Photovoltaic pumping system, method and device

Abstract

The invention relates to a photovoltaic pumping system, method and device. The method comprises the following steps: acquiring environment parameter information and growth stage information of crops; obtaining the irrigation water demand of the crops according to the environment parameter information and the growth stage information of the crops; acquiring illumination intensity within a preset time length; determining the first power generation quantity of all the photovoltaic modules according to the illumination intensity within the preset time duration; acquiring first target electric quantity required by all water pumps for outputting irrigation water demand according to preset power; when the electricity generation amount is larger than or equal to the first target electricity amount, all water pumps are controlled to start working according to preset power; and when the electricity generation amount is smaller than the first target electricity amount, all the water pumps are controlled to start working according to preset power, and the central energy storage system is controlled to complement the difference electricity amount.

Description

Technical Field

[0001] The present disclosure relates to the field of photovoltaic water pumping, and in particular to a photovoltaic water pumping system, method and device. Background Art

[0002] Photovoltaic pumping system is a system that uses solar photovoltaic power generation to drive water pumps. Its core principle is to convert solar energy into direct current through photovoltaic modules, and then convert the direct current into alternating current through photovoltaic pumping inverters to provide power for the water pump motor to pump water from low to high.

[0003] With the development of renewable energy technology, photovoltaic pumping systems have been widely used in agricultural irrigation.

[0004] However, due to the influence of weather changes, the power generation of photovoltaic modules is unstable, which leads to unstable operation of the water pump, thus affecting the stability of the photovoltaic pumping system. Summary of the invention

[0005] In order to overcome the problems existing in the related art, the embodiments of the present disclosure provide a photovoltaic pumping system, method and device. The technical solution is as follows:

[0006] According to a first aspect of an embodiment of the present disclosure, there is provided a photovoltaic pumping system, comprising:

[0007] controller, central energy storage system and multiple photovoltaic pumping subsystems;

[0008] Each of the photovoltaic pumping subsystems comprises: a photovoltaic module, and a water pump connected to the photovoltaic module;

[0009] The controller is respectively connected to the central energy storage system, the photovoltaic assembly and the water pump;

[0010] The central energy storage system is connected to each of the photovoltaic modules.

[0011] A second aspect of the present disclosure provides a photovoltaic pumping method, which is applied to a controller in the photovoltaic pumping system of the first aspect, and comprises:

[0012] Obtain information on environmental parameters and crop growth stages;

[0013] Acquiring the irrigation water requirement of the crop according to the environmental parameter information and the growth stage information of the crop;

[0014] Get the light intensity within a preset time length;

[0015] Determining a first power generation of all the photovoltaic modules according to the light intensity within the preset time length;

[0016] Obtaining a first target amount of electricity required for all the water pumps to output the irrigation water demand according to a preset power;

[0017] When the power generation is greater than or equal to the first target power, controlling all the water pumps to start working according to the preset power;

[0018] When the power generation amount is less than the first target power, all the water pumps are controlled to start working according to the preset power, and the central energy storage system is controlled to make up for the power difference.

[0019] In one embodiment, after controlling all the water pumps to start working according to the preset power, the method further includes:

[0020] Control each of the photovoltaic modules to store the remaining electricity in the central energy storage system.

[0021] In one embodiment, after controlling each of the photovoltaic modules to store the remaining electricity in the central energy storage system, the method further includes:

[0022] Obtaining the real-time charge state of the central energy storage system;

[0023] When it is detected that the real-time state of charge of the central energy storage system meets the preset state of charge requirement, each of the photovoltaic components is controlled to reduce the output power.

[0024] In one embodiment, when the power generation is less than the first target power, controlling all the water pumps to start working according to the preset power, and controlling the central energy storage system to make up for the power difference, includes:

[0025] When the power generation amount is less than the first target power generation amount, obtaining a difference in power between the first target power generation amount and the first power generation amount;

[0026] Obtaining the remaining power of the central energy storage system;

[0027] When it is detected that the remaining power of the central energy storage system is greater than the difference power, all the water pumps are controlled to operate according to the preset power, and the central energy storage system is controlled to make up the difference power;

[0028] When it is detected that the remaining power of the central energy storage system is not greater than the difference power, obtaining a target water pump whose power can be reduced;

[0029] Obtaining a first target power of the target water pump according to the sum of the remaining power of the central energy storage system and the first power generation;

[0030] The target water pump is controlled to operate according to the first target power, the remaining water pumps are controlled to operate according to the preset power, and the central energy storage system is controlled to make up for the difference in power.

[0031] In one embodiment, the method further comprises:

[0032] When a failure of the photovoltaic module in the photovoltaic pumping subsystem is detected, determining a second power generation of the photovoltaic module in the remaining photovoltaic pumping subsystem according to the light intensity within the remaining time length;

[0033] Obtain the remaining irrigation water required to be output by the water pumps in the remaining photovoltaic pumping subsystem within the remaining time length, and the second target power of each of the water pumps;

[0034] When the second power generation is greater than or equal to the power corresponding to the second target power output by the water pumps in the remaining photovoltaic pumping subsystems, the water pumps in the remaining photovoltaic pumping subsystems are controlled to start working according to the second target power, and the photovoltaic modules are controlled to store the remaining power in the central energy storage system;

[0035] When the second power generation is less than the power corresponding to the second target power output by the water pumps in the remaining photovoltaic pumping subsystems, the water pumps in the remaining photovoltaic pumping subsystems are controlled to start working according to the second target power, and the central energy storage system is controlled to make up for the power difference.

[0036] In one embodiment, the method further comprises:

[0037] Acquiring real-time operating data of each of the photovoltaic modules;

[0038] When it is detected that the real-time operation data of the photovoltaic component does not meet the preset photovoltaic component operation requirements, outputting the identification of the photovoltaic component that does not meet the preset photovoltaic component operation requirements;

[0039] Acquire real-time operation data of each of the water pumps;

[0040] When it is detected that the real-time operation data of the water pump does not meet the preset water pump operation requirements, an identification of the water pump that does not meet the preset water pump operation requirements is output.

[0041] In one embodiment, the method further comprises:

[0042] Obtaining the reason why the photovoltaic component does not meet the preset photovoltaic component operation requirement;

[0043] Obtaining the reason why the water pump does not meet the preset water pump operation requirement;

[0044] Generate a fault diagnosis report, the fault diagnosis report including: the identification of the photovoltaic component that does not meet the preset photovoltaic component operation requirements, and the reason why the photovoltaic component does not meet the preset photovoltaic component operation requirements; the identification of the water pump that does not meet the preset water pump operation requirements, and the reason why the water pump does not meet the preset water pump operation requirements;

[0045] The fault diagnosis report is outputted.

[0046] In one embodiment, the method further comprises:

[0047] Obtaining the remaining power of each photovoltaic module;

[0048] Transmitting the value of the remaining power to the blockchain network;

[0049] Receiving transaction settlement information returned by the blockchain network;

[0050] Output the transaction settlement information.

[0051] A third aspect of the present disclosure provides a photovoltaic pumping device, which is applied to a controller in the photovoltaic pumping system of the first aspect, and comprises:

[0052] A first acquisition module is used to acquire environmental parameter information and crop growth stage information;

[0053] A second acquisition module, used for acquiring the irrigation water requirement of the crop according to the environmental parameter information and the growth stage information of the crop;

[0054] A third acquisition module is used to obtain the light intensity within a preset time length;

[0055] A fourth acquisition module, configured to determine a first power generation amount of all the photovoltaic modules according to the light intensity within the preset time length;

[0056] A fifth acquisition module, used for acquiring a first target amount of electricity required for all the water pumps to output the irrigation water demand according to a preset power;

[0057] A first control module, configured to control all the water pumps to start working according to the preset power when the power generation is greater than or equal to the first target power;

[0058] The second control module is used to control all the water pumps to start working according to the preset power when the power generation is less than the first target power, and control the central energy storage system to make up the difference in power.

[0059] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0061] Figure 1 is a schematic diagram of a photovoltaic pumping system according to an exemplary embodiment Figure 1 .

[0062] Figure 2 is a schematic diagram of a photovoltaic pumping system according to an exemplary embodiment Figure 2 .

[0063] Figure 3 The process diagram of a photovoltaic water pumping method according to an exemplary embodiment is shown in FIG. Figure 1 .

[0064] Figure 4 The process diagram of a photovoltaic water pumping method according to an exemplary embodiment is shown in FIG. Figure 2 .

[0065] Figure 5 The process diagram of a photovoltaic water pumping method according to an exemplary embodiment is shown in FIG. Figure 3 .

[0066] Figure 6 According to an exemplary embodiment Figure 1 Flow chart of the execution steps of step S107 in the photovoltaic pumping method.

[0067] Figure 7 The process diagram of a photovoltaic water pumping method according to an exemplary embodiment is shown in FIG. Figure 4 .

[0068] Figure 8 The figure is a flowchart of a fault diagnosis process according to an exemplary embodiment.

[0069] Fig. 9 is a schematic diagram of a flow chart of a power allocation stage according to an exemplary embodiment.

[0070] Fig.10 It is a schematic structural diagram of a photovoltaic pumping device according to an exemplary embodiment.

[0071] Description of reference numerals:

[0072] 1-controller; 2-central energy storage system; 21-battery pack; 22-bidirectional DC / DC converter; 3-photovoltaic pumping subsystem; 31-photovoltaic module; 311-photovoltaic array, 312-DC / DC converter; 313-DC / AC inverter; 32-water pump. DETAILED DESCRIPTION

[0073] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0074] Figure 1 is a schematic diagram of a photovoltaic pumping system according to an exemplary embodiment. Figure 1 As shown, the photovoltaic pumping system includes:

[0075] Controller 1, central energy storage system 2 and multiple photovoltaic pumping subsystems 3;

[0076] Each of the photovoltaic pumping subsystems 3 comprises: a photovoltaic module 31, and a water pump 32 connected to the photovoltaic module 31;

[0077] The controller 1 is connected to the central energy storage system 2, the photovoltaic module 31 and the water pump 32 respectively;

[0078] The central energy storage system 2 is connected to each of the photovoltaic components 31 .

[0079] Further, such as Figure 2 As shown, the photovoltaic pumping subsystem 3 includes: a photovoltaic array, a DC / DC converter and a DC / AC inverter, and the central energy storage system 2 includes: a battery group 21 and a bidirectional DC / DC converter 22.

[0080] Further, such as Figure 2 As shown, the photovoltaic pumping subsystem includes: a photovoltaic array, a DC / DC converter and a DC / AC inverter, and the central energy storage system includes: a battery pack and a bidirectional DC / DC converter.

[0081] Wherein, the DC / DC converter and the bidirectional DC / DC converter are connected to the DC bus.

[0082] The present disclosure also provides a photovoltaic pumping method for a controller used in the photovoltaic pumping system. Figure 3 As shown, the method comprises the following steps:

[0083] S101. Obtain environmental parameter information and crop growth stage information.

[0084] The environmental parameter information may be obtained through a set sensor, and the environmental parameter information includes but is not limited to: temperature information and humidity information. For example, the temperature information may be obtained through a temperature sensor, and the humidity information may be obtained through a humidity sensor.

[0085] When obtaining the growth stage information of crops, images of the crops can be obtained through equipment such as drones, and then the growth stage information of the crops can be obtained based on image recognition methods.

[0086] For example, the collected images can be preprocessed, including grayscale, noise reduction, image enhancement and other operations. For example, the median filter method is used to remove salt and pepper noise in the image to improve the image quality. Then, the contour of the crop is extracted by edge detection algorithm (such as Canny edge detection), and the morphological characteristics of the crop are identified according to the shape and size of the contour to determine the growth stage. For the color characteristics of the crop, the color space can be converted (such as from RGB to HSV color space), and then the pixels in a specific color range can be extracted for analysis. For example, when judging whether the fruit is ripe, the maturity can be determined by analyzing the hue (H), saturation (S) and lightness (V) values ​​of the fruit color in the HSV color space.

[0087] Convolutional neural networks (CNN) can also be used for image recognition. Specifically, you first need to build a suitable CNN model, such as the commonly used ResNet, VGGNet and other model architectures. Then, collect a large number of crop images labeled with different growth stages as training data sets to train the model. The trained model can classify newly collected crop images and directly output the growth stage of the crop. For example, by training on a data set containing tens of thousands of images of wheat from germination to maturity, the resulting model can accurately classify the growth stage of newly captured wheat field images with an accuracy rate of more than 80%-90%.

[0088] S102: Obtain irrigation water requirement of crops according to environmental parameter information and crop growth stage information.

[0089] The growth stages of crops can include: germination stage, seedling stage, tillering stage (gramineae crops), jointing stage, booting stage (gramineae crops), heading stage (gramineae crops), flowering stage, filling stage (gramineae crops and some legume crops) and maturity stage.

[0090] Different growth stages require different amounts of irrigation. Take cereals as an example:

[0091] Germination period: The soil moisture content is maintained at 60%-70% of the field water holding capacity. If the soil moisture is poor after sowing, it is necessary to irrigate once, with an irrigation volume of about 30-40 cubic meters per mu to ensure smooth germination of the seeds.

[0092] Tillering stage: Soil moisture content should be 70%-80% of field water holding capacity. Depending on soil dryness and wetness, water is generally applied once every 10-15 days, 40-50 cubic meters per mu each time, to promote the occurrence and growth of tillers.

[0093] Jointing stage: This is a critical period for wheat growth, and the demand for water increases. The soil moisture content should reach 75%-85% of the field water holding capacity. Water once every 10-12 days, 50-60 cubic meters per mu each time, which is conducive to the elongation of stem nodes and the differentiation of ears.

[0094] Heading stage - grain filling stage: the soil moisture content is maintained at 70%-80% of the field water holding capacity. During this stage, water is irrigated every 8-10 days, 40-50 cubic meters per mu each time, to ensure that the number of wheat ears increases and the grains are full.

[0095] Maturity period: In order to ensure the quality of wheat and facilitate harvesting, the moisture should be properly controlled during the maturity period. The soil moisture content should be controlled at 60%-70% of the field water holding capacity, and irrigation should be reduced or stopped.

[0096] Among them, an irrigation water requirement table can be preset, which includes the mapping relationship between environmental parameter information, crop growth stage information and irrigation water requirement. After obtaining the environmental parameter information and crop growth stage information, the irrigation water requirement of the crops can be obtained by looking up the table.

[0097] When crops require irrigation, follow these steps:

[0098] S103: Obtain the light intensity within a preset time length.

[0099] When irrigating, you can preset the length of time required for irrigation in advance, for example: irrigation is completed in 10 hours, so you need to pay attention to the light intensity within these 10 hours.

[0100] The light intensity within a preset time length can be obtained through the network.

[0101] S104: Determine a first power generation amount of all photovoltaic modules according to the light intensity within a preset time length.

[0102] After the light intensity within the preset time length is obtained, the power generation of each photovoltaic module can be obtained, thereby obtaining the first power generation of all photovoltaic modules within the preset time length.

[0103] S105: Obtain a first target amount of electricity required for all water pumps to output irrigation water according to a preset power.

[0104] S106: When the power generation is greater than or equal to the first target power, control all water pumps to start working according to the preset power.

[0105] When the first power generation of all photovoltaic modules within the preset time length is greater than or equal to the power required for irrigation, all water pumps are directly controlled to start working at the preset power.

[0106] S107: When the power generation is less than the first target power, all water pumps are controlled to start working according to the preset power, and the central energy storage system is controlled to make up for the power difference.

[0107] When the first power generation of all photovoltaic modules within the preset time length is less than the power required for irrigation, that is, the first power generation of all photovoltaic modules within the preset time length cannot make the water pump run stably according to the preset power, the central energy storage system can make up the difference in power at this time, so that the water pump can run stably, thereby improving the stability of the photovoltaic pumping system.

[0108] In one embodiment, in step S106, after controlling all water pumps to start working according to the preset power, each photovoltaic module can also be controlled to store the remaining power in the central energy storage system, so as to effectively save electricity, make full use of excess solar energy, and improve energy utilization efficiency.

[0109] In one embodiment, after controlling each photovoltaic module to store the remaining power in the central energy storage system, as shown in FIG. Figure 4 As shown, the above method also includes the following steps A1-A2:

[0110] A1. Obtain the real-time charge status of the central energy storage system.

[0111] A2. When it is detected that the real-time state of charge of the central energy storage system meets the preset state of charge requirement, each photovoltaic module is controlled to reduce the output power.

[0112] Among them, satisfying the preset state of charge may be greater than a preset state of charge threshold, for example: the preset state of charge threshold is 95%. When the power generation is greater than the first target power corresponding to the irrigation water demand, the excess power can be calculated and the excess power can be preferentially stored in the central energy storage system. If the real-time SOC of the central energy storage system is greater than 95%, the output power of each photovoltaic module is reduced by adjusting the DC / DC converter of each photovoltaic module.

[0113] In another embodiment, Figure 5As shown, in step S106, after all water pumps are controlled to start working according to the preset power, the method further includes the following sub-steps B1-B4:

[0114] B1. Obtain the remaining power of each photovoltaic module;

[0115] B2. Transmit the value of the remaining power to the blockchain network;

[0116] B3. Receive transaction settlement information returned by the blockchain network;

[0117] B4. Output transaction settlement information.

[0118] With the continuous development of distributed energy resources (such as solar photovoltaic power generation, small wind power generation, home energy storage equipment, etc.), the traditional centralized energy trading model is difficult to meet the trading needs of distributed energy. Blockchain technology provides a decentralized, transparent, secure and efficient solution for distributed energy trading. Blockchain is a distributed ledger technology that links transaction data in the form of blocks through cryptographic methods. Each block contains transaction information within a certain period of time.

[0119] Accurate energy metering is the basis of distributed energy trading. It can obtain the remaining power of each photovoltaic module, and then upload the remaining power value to the blockchain so that transactions can be settled based on the actual power consumption.

[0120] In one possible implementation, an energy trading module may be provided in the controller, which implements a distributed energy trading mechanism based on blockchain, and may use Ethereum smart contracts to realize automated energy trading and settlement, and automatically execute long-term energy purchase agreements (PPAs) through smart contracts. Specifically:

[0121] a) Treat each PV pumping subsystem as a microgrid node, so that the surplus power of the PV modules in each PV pumping subsystem can be traded;

[0122] b) Provide API interface to interact with external power grid and energy market.

[0123] When trading, a consensus algorithm (such as Proof of Stake PoS) can be used to maintain the security and efficiency of the transaction, and a real-time pricing mechanism can be adopted to dynamically adjust the price of electricity based on supply and demand.

[0124] In one embodiment, Figure 6 As shown, when the power generation is less than the first target power, all water pumps are controlled to start working according to the preset power, and the central energy storage system is controlled to make up for the difference in power, including the following sub-steps S1071-S1076:

[0125] S1071. When the power generation amount is less than the first target power generation amount, obtain the difference power between the first target power generation amount and the first power generation amount.

[0126] S1072. Obtain the remaining power of the central energy storage system.

[0127] S1073. When it is detected that the remaining power of the central energy storage system is greater than the difference power, all water pumps are controlled to operate at a preset power, and the central energy storage system is controlled to make up for the difference in power.

[0128] S1074. When it is detected that the remaining power of the central energy storage system is not greater than the difference power, obtain a target water pump whose power can be reduced.

[0129] S1075. Obtain a first target power of the target water pump according to the sum of the remaining power of the central energy storage system and the first power generation.

[0130] S1076. Control the target water pump to operate according to the first target power, control the remaining water pumps to operate according to the preset power, and control the central energy storage system to make up for the difference in power.

[0131] When the power generation is less than the first target power corresponding to the irrigation water demand, the power gap is calculated and the insufficient power is supplemented from the central energy storage system first. If the power of the central energy storage system is insufficient to supplement or the remaining state of charge of the central energy storage system is low, for example, SOC<20%, the working power of some water pumps is reduced according to the priority of the water pumps.

[0132] Among them, reducing the working power of some water pumps according to the priority of the water pumps can be achieved through the following steps F1-F5:

[0133] F1. Get the water pump list.

[0134] First, obtain the real-time operating data of all water pumps, including power, current, flow, etc.

[0135] F2. Evaluate priorities.

[0136] According to the priority principle, each pump is assigned a priority level, for example:

[0137] Critical water pump: Priority 1;

[0138] Auxiliary water pump: priority 2;

[0139] Pumps with high risk of failure: Priority 3.

[0140] Water pump priority selection principle:

[0141] 1. Importance of water pumps: Sort the water pumps according to their importance in the irrigation process. Priority should be given to ensuring that key water pumps (e.g., water pumps responsible for the main irrigation task) maintain their operating power, while the power of auxiliary water pumps can be considered to be reduced.

[0142] 2. Operation efficiency: Monitor the efficiency of each pump in the current working state, and give priority to reducing the power of those pumps with lower efficiency or smaller load. This can be achieved by real-time monitoring of its flow rate, head and other parameters.

[0143] 3. Failure risk: If the operating data of some water pumps (such as temperature, current, etc.) are in an abnormal state, it is necessary to reduce the operating power of these water pumps first to avoid failure.

[0144] 4. Rotation priority: You can set a rotation strategy to regularly reduce the power of different pumps to ensure that all pumps have a balanced load and service life in long-term operation.

[0145] F3. Select a water pump with reduced power.

[0146] Determine the number of pumps that need to be powered down based on the available power and the current SOC value.

[0147] Start with the highest priority pump and if it is still low, move down to lower priority pumps.

[0148] F4. Specific strategies for reducing power.

[0149] You can set a percentage to reduce the power. For example, the power of the priority 3 pump is reduced by 30%, the power of the priority 2 pump is reduced by 20%, and the priority 1 pump remains unchanged until the power returns to a safe range.

[0150] F5. Control execution.

[0151] The controller sends a command to the selected water pump to perform the corresponding power reduction.

[0152] Example:

[0153] Assume the system has three pumps A, B and C:

[0154] Pump A (Priority 1): Mainly responsible for critical irrigation.

[0155] Pump B (Priority 2): Auxiliary irrigation, higher efficiency.

[0156] Pump C (Priority 3): Assists irrigation but is less efficient.

[0157] If SOC < 20% and power reduction is required, the system will:

[0158] 1. Keep the power of pump A unchanged.

[0159] 2. Reduce the power of pump B by 10% (e.g., if the operating power is 100W, reduce it to 90W).

[0160] 3. Reduce the power of pump C by 30% (e.g., if the operating power is 80W, reduce it to 56W).

[0161] This priority strategy can ensure that irrigation tasks are completed while properly managing power and extending system life.

[0162] In one embodiment, the method further comprises the following sub-steps C1-C4:

[0163] C1. When a failure of a photovoltaic module in a photovoltaic pumping subsystem is detected, the second power generation of the photovoltaic modules in the remaining photovoltaic pumping subsystem is determined according to the light intensity within the remaining time length;

[0164] C2, obtaining the remaining irrigation water demand output by the water pumps in the remaining photovoltaic pumping subsystem within the remaining time length, and the second target power of each water pump;

[0165] C3. When the second power generation is greater than or equal to the power corresponding to the second target power output by the remaining water pumps, the water pumps in the remaining photovoltaic pumping subsystems are controlled to start working according to the second target power, and the photovoltaic modules are controlled to store the remaining power in the central energy storage system;

[0166] C4. When the second power generation is less than the power corresponding to the second target power output by the remaining water pumps, the water pumps in the remaining photovoltaic pumping subsystems are controlled to start working according to the second target power, and the central energy storage system is controlled to make up for the difference in power.

[0167] When a photovoltaic pumping subsystem fails, the faulty photovoltaic pumping subsystem can be immediately isolated, and the second power generation of the photovoltaic components in the remaining photovoltaic pumping subsystems can be recalculated according to the light intensity within the remaining time. In addition, the remaining irrigation water demand output by the pumps in the remaining photovoltaic pumping subsystems within the remaining time and the second target power of each pump can be obtained. Then, the working mode of other photovoltaic pumping subsystems can be adjusted to increase the output power of the pumps. If necessary, electric energy can be supplemented from the central energy storage system to maintain the overall water supply capacity.

[0168] In the present disclosure, when a photovoltaic pumping system fails, intelligent scheduling can be performed to improve system reliability and maintainability.

[0169] In another possible implementation, Figure 7 As shown, the above steps can also be implemented by following steps G1-G9:

[0170] G1. Start.

[0171] In this step, the system starts and enters the coordinated control stage.

[0172] G2. Receive system status data.

[0173] Receive current system status data from various sensors and monitoring modules, including photovoltaic power generation (Pgen), water pump load (Pload), energy storage system state of charge (SOC), actual water supply (Q) and water demand (Qdemand).

[0174] G3. Estimate the light and water demand for the next 24 hours.

[0175] Use weather forecasts or historical data analysis to predict light intensity and water demand over the next 24 hours.

[0176] G4. Establish a system dynamic model.

[0177] Based on the received current system status data and prediction results, a system dynamic model including photovoltaic power generation, energy storage, water pump load and water resource dynamics is established.

[0178] G5. Define multi-objective optimization function

[0179] Determine the optimization goal and define the multi-objective optimization function: J = w1*∑(Pgen-Pload)^2+w2*(SOC-SOCtarget)^2+w3*∑(Q-Qdemand)^2+w4*Cost;

[0180] Among them, J represents the total value of the optimization objective function, and the goal is to minimize J to achieve the best system performance; w1, w2, w3, and w4 represent weight factors, which are used to balance the importance of different optimization objectives. Their values ​​can be adjusted according to system requirements and priorities. For example, if the value of w1 is large, it means that the balance between total power generation and total load is given a higher priority; Pgen represents the total power generation of the system, which is the sum of the electric energy generated by energy sources such as photovoltaic components. It needs to be compared with the load during optimization to ensure that the power supply can meet the demand; Pload represents the total load of the system, that is, the sum of the electric energy required by all load devices (such as water pumps, etc.). By comparing with Pgen, the supply and demand balance is evaluated; SOC represents the state of charge of the energy storage system, which indicates the current power level of the energy storage system battery, usually expressed as a percentage (for example: 10 0% means full charge, 0% means no charge), ensuring that the energy storage system operates within a safe range to avoid overcharging or over-discharging; SOCtarget means the target state of charge, the preset SOC level that you want to maintain, so that the energy storage system operates in the best condition, thereby extending battery life and improving efficiency; Q means the actual water supply of the system, which means the amount of water that the system can currently provide, which needs to be compared with the water demand to ensure that the needs of irrigation or other purposes are met; Qdemand means the water demand, which means the amount of water that the system needs to meet. By comparing with Q, it is evaluated whether the water supply capacity meets the demand; Cost means the operating cost of the system, which usually includes electricity cost, maintenance cost and other related expenses. Considering cost in optimization can help achieve economic benefits and ensure that operating expenses are reduced while meeting water supply and electricity needs.

[0181] Among them, the meaning of each item of the optimization function is:

[0182] The first term: w1*∑(Pgen-Pload)^2, aims to minimize the difference between power generation and load. The smaller the difference, the better the balance between supply and demand, and the more efficient the system operation.

[0183] The second term: w2*(SOC-SOCtarget)^2, aims to keep the state of charge of the energy storage system close to the target value, ensuring that the battery is within a safe and efficient operating range.

[0184] The third item: w3*∑(Q-Qdemand)^2, aims to ensure that the actual water supply is consistent with the water demand and avoid waste or shortage of water resources.

[0185] The fourth item: w4*Cost, aims to take economic factors into account in system operation and ensure that the operating cost is within an acceptable range, thereby improving the overall economic benefits of the system.

[0186] Through the detailed explanation of the above items, it can be seen that this multi-objective optimization function aims to achieve the optimal configuration of system performance by weighted summation of different objectives, taking into account power generation, energy storage status, water supply capacity and operating costs. This optimization method helps to achieve efficient resource management in a dynamically changing environment.

[0187] G6. Use the sequential quadratic programming (SQP) algorithm to solve optimization problems.

[0188] The SQP algorithm is applied to solve the optimization function and obtain the optimal control sequence for the next 24 hours, including the output power of the photovoltaic module, the working power of the water pump and the charging / discharging strategy of the energy storage system.

[0189] G7. Adjust control strategy in real time.

[0190] This step enters the logical judgment stage of real-time adjustment of control strategy:

[0191] G7.1 Total power generation > water demand.

[0192] If the total power generation is greater than the water demand:

[0193] Increase the water pump power: According to the system dynamic model and water demand, appropriately increase the working power of the water pump.

[0194] Calculate excess energy: Determine excess energy and store it in a central energy storage system.

[0195] Check the energy storage system status: If the SOC of the energy storage system is greater than 95%:

[0196] Reduce the output power of PV panels: Reduce the output power of PV panels by adjusting the DC / DC converter to avoid overcharging.

[0197] G7.2 Total power generation < water demand.

[0198] If the total power generation is less than the water demand:

[0199] Calculate the energy gap: Determine the exact amount of energy your system is short of.

[0200] Prioritize supplementing insufficient electricity from the energy storage system: Use the electricity from the energy storage system to make up for the energy gap.

[0201] Check the energy storage system status: If the SOC is less than 20%:

[0202] Reduce the operating power of some pumps according to priority: Select low-priority pumps to reduce power to ensure the completion of critical water use tasks.

[0203] G7.3 subsystem failure.

[0204] If a subsystem failure is detected:

[0205] Isolate the faulty subsystem immediately: Deactivate the faulty subsystem to ensure the overall safety of the system.

[0206] Recalculate available generation and water demand: Update system dynamics model.

[0207] Adjust the working mode of other subsystems: adjust the output power of other pumps according to the new power generation and water consumption requirements.

[0208] Supplement electrical energy from the energy storage system when necessary: ​​ensure that the overall water supply capacity is not affected.

[0209] G8. After adjusting the control strategy, execute the control command.

[0210] According to the real-time adjusted control strategy, control commands are issued to each subsystem to implement the adjusted working parameters.

[0211] G9. End.

[0212] After completing a coordinated control cycle, return to the step of receiving system status data and execute it cyclically to adapt to the changing environment and needs.

[0213] Each step is based on the results and output of the previous step, forming a closed-loop control system. By continuously receiving real-time data, prediction, modeling, optimization, adjustment and execution, the system is ensured to operate efficiently and stably.

[0214] The present disclosure also has a fault diagnosis function, thereby improving the reliability and maintainability of the photovoltaic pumping system, which specifically includes the following sub-steps D1-D4:

[0215] D1. Obtain real-time operating data of each photovoltaic module.

[0216] The real-time operation data of the photovoltaic module may include: the voltage of the photovoltaic module, the current of the photovoltaic module, the power of the photovoltaic module, the accumulated power generation of the photovoltaic module and the operation data and status of the inverter.

[0217] Specific:

[0218] PV module voltage: reflects the potential difference between the two ends of the PV module. When working normally, the voltage will fluctuate within a certain range. Voltage data is very important for judging the connection status of the module, whether the line is normal, and the matching status of the inverter. For example, if the voltage of a certain module is abnormally low, it may be that the internal circuit of the module is broken or faulty, resulting in the inability of the current to pass normally, thereby causing the voltage to drop; if the voltage is abnormally high, it may be that there is a problem with the connection with other modules, or the control strategy of the inverter is abnormal.

[0219] The current of a photovoltaic module: represents the flow of electrons in a photovoltaic module and is an important indicator for measuring the power generation capacity of a photovoltaic module. The current will change under different light intensity and temperature conditions. When the light intensity increases, the current will increase accordingly; conversely, when the light intensity decreases, the current will decrease. By monitoring the current data in real time, you can understand the power generation efficiency of the photovoltaic module and whether there are safety hazards such as leakage.

[0220] The power of a photovoltaic module is the product of voltage and current, which directly reflects the power generation output capacity of a photovoltaic module. The power will change with environmental factors such as light and temperature, as well as the performance of the module itself. Real-time monitoring of power data can help operation and maintenance personnel understand the power generation of the photovoltaic system and promptly identify components with abnormal power reduction for maintenance and replacement.

[0221] Cumulative power generation of PV modules: records the total power generation of PV modules from the start of operation to the current moment. The cumulative power generation data can be used to evaluate the service life, power generation performance and return on investment of PV modules.

[0222] Inverter operation data and status: The inverter is a key device that converts the DC power generated by the photovoltaic module into AC power. Its operation data and status are crucial to the overall performance of the photovoltaic system. Including the inverter's input voltage, input current, output voltage, output current, power factor, frequency and other parameters, as well as the inverter's operating status (such as normal operation, fault shutdown, standby, etc.)

[0223] D2. When it is detected that the real-time operation data of a photovoltaic module does not meet the preset photovoltaic module operation requirements, an identification of the photovoltaic module that does not meet the preset photovoltaic module operation requirements is output.

[0224] Each photovoltaic module is tested, and when a problem is detected in a photovoltaic module, the identification of the problematic photovoltaic module will be output so that the staff can check and repair it in time.

[0225] D3. Obtain real-time operating data of each water pump.

[0226] The real-time operation data of the water pump may include: electrical parameter data of the water pump, hydraulic parameter data of the water pump, mechanical parameter data of the water pump and the operation time of the water pump.

[0227] Among them, the electrical parameter data of the water pump includes:

[0228] Water pump voltage: reflects the input voltage value of the water pump motor. Voltage stability is crucial to the normal operation of the water pump. Too high or too low voltage may cause the water pump motor to malfunction or operate abnormally. For example, too low voltage may prevent the motor from reaching the rated power, affecting the pumping capacity of the water pump; too high voltage may damage the insulation of the motor and shorten the service life of the motor.

[0229] The current of the water pump is a key parameter to measure the operating status of the water pump motor. During normal operation, the current will fluctuate within a certain range. If the current suddenly increases, it may be that the water pump is overloaded, blocked or has mechanical problems, causing the motor to require a larger current to drive; conversely, if the current is too small, it may be that the motor has failed, or the water inlet of the water pump is blocked, resulting in insufficient water flow and reduced motor load.

[0230] Water pump power: Power is the product of voltage and current, which directly reflects the energy consumption and working efficiency of the water pump. By monitoring the power data in real time, you can understand whether the operation status of the water pump is normal and whether it is running efficiently. If the power changes abnormally, you need to check the operation of the water pump in time to find out the problem.

[0231] Pump frequency (for variable frequency pumps): For variable frequency controlled pumps, frequency is an important real-time operating data. By changing the frequency, the pump speed can be adjusted to control the water flow and pressure. Real-time monitoring of the frequency can help you understand whether the pump speed meets the requirements and whether the variable frequency control system is working properly.

[0232] Among them, the hydraulic parameter data of the water pump include:

[0233] Flow rate: refers to the volume of water delivered by a water pump per unit time. The size of the flow rate directly affects the working effect and application scenarios of the water pump. For example, in an urban water supply system, the flow rate of the water pump needs to be adjusted in real time according to the water demand in different time periods to ensure the stability of water supply. Real-time flow monitoring can help operators understand whether the water delivery capacity of the water pump meets the demand, and whether there are problems such as leakage or pipe blockage.

[0234] Head: refers to the height to which the water pump can lift water. Head is an important parameter for water pump selection and application. Different application scenarios require water pumps with different heads. Real-time monitoring of the head can ensure that the water pump operates within the designed head range to avoid affecting the normal operation of the water pump due to insufficient or excessive head.

[0235] Pressure: includes the inlet and outlet pressures of the water pump. The inlet pressure reflects the water inlet conditions of the water pump, while the outlet pressure reflects the water delivery capacity of the water pump and the resistance of the system. For example, in a fire water pump system, the outlet pressure must meet the pressure requirements of fire water, otherwise it will affect the effect of fire fighting. Real-time monitoring of pressure data can help operators promptly detect abnormal pressure in the system and take appropriate measures to adjust it.

[0236] Among them, the mechanical parameter data of the water pump include:

[0237] Vibration: The water pump will generate a certain amount of vibration during operation. The amplitude and frequency of the vibration can reflect the mechanical state of the water pump. If the vibration is too large, it may be caused by reasons such as the unstable installation foundation of the water pump, unbalanced coupling, bearing wear or impeller damage. By installing a vibration sensor, the vibration of the water pump can be monitored in real time, mechanical faults can be discovered in time, and the faults can be avoided from further expansion.

[0238] Temperature: including the temperature of the water pump motor and the temperature of the bearings. The temperature rise may be caused by motor overload, poor heat dissipation or bearing wear. Real-time monitoring of temperature data can help operators detect overheating problems in time and take appropriate heat dissipation measures or shut down for maintenance to prevent motor or bearing damage.

[0239] Speed: Speed ​​refers to the rotation speed of the pump impeller, which directly affects the flow rate and head of the pump. For pumps using variable frequency control, the speed can be adjusted by changing the frequency; for fixed frequency pumps, the speed is fixed. Real-time monitoring of the speed can help you understand whether the pump's operating speed is normal and whether it is consistent with the design parameters.

[0240] Pump operation time: Recording the cumulative operation time of the pump is of great significance for evaluating the service life of the pump and performing maintenance. According to the operation time, a reasonable maintenance plan can be formulated to regularly inspect and maintain the pump to extend the service life of the pump.

[0241] D4. When it is detected that the real-time operation data of a water pump does not meet the preset water pump operation requirements, an identification of the water pump that does not meet the preset water pump operation requirements is output.

[0242] During the operation of the system, the real-time operating data of each device can be monitored in real time. When a failure is detected in a certain device, prompt information will be given in time to prompt the staff to handle it in time, thereby improving the stability of the system.

[0243] In one embodiment, a fault diagnosis report may also be generated, specifically including the following sub-steps E1-E4:

[0244] E1. Obtain the reason why the photovoltaic module does not meet the preset photovoltaic module operation requirements.

[0245] E2. Obtain the reason why the pump does not meet the preset pump operation requirements.

[0246] E3. Generate a fault diagnosis report, which includes: the identification of the PV modules that do not meet the preset PV module operation requirements, and the reasons why the PV modules do not meet the preset PV module operation requirements; the identification of the water pump that does not meet the preset water pump operation requirements, and the reasons why the water pump does not meet the preset water pump operation requirements.

[0247] E4. Output fault diagnosis report.

[0248] The present disclosure can also output a detailed fault diagnosis report, so that the operator can quickly locate the cause of the problem. If the real-time temperature of the water pump is greater than the preset water pump temperature, it can be output that the temperature increase may be caused by motor overload, poor heat dissipation or bearing wear, which can help the operator to promptly detect overheating problems and take corresponding heat dissipation measures or shut down for maintenance to prevent motor or bearing damage.

[0249] In another embodiment of the present disclosure, the above fault diagnosis can also adopt a deep learning algorithm based on a graph neural network (GNN) and an attention mechanism, such as Figure 8 As shown, specifically:

[0250] a. Construct a topological diagram of the relationship between the various devices in the photovoltaic pumping system. Each node represents a device, and the edge represents the physical or logical connection relationship between the devices;

[0251] b. Use the trained graph convolutional network (GCN) to extract the topological features between devices;

[0252] c. Collect current operation data in real time;

[0253] d. Combined with the long short-term memory (LSTM) network, it captures the temporal dependencies between devices when each device is running;

[0254] e. Use a multi-head attention mechanism to focus on each device and the abnormal patterns of each device, and use contrastive learning methods to improve the model's sensitivity to abnormal patterns;

[0255] f. Based on the abnormal pattern, compare the current running data with the predicted value in real time and calculate the abnormal score;

[0256] g. Check whether the anomaly score is greater than the adaptive threshold;

[0257] h. When the anomaly score exceeds the adaptive threshold, a fault alarm is triggered. Further, explainable AI technology can be used to generate a fault diagnosis report, including the fault type, location, and severity. When the anomaly score does not exceed the adaptive threshold, return to step c.

[0258] i. Based on Bayesian network, predict the remaining service life of each device;

[0259] j. Generate optimized maintenance plans to balance maintenance costs and system reliability.

[0260] The present disclosure also provides a specific implementation scheme for power distribution, such as Fig. 9As shown in the figure, the specific implementation scheme of the power allocation stage is described, especially how to use deep reinforcement learning (DRL) technology for adaptive power allocation. This is closely related to the optimization and control strategy of the entire system, especially the coordinated control stage mentioned above. The scheme includes the following sub-steps H1-H7:

[0261] H1. Start.

[0262] Initialize the system and prepare for the power allocation phase. In this step, start all necessary hardware and software components to ensure that the data acquisition system is functioning properly and ready for the power allocation phase.

[0263] H2. Initialize the DQN network.

[0264] Network structure: Build a deep Q network (DQN), including input layer, hidden layer and output layer.

[0265] Input layer: contains 4 state parameters (light intensity, SOC (state of charge), water pump load, system parameters).

[0266] Hidden layer: 3 fully connected layers, using ReLU activation function, 128 neurons in each layer.

[0267] Output layer: Outputs the Q value of each action in each action space A.

[0268] Information transmission: After the network is successfully initialized, it is ready to receive current status data.

[0269] H3. Get the current system status.

[0270] Get current status parameters from sensors or data acquisition systems:

[0271] Light intensity (I): The light intensity in the current environment.

[0272] SOC (State Of Charge): The state of charge of the central energy storage system, reflecting the degree of charge of the battery, generally ranging from 0% to 100%.

[0273] Pump load (P load ): Current water pump load, expressed in power.

[0274] System parameters (such as temperature, humidity and other influencing factors).

[0275] Output: state vector S = (I, SOC, P load , system parameters) are used for subsequent decision making.

[0276] H4. Use the ε-greedy strategy to select actions.

[0277] Explore and Exploit:

[0278] H4.1 Random exploration (selecting random actions with probability ε): used to explore new states and improve the diversity of the algorithm.

[0279] H4.2 Select the action with the largest Q value (select the best action with probability 1-ε): Select the action with the highest Q value to maximize the expected future reward.

[0280] Here, the ε value is a constant less than 1, which is gradually decreased (for example, from 1 to 0.1) as learning proceeds to reduce randomness.

[0281] Output: The selected action a, which will be executed.

[0282] Here, action a is selected by using the ε-greedy strategy.

[0283] Exploration (with probability e): The algorithm randomly chooses an action to explore new policies and states.

[0284] Utilize (with probability 1-e): Choose the best action currently known, that is, the action with the largest Q value in the current state S.

[0285] H5. Execute the selected action.

[0286] Adjust the duty cycle (D) of the DC / DC converter and the modulation index (M) of the DC / AC inverter:

[0287] DC / DC converter duty cycle (D): determines the voltage level of the output DC power and is adjusted according to the selected action.

[0288] DC / AC inverter modulation index (M): determines the frequency and amplitude of the output AC power.

[0289] Output: Voltage and current are adjusted and the system state is about to change.

[0290] H6. Observe new states and rewards.

[0291] New state (S'): After executing the action, get the new state parameters.

[0292] Reward function (R): Calculates the reward after the current action, which is used to update the Q value later:

[0293] Reward function R = m1×power generation efficiency + m2×water supply efficiency + m3×energy balance - m4×equipment stress.

[0294] in:

[0295] Power generation efficiency: measures the efficiency of photovoltaic panels in converting light energy into electrical energy.

[0296] Water supply efficiency: evaluates the ability of a pump to convert electrical energy into water for pumping.

[0297] Energy balance: indicates the degree of match between system power generation and power supply demand.

[0298] Equipment stress: Consider the load and operating status of the equipment. Excessive stress may cause equipment damage.

[0299] m1, m2, m3, and m4 are weight factors used to balance the importance of different optimization objectives, and their values ​​can be adjusted according to system requirements.

[0300] Output: New state (S') and corresponding reward (R), which are used for subsequent training and Q value update.

[0301] H7. Store experience in the replay buffer.

[0302] Store the current state, selected action, new state, and reward in the experience replay buffer (ReplayBuffer).

[0303] Output: Experience successfully stored, ready to enter the training phase.

[0304] H8. Sample batches of data from the playback buffer.

[0305] A batch of stored experiences is randomly selected for training to break dependencies and improve the stability of learning.

[0306] Output: Selected batch data for DQN network training.

[0307] H9. Train the DQN network.

[0308] Output: Updated network weights, so the DQN model can more accurately estimate the value of future actions.

[0309] H10. Determine and update the target network every 100 steps.

[0310] After every 100 time steps, the parameters of the target network (θ') are updated to the parameters of the current network (θ) to improve the stability of learning.

[0311] Output: The updated target network is ready for future Q-value calculations.

[0312] H11. Adjust the parameters of DC / DC converter and DC / AC inverter.

[0313] According to the new DQN output, the duty cycle D of the converter and the modulation index M of the inverter are adjusted to achieve optimal power distribution.

[0314] Output: The power allocation strategy of the system is optimized.

[0315] H12. Determine whether the end condition is met.

[0316] If the preset end condition is met (such as reaching a certain number of learning times or achieving a certain performance target), the algorithm ends.

[0317] Otherwise, return to step H3, continue to obtain the current system state, and proceed to the next iteration.

[0318] H13. End.

[0319] The system completes the power allocation process and can output the results or proceed to the next task.

[0320] The purpose of the power distribution stage is to:

[0321] 1. Optimize power distribution: The goal of this stage is to achieve intelligent distribution of output power of various devices in the system (such as photovoltaic modules, energy storage systems, water pumps, etc.) through deep reinforcement learning algorithms to achieve the best operating effect.

[0322] 2. Improve efficiency and stability: Through adaptive learning and adjustment of system parameters, ensure that the optimal power distribution can be achieved quickly and stably under different working conditions (such as changes in light intensity, energy storage status, etc.).

[0323] In the coordinated control stage, the multi-objective optimization functions mentioned (such as power generation, water demand, operating costs, etc.) provide the decision basis for the power allocation stage. The power allocation module further optimizes the specific implementation of these goals through deep reinforcement learning algorithms. The logic of real-time adjustment of control strategies in the coordinated control stage (such as adjusting the pump power according to changes in power generation and water demand) is closely related to the adaptive adjustment in the power allocation stage.

[0324] In the power allocation stage, a Markov decision process (MDP) model is established, taking into account state parameters such as light intensity and SOC, which are part of the system dynamic model in the coordinated control stage.

[0325] The power allocation stage requires real-time system status data (such as light intensity, SOC, etc.), which are obtained from the coordinated control stage. The two together constitute a complete feedback control system.

[0326] The reward function in the power allocation stage (including power generation efficiency, water supply efficiency, energy balance and equipment stress) complements the multi-objective optimization function in the coordinated control stage. These indicators jointly guide the system towards the optimal operating state.

[0327] In summary, the content of the power allocation stage is closely linked to the coordinated control of the entire system, aiming to achieve more detailed control and optimization through adaptive algorithms to achieve efficient and stable operation of the system. This part provides a detailed implementation plan for how to dynamically adjust system parameters and strategies while achieving the goal, and is a key component of the entire system optimization framework.

[0328] The present disclosure can also set a human-machine interface in the controller, and the human-machine interface is connected to a responsive visualization interface based on the Web. The D3.js library can be used in the visualization interface to display the operation data of the photovoltaic pumping subsystem and the topological structure of the current photovoltaic pumping subsystem in real time. A customizable dashboard can also be provided to display the real-time operation data of the photovoltaic components and the water pump. The operator can also set system parameters in the visualization interface, such as: parameters of the photovoltaic components, parameters of the water pump and the priority of the water pump, etc. Role-based access control can also be provided to support multi-level permission management. Different operator IDs correspond to different operation permissions. A natural language processing (NLP) module can also be integrated to support voice control and intelligent assistant functions. WebRTC technology can also be used to support real-time video monitoring and remote collaboration, and a REST API is provided to support integration with third-party systems. Progressive Web Application (PWA) technology is used to achieve offline access and push notifications. A responsive design is used to adapt to display devices of different sizes and support mobile monitoring.

[0329] Based on the same inventive concept, the embodiment of the present application also provides a photovoltaic pumping device for implementing the photovoltaic pumping method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more photovoltaic pumping device embodiments provided below can refer to the limitations of the photovoltaic pumping method above, and will not be repeated here.

[0330] Fig.10 is a schematic diagram of a photovoltaic pumping device according to an exemplary embodiment. Fig.10 As shown, the photovoltaic pumping device is applied to the controller, and the photovoltaic pumping device system includes:

[0331] The first acquisition module 201 is used to acquire environmental parameter information and crop growth stage information;

[0332] A second acquisition module 202 is used to acquire the irrigation water requirement of the crop according to the environmental parameter information and the growth stage information of the crop;

[0333] The third acquisition module 203 is used to obtain the light intensity within a preset time length;

[0334] A fourth acquisition module 204 is used to determine a first power generation amount of all the photovoltaic modules according to the light intensity within the preset time length;

[0335] A fifth acquisition module 205 is used to acquire a first target amount of electricity required for all the water pumps to output the irrigation water demand according to a preset power;

[0336] A first control module 206 is used to control all the water pumps to start working according to the preset power when the power generation is greater than or equal to the first target power;

[0337] The second control module 207 is used to control all the water pumps to start working according to the preset power when the power generation is less than the first target power, and control the central energy storage system to make up for the power difference.

[0338] In one embodiment, the first control module 206 is further used to control each of the photovoltaic components to store the remaining electricity into the central energy storage system after controlling all of the water pumps to start working according to the preset power.

[0339] In one embodiment, after controlling each of the photovoltaic components to store the remaining electricity in the central energy storage system, the first control module 206 is further configured to:

[0340] Obtaining the real-time charge state of the central energy storage system;

[0341] When it is detected that the real-time state of charge of the central energy storage system meets the preset state of charge requirement, each of the photovoltaic components is controlled to reduce the output power.

[0342] In one embodiment, the second control module is specifically configured to:

[0343] When the power generation amount is less than the first target power generation amount, obtaining a difference in power between the first target power generation amount and the first power generation amount;

[0344] Obtaining the remaining power of the central energy storage system;

[0345] When it is detected that the remaining power of the central energy storage system is greater than the difference power, all the water pumps are controlled to operate according to the preset power, and the central energy storage system is controlled to make up the difference power;

[0346] When it is detected that the remaining power of the central energy storage system is not greater than the difference power, obtaining a target water pump whose power can be reduced;

[0347] Obtaining a first target power of the target water pump according to the sum of the remaining power of the central energy storage system and the first power generation;

[0348] The target water pump is controlled to operate according to the first target power, the remaining water pumps are controlled to operate according to the preset power, and the central energy storage system is controlled to make up for the difference in power.

[0349] In one embodiment, the apparatus further comprises:

[0350] A first determination module is used to determine the second power generation of the photovoltaic components in the remaining photovoltaic pumping subsystem according to the light intensity within the remaining time length when a failure of the photovoltaic components in the photovoltaic pumping subsystem is detected;

[0351] A sixth acquisition module, used for acquiring the remaining irrigation water demand output by the water pumps in the remaining photovoltaic pumping subsystem within the remaining time length, and the second target power of each of the water pumps;

[0352] A third control module is used to control the remaining water pumps in the photovoltaic pumping subsystem to start working according to the second target power when the second power generation is greater than or equal to the power corresponding to the second target power output by the water pumps in the remaining photovoltaic pumping subsystem, and control the photovoltaic components to store the remaining power in the central energy storage system;

[0353] The fourth control module is used to control the remaining water pumps in the photovoltaic pumping subsystem to start working according to the second target power when the second power generation is less than the power corresponding to the second target power output by the water pumps in the remaining photovoltaic pumping subsystem, and control the central energy storage system to make up for the power difference.

[0354] In one embodiment, the apparatus further comprises:

[0355] A seventh acquisition module, used to acquire real-time operation data of each photovoltaic module;

[0356] A first output module is used to output an identification of the photovoltaic component that does not meet the preset photovoltaic component operation requirements when it is detected that the real-time operation data of the photovoltaic component does not meet the preset photovoltaic component operation requirements;

[0357] The seventh acquisition module is also used to acquire the real-time operation data of each of the water pumps;

[0358] The first output module is further used to output an identification of the water pump that does not meet the preset water pump operation requirements when it is detected that the real-time operation data of the water pump does not meet the preset water pump operation requirements.

[0359] In one embodiment, it further includes:

[0360] An eighth acquisition module is used to acquire the reason why the photovoltaic assembly does not meet the preset photovoltaic assembly operation requirement;

[0361] An eighth acquisition module is further used to acquire the reason why the water pump does not meet the preset water pump operation requirement;

[0362] The first output module is further used to generate a fault diagnosis report, wherein the fault diagnosis report includes: an identification of the photovoltaic component that does not meet the preset photovoltaic component operation requirements, and a reason why the photovoltaic component does not meet the preset photovoltaic component operation requirements; an identification of the water pump that does not meet the preset water pump operation requirements, and a reason why the water pump does not meet the preset water pump operation requirements;

[0363] The first output module is also used to output the fault diagnosis report.

[0364] In one embodiment, the apparatus further comprises:

[0365] A ninth acquisition module, used for acquiring the remaining power of each photovoltaic module;

[0366] A transmission module, used to transmit the value of the remaining power to the blockchain network;

[0367] A receiving module, used to receive transaction settlement information returned by the blockchain network;

[0368] The second output module is also used to output the transaction settlement information.

[0369] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The description and examples are intended to be exemplary only, and the true scope and spirit of the present disclosure are indicated by the following claims.

[0370] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A photovoltaic pumping system, characterized in that: include: A controller (1), a central energy storage system (2) and a plurality of photovoltaic pumping subsystems (3); Each of the photovoltaic pumping subsystems (3) comprises: a photovoltaic module (31), and a water pump (32) connected to the photovoltaic module (31); The controller (1) is connected to the central energy storage system (2), the photovoltaic module (31) and the water pump (32) respectively; The central energy storage system (2) is connected to each of the photovoltaic modules (31).

2. A photovoltaic pumping method, characterized in that: The photovoltaic water pumping method is applied to the controller in the photovoltaic water pumping system according to claim 1, and the method comprises: Obtain information on environmental parameters and crop growth stages; Acquiring the irrigation water requirement of the crop according to the environmental parameter information and the growth stage information of the crop; Get the light intensity within a preset time length; Determining a first power generation of all the photovoltaic modules according to the light intensity within the preset time length; Obtaining a first target amount of electricity required for all the water pumps to output the irrigation water demand according to a preset power; When the power generation is greater than or equal to the first target power, controlling all the water pumps to start working according to the preset power; When the power generation amount is less than the first target power, all the water pumps are controlled to start working according to the preset power, and the central energy storage system is controlled to make up for the power difference.

3. The method according to claim 2, characterized in that After controlling all the water pumps to start working according to the preset power, the method further includes: Control each of the photovoltaic modules to store the remaining electricity in the central energy storage system.

4. The method according to claim 3, characterized in that After controlling each of the photovoltaic modules to store the remaining electricity in the central energy storage system, the method further includes: Obtaining the real-time charge state of the central energy storage system; When it is detected that the real-time state of charge of the central energy storage system meets the preset state of charge requirement, each of the photovoltaic components is controlled to reduce the output power.

5. The method according to claim 2, characterized in that: When the power generation amount is less than the first target power, controlling all the water pumps to start working according to the preset power, and controlling the central energy storage system to make up for the difference in power, includes: When the power generation amount is less than the first target power generation amount, obtaining a difference in power between the first target power generation amount and the first power generation amount; Obtaining the remaining power of the central energy storage system; When it is detected that the remaining power of the central energy storage system is greater than the difference power, all the water pumps are controlled to operate according to the preset power, and the central energy storage system is controlled to make up the difference power; When it is detected that the remaining power of the central energy storage system is not greater than the difference power, obtaining a target water pump whose power can be reduced; Obtaining a first target power of the target water pump according to the sum of the remaining power of the central energy storage system and the first power generation; The target water pump is controlled to operate according to the first target power, the remaining water pumps are controlled to operate according to the preset power, and the central energy storage system is controlled to make up for the difference in power.

6. The method according to claim 2, characterized in that The method further comprises: When a failure of the photovoltaic module in the photovoltaic pumping subsystem is detected, determining a second power generation of the photovoltaic module in the remaining photovoltaic pumping subsystem according to the light intensity within the remaining time length; Obtain the remaining irrigation water required to be output by the water pumps in the remaining photovoltaic pumping subsystem within the remaining time length, and the second target power of each of the water pumps; When the second power generation is greater than or equal to the power corresponding to the second target power output by the water pumps in the remaining photovoltaic pumping subsystems, the water pumps in the remaining photovoltaic pumping subsystems are controlled to start working according to the second target power, and the photovoltaic modules are controlled to store the remaining power in the central energy storage system; When the second power generation is less than the power corresponding to the second target power output by the water pumps in the remaining photovoltaic pumping subsystems, the water pumps in the remaining photovoltaic pumping subsystems are controlled to start working according to the second target power, and the central energy storage system is controlled to make up for the power difference.

7. The method according to claim 2, characterized in that The method further comprises: Acquiring real-time operating data of each of the photovoltaic modules; When it is detected that the real-time operation data of the photovoltaic assembly does not meet the preset photovoltaic assembly operation requirements, outputting an identification of the photovoltaic assembly that does not meet the preset photovoltaic assembly operation requirements; Acquire real-time operation data of each of the water pumps; When it is detected that the real-time operation data of the water pump does not meet the preset water pump operation requirements, an identification of the water pump that does not meet the preset water pump operation requirements is output.

8. The method according to claim 7, characterized in that The method further comprises: Obtaining the reason why the photovoltaic component does not meet the preset photovoltaic component operation requirement; Obtaining the reason why the water pump does not meet the preset water pump operation requirement; Generate a fault diagnosis report, the fault diagnosis report including: the identification of the photovoltaic component that does not meet the preset photovoltaic component operation requirements, and the reason why the photovoltaic component does not meet the preset photovoltaic component operation requirements; the identification of the water pump that does not meet the preset water pump operation requirements, and the reason why the water pump does not meet the preset water pump operation requirements; The fault diagnosis report is outputted.

9. The method according to claim 2, characterized in that: The method further comprises: Obtaining the remaining power of each photovoltaic module; Transmitting the value of the remaining power to the blockchain network; Receiving transaction settlement information returned by the blockchain network; Output the transaction settlement information.

10. A photovoltaic pumping device, characterized in that: The photovoltaic pumping device is applied to the controller in the photovoltaic pumping system according to claim 1, and the device comprises: A first acquisition module is used to acquire environmental parameter information and crop growth stage information; A second acquisition module, used for acquiring the irrigation water requirement of the crop according to the environmental parameter information and the growth stage information of the crop; A third acquisition module is used to obtain the light intensity within a preset time length; A fourth acquisition module, used to determine the first power generation of all the photovoltaic components according to the light intensity within the preset time length; A fifth acquisition module is used to acquire a first target amount of electricity required for all the water pumps to output the irrigation water demand according to a preset power; A first control module, configured to control all the water pumps to start working according to the preset power when the power generation is greater than or equal to the first target power; The second control module is used to control all the water pumps to start working according to the preset power when the power generation is less than the first target power, and control the central energy storage system to make up the difference in power.

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