System and method for irradiating a crop

Abstract

System and method are disclosed for irradiating a crop of plants. The system (1) comprises a power consuming irradiation system (3) for irradiating the crop (11); and a data processing system comprising at least one processor (10), which is configured to: - receive or determine a prediction of a carbon intensity (24) of a power supply over a period of time; - receive or determine properties of the irradiation system (3), the properties including a relation between a power consumption of the irradiation system and a light output of the irradiation system (3); - receive or determine a contribution of the light output of the irradiation system over the period of time to a carbon footprint of the crop or a component thereof, based on the properties of the irradiation system and the prediction of the carbon intensity (24) of the power supply over the period of time; - receive or determine one or more radiation constraints for the crop over at least the period of time; - determine a radiation recipe that minimises the carbon footprint of the crop or the component thereof while satisfying the one or more radiation constraints, based on the contribution of the light output of the irradiation system over the period of time to the carbon footprint of the crop or component thereof; and - control the irradiation system (3) to irradiate the crop (11) in accordance with the determined radiation recipe.

Description

[0001] System and method for irradiating a crop

[0002] TECHNICAL FIELD

[0003] This disclosure relates to a system for irradiating a crop, in particular to such system comprising an irradiation system for irradiating the crop; and a data processing system in controlling communication with the irradiation system and comprising at least one processor. This disclosure further relates to a corresponding computer-implemented method for irradiating a crop, and to a computer program and computer-readable storage medium for performing such method.

[0004] BACKGROUND

[0005] In many regions in the world, growing crops in greenhouses requires the addition of supplemental LED light during parts of days which may vary in the course of the year. In many vertical farms, those without any daylight, LED light is the sole source of light. Electric power consumed by the lighting forms a contribution to the carbon footprint of the produced crops. If more energy is consumed by the power consuming irradiation system, the carbon footprint of the crops is - in general - increased.

[0006] US 2019 / 259108 Al discloses different techniques of controlling an agricultural system, as for example a controlled agricultural system, an agricultural light fixture and a method for agricultural management. The document disclosed the concept of “Eco Certificates” wherein ecologically evaluated light recipes are used for illumination purposes or an ecological overall balance of the agricultural production method or of the agricultural production facility can be taken into account when selecting the illumination variants. Therein, aspects of life-cycle assessment, energy consumption or a carbon footprint are considered.

[0007] However, the above doesn’t take into account that different types of power contribute to a higher or lower extent to a carbon footprint. Power is supplied to the irradiation system from the grid, which encompasses power from a collection of energy sources. The energy source mix (combination of fossil, nuclear, and renewable energy) used to generate the electricity for supply to the energy consuming irradiation system changes from hour to hour, and can be predicted for hours and days to come. There is a clear trend towards paying for electricity per carbon footprint (amount of CO2 emission per unit of sellable crops, instead of paying for electricity usage (kWh)).

[0008] In light of the above, there is a need in the art for a system and method for improving the performance of systems and methods in terms of carbon footprint. To the best knowledge of the creators of the present disclosure, this approach to crop growing has not been attempted at all before the date of submission of the present disclosure.

[0009] SUMMARY

[0010] To that end, a system for irradiating a crop is disclosed. The system comprises: an irradiation system for irradiating the crop; and a data processing system in controlling communication with the irradiation system and comprising at least one processor, wherein the processor is configured to:

[0011] - receive or determine a prediction of a carbon intensity of a power supply over a period of time;

[0012] - receive or determine properties of the irradiation system, the properties including a relation between a power consumption of the irradiation system and a light output of the irradiation system;

[0013] - receive or determine a contribution of the light output of the irradiation system over the period of time to a carbon footprint of the crop or a component thereof, based on the properties of the irradiation system and the prediction of the carbon intensity of the power supply over the period of time;

[0014] - receive or determine one or more radiation constraints for the crop over at least the period of time;

[0015] - determine a radiation recipe that minimises the carbon footprint of the crop or the component thereof while satisfying the one or more radiation constraints, based on the contribution of the light output of the irradiation system over the period of time to the carbon footprint of the crop or component thereof; and

[0016] - control the irradiation system to irradiate the crop in accordance with the determined radiation recipe.

[0017] Especially also the prediction of a variation in the carbon intensity of a power supply over time is received or determined.

[0018] Preferred embodiments are defined in the appended dependent claims. In the system according to the present disclosure, the processor may further be configured to receive or determine one or more variables related to the power supply, the radiation, and / or the crop or component thereof; wherein determining the radiation recipe comprises optimizing the one or more variables related to the power supply, the radiation, and / or the crop, to achieve a minimized carbon footprint for the crop..

[0019] In the system according to the present disclosure, each of the one or more variables related to the power supply, the radiation, and / or the crop or component thereof may be assigned an adjustable weight; and the determination of the radiation recipe may use a weighted optimisation algorithm.

[0020] In the system according to the present disclosure, the one or more variables related to the power supply, the radiation, and / or the crop may be one of:

[0021] - a cost of electricity per unit energy supplied by the power supply,

[0022] - a cost of electricity per unit weight of the crop or component thereof, and / or

[0023] - a light-use-efficiency.

[0024] In the system according to the present disclosure, the one or more radiation constraints may comprise at least one of:

[0025] - a daily-light-integral,

[0026] - a daily-photosynthesis-integral,

[0027] - a minimum dark period,

[0028] - a minimum light period,

[0029] - a periodic crop production, or

[0030] - a periodic harvest.

[0031] In the system according to the present disclosure, the period of time may be at least 2 hours, at least 6 hours, at least 12 hours, or at least 24 hours.

[0032] In the system according to the present disclosure, the processor may further be configured to receive or determine a further prediction for a carbon intensity of a further power supply over the period of time; and the determination of the radiation recipe may then further be based on the further prediction for a carbon intensity of a further power supply over the period of time.

[0033] In the system according to the present disclosure, the processor may further be configured to receive or determine power grid data, and determining the radiation recipe may then comprises optimising based on the power grid data.

[0034] In the system according to the present disclosure, the radiation recipe may comprise at least a time-dependent intensity of radiation over the period of time. In the system according to the present disclosure, the at least one processor may further be configured to: receive or determine an additional prediction of a carbon intensity of the power supply over a further period of time, the further period of time being longer than the period of time; and then determine at least one of the one or more radiation constraints based on the additional prediction of a carbon intensity of the power supply over a further period of time.

[0035] In the system according to the present disclosure, the processor may further be configured to receive or determine a prediction of a natural radiation intensity over the period of time and / or, if applicable, the further period of time; and determining the radiation recipe may then comprise optimising based on the prediction of the natural radiation intensity over the period of time and / or, if applicable, the further period of time.

[0036] The system according to the present disclosure may further comprise an interface configured to enable an operator or user to define and / or modify at least one of the one or more radiation constraints.

[0037] In a further aspect, the present disclosure relates to a computer-implemented method for irradiating a crop by controlling an irradiation system, comprising:

[0038] - receiving or determining a prediction of a carbon intensity of a power supply over a period of time;

[0039] - receiving or determining properties of the irradiation system, the properties including a relation between a power consumption of the irradiation system and a light output of the irradiation system;

[0040] - receiving or determining a contribution of the light output of the irradiation system over the period of time to a carbon footprint of the crop or a component thereof, based on the properties of the irradiation system and the prediction of the carbon intensity of the power supply over the period of time;

[0041] - receiving or determining one or more radiation constraints for the crop over the period of time;

[0042] - determining a radiation recipe that minimises the carbon footprint of the crop or the component thereof while satisfying the one or more radiation constraints, based on the contribution of the light output of the irradiation system over the period of time to the carbon footprint of the crop or component thereof; and

[0043] - using the determined radiation recipe for controlling the irradiation system.

[0044] Thus, a system as described above and hereinafter may be controlled using this method. The method may be executed, for example, by the data processing system described above and hereinafter. Moreover, a computer program for carrying out the methods described herein, as well as a computer readable storage-medium storing the computer program are provided. A computer program may, for example, be downloaded by or uploaded to an existing device or be stored upon manufacturing of these systems.

[0045] A computer-readable storage medium stores at least one software code portion, the software code portion, when executed or processed by a computer, being configured to perform executable operations comprising: obtaining a target light level, determining a first set of light settings for a set of one or more lights and / or a first set of daylight blocker settings for a set of one or more daylight blockers based on said target light level, controlling said set of lights based on said first set of light settings and / or said set of daylight blockers based on said first set of daylight blocker settings, receiving from a user device information indicating a quality of a data signal received by said user device from one or more lights of said set of lights, said data signal being transmitted by modulating a light signal and said signal quality being determined by said user device, determining a second set of light settings for said set of lights based on said first set of light settings and said determined signal quality and / or a second set of daylight blocker settings for said set of daylight blockers based on said first set of daylight blocker settings and said determined signal quality, and controlling said set of lights based on said second set of light settings and / or said set of daylight blockers based on said second set of daylight blocker settings.

[0046] As will be appreciated by one skilled in the art, aspects of the present invention may be embodied as a device, a method or a computer program product. Accordingly, aspects of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment (including firmware, resident software, microcode, etc.) or an embodiment combining software and hardware aspects that may all generally be referred to herein as a "circuit", "module" or "system." Functions described in this disclosure may be implemented as an algorithm executed by a processor / microprocessor of a computer. Furthermore, aspects of the present invention may take the form of a computer program product embodied in one or more computer readable medium(s) having computer readable program code embodied, e.g., stored, thereon.

[0047] Any combination of one or more computer readable medium(s) may be utilized. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a computer readable storage medium may include, but are not limited to, the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of the present invention, a computer readable storage medium may be any tangible medium that can contain, or store, a program for use by or in connection with an instruction execution system, apparatus, or device.

[0048] A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.

[0049] Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fibre, cable, RF, etc., or any suitable combination of the foregoing. Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java(TM), Smalltalk, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer, or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider).

[0050] Aspects of the present invention are described below with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the present invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor, in particular a microprocessor or a central processing unit (CPU), of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer, other programmable data processing apparatus, or other devices create means for implementing the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0051] These computer program instructions may also be stored in a computer readable medium that can direct a computer, other programmable data processing apparatus, or other devices to function in a particular manner, such that the instructions stored in the computer readable medium produce an article of manufacture including instructions which implement the function / act specified in the flowchart and / or block diagram block or blocks.

[0052] The computer program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0053] The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of devices, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the blocks may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and / or flowchart illustrations, and combinations of blocks in the block diagrams and / or flowchart illustrations, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Aspects of the invention will be explained in greater detail by reference to exemplary embodiments shown in the drawings, in which:

[0055] FIG. 1 schematically illustrates a system for irradiating a crop according to an embodiment;

[0056] FIG. 2 schematically illustrates steps of a method according to an embodiment;

[0057] FIG. 3 schematically illustrates carbon intensities of power from three distinct grids at different locations in the same period of time;

[0058] FIG. 4 schematically illustrates variation of carbon intensity of power from a single grid over the course of a day;

[0059] FIG. 5 schematically illustrates a strategy (recipe) of supplemental irradiation for growing tomatoes;

[0060] FIG. 6 schematically illustrates a recipe of supplemental irradiation for growing tomatoes according to the principles of the present disclosure;

[0061] FIG. 7 schematically illustrates temperature variation in a greenhouse over the course of a day;

[0062] FIG. 8 schematically illustrates CO2 level variations in a greenhouse over the course of a day;

[0063] FIG. 9 schematically illustrates a recipe for irradiating plants in a vertical farm without daylight; and

[0064] FIG. 10 is a block diagram of an exemplary data processing system for performing the method of the invention.

[0065] DETAILED DESCRIPTION OF THE DRAWINGS

[0066] In the figures, the same or similar reference numbers indicate identical or similar elements, components or functional units.

[0067] In Fig. 1, an exemplary system 1 for irradiating a crop of plants 11 is shown, for example in a green house. However, the present disclosure may equally well be deployed in a vertical farm setting, which may be closed off and receive no daylight. System 1 comprises a power consuming irradiation system 3, comprising light sources 5, for example LED light sources, which are connected to a hub 7. Hub 7 is provided with electrical energy by a grid 13 forming a power supply for allowing irradiation system 3 to consume power for converting the electrical power into irradiation to promote growth of the crop of plants 11. Power from grid 13 is distributed over light sources 5 by hub 7. A secondary or auxiliary or local grid 15 may additionally be present.

[0068] Hub 7 is further connected to a data processing system comprising at least one processor 10. Processor 10 is able to acquire information on carbon intensity of power supplied by grid 13 from a source 9. If a secondary or auxiliary or local grid 15 is present, processor 10 may acquire information on carbon intensity of power supplied by grid 15 from the same source 9 or an additional source 17. A network, such as the internet, may be present between either of the sources 9, 17 and processor 10.

[0069] More in detail, the information on carbon intensity may be received or determined by processor 10. Information on carbon intensity provides a measure of the amount of carbon released for the production of power from either grid 13 or 15 at a plurality of times during a period of time, because carbon intensity may vary in the course of the time period. This, i.e., the variability of the carbon intensity of electricity over time, is in fact a basis of the insight resulting in the present disclosure.

[0070] Namely, processor 10 is configured to perform the method steps of Fig. 2, which do not necessarily need to be performed in the shown and described order in time.

[0071] In step 201, processor 10 receives or determines a prediction of a carbon intensity of a power supply over a period of time. The prediction provides insight into carbon intensity variations in the course of the time period which may be a prognosis that is instantaneously generated, possibly by processor 10 or remotely or can be based on experience or prior knowledge. For example, a contribution by solar power to the power supply via either of grids 13, 15 diminishes at night, which could be indicative of a higher carbon intensity. A very coarse estimate of carbon intensity variation may therefore already quite easily be obtained, acquired, received or determined, for processor 10 to use, i.e. high carbon intensity at night and low(er) in the day time, even without any instantaneous input into the computer or data processing system being necessary, in particular if a grid or power supply exhibits a sufficient and predictable degree of periodicity (e.g. day / night rhythm). This may also apply to the below described further and additional prediction(s) of carbon intensity of any power supply in any period of time.

[0072] In step 202, processor 10 receives or determines properties of the irradiation system, the properties including a relation between a power consumption of the irradiation system and a light output of the irradiation system. It is noted that the properties may be determined beforehand, and stored in a memory, for processor 10 to retrieve. However, for taking changes in the irradiation system into account, a regular update of this irradiation system characteristic is recommendable, and in an ultimate extreme embodiment, the processor may take instantaneous variations in the radiation system into account for determining this irradiation system characteristic.

[0073] In step 203, processor 10 receives or determines a contribution of the light output of the irradiation system over the period of time to a carbon footprint of the crop or a component thereof, based on the properties of the irradiation system and the prediction of the carbon intensity of the power supply over the period of time. In this step, an amount of released carbon is correlated to irradiation from the irradiation system for irradiating the crop of plants 11. Preferably this is determined by processor 10, and for a plurality of time slots at different locations within the periods of time, and / or for longer / shorter periods of time.

[0074] Ahead of step 203, or following step 203, in step 204 processor 10 receives or determines one or more radiation constraints for the crop of plants over at least the period of time. The radiation constraints may relate to a longer or shorter time period than the period of time. Therefrom, an irradiation amount for the irradiation system 3 to furnish to the crop of plants 11 in the period of time may be obtained, possibly after deducting an amount of daytime light from the desired amount of irradiation. In doing so, processor 10 may take an amount of sunlight in the daytime and a minimum dark period into account, as well as other constraints, such as a daily-light-integral (DLI), a daily-photosynthesis-integral, a minimum light period, a periodic crop production, or a periodic harvest. In any case, the controlling process would have to encompass parameters for optimal development of the crop of plants 11, taking the previous or already achieved development (and thus the stage of development of the crop of plants 11) into account.

[0075] In step 205, processor 10 determines a radiation recipe that minimises the carbon footprint of the crop or the component thereof while satisfying the one or more radiation constraints, based on the contribution of the light output of the irradiation system over the period of time to the carbon footprint of the crop or component thereof. This is to say that processor 10 determines when, in the period of time, the irradiation system should be activated to use power / energy at the lowest available carbon intensity to result in the lowest possible carbon footprint, while securing the best possible irradiation recipe in relation to the requirements of the crop of plants 11, on the basis of the radiation constraints.

[0076] After having determined the optimum recipe, which is optimized in terms of the amounts of irradiation required for proper development of the crop of plants 11 in accordance with the constraints and of the carbon intensity of power / energy available at distinct times during the period of time, processor 10 controls the irradiation system to irradiate the crop in accordance with the determined radiation recipe.

[0077] Thus, requirements of the crop of plants 11 for proper or optimized further development according to crop or plant 11 related constraints may be met, by activating the irradiation system 3 at times or in time slots during which the contribution of the irradiation system 3 to the carbon footprint of the crop of plants 11 is minimized. The referenced minimalization of the carbon footprint of the crop of plants may be limited to the period of time or to the time slots during which the irradiation system 3 is activated, or to a lengthier time up to and including the entire development cycle of the crop of plants 11.

[0078] Therefore, optionally, processor 10 can receive or determine one or more variables related to the power supply, the radiation, and / or the crop or component thereof; and determine the radiation recipe by extremising or optimizing the one or more variables related to the power supply, the radiation, and / or the crop, as well as the timing of activating the irradiation system 3, to achieve a minimalized carbon footprint for the crop of plants 11. In such an embodiment, each of the one or more variables related to the power supply, the radiation, and / or the crop or component thereof is assigned an adjustable weight; and the determination of the radiation recipe uses a weighted optimisation algorithm to arrive at a recipe at which the timing of activating the irradiation system 3 is optimized in terms of the carbon footprint of the crop of plants 11 ultimately produced. With or without the weighted optimization, the one or more variables related to the power supply, the radiation, and / or the crop may be one of: a cost of electricity per unit energy supplied by the power supply, a cost of electricity per unit weight of the crop or component thereof, confidence level in the prediction of the carbon intensity of the electricity supply, a light-use-efficiency, a modification or operation to be performed on the crop, time periods with availability of natural radiation, time periods with an oversupply of electricity in the grid, a cost of labour to be performed on the crop, and / or a net profit. Regarding the confidence level for the prediction of the carbon intensity, it is noted here, that in practice, the quality of the carbon intensity prediction of electricity may vary considerably. Al systems may be used to provide a confidence level for its predicted carbon intensity. Modification / operations performed on crops may involve pruning, trimming of the plants by machines or workers, and the like. This complements cost of labour performed on plants and both are clearly plant related parameters.

[0079] Regarding potential oversupply, its noted here that with the rise of solar and wind power, there is occasionally too much power available in the grid. For instance, it is known that our streetlighting in German cities is occasionally switched on at noon during a sunny and windy day in Northern Germany to help bum off the excess solar / wind energy from the grid. In The Netherlands, quite a number of growers participate in “emergency power” contracts with the central power infrastructure company TenneT with the aim to stabilize the grid. In case there is too much power available, these growers switch on the irradiation system and get paid to do so.

[0080] A duration of the period of time may be 2, 6, 12, or at least 24 hours. Or it may encompass weeks, months or even a year or more, or even the entire growth cycle of the crop of plants 11. Additionally or alternatively, the period of time may encompass a period in which the carbon intensity of the power supply to the irradiation system 3 may be predictable on the basis of instantaneously provided information, or on the basis of prior knowledge. In a possible embodiment, processor 10 may receive or determine a further prediction for a carbon intensity of a further power supply over the period of time; and the determination of the radiation recipe is further based on the further prediction for a carbon intensity of a further power supply over the period of time. This allows the processor to select the further power supply, which may be formed by a secondary or auxiliary or local grid 15 to be selected for supply of power / energy to the irradiation system 3, based on carbon intensity information from either of the sources 9, 17. This may involve a trade-off between lower capacity but low footprint power / energy from a mainly sustainable source grid 15 with much low-carbon-intensity power / energy against a higher power energy requirement for the irradiation system 3 to be fulfilled by a mainly carbon intense primary power supply 13, or a mix thereof.

[0081] The processor 10 may further be configured to receive or determine an additional prediction of a carbon intensity of the power supply over a further period of time. Then, the further period of time is for example longer than the period of time. The processor 10 may then determine at least one of the one or more radiation constraints based on the additional prediction of a carbon intensity of the power supply over a further period of time.

[0082] For application in a greenhouse, the processor may further be configured to receive or determine a prediction of a natural radiation intensity. Determining the radiation recipe then comprises optimising based on the prediction of the natural radiation intensity. Therein, the natural radiation intensity can be deducted from the requirement and constraints, and only supplemental irradiation needs to be generated by the irradiation system 3 to furnish optimal amounts of light at desired moments to the crop of plants 11, while minimizing the carbon footprint required to achieve this. An interface, forming an integral component of a computer containing processor 10, may be configured to allow a user or an operator to define and / or modify at least one of the one or more radiation constraints. This allows the operator to change settings when this may be considered necessary. The interface may be displayed on a monitor connected to the computer or data processing system 300 in figure for performing the method of the invention

[0083] The creators of the present disclosure have recognized that the electricity cost per kWh is presently not or hardly at all correlated with the carbon intensity per kWh, while carbon footprint will in the future become an important factor when determining a cost of horticultural produce from crops of plants 11 and amounts of energy consumed therefore, as well as the nature (origin and carbon intensity) of energy consumed by irradiation system 3. There is therefore the need to optimize for the combination of electricity cost AND the carbon intensity AND horticulture yield over preferably entire growing cycles. Real-time information on the price of electricity and the carbon intensity as well as the 24h forecast as well as the 7-day forecast can be utilized. In one embodiment, in a vertical farm if there is a high carbon intensity forecasted for Wednesday and Thursday, the lighting and climate control may be pro-actively adjusted so that the plants enter a slow-growth state. Once the high carbon intensity event in the electricity grid is over, a high growth state can be induced to compensate for time lost during the high carbon intensity event and thereby it’s possible to maximally ensure the targeted yield and harvest date. Hence, while in current state of the art the same light recipe is repeated for all days of the week, or possibly varied only in dependence of the growth state of the crop of plants 11, it is proposed here to utilize adaptive light recipes to minimize the carbon intensity of electricity consumed by irradiation system 3, or only consume power at points or period in time within the period of time at which the carbon intensity of the consumed power is low, and - in doing so - reduce the carbon footprint of produce harvested from crops of plants 11.

[0084] Suitable measures (key-performance-indicators) for sustainability in the context of the present disclosure are:

[0085] • The grams of equivalent CO2 emitted to produce one kWh of electricity, referred to herein as carbon intensity; and

[0086] • The kg of equivalent CO2 emitted to power irradiation system 3 per kg of sellable produce from crops of plants 11 resulting from the deployment of the irradiation system 3, referred to herein as a carbon footprint. Currently, in most countries, the energy mix for generating electricity is a combination of fossil energy (gas or coal based), nuclear energy, and renewable energy (wind and solar based). Furthermore, this energy mix changes from hour to hour, since the availability of renewable energy changes from hour to hour and from day to day (e.g., due to the variability in wind velocity and daylight).

[0087] The challenge addressed in the present disclosure relates for example to supplemental LED lighting from irradiation system 3 to increase crop production at times when there is insufficient daylight, is the increase in carbon footprint.

[0088] For the horticulture domain, minimizing the carbon footprint of crop production by optimally scheduling the supplemental light is challenging: Minimizing the carbon footprint influences other factors, such as the cost of electricity, the light-use- efficiency, the net income, as well as the crop’s health.

[0089] The present disclosure aims to provide a solution to the aforementioned challenge of applying (supplemental) lighting through deployment of the irradiation system 3, such as to minimize the carbon footprint, while optimizing other goals and obeying boundary conditions and constraints, e.g. related to crop development.

[0090] The herein proposed method entails one or more of the following:

[0091] • Determine a constraint for a crop such as a desired daily-light-integral (DLI), to ensure a healthy crop or a desired fruit weight.

[0092] • Retrieve a forecast of the carbon intensity for the coming period (e.g., the coming 2 hours, the coming day, or coming days).

[0093] • Distribute the supplemental light over the coming period in such a manner that the carbon footprint is minimized and the constraint is obeyed.

[0094] • Next to minimizing the carbon footprint and obeying the constraint, at the same time, another quantity is optimized by giving it a relative weight. Examples of such other quantities are: o Cost of electricity (€ / kWh or € / kg), to be minimized o Light-use-efficiency (g / mol or g / kWh), to be maximized o Cost of labour performing the manual work on the plants in the greenhouse, to be minimized o Net income (€ / kg), to be maximized

[0095] • The relative weight factors can / will vary over the day. For instance, the cost of labour for performing the manual clipping on the plants in the greenhouse is higher during night hours than during 09:00-17:00. As workers in a vertical farm can only perform their manual tasks with the light switched on, the optimized scheduling based on minimizing the carbon intensity and the optimized scheduling for minimizing the labour cost may conflict with each other.

[0096] Instead of (or in addition to) using a desired DLI (or range of DLIs) as a constraint, more / other constraints are possible:

[0097] • A desired daily-photosynthesis-integral.

[0098] • A desired (daily) crop production or harvest (biomass increase of the whole plant or the fruits).

[0099] It is noted that it is possible to have a storage battery in between the electricity grid and the lighting infrastructure. In that case, instead of energizing irradiation system 3 to consume energy and ‘applying supplement light’, the consumed energy may be used for ’charging the battery’ .

[0100] It is expected that vertical farms may utilize hybrid solutions with some electricity coming from the grid and some being produced locally.

[0101] Similarly, greenhouses may utilize gas to both heat the greenhouse as well as generate their own electricity (called CHP (Co-generation of Heat and Power)). We propose that when the carbon intensity of the electricity obtained from the utility grid is high, the CHP is activated despite no heating being required (typically, the heat generated can be stored in a water buffer). When the carbon intensity of the grid has improved, the CHP may be switched off.

[0102] Fig. 3 schematically illustrates variations in time of carbon intensities of power from three distinct grids 13, 15 in the same period of time. These graphs may have been derived, optionally and possibly instantaneously by the processor, from (raw) power grid data. From visual inspection of this illustration in Fig. 3, it is immediately evident that a lowermost graph for one of the three grids 13 is the only one that appears to exhibit a daily rhythm to some degree, while the other two 15 are more erratic, in that these appear to exhibit less temporal patterns. However, based on this insight, irradiation system 3 may be controlled by controller 10 to select one of the grids 13, 15 for consumption of power therefrom, that exhibits a lower carbon intensity at any given point in time during the period of time.

[0103] Fig. 4 shows variations through the day of carbon intensity of power from a grid 13 in a graph 24. Contributions from solar energy sources cause a dip in carbon intensity of energy supplied by grid 13 in the middle of the day. Exploiting such a dip by consuming energy during these hours of the day allows for a reduction of the carbon footprint for growing the produce of the crop of plants 11. However, clearly, there’s a trade-off, because at those hours there’s likely to be enough daylight.

[0104] Herein below, an exemplary exploitation of the concepts according to the present disclosure is set out. As an example, growing tomatoes is considered in a high-tech greenhouse equipped with supplemental lighting. Tomatoes in general require a certain total amount of photosynthetically active light during a day, called daily-light-integral (DLI), expressed in mol / m2 / day. This desired amount of light depends, among others, on plant load (the number of fruits per m2), the desired fresh weight of the fruits, the fruit development period (the time it takes for a small fruit to become a harvestable fruit), and the light-use- efficiency (the number of grams of tomato resulting from a mole of photosynthetically active light (a mole being a number of photons equal to Avogadro’s constant (6.0 1023))). The part of light that is photosynthetically active is the part in the wavelength range 400 nm - 700 nm.

[0105] For tomatoes, in The Netherlands during the period from autumn until spring, the desired DLI is typical in the range 14 - 16 mol / m2 / day. In case the DLI supplied is too low, the tomatoes will not achieve their desired weight. Also, the quality of the plants and tomatoes will be adversely affected.

[0106] Since in The Netherlands during the period from autumn until spring daylight alone is on many days not sufficient to reach a desired DLI, supplemental light is needed.

[0107] In Figure 5, a typical situation is shown during a day in winter or a cloudy day in summer.

[0108] The DLI of the daylight alone is 9.7 mol / m2 / day in this example (line 20). To reach a desired DLI of 15 mol / m2 / day, the supplemental lighting needs to produce the additional 5.3 mol / m2 / day (line 21 indicating the recipe for supplemental irradiation). The total accrued irradiation is at line 22.

[0109] In this example, the greenhouse is equipped with dimmable LED lighting with a maximum light output of 200 pmol / m2 / s (dotted line 23). The distribution of the supplemental light over the day is chosen such that the total amount of photosynthesis is maximized (photosynthesis equals the amount of CO2 assimilated per m2per second). Here, the fact that the efficiency of photosynthesis is lower at higher light levels is taken into account (for which an advanced photosynthesis model was used). Also, the fact that plants need a preferably contiguous dark period (typically 6 hours for tomato) is included. Data displayed in Figure 7 and 8 for respectively temperature and CO2 level in the greenhouse was also included. Similar graphs for costs of electricity, which also varies in the course of a day, are readily available. Namely, the skilled person would be much inclined to deploy an irradiation strategy or recipe like the one in Fig. 5, in view of the fact that the efficiency of photosynthesis is lower at higher light levels. Notwithstanding this prejudice, it is proposed here to adjust the recipe to, for example, the irradiation distribution of Fig. 6.

[0110] According to the recipe of Fig. 6, the same amount of supplemental light is irradiated onto the plants 11 in a distribution over the day at which the carbon intensity 24 in Fig. 4 is low, such as to result in the lowest attainable carbon footprint. The results are shown in Figure 6 and set out in the below table:

[0111] Here also use was made use of the data shown in Fig. 4 for carbon intensity distribution in time for the grid 13. Distributing the supplemental light over the day such as to maximize photosynthesis results in a carbon footprint of 2.03 kg equivalent CO2 emitted per kg of tomato produced. Distributing the supplemental light such as to minimize the carbon footprint on the other hand more than halves the carbon footprint, albeit at the expense of the photosynthesis. Alternatively, a compromise is reached by optimizing both on photosynthesis as well as carbon footprint (for the example, resulting in a decrease in carbon footprint of 35% whereas photosynthesis decreases by only 6%).

[0112] Figure 9 shows a graph 21 for irradiation of plants 11 in a vertical farm setting, without daylight, which graph 21 again represents a recipe for deployment of the irradiation system 3. In this Fig. 9, also an approximation is included of the graph 24 in Fig. 4 representing the carbon intensity of power in the form of electricity, supplied by grid 13 over the course of a day.

[0113] A traditional recipe for irradiating for instance lettuce when growing lettuce in a vertical farm setting would yield a horizontal graph below the maximum available irradiation of irradiation system 3 according to line 23, for most of the day, for example 18 hours with a light level of 200 pmol / m2 / s, and a selectable number of dark hours (e.g. 6 dark hours). However, as shown in Fig. 9, irradiation system 3 is deployed using a recipe in accordance with the principles of the present disclosure and irradiates maximally at 300 pmol / m2 / s during hours at which the carbon intensity according to line 24 is low. This yields a far reduced carbon footprint for produce from a crop of (here: lettuce) plants 11 :

[0114] Herein above, it was assumed that the installed maximum light level is 300 pmol / m2 / s. Installing higher light levels allows to minimize the carbon footprint even further, albeit that it requires a higher investment.

[0115] It is noted here that multiple aspects of horticulture may be optimized together, which may require intricate calculations, which the skilled person is readily capable of developing for implementation on or by a computer. Such aspects, in addition to carbon footprint and carbon intensity, comprise any one or more than one of light-use efficiency, electricity cost, DLI (as mentioned above), grower income, et cetera.

[0116] Fig. 10 depicts a block diagram illustrating an exemplary data processing system that may be at the heart of the system and / or perform the method as described herein reference.

[0117] As shown in Fig. 10, the data processing system 300 may include at least one processor 302 coupled to memory elements 304 through a system bus 306. As such, the data processing system may store program code within memory elements 304. Further, the processor 302 may execute the program code accessed from the memory elements 304 via a system bus 306. In one aspect, the data processing system may be implemented as a computer that is suitable for storing and / or executing program code. It should be appreciated, however, that the data processing system 300 may be implemented in the form of any system including a processor and a memory that is capable of performing the functions described within this specification.

[0118] The memory elements 304 may include one or more physical memory devices such as, for example, local memory 308 and one or more bulk storage devices 310. The local memory may refer to random access memory or other non-persistent memory device(s) generally used during actual execution of the program code. A bulk storage device may be implemented as a hard drive or other persistent data storage device. The processing system 300 may also include one or more cache memories (not shown) that provide temporary storage of at least some program code in order to reduce the quantity of times program code must be retrieved from the bulk storage device 310 during execution. The processing system 300 may also be able to use memory elements of another processing system, e.g. if the processing system 300 is part of a cloud-computing platform.

[0119] Input / output (I / O) devices depicted as an input device 312 and an output device 314 optionally can be coupled to the data processing system. Examples of input devices may include, but are not limited to, a keyboard, a pointing device such as a mouse, a microphone (e.g. for voice and / or speech recognition), or the like. Examples of output devices may include, but are not limited to, a monitor or a display, speakers, or the like. Input and / or output devices may be coupled to the data processing system either directly or through intervening VO controllers.

[0120] In an embodiment, the input and the output devices may be implemented as a combined input / output device (illustrated in Fig. 10 with a dashed line surrounding the input device 312 and the output device 314). An example of such a combined device is a touch sensitive display, also sometimes referred to as a “touch screen display” or simply “touch screen”. In such an embodiment, input to the device may be provided by a movement of a physical object, such as e.g. a stylus or a finger of a user, on or near the touch screen display.

[0121] A network adapter 316 may also be coupled to the data processing system to enable it to become coupled to other systems, computer systems, remote network devices, and / or remote storage devices through intervening private or public networks. The network adapter may comprise a data receiver for receiving data that is transmitted by said systems, devices and / or networks to the data processing system 300, and a data transmitter for transmitting data from the data processing system 300 to said systems, devices and / or networks. Modems, cable modems, and Ethernet cards are examples of different types of network adapter that may be used with the data processing system 300.

[0122] As pictured in Fig. 10, the memory elements 304 may store an application 318. In various embodiments, the application 318 may be stored in the local memory 308, the one or more bulk storage devices 310, or separate from the local memory and the bulk storage devices. It should be appreciated that the data processing system 300 may further execute an operating system (not shown in Fig. 10) that can facilitate execution of the application 318. The application 318, being implemented in the form of executable program code, can be executed by the data processing system 300, e.g., by the processor 302. Responsive to executing the application, the data processing system 300 may be configured to perform one or more operations or method steps described herein.

[0123] Various embodiments of the invention may be implemented as a program product for use with a computer system, where the program(s) of the program product define functions of the embodiments (including the methods described herein). In one embodiment, the program(s) can be contained on a variety of non-transitory computer-readable storage media, where, as used herein, the expression “non-transitory computer readable storage media” comprises all computer-readable media, with the sole exception being a transitory, propagating signal. In another embodiment, the program(s) can be contained on a variety of transitory computer-readable storage media. Illustrative computer-readable storage media include, but are not limited to: (i) non-writable storage media (e.g., read-only memory devices within a computer such as CD-ROM disks readable by a CD-ROM drive, ROM chips or any type of solid-state non-volatile semiconductor memory) on which information is permanently stored; and (ii) writable storage media (e.g., flash memory, floppy disks within a diskette drive or hard-disk drive or any type of solid-state random-access semiconductor memory) on which alterable information is stored. The computer program may be run on the processor 302 described herein.

[0124] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and / or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0125] The corresponding structures, materials, acts, and equivalents of all means or step plus function elements in the claims below are intended to include any structure, material, or act for performing the function in combination with other claimed elements as specifically claimed. The description of embodiments of the present invention has been presented for purposes of illustration, but is not intended to be exhaustive or limited to the implementations in the form disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope of the present invention. The embodiments were chosen and described in order to best explain the principles and some practical applications of the present invention, and to enable others of ordinary skill in the art to understand the present invention for various embodiments with various modifications as are suited to the particular use contemplated.

Claims

CLAIMS:

1. A system for irradiating a crop, the system comprising: an irradiation system for irradiating the crop; and a data processing system in controlling communication with the irradiation system and comprising at least one processor, wherein the processor is configured to: receive or determine a prediction of a carbon intensity of a power supply over a period of time; receive or determine properties of the irradiation system, the properties including a relation between a power consumption of the irradiation system and a light output of the irradiation system; receive or determine a contribution of the light output of the irradiation system over the period of time to a carbon footprint of the crop or a component thereof, based on the properties of the irradiation system and the prediction of the carbon intensity of the power supply over the period of time; receive or determine one or more radiation constraints for the crop over at least the period of time; determine a radiation recipe that minimizes the carbon footprint of the crop or the component thereof while satisfying the one or more radiation constraints, based on the contribution of the light output of the irradiation system over the period of time to the carbon footprint of the crop or component thereof; and control the irradiation system to irradiate the crop in accordance with the determined radiation recipe.

2. The system as claimed in claim 1, wherein the processor is further configured to receive or determine one or more variables related to the power supply, the radiation, and / or the crop or component thereof; and wherein determining the radiation recipe comprises optimizing the one or more variables related to the power supply, the radiation, and / or the crop to achieve a minimized carbon footprint for the crop.

3. The system as claimed in claim 2, wherein each of the one or more variables related to the power supply, the radiation, and / or the crop or component thereof is assigned an adjustable weight; and wherein the determination of the radiation recipe uses a weighted optimisation algorithm.

4. The system as claimed in any one of claim 2 or claim 3, wherein the one or more variables related to the power supply, the radiation, and / or the crop is one of: a cost of electricity per unit energy supplied by the power supply, a cost of electricity per unit weight of the crop or component thereof, confidence level in the prediction of the carbon intensity of the electricity supply, a light-use-efficiency, a modification or operation to be performed on the crop, time periods with availability of natural radiation, and / or time periods with an oversupply of electricity in the grid.

5. The system as claimed in any one of the preceding claims, wherein the one or more radiation constraints comprise at least one of: a daily-light-integral, a daily-photosynthesis-integral, a minimum dark period, and / or a minimum light period.

6. The system as claimed in any one of the preceding claims, wherein the period of time is at least 2 hours, at least 6 hours, at least 12 hours, or at least 24 hours.

7. The system as claimed in any one of the preceding claims, wherein the processor is further configured to receive or determine a further prediction for a carbon intensity of a further power supply over the period of time; and wherein the determination of the radiation recipe is further based on the further prediction for a carbon intensity of a further power supply over the period of time.

8. The system as claimed in any one of the preceding claims, wherein the processor is further configured to receive or determine power grid data, and wherein determining the radiation recipe comprises optimising based on the power grid data.

9. The system as claimed in any one of the preceding claims, wherein the radiation recipe comprises at least a time-dependent intensity of radiation over the period of time.

10. The system as claimed in any one of the preceding claims, wherein the at least one processor is further configured to: receive or determine an additional prediction of a carbon intensity of the power supply over a further period of time, the further period of time being longer than the period of time; and determine at least one of the one or more radiation constraints based on the additional prediction of a carbon intensity of the power supply over the further period of time.

11. The system as claimed in any one of the preceding claims, wherein the processor is further configured to receive or determine a prediction of a natural radiation intensity over the period of time and / or, when dependent on claim 10, over the further period of time; and wherein determining the radiation recipe comprises optimising based on the prediction of the natural radiation intensity over the period of time and / or, when dependent on claim 10, over the further period of time.

12. The system as claimed in any one of the preceding claims, further comprising an interface configured to enable an operator or user to define and / or modify at least one of the one or more radiation constraints.

13. A computer-implemented method for irradiating a crop by controlling an irradiation system, the method comprising:receiving or determining a prediction of a carbon intensity of a power supply over a period of time; receiving or determining properties of the irradiation system, the properties including a relation between a power consumption of the irradiation system and a light output of the irradiation system; receiving or determining a contribution of the light output of the irradiation system over the period of time to a carbon footprint of the crop or a component thereof, based on the properties of the irradiation system and the prediction of the carbon intensity of the power supply over the period of time; receiving or determining one or more radiation constraints for the crop over the period of time; determining a radiation recipe that minimises the carbon footprint of the crop or the component thereof while satisfying the one or more radiation constraints, based on the contribution of the light output of the irradiation system over the period of time to the carbon footprint of the crop or component thereof; and using the determined radiation recipe for controlling the irradiation system.

14. A computer program comprising instructions which, when executed by a data processing system of a system as claimed in one of claims 1 to 12, causes the system to perform the method as claimed in claim 13.

15. A computer-readable storage medium having stored thereon a computer program as claimed in claim 14.

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