Method and device for controlling an electrical network

Abstract

The invention relates to a method and device for controlling an electrical network (10) at a point of consumption (20) which controls an electrical load (30) connected to the electrical network. The method proposes a real-time control algorithm for the balance of the interconnected electrical network by the instantaneous adaptation of the electrical load at the point of consumption in order to optimize the frequency system services (primary, secondary and tertiary reserves) with a permanent anti-blackout effect.The process includes a measurement step (41) of electrical voltages, an estimation step (42, 43), at the point of consumption, of variables representative of the equilibrium state of the electrical network including the frequency and frequency variation of the electrical network as well as the difference between total electrical power produced and consumed, and a control step (44) to modify the electrical consumption of the electrical load when said estimated representative variables are outside a predetermined operating range. (Fig. 1).

Description

Title of the invention: Method and device for controlling an electrical network Technical field of the invention

[0001] The invention relates to the general field of electrical distribution networks, in particular the monitoring of the imminence of an imbalance in an electrical network.

[0002] The invention relates more specifically to a method for controlling a consumption point of the electrical network which, from an estimation of the variables representative of the state of equilibrium of the electrical network at this consumption point, makes it possible in real time to temporarily reduce or increase the consumption of the consumption point. The invention also relates to a device capable of implementing such a method. The invention therefore proposes a real-time control algorithm for the balance of an interconnected electrical network by the instantaneous adaptation of the load of a consumption point, with a view to optimizing the frequency system services (primary, secondary and tertiary reserves) with a permanent anti-blackout effect. State of the prior art

[0003] To ensure the stability and reliability of an electrical network to which energy producers and energy consumers are connected, it is obviously necessary to constantly balance the electrical power consumed by the consumers with that produced by the producers. Any sudden change in production or consumption leads to an imbalance that can induce instability in the frequency and voltage of the electrical network compared to their nominal value (for example 50Hz and 230V for the public AC network). Such frequency and voltage instabilities are not acceptable because they can seriously damage equipment connected to the electrical network as well as transmission and distribution power lines.It is to protect them in the event of network instability that high-voltage source stations must be disconnected, which can lead to cascading power cuts leading to a local or general collapse of the electricity network, also called a blackout.

[0004] An electricity network manager (also sometimes called a network operator) is an entity whose mission is to monitor the state of the electricity network so that all users connected to the electricity network are guaranteed to be supplied with a frequency and voltage within standardized operating ranges, specified in particular in the European standard EN 50160 for the characteristics of the electrical wave (voltage, frequency, etc.) supplied by public distribution networks. tribute.

[0005] Depending on consumption demands, the network manager is constantly able to activate / deactivate energy producers. When an overload, i.e. an excess of consumption compared to production, is foreseeable in time (linked for example to weather forecasts indicating an imminent drop in temperatures or to significant use of household appliances at the end of the day), the manager can plan for example the launch of an additional power plant unit or the activation of one or more renewable energy sources, for example a hydroelectric dam, to absorb this overload.On the other hand, when an overload occurs suddenly or when no energy source is quickly available, network controllers can relieve part of the electricity network, in particular by temporarily cutting off pre-selected large industrial consumers of electrical energy (such as steelworks, paper mills, refineries, etc.) and certain medium voltage feeders (MV or HTA High Voltage A) from source substations to rebalance the network, while avoiding cutting off sensitive consumers (such as hospitals, data centers, etc.). The manager can also, via network interconnections with neighboring countries or regions, choose to import a quantity of electricity during these peak periods, but this possibility presents a high cost for the manager because the energy is then purchased at a high price.Conversely, in the event of sudden underload or overproduction, the manager can also, via network interconnections, choose to export a quantity of electricity during these periods.

[0006] As is known, the electricity network manager has a central supervision and remote control system of the SCADA (Supervisory Control and Data Acquisition) type which carries out numerous measurements of parameters of the electricity network in real time to detect possible imbalances and to remotely control, in the event of a sudden overload, the very rapid disconnection (i.e. with a delay of the order of a second) of a few targeted electrical installations which are in permanent communication with the manager's central system.

[0007] For reasons of efficiency, these targeted electrical installations are large consumers of electrical energy (calling for example on the order of several megawatts) because their temporary disconnection from the electrical network makes it possible to generate large reductions in consumption. But this solution can only be applied to a limited number of installations, and furthermore it can prove penalizing for the productivity of these installations and present a high cost for the manager in terms of compensation.

[0008] It would therefore be advantageous to have a decentralized solution which allows, rather than cutting off a few large targeted consumers from a central system, to be able to temporarily disconnect a much larger quantity of small energy consumers (for example, part of the heating in private homes). In fact, the same reduction in overall electricity consumption of, for example, 100MW is achieved by cutting 1kW at 100,000 small consumers, rather than 10MW at 10 large consumers.

[0009] Nevertheless, in such a decentralized solution, it is not realistic for reasons of cost and feasibility that all these numerous small consumers have permanent real-time communication with a remote control system of the network manager, while waiting for example for a rapid disconnection order coming from this system.

[0010] Document JP2001103669A describes a solution for measuring variations in different electrical variables in order to estimate the imbalance between demand and supply at each electrical substation to be monitored. Document US2019379237A1 describes a solution for controlling the frequency of an electrical network by calculating the frequency variations on smart sockets so as to locally control these sockets by comparing the calculated frequency with a threshold sent from a remote substation. Similarly, in document US2015112501A1, each electrical load detects a frequency variation in an electrical network and is capable of reducing or increasing its energy consumption accordingly, based on criteria previously received from a central system. Statement of the invention

[0011] This is why the invention aims to remedy all or part of these drawbacks by proposing a solution where each consumer connected to the distribution network locally has an autonomous system which is capable of detecting in real time the imminence of an imbalance in the electrical network and which is capable of carrying out with very high reactivity (of the order of a second) a temporary modification (i.e. a reduction in the event of overconsumption or an increase in the event of overproduction) of the power called by this consumer.

[0012] This solution will be more economical for the network manager and will make less use of the targeted large energy consumers. In addition, it will be more responsive to avoid an imbalance, because the time required for a change in power demand for a large number of N small autonomous consumers of 1kW to 10kW is less than that required for a change in power demand for a few large consumers of 10MW for example. Similarly, the time taken to restart N small consumers will be less than that of large consumers and, above all, less disruptive for the entire network.

[0013] For this, the invention describes a method for controlling an electrical network of dis at a consumption point of said electrical network, the consumption point being able to control an electrical load connected to the electrical network, characterized in that the method comprises a step of measuring electrical voltages at the consumption point, a step of estimating, at said consumption point, variables representative of a state of equilibrium of the electrical network from said measured electrical voltages, said representative variables comprising the frequency f and the temporal variation of frequency df / dt of the electrical network as well as the difference AP between the electrical power produced and the electrical power consumed in the electrical network, and a control step during which the electrical consumption of the electrical load is modified when said estimated representative variables are outside a predetermined operating range.

[0014] According to one characteristic, the estimation step firstly carries out an estimation of the frequency f of the electrical network from the voltages measured at the consumption point, and an estimation of the frequency variation df / dt of the electrical network.

[0015] According to another characteristic, the estimation of the frequency uses an extended Kalman filter and the estimation of the frequency variation also uses an extended Kalman filter. According to another characteristic, the estimation of the frequency uses an extended Kalman filter in redundancy with a phase-locked loop type system.

[0016] According to another characteristic, the estimation step also performs in real time an estimation of the difference AP between electrical power produced and electrical power consumed, using an extended Kalman filter, one of the state variables of which is a calibration parameter a representing the inertia of the electrical network.

[0017] According to another characteristic, the control method comprises a periodic recalibration step during which the calibration parameter a is updated periodically by communication between the consumption point and an electricity network manager.

[0018] According to another characteristic, the predetermined operating domain is identified by thresholds for the variables representative of the equilibrium state of the network, said thresholds being updated during the periodic recalibration step. According to another characteristic, said thresholds are interdependent with each other.

[0019] According to another characteristic, during the control step, the electrical consumption of the electrical load is reduced when the variables representative of the equilibrium state are below the predetermined operating range and the electrical consumption of the electrical load is increased when the variables representative of the equilibrium state are above the predetermined operating range. determined.

[0020] According to another characteristic, during the recalibration step, information on the forecast difference between power produced and power consumed APpredicted is provided by the network manager and is used in the control step to determine the predetermined operating domain.

[0021] The invention also describes a device for controlling an electrical distribution network integrated into a consumption point of said electrical network, characterized in that the device comprises means for measuring electrical voltages at the consumption point, a calculation unit for estimating variables representative of a state of equilibrium of the electrical network and means for controlling an electrical load controlled by the consumption point, with the aim of implementing said control method.

[0022] According to one characteristic, the device also comprises communication means, for communicating, via an Internet of Things (IoT) platform, the consumption point with an electricity network manager, and according to another characteristic, the device is integrated into a communicating electricity meter. brief description of the figures

[0023] Other characteristics and advantages of the invention will emerge on reading the description which follows, with reference to the appended figures in which:

[0024] [Fig-1]: [Fig.l] shows a simplified diagram of a device capable of implementing implements a control method in accordance with the invention,

[0025] [Fig.2]: [Fig.2] represents a simplified schematic view of the control method according to the invention. detailed description of an embodiment

[0026] With reference to [Fig.l], an alternating current distribution network is shown diagrammatically by the reference 10. The electrical network 10 obviously comprises a large number of consumption points. [Fig.l] shows a consumption point 20 which controls an electrical load 30 supplied by the electrical network 10. The electrical network 10 may be a single-phase or polyphase alternating current network.

[0027] The consumption point 20 may for example be located directly at a socket, a circuit breaker or an electrical cable supplying any electrical load 30 such as an electric heating circuit in a home, an electric vehicle charging station (public or residential), an industrial production line, or others (case of an emergency generator or case of a V2G (Vehicle to Grid) type device). But the consumption point 20 may also be located at a communicating electricity meter, such as the main meter of an individual home (for example a Linky type meter in France), capable of controlling different loads of this home, or even a prepayment electricity meter or a divisional meter. Other use cases for consumption point 20 are of course possible.

[0028] In the embodiment presented, the consumption point 20 integrates a control device capable of implementing the control method described later. This control device comprises means 21 for measuring the electrical voltages present at the consumption point 20. If the electrical network 10 is single-phase, the measuring means 21 measure the phase-neutral voltage and if the electrical network 10 is polyphase, the measuring means 21 then measure the voltages between phases or between phases-neutral. The control device of the consumption point 20 also comprises control means 23 capable of controlling the power supply of the electrical load 30.

[0029] In addition, the control device comprises a calculation unit 22 comprising a microcontroller and a memory, the microcontroller being capable of running a program stored in this memory. The calculation unit 22 is capable of reading the information coming from the measuring means 21, for example through an analog-digital converter (ADC), and of controlling the control means 23. These control means 23 are for example a cut-off device of the contactor or relay type in simple cases, but also an analog control or by digital connection bus to control more complex loads 30.

[0030] The control device may also comprise communication means 24, for example of the RF (Radio Frequency) type, such as Wifi, 5G, Bluetooth, Lora, etc., or of the PLC (Power Line Carrier) type, enabling it to communicate with the outside world via the Internet. Thanks to the communication means 24, the consumption point 20 is in particular capable of communicating via an IoT (Internet of Things) platform with a transport or distribution manager of the electricity network (RTE or Enedis in France).

[0031] According to the invention, the calculation unit 22 of the consumption point 20 stores and executes a program capable of implementing the different steps of the method described below and represented in [Fig.2].

[0032] The control method comprises a first step 41 of acquiring samples of the voltages measured at the consumption point 20 by the measuring means 21. The sampling frequency of these measurements must be high to have sufficient precision of the voltage variations that one seeks to determine. A sampling of the measurements of the order of several kHz is necessary (for example 2 or 4 kHz). This step 41, called the measuring step, therefore comprises a physical observation phase electrical voltages then a phase of conversion into digital values.

[0033] From the measured electrical voltages, the control method then comprises an estimation step 42, 43 making it possible to determine variables which are representative of the equilibrium state of the electrical network 10. These representative variables include the frequency f of the electrical network and its temporal variation df / dt (also called ROCOF - Rate of Change of Frequency), as well as the difference AP between total electrical power produced and total electrical power consumed on the electrical network. In this respect, the estimation step is composed of a first estimator block 42 of the frequency and the frequency variation, and a second estimator block 43 of the state of the network.

[0034] The frequency estimator block 42 calculates very precisely the frequency festimated and the frequency variation df / dtestimated of the electrical network 10 from the voltages measured during step 41. The estimation of the frequency is made with a precision better than 1 mHz and the estimation of the frequency variation is made with a precision better than 10 mHz / s.

[0035] To estimate the frequency f, the frequency estimator block 42 can use an extended Kalman filter (EKF) after a transformation of the measured voltages into complex writing. Another solution consists of using a phase-locked loop (PLL) type system. The solution with a Kalman filter rather favors the speed of obtaining the result while the solution with a PLL system rather favors the precision of the result. The frequency estimator block 42 can also advantageously combine these two solutions in a redundant manner, which in particular makes it possible to regularly recalibrate the parameters of the Kalman filter more easily using the PLL system. The frequency estimator block 42 also calculates the frequency variation df / dt using an extended Kalman filter.

[0036] Once the frequency f and the frequency variation df / dt have been acquired in the block 42, the network state estimator block 43 is responsible for estimating in real time the difference APestimated between produced electrical power and consumed electrical power. This estimator block 43 is based on a physical model comprising the following four state variables: i) the frequency f of the electrical network, ii) the derivative of the frequency with respect to time df / dt, iii) the difference AP between produced power and consumed power, and iv) a state variable called a which is a calibration parameter representing the inertia of the electrical network 10. This calibration parameter a is given by the following equation:

[0037] a = ZHSn / f0

[0038] in which: i) f0 represents the nominal frequency of the electrical network (by example 50 Hz in Europe), ii) H represents the inertia constant, which is the response time in seconds of all synchronized rotating machines (i.e. turbines and generators, with the notable exception of wind turbines) in the interconnected power grid following a power demand pulse from the grid, and iii) Sn represents the nominal power of all synchronized rotating machines in the power grid.

[0039] The equation of the physical model used is based on a universal equation of interconnected electrical networks which is:

[0040] ÎL - f dt ~ J Q'2H.Sn

[0041] we then obtain the following equation to estimate the difference between total power produced and total power consumed:

[0042] \P = garlic

[0043] It can be seen that the higher H and Sn are, that is to say the higher the nominal power of the network and the response time are, the higher the calibration parameter a representing the inertia of the electrical network 10 is, and therefore the lower the frequency variation df / dt is, which means that the electrical network 10 has a high inertia and is stable. Conversely, lower values ​​of H and Sn give a lower value of the calibration parameter a indicating that the electrical network 10 is less stable. Thus, an electrical network comprising for example a large number of wind turbines as energy sources, will have a low value of the calibration parameter a (because H is low), and therefore a greater risk of blackout, which reinforces the usefulness of the present invention.

[0044] The network state estimator block 43 also uses an extended Kalman filter to estimate these four state variables which are f, df / dt, AP and a. The initial conditions of the filter can be the following: the state variable f is equal to the nominal frequency f0, the derivative df / dt and the difference AP are equal to 0, the calibration parameter a is equal to an initial value a0.

[0045] According to a simplified variant of the invention, the calibration parameter a is a fixed internal datum, which is a function of the extent and configuration of the network, because it is considered that the configuration variations of the electrical network 10 are minimal (for example, the case of a basic, non-interconnected electrical network). It could also be envisaged to have several fixed values ​​of the calibration parameter a, such as an average value between a maximum value and a minimum value. In these different cases, this or these calibration parameters a are directly stored in the memory of the calculation unit 22.

[0046] According to a more elaborate variant, the calibration parameter a is likely to vary following in particular possible significant changes in the power injected into the network by non-synchronized energy sources (in particular wind turbines), or interconnections with other electrical networks. It is therefore preferable to have a regular update of the calibration parameter a to obtain better accuracy of the calculations. This is why the control method includes a periodic recalibration step 46 which provides a periodic update of the calibration parameter a (typically once every ten minutes for example). The communication means 24 of the consumption point 20 in fact make it possible to communicate with a network manager who is responsible for regularly broadcasting an updated value of the calibration parameter a, for example via an IoT platform. In addition, from the value of a thus periodically refreshed, the network state estimator block 43 evaluates in real time the fluctuations ôa of a in order to recalibrate the equation [°° 47 1 AP=(« + ô8),ÿ

[0048] so as to detect any significant change in the inertia of the network between two periodic recalibrations (loss of line, change in interconnections, islanding, intermittence of renewable energies, etc.).

[0049] Once the frequency f, the frequency variation df / dt and the difference AP between power produced and power consumed are estimated, the control method then comprises a control step 44 in which these variables representative of the equilibrium state of the network 10 are analyzed with respect to a predetermined operating domain, to determine whether or not there is an imbalance in the state of the network and therefore whether or not it is necessary to temporarily reduce or increase the power called by the load 30 connected to the consumption point 20, until the conditions of this predetermined operating domain are restored.

[0050] According to a first completely autonomous embodiment, the predetermined operating domain is simply composed of high (fseuiihaut, df / dt seuilhaut, APseuiihaut) and low (fseuilbas, df / d^e^, APseuUbas) limit thresholds which must not be crossed. These fixed thresholds are stored in the memory of the calculation unit 22.

[0051] According to a second embodiment, the thresholds are variable and can thus be updated periodically thanks to a dialogue between the communication means 24 and the network manager, during the periodic recalibration step 46. As for the updating of the calibration parameter a, an update period of the order of ten minutes for the thresholds is sufficient.

[0052] In these first two embodiments, the control step 44 thus continuously performs a test to determine whether the value of one of the estimated variables, namely: f df / dtestimated or APestimated, is below or above the corresponding thresholds.

[0053] For example, if festimated < fseuUbas or if df / dtestimated < df / d^e^ or if APestimated < APseuUbas, this means that at least one of the estimated variables is below the domain of func operation, it is then considered that there is an imminent risk of network imbalance due to overconsumption and therefore the control step 44 asks a control block 45 to reduce the consumption of the load 30. Conversely, If estimated Ceuilhaut OR If df / dtesümé > df / dC^ih^ OR If APesümé > APseumlaut, This means that at least one of the estimated variables is above the operating domain, it is then considered that there is an imminent risk of network imbalance due to underconsumption (or overproduction) and therefore the control step 44 asks the control block 45 to increase the consumption of the load 30. In the case of overproduction, it is also possible to consider a reduction in production by ordering the shutdown of a generator if the case arises.

[0054] According to another embodiment, the thresholds of the operating domain of the three variables f, df / dt, AP are interdependent with each other, that is to say they can be linked together by one or more functions. It is thus possible in particular to use the so-called phase plane technique which is applicable to a second-order non-linear system. The phase plane gives the plot of a point X(t) whose abscissa and ordinate coordinates are the values ​​taken by the two state variables which are the frequency f(t) and the power difference AP(t). Such a method makes it possible to obtain an operating domain which is better refined.

[0055] According to another more complex embodiment, the operating domain of the three variables f, df / dt, AP is estimated by the calculation unit 22 using a convolutional neural network whose learning settings have been transmitted by the network manager. This makes it possible to increase the autonomy of the consumption point control device 20, by spacing out the periodic updates from the network manager or even in a degraded mode where communications by the communication means 24 are not operational.

[0056] In another advantageous embodiment, the invention can be used to avoid having to resort to so-called "secondary" energy reserves (such as, for example, hydroelectric dams, etc.), thanks to a more elaborate calculation of the AP thresholds.

[0057] Indeed, it is known that the electrical network 10 includes so-called "primary" energy reserves. These primary reserves are activated automatically by simply varying the power produced by the synchronous rotating machines of the electrical network, thanks to a variation in the rotation speed of their turbines. This variation in power noted ôP is then given by the relationship:

[0058] _f\ V estimates J 0 /

[0059] in which: i) f0 is the nominal frequency of the network and ii) Z is a coefficient which is approximately equal to: ôPmax! where ôPmax represents all the reserves existing pre-established primaries and ôfmax represents the maximum frequency deviation allowed from the nominal frequency f0. In France, the total of primary reserves ôPmax is equal to approximately 600 MW and the maximum frequency deviation ôfmax allowed is set at approximately 50mHz.

[0060] If the primary reserves are not sufficient to bring the actual frequency of the network back to the nominal frequency of 50 Hz, the network manager then activates the secondary or even tertiary reserves and / or operates pre-programmed peak load shedding, but with an execution time ranging from several tens of seconds to several minutes depending on the type of reserve. In such a case, the invention, which typically reacts to the second, can then be used in anticipation to try to avoid the activation of these reserves, which would be advantageous for the network manager. The consumption point 20 would then behave as a sort of temporary additional primary reserve because it can react autonomously and very dynamically (typically 1 second).

[0061] If the primary reserves are not sufficient to bring the actual frequency of the network back to the nominal frequency, the network managers have a system called "peak shedding". These shedding systems consist of programming remotely and in advance (i.e. with an advance greater than 10 minutes), the load shedding of different consumers for a predetermined duration based on a time-stamped consumption forecast. The disadvantage is that these load sheddings programmed in advance are often activated when this was not necessary because AP does not reach the value that was planned and which justified load shedding. In such a case, the invention can then be used to compensate for an error in the load shedding instruction and thus avoid avoiding unnecessary shedding.

[0062] For this, the invention uses information for forecasting the difference between power produced and power consumed, called APpredicted, which is provided by the network manager for example during the recalibration step 46. This information APpredicted gives the forecasts of the difference between power produced and power consumed to come over the next few hours. For example, it is possible to envisage a forecast of APpredicted which is sampled every 10 seconds, which makes sixty values ​​of APpredicted to be received in a sliding manner every ten minutes by the communication means 24. Other sampling frequencies of the information for forecasting the difference APpredicted are obviously possible. In this case, the expression X.(festimated - fo) + APpredicted can be used as a threshold reference of the predetermined operating domain, in order to detect whether one is outside the operating domain. The control step 44 then performs the following functionality:

[0063] a) If X.(festimated - fo) + APpredicted > APestimated, this means that the primary reserves will be sufficient for this power deviation forecast APpredicted, without the help of reserves secondary, so no need to control a change in the electrical consumption of load 30,

[0064] b) If X.(fesümé - fo) + APprévu < APestimated, this means that the primary reserves will not be sufficient in time for this prediction of APprévu, and therefore that we will be below the predetermined operating range. In this case, to avoid having to resort to secondary reserves, the control step 44 controls a reduction in the electrical consumption of the load 30.

[0065] c) If X.(festimated - fo) + APpredicted "APestimated, this means that the primary reserves will be very insufficient in time for this forecast of APpredicted, making it possible to deduce the imminent imminence of a blackout, which means that the secondary and tertiary reserves could then not be triggered in time to help avoid this blackout. To avoid this, the control step 44 can then quickly control a significant reduction in the electrical consumption of the load 30.

[0066] When a reduction in consumption of the load 30 is requested during the control step 44, the control block 45 can do so in different ways. According to a first simple variant, the control block 45 completely stops consumption by disconnecting the load 30 from the network 10, by means of a cut-off device 23 of the contactor or relay type, which obviously amounts to making a total reduction of 100% of the consumption of the load 30 as long as the conditions of the operating domain are not restored.

[0067] According to a second variant, well suited for example to a load 30 of the electric heating type, the control block 45 temporarily reduces the consumption by controlling intermittent operation of the load 30. For example, if one wishes to partially reduce the consumption by a factor of 50%, the control block 45 alternately orders the disconnection then the reconnection of the load 30 over small identical periods of time, as long as the conditions of the operating domain are not restored.

[0068] According to a third variant, the control block 45 can reduce the consumption of the consumption point 20 by other means, for example by reducing the current consumed by the load 30, or, in the case where the load 30 is an electric motor, by reducing its speed using power electronics.

[0069] According to a fourth variant, if the consumption point 20 controls several electrical loads 30 (in the case of an individual residential electrical meter in particular), the control unit 45 can choose to disconnect from the network 10 only some of its non-essential loads and not others.

[0070] Other variants are of course possible to temporarily reduce or increase the electrical consumption at a consumption point 20.

[0071] When the conditions of the operating domain are restored, it is necessary to take Be careful to avoid starting instability again if many loads 30 reconnect at the same time. To do this, various known means are possible to stagger the restart of the loads, such as setting up an individual random restoration time delay for each consumption point 20.

[0072] Thus, thanks to the invention, the device for controlling the consumption point 20 can operate autonomously, based solely on voltage measurements of the electrical network 10, variables estimated in real time from these measurements and parameters stored locally at the consumption point 20. In this way the consumption point 20 can monitor in real time the imminence of a risk of imbalance in the network and can decide to temporarily reduce the consumption of the loads linked to this consumption point 20, so that the electrical network 10 is relieved and avoids a potential blackout.

[0073] When communication from the consumption point 20 with the electricity network manager is used, this communication is done at low speed since it is mainly used for parameter updates with a periodicity of the order of only a few minutes (calibration parameter a, thresholds of the operating domain, forecasts of power deviation APprévis, etc.). It is therefore easy to install and execute the control method of the invention in multiple consumption points 20 of the network 10, without creating communication constraints to control these different consumption points 20.

[0074] Naturally, the invention is described in the above by way of example. It is understood that those skilled in the art are able to carry out different variant embodiments of the invention without departing from the scope of the invention.

Claims

Claims

1. Method for controlling an electrical distribution network (10) at a consumption point (20) of said electrical network (10), the consumption point (20) being able to control an electrical load (30) connected to the electrical network (10), the method comprising: - a step of measuring (41) electrical voltages at the consumption point (20), - a step of estimating (42, 43) at said consumption point (20) variables representative of a state of equilibrium of the electrical network (10) from said measured electrical voltages, said representative variables comprising the frequency (f) and the temporal variation of frequency (df / dt) of the electrical network as well as the difference (AP) between the electrical power produced and the electrical power consumed in the electrical network, the estimation step (42) firstly carrying out an estimation of the frequency (f) of the electrical network from the voltages measured at the consumption point, and an estimation of the variation of frequency (df / dt) of the electrical network (10), - a control step (44) during which the electrical consumption of the electrical load (30) is modified when said estimated representative variables are outside a predetermined operating range, characterized in that: - the estimation step (43) performs in real time an estimation of the difference (AP) between electrical power produced and electrical power consumed, using an extended Kalman filter, one of the state variables of which is a calibration parameter (a) representing the inertia of the electrical network (10), - the control method comprises a periodic recalibration step (46) during which the calibration parameter (a) is updated periodically by communication between the consumption point (20) and a manager of the electrical network, and during which information predicting the difference between power produced and power consumed (APpredicted) is provided by the network manager and is used in the control step (44) to determine the predetermined operating domain.

2. Control method according to claim 1, characterized in that frequency estimation uses an extended Kalman filter and frequency variation estimation also uses an extended Kalman filter.

3. Control method according to claim 1, characterized in that the estimation of the frequency uses an extended Kalman filter in redundancy with a phase-locked loop type system.

4. Control method according to claim 1, characterized in that the predetermined operating domain is identified by thresholds for the variables representative of the equilibrium state of the network, said thresholds being updated during the periodic recalibration step (46).

5. Control method according to claim 1, characterized in that the predetermined operating domain is identified by thresholds for the variables representative of the equilibrium state of the network, said thresholds being interdependent with each other.

6. Control method according to any one of claims 1 to 5, characterized in that during the control step (44), the electrical consumption of the electrical load (30) is reduced when said variables representative of the equilibrium state are below the predetermined operating range.

7. Control method according to claim 6, characterized in that during the control step (44), the electrical load (30) is disconnected from the electrical network (10) when said variables representative of the equilibrium state are below the predetermined operating range.

8. Control method according to any one of claims 1 to 5, characterized in that during the control step (44), the electrical consumption of the electrical load (30) is increased when said variables representative of the equilibrium state are above the predetermined operating range.

9. Device for controlling an electrical distribution network (10) integrated into a consumption point (20) of said electrical network (10), characterized in that the device comprises means for measuring (21) electrical voltages at the consumption point (20), a calculation unit (22) for estimating variables representative of a state of equilibrium of the electrical network and means for controlling (23) an electrical load (30) controlled by the consumption point (20), for the purpose of implementing the control method according to one of the preceding claims.

10. Control device according to the preceding claim, characterized in that the device also comprises communication means (24), for communicating via an IoT platform the consumption point (20) with a manager of the electricity network (10).

11. Control device according to the preceding claim, characterized in that the device is integrated into a communicating electricity meter.

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