A solar greenhouse energy-saving optimization control method and device

Abstract

The present invention relates to a method and device for optimizing energy conservation in a solar greenhouse. The device comprises: a data acquisition module, a signal conditioning module, an analysis and processing module, a controller module, and an execution output module. The data acquisition module mainly comprises a carbon dioxide concentration sensor, an indoor temperature and humidity sensor, a toxic and harmful gas concentration sensor, a light sensor, a soil moisture sensor, and a monitoring camera. The present invention utilizes the characteristics of adjustable environmental parameters in a solar greenhouse, combines the energy demand of agricultural production, and proposes a method and device for optimizing energy conservation in a solar greenhouse. The method and device take new energy power generation as the basic energy source, comprehensively considers the local consumption of renewable energy, and takes into account the operation cost of the network. While minimizing the operation cost of the system, it also ensures the maximization of the benefits of agricultural products in the greenhouse. Compared with the previous system that considers a single optimization target, the advantages are more obvious.

Description

Technical Field

[0001] The present invention relates to the field of renewable energy power generation optimization control and agricultural greenhouse technology, and in particular to a solar greenhouse energy-saving optimization control method and device. Background Art

[0002] The cost of energy use in the agricultural production process accounts for more than 20% of its production cost, and the operating cost issue needs to be considered. As an important part of modern efficient agriculture, greenhouses have the characteristics of controllable indoor environmental parameters, so they can obtain higher agricultural product returns. With my country's increasing attention to ecological issues, in the context of achieving the dual carbon goals, photovoltaic power generation technology has been widely used in the agricultural field, and some problems have also emerged. Photovoltaic power generation is connected to the system as the energy source of the solar greenhouse. Although it can provide part of the energy, the analysis of the operating cost of the system is still unclear. It fails to effectively utilize the controllable environmental parameters such as ambient temperature, light intensity, temperature and humidity in the solar greenhouse, and combines the characteristics of agricultural production to optimize the control of energy supply to reduce the operating cost of distributed photovoltaic access to the solar greenhouse. Summary of the invention

[0003] Aiming at the production characteristics of solar greenhouses, the present invention proposes an energy-saving optimization control method that comprehensively considers the characteristics of distributed photovoltaic power generation, agricultural production equipment, etc., and provides an energy-saving optimization control method and device for a solar greenhouse.

[0004] In order to achieve the above purpose, the technical solution adopted by the present invention is:

[0005] A solar greenhouse energy-saving optimization control method comprises the following steps:

[0006] 1) Collect greenhouse environmental parameters (greenhouse data) and perform signal conditioning;

[0007] 2) After signal conditioning, in the case of the classic solar greenhouse model, for strongly correlated data, the historical data of greenhouse environmental parameters and energy consumption of corresponding equipment are used to fit the data based on the principle of least squares method to find the mapping relationship between greenhouse environmental parameters and equipment energy consumption.

[0008] The mapping relationships include: the relationship between the temperature in the greenhouse and the daily energy consumption of heating equipment (such as air source heat pumps), the relationship between the soil moisture conditions and the daily energy consumption of water-fertilizer integrated equipment, the relationship between the concentration of toxic and harmful gases in the greenhouse and the daily energy consumption of ventilation equipment (such as exhaust fans), the relationship between the light intensity in the greenhouse and the daily energy consumption of supplementary lighting equipment (such as supplementary lights), and the relationship between the carbon dioxide concentration in the greenhouse and the daily energy consumption of the carbon dioxide generator.

[0009] 3) According to the model and performance of photovoltaic panels, the mapping relationship between outdoor environmental parameters and the total output of photovoltaic panels is determined, and then the load and photovoltaic output are integrated to minimize the electricity cost and obtain the final objective function.

[0010] 4) The environmental conditions for crop growth are taken as inequality constraints, and the conservation of electric energy is taken as equality constraints to determine the boundary conditions. Finally, the Lagrange multiplier method is used to solve the problem and the environmental parameters of each greenhouse under the optimal solution conditions are obtained. Based on this, a suitable hysteresis interval is set and compared with the received current greenhouse environmental parameters to output the optimal greenhouse environmental parameters.

[0011] In order to minimize the operating cost, the objective function is expressed in the form of minimizing the electricity cost. The objective function in step 3) is defined as:

[0012] F=minf=w pg (T c , H t , L t , s , D t , T AC , G AC )×p (1)

[0013] Where, F is the minimum electricity cost of the solar greenhouse; w pg is the electric energy transmitted from the power grid to the greenhouse; p is the electricity price; T c is the temperature in the greenhouse; H t is the concentration of toxic and harmful gases in the greenhouse; L t is the light intensity in the greenhouse; ρ s D is soil moisture; t is the carbon dioxide concentration in the greenhouse; T AC is the operating temperature of the solar panel; G AC Indicates the actual outdoor light intensity.

[0014] According to the law of energy conservation, the equality constraint in step 4) is:

[0015] w pg =w all -w ppg -C (2)

[0016] w all =∑w c +w s +w h +w b +w d +w others (3)

[0017] In the formula, w all is the total amount of electrical energy used by the load in the greenhouse; wppg is the total daily output of photovoltaic power; C is the power of the energy storage device (battery). c is the daily energy consumption of the heating equipment in the greenhouse; w s is the daily energy consumption of the water-fertilizer integrated equipment in the greenhouse; w h is the daily energy consumption of ventilation equipment in the greenhouse; w b Daily energy consumption of supplementary lighting equipment in the greenhouse; w d is the daily energy consumption of the carbon dioxide generator in the greenhouse; w others is the daily energy consumption of sensor equipment in the greenhouse (constant).

[0018] in,

[0019]

[0020] In the formula, w ppg is the total daily output of photovoltaic power; P STC G is the maximum test power under standard test conditions; AC Indicates the actual outdoor light intensity, kW / m 2 ; G STC is the outdoor light intensity under standard test conditions, with a value of 1kW / m 2 ; k is the power temperature coefficient, the value is -0.43% / k; T AC is the operating temperature of the photovoltaic panel; T STC The reference temperature under standard test conditions is 25°C. The standard test conditions are solar radiation intensity G STC =1kW / m 2 , battery surface temperature T STC The temperature is 25℃ and the optical quality of the point in the atmosphere is AM1.5.

[0021]

[0022] Where P ch (t) and P dis (t) are the charging and discharging power of the battery at time t; η ch and η dis are the battery charging and discharging efficiency respectively.

[0023]

[0024] In the formula, w c is the daily energy consumption of the heating equipment in the greenhouse; Q hp is the heating capacity; COP is the coefficient of performance; where Q hp and COP vs. greenhouse temperature T c and the air source heat pump outlet water temperature T s1 Related; S frDescribes the defrost status. "0" indicates that the air source heat pump is in defrost status, and "1" indicates that the air source heat pump is not defrosted. vent is the power consumption of the exhaust fan; air is the air volume flow entering the air source heat pump, where the power consumption of the exhaust fan is P vent Determine the air volume flow rate q entering the air source heat pump air .

[0025]

[0026] In the formula, w s is the daily energy consumption of the integrated water and fertilizer equipment in the greenhouse; K represents the water pump conversion efficiency; A gh,k represents the crop planting area of ​​the kth greenhouse, m 2 ; n represents the total number of greenhouse irrigation periods; K c,i represents the crop coefficient of the i-th crop; ET0 represents the reference evapotranspiration, mm, where ET0 is related to soil moisture p s related.

[0027]

[0028] In the formula, w h is the daily energy consumption of ventilation equipment in the greenhouse; h.f represents the total rated power of the fth greenhouse exhaust fan, kW; K h.f K represents the proportion of the number of exhaust fans in the entire greenhouse working in the time period t. h.f ∈[0,1], where K h.f The concentration of toxic and harmful gases in the greenhouse t related.

[0029]

[0030] In the formula, w b Daily energy consumption of supplementary lighting equipment in the greenhouse; b.f represents the total rated power of the fth greenhouse fill light, kW; K b.f Indicates the proportion of the number of supplementary lights working in the entire greenhouse during the t period, K b.f ∈[0,1], where K b.f The light intensity in the greenhouse is L t related.

[0031]

[0032] In the formula, w d is the daily energy consumption of the carbon dioxide generator in the greenhouse; p d.f represents the total rated power of the fth greenhouse carbon dioxide generator, kW; K d.fK represents the proportion of the number of working carbon dioxide generators in the entire greenhouse during the time period t, d.f ∈[0, 1], where K d.f The concentration of carbon dioxide in the greenhouse t related.

[0033] To ensure the normal use and service life of energy storage, energy storage must meet the following power constraints:

[0034] P ch.min ≤P ch (t)≤P ch.max (11)

[0035] P dis.min ≤P dis (t)≤P dis.max (12)

[0036] C min ≤C(t)≤C max (13)

[0037] Where: P ch.min and P ch.max are the minimum and maximum values ​​of charging power respectively; P dis.min and P dis.max are the minimum and maximum values ​​of discharge power respectively; C min and C max are the minimum and maximum values ​​of the energy storage capacity respectively.

[0038] Step 4) The inequality constraint is:

[0039] T c(min) ≤T c ≤T c(max) (14)

[0040] ρ s(min) ≤ρ s ≤ρ s(max) (15)

[0041] 0≤H t ≤H t(max) (16)

[0042] L t(min) ≤L t ≤L t(max) (17)

[0043] D t(min) ≤D t ≤D t(max) (18)

[0044] w ppg(min) ≤w ppg ≤wppg(max) (19)

[0045] A solar greenhouse energy-saving optimization control device, comprising:

[0046] The data acquisition module is used to collect environmental data; the data acquisition module includes a carbon dioxide concentration sensor, an indoor temperature and humidity sensor, a toxic and harmful gas concentration sensor, a light sensor, a soil moisture sensor and a surveillance camera. It is locally networked through WSN and then transmitted to the cloud server and storage device through a specific Internet device, thereby realizing real-time status perception.

[0047] The signal conditioning module is used to perform signal conditioning on the environmental data collected by the data acquisition module, and then transmit the conditioned environmental data to the analysis and processing module;

[0048] The analysis and processing module is used to use the environmental conditions for crop growth as inequality constraints and the conservation of electric energy as equality constraints to determine the boundary conditions, and finally use the Lagrange multiplier method to find the environmental parameters in each greenhouse under the optimal solution conditions. Based on this, a suitable hysteresis interval is set and compared with the received current greenhouse environmental parameters to obtain the pre-issued control instructions, which are sent to the controller module via the wireless network.

[0049] The controller module is used to receive control instructions from the analysis and processing module and control the execution output module.

[0050] The execution output module is used to change the operating status of each execution output device in the greenhouse according to the control instructions issued by the controller module.

[0051] The output devices include: water-fertilizer integrated equipment, carbon dioxide generator, exhaust fan, fill light, and air source heat pump.

[0052] The beneficial effects of the present invention are as follows: the present invention utilizes the characteristic of adjustable environmental parameters in a solar greenhouse, combines with the energy demand of agricultural production, and proposes a solar greenhouse energy-saving optimization control method and device, which uses new energy (solar energy) power generation as the basic energy source, comprehensively considers the local consumption of renewable energy while taking into account the network operation cost issue, and minimizes the system operation cost while ensuring the maximization of the benefits of agricultural products in the greenhouse. Compared with the previous system that considers a single optimization target, the advantages are more obvious.

[0053] The present invention controls environmental parameters within the optimal range suitable for crop growth through a sensor system, a control system, and an execution output system, and optimizes the output of a photovoltaic power generation system, so that the electricity cost required for the operation of a solar greenhouse production system is minimized, thereby improving energy-saving effects and reducing production costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] The present invention has the following accompanying drawings:

[0055] Figure 1 It is a schematic diagram of the structure of the solar greenhouse energy-saving optimization control device of the present invention.

[0056] Figure 2 It is a schematic diagram of the energy-saving optimization control strategy of the solar greenhouse of the present invention. DETAILED DESCRIPTION

[0057] The present invention is further described in detail below in conjunction with the accompanying drawings.

[0058] In order to make the purpose, technical solutions and advantages of the present invention more clear, specific implementation examples of the present invention are described below in conjunction with the accompanying drawings.

[0059] Figure 1 This is a diagram of the structure of the solar greenhouse energy-saving optimization control device of the present invention. Figure 1 As shown, the control device includes a data acquisition module (mainly including a carbon dioxide concentration sensor, an indoor temperature and humidity sensor, a toxic and harmful gas concentration sensor, a light sensor, a soil moisture sensor and a surveillance camera), a signal conditioning module, an analysis and processing module, a controller module, and an execution output module (water-fertilizer integrated equipment, a carbon dioxide generator, a fill light, an exhaust fan, an air source heat pump, etc.). The various data collected from the solar greenhouse are amplified and conditioned by the signal conditioning module and transmitted to the analysis and processing module. The analysis and processing module uses the established data model algorithm to find out the various environmental parameters under the optimal solution conditions, and compares them with the received current greenhouse environmental parameters to obtain a pre-issued control signal, which reaches the local controller module through the wireless network to control the working state of the local execution output device (water-fertilizer integrated equipment, carbon dioxide generator, exhaust fan, fill light, air source heat pump, etc.), for example: motor start and stop, fill light on and off.

[0060] Figure 2 This is a strategy diagram of the solar greenhouse energy-saving optimization control method of the present invention.

[0061] Specifically, greenhouse data is collected. In the case of the classic solar greenhouse model, for strongly correlated data, the greenhouse data and a large amount of historical data on the energy consumption of each corresponding device are used to fit the data using the least squares method to find the mapping relationship between greenhouse data and equipment energy consumption:

[0062]

[0063] In the formula, w c is the daily energy consumption of the heating equipment in the greenhouse; Q hp is the heating capacity; COP is the coefficient of performance; where Q hp and COP vs. greenhouse temperature T c and the air source heat pump outlet water temperature Ts1 Related; S fr Describes the defrost status. "0" indicates that the air source heat pump is in defrost status, and "1" indicates that the air source heat pump is not defrosted. vent is the power consumption of the exhaust fan; air is the air volume flow entering the air source heat pump, where the power consumption of the exhaust fan is P vent Determine the air volume flow rate q entering the air source heat pump air .

[0064]

[0065] In the formula, w s is the daily energy consumption of the integrated water and fertilizer equipment in the greenhouse; K represents the water pump conversion efficiency; A gh,k represents the crop planting area of ​​the kth greenhouse, m 2 ; n represents the total number of greenhouse irrigation periods; K c,i represents the crop coefficient of the i-th crop; ET0 represents the reference evapotranspiration, mm, where ET0 is related to soil moisture p s related.

[0066]

[0067] In the formula, w h is the daily energy consumption of ventilation equipment in the greenhouse; h.f represents the total rated power of the fth greenhouse exhaust fan, kW; K h.f K represents the proportion of the number of exhaust fans in the entire greenhouse working in the time period t. h.f ∈[0,1], where K h.f The concentration of toxic and harmful gases in the greenhouse t related.

[0068]

[0069] In the formula, w b Daily energy consumption of supplementary lighting equipment in the greenhouse; b.f represents the total rated power of the fth greenhouse fill light, kW; K b.f Indicates the proportion of the number of supplementary lights working in the entire greenhouse during the t period, K b.f ∈[0, 1], where K b.f The light intensity in the greenhouse is L t related.

[0070]

[0071] In the formula, w d is the daily energy consumption of the carbon dioxide generator in the greenhouse; p d.frepresents the total rated power of the fth greenhouse carbon dioxide generator equipment, kW; K d.f K represents the proportion of the number of working carbon dioxide generators in the entire greenhouse during the time period t, d.f ∈[0, 1], where K d.f The concentration of carbon dioxide in the greenhouse t related.

[0072] Specifically, since different crops have different requirements for environmental conditions, in order to promote the growth and development of plants and thus obtain high quality and high yield, the environmental condition constraints for crop growth are taken as inequality constraints, which leads to the following inequality constraints:

[0073] T c(min) ≤T c ≤T c(max)

[0074] ρ s(min) ≤ρ s ≤ρ s(max)

[0075] 0≤H t ≤H t(max)

[0076] L t(min) ≤L t ≤L t(max)

[0077] D t(min) ≤D t ≤D t(max)

[0078] w ppg(min) ≤w ppg ≤w ppg(max)

[0079] Specifically, according to the models and performance of various photovoltaic panels, the mapping relationship between outdoor environmental parameters and the total output of photovoltaic panels is determined, and then the load and photovoltaic output are integrated to obtain the final objective function:

[0080] F=minf=w pg (T c , H t , L t , s , D t 、T AC , G AC )×p

[0081] Where, F is the minimum electricity cost of the solar greenhouse; W pg is the electric energy transmitted by the power grid to the park; p is the electricity price.

[0082] According to the law of energy conservation, the equality constraint is:

[0083] w pg =w all -w ppg -C

[0084] w all =∑w c +w s +w h +w b +w d +w others

[0085] In the formula, w all is the total amount of electrical energy used by the load in the greenhouse; w ppg is the total daily output of photovoltaic power; C is the power of the energy storage device (battery). c is the daily energy consumption of the heating equipment in the greenhouse; w s is the daily energy consumption of the water-fertilizer integrated equipment in the greenhouse; w h is the daily energy consumption of ventilation equipment in the greenhouse; w b Daily energy consumption of supplementary lighting equipment in the greenhouse; w d is the daily energy consumption of the carbon dioxide generator in the greenhouse; w others is the daily energy consumption of sensor equipment in the greenhouse (constant).

[0086] Among them, the total daily output of photovoltaic power meets the following requirements:

[0087]

[0088] w ppg(min) ≤w ppg ≤w ppg(max)

[0089] Battery charging and discharging meets:

[0090]

[0091] P ch.min ≤P ch (t)≤P ch.max

[0092] P dis.min ≤P dis (t)≤P dis.max

[0093] C min ≤C(t)≤C max

[0094] By using the Lagrange multiplier method and considering the constraints, the environmental parameters in the greenhouse under the optimal solution conditions are obtained. Based on this, the appropriate hysteresis interval is set and compared with the received current environmental parameters in the greenhouse to obtain the pre-issued control instructions.

[0095] Specifically, the control instruction reaches the execution output module through the wireless network, and the working state of the local execution device is controlled according to the control instruction received by the device driver.

[0096] The above implementation modes are only used to illustrate the present invention, but not to limit the present invention. Ordinary technicians in the relevant technical field can make various changes and modifications without departing from the essence and scope of the present invention. Therefore, all equivalent technical solutions also belong to the protection scope of the present invention.

[0097] The contents not described in detail in this specification belong to the prior art known to professional and technical personnel in this field.

Claims

1. A solar greenhouse energy-saving optimization control method, characterized in that: The steps include: 1) Collect environmental parameters in the greenhouse and perform signal conditioning; 2) After signal conditioning, in the case of the classic solar greenhouse model, for strongly correlated data, the historical data of greenhouse environmental parameters and energy consumption of corresponding equipment are used to fit the data based on the principle of least squares method to find the mapping relationship between greenhouse environmental parameters and equipment energy consumption; 3) According to the model and performance of photovoltaic panels, the mapping relationship between outdoor environmental parameters and the total output of photovoltaic panels is determined, and then the load and photovoltaic output are integrated to minimize the electricity cost and obtain the final objective function; 4) The environmental condition constraints for crop growth are used as inequality constraints, and the conservation of electric energy is used as an equality constraint to determine the boundary conditions. Finally, the Lagrange multiplier method is used to solve the problem, and the environmental parameters of each greenhouse under the optimal solution conditions are obtained. The hysteresis interval is set accordingly, and compared with the received current greenhouse environmental parameters, and the optimal greenhouse environmental parameters are output; Step 3) The objective function is defined as: F=minf=w pg (T c 、H t 、L t 、ρ s 、D t 、T AC 、G AC )×p (1) Where, F is the minimum electricity cost of the solar greenhouse; w pg is the electric energy transmitted from the power grid to the greenhouse; p is the electricity price; T c is the temperature in the greenhouse; H t is the concentration of toxic and harmful gases in the greenhouse; L t is the light intensity in the greenhouse; ρ s D is soil moisture; t is the carbon dioxide concentration in the greenhouse; T AC is the operating temperature of the solar panel; G AC Indicates the actual outdoor light intensity; Step 4) The equality constraint is: w pg =w all -w ppg -C (2) In all =∑w c +in s +in h +in b +in d +in others (3) In the formula, w all is the total amount of electrical energy used by the load in the greenhouse; w ppg is the total daily output of photovoltaic power; C is the power of energy storage device; w c is the daily energy consumption of the heating equipment in the greenhouse; w s is the daily energy consumption of the water-fertilizer integrated equipment in the greenhouse; w h is the daily energy consumption of ventilation equipment in the greenhouse; w b Daily energy consumption of supplementary lighting equipment in the greenhouse; w d is the daily energy consumption of the carbon dioxide generator in the greenhouse; w others is the daily energy consumption of the sensor equipment in the greenhouse, which is a constant; Step 4) The inequality constraint is: T c(min) ≤T c ≤T c(max) (14) r s(min) ≤ρ s ≤ρ s(max) (15) 0≤H t ≤H t(max) (16) L t(min) ≤L t ≤L t(max) (17) D t(min) ≤D t ≤D t(max) (18) In ppg(min) ≤in ppg ≤in ppg(max) (19)。 2. The solar greenhouse energy-saving optimization control method according to claim 1, characterized in that: The mapping relationships include: the relationship between the temperature in the greenhouse and the daily energy consumption of the heating equipment, the relationship between the soil moisture condition and the daily energy consumption of the water-fertilizer integrated equipment, the relationship between the concentration of toxic and harmful gases in the greenhouse and the daily energy consumption of the ventilation equipment, the relationship between the light intensity in the greenhouse and the daily energy consumption of the supplementary lighting equipment, and the relationship between the carbon dioxide concentration in the greenhouse and the daily energy consumption of the carbon dioxide generator.

3. The solar greenhouse energy-saving optimization control method according to claim 1, characterized in that: In the formula, w ppg is the total daily output of photovoltaic power; P STC G is the maximum test power under standard test conditions; AC Indicates the actual outdoor light intensity, kW / m 2 ; G STC is the outdoor light intensity under standard test conditions, with a value of 1kW / m 2 ; k is the power temperature coefficient, the value is -0.43% / k; T AC is the operating temperature of the photovoltaic panel; T STC The reference temperature under standard test conditions is 25°C; the standard test conditions are solar radiation intensity G STC =1kW / m 2 , battery surface temperature T STC The temperature is 25℃, and the point-to-atmosphere optical quality is AM1.5; Where P ch (t) and P dis (t) are the charging and discharging power of the battery at time t; h ch and h dis are the battery charging and discharging efficiency respectively.

4. The solar greenhouse energy-saving optimization control method according to claim 1, characterized in that: In the formula, w c is the daily energy consumption of the heating equipment in the greenhouse; Q hp is the heating capacity; COP is the coefficient of performance; where Q hp and COP vs. greenhouse temperature T c and the air source heat pump outlet water temperature T s1 Related; S fr Describes the defrost status, "0" indicates that the air source heat pump is in defrost state, "1" indicates that the air source heat pump is not defrosted; P vent is the power consumption of the exhaust fan; air is the air volume flow entering the air source heat pump, where the power consumption of the exhaust fan is P vent Determine the air volume flow rate q entering the air source heat pump a i r ; In the formula, w s is the daily energy consumption of the integrated water and fertilizer equipment in the greenhouse; K represents the water pump conversion efficiency; A gh,k represents the crop planting area of ​​the kth greenhouse, m 2 ; n represents the total number of greenhouse irrigation periods; K c,i represents the crop coefficient of the i-th crop; ET0 represents the reference evapotranspiration, mm, where ET0 is related to soil moisture p s related; In the formula, w h is the daily energy consumption of ventilation equipment in the greenhouse; h.f represents the total rated power of the fth greenhouse exhaust fan; K h.f K represents the proportion of the number of exhaust fans in the entire greenhouse working in the time period t. h.f ∈[0,1], where K h.f The concentration of toxic and harmful gases in the greenhouse t related; In the formula, w b Daily energy consumption of supplementary lighting equipment in the greenhouse; b.f represents the total rated power of the fth greenhouse fill light; K b.f Indicates the proportion of the number of supplementary lights in the entire greenhouse working in the time period t, K b.f ∈[0,1], where K b.f The light intensity in the greenhouse is L t related; In the formula, w d is the daily energy consumption of the carbon dioxide generator in the greenhouse; p d.f represents the total rated power of the fth greenhouse carbon dioxide generator; K d.f K represents the proportion of the number of working carbon dioxide generators in the entire greenhouse during the time period t, d.f ∈[0,1], where K d.f The concentration of carbon dioxide in the greenhouse t related.

5. The solar greenhouse energy-saving optimization control method according to claim 1, characterized in that: To ensure the normal use and service life of energy storage, energy storage must meet the following power constraints: P ch×min ￡P ch (t)￡P ch×max (11) P dis×min ￡P dis (t)￡P dis×max (12) C min ￡C(t)￡C max (13) Where: P ch×min and P ch×max are the minimum and maximum values ​​of charging power respectively; P dis×min and P dis×max are the minimum and maximum values ​​of discharge power respectively; C min and C max are the minimum and maximum values ​​of the energy storage capacity respectively.

6. A solar greenhouse energy-saving optimization control device using the solar greenhouse energy-saving optimization control method of claim 1, characterized in that: include: A data acquisition module, used for collecting environmental data; The signal conditioning module is used to perform signal conditioning on the environmental data collected by the data acquisition module, and then transmit the conditioned environmental data to the analysis and processing module; The analysis and processing module is used to use the environmental condition constraints of crop growth as inequality constraints and the conservation of electric energy as equality constraints to determine the boundary conditions, and finally use the Lagrange multiplier method to find the environmental parameters of each greenhouse under the optimal solution conditions, and set the hysteresis interval accordingly, and compare it with the received current greenhouse environmental parameters to obtain the pre-issued control instructions, which are sent to the controller module through the wireless network; The controller module is used to receive control instructions from the analysis and processing module and control the execution output module; The execution output module is used to change the operating status of each execution output device in the greenhouse according to the control instructions issued by the controller module.

7. The solar greenhouse energy-saving optimization control device according to claim 6, characterized in that: The data acquisition module includes: carbon dioxide concentration sensor, indoor temperature and humidity sensor, toxic and harmful gas concentration sensor, light sensor, soil moisture sensor and surveillance camera. It is locally networked through WSN and then transmitted to cloud server and storage device through Internet access device, so as to realize real-time status perception. The executive output equipment includes: water-fertilizer integrated equipment, carbon dioxide generator, exhaust fan, fill light and air source heat pump.

Images