EP2892753A2

EP2892753A2 - Recharging of a pool of batteries

Info

Publication number: EP2892753A2
Application number: EP13759702.7A
Authority: EP
Inventors: Hervé GUILLOU; Duy Long Ha; Mireille Jacomino; Van-Dat CUNG
Original assignee: Commissariat a lEnergie Atomique et aux Energies Alternatives CEA
Current assignee: Commissariat a lEnergie Atomique et aux Energies Alternatives CEA
Priority date: 2012-09-05
Filing date: 2013-09-04
Publication date: 2015-07-15
Also published as: FR2995149A1; FR2995149B1; BR112015004682A2; WO2014037356A3; WO2014037356A2; JP2015530860A; US20150236531A1; CN104755313A

Abstract

Method of managing the charging of a pool of batteries on the basis of a charging system (1) comprising several charging posts (2) powered electrically from at least one energy production source (5, 6) characterized in that it comprises the following steps: a. Initialisation (E5) of a date of recharging for each battery of the pool of batteries, then in that it comprises the following steps for a battery considered: b. Definition of a neighbourhood (E12) comprising a set of recharging dates in proximity to the recharging date previously adopted for the battery considered, c. Calculation of the performance (E13) of a new solution obtained by replacing the recharging date previously adopted for the battery considered with recharging dates lying within the neighbourhood defined in the previous step, then d. Storage (E14) of the recharging date which gives the best performance following the performance calculation (E13) of the previous step and replacing of the recharging date previously adopted with this new recharging date which gives the best performance, then in that it comprises the following steps: e. Testing of a criterion of end of calculation (E20), f. If the end of calculation criterion is not attained, new iteration of steps b to d above while considering a neighbourhood of reduced duration with respect to the previous iteration for a battery considered.

Description

Recharging a battery of batteries

The invention relates to a method for managing the charge of a battery bank implemented at a charging system powered by at least one energy source. It also relates to a battery charging system as such implementing such a method.

There are many devices operating with a rechargeable battery, such as electric or hybrid motor vehicles. When the user of such an electrical device realizes that the charge of his battery is too low, he connects it to a recharging system which uses as input the power supplied by a source of electrical energy to transmit an output. charging current of the battery.

When the electrical device concerned is an electric vehicle, the battery charging system may be in the form of a shelter defining a parking space and electrically equipped for the electrical connection with the battery. Such a shelter can be equipped with photovoltaic panels generating electrical energy which is used for recharging the vehicle's battery. In practice, the driver positions his vehicle under the shelter, electrically connects to a power outlet arranged at the shelter, which has the effect of immediately initiating recharging of the battery of his vehicle. The charging phase is then automatically stopped by the charging system as soon as the battery reaches its full charge.

Existing charging systems are not optimized. Indeed, the charging of the different batteries is generally initiated from their electrical connection with the system, with the aim of their full charge. However, this recharge may require energy from an expensive and / or polluting electricity source at the time of recharging the battery. In addition, this source of energy may be insufficient at a given moment, especially if too many batteries are charging simultaneously and / or if renewable energy sources are used, such as a solar or wind source, by nature fluctuating.

To overcome these drawbacks, the document FR2952247 proposes a planning for the charging of electric vehicle batteries on the basis of knowledge of their departure date and a desired level of charge.

The document US5548200 proposes to determine the choice of electrical conditions and the time of charging to optimize the cost of charging during off-peak hours, for example.

Existing solutions are still insufficient to make the best use of recharging a battery bank in a situation where the batteries arrive randomly at a given recharging system, which exploits the electrical power from at least one source of power. energy intermittent or simply discontinuous or rare, to supply these recharges, this source may be variable more or less unpredictable, such as photovoltaic or wind energy sources.

On the other hand, the solutions must be adapted to a charging system that can accommodate a large number of vehicles, for which the algorithms for optimizing the recharging of the batteries may be saturated and unsuitable, since the optimization calculation of the process of vehicle load management is performed at each entry and / or exit of a vehicle. Thus, it is necessary to define a method for managing the load of electric vehicles that makes it possible to quickly converge towards a solution using a reasonable computing power and not too expensive, to suit the management of a park. which may include a large number of batteries, for example the management of at least 100,000 vehicles (or batteries) or at least 1 million vehicles (or batteries). Finally, there is therefore a need for an improved solution for intelligent management of the charging of a battery (s) which can include a large number of batteries, compatible with the use of an intermittent energy source and more generally from a source of energy that is unavailable on a continuous basis. For example, such a power source may be of the solar or wind type as mentioned above, or could be a national power grid whose use should be optimized and reduced, to meet cost constraints or local supply for example. A general object of the invention is therefore to propose an optimized management solution for recharging a battery bank, which meets the objectives mentioned above and does not include all or part of the disadvantages of the solutions of the state of the technique. More specifically, a first object of the invention is to propose a charging solution for a battery bank that converges rapidly to an optimized solution to be able to process a large number of batteries entering and leaving a charging system according to a significant frequency and any. A second object of the invention is to propose a charging solution for a battery bank preferably using a certain chosen source of energy, which can be intermittent. A third object of the invention is to provide a charging solution of a battery bank compatible with a random arrival of batteries on charging stations.

For this purpose, the invention is based on a method of managing the charge of a battery bank from a charging system comprising a plurality of charging terminals electrically powered from at least one power generation source. , characterized in that it comprises the following steps:

at. Initializing a recharge date for each battery in the battery park,

then in that it comprises the following steps for a considered battery:

b. Definition of a neighborhood comprising a set of recharge dates close to the charging date previously selected for the battery in question,

vs. Calculation of the performance of a new solution obtained by replacing the recharge date previously selected for the battery considered by recharge dates included in the neighborhood defined in the previous step, then

d. Memorization of the recharge date which gives the best performance following the calculation of performance of the previous step and replacement of the recharge date previously retained by this new recharge date which gives the best performance, then in that it includes the following steps :

e. Test of a criterion of end of computation, f. If the criterion of end of computation is not reached, new iteration of the steps b to d above by considering a neighborhood of reduced duration compared to the previous iteration for a considered battery. A neighborhood is advantageously formed by a time space comprising a few elementary time intervals extending around the recharge date previously selected for the battery in question. Each elementary time interval can be associated with a possible recharge date. At each iteration, the neighborhood may comprise a shorter and shorter duration, by means of elementary time intervals defined so as to form this shorter and shorter duration.

Steps b to d can be repeated for all batteries in the battery bank, or for a multitude of batteries. These steps can be repeated for this multitude of batteries at the same time, to define a global solution.

A neighborhood may be a time space extending around the recharge date previously selected and include less than 10 recharge dates to be tested, and / or the different recharge dates of the neighborhood may be successive and separated according to a given time step and / or be chosen randomly in the vicinity, and / or the different possible charging dates of the neighborhood may be distributed on either side of the recharge date previously selected and include the recharge date previously selected.

The charge management method of a battery bank may comprise a step of calculating the performance of a new solution that takes into account the proportion of energy used from one or more sources of renewable energy, such as a photovoltaic and / or wind source, and / or the overall cost of the energy used.

The method of managing the charge of a battery bank may include a step of calculating a prediction of renewable energy production by a renewable photovoltaic or wind energy source of the charging system.

The step of initializing a recharge date for each battery of the battery park may consist in choosing as initial value the date of arrival in the charging system of each battery.

The method of managing the charge of a battery bank may comprise a preliminary phase of memorizing all or part of the following parameters:

the number of batteries present in the charging system at a given moment;

the charge profile of each battery;

the state of charge of each battery;

- a recharge date at the earliest, and / or at the latest, for each battery;

a duration, on which one seeks to optimize the charge of the batteries present;

a number of periods, which makes it possible to discretize the time over this considered period;

a precision, in the form of a whole number of periods;

a temporal division, which allows a more or less important division of a considered duration;

- a formula for calculating the performance. The method of managing the charge of a battery bank may comprise the following steps:

Estimating future power generation by at least one source of energy, the predicted energy E _pr edits and the predicted power P publishes _pr (t) as a function of time t, during a reference period, by at least one source of energy production;

Estimated needs énergieΣ E _j (t) for recharging the batteries present in the charging system;

- Calculation of a dummy power Pfictive less than or equal to the predicted power and able to meet all or part of this energy requirement in a fictitious period distinct or not from the reference period;

Planning of recharges of the batteries present in the charging system during this fictitious period.

The test of an end-of-calculation criterion may include all or part of the following tests:

the performance of the solution obtained is greater than or equal to a predefined threshold; and or

the number of iterations reaches a predefined threshold; and or

the temporal division made from the time step reaches a predefined threshold; and or

- the duration of a neighborhood is less than a predefined threshold; and or

the duration between two intervals distributed around the previously selected recharge date is less than a predefined threshold; and or

the number of iterations without improvement in performance reaches a predefined threshold. The charge management method of a battery bank may then comprise a step of charging each charge system battery according to a chosen charge profile, starting from a charging start date deduced directly or indirectly from the charging system. recharge date calculated by the process after reaching the end of calculation criterion.

Steps a to f can be implemented at each input and / or output of a battery of the charging system.

The invention also relates to a charging system of a battery bank comprising a plurality of charging terminals electrically powered from at least one power generation source, characterized in that it comprises a central unit which the method of managing the charge of the battery bank as described above.

The charging system of a battery bank may include a source of renewable energy production, solar and / or wind. The charging terminals of the system can be arranged on parking spaces for recharging a fleet of electric motor vehicle batteries.

The charging system of a battery bank may comprise a central server, this central server being connected to the central unit of a charging system by at least one communication means.

These objects, features and advantages of the present invention will be set forth in detail in the following description of an embodiment particular is non-limiting in connection with the attached figures among which:

FIG. 1 schematically represents a battery charging system implementing the method of recharging batteries according to one embodiment of the invention.

FIG. 2 represents an algorithm of a battery recharge management method according to the embodiment of the invention.

Figures 3 to 1 1 illustrate the implementation of the algorithm of a battery recharge management method according to the embodiment of the invention in the context of a particular scenario by way of example. The invention will be illustrated in the case of a fleet of electric vehicles as an example. Such an electric vehicle can be an electric bike, an electric car, a segway, an electric scooter, etc. Naturally, the invention could easily be transposed to any electrical device equipped with a battery for its power supply, and requiring recharging phases of its battery. In addition, for reasons of simplification, it will be considered in the following description that each vehicle is equipped with a single battery. However, the process could of course be applied similarly to vehicles with multiple batteries. This is why the invention is more generally concerned with the problem of recharging a battery of batteries, especially in the case of a large number of batteries and where their use is random and does not allow to know precisely the individual batteries. moments when their refill will be necessary. Figure 1 illustrates a battery charging system according to one embodiment. This system comprises a charging device 1 comprising different charging terminals 2, on which vehicle batteries 8 can be electrically connected for the implementation of their charging. The charging device 1 is connected to one or more sources 5 of electric power production by an electrical connection 3, these sources being renewable and intermittent, such as photovoltaic or wind, in this particular example, and optionally connected to a traditional electrical network 6 to cope with the possible shortcomings of the previous sources. The objective is of course not to use the traditional electricity grid 6 to avoid saturating it and take advantage of less polluting and renewable sources of energy production available to the recharging device 1. The latter can thus be in the form of a parking space where each place is equipped with a battery charging station powered by photovoltaic panels, arranged for example on a roof of the car park.

The charging system further comprises a central unit 10, which comprises software (software) and hardware (hardware) means for controlling the charging device 1, so as to implement the charging method which will be detailed below. . This central unit 10 thus comprises in particular the intelligence of the charging system, in the form of any type of computer. It includes a prediction module 1 1 which implements a prediction calculation of electricity production, including that available from intermittent energy sources. It also implements a prediction calculation of the evolution of the price of electricity from the grid 6 or other permanent sources, and a prediction calculation of the arrival and / or departure of the electric vehicles. This prediction module can work from local and autonomous manner and / or from information, and / or calculations, made remotely on a server 15, connected to the central unit 10 by a communication means 16. The central unit 10 further comprises a optimization module 12 which includes the functions and algorithms for automatically defining when and how each battery connected to the charging system 1 is to be recharged. It also includes a local database 13 which allows the storage of data concerning the batteries to be charged, data representing the state of the charging system, history of past operations, etc.

The charging system is optionally connected to a central server 15, as mentioned above, by one or more communication means 16. This central server 15, which can be connected to several battery charging systems, receives information such as data. weather forecast data for example, and may participate in all or part of the calculations necessary for the operation of a charging system. Preferably, the latter is relatively autonomous, or even completely autonomous, and implements a battery charge management method using a simple and fast calculation, implemented on a computer comprising limited computing means .

Alternatively, this charging system can exploit all other sources of energy than those mentioned, according to any number. On the other hand, the management method that defines its operation can be implemented by a remote or local central unit, in cooperation or not with a remote server 15, with any computing power. We will now describe in connection with Figure 2 an embodiment of a charge management method of a battery bank, implemented by the charging system described above. The method comprises a prior phase E0 for defining and memorizing important parameters used by the future optimization calculation implemented by the method.

In one embodiment, among the parameters considered during this prior phase, the first parameters listed below relate directly to the batteries involved:

- The number of vehicles present in the charging system at a given moment, that is to say the number of batteries to be charged;

- The charge profile of each battery, as provided by the battery manufacturer for example;

- The state of charge of each battery;

- A recharge date at the earliest, and / or at the latest, for each battery.

These first parameters can be automatically transmitted by the onboard computer of each vehicle when it enters the charging system, by any means of remote communication with the central unit for example, and / or at least partly by an action voluntary driver of the vehicle. Secondly, second parameters directly relate to the optimization calculation that will be performed. These second parameters are for example entered by a manager of the battery charging system, via a human machine interface associated with the central unit 10 of the system. They allow him to perform an adjustment of the process implemented, to choose for example the compromise between the calculation time and performance of the result. Alternatively, default settings may be used. These second parameters are among:

A duration, on which it is sought to optimize the charge of the batteries present, for example a day;

- A number of periods, which allows to discretize the time over this period considered. A period may for example be of the order of a minute or a second. Advantageously, the period will be chosen so that each charge profile of the batteries represents an integer multiple of periods;

- Precision, which represents the desired accuracy when planning the battery charge. This precision can be in the form of a whole number of periods. This parameter makes it possible to choose a compromise between the desired precision and the calculation time, as will appear later;

- A temporal division p, which allows a more or less important division of a period considered, as will be explained later.

Finally, third parameters refer to the environment and to the search for performance of the charging system. In particular, a performance criterion is defined in this preliminary phase, which is used to determine whether a certain solution should be considered better than another. This criterion notably takes into account the percentage of renewable energy globally used for the charging of all the batteries, while respecting imposed dates. Different embodiments can naturally be defined, considering all or part of the parameters explained above or other parameters. Then, a second phase of the method consists of an optimization calculation that leads to a solution to define the efficient charging of all batteries of the charging system, according to a certain predefined performance criterion, mentioned above. above.

According to this embodiment, the battery charging management method calculates a variable that corresponds to the moment of the beginning (or the end) of the charge of each battery present in the charging system, more generally called the date of charging. refill. Naturally, any other date characteristic of the organization of the recharges of battery can serve as variable of the process, or even any other value which makes it possible to define the modalities of the recharge, thus indirectly a date of reloading. Then, as soon as the charge is engaged for a given battery at the date determined by the method, this charge is executed in full by applying the charge profile of the given battery.

This second phase takes place by implementing a certain number of iterations, which make it possible to converge towards an optimal solution.

For this, an initialization step E5 of the calculation is first performed by filling in any initial value for each recharge date of each battery of the charging system. Alternatively, a initial value favorable to the calculation can be chosen, as the arrival date in the charging system of each battery.

Then, the total duration considered is divided into a number of elementary time intervals, at a repeated step E10 for each iteration, making it possible to consider at each iteration a new step of time smaller and smaller. For this, the temporal clipping coefficient p is used. As a variant, this division is not carried out in this distinct step E10, which is therefore optional, but subsequently during the definition of the neighborhoods.

Then, the following steps are performed:

In the first step E1 1, a given battery is selected. As the steps described below are performed for all the batteries, they can be selected successively one after the other, in any order, which may be the order of arrival of the batteries for example. Alternatively, they can be processed by decreasing energy (or state of charge).

In the second step E12, a neighborhood of the battery is defined. This neighborhood is defined as a time space extending around the recharge date stored at the previous iteration for this battery, and comprising a maximum of a few elementary time intervals arranged around the recharge date.

In this embodiment, the neighborhood comprises elementary intervals divided equally before and after the start of recharge date, for example p elementary intervals before and after two. Naturally, the neighborhood is also limited by the overall duration considered, outside of which one does not leave, and by the dates of beginning of recharging at the earliest and at the latest indicated for the considered battery. This neighborhood therefore comprises a chosen number of intervals, each interval being delimited by interval dates, for example a start date of each interval, these dates being distributed in the vicinity, in the vicinity of the previously selected and stored recharge date. for a considered battery.

More generally, a neighborhood corresponds to a set of recharge dates (or any other variable that the process seeks to define), which are to be tested, distributed near a previously selected recharge date, for example, dividing before and / or after this recharge date, and following in a time step defined for this iteration considered. This neighborhood therefore makes it possible not to test all the solutions over the entire period considered, which would make a heavier calculation, but to be restricted to a smaller number of possibilities, positioned near a solution already envisaged at a given moment in time. calculation. Advantageously, this neighborhood thus comprises a number less than 10 possibilities, advantageously equal to 2 possibilities.

Alternatively, the neighborhood may be defined as any time space extending around the recharge date previously stored at the previous iteration for a given battery, and comprising a total duration corresponding to a few elementary time intervals. These elementary intervals can be defined deterministically, according to a principle as described above, or alternatively in a random manner, so as to have a shorter and shorter duration at each iteration. These intervals can be divided equally before and after the recharge date stored, or in a non-homogeneous manner. In addition, the different intervals considered in the vicinity may have equal or different durations. Thus, one solution may be to randomly select a (predefined) number of values within the neighborhood.

A third step E13 then consists of a displacement of the recharge date of the battery considered on each of the dates of each elementary interval of the neighborhood of the battery considered, developed in the previous step. For each of the dates of each elementary interval, the calculation of the performance parameter is performed to test the relevance of each of these dates that represent different possibilities. According to a non-limiting example, mentioned above, the performance is related to the amount of energy consumed from a production by a renewable energy source, for example photovoltaic. Thus, for each solution envisaged, the energy required is calculated and more precisely, the quantity of renewable energy required, according to an estimate of its production, is calculated. In this example, the best-performing solution is the one that uses the largest proportion of energy from a renewable energy source. The invention does not relate specifically to this calculation of the most efficient solution, and other criteria and methods of calculation can be retained. The determination of a neighborhood explained in the previous step therefore limits the possibilities tested in this step and to maintain a reasonable processing time, while allowing to improve the solution, to finally converge to an optimal final solution. When all this time space on a neighborhood has been tested, a fourth step E14 of memorizing the most optimal solution is carried out. These steps are therefore repeated for all the batteries, and make it possible to gradually define more and more optimal solutions. When all the batteries have been thus treated by the preceding steps E12 and E13, a step E20 of determining the end of the calculation or not is implemented.

The end of the calculation can be decided according to several criteria:

- The performance of the solution obtained corresponds to a predefined threshold as acceptable; and or

- The number of iterations reaches a predefined threshold. This approach allows to control the calculation time; and or

- The temporal division reaches the predefined precision in the preliminary phase; and or

- There has been a number of predefined iterations without improvement of the performance parameter of the solution. This approach avoids wasting time by important iterations without improving the result; and or

- the duration of a neighborhood is less than a predefined threshold; and or

the duration between two intervals distributed around the previously selected recharge date is less than a predefined threshold.

The method thus comprises a step E20 of testing an end of calculation criterion. As a remark, the invention does not relate specifically to this end-of-calculation test, and many solutions can be chosen, in particular according to the desired compromise between the computation time. and accuracy, taking into account at least one of the preceding criteria given as non-limiting examples.

If the end-of-calculation criterion is not reached, the method implements a step of reducing the time step E25, according to the predefined step p and mentioned above, then starts a new iteration on all the batteries, according to the steps E1 1 to E14 described above, with a finer temporal division. As a variant, any mechanism making it possible to reduce the duration of the elementary intervals considered can be implemented during this step E25, preferably enabling the duration of the intervals to be reduced by at least a factor of 2, or even for any factor strictly greater than 1.

When the end of calculation criterion is reached, the method then triggers the recharging of each battery present in the charging system according to the recharge date calculated for each of them.

This calculation is repeated each time this is considered necessary, especially at each input of a battery in the charging system, and optionally also at each output.

As it appears therefore previously, the calculation is implemented at a given moment on all the batteries present in the charging system, and makes it possible to define a global solution for future charging of all the batteries. It is therefore a powerful optimization, which does not just look for the best solution for a single battery that would enter the charging system. Alternatively, this calculation could be performed on a multitude of batteries, not necessarily all. According to a variant of the embodiment described above, if a load profile of a vehicle does not correspond to an integer number of periods, it is possible to slightly modify this profile during the initialization step E5, for example by lengthening or decreasing it, to reach a modified profile representing a whole number of periods.

Figures 3 to 1 1 illustrate the calculation described above, implemented by the algorithm of the battery charging management method, according to a particular scenario by way of example.

In this example deliberately simplified for a reason of understanding of the operating principle, the charging system comprises three batteries to manage, the load profiles 21, 22, 23 are identical and represented by a rectangular shape in the figures. The horizontal length of these rectangles corresponds to the time necessary to obtain the full charge of the battery from its empty state, and the height of these rectangles corresponds to the electric power of charge necessary for recharging. Thus, a rectangle corresponds to a very simple charge profile of a battery, which requires the reception of a constant electric power for a predefined duration, for example 3 kW for 300 minutes. Naturally, the method of managing the recharging of batteries can be implemented with different charging profile batteries, more complex, any, and with batteries having between them different charge profiles.

The parameters of the calculation, indicated in the preliminary step E0, are here as follows: - Each vehicle stays in the charging system all day;

- The photovoltaic power available during the day is estimated by curve 25;

- The chosen performance criterion of the charging system is to implement the charge of each battery using a maximum of photovoltaic power;

- Number of periods: 900 minutes;

- Accuracy: 15 minutes;

- Cutting: 3.

On the other hand, the variables to be determined by the calculation are in this example the start of recharge dates for each of the three batteries. The initialization step E5 consists in considering the recharge of each battery as soon as they enter the charging system, starting from the initial moment 0 (the beginning of the day in this example). This solution is of course not optimal since it clearly appears that recharging the batteries according to this initial solution would require a high power at the beginning of the day, a significant portion of which beyond the curve 25, thus requiring the use of electric power. additional, in addition to the available photovoltaic power. On the contrary, a large part of photovoltaic power would be available later and not used beyond the instant 300.

The first iteration of the calculation makes it possible to cut the total available time (between 0 and 900) in three intervals, defined respectively by the three initial dates 0, 300 and 600. Thereafter we will content ourselves to define each neighborhood by a set dates. These three intervals form the neighborhoods of the three batteries during this first iteration.

The consideration of the first battery represented by the lower rectangle 21 in FIG. 3 makes it possible to arrive at a new, more favorable recharge date at the instant 300, as represented by FIG. 4.

Similarly, considering the neighborhood of the second battery, represented by the lower rectangle 22 in the figures, shows that its displacement towards a recharge at instant 300 gives a better solution than that shown in FIG. to opt for an improved solution illustrated in Figure 5. Finally, this first iteration ends with the displacement of the third battery, represented by the rectangle 23 in the figures. The optimal solution chosen is recharge date 600 for this battery, which brings us to the charging configuration of Figure 6.

Then, the time step is divided by three, in application of step E25 of the method, and a second iteration is implemented. The neighborhood of the first two batteries is defined by the dates 100, 200, 300, 400, 500. The optimal position of the first battery is obtained by its recharge date 200, as represented by FIG.

The optimal solution for the second battery is slot 300. It remains unchanged. The neighborhood of the third battery becomes 400, 500, 600. Note, the following dates, beyond 600, are not explored since it would come out of the upper limit fixed at time 900 because the recharge requires a duration of 300 minutes, according to this example. The optimal position retained is for the moment 500, which induces the new temporal distribution represented by FIG.

In this exemplary embodiment, the coefficient of performance used during step E13 previously detailed is not specified. However, it appears visually on all of Figures 3 to 8 that the evolution of the temporal distribution of the batteries charges makes it possible to resort more and more to the available photovoltaic power. It appears in fact visually that the load powers which require the use of a non-photovoltaic power, as illustrated by the surfaces of the rectangles 21, 22 and 23 which exceed the curve 25 of available photovoltaic power, are becoming weaker.

The second iteration being completed, the temporal division is refined again, by cutting the elementary time intervals in three again, which makes it possible to define the neighborhood of the first battery by the start dates 133, 166, 200, 233, 266 , distributed around the solution 200 defined at the previous iteration. The testing of these different solutions, defined by this neighborhood, leads to an improved and optimized choice for the new date 166, represented by FIG. 9.

For the second battery, the choice remains unchanged and the tests on the neighborhood defined by the dates 433, 466, 500, 533, 566 for the third battery make it possible to opt for the date 466, and the solution finally represented by FIG. . The considered periods are again divided into three, which allows to reach a temporal division in elementary periods of 1 1 minutes. Since this value is less than or equal to the precision defined in the prior phase, it is therefore the last iteration.

The neighborhoods of the first and second batteries are then defined by the following respective dates: 144, 155, 166, 177, 188 and 277, 288, 300, 31 1, 322. The tests on these neighborhoods do not make it possible to improve the solution. defined at the previous iteration, which is therefore preserved. Finally, the neighborhood of the third battery is: 444, 455, 466, 477, 488. It turns out that the choice 455 is optimal, which is shown in Figure 1 1. At the end of this iteration, the end of charge criterion being reached (the predefined precision in this case), the process stops these iterations and retains the latter solution.

The method has been previously explained on the basis of a performance based on a curve for estimating the photovoltaic power available during the day. On this basis, the method thus calculates for each solution considered the amount of energy or power consumed from the estimated photovoltaic production, the performance of a given solution being considered more important than another if this quantity is larger.

However, similarly, any other curve can be used. Thus, according to an alternative embodiment, it is for example possible to provide a period shorter than the reference period of a day, which we call a notional period since defined from a fictitious energy, to initiate and plan the optimal short-term recharge of the batteries present within the charging device. As a result, the batteries are recharged at the earliest and in a manner compatible with the available energy, which makes it possible to keep a subsequent energy reserve in case of arrival of one or more other batteries during the day. In addition, the planning defines a power consumption curve that best follows, as closely as possible, the profile of the predetermined hypothetical power curve, in an optimized distribution. Another curve is thus defined in replacement of the curve previously illustrated, but used in the same way in the implementation of the method.

For this, the method according to this variant embodiment comprises a first step of determining the energy requirement E, (t) of each battery i present on the park at time t. This energy requirement E, (t) depends, for example, on the state of charge of the battery i, which makes it possible to deduce the energy necessary to reach its full load, its particular charge profile, etc. This calculation allows to know the total energy requirement at time t considered at the recharging device, calculated parΣ E _j (t).

During this first stage, the projected energy Ep _re known to be produced by the energy sources 5, 6 of the charging system on the day is estimated from meteorological forecast data or any other method, such as a a so-called persistence method consisting of taking the previous day's energy production measurements, or on the basis of stored curves, as a seasonality curve. These data can therefore be estimated theoretically and / or empirically. The predicted or predicted power Ppredite (t) at each instant t of the day is thus also estimated. The forecast period will be referred to as the reference period. In addition, the forecast energy E _pa rcstat that will be consumed by the batteries in the day from time t for recharging is also estimated, for example from statistical data of energy consumption of the charging device, from a memorization of past consumption. This statistical data thus takes into account the expected use of the parking lot. They can be separated into several categories to take into account the different nature of very different statistics, like the week or the weekend.

As a remark, the whole description considers the day as a reference period for the implementation of the process. However, any other reference period is possible.

In a second step, the method comprises the calculation of a fictitious energy Efictive (t), which corresponds to an energy that one wishes to use to meet the need identified in the planning at time t, as will appear more clear afterwards.

In this embodiment, this fictitious energy is defined by:

E predicted

The ratio Ep _re _pa rcstat called E represents energy share can answer the statistical request batteries. The fictional energy thus defined takes into account both the energy requirement of the batteries and the energy a priori actually available to meet them. Alternatively, another function could have been defined for the calculation of this fictitious energy, for example of simplified way without taking into account this ratio, that is to say for example by considering that E _pa rcstat = E _prccite- Alternatively, this ratio can also be arbitrarily defined, regardless of Ep _ré said and E _pa rcstat for adapt the fictitious power curve to take into account user criteria, using a formula such as:

Efictive (t) = r Σ _j & (t).

For example, if it is known that the battery bank is undersized compared to the needs, the predicted energy will always be lower than the energy consumed: the ratio r will be between 0 and 1. However, if it is known that the battery bank is oversized compared to the needs, the predicted energy will always be greater than the energy consumed: the ratio r will be greater than 1. However, a value greater than 2 would not be interesting insofar as the park being over-sized to excess, it is no longer necessary to use the invention which tends to bring the two curves of prediction and consumption. Thus, in general, we choose r between 0 and 2 inclusive.

In a third step, the method determines a fictitious power curve, which makes it possible to distribute the fictitious energy to be used over time. This step first requires the calculation of a time t ₀ for which the energy produced by the sources of the recharging device corresponds to half of the imaginary energy calculated in the previous step. The instant t ₀ is therefore defined by the following equation:

2 [Ppredite (u) of] - Ppredite (u) of = Efictive

We will call the fictitious period the period from 0 to 2t ₀ .

Then the dummy power curve is defined by: "fictitious (t) = Ppredite (t) SI t <t ₀ ,

Pfictive (t) = min [Ppredite (2t ₀ - t); Ppredite (t)] SI t ₀ <t <2t ₀

Pfictive (t) = 0 SI t> 2 t ₀ This approach makes it possible to determine a fictitious curve of energy production provided by the energy sources 5, 6 of the charging system, which is optimal in the short term to respond to the identified need of the battery bank or just enough to cover this need. In the particular case for which the fictitious energy is greater than the predicted energy, that is to say the energy that will be produced by the energy sources 5, 6 according to a prediction calculation, then the fictitious curve is chosen equal to the predicted power curve. Then, the recharging process implements a fourth stage of planning the recharge of the batteries of the park within the fictitious power curve defined in the previous step. This planning is then done according to the method described above, this fictitious curve replacing the curve 25 illustrated in Figures 3 to 1 1.

Claims

claims

A method of managing the charge of a battery bank from a charging system (1) comprising a plurality of charging terminals (2) electrically powered from at least one source (5, 6) for generating energy, characterized in that it comprises the following steps:

Initialization (E5) of a recharge date for each battery of the battery park,

then in that it comprises the following steps for a considered battery:

Definition of a neighborhood (E12) formed by a temporal space comprising a few elementary time intervals extending around the recharge date previously selected for the battery in question, each elementary time interval being associated with a recharge date,

Calculation of the performance (E13) of a new solution obtained by replacing the recharge date previously selected for the battery considered by recharge dates of the elementary time intervals included in the neighborhood defined in the previous step, then

Memorization (E14) of the recharge date which gives the best performance following the performance calculation (E13) of the previous step and replacement of the recharge date previously retained by this new recharge date which gives the best performance,

then in that it comprises the following steps:

Test of an end of calculation criterion (E20),

If the criterion of end of computation is not reached, new iteration of steps b to d above considering a neighborhood of duration reduced compared to the previous iteration for a battery considered, this neighborhood comprising a duration corresponding to elementary time intervals defined so as to form a shorter and shorter duration at each iteration.

A method of managing the charge of a battery bank according to the preceding claim, characterized in that steps b to d are repeated for a multitude, or all batteries in the battery bank.

Method for managing the charge of a battery bank according to one of the preceding claims, characterized in that a neighborhood is a time space extending around the recharge date previously selected and comprises less than 10 recharge dates to test, and / or in that the different recharge dates of the neighborhood are successive and separated according to a given time step and / or are randomly selected in the vicinity, and / or in that the different possible charging dates of the neighborhood are allocated on both sides of the date of reloading previously selected and include this date of reloading previously retained.

Method for managing the charge of a battery bank according to one of the preceding claims, characterized in that it comprises a step of calculating the performance (E13) of a new solution that takes into account the proportion of energy used from one or more sources of renewable energy, such as a photovoltaic and / or wind source, and / or the overall cost of the energy used. A method for managing the charge of a battery bank according to the preceding claim, characterized in that it comprises a step of calculating a prediction of renewable energy production by a photovoltaic or wind turbine renewable energy source of the system charge.

Battery charge management method according to one of the preceding claims, characterized in that the initialization step (E5) of a charging date for each battery of the battery park consists in choosing as initial value the arrival date in the charging system of each battery.

Method for managing the charge of a battery bank according to one of the preceding claims, characterized in that it comprises a preliminary phase (EO) for storing all or part of the following parameters:

the number of batteries present in the charging system at a given moment;

the charge profile of each battery;

the state of charge of each battery;

a recharge date at the earliest, and / or at the latest, for each battery;

a duration, on which one seeks to optimize the charge of the batteries present;

a precision, in the form of a whole number of periods;

a temporal division, which allows a more or less important division of a considered duration; a formula for calculating the performance.

8. Method for managing the charge of a battery bank according to one of the preceding claims, characterized in that it comprises the following steps:

Estimating future power generation by at least one source of energy, the predicted energy Ep _re-called and the predicted power P publishes _pr (t) as a function of time t, during a reference period, by at least one source of energy production;

Estimated needs énergieΣ B _j (t) for recharging the batteries present in the charging system;

Calculation of a fictitious power Pfictive less than or equal to the predicted power and capable of meeting all or part of this energy requirement in a fictitious period distinct or distinct from the reference period;

Method for managing the load of a battery bank according to one of the preceding claims, characterized in that the test of an end-of-calculation criterion comprises all or part of the following tests:

the number of iterations reaches a predefined threshold; and or

- the duration of a neighborhood is less than a predefined threshold; and or the duration between two intervals distributed around the previously selected recharge date is less than a predefined threshold; and or

the number of iterations without improvement in performance reaches a predefined threshold.

A method of managing the charge of a battery bank according to one of the preceding claims, characterized in that it then comprises a step of charging each battery of the charging system according to a chosen charge profile, starting from a charge start date deducted directly or indirectly from the recharge date calculated by the process after reaching the end of calculation criterion. 1 1. Battery charge management method according to one of the preceding claims, characterized in that steps a to f are implemented at each input and / or output of a battery of the charging system. 12. Charging system (1) for a battery bank comprising a plurality of charge terminals (2) electrically powered from at least one power generation source (5, 6), characterized in that it comprises a central unit (10) which implements the charge management method of the battery bank according to one of the preceding claims.

Charging system (1) of a battery bank according to the preceding claim, characterized in that it comprises a source (5) of renewable energy production, solar and / or wind.

14. Charging system (1) of a battery bank according to claim 12 or 13, characterized in that its charging terminals (2) are arranged on parking spaces for recharging a fleet of vehicles batteries. electric cars.

15. charging system (1) of a battery bank according to one of claims 12 to 14, characterized in that it comprises a central server (15), the central server being connected to the central unit (10). ) of a charging system by at least one communication means (16).