A method and system for controlling the growth of green plants using LED plant growth lamps

Abstract

The application relates to the technical field of green plant growth control, in particular to a method and system for controlling green plant growth by using an LED plant growth lamp, the method comprising the following steps: acquiring first data; monitoring the light intensity and photosynthetic photon flux density in a first period, calculating the first period average photosynthetic photon flux density and the first period light duration, recording the initial electric quantity and the control starting moment; constructing a first optimization objective function and optimization constraint conditions; calculating the optimal LED plant growth lamp power by using a particle swarm optimization algorithm; and setting the LED plant growth lamp power as the optimal LED plant growth lamp power from the control starting moment until the first period ends. The application optimizes the control of the LED plant growth lamp power, so that the load rate of the energy storage battery reaches a better level under the premise of ensuring that the green plants obtain suitable photosynthetic photon accumulation, and the service life of the energy storage battery is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of green plant growth control, and particularly relates to a method and system for controlling green plant growth by using an LED plant growth lamp. BACKGROUND

[0002] LED plant growth lamps are widely used in the planting and cultivation of green plants. During the day, green plants perform photosynthesis by receiving natural light. At night, the green plants are provided with light by LED plant growth lamps, so as to promote the growth of the green plants. The amount of light received by the green plants in a time period can be measured by the amount of photosynthetic photon flux density. In the prior art, the amount of photosynthetic photon flux density in a day can also be described by the daily total light integral. However, if the time period for statistics deviates slightly from a day, the daily total light integral cannot accurately express the amount of photosynthetic photon flux density. Therefore, it is more appropriate to directly use the amount of photosynthetic photon flux density for measurement. For different green plants, the appropriate amount of photosynthetic photon flux density is often different. The LED plant growth lamp controls the growth of the green plants by controlling the amount of photosynthetic photon flux density received by the green plants at night. The greater the power of the LED plant growth lamp, the more the amount of photosynthetic photon flux density provided to the green plants at night, and vice versa.

[0003] With the development of new energy technology, a new type of LED plant growth lamp will be applied more and more. The new type of LED plant growth lamp is composed of a photovoltaic panel, an energy storage battery and a power-adjustable LED plant growth lamp. During the day, when the intensity of natural light exceeds a threshold value, the photovoltaic panel converts solar energy into electrical energy by receiving natural light and stores the electrical energy in the energy storage battery. At night, the energy storage battery discharges to the LED plant growth lamp, which illuminates the plants to receive light at night, thereby controlling the growth of the green plants. However, since the green plants receive different amounts of natural light during the day, the photovoltaic panel absorbs different amounts of solar energy. Therefore, in order to make the green plants receive the amount of photosynthetic photon flux density within a pre-set range in the entire time period, the power of the LED plant growth lamp is different, and thus the load rate of the energy storage battery is different. However, for the energy storage battery, there is an optimal load rate. The greater the deviation between the actual load rate and the optimal load rate, the shorter the service life of the energy storage battery. The prior art has not yet studied the power of the LED plant growth lamp and the load rate of the energy storage battery together, resulting in the mismatch between the two.

[0004] Therefore, it is necessary to control the power of the LED plant growth lamp to ensure that the green plants receive the appropriate amount of photosynthetic photon flux density, so as to make the load rate of the energy storage battery reach a better level and thus improve the service life of the energy storage battery. SUMMARY

[0005] (1) Technical problem to be solved

[0006] The present application aims to provide a method and system for controlling the growth of green plants by using LED plant growth lamps, so as to achieve a better load rate of the energy storage battery by controlling the power of the LED plant growth lamp, and thus improve the service life of the energy storage battery.

[0007] (2) Technical solutions

[0008] To achieve the above-mentioned purpose, the present application provides a method for controlling the growth of green plants by using LED plant growth lamps, which comprises the following steps:

[0009] S1, obtaining first data; the first data includes a first period, a second period, a second period predicted average light intensity, a second period predicted average photosynthetic photon flux density, a second period predicted light duration, a photovoltaic panel photoelectric conversion efficiency, and a photovoltaic panel area.

[0010] S2, monitoring the light intensity and the photosynthetic photon flux density in the first period, and when the light intensity in the first period first decreases to a first threshold value set in advance, calculating the first period average photosynthetic photon flux density and the first period light duration after a first sampling and holding time set in advance, recording the power of the energy storage battery as an initial power, and recording the current time as a control starting time; the light intensity is continuously less than the first threshold value within the first sampling and holding time.

[0011] S3, constructing a first optimization objective function and optimization constraints according to the first period average photosynthetic photon flux density, the first period light duration, the initial power, and the first data; the optimization variable of the first optimization objective function is the power of the LED plant growth lamp; the optimal LED plant growth lamp power is calculated by using a particle swarm optimization algorithm with the minimum value of the first optimization objective function as the target.

[0012] S4, starting the LED plant growth lamp from the control starting time, setting the power of the LED plant growth lamp as the optimal LED plant growth lamp power, and closing the LED plant growth lamp until the first period ends.

[0013] Further, the method for obtaining the first data comprises:

[0014] obtaining the first period, the second period, the second period predicted average light intensity, the second period predicted average photosynthetic photon flux density, the second period predicted light duration, the photovoltaic panel photoelectric conversion efficiency, and the photovoltaic panel area.

[0015] The first period is a period in which the current LED plant growth lamp control is located; the second period is a period in which the next LED plant growth lamp control is expected to be located; in the first period, the light intensity is first increased to a first threshold value, and the time after a second sampling holding time set in advance is delayed is the starting point of the first period, and the starting point of the first period plus 86400 seconds is the end point of the first period; the light intensity is continuously greater than the first threshold value within the second sampling holding time; the end point of the first period is the starting point of the second period; and the starting point of the second period plus 86400 seconds is the end point of the second period.

[0016] Further, the method for monitoring the light intensity and the photosynthetic photon flux density in the first period, when the light intensity in the first period is first decreased to a first threshold value set in advance, and after a first sampling holding time set in advance is delayed, the first period average photosynthetic photon flux density and the first period light duration are calculated, the power of the energy storage battery is recorded, which is recorded as an initial power, and the current time is recorded, which is recorded as a control starting time, comprises:

[0017] The light intensity in the first period is monitored by using a light intensity monitoring instrument, and the photosynthetic photon flux density in the first period is monitored by using a photosynthetic photon flux density monitoring instrument; when the light intensity in the first period is first decreased to a first threshold value set in advance, and after a first sampling holding time set in advance is delayed, the first period average photosynthetic photon flux density and the first period light duration are calculated, the power of the energy storage battery is recorded, which is recorded as an initial power, and the current time is recorded, which is recorded as a control starting time.

[0018] The first period average photosynthetic photon flux density represents an average value of the photosynthetic photon flux density during the period from the starting point of the first period to the control starting time; and the first period light duration represents a time length from the starting point of the first period to the control starting time.

[0019] Further, the method for constructing a first optimization objective function and an optimization constraint condition according to the first period average photosynthetic photon flux density, the first period light duration, the initial power and the first data comprises:

[0020] The first optimization objective function is constructed, and the first optimization objective function is represented as:

[0021] ;

[0022] wherein, represents the first optimization objective function; represents an optimal load rate of the energy storage battery obtained in advance; represents an LED plant growth lamp power, in kilowatts; represents a rated output power of the energy storage battery obtained in advance, in kilowatts; The number of LED plant growth lamps is represented.

[0023] According to the pre-obtained photosynthetic photon flux density samples generated by the LED plant growth lamp under different powers, a first conversion function is fitted ; the independent variable of the first conversion function is the power of the LED plant growth lamp, and the dependent variable of the first conversion function is the photosynthetic photon flux density of the LED plant growth lamp, in units of micromoles per square meter per second.

[0024] An optimization constraint condition is constructed, which includes a first constraint condition, a second constraint condition, a third constraint condition, a fourth constraint condition, and a fifth constraint condition.

[0025] The first constraint condition is:

[0026] ;

[0027] wherein, is a pre-obtained upper limit of the power of the LED plant growth lamp, in units of kilowatts, representing the maximum input power allowed by the LED plant growth lamp.

[0028] The second constraint condition is:

[0029] ;

[0030] wherein, represents a lower limit of the photosynthetic photon accumulation, in units of moles per square meter; represents an upper limit of the photosynthetic photon accumulation, in units of moles per square meter; represents the length of time of the first period calculated, in units of seconds; represents the first period of light duration, in units of seconds; represents the first period average photosynthetic photon flux density, in units of micromoles per square meter per second; the lower limit of the photosynthetic photon accumulation and the upper limit of the photosynthetic photon accumulation are obtained by pre-setting.

[0031] The third constraint condition is:

[0032] ;

[0033] wherein, represents the initial electric quantity, in units of kilowatt-hours.

[0034] The fourth constraint condition is:

[0035] ;

[0036] wherein, represents the maximum load rate of the energy storage battery obtained in advance.

[0037] calculating the second-period predicted minimum power of the LED plant growth lamp , the second-period predicted photovoltaic power generation .

[0038] The fifth constraint condition is:

[0039] ;

[0040] wherein, represents and the minimum value; represents the second-period predicted illumination duration, in seconds; represents the pre-obtained energy storage battery capacity, in kilowatt-hours.

[0041] Further, the method for calculating the second-period predicted minimum power of the LED plant growth lamp , the second-period predicted photovoltaic power generation comprises:

[0042] calculating the second-period predicted minimum power of the LED plant growth lamp, wherein the calculation formula of the second-period predicted minimum power of the LED plant growth lamp is:

[0043] ;

[0044] wherein, represents the inverse function of the first conversion function; represents the second-period predicted minimum photosynthetic photon flux density of the LED plant growth lamp, in micromoles per square meter per second; the unit of is kilowatt; the calculation formula of is:

[0045] ;

[0046] wherein, represents the second-period predicted average photosynthetic photon flux density.

[0047] calculating the second-period predicted photovoltaic power generation, wherein the calculation formula of the second-period predicted photovoltaic power generation is:

[0048] ;

[0049] wherein, represents the second-period predicted average illumination intensity, in watts per square meter; represents the area of the photovoltaic panel, in square meters; represents the photoelectric conversion efficiency of the photovoltaic panel; the unit of is kilowatt-hours.

[0050] Based on the same inventive concept, in another aspect, the present application also provides a system for controlling the growth of green plants by using LED plant growth lamps, the system comprising:

[0051] a first data acquisition module for acquiring first data; the first data comprising a first period, a second period, a second period predicted average light intensity, a second period predicted average photosynthetic photon flux density, a second period predicted light duration, a photovoltaic panel photoelectric conversion efficiency, and a photovoltaic panel area.

[0052] a monitoring module connected to the first data acquisition module, for monitoring the light intensity and photosynthetic photon flux density in the first period, and when the light intensity in the first period first drops to a pre-set first threshold value, after a pre-set first sampling holding time, calculating the first period average photosynthetic photon flux density and the first period light duration, recording the energy of the energy storage battery as an initial energy, and recording the current time as a control starting time; and the light intensity continues to be less than the first threshold value within the first sampling holding time.

[0053] an optimization calculation module connected to the monitoring module, for constructing a first optimization objective function and optimization constraints according to the first period average photosynthetic photon flux density, the first period light duration, the initial energy, and the first data; the optimization variable of the first optimization objective function being the LED plant growth lamp power; and using a particle swarm optimization algorithm to calculate the optimal LED plant growth lamp power, with the goal of minimizing the value of the first optimization objective function.

[0054] a power control module connected to the optimization calculation module, for starting the LED plant growth lamp from the control starting time, setting the LED plant growth lamp power to the optimal LED plant growth lamp power, and turning off the LED plant growth lamp until the first period ends.

[0055] Further, the first data acquisition module comprises:

[0056] a data reading module for acquiring the first period, the second period, the second period predicted average light intensity, the second period predicted average photosynthetic photon flux density, the second period predicted light duration, the photovoltaic panel photoelectric conversion efficiency, and the photovoltaic panel area.

[0057] The first period is a period in which the current LED plant growth lamp control is located; the second period is a period in which the next LED plant growth lamp control is located; in the first period, the light intensity is first increased to a first threshold value, and the time after a second sampling holding time set in advance is delayed is the starting point of the first period, and the starting point of the first period plus 86400 seconds is the end point of the first period; the light intensity is greater than the first threshold value during the second sampling holding time; the end point of the first period is the starting point of the second period; the starting point of the second period plus 86400 seconds is the end point of the second period.

[0058] Further, the monitoring module comprises:

[0059] The data acquisition module is configured to monitor the light intensity of the first period by using a light intensity monitoring instrument, and monitor the photosynthetic photon flux density of the first period by using a photosynthetic photon flux density monitoring instrument; when the light intensity of the first period is first decreased to a first threshold value set in advance, and after a first sampling holding time set in advance is delayed, the first period average photosynthetic photon flux density, the first period light duration, the power of the energy storage battery, recorded as the initial power, and the current time, recorded as the control starting time, are calculated.

[0060] The first period average photosynthetic photon flux density represents the average value of the photosynthetic photon flux density during the period from the starting point of the first period to the control starting time; and the first period light duration represents the time length from the starting point of the first period to the control starting time.

[0061] Further, the optimization calculation module comprises:

[0062] The first optimization objective function construction module is configured to construct a first optimization objective function, which is represented as:

[0063] ;

[0064] wherein, represents the first optimization objective function; represents an optimal load rate of the energy storage battery obtained in advance; represents the power of the LED plant growth lamp, and the unit is kilowatt; represents the rated output power of the energy storage battery obtained in advance, and the unit is kilowatt; represents the number of LED plant growth lamps.

[0065] The fitting module is connected with the first optimization objective function construction module, and is configured to fit the first conversion function ; the independent variable of the first conversion function is LED plant growth lamp power, and the dependent variable of the first conversion function is LED plant growth lamp photosynthetic photon flux density, unit: micromole per square meter per second.

[0066] The constraint condition construction module is connected with the fitting module, and is used for constructing optimization constraint conditions, the optimization constraint conditions including a first constraint condition, a second constraint condition, a third constraint condition, a fourth constraint condition and a fifth constraint condition.

[0067] The first constraint condition is:

[0068] ;

[0069] wherein, is a pre-obtained upper limit of LED plant growth lamp power, unit: kilowatt, representing the maximum input power allowed by the LED plant growth lamp.

[0070] The second constraint condition is:

[0071] ;

[0072] wherein, represents a lower limit of photosynthetic photon accumulation, unit: mole per square meter; represents an upper limit of photosynthetic photon accumulation, unit: mole per square meter; represents a calculated time length of the first period, unit: second; represents a first period light duration, unit: second; represents a first period average photosynthetic photon flux density, unit: micromole per square meter per second; the lower limit of photosynthetic photon accumulation and the upper limit of photosynthetic photon accumulation are obtained by pre-setting.

[0073] The third constraint condition is:

[0074] ;

[0075] wherein, represents an initial electric quantity, unit: kilowatt-hour.

[0076] The fourth constraint condition is:

[0077] ;

[0078] wherein, represents a pre-obtained maximum load rate of the energy storage battery.

[0079] The second period predicted LED plant growth lamp minimum power , the second period predicted photovoltaic generated electric quantity .

[0080] The fifth constraint condition is:

[0081] ;

[0082] wherein, represents the minimum value of and ; represents the second period predicted light duration, in seconds; represents the pre-obtained energy storage battery capacity, in kilowatt-hours.

[0083] Further, the constraint condition construction module comprises:

[0084] a second period predicted LED plant growth lamp minimum power calculation module, configured to calculate a second period predicted LED plant growth lamp minimum power, wherein a calculation formula of the second period predicted LED plant growth lamp minimum power is:

[0085] ;

[0086] wherein, represents an inverse function of the first conversion function; represents a second period predicted LED plant growth lamp minimum photosynthetic photon flux density, in micromole per square meter per second; , in kilowatts; , wherein a calculation formula of

[0087] ;

[0088] wherein, represents a second period predicted average photosynthetic photon flux density.

[0089] a second period predicted photovoltaic generated power calculation module, connected with the second period predicted LED plant growth lamp minimum power calculation module, configured to calculate a second period predicted photovoltaic generated power, wherein a calculation formula of the second period predicted photovoltaic generated power is:

[0090] ;

[0091] wherein, represents a second period predicted average light intensity, in watts per square meter; represents a photovoltaic panel area, in square meters; represents a photovoltaic panel photoelectric conversion efficiency; , in kilowatt-hours.

[0092] (3) Beneficial effects

[0093] Compared with the prior art, the present application has the following advantages:

[0094] According to the first period average photosynthetic photon flux density, the first period light duration, the initial electric quantity, the first data, a first optimization objective function is constructed, and an optimization constraint condition is constructed, and an optimization variable of the first optimization objective function is an LED plant growth lamp power. Then, the first optimization objective function is taken as the minimum value, and an optimal LED plant growth lamp power is calculated by using a particle swarm optimization algorithm. Since the first optimization objective function reflects the deviation amount of the load rate of the energy storage battery and the optimal load rate of the energy storage battery, and the optimization constraint condition considers whether the photosynthetic photon accumulation amount obtained by the green plants is suitable and other factors, the optimal LED plant growth lamp power calculated can make the load rate of the energy storage battery reach a better level on the premise of ensuring that the green plants obtain a suitable photosynthetic photon accumulation amount, and further improve the service life of the energy storage battery. In addition, the optimization constraint condition also considers the dynamic change of the energy consumption and charging amount of the energy storage battery in the second period and the first period under the condition of the photovoltaic generated electric energy, and is suitable for application in the LED plant growth lamp power control scene with photovoltaic energy storage. BRIEF DESCRIPTION OF DRAWINGS

[0095] Figure 1 A flow chart of a method for controlling growth of green plants by using an LED plant growth lamp according to Embodiment 1 of the present application;

[0096] Figure 2 A module composition schematic diagram of a system for controlling growth of green plants by using an LED plant growth lamp according to Embodiment 2 of the present application. DETAILED DESCRIPTION

[0097] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0098] Before examples are given, the application scenario of the concept of the present application needs to be described. The present application is applied to LED plant growth lamp power control powered by photovoltaic energy storage. During the day, when the natural light intensity exceeds a threshold value, the photovoltaic panel converts solar energy into electric energy by receiving natural light, and stores the electric energy into an energy storage battery. At night, the energy storage battery discharges to the LED plant growth lamp, and the plant receives light through illumination by the LED plant growth lamp, thereby controlling the growth of the green plants. The present embodiment aims to control the LED plant growth lamp power, so that the load rate of the energy storage battery reaches a better level on the premise of ensuring that the green plants obtain a suitable photosynthetic photon accumulation amount, and further improves the service life of the energy storage battery.

[0099] Embodiment 1: As shown in the figure, the embodiment provides a method for controlling the growth of green plants by using LED plant growth lamps, and the method comprises the following steps: Figure 1

[0100] S1, obtaining first data; the first data comprises a first period, a second period, a second period predicted average light intensity, a second period predicted average photosynthetic photon flux density, a second period predicted light duration, a photovoltaic panel photoelectric conversion efficiency, and a photovoltaic panel area obtained in advance.

[0101] S2, monitoring the light intensity and photosynthetic photon flux density in the first period, and when the light intensity in the first period first decreases to a first threshold value set in advance, the first period average photosynthetic photon flux density and the first period light duration are calculated after a first sampling holding time set in advance is delayed, the power of the energy storage battery is recorded as an initial power, and the current time is recorded as a control starting time; the light intensity is continuously less than the first threshold value within the first sampling holding time.

[0102] S3, constructing a first optimization objective function and optimization constraints according to the first period average photosynthetic photon flux density, the first period light duration, the initial power, and the first data; the optimization variable of the first optimization objective function is the power of the LED plant growth lamp; the optimal LED plant growth lamp power is calculated by using a particle swarm optimization algorithm with the minimum value of the first optimization objective function as the target.

[0103] S4, starting the LED plant growth lamp from the control starting time, setting the power of the LED plant growth lamp as the optimal LED plant growth lamp power, and closing the LED plant growth lamp until the first period ends.

[0104] Exemplarily, a photovoltaic panel with an area of 54 square meters is connected with a lithium iron phosphate energy storage battery with a rated capacity of 40.5 kilowatt-hours and a rated output power of 5 kilowatts, the energy storage battery supplies power to 20 LED plant growth lamps, and the power adjustment range of each plant growth lamp is 0 watts to 200 watts. The 20 LED plant growth lamps are dispersedly arranged in a plant growth greenhouse, and the illumination ranges of the 20 LED plant growth lamps do not overlap with each other.

[0105] ​Obtaining first data. The first data includes a first period, a second period, a second period predicted average light intensity, a second period predicted average photosynthetic photon flux density, a second period predicted light duration, a photovoltaic panel photoelectric conversion efficiency, and a photovoltaic panel area. The first period is from 6:15:00 on the current day to 6:15:00 on the next day, and the second period is from 6:15:00 on the next day to 6:15:00 on the third day. The first period is the period in which the current round of LED plant growth lamp control is located; the second period is the period in which the next round of LED plant growth lamp control is expected to be located. The data is extracted from the Jihe Energy Meteorological Big Data Platform, and the second period predicted average light intensity is derived to be 198 watts per square meter, the second period predicted average photosynthetic photon flux density is derived to be 904 micromoles per square meter per second, and the second period predicted light duration is derived to be 12 hours. Through device parameter inquiry, the photovoltaic panel photoelectric conversion efficiency is obtained to be 20.5%, and the photovoltaic panel area is obtained to be 18 square meters. The second period predicted average photosynthetic photon flux density represents the number of micromoles of photons per square meter falling within the wavelength range of 400-700 nanometers per second, reflecting the intensity of photosynthetically active radiation, i.e., the number of micromoles of photons that are helpful for the growth of green plants. For a specific geographic location, the second period predicted average photosynthetic photon flux density is directly proportional to the second period predicted average light intensity.

[0106] The light intensity and photosynthetic photon flux density in the first period are monitored by light intensity monitoring instruments and photosynthetic photon flux density monitoring instruments using a continuous monitoring method. When the light intensity in the first period first drops to a pre-set first threshold, the first period average photosynthetic photon flux density and the first period light duration are calculated after a pre-set first sampling holding time. The purpose of setting the first sampling holding time is to prevent misjudgment caused by instantaneous mutation of the light intensity in the first period. When the light intensity first drops to the first threshold of 10 watts per square meter at 18:42:00, the first sampling holding time of 15 minutes is delayed, and it is confirmed that the light intensity has been below 10 watts per square meter within the first sampling holding time of 15 minutes. The current time, i.e., 18:57:00, is recorded as the control starting time. According to the monitoring data from 6:15:00 to 18:57:00, the first period average photosynthetic photon flux density is calculated to be 942 micromoles per square meter per second, and the first period light duration is calculated to be 45,720 seconds using the average value calculation method. In addition, the energy storage battery is recorded to have an electric quantity of 39.8 kilowatt-hours, i.e., an initial electric quantity of 39.8 kilowatt-hours.

[0107] According to the first period average photosynthetic photon flux density, the first period light duration, the initial electric quantity, the first data, a first optimization objective function is constructed, and an optimization constraint condition. The optimization variable of the first optimization objective function is the LED plant growth lamp power. The optimization objective of the first optimization objective function is that the load rate of the energy storage battery reaches a better level, that is, the deviation amount of the load rate of the energy storage battery from the optimal load rate of the energy storage battery is minimum. For each energy storage battery, there is an optimal load rate. The optimal load rate of the energy storage battery is related to the type of the battery. For a lithium iron phosphate energy storage battery, when the load rate is greater than 80%, lithium dendrite growth is accelerated, thereby reducing the service life of the energy storage battery; when the load rate is lower than 30%, passivation is prone to occur, thereby reducing the utilization rate of active substances of the energy storage battery. Considering the service life and efficiency comprehensively, the optimal load rate of the lithium iron phosphate energy storage battery is 60% through statistical data calculation. Therefore, the optimal load rate of the energy storage battery in the embodiment is set to 60%. However, if the LED plant growth lamp power is directly set to make the load rate of the energy storage battery exactly 60%, the optimization constraint condition may not be met. In addition to considering the electrical relationship constraint of the energy storage battery power, whether the photosynthetic photon accumulation amount obtained by the green plant is appropriate is also considered, that is, it cannot be too high or too low. Taking the minimum value of the first optimization objective function as the target, the optimal LED plant growth lamp power is calculated to be 142 W, that is, 0.142 kW by using a particle swarm optimization algorithm.

[0108] From the control starting moment, that is, 18:57:00, the LED plant growth lamp is turned on and the power is set to 0.142 kW per lamp, and the total power of 20 LED plant growth lamps is 2.84 kW, and the load rate of the energy storage battery is 56.8%. The running continues to the first period termination, that is, 6:15:00 the next day, a total of 40,680 seconds, and the consumed electric energy is 32.092 kWh. After the first period termination, the remaining electric quantity of the energy storage battery is 7.708 kWh. Next, in the second period, the photovoltaic cell continues to charge the energy storage battery, and then supplies power to the LED plant growth lamp when the light intensity is lower than the first threshold.

[0109] Further, the method for obtaining the first data comprises:

[0110] The first period, the second period, the second period predicted average light intensity, the second period predicted average photosynthetic photon flux density, the second period predicted light duration, the photovoltaic panel photoelectric conversion efficiency, and the photovoltaic panel area are obtained.

[0111] The first period is a period in which the current LED plant growth lamp control is located; the second period is a period in which the next LED plant growth lamp control is located; in the first period, the light intensity is first increased to a first threshold value, and the starting point of the first period is the time after a second sampling and holding time is delayed; the light intensity is continuously greater than the first threshold value in the second sampling and holding time; the starting point of the second period is the end point of the first period; the end point of the second period is the starting point of the second period plus 86400 seconds.

[0112] Exemplarily, the first threshold value is 10 watts per square meter, the second sampling and holding time is 15 minutes, the first period is from 6:15:00 on the current day to 6:15:00 on the next day, and the second period is from 6:15:00 on the next day to 6:15:00 on the third day.

[0113] Further, the method for monitoring the light intensity and the photosynthetic photon flux density in the first period, when the light intensity in the first period is first decreased to a first threshold value, and after a first sampling and holding time is delayed, the first period average photosynthetic photon flux density and the first period light duration are calculated, the power of the energy storage battery is recorded, and is recorded as the initial power, and the current time is recorded, and is recorded as the control starting time.

[0114] The light intensity monitoring instrument is used to monitor the light intensity in the first period, and the photosynthetic photon flux density monitoring instrument is used to monitor the photosynthetic photon flux density in the first period; when the light intensity in the first period is first decreased to a first threshold value, and after a first sampling and holding time is delayed, the first period average photosynthetic photon flux density and the first period light duration are calculated, the power of the energy storage battery is recorded, and is recorded as the initial power, and the current time is recorded, and is recorded as the control starting time.

[0115] The first period average photosynthetic photon flux density represents the average value of the photosynthetic photon flux density during the period from the starting point of the first period to the control starting time; and the first period light duration represents the time length from the starting point of the first period to the control starting time.

[0116] Exemplarily, by deploying the light intensity monitoring instrument and the photosynthetic photon flux density monitoring instrument, a continuous monitoring method of collecting data every 60 seconds is adopted to obtain real-time monitoring data of the first period starting from 6:15:00 on the current day. The control starting time is 18:57:00 by monitoring and calculation. The average value of the photosynthetic photon flux density during the period from 6:15:00 on the current day to 18:57:00 on the current day is calculated, and is recorded as the first period average photosynthetic photon flux density.

[0117] Further, the method of constructing a first optimization objective function according to the first-period average photosynthetic photon flux density, the first-period light duration, the initial electric quantity, and the first data comprises:

[0118] The first optimization objective function is constructed and is expressed as:

[0119] ;

[0120] wherein, represents the first optimization objective function; represents the optimal load rate of the energy storage battery obtained in advance; represents the LED plant growth lamp power, in kilowatts; represents the rated output power of the energy storage battery obtained in advance, in kilowatts; represents the number of LED plant growth lamps.

[0121] According to the photosynthetic photon flux density samples of the LED plant growth lamp at different powers obtained in advance, a first conversion function is fitted ; the independent variable of the first conversion function is the LED plant growth lamp power, and the dependent variable of the first conversion function is the photosynthetic photon flux density of the LED plant growth lamp, in micromoles per square meter per second.

[0122] The optimization constraint condition is constructed, and the optimization constraint condition comprises a first constraint condition, a second constraint condition, a third constraint condition, a fourth constraint condition, and a fifth constraint condition.

[0123] The first constraint condition is:

[0124] ;

[0125] wherein, is the upper limit of the LED plant growth lamp power obtained in advance, in kilowatts, indicating the maximum input power allowed by the LED plant growth lamp.

[0126] The second constraint condition is:

[0127] ;

[0128] wherein, represents the lower limit of the photosynthetic photon accumulation, in moles per square meter; represents the upper limit of the photosynthetic photon accumulation, in moles per square meter; represents the time length of the first period calculated, in seconds; represents the first-period light duration, in seconds; represents the first cycle average photosynthetic photon flux density, unit: micro mole per square meter per second; the lower limit of photosynthetic photon accumulation and the upper limit of photosynthetic photon accumulation are obtained in advance.

[0129] The third constraint condition is:

[0130] ;

[0131] wherein, represents the initial electric quantity, unit: kilowatt hour.

[0132] The fourth constraint condition is:

[0133] ;

[0134] wherein, represents the maximum load rate of the energy storage battery obtained in advance.

[0135] The second cycle predicted minimum power of the LED plant growth lamp is calculated as The second cycle predicted electric quantity generated by the photovoltaic is calculated as .

[0136] The fifth constraint condition is:

[0137] ;

[0138] wherein, represents the minimum value of and ; represents the second cycle predicted illumination time length, unit: second; represents the capacity of the energy storage battery obtained in advance, unit: kilowatt hour.

[0139] Exemplarily, according to a pre-acquired sample of photosynthetic photon flux density generated by the LED plant growth lamp at different powers, a first conversion function is fitted by using a nonlinear fitting algorithm. Then, a first constraint condition, a second constraint condition, a third constraint condition, a fourth constraint condition and a fifth constraint condition are constructed. The first constraint condition reflects the adjustable range of the power of the LED plant growth lamp. The second constraint condition indicates that the cumulative amount of photosynthetic photons accumulated by the green plants in the first period after receiving natural light during the day and receiving LED plant growth lamp light at night should be within the interval of the lower limit of the cumulative amount of photosynthetic photons to the upper limit of the cumulative amount of photosynthetic photons. For different green plants, the values of the lower limit of the cumulative amount of photosynthetic photons and the upper limit of the cumulative amount of photosynthetic photons are also different. The third constraint condition indicates that the power consumed by the LED plant growth lamp in the first period of the opening time period cannot exceed the initial power, otherwise the power will be insufficient. The fourth constraint condition indicates that the load rate of the energy storage battery generated by 20 LED plant growth lamps cannot exceed the maximum load rate of the energy storage battery. Here, the maximum load rate of the energy storage battery is set to 100%. The fifth constraint condition is that considering the power generated by the photovoltaic in the second period, the power of the energy storage battery should be sufficient to meet the lighting needs of the green plants in the second period, unless the lighting needs of the second period cannot be met even if the energy storage battery is fully charged. The second period predicted lighting time can be calculated by numerical weather prediction.

[0140] Further, the method for calculating the second period predicted minimum power of the LED plant growth lamp , the second period predicted photovoltaic generated power comprises:

[0141] calculating the second period predicted minimum power of the LED plant growth lamp, the calculation formula of the second period predicted minimum power of the LED plant growth lamp is:

[0142] ;

[0143] wherein, represents the inverse function of the first conversion function; represents the second period predicted minimum photosynthetic photon flux density of the LED plant growth lamp, the unit is micromole per square meter per second; the unit of is kilowatt; the calculation formula of is:

[0144] ;

[0145] wherein, represents the second period predicted average photosynthetic photon flux density.

[0146] calculating the second period predicted photovoltaic generated power, the calculation formula of the second period predicted photovoltaic generated power is:

[0147] ;

[0148] wherein, represents the second period predicted average light intensity, in units of watts per square meter; represents the photovoltaic panel area, in units of square meters; represents the photovoltaic panel photoelectric conversion efficiency; the unit of is kilowatt-hour.

[0149] Exemplarily, the second period predicted average light intensity and the second period predicted average photosynthetic photon flux density can be calculated by numerical weather prediction. The second period predicted average light intensity and the second period predicted average photosynthetic photon flux density only include the light intensity and the photosynthetic photon flux density generated by natural light.

[0150] Embodiment 2: based on the same inventive concept, as Figure 2 shown, the embodiment also provides a system for controlling the growth of green plants by using an LED plant growth lamp, the system comprising:

[0151] a first data acquisition module for acquiring first data; the first data includes a first period, a second period, a second period predicted average light intensity, a second period predicted average photosynthetic photon flux density, a second period predicted light duration, a photovoltaic panel photoelectric conversion efficiency, and a photovoltaic panel area obtained in advance.

[0152] a monitoring module connected with the first data acquisition module, for monitoring the light intensity and the photosynthetic photon flux density in the first period, and when the light intensity in the first period first drops to a pre-set first threshold value, after a pre-set first sampling holding time, the first period average photosynthetic photon flux density and the first period light duration are calculated, the power of the energy storage battery is recorded as an initial power, and the current time is recorded as a control starting time; the light intensity continues to be less than the first threshold value within the first sampling holding time.

[0153] an optimization calculation module connected with the monitoring module, for constructing a first optimization objective function and optimization constraints according to the first period average photosynthetic photon flux density, the first period light duration, the initial power, and the first data; the optimization variable of the first optimization objective function is the LED plant growth lamp power; the optimal LED plant growth lamp power is calculated by using a particle swarm optimization algorithm with the goal of minimizing the value of the first optimization objective function.

[0154] a power control module connected with the optimization calculation module, for starting the LED plant growth lamp from the control starting time, setting the LED plant growth lamp power as the optimal LED plant growth lamp power, and turning off the LED plant growth lamp until the first period ends.

[0155] Further, the first data acquisition module comprises:

[0156] a data reading module, configured to acquire the first period, the second period, the second period predicted average light intensity, the second period predicted average photosynthetic photon flux density, the second period predicted light duration, the photovoltaic panel photoelectric conversion efficiency, and the photovoltaic panel area.

[0157] The first period is a period in which the current LED plant growth lamp control is located; the second period is a period in which the next LED plant growth lamp control is expected to be located; in the first period, the starting point of the first period is the time point at which the light intensity first rises to a first threshold value and then is delayed for a second sampling holding time set in advance; the ending point of the first period is the starting point of the first period plus 86400 seconds; the light intensity is continuously greater than the first threshold value within the second sampling holding time; the starting point of the second period is the ending point of the first period; the ending point of the second period is the starting point of the second period plus 86400 seconds.

[0158] Further, the monitoring module comprises:

[0159] a data acquisition module, configured to monitor the light intensity of the first period by using a light intensity monitoring instrument and monitor the photosynthetic photon flux density of the first period by using a photosynthetic photon flux density monitoring instrument; when the light intensity of the first period first falls to a first threshold value set in advance and then is delayed for a first sampling holding time set in advance, the first period average photosynthetic photon flux density and the first period light duration are calculated, the power of the energy storage battery is recorded as an initial power, and the current time is recorded as a control starting time.

[0160] The first period average photosynthetic photon flux density represents the average value of the photosynthetic photon flux density during the period from the starting point of the first period to the control starting time; and the first period light duration represents the time length from the starting point of the first period to the control starting time.

[0161] Further, the optimization calculation module comprises:

[0162] a first optimization objective function construction module, configured to construct a first optimization objective function, the first optimization objective function being represented as:

[0163] ;

[0164] wherein, represents the first optimization objective function; represents an optimal load rate of the energy storage battery obtained in advance; represents the LED plant growth lamp power, in kilowatts; represents the rated output power of the energy storage battery obtained in advance, in kilowatts; represents the number of LED plant growth lamps.

[0165] The fitting module is connected with the first optimization objective function construction module, and is configured to fit the first conversion function according to the photosynthetic photon flux density samples generated by the LED plant growth lamp at different powers obtained in advance. The independent variable of the first conversion function is the power of the LED plant growth lamp, and the dependent variable of the first conversion function is the photosynthetic photon flux density of the LED plant growth lamp, in micromoles per square meter per second.

[0166] The constraint condition construction module is connected with the fitting module, and is configured to construct optimization constraints, the optimization constraints including a first constraint condition, a second constraint condition, a third constraint condition, a fourth constraint condition and a fifth constraint condition.

[0167] The first constraint condition is:

[0168] ;

[0169] wherein, represents the upper limit of the power of the LED plant growth lamp obtained in advance, in kilowatts, indicating the maximum input power allowed by the LED plant growth lamp.

[0170] The second constraint condition is:

[0171] ;

[0172] wherein, represents the lower limit of the photosynthetic photon accumulation, in moles per square meter; represents the upper limit of the photosynthetic photon accumulation, in moles per square meter; represents the length of the first period calculated, in seconds; represents the length of the first period of illumination, in seconds; represents the average photosynthetic photon flux density of the first period, in micromoles per square meter per second; the lower limit of the photosynthetic photon accumulation and the upper limit of the photosynthetic photon accumulation are obtained by pre-setting.

[0173] The third constraint condition is:

[0174] ;

[0175] wherein, represents the initial electric quantity, in kilowatt-hours.

[0176] The fourth constraint condition is:

[0177] ;

[0178] wherein, represents the maximum load rate of the energy storage battery obtained in advance.

[0179] calculating the second-period predicted LED plant growth lamp minimum power , the second-period predicted photovoltaic power generation .

[0180] The fifth constraint condition is:

[0181] ;

[0182] wherein, represents the minimum value of and ; represents the second-period predicted illumination duration, in seconds; represents the energy storage battery capacity obtained in advance, in kilowatt-hours.

[0183] Further, the constraint condition construction module comprises:

[0184] The second-period predicted LED plant growth lamp minimum power calculation module is configured to calculate the second-period predicted LED plant growth lamp minimum power, and the calculation formula of the second-period predicted LED plant growth lamp minimum power is:

[0185] ;

[0186] wherein, represents the inverse function of the first conversion function; represents the second-period predicted LED plant growth lamp minimum photosynthetic photon flux density, in micromole per square meter per second; , in kilowatts; The calculation formula of

[0187] ;

[0188] wherein, represents the second-period predicted average photosynthetic photon flux density.

[0189] The second-period predicted photovoltaic power generation calculation module is connected with the second-period predicted LED plant growth lamp minimum power calculation module and configured to calculate the second-period predicted photovoltaic power generation, and the calculation formula of the second-period predicted photovoltaic power generation is:

[0190] ;

[0191] wherein, represents the second period prediction average light intensity, unit: watt per square meter; represents the photovoltaic panel area, unit: square meter; represents the photovoltaic panel photoelectric conversion efficiency; unit: kilowatt hour.

[0192] It should be noted that, as for the system in the above-mentioned embodiments, the specific manner in which each module performs operations has been described in detail in the embodiments related to the method, and will not be described in detail here.

[0193] Finally, it should be noted that: although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacements for part of the technical features, any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A method of controlling the growth of a green plant with an LED plant growth light, characterized in that, The method includes the following steps: S1, acquire first data; the first data includes a first period, a second period, the second period predicted average light intensity, the second period predicted average photosynthetic photon flux density, the second period predicted light duration, the photovoltaic panel photoelectric conversion efficiency, and the photovoltaic panel area. S2, monitor the light intensity and photosynthetic photon flux density of the first cycle. When the light intensity of the first cycle first drops to a preset first threshold, and then after a preset first sampling hold time, calculate the average photosynthetic photon flux density and the illumination duration of the first cycle, record the energy storage battery charge as the initial charge, and record the current time as the control start time; the light intensity remains less than the first threshold during the first sampling hold time. S3. Based on the average photosynthetic photon flux density of the first cycle, the illumination duration of the first cycle, the initial charge, and the first data, construct a first optimization objective function and optimization constraints; the optimization variable of the first optimization objective function is the power of the LED plant growth lamp; with the goal of minimizing the value of the first optimization objective function, use the particle swarm optimization algorithm to calculate the optimal power of the LED plant growth lamp. The first optimization objective function is expressed as: ； wherein, represents a first optimization objective function; represents an optimal load rate of the energy storage battery obtained in advance; represents the power of the LED plant growth lamp, in kilowatts; represents the rated output power of the energy storage battery obtained in advance, in kilowatts; represents the number of LED plant growth lamps; S4: Starting from the control start time, turn on the LED plant grow light, set the LED plant grow light power to the optimal LED plant grow light power, and turn off the LED plant grow light when the first cycle ends.

2. A method of controlling growth of a green plant with an LED plant growth lamp as claimed in claim 1, wherein, The method for obtaining the first data includes: Obtain the first period, the second period, the second period's predicted average light intensity, the second period's predicted average photosynthetic photon flux density, the second period's predicted illumination duration, the photovoltaic panel's photoelectric conversion efficiency, and the photovoltaic panel area. The first cycle is the cycle in which the current round of LED plant grow light control occurs; the second cycle is the cycle in which the next round of LED plant grow light control is expected to occur; in the first cycle, the starting point of the first cycle is the moment after the light intensity first rises to the first threshold and is delayed by a pre-set second sampling hold time, and the ending point of the first cycle is the starting point plus 86400 seconds; during the second sampling hold time, the light intensity continues to be greater than the first threshold; the ending point of the first cycle is the starting point of the second cycle; and the ending point of the second cycle is the starting point plus 86400 seconds.

3. A method of controlling the growth of a green plant with an LED plant growth lamp as claimed in claim 2, characterized in that, The method for monitoring the light intensity and photosynthetic photon flux density of the first cycle, calculating the average photosynthetic photon flux density and the illumination duration of the first cycle after the light intensity of the first cycle first drops to a preset first threshold and then delaying for a preset first sampling hold time, recording the energy storage battery charge as the initial charge, and recording the current time as the control start time includes: The light intensity of the first cycle is monitored using a light intensity monitoring instrument, and the photosynthetic photon flux density of the first cycle is monitored using a photosynthetic photon flux density monitoring instrument. When the light intensity of the first cycle first drops to a preset first threshold, and after a preset first sampling hold time, the average photosynthetic photon flux density and the illumination duration of the first cycle are calculated. The energy storage battery charge is recorded as the initial charge, and the current time is recorded as the control start time. The average photosynthetic photon flux density of the first cycle represents the average value of the photosynthetic photon flux density from the start point of the first cycle to the control start time; the illumination duration of the first cycle represents the length of time from the start point of the first cycle to the control start time.

4. A method of controlling the growth of a green plant with an LED plant growth lamp as claimed in claim 3, characterized in that, The method for constructing a first optimization objective function and optimization constraints based on the first cycle average photosynthetic photon flux density, the first cycle illumination duration, the initial charge, and the first data includes: Construct the first optimization objective function; According to a pre-acquired sample of photosynthetic photon flux density generated by the LED plant growth lamp under different powers, a first conversion function is fitted ; the independent variable of the first conversion function is the power of the LED plant growth lamp, and the dependent variable of the first conversion function is the photosynthetic photon flux density of the LED plant growth lamp, in units of micromoles per square meter per second; Construct optimization constraints, which include a first constraint, a second constraint, a third constraint, a fourth constraint, and a fifth constraint. The first constraint is: ； wherein, is the pre-obtained upper limit of the power of the LED plant growth lamp, in kilowatts, representing the maximum input power allowed by the LED plant growth lamp; The second constraint is: ； wherein, represents a lower limit of the cumulative amount of photosynthetic photons, in moles per square meter; represents an upper limit of the cumulative amount of photosynthetic photons, in moles per square meter; represents a calculated length of the first period, in seconds; represents a length of the first period of illumination, in seconds; represents a first period average photosynthetic photon flux density, in micromoles per square meter per second; the lower limit of the cumulative amount of photosynthetic photons and the upper limit of the cumulative amount of photosynthetic photons are obtained by pre-setting; The third constraint is: ； in, This indicates the initial electrical charge, expressed in kilowatt-hours. The fourth constraint is: ； in, This indicates the maximum load rate of the energy storage battery obtained in advance; The minimum power of the LED plant grow light predicted for the second cycle was calculated. Second cycle prediction of photovoltaic power generation ; The fifth constraint is: ； in, express and The minimum value; This indicates the predicted duration of illumination in the second cycle, in seconds. This indicates the pre-determined energy storage battery capacity, expressed in kilowatt-hours.

5. A method for controlling plant growth using LED plant growth lights as described in claim 4, characterized in that, The calculation yields the minimum power of the predicted LED plant growth lamp for the second cycle. Second cycle prediction of photovoltaic power generation The methods include: The minimum power of the LED plant grow light predicted for the second cycle was calculated. The formula for calculating the minimum power of the LED plant grow light predicted for the second cycle is as follows: ； in, This represents the inverse function of the first transformation function; This indicates the minimum photosynthetic photon flux density of the LED plant growth light predicted in the second period, in micromoles per square meter per second. The unit is kilowatt; The calculation formula is: ； in, This represents the predicted average photosynthetic photon flux density for the second period. The predicted photovoltaic power generation for the second cycle is calculated using the following formula: ； in, This represents the predicted average light intensity for the second period, expressed in watts per square meter. This indicates the area of ​​the photovoltaic panel, in square meters. Indicates the photoelectric conversion efficiency of a photovoltaic panel; The unit is kilowatt-hour.

6. A system for controlling the growth of green plants using LED plant growth lights, characterized in that, The system includes: The first data acquisition module is used to acquire first data; the first data includes a first period, a second period, the second period predicted average light intensity, the second period predicted average photosynthetic photon flux density, the second period predicted light duration, the photovoltaic panel photoelectric conversion efficiency, and the photovoltaic panel area. The monitoring module, connected to the first data acquisition module, is used to monitor the light intensity and photosynthetic photon flux density of the first cycle. When the light intensity of the first cycle first drops to a preset first threshold, and after a preset first sampling hold time, the average photosynthetic photon flux density and the illumination duration of the first cycle are calculated. The battery charge is recorded as the initial charge, and the current time is recorded as the control start time. The light intensity remains below the first threshold during the first sampling hold time. An optimization calculation module, connected to the monitoring module, is used to construct a first optimization objective function and optimization constraints based on the first cycle average photosynthetic photon flux density, the first cycle illumination duration, the initial charge, and the first data. The optimization variable of the first optimization objective function is the power of the LED plant growth lamp. The optimal LED plant growth lamp power is calculated using a particle swarm optimization algorithm with the goal of minimizing the value of the first optimization objective function. The first optimization objective function is expressed as: ； in, This represents the first optimization objective function; This indicates the optimal load rate of the energy storage battery obtained in advance; This indicates the power of the LED plant grow light, measured in kilowatts. This indicates the pre-determined rated output power of the energy storage battery, expressed in kilowatts. Indicates the number of LED plant grow lights; The power control module, connected to the optimization calculation module, is used to turn on the LED plant grow lights from the start of control, set the LED plant grow light power to the optimal LED plant grow light power, and turn off the LED plant grow lights at the end of the first cycle.

7. A system for controlling plant growth using LED plant growth lights as described in claim 6, characterized in that, The first data acquisition module includes: The data reading module is used to acquire the first period, the second period, the predicted average light intensity of the second period, the predicted average photosynthetic photon flux density of the second period, the predicted illumination duration of the second period, the photovoltaic conversion efficiency of the photovoltaic panel, and the area of ​​the photovoltaic panel. The first cycle is the cycle in which the current round of LED plant grow light control occurs; the second cycle is the cycle in which the next round of LED plant grow light control is expected to occur; in the first cycle, the starting point of the first cycle is the moment after the light intensity first rises to the first threshold and is delayed by a pre-set second sampling hold time, and the ending point of the first cycle is the starting point plus 86400 seconds; during the second sampling hold time, the light intensity continues to be greater than the first threshold; the ending point of the first cycle is the starting point of the second cycle; and the ending point of the second cycle is the starting point plus 86400 seconds.

8. A system for controlling plant growth using LED plant growth lights as described in claim 7, characterized in that, The monitoring module includes: The data acquisition module is used to monitor the light intensity of the first cycle using a light intensity monitoring instrument and the photosynthetic photon flux density of the first cycle using a photosynthetic photon flux density monitoring instrument. When the light intensity of the first cycle first drops to a preset first threshold, and after a preset first sampling hold time, the average photosynthetic photon flux density and the illumination duration of the first cycle are calculated. The battery charge is recorded as the initial charge, and the current time is recorded as the control start time. The average photosynthetic photon flux density of the first cycle represents the average value of the photosynthetic photon flux density from the start point of the first cycle to the control start time; the illumination duration of the first cycle represents the length of time from the start point of the first cycle to the control start time.

9. A system for controlling the growth of green plants using LED plant growth lights as described in claim 8, characterized in that, The optimization calculation module includes: The first optimization objective function construction module is used to construct the first optimization objective function; The fitting module, connected to the first optimization objective function construction module, is used to fit the first transformation function based on pre-acquired photosynthetic photon flux density samples generated by LED plant growth lights at different power levels. The independent variable of the first conversion function is the power of the LED plant growth lamp, and the dependent variable of the first conversion function is the luminous photon flux density of the LED plant growth lamp, in micromoles per square meter per second. The constraint construction module, connected to the fitting module, is used to construct optimization constraints, which include a first constraint, a second constraint, a third constraint, a fourth constraint, and a fifth constraint. The first constraint is: ； in, The power limit of the LED grow light is obtained in advance, in kilowatts, representing the maximum allowable input power of the LED grow light; The second constraint is: ； in, This indicates the lower limit of the cumulative amount of photosynthetically synthesized photons, expressed in moles per square meter. This indicates the upper limit of the cumulative amount of photosynthetically synthesized photons, expressed in moles per square meter. This indicates the length of the calculated first cycle, in seconds. This indicates the duration of the first illumination cycle, in seconds. The average photosynthetic photon flux density during the first period is expressed in micromoles per square meter per second; the lower limit and upper limit of the cumulative photosynthetic photon amount are obtained through pre-setting. The third constraint is: ； in, This indicates the initial electrical charge, expressed in kilowatt-hours. The fourth constraint is: ； in, This indicates the maximum load rate of the energy storage battery obtained in advance; The minimum power of the LED plant grow light predicted for the second cycle was calculated. Second cycle prediction of photovoltaic power generation ; The fifth constraint is: ； in, express and The minimum value; This indicates the predicted duration of illumination in the second cycle, in seconds. This indicates the pre-determined energy storage battery capacity, expressed in kilowatt-hours.

10. A system for controlling the growth of green plants using LED plant growth lights as described in claim 9, characterized in that, The constraint construction module includes: The second-cycle prediction LED plant grow light minimum power calculation module is used to calculate the minimum power of the LED plant grow light in the second cycle. The calculation formula for the minimum power of the LED plant grow light in the second cycle is as follows: ； in, This represents the inverse function of the first transformation function; This indicates the minimum photosynthetic photon flux density of the LED plant growth light predicted in the second period, in micromoles per square meter per second. The unit is kilowatt; The calculation formula is: ； in, This represents the predicted average photosynthetic photon flux density for the second period. The second-cycle photovoltaic power generation calculation module is connected to the second-cycle LED plant growth light minimum power calculation module. It is used to calculate the second-cycle predicted photovoltaic power generation. The calculation formula for the second-cycle predicted photovoltaic power generation is as follows: ； in, This represents the predicted average light intensity for the second period, expressed in watts per square meter. This indicates the area of ​​the photovoltaic panel, in square meters. Indicates the photoelectric conversion efficiency of a photovoltaic panel; The unit is kilowatt-hour.

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