CN105159257A - Integrated control system and method for plant factory - Google Patents

Integrated control system and method for plant factory Download PDF

Info

Publication number
CN105159257A
CN105159257A CN201510528624.5A CN201510528624A CN105159257A CN 105159257 A CN105159257 A CN 105159257A CN 201510528624 A CN201510528624 A CN 201510528624A CN 105159257 A CN105159257 A CN 105159257A
Authority
CN
China
Prior art keywords
mrow
production
msubsup
plant
energy consumption
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN201510528624.5A
Other languages
Chinese (zh)
Other versions
CN105159257B (en
Inventor
冯毅萍
荣冈
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Zhejiang University ZJU
Original Assignee
Zhejiang University ZJU
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Zhejiang University ZJU filed Critical Zhejiang University ZJU
Priority to CN201510528624.5A priority Critical patent/CN105159257B/en
Publication of CN105159257A publication Critical patent/CN105159257A/en
Application granted granted Critical
Publication of CN105159257B publication Critical patent/CN105159257B/en
Expired - Fee Related legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00—Programme-control systems
    • G05B19/02—Programme-control systems electric
    • G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
    • G05B19/41865—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM] characterised by job scheduling, process planning, material flow
    • A—HUMAN NECESSITIES
    • A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
    • A01C—PLANTING; SOWING; FERTILISING
    • A01C23/00—Distributing devices specially adapted for liquid manure or other fertilising liquid, including ammonia, e.g. transport tanks or sprinkling wagons
    • A01C23/04—Distributing under pressure; Distributing mud; Adaptation of watering systems for fertilising-liquids
    • A—HUMAN NECESSITIES
    • A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
    • A01G—HORTICULTURE; CULTIVATION OF VEGETABLES, FLOWERS, RICE, FRUIT, VINES, HOPS OR SEAWEED; FORESTRY; WATERING
    • A01G7/00—Botany in general
    • A01G7/04—Electric or magnetic or acoustic treatment of plants for promoting growth
    • A01G7/045—Electric or magnetic or acoustic treatment of plants for promoting growth with electric lighting
    • A—HUMAN NECESSITIES
    • A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
    • A01G—HORTICULTURE; CULTIVATION OF VEGETABLES, FLOWERS, RICE, FRUIT, VINES, HOPS OR SEAWEED; FORESTRY; WATERING
    • A01G9/00—Cultivation in receptacles, forcing-frames or greenhouses; Edging for beds, lawn or the like
    • A01G9/24—Devices or systems for heating, ventilating, regulating temperature, illuminating, or watering, in greenhouses, forcing-frames, or the like
    • A01G9/246—Air-conditioning systems
    • A—HUMAN NECESSITIES
    • A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
    • A01G—HORTICULTURE; CULTIVATION OF VEGETABLES, FLOWERS, RICE, FRUIT, VINES, HOPS OR SEAWEED; FORESTRY; WATERING
    • A01G9/00—Cultivation in receptacles, forcing-frames or greenhouses; Edging for beds, lawn or the like
    • A01G9/24—Devices or systems for heating, ventilating, regulating temperature, illuminating, or watering, in greenhouses, forcing-frames, or the like
    • A01G9/247—Watering arrangements
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00—Program-control systems
    • G05B2219/30—Nc systems
    • G05B2219/32—Operator till task planning
    • G05B2219/32089—Action and material and technology combined to manufacture product
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A40/00—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production
    • Y02A40/10—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production in agriculture
    • Y02A40/25—Greenhouse technology, e.g. cooling systems therefor
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P80/00—Climate change mitigation technologies for sector-wide applications
    • Y02P80/10—Efficient use of energy, e.g. using compressed air or pressurized fluid as energy carrier

Landscapes

  • Life Sciences & Earth Sciences (AREA)
  • Environmental Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Soil Sciences (AREA)
  • General Engineering & Computer Science (AREA)
  • Manufacturing & Machinery (AREA)
  • Quality & Reliability (AREA)
  • Water Supply & Treatment (AREA)
  • General Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Biodiversity & Conservation Biology (AREA)
  • Botany (AREA)
  • Ecology (AREA)
  • Forests & Forestry (AREA)
  • Cultivation Of Plants (AREA)

Abstract

The invention discloses an integrated control system and a method for a plant factory. According to the technical scheme of the invention, with the economic benefit as a top criterion, an initial production scheme is formed in line with a production and management database according to a preset production cycle. Meanwhile, the initial production scheme is modified according to the mechanism characteristics of plants and the actual energy cost during the application period of the initial production scheme, so that optimal production schemes for different crop strains are obtained. Production schemes for different crop strains are established, so that an optimal production plan can be obtained. Not only the growth mechanism characteristics of plants are given consideration to, but also technological requirements on the actual production process of the plant factory are met. Therefore, the practical significance of the production planning and scheduling is enhanced, and an integrated optimization solution is provided for the plant factory. Meanwhile, the integrated optimization for the production plan and the manufacturing process operation of the plant factory is realized.

Description

Plant factory integrated control system and method
Technical Field
The invention relates to the field of plant factory control, in particular to a plant factory integrated control system and method.
Background
The aim of modern agricultural production is to achieve high yield, high efficiency, high quality and low consumption. The development of modern facility agriculture represented by plant factories conforms to the trend of the times, the modern information technology and the agricultural engineering technology are integrated, the traditional extensive agricultural production is modified by industrialized fine management, and a good effect is achieved.
The plant factory production process control comprises two subsystems of environment and water and fertilizer. The environmental factors comprise temperature, humidity, illumination, carbon dioxide concentration and the like, and the environmental control subsystem is used for creating good environmental conditions for the growth of crops by controlling the environmental climate factors. The water and fertilizer control subsystem comprises an irrigation part and a fertilization control part, and mainly controls the irrigation water quantity and the fertilizer quality (such as EC/PH value). In recent years, plant factory basic control technology is greatly improved, factory environment control and water and fertilizer regulation are gradually automated, and supporting facilities are increasingly complete.
The operation, production and scheduling are a core problem of fine management of plant factories, namely how to make a periodical planting plan according to related information so as to obtain the optimal production benefit. Due to the characteristics of different production periods of agricultural crops, inflexibility in production plan formulation and the like, the accuracy of production plan formulation has a great influence on the final economic benefit of a plant factory.
In addition, because plant growth has high dependence on environmental temperature, energy consumption optimization and temperature regulation and control technology has been the focus of research in the field of plant greenhouses. The traditional plant factory control focuses on the control of basic environmental factors, and with the actual requirements of energy conservation, high efficiency and cost optimization, an integrated optimization operation regulation and control system and method become a new research hotspot.
An invention patent with patent number CN201410735279 discloses a greenhouse device for monitoring plant factory growth factors and a monitoring method thereof, which comprises a greenhouse device, a carbon dioxide monitoring module, an ozone monitoring module and an ethylene monitoring module.
The invention patent with the patent number of CN201410684635 discloses a greenhouse type plant factory system for flower production, which comprises an intelligent environment system, a soilless culture system and an upper control system.
The invention patent with the patent number CN201410588304 discloses an illumination control system and method for an intelligent plant factory applying multi-color LEDs, which adjust the light emitting power of the LED plant lamps with multiple colors by performing continuous and real-time online detection on the light emitting power of the LED plant lamps with multiple colors and combining the illumination requirements of plants at different growth stages, so that the plants in the plant factory are in the optimal growth state.
The invention patent with the patent number of CN201310414613 relates to a method for realizing a production line type plant factory based on plant growth characteristics and rules, provides an extensible plant production mode, and simulates the optimal growth environment of plants in the whole growth process.
The invention patent with the patent number CN201310037258 relates to a plant growing system, which comprises a surrounding type planting area which is independent from the outside and utilizes natural light sources, a central control system for controlling the environment in the planting area, and a sub-control system connected with the central control system.
The invention patent with the patent number of CN201210573160 relates to a greenhouse temperature control system, which comprises a cold-heat exchanger, a cold-hot water dual-purpose heat preservation storage box, a cold-hot air circulation distributor and an air supply and exhaust system, so that the indoor temperature of a greenhouse or other places can be freely regulated and controlled, and the temperature can be rapidly reduced or increased in a short time, thereby reducing the initial investment cost and the long-time running cost of a user.
The invention patent with the patent number of CN201410271472 relates to an energy-saving greenhouse control system based on time, which comprises a real-time and historical database system, a greenhouse sensing system, a partition controller and a computer control system.
The invention patent with the patent number of CN201310316947 discloses a greenhouse control method and a controller for planting industry, wherein actual temperature values correspond to preset temperature information, air inlet gear information corresponding to the actual temperature information or the actual time information is obtained, and the controller controls air vents to open corresponding gears.
The invention patent with the patent number of CN201310296504 provides a greenhouse control method based on CFD numerical simulation, PID parameter setting is realized through calculation simulation and calculation, and an engineer can determine PID control parameters of a greenhouse without going to a greenhouse site or the greenhouse is in a design stage.
The invention patent with the patent number CN201110359701 discloses a greenhouse control device, which comprises a solar panel and an electric energy conversion device which are arranged on the top of a greenhouse, and a storage battery, a temperature sensor, a humidity sensor, a humidifier, a warmer, a controller and a lighting device which are arranged in the greenhouse.
The invention patent with the patent number CN200710041549 discloses a greenhouse intelligent control method, which is realized by controlling the whole climate of a greenhouse on the basis of a crop intelligent database, tracking the real-time information during the growth period of crops, correcting and perfecting the database, superposing chaotic signals in input data for controlling the greenhouse climate and then optimally adjusting by a neural network controller.
The invention patent with the patent number of CN200410014434 discloses a greenhouse environment control technology based on economic optimization, which establishes a database of environmental factors and crop growth and a control effect database. Calculating the expected regulation quantity of the environmental factors which can be reached in a set time period, and simultaneously calculating the control cost P consumed by the mechanism action in the time period; then calculating an economic output value C of the crops; and determining a control scheme which is formed by combining different action states of the regulating mechanism and takes the economic optimum as a control target by calculating and selecting the maximum C/P value.
Yangmei of Jiangsu university provides a greenhouse environment factor regulation and optimization method based on information fusion, and a greenhouse crop C02 concentration-photosynthetic rate prediction model, a temperature-photosynthetic rate prediction model and C0 are established2A loss cost model, a temperature regulation and control cost model and the like, and a market price rule model is established according to the seasonal change rule of the price.
The modeling of the modern greenhouse temperature hybrid system of the greenhouse hybrid automaton model is established by taking outdoor environment factors as the continuous input quantity of the system, the opening and closing states of the skylight as discrete variables and the indoor temperature as the continuous output quantity. The Chinese academy of sciences, the prince ocean and the like propose a greenhouse temperature and humidity control method based on switching control.
Disclosure of Invention
In view of the deficiencies of the prior art, the present invention provides a plant factory integrated control system and method. According to the invention, by referring to the growth rule and physiological characteristics of plants, the factors and the degree influencing the plant factory environment factors are quantitatively or qualitatively researched by constructing an energy balance and mass balance equation in the plant production process, the energy consumption load required for maintaining the specific environment of the greenhouse is calculated and controlled, an environment regulation and control algorithm integrating energy optimization is established, an optimal planting scheme for plant growth of the plant factory is provided, the effects of energy conservation and efficiency improvement are achieved, and a guide basis is provided for design, production, development and environment regulation and control of the plant factory.
A plant factory integrated control system comprising:
a production management database which comprises resource data, environment data, production data and marketing data of the plant factory;
an operation planning module integrating production conditions forms an initial production scheme according to a preset production period and a production operation database on the basis of the principle of highest economic benefit, and corrects the initial production scheme according to the mechanism characteristics of plants under the initial production scheme and the actual energy consumption cost of a plant factory to obtain an optimal production scheme;
the plant production process simulator simulates the mechanism characteristics of the plant under the initial production scheme according to the real-time growth environment and feeds back the mechanism characteristics to the operation planning module for correcting the initial production scheme;
the energy consumption control module is used for calculating the actual energy consumption cost of the plant factory under the initial production scheme by using the multi-medium energy consumption model and feeding the actual energy consumption cost back to the operation planning module for correcting the initial production scheme;
and the information acquisition and environment control module is used for acquiring the real-time growth environment of the plant and controlling the growth environment of the plant according to the optimal production scheme output by the operation plan module integrating the production conditions.
The resource data comprises the number, the structure, the planting capacity, the average value of the energy consumption of the device (namely the initial value of the average energy consumption coefficient of the seedbed in each production period) and the like of the plant factory cultivation shelves;
the environmental data comprises environmental factors of each workshop in the plant factory, wherein the environmental factors comprise illumination, temperature, air, PH value in water, dissolved oxygen, nutrient-rich data and the like;
the production data comprises basic mechanism data of the cultivated plants, operation scheduling, working condition monitoring, remote service and the like;
the marketing data comprises the cost price of production agricultural materials, raw materials, seeds and the like, and the market supply and demand conditions, price fluctuation and other data of finished plants.
The basic energy consumption cost data (including the initial energy consumption cost and the initial energy consumption coefficient) and the product market price and demand data (namely the supply chain model) of the plant factory can be obtained according to the production operation database.
The production cycle of the invention can be set according to the specific plant planting condition.
The plant production process simulator simulates the mechanism characteristics of plants under different production schemes by utilizing a preset plant growth mechanism model library and a growth environment control model library;
the plant growth mechanism model library comprises at least one plant growth mechanism model;
the growing environment control model library comprises at least one growing environment control model (namely an environment simulation model).
When the initial production scheme is simulated, the corresponding plant growth mechanism model and the corresponding growth environment control model are called according to the initial production scheme for calculation, and a simulation result can be obtained. The growth condition characteristics of the plants under different production schemes are compared through simulation analysis, and simulation verification is provided for the plant factory production plan scheduling and optimization strategy.
The operation planning module outputs an optimal production scheme which comprises a production operation planning scheme of the plant in a corresponding production period and a corresponding environment control given value.
The production condition integrated job planning module (i.e., the optimal production plan) of the present invention actually integrates a plant growth environment model, energy consumption cost, and supply chain model. Assuming that the prices and supply and demand conditions of different plants in a production planning cycle (i.e. a production cycle) are known, a plurality of different plants are planted in one production cycle, and an objective function is established by maximizing economic benefits.
Preferably, the optimal production plan is made by solving the following objective function under the constraint conditions of raw material market supply constraint, product market demand constraint and seedbed planting amount constraint:
<math> <mrow> <msup> <mi>MaxP</mi> <mi>k</mi> </msup> <mo>=</mo> <munder> <mo>&Sigma;</mo> <mi>i</mi> </munder> <mrow> <msubsup> <mi>D</mi> <mi>i</mi> <mi>k</mi> </msubsup> <mo>*</mo> <msubsup> <mi>s</mi> <mi>i</mi> <mi>k</mi> </msubsup> </mrow> <mo>-</mo> <munder> <mo>&Sigma;</mo> <mi>n</mi> </munder> <mrow> <msubsup> <mi>Q</mi> <mi>n</mi> <mi>k</mi> </msubsup> <mo>*</mo> <msubsup> <mi>v</mi> <mi>n</mi> <mi>k</mi> </msubsup> </mrow> <mo>-</mo> <munder> <mo>&Sigma;</mo> <mi>u</mi> </munder> <munder> <mo>&Sigma;</mo> <mi>m</mi> </munder> <msubsup> <mi>R</mi> <mrow> <mi>u</mi> <mo>,</mo> <mi>m</mi> </mrow> <mi>k</mi> </msubsup> <mo>*</mo> <mi>W</mi> </mrow> </math>
wherein, PkFor the plant wide profit for the kth production cycle,
the demand for the ith plant in the kth production cycle,
for the sale price of the ith plant in the kth production cycle,
for the procurement of the nth material in the kth production period,
for the purchase price of the nth material in the kth production period,
bed throughput of the mth bed in the mth production scenario during the kth production cycle;
w is the average energy consumption coefficient (i.e., energy consumption coefficient) of the seedbed in each production cycle, and is usually treated as a constant in calculation.
The energy consumption coefficient and the energy consumption cost can be deduced mutually, namely, when any one of the energy consumption coefficient and the energy consumption cost is known, the other energy consumption coefficient and the energy consumption cost can be deduced. In the present invention, the initial value of W (i.e., the initial energy consumption coefficient) can be calculated from the production and management database.
Wherein, the raw material market supply constraint is as follows:
<math> <mrow> <mtable> <mtr> <mtd> <mrow> <msubsup> <mi>Q</mi> <mi>n</mi> <mrow> <mi>l</mi> <mi>o</mi> <mi>w</mi> </mrow> </msubsup> <mo>&le;</mo> <msubsup> <mi>Q</mi> <mi>n</mi> <mi>k</mi> </msubsup> <mo>&le;</mo> <msubsup> <mi>Q</mi> <mi>n</mi> <mrow> <mi>u</mi> <mi>p</mi> </mrow> </msubsup> </mrow> </mtd> <mtd> <mrow> <mo>&ForAll;</mo> <mi>k</mi> <mo>,</mo> <mi>n</mi> </mrow> </mtd> </mtr> </mtable> <mo>,</mo> </mrow> </math>
wherein,the lower limit of the procurement amount of the nth material,is the upper limit of the procurement amount of the nth raw material.
The product market demand constraints are as follows:
<math> <mrow> <mtable> <mtr> <mtd> <mrow> <msubsup> <mi>D</mi> <mi>i</mi> <mrow> <mi>l</mi> <mi>o</mi> <mi>w</mi> </mrow> </msubsup> <mo>&le;</mo> <msubsup> <mi>D</mi> <mi>i</mi> <mi>k</mi> </msubsup> <mo>&le;</mo> <msubsup> <mi>D</mi> <mi>i</mi> <mrow> <mi>u</mi> <mi>p</mi> </mrow> </msubsup> </mrow> </mtd> <mtd> <mrow> <mo>&ForAll;</mo> <mi>i</mi> <mo>,</mo> <mi>k</mi> </mrow> </mtd> </mtr> </mtable> <mo>,</mo> </mrow> </math>
wherein,the lower limit of the demand of the i-th plant,the upper limit of the demand of the i-th plant. Usually I ═ 1,2, … …, I are the number of plant species, depending on the applicationUse case. k increases in order as time progresses, with no upper limit in principle.
The planting amount of the seedbed is restrained:
<math> <mrow> <mtable> <mtr> <mtd> <mrow> <msubsup> <mi>R</mi> <mi>u</mi> <mrow> <mi>l</mi> <mi>o</mi> <mi>w</mi> </mrow> </msubsup> <mo>&le;</mo> <munder> <mo>&Sigma;</mo> <mi>m</mi> </munder> <msubsup> <mi>R</mi> <mrow> <mi>u</mi> <mo>,</mo> <mi>m</mi> </mrow> <mi>k</mi> </msubsup> <mo>&le;</mo> <msubsup> <mi>R</mi> <mi>u</mi> <mrow> <mi>u</mi> <mi>p</mi> </mrow> </msubsup> </mrow> </mtd> <mtd> <mrow> <mo>&ForAll;</mo> <mi>u</mi> <mo>&Element;</mo> <mi>U</mi> <mo>,</mo> <mi>k</mi> <mo>,</mo> <mi>m</mi> </mrow> </mtd> </mtr> </mtable> <mo>,</mo> </mrow> </math>
the u-th seedbed is at the lower limit of the seedbed production capacity of the m-th production scheme,the u-th seedbed was at the upper limit of the seedbed throughput of the m-th production scheme.
The initial energy consumption coefficient and each constraint condition can be obtained according to the production and operation database (can be directly obtained or obtained by calculation and derivation according to data in the production and operation database), and the energy consumption coefficient and the energy consumption cost can be mutually derived, namely, the other one can be derived by knowing any one of the energy consumption coefficient and the energy consumption cost.
The information acquisition and environment control unit comprises the information acquisition and control of environmental factors such as temperature, humidity, illumination, carbon dioxide concentration and the like, and relates to illumination, temperature, humidity, pH value, CO in a plant factory2Professional sensors and special controllers for spraying, rolling and LED illumination control.
Preferably, the information acquisition and environment control unit is provided with an illumination control subsystem. Comprises an illumination formula and a corresponding control means. By establishing an illumination formula, a control scheme is determined according to the growth requirements of different plants in different periods, and the optimal effect is achieved.
Preferably, the illumination control subsystem control elements include photosynthetically active light quantum flux density, illumination period and spectral distribution.
Preferably, the illumination control subsystem comprises the following illumination control means:
different light source types: such as ordinary sodium mercury and incandescent lamps, fluorescent lamps, LED lamps, and some special light sources (e.g., far infrared and UV).
Different illumination times: the illumination is controlled by controlling the activation time of the light source.
Different illumination intensities or numbers such as voltage current or number of LED lamps, etc.
Different spectral proportions: in the case of using a plurality of light sources of different wavelengths at the same time, the light irradiation is controlled by changing the spectral components by adjusting the ratio of the light from the different light sources.
Different light source position distributions and settings of the light barriers.
Different illumination distances: there is also a method of moving the light source to vary the distance between the light source and the plant to control the illumination.
Preferably, the information acquisition and environment control unit is provided with a temperature control subsystem. The temperature has great influence on the growth, the yield and the quality of crops (namely plants), and the aim of temperature control is to maintain the dynamic proper temperature of the growth and the development process of the crops. The temperature control means includes a heat source, a heat medium pipe, a radiator, and the like.
Preferably, the heat source is fossil fuel (coal, oil, natural gas), electricity, waste heat, geothermal heat, or the like.
Preferably, the plant factory uses a hot water heating system for central heating. The hot water heating system consists of a hot water boiler, a heat supply pipeline, a radiator and the like.
Preferably, low-temperature hot-water heating (the supply and return water temperatures are 95 ℃ and 70 ℃ respectively) is used. The heat sink is disposed adjacent to the crop layer or under the growing bed. The radiators are arranged uniformly in the chamber in order to obtain a resulting temperature distribution.
Preferably, the plant factory adopts a ventilation device to remove excess heat and excess water vapor in the room so as to adjust air humidity and supplement CO2And the like.
Preferably, the ventilation means includes both natural ventilation and forced ventilation. The natural ventilation is to promote air flow by utilizing hot pressing caused by indoor and outdoor temperature difference or wind pressure caused by natural wind power, and the forced ventilation is to realize the flow between indoor and outdoor air by utilizing the pressure difference of indoor and outdoor air caused by mechanical rotation power of a fan.
Preferably, in summer, the plant factory adopts covering materials, wet curtain-fan cooling, fine mist-fan cooling and other methods for cooling.
Preferably, the information collection and environment control unit is provided with a humidity control subsystem. The humidity control comprises two aspects of humidification and dehumidification. The humidifying means comprises methods such as spray humidification, humidification of a wet curtain fan cooling system, artificial irrigation and the like.
Preferably, the information acquisition and environment control unit is provided with a nutrient solution control subsystem. Comprises a nutrient solution circulating system, an operation control system and an ultraviolet disinfection system.
Preferably, the nutrient solution circulating system consists of a cultivation bed, a nutrient solution pool, an industrial pipeline system, a return pipeline system and an automatic fertigation machine. The cultivation bed is used for containing nutrient solution and providing nutrition and moisture for crops. The nutrient solution pool is a container for storing and supplying nutrient solution for the cultivation bed, and the solution in the mother solution tank, the acid tank, the alkali tank and the clear water tank flows into the nutrient solution pool under the control of the electromagnetic valve. The liquid supply pipeline system firstly leads the nutrient solution in the liquid storage pool to the cultivation bed for supplying crops, and mainly comprises a liquid supply pipeline, a valve for regulating flow and the like; the return pipeline system is used for returning the nutrient solution in the cultivation bed to the liquid storage tank and mainly comprises a return pipeline, a return device in the cultivation bed and the like.
Preferably, the automatic fertigation machine is connected with the liquid supply pipeline system, is used for automatically proportioning and mixing the nutrient solution and transmitting the nutrient solution to the liquid supply pipeline system, and mainly comprises a set of Venturi type fertilizer pumps, and the fertilizer pump device also comprises an electric control fertilizer valve, a fertilizer flow regulator and a polyethylene fitting part; a special electric water pump is used for maintaining the water pressure difference necessary for the operation of the Venturi fertilizer pump through the bypass pipe.
Preferably, the liquid reservoir is provided below the ground surface so that the nutrient solution flowing out of the cultivation bed is returned to the liquid reservoir. The volume of the liquid storage tank is required to ensure enough water supply and circulation flow of the plants. The liquid supply pipe is from the underground liquid storage tank, through the water pump and then to each cultivation bed.
Preferably, all the pipelines need to be plastic pipes, so that the nutrient solution is prevented from corroding the pipelines.
Preferably, the information acquisition and environment control unit is provided with CO2And a control subsystem. Depending on the kind of carbon source, CO2Generators broadly classified as hydrocarbon CO2Generator and CO2A propellant. CO 22The concentration is controlled mainly by CO2Steel cylinder, pressure reducing valve, flowmeter, electromagnetic valve, supply pipeline and CO2And (4) a concentration sensor.
Preferably, CO is2The concentration sensor can adopt infrared non-diffusion CO2A sensor.
Preferably, CO is controlled in the loop2The gas is discharged into the air supply pipeline through the pressure reducing constant flow valve, the flowmeter and the electromagnetic valve from the steel cylinder, and finally the gas is sent into the air supply clamping channel by the air supply machine and is evenly sent into the three-dimensional planting surface of the cultivation frame through the laminar air supply outlet.
Preferably, CO2The concentration is generally controlled to be 1000-1500 mL/L, and the specific concentration depends on different plants.
Preferably, the CO is started only in the illumination-on state2A gas control system, so that the photosynthesis of plants in the photoperiod can be satisfied for CO2Without causing CO emissions during the dark phase2Loss of gas.
Preferably, the plant growth mechanism model base researches the influence of different light intensity, light quality and various nutrient concentration interaction on the growth, yield and nutritional quality of vegetables on the basis of screening the formula of the nutrient solution suitable for the aerial fog cultivation of vegetable crops such as lettuce and the like, the temperature, the illumination, the humidity, the carbon dioxide set value and the like, and obtains an optimized plant growth curve model.
Preferably, the growth environment control model library establishes an environment energy balance and mass balance equation by constructing a greenhouse environment steady-state or dynamic mechanism model, and researches the influence mode and the influence degree on the environment factors in the plant factory under the control action of various environment factors.
Preferably, the growing environment control model library is provided with a greenhouse environment energy consumption balance model, and the greenhouse environment energy consumption balance model takes environment parameters inside and outside a greenhouse as input and sends control signals to the ventilation regulating subsystem, the temperature regulating subsystem, the illumination regulating subsystem and the humidity regulating subsystem. The model equation is as follows:
ΔQ＝Qrad+Qheat+Qvent+Qcac+Qcrad+Qsoil+Qleaf-Qcool-Qtran-Qp-Qs
in the formula: delta Q is sensible heat increment of air in the greenhouse, and the unit is W;
<math> <mrow> <mi>&Delta;</mi> <mi>Q</mi> <mo>=</mo> <msub> <mi>V&rho;c</mi> <mi>p</mi> </msub> <mfrac> <mrow> <mo>&part;</mo> <msub> <mi>T</mi> <mrow> <mi>a</mi> <mi>i</mi> </mrow> </msub> </mrow> <mrow> <mo>&part;</mo> <mi>t</mi> </mrow> </mfrac> </mrow> </math>
wherein,
v: volume of the inner space of the greenhouse in m3；
ρ: density of air inside greenhouse in kg/m3；
cp: the specific heat of the air inside the greenhouse is expressed by J/(kg. K);
Tai: the temperature of the air inside the greenhouse, in units of K;
Qrad: solar illumination radiation energy, in units of W;
Qrad＝ARn
wherein,
a: surface area of the greenhouse in m2；
Rn: sun of the sunEnergy density of photothermal radiation in Wm-2；
Qheat: heating energy (neglected when not heated) in units of W;
Qvent: ventilation heat exchange energy in units of W;
Qvent＝ρcp(Tao-Tai)VR
wherein,
ρ: density of air inside greenhouse in kg/m3；
cp: the specific heat of the air inside the greenhouse is expressed by J/(kg. K);
v: effective ventilation area (m) for ventilation window2)；
R: ventilation coefficient in ms-1；
Tao: temperature outside the greenhouse in K;
Tai: temperature inside the greenhouse, in units of K;
Qcac: the energy of heat conduction with the outside is W;
Qcac＝qi*Ac＝hciAc(Tao-Tai)
wherein,
qi: heat flow density in wm-2；
hci: thermal conductivity of air in wm-1k-1；
Ac: area of greenhouse covering layer, unit is m2；
Tao: temperature outside the greenhouse in K;
Tai: temperature inside the greenhouse, in units of K;
Qcrad: long-wave radiation energy is W, and the water culture greenhouse ignores;
Qsoil: heat exchange energy with soil in units of W; omitting a water culture greenhouse;
Qleaf: the heat conduction energy of the air in the greenhouse and the crop leaf surface is W;
Qleaf＝2Aphp(Tp-Tai)
wherein,
Ap: the total area of the crop leaves;
hp: thermal conductivity of the blade in wm-1k-1；
Tp: temperature of plant leaves in units of K;
Tai: temperature inside the greenhouse, in units of K;
Qcool: the energy taken away by the heat unit is in W;
Qtran: the unit of energy required by crop transpiration is W;
Qtran＝H*mtr
wherein,
h: heat of vaporization;
mtr: transpiration amount;
Qp: energy required for crop photosynthesis (neglected);
Qs: the heat dissipation capacity of the periphery of the greenhouse is W, and the heat dissipation capacity can be ignored for greenhouses with larger volume and connected with other greenhouses around;
in summary, the energy consumption balance equation of the greenhouse environment can be obtained as follows:
<math> <mrow> <msub> <mi>Vpc</mi> <mi>p</mi> </msub> <mfrac> <mrow> <mo>&part;</mo> <msub> <mi>T</mi> <mrow> <mi>a</mi> <mi>i</mi> </mrow> </msub> </mrow> <mrow> <mo>&part;</mo> <mi>t</mi> </mrow> </mfrac> <mo>=</mo> <msub> <mi>AR</mi> <mi>n</mi> </msub> <mo>+</mo> <msub> <mi>h</mi> <mrow> <mi>c</mi> <mi>i</mi> </mrow> </msub> <msub> <mi>A</mi> <mi>c</mi> </msub> <mrow> <mo>(</mo> <msub> <mi>T</mi> <mrow> <mi>a</mi> <mi>i</mi> </mrow> </msub> <mo>-</mo> <msub> <mi>T</mi> <mrow> <mi>a</mi> <mi>o</mi> </mrow> </msub> <mo>)</mo> </mrow> <mo>+</mo> <msub> <mi>&rho;c</mi> <mi>p</mi> </msub> <mrow> <mo>(</mo> <msub> <mi>T</mi> <mrow> <mi>a</mi> <mi>o</mi> </mrow> </msub> <mo>-</mo> <msub> <mi>T</mi> <mrow> <mi>a</mi> <mi>i</mi> </mrow> </msub> <mo>)</mo> </mrow> <mi>V</mi> <mi>R</mi> <mo>+</mo> <mn>2</mn> <msub> <mi>A</mi> <mi>p</mi> </msub> <msub> <mi>h</mi> <mi>p</mi> </msub> <mrow> <mo>(</mo> <msub> <mi>T</mi> <mi>p</mi> </msub> <mo>-</mo> <msub> <mi>T</mi> <mrow> <mi>a</mi> <mi>i</mi> </mrow> </msub> <mo>)</mo> </mrow> <mo>+</mo> <msub> <mi>Q</mi> <mrow> <mi>h</mi> <mi>e</mi> <mi>a</mi> <mi>t</mi> </mrow> </msub> <mo>-</mo> <msub> <mi>Q</mi> <mrow> <mi>c</mi> <mi>o</mi> <mi>o</mi> <mi>l</mi> </mrow> </msub> <mo>-</mo> <msub> <mi>Q</mi> <mrow> <mi>t</mi> <mi>r</mi> <mi>a</mi> <mi>n</mi> </mrow> </msub> </mrow> </math>
preferably, the growing environment control model library is provided with a greenhouse humidity simulation model. Assuming that the temperature and humidity distribution in the greenhouse is all hooked, and the temperature and humidity distribution of the crop canopy is all hooked, then a dynamic greenhouse humidity mechanism model based on water vapor balance can be established:
E＝Et+Ep+Ed+Es-Er-El-Ef-Eleak
wherein,
e is the water vapor content in the greenhouse;
Etthe water vapor content generated by the transpiration of greenhouse crops;
Epthe water vapor content generated by the evaporation of the greenhouse wet curtain;
Edwater vapor content generated for greenhouse spraying;
Esthe water vapor content generated by greenhouse soil evaporation;
Ercondensing water on the greenhouse cover and the guardrail;
Elthe water vapor content resulting from ventilation of the skylight;
Efthe water vapor content generated by the ventilation of the fan;
Eleakfor moisture leakage through greenhouse covers and guard rail gaps.
The plant factory uses cement as ground inside, and crops are plantedIn the flowerpot, the flowerpot is placed on a cultivation bed, so that the soil moisture evaporation is less and can be approximately ignored (E)s＝0)。
When the fan is started to conduct indoor forced ventilation, the moisture leakage through the gap in the greenhouse is smaller than ventilation water vapor exchange, and the moisture leakage can be ignored. (E)leak＝0)。
Meanwhile, if the influence of different covering materials in the greenhouse on the humidity in the greenhouse is small, the covering materials are equivalent to the same material (E)r＝0)。
Default is only wet curtain humidification, then Ed＝0。
The expression can now be simplified as:
E＝Et+Ep-Er-El-Ef
preferably, the energy consumption control module divides the energy consumption of the plant factory into fixed energy consumption and variable energy consumption, analyzes important factors influencing the energy consumption, and establishes a plant factory multi-medium energy consumption model. Energy consumption cost is introduced into a production plan, and energy consumption coefficients are subjected to feedback correction, so that the production plan can accurately estimate the multi-medium energy consumption cost, calculate and control actual energy consumption load required by maintaining a specific environment of a greenhouse, and provide a guide basis for plant factory design, production, development and environment regulation.
The multi-media energy consumption model for a plant is as follows:
<math> <mrow> <mtable> <mtr> <mtd> <mrow> <msub> <mi>E</mi> <mrow> <mi>u</mi> <mo>,</mo> <mi>c</mi> </mrow> </msub> <mo>=</mo> <msub> <mi>&alpha;</mi> <mrow> <mi>u</mi> <mo>,</mo> <mi>c</mi> </mrow> </msub> <msub> <mi>F</mi> <mi>u</mi> </msub> <mo>+</mo> <msub> <mi>&beta;</mi> <mrow> <mi>u</mi> <mo>,</mo> <mi>c</mi> <mo>,</mo> <mi>p</mi> </mrow> </msub> <msub> <mi>PP</mi> <mrow> <mi>c</mi> <mo>,</mo> <mi>p</mi> </mrow> </msub> <mo>+</mo> <msub> <mi>&theta;</mi> <mrow> <mi>u</mi> <mo>,</mo> <mi>c</mi> </mrow> </msub> <msub> <mi>OP</mi> <mi>u</mi> </msub> <mo>+</mo> <msub> <mi>CD</mi> <mrow> <mi>u</mi> <mo>,</mo> <mi>c</mi> </mrow> </msub> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <mo>&ForAll;</mo> <mi>c</mi> <mo>&Element;</mo> <mi>C</mi> <mo>,</mo> <mi>p</mi> <mo>&Element;</mo> <mi>P</mi> <mo>,</mo> <mi>u</mi> <mo>&Element;</mo> <mi>U</mi> </mrow> </mtd> </mtr> </mtable> <mo>,</mo> </mrow> </math>
wherein,
c is an energy medium set;
p is a mechanism characteristic set;
u is a seedbed set;
Eu,cthe requirement of the seedbed u for the energy medium c;
Futhe amount of cultivation of the seedbed u;
PPu,pis the mechanism characteristic of the plant cultivated on the seedbed u;
OPua planting scheme (process route, operation level, etc.) for the seedbed u;
CDu,ca fixed utility of the energy medium c consumed by the seedbed u is a constant (value according to an actual application scene);
αu,cthe energy consumption coefficient of the cultivation number of the seedbed u to the energy medium c;
βu,c,pthe energy consumption coefficient of the mechanism characteristic p of the plant cultivated on the seedbed u to the energy medium c;
θu,cthe energy consumption coefficient of the energy medium c for the planting scheme of the seedbed u.
The multi-media energy consumption model comprises the following variables: the cultivation amount of the seedbed, the types and the characteristics of the plants and the technological parameters of the seedbed production process, and the public engineering of each medium energy source is considered in the fixed energy consumption. For the plant factory planting operation process, the preferable necessary process route and the optimized process parameters can achieve good energy-saving effect. In addition, the dynamic control level of environmental factors of plant factories can also affect the actual energy consumption of the plant factories after the operating conditions of the seedbed facilities are given. The planting scheme not only can influence the energy consumption of the system, but also can restrict the production optimization by energy consumption indexes, and further can influence the selection of the planting scheme and the optimization of operating conditions.
In a multi-medium energy consumption model of a crop production plan, multi-medium energy consumption coefficients of different seedbeds based on different cultivation schemes (planting schemes) are introduced, and the change of energy consumption can be accurately reflected only by correcting the actual energy consumption value of the seedbed, so that the multi-medium energy consumption model based on multiple working conditions is required to be used for feedback correction to obtain a proper parameter value.
The invention also provides a plant factory integrated control method, which forms an initial production scheme according to a preset production period and a production operation database on the basis of the principle of highest economic benefit, and corrects the initial production scheme according to the mechanism characteristics of the plants under the initial production scheme and the actual energy consumption cost to obtain the optimal production scheme with the highest economic benefit.
The initial production schedule was modified as follows:
step 1, calculating to obtain the actual energy consumption cost of the plant factory according to an initial production scheme;
step 2, comparing the actual energy consumption cost and the initial energy consumption cost of the plant factory:
if the difference value between the two is smaller than the threshold value, taking the initial production scheme as the optimal production scheme;
otherwise, updating the initial energy consumption cost to be the current actual energy consumption cost, calculating the average energy consumption coefficient of the seedbed in each production period by using the updated initial energy consumption cost, solving the average energy consumption coefficient as a given initial value of the energy consumption coefficient to obtain a new initial generation scheme, and returning to the step 1.
In the method, the mechanism characteristics of the plants under the initial production scheme are obtained by simulating the plant production process of the initial production scheme, and the actual energy consumption cost under the initial production scheme is calculated by using a multi-medium energy consumption model.
According to the method, the production scheme is formulated according to different crop varieties, the accessibility of the production plan optimization result is verified based on the plant factory control system simulation model established by the process simulation software, and the feedback correction is performed on the production through process simulation, so that the formulation process of the production plan not only considers the crop mechanism, but also considers the process requirements of the actual production process of the plant factory, and the production plan scheduling has greater practical significance. According to the integrated optimization method of plant factory operation and production plan based on plant production simulation, a solution for seeking the integrated optimization of the plant factory is provided, and the integrated optimization of the production plan and the plant factory production process operation is realized.
Drawings
FIG. 1 is a schematic diagram of the composition of an integrated plant factory control system according to the present invention;
FIG. 2 is a schematic diagram of a plant factory integrated control method according to the present invention;
fig. 3 is a schematic diagram illustrating a principle of the feedback correction strategy according to the embodiment.
Detailed Description
The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.
As shown in fig. 1, the plant factory integrated control system of the present embodiment includes:
the production and operation database mainly comprises information such as product market demands, initial energy consumption cost and the like, and is specifically divided into the following steps: basic data in aspects of resource data, environmental data, production data, marketing data and the like of the plant factory, and the like, wherein:
the resource data comprises the number, the structure, the planting capacity, the average value of the energy consumption of the device (the initial value of the energy consumption coefficient) and the like of the plant factory cultivation shelves;
the environmental data comprises data of environmental factors of each workshop, such as illumination, temperature, air, PH value in water, dissolved oxygen, rich nutrients and the like;
the production data comprises basic mechanism data of the cultivated crops, operation scheduling, working condition monitoring, remote service and the like;
the marketing data comprises the cost price of production agricultural materials, raw materials, seeds and the like, and the market supply and demand condition, price fluctuation and other data of finished crops.
The plant production process simulator compares the growth conditions (mechanism characteristics) of plants under different production schemes (namely crop planting schemes) according to real-time growth environment simulation analysis, and outputs the growth conditions as feedback correction information to the operation plan module of the integrated production condition;
the plant production process simulator is preset with a growth mechanism model library (namely a plant growth mechanism model library) and a growth environment control model library (namely an environment control model library), wherein the plant growth mechanism model library comprises at least one plant growth mechanism model; the growing environment control model library comprises at least one growing environment control model.
On the basis of screening a nutrient solution formula suitable for aerosol cultivation of vegetable crops such as lettuce and the like, temperature, illumination, humidity, carbon dioxide set values and the like, the plant growth mechanism model library researches the influence of interaction of different light intensity, light quality and various nutrient concentrations on the growth, yield and nutrient quality of vegetables to obtain an optimized plant growth curve model. The growth environment control model library establishes an environment energy balance and mass balance equation by constructing a greenhouse environment steady state or dynamic mechanism model, and researches the influence mode and the influence degree of various environmental factors on environmental factors in a plant factory under the control action of the environmental factors.
An operation planning module integrating production conditions forms an initial production scheme according to a preset production period and a production operation database on the basis of the principle of highest economic benefit, and corrects the initial production scheme according to the mechanism characteristics of plants under the initial production scheme and the actual energy consumption cost of a plant factory to obtain an optimal production scheme;
the optimal production plan output by the operation planning module of the embodiment is actually a planting plan customized for different growth stages of crops.
The operation plan module integrating production conditions integrates a crop growth environment model, energy consumption cost and a supply chain model, and the period of a production plan can be set according to specific plant planting conditions. Assuming that the prices and supply and demand conditions of different plants in a production planning period are known, planting a plurality of different plants in one period, establishing a model by taking the economic benefit maximization as an objective function, and solving to obtain an optimal production scheme.
The optimal production scheme formulated in this example is obtained by solving the following objective function under the constraint conditions of raw material market supply constraint, product market demand constraint and seedbed planting amount constraint:
<math> <mrow> <msup> <mi>MaxP</mi> <mi>k</mi> </msup> <mo>=</mo> <munder> <mo>&Sigma;</mo> <mi>i</mi> </munder> <mrow> <msubsup> <mi>D</mi> <mi>i</mi> <mi>k</mi> </msubsup> <mo>*</mo> <msubsup> <mi>s</mi> <mi>i</mi> <mi>k</mi> </msubsup> </mrow> <mo>-</mo> <munder> <mo>&Sigma;</mo> <mi>n</mi> </munder> <mrow> <msubsup> <mi>Q</mi> <mi>n</mi> <mi>k</mi> </msubsup> <mo>*</mo> <msubsup> <mi>v</mi> <mi>n</mi> <mi>k</mi> </msubsup> </mrow> <mo>-</mo> <munder> <mo>&Sigma;</mo> <mi>u</mi> </munder> <munder> <mo>&Sigma;</mo> <mi>m</mi> </munder> <msubsup> <mi>R</mi> <mrow> <mi>u</mi> <mo>,</mo> <mi>m</mi> </mrow> <mi>k</mi> </msubsup> <mo>*</mo> <mi>W</mi> </mrow> </math>
wherein, PkFor the plant wide profit for the kth production cycle,
the demand for the ith plant in the kth production cycle,
for the sale price of the ith plant in the kth production cycle,
for the procurement of the nth material in the kth production period,
for the purchase price of the nth material in the kth production period,
bed throughput of the mth bed in the mth production scenario during the kth production cycle;
w is the average energy cost coefficient of the device (i.e., the seedbed) in each cycle.
Wherein, the raw material market supply constraint is as follows:
<math> <mrow> <mtable> <mtr> <mtd> <mrow> <msubsup> <mi>Q</mi> <mi>n</mi> <mrow> <mi>l</mi> <mi>o</mi> <mi>w</mi> </mrow> </msubsup> <mo>&le;</mo> <msubsup> <mi>Q</mi> <mi>n</mi> <mi>k</mi> </msubsup> <mo>&le;</mo> <msubsup> <mi>Q</mi> <mi>n</mi> <mrow> <mi>u</mi> <mi>p</mi> </mrow> </msubsup> </mrow> </mtd> <mtd> <mrow> <mo>&ForAll;</mo> <mi>k</mi> <mo>,</mo> <mi>n</mi> </mrow> </mtd> </mtr> </mtable> <mo>,</mo> </mrow> </math>
wherein,the lower limit of the procurement amount of the nth material,is the upper limit of the procurement amount of the nth raw material.
The product market demand is constrained as follows:
<math> <mrow> <mtable> <mtr> <mtd> <mrow> <msubsup> <mi>D</mi> <mi>i</mi> <mrow> <mi>l</mi> <mi>o</mi> <mi>w</mi> </mrow> </msubsup> <mo>&le;</mo> <msubsup> <mi>D</mi> <mi>i</mi> <mi>k</mi> </msubsup> <mo>&le;</mo> <msubsup> <mi>D</mi> <mi>i</mi> <mrow> <mi>u</mi> <mi>p</mi> </mrow> </msubsup> </mrow> </mtd> <mtd> <mrow> <mo>&ForAll;</mo> <mi>i</mi> <mo>,</mo> <mi>k</mi> </mrow> </mtd> </mtr> </mtable> <mo>,</mo> </mrow> </math>
wherein,the lower limit of the demand of the i-th plant,the upper limit of the demand of the i-th plant.
And (3) restricting the planting amount of the seedbed:
<math> <mrow> <mtable> <mtr> <mtd> <mrow> <msubsup> <mi>R</mi> <mi>u</mi> <mrow> <mi>l</mi> <mi>o</mi> <mi>w</mi> </mrow> </msubsup> <mo>&le;</mo> <munder> <mo>&Sigma;</mo> <mi>m</mi> </munder> <msubsup> <mi>R</mi> <mrow> <mi>u</mi> <mo>,</mo> <mi>m</mi> </mrow> <mi>k</mi> </msubsup> <mo>&le;</mo> <msubsup> <mi>R</mi> <mi>u</mi> <mrow> <mi>u</mi> <mi>p</mi> </mrow> </msubsup> </mrow> </mtd> <mtd> <mrow> <mo>&ForAll;</mo> <mi>u</mi> <mo>&Element;</mo> <mi>U</mi> <mo>,</mo> <mi>k</mi> <mo>,</mo> <mi>m</mi> </mrow> </mtd> </mtr> </mtable> <mo>,</mo> </mrow> </math>
the u-th seedbed is at the lower limit of the seedbed production capacity of the m-th production scheme,the u-th seedbed was at the upper limit of the seedbed throughput of the m-th production scheme.
The plant production process simulator simulates the mechanism characteristics of the plant under the initial production scheme according to the real-time growth environment and feeds back the mechanism characteristics to the operation planning module for correcting the initial production scheme;
the plant production process simulator simulates the mechanism characteristics of plants of different production schemes by utilizing a preset plant growth mechanism model library and a growth environment control model library, wherein the plant growth mechanism model library comprises at least one plant growth mechanism model; the growing environment control model library comprises at least one growing environment control model. The growth condition characteristics of the plants under different production schemes are compared through simulation analysis, and simulation verification is provided for the plant factory production plan scheduling and optimization strategy.
The energy consumption control module is used for calculating the actual energy consumption cost of the plant factory under the initial production scheme by using the multi-medium energy consumption model and feeding the actual energy consumption cost back to the operation planning module for correcting the initial production scheme;
the energy consumption control module of the embodiment comprises energy consumption models of related water, electricity, steam, fuel and the like, the energy consumption of the plant factory is divided into fixed energy consumption and variable energy consumption, important factors influencing the energy consumption of the plant factory are analyzed, and the plant factory multi-medium energy consumption model is established. An energy consumption cost model is introduced into a production plan, and the parameters of the energy consumption cost model are subjected to feedback correction, so that the production plan can accurately estimate the multi-medium energy consumption cost, calculate and control the energy consumption load required by maintaining the specific environment of the greenhouse, and provide a guide basis for plant factory design, production, development and environment regulation.
The multimedia energy consumption model of the embodiment is as follows:
<math> <mrow> <mtable> <mtr> <mtd> <mrow> <msub> <mi>E</mi> <mrow> <mi>u</mi> <mo>,</mo> <mi>c</mi> </mrow> </msub> <mo>=</mo> <msub> <mi>&alpha;</mi> <mrow> <mi>u</mi> <mo>,</mo> <mi>c</mi> </mrow> </msub> <msub> <mi>F</mi> <mi>u</mi> </msub> <mo>+</mo> <msub> <mi>&beta;</mi> <mrow> <mi>u</mi> <mo>,</mo> <mi>c</mi> <mo>,</mo> <mi>p</mi> </mrow> </msub> <msub> <mi>PP</mi> <mrow> <mi>c</mi> <mo>,</mo> <mi>p</mi> </mrow> </msub> <mo>+</mo> <msub> <mi>&theta;</mi> <mrow> <mi>u</mi> <mo>,</mo> <mi>c</mi> </mrow> </msub> <msub> <mi>OP</mi> <mi>u</mi> </msub> <mo>+</mo> <msub> <mi>CD</mi> <mrow> <mi>u</mi> <mo>,</mo> <mi>c</mi> </mrow> </msub> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <mo>&ForAll;</mo> <mi>c</mi> <mo>&Element;</mo> <mi>C</mi> <mo>,</mo> <mi>p</mi> <mo>&Element;</mo> <mi>P</mi> <mo>,</mo> <mi>u</mi> <mo>&Element;</mo> <mi>U</mi> </mrow> </mtd> </mtr> </mtable> <mo>,</mo> </mrow> </math>
wherein,
c is an energy medium set;
p is a mechanism characteristic set;
u is a seedbed set;
Eu,cthe requirement of the seedbed u for the energy medium c;
Futhe amount of cultivation of the seedbed u;
PPu,pis the mechanism characteristic of the plant cultivated on the seedbed u;
OPua planting scheme (process route, operation level, etc.) for the seedbed u;
CDu,ca fixed utility of energy medium c consumed for the seedbed u, constant;
αu,cthe energy consumption coefficient of the cultivation number of the seedbed u to the energy medium c;
βu,c,pthe energy consumption coefficient of the mechanism characteristic p of the plant cultivated on the seedbed u to the energy medium c;
θu,cthe energy consumption coefficient of the energy medium c for the planting scheme of the seedbed u.
And the information acquisition and environment control module is used for acquiring the real-time growth environment of the plant and controlling the growth environment of the plant according to the production scheme output by the operation plan module integrating the production conditions.
As shown in fig. 2, the greenhouse environment information collecting and controlling unit of the present embodiment includes a temperature adjusting unit, a humidity adjusting unit, an illumination adjusting unit, a carbon dioxide adjusting unit, a nutrient solution controlling unit, a safety monitoring unit and an outdoor weather station, wherein the controlling unit receives signals from the weather station and coordinates these subsystems;
the temperature adjusting unit comprises a first temperature sensor, a hot water heating system, an air conditioning unit and an evaporating device, and the control unit controls the hot water heating system and the air conditioning unit according to a temperature signal in the greenhouse collected by the first temperature sensor.
The air conditioning unit and the evaporation plant are used as heat-using units to exchange heat with hot water in the heat collecting water tank or are directly communicated with the heat collecting water tank through pipelines.
When the temperature in the factory is higher than the set temperature, the hot water in the heat collecting water tank supplies hot water to the air conditioning unit, the air conditioning unit performs refrigeration, and when the humidity in the greenhouse is lower than the set humidity (the set humidity is set according to the crop species and the growth cycle), the heat collecting water tank supplies water to the evaporation device for increasing the humidity of the air in the greenhouse.
The humidity adjusting unit comprises a first humidity sensor, a spraying device and an evaporating device; the control unit controls the spraying device and the evaporating device according to the humidity signal in the greenhouse collected by the first humidity sensor;
the ventilation regulating unit comprises a first ventilation sensor and a ventilation device; the control unit controls the ventilation device according to the wind speed and wind direction signals in the greenhouse collected by the first ventilation sensor.
The ventilation device comprises a fan arranged in the greenhouse and an automatic window arranged on the side wall and/or the ceiling, and the fan and the automatic window are controlled by the control unit.
The automatic window sets up the lateral wall or the ceiling in the greenhouse, also can the lateral wall and the ceiling all set up automatic window, and the control unit controls opening and closing of automatic window according to the ventilation information of gathering in the inside first ventilation sensor in greenhouse and the weather station, controls the inside ventilation in greenhouse.
The illumination adjusting unit comprises a first illumination sensor, a light source and a sun shading device, the control unit establishes illumination formulas according to different periods of different plants according to light intensity signals in the greenhouse collected by the first illumination sensor, determines a control scheme and controls the light source and the sun shading device.
The sun-shading device is a sun-shading curtain and a driving motor for controlling the opening and closing of the sun-shading curtain, and the driving motor is controlled by the control unit. The shading curtain is used for sheltering from external light, and the control unit controls opening and closing of the shading curtain according to the illumination signal collected by the weather station and the indoor illumination signal collected by the first illumination sensor, so that illumination inside the greenhouse is adjusted.
CO2The control unit comprises a first CO2Sensor, CO2The gas source generating device and the control unit are based on the first CO2Greenhouse internal CO collected by sensor2Concentration signal, according to CO of different plants in different time periods2Demand forConcentration recipe, determination of control scheme, control of CO2Air supply and ventilation means.
The nutrient solution adjusting unit comprises a first nutrient element sensor, a nutrient solution circulating system and an ultraviolet disinfection system. The control unit determines a control scheme according to nutrient elements in the nutrient solution pool acquired by the first nutrient element sensor and nutrient demand formulas of different plants in different time periods, and controls the nutrient solution feeding system and the nutrient solution circulating system.
The operation control system controls the water flow and the nutrient proportioning of each valve by a software program. The whole system consists of software, hardware, transmission equipment, sensors, environment control, irrigation control and nutrition control. The system accurately controls the proportion of water and fertilizer liquid through the fertilizing pump so as to achieve the purpose of accurately controlling the concentration of the fertilizer. The working principle is as follows: the controller calculates water flow by collecting signals of the electronic water meter, judges whether actual water flow reaches a set value or not through a program, and automatically cuts off the electromagnetic valve when the irrigation water amount reaches the set value, so that the irrigation water amount is automatically controlled. The fertilizer box is provided with a liquid level sensor which automatically detects the water level by measuring the change of the water level resistance. When the fertilizer is used up, the resistance value is very large, the sensor detects a resistance value change signal and then transmits the resistance value change signal to the controller, the controller drives the alarm to give out an alarm sound, the electromagnetic valve of the water inlet is cut off, and the fertilizer applicator stops working automatically.
In order to control the unbalance of the microenvironment in the greenhouse to cause irreversible damage to crops, a safety monitoring device is also arranged in the greenhouse and is controlled by a control unit. When the environmental parameters in the greenhouse exceed the limit values (the environmental parameter values under the extreme environment which can be born by crops), the safety monitoring device sends out alarm signals, and the change required is manually controlled in time.
The weather station is used for collecting information such as the temperature, the humidity, the wind direction, the wind speed, the solar radiation and the rainfall outside the greenhouse, and can adopt a small weather station special for agricultural production. The greenhouse humidity sensor comprises a second ventilation sensor, a second temperature sensor, a second illumination sensor, a second humidity sensor and a rainfall sensor, wherein the second ventilation sensor is used for collecting external environment parameters of the greenhouse.
The weather station adopts the dedicated small-size outdoor weather station of agricultural production, and second temperature sensor is shielded, and solar radiation does not influence second temperature sensor. The rain sensor is placed in a shadow-free place so as not to affect the measurement of solar radiation.
The second ventilation sensor, the second temperature sensor, the second illumination sensor, the second humidity sensor and the rainfall sensor of the weather station are used for collecting external environment parameters of the greenhouse, and according to the environment parameters, the internal environment parameters of the greenhouse are controlled through the control unit, so that the microclimate suitable for crop growth is formed.
First and second temperature sensors: precision: + 1% in the range of 0-50 deg.
First and second humidity sensors: precision + 3% RH (relative humidity), range 10-100%.
First and second illumination sensors: the precision is + 8%, and the range is 0-10 ten thousand LUX.
The control unit collects signals of temperature, humidity, ventilation, illumination and nutrient solution in and out of a weather station and a room, sends the signals into a production database, gives out production schemes customized for different stages of crops through optimized calculation of a plant factory integrated control system, controls a corresponding air conditioning unit, a spraying device, an evaporation device, a ventilation device, a light source, a shading device, a nutrient solution circulating system and the like, and adjusts microclimate and nutrient solution formula in the greenhouse to meet the planting requirements of different crops.
The input signal of the control unit can be adjusted by manually inputting corresponding environmental parameters (such as temperature, humidity and the like), so that the working rationality of the control unit is improved.
The method establishes an environment regulation and control algorithm integrating energy optimization by constructing a steady-state or dynamic plant growth mechanism model and a plant factory energy balance and mass balance equation, provides an optimal planting scheme for crop growth in a plant factory, and achieves the effects of energy conservation and efficiency improvement. Provides theoretical guidance for plant factory design, production, development and environmental regulation.
The hardware part of the plant factory integrated control system adopts Siemens S7-300 series PLC modules, all input and output interface circuits are isolated by photoelectricity, so that the external circuit of the greenhouse is electrically isolated from the internal circuit of the PLC, the plant factory integrated control system has complete monitoring and diagnosis functions, once the power supply or other software and hardware are abnormal, the CPU immediately takes effective measures to prevent the fault from being enlarged, and the plant factory integrated control system can be manually controlled in an emergency state. The liquid crystal display and the touch screen are used in a matched manner, so that the human-computer interface is greatly improved.
The plant factory integrated control system software part of this embodiment adopts an expert analysis system, and the basic database optimizes and calculates each original parameter by receiving external original information (resources, environment, production, marketing, etc.), a large number of internally stored professional standards, a crop mechanism model (i.e., a plant growth mechanism model), a growth environment control model, a multi-medium energy consumption model of each production device, an initial value of an average energy consumption coefficient (i.e., an initial energy consumption coefficient), and the like, and makes a specific production operation scheme for different crops, and simultaneously issues corresponding environment control parameters to an execution mechanism of a field control unit. The integrated optimization of the production plan and the plant factory production process operation is realized, and the specific functions are as follows:
1) information monitoring of the sensor: and various sensor information is collected and displayed on a screen in real time, so that the observation is facilitated.
2) Greenhouse equipment control module: the corresponding environment adjusting devices, such as electromagnetic valves, wet curtains, fans and the like in the greenhouse environment adjusting system, can be controlled by the modules. According to the set control mode, two modes of manual control (directly clicking the equipment to be controlled from the screen) and automatic control can be adopted. And different control strategies can be independently set and adopted by different devices.
3) A production process simulation module: and (4) sending the plant mechanism model into a plant mechanism model library according to the environmental working condition given by the production operation plan scheme given by the system, and simulating the plant production process. And simulation verification is provided for plant factory production plan scheduling and optimization strategies by comparing the mechanism characteristics of the plants under different production schemes through simulation analysis.
4) An energy consumption control module: by establishing a multi-medium energy consumption model of each production device of the plant factory, introducing a multi-medium energy consumption model calculation result into a production plan and performing feedback correction on an energy consumption coefficient, the production plan can accurately estimate the multi-medium energy consumption cost, calculate and control the energy consumption load required by maintaining the specific environment of the greenhouse, and provide a guidance basis for plant factory design, production, development and environment regulation.
5) A production operation planning module: the crop growth environment model, the energy consumption cost and the supply chain model are integrated, and the period of the production plan can be set according to the specific plant planting condition. And (4) giving a production operation plan scheme of a certain plant in a specific production period and a corresponding environmental control given value.
6) The alarm function is as follows: alarm of too high or too low absolute values (e.g. temperature, humidity); an alarm in the form of too high or too low a float value (e.g. warm setting); conditional linked alarm (e.g. temperature comparison between inside and outside of the greenhouse); and setting a form alarm (such as control equipment) for the difference value, and the like. All alarm functions can set their priority level, and when there is an alarm, the related equipment can be set to automatically fail for a period of time, so that the whole system has certain safety.
7) A data recording module: the module can download various stored data, namely sensor data and state data of various control devices from the controller, and can represent the data on a screen in a graph or report form mode, so that a user can observe and analyze the data. Meanwhile, the data can be stored into a universal text format, and other software is used for analyzing the data.
8) An event recording function: a record of the operation of the device, or any other event, may be kept that provides the user with an understanding of the number and status of operations on the device; thereby making a correct judgment of the maintenance and repair of the equipment. For example: the motor belt abrasion and the electric fan motor damage can be judged, and the energy consumption can be calculated.
8) Setting screen display items: the user can set items displayed on the screen by himself, such as information of various sensors, states of the equipment or pictures, so that the user can know the state of the greenhouse more clearly.
The plant factory integrated control system of the embodiment specifically comprises the following operation steps:
1) starting a light source to simulate sunlight, and after the set illumination intensity is reached, starting the shading screen to expand by the control unit, so that the intensity of the light source is reduced;
2) the control unit starts the heat source and the heat using unit to stably control the temperature at the initial set temperature;
3) starting the spraying device to simulate precipitation, and controlling the automatic window to close by the control unit;
4) the spraying device simulates irrigation and fertilization;
5) the control unit starts the air conditioning unit to cool;
6) collecting sensor data after the environmental parameters in the greenhouse are stable;
7) setting a planting period in an operation plan module, performing operation plan optimization calculation analysis, and giving an initial value of a planting scheme instruction;
8) the planting scheme instruction initial value given by the operation planning module is sent to a production process simulator for simulation, the accessibility of the instruction is verified, and a simulation correction result is fed back to the operation planning module;
9) meanwhile, an initial value of a planting scheme instruction given by the operation planning module is sent to the energy consumption control module, the parameters of the energy consumption cost model are subjected to feedback correction, so that the production plan can accurately estimate the multi-medium energy consumption cost, and a simulation correction result is fed back to the operation planning module;
10) the operation planning module synthesizes the feedback results of the 8 and 9 steps, carries out optimization analysis calculation again, and issues an actual planting scheme instruction and a corresponding control unit set value; and carrying out plant production operation under optimized regulation and control on the actuating mechanisms of the control units.
When the plant factory integrated control system based on this embodiment controls a plant factory: and forming an initial production scheme according to a preset production period and a production operation database on the basis of the principle of highest economic benefit, and correcting the initial production scheme according to the mechanism characteristics of the plants and the actual energy consumption cost under the initial production scheme to obtain the optimal production scheme with the highest economic benefit.
The initial production scheme is modified according to the following strategy:
and solving the multi-medium energy consumption model according to the optimal production scheme to obtain a current production energy consumption value of the plant factory, then comparing the calculated current production energy consumption with a preset initial energy consumption value, if the difference value of the two is smaller than a threshold value, not performing feedback correction, otherwise, performing parameter fitting according to the calculation result data of the multi-medium energy consumption model to obtain a new parameter value to replace the energy consumption coefficient in the production and planting plan, and solving the plan again. And repeating the iteration until the threshold condition is met, and terminating the iteration process.
The plant factory integrated control method of the embodiment refers to a feedback correction strategy of a multi-medium energy consumption model and a production plan. In the crop production plan model, energy consumption coefficients of different seedbeds based on different cultivation schemes are included, and the change of energy consumption can be accurately reflected only by correcting an actual multi-medium energy consumption model of the seedbed, so that a multi-medium energy consumption model based on multiple working conditions is required to be used for feedback correction to obtain an appropriate parameter value.
As shown in fig. 3, the method is implemented by performing modification through the following steps:
step 1, calculating to obtain the actual energy consumption cost of the plant factory according to an initial production scheme;
step 2, comparing the actual energy consumption cost and the initial energy consumption cost of the plant factory:
if the difference value between the two is smaller than the threshold value, taking the initial production scheme as the optimal production scheme;
otherwise, updating the initial energy consumption cost to be the current actual energy consumption cost, calculating the average energy consumption coefficient of the seedbed in each production period by using the updated initial energy consumption cost, solving according to the calculation result to obtain a new initial production scheme, and returning to the step 1.
The threshold value is set according to the actual application condition and can be adjusted according to requirements.
In this embodiment, the average energy consumption coefficient of the seedbed in each production cycle is calculated by parameter fitting using the updated initial energy consumption cost: and (4) according to the actual energy consumption value, the energy consumption cost of each medium for the production device is obtained through flattening, and the average energy consumption coefficient (namely the energy consumption coefficient W) of the seedbed in each production period is obtained through calculation.
According to the method, a crop production operation plan is made according to different crop types, the accessibility of a production plan optimization result is verified based on a plant factory production simulation software model, and the production operation plan is subjected to feedback correction through crop production process simulation, so that the crop mechanism and the operation requirement of the actual production process of a plant factory are considered in the making process of the production plan, and the production plan scheduling has great practical significance. According to the integrated optimization method of plant factory operation and production plan based on production simulation, a solution for seeking the integrated optimization of the plant factory is provided, and the integrated optimization of the production plan and the plant factory production process operation is realized.
The invention establishes an environment regulation algorithm of integrated energy optimization by constructing a steady-state or dynamic plant growth mechanism model and a plant factory energy balance and mass balance equation, gives an optimal planting scheme of plant factory crop growth and corresponding control unit set values, gives a control adjustment strategy for a greenhouse control system, outputs a control instruction and issues various execution modules (mechanisms such as a driving motor, a switch and the like), thereby realizing the automatic control of the simulation experiment greenhouse. Meanwhile, the effects of energy conservation and efficiency improvement are achieved. Provides theoretical guidance for plant factory design, production, development and environmental regulation.
The above-mentioned embodiments are intended to illustrate the technical solutions and advantages of the present invention, and it should be understood that the above-mentioned embodiments are only the most preferred embodiments of the present invention, and are not intended to limit the present invention, and any modifications, additions, equivalents, etc. made within the scope of the principles of the present invention should be included in the scope of the present invention.

Claims (10)

1. A plant factory integrated control system, comprising:
a production management database which comprises resource data, environment data, production data and marketing data of the plant factory;
an operation planning module integrating production conditions forms an initial production scheme according to a preset production period and a production operation database on the basis of the principle of highest economic benefit, and corrects the initial production scheme according to the mechanism characteristics of plants under the initial production scheme and the actual energy consumption cost of a plant factory to obtain an optimal production scheme;
the plant production process simulator simulates the mechanism characteristics of the plant under the initial production scheme according to the real-time growth environment and feeds back the mechanism characteristics to the operation planning module for correcting the initial production scheme;
the energy consumption control module is used for calculating the actual energy consumption cost of the plant factory under the initial production scheme by using the multi-medium energy consumption model and feeding the actual energy consumption cost back to the operation planning module for correcting the initial production scheme;
and the information acquisition and environment control module is used for acquiring the real-time growth environment of the plant and controlling the growth environment of the plant according to the optimal production scheme output by the operation plan module integrating the production conditions.
2. The integrated plant factory control system according to claim 1, wherein said plant production process simulator simulates plant mechanistic characteristics under different production schemes using a preset plant growth mechanism model library and a growth environment control model library;
the plant growth mechanism model library comprises at least one plant growth mechanism model;
the growing environment control model library comprises at least one growing environment control model.
3. The integrated plant factory control system according to claim 2, wherein said optimal production schedule output by said operation schedule module includes production operation schedule schedules for plants in corresponding production cycles and corresponding growth environment control setpoint values.
4. The plant factory integrated control system according to claim 3, wherein the initial production schedule is formed by solving the following objective function under the constraints of raw material market supply constraints, product market demand constraints and plant volume constraints of the seedbed:
<math> <mrow> <msup> <mi>MaxP</mi> <mi>k</mi> </msup> <mo>=</mo> <munder> <mo>&Sigma;</mo> <mi>i</mi> </munder> <mrow> <msubsup> <mi>D</mi> <mi>i</mi> <mi>k</mi> </msubsup> <mo>*</mo> <msubsup> <mi>s</mi> <mi>i</mi> <mi>k</mi> </msubsup> </mrow> <mo>-</mo> <munder> <mo>&Sigma;</mo> <mi>n</mi> </munder> <mrow> <msubsup> <mi>Q</mi> <mi>n</mi> <mi>k</mi> </msubsup> <mo>*</mo> <msubsup> <mi>v</mi> <mi>n</mi> <mi>k</mi> </msubsup> </mrow> <mo>-</mo> <munder> <mo>&Sigma;</mo> <mi>u</mi> </munder> <munder> <mo>&Sigma;</mo> <mi>m</mi> </munder> <msubsup> <mi>R</mi> <mrow> <mi>u</mi> <mo>,</mo> <mi>m</mi> </mrow> <mi>k</mi> </msubsup> <mo>*</mo> <mi>W</mi> </mrow> </math>
wherein, PkFor the plant wide profit for the kth production cycle,
the demand for the ith plant in the kth production cycle,
for the sale price of the ith plant in the kth production cycle,
for the procurement of the nth material in the kth production period,
for the purchase price of the nth material in the kth production period,
bed throughput of the mth bed in the mth production scenario during the kth production cycle;
w is the average energy consumption coefficient of the seedbed in each production period.
5. The integrated plant factory control system of claim 4, wherein said raw material market supply constraints are as follows:
<math> <mfenced open = '' close = ''> <mtable> <mtr> <mtd> <mrow> <msubsup> <mi>Q</mi> <mi>n</mi> <mrow> <mi>l</mi> <mi>o</mi> <mi>w</mi> </mrow> </msubsup> <mo>&le;</mo> <msubsup> <mi>Q</mi> <mi>n</mi> <mi>k</mi> </msubsup> <mo>&le;</mo> <msubsup> <mi>Q</mi> <mi>n</mi> <mrow> <mi>u</mi> <mi>p</mi> </mrow> </msubsup> </mrow> </mtd> <mtd> <mrow> <mo>&ForAll;</mo> <mi>k</mi> <mo>,</mo> <mi>n</mi> <mo>,</mo> </mrow> </mtd> </mtr> </mtable> </mfenced> </math>
wherein,the lower limit of the procurement amount of the nth material,is the upper limit of the procurement amount of the nth raw material.
6. The integrated plant factory control system of claim 4, wherein said product market demand constraints are as follows:
<math> <mfenced open = '' close = ''> <mtable> <mtr> <mtd> <mrow> <msubsup> <mi>D</mi> <mi>i</mi> <mrow> <mi>l</mi> <mi>o</mi> <mi>w</mi> </mrow> </msubsup> <mo>&le;</mo> <msubsup> <mi>D</mi> <mi>i</mi> <mi>k</mi> </msubsup> <mo>&le;</mo> <msubsup> <mi>D</mi> <mi>i</mi> <mrow> <mi>u</mi> <mi>p</mi> </mrow> </msubsup> </mrow> </mtd> <mtd> <mrow> <mo>&ForAll;</mo> <mi>i</mi> <mo>,</mo> <mi>k</mi> <mo>,</mo> </mrow> </mtd> </mtr> </mtable> </mfenced> </math>
wherein,the lower limit of the demand of the i-th plant,the upper limit of the demand of the i-th plant.
7. The integrated plant factory control system according to claim 4, wherein said planting amount of said seedbed is constrained by:
<math> <mfenced open = '' close = ''> <mtable> <mtr> <mtd> <mrow> <msubsup> <mi>R</mi> <mi>u</mi> <mrow> <mi>l</mi> <mi>o</mi> <mi>w</mi> </mrow> </msubsup> <mo>&le;</mo> <munder> <mo>&Sigma;</mo> <mi>m</mi> </munder> <msubsup> <mi>R</mi> <mrow> <mi>u</mi> <mo>,</mo> <mi>m</mi> </mrow> <mi>k</mi> </msubsup> <mo>&le;</mo> <msubsup> <mi>R</mi> <mi>u</mi> <mrow> <mi>u</mi> <mi>p</mi> </mrow> </msubsup> </mrow> </mtd> <mtd> <mrow> <mo>&ForAll;</mo> <mi>u</mi> <mo>&Element;</mo> <mi>U</mi> <mo>,</mo> <mi>k</mi> <mo>,</mo> <mi>m</mi> <mo>,</mo> </mrow> </mtd> </mtr> </mtable> </mfenced> </math>
the u-th seedbed is at the lower limit of the seedbed production capacity of the m-th production scheme,the u-th seedbed was at the upper limit of the seedbed throughput of the m-th production scheme.
8. The integrated plant factory control system according to any one of claims 1 to 7, wherein the multi-media energy consumption model of the plant factory is as follows:
<math> <mrow> <mtable> <mtr> <mtd> <mrow> <msub> <mi>E</mi> <mrow> <mi>u</mi> <mo>,</mo> <mi>c</mi> </mrow> </msub> <mo>=</mo> <msub> <mi>&alpha;</mi> <mrow> <mi>u</mi> <mo>,</mo> <mi>c</mi> </mrow> </msub> <msub> <mi>F</mi> <mi>u</mi> </msub> <mo>+</mo> <msub> <mi>&beta;</mi> <mrow> <mi>u</mi> <mo>,</mo> <mi>c</mi> <mo>,</mo> <mi>p</mi> </mrow> </msub> <msub> <mi>PP</mi> <mrow> <mi>c</mi> <mo>,</mo> <mi>p</mi> </mrow> </msub> <mo>+</mo> <msub> <mi>&theta;</mi> <mrow> <mi>u</mi> <mo>,</mo> <mi>c</mi> </mrow> </msub> <msub> <mi>OP</mi> <mi>u</mi> </msub> <mo>+</mo> <msub> <mi>CD</mi> <mrow> <mi>u</mi> <mo>,</mo> <mi>c</mi> </mrow> </msub> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <mo>&ForAll;</mo> <mi>c</mi> <mo>&Element;</mo> <mi>C</mi> <mo>,</mo> <mi>p</mi> <mo>&Element;</mo> <mi>P</mi> <mo>,</mo> <mi>u</mi> <mo>&Element;</mo> <mi>U</mi> </mrow> </mtd> </mtr> </mtable> <mo>,</mo> </mrow> </math>
wherein C is an energy medium set;
p is a mechanism characteristic set;
u is a seedbed set;
Eu,cthe requirement of the seedbed u for the energy medium c;
Futhe amount of cultivation of the seedbed u;
PPu,pis the mechanism characteristic of the plant cultivated on the seedbed u;
OPua planting scheme of a seedbed u;
CDu,ca fixed utility of energy medium c consumed for the seedbed u, constant;
αu,cthe energy consumption coefficient of the cultivation number of the seedbed u to the energy medium c;
βu,c,pthe energy consumption coefficient of the mechanism characteristic p of the plant cultivated on the seedbed u to the energy medium c;
θu,cthe energy consumption coefficient of the energy medium c for the planting scheme of the seedbed u.
9. A plant factory integrated control method is characterized in that an initial production scheme is formed according to a preset production period and a production operation database on the basis of the principle that economic benefit is the highest, and the initial production scheme is corrected according to mechanism characteristics of plants under the initial production scheme and actual energy consumption cost to obtain the optimal production scheme with the highest economic benefit.
10. The integrated plant factory control method according to claim 9, wherein the modification of the initial production schedule is performed by:
step 1, calculating to obtain the actual energy consumption cost of the plant factory according to an initial production scheme;
step 2, comparing the actual energy consumption cost and the initial energy consumption cost of the plant factory:
if the difference value between the two is smaller than the threshold value, taking the initial production scheme as the optimal production scheme;
otherwise, updating the initial energy consumption cost to be the current actual energy consumption cost, calculating the average energy consumption coefficient of the seedbed in each production period by using the updated initial energy consumption cost, solving according to the calculation result to obtain a new initial production scheme, and returning to the step 1.
CN201510528624.5A 2015-08-25 2015-08-25 A kind of plant factor's integrated control system and method Expired - Fee Related CN105159257B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201510528624.5A CN105159257B (en) 2015-08-25 2015-08-25 A kind of plant factor's integrated control system and method

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201510528624.5A CN105159257B (en) 2015-08-25 2015-08-25 A kind of plant factor's integrated control system and method

Publications (2)

Publication Number Publication Date
CN105159257A true CN105159257A (en) 2015-12-16
CN105159257B CN105159257B (en) 2017-09-19

Family

ID=54800143

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201510528624.5A Expired - Fee Related CN105159257B (en) 2015-08-25 2015-08-25 A kind of plant factor's integrated control system and method

Country Status (1)

Country Link
CN (1) CN105159257B (en)

Cited By (24)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106772693A (en) * 2016-11-18 2017-05-31 广西大学 Temperature prompt system
CN107368111A (en) * 2016-08-01 2017-11-21 北京航空航天大学 A kind of set based on Plant Light period-interleaving maintains the method for oxygen and gas concentration lwevel stabilization in plant factor
CN107870611A (en) * 2016-09-28 2018-04-03 横河电机株式会社 Workshop analogue means and workshop analogy method
CN108012912A (en) * 2017-12-15 2018-05-11 浙江清华长三角研究院 A kind of nutrient solution adjust automatically cyclic irrigation System and method for based on Internet of Things
WO2018133353A1 (en) * 2017-01-18 2018-07-26 深圳前海弘稼科技有限公司 Nutrient solution control method and control device
CN108460695A (en) * 2018-03-28 2018-08-28 辛庆强 A kind of agriculture and animal husbandry siphunculus reason systems and management method
CN108762140A (en) * 2018-05-21 2018-11-06 江西省计算技术研究所 A kind of green house of vegetables monitor control system and method
CN110226499A (en) * 2019-05-31 2019-09-13 大连民族大学 A kind of device and application method of flexible solar thin web induction self water feeding
CN110488690A (en) * 2019-08-05 2019-11-22 安徽众星电气科技有限公司 A kind of batch production dendrobium nobile ecological park automatic control system
CN110786208A (en) * 2019-11-28 2020-02-14 贵州光合新植科技有限公司 Plant planting technology evolution method based on artificial illumination planting technology
CN110996653A (en) * 2017-06-29 2020-04-10 二氧化碳I有限公司 Environmental control system
CN111399470A (en) * 2020-04-29 2020-07-10 中国建材国际工程集团有限公司 Plant factory control system
CN111615969A (en) * 2020-04-28 2020-09-04 青岛理工大学 Greenhouse water and fertilizer integrated control system based on PLC and control method thereof
CN111665887A (en) * 2020-07-02 2020-09-15 广州形银科技有限公司 Data monitoring equipment for communication technology
CN111683521A (en) * 2018-01-08 2020-09-18 海德罗花园有限公司 Method for selecting and delivering edible plants with specific nutrient components
CN112005679A (en) * 2020-08-20 2020-12-01 大连理工大学 Water and fertilizer integrated distribution method for precision agriculture
CN112465316A (en) * 2020-11-16 2021-03-09 中国科学院合肥物质科学研究院 Price factor-integrated aeroponic crop nutrient solution demand response regulation and control evaluation system
CN113168599A (en) * 2019-07-04 2021-07-23 欧姆龙株式会社 Plant cultivation management system and plant cultivation management device
CN113163725A (en) * 2018-09-28 2021-07-23 洛科威国际有限公司 Plant growth control system
CN113190064A (en) * 2021-04-12 2021-07-30 中国农业大学 Optimal control method for light intensity of plant factory
CN113554294A (en) * 2021-07-15 2021-10-26 上海赛扬信息技术有限公司 Plant factory operation management method, device and system based on BIM technology
WO2023087483A1 (en) * 2021-11-18 2023-05-25 江苏大学 Greenhouse environment optimization design method considering crop production benefits and energy consumption reduction
TWI817135B (en) * 2021-06-08 2023-10-01 遠東科技大學 Method, computer program and computer readable medium for automatically selecting energy-saving environmental control apparatus in agricultural field
CN117762078A (en) * 2024-02-22 2024-03-26 连云港银丰食用菌科技有限公司 Intelligent control method for edible fungus room environment

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102736596A (en) * 2012-06-11 2012-10-17 南京农业大学 Multi-scale greenhouse environment control system based on crop information fusion
CN102835278A (en) * 2012-09-18 2012-12-26 浙江大学 Multi-source combined cold and heat supply simulated experiment greenhouse
JP2013005766A (en) * 2011-06-26 2013-01-10 Yukio Kurokawa Plant factory for japan restoration
CN202694113U (en) * 2012-06-29 2013-01-23 南京农业大学 Greenhouse environmental control system fused with crop information
CN103884075A (en) * 2014-01-06 2014-06-25 浙江工业大学 Computational fluid dynamics and energy prediction hybrid based greenhouse energy-saving control method

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2013005766A (en) * 2011-06-26 2013-01-10 Yukio Kurokawa Plant factory for japan restoration
CN102736596A (en) * 2012-06-11 2012-10-17 南京农业大学 Multi-scale greenhouse environment control system based on crop information fusion
CN202694113U (en) * 2012-06-29 2013-01-23 南京农业大学 Greenhouse environmental control system fused with crop information
CN102835278A (en) * 2012-09-18 2012-12-26 浙江大学 Multi-source combined cold and heat supply simulated experiment greenhouse
CN103884075A (en) * 2014-01-06 2014-06-25 浙江工业大学 Computational fluid dynamics and energy prediction hybrid based greenhouse energy-saving control method

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
徐立鸿 等: "面向控制的温室系统小气候环境模型要求与现状", 《农业工程学报》 *

Cited By (30)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107368111A (en) * 2016-08-01 2017-11-21 北京航空航天大学 A kind of set based on Plant Light period-interleaving maintains the method for oxygen and gas concentration lwevel stabilization in plant factor
CN107368111B (en) * 2016-08-01 2020-04-21 北京航空航天大学 Method for maintaining stable concentrations of oxygen and carbon dioxide in plant factory based on plant photoperiod staggered setting
CN107870611A (en) * 2016-09-28 2018-04-03 横河电机株式会社 Workshop analogue means and workshop analogy method
CN106772693A (en) * 2016-11-18 2017-05-31 广西大学 Temperature prompt system
WO2018133353A1 (en) * 2017-01-18 2018-07-26 深圳前海弘稼科技有限公司 Nutrient solution control method and control device
CN110996653A (en) * 2017-06-29 2020-04-10 二氧化碳I有限公司 Environmental control system
CN108012912A (en) * 2017-12-15 2018-05-11 浙江清华长三角研究院 A kind of nutrient solution adjust automatically cyclic irrigation System and method for based on Internet of Things
CN111683521A (en) * 2018-01-08 2020-09-18 海德罗花园有限公司 Method for selecting and delivering edible plants with specific nutrient components
CN108460695A (en) * 2018-03-28 2018-08-28 辛庆强 A kind of agriculture and animal husbandry siphunculus reason systems and management method
CN108762140A (en) * 2018-05-21 2018-11-06 江西省计算技术研究所 A kind of green house of vegetables monitor control system and method
CN113163725A (en) * 2018-09-28 2021-07-23 洛科威国际有限公司 Plant growth control system
CN110226499A (en) * 2019-05-31 2019-09-13 大连民族大学 A kind of device and application method of flexible solar thin web induction self water feeding
CN113168599A (en) * 2019-07-04 2021-07-23 欧姆龙株式会社 Plant cultivation management system and plant cultivation management device
EP3996012A4 (en) * 2019-07-04 2023-08-02 OMRON Corporation Plant cultivation management system and plant cultivation management device
CN110488690A (en) * 2019-08-05 2019-11-22 安徽众星电气科技有限公司 A kind of batch production dendrobium nobile ecological park automatic control system
CN110786208A (en) * 2019-11-28 2020-02-14 贵州光合新植科技有限公司 Plant planting technology evolution method based on artificial illumination planting technology
CN111615969A (en) * 2020-04-28 2020-09-04 青岛理工大学 Greenhouse water and fertilizer integrated control system based on PLC and control method thereof
CN111399470A (en) * 2020-04-29 2020-07-10 中国建材国际工程集团有限公司 Plant factory control system
CN111665887A (en) * 2020-07-02 2020-09-15 广州形银科技有限公司 Data monitoring equipment for communication technology
CN112005679A (en) * 2020-08-20 2020-12-01 大连理工大学 Water and fertilizer integrated distribution method for precision agriculture
CN112465316A (en) * 2020-11-16 2021-03-09 中国科学院合肥物质科学研究院 Price factor-integrated aeroponic crop nutrient solution demand response regulation and control evaluation system
CN112465316B (en) * 2020-11-16 2024-05-03 中国科学院合肥物质科学研究院 Mist culture crop nutrient solution demand response regulation and evaluation system integrating price factors
CN113190064A (en) * 2021-04-12 2021-07-30 中国农业大学 Optimal control method for light intensity of plant factory
CN113190064B (en) * 2021-04-12 2022-06-14 中国农业大学 Optimal control method for light intensity of plant factory
TWI817135B (en) * 2021-06-08 2023-10-01 遠東科技大學 Method, computer program and computer readable medium for automatically selecting energy-saving environmental control apparatus in agricultural field
CN113554294A (en) * 2021-07-15 2021-10-26 上海赛扬信息技术有限公司 Plant factory operation management method, device and system based on BIM technology
WO2023087483A1 (en) * 2021-11-18 2023-05-25 江苏大学 Greenhouse environment optimization design method considering crop production benefits and energy consumption reduction
GB2621942A (en) * 2021-11-18 2024-02-28 Univ Jiangsu Greenhouse environment optimization design method considering crop production benefits and energy consumption reduction
CN117762078A (en) * 2024-02-22 2024-03-26 连云港银丰食用菌科技有限公司 Intelligent control method for edible fungus room environment
CN117762078B (en) * 2024-02-22 2024-06-11 连云港银丰食用菌科技有限公司 Intelligent control method for edible fungus room environment

Also Published As

Publication number Publication date
CN105159257B (en) 2017-09-19

Similar Documents

Publication Publication Date Title
CN105159257B (en) A kind of plant factor&#39;s integrated control system and method
US10390496B2 (en) Environmental control system for plant growth management
CN104798627B (en) The automaton of plant growth environment
Brechner et al. Hydroponic lettuce handbook
CN102835278B (en) Multi-source combined cold and heat supply simulated experiment greenhouse
Achour et al. Supervisory model predictive control for optimal operation of a greenhouse indoor environment coping with food-energy-water nexus
WO2020133669A1 (en) Plant factory
CN204796328U (en) Vegetables wisdom big -arch shelter based on thing networking
CN101002533A (en) Calculation method for multiple factor coordination control of greenhouse environment
Revathi et al. Design of solar-powered forced ventilation system and energy-efficient thermal comfort operation of greenhouse
CN112425502B (en) Intelligent ETFE air pillow type film structure plant rapid growth environment adjusting device
CN114946447A (en) Artificial intelligence-based plant growth parameter decision method and system
Udovichenko et al. Framework for design and optimization of a retrofitted light industrial space with a renewable energy-assisted hydroponics facility in a rural northern canadian community
Montero et al. Greenhouse engineering: new technologies and approaches
CN214546341U (en) Gas turbine generator set power supply three-dimensional plant cultivation system
CN113625806A (en) Efficiency-optimal greenhouse plant regulation and control method facing carbon neutralization demand
Morozova Methodology for controlling greenhouse microclimate parameters and yield forecast using neural network technologies
CN115606438A (en) Intelligent regulation and control device and method for animal and plant illumination
KR20200053833A (en) Plant cultivating apparatus
Bot A validated physical model of greenhouse climate
Zhang et al. Environmental control of PFALs
KR20220086292A (en) Growth period control system
Van Henten et al. Improving the efficiency of greenhouse climate control: an optimal control approach
Ghaffarpour et al. Calculation of energy consumption, tomato yield, and electricity generation in a PV-integrated greenhouse with different solar panels configuration
Kumar et al. Climate regulation in protected structures: A review

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
C10 Entry into substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant
CF01 Termination of patent right due to non-payment of annual fee

Granted publication date: 20170919

Termination date: 20200825

CF01 Termination of patent right due to non-payment of annual fee