the water pump is controlled by the system, and the irrigation needs of crops are met by reasonably adjusting the water volume.

[0024] The spray module includes a lifting pole and a nozzle mounted on it, which is used to accurately spray water and fertilizer on crops. The lifting pole is designed to adjust the height of the nozzle to meet the growth needs of different crops. The spray module is connected to the water intake module to ensure efficient water delivery.

[0025] The function of the dosing module is to provide fertilizers or medicines to the spraying module according to the set demand. By controlling the valve and flow sensor, the delivery amount of medicines or fertilizers is accurately controlled to ensure the accuracy and efficiency of the fertilization process. This is crucial for precision agriculture, which can reduce resource waste and avoid over-fertilization.

[0026] The processing unit collects and processes data to make real-time judgments and adjustments to ensure that the entire system is optimized and regulated according to actual conditions.

[0027] The acquisition module is responsible for collecting key data of system operation, including light intensity, remaining power of the energy storage device, and the time point of collecting these data. These data provide the basis for subsequent predictions and adjustments.

[0028] The storage database stores historical data related to fertigation, which is divided into two categories: the first type of data is the historical record of real-time data such as light intensity and energy storage power. The second type of data is the total water volume, fertilizer usage, and total power consumption data for each fertigation. These data are helpful for analyzing the power consumption of the system and the effect of fertigation under different conditions. Through the storage and analysis of historical data, the system can make accurate predictions and decisions, thereby optimizing subsequent operations.

[0029] Based on the historical data of light intensity and energy storage capacity, the prediction module can calculate the natural power consumption and remaining power of the system in a certain period of time in the future (such as until a preset time point). By comparing the predicted remaining power with the current power demand (such as the power required for irrigation and fertilization), the prediction module determines whether the irrigation and fertilization strategy needs to be adjusted. If the prediction results show that the remaining power is not enough to complete the original task, the system will make corresponding adjustments.

[0030] Adjustment module: When the prediction module finds that the power is insufficient, the adjustment module will make adjustments based on the power gap. The adjustment method can be to reduce the amount of irrigation water, reduce the amount of fertilizer, or change the schedule of irrigation and fertilization to ensure that the system can continue to operate stably in the case of insufficient power. In addition, if the power gap is large, the system will also issue a shutdown warning to remind the operator to pay attention to possible system failures or the risk of failure to complete the task.

[0031] It is understandable that the system can dynamically analyze and adjust according to the data collected in real time (such as light intensity, energy storage capacity, etc.). If the remaining power of the system cannot meet the established irrigation and fertilization strategy, the processing unit will optimize the irrigation and fertilization tasks according to the power gap. For example, the fertilization time may be extended, irrigation may be carried out in batches, or the amount of water and fertilizer may be reduced to ensure that the system can continue to operate without shutdown. The operation mode is adjusted in time according to the photovoltaic power generation situation to avoid system shutdown caused by insufficient power and ensure that irrigation and fertilization work can be completed on time. This is of great significance to the sustainability and stability of agricultural production, especially in remote areas without municipal power grid power supply. Through intelligent data collection, prediction and adjustment, the degree of automation of agricultural production has been greatly improved and human intervention has been reduced. At the same time, the system can flexibly adjust the irrigation and fertilization strategy according to the specific crop type and growth environment, which helps to improve the growth quality and yield of crops and improve the utilization efficiency of agricultural resources.

[0032] In some embodiments of the present application, when the natural power consumption of the energy storage device from the current time to the preset time point is calculated according to the first historical data, it includes: Obtain the light intensity and the minimum light intensity for photovoltaic panels to generate electricity and compare them. When the light intensity is less than or equal to the minimum light intensity, intercept n groups of first historical data; when the light intensity is greater than the minimum light intensity, stop intercepting, calculate and obtain the first natural power consumption based on the intercepted first historical data, repeat the calculation and obtain, and obtain x groups of natural power consumption data; The natural power consumption satisfies the following relationship: ; ; in, represents the i-th natural power consumption, i is a positive integer; n represents the number of groups of first historical data intercepted when the light intensity is less than or equal to the minimum light intensity; Indicates the remaining power of the first historical data of the i-th group; Indicates the acquisition time of the first historical data of the i-th group; represents natural power consumption; k represents a floating coefficient, k is (1,1.1]; x represents the number of repeated calculations.

[0033] It is understandable that by calculating the natural power consumption of the energy storage device based on the first historical data, the power consumption of the photovoltaic energy storage system in the future can be accurately predicted. This calculation method fully considers the change in light intensity, so as to reasonably predict the power consumption of the system under different light conditions.

[0034] By comparing the light intensity with the minimum light intensity, when the light intensity is lower than or equal to the minimum light intensity, the system will intercept the first historical data and perform calculations to estimate the natural power consumption under low light conditions. This can reflect the power consumption pattern of the energy storage device under insufficient sunlight.

[0035] When the light intensity is higher than the minimum light intensity, the system stops capturing data. This can avoid errors in predicting power consumption through historical data under strong light conditions, because when the light is sufficient, the power generation of photovoltaic panels will increase significantly, affecting the accurate prediction of power consumption.

[0036] By setting the floating coefficient k in the range of (1,1.1], the power fluctuations that may exist in the actual system can be taken into account. This floating coefficient helps to make appropriate corrections to the calculation of natural power consumption and avoid errors caused by relying solely on historical data. For example, the fluctuations in power consumption in the system under different seasons or weather changes can be compensated by adjusting the value of k.

[0037] By repeating the calculation (x times) to obtain multiple natural power consumption data, the accuracy of the prediction can be improved by accumulating multiple calculation results. This method can reduce the accidental errors or abnormal values ​​that may be caused by a single calculation and improve the reliability and stability of the calculation results.

[0038] The system can dynamically adjust the power consumption prediction method according to the actual light intensity, flexibly adapt to different light conditions, and avoid deviations in strong or weak light. This means that the system can better adapt to different weather and environmental conditions, ensuring accurate natural power consumption prediction under different light intensities.

[0039] By accurately predicting natural power consumption, the system can reasonably allocate the power of the energy storage device to avoid problems such as insufficient power or excessive consumption. This not only improves the system's energy management capabilities, but also effectively reduces energy waste, extends the service life of equipment, and optimizes the efficiency of power use.

[0040] By calculating the natural power consumption and comparing it with the remaining power, the system can predict the future power shortage in advance. If the power is insufficient, the system will take corresponding adjustment measures, such as reducing the intensity of irrigation and fertilization or adjusting the frequency of fertilization, so as to ensure that it can continue to work when the power is insufficient.

[0041] Based on the prediction results of natural power consumption and remaining power, the system can effectively predict and prevent shutdowns caused by insufficient power. Measures can be taken in advance to adjust or optimize and improve the operational stability and reliability of the system.

[0042] In some embodiments of the present application, when the predicted remaining power of the energy storage device from the current time to the preset time point is calculated according to the first historical data, it also includes: The predicted remaining power satisfies the following relationship: ; in, Indicates the estimated remaining power. Indicates the current time point. Indicates a preset time point.

[0043] When comparing the predicted remaining power with the corresponding total power consumption to determine whether the initial fertigation strategy should be adjusted, it includes: If the predicted remaining electricity is greater than the total electricity consumption, it is determined that the initial irrigation and fertilization strategy does not need to be adjusted; If the predicted remaining power is less than or equal to the total power consumption, the stored power of the energy storage device from the current time to the preset time point is predicted based on the light intensity. When the sum of the predicted remaining power and the stored power is greater than the total power consumption, it is judged that the initial irrigation and fertilization strategy does not need to be adjusted; when the sum of the predicted remaining power and the stored power is lower than or equal to the total power consumption, it is judged that the initial irrigation and fertilization strategy needs to be adjusted.

[0044] It should be noted that by predicting the remaining power from the current time to the preset time point based on the first historical data, the system can understand the power consumption trend of the energy storage device in advance, thereby providing data support for subsequent irrigation and fertilization operations. This enables the system to reasonably foresee the future power status and avoid downtime or inability to continue to perform tasks due to insufficient power.

[0045] By comparing the predicted remaining power with the corresponding total power consumption, the system can determine whether the current power is sufficient to support the initially set irrigation and fertilization strategy. If the predicted remaining power is greater than the total power consumption, it means that the current power is sufficient and the initial strategy does not need to be adjusted and can continue to be executed as planned. This avoids unnecessary adjustments and helps the system maintain efficient operation.

[0046] If the predicted remaining power is less than or equal to the total power consumption, the system needs to predict the future power storage of the energy storage device based on the current light intensity to determine whether the irrigation and fertilization strategy needs to be adjusted. If the system finds through prediction that the remaining power plus the stored power of the energy storage device is still insufficient to meet the total power demand, the irrigation and fertilization strategy will be automatically adjusted to ensure that the system will not continue to operate when the power is insufficient.

[0047] Light intensity is a key factor affecting photovoltaic power generation, so the system predicts the stored energy of the energy storage device based on the current light intensity, and then calculates the remaining power in the future. Such predictions can more flexibly adapt to changes in weather and environment, ensuring that the system can still accurately assess the power status when the light is weak or changes greatly, avoiding shutdowns or untimely adjustments due to insufficient power.

[0048] By combining the predicted remaining power with the power stored in the energy storage device to predict future power, the system can more comprehensively consider the power provided by various power sources (such as energy storage devices and photovoltaic panels), ensuring that no power source is overlooked. This combination can improve the accuracy of the forecast and ensure that the power input from the photovoltaic panels can be effectively used even when the power of the energy storage device is low, thereby reducing the need for adjustments.

[0049] When the remaining power is predicted to be sufficient, the system can avoid unnecessary adjustments to the fertigation strategy and maintain the stability and consistency of fertigation operations. This ensures that the system operates efficiently when there is sufficient sunlight, while reducing unnecessary calculations and adjustments, saving system resources and computing time.

[0050] When it is predicted that the remaining power is insufficient, the system will automatically adjust the irrigation and fertilization strategy and adopt a more energy-saving method (such as reducing the frequency of irrigation, reducing the amount of water or fertilizer), thereby avoiding system shutdown due to insufficient power. This allows the system to ensure basic irrigation and fertilization functions even when resources are tight.

[0051] The system can dynamically adjust the irrigation and fertilization strategy to adapt to different light and power conditions, improving the system's adaptive ability. For example, when the light is strong, the system can remain unchanged, but when the light is insufficient, the strategy can be flexibly adjusted based on the energy storage power and light intensity. This adaptive ability helps ensure the continuous and stable operation of the system and reduce system instability or energy waste caused by environmental changes.

[0052] By continuously monitoring and comparing the remaining power and power consumption, the system can determine in advance whether the power is sufficient and take necessary adjustment measures when the power is insufficient. In this way, the system can avoid downtime caused by insufficient power to the greatest extent, ensure the reliability and efficiency of system operation, and reduce operation interruptions or energy waste caused by insufficient power.

[0053] In some embodiments of the present application, the stored electrical energy is obtained by the following method: ; in, Represents the stored electrical energy from time t to the preset time point, represents the light intensity at time t, represents the area of ​​the photovoltaic panel, Represents the conversion efficiency of photovoltaic panels, represents the charging efficiency of the energy storage device, Indicates the maximum capacity of the energy storage device, It means taking the smaller value of a and b. represents the security factor, Take [0.8,1).

[0054] It should be noted that the protection factor is used to reduce the calculated value of the stored electric energy, always ensuring that the actual electric energy stored in the energy storage device is greater than the calculated value, and preventing the energy storage device from consuming abnormally fast power due to aging or other factors.

[0055] In some embodiments of the present application, when the initial fertigation strategy is adjusted according to the electricity deficit, it includes: Obtain the power gap and the predicted light intensity after a preset time point, obtain the predicted daily stored power based on the predicted light intensity, and determine whether to divide the initial irrigation and fertilization strategy completed once into several batches based on the power gap and the predicted daily stored power, and determine the number of batches when it is determined that division is required; The daily detection cycle of stored electric energy is 24h.

[0056] In some embodiments of the present application, judging whether to divide the initial fertigation strategy completed once into several batches based on the power gap and the predicted daily stored power and determining the number of batches when it is judged that division is required includes: S1: Compare the current power gap with the predicted daily stored power. When the predicted daily stored power is greater than or equal to the power gap, do not divide the initial irrigation and fertilization strategy. When the predicted daily stored power is less than the power gap, calculate the difference between the power gap and the daily stored power and record it as the Yth power difference, and obtain the daily stored power again. S2: Compare the daily stored electric energy with the Yth electric energy difference. When the daily stored electric energy is greater than or equal to the Yth electric energy difference, determine to divide the batch into Y+1 times; when the daily stored electric energy is less than the Yth electric energy difference, obtain the daily stored electric energy again and repeat step S2 until the daily stored electric energy is greater than or equal to the Yth electric energy difference.

[0057] It should be noted that by comparing the power gap with the predicted daily stored power, the system can determine whether the initial irrigation and fertilization strategy needs to be divided. This judgment mechanism ensures that when the energy storage is not enough to support the entire irrigation and fertilization task at one time, the system can automatically divide the task into several batches and complete it step by step. Such a strategy avoids system downtime or failure to complete tasks on time due to insufficient power.

[0058] By calculating the difference between the current power gap and the predicted daily stored power, the system can evaluate whether the power gap can be made up through solar charging in the next 24 hours. If the predicted stored power is sufficient to meet the power demand, the irrigation and fertilization tasks can be completed as planned; if the power is insufficient, the tasks will be carried out in batches to avoid consuming too much power at one time.

[0059] If the difference between the daily stored energy and the power cannot meet the power required for one-time irrigation and fertilization, the system will gradually obtain more daily stored energy to determine whether to increase the number of batches. In this way, the system can flexibly adjust the task completion method and batch number according to the daily light conditions, thereby ensuring that the irrigation and fertilization tasks can be completed under limited power conditions.

[0060] Dividing a one-time irrigation and fertilization task into several batches helps balance the consumption of energy storage power and changes in light intensity. By adjusting the task batches in a timely manner, the system can make full use of the light resources every day without exceeding the power limit, effectively extending the system's operating time.

[0061] The system dynamically adjusts according to real-time power demand and light intensity to ensure that fertigation operations are not restricted by power shortages. For example, if the predicted daily stored power is less than the power gap, the system will calculate the difference and repeatedly obtain stored power before continuing fertigation to ultimately determine the appropriate number of batches. This flexibility enables the system to cope with different power supply and operation requirements, enhancing overall stability.

[0062] Due to the uncertainty of factors such as light intensity, weather and power supply, the system can make timely adjustments in the face of uncertainty by making dynamic predictions based on the daily detection cycle (24 hours) of stored energy. For example, if the light intensity is lower than expected, the system will automatically determine whether the energy storage can meet the demand and adjust the batches of fertilization and irrigation to avoid the risk of running out of power.

[0063] By dynamically adjusting the power gap and the difference between the daily stored power, the system ensures that the power consumed by each irrigation and fertilization is matched with the currently available stored power. This precise control helps to maximize the use of the power generated by the photovoltaic system, reduce unnecessary energy waste, and ensure that the system can still operate efficiently when resources are limited.

[0064] Through this intelligent adjustment mechanism, the system can automatically determine whether it is necessary to divide the irrigation and fertilization tasks according to factors such as power, light, and crop demand, and dynamically adjust the strategy according to real-time power and light changes. In this way, farmland management will be more automated and intelligent, reducing manual intervention and operational errors, and improving work efficiency and management accuracy.

[0065] In some embodiments of the present application, when the initial fertigation strategy is adjusted according to the electricity deficit, it also includes: Determine the timing of irrigation and fertilization based on the predicted light intensity; The predicted light intensity and the corresponding predicted time are obtained, and a predicted light intensity-predicted time curve is established. When the slope of the predicted light intensity-predicted time curve is greater than zero, the predicted time is used as the time point for irrigation and fertilization.

[0066] It should be noted that by dynamically determining the time point of irrigation and fertilization based on the changing trend of light intensity, the execution of irrigation and fertilization tasks can be optimized, the use of solar energy resources can be maximized, energy waste can be reduced, the system's work efficiency can be improved, and its adaptability to environmental changes can be enhanced. This intelligent time point adjustment mechanism helps to improve the automation level of agricultural management, reduce energy consumption, and improve overall benefits.

[0067] In some embodiments of the present application, the processing unit further includes: The early warning module is configured to send out an early warning signal when the number of repetitions of step S2 is greater than 7.

[0068] It should be noted that the number of repetitions of step S2 refers to the number of times the system continuously calculates and compares the difference between the daily stored power and the power gap when determining whether the irrigation and fertilization strategy needs to be divided into multiple batches. If the daily stored power cannot meet the power gap, the system will enter the process of repeatedly obtaining stored power until the daily stored power is sufficient.

[0069] The warning module is configured to issue a warning signal when the number of repetitions of step S2 exceeds 7. This setting means that when the system fails to meet the power gap by acquiring new daily stored power for many times, it indicates that the system may face a greater risk of power shortage or poor lighting conditions, which may affect the normal progress of irrigation and fertilization tasks.

[0070] In the case of a large power gap, the system will calculate multiple power replenishment. If the number of repetitions is too many (more than 7 times, i.e., seven days), it means that it is difficult to replenish power, which may be due to insufficient light conditions, reduced efficiency of the photovoltaic power generation system, or other problems. At this time, the system administrator is reminded through the early warning signal, and timely measures can be taken to prevent the system from continuing to run and causing energy waste or failure to complete the task.

[0071] When the number of repetitions is too high, the triggering of early warning signals can prompt the system to adjust its strategy. For example, the system may need to consider temporary backup power supply, or re-evaluate the timing and batch division of fertigation tasks. By identifying potential problems in advance, the system can avoid long-term inefficient operation and ensure that fertigation tasks can be completed smoothly.

[0072] The design of the early warning module enhances the reliability of the system, avoiding the need to continue irrigation and fertilization in extreme situations (such as long-term lack of sufficient power support) and preventing crops from being affected by insufficient power. This can not only protect the growth of crops, but also avoid production losses caused by system failures or insufficient energy.

[0073] Through the early warning module, the system can automatically detect and respond to potential power shortages without frequent human intervention. By setting a threshold (such as more than 7 repetitions), an early warning can be automatically triggered, improving the automation and efficiency of management while reducing human errors.

[0074] The introduction of the early warning module enables the system to have a higher level of intelligent response mechanism, which can actively warn when abnormal situations occur, prompting users or managers to take necessary countermeasures, thereby improving the intelligence level of the system and the safety of operation.

[0075] See also Figure 2 As shown, an embodiment of the present invention provides an irrigation and fertilization management method based on photovoltaic drive, comprising: Convert solar energy into electricity through photovoltaic panels, and store or provide electricity through energy storage devices; extract water through water pumps; spray through lifting poles and nozzles installed on the lifting poles; transport medicines or fertilizers; Obtaining light intensity, remaining power stored in the energy storage device, and corresponding acquisition time; The remaining power, light intensity and acquisition time are stored as the first historical data, and the total irrigation water volume, total fertilizer volume and total power consumption of each irrigation and fertilization in the initial fertigation strategy are stored as the second historical data; Determine the type of crop and obtain the initial fertilization and irrigation strategy for the crop, calculate the natural power consumption and predicted remaining power of the energy storage device from the current time to the preset time point based on the first historical data, compare the predicted remaining power with the corresponding total power consumption, and determine whether the initial fertilization and irrigation strategy should be adjusted; When the initial fertigation strategy is adjusted, the difference between the total power consumption and the predicted remaining power is calculated and recorded as the power gap; the initial fertigation strategy is adjusted according to the power gap, and at the same time, it is determined whether to issue a system shutdown warning.

[0076] It can be understood that the photovoltaic-driven irrigation and fertilization management method of the present invention realizes dynamic adjustment, energy optimization and intelligent early warning of the irrigation and fertilization process through intelligent power management, real-time data collection and historical data analysis, thereby improving the efficiency of agricultural production, saving energy, reducing human intervention, and ensuring the supply of water and fertilizer required for crop growth, with significant economic and environmental benefits.

[0077] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A photovoltaic-driven irrigation and fertilization management system, characterized in that: including an execution unit and a processing unit; The execution unit comprises: A photovoltaic energy storage module is provided with a photovoltaic panel and an energy storage device, wherein the photovoltaic energy storage module is configured to convert solar energy into electrical energy through the photovoltaic panel and store or provide electrical energy through the energy storage device; A water intake module is configured to extract water from a source through a water pump; A spraying module, provided with a lifting pole and a spray head mounted on the lifting pole, the spraying module is connected to the water intake module, and the spraying module is configured to perform a spraying operation; A dosing module is provided with a control valve and a flow sensor for controlling the start and stop of the dosing process, the dosing module is connected to the spray head, and the dosing module is configured to deliver medicine or fertilizer to the spraying module; The processing unit comprises: A collection module, configured to obtain light intensity, the remaining power stored in the energy storage device and the corresponding acquisition time; A storage database storing initial fertigation strategies for different crops, wherein the storage database is further configured to store the remaining power, light intensity and acquisition time as first historical data, and store the total irrigation water volume, total fertilizer volume and total power consumption for each fertigation in the initial fertigation strategy as second historical data; a prediction module configured to determine the type of crop and obtain the initial fertigation strategy for the crop, calculate the natural power consumption and predicted remaining power of the energy storage device from the current time to a preset time point according to the first historical data, compare the predicted remaining power with the corresponding total power consumption, and determine whether the initial fertigation strategy is adjusted; The adjustment module is configured to calculate the difference between the total power consumption and the predicted remaining power when adjusting the initial fertigation strategy, and record it as the power gap; adjust the initial fertigation strategy according to the power gap, and at the same time, determine whether to issue a system shutdown warning.

2. The photovoltaic-driven irrigation and fertilization management system according to claim 1, characterized in that: When the natural power consumption of the energy storage device from the current time to the preset time point is calculated according to the first historical data, it includes: The light intensity is obtained and compared with the minimum light intensity for the photovoltaic panel to generate electricity. When the light intensity is less than or equal to the minimum light intensity, n groups of the first historical data are intercepted; when the light intensity is greater than the minimum light intensity, interception is stopped, and the first natural power consumption is calculated based on the intercepted first historical data, and the calculation is repeated to obtain x groups of natural power consumption data; The natural power consumption satisfies the following relationship: ； ； in, represents the i-th natural power consumption, i is a positive integer; n represents the number of groups of the first historical data intercepted when the light intensity is less than or equal to the minimum light intensity; Indicates the remaining power of the i-th group of the first historical data; represents the acquisition time of the first historical data of the i-th group; represents natural power consumption; k represents a floating coefficient, k is (1,1.1]; x represents the number of repeated calculations.

3. The photovoltaic-driven irrigation and fertilization management system according to claim 2, characterized in that: When the predicted remaining power of the energy storage device from the current time to the preset time point is calculated according to the first historical data, it also includes: The predicted remaining power satisfies the following relationship: ； in, Indicates the estimated remaining power. Indicates the current time point. Indicates a preset time point.

4. The photovoltaic-driven irrigation and fertilization management system according to claim 3 is characterized in that: When the predicted remaining power is compared with the corresponding total power consumption to determine whether the initial fertigation strategy is to be adjusted, the method includes: If the predicted remaining power is greater than the total power consumption, it is determined that the initial fertigation strategy does not need to be adjusted; If the predicted remaining power is less than or equal to the total power consumption, the stored power of the energy storage device from the current time to the preset time point is predicted based on the light intensity; when the sum of the predicted remaining power and the stored power is greater than the total power consumption, it is determined that the initial fertilization strategy does not need to be adjusted; when the sum of the predicted remaining power and the stored power is lower than or equal to the total power consumption, it is determined that the initial fertilization strategy needs to be adjusted.

5. The photovoltaic-driven irrigation and fertilization management system according to claim 4, characterized in that: The stored electric energy is obtained by the following method: ； in, represents the stored electric energy from time t to the preset time point, represents the light intensity at time t, represents the area of ​​the photovoltaic panel, represents the conversion efficiency of the photovoltaic panel, represents the charging efficiency of the energy storage device, represents the maximum capacity of the energy storage device, It means taking the smaller value of a and b. represents the security factor, Take [0.8,1).

6. The photovoltaic-driven irrigation and fertilization management system according to claim 5, characterized in that: When the initial irrigation and fertilization strategy is adjusted according to the electricity gap, it includes: Obtain the power gap and the predicted light intensity after a preset time point, obtain the predicted daily stored electric energy based on the predicted light intensity, and determine whether to divide the initial fertilization strategy completed at one time into several batches based on the power gap and the predicted daily stored electric energy, and determine the number of batches when it is determined that division is required; The daily detection period of stored electric energy is 24 hours.

7. The photovoltaic-driven irrigation and fertilization management system according to claim 6, characterized in that: Based on the power gap and the predicted daily stored power, determining whether to divide the initial fertigation strategy completed once into several batches and determining the number of batches when it is determined that division is required includes: S1: Compare the current power gap with the predicted daily stored power. When the predicted daily stored power is greater than or equal to the power gap, do not divide the initial irrigation and fertilization strategy. When the predicted daily stored power is less than the power gap, calculate the difference between the power gap and the daily stored power and record it as the Yth power difference, and obtain the daily stored power again. S2: Compare the daily stored electric energy with the Yth electric energy difference. When the daily stored electric energy is greater than or equal to the Yth electric energy difference, determine to divide the batches into Y+1 times; when the daily stored electric energy is less than the Yth electric energy difference, obtain the daily stored electric energy again and repeat step S2 until the daily stored electric energy is greater than or equal to the Yth electric energy difference.

8. The photovoltaic-driven irrigation and fertilization management system according to claim 7, characterized in that: When the initial fertigation strategy is adjusted according to the electricity deficit, it also includes: Determine the time point of irrigation and fertilization according to the predicted light intensity; The predicted light intensity and the corresponding predicted time are obtained, and a predicted light intensity-predicted time curve is established. When the slope of the predicted light intensity-predicted time curve is greater than zero, the predicted time is used as the time point for irrigation and fertilization.

9. The photovoltaic-driven irrigation and fertilization management system according to claim 8, characterized in that: The processing unit also includes: The early warning module is configured to send out an early warning signal when the number of repetitions of step S2 is greater than 7.

10. A photovoltaic-driven fertigation management method, applied to the photovoltaic-driven fertigation management system according to any one of claims 1 to 9, characterized in that: The method includes: Convert solar energy into electrical energy through photovoltaic panels, and store or provide electrical energy through energy storage devices; extract water through water pumps; spray through lifting poles and nozzles installed on the lifting poles; transport medicines or fertilizers; Acquire light intensity, remaining power stored in the energy storage device, and corresponding acquisition time; The remaining power, light intensity and acquisition time are stored as first historical data, and the total irrigation water volume, total fertilizer volume and total power consumption of each irrigation and fertilization in the initial fertigation strategy are stored as second historical data; Determine the type of crop and obtain the initial fertilization strategy for the crop, calculate the natural power consumption and predicted remaining power of the energy storage device from the current time to the preset time point according to the first historical data, compare the predicted remaining power with the corresponding total power consumption, and determine whether the initial fertilization strategy should be adjusted; When the initial fertigation strategy is adjusted, the difference between the total power consumption and the predicted remaining power is calculated and recorded as the power gap; the initial fertigation strategy is adjusted according to the power gap, and at the same time, it is determined whether to issue a system shutdown warning.

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