FR3134282A1 - Method for controlling an agrivoltaic device. - Google Patents

Abstract

Method for controlling an agrivoltaic system, comprising: - a shade house comprising mobile photovoltaic panels arranged above a set of cultivated plants, - a real-time control and data acquisition system, to control the position horizontal, vertical or angular of the panels, and - an optimization module, to determine the optimal position of the panels based at least on the phenological stage of said plants, with reference to a model comprising for each plant: a set of phenological stages and a correspondence between said stage and at least one of: - a set of physiological needs; - a set of agro-climatic sensitivities; - a set of agro-climatic indicators; to place plants in microclimatic conditions favorable to obtaining a desired agricultural result while seeking to achieve optimum photoelectric energy production compared to a reference outside plant cultivation. Figure for abstract: Fig. 2.

Description

Method for controlling an agrivoltaic device.

The present invention relates to the field of agrivoltaism, that is to say a production of electrical energy using photovoltaic cells coupled with agricultural production, the aim of which is to protect crops from climatic hazards and modulate the microclimate in the face of climate change, in order to ensure viable, sustainable agricultural production and solar-powered electricity production on the same surface.

Agricultural production is ensured by a set of cultivated plants. The plants can be the same or different.

Electricity production is ensured by a set of photovoltaic panels arranged on a supporting structure, covering all or part of the cultivated plants. As described later, the photovoltaic panels are mobile, for example to follow the path of the sun.

Optimizing electricity production generally involves orienting photovoltaic panels perpendicular to the sun's rays. But this optimization of electricity production can prove to be detrimental to the optimization of agricultural production, for example due to a shadow cast by photovoltaic panels on cultivated plants.

There are solutions that seek to resolve this technological challenge, in particular through the example given in the state of the prior art document FR3019274.

The present invention aims to further improve existing solutions.

For the purposes of the present invention, “variety” and “cultivar” are understood indiscriminately.

The notion of “variety” is not limited to that of taxonomic rank. It must be understood within the meaning of the present invention as the cultivated plant or its type. We will therefore speak of agricultural production of a “variety” of fruit trees, as much as of agricultural production of a “variety” of strawberries, etc.

By modifying the microclimatic conditions under an agrivoltaic device, the present invention makes it possible to reduce abiotic stress (water, thermal and radiative) for plants, ensure their physiological needs, protect them against climatic hazards, and makes it possible to find a synergy between production agricultural and photovoltaic electricity production.

More precisely, the invention relates, according to a first of its objects, to a method of controlling an agrivoltaic device, said agrivoltaic device comprising:

- a set of photovoltaic panels arranged above an area comprising a set of cultivated plants,

- a set of actuators, configured to modify the position of said set of panels,

- a supporting structure which supports the photovoltaic panels, said panels being movable in at least one of: in rotation relative to a horizontal axis; in translation in a horizontal plane, in translation along a vertical axis, so as to be able to adopt several horizontal, vertical or angular positions thanks to said set of actuators, and arranged at a height less than a predetermined value of a set of cultivated plants , the shadow projected on the plants by the photovoltaic panels being modified by the change in position or angle of said panels, thus modifying the microclimatic conditions of the area comprising all of the cultivated plants;

- a real-time control and data acquisition system, configured to control the horizontal, vertical or angular position of the set of photovoltaic panels,

– a server, configured to receive and store agro-climatic data and comprising an optimization module comprising lines of code defining its operation and configured to issue control instructions to the control system for the position of the photovoltaic panels;

the method comprising steps consisting of:

- determine the phenological stage at which said plants are found;

- receive, through an optimization module, a set of agro-climatic data relating to the area including a set of cultivated plants;

- calculate, by the optimization module, a set of agro-climatic indicators based on said agro-climatic data,

- transmit, by the optimization module to the control system, a control instruction, including the horizontal, vertical or angular position that at least one photovoltaic panel must adopt for a given period, the control instruction being a function of the set of agro-climatic indicators.

In particular, the calculation by the optimization module of a set of agro-climatic indicators can be implemented thanks to modeling taking into account the impact of photovoltaic panels on the microclimate. We can link these indicators to the conditions for good development of crops by phenological stage, allowing the construction of the yield and the quality of agricultural production and calculate the electrical production thanks to a modeling of the electrical output for any position of the photovoltaic panels.

We can predict that the control instruction is determined by an optimization algorithm, having been previously trained on a set of agro-climatic data composed of data constructed using data from local climatic histories and evolution models. climate, allowing relevant decisions to be made given the variety of climate scenarios that may occur.

The set of agro-climatic indicators can take into account the microclimatic impact of the agrivoltaic system.

In particular, we can predict that the microclimatic impact of the agrivoltaic device is taken into account thanks to modeling of the microclimate induced by the agrivoltaic device, such as the shadow cast, the temperature of the air, of the ground, the potential evapotranspiration , hygrometry, wind, soil humidity, etc. using data from the shade house dimensional calculation module.

Electricity production can take into account all the positions of the photovoltaic panels, thanks to modeling of the electric production which can in particular calculate the loss of electric production when the panels are not in an angular position corresponding to maximum production.

We can plan to calculate, by the optimization module, the microclimate modulation and protection needs for the plants based on the relevant agro-climatic indicators, specific to cultivated plants, the impact of these indicators on the potential yield of the cultivated plants, for each phenological stage determined elsewhere.

We can also provide a step consisting of:

- assign a weight to each calculated agro-climatic indicator; the weight assigned being a function of the phenological stage determined.

More precisely, we can plan to assign a weight to each calculated agro-climatic indicator and to electricity production; the weight assigned being a function of the impact on the potential yield of the crops, a function of the phenological stage determined and which can be positive or negative depending on its impact on agricultural and electrical production. These weights allow the optimization algorithm to determine the position of the panels, ensuring the proper development of crops while ensuring significant electrical production.

We can predict that the agro-climatic data is sent by at least one of:

- local agro-climatic sensors, placed under the set of photovoltaic panels;

- remote agro-climatic sensors, arranged at a distance less than a predetermined value from the area comprising said set of cultivated plants, but not under the set of photovoltaic panels;

- satellite sensors;

agro-climatic data can also be:

- historical data recorded in a memory; And

- weather forecast data.

We can plan at least one of the steps among:

- a determination of the physiological needs of said plants by phenological stage;

- a modeling of the electrical production of said photovoltaic panels at least per time step and by the relative position of said photovoltaic panels and the sun;

- a dimensional calculation of the supporting structure which supports the photovoltaic panels;

- a determination of the microclimatic conditions of the area comprising all the cultivated plants of the agrivoltaic system;

- a modeling of the desired agricultural result of said plants, according to the agro-climatic indicators of said plants, for each phenological stage of said plants;

the control instruction being a function of at least one of said steps.

We can also provide steps consisting of:

- detect or predict a predetermined climatic or meteorological event; And

- issue an instruction to control the horizontal, vertical or angular position of at least one photovoltaic panel, depending on the moment at which said climatic or meteorological event is predicted or detected.

It is also possible to provide a step consisting of simulating the electrical production of the agrivoltaic device as a function at least of its latitude and the relative position of the photovoltaic panels relative to the sun, said photovoltaic panels being able to be bifacial.

We can provide an automatic learning step, configured to simultaneously optimize the production of electricity of photovoltaic origin and the agricultural production of said plants,

the learning being based on said agro-climatic data.

Preferably, the training of the algorithm for optimizing the control instructions for photovoltaic panels uses historical agro-climatic data, and allows learning through varied and diversified climatic scenarios in order to generate control instructions for the photovoltaic panels. the position of the panels of the agrivoltaic device maximizing agricultural and electrical production.

It can be envisaged that the step consisting of determining the phenological stage at which said plants are found is implemented by declaration, by calendar date, by image processing of said plants, or by accumulation of degrees/day, possibly including an effect shading.

It can be envisaged that the agrivoltaic device is also connected to a set of at least one meteorological station, possibly in a network;

the agro-climatic data received by the optimization module being issued at least by said set of at least one meteorological station.

According to another of its objects, the invention also relates to a computer program comprising program code instructions for executing the steps of the method according to the invention, when said program is executed on a computer.

Other characteristics and advantages of the present invention will appear more clearly on reading the following description given by way of illustrative and non-limiting example and made with reference to the appended figures.

illustrates an agrivoltaic device according to the prior art;

illustrates a functional diagram for the implementation of an embodiment of the method according to the invention;

illustrates the sending of agro-climatic data to a server according to the invention.

detailed description

The present invention is based on determining the phenological stage of cultivated plants, and on controlling the position of the photovoltaic panels in particular at the determined phenological stage.

Preferably, the phenological stages are those of the BBCH scale.

We can provide a set of phenological stages per plant or group of plants (for example pome fruits, notably vines; stone fruits, etc.).

*Agrivoltaic device*

An agrivoltaic device, also called a “shade”, is illustrated on the .

It includes a supporting structure which supports a set of photovoltaic panels.

The cultivated plants can be of any type and for example be market gardens, vines, trees – particularly fruit trees, shrubs, etc. including a plurality of different plants.

It is planned to determine the phenological stage, of development or growth, at which said plants are found, for example the emergence from dormancy, budding, flowering, maturation, etc.

For example, the phenological stage can be declared, in particular via a graphical interface. It can also be determined by calendar date, more precisely by the difference between today's date and the sowing date, or by day degrees.

It can also be determined by image processing of said plants. For example, we produce a set of images of cultivated plants, manually, by camera or by drone, and image processing software makes it possible to determine the phenological stage. Preferably for this purpose, artificial intelligence software is implemented including learning adapted to each cultivated plant. Finally, the phenological stage can also be determined by a calculation of the cumulative degree days, this calculation possibly including an effect of the agrivoltaic installation on the microclimate.

Phenological stage can be determined by several of the preceding means.

There is therefore a sharing of solar light radiation between photovoltaic panels and cultivated plants, indiscriminately called “crops”.

An optimization module described later makes it possible to optimize agricultural production and photovoltaic production, that is to say, to optimize this light sharing. For example, in the meiosis phase, we can plan to promote sunlight for cultivated plants to the detriment of photovoltaic electricity production.

By the presence of photovoltaic panels arranged above part of the cultivated plants, the shade structure has an impact on them because it creates shade, it therefore has an impact on the radiation, on the wind local, on soil humidity (evapotranspiration is then limited), on temperature, etc.

Photovoltaic panels can also serve as physical protection (for example against hail), and have a microclimatic impact (temperature, radiation, etc.) on the cultivated area.

The supporting structure comprises uprights which support a framework on which the photovoltaic panels are articulated.

Photovoltaic panels are mobile.

Preferably, they are mobile in rotation from east to west to follow the solar path. We can therefore modify their angular position. In this case they are movable in rotation relative to a horizontal axis, and movable in translation in a horizontal or vertical plane, as illustrated by the double arrows on the , thanks to a set of actuators.

The photovoltaic panels can be retractable or even stackable.

They can thus adopt:
- several horizontal positions, for example to move the shadow projected from photovoltaic panels onto cultivated plants,
- several vertical positions, for example by adjusting the height of the photovoltaic panels on the supporting structure, which also makes it possible to modify the shadow projected by the photovoltaic panels on the cultivated plants, and
- several angular positions, for example to adapt the angular position of the photovoltaic panels to the position of the sun.

The position or orientation of the photovoltaic panels modifies the microclimatic conditions of the cultivated plants of the agrivoltaic device, for example depending on the shade projected (or not), which impacts the irradiance received by the crops, the leaf temperature, the hygrometry, soil temperature, evapotranspiration of the soil or wind passing between the photovoltaic panels and the cultivated plants.

The present invention makes it possible to adapt the position or orientation of photovoltaic panels according to the physiological needs of crops or their needs for protection against climatic hazards.

*SCADA*

The agrivoltaic device is expected to include a real-time control and data acquisition system, known by the acronym SCADA for Supervisory Control And Data Acquisition in English, which is a large-scale remote management system allowing remote control technical installations, and which is configured to control the horizontal, vertical or angular position of all the photovoltaic panels.

* Agro-climatic sensors *

The agrivoltaic device is expected to comprise a set of at least one agro-climatic sensor.

Agro-climatic sensors can be local, that is to say placed under the set of photovoltaic panels.

The agro-climatic sensors can be remote, that is to say arranged at a distance less than a predetermined value from the area comprising said set of cultivated plants, but not under the set of photovoltaic panels.

Typically, remote agro-climatic sensors are placed at a distance from the area comprising all the cultivated plants. Preferably, the remote agro-climatic sensors are located in a geographical area likely to have a meteorological or climatic impact on the area comprising all of the cultivated plants, for example upstream of the prevailing winds.

We can also provide satellite sensors which make it possible to measure or calculate a meteorological or climatic impact on the area comprising all the cultivated plants.

Agro-climatic data can come from local, remote or satellite agro-climatic sensors, as illustrated in the .

They can also come from a server memory which records historical data, for example historical data from local or remote agro-climatic sensors.

They can also come from a memory of a server which calculates weather forecasts.

Agro-climatic data can come from all or part of the sources cited above, that is to say that agro-climatic data can be combined, for example satellite data are combined with local agro-climatic data, forecasts are combined with local agro-climatic data, etc.

For example, a low pressure system is detected by a satellite. A weather model predicts thunderstorms over the area including all cultivated plants within a predetermined time frame. Local agro-climatic sensors do not yet detect any variation in pressure, temperature or humidity, but remote agro-climatic sensors detect a sudden variation in at least one of these values.

Agro-climatic data, from local or remote agro-climatic sensors, or weather forecasts, make it possible, for example, to detect or predict a predetermined climatic or meteorological event.

Agro-climatic data is sent to a remote server.

* Server *

We provide a remote server which is configured to receive agro-climatic data, and issue instructions for controlling the position of all the panels to the SCADA, as illustrated in the figure. .

The server includes lines of code, governing the operation of a plurality of modules described below, which make it possible to determine the position of the photovoltaic panels in order to maximize agricultural and electrical production, based at least on the agro-climatic indicators calculated , then to send to the SCADA the position control instructions for all the panels of the agrivoltaic device.

* Agro-climatic indicators *

From agro-climatic data, preferably local agro-climatic data (measured or transposed), we can plan to calculate a set of agro-climatic indicators over different periods of the year or phenological stages.

Preferably, agro-climatic indicators depend on the plants grown.

Agro-climatic indicators can be a known index, for example a drought index, a night coolness index, Huglin index, rainfall distribution, etc. which are calculated or known from a database.

Agro-climatic indicators can be a combination or ratio of agro-climatic data, for example an incident radiation/temperature index, which has a particular influence on photosynthesis, etc.

Agro-climatic indicators can also be an accumulation of agro-climatic data, for example an accumulation of sunshine, an accumulation of temperature; an accumulation of irradiance received, in particular at a predetermined height from the ground over a predetermined period, an accumulation of radiation received for photosynthetically active radiation greater than 800 µmol.m ^-2 .s ^-1 , an accumulation of rain, a number of dry days, a number of rainy days (preferably with a daily amount of rain > 1mm), a number of annual frost days, a number of frost days in spring, a maximum duration of frost days, a sum freezing temperature, a number of hot days where the temperature is higher than 27°C, a number of very hot days where the temperature is higher than 30°C, a cumulative average temperature over a period, a cumulative average temperature base 6° C over a period, a cumulative average temperature based on 0°C, a water deficit, in particular with a cumulative Rain evapotranspiration calculation over a period, a number of days with water deficit less than -5 mm over a predetermined period, etc.

We can plan to classify the agro-climatic indicators by phenological stage, that is to say, to calculate only the indicators of the phenological stage at which the cultivated plants are found.

* Description of cultivated plants *

Crops are described by sizing according to their stage of development (for example by measuring the height of the canopy, the length of the stem, etc.).

Crops are described according to a set of physiological characteristics, such as water, thermal or radiative stress limits and according to each phenological stage.

Crops are described by their relevant agro-climatic indicators, and their impact on the development and future yield and quality of agricultural production.

Crop sensitivities are defined here as the impact of relevant agro-climatic indicators on their development for the construction of agricultural yield, for each phenological stage, for example the cumulative scalding temperature will be relevant for wheat and will have an impact strongly negative during the rising period.

They are assigned values, negative or positive, in relation to reference values of agro-climatic indicators, representing the impact on the development of crops or the construction of yield or the quality of agricultural production;

* Weighting *

We can provide a weighting module, preferably by phenological stage, configured to assign a set of points to the indicators, and accumulate them according to the following criteria:

A set of points is allocated to electricity production, for example by increments of quantity produced or proportionally to the quantity produced;

A set of points is assigned to avoided stress;

A set of points is assigned to the amount of radiation or if the amount of radiation is greater than a predetermined threshold value;

Etc.

We can then accumulate all the points allocated and control the position of the panels according to the difference between the accumulation of all the points allocated and a predetermined threshold value.

For example, for each criterion, we calculate the difference between the accumulation of all the points allocated for said criterion and a predetermined threshold value for said criterion.

We can thus control the position of the photovoltaic panels, for example according to priority, starting with the criterion which presents the greatest difference.

For example, the quantity of cumulative radiation determined is less than a threshold value, and presents the greatest deviation. We can conclude that the photovoltaic panels cast too much shadow and that their position or orientation should be modified so as to allow more incident radiation to pass through.

The advantage of a weighting module by phenological stage is that, for two different phenological stages, the same sensors, even if they result in the same measurement values, will not give the same weightings, which makes it possible to control the position photovoltaic panels as close as possible to the real needs of cultivated plants, that is to say controlling the position of photovoltaic panels, therefore the production of electrical energy and the production of cultivated plants, by phenological stage.

* Modules *

An optimization module and at least one of the other modules described below are provided, in communication with the optimization module, and in this case all on the remote server.

* Heuristic module *

We can provide a heuristic module, which includes a set of rules, which correspond to a course of action, that is to say the position that the photovoltaic panels must adopt in the event of predetermined events, for example bad weather, or in the event of singular events, for example rainfall below or above a threshold value, a wind speed above a threshold value, an episode of hail, frost, an air or ground temperature below or above a threshold value, etc.

It is thus possible to protect the shade house or the plants, by calculating the risk or connecting to a weather station.

Preferably the heuristic module, if activated, bypasses all other modules.

* Optimization module *

The remote server is expected to include an optimization module, configured to optimize both photovoltaic energy production and crop production.

For this purpose, it aims to determine the optimal position of all the photovoltaic panels as a function at least of the relative position of said photovoltaic panels and the sun, and to place the plants in microclimatic conditions favorable to obtaining a desired agricultural result while seeking to achieve an optimum reducing the production of photoelectric energy as little as possible.

It makes it possible to determine the optimal position of photovoltaic panels from:
- agro-climatic data, which can be historical data, in real time, or predictions, and in this case based on agro-climatic indicators,
- information relating to cultivated plants (in particular the phenological stage),
- information on the structure of the agrivoltaic device.

The optimization module includes a calculator and a set of at least one memory, as well as wired or wireless communication means.

The optimization module is configured to receive data and issue control instructions.

In this case, the optimization module is configured to receive agro-climatic data or agro-climatic indicators.

The agro-climatic data includes at least one of:
- pedoclimatic data, which relate to all the external climatic conditions to which the soil of cultivated plants is subject, and for example temperature, hydromorphy, hygrometry, aeration, partial CO ₂ pressure , rainfall, wind, etc. ; And
- meteorological data, the processing of which aims to assist in the management of agricultural operations and agricultural forecasting.

The agro-climatic data is sent by at least one of the agro-climatic sensors.

At the output of the optimization module, it issues control instructions to the SCADA to optimally position the photovoltaic panels.

It can be expected that the optimization module includes a machine learning algorithm.

In this case, the machine learning algorithm is configured to simultaneously optimize the production of electricity from photovoltaic sources and the agricultural production of plants.

Preferably, a learning step is provided based on at least one of the data sets among:

- local and/or remote agro-climatic data, that is to say coming respectively from local and/or remote agro-climatic sensors, in real time, and described subsequently;

- historical data recorded in a memory; And

- weather forecast data.

We can plan a local and global predictive weather model, in time and space. For example, the weather model makes it possible to calculate a predetermined risk over a predetermined geographical area within a predetermined time range, for example a risk of rain on a plot in less than 3 hours, a heatwave episode in the region for the next 3 weeks, etc. . The model can include the calculation of a confidence index or a probability rate.

This makes it possible to anticipate the control of the shade house over a time horizon of a few hours to a few days.

We can plan a training step on local data, for example radiation, temperature, wind, humidity, etc.

We can provide a step for deciding the position (vertical, horizontal, angular) of the photovoltaic panels according to a predetermined time step, a predetermined sequence, for example slaved to the time of year.

For example, we can provide a decision step for the position (vertical, horizontal, angular) of the photovoltaic panels every hour in winter; every 10 minutes in summer, etc. or whose time step is slaved to the sunshine curve.

Preferably, a review stage is planned at the end of the year, consisting of determining at least the production of photovoltaic electrical energy.

* Module for determining physiological needs *

We can provide a module for determining the physiological needs of plants.

Indeed, plants are sensitive; for example, they are sensitive to cold, heat, frost, hail, drought, etc. and this sensitivity is a function in particular of the phenological stage but sometimes also of hygrometry.

Due to this sensitivity, agro-climatic conditions can put cultivated plants in a stressful situation.

Although stressful situations are generally considered to be avoided, certain stresses are nevertheless sought after, for example vines need controlled water stress to produce quality grapes for winemaking.

This module makes it possible to determine the physiological needs of plants by phenological stage, for example in the form of a correspondence table.

Typically, each phenological stage corresponds to a set of needs, for example, an average temperature, average daily sunshine, etc.

The physiological needs of plants may include, for example, the content of macroelements (carbon, oxygen, hydrogen, nitrogen, phosphorus, sulfur, potassium, calcium, magnesium); in trace elements (iron, manganese, copper, zinc, boron, molybdenum); the values of which are obtained by chemical measurements of the soil but on which the shade house a priori has little or no influence.

The physiological needs of plants include water content; the amount of light, temperature, etc. which are agro-climatic data.

Physiological needs can also include agro-climatic indicators to be achieved, for example cumulative sunshine, cumulative temperature; etc. over a given period, the period may be a predefined duration, for example a number of days, or the phenological stage as a whole.

This module makes it possible to define light and water requirements, or stress limits, to ensure the yield of a given plant crop.

This module also allows you to calculate the period of time during which plants are subjected to stress, in relation to their phenological stage. The optimization module can thus control the position of the photovoltaic panels based on this temporal weighting.

For example, exposing cultivated plants to thermal stress (for example a heatwave) over a period of one day does not have the same impact as over a period of several weeks. The present invention makes it possible to take these elements into consideration by the optimization module.

Typically, stress limits are known by threshold values stored in a memory. By comparing the values of agro-climatic indicators to the corresponding threshold values, it can be determined whether crops present water stress (soil humidity above or below a predetermined threshold value), thermal stress (soil temperature air or soil beyond or below a predetermined threshold value), or radiative stress (luminosity beyond a predetermined threshold value).

Preferably, the module for determining the physiological needs of plants includes the optimal values of the physiological needs of cultivated plants for each phenological stage.

For example, temperature is very important for the budding stage but less so for the maturation stage.

* Electricity production modeling module *

We can provide a module for modeling the electrical production of photovoltaic panels.

This module makes it possible to model the quantity of photovoltaic energy produced by the agrivoltaic device at least per time step and by the relative position of the photovoltaic panels and the sun. The relative position can be known for example based on the date in the calendar or based on sensors, for example photodiodes.

It makes it possible to calculate, possibly predict, the quantity of photovoltaic electricity produced even in non-optimal photovoltaic panel positions for the production of photovoltaic electricity.

Preferably, it is planned to simulate the electrical production of the agrivoltaic device as a function at least of its latitude and the relative position of the photovoltaic panels in relation to the sun.

Preferably the monofacial or bifacial nature of the photovoltaic panels is taken into account in the simulation of electricity production. Indeed, bifacial photovoltaic panels also produce by reverberation on the ground, that is to say diffuse radiation and reflected radiation.

This module advantageously takes into account the bifaciality coefficient; the network incidence loss parameters, or “IAM” or “array incidence loss”, as described for example on the page https://www.pvsyst.com/help/iam_loss.htm.

This module is connected to the dimensional calculation module of the supporting structure.

* Shade dimensional calculation module *

We can provide a dimensional calculation module for the supporting structure which supports the photovoltaic panels.
This module allows you to calculate or record at least one of:
- the distance between the posts of the supporting structure which supports the photovoltaic panels,
- the height of the photovoltaic panels, that is to say the height of the axis of rotation of the photovoltaic panels,
- the minimum value and the maximum value of the angle of rotation of the photovoltaic panels,
- the minimum and maximum position of translation of the photovoltaic panels, both vertically and in a horizontal plane;
- the possible transparency of the photovoltaic panels,
- the azimuth of the photovoltaic panels,
- the GPS coordinates of the photovoltaic panels,
- the inclination of the photovoltaic panels,
- the dimensions of the photovoltaic panels, their transparency,
- the model, the electrical characteristics of the photovoltaic panels,
- etc.

*Transposition module*

This module calculates the micro-climatic impact of the shade house.

Remote agro-climatic data can be used in place of local agro-climatic data, but this may introduce bias since remote microclimatic conditions are generally different from local microclimatic conditions.

For this purpose, we can provide a module for transposing the value of agro-climatic data, which makes it possible to determine the influence of the shade house on the microclimate, by comparison with a control zone without shade house.

In this case, we provide agro-climatic data transposition module which transposes at least certain remote agro-climatic data (outside the shade house) into local agro-climatic data (under the shade house), for example the incident radiation, the temperature, the wind, etc.

The transposition module is connected to the dimensional calculation module of the supporting structure.

It is configured to transpose the value of remote agro-climatic data into the value of local agro-climatic data, with reference to a mathematical model taking into account shading, for example a correspondence table, which depends in particular on the supporting structure and of latitude.

Preferably, the distant agro-climatic data are measured in a three-dimensional benchmark, and according to a predetermined step, in this case 10 cm x 10 cm in a horizontal plane.

Preferably, the transposition module is also configured to calculate the potential evapotranspiration (ETP) of the soil under the shade, the loamy, clayey or calcareous nature of the soil being known, for example by a prior diagnosis. The useful reserve of the ground under the shade is also known, for example thanks to the preliminary diagnosis. A water balance is also calculated, knowing the rainfall inputs (measured or averaged). We can then control the shading of the photovoltaic panels so that, the potential evapotranspiration having been calculated, the water balance remains positive.

The transposition module is also configured to calculate a risk of stress (water, radiative or thermal), the stress being dependent on the phenological stage. Stress is an agro-climatic sensitivity. For example, plants are particularly sensitive to water stress at a certain phenological stage and less sensitive to water stress at other phenological stages.

For example, water stress is detected if the water balance is below a predetermined threshold value. The risk of water stress can be controlled by the value of the difference between the water balance value and the predetermined threshold value.

* Agricultural result modeling module *

We can provide a module for modeling the desired agricultural result of cultivated plants.

This module makes it possible to model agricultural production according to the physiological needs and agro-climatic sensitivities of said plants, for each phenological stage of said plants.

We can predict that agricultural production takes precedence over photovoltaic production, so that the position of a photovoltaic panel, which could for example be perpendicular to the sun's rays to optimize electricity production, can see its position pivot so that it is no longer perpendicular to the rays of the sun, to optimize agricultural production, or vice versa depending on local climatic conditions.

But more generally, the present invention aims to optimize both agricultural production and the production of photovoltaic energy.

Typically, this module is configured to calculate the agricultural result sought by the sum of agricultural results by phenological stage, under shade.

It is possible to provide an instruction for controlling the horizontal, vertical or angular position of the photovoltaic panels as a function of the result of the calculation of at least one of said modules, thanks to an optimization algorithm of the optimization module.

The optimization module can thus issue a control instruction to said SCADA control system, for example to anticipate a climatic event which approaches the area of cultivated plants, and for example unfold the photovoltaic panels as much as possible so that they protect the whole of cultivated plants from rain, snow, hail, etc.

Unlike the case above, for example after a long humid period, or without sunshine, the control instruction to the SCADA control system can be to fold the photovoltaic panels as far as possible in order to leave maximum sunlight for the cultivated plants.

The control instruction sent to the SCADA control system includes the horizontal, vertical or angular position that at least one photovoltaic panel must adopt for a given period, i.e. a determined time range.

According to the invention, the horizontal, vertical or angular position is a function of at least said determined phenological stage and the relative position of said photovoltaic panel and the sun, which is linked to the day of the year and the time of day; as well as the relative position of said photovoltaic panel and said plants, that is to say in particular the shadow projected by a photovoltaic panel on the plants, as a function of its horizontal and vertical position, as well as its angular position.

Thanks to the present invention, for example depending on the season, the sowing date and possibly other parameters, the SCADA can control, automatically and regularly, the position and orientation of the photovoltaic panels so as to meet the needs sunshine, temperature, hygrometry, rainfall of crops over a given period of time.

For example, photovoltaic panels are oriented during a fraction of the day according to a first position to let in as much light as possible, to the detriment of electricity production. Then, once the plants' need for sunlight is satisfied, the photovoltaic panels are oriented during another fraction of the day in a second position to maximize electricity production.

However, for example if an agro-climatic data, for example the local temperature measured at the level of the cultivated plants is excessive, or greater than a predetermined value, the orientation of the photovoltaic panels can be modified to shelter the cultivated plants from the sun by the projected shadow of the photovoltaic panels and thus avoid excessive heating of them.

The invention is not limited to the embodiments previously described.

It can be expected that the agrivoltaic device is also connected to a set of at least one meteorological station, that is to say to remote agro-climatic sensors.

For example, a plurality of networked weather stations can be provided.

The agro-climatic data emitted by the set of meteorological stations are received by the optimization module.

Nomenclature

10 photovoltaic panel

20 supporting structure

21 post

30 cultivated plants

100 agrivoltaic device

200 server

210 optimization module

220 heuristic module

230 module for determining physiological needs

240 electrical production modeling module

250 transposition module

260 agricultural result modeling module

300 real-time control and data acquisition (SCADA) system

400 local agro-climatic sensors

410 remote agro-climatic sensors

420 satellite

Claims (10)

Method for controlling an agrivoltaic device, said agrivoltaic device comprising:
- a set of photovoltaic panels arranged above an area comprising a set of cultivated plants,
- a set of actuators, configured to modify the position of said set of panels
- a supporting structure which supports the photovoltaic panels, said panels being movable in at least one of: in rotation relative to a horizontal axis, in translation in a horizontal plane, in translation along a vertical axis, so as to be able to adopt several horizontal, vertical or angular positions thanks to said set of actuators, and arranged at a height lower than a predetermined value of a set of cultivated plants, the shadow projected on the plants by the photovoltaic panels being modified by the change in position or corner of said panels, thus modifying the microclimatic conditions of the area comprising all the cultivated plants,
- a real-time control and data acquisition system, configured to control the horizontal, vertical or angular position of the set of photovoltaic panels,
– a server, configured to receive and store agro-climatic data, and comprising an optimization module comprising lines of code defining its operation and configured to issue control instructions to the control system for the position of the photovoltaic panels;
the method comprising steps consisting of:
- determine the phenological stage at which said plants are found;
- receive, through an optimization module, a set of agro-climatic data relating to the area comprising a set of cultivated plants;
- calculate, by the optimization module, a set of agro-climatic indicators based on said agro-climatic data;
- transmit, by the optimization module to the control system, a control instruction including the horizontal, vertical or angular position that at least one photovoltaic panel must adopt for a given period, the control instruction being a function of the set of agro-climatic indicators. A method according to claim 1, further comprising a step consisting of:
- assign a weight to each calculated agro-climatic indicator; the weight assigned being a function of the phenological stage determined. Method according to claim 1 or 2, in which the agro-climatic data are sent by at least one of:
- local agro-climatic sensors, placed under the set of photovoltaic panels;
- remote agro-climatic sensors, arranged at a distance less than a predetermined value from the area comprising said set of cultivated plants, but not under the set of photovoltaic panels;
- satellite sensors;
agro-climatic data can also be:
- historical data recorded in a memory; And
- weather forecast data. Method according to any one of the preceding claims, comprising at least one of the steps among:
- a determination of the physiological needs of said plants by phenological stage;
- a modeling of the electrical production of said photovoltaic panels at least per time step and by the relative position of said photovoltaic panels and the sun;
- a dimensional calculation of the supporting structure which supports the photovoltaic panels;
- a determination of the microclimatic conditions of the area comprising all the cultivated plants of the agrivoltaic device;
- a modeling of the desired agricultural result of said plants, according to the agro-climatic indicators of said plants, for each phenological stage of said plants;
the control instruction being a function of at least one of said steps. Method according to any one of the preceding claims, further comprising steps consisting of:
- detect or predict a predetermined climatic or meteorological event; And
- issue an instruction for controlling the horizontal, vertical or angular position of at least one photovoltaic panel, depending on the moment at which said climatic or meteorological event is predicted or detected. Method according to any one of the preceding claims, further comprising a step consisting of simulating the electrical production of the agrivoltaic device as a function at least of its latitude and the relative position of the photovoltaic panels with respect to the sun, said photovoltaic panels being able to be bifacial . Method according to any one of the preceding claims, comprising an automatic learning step, configured to simultaneously optimize the production of electricity of photovoltaic origin and the agricultural production of said plants,
the learning being based on said agro-climatic data. Method according to any one of the preceding claims, in which the step of determining the phenological stage at which said plants are is implemented by declaration, by calendar date, by image processing of said plants, or by accumulation of degrees / day, possibly including a shading effect. Method according to any one of the preceding claims, in which the agrivoltaic device is also connected to a set of at least one meteorological station, possibly in a network;
the agro-climatic data received by the optimization module being issued at least by said set of at least one meteorological station. A computer program, comprising program code instructions for carrying out the steps of the method according to any preceding claim, when said program is executed on a computer.