Photovoltaic water pump irrigation system

Abstract

The invention discloses a photovoltaic water pump irrigation system, and relates to the field of photovoltaic technology, and the system comprises an illumination information collection module which is used for obtaining the radiation intensity distribution and environment temperature fluctuation data of a photovoltaic cell array in a target area, and combining the change of a light incident angle to obtain the illumination information of the photovoltaic cell array. Illumination information of different time periods every day is collected in real time through a sensor, and the output power performance of the array under specific seasonal illumination changes is judged. According to the photovoltaic water pump irrigation system, a remote monitoring platform is constructed by utilizing the Internet of Things technology, the running state of the system is monitored in real time, and faults are found and processed in time. The energy efficiency ratio and the operation stability of the system in a specific environment are verified through field tests, and a reliable irrigation solution is provided for remote areas.

Description

Technical Field

[0001] The present invention relates to the field of photovoltaic technology, and in particular to a photovoltaic water pump irrigation system. Background Art

[0002] The design of a solar water pump irrigation system involves several technical challenges, primarily in the photovoltaic array, water pump, and control system. The photovoltaic array layout needs to be optimized based on varying lighting conditions to maximize output efficiency.

[0003] However, existing photovoltaic array layouts often fail to maintain stable output efficiency under varying light intensities, resulting in low system efficiency. Pump impeller design requires minimizing impact losses and ensuring effective matching between the motor and pump. However, current designs are often inefficient, with insufficient motor-pump matching accuracy, increasing energy consumption. Furthermore, the implementation of maximum power point tracking (MPPT) algorithms often relies on general-purpose algorithms and is often implemented in software, resulting in slow response and difficulty adapting to rapid environmental changes. Intelligent charge and discharge control of the battery pack is also a key issue in the system. Existing technologies typically rely on voltage detection for charge and discharge control, but this approach is susceptible to factors such as battery aging and temperature fluctuations, leading to unstable battery performance and even shortened battery life. Remote monitoring systems for solar pump systems face technical challenges in data collection, transmission, and analysis. Especially in the application of IoT technology, data real-time and reliability remain bottlenecks. In system pilot production and performance evaluation, effective verification in typical application scenarios and optimization of design solutions based on test results remain pressing technical challenges. Summary of the Invention

[0004] The purpose of the present invention is to provide a photovoltaic water pump irrigation system to solve the problems existing in the prior art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a photovoltaic water pump irrigation system, the system comprising: The light information acquisition module is used to obtain the radiation intensity distribution and ambient temperature fluctuation data of the photovoltaic cell array in the target area. Combined with the changes in the incident angle of light, the sensor collects real-time light information at different times of the day to determine the output power performance of the array under specific seasonal light changes; The fault monitoring and optimization module is used to determine the location of system faults in remote mountain irrigation scenarios based on radiation intensity distribution and ambient temperature fluctuation data. Using fault location data collected by the remote monitoring platform, combined with seasonal light variations and fluctuations in brushless DC motor efficiency, it adjusts array spacing design and motor starting torque parameters to determine an optimized operation plan for small-scale irrigation in remote, off-grid areas. The test and stability assessment module is used to deploy test systems in remote mountainous areas and arid areas without electricity according to the optimized operation plan. It collects energy efficiency data of the system under specific light incident angles and AC variable frequency motor speed regulation to determine the overall operational stability of the system.

[0006] Preferably, the fault monitoring and optimization adjustment module determines the fault location of the system in a remote mountainous irrigation scenario based on the radiation intensity distribution and ambient temperature fluctuation data, including: Based on the radiation intensity distribution and ambient temperature fluctuation data, the effect of array tilt angle and array orientation adjustment on output efficiency was analyzed; Considering the impact of shadows and array spacing design, an array layout plan suitable for irrigation scenarios in remote mountainous areas is determined.

[0007] Preferably, the fault monitoring and optimization adjustment module determines the fault location of the system in the remote mountainous irrigation scenario based on the radiation intensity distribution and the ambient temperature fluctuation data, and further includes: Calculate the load demand in the irrigation scenario by combining the output power data of the array layout plan with the pump flow demand and pump head parameters; Obtain the performance curves of brushless DC motor efficiency and AC variable frequency motor speed regulation to determine whether the motor rated power range meets the requirements of operating load fluctuations.

[0008] Preferably, the fault monitoring and optimization adjustment module determines the fault location of the system in the remote mountainous irrigation scenario based on the radiation intensity distribution and the ambient temperature fluctuation data, and further includes: Analyze the stability of the motor's starting torque and heat dissipation performance during long-term operation in remote and arid areas, based on the motor's rated power range and pump head parameters; Determine the capacity matching solution between motors and pumps in small-scale irrigation scenarios.

[0009] Preferably, the fault monitoring and optimization adjustment module determines the fault location of the system in the remote mountainous irrigation scenario based on the radiation intensity distribution and the ambient temperature fluctuation data, and further includes: According to the capacity matching plan, the output voltage and current data of the photovoltaic array are collected under specific array tilt angles and array orientation adjustments; An improved perturbation observation method is used to design a hardware circuit based on a single chip microcomputer to determine the maximum power point position.

[0010] Preferably, the fault monitoring and optimization adjustment module determines the fault location of the system in the remote mountainous irrigation scenario based on the radiation intensity distribution and the ambient temperature fluctuation data, and further includes: The output data of the maximum power point position is used, combined with the motor's heat dissipation performance and operating load fluctuations, to drive the power tube to perform voltage regulation on the battery pack; Obtain the charge and discharge status of battery packs in remote areas without electricity and determine intelligent control strategies.

[0011] Preferably, the fault monitoring and optimization adjustment module determines the fault location of the system in the remote mountainous irrigation scenario based on the radiation intensity distribution and the ambient temperature fluctuation data, and further includes: Based on the intelligent control strategy, the Internet of Things technology is used to build a remote monitoring platform to obtain real-time operating data from the radiation intensity distribution of the photovoltaic array and the water pump flow demand; Determine the location of system faults in remote mountain irrigation scenarios.

[0012] Preferably, the illumination information acquisition module further includes: Light intensity adjustment module, used to automatically adjust the light receiving angle of the photovoltaic cell array according to different seasonal lighting conditions to improve the light intensity collection efficiency; The time scheduling system is used to adjust the frequency of light information collection according to the light conditions at different times of the day to improve the operating efficiency of the photovoltaic array.

[0013] Preferably, the fault monitoring and optimization adjustment module further includes: Environmental impact analysis unit, used to analyze the impact of seasonal light changes on system performance and provide adjustment solutions; The motor torque regulation unit is used to adjust the starting torque and operating parameters of the motor in real time according to the efficiency fluctuation of the brushless DC motor to optimize motor performance and reduce energy waste; The system optimization feedback interface is used to automatically adjust the array spacing design and perform performance adjustments based on data feedback during operation to ensure stable operation of the system under different environmental conditions.

[0014] Preferably, the test and stability assessment module further includes: System operation data acquisition unit, used to collect system power output, energy efficiency ratio and working status data in real time during the test; Data analysis and evaluation unit, used to process collected test data, analyze the system's energy efficiency performance under different environments and working conditions, and output stability reports; The tuning instruction generation unit is used to automatically generate optimization plans based on the evaluation results and guide the tuning adjustments during system operation.

[0015] It can be seen from the above technical solution that the present invention has the following beneficial effects: This photovoltaic water pump irrigation system collects data on the radiation intensity distribution and ambient temperature fluctuations of the photovoltaic array. By combining this with changes in light incidence angle, it analyzes the impact of array layout on output efficiency and determines an array design suitable for mountainous terrain. It then selects an appropriate motor and adjusts its capacity based on the pump load requirements. It also uses an improved perturbation-observation method to design a maximum power point tracking circuit, and formulates an intelligent control strategy based on the battery pack's charge and discharge status. A remote monitoring platform, built using IoT technology, monitors system operation in real time and promptly detects and addresses faults. Field trials validate the system's energy efficiency and operational stability under specific conditions, providing a reliable irrigation solution for remote areas. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 This is a connection diagram of the system modules of the present invention. DETAILED DESCRIPTION

[0017] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 making creative efforts are within the scope of protection of the present invention.

[0018] like Figure 1 As shown, the present invention provides a technical solution: a photovoltaic water pump irrigation system, the system comprising: The light information acquisition module is used to obtain the radiation intensity distribution and ambient temperature fluctuation data of the photovoltaic cell array in the target area. Combined with the changes in the incident angle of light, the sensor collects real-time light information at different times of the day to determine the output power performance of the array under specific seasonal light changes; The fault monitoring and optimization module is used to determine the location of system faults in remote mountain irrigation scenarios based on radiation intensity distribution and ambient temperature fluctuation data. Using fault location data collected by the remote monitoring platform, combined with seasonal light variations and fluctuations in brushless DC motor efficiency, it adjusts array spacing design and motor starting torque parameters to determine an optimized operation plan for small-scale irrigation in remote, off-grid areas. The test and stability assessment module is used to deploy test systems in remote mountainous areas and arid areas without electricity according to the optimized operation plan. It collects energy efficiency data of the system under specific light incident angles and AC variable frequency motor speed regulation to determine the overall operational stability of the system.

[0019] The operation of this photovoltaic water pump irrigation system is based on the basic principle of converting light energy into electrical energy and driving the water pump to pump water. It relies on three core modules to collaboratively implement light monitoring, fault diagnosis and system optimization, and stability assessment. First, the light information acquisition module uses high-precision solar radiation sensors and ambient temperature sensors deployed around the photovoltaic array to monitor the radiation intensity and temperature changes in the target area in real time. During the data acquisition process, the module combines the time-varying characteristics of the light incident angle to generate a time-series light data curve, and then derives the output power performance of the photovoltaic cell array at different time periods and identifies seasonal variation patterns. The collected information is not only used to evaluate the current power generation efficiency, but also serves as the basic data source for subsequent system operation optimization and fault diagnosis.

[0020] Secondly, the fault monitoring and optimization module utilizes this environmental data and information fed back by the remote monitoring platform to establish a multi-source data fusion model to identify potential fault points caused by sudden environmental changes or hardware aging. This module analyzes the correlation between light fluctuations, temperature anomalies, and unstable motor operation to locate key component failures. Based on topographical characteristics and sunlight distribution, it proposes strategies for optimizing array spacing and adaptively adjusting the starting torque of the brushless DC motor. Through a parameter tuning mechanism, the system dynamically adjusts the motor starting performance under varying irradiance conditions, thereby maintaining a stable output of pumped water.

[0021] Finally, the testing and stability assessment module, based on the optimized parameters, deployed a test system in a representative remote area and continuously tracked the system's performance under varying lighting angles, load conditions, and motor speed control strategies. This module collected key operating metrics such as voltage, current, speed, and flow, calculated the energy efficiency ratio, and assessed the system's stability fluctuation range. Through long-term operational experiments, this module not only verified the effectiveness of the optimization solution but also established a database of operational experience applicable to similar environments, providing data support for future deployment.

[0022] This system is based on the basic principle of converting solar energy into electrical energy and driving water pumps for irrigation. Through the collaborative work of three modules, namely the light information collection module, the fault monitoring and optimization adjustment module, and the test and stability assessment module, the system can achieve efficient operation of the photovoltaic irrigation system in remote areas.

[0023] First, the light information acquisition module uses radiation sensors and ambient temperature sensors installed around the photovoltaic cell array to monitor the solar radiation intensity and air temperature changes in the target area in real time. This module can combine the changes in the solar radiation angle at different time periods throughout the day to form a dynamic response relationship between light intensity and the output power of the photovoltaic array. Specifically, the module considers the area of ​​the photovoltaic module, the standard conversion efficiency, the current actual radiation intensity, and the degree to which the temperature deviates from the standard temperature to comprehensively calculate the actual output electrical power. When predicting changes in sunlight, historical meteorological data and real-time measurement results can be used to establish an irradiance intensity curve that approximates a sinusoidal waveform to reasonably simulate the light change trend between sunrise and sunset.

[0024] Secondly, the fault monitoring and optimization module uses the collected environmental data, combined with system operating information fed back by the remote monitoring platform, to diagnose potential fault points and optimize operating parameters through multi-data fusion. A common method for determining system efficiency is to compare the electrical energy consumed per unit time for pumping water with the potential energy output by the pump. If an increase in system energy consumption per unit time is detected and cannot be explained by fluctuations in light intensity, it may be due to performance degradation caused by motor efficiency, mechanical jamming, or component aging. In this case, the system automatically activates a fault identification program and recalculates the required motor starting torque based on the actual motor load, pump head, and pumping flow rate, ensuring that the starting torque exceeds the minimum operating requirement. Furthermore, the spacing between arrays is adjusted based on the site topography and local sunlight angle. For example, at noon on the winter solstice, when the sun is at its lowest altitude, the array spacing needs to be increased to avoid shadows and improve overall light utilization.

[0025] Finally, the testing and stability assessment module verifies the system in real-world application scenarios. After deploying the optimized system in remote, arid areas, the system's energy efficiency ratio (EER) is evaluated by continuously collecting key operating parameters such as voltage, current, and flow. This compares the efficiency relationship between the water flow potential energy output by the pump and the electrical energy provided by the photovoltaic system. This real-time operating data is used to develop a long-term performance model to assess the system's stability and adaptability under different seasons and lighting conditions. This data also provides data support for future large-scale deployment and parameter tuning.

[0026] The photovoltaic water pump irrigation system provided by this invention can adapt to operational requirements in diverse geographical environments and climatic conditions, making it particularly suitable for remote mountainous areas and arid areas without electricity. The system collects key environmental variables in real time and dynamically optimizes the layout structure and motor parameters, effectively improving the energy conversion efficiency of the photovoltaic array and the compatibility of water pump operation. Through remote monitoring and intelligent analysis, fault locations can be quickly located and parameter corrections can be made, significantly improving the system's maintenance efficiency and reliability. Finally, the system demonstrated excellent adaptability and sustained operation capabilities in stability assessments, making it suitable for low-cost, high-efficiency irrigation deployment.

[0027] The fault monitoring and optimization module determines the location of faults in remote mountain irrigation scenarios based on radiation intensity distribution and ambient temperature fluctuation data. Based on the radiation intensity distribution and ambient temperature fluctuation data, the effect of array tilt angle and array orientation adjustment on output efficiency was analyzed; Considering the impact of shadows and array spacing design, an array layout plan suitable for irrigation scenarios in remote mountainous areas is determined.

[0028] In this implementation, the fault monitoring and optimization module analyzes the spatial distribution of solar radiation intensity and ambient temperature variations to identify potential fault locations in irrigation systems operating in remote mountainous areas. Key technologies for this are evaluating the impact of the PV array's installation position on power generation efficiency and optimizing solar shading and array spacing.

[0029] First, in terms of array attitude analysis, the system uses measured illumination data and temperature information, combined with the changes in the sun's altitude and azimuth at different times and seasons, to evaluate the impact of the photovoltaic array's tilt angle and orientation angle on the efficiency of receiving solar energy. For example, based on the angle between sunlight and the array surface, the system calculates the degree of influence of this angle on the amount of solar radiation received per unit area, thereby determining whether the current array attitude is in the optimal state. Usually, the optimal tilt angle will be slightly higher or slightly lower than the local latitude value, and the orientation of the array is preferably due south. The specific adjustment angle depends on the utilization target of sunlight in the early morning or evening. The system compares the annual sunlight utilization curves under different attitudes and selects the tilt and orientation scheme with the highest average annual energy efficiency as the recommended parameters.

[0030] Secondly, in terms of spacing and shading optimization, in order to prevent the front and back photovoltaic arrays from blocking each other during periods of low solar altitude, the system calculates the minimum safe spacing based on the lowest solar altitude at noon on the local winter solstice, combined with the height difference between the front and rear edges of the array. For example, in mid-latitude regions, the sun is lower at the winter solstice, and the distance between the arrays needs to be large enough to ensure that the front arrays do not block the illuminated surface of the rear arrays at noon. This calculation is based on a simulation of the geometric relationship between the solar elevation angle and the projection of the photovoltaic array. In complex terrain, the system will also combine local terrain, mountain shadow projection, and building shading factors to propose stepped arrangements or regional layout suggestions.

[0031] For fault identification, the system compares the power output of arrays. If one array's power is significantly lower than that of adjacent arrays, and the light intensity and temperature at its location are normal, the system initially determines that the array's lighting efficiency may have decreased due to improper orientation, obstructions, or installation errors. Furthermore, when combined with a thermal imaging module, it can further identify hot spots in battery modules caused by uneven localized light exposure, providing additional support for fault diagnosis.

[0032] In summary, this module can not only timely locate energy efficiency decline caused by poor environmental adaptability or unreasonable arrangement, but also automatically provide array posture adjustment suggestions and reasonable arrangement plans to ensure the system's optimal power generation state in complex mountainous environments.

[0033] The fault monitoring and optimization adjustment module determines the fault location of the system in remote mountainous irrigation scenarios based on radiation intensity distribution and ambient temperature fluctuation data, and also includes: Calculate the load demand in the irrigation scenario by combining the output power data of the array layout plan with the pump flow demand and pump head parameters; Obtain the performance curves of brushless DC motor efficiency and AC variable frequency motor speed regulation to determine whether the motor rated power range meets the requirements of operating load fluctuations.

[0034] In this embodiment, to ensure that the photovoltaic system drives the water pump to achieve efficient and stable irrigation operation, the system needs to comprehensively evaluate the load demand based on the relationship between the actual output capacity of the photovoltaic array and the working requirements of the water pump, and confirm whether the configured motor can meet the operating conditions.

[0035] First, the system uses the power output data from the actual array layout as its basic input. This output power is calculated using a previously established prediction model combined with actual solar radiation intensity, ambient temperature, array inclination and orientation, reflecting the system's maximum power supply capacity within a specific time period.

[0036] Next, the system calculates the total load power required by the pump under normal operation based on the pump's operating parameters in the irrigation scenario, including flow demand and head. The flow rate is calculated based on the irrigated area and unit irrigation time, for example, the amount of water required to irrigate 10 mu of farmland in one hour. The head refers to the total vertical height difference and pipe resistance required to overcome from the water source to the irrigation destination. The system then estimates the required drive power based on the pump's actual energy efficiency (typically between 60% and 80%). This load value reflects the minimum power supply required by the photovoltaic system for actual irrigation.

[0037] The system then retrieves performance curve information for brushless DC motors and AC variable-frequency motors from a database or actual measurements. Performance curves typically include characteristics such as the motor's efficiency distribution and power output variations at different speeds and loads. By comparing the current load power value with the motor's rated output range, the system determines whether the motor can meet the load fluctuations in irrigation scenarios. If the load power exceeds the motor's rated output range, the system will indicate a risk of insufficient power and recommend replacing it with a motor of a higher power rating. If the current motor is significantly overpowered, it will also recommend downsizing the motor to save costs and improve efficiency.

[0038] In addition, for systems using variable-frequency motors, the module also analyzes the motor's output stability under different frequency adjustments, confirming its response speed and sustainability during high- and low-load transitions, ensuring the pump can continue to operate smoothly when light conditions fluctuate.

[0039] In summary, the module ensures coordinated power transmission between the photovoltaic array, motor, and water pump through series power evaluation, motor performance comparison, and output adaptability analysis, providing a dynamic adjustment basis for system operation and improving stability and reliability in remote irrigation tasks.

[0040] The fault monitoring and optimization adjustment module determines the fault location of the system in remote mountainous irrigation scenarios based on radiation intensity distribution and ambient temperature fluctuation data, and also includes: Analyze the stability of the motor's starting torque and heat dissipation performance during long-term operation in remote and arid areas, based on the motor's rated power range and pump head parameters; Determine the capacity matching solution between motors and pumps in small-scale irrigation scenarios.

[0041] In this embodiment, to ensure the long-term stable operation of the photovoltaic water pump system in small-scale irrigation scenarios in remote and arid areas, the fault monitoring and optimization adjustment module focuses on analyzing the motor's starting capability and heat dissipation performance, while also evaluating the capacity matching relationship between the motor and the water pump.

[0042] First, the system calculates the starting torque required to overcome the hydrostatic pressure at pump startup based on the pump head and flow parameters determined by the on-site irrigation needs. This calculation takes into account the water density, the head corresponding to the terrain drop, the water flow rate, and the pump shaft speed. The result is compared with the maximum torque capacity of the selected motor at startup. If the motor's starting torque is insufficient to meet this requirement, the system will identify it as a risk of insufficient starting failure and prompt the user to replace the motor with a motor with higher starting capacity, adjust the pump type, reduce the head, or reduce the initial load pressure.

[0043] Secondly, when assessing long-term operational reliability, the system considers the motor's adaptability to heat dissipation in remote, high-temperature environments. This process first estimates the motor's power loss during operation, which is equal to the motor's total power multiplied by its energy efficiency loss. Then, based on the local maximum temperature and the motor's heat dissipation performance parameters, the system calculates the maximum temperature the motor windings may reach. If this temperature exceeds the safe tolerance limit of the motor's insulation material, the system will indicate an overheating risk and recommend installing a heat sink, forced air cooling, or selecting a motor with a higher insulation grade and improved efficiency.

[0044] Finally, to ensure a reasonable capacity ratio between the motor and the water pump in small-scale irrigation applications, the system provides the following matching strategy: the rated power of the motor should be slightly higher than the actual load power of the water pump, about 10 to 20 percent, to absorb the power fluctuations caused by load fluctuations and changes in light intensity; the starting torque of the motor should be at least 120 percent of the actual demand to ensure a stable starting process; in addition, it is recommended to select a motor with a good natural heat dissipation structure or a built-in cooling mechanism to enhance the system's ability to continue operating in extreme environments.

[0045] In summary, this module achieves a comprehensive adaptation assessment of small-scale irrigation power systems through systematic modeling and analysis of motor starting torque and heat dissipation performance, combined with water pump load characteristics, significantly improving the system's safety, stability, and technical and economic efficiency in remote areas.

[0046] The fault monitoring and optimization adjustment module determines the fault location of the system in remote mountainous irrigation scenarios based on radiation intensity distribution and ambient temperature fluctuation data, and also includes: According to the capacity matching plan, the output voltage and current data of the photovoltaic array are collected under specific array tilt angles and array orientation adjustments; An improved perturbation observation method is used to design a hardware circuit based on a single chip microcomputer to determine the maximum power point position.

[0047] To ensure optimal power output from photovoltaic arrays in remote mountainous irrigation scenarios, this system employs an improved perturbation-and-observe method, using a microcontroller-controlled hardware circuit to perform maximum power point tracking. This process involves two key components: first, collecting voltage and current data from the array at different positions based on a capacity matching scheme; and second, using a control algorithm to determine whether the photovoltaic modules are currently operating at their maximum power point.

[0048] First, the system adjusts the tilt angle and orientation of the PV array based on the previously determined capacity matching plan to maximize solar radiation within the target time period. During this state, voltage and current sensors respectively collect the array's actual output voltage and current. The system multiplies these values ​​to obtain the current power value and continuously records these values ​​in a time series for subsequent power trend analysis. The system then uses the perturbation-and-observe method to determine the maximum power point. Specifically, each time a new set of voltage and current data is collected, the system compares it with the previous data to calculate the power trend. If the current power is higher than the previous one and the voltage is also rising, the adjustment direction is correct and the system will continue to adjust in the original direction. If the current power is increasing but the voltage is decreasing, the system will determine the current direction is incorrect and reverse the voltage adjustment. If the power decreases, the system will adjust the voltage control direction to attempt to return to a higher power operating point, regardless of whether the voltage rises or falls. To improve the algorithm's stability under conditions of cloudy mountains and frequent light fluctuations, the system also introduced two optimization mechanisms: one is to adopt a step strategy with adjustable change amplitude, that is, to use large step sizes for rapid adjustment when power changes drastically, and to use small step sizes for detailed search when changes slow down; the second is to add a sliding average judgment mechanism to smooth continuous power values ​​and reduce the interference of short-term abnormal disturbances on algorithm judgment.

[0049] All control strategies are executed in real time by the microcontroller. The microcontroller has an embedded analog-to-digital conversion module that reads sensor data in real time and outputs control signals to the pulse-width modulation control port of the DC converter, adjusting the duty cycle to change the output voltage, thereby guiding the system operating point toward maximum power. Furthermore, to ensure safe and reliable system operation, the hardware circuit is equipped with voltage protection, overcurrent detection, and temperature sensing modules to implement power-limiting protection for the system in extreme weather or when the equipment overheats. Through the aforementioned working mechanism, the system can quickly and accurately track and maintain the photovoltaic array operating at its optimal power output state under complex environmental conditions, significantly improving the overall system's energy efficiency output and irrigation stability.

[0050] The fault monitoring and optimization adjustment module determines the fault location of the system in remote mountainous irrigation scenarios based on radiation intensity distribution and ambient temperature fluctuation data, and also includes: The output data of the maximum power point position is used, combined with the motor's heat dissipation performance and operating load fluctuations, to drive the power tube to perform voltage regulation on the battery pack; Obtain the charge and discharge status of battery packs in remote areas without electricity and determine intelligent control strategies.

[0051] In this embodiment, in order to achieve energy autonomy and stable operation of the system in remote areas without electricity, the system uses the output power data obtained through maximum power point tracking, combined with the motor's heat dissipation capacity and fluctuations in the operating load, to control the power regulation element to perform voltage regulation operations on the battery pack, and determine the appropriate intelligent control strategy by analyzing the current state of the battery pack.

[0052] First, the system uses voltage and current sensors to obtain the actual output voltage and current of the PV array at its maximum power point and calculates the output power at that point. Based on the battery's current state and desired charging characteristics, the system uses a microcontroller to output a regulation signal, controlling the on-duty cycle of power transistors such as field-effect transistors (FETs) or insulated-gate bipolar transistors (IGBTs), resulting in a DC converter output voltage that matches the battery's charging curve. This output voltage is typically higher than the battery voltage to enable charging. Depending on the battery type, the system enters either a constant current or constant voltage phase, ensuring a safe and efficient charging process.

[0053] While performing voltage regulation, the system also collects real-time data on the motor's operating temperature and load change rate to assess the risk of instability due to overheating or load fluctuations. To this end, the system calculates an instantaneous output power limit, which is the system's rated output power minus the power derating required due to rising motor temperatures and the buffer margin required for rapid load changes. If the actual output power exceeds this limit, the system will limit the current by adjusting the output amplitude of the power transistor to prevent motor overheating or system tripping.

[0054] In addition, to achieve intelligent management, the system also makes real-time judgments on the battery pack's charging status, including collecting the current terminal voltage, current, temperature, and estimated state of charge percentage. Depending on the different ranges of the state of charge, the system will implement corresponding control strategies: When the state of charge is higher than 85 percent and there are sufficient solar resources, the system will switch the charging mode to trickle charging or stop charging to extend battery life; when the state of charge is lower than 20 percent, the system will shut down non-critical loads and enter energy-saving mode to ensure continuous power supply for basic irrigation tasks; within the normal charge range, the system intelligently adjusts the power supply period and power distribution based on the balance between current load demand and remaining power, such as giving priority to high-efficiency irrigation equipment or implementing a timed irrigation plan.

[0055] The above control strategy can be set based on fixed threshold logic, or it can be dynamically optimized through fuzzy control or prediction model based on long-term operation data.

[0056] In summary, the system integrates multiple factors such as maximum power output, motor thermal stability, and battery state of charge into the voltage regulation and intelligent control process, realizing a true closed-loop energy control mechanism. This is particularly suitable for remote areas without electricity, and can achieve a stable, efficient, and autonomous photovoltaic irrigation operation solution.

[0057] The fault monitoring and optimization adjustment module determines the fault location of the system in remote mountainous irrigation scenarios based on radiation intensity distribution and ambient temperature fluctuation data, and also includes: Based on the intelligent control strategy, the Internet of Things technology is used to build a remote monitoring platform to obtain real-time operating data from the radiation intensity distribution of the photovoltaic array and the water pump flow demand; Determine the location of system faults in remote mountain irrigation scenarios.

[0058] In this implementation, the system incorporates IoT technology to build a remote monitoring platform, enabling real-time operational status monitoring and fault identification of photovoltaic water pump irrigation systems in remote mountainous areas. The monitoring platform wirelessly aggregates sensor data from key equipment, such as photovoltaic arrays, water pumps, and batteries, to a cloud-based system, enabling continuous analysis of system performance and early warning.

[0059] First, at the data collection level, the platform deploys a variety of sensors to capture core system operating parameters. These include: a light sensor to record solar radiation intensity per unit area; a temperature sensor to record the current ambient temperature; voltage and current sensors to record the output capacity of the photovoltaic array; a water flow sensor and pressure sensor to record the amount of water delivered by the pump and the corresponding head; a motor temperature sensor, and a battery state-of-charge acquisition module. All sensors connect to a data gateway via low-power wireless modules such as LoRa, NB-IoT, or cellular networks, ultimately uploading data to a remote data server.

[0060] The system then performs model calculations and comparative analysis on the collected data on the cloud platform, establishing two types of key performance prediction models. One is the photovoltaic array power model, which calculates the maximum electrical power that the system can theoretically output based on parameters such as light intensity, temperature, component area, and efficiency. The effect of temperature on the attenuation of component efficiency is also taken into account: the higher the temperature, the lower the efficiency. The other is the irrigation load model, which uses measured water flow and head data, combined with water density, gravitational acceleration, and pump efficiency, to estimate the input power required by the pump under these operating conditions. Both models are based on engineering physics constants and equipment technical parameters, and are continuously compared and corrected with measured data.

[0061] When determining system fault points, the platform executes a series of rule-based judgment logic. For example, if the measured photovoltaic output power is significantly lower than the theoretical calculated value, while the current light intensity and ambient temperature are within the normal range, the platform will initially determine that there may be faults such as PV panel obstruction, layout angle deviation, or poor cable connection. If the water pump's power remains stable but the output water volume is lower than expected, the system may have problems such as pipe blockage, insufficient head setting, or pump aging. If the motor temperature exceeds the threshold for a long period of time, the system indicates the risk of abnormal heat dissipation or excessive load. If the battery is detected to be in an abnormally low state during periods of high sunlight, the system will further analyze whether there is battery performance degradation or control logic failure.

[0062] The platform displays all analysis results in real time on a visual interface, displaying fault type, severity, and geographic location. Maintenance personnel can remotely identify specific problem areas and schedule targeted repairs or adjust operating parameters remotely. The system also automatically records and archives fault characteristics to form a historical analysis database for equipment operation, supporting future optimization designs and intelligent forecasting.

[0063] In summary, this working principle realizes efficient remote management and autonomous fault identification mechanism of photovoltaic irrigation systems in remote areas through the synergy of perception layer, communication layer, analysis layer and control layer, greatly improving the system operation efficiency and maintenance response speed.

[0064] The light information collection module also includes a light intensity adjustment module for automatically adjusting the light receiving angle of the photovoltaic cell array according to different seasonal light conditions to improve the light intensity collection efficiency; The time scheduling system is used to adjust the frequency of light information collection according to the light conditions at different times of the day to improve the operating efficiency of the photovoltaic array.

[0065] In this embodiment, the light information acquisition module integrates a light intensity adjustment module with a time scheduling system to achieve refined acquisition and dynamic management of solar radiation energy, significantly improving the energy conversion efficiency of the photovoltaic array across different seasons, time periods, and climatic conditions. Specifically, the light intensity adjustment module, through an embedded angle calculation unit and actuator, calculates the changes in the solar altitude and azimuth in real time based on the local geographic location, the current date, and a preset seasonal light model. It then adjusts the tilt angle of the photovoltaic array accordingly, ensuring that the photovoltaic surface always receives solar radiation as vertically as possible, thereby maximizing the effective amount of light received. The module can adopt a single-axis or dual-axis tracking structure, combined with a stepper motor or hydraulic actuator. Through a high-precision position feedback mechanism, closed-loop control of angle changes adapts to the natural variation of low solar elevation angles in winter and strong direct solar radiation in summer. Furthermore, the time scheduling system dynamically adjusts the data collection frequency based on real-time light intensity curves and prediction models: increasing the sampling frequency during the rapid light changes in the early morning and evening to capture the detailed changes in the photovoltaic array's response; reducing the sampling frequency during the midday light period or cloudy weather to reduce system power consumption while preventing redundant data from interfering with analysis accuracy. Furthermore, the time scheduling strategy incorporates environmental perception and historical data training results, enabling autonomous optimization via local control algorithms and updating the strategy table with weather forecast information from a remote server. Throughout system operation, light intensity regulation and sampling rhythm control work in tandem to not only ensure the representativeness and timeliness of light data but also significantly improve the specific power output of photovoltaic modules through posture optimization. This is particularly suitable for applications in areas with unstable light resources or complex terrain, helping to ensure the continuous energy supply and intelligent operation of the irrigation system.

[0066] The fault monitoring and optimization adjustment module also includes: Environmental impact analysis unit, used to analyze the impact of seasonal light changes on system performance and provide adjustment solutions; The motor torque regulation unit is used to adjust the starting torque and operating parameters of the motor in real time according to the efficiency fluctuation of the brushless DC motor to optimize motor performance and reduce energy waste; The system optimization feedback interface is used to automatically adjust the array spacing design and perform performance adjustments based on data feedback during operation to ensure stable operation of the system under different environmental conditions.

[0067] In this embodiment, the fault monitoring and optimization module implements three subunits: environmental impact analysis, dynamic motor torque control, and system feedback regulation. This module enables adaptive operation and multi-dimensional energy efficiency optimization of the photovoltaic water pump irrigation system under complex climate conditions. First, the environmental impact analysis unit models the changing trends of solar incidence angle, sunshine duration, and irradiance intensity across different seasons based on a solar year cycle model and historical sunlight data. By comparing this with real-time sunlight data, it analyzes the impact of the current environment on the system's power generation efficiency and load response. When a declining sunlight utilization rate due to seasonal changes is identified, the system proposes adjustments, including array attitude angle adjustment, operating time switching, and charge-discharge strategy optimization, to mitigate output power fluctuations caused by environmental changes. Second, the motor torque regulation unit obtains the brushless DC motor's operating efficiency curve and current motor temperature, current, and speed data in real time to determine whether the motor is in its efficient operating range. Based on the load variation caused by sunlight fluctuations, it dynamically adjusts its starting torque and speed regulation strategy. This ensures that the motor operates at optimal efficiency while maintaining driving capacity, reducing energy consumption and heat loss in the inefficient range, thereby improving overall system responsiveness and energy efficiency. Thirdly, the system optimization feedback interface collects operating parameters such as voltage differences between arrays, light shading conditions, motor load rate, and irrigation water flow, and builds an operating status feedback model based on rule logic or machine learning algorithms. When it identifies problems such as shading or insufficient spacing in the array arrangement, it automatically recommends adjusting the array spacing, staggered installation, or arrangement density to improve light utilization and water pump operation efficiency. At the same time, the interface can also link other modules to automatically implement small-scale arrangement fine-tuning and scheduling strategy corrections to achieve feedback closed-loop control. Overall, this working mechanism effectively enhances the system's adaptability to changes in the external environment, reduces the frequency of manual intervention, and significantly improves the stability, reliability, and energy utilization of the irrigation system under multiple climate conditions throughout the year.

[0068] The testing and stability assessment module also includes: System operation data acquisition unit, used to collect system power output, energy efficiency ratio and working status data in real time during the test; Data analysis and evaluation unit, used to process collected test data, analyze the system's energy efficiency performance under different environments and working conditions, and output stability reports; The tuning instruction generation unit is used to automatically generate optimization plans based on the evaluation results and guide the tuning adjustments during system operation.

[0069] In this embodiment, the testing and stability assessment module integrates a system operation data acquisition unit, a data analysis and evaluation unit, and a tuning instruction generation unit to form a closed-loop operational performance assessment and intelligent tuning system. During the test deployment phase, the system operation data acquisition unit connects to voltage, current, flow rate, and temperature sensors on the photovoltaic output side, motor control side, and pump load side to continuously and in real time acquire power output, energy efficiency ratio (EER) indicators (energy consumed per unit of water flow), and overall system operating status parameters. The acquisition process covers various time periods and weather conditions to ensure broad data representation. Subsequently, the data analysis and evaluation unit organizes and models this raw data, identifying operational efficiency and response stability under various typical scenarios, including high and low irradiation, varying temperatures, and varying loads. By comparing and analyzing energy efficiency trends under various environmental variables, the system quantifies the system's performance under specific conditions. The system ultimately outputs an operational stability assessment report containing key indicators such as the system's average EER, failure rate, and response latency. Based on the evaluation results, the tuning instruction generation unit will call upon the system's preset strategy database and, in conjunction with the evaluation conclusions, automatically generate tuning recommendations. These recommendations include array angle adjustment, motor operating parameter setting, battery discharge strategy optimization, and other instructions. These recommendations can then be sent directly to the system control module via the control interface for implementation. This module also supports comparing operating data before and after the test to verify the effectiveness of the tuning measures and further modify the strategy, achieving intelligent closed-loop control of the entire process from data collection and analysis to execution. Through this working mechanism, the system not only achieves dynamic verification of its adaptability to complex environments, but also possesses self-learning and optimization capabilities, effectively improving the performance stability and intelligent operation and maintenance level of the photovoltaic water pump irrigation system in actual deployment.

[0070] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A photovoltaic water pump irrigation system, characterized in that: The system comprises: The light information acquisition module is used to obtain the radiation intensity distribution and ambient temperature fluctuation data of the photovoltaic cell array in the target area. Combined with the changes in the incident angle of light, the sensor collects real-time light information at different times of the day to determine the output power performance of the array under specific seasonal light changes; The fault monitoring and optimization module is used to determine the location of system faults in remote mountain irrigation scenarios based on radiation intensity distribution and ambient temperature fluctuation data. Using fault location data collected by the remote monitoring platform, combined with seasonal light variations and fluctuations in brushless DC motor efficiency, it adjusts array spacing design and motor starting torque parameters to determine an optimized operation plan for small-scale irrigation in remote, off-grid areas. The test and stability assessment module is used to deploy test systems in remote mountainous areas and arid areas without electricity according to the optimized operation plan. It collects energy efficiency data of the system under specific light incident angles and AC variable frequency motor speed regulation to determine the overall operational stability of the system.

2. A photovoltaic water pump irrigation system according to claim 1, characterized in that: The fault monitoring and optimization adjustment module determines the fault location of the system in a remote mountain irrigation scenario based on the radiation intensity distribution and ambient temperature fluctuation data, including: Based on the radiation intensity distribution and ambient temperature fluctuation data, the effect of array tilt angle and array orientation adjustment on output efficiency was analyzed; Considering the impact of shadows and array spacing design, an array layout plan suitable for irrigation scenarios in remote mountainous areas is determined.

3. A photovoltaic water pump irrigation system according to claim 2, characterized in that: The fault monitoring and optimization adjustment module determines the fault location of the system in the remote mountain irrigation scenario based on the radiation intensity distribution and the ambient temperature fluctuation data, and further includes: Calculate the load demand in the irrigation scenario by combining the output power data of the array layout plan with the pump flow demand and pump head parameters; Obtain the performance curves of brushless DC motor efficiency and AC variable frequency motor speed regulation to determine whether the motor rated power range meets the requirements of operating load fluctuations.

4. A photovoltaic water pump irrigation system according to claim 3, characterized in that: The fault monitoring and optimization adjustment module determines the fault location of the system in the remote mountainous irrigation scenario based on the radiation intensity distribution and the ambient temperature fluctuation data, and further includes: Analyze the stability of the motor's starting torque and heat dissipation performance during long-term operation in remote and arid areas, based on the motor's rated power range and pump head parameters; Determine the capacity matching solution between motors and pumps in small-scale irrigation scenarios.

5. The photovoltaic water pump irrigation system according to claim 4, characterized in that: The fault monitoring and optimization adjustment module determines the fault location of the system in the remote mountain irrigation scenario based on the radiation intensity distribution and the ambient temperature fluctuation data, and further includes: According to the capacity matching plan, the output voltage and current data of the photovoltaic array are collected under specific array tilt angles and array orientation adjustments; An improved perturbation observation method is used to design a hardware circuit based on a single chip microcomputer to determine the maximum power point position.

6. The photovoltaic water pump irrigation system according to claim 5, characterized in that: The fault monitoring and optimization adjustment module determines the fault location of the system in the remote mountain irrigation scenario based on the radiation intensity distribution and the ambient temperature fluctuation data, and further includes: The output data of the maximum power point position is used, combined with the motor's heat dissipation performance and operating load fluctuations, to drive the power tube to perform voltage regulation on the battery pack; Obtain the charge and discharge status of battery packs in remote areas without electricity and determine intelligent control strategies.

7. The photovoltaic water pump irrigation system according to claim 6, characterized in that: The fault monitoring and optimization adjustment module determines the fault location of the system in the remote mountain irrigation scenario based on the radiation intensity distribution and the ambient temperature fluctuation data, and further includes: Based on the intelligent control strategy, the Internet of Things technology is used to build a remote monitoring platform to obtain real-time operating data from the radiation intensity distribution of the photovoltaic array and the water pump flow demand; Determine the location of system faults in remote mountain irrigation scenarios.

8. The photovoltaic water pump irrigation system according to claim 1, characterized in that: The illumination information acquisition module further includes: Light intensity adjustment module, used to automatically adjust the light receiving angle of the photovoltaic cell array according to different seasonal lighting conditions to improve the light intensity collection efficiency; The time scheduling system is used to adjust the frequency of light information collection according to the light conditions at different times of the day to improve the operating efficiency of the photovoltaic array.

9. The photovoltaic water pump irrigation system according to claim 1, characterized in that: The fault monitoring and optimization adjustment module also includes: Environmental impact analysis unit, used to analyze the impact of seasonal light changes on system performance and provide adjustment solutions; The motor torque regulation unit is used to adjust the starting torque and operating parameters of the motor in real time according to the efficiency fluctuation of the brushless DC motor to optimize motor performance and reduce energy waste; The system optimization feedback interface is used to automatically adjust the array spacing design and perform performance adjustments based on data feedback during operation to ensure stable operation of the system under different environmental conditions.

10. The photovoltaic water pump irrigation system according to claim 1, characterized in that: The test and stability assessment module also includes: System operation data acquisition unit, used to collect system power output, energy efficiency ratio and working status data in real time during the test; Data analysis and evaluation unit, used to process collected test data, analyze the system's energy efficiency performance under different environments and working conditions, and output stability reports; The tuning instruction generation unit is used to automatically generate optimization plans based on the evaluation results and guide the tuning adjustments during system operation.

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