EP4150553A1 - Procédé de gestion d'énergie - Google Patents
Procédé de gestion d'énergieInfo
- Publication number
- EP4150553A1 EP4150553A1 EP21725769.0A EP21725769A EP4150553A1 EP 4150553 A1 EP4150553 A1 EP 4150553A1 EP 21725769 A EP21725769 A EP 21725769A EP 4150553 A1 EP4150553 A1 EP 4150553A1
- Authority
- EP
- European Patent Office
- Prior art keywords
- zone
- energy
- function
- parameters
- transmitter
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000007726 management method Methods 0.000 title claims abstract description 38
- 238000000034 method Methods 0.000 claims abstract description 25
- 238000005457 optimization Methods 0.000 claims description 59
- 238000009434 installation Methods 0.000 claims description 29
- 238000005265 energy consumption Methods 0.000 claims description 17
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 claims description 7
- 229910052799 carbon Inorganic materials 0.000 claims description 7
- 230000001419 dependent effect Effects 0.000 claims description 4
- 230000006870 function Effects 0.000 description 42
- 238000012545 processing Methods 0.000 description 10
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 6
- 238000004590 computer program Methods 0.000 description 5
- 230000015654 memory Effects 0.000 description 5
- 230000008569 process Effects 0.000 description 5
- 238000004378 air conditioning Methods 0.000 description 3
- 238000004891 communication Methods 0.000 description 3
- 230000006399 behavior Effects 0.000 description 2
- 230000008859 change Effects 0.000 description 2
- 238000001514 detection method Methods 0.000 description 2
- 238000010438 heat treatment Methods 0.000 description 2
- 238000012886 linear function Methods 0.000 description 2
- 230000003190 augmentative effect Effects 0.000 description 1
- 238000009529 body temperature measurement Methods 0.000 description 1
- 210000004899 c-terminal region Anatomy 0.000 description 1
- 210000004027 cell Anatomy 0.000 description 1
- 238000007599 discharging Methods 0.000 description 1
- 230000004907 flux Effects 0.000 description 1
- 239000000295 fuel oil Substances 0.000 description 1
- 230000002068 genetic effect Effects 0.000 description 1
- 239000011521 glass Substances 0.000 description 1
- 238000009413 insulation Methods 0.000 description 1
- 238000002955 isolation Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 239000002699 waste material Substances 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
Definitions
- the present invention relates to a method of managing the energy consumed by at least one energy consuming device in an area of space.
- the present invention also relates to an associated management installation.
- solutions have been developed to reduce the energy consumption of a building. Such solutions generally use complex modeling of the building. They are thus long and tedious to deploy on a large scale. In addition, the solutions developed for one type of building are not easily transposable to another type of building.
- the subject of the invention is a method for managing the energy consumed by at least one energy consuming device in an area of space, the method being implemented by a management installation comprising: a . at least one transmitter associated with at least one energy consuming device, each transmitter being able to send data relating to the energy consumption and / or the state of the associated energy consuming device (s), b. at least one actuator associated with at least one energy consuming device, each actuator being able to actuate the associated energy consuming device (s) as a function of commands received by the actuator, and c. an optimization device suitable for generating commands intended for each actuator as a function of data sent by each transmitter, the management method comprising: a. an initialization phase comprising: i.
- the supply of a physical model of the zone being a function describing the evolution of a descriptive parameter of the zone as a function of at least a first group of parameters dependent on the energy consuming device (s) of the area, ii. the supply of an objective function materializing an energy objective to be satisfied for the area of the space, the objective function depending on the parameters of the first group of parameters, iii. the provision of an optimization problem aiming to minimize the objective function under a set of constraints, the constraints comprising at least:
- a second constraint relating to compliance with a comfort constraint relating to a user of the zone comprising at each successive instant: i. the sending, by each transmitter of the management installation, of data relating to energy consumption and / or the state of the associated energy consuming device (s), ii. the determination, by the optimization device, of a value for the descriptive parameter and of a value for each parameter of the first group of parameters as a function of the data transmitted by each transmitter, iii. the resolution, by the optimization device, of the optimization problem as a function of the determined values so as to obtain an optimal value for each parameter of the first group of parameters at the following instant, and iv.
- the method comprises one or more of the following characteristics, taken in isolation or according to all the technically possible combinations:
- the operating phase includes the actuation of the energy-consuming device (s) by the corresponding actuator (s) according to the command (s) sent by the optimization device, the actuation being advantageously carried out automatically;
- the management installation comprises a home automation unit capable of communicating, on the one hand, with each transmitter and each actuator and, on the other hand, with the optimization device, the data sent by each transmitter being transmitted to the device. optimization via the home automation unit, the commands generated and sent by the optimization device being transmitted to each actuator via the home automation unit;
- the physical model of the area is determined by the optimization device from the following steps: a. the provision of a historical data from the transmitters of the area management facility, b. determining a history of values for each parameter of the physical model of the area based on the data history provided, c. providing a generic model, and d. the calibration of the generic model for the area according to the history of values determined for each parameter to obtain the physical model of the area;
- the management installation further comprises at least one additional transmitter not associated with an energy consuming device and capable of sending data independent of the energy consuming devices and relating to the area, the physical model of the area being, moreover, a function of at least a second group of parameters independent of the energy consuming device (s) of the zone, the operating phase comprising the sending at each successive moment, by each additional transmitter of the installation management, of data relating to the zone, the operating phase further comprising the determination, by the optimization device, of a value for each parameter of the second group of parameters as a function of the data transmitted by each transmitter additional, the resolution of the optimization problem also being a function of the values determined for each parameter of the second group of parameters; the second constraint stipulates that the descriptive parameter is included in a range of predetermined values;
- the first group of parameters comprises at least one parameter chosen from among the following parameters: the power consumed by the or by each energy consuming device in the zone, the set temperature of at least one or each device in the zone and the current operating state of at least one or each device in the zone;
- the physical model of the zone is a thermal model and the descriptive parameter is the average interior temperature in the zone, or the physical model of the zone is a light power model and the descriptive parameter is relative to the average light power in the area.
- the zone comprises only one energy consuming device, the physical model of the zone being the physical model of said energy consuming device;
- the objective to be met is chosen from: minimizing energy consumption in the area, minimizing the energy bill in the area and minimizing a carbon cost in the area.
- the present description further relates to an installation for managing the energy consumed by at least one energy consuming device in an area of the space
- the management installation comprising: a. at least one transmitter associated with at least one energy consuming device, each transmitter being able to send data relating to energy consumption and / or the state of the associated energy consuming device (s), b. at least one actuator associated with at least one energy consuming device, each actuator being able to actuate the associated energy consuming device (s) as a function of commands received by the actuator, and c. an optimization device suitable for generating commands for each actuator based on data sent by each transmitter, the management installation being suitable for implementing a management method as described above.
- Figure 1 a schematic representation of an example of energy consuming devices and an installation for managing the energy consumption of said devices
- Figure 2 a schematic representation of an example of an area of space (living in a building) comprising different energy consuming devices, and
- FIG. 3 a flowchart of an example of a management process.
- Zone 5 of space is, for example, an area of a building or any other area of space comprising one or more energy consuming devices 6.
- Each energy-consuming device 6 is specific to consuming energy.
- the energy is, for example, of an electrical nature or of any other nature, such as gas or fuel oil.
- Each energy-consuming device 6 is, for example, supplied with energy by an external or internal power source.
- an external power source is, for example, the electrical network and an internal power source is, for example, a battery or a cell.
- zone 5 of the space is a room in a building.
- zone 5 includes five energy consuming devices 6, namely an electric heater 6A, an air conditioner 6B, a record player 6C, a television 6D and a light fixture 6E.
- the energy consuming devices 6 are connected to the mains supply.
- the management installation 4 comprises at least one transmitter 7, at least one actuator 8, a home automation box 9 (optional) and an optimization device 10.
- Each transmitter 7, each actuator 8 and the home automation box 9 are arranged in the zone 5 of the considered space.
- Each transmitter 7 is associated with at least one energy-consuming device 6 of zone 5.
- the number of transmitters 7 is adapted according to the intended application so that all the energy-consuming devices 6 considered for the zone 5 are associated with at least one transmitter 7.
- each transmitter 7 is associated with an energy consuming device 6 which is specific to it.
- Each transmitter 7 is able to send data relating to the energy consumption and / or the state of the corresponding energy consuming devices 6.
- the installation 4 comprises at least one additional transmitter 7a not associated with an energy-consuming device 6 and capable of sending data independent of the energy-consuming devices 6.
- the data are, for example, relative data. to the environment of zone 5. More precisely, the data are, for example, the temperature outside of zone 5 or the level of sunshine of zone 5.
- Each transmitter 7, 7a is able to send the corresponding data either directly to the optimization device 10, or via the home automation unit 9 when such a unit exists.
- the communication between each transmitter 7, 7bis and the home automation unit 9 when such a unit exists is, for example, carried out by a wireless link, for example, via the Z-Wave protocol or by Wi-Fi or even Bluetooth.
- Each transmitter 7, 7a is, for example, chosen from: a wireless wall switch and a multifunction sensor.
- the functionalities of the multifunction sensor are, for example, chosen from motion detection, opening detection, temperature measurement and light measurement.
- Each actuator 8 is associated with at least one energy-consuming device 6 of zone 5.
- the number of actuators 8 is adapted according to the intended application so that all the energy-consuming devices 6 considered for the zone 5 are associated with at least one actuator 8.
- each actuator 8 is associated with an energy consuming device 6 which is specific to it.
- Each actuator 8 is able to receive a command from the optimization device 10.
- the command is transmitted either directly by the optimization device 10, or via the home automation unit 9 when such a unit exists.
- the communication between each actuator 8 and the home automation unit 9 when such a unit exists is, for example, carried out by a wireless link, for example, via the Z-Wave protocol or by Wi-Fi or even Bluetooth.
- Each actuator 8 is able to actuate the corresponding energy-consuming device (s) 6 so as to execute the command received.
- the command is, for example, a command to start, stop or modify the programming of the corresponding energy-consuming device (s) 6.
- the home automation unit 9 is able to communicate, on the one hand, with the transmitters 7 and actuators 8 of the management installation 4 and, on the other hand, with the device. optimization 10.
- the communication between the home automation unit 9 and the optimization device 10 is, for example, carried out via an Internet box placed in zone 5.
- the optimization device 10 comprises a data processing unit 16 and memories 18.
- the optimization device 10 is, for example, hosted by one or more remote servers (in English "cloud").
- the data processing unit 16 interacts with a computer program product.
- the computer program product comprises an information medium readable by the data processing unit 16.
- the readable information medium is a medium suitable for storing electronic instructions and capable of being coupled to a bus of a. computer system.
- the information medium is a memory 18 of the optimization device 10.
- the information carrier stores the computer program including program instructions.
- the computer program is loadable on the data processing unit 16 and is adapted to cause the implementation of an energy management method when the computer program is implemented on the processing unit. 16 of the optimization device 10.
- the energy management method will be described in more detail in the remainder of the description.
- At least one memory 18 of the optimization device 10 is configured to store, for a predetermined period (possibly unlimited), the data coming from the home automation unit 7 and the commands generated by the processing unit 16.
- the processing unit 16 and all the memories 18 of the management device are hosted on the same server.
- the processing unit 16 and at least the memory 18 on which are stored the data coming from the home automation unit 7 and the commands generated by the processing module 16 are hosted on separate servers. In this case, the servers are able to communicate with each other.
- FIG. 3 illustrates an example of the steps of an energy management method.
- the management process comprises two distinct phases: an initialization phase 100 and an operational phase 200.
- the initialization phase 100 is a calibration phase during which the method (and in particular the optimization device 10) is adapted to the zone 5 considered, as well as to the energy objective to be satisfied and to the constraints to be respected. for zone 5.
- the initialization phase 100 therefore takes place each time a new zone 5 is considered.
- the operating phase 200 is an implementation phase which takes place after the corresponding initialization phase 100.
- the operating phase 200 is implemented at different successive instants, and preferably at each instant so as to control over time the various energy-consuming devices 6 of zone 5. By the term “every instant”, it is heard at each predefined time step.
- the time step is, for example, of the order of seconds or minutes or hours.
- the time step allows implementation in real time.
- the initialization phase 100 includes a step 110 of providing a physical model of area 5.
- the physical model is a function describing the evolution of a descriptive parameter P d of zone 5 as a function of at least a first group of parameters u depending on the energy consuming device (s) 6 of zone 5.
- the physical model is also a function of at least a second group of parameters h independent of the energy consuming device (s) 6 in zone 5.
- the descriptive parameter P d is a parameter relating to a characteristic of zone 5 and capable of changing over time as a function of the values of the parameters u of the first group, and, where appropriate, of the values of the parameters h of the second group.
- the descriptive parameter P d depends on the targeted application.
- the descriptive parameter P d is the average interior temperature Ti in zone 5, the average interior brightness of zone 5 or the average temperature of an element, such as a hot water tank, present in the room. zone 5.
- the first group of parameters u is a set of parameters relating to characteristics of zone 5 that are dependent or intrinsically linked to the operation of energy consuming devices 6.
- the first group of parameters u comprises at least one of the following parameters from among: the power consumed (electrical power if electrical devices) by or by each device 6 of zone 5 (overall power consumed or power consumed by device by appliance), the setpoint temperature of at least one or each appliance 6 in zone 5 and the current operating state (off or on) of at least one or each appliance 6 in zone 5.
- the second group of parameters h is a set of parameters relating to characteristics of zone 5 independent of the operation of energy consuming devices 6. In other words, the operation of energy consuming devices 6 of zone 5 n 'does not influence the values of the parameters h of the second group.
- the second group of parameters h includes the outside temperature in zone 5, the level of sunshine in zone 5, the occupancy rate (in number of people) in zone 5, the air quality in zone 5 or the proportion of glazed surface in zone 5.
- the physical model of zone 5 is determined by the optimization device 10 as a function of a generic model and of a history of values, measured specifically for zone 5, by the transmitters 7 of the installation. management 4.
- the generic model is, for example, a “gray box” type model, that is to say a model using a simplified physical representation of a zone of space.
- the generic model is of the “white box” or “black box” type.
- a history of values is then determined for the descriptive parameter P d , the parameters u of the first group of parameters and, where appropriate, the parameters h of the second group of parameters.
- the determination is, for example, carried out by the optimization device 10.
- the optimization device 10 then performs a calibration of the generic model according to the history of values, which makes it possible to obtain the physical model specific to the zone 5 considered.
- Calibration consists, for example, of a learning phase of the generic model.
- the physical model of zone 5 is a thermal model and the descriptive parameter P d is the average interior temperature Ti in zone 5.
- the first group of parameters u comprises at least the electrical power consumed by the or each device of zone 5.
- the second group of parameters h comprises at least one parameter chosen from: the temperature outside of zone 5, the overall level of sunshine of zone 5, the solar flux entering through any glass walls of the zone 5 and the occupancy rate (number of people) of zone 5.
- the values of the coefficients and matrices (eg: a, A and B) defining the function f are calibrated, which allows an explicit knowledge of the function f.
- the function f makes it possible to give the value of by a simple operation.
- thermal aspect is given by way of illustration. Those skilled in the art will understand that the present invention applies to any other type of physical models or areas of space considered.
- the physical model of zone 5 is a model of light power and the descriptive parameter P d relates to the average light power in zone 5.
- zone 5 comprises a single power consuming device 6 and the physical model of zone 5 is the physical model of said power consuming device 6.
- the power consuming device. 6 is a hot water tank and the physical model is the thermal model of the hot water tank.
- Zone 5 is an electric vehicle, the power consuming device 6 is a battery, and the physical model is the physical model of the battery charging and discharging.
- the initialization phase 100 includes a step 120 of determining an objective function G materializing an energy objective to be satisfied for zone 5.
- the objective function G depends at least on the parameters u of the first group of parameters.
- the function G does not depend on the parameters h of the second group of parameters.
- the objective to be met is chosen from: minimizing energy consumption in zone 5, minimizing the energy bill in zone 5 and minimizing a carbon cost in zone 5.
- the objective function G aims, for example, to: minimize the total energy consumption of zone 5 over a horizon of T time step and is written as
- the function G is a linear function.
- the objective function G is non-linear. It is, for example, quadratic, polynomial or even exponential.
- the initialization phase 100 includes a step 130 of determining an optimization problem aimed at minimizing the objective function G under a set of constraints.
- the optimization problem is, therefore, a single-objective problem under multiple constraints.
- the set of constraints includes at least two constraints, namely:
- the first constraint stipulates that the evolution of the descriptive parameter P d of zone 5 is consistent with the physical model of zone 5.
- the second constraint is a predetermined constraint based on user preferences.
- the second constraint is personalized by name according to the users of zone 5.
- the second constraint relates, for example, to the descriptive parameter P d of zone 5.
- the second constraint stipulates that the descriptive parameter P d is included in a range of predetermined values (limited descriptive parameter).
- the first constraint is compliance with the thermal model given by the function f, namely:
- the second constraint which is a comfort constraint, concerns the average interior temperature Ti in zone 5 (the building in this case).
- the second constraint thus materializes for example in the form of the following inequation:
- K ineq (Ti) (7) - 21.19 - 7 )) meaning both 7) - 21 £ 0 or 7) £ 21 and 19 - 7) £ 0 or 7)> 19.
- the 19 ° C and 21 ° C terminals are called comfort terminals.
- the optimization problem is written in the form of a minimization of a function G depending on the first group of parameters u that we want to control under a set of constraints.
- the G function corresponds, for example, to minimizing energy consumption, the energy bill or the carbon cost.
- the optimization problem is written as follows: mm (G (u)) (5)
- the comfort constraint is, for example, relative to a minimum light power in zone 5.
- the comfort constraint is, for example, relative to the temperature of the water in the hot water tank over a given time range.
- the comfort constraint is, for example, relative to the date on which the battery must be charged.
- the operating phase 200 comprises a step 210 for sending (at any time), by each transmitter 7 of the management installation 4, data relating to the energy consumption and / or the state of the consuming device (s). energy 6 associates. Where applicable, each additional transmitter 7a also sends data relating to zone 5.
- the data is received by the optimization device 10, possibly via the home automation box 9 when such a box exists.
- the operating phase 200 comprises a step 220 of determining, by the optimization device 10, a value for the descriptive parameter Pd, a value for each parameter u of the first group of parameters and, where appropriate, worth for each parameter h of the second group of parameters as a function of the data transmitted by each transmitter 7, 7a.
- the operating phase 200 includes a step 230 for solving the optimization problem as a function of the values received so as to obtain an optimal value for each parameter u of the first group of parameters at the following instant.
- a step is performed by the optimization device 10, in particular by the processing module 16, that is to say it is implemented by computer.
- the resolution of the optimization problem is done using an optimal control algorithm, such as dynamic programming or the Pontryagin maximum principle.
- the resolution of the optimization problem is, for example, carried out by means of an algorithm of the augmented Lagrangian type, of an algorithm of the interior points type or even of a projected gradient type algorithm.
- the algorithms used are of the simplex type.
- the resolution of the optimization problem is not based on a genetic type algorithm.
- the operating phase 200 comprises a step 240 of generating, by the optimization device 10, at least one command for each energy consuming device 6 of zone 5 according to the optimum values obtained.
- the control allows the operation of 6 energy consuming devices to be changed (different operating programs, on-off).
- the control consists in controlling the energy consuming devices 6 to reach these optimum values.
- Each command generated is sent to the corresponding actuator (s), possibly via the home automation unit 9 when such a unit exists.
- the operating phase 200 comprises a step 250 of actuating the energy-consuming device (s) 6 by the corresponding actuator (s) according to the command (s) sent by the optimization device 10.
- the actuation is advantageously carried out automatically (without user intervention). This makes it possible to automatically control the energy consuming devices 6 in zone 5.
- the actuation step 250 is carried out under the control of the user who decides whether or not to send the commands generated to the energy consuming devices 6.
- the method makes it possible to determine the commands of each energy consuming device in a few milliseconds or a few tenths of a second depending on the degree of precision of the physical model and the choice of modeling (continuous or discrete, linear or not).
- Such a method is easily adaptable to all types of physical models. It is also easy to add or modify the constraints of the optimization problem. For example, the modification of the comfort constraint is easily done by changing the parameters of the KJneq comfort function.
- the thermal case it is for example possible to prevent the passage from an air conditioning mode to a heating mode.
- the process reduces energy waste.
- controlling energy-consuming devices makes it possible to optimize consumption in buildings while satisfying user comfort.
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- Tourism & Hospitality (AREA)
- General Health & Medical Sciences (AREA)
- Human Resources & Organizations (AREA)
- Public Health (AREA)
- Primary Health Care (AREA)
- Strategic Management (AREA)
- Water Supply & Treatment (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
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Abstract
Description
Claims
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
FR2004852A FR3110260B1 (fr) | 2020-05-15 | 2020-05-15 | Procédé de gestion d’énergie |
PCT/EP2021/062807 WO2021229045A1 (fr) | 2020-05-15 | 2021-05-14 | Procédé de gestion d'énergie |
Publications (1)
Publication Number | Publication Date |
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EP4150553A1 true EP4150553A1 (fr) | 2023-03-22 |
Family
ID=71784296
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
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EP21725769.0A Pending EP4150553A1 (fr) | 2020-05-15 | 2021-05-14 | Procédé de gestion d'énergie |
Country Status (3)
Country | Link |
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EP (1) | EP4150553A1 (fr) |
FR (1) | FR3110260B1 (fr) |
WO (1) | WO2021229045A1 (fr) |
Family Cites Families (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
FR2967793B1 (fr) * | 2010-11-22 | 2014-07-25 | Bnext Energy | Systeme de gestion de l'energie dans un batiment |
FR2989476B1 (fr) * | 2012-04-12 | 2016-02-19 | Commissariat Energie Atomique | Procede et systeme de pilotage d'une installation de gestion de l'energie |
FR3003657A1 (fr) * | 2013-03-19 | 2014-09-26 | Adagos | Procede de realisation d'un diagnostic thermique d'un batiment ou d'une partie d'un batiment |
-
2020
- 2020-05-15 FR FR2004852A patent/FR3110260B1/fr active Active
-
2021
- 2021-05-14 WO PCT/EP2021/062807 patent/WO2021229045A1/fr active Application Filing
- 2021-05-14 EP EP21725769.0A patent/EP4150553A1/fr active Pending
Also Published As
Publication number | Publication date |
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FR3110260A1 (fr) | 2021-11-19 |
WO2021229045A1 (fr) | 2021-11-18 |
FR3110260B1 (fr) | 2023-01-06 |
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