Multi-energy complementary heat supply greenhouse system

Abstract

The invention discloses a multi-energy complementary heat supply greenhouse system. According to the invention, by integrating solar energy, geothermal energy, biomass energy and other multi-element heat sources with the bionic porous heat energy storage module, the stability and complementarity of energy supply are significantly improved. The solar module efficiently collects heat when illumination is sufficient, the geothermal energy module provides stable basic heat, the biomass energy module can flexibly supplement energy consumption gaps in cloudy and rainy days or at night, and the three modules are cooperatively input through a heat exchange interface of the bionic porous storage module, so that the problem that single energy is limited by climate and time is effectively solved; the running state of each module is monitored in real time through a multi-parameter sensor, execution equipment such as an electric valve and a circulating pump is accurately adjusted, the input proportion of different heat sources and the heat release rhythm of the storage module are dynamically balanced, and meaningless loss of heat energy in the transmission and storage process is reduced; and a more stable and controllable environmental condition is created for the growth of greenhouse crops.

Description

Technical Field

[0001] This invention belongs to the field of greenhouse heating technology, specifically a multi-energy complementary heating greenhouse system. Background Technology

[0002] A greenhouse heating system is a heat supply and regulation system set up in greenhouse agriculture to maintain a suitable temperature environment for crop growth. It is one of the important facilities for achieving efficient agricultural production throughout the year. This system typically consists of a heat source (such as a boiler, heat pump, solar collector, or geothermal equipment), a heating network, temperature control devices, and terminal heat dissipation equipment (such as hot water pipes, heating cables, or warm air blowers). It uses automated control technology to regulate the temperature distribution within the greenhouse to meet the differentiated thermal requirements of different crops. The design of the heating system must comprehensively consider factors such as greenhouse structure, local climate conditions, energy type, and crop type to achieve energy-efficient, stable, and reliable operation. Modern greenhouse heating systems often incorporate intelligent monitoring and Internet of Things (IoT) technology to achieve remote control and energy consumption optimization. They are widely used in facility agriculture fields such as vegetables, flowers, and seedling cultivation, playing a vital role in improving agricultural product yield and quality and promoting the modernization of agriculture.

[0003] However, existing technologies mostly rely on a single energy source for heating, which is easily affected by climate and time constraints, leading to unstable supply. Furthermore, the lack of a multi-source coordination mechanism makes it difficult to flexibly complement each other. Traditional thermal energy storage methods have low heat exchange efficiency and large transmission and storage losses. Control methods are crude and it is difficult to dynamically adjust the rhythm of energy input and release. At the same time, they rely on external power grids for power supply, resulting in insufficient system autonomy. Summary of the Invention

[0004] The purpose of this invention is to provide a multi-energy complementary heating greenhouse system in order to solve the problems mentioned above.

[0005] The technical solution adopted in this invention is as follows: a multi-energy complementary heating greenhouse system, characterized in that: the system includes: a solar heating module, a geothermal heating module, a biomass heating module, a wind power supply module, an intelligent control system, and a biomimetic porous thermal energy storage and release module;

[0006] The biomimetic porous thermal energy storage and release module is internally equipped with: a phase change material module, a heat exchanger module, and an intelligent sensing and release module;

[0007] The output end of the copper circulation pipeline of the solar heating module is connected to the first input interface of the heat exchanger of the biomimetic porous thermal energy storage and release module.

[0008] The hot water outlet of the geothermal energy heating module heat pump unit is connected to the second input interface of the heat exchanger.

[0009] The hot water output terminal of the biomass energy heating module boiler is connected to the third input interface of the heat exchanger, and the three together serve as the heat source input for the thermal energy storage module.

[0010] The AC output terminal of the wind power supply module inverter is connected to the power supply terminal of the intelligent control system PLC, and the power is supplied to power equipment such as solar circulating pump, geothermal submersible pump, and biomass conveyor.

[0011] The temperature sensors of the intelligent control system are connected to the temperature measurement points of the solar thermal storage tank, the geothermal heat pump outlet pipe, and the biomass boiler exhaust outlet; the flow sensor is connected to the heat exchanger inlet circulation pipe section; and the pressure sensor is connected to the geothermal glycol heat exchange loop.

[0012] The intelligent control system's electric regulating valves are connected to the valves in each input circuit of the heat exchanger, the frequency converter is connected to the solar circulating pump motor controller, and the electromagnetic reversing valve is connected to the geothermal water circuit switching valve to achieve regulation. The output end of the heat exchanger is connected to the greenhouse's end-of-line heat dissipation equipment through the heating network.

[0013] In a preferred embodiment, the solar heating module internally comprises an all-glass vacuum tube collector, a stainless steel storage tank, a copper circulation pipeline, and a shielded circulation pump. The all-glass vacuum tube collector consists of 50 Φ58×1800mm vacuum tubes, each containing an inner tube made of high borosilicate glass and an outer tube made of aluminized carbon nitride film, converting solar energy into heat energy through thermosiphon principle. The stainless steel storage tank has a capacity of 5 cubic meters and a double-layer structure, with an inner layer of 304 stainless steel and an outer layer of 50mm thick polyurethane insulation, used to store the hot water generated by the collector. The copper circulation pipeline connects the collector and the storage tank, with a diameter of DN32, a wall thickness of 1.5mm, and a 20mm thick layer of rubber-plastic insulation to reduce heat loss. The shielded circulation pump has a power of 2.2kW and a head of 15m, installed at the pipeline return inlet, continuously circulating the hot water from the collector to the storage tank.

[0014] In a preferred embodiment, the geothermal heating module internally includes U-shaped buried heat exchange pipes, a water-to-water heat pump unit, ethylene glycol heat exchange medium, and a dual-well reinjection system. The U-shaped buried heat exchange pipes are made of PE100 material with a nominal pressure of 1.6 MPa, a pipe diameter of DN32, a single-hole depth of 120 m, and a total of 20 sets of buried holes arranged at 4 m intervals, connected to form a heat exchange network via horizontal manifolds. The water-to-water heat pump unit, model RW-100, has an input power of 25 kW and a COP value of 4.2, and can raise the low-temperature heat energy extracted from the buried pipes at 10-15℃ to a heating temperature of 45-50℃. The ethylene glycol heat exchange medium is a 30% concentration aqueous solution with a freezing point of -15℃, filling the closed loop between the buried pipes and the heat pump evaporator. The dual-well reinjection system includes a depth of 150 m and a water output of 20 m³ / h. 3A pumping well with a depth of 140m and a reinjection volume of 18m³ / h. 3 The reinjection wells, with a capacity of / h, use a 7.5kW submersible pump to extract groundwater, which is then recharged after heat exchange in a plate heat exchanger to maintain groundwater level balance.

[0015] In a preferred embodiment, the biomass heating module internally includes a chain grate biomass boiler, a reinforced concrete fuel silo, a screw conveyor, and a bag filter. The chain grate biomass boiler has a rated thermal power of 2.8MW, employs an inclined chain grate with a length of 3m and a width of 1.5m, and can burn granular biomass fuel with a diameter of 6-8mm and a calorific value of 16-18MJ / kg. The reinforced concrete fuel silo has a volume of 30 cubic meters, with 10mm thick anti-corrosion ceramic tiles lining the inner wall. An automatic weighing sensor with an accuracy of ±0.5% is installed at the top to monitor fuel levels. The screw conveyor has a DN200 pipe diameter, a 3kW motor, and a 30° inclination angle, uniformly conveying the granular material from the fuel silo to the boiler feed inlet. The bag filter is a pulse-jet type with a filtration area of ​​120㎡. The filter bags are made of PPS needle-punched felt, with a temperature resistance of 190℃ and a dust removal efficiency of 99%. The dust content in the treated flue gas is ≤30mg / m³. 3 .

[0016] In a preferred embodiment, the wind power supply module internally houses a permanent magnet synchronous wind turbine, a lithium iron phosphate battery pack, a sine wave inverter, and an outdoor waterproof combiner box. The permanent magnet synchronous wind turbine is model FD-500, with a rated power of 500W, a rotor diameter of 3.2m, and is made of 3-blade fiberglass. Its starting wind speed is 3m / s. It is fixed to a 12m high steel tower via flanges. The tower wall thickness is 4mm, and the bottom diameter is 200mm. The lithium iron phosphate battery pack consists of 16 12V / 100Ah batteries connected in series, with a total voltage of 192V and a capacity of 100Ah. It is housed in an IP65-rated waterproof battery box and has a cycle life of ≥2000 cycles. The sine wave inverter has a power of 1000W and a conversion efficiency of 92%, converting battery DC power to 220V / 50Hz AC power; the outdoor waterproof combiner box contains 6 input terminals, each with a fuse and 1 output terminal, and is coated with 0.2mm thick polyurethane anti-corrosion paint to collect the output current of multiple wind turbines.

[0017] In a preferred embodiment, the intelligent control system internally includes a Siemens S7-1200 PLC controller, a multi-parameter sensor network, an electric actuator assembly, and a LoRa wireless communication module. The Siemens S7-1200 PLC controller is equipped with a CPU 1214C, integrating 6DI / 4DO / 2AI inputs, and expanding with three analog input modules, each with 8AI inputs, for processing signals such as temperature, pressure, and flow rate. The multi-parameter sensor network includes Pt100 temperature sensors with an accuracy of ±0.5℃, deployed at the thermal storage tank, buried pipes, and boiler outlet; and turbine flow meters with an accuracy of ±1% and a range of 0-50m. 3 The system includes a pressure transmitter (0-1MPa range, ±0.2% accuracy) installed in the circulation pipeline, used to monitor the pressure of the heat pump system. The electric actuator assembly includes an electric regulating valve (DN32, ±1% adjustment accuracy), a frequency converter (0-50Hz frequency range) for controlling the circulation pump speed, an electromagnetic directional valve for controlling the water circuit switching in the geothermal energy system, and a LoRa wireless communication module (model E32-433T20D) with a transmission distance of 3km, uploading field data to an industrial tablet PC and a 7-inch touchscreen monitoring terminal for remote monitoring and automatic adjustment of the heating system.

[0018] In a preferred embodiment, the porous material core module internally incorporates a biomimetic porous ceramic substrate, honeycomb-like microchannels, a highly interconnected pore structure, and temperature and corrosion resistance. The biomimetic porous ceramic substrate, primarily composed of alumina, is manufactured through a high-temperature sintering process at 1200℃, forming a three-dimensional interconnected pore network. The microchannels are arranged in a regular honeycomb pattern, with a porosity controlled between 75% and 85%, and a pore size distribution concentrated in the range of 0.1 to 1 mm. This structure ensures both the heat flow permeation path within the material and provides stable mechanical support. The highly interconnected pore structure is characterized by interconnected channels with a connectivity rate exceeding 90%, avoiding heat storage blind spots caused by localized dead pores. The temperature and corrosion resistance is determined by the chemical composition of the ceramic substrate, with alumina comprising over 85% and silicon oxide 10%. It can withstand temperature fluctuations from -50℃ to 800℃. In high-humidity greenhouse environments, the oxide film formed on the surface effectively resists the erosion of acid mist and moisture.

[0019] In a preferred embodiment, the phase change material module internally comprises an organic phase change medium, an inorganic phase change medium, a vacuum impregnation filling layer, and a stability regulating component. The organic phase change medium is a decanoic acid-stearic acid eutectic, with a phase change temperature range of 20-50℃, a latent heat of phase change of 150-200 kJ / kg, and stable chemical properties without supercooling. The inorganic phase change medium is sodium sulfate decahydrate, with a phase change temperature of 50-80℃ and a latent heat of 250-300 kJ / kg, suitable for high-temperature thermal storage applications. Both media are filled into the pores of the porous ceramic using a vacuum impregnation process: first, the porous substrate is evacuated to -0.1 MPa to remove air; then, the molten phase change material is pressed into the pores at a pressure of 0.5 MPa, achieving a filling rate of 92%–95%. The stability regulating components include nucleating agent borax and thickening agent silica aerogel. The amount of borax added is 0.5% to 1% of the mass of the phase change material, which is used to suppress supercooled crystallization. The amount of silica aerogel added is 1% to 2%, which prevents phase separation of hydrated salts by forming a network structure.

[0020] In a preferred embodiment, the heat exchanger module internally comprises miniature copper pipes, a serpentine arrangement, surface spiral fins, and a multi-loop parallel structure. The miniature copper pipes are made of T2 copper, with a diameter of 1–3 mm and a wall thickness of 0.2–0.5 mm, and are arranged longitudinally along the porous material layer. The pipes extend in a serpentine path within the phase change material layer, with adjacent pipes spaced 5–10 mm apart, extending the heat transfer path within the material. Surface spiral fins are machined onto the outer surface of the pipes, with a fin height of 0.5 mm and a spacing of 1 mm, formed by turning, increasing the contact area between the pipes and the phase change material. The multi-loop parallel structure divides the heat exchanger into 4–8 independent sub-loops, each containing 20–30 miniature pipes, connected to the heating network interfaces of different areas of the greenhouse. Each loop inlet is equipped with an electrically adjustable valve, controlling the flow distribution of each loop through valve opening.

[0021] In a preferred embodiment, the intelligent sensing and release module collects the ambient temperature sequence T in real time through temperature sensors distributed in different areas of the greenhouse. env ={t1,t2,...,t n Simultaneously, external energy input data such as solar irradiance S, ground source heat pump operating power Pgeo, and biomass boiler heating rate Qbio are input. After preprocessing (moving average filtering to eliminate noise), these data are input into a temperature prediction model based on LSTM (Long Short-Term Memory Network). This model predicts the greenhouse temperature change trend T^pred={t^n+1,t^n+2,...,t^n+120} within the next 2 hours using historical 3-hour data (window length L=180 minutes).

[0022] Predicted results and the set target temperature T set(Determined by the growth requirements of the crop, such as the suitable temperature for tomato growth being 18-25℃) After comparison, the optimal heat release rate q is calculated using the Model Predictive Control (MPC) algorithm. release This rate must simultaneously satisfy the remaining energy storage E of the phase change material. PCM Constraints (to avoid excessive release leading to energy depletion) and the maximum transfer power Q of the heat exchanger max The limitation is determined by the thermal conductivity of the material in the micropipe network. Ultimately, the system achieves q by adjusting the opening of the heat exchanger valves (continuously adjustable from 0% to 100%). release The system ensures accurate execution and feeds back the deviation between the actual release amount and the predicted value to the LSTM model, dynamically updating the prediction parameters to improve long-term prediction accuracy.

[0023] Wherein: the hidden state update equation of the LSTM temperature prediction model is:

[0024] h t =σ g (W gh h t-1 +W gx x t +b g )⊙tanh(W ch h t-1 +W cx x t +b c )+(1-σ g (W gh h t-1 +W gx x t +b g ))⊙h t-1 ;

[0025] Where: ht represents the hidden state vector at time t (dimension d) h =64, representing an abstract characteristic of historical temperature changes;

[0026] x t The input vector at time t (containing T) env (t), S(t), P geo (t), Q bio (t), dimension d x =4); W gh W gx Represents the weight matrix of the gated unit (size d) h ×d h and d h ×d x );

[0027] W ch W cxRepresents the candidate state weight matrix (same size as before);

[0028] b g ,b c Represents the gating unit and the candidate state bias vector (dimension d) h );

[0029] σ g This represents the sigmoid activation function (output range [0,1], controlling the ratio of information forgotten to retained);

[0030] ⊙ indicates element-wise multiplication.

[0031] The objective function for model predictive control is calculated as follows:

[0032]

[0033] Where: N represents the prediction time domain (N = 120 minutes, corresponding to a 2-hour prediction window);

[0034] λ1 represents the temperature deviation penalty coefficient (with a value of 10^3103, prioritizing temperature stability);

[0035] λ2 represents the penalty coefficient for changes in release rate (valued at 10^2102 to avoid frequent actuator movements);

[0036] Tpred(t+k|t) represents the temperature at time t+k predicted based on data at time t;

[0037] q release (k|t) represents the rate of heat release at time t+k calculated from time t (unit: kW).

[0038] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0039] 1. This invention significantly improves the stability and complementarity of energy supply by integrating multiple heat sources such as solar energy, geothermal energy, and biomass energy with a biomimetic porous thermal energy storage module. The solar energy module efficiently collects heat when there is sufficient sunlight, the geothermal energy module provides stable basic heat, and the biomass energy module can flexibly supplement the energy gap on cloudy days or at night. The three are input in coordination through the heat exchange interface of the biomimetic porous storage module, effectively solving the shortcomings of single energy sources being limited by climate and time, ensuring that the greenhouse has a continuous supply of heat energy around the clock, and avoiding the temperature fluctuation problem caused by energy interruption in traditional single heating methods.

[0040] 2. In this invention, multi-parameter sensors monitor the operating status of each module in real time, precisely adjusting actuators such as electric valves and circulating pumps to dynamically balance the input ratio of different heat sources and the heat release rhythm of the storage module, reducing unnecessary heat loss during transmission and storage. The wind power supply module provides power support for the control system and power equipment, reducing dependence on the external power grid and further enhancing the system's autonomy. The biomimetic porous storage module, with its efficient heat exchange structure, can quickly absorb heat from multiple heat sources and release it on demand, resulting in a significantly higher heat utilization rate than traditional single storage methods. Ultimately, this achieves highly efficient coordination throughout the entire process from energy collection, storage to release, creating more stable and controllable environmental conditions for greenhouse crop growth. Attached Figure Description

[0041] Figure 1 This is an overall system block diagram of the present invention;

[0042] Figure 2 This is a system block diagram of the biomimetic porous thermal energy storage and release module in this invention. Detailed Implementation

[0043] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0044] Reference Figure 1-2 ,

[0045] A multi-energy complementary heating greenhouse system includes: a solar heating module, a geothermal heating module, a biomass heating module, a wind power supply module, an intelligent control system, and a biomimetic porous heat storage and release module;

[0046] The internal components of the biomimetic porous thermal energy storage and release module include: a phase change material module, a heat exchanger module, and an intelligent sensing and release module.

[0047] The output end of the copper circulation pipeline of the solar heating module is connected to the first input interface of the heat exchanger of the biomimetic porous thermal energy storage and release module.

[0048] The hot water outlet of the geothermal energy heating module heat pump unit is connected to the second input interface of the heat exchanger.

[0049] The hot water output of the biomass energy heating module boiler is connected to the third input interface of the heat exchanger, and the three together serve as the heat source input for the thermal energy storage module.

[0050] The AC output terminal of the wind power supply module inverter is connected to the power supply terminal of the intelligent control system PLC, and then supplies power to power equipment such as solar circulating pumps, geothermal submersible pumps, and biomass conveyors.

[0051] The temperature sensors of the intelligent control system are connected to the temperature measurement points of the solar thermal storage tank, the geothermal heat pump outlet pipe, and the biomass boiler exhaust outlet; the flow sensor is connected to the inlet circulation pipe section of the heat exchanger; and the pressure sensor is connected to the geothermal glycol heat exchange loop.

[0052] The intelligent control system's electric regulating valves connect to the valves in each input circuit of the heat exchanger, the frequency converter connects to the solar circulating pump motor controller, and the electromagnetic reversing valve connects to the geothermal water circuit switching valve to achieve regulation. The output end of the heat exchanger is connected to the greenhouse's end-of-line heat dissipation equipment via a heating network.

[0053] The solar heating module internally consists of an all-glass vacuum tube collector, a stainless steel storage tank, a copper circulation pipeline, and a shielded circulation pump. The all-glass vacuum tube collector comprises 50 Φ58×1800mm vacuum tubes. Each tube has an inner tube made of high borosilicate glass and an outer tube with an aluminized carbon nitride film, converting solar energy into heat energy through thermosiphon principle. The stainless steel storage tank has a capacity of 5 cubic meters and a double-layer structure: an inner layer of 304 stainless steel and an outer layer of 50mm thick polyurethane insulation, used to store the hot water produced by the collector. The copper circulation pipeline connects the collector and the storage tank. It has a diameter of DN32, a wall thickness of 1.5mm, and is wrapped with 20mm thick rubber-plastic insulation to reduce heat loss. The shielded circulation pump has a power of 2.2kW and a head of 15m, installed at the return inlet of the pipeline, continuously circulating the hot water from the collector to the storage tank.

[0054] The geothermal heating module internally includes U-shaped buried heat exchange pipes, a water-to-water heat pump unit, ethylene glycol heat exchange medium, and a dual-well reinjection system. The U-shaped buried heat exchange pipes are made of PE100 material with a nominal pressure of 1.6MPa, a diameter of DN32, and a single-hole depth of 120m. A total of 20 sets of buried holes are arranged, spaced 4m apart, and connected to form a heat exchange network via horizontal manifolds. The water-to-water heat pump unit, model RW-100, has an input power of 25kW and a COP of 4.2, and can raise the low-temperature heat energy extracted from the buried pipes (10-15℃) to a heating temperature of 45-50℃. The ethylene glycol heat exchange medium is a 30% concentration aqueous solution with a freezing point of -15℃, filling the closed loop between the buried pipes and the heat pump evaporator. The dual-well reinjection system includes a depth of 150m and a flow rate of 20m³ / h. 3 A pumping well with a depth of 140m and a reinjection volume of 18m³ / h. 3 The reinjection wells, with a capacity of / h, use a 7.5kW submersible pump to extract groundwater, which is then recharged after heat exchange in a plate heat exchanger to maintain groundwater level balance.

[0055] The biomass heating module internally includes a chain grate biomass boiler, a reinforced concrete fuel silo, a screw conveyor, and a bag filter. The chain grate biomass boiler has a rated thermal power of 2.8MW, employing an inclined chain grate with a length of 3m and a width of 1.5m. It can burn granular biomass fuel with a diameter of 6-8mm and a calorific value of 16-18MJ / kg. The reinforced concrete fuel silo has a volume of 30 cubic meters, with 10mm thick anti-corrosion ceramic tiles lining the inner walls. An automatic weighing sensor with an accuracy of ±0.5% monitors the fuel level at the top. The screw conveyor has a DN200 pipe diameter, a 3kW motor, and a 30° inclination angle, uniformly conveying the granular material from the fuel silo to the boiler feed inlet. The bag filter uses a pulse-jet cleaning system with a filtration area of ​​120㎡. The filter bags are made of PPS needle-punched felt, resistant to temperatures up to 190℃, and have a dust removal efficiency of 99%, resulting in a dust content in the treated flue gas ≤30mg / m³. 3 .

[0056] The wind power module internally houses a permanent magnet synchronous wind turbine, a lithium iron phosphate battery pack, a sine wave inverter, and an outdoor waterproof combiner box. The permanent magnet synchronous wind turbine, model FD-500, has a rated power of 500W, a rotor diameter of 3.2m, and is made of 3-blade fiberglass. It has a starting wind speed of 3m / s and is fixed to a 12m high steel tower via flanges. The tower wall thickness is 4mm, and the bottom diameter is 200mm. The lithium iron phosphate battery pack consists of 16 12V / 100Ah batteries connected in series, with a total voltage of 192V and a capacity of 100Ah. It is housed in an IP65-rated waterproof battery box with a cycle life of ≥2000 cycles. The sine wave inverter has a power of 1000W and a conversion efficiency of 92%, converting battery DC power to 220V / 50Hz AC power; the outdoor waterproof combiner box contains 6 input terminals, each with a fuse and 1 output terminal, and is coated with 0.2mm thick polyurethane anti-corrosion paint to collect the output current of multiple wind turbines.

[0057] The intelligent control system internally includes a Siemens S7-1200 PLC controller, a multi-parameter sensor network, an electric actuator assembly, and a LoRa wireless communication module. The Siemens S7-1200 PLC controller is equipped with a CPU 1214C, integrating 6DI / 4DO / 2AI inputs, and expanding with three analog input modules, each with 8AI inputs, for processing signals such as temperature, pressure, and flow. The multi-parameter sensor network includes Pt100 temperature sensors with an accuracy of ±0.5℃, deployed in the thermal storage tank, underground pipes, and boiler outlet; and turbine flow meters with an accuracy of ±1% and a range of 0-50m. 3The system includes a pressure transmitter (0-1MPa range, ±0.2% accuracy) installed in the circulation pipeline, used to monitor the pressure of the heat pump system. The electric actuator assembly includes an electric regulating valve (DN32, ±1% adjustment accuracy), a frequency converter (0-50Hz frequency range) for controlling the circulation pump speed, an electromagnetic directional valve for controlling the water circuit switching in the geothermal energy system, and a LoRa wireless communication module (model E32-433T20D) with a transmission distance of 3km, uploading field data to an industrial tablet PC and a 7-inch touchscreen monitoring terminal for remote monitoring and automatic adjustment of the heating system.

[0058] The core module of the porous material features a biomimetic porous ceramic substrate, honeycomb-like microchannels, a highly interconnected pore structure, and temperature and corrosion resistance. The biomimetic porous ceramic substrate, primarily composed of alumina, is manufactured through a 1200℃ high-temperature sintering process, forming a three-dimensional interconnected pore network. The microchannels are arranged in a regular honeycomb pattern, with a porosity controlled between 75% and 85%, and a pore size distribution concentrated in the 0.1–1 mm range. This structure ensures both heat flow permeation pathways within the material and provides stable mechanical support. The highly interconnected pore structure is characterized by interconnected channels with a connectivity rate exceeding 90%, avoiding heat storage blind spots caused by localized dead pores. The temperature and corrosion resistance properties are determined by the chemical composition of the ceramic substrate, with alumina accounting for over 85% and silicon oxide for 10%. It can withstand temperature fluctuations from -50℃ to 800℃. In high-humidity greenhouse environments, the oxide film formed on the surface effectively resists the erosion of acid mist and moisture.

[0059] The phase change material module internally comprises an organic phase change medium, an inorganic phase change medium, a vacuum impregnation filling layer, and stability regulating components. The organic phase change medium is a decanoic acid-stearic acid eutectic, with a phase change temperature range of 20-50℃ and a latent heat of change of 150-200 kJ / kg. It exhibits chemical stability and no supercooling. The inorganic phase change medium is sodium sulfate decahydrate, with a phase change temperature of 50-80℃ and a latent heat of change of 250-300 kJ / kg, suitable for high-temperature thermal storage applications. Both media are filled into the pores of porous ceramics using a vacuum impregnation process: first, the porous substrate is evacuated to -0.1 MPa to remove air; then, the molten phase change material is pressed into the pores at a pressure of 0.5 MPa, achieving a filling rate of 92%–95%. The stability regulating components include nucleating agent borax and thickening agent silica aerogel. The amount of borax added is 0.5% to 1% of the mass of the phase change material, which is used to suppress supercooled crystallization. The amount of silica aerogel added is 1% to 2%, which prevents phase separation of hydrated salts by forming a network structure.

[0060] The heat exchanger module internally incorporates miniature copper pipes, a serpentine layout, surface spiral fins, and a multi-loop parallel structure. The miniature copper pipes, made of T2 copper, have a diameter of 1–3 mm and a wall thickness of 0.2–0.5 mm, and are arranged longitudinally along the porous material layer. Within the phase change material layer, the pipes extend in a serpentine path, with adjacent pipes spaced 5–10 mm apart, extending the heat transfer path within the material. Surface spiral fins, machined onto the outer surface of the pipes, are 0.5 mm high and spaced 1 mm apart, formed by turning, increasing the contact area between the pipes and the phase change material. The multi-loop parallel structure divides the heat exchanger into 4–8 independent sub-loops, each containing 20–30 miniature pipes, connected to the heating network interfaces of different areas of the greenhouse. Each loop inlet is equipped with an electrically adjustable valve, controlling the flow distribution within each loop through valve opening.

[0061] The intelligent sensing and release module collects the ambient temperature sequence T in real time through temperature sensors distributed in different areas of the greenhouse. env ={t1,t2,...,t n Simultaneously, external energy input data such as solar irradiance S, ground source heat pump operating power Pgeo, and biomass boiler heating rate Qbio are input. After preprocessing (moving average filtering to eliminate noise), these data are input into a temperature prediction model based on LSTM (Long Short-Term Memory Network). This model predicts the greenhouse temperature change trend T^pred={t^n+1,t^n+2,...,t^n+120} within the next 2 hours using historical 3-hour data (window length L=180 minutes).

[0062] Predicted results and the set target temperature T set (Determined by the growth requirements of the crop, such as the suitable temperature for tomato growth being 18-25℃) After comparison, the optimal heat release rate q is calculated using the Model Predictive Control (MPC) algorithm. release This rate must simultaneously satisfy the remaining energy storage E of the phase change material. PCM Constraints (to avoid excessive release leading to energy depletion) and the maximum transfer power Q of the heat exchanger max The limitation is determined by the thermal conductivity of the material in the micropipe network. Ultimately, the system achieves q by adjusting the opening of the heat exchanger valves (continuously adjustable from 0% to 100%). release The system ensures accurate execution and feeds back the deviation between the actual release amount and the predicted value to the LSTM model, dynamically updating the prediction parameters to improve long-term prediction accuracy.

[0063] Wherein: the hidden state update equation of the LSTM temperature prediction model is:

[0064] h t =σ g (W gh h t-1+W gx x t +b g )⊙tanh(W ch h t-1 +W cx x t +b c )+(1-σ g (W gh h t-1 +W gx x t +b g ))⊙h t-1 ;

[0065] Where: ht represents the hidden state vector at time t (dimension d) h =64, representing an abstract characteristic of historical temperature changes;

[0066] x t The input vector at time t (containing T) env (t), S(t), P geo (t), Q bio (t), dimension d x =4); W gh W gx Represents the weight matrix of the gated unit (size d) h ×d h and d h ×d x );

[0067] W ch W cx Represents the candidate state weight matrix (same size as before);

[0068] b g ,b c Represents the gating unit and the candidate state bias vector (dimension d) h );

[0069] σ g This represents the sigmoid activation function (output range [0,1], controlling the ratio of information forgotten to retained);

[0070] ⊙ represents element-wise multiplication.

[0071] The objective function for model predictive control is calculated as follows:

[0072]

[0073] Where: N represents the prediction time domain (N = 120 minutes, corresponding to a 2-hour prediction window);

[0074] λ1 represents the temperature deviation penalty coefficient (with a value of 10^3103, prioritizing temperature stability);

[0075] λ2 represents the penalty coefficient for changes in release rate (valued at 10^2102 to avoid frequent actuator movements);

[0076] Tpred(t+k|t) represents the temperature at time t+k predicted based on data at time t;

[0077] q release (k|t) represents the rate of heat release at time t+k calculated from time t (unit: kW).

[0078] From the above, we can conclude that:

[0079] This invention significantly improves the stability and complementarity of energy supply by integrating multiple heat sources such as solar energy, geothermal energy, and biomass energy with a biomimetic porous thermal energy storage module. The solar energy module efficiently collects heat when there is sufficient sunlight, the geothermal energy module provides stable basic heat, and the biomass energy module can flexibly supplement energy shortages on cloudy days or at night. The three are input in synergy through the heat exchange interface of the biomimetic porous storage module, effectively solving the shortcomings of single energy sources being limited by climate and time, ensuring that the greenhouse has a continuous supply of heat energy around the clock, and avoiding the temperature fluctuation problem caused by energy interruption in traditional single heating methods.

[0080] In this invention, multi-parameter sensors monitor the operating status of each module in real time, precisely adjusting actuators such as electric valves and circulating pumps to dynamically balance the input ratio of different heat sources and the heat release rhythm of the storage module, reducing unnecessary heat loss during transmission and storage. The wind power supply module provides power support for the control system and power equipment, reducing dependence on the external power grid and further enhancing the system's autonomy. The biomimetic porous storage module, with its efficient heat exchange structure, can quickly absorb heat from multiple heat sources and release it on demand, resulting in a significantly higher heat utilization rate than traditional single storage methods. Ultimately, this achieves highly efficient coordination throughout the entire process from energy collection, storage to release, creating more stable and controllable environmental conditions for greenhouse crop growth.

[0081] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the term "comprising" or any other variations thereof is intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0082] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A multi-energy complementary heating greenhouse system, characterized in that: The system includes: a solar heating module, a geothermal heating module, a biomass heating module, a wind power supply module, an intelligent control system, and a biomimetic porous thermal energy storage and release module; The biomimetic porous thermal energy storage and release module is internally equipped with: a phase change material module, a heat exchanger module, and an intelligent sensing and release module; The output end of the copper circulation pipeline of the solar heating module is connected to the first input interface of the heat exchanger of the biomimetic porous thermal energy storage and release module. The hot water outlet of the geothermal energy heating module heat pump unit is connected to the second input interface of the heat exchanger. The hot water output end of the biomass energy heating module boiler is connected to the third input interface of the heat exchanger, and the three together serve as the heat source input for the thermal energy storage module. The AC output terminal of the wind power supply module inverter is connected to the power supply terminal of the intelligent control system PLC, and is used to supply power to power equipment such as solar circulating pump, geothermal submersible pump, and biomass conveyor. The temperature sensors of the intelligent control system are connected to the temperature measurement points of the solar thermal storage tank, the geothermal heat pump outlet pipe, and the biomass boiler exhaust outlet; the flow sensor is connected to the heat exchanger inlet circulation pipe section; and the pressure sensor is connected to the geothermal glycol heat exchange loop. The intelligent control system's electric regulating valve is connected to the valves of each input circuit of the heat exchanger, the frequency converter is connected to the solar circulating pump motor controller, and the electromagnetic reversing valve is connected to the geothermal water circuit switching valve to achieve regulation; the output end of the heat exchanger is connected to the greenhouse end heat dissipation equipment through the heating network.

2. The multi-energy complementary heating greenhouse system as described in claim 1, characterized in that: The solar heating module is equipped with an all-glass vacuum tube collector, a stainless steel heat storage tank, a copper circulation pipeline, and a shielded circulation pump.

3. The multi-energy complementary heating greenhouse system as described in claim 1, characterized in that: The geothermal heating module is internally equipped with a U-shaped buried heat exchange pipe, a water-to-water heat pump unit, ethylene glycol heat exchange medium, and a dual-well reinjection system.

4. The multi-energy complementary heating greenhouse system as described in claim 1, characterized in that: The biomass heating module is internally equipped with a chain grate biomass boiler, a reinforced concrete fuel silo, a screw conveyor, and a bag filter dust collector.

5. The multi-energy complementary heating greenhouse system as described in claim 1, characterized in that: The wind power supply module is equipped with a permanent magnet synchronous wind turbine, a lithium iron phosphate energy storage battery pack, a sine wave inverter, and an outdoor waterproof combiner box.

6. The multi-energy complementary heating greenhouse system as described in claim 1, characterized in that: The intelligent control system is internally equipped with a Siemens S7-1200 PLC controller, a multi-parameter sensor network, an electric actuator group, and a LoRa wireless communication module.

7. A multi-energy complementary heating greenhouse system as described in claim 1, characterized in that: The core module of the porous material is internally equipped with a biomimetic porous ceramic substrate, honeycomb micro-channels, highly interconnected pore structure, and temperature and corrosion resistance.

8. The multi-energy complementary heating greenhouse system as described in claim 1, characterized in that: The phase change material module contains an organic phase change medium, an inorganic phase change medium, a vacuum impregnation filling layer, and a stability regulating component.

9. A multi-energy complementary heating greenhouse system as described in claim 1, characterized in that: The heat exchanger module is internally equipped with miniature copper pipes, a serpentine layout, surface spiral fins, and a multi-loop parallel structure.

10. A multi-energy complementary heating greenhouse system as described in claim 1, characterized in that: The intelligent sensing and release module collects the ambient temperature sequence T in real time through temperature sensors distributed in different areas of the greenhouse. env ={t1,t2,...,t n }, and simultaneously input external energy data such as solar irradiance S, ground source heat pump operating power Pgeo, and biomass boiler heating rate Qbio; After preprocessing (moving average filtering to eliminate noise), these data are input into a temperature prediction model based on LSTM (Long Short-Term Memory Network). This model uses historical 3-hour data (window length L = 180 minutes) to predict the greenhouse temperature change trend T^pred = {t^n+1, t^n+2, ..., t^n+120} in the next 2 hours. Predicted results and the set target temperature T set (Determined by the growth requirements of the crop, such as the suitable temperature for tomato growth being 18-25℃) After comparison, the optimal heat release rate q is calculated using the Model Predictive Control (MPC) algorithm. release This rate must simultaneously satisfy the remaining energy storage E of the phase change material. PCM Constraints (to avoid excessive release leading to energy depletion) and the maximum transfer power Q of the heat exchanger max The limitation (determined by the thermal conductivity of the material in the micropipe network); ultimately, the system achieves q by adjusting the opening of the heat exchanger valves (continuously adjustable from 0% to 100%). release The precise execution of the data, while feeding the deviation between the actual release and the predicted value back to the LSTM model, dynamically updates the prediction parameters to improve long-term prediction accuracy. Wherein: the hidden state update equation of the LSTM temperature prediction model is: h t =σ g (W gh h t-1 +W gx x t +b g )⊙tanh(W ch h t-1 +W cx x t +b c )+(1-σ g (W gh h t-1 +W gx x t +b g ))⊙h t-1 ; Where: ht represents the hidden state vector at time t (dimension d) h =64, representing an abstract characteristic of historical temperature changes; x t The input vector at time t; W gh W gx Represents the weight matrix of the gated unit; W ch W cx Represents the candidate state weight matrix; b g ,b c This represents the bias vector between the gating unit and the candidate state; σ g This represents the sigmoid activation function; ⊙ represents element-wise multiplication; The objective function for model predictive control is calculated as follows: Where: N represents the prediction time domain; λ1 represents the temperature deviation penalty coefficient; λ2 represents the penalty coefficient for changes in release rate; Tpred(t+k|t) represents the temperature at time t+k predicted based on data at time t; q release (k|t) represents the rate of heat release at time t+k calculated from time t (unit: kW).

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