Perovskite photovoltaic phase change composite heat dissipation and temperature control synergistic device for greenhouse power supply

Abstract

This invention discloses a perovskite photovoltaic phase change composite heat dissipation and temperature control synergistic device for greenhouse energy supply, belonging to the field of greenhouse photovoltaic temperature control technology. It aims to solve the technical problems of unstable power supply, repeated fluctuations in water and fertilizer temperature, and chelate bond breakage caused by photovoltaic power fluctuations in greenhouse perovskite photovoltaic energy supply systems. The device includes a synergistic control unit, a photovoltaic power fluctuation identification module, a two-stage filtering synergistic control module, a multi-type chelate water and fertilizer adaptation module, an operation and maintenance early warning linkage module, a perovskite photovoltaic energy supply module, a phase change composite heat dissipation module, a greenhouse temperature control module, a water and fertilizer supply module, and an irrigation module. The synergistic control unit coordinates the collaborative operation of all modules, and the photovoltaic power fluctuation identification module collects the power output of the perovskite photovoltaic energy supply module and greenhouse illumination data. This invention has the advantages of accurately identifying photovoltaic power fluctuations and achieving synergistic control of electrical and thermal filtering, stabilizing power supply and water and fertilizer temperature to protect chelate bonds.

Description

Technical Field

[0001] This invention relates to the field of greenhouse photovoltaic temperature control technology, and more specifically, to a perovskite photovoltaic phase change composite heat dissipation and temperature control synergistic device for greenhouse power supply. Background Technology

[0002] In the field of greenhouse cultivation combined with photovoltaic power supply, perovskite photovoltaic modules are widely used in greenhouse power supply systems due to their high power generation efficiency and adaptability to greenhouse installation scenarios. However, in actual operation, photovoltaic power is prone to various types of fluctuations, such as high-frequency small amplitude, high-frequency large amplitude, and high-frequency superposition, due to factors such as changes in light intensity and fluctuations in weather conditions. Existing greenhouse photovoltaic power supply and temperature control coordination devices have not built a precise identification, regulation, and adaptation system for such power fluctuations. As a result, power fluctuations not only affect the stability of greenhouse power supply but also cause the heat exchange state of the phase change heat dissipation module to become disordered, leading to repeated hot and cold alternations in water and fertilizer temperatures. This damages the stability of the chelate bonds in chelated water and fertilizer, resulting in the loss of water, fertilizer, and nutrients. At the same time, it is impossible to simultaneously meet the coordinated needs of photovoltaic module heat dissipation and greenhouse temperature control, increasing greenhouse operation and maintenance costs. This restricts the large-scale application of perovskite photovoltaic technology in the field of greenhouse cultivation and has become the core technical challenge currently facing greenhouse photovoltaic power supply and temperature control coordination systems.

[0003] In existing technologies, some greenhouse photovoltaic power supply devices simply set up photovoltaic power supply modules and heat dissipation modules without accurately identifying and specifically controlling photovoltaic power fluctuations. This fails to solve the chain reaction problems caused by power fluctuations, such as unstable power supply, water and fertilizer temperature fluctuations, and chelate bond breakage. Other devices attempt to implement filtering and control, but fail to achieve coordinated linkage between electrical and thermal filtering, and do not dynamically adapt to water and fertilizer types, resulting in poor control effects. Furthermore, they lack a sound operation and maintenance early warning and fault handling mechanism, making it impossible to detect and alleviate problems such as chelate bond breakage and pipeline abnormalities in a timely manner. This further exacerbates the operation and maintenance burden and cost of greenhouse cultivation, making it difficult to meet the requirements of large-scale and refined greenhouse cultivation for power supply stability, water and fertilizer stability, and temperature control accuracy. In view of this, we propose a perovskite photovoltaic phase change composite heat dissipation and temperature control synergistic device for greenhouse power supply. Summary of the Invention

[0004] The purpose of this invention is to provide a perovskite photovoltaic phase change composite heat dissipation and temperature control synergistic device for greenhouse energy supply, so as to solve the technical problems of unstable energy supply caused by photovoltaic power fluctuation, repeated fluctuation of water and fertilizer temperature and breakage of chelate bonds in greenhouse perovskite photovoltaic energy supply system.

[0005] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a perovskite photovoltaic phase change composite heat dissipation and temperature control collaborative device for greenhouse energy supply, comprising a collaborative control unit, a photovoltaic power fluctuation identification module, a two-stage filter collaborative control module, a multi-type chelated water and fertilizer adaptation module, an operation and maintenance early warning linkage module, a perovskite photovoltaic energy supply module, a phase change composite heat dissipation module, a greenhouse temperature control module, a water and fertilizer supply module, and an irrigation module. The collaborative control unit coordinates the coordinated operation of each module. The photovoltaic power fluctuation identification module collects power output and greenhouse illumination data from the perovskite photovoltaic power supply module, identifies photovoltaic power fluctuation characteristics, and predicts potential fluctuations. The dual-level filtering collaborative control module links the perovskite photovoltaic power supply module and the phase change composite heat dissipation module based on the fluctuation identification results, realizing the coordinated linkage of photovoltaic power electrical filtering and phase change energy storage thermal filtering. The multi-type chelated water and fertilizer adaptation module identifies the water and fertilizer types and characteristics of the water and fertilizer supply module and dynamically adapts the filtering parameters. The operation and maintenance early warning linkage module monitors the stability of water and fertilizer chelate bonds and the operating status of irrigation module pipelines, and realizes early warning and fault handling, forming a fully closed-loop collaboration.

[0006] Preferably, the photovoltaic power fluctuation identification module includes a light acquisition unit and a weather early warning unit; The light acquisition unit is used to collect data on changes in light intensity in the greenhouse, and the weather warning unit is used to provide weather warning data for the surrounding area of ​​the greenhouse. The photovoltaic power fluctuation identification module analyzes the power output data and light intensity change data of the perovskite photovoltaic power supply module through a preset identification algorithm, identifies three types of fluctuations: high-frequency small fluctuations, high-frequency large fluctuations, and high-frequency superimposed fluctuations, extracts the core features of each type of fluctuation, and predicts the precursors of photovoltaic power fluctuations caused by sudden changes in light intensity by combining meteorological early warning data, and transmits the fluctuation identification results and precursor information to the collaborative control unit.

[0007] Preferably, the preset recognition algorithm extracts wave features and determines wave type using a formula, which is: ; By frequency The numerical range and the maximum power fluctuation amplitude within the preset time period Determine the type of fluctuation; in, For photovoltaic power fluctuation frequency, For the photovoltaic power fluctuation cycle, The number of times photovoltaic power data was collected. The data collection time interval For the first The photovoltaic power output value collected this time. This represents the average photovoltaic power output over a preset time period. The standard deviation of photovoltaic power fluctuation. This represents the maximum power fluctuation amplitude within a preset time period.

[0008] Preferably, the dual-stage filtering and coordinated control module includes a photovoltaic power electrical filtering submodule and a phase change energy storage thermal filtering submodule, and the two submodules operate in coordination under the control of the coordinated control unit; The photovoltaic power filtering submodule is linked to an energy storage unit, which is used to store excess electrical energy generated by the perovskite photovoltaic power supply module. The photovoltaic power filtering submodule stabilizes the output power of the perovskite photovoltaic power supply module through energy compensation, thus offsetting the impact of power fluctuations on the stability of power supply. The phase change energy storage thermal filter submodule utilizes the thermal inertia characteristics of the phase change material in the phase change composite heat dissipation module to adjust the heat exchange state of the phase change material, thereby offsetting the water and fertilizer temperature fluctuations in the water and fertilizer supply module caused by power fluctuations. The two work together to achieve dual suppression of power and temperature fluctuations.

[0009] Preferably, the energy compensation of the photovoltaic power filter submodule is calculated using the following formula: ; in, This represents the instantaneous energy compensation amount of the electrical filtering submodule. This is the energy compensation coefficient. For photovoltaic power fluctuation frequency, The maximum power fluctuation range within a preset time period. Energy conversion efficiency of energy storage units. For instantaneous compensation time; The dual-level filtering collaborative control module dynamically adjusts the operating priority and control intensity of the photovoltaic power electric filtering submodule and the phase change energy storage thermal filtering submodule according to the fluctuation type output by the photovoltaic power fluctuation identification module, so as to achieve a balance between chelate bond protection and greenhouse energy supply.

[0010] Preferably, the control intensity of the phase change energy storage thermal filter submodule is characterized by the heat exchange rate of the phase change material, which is calculated using the following formula: ; in, The heat exchange rate of the phase change material. This represents the instantaneous energy compensation amount of the electrical filtering submodule. For the density of phase change materials, This refers to the specific heat capacity of the phase change material. This represents the difference between the target temperature for water and fertilizer application and the actual temperature. This refers to the contact area between the phase change material and the water and fertilizer. This is for instantaneous compensation time.

[0011] Preferably, the multi-type chelated water and fertilizer adaptation module includes a water and fertilizer characteristic identification unit and a parameter adaptation unit; The water and fertilizer characteristic identification unit is used to collect the type and core characteristics of chelated water and fertilizer in the water and fertilizer supply module in real time. The parameter adaptation unit is used to preset the chelate bond stability requirements corresponding to different types of chelated water and fertilizer. The parameter adaptation unit constructs a linkage logic between photovoltaic power fluctuation characteristics and water and fertilizer adaptation parameters. The water and fertilizer characteristic identification unit transmits the water and fertilizer identification results to the collaborative control unit, which then controls the dual-level filtering collaborative control module to dynamically adjust the filtering control parameters. The linkage logic is implemented using the following formula: ; in, For the filter parameter adaptation coefficients of the two-stage filter collaborative control module, The heat exchange rate of the phase change material. The thermal stability coefficients of chelate bonds in different types of chelated water-fertilizers. For instantaneous compensation time, For the density of phase change materials, This refers to the specific heat capacity of the phase change material. This represents the difference between the target temperature for water and fertilizer application and the actual temperature. This refers to the contact area between the phase change material and the water and fertilizer.

[0012] Preferably, the operation and maintenance early warning linkage module includes a status monitoring unit, an early warning unit, and a fault handling unit; The status monitoring unit is used to monitor in real time the stability of the chelate bonds of chelated water and fertilizer in the water and fertilizer supply module and the pipeline operation status of the irrigation module. The status monitoring unit is preset with a chelate bond stability threshold and a pipeline operation safety threshold. When the status monitoring unit detects that the stability of the chelate bond is lower than the preset threshold or the pipeline operation status is abnormal, the early warning unit issues an early warning signal and transmits the monitoring data to the collaborative control unit. Under the control of the collaborative control unit, the fault handling unit links the dual-level filter collaborative control module to adjust the control parameters, and simultaneously links the water and fertilizer mixing unit and the pipeline filtration unit to start the handling procedure. The stability of the chelate bond is determined by the following formula: ; in, For the actual stability of the chelate bond, For the filter parameter adaptation coefficients of the two-stage filter collaborative control module, For the safe and stable temperature of chelated water and fertilizer, This refers to the actual temperature of the water and fertilizer. To determine the degree of fit between the actual temperature of the water and fertilizer system and the safe and stable temperature. A preset warning threshold is set for chelate bond stability.

[0013] Preferably, the perovskite photovoltaic power supply module provides core power, which is linked to the photovoltaic power filtering sub-module of the dual-level filter collaborative control module, and dynamically adjusts the power output state according to the instructions of the collaborative control unit. Part of the power is directly used to power the greenhouse temperature control module, water and fertilizer supply module, irrigation module and various control modules, and the other part of the power is stored in the energy storage unit for energy compensation during power fluctuations, greenhouse nighttime power supply and emergency power supply. The phase change composite heat dissipation module receives the heat generated by the perovskite photovoltaic power supply module components, and stores and releases the heat through the phase change material inside the module. This provides heat support for the regulation of the phase change energy storage heat filter submodule. At the same time, it distributes the stored heat to the greenhouse according to the needs of the greenhouse temperature control module, realizing the synergy between heat dissipation of the perovskite photovoltaic power supply module components and greenhouse temperature control.

[0014] Preferably, the status monitoring unit determines the stability of the chelate bond by monitoring the physicochemical properties of the water and fertilizer in the water and fertilizer supply module, and determines the pipeline operating status by monitoring the pressure changes in the irrigation module pipeline. The status monitoring unit is connected to the data storage unit, which is used to store monitoring data and form a historical operation database, providing data support for the optimization of the identification algorithm of the photovoltaic power fluctuation identification module, the adaptation of the filter parameters of the dual-level filter collaborative control module, and the adjustment of the early warning threshold of the operation and maintenance early warning linkage module. The optimization coefficient of the photovoltaic power fluctuation identification algorithm is calculated using the following formula: ; in, These are the optimization coefficients for the photovoltaic power fluctuation identification algorithm. A pre-set warning threshold is set for chelate bond stability. For the actual stability of the chelate bond, These are the initial coefficients for the fluctuation identification algorithm. For photovoltaic power fluctuation frequency, This is the average frequency of photovoltaic power fluctuations over a preset time period.

[0015] Compared with the prior art, the beneficial effects of the present invention are: 1. This invention constructs a fully closed-loop collaborative system of "fluctuation identification - filtering and control - water and fertilizer adaptation - operation and maintenance support" by setting up a photovoltaic power fluctuation identification module, a two-level filtering and collaborative control module, a multi-type chelated water and fertilizer adaptation module, an operation and maintenance early warning linkage module, and a collaborative control unit. It can accurately identify different types of photovoltaic power fluctuations and predict the precursors of fluctuations. Through the coordinated linkage of electrical filtering and thermal filtering, it stabilizes photovoltaic power supply and water and fertilizer temperature, avoids thermal shock caused by power fluctuations from damaging chelate bonds, and takes into account the heat dissipation of perovskite photovoltaic modules and the temperature control requirements of greenhouses. It effectively solves the problems of poor control targeting and insufficient coordination of existing devices, ensures the stability of greenhouse power supply and water and fertilizer nutrient stability, and promotes the large-scale application of perovskite photovoltaic technology in the field of greenhouse planting.

[0016] 2. This invention also uses a multi-type chelated water and fertilizer adaptation module to identify water and fertilizer types and characteristics in real time, construct a linkage logic between fluctuation characteristics and water and fertilizer adaptation parameters, and dynamically adjust the dual-level filtering control parameters. This enables the same device to accurately adapt to multiple different types of chelated water and fertilizer without having to change the control device or adjust the equipment parameters for different water and fertilizer types. This greatly improves the versatility and practicality of the device, while further strengthening the stability protection effect of chelate bonds, reducing water and fertilizer nutrient loss, and lowering the cost of water and fertilizer input in greenhouses.

[0017] 3. This invention also uses an operation and maintenance early warning linkage module to monitor the stability of chelate bonds and the operating status of irrigation pipelines in real time. It presets stability thresholds and safety thresholds, and issues early warning signals in a timely manner when an abnormality occurs, and links the fault handling unit to start the corresponding handling procedure, realizing a closed-loop linkage between early warning and fault handling. At the same time, through data storage and algorithm self-optimization mechanism, it continuously improves the accuracy of fluctuation identification and control effect, reduces the frequency of manual monitoring and intervention, reduces the labor intensity of operation and maintenance personnel, further reduces the operation and maintenance cost of greenhouses, and realizes the intelligent and efficient operation of greenhouse photovoltaic power supply and temperature control system. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the overall collaborative framework of the present invention; Figure 2 This is a schematic diagram of the composition and data flow of the photovoltaic power fluctuation identification module of the present invention; Figure 3 This is a schematic diagram of the framework of the dual-stage filtering collaborative control module of the present invention, showing its composition and linkage. Figure 4 This is a schematic diagram of the internal structure of the multi-type chelated water and fertilizer adaptation module of the present invention. Figure 5 This is a schematic diagram of the framework of the operation and maintenance early warning linkage module and the monitoring objects of the present invention. Detailed Implementation

[0019] To facilitate understanding of the technical solution of the present invention by those skilled in the art, the technical solution of the present invention will now be further described in conjunction with the accompanying drawings.

[0020] Example 1, such as Figures 1-5 As shown, this invention provides a perovskite photovoltaic phase change composite heat dissipation and temperature control synergistic device for greenhouse power supply, comprising: The system includes a photovoltaic power fluctuation identification module, a two-stage filtering and coordinated control module, a multi-type chelated water and fertilizer adaptation module, an operation and maintenance early warning linkage module, and a coordinated control unit. Each module is linked with the perovskite photovoltaic power supply module, the phase change composite heat dissipation module, the greenhouse temperature control module, the water and fertilizer supply module, and the irrigation module.

[0021] The collaborative control unit coordinates the coordinated operation of all modules, while the photovoltaic power fluctuation identification module collects photovoltaic power output and illumination data in real time, identifies different types of photovoltaic power fluctuation characteristics, and predicts the precursors of fluctuations. Based on the fluctuation identification results, the dual-stage filtering and coordinated control module links the perovskite photovoltaic power supply module and the phase change composite heat dissipation module to achieve coordinated linkage between photovoltaic power electrical filtering and phase change energy storage thermal filtering, stabilize water and fertilizer temperature and power supply stability, and avoid thermal shock breakage of chelate bonds caused by fluctuations. The multi-type chelated water and fertilizer adaptation module identifies water and fertilizer types and characteristics, and dynamically adapts and adjusts filter parameters. The operation and maintenance early warning linkage module monitors the stability of chelate bonds and the operating status of irrigation pipelines, realizes early warning and fault linkage, and forms a closed-loop collaboration of "fluctuation identification - filtering and control - water and fertilizer adaptation - operation and maintenance support". It takes into account the greenhouse temperature control and the heat dissipation needs of perovskite photovoltaic modules, improves the utilization rate of photovoltaic energy supply and the stability of water and fertilizer nutrients, and reduces the operation and maintenance cost of greenhouse. In an embodiment of the present invention, the photovoltaic power fluctuation identification module is linked with the light acquisition unit and the weather warning unit. It analyzes the photovoltaic power output data and light intensity change data through a preset identification algorithm, identifies three types of fluctuations: high-frequency small fluctuations, high-frequency large fluctuations, and high-frequency superimposed fluctuations, and extracts the core features of each type of fluctuation simultaneously. At the same time, it combines weather warning data to predict the precursors of photovoltaic power fluctuations caused by sudden changes in light intensity. The fluctuation identification results and precursor information are transmitted to the collaborative control unit in real time to provide data support for subsequent filtering and regulation, thereby achieving accurate identification and early prediction of photovoltaic power fluctuations.

[0022] The preset recognition algorithm extracts fluctuation features and determines fluctuation type using the following formula: ; By frequency The numerical range and the maximum power fluctuation amplitude within the preset time period Determine the type of fluctuation; in, The photovoltaic power fluctuation frequency characterizes how frequently the photovoltaic power output value changes over time, and is one of the core parameters for determining the type of fluctuation. The photovoltaic power fluctuation period is the time required for the photovoltaic power to complete one full fluctuation, which is inversely related to the fluctuation frequency. The number of photovoltaic power data acquisitions is the total number of times the photovoltaic power output value is collected within a preset time period, which is used to calculate the standard deviation of power fluctuation. This refers to the data acquisition time interval, which is the time interval between two acquisitions of photovoltaic power output values, to ensure the continuity and standardization of the acquired data. For the first The photovoltaic power output value collected in a single acquisition is the actual power output data of the perovskite photovoltaic power supply module obtained in a single acquisition. This is the average photovoltaic power output over a preset time period, i.e., by averaging all photovoltaic power output values ​​collected within that preset time period. The arithmetic mean is used to obtain the photovoltaic power baseline value, which is then used to calculate the power fluctuation deviation. The standard deviation of photovoltaic power fluctuation is used to characterize the degree of dispersion of photovoltaic power output value relative to the average value within a preset time period. The greater the dispersion, the more severe the power fluctuation. The maximum power fluctuation amplitude within a preset time period is determined by calculating the amplitude of all individual power fluctuations. The maximum value of the photovoltaic power fluctuation is obtained from the maximum range of photovoltaic power fluctuation. The core of this formula is used to accurately extract photovoltaic power fluctuation characteristics and determine the fluctuation type. First, the basic definition of fluctuation frequency is clarified through the conventional correlation between frequency and period. Then, combined with photovoltaic power acquisition data, the photovoltaic power fluctuation frequency is calculated by dividing the number of acquisitions by the product of the data acquisition time interval and the standard deviation of power fluctuation. Simultaneously, by extracting the maximum power fluctuation amplitude within a preset time period and combining it with the numerical range of the fluctuation frequency, the three fluctuation types are accurately determined, providing core input parameters for subsequent two-stage filtering and coordinated control. The entire operational logic revolves around "data acquisition - feature extraction - type determination," ensuring the accuracy and specificity of fluctuation identification.

[0023] In an embodiment of the present invention, the dual-stage filtering collaborative control module includes a photovoltaic power electric filtering submodule and a phase change energy storage thermal filtering submodule, and the two submodules operate collaboratively under the control of the collaborative control unit. The electric filter submodule is linked with the perovskite photovoltaic power supply module and the energy storage unit to stabilize the photovoltaic output power through energy compensation, thereby offsetting the impact of power fluctuations on the stability of power supply. The thermal filtering submodule is linked with the phase change composite heat dissipation module. By utilizing the thermal inertia characteristics of the phase change material, the heat exchange state of the phase change material is adjusted to offset the water and fertilizer temperature fluctuations caused by power fluctuations, and to avoid repeated hot and cold alternations in the water and fertilizer. The two work together to achieve dual suppression of power fluctuations and temperature fluctuations, with a focus on ensuring the stability of chelate bonds. The energy compensation of the electrical filter submodule is calculated using the following formula: ; in, The instantaneous energy compensation amount of the electric filter submodule is the instantaneous energy value that the electric filter submodule needs to obtain from the energy storage unit in order to stabilize the photovoltaic output power. It is the core basis for the regulation of the electric filter submodule. The energy compensation coefficient is used to calibrate the rationality of the energy compensation amount. Its value is dynamically calibrated by the remaining power of the energy storage unit to ensure that the energy compensation meets the power stability requirements while avoiding energy waste of the energy storage unit. The photovoltaic power fluctuation frequency characterizes the frequency of photovoltaic power fluctuations and directly affects the amount of energy compensation. The maximum power fluctuation amplitude within a preset time period represents the maximum range of photovoltaic power fluctuation and is one of the core parameters that determines the amount of energy compensation. The energy conversion efficiency of an energy storage unit, which is the conversion ratio between the electrical energy released by the energy storage unit and the electrical energy stored, is used to calibrate the actual usable value of the energy compensation amount and ensure the accuracy of energy compensation. The instantaneous compensation time is the length of time for the electric filter submodule to perform energy compensation once. It is linked to the data acquisition time interval to ensure that the energy compensation can adapt to photovoltaic power fluctuations in a timely manner. This formula is used to calculate the instantaneous energy compensation of the electric filter submodule, thereby achieving stable control of photovoltaic output power. The calculation logic uses the fluctuation frequency and the maximum power fluctuation amplitude as core input parameters, combined with the energy compensation coefficient, the energy conversion efficiency of the energy storage unit, and the instantaneous compensation time. Through the multiplication of multiple parameters, the instantaneous energy compensation required to achieve power stability is accurately calculated. The instantaneous compensation time is linked to the data acquisition time interval to ensure the timeliness and adaptability of energy compensation. The energy compensation calculated by this formula can not only stabilize the photovoltaic output power but also provide a reliable energy basis for the control of the thermal filter submodule, realizing the synergistic linkage between electric and thermal filtering.

[0024] In an embodiment of the present invention, the dual-stage filtering collaborative control module can dynamically adjust the operating priority and control intensity of the two sub-modules according to the fluctuation type output by the photovoltaic power fluctuation identification module: To address high-frequency, small-amplitude fluctuations, the system primarily uses a phase-change energy storage thermal filtering submodule, supplemented by a photovoltaic power electrical filtering submodule, with a focus on suppressing temperature fluctuations. In response to high-frequency and large fluctuations, the two sub-modules operate synchronously at high intensity, ensuring both power and temperature stability. In response to high-frequency superimposed fluctuations, priority is given to ensuring the operation of the phase change energy storage thermal filter submodule, and the power supply priority of non-core loads in the greenhouse is temporarily adjusted. Normal power supply distribution is restored after the fluctuations are relieved, thus achieving a balance between chelate bond protection and greenhouse power supply. The control intensity (heat exchange rate of the phase change material) of the thermal filtering submodule is calculated using the following formula: ; in, The heat exchange rate of the phase change material, i.e. the control intensity of the heat filter submodule, characterizes the amount of heat transferred between the phase change material and water and fertilizer per unit time, and is the core basis for the control of the heat filter submodule. The instantaneous energy compensation for the electrical filter submodule provides the energy basis for the heat exchange of the thermal filter submodule and directly affects the magnitude of the heat exchange rate. The density of a phase change material, i.e., the mass of a phase change material per unit volume, is one of the core parameters characterizing the thermophysical properties of a phase change material and affects its heat exchange capacity. The specific heat capacity of a phase change material is the amount of heat that a unit mass of phase change material needs to absorb or release to raise or lower the temperature by a unit. It characterizes the heat storage capacity of a phase change material and directly affects the precision of heat exchange rate control. The difference between the target temperature for water and fertilizer and the actual temperature, i.e., the difference between the preset safe and stable temperature for water and fertilizer and the current measured temperature for water and fertilizer, is used to calibrate the direction and intensity of the heat exchange rate control. The contact area between the phase change material and the water and fertilizer is the size of the area in direct contact between the phase change material and the water and fertilizer. The larger the contact area, the higher the heat exchange efficiency, and the greater the influence on the heat exchange rate.

[0025] The instantaneous compensation time is the length of time for the thermal filter submodule to perform heat exchange regulation in a single operation. It is synchronized with the instantaneous compensation time of the electrical filter submodule to ensure the synergy of the two-stage filtering. The core of this formula is used to calculate the control intensity of the thermal filtering submodule (i.e., the heat exchange rate of the phase change material), achieving precise suppression of water and fertilizer temperature fluctuations. The calculation logic uses the instantaneous energy compensation amount as the core input parameter, combined with the density of the phase change material, specific heat capacity, water and fertilizer temperature difference, and the contact area between the phase change material and the water and fertilizer. It also introduces the instantaneous compensation time, and accurately calculates the required heat exchange rate of the phase change material by dividing the energy compensation amount by the product of each parameter. This calculation logic links the energy compensation of the electrical filter with the temperature control of the thermal filter, ensuring that the control intensity of the thermal filtering submodule can adapt to photovoltaic power fluctuations, achieving precise suppression of temperature fluctuations, and forming a synergistic linkage with the electrical filter submodule to jointly ensure the stability of the chelate bond.

[0026] In an embodiment of the present invention, the multi-type chelated water and fertilizer adaptation module includes a water and fertilizer characteristic identification unit and a parameter adaptation unit. The water and fertilizer characteristic identification unit collects the type and core characteristics of the chelated water and fertilizer used in the greenhouse in real time. The parameter adaptation unit presets the chelate bond stability requirements corresponding to different types of chelated water and fertilizer, constructs the linkage logic between fluctuation characteristics and water and fertilizer adaptation parameters, and transmits the water and fertilizer identification results to the collaborative control unit. The collaborative control unit controls the two-level filtering collaborative regulation module to dynamically adjust the filtering regulation parameters. The linkage logic between fluctuation characteristics and water-fertilizer adaptation parameters is achieved through the following formula: ; in, The filter parameter adaptation coefficient of the dual-stage filter collaborative control module is a dimensionless coefficient that characterizes the degree of adaptation between the dual-stage filter control parameters and the currently used chelated water and fertilizer. It is the core basis for dynamically adjusting the filter parameters. The heat exchange rate of the phase change material characterizes the current control intensity of the thermal filter submodule and directly affects the size of the adaptation coefficient. The thermal stability coefficient of the chelate bond for different types of chelated water-fertilizer is a preset parameter that is dynamically adjusted according to the different types of chelated water-fertilizer, characterizing the ability of different water-fertilizer chelate bonds to resist temperature fluctuations. To compensate for the instantaneous time, it is synchronized with the control time of the two-stage filter to ensure that the adaptation coefficient can adapt to the current control state in a timely manner; The density of the phase change material is used to calibrate the rationality of the fit coefficient, ensuring that the fit coefficient can fit the thermophysical properties of the phase change material. The specific heat capacity of a phase change material characterizes its heat storage capacity and affects the accuracy of the fit coefficient. The difference between the target temperature and the actual temperature of the water and fertilizer system is used to calibrate the adjustment direction of the adaptation coefficient, ensuring that the adaptation coefficient can fit the current water and fertilizer temperature state. The contact area between the phase change material and water and fertilizer affects the heat exchange efficiency, which in turn affects the rationality of the adaptation coefficient. The core of this formula is used to calculate the filter parameter adaptation coefficient of the dual-stage filter collaborative control module, achieving precise adaptation of filter control to multiple types of chelated water and fertilizer. The calculation logic uses the heat exchange rate of the phase change material as the core input parameter, combined with the chelate bond thermal stability coefficient, instantaneous compensation time, phase change material density, specific heat capacity, water-fertilizer temperature difference, and contact area of ​​different types of chelated water and fertilizer. Through multi-parameter collaborative calculation, the calculation result is finally presented as a dimensionless coefficient. This coefficient can accurately characterize the degree of adaptation between the filter control parameters and different types of chelated water and fertilizer, providing a core basis for the collaborative control unit to dynamically adjust the dual-stage filter control parameters, realizing the adaptation of the same device to multiple different types of chelated water and fertilizer, taking into account both the filtering effect and the stability of the chelate bond.

[0027] In an embodiment of the present invention, the operation and maintenance early warning linkage module includes a status monitoring unit, an early warning unit and a fault handling unit. The status monitoring unit monitors the stability of the chelate bonds of chelated water and fertilizer and the operating status of the greenhouse irrigation pipeline in real time, and presets a stability threshold and an operating safety threshold. When the stability of the chelate bond is detected to be lower than the preset threshold, or when the operation of the irrigation pipeline is abnormal, the early warning unit immediately issues an early warning signal and transmits the monitoring data to the collaborative control unit. Under the control of the collaborative control unit, the fault handling unit links the dual-level filter collaborative control module to adjust the control parameters, and at the same time links the water and fertilizer mixing unit and the pipeline filtration unit to start the corresponding handling program, so as to alleviate the tendency of chelate bond breakage, avoid irrigation pipeline blockage, and realize the closed-loop linkage of operation and maintenance early warning and fault handling. The stability determination and early warning threshold calibration of the chelate bond are achieved through the following formula: ; Preset warning threshold ,when At that time, the early warning unit issues an early warning signal and simultaneously... Feedback is sent to the collaborative control unit to provide a basis for adjusting the parameters of the fault handling unit; in, The actual stability of the chelate bond is expressed as a percentage, which represents the degree of integrity of the chelate bond in the current chelated state of water and fertilizer. It is the core parameter for determining whether the chelate bond is broken and whether the water and fertilizer nutrients are ineffective. The filter parameter adaptation coefficient of the two-stage filter collaborative control module represents the degree of adaptation between the filter control and the current water and fertilizer type, and directly affects the stability of the chelate bond; The safe and stable temperature for chelated water and fertilizer is the preset temperature that ensures that the chelate bonds do not break and the nutrients in the water and fertilizer remain stable. It is the benchmark value for judging whether the water and fertilizer temperature is reasonable. The actual temperature of the water and fertilizer, i.e. the temperature of the chelated water and fertilizer as currently measured, is one of the core environmental parameters affecting the stability of the chelate bond; The degree of fit between the actual water and fertilizer temperature and the safe and stable temperature is a dimensionless parameter that characterizes the extent to which the current water and fertilizer temperature deviates from the safe and stable temperature. The higher the degree of fit, the closer the water and fertilizer temperature is to the safe and stable temperature, and the more stable the chelate bond is. The chelate bond stability preset warning threshold, expressed as a percentage, is the critical value that triggers the warning signal. When the actual stability of the chelate bond is lower than this threshold, it indicates that there is a risk of breakage of the chelate bond, and the warning and fault handling procedures need to be initiated. The core of this formula is used to accurately determine the actual stability of chelate bonds and calibrate the warning threshold. The calculation logic uses the filter parameter adaptation coefficient as the core input parameter, combined with the safe and stable temperature of the chelated water and fertilizer and the actual temperature. By calculating the degree of fit between the actual water and fertilizer temperature and the safe and stable temperature, it is multiplied by the filter parameter adaptation coefficient and converted into a percentage to obtain the actual stability of the chelate bonds. By comparing the actual stability with the preset warning threshold, the stability of the chelate bonds is determined in real time. When the actual stability is lower than the warning threshold, a warning signal is triggered, providing a basis for fault handling. The entire calculation logic directly links the filtering control effect with the stability of the chelate bonds, ensuring the accuracy of stability determination and the timeliness of warning. In embodiments of the present invention, the collaborative control unit serves as the core control hub of the device. It receives various data transmitted from the photovoltaic power fluctuation identification module, the multi-type chelated water and fertilizer adaptation module, and the operation and maintenance early warning linkage module. Combining the heat dissipation requirements of the perovskite photovoltaic module, the greenhouse temperature control requirements, the water and fertilizer supply requirements, and the operation requirements of the irrigation module, it formulates a collaborative control strategy to control the operating status of each module and related unit. This achieves integrated collaboration of photovoltaic power fluctuation control, chelated water and fertilizer protection, greenhouse temperature control, photovoltaic module heat dissipation, and irrigation operation and maintenance, ensuring that the operating logic of each module is coherent and the control is precise, thereby improving the overall operating efficiency of the device.

[0028] In an embodiment of the present invention, the perovskite photovoltaic power supply module provides core power to the device and links the electrical filtering sub-module of the dual-level filter collaborative control module. According to the instructions of the collaborative control unit, the power output state is dynamically adjusted. Part of the power is directly used to power the greenhouse temperature control module, water and fertilizer supply module, irrigation module and various control modules, while the other part of the power is stored in the energy storage unit for energy compensation during fluctuation periods, nighttime power supply and emergency power supply during fault handling, taking into account both power supply stability and energy utilization rate.

[0029] In an embodiment of the present invention, the phase change composite heat dissipation module is linked with the thermal filtering sub-module of the dual-stage filter collaborative control module and the greenhouse temperature control module. On the one hand, it receives the heat dissipation generated by the perovskite photovoltaic module, and realizes the storage and release of heat through the phase change material, providing heat support for thermal filtering control and stabilizing the water and fertilizer temperature. On the other hand, based on the greenhouse temperature control requirements, the stored photovoltaic heat dissipation is rationally distributed to the greenhouse, realizing the synergy between photovoltaic module heat dissipation and greenhouse temperature control, improving the utilization rate of photovoltaic heat dissipation, and at the same time avoiding the photovoltaic modules from affecting the power generation stability due to overheating.

[0030] In an embodiment of the present invention, the status monitoring unit determines the stability of chelate bonds by monitoring the physicochemical properties of water and fertilizer, and determines the operating status of the irrigation pipeline by monitoring the pressure changes of the irrigation pipeline. The monitoring data is transmitted to the collaborative control unit in real time and stored in the data storage unit to form a historical operation database. This provides data support for the optimization of photovoltaic power fluctuation identification algorithms, the adaptation of filter control parameters, and the adjustment of early warning thresholds, thereby achieving self-optimization of the device's control accuracy and further improving the chelate bond protection effect and operation and maintenance efficiency. The optimization coefficients of the photovoltaic power fluctuation identification algorithm are calculated using the following formula: ; in, is the optimization coefficient of the photovoltaic power fluctuation identification algorithm, and is a dimensionless coefficient that characterizes the optimization direction and magnitude of the fluctuation identification algorithm; A preset warning threshold for chelate bond stability is set as a benchmark value for judging the deviation of chelate bond stability, which affects the magnitude and direction of the optimization coefficient; The actual stability of the chelate bond represents the current actual state of the chelate bond and is the core feedback parameter for algorithm optimization. These are the initial coefficients for the fluctuation identification algorithm, i.e., the basic adjustment coefficients of the fluctuation identification algorithm before optimization, used to calibrate the initial amplitude of the optimization coefficients; The photovoltaic power fluctuation frequency characterizes the frequency of current photovoltaic power fluctuations and is used to calibrate the adaptability of the optimization coefficients. The average frequency of photovoltaic power fluctuations over a preset time period is calculated by considering all fluctuation frequencies within that preset time period. The arithmetic mean is used to obtain the baseline value of the fluctuation frequency, which is used to characterize the average level of photovoltaic power fluctuation over a period of time. Combined with the current fluctuation frequency, it improves the accuracy of the optimization coefficient. The core of this formula is used to calculate the optimization coefficients of the photovoltaic power fluctuation identification algorithm, enabling the algorithm to self-optimize. The operation logic takes the actual stability of the chelate bond as the core input parameter, combined with the preset warning threshold for chelate bond stability, the initial coefficients of the algorithm, the frequency of photovoltaic power fluctuation, and the average frequency of fluctuation within a preset time. By calculating the deviation ratio between the actual stability of the chelate bond and the warning threshold, and then multiplying it by the initial coefficients of the algorithm and the ratio of the fluctuation frequency to the average frequency, the algorithm optimization coefficients are obtained. These coefficients can accurately characterize the optimization direction and magnitude of the fluctuation identification algorithm, linking the chelate bond stability feedback with the optimization of the fluctuation identification algorithm, realizing a fully closed-loop progression of "fluctuation identification - filtering and control - stability feedback - algorithm optimization", and improving the accuracy of fluctuation identification.

[0031] In an embodiment of the present invention, the energy storage unit is linked with the perovskite photovoltaic power supply module and the dual-stage filter coordinated control module to store the excess electrical energy generated by the photovoltaic power supply module and provide instantaneous energy compensation to the electrical filter submodule when the photovoltaic power fluctuates, thereby stabilizing the photovoltaic output power. During non-sunlight periods, it provides power for water and fertilizer insulation, greenhouse nighttime temperature control, and standby operation of various modules, ensuring stable operation of the device around the clock, while reducing energy waste and improving the overall utilization rate of photovoltaic energy supply.

[0032] In embodiments of the present invention, the identification algorithm of the photovoltaic power fluctuation identification module can be self-trained and optimized through historical fluctuation data, light data, and water and fertilizer protection effect data, gradually improving the accuracy of fluctuation identification and the predictive timeliness of fluctuation precursors, reducing the problem of chelate bond breakage caused by untimely fluctuation identification, and providing a more accurate control basis for the dual-stage filter collaborative control module.

[0033] The embodiments disclosed in this invention are preferred embodiments, but are not limited thereto. Those skilled in the art can easily understand the spirit of this invention based on the above embodiments and make different extensions and variations, but as long as they do not depart from the spirit of this invention, they are all within the protection scope of this invention.

Claims

1. A perovskite photovoltaic phase change composite heat dissipation and temperature control synergistic device for greenhouse energy supply, characterized in that, It includes a collaborative control unit, a photovoltaic power fluctuation identification module, a two-stage filter collaborative control module, a multi-type chelated water and fertilizer adaptation module, an operation and maintenance early warning linkage module, a perovskite photovoltaic power supply module, a phase change composite heat dissipation module, a greenhouse temperature control module, a water and fertilizer supply module, and an irrigation module. The collaborative control unit coordinates the coordinated operation of each module. The photovoltaic power fluctuation identification module collects power output and greenhouse illumination data from the perovskite photovoltaic power supply module, identifies photovoltaic power fluctuation characteristics, and predicts potential fluctuations. The dual-level filtering collaborative control module links the perovskite photovoltaic power supply module and the phase change composite heat dissipation module based on the fluctuation identification results, realizing the coordinated linkage of photovoltaic power electrical filtering and phase change energy storage thermal filtering. The multi-type chelated water and fertilizer adaptation module identifies the water and fertilizer types and characteristics of the water and fertilizer supply module and dynamically adapts the filtering parameters. The operation and maintenance early warning linkage module monitors the stability of water and fertilizer chelate bonds and the operating status of irrigation module pipelines, and realizes early warning and fault handling, forming a fully closed-loop collaboration.

2. The perovskite photovoltaic phase change composite heat dissipation and temperature control synergistic device for greenhouse energy supply according to claim 1, characterized in that, The photovoltaic power fluctuation identification module includes a light acquisition unit and a weather early warning unit; The light acquisition unit is used to collect data on changes in light intensity in the greenhouse, and the weather warning unit is used to provide weather warning data for the surrounding area of ​​the greenhouse. The photovoltaic power fluctuation identification module analyzes the power output data and light intensity change data of the perovskite photovoltaic power supply module through a preset identification algorithm, identifies three types of fluctuations: high-frequency small fluctuations, high-frequency large fluctuations, and high-frequency superimposed fluctuations, extracts the core features of each type of fluctuation, and predicts the precursors of photovoltaic power fluctuations caused by sudden changes in light intensity by combining meteorological early warning data, and transmits the fluctuation identification results and precursor information to the collaborative control unit.

3. The perovskite photovoltaic phase change composite heat dissipation and temperature control synergistic device for greenhouse energy supply according to claim 2, characterized in that, The preset recognition algorithm extracts wave features and determines wave type through a formula, which is: ； By frequency The numerical range and the maximum power fluctuation amplitude within the preset time period Determine the type of fluctuation; in, For photovoltaic power fluctuation frequency, For the photovoltaic power fluctuation cycle, The number of times photovoltaic power data was collected. The data collection time interval For the first The photovoltaic power output value collected this time. This represents the average photovoltaic power output over a preset time period. The standard deviation of photovoltaic power fluctuation. This represents the maximum power fluctuation amplitude within a preset time period.

4. The perovskite photovoltaic phase change composite heat dissipation and temperature control synergistic device for greenhouse energy supply according to claim 1, characterized in that, The dual-stage filtering and coordinated control module includes a photovoltaic power electric filtering submodule and a phase change energy storage thermal filtering submodule. The two submodules operate in coordination under the control of the coordinated control unit. The photovoltaic power filtering submodule is linked to an energy storage unit, which is used to store excess electrical energy generated by the perovskite photovoltaic power supply module. The photovoltaic power filtering submodule stabilizes the output power of the perovskite photovoltaic power supply module through energy compensation, thus offsetting the impact of power fluctuations on the stability of power supply. The phase change energy storage thermal filter submodule utilizes the thermal inertia characteristics of the phase change material in the phase change composite heat dissipation module to adjust the heat exchange state of the phase change material, thereby offsetting the water and fertilizer temperature fluctuations in the water and fertilizer supply module caused by power fluctuations. The two work together to achieve dual suppression of power and temperature fluctuations.

5. The perovskite photovoltaic phase change composite heat dissipation and temperature control synergistic device for greenhouse energy supply according to claim 4, characterized in that, The energy compensation of the photovoltaic power filter submodule is calculated using the following formula: ； in, This represents the instantaneous energy compensation amount of the electrical filtering submodule. This is the energy compensation coefficient. For photovoltaic power fluctuation frequency, The maximum power fluctuation range within a preset time period. Energy conversion efficiency of energy storage units. For instantaneous compensation time; The dual-level filtering collaborative control module dynamically adjusts the operating priority and control intensity of the photovoltaic power electric filtering submodule and the phase change energy storage thermal filtering submodule according to the fluctuation type output by the photovoltaic power fluctuation identification module, so as to achieve a balance between chelate bond protection and greenhouse energy supply.

6. The perovskite photovoltaic phase change composite heat dissipation and temperature control synergistic device for greenhouse energy supply according to claim 5, characterized in that, The control intensity of the phase change energy storage thermal filter submodule is characterized by the heat exchange rate of the phase change material, which is calculated using the following formula: ； in, The heat exchange rate of the phase change material. This represents the instantaneous energy compensation amount of the electrical filtering submodule. For the density of phase change materials, This refers to the specific heat capacity of the phase change material. This represents the difference between the target temperature for water and fertilizer application and the actual temperature. This refers to the contact area between the phase change material and the water and fertilizer. This is for instantaneous compensation time.

7. The perovskite photovoltaic phase change composite heat dissipation and temperature control synergistic device for greenhouse energy supply according to claim 1, characterized in that, The multi-type chelated water and fertilizer adaptation module includes a water and fertilizer characteristic identification unit and a parameter adaptation unit. The water and fertilizer characteristic identification unit is used to collect the type and core characteristics of chelated water and fertilizer in the water and fertilizer supply module in real time. The parameter adaptation unit is used to preset the chelate bond stability requirements corresponding to different types of chelated water and fertilizer. The parameter adaptation unit constructs a linkage logic between photovoltaic power fluctuation characteristics and water and fertilizer adaptation parameters. The water and fertilizer characteristic identification unit transmits the water and fertilizer identification results to the collaborative control unit, which then controls the dual-level filtering collaborative control module to dynamically adjust the filtering control parameters. The linkage logic is implemented using the following formula: ； in, For the filter parameter adaptation coefficients of the two-stage filter collaborative control module, The heat exchange rate of the phase change material. The thermal stability coefficients of chelate bonds in different types of chelated water-fertilizers. For instantaneous compensation time, For the density of phase change materials, This refers to the specific heat capacity of the phase change material. This represents the difference between the target temperature for water and fertilizer application and the actual temperature. This refers to the contact area between the phase change material and the water and fertilizer.

8. The perovskite photovoltaic phase change composite heat dissipation and temperature control synergistic device for greenhouse energy supply according to claim 1, characterized in that, The operation and maintenance early warning linkage module includes a status monitoring unit, an early warning unit, and a fault handling unit; The status monitoring unit is used to monitor in real time the stability of the chelate bonds of chelated water and fertilizer in the water and fertilizer supply module and the pipeline operation status of the irrigation module. The status monitoring unit is preset with a chelate bond stability threshold and a pipeline operation safety threshold. When the status monitoring unit detects that the stability of the chelate bond is lower than the preset threshold or the pipeline operation status is abnormal, the early warning unit issues an early warning signal and transmits the monitoring data to the collaborative control unit. Under the control of the collaborative control unit, the fault handling unit links the dual-level filter collaborative control module to adjust the control parameters, and simultaneously links the water and fertilizer mixing unit and the pipeline filtration unit to start the handling procedure. The stability of the chelate bond is determined by the following formula: ； in, For the actual stability of the chelate bond, For the filter parameter adaptation coefficients of the two-stage filter collaborative control module, For the safe and stable temperature of chelated water and fertilizer, This refers to the actual temperature of the water and fertilizer. To determine the degree of fit between the actual temperature of the water and fertilizer system and the safe and stable temperature. A preset warning threshold is set for chelate bond stability.

9. A perovskite photovoltaic phase change composite heat dissipation and temperature control synergistic device for greenhouse energy supply according to claim 1, characterized in that, The perovskite photovoltaic power supply module provides core power, which is linked to the photovoltaic power filtering sub-module of the dual-level filter collaborative control module. It dynamically adjusts the power output state according to the instructions of the collaborative control unit. Part of the power is directly used to power the greenhouse temperature control module, water and fertilizer supply module, irrigation module and various control modules, while the other part of the power is stored in the energy storage unit for energy compensation during power fluctuations, greenhouse nighttime power supply and emergency power supply. The phase change composite heat dissipation module receives the heat generated by the perovskite photovoltaic power supply module components, and stores and releases the heat through the phase change material inside the module. This provides heat support for the regulation of the phase change energy storage heat filter submodule. At the same time, it distributes the stored heat to the greenhouse according to the needs of the greenhouse temperature control module, realizing the synergy between heat dissipation of the perovskite photovoltaic power supply module components and greenhouse temperature control.

10. A perovskite photovoltaic phase change composite heat dissipation and temperature control synergistic device for greenhouse energy supply according to claim 1, characterized in that, The status monitoring unit determines the stability of chelate bonds by monitoring the physicochemical properties of water and fertilizer in the water and fertilizer supply module, and determines the operating status of the pipeline by monitoring the pressure changes in the irrigation module pipeline. The status monitoring unit is connected to the data storage unit, which is used to store monitoring data and form a historical operation database, providing data support for the optimization of the identification algorithm of the photovoltaic power fluctuation identification module, the adaptation of the filter parameters of the dual-level filter collaborative control module, and the adjustment of the early warning threshold of the operation and maintenance early warning linkage module. The optimization coefficient of the photovoltaic power fluctuation identification algorithm is calculated using the following formula: ； in, These are the optimization coefficients for the photovoltaic power fluctuation identification algorithm. A pre-set warning threshold is set for chelate bond stability. For the actual stability of the chelate bond, These are the initial coefficients for the fluctuation identification algorithm. For photovoltaic power fluctuation frequency, This is the average frequency of photovoltaic power fluctuations over a preset time period.

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