Perovskite photovoltaic power supply regulation method and system based on agricultural ecological warehouse

Abstract

The application discloses a perovskite photovoltaic power supply regulation method and system based on an agricultural ecological warehouse. The method obtains environmental parameters, crop growth state data and real-time power generation operation data of the perovskite photovoltaic module in the agricultural ecological warehouse; according to the above parameters and data, the real-time environmental regulation energy consumption demand of the agricultural ecological warehouse is calculated; based on the real-time power generation operation data and the energy consumption demand, a power supply regulation strategy is generated, and then the output power distribution of the photovoltaic module is controlled and the operating state of the environmental regulation equipment is adjusted. The application also executes electrical voltage reduction and water cooling and spraying cooling in linkage when the working temperature of the module exceeds the limit, and controls the photovoltaic to deviate from the maximum power point when the battery is fully charged. The application realizes accurate dynamic matching of the agricultural environmental load and the photovoltaic power supply, effectively suppresses the thermal decay of the perovskite material, and guarantees the long-term stable operation of the system.

Description

Technical Field

[0001] This invention relates to the field of photovoltaic power generation and agricultural microgrid control technology, specifically to a method and system for regulating perovskite photovoltaic power supply based on agricultural ecological warehouses. Background Technology

[0002] With the integration of facility agriculture and new energy technologies, deploying semi-transparent perovskite photovoltaic modules on the translucent top of agricultural ecological warehouses to achieve top-level power generation and internal planting has become a common application model for agricultural photovoltaics. Existing systems typically control the photovoltaic power generation unit and the agricultural environmental control unit as two relatively independent subsystems. The photovoltaic inverter control focuses on tracking maximum power output, while the operating status of environmental control equipment within the agricultural ecological warehouse, such as temperature and humidity regulation, ventilation, and supplemental lighting, is adjusted according to external climate conditions and different growth stages of the crops, resulting in a dynamic change in its electrical load. This isolated control logic prevents the power generation on the power supply side from establishing a data correlation with the actual agricultural energy consumption demand on the load side. This leads to ineffective energy consumption when there is sufficient sunlight but low load, and a lack of a coordinated energy dispatch mechanism for energy storage and non-core loads when there is insufficient sunlight or a surge in environmental control loads.

[0003] Furthermore, perovskite photovoltaic materials exhibit more pronounced thermal sensitivity compared to traditional silicon-based modules. Under high outdoor irradiance or long-term continuous operation, heat accumulation within the module can lead to material structure degradation, causing irreversible decline in photoelectric conversion efficiency. Conventional photovoltaic microgrid dispatching systems only focus on balancing electrical parameters, failing to incorporate module operating temperature into the power supply control logic or establish proactive thermal protection strategies to address heat generation issues. The failure to utilize existing sprinkler or ventilation equipment in agricultural ecological warehouses to create a coordinated cooling system with the photovoltaic power generation system makes perovskite photovoltaic modules prone to accelerated aging under high-temperature conditions, impacting the long-term operational stability of the entire power supply system in agricultural facility scenarios. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a perovskite photovoltaic power supply regulation method and system based on agricultural ecological warehouses. This solves the problem that existing agricultural facilities' photovoltaic power supply systems cannot match power output to the dynamic environmental needs of crop growth, and that existing systems lack a thermal management mechanism for the high-temperature degradation characteristics of perovskite materials, resulting in the inability to form an effective linkage regulation between photovoltaic power generation units and agricultural environmental control equipment.

[0005] To achieve the above objectives, the present invention provides the following technical solution: The first aspect of this invention provides a method for regulating perovskite photovoltaic power supply based on an agricultural ecological warehouse, comprising the following steps: To acquire environmental parameters and crop growth status data within the agricultural ecological warehouse; Obtain real-time power generation and operation data of perovskite photovoltaic modules; Based on the environmental parameters and the crop growth status data, calculate the real-time environmental control energy consumption requirements of the agricultural ecological warehouse; Based on the real-time power generation operation data and the real-time environmental regulation energy consumption demand, a power supply regulation strategy is generated. According to the power supply regulation strategy, the output power distribution of the perovskite photovoltaic module is controlled, and the operating status of the environmental regulation equipment in the agricultural ecological warehouse is adjusted.

[0006] This invention establishes a computational mapping between the environmental needs of agricultural ecological warehouses and the operating data of photovoltaic power sources by synchronously collecting environmental data from the agricultural growing season and the power needs of microgrids. It integrates the output power of photovoltaic power generation and the operating load of environmental control equipment into a closed-loop control logic to achieve real-time matching between power generation on the source side and power consumption on the load side.

[0007] Furthermore, the acquisition of environmental parameters and crop growth status data within the agricultural ecological warehouse includes: collecting real-time light intensity, real-time temperature, real-time humidity, and real-time carbon dioxide concentration within the agricultural ecological warehouse as the environmental parameters; The acquisition of real-time power generation operation data of the perovskite photovoltaic module includes: collecting the output voltage, output current and surface operating temperature of the perovskite photovoltaic module as the real-time power generation operation data.

[0008] Furthermore, the step of calculating the real-time environmental control energy consumption requirement of the agricultural ecological warehouse based on the environmental parameters and the crop growth status data includes: Based on the crop growth status data, determine the target light intensity and target temperature required for the current growth cycle; Calculate the differences between the real-time light intensity and the real-time temperature in the environmental parameters and the target light intensity and the target temperature, respectively; The difference is input into a preset energy consumption prediction model to calculate the electrical load required to adjust the agricultural ecological warehouse to the target light intensity and the target temperature, which is used as the energy consumption requirement for real-time environmental regulation.

[0009] The above steps calculate the deviation values ​​of environmental physical quantities and convert them into the absolute electrical load required for the operation of environmental control equipment, providing basic data for subsequent microgrid power allocation.

[0010] Furthermore, the step of generating a power supply control strategy based on the real-time power generation operation data and the real-time environmental regulation energy consumption demand includes: Calculate the real-time power generation corresponding to the real-time power generation operation data; When the real-time power generation is less than the real-time environmental control energy consumption requirement, the power supply control strategy is determined to be a shortfall power supply control strategy. The power supply deficit control strategy includes: generating a discharge command to call up the energy storage battery, and generating a load shedding command to reduce the operating power of non-core loads in the environmental control equipment.

[0011] Furthermore, controlling the output power distribution of the perovskite photovoltaic module includes: When implementing the power shortage control strategy, the output power of the perovskite photovoltaic module is transmitted to the environmental control equipment through the DC bus. According to the discharge command, the bidirectional DC / DC converter is controlled to operate in discharge mode, so that the energy storage battery outputs electrical energy to the DC bus to compensate for the difference between the real-time power generation and the real-time environmental regulation energy consumption demand.

[0012] When photovoltaic power supply is insufficient, this system uses the underlying electrical control topology to schedule energy storage and ensure the continuous operation of environmental control equipment.

[0013] Furthermore, the step of generating a power supply control strategy based on the real-time power generation operation data and the real-time environmental regulation energy consumption demand includes: When the real-time power generation corresponding to the real-time power generation operation data is greater than the real-time environmental regulation energy consumption demand, the power supply regulation strategy is determined as a surplus power supply regulation strategy. The surplus power supply regulation strategy includes generating charging instructions for charging the energy storage battery.

[0014] Furthermore, controlling the output power distribution of the perovskite photovoltaic module according to the power supply regulation strategy includes: Obtain the real-time state of charge value of the energy storage battery; When the real-time state of charge value is greater than the preset charge threshold, the perovskite photovoltaic module is controlled to leave the maximum power point tracking mode and the output voltage of the perovskite photovoltaic module is limited to reduce the real-time power generation.

[0015] This step involves actively deviating from the maximum power point through inverter control when the system's electrical energy approaches saturation, thereby reducing the power at the source and preventing overcharging of the energy storage battery.

[0016] Furthermore, the step of generating a power supply control strategy based on the real-time power generation operation data and the real-time environmental regulation energy consumption demand also includes: When the surface operating temperature is greater than the preset safe temperature threshold, the power supply control strategy is determined to be a thermal protection control strategy. The thermal protection control strategy includes: reducing the operating voltage of the perovskite photovoltaic module to reduce the heat generated by photoelectric conversion, and generating a control signal for activating the top cooling device in the environmental control equipment.

[0017] This step addresses the thermosensitive properties of perovskite materials by combining electrical voltage reduction to limit heat generation with physical heat dissipation from external devices, thereby suppressing component thermal decay and maintaining photoelectric conversion performance.

[0018] Furthermore, adjusting the operating status of the environmental control equipment within the agricultural ecological warehouse includes: The top cooling device in the environmental control equipment includes a water-cooled spray solenoid valve installed on the light-transmitting top of the agricultural ecological warehouse. Upon receiving the control signal, the water-cooled spray solenoid valve is opened to spray and cool the surface of the perovskite photovoltaic module until the surface operating temperature drops below the safe temperature threshold.

[0019] A second aspect of the present invention provides a perovskite photovoltaic power supply regulation system based on an agricultural ecological warehouse, used to implement the above-mentioned perovskite photovoltaic power supply regulation method based on an agricultural ecological warehouse, the system comprising: The data acquisition module is used to acquire environmental parameters and crop growth status data within the agricultural ecological warehouse, as well as real-time power generation operation data of the perovskite photovoltaic modules. The energy consumption calculation module is used to calculate the real-time environmental control energy consumption requirements of the agricultural ecological warehouse based on the environmental parameters and the crop growth status data. The strategy generation module is used to generate power supply control strategies based on the real-time power generation operation data and the real-time environmental regulation energy consumption requirements. The collaborative control module is used to control the output power distribution of the perovskite photovoltaic module according to the power supply regulation strategy, and to adjust the operating status of the environmental control equipment in the agricultural ecological warehouse.

[0020] This invention provides a method and system for regulating perovskite photovoltaic power supply based on agricultural ecological warehouses. It has the following beneficial effects: 1. This invention converts crop growth status and environmental parameters into quantified electrical load demands, and compares them with the real-time power generation of photovoltaic modules. This comparison serves as a control benchmark for adjusting environmental control equipment and photovoltaic output power. This closed-loop control logic, which directly links agricultural environmental demands with electrical loads, solves the problem of low matching between source-side power generation and load-side power consumption in conventional agricultural photovoltaic systems, thereby improving the system's energy distribution and utilization efficiency.

[0021] 2. This invention introduces a combined electrical and physical thermal protection mechanism into the power supply strategy. By actively reducing the photovoltaic module's operating voltage when the module's surface temperature exceeds a safe threshold to reduce internal heat generation from photoelectric conversion, and simultaneously coordinating with the water-cooled spray solenoid valve on the top of the storage compartment for external physical cooling, the module's surface temperature is quickly controlled within a safe range, thus slowing down the thermal degradation process of the perovskite material.

[0022] 3. This invention integrates microgrid management logic for charge / discharge scheduling and active power limiting at the source end into the control layer. When the system has a power deficit, a bidirectional DC / DC converter is invoked to control the discharge of the energy storage battery; when the system has a power surplus and the energy storage battery reaches its upper charge threshold, the photovoltaic modules are controlled to actively deviate from their maximum power point to reduce power output. This control method maintains the continuous operation of environmental control equipment while eliminating the risk of hardware damage from battery overcharging. Attached Figure Description

[0023] Figure 1 This is a structural block diagram of a perovskite photovoltaic power supply control system based on an agricultural ecological warehouse according to an embodiment of the present invention; Figure 2 This is a flowchart of a perovskite photovoltaic power supply regulation method based on an agricultural ecological warehouse according to an embodiment of the present invention; Figure 3 This is a schematic diagram illustrating the signal sampling and parameter calculation principle according to an embodiment of the present invention; Figure 4 This is a steady-state data acquisition and basic control logic diagram according to an embodiment of the present invention; Figure 5 This is a schematic diagram of the microenvironment time-varying prediction logic according to an embodiment of the present invention; Figure 6 This is a flowchart of boundary extremum determination and model derivation according to an embodiment of the present invention; Figure 7 This is a flowchart of the source-load bidirectional collaborative control according to an embodiment of the present invention; Figure 8 This is a schematic diagram of the feedforward compensation execution principle according to an embodiment of the present invention. Detailed Implementation

[0024] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0025] See attached document Figure 1The present invention provides a perovskite photovoltaic power supply control system based on an agricultural ecological warehouse, which may include: a photovoltaic array, a converter, an electrical sampling module, an environmental acquisition module, an environmental control controller, an actuator, and a control unit.

[0026] A photovoltaic array is installed on the light-transmitting top or side wall of the agricultural eco-barrel. The photovoltaic array includes at least one perovskite photovoltaic module, the side surface of which faces the interior of the agricultural eco-barrel into contact with the air inside the eco-barrel to form a surface for heat and moisture exchange.

[0027] The power output terminal of the photovoltaic array is electrically connected to the input terminal of the converter, and the output terminal of the converter is connected to the electrical load and / or energy storage device. The electrical load includes at least a ventilator and a humidifying water pump as environmental control loads.

[0028] In one embodiment for ensuring continuous operation of a ventilator and a humidifying pump, the output of the converter is connected to a DC bus, the ventilator and the humidifying pump are powered by the DC bus, and the energy storage device is connected to the DC bus through a bidirectional energy storage converter.

[0029] An electrical sampling module is installed in the output circuit of the photovoltaic array to collect the output voltage and current signals of the photovoltaic array. The control unit calculates the output power of the photovoltaic array based on the output voltage and current signals.

[0030] The electrical sampling module also includes a load-side voltage sampling unit and a load-side current sampling unit located on the converter output side or DC bus. The control unit calculates the load power of the electrical load based on the sampling data output by the load-side voltage sampling unit and the load-side current sampling unit.

[0031] The electrical sampling module also includes a reference photovoltaic module. The reference photovoltaic module and the photovoltaic array are placed in the same or equivalent light and heat / humidity environment and maintained in an open-circuit detection state. The control unit acquires the open-circuit voltage of the reference photovoltaic module and calculates the estimated open-circuit voltage of the photovoltaic array based on a pre-calibrated open-circuit voltage conversion factor between the reference photovoltaic module and the photovoltaic array. .

[0032] The environmental acquisition module includes an irradiance sensor, a first temperature and humidity sensor, and a second temperature and humidity sensor.

[0033] An irradiance sensor is placed at the location of the photovoltaic array or at a location with equivalent light-receiving conditions to the photovoltaic array, and is used to collect the solar irradiance at the location of the photovoltaic array.

[0034] The first temperature and humidity sensor is installed in the vicinity of the inner surface of the perovskite photovoltaic module to collect temperature data in the vicinity of the module. relative humidity of the area adjacent to the component The second temperature and humidity sensor is installed in the crop canopy area within the agricultural ecological warehouse to collect crop canopy temperature data. and relative humidity of crop canopy .

[0035] The control unit adjusts the temperature based on the temperature of the area adjacent to the component. relative humidity of the area adjacent to the component The system predicts the temperature and humidity conditions in the vicinity of the component, determines the upper limit of the allowable rate of change of the hysteresis effect, and calculates the feedforward compensation. The control unit adjusts the temperature based on the crop canopy temperature. and relative humidity of crop canopy Calculate the crop canopy environment deviation index to determine the degree to which the crop canopy environment deviates from the suitable temperature and humidity range.

[0036] The control signal output of the environmental controller is connected to the actuator. The actuator includes a ventilator and a humidifying water pump installed inside the agricultural ecological warehouse.

[0037] The control unit is connected to the electrical sampling module, the environmental acquisition module, and the control terminal of the converter. The control unit establishes a bidirectional data connection with the environmental controller via a communication bus.

[0038] Before outputting the target control command to the actuator, the environmental controller writes the target electromechanical command vector to be executed into the command register, and postpones the output of the target electromechanical command vector to the actuator within a preset command determination time limit. The target electromechanical command vector to be executed includes at least one of the following: the target speed parameter of the fan and the target power parameter, target speed parameter, or target flow rate parameter of the humidifying water pump.

[0039] The control unit reads the target electromechanical instruction vector to be executed from the instruction register through the communication bus. Based on the target electromechanical instruction vector to be executed and the currently collected environmental data, it predicts the temperature and humidity changes in the vicinity of the component caused by the action of the actuator, and determines the execution mode of the target electromechanical instruction vector to be executed based on the prediction results.

[0040] When the predicted temperature and humidity changes in the vicinity of the component are within the preset allowable range, the control unit sends a command execution permission signal to the environmental controller. After receiving the command execution permission signal, the environmental controller drives the corresponding actuator according to the electromechanical command vector of the target to be executed.

[0041] When the predicted rate of change of temperature or relative humidity in the vicinity of the component exceeds the corresponding allowable upper limit, and the crop canopy environment has not yet reached the emergency adjustment conditions, the control unit sends an actuator command rate of change limit vector to the environmental controller. Based on the actuator command rate of change limit vector, the environmental controller converts the target electromechanical command to be executed from a step change command to a gradual change command with a limited rate of change, and drives the actuator according to the gradual change command.

[0042] When the crop canopy environment reaches the preset emergency adjustment conditions, or when the temperature and humidity change rate limit conditions of the adjacent area of ​​the component and the crop canopy environment adjustment conditions cannot be met simultaneously, the control unit sends an emergency execution permission and protection trigger signal to the environmental controller. After receiving the emergency execution permission and protection trigger signal, the environmental controller does not impose change rate limits on the electromechanical command to be executed and drives the actuator to execute the electromechanical command to be executed; at the same time, the control unit controls the converter to enter the fixed voltage protection mode.

[0043] See attached document Figure 2 This invention provides a perovskite photovoltaic power supply regulation method based on agricultural ecological warehouses. The method is executed by a regulation unit, an environmental controller, an electrical sampling module, an environmental acquisition module, and a converter, and includes the following steps.

[0044] S10, the control unit obtains the output voltage and output current data of the photovoltaic array within a control cycle through the electrical sampling module, and calculates the instantaneous output power, instantaneous conductance and incremental conductance of the photovoltaic array based on the output voltage and output current data.

[0045] S20, the control unit obtains the temperature of the area adjacent to the component through the environmental acquisition module. Relative humidity of the area adjacent to the component Crop canopy temperature and relative humidity of crop canopy .

[0046] S30: Before outputting the target control command to the ventilator and humidifier pump, the environmental controller writes the target electromechanical command vector to be executed into the command to be executed register, and postpones the output of the target electromechanical command vector to be executed within the preset command determination time limit.

[0047] S40, the control unit predicts the rate of change based on the average temperature of the area adjacent to the component. The average predicted rate of change of relative humidity in the vicinity of the component Determine the sign of the direction of temperature change, the sign of the direction of humidity change, and the relative proportion of the rate of temperature change.

[0048] S50, when the predicted rate of change in temperature or relative humidity in the vicinity of the component exceeds the corresponding allowable upper limit, the control unit adjusts the control based on the current crop canopy temperature. Current relative humidity of crop canopy In addition, the predicted values ​​of crop canopy temperature and humidity at the end of the prediction time window are used to calculate the crop canopy environment deviation index. .

[0049] S60, when the predicted temperature and humidity changes in the vicinity of the component are within the preset allowable range, or when the actuator command change rate limit vector has taken effect and the recalculated average predicted temperature and humidity change rate is within the preset allowable range, the control unit performs feedforward compensation.

[0050] See attached document Figure 3 In one possible implementation, for step S10, the control unit acquires electrical data within the sampling period and performs state quantity calculations. This process may include the following sub-steps.

[0051] S11, the control unit synchronously samples the output voltage and output current of the photovoltaic array through the electrical sampling module.

[0052] Within a control cycle, the control unit filters the multiple voltage and current sample values ​​obtained, and determines the representative voltage value corresponding to that control cycle based on the filtering results. and current representation value .

[0053] S12, the control unit adjusts according to the voltage representative value. and current representation value Calculate the instantaneous output power, instantaneous conductance, and incremental conductance of the photovoltaic array.

[0054] The instantaneous output power of the photovoltaic array during the kth control cycle Calculate according to the following formula: ; Before calculating the instantaneous conductance, the control unit uses the voltage representative value. Compared with the preset voltage minimum threshold Compare the voltage minimum threshold. It is a voltage value greater than zero.

[0055] when At that time, the control unit calculates the instantaneous conductance according to the following formula. : ; when At that time, the control unit does not perform the above division operation, and will adjust the instantaneous conductance. Write the preset alternative value and set the instantaneous conductance invalid flag.

[0056] The control unit reads the voltage representative value from the previous control cycle from the internal buffer. and current representation value And calculate the voltage change according to the following formula. and change in current : ; ; when Greater than or equal to the preset voltage dead zone threshold At that time, the control unit calculates the incremental conductance according to the following formula. : ; when At that time, the control unit does not perform the division operation on the incremental conductance, and will divide the incremental conductance. Write a preset invalid value and set the incremental conductance invalid flag.

[0057] During the control cycle in which the incremental conductance invalid flag is set, the control unit does not use Conductivity comparison is performed based on the change in current. The relationship between the base reference voltage and the preset current tolerance threshold determines the adjustment direction of the base reference voltage.

[0058] See attached document Figure 4 In one possible implementation, for step S20, the control unit acquires environmental data and performs basic maximum power point tracking. This process may include the following sub-steps.

[0059] S21, the control unit obtains the temperature of the area adjacent to the component through the environmental acquisition module. Relative humidity of the area adjacent to the component Crop canopy temperature and relative humidity of crop canopy .

[0060] S22, the control unit determines whether the agricultural ecological warehouse is in a steady state based on the current effective electromechanical commands of the environmental controller and the changes in environmental parameters.

[0061] Control unit setting instruction observation window And in the command observation window The internal calculation of the currently valid electromechanical command vector is performed separately. The changes in each instruction component.

[0062] When the change in the fan command component is lower than the corresponding fan command stability threshold, and the change in the humidifier pump command component is lower than the corresponding humidifier pump command stability threshold, the control unit determines that the currently valid electromechanical command is within the command observation window. The internal environment remains stable.

[0063] The control unit also calculates the measured rate of temperature change in the vicinity of the component based on continuously collected environmental parameters. Measured rate of change of relative humidity in the vicinity of the component .

[0064] When the following conditions are met simultaneously, and each condition is maintained continuously for a period of time until the environment remains stable. At that time, the control unit determined that the agricultural ecological warehouse was in a steady state: First, the current effective electromechanical command vector Each instruction component in the instruction set satisfies the corresponding instruction stability condition. Second, the absolute value of the measured rate of temperature change in the region adjacent to the component. Not greater than the stable threshold of temperature change rate in the vicinity of the component; Third, the absolute value of the measured rate of change of relative humidity in the vicinity of the component. Not greater than the stable threshold of relative humidity change rate in the vicinity of the component; When the agricultural ecological warehouse has not yet met the steady-state determination conditions, the control unit does not update the base reference voltage according to step S23, and maintains the previous effective base reference voltage; when a sudden change is detected in the electromechanical command to be executed, the control unit proceeds to step S30 to predict the temperature and humidity changes caused by the electromechanical command to be executed.

[0065] S23, when the agricultural ecological warehouse is in a steady state and the converter is not in a fixed voltage protection mode, the control unit calculates the instantaneous conductance based on step S10. Incremental conductance Voltage change and change in current The incremental conductance method is used to update the base reference voltage. .

[0066] When the incremental conductance invalid flag is set, or Less than the voltage dead zone threshold At that time, the control unit adjusts according to the change in current. Perform the following judgment: when Not greater than the preset current tolerance threshold At that time, the control unit maintains the base reference voltage. constant; when At that time, the control unit will adjust the base reference voltage. Increase ; when At that time, the control unit will adjust the base reference voltage. Decrease ; When instantaneous conductivity and incremental conductance All are effective, and Greater than or equal to the voltage dead zone threshold At that time, the control unit calculates the incremental conductance judgment deviation according to the following formula. : .

[0067] when Not greater than the preset conductivity tolerance threshold At this time, the control unit determines that the current operating point is within the preset tolerance range of the maximum power point and maintains the base reference voltage. constant.

[0068] when When this occurs, it indicates that the output power corresponding to the current operating point increases with the increase of the output voltage, and the control unit will adjust the base reference voltage. Increase .

[0069] when When this occurs, it indicates that the output power at the current operating point decreases as the output voltage increases, and the control unit adjusts the base reference voltage. Decrease .

[0070] The control unit updates the base reference voltage according to the following relationship: ; in, The value is 0 or ; This is the base reference voltage limiting function. The upper limit of the base reference voltage is lower than the estimated open-circuit voltage of the photovoltaic array. The lower limit of the base reference voltage is higher than the preset short-circuit risk voltage.

[0071] When the feedforward compensation is initiated in the subsequent step S60, the step S23 generated It is used as a base reference voltage in the calculation of the final reference voltage, rather than directly replacing the final reference voltage after superimposing the feedforward compensation voltage.

[0072] See attached document Figure 5In one possible implementation, for step S30, the control unit acquires electromechanical action parameters and performs feedforward prediction calculations. This process may include the following sub-steps.

[0073] S31, the control unit reads the target electromechanical instruction vector to be executed from the instruction register to be executed written by the environmental controller through the communication bus.

[0074] The control unit records the current valid electromechanical command vector actually output by the environmental controller before the command change as follows: And calculate the change in command corresponding to each actuator according to the following formula: ; Where m represents the m-th instruction component in the target electromechanical instruction vector to be executed; This represents the target instruction value for the m-th actuator; This indicates the current valid instruction value of the executing mechanism before the instruction was changed.

[0075] The control unit will set the absolute value of each command change. With the corresponding instruction mutation threshold Compare them. When any instruction component satisfies... When the control unit determines that the target electromechanical instruction to be executed has changed abruptly relative to the currently valid electromechanical instruction, it executes step S32.

[0076] When none of the instruction components in the target electromechanical instruction vector exceed their corresponding instruction mutation threshold, and no other protection triggering conditions are detected, the control unit sends an instruction execution permission signal to the environmental controller. Upon receiving the instruction execution permission signal, the environmental controller drives the actuator according to the target electromechanical instruction vector.

[0077] When a sudden change occurs in the target electromechanical command to be executed, the control unit completes the calculations of steps S32 to S50 within the command determination time limit, and returns the command execution permission signal, the actuator command change rate limit vector, or the emergency execution permission and protection trigger signal to the environmental controller.

[0078] S32, when the target electromechanical command to be executed undergoes a sudden change, the control unit adopts a discrete state-space model to predict the impact of the target electromechanical command to be executed on the temperature and relative humidity of the area adjacent to the component.

[0079] The control unit records the temperature of the component's vicinity before the instruction change, which was in a steady-state phase, as... The relative humidity of the region adjacent to the component in steady state before the instruction mutation is denoted as . And construct the temperature and humidity deviation state vector of the component's vicinity. : ; in, and These are the temperature and relative humidity of the component's vicinity, collected when the prediction begins.

[0080] The control unit records the current valid electromechanical command vector before the instruction mutation as: And according to the target electromechanical command vector to be executed Constructing the predictive electromechanical instruction sequence within the prediction time window .

[0081] When predicting target instructions without rate of change limits, the corresponding predictive electromechanical instructions for each prediction step are: ; The control unit calculates the command deviation vector corresponding to each prediction step according to the following formula: ; The control unit adjusts the temperature based on the temperature of the area adjacent to the current component. relative humidity of the area adjacent to the component Given the temperature and humidity range, the corresponding state transition matrix A and actuator input matrix B are read from the pre-stored parameter table.

[0082] Among them, the state transition matrix A is used to characterize the change of temperature and humidity deviation state in the vicinity of the component over time when there are no new command changes; the actuator input matrix B is used to characterize the impact of command changes of the ventilator and humidification pump on the temperature and relative humidity in the vicinity of the component.

[0083] The control unit performs multi-step state recursion prediction according to the following formula: ; in: ; ; n is the number of prediction steps; To predict the sampling period; Prediction Time Window ; The control unit denotes the state vector obtained in the nth prediction step as: Temperature in the vicinity of the component at the end of the prediction time window. relative humidity of the area adjacent to the component Calculate according to the following formulas respectively: ; ; in, and They are respectively The first and second components.

[0084] The control unit calculates the average predicted rate of change of temperature in the vicinity of the component based on the difference between the predicted value at the end of the prediction time window and the measured value at the beginning of the prediction. The average predicted rate of change of relative humidity in the vicinity of the component : ; ; The state transition matrix A and the actuator input matrix B are identified in advance through the actuator step response test.

[0085] S33, the control unit outputs the temperature and humidity prediction results of the area near the component, and re-executes the state prediction after the change rate of the actuator command is limited.

[0086] When step S50 generates the actuator command change rate limit vector, the control unit generates a limit electromechanical command sequence within the prediction time window based on the actuator command change rate limit vector. .

[0087] The control unit uses a limiting electromechanical command sequence. Replacement step S32 Recalculate the command deviation sequence, predict temperature and humidity conditions, and the average predicted rate of change of temperature in the component's vicinity. and the average predicted rate of change of relative humidity in the vicinity of the component .

[0088] Recalculated and It is used to determine whether the temperature and humidity changes after the command change rate limit have entered the corresponding allowable range, and serves as the input for calculating the feedforward compensation voltage in step S60.

[0089] See attached document Figure 6 In one possible implementation, for step S40, the control unit extracts boundary extrema through a specific network model and performs a comparison determination. This process may include the following sub-steps.

[0090] S41, the control unit calculates the average predicted rate of change of temperature in the vicinity of the component based on the component's adjacent area temperature predicted in step S30. The average predicted rate of change of relative humidity in the vicinity of the component Determine the direction of temperature change, the direction of humidity change, and the relative proportion of the rate of temperature change.

[0091] The control units respectively adopted the normalized scale of temperature change rate. Normalized scale of humidity change rate ,right and The absolute value is dimensionless to obtain the normalized rate of change of temperature. and normalized rate of change of humidity : ; ; in, and All are preset parameters that are greater than zero, and are determined according to the calibration range of temperature change rate and relative humidity change rate, respectively.

[0092] when Greater than or equal to the preset ratio calculation lower limit At that time, the control unit calculates the relative proportion ρ of the temperature change rate according to the following formula: ; when Less than the lower limit of the ratio calculation At that time, the control unit sets ρ to the preset intermediate value of 0.5.

[0093] The control units are each set with a temperature direction determination threshold. Humidity direction determination threshold And determine the sign of the direction of temperature change according to the following rules. Symbol for the direction of humidity change : when hour, ; when hour, 0; when hour, ; when hour, ; when hour, ; when hour, ; Before inputting the direction sign into the radial basis function neural network, the control unit follows the formula below. and Map to the interval [0, 1]: ; ; The control unit adjusts the temperature based on the temperature of the area adjacent to the current component. Relative humidity of the area adjacent to the current component Normalized temperature directional value Normalized humidity directional value And the relative proportion of temperature change rate ρ, to construct the original input feature vector. : ; The control unit uses the same max-min normalization parameters as the model training phase to process the original input feature vector. Normalization is performed. For the q-th input feature, its normalized value is calculated according to the following formula: ; in, and Let X and q be the lower and upper bounds of normalization used for the q-th input feature during model training, respectively. The five-dimensional input feature vector obtained after normalization is denoted as X.

[0094] S42, the control unit inputs the normalized input feature vector X into the pre-trained hysteresis effect environmental change rate tolerance upper limit determination model, and obtains the temperature change rate tolerance upper limit prediction value and humidity change rate tolerance upper limit prediction value through model forward calculation.

[0095] The model for determining the allowable upper limit of the rate of change of the hysteresis effect uses a radial basis function neural network. The radial basis function neural network consists of an input layer, a hidden layer, and an output layer.

[0096] The hidden layer consists of L radial basis function nodes, each using a Gaussian radial basis function. The output of the j-th radial basis function node... Calculate according to the following formula: ; in, Let j be the center vector of the j-th radial basis function node. Let be the width of the basis functions for the j-th radial basis function node. Represents the input feature vector X and the center vector The Euclidean distance between them.

[0097] The output layer consists of two output nodes. The i-th original output value of the model is calculated according to the following formula: ; in, Let be the connection weight between the j-th radial basis function node and the i-th output node; when i=1, Predicted upper limit of allowable temperature change rate When i=2, Predicted upper limit of humidity change rate .

[0098] Both the training labels and the model outputs use non-negative values. The control unit applies a non-negative limit to the raw model output to avoid negative upper limits for the rate of change due to model fitting errors.

[0099] S43, before deploying the model for determining the upper limit of the allowable rate of change of the hysteresis effect to the control unit, training samples are obtained through calibration experiments of the upper limit of the allowable rate of change of temperature and humidity, and the radial basis function neural network is trained offline.

[0100] The calibration test was conducted in an environmental test chamber capable of independently adjusting temperature and relative humidity. During the test, the perovskite photovoltaic module to be calibrated was set under preset irradiation conditions, and before each temperature and humidity change test, the temperature, relative humidity, and output status of the module's vicinity were brought to preset stable conditions.

[0101] For each group of components, the temperature in the vicinity of the component, the relative humidity in the vicinity of the component, the direction of temperature change, and the direction of humidity change are set according to the preset relative proportion of temperature change rate ρ, and the overall amplitude of temperature and humidity change rate is increased step by step.

[0102] The duration of temperature and humidity changes at each level is the same as the prediction time window τ used in step S32. This ensures that the upper limit of the allowable rate of change obtained from the calibration test corresponds to the prediction time window used in actual control.

[0103] After each temperature and humidity change, the environmental conditions are restored to the preset baseline state, and after a preset recovery time, the stable photoelectric conversion efficiency of the perovskite photovoltaic module is measured again.

[0104] The stable photoelectric conversion efficiency before the application of temperature and humidity changes is used as the baseline efficiency. When the percentage decrease in the restored stable photoelectric conversion efficiency relative to the baseline efficiency reaches or exceeds the preset performance degradation percentage, this level of temperature and humidity change condition is defined as the performance degradation level. The absolute values ​​of the temperature change rate and humidity change rate corresponding to the next higher safety test level adjacent to this performance degradation level are used as the allowable upper limit labels for the temperature change rate and humidity change rate under this set of input conditions, respectively.

[0105] The number of hidden layer nodes L is determined based on the distribution of training samples and validation error. (Center vector) The basis function width is determined based on the cluster centers obtained from clustering the training samples. Determined based on the distance between the corresponding center vector and its adjacent center vectors; in the center vector and basis function width Once determined, the connection weights are calculated using the orthogonal least squares method. .

[0106] S44, the control unit compares the average predicted change rate of temperature in the vicinity of the component and the average predicted change rate of relative humidity in the vicinity of the component obtained in step S30 with the actual control allowable upper limit determined in step S43.

[0107] Control unit calculation and The absolute value of the result is determined, and the following judgment is performed: when and When the control unit determines that the predicted temperature and humidity changes in the vicinity of the component are within the preset allowable range, step S60 is executed.

[0108] when or When the control unit determines that the predicted rate of temperature change or relative humidity change in the vicinity of the component exceeds the corresponding allowable upper limit, step S50 is executed.

[0109] See attached document Figure 7 Regarding step S50, after predicting the extreme value of environmental abrupt change, the control unit performs bidirectional coordinated control of the source-side photovoltaic modules and the load-side environmental control equipment based on the physiological state of the crop. This process specifically includes the following sub-steps.

[0110] S51, the control unit adjusts according to the current crop canopy temperature. and the current relative humidity of the crop canopy The current crop canopy environment deviation index is calculated, and the crop canopy temperature and humidity status is predicted after the execution of the target electromechanical command.

[0111] The control unit records the crop canopy temperature in a steady-state phase before the command change as: The relative humidity of the crop canopy in a steady state before the instruction change is recorded as... And construct the crop canopy temperature and humidity deviation state vector. : ; in, and These are the crop canopy temperature and crop canopy relative humidity collected during the current control cycle.

[0112] The control unit pre-stores the state transition matrix corresponding to the crop canopy region. and actuator input matrix And using the same prediction sampling period as in step S32. The prediction steps n and prediction time window τ are used to perform multi-step recursive prediction of crop canopy temperature and humidity status: ; in: ; ; ; ; Crop canopy temperature at the end of the forecast time window and relative humidity of crop canopy Calculate according to the following formulas respectively: ; ; in, and These are the first and second components of the crop canopy temperature and humidity deviation state vector for the nth prediction step, respectively.

[0113] State transition matrix and actuator input matrix Preliminary identification is achieved through step response tests of the actuator.

[0114] The control unit also pre-stores the appropriate canopy temperature for the target crop at the current phenological stage. Suitable relative humidity of the canopy Temperature normalization scale and relative humidity normalization scale . and All parameters are greater than zero.

[0115] The control unit calculates the current normalized temperature deviation according to the following formula. and current normalized humidity deviation : ; ; Current crop canopy environment deviation index Calculate according to the following formula: ; in, As a weight for temperature deviation, The relative humidity deviation is the weighting factor. , ,and .

[0116] The control units use the same normalization scale and calculate the predicted normalized temperature deviation according to the following formula. and predicted normalized humidity bias : ; ; Predicting crop canopy environment deviation index Calculate according to the following formula: ; The control unit determines the larger of the current crop canopy environment deviation index and the predicted crop canopy environment deviation index as the crop canopy environment deviation index for this control period. : ; Temperature deviation weight relative humidity deviation weight Suitable canopy temperature Suitable relative humidity of the canopy Temperature normalization scale and relative humidity normalization scale The parameters can be read from a pre-stored crop parameter table based on the target crop type and phenological stage, or determined through cultivation calibration experiments.

[0117] The control unit presets a protection exit threshold. and emergency protection trigger threshold ,in: ; Protection exit threshold Used to determine whether exiting the fixed voltage protection mode is permitted. and A mode switching hysteresis interval is formed between them.

[0118] S52, when step S40 determines that the average predicted change rate of temperature or the average predicted change rate of relative humidity in the vicinity of the component exceeds the corresponding allowable upper limit, the crop canopy environment deviation index... Less than the emergency protection trigger threshold Furthermore, when the converter is not currently in fixed voltage protection mode, the control unit determines the actuator command change rate limit vector.

[0119] The actuator command change rate constraint vector includes the allowable change rate of the ventilator command and the allowable change rate of the humidifier pump command. Based on the candidate actuator command change rates, the control unit generates a candidate gradual command sequence corresponding to the prediction time window τ. .

[0120] For the m-th actuator, candidate gradient instructions are generated according to the following formula: ; in, ; The target instruction value for the m-th actuator; Let m be the allowable rate of change for candidate instructions of the m-th actuator; Used to limit the amount of instruction change within a single prediction step. to between.

[0121] The control unit will select candidate gradient command sequences Input the predicted temperature and humidity status of the component's neighborhood in step S32 and the predicted temperature and humidity status of the crop canopy in step S51, respectively, to obtain the average predicted change rate of temperature in the neighborhood of the candidate component. The predicted average rate of change of relative humidity in the vicinity of the candidate component and the candidate crop canopy environment deviation index .

[0122] The control unit constructs an optimization problem constrained by the rate of change of actuator commands. The optimization problem aims to minimize the weighted deviation between the candidate actuator commands and the target electromechanical commands to be executed at the end of the prediction time window. The objective function can be expressed as: ; The optimization problem constrained by the rate of change of the actuator command includes at least the following constraints: (1) ; (2) ; (3) ; The control unit solves the constrained optimization problem, satisfying all constraints and making the objective function... The vector with the smallest instruction rate of change is determined as the instruction rate of change limit vector of the actuator.

[0123] The control unit sends the actuator command change rate limit vector to the environmental controller via the communication bus. Based on the actuator command change rate limit vector, the environmental controller converts the target electromechanical command to be executed into a gradual command with a limited change rate, and drives the ventilator and humidification pump according to the gradual command.

[0124] Continuing to reduce the rate of change of actuator commands will lead to Greater than or equal to If the constraint optimization problem has no feasible solution, the control unit stops restricting the electromechanical instructions to be executed, sends an emergency execution permission and protection trigger signal to the environmental controller, and controls the converter to enter the fixed voltage protection mode.

[0125] S53, when the crop canopy environment deviates from the index Greater than or equal to the emergency protection trigger threshold At this time, the control unit allows the environmental controller to prioritize the execution of the target electromechanical commands to be executed and controls the converter to enter the fixed voltage protection mode.

[0126] After receiving the emergency execution permission and protection trigger signal, the environmental controller does not impose a rate of change limit on the electromechanical instructions to be executed, and drives the ventilator and humidifier pump according to the electromechanical instructions to be executed.

[0127] When entering the fixed voltage protection mode, the control unit stops the base maximum power point tracking and smoothly switches the reference voltage on the photovoltaic array side from the current base reference voltage to the photovoltaic array side protection reference voltage. .

[0128] The open-circuit voltage is estimated using the following formula. Sure: ; in, To preset the protection voltage proportional coefficient, .

[0129] First, crop canopy environment deviation index Less than or equal to the protection exit threshold ; When all of the above protection exit conditions are met, the control unit controls the converter to exit the fixed voltage protection mode.

[0130] In fixed voltage protection mode, when the output power of the photovoltaic array Less than the power required by the ventilator and humidifier pump At that time, the control unit determines the power gap according to the following formula. : ; The control unit adjusts according to the power gap. The allowable discharge power of the energy storage device and the allowable output power of the bidirectional energy storage converter are used to determine the energy storage output power command and control the energy storage device to output power to the DC bus through the bidirectional energy storage converter.

[0131] See attached document Figure 8 In step S60, the control unit introduces a feedforward mechanism based on conventional closed-loop control, and outputs the final pulse width modulation duty cycle command to drive the converter. This process specifically includes the following sub-steps.

[0132] S61, the control unit predicts the rate of change based on the average temperature of the area adjacent to the component. The predicted average change rate of relative humidity in the vicinity of the component and open-circuit voltage temperature correction Calculate the target hysteresis compensation voltage .

[0133] Target hysteresis compensation voltage Calculate according to the following formula: ; In the formula, This is the temperature compensation weighting coefficient. This is the humidity compensation weighting coefficient.

[0134] Temperature compensation weighting coefficient Humidity compensation weighting coefficient The isolation was determined in advance through temperature step isolation tests and humidity step isolation tests on the same batch of perovskite photovoltaic modules.

[0135] The control unit uses the difference between the actual maximum power point voltage and the baseline reference voltage without feedforward compensation as the target feedforward compensation voltage sample, and then uses each target feedforward compensation voltage sample and its corresponding... , and The least squares fitting method is used to determine and .

[0136] Open circuit voltage temperature correction This is used to correct for the estimated open-circuit voltage increment caused by temperature changes in the vicinity of the module within the prediction time window. The control unit pre-stores the open-circuit voltage-temperature correction relationship of the photovoltaic array. .

[0137] Open-circuit voltage-temperature correction relationship Pre-calibration was achieved through temperature characteristic tests of the same batch of perovskite photovoltaic modules.

[0138] The control unit adjusts the temperature based on the temperature of the area adjacent to the current component. Temperature in the region adjacent to the prediction component at the end of the prediction time window Calculate the open-circuit voltage temperature correction using the following formula. : ; S62, the control unit converts the target hysteresis compensation voltage into the actual applied hysteresis compensation voltage, and uses the actual applied hysteresis compensation voltage as an additional bias to the base reference voltage.

[0139] During the feedforward compensation phase, the control unit will use the target hysteresis compensation voltage calculated in step S61. This serves as the target value for the hysteresis compensation voltage during the current control cycle. The hysteresis compensation voltage is used as an additional bias and is not written into the base reference voltage. The historical cumulative value.

[0140] The control unit adds the base reference voltage and the hysteresis compensation voltage to obtain the unlimited reference voltage. : ; The control unit then limits the unlimited reference voltage according to the following formula to obtain the target reference voltage. : ; in, This means restricting x to to between; This is the minimum allowable reference voltage on the photovoltaic array side; This is the maximum permissible reference voltage for the current control cycle.

[0141] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for regulating perovskite photovoltaic power supply based on agricultural ecological warehouses, characterized in that, Includes the following steps: To acquire environmental parameters and crop growth status data within the agricultural ecological warehouse; Obtain real-time power generation and operation data of perovskite photovoltaic modules; Based on the environmental parameters and the crop growth status data, calculate the real-time environmental control energy consumption requirements of the agricultural ecological warehouse; Based on the real-time power generation operation data and the real-time environmental regulation energy consumption demand, a power supply regulation strategy is generated. According to the power supply regulation strategy, the output power distribution of the perovskite photovoltaic module is controlled, and the operating status of the environmental regulation equipment in the agricultural ecological warehouse is adjusted.

2. The method for regulating perovskite photovoltaic power supply based on agricultural ecological warehouses according to claim 1, characterized in that, The acquisition of environmental parameters and crop growth status data within the agricultural ecological warehouse includes: The real-time light intensity, real-time temperature, real-time humidity, and real-time carbon dioxide concentration within the agricultural ecological warehouse are collected as environmental parameters. The acquisition of real-time power generation operation data of perovskite photovoltaic modules includes: The output voltage, output current, and surface operating temperature of the perovskite photovoltaic module are collected as the real-time power generation operation data.

3. The method for regulating perovskite photovoltaic power supply based on agricultural ecological warehouses according to claim 1, characterized in that, The step of calculating the real-time environmental control energy consumption requirement of the agricultural ecological warehouse based on the environmental parameters and the crop growth status data includes: Based on the crop growth status data, determine the target light intensity and target temperature required for the current growth cycle; Calculate the differences between the real-time light intensity and the real-time temperature in the environmental parameters and the target light intensity and the target temperature, respectively; The difference is input into a preset energy consumption prediction model to calculate the electrical load required to adjust the agricultural ecological warehouse to the target light intensity and the target temperature, which is used as the energy consumption requirement for real-time environmental regulation.

4. The method for regulating perovskite photovoltaic power supply based on agricultural ecological warehouses according to claim 1, characterized in that, The generation of a power supply control strategy based on the real-time power generation operation data and the real-time environmental regulation energy consumption demand includes: Calculate the real-time power generation corresponding to the real-time power generation operation data; When the real-time power generation is less than the real-time environmental control energy consumption requirement, the power supply control strategy is determined to be a shortfall power supply control strategy. The power supply deficit control strategy includes: generating a discharge command to call up the energy storage battery, and generating a load shedding command to reduce the operating power of non-core loads in the environmental control equipment.

5. The method for regulating perovskite photovoltaic power supply based on agricultural ecological warehouses according to claim 4, characterized in that, The control of the output power distribution of the perovskite photovoltaic module includes: When implementing the power shortage control strategy, the output power of the perovskite photovoltaic module is transmitted to the environmental control equipment through the DC bus. According to the discharge command, the bidirectional DC / DC converter is controlled to operate in discharge mode, so that the energy storage battery outputs electrical energy to the DC bus to compensate for the difference between the real-time power generation and the real-time environmental regulation energy consumption demand.

6. The method for regulating perovskite photovoltaic power supply based on agricultural ecological warehouses according to claim 1, characterized in that, The generation of a power supply control strategy based on the real-time power generation operation data and the real-time environmental regulation energy consumption demand includes: When the real-time power generation corresponding to the real-time power generation operation data is greater than the real-time environmental regulation energy consumption demand, the power supply regulation strategy is determined as a surplus power supply regulation strategy. The surplus power supply regulation strategy includes generating charging instructions for charging the energy storage battery.

7. The method for regulating perovskite photovoltaic power supply based on agricultural ecological warehouses according to claim 6, characterized in that, The step of controlling the output power distribution of the perovskite photovoltaic module according to the power supply regulation strategy includes: Obtain the real-time state of charge value of the energy storage battery; When the real-time state of charge value is greater than the preset charge threshold, the perovskite photovoltaic module is controlled to leave the maximum power point tracking mode and the output voltage of the perovskite photovoltaic module is limited to reduce the real-time power generation.

8. The method for regulating perovskite photovoltaic power supply based on agricultural ecological warehouses according to claim 2, characterized in that, The step of generating a power supply control strategy based on the real-time power generation operation data and the real-time environmental regulation energy consumption demand further includes: When the surface operating temperature is greater than the preset safe temperature threshold, the power supply control strategy is determined to be a thermal protection control strategy. The thermal protection control strategy includes: reducing the operating voltage of the perovskite photovoltaic module to reduce the heat generated by photoelectric conversion, and generating a control signal for activating the top cooling device in the environmental control equipment.

9. The method for regulating perovskite photovoltaic power supply based on agricultural ecological warehouses according to claim 8, characterized in that, Adjusting the operating status of the environmental control equipment within the agricultural ecological warehouse includes: The top cooling device in the environmental control equipment includes a water-cooled spray solenoid valve installed on the light-transmitting top of the agricultural ecological warehouse. Upon receiving the control signal, the water-cooled spray solenoid valve is opened to spray and cool the surface of the perovskite photovoltaic module until the surface operating temperature drops below the safe temperature threshold.

10. A perovskite photovoltaic power supply regulation system based on an agricultural ecological warehouse, used to implement the perovskite photovoltaic power supply regulation method based on an agricultural ecological warehouse as described in any one of claims 1 to 9, characterized in that, The system includes: The data acquisition module is used to acquire environmental parameters and crop growth status data within the agricultural ecological warehouse, as well as real-time power generation operation data of the perovskite photovoltaic modules. The energy consumption calculation module is used to calculate the real-time environmental control energy consumption requirements of the agricultural ecological warehouse based on the environmental parameters and the crop growth status data. The strategy generation module is used to generate power supply control strategies based on the real-time power generation operation data and the real-time environmental regulation energy consumption requirements. The collaborative control module is used to control the output power distribution of the perovskite photovoltaic module according to the power supply regulation strategy, and to adjust the operating status of the environmental control equipment in the agricultural ecological warehouse.

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