Providing a balancing power supply using several pooled electric vehicles

Abstract

The invention relates to a method for providing control power by means of a pool comprising several electric vehicles (EVs), comprising the steps of: determining the respective charging flexibilities of the charging pairs ([EVSE / EV]-1 - [EVSE / EV]-n) assigned to the pool from electric vehicles (EVs) and charging points (EVSEs); establishing a grid frequency-dependent PRL power curve (P PRL ) for each charging pair ([EVSE / EV]-1 to [EVSE / EV]-n) based on its respective charging flexibility; transfer of the PRL power curves (P PRL ) of the charging pairs ([EVSE / EV]-1 - [EVSE / EV]-n) to associated charging controllers, which are configured to charge the associated electric vehicle (EV) at least depending on a current grid frequency (f) according to its PRL power curve (P PRL ) to control; setting up, by the pooling instance (Pl), an overall PRL performance curve (P PRL | p ), which is an aggregation of PRL performance curves (P PRL) individual charging pairs ([EVSE / EV]-1 - [EVSE / EV]-n) corresponds; and calculating a control power provided by the electric vehicles (EV) of the pool based on the overall PRL power curve (P PRL | p ).

Description

[0001] The invention relates to a method for providing control power by means of a pool comprising several electric vehicles. The invention also relates to a computer program product comprising code which, when executed on a data processing device, performs the method. The invention further relates to a control system comprising several charging pairs consisting of individual electric vehicles and charging points, the charging processes of which can be controlled by means of a charging controller, and a central pooling instance that is data-linked to the respective charging controllers, wherein the control system is configured to perform the method.

[0002] It is known from the prior art that primary control reserve (PCR, also known internationally as "Frequency Containment Reserve", FCR) is provided by individual charging pairs, each comprising a charging station and a connected electric vehicle. It is also known that candidates for providing primary control reserve are selected from a group (a "pool") of such charging pairs. The provision of the primary control reserve P PRL (f) is controlled locally by a local measurement of the mains frequency f, e.g. according to the relationship P PRL (f) = P {PQ} · Δf / 200 mHz, where P {PQ} The maximum available (prequalified) power corresponds to Δf, and the deviation of the measured grid frequency f from a target grid frequency f0 corresponds to Δf. Δf may be limited by a maximum achievable frequency deviation, if this deviation is exceeded, P {PQ}is not increased further. For example, the target grid frequency f0 can be 50 Hz or 60 Hz, depending on which target grid frequency f0 the power supply network receiving the primary control power uses.

[0003] One problem with using electric vehicle traction batteries to provide primary control reserve is that, due to the minimum bid size of 5 MW for control reserve, a large number of vehicles, typically charging (and / or discharging) at a charging power P of approximately ± 10 kW, must be pooled to meet this minimum bid size. Additionally, any electric vehicles that fail must be compensated for by other electric vehicles. This is typically achieved by a pooling entity aggregating individual vehicles into a pool to market the primary control reserve of the pooled electric vehicles on an ancillary services market via market access, for example, through an energy market aggregator. The energy market aggregator is then obligated to monitor and provide proof of the primary control reserve provided to the grid operator.This means that the energy market aggregator must transmit the currently provided control power to the grid operator (e.g., to the grid operator's control center, for example via the IEC-104 protocol) for monitoring purposes at specific time intervals (latency), e.g., less than 10 seconds. If necessary, the power data can be provided subsequently to verify the primary control power provided by the pool or the individual charging pairs.

[0004] In conventional technical units that provide primary control reserve (e.g., generators at power plants or large battery storage systems), the primary control reserve of the system is continuously measured and transmitted to the grid operator via a digital channel through the energy market aggregator – thus monitoring each system individually. With many thousands of charging pairs aggregated into a pool (e.g., in the sense of a virtual power plant), this approach leads to very large volumes of data and also to the problem that the measured values ​​from different charging pairs often arrive asynchronously. Summing the measured power of the individual charging pairs into a total power, which is then reported to the grid operator, means that the aforementioned latency criterion of less than 10 seconds for monitoring the total primary control reserve provided cannot be met. Furthermore, due to the asynchronous nature of the measured values, there is also the problem of correct aggregation, i.e.,the problem of how to deal with measurements from different charging pairs that are measured at different but close times.

[0005] US 10,663,932 B2 discloses methods, devices, and systems for charging and discharging an energy storage device connected to a power distribution system. In one exemplary embodiment, a controller monitors the electrical characteristics of a power distribution system and provides an output to a bidirectional charger, which charges or discharges an energy storage device (e.g., a battery in a plug-in hybrid electric vehicle, PHEV). The controller can contribute to stabilizing the power distribution system by increasing the charging rate when there is a power surplus in the power distribution system (e.g., when the frequency of an AC grid exceeds an average value) or by discharging power from the energy storage device to stabilize the grid when there is a power shortage in the power distribution system (e.g., when the frequency of an AC grid is below an average value).

[0006] WO 2020 / 120457 A2 discloses a device for charging and discharging the drive energy storage system of a hybrid or electric vehicle. The device comprises a frequency measurement module configured to measure the grid frequency of a power supply network; a control module configured to control, based on the measured grid frequency, charging the drive energy storage system from the power supply network or discharging it into the power supply network to provide ancillary services; and a first communication module configured to communicate with the hybrid or electric vehicle as a master for the provision of ancillary services. The method describes the bundling of several vehicles into a vehicle pool and the activation of individual vehicles within the pool to provide ancillary services.

[0007] US 2008 / 0052145 A1 discloses systems and methods for a power aggregation system. In one implementation, a service establishes individual internet connections to numerous electrical resources that are temporarily connected to the power grid, such as electric vehicles. The service optimizes power flows to meet the needs of each resource and resource owner while aggregating flows across numerous resources to meet the demands of the power grid. The service can bring large quantities of electric vehicle batteries online as a new, dynamically aggregated power resource for the grid. Electric vehicle owners can participate in a power trading economy regardless of where they connect to the grid.

[0008] DE 10 2009 050 042 A1 discloses a charging station for electric vehicles. Grid stabilization is achieved by providing a grid frequency measuring device for recording the grid frequency and for detecting deviations from a target frequency, and by providing a load control device in operative connection with the grid frequency device such that, in the event of a detected deviation of the grid frequency from the target frequency, the load control device regulates the electrical power supplied to an electric vehicle from the charging station.

[0009] DE 10 2022 127 911 A1 discloses a method for providing primary control reserve for an energy market, comprising the steps of: predicting a multitude of mobility behaviors of a multitude of electrically powered motor vehicles using an electronic computing device; determining a potentially available primary control reserve depending on the prediction using the electronic computing device; generating a control schedule for regulating the energy supply of a respective motor vehicle using the electronic computing device; when the primary control reserve is requested by the energy market, transmitting an individual control to respective local control units at the respective motor vehicles depending on the control schedule using a communication device and executing the individual control of a respective motor vehicle using the local control unit.Furthermore, a computer program product and a rule system are disclosed.

[0010] DE 10 2017 209 801 A1 relates to a method for operating a large number of technical units as a network on an electrical distribution network. It provides that a central control device receives flexibility data from each technical unit, indicating a power range within which its electrical power may or is expected to vary. Based on the flexibility data of each unit, an individual, non-binding incentive function is determined for each unit, depending on a predetermined optimization goal of the network, and provided to the respective unit. In response to the individual incentive function, each unit then receives a schedule describing the time course of the planned power exchange according to a local optimization goal of the unit. From these schedules, an overall schedule for the network is generated.

[0011] DE 10 2022 129 783 A1 discloses a system for relieving the load on a local power grid and a higher-level power grid, which are electrically coupled to each other at a grid connection point, comprising at least one charging unit electrically connectable to the local power grid for electrically charging an electrically powered vehicle, wherein the charging unit has an energy storage device, a computing unit coupled to the at least one charging unit via a signal connection, comprising a processor, a data storage device and a receiving unit for receiving grid data, which represents at least a demand for electrical power from the local power grid and a grid frequency of the higher-level power grid, wherein the computing unit is configured to determine, based on the grid data, an electrical power to be supplied to the higher-level power grid and / or the local power grid, and wherein the computing unit is configuredto control the charging and / or discharging of the energy storage system in such a way that the determined electrical power is supplied to the higher-level power grid and / or the local power grid.

[0012] It is an object of the present invention to at least partially overcome the disadvantages of the prior art in providing primary control power from a pool of electric vehicles and, in particular, to inform a market participant of an energy market, especially network operator and / or energy aggregator, about a total primary control power provided by a pool of electric vehicles with a particularly low latency.

[0013] This problem is solved according to the features of the independent claims. Preferred embodiments can be found in particular in the dependent claims.

[0014] The task is solved by a procedure for providing balancing power to an energy market using a pool comprising several electric vehicles, with the following steps: - Determining the respective charging flexibilities of the charging pairs of electric vehicles and charging points assigned to the pool; - Establishing a mains frequency-dependent PRL power curve for each charging pair based on its respective charging flexibility; - Transmitting the PRL power curves of the charging pairs to respective charging controllers, which are set up to control the charging of the respective associated electric vehicles depending on the current grid frequency according to its PRL power curve; - Establishing, through the pooling instance, an overall PRL power curve that corresponds to an aggregation of PRL power curves of individual charging pairs, - Calculating the control power provided by the electric vehicles (EVs) of the pool based on the overall PRL power curve (P PRL | p ).

[0015] This method offers the advantage that the control power provided by the pool can be calculated with a latency of well under 10 seconds, e.g., almost in real time at approximately 1 second. It leverages the fact that the individual control power curves or functions of the charging pairs assigned to or currently participating in the pool can be quickly aggregated into the overall control power curve. This overall control power curve accurately reflects the control power provided by the entire pool as a function of the grid frequency. It is assumed that the grid frequency is the same for all electric vehicles connected to the pool, which is generally the case, for example, when the charging points are connected to the same grid. The control power provided can therefore be calculated using a single function, namely the overall control power curve, which is typically achieved in less than one second.

[0016] Furthermore, the control power provided, calculated via the overall PRL power curve, corresponds to the actual control power provided with high accuracy and low tolerance. The overall PRL power curve can even be predicted with high accuracy for points in the immediate future. This is based on the fact that the charging pairs follow the control signals specified by their individual PRL power curves with a very high probability, and that individual failures, with a typical large number of electric vehicles participating in the pool (typically more than a thousand or tens of thousands), are below the tolerance threshold. If vehicles fail and / or join, this can be registered promptly through continuous monitoring of the pool, and the overall PRL power curve can be recalculated.

[0017] The sequence of the procedural steps is not limited to the above sequence. Rather, at least two of these procedural steps can also be carried out in a different sequence than specified, or even simultaneously.

[0018] It is important to understand that the standard control reserve is a primary control reserve. However, it can also be a secondary control reserve, etc.

[0019] The balancing power, in particular primary control power, can be made available to the electricity grid to which the charging points of the charging pairs are connected, or to an associated grid operator. The balancing power can be offered directly to the grid operator by the pooling entity or indirectly via another market participant, such as an energy market aggregator, acting as an intermediary.

[0020] In general, the total flexibility of the pool can be offered in advance to a market participant, such as the grid operator or the energy market aggregator, for use in balancing services, particularly primary control reserve, for a specific time period. Upon acceptance of the offer in whole or in part, a corresponding overall primary control reserve power curve can be transmitted to the market participant in advance. The market participant can then call upon the balancing service as needed. Therefore, a training course can generally consist of two phases: first, the offer phase, and then the control phase, which reacts to a call for balancing service. The offer phase can be, and typically is, carried out much earlier than the control phase.

[0021] It is particularly important that the balancing power only needs to be provided by the pooling instance if the grid operator requires it. To cover the required balancing power, a suitable overall balancing power curve can be established using the pooling instance, which may not include all charging pairs in the pool, but only a subset of them. This can be implemented, for example, by having a (demand) signal sent directly from the grid operator or indirectly via an intermediary such as an energy market aggregator to the pooling instance. The pooling instance then sends appropriate activation signals to selected, or possibly all, charging pairs in the pool or their charging controllers to aggregate the desired overall balancing power curve. These activated charging controllers then adjust the charging power accordingly.The charging behavior of the associated charging pair is modified based on the respective PRL power curves. The creation of the overall PRL power curve, which corresponds to an aggregation of the PRL power curves of individual charging pairs, can therefore also be described as "selective" or "demand-based" configuration. If not all charging pairs are activated or selected to provide balancing power, the decision as to which charging pairs are activated and which are deactivated can be made based on one or more criteria, such as the amount of balancing power that can be provided, the expected connection duration, the battery state of charge, the setting whether battery discharge is also permitted, contractually agreed priority rules, etc.If the demand for balancing power changes, specific charging pairs can be additionally activated or deactivated to provide balancing power, depending on the situation. When charging pairs are deactivated, their charging controllers adjust their charging power again without regard to the respective primary control power curves. The above procedure for providing balancing power, especially primary control power, is therefore only necessary if the balancing power is drawn from a previously created pool of charging pairs. Consequently, it is a further development that the pooling instance only activates as many charging pairs as are necessary to fulfill the requested balancing power. This is particularly advantageous if not all of the pool's offered flexibility or balancing power is accepted and / or actually used, but only a portion of it.

[0022] The electric vehicle can be, for example, a plug-in hybrid vehicle (PHEV) or a fully electric vehicle, such as a battery electric vehicle (BEV). In this case, the electric vehicle's energy storage system can consist of at least one traction battery. The electric vehicle can be, for example, a passenger car, truck, bus, motorcycle, etc.

[0023] In this context, "charging" can be understood to mean both charging and discharging.

[0024] Determining charging flexibility is a well-established principle and relies on a charging plan for the connected electric vehicle, developed taking into account charging constraints. This plan might, for example, include a desired target charge level at a specific or estimated disconnection time. The charging plan depends on the charging constraints of the charging point (e.g., its charging capacity), the electric vehicle (e.g., its charging capacity, charging mode such as "instant charging" or "delayed charging," etc.), and potentially also the local power grid (e.g., periods of particularly cost-effective charging) and the higher-level power grid (e.g., a maximum available charging capacity). The charging plan can be optimized for cost and / or environmental impact.The charging schedule can be established by the vehicle, the charging point, or another entity such as a home energy management system (HEMS). Once the charging schedule is established, it is implemented by the energy supplier to which the charging point is connected. The charging power profile assigned to the schedule is also referred to as the "baseline."

[0025] If the target state of charge can only be achieved by setting the maximum charging power, there is no way to deviate from the charging plan; it is therefore not flexibly modifiable. In other words, this charging plan offers no flexibility. However, most charging plans do offer some flexibility, meaning that temporary deviations from the charging plan are possible as long as the target state of charge, or a predefined range around the target state of charge, is still reached. For example, if a charging plan specifies "instant charging" to a target state of charge of 80% SoC, and the target state of charge is reached after two hours, but the electric vehicle is not scheduled to be disconnected until six hours later, the charging plan will result in a four-hour rest period for the traction battery, during which it is maintained at the previously reached target state of charge of 80% SoC.The "baseline" corresponds to the maximum charging power during instant charging and to zero during the subsequent rest phase. The rest phase can be used to temporarily charge and discharge the traction battery, as long as the target state of charge is at least approximately reached when disconnecting.

[0026] Other charging scenarios include "late charging", where there is a rest period after connecting the electric vehicle, as the electric vehicle is charged at the latest possible time with maximum charging power.

[0027] However, in practice, most charging plans lie between the two extremes of "instant charging" and "delayed charging" and usually show longer charging times at a lower power output than the maximum power, especially – as already indicated above – optimized for specific charging goals, e.g., particularly cost-effective charging and / or particularly environmentally friendly charging, possibly in conjunction with other consumers and, if available, intermediate storage and / or energy generation facilities on a property, etc. Charging flexibility is also generally available here.

[0028] These "charging flexibilities" are typically subject to certain boundary conditions, such as the maximum permissible deviation from the baseline (e.g., ± 10% SoC), a maximum number of discharge cycles within the coupling period, the decision as to whether discharging is possible or permitted, and whether the charge levels should not exceed or fall below the baseline, etc. In this case, the flexibility is used to provide primary control reserve. When the grid frequency is detected as being too low, the vehicle feeds energy back into the grid in addition to the baseline; when the grid frequency is too high, it feeds energy into the grid in addition to the baseline, each within the limits of the permitted flexibility. If the baseline is zero, this corresponds to net energy feed-in when the grid frequency is too low and net energy feed-in when the grid frequency is too high.If, however, the vehicle is currently being charged according to the baseline, a lower energy level or slower charging rate compared to the baseline is possible if the grid frequency is too low, while a higher energy level or faster charging rate is possible if the grid frequency is too high. This takes advantage of the fact that the grid frequency increases when energy is fed into the grid and decreases when energy is drawn. Establishing a baseline in which the electric vehicle is charged for a longer period, especially continuously, at a lower power than its maximum power is particularly helpful for providing primary control reserve even for electric vehicles that do not allow (physical) discharge.In addition, it can be advantageous that the charging power according to the baseline is absolutely greater than the absolutely permissible maximum value of a discharge for primary control power, so that the resulting total power that actually flows into the electric vehicle remains positive.

[0029] The charging flexibilities of the respective charging pairs in the pool can be determined in a generally known manner, and in particular, updated, e.g., taking into account already utilized charging flexibilities, changes in charging boundary conditions, etc. The charging flexibilities can, for example, be determined by the same entity that created the charging plan.

[0030] The central pooling instance is connected to the charging pairs in the pool via data, either directly or indirectly via a HEMS or similar device. This allows charging flexibilities to be transmitted to the pooling instance. The grid frequency-dependent PRL power curves for each charging pair are generated by the pooling instance based on their respective charging flexibilities. The pooling instance can be, for example, an IT system of a vehicle manufacturer or fleet operator.

[0031] A grid frequency-dependent PRL power curve for a charging pair corresponds to a relationship, representable as a curve, between the grid frequency and the control power to be provided by this charging pair.

[0032] The individual primary control reserve (PCR) curves are transmitted to the corresponding charging controllers of the respective charging pairs. The charging controllers are configured to control the charging (charging or discharging) of the electric vehicle according to its PCR curve, depending on the current grid frequency. The charging controllers operate autonomously, i.e., without further intervention from the pooling instance. Controlling the charging according to the PCR curve can be implemented, for example, by the charging controller superimposing the primary control reserve to be provided, derived from the PCR curve and the grid frequency, onto the baseline and then executing the charging process of the traction battery(ies) accordingly.

[0033] Furthermore, the pooling instance aggregates the overall primary control reserve (PCR) power curve from the (particularly selected) individual PCR power curves, for example, by simple addition. The overall PCR power curve represents the primary control reserve to be provided by the entire vehicle pool as a function of the current grid frequency. Since it can be assumed that the charging pairs follow the control signals of their charging controllers, as specified by their individual PCR power curves, with a very high probability, and that individual failures, with a typical high number of electric vehicles participating in the pool, are below the tolerance threshold, the primary control reserve to be provided, as represented by the overall PCR power curve, can be equated with the primary control reserve actually provided with sufficiently high accuracy.Consequently, it is advantageously possible to approximate the actual control power provided by the pool with high accuracy simply by calculating the overall PRL power curve using the known current grid frequency. Since this is a simple calculation, the control power can be (re)calculated at very short intervals.

[0034] One configuration involves generating the individual PRL power curves locally at the charging pairs (i.e., by the charging pairs themselves, their associated charging controllers, or local energy management systems that consider the respective charging pair) based on their respective charging flexibilities. These curves are then reported or transmitted to the pooling instance, which uses aggregation to generate the overall PRL power curve. This has the advantage of relieving the pooling instance of the computational overhead of calculating the individual (local) PRL power curves. The individual PRL power curves can then also be transmitted locally (i.e., without involving the pooling instance) to the associated charging controllers if the charging controllers have not already generated them. Generating the overall PRL power curve by aggregation, particularly addition, from the individual PRL power curves is advantageously very easy to implement.In a training course, the charging flexibilities of the charging pairs assigned to the pool can be reported or transferred to the pooling instance, which then creates an overall charging flexibility and offers it to market participants for use as balancing power.

[0035] One configuration involves reporting the charging flexibilities of the charging pairs assigned to the pool to the pooling instance. The pooling instance then uses this information to generate individual PRL (Predictive Load) power curves for each charging pair and transmit them to the corresponding charging controllers. This offers the advantage of relieving local instances of the burden of calculating the associated PRL power curves, and the pooling instance can also coordinate the individual PRL power curves if necessary. Furthermore, the pooling instance can easily calculate and generate the overall PRL power curve from the individual PRL power curves. Here, too, an overall charging flexibility can be calculated from the individual charging flexibilities and offered to market participants for use as balancing power.

[0036] One configuration involves reporting or transmitting the charging flexibilities of the charging pairs assigned to the pool to the pooling instance, which then uses this information to construct the overall PRL power curve (e.g., first by calculating the overall charging flexibility from the individual charging flexibilities and then calculating the overall PRL power curve), and then using the overall PRL power curve to disaggregate the individual PRL power curves for each charging pair and transmitting them to the corresponding charging controllers.

[0037] Transmitting the charging flexibilities of individual charging pairs to the pooling instance can involve transmitting not the fully determined charging flexibilities themselves, but (only) the data required to issue them, such as the respective charging requests, charging boundary conditions, and, if applicable, baselines. The pooling instance can then determine the respective charging flexibilities from this data. This "centralized" determination of individual charging flexibilities and, if applicable, baselines, offers the advantage of simplifying updates to the calculation logic. Conversely, a "decentralized" determination of individual charging flexibilities is advantageous for reducing the computational overhead of the pooling instance.

[0038] In general, the baselines of individual charging pairs can be determined centrally or decentrally. In the former case, the baselines can then be transmitted to the respective charging controllers, and in the latter case, to the pooling instance. The pooling instance can then, through further processing (e.g., aggregation), determine an overall baseline for the pool and offer it on the market for purposes other than providing a control line.

[0039] One configuration involves charging points that are components of local power grids, connected via an energy meter to a mains power grid, which receives the control reserve, particularly primary control reserve. A local power grid could, for example, be the power grid of a property connected to the mains power grid via the energy meter. Additionally, each charging point may have its own energy meter. A property could be, for example, a commercial or private property, such as a charging park, a parking lot with multiple charging stations, a residential building, especially a single-family home, etc. A property can have one or more charging points. The charging point could be a charging station, a wallbox, an inductive charging pad, etc.

[0040] One design involves monitoring, and in particular measuring, the grid frequency via energy meters connected to the power grid. This allows the grid frequency for providing balancing power to be determined advantageously and very quickly. The monitored grid frequency is then transmitted to at least one charging controller of the local power grid, which can control the charging of at least one charging pair. The charging controller then controls the charging of the at least one charging pair it can control using the respective PRL power curve, e.g., by superimposing it with the respective baseline.

[0041] It is a configuration in which a single PRL power curve for a charging pair is a particularly continuous function P PRL (f) the requested regular benefit P PRL with the properties - for f ≤ f PRL,min : P PRL (f) = - P PRL,min with f PRL,mina predetermined lower frequency threshold below a target mains frequency f0 and P PRL,min > 0 of an absolute maximum control power that can be discharged by the electric vehicle, - for f PRL,min < f < f PRL,max : K PRL (f) with f PRL,max a predetermined upper frequency threshold above the target mains frequency f0 and K PRL (f) a curve segment that increases monotonically with higher network frequencies f, - for f ≥ f PRL,max : P PRL (f) = P PRL,max with P PRL,max which corresponds to the maximum control power that can be charged by the electric vehicle. The following applies - P PRL,min ≤ P PRL (f) ≤ P PRL,max In particular, K PRL (f) continuously approaches the frequency thresholds f PRL,min and f PRL,max on. In particular, K PRL (f) strictly monotonically increasing. In particular, K PRL (f0) = 0. In general, the deviations from the target network frequency f0, namely Δf PRL,min = f0 - fPRL,min and Δf PRL,max = f PRL,max - f0 may be the same or different in magnitude. Also, P PRL,min and P PRL,max The amounts may be the same or different.

[0042] The PRL power curves P(f) can be the same or different for at least two charging pairs. For example, f PRL,min , f PRL,max , f min , P PRL,min and / or P PRL,max as well as the curve shape of K PRL (f) distinguish.

[0043] It is a design feature that the curve section K PRL (f) is at least piecewise linear. This facilitates the aggregation of the individual PRL performance curves into the overall PRL performance curve. It is a further development that the curve segment K PRL (f) corresponds to a linear function with a constant slope. It is a further development that the curve segment K PRL(f) is structured like a polygon. In particular, non-linear curves can also be approximated in this way while still using simple aggregation. If the curve segment K corresponds PRL (f) of a linear function, this can also be described in further education as - - s · P PRL,min with s = Δf PRL,min / f PRL,min for f PRL,min < f < f0; - 0 for f = f0; - + s · P PRL,max with s = Δf PRL,max / f PRL,max for f0 < f < f PRL,max be expressed.

[0044] One configuration involves the charging control system executing a charging process for the electric vehicle of the charging pair based on a charging curve that corresponds to a superposition of an associated baseline with the PRL power curve. This is advantageously particularly easy to implement. In this configuration, feeding control power back from the electric vehicle corresponds to a reduction of the baseline, and receiving control power into the electric vehicle corresponds to an increase of the baseline. The fact that the charging curve corresponds to a superposition of an associated baseline with the PRL power curve specifically means that, at a given time, the baseline value applicable at that time and the value calculated from the grid frequency at that time using the PRL power curve or function are aggregated, in particular added.

[0045] Thus, a baseline performance P is established. Bas(t) taken into account, the total charging power P can be determined at a specific time t. ges the relationship P ges (f) = P Bas + P PRL (f) be assumed.

[0046] One configuration involves the central pooling instance setting up the overall primary control reserve (PCR) power curve in such a way that, as it approaches at least one of the frequency thresholds, it flattens out towards the corresponding predefined minimum and / or maximum primary control reserve. This achieves the advantage of stabilizing the pool's control, as small jumps can occur in the gradient of the overall PCR power curve, and this configuration results in a "smoother" overall PCR power curve. This configuration of the overall PCR power curve can be achieved, for example, by having the pooling instance select or selectively activate the individual PCR power curves required to provide the requested control reserve when not all of them are needed.

[0047] It is a configuration such that if the mains frequency f is within a deadband of f0 - f Tmin ≤ f ≤ f0 + f Tmax with f Tmax > 0 around the target frequency f0, at which point no primary control power is requested from the pool. This can be particularly advantageous if other participants in the control loop are also active, in order to avoid oversteering. If a deadband is taken into account, the primary control power curve can, for example, assume the value zero there or form a plateau with the value zero. In particular, the curve segment K PRL (f) exhibit such a plateau in the dead zone and otherwise at least in sections a strictly monotonically increasing course.

[0048] One design feature involves recalculating the overall primary control reserve (PCR) power curve at regular intervals. This advantageously minimizes the difference between calculated and actual total primary control reserve. Recalculating the overall PCR power curve can include, for example, deleting the PCR power curves of temporarily disconnected electric vehicles, adding PCR power curves of newly added charging pairs, and / or updating existing PCR power curves. This recalculation or updating can be implemented quickly, e.g., approximately every second.

[0049] It is an additional or alternative design feature that the overall primary control reserve (PRL) performance curve is recalculated or updated in response to events. This also advantageously helps to keep the difference between calculated and actually delivered total primary control reserve low.

[0050] It is further information that an event includes the coupling and / or disconnection of an electric vehicle to or from a charging point, local interventions by HEMS, a customer switching to instant charging, the presence of competing interventions by other control options, e.g. according to §14a Energy Industry Act, etc.

[0051] One configuration involves calculating the balancing power based on the overall PRL power curve using the pooling instance, and the result of the calculation being reported or transmitted to at least one relevant market participant, e.g., for monitoring and / or reporting purposes. The relevant market participant comprises at least one market participant with whom an agreement has been reached to report the balancing power. In particular, the pooling instance or its operator may be obligated to report the calculated balancing power to the relevant market participant.

[0052] One configuration involves calculating the balancing power based on the overall balancing power curve in such a way that the overall balancing power curve generated by the pooling instance is reported or transmitted to at least one relevant market participant. This at least one relevant market participant can then calculate the likely balancing power provided. If the overall balancing power curve is modified, it is transmitted to the at least one relevant market participant in the following manner.

[0053] The task can also be solved by a computer program product comprising code which, when executed on a data processing device, performs the procedure as described above. The computer program product can be designed analogously to the procedure, and vice versa, and offers the same advantages.

[0054] The task is further solved by a control system comprising several charging pairs consisting of individual electric vehicles and charging points, whose charging processes can be controlled by a charging controller, as well as a central pooling instance linked to the respective charging controllers via data technology, wherein the control system is configured to carry out the procedure as described above. The control system can be designed analogously to the procedure and the computer program product, and vice versa, and offers the same advantages.

[0055] The properties, features and advantages of this invention described above, as well as the manner in which they are achieved, will become clearer and more easily understood in connection with the following schematic description of an exemplary embodiment, which will be explained in more detail in conjunction with the drawings. Fig. Figure 1 shows a property connected to an energy supply network, which has a charging point to which an electric vehicle is connected; Fig. Figure 2 shows a possible baseline and charging flexibility as a plot of electrical power against time; Fig. Figure 3 shows a sketch of a system with market participants, an external pooling instance, and multiple load pairs; Fig. Figure 4 shows a possible PRL power curve for a charging pair as a plot of electrical power against a mains frequency; Fig. Figure 5 shows a possible overall PRL power curve as a plot of electrical power against a mains frequency; and Fig. Figure 6 shows a possible sequence of events.

[0056] Fig. Figure 1 shows a property LS connected to the EVN energy supply network, which has a charging point EVSE to which an electric vehicle EV is connected, here via a charging cable. The electrical energy or power exchanged between the property LS and the EVN energy supply network can be sustainably monitored by an energy meter, e.g., a "smart meter" SM present at the connection point and / or an optional energy meter EM belonging to the property LS. The smart meter SM and the optional energy meter EM can also measure the current grid frequency f and transmit it via a data network value. The property LS, e.g., a single-family home, has, in addition to the charging point EVSE, electrical consumers (not shown) and may optionally also have electrical energy generation equipment (not shown) such as a photovoltaic system, a wind turbine, etc., as well as at least one stationary energy storage system (not shown).

[0057] The charging point EVSE and the electric vehicle EV form a charging pair with associated charging boundary conditions. These charging boundary conditions can include, for example, maximum charging capacities of the charging point EVSE and the electric vehicle EV, as well as the possibility of bidirectional charging, i.e., not only charging but also discharging.

[0058] Together with a charging request, e.g., regarding a specified or predicted departure time, a target state of charge, or target optimization (e.g., for particularly cost-effective and / or environmentally friendly charging), etc., a future-oriented charging plan can be created with a baseline representing the required charging power. This charging plan can typically take into account variable electricity prices, the electricity mix, feed-in tariffs, and power limitations of the EVN energy supply network.

[0059] In particular, if the property (LS) is equipped with an electrical power generation unit and / or a stationary energy storage system, the flow of electricity within the property (LS), and, if an electric vehicle (EV) is connected, also to the vehicle, can optionally be controlled by an energy management system, such as a home energy management system (HEMS). The charging plan can then also take into account, for example, the electrical energy generated by the property and / or the possibility of intermediate storage, in order to achieve optimized charging. The charging plan for the electric vehicle (EV) can be generated, for example, by the electric vehicle (EV), the charging point (EVSE), or the energy management system. A charging controller (not shown) that implements the charging plan by outputting corresponding control signals can be integrated into the electric vehicle (EV), the charging point (EVSE), or the energy management system.If the instance creating the charging plan does not include the charging controller, the charging plan can be appropriately transferred from this instance to the charging controller.

[0060] Fig. Figure 2 shows a possible baseline P as a plot of electrical power P in kW against time t. bas , P_bas, and a charging flexibility P used to provide control performance PRL , P_PRL. The baseline P bas The duration shown has been assumed to be constant for the example given, specifically with P. bas > 0, i.e., that the electric vehicle EV is charged with constant power over the indicated time period according to the charging plan, e.g. from the energy supply network EVN, the local electrical energy generation facility and / or from the stationary intermediate storage.

[0061] In the case of the charging pair EV, EVSE with bidirectional charging capability assumed here, it is assumed that charging flexibility can be provided over the time period shown, namely in the form of a charging (P > P). bas ) or a discharge (P < P bas ) of the traction battery(ies) of the electric vehicle EV. Shown is the actual course of the control power P provided within the framework of charging flexibility. PRL While the charging flexibility is predictable, the control power P is determined PRL from the current mains voltage f or its deviation from the target value f0. This corresponds to an "a posteriori" view, such as that which can be generated by a reporting system based on measurement data (not substitute values).

[0062] Fig. Figure 3 shows a sketch of a system with market participants EMA, ENV, a pooling instance Pl and several loading pairs [EVSE / EV]-1, ...., [EVSE / EV]-n, where n can typically be in the range of 1000 ... 100,000, but is not limited to this range.

[0063] The n charging pairs [EVSE / EV]-1, ..., [EVSE / EV]-n, which are data-linked to the pooling instance Pl, transmit their respective baselines and flexibilities to the pooling instance PI. Alternatively, the charging requests and charging boundary conditions, etc., of the charging pairs [EVSE / EV]-1, ..., [EVSE / EV]-n are transmitted to the pooling instance PI, which then determines the respective baselines and flexibilities. The pooling instance Pl can then, for example, aggregate the baselines and offer them to market participants in an energy market for servicing, such as an energy market aggregator EMA. The aggregated flexibilities are also offered to the market participants of the energy market, in this case as a contribution to primary control reserve. How much of the potentially available aggregated flexibility is then used as primary control reserve P PRL(f) is provided, depends on the occurring grid frequency fluctuations and, for example, on a call-up by the relevant market participant, e.g., the energy market aggregator EMA. If the offered aggregated flexibility is accepted (in whole or in part) by a market participant, the associated primary control reserve P PRL(f) by controlling the charging pairs [EVSE / EV]-1, ..., [EVSE / EV]-n by means of a local measurement of the grid frequency f, provided locally on a pro rata basis. The pooling instance PI reports the aggregated primary control reserve, in particular to the receiving market participant, e.g., the operator of the energy supply network ENV and / or the energy market aggregator EMA. The latter may be the case, for example, if the energy market aggregator EMA is obligated to monitor and provide proof of the primary control reserve provided to the network operator ENV. This means that the energy market aggregator EMA must transmit the currently provided control reserve to the network operator ENV (e.g., to the control center of the network operator ENV, for example, via the IEC-104 protocol) for monitoring purposes at specific intervals, e.g., less than 10 seconds.

[0064] In order to comply with this latency time, the pooling instance PI creates individual grid frequency-dependent PRL power curves for all existing charging pairs [EVSE / EV]-1, ..., [EVSE / EV]-n that are authorized for use of primary control reserve, based on their respective charging flexibilities, and transmits these to the respective charging controllers.

[0065] The charging controllers then control the charging processes of the respective charging pairs [EVSE / EV]-1, ..., [EVSE / EV]-n, also taking into account the respective associated PRL power curves by means of a local measurement of the grid frequency f. For example, the primary control power provided via the PRL power curve can be superimposed on a baseline.

[0066] The pooling instance PI aggregates a grid frequency-dependent overall primary control power curve from the individual primary control power curves of the charging pairs [EVSE / EV]-1, ..., [EVSE / EV]-n, e.g., by adding the individual primary control power curves. The pooling instance Pl then reports the value of the overall primary control power curve as a function of the current grid frequency as the (total) primary control power provided.

[0067] To verify the total primary control power actually provided by the pool of charging pairs [EVSE / EV]-1, ...., [EVSE / EV]-n, the performance data can be provided subsequently, if required.

[0068] Fig. Figure 4 shows a possible charging curve P for a charging pair [EVSE / EV]-1, ..., [EVSE / EV]-n, plotted against an electrical power P in kW and a grid frequency f in Hz. ges (f), P_total, for a specific time, for which P ges (f) = P Bas + P PRL (f) with P Basthe value of the baseline at this time and P PRL (f) of the individual PRL power curve. The course of the charging curve P ges (f) corresponds to the shape of the PRL power curve, but is modified by the value P Bas shifted along the P-axis. Is P Bas = 0, P applies ges (f) = P PRL (f).

[0069] The PRL performance curve P PRL (f) is continuous, where the following holds - for f ≤ f PRL,min : P PRL (f) = - P PRL,min with f PRL,min , f_PRL,min, a predefined lower frequency threshold below a target mains frequency f0 and P PRL,min , P_PRL,min, a maximum control power that can be discharged by the electric vehicle EV, where P PRL,min is assumed to be greater than zero. By P PRL (f) = - P PRL,min A value < 0 indicates that, from the perspective of the electric vehicle (EV), primary power energy is being discharged to raise the grid frequency f, which is too low. - for f PRL,min< f < f PRL,max : K PRL (f), K_PRL (f), with f PRL,max , f_PRL,max, a predefined upper frequency threshold above the target mains frequency f0 and K PRL (f) a linear curve segment following the frequency thresholds, - for f ≥ f PRL,max : P PRL (f) = P PRL,max with P PRL,max , P_PRL,max, a maximum control power that can be charged by the electric vehicle EV, which is greater than zero. By P PRL (f) = P PRL,max A value > 0 indicates that, from the perspective of the electric vehicle (EV), primary power energy is being charged to reduce the excessively high grid frequency f.

[0070] Furthermore, K applies here PRL (f0) = 0. In general, the deviations from the target network frequency f0, namely Δf PRL,min = f0 - f PRL,min and Δf PRL,max = f PRL,max - f0 may be the same or different in magnitude. Also, P PRL,min and P PRL,maxThe amounts may be the same or different.

[0071] Since the curve section K PRL (f) corresponds to a linear function with a constant slope, this can also be expressed here as - - s · P PRL,min with s = Δf PRL,min / f PRL,min for f PRL,min < f < f0; - 0 for f = f0; - + s · P PRL,max with s = Δf PRL,max / f PRL,max for f0 < f < f PRL,max can be expressed. The current value P bas Taking the baseline into account, the current value of the charging curve P is calculated as follows: ges - P ges = P bas - P PRL,min for f ≤ f PRL,min ; - P ges = P bas - s · P PRL,min with s = Δf PRL,min / f PRL,min for f PRL,min < f < f0; - P ges = P bas for f = f0; - P ges = P bas + s · P PRL,max with s = Δf PRL,max / f PRL,maxfor f0 < f < f PRL,max - P ges = P bas + P PRL,min for f ≥ f PRL,min .

[0072] Possible values ​​could include, for example, f0 = 50 Hz, f PRL,min = 49.8 Hz, f PRL,max = 50.2 Hz and P PRL,min and P PRL,max = 2 kW can be assumed.

[0073] Fig. Figure 5 shows a plot of electrical power P in kW against a mains frequency f in Hz, a possible result obtained by adding all baselines and the individual PRL power curve P PRL (f) of all participating charging pairs [EVSE / EV]-1, ..., [EVSE / EV]-n. Since the individual PRL power curves P PRL (f) different values ​​for f PRL,min , f PRL,max , P PRL,min and P PRL,max The overall charging curve P can exhibit ges | p(f) is then not constant, but usually linear in a piecewise or polygonal manner, as shown here. It flattens out at least approximately asymptotically towards the values ​​P PRL,min and P PRL,max from which, by means of the pooling instance Pl, the individual PRL performance curves P can be appropriately designed. PRL (f) can be achieved in a targeted manner.

[0074] In particular, P applies bas | p = Σ P bas of the individual charging pairs, P PRL,min | p = Σ P PRL,min of the individual charging pairs, P PRL,max | p = Σ P PRL,max of the individual charging pairs, f PRL,min | p = min {f PRL,min} of the individual loading pairs and f PRL,max | p = max {f PRL,max} of the individual load pairs.

[0075] Fig. Figure 6 shows a possible sequence of events, in particular based on the example in Fig. 3 systems shown.

[0076] In step S1, baselines and charging flexibilities are determined for the charging pairs [EVSE / EV]-1, ..., [EVSE / EV]-n assigned to the pool, consisting of n electric vehicles EV and charging points EVSE. This can be done by the charging pairs [EVSE / EV]-1, ..., [EVSE / EV]-n or their charging controllers, or alternatively, after the baselines and charging flexibilities have been transmitted by the pooling instance Pl.

[0077] In the pooling instance Pl, in step S2, respective grid frequency-dependent PRL power curves are established for the respective charging pairs [EVSE / EV]-1, ..., [EVSE / EV]-n based on the charging flexibilities.

[0078] In step S3, the PRL power curves are transferred from the pooling instance Pl to charging controllers for the respective charging pairs [EVSE / EV]-1, ..., [EVSE / EV]-n. The charging controllers output control signals to the corresponding charging pair [EVSE / EV]-1, ..., [EVSE / EV]-n to control the charging process. In particular, the charging controllers can superimpose or adjust their respective baselines with the control powers resulting from the grid frequency-dependent PRL power curves. The charging controllers can also contain parameters for the reserve for local control of the primary control power.

[0079] In step S4, the pooling instance Pl generates an overall PRL power curve, which corresponds to an aggregation of the PRL power curves for the individual charging pairs [EVSE / EV]-1 to [EVSE / EV]-n.

[0080] In step S5, the maximum primary control reserve resulting from the overall primary control reserve (PCR) power curve is released to an intermediary or marketer, e.g., an energy market aggregator (EMA), for activation. Prior to step S1 (e.g., one day earlier), an offer phase may have taken place, during which the flexibility or available control reserve was offered to a marketer and at least partially accepted. Therefore, a training course can essentially consist of two phases: first, the offer phase, and then the activation phase, which reacts to a call for control reserve.

[0081] If the maximum primary control reserve is accepted by the marketer, in step S6 the charging pairs [EVSE / EV]-1 to [EVSE / EV]-n available for providing the primary control reserve are released by the pooling instance PI for local provision of the primary control reserve and then provide their individual primary control reserve.

[0082] With the release of the provision of the individual primary control powers, in step S7 the pooling instance PI calculates the primary control power provided by the pool from the total PRL power curve and reports it to the responsible instance, e.g. the marketer, who forwards it to the network operator.

[0083] This will continue until the marketer no longer accepts primary control reserve.

[0084] In step S8, it is checked whether an update time interval (e.g., one second) has been reached or whether an event relevant for an update has been registered. If this is not the case ("N"), the overall PRL performance curve is retained; otherwise ("J") it is updated, e.g., by branching to step S1, as shown.

[0085] Of course, the present invention is not limited to the embodiment shown.

[0086] In general, “ein”, “eine”, etc. can be understood to mean singular or plural, especially in the sense of “at least one” or “one or more”, etc., unless this is explicitly excluded, e.g. by the expression “exactly one”, etc.

[0087] A numerical specification can also include exactly the specified number as well as a usual tolerance range, unless this is explicitly excluded. Reference symbol list EM energy meter EMA Energy Market Aggregator EV electric vehicle EVN energy supply network EVSE charging point [EVSE / EV]-i i-th charging pair f mains frequency f0 Target mains frequency f_PRL,max Upper frequency threshold f_PRL,min Lower frequency threshold HEMS Home Energy Management System K_PRL curve segment of primary control power LS property P Electrical power P bas Baseline P_total Single charging curve P_PRL Primary control reserve f_PRL,max Maximum chargeable control power P_PRL,min Maximum dischargeable control power PI Pooling Instance S1-S8 process steps SM Smart Meter t time |p Pool-related size QUOTES INCLUDED IN THE DESCRIPTION

[0000] This list of documents cited by the applicant was automatically generated and is included solely for the reader's convenience. The list is not part of the German patent or utility model application. The DPMA accepts no liability for any errors or omissions. Cited patent literature

[0000] US 10 663 932 B2

[0005] WO 2020 / 120457 A2

[0006] US 2008 / 0052145 A1

[0007] DE 10 2009 050 042 A1

[0008] DE 10 2022 127 911 A1

[0009] DE 10 2017 209 801 A1

[0010] DE 10 2022 129 783 A1

[0011]

Claims

[1] Method for providing ancillary services by means of a pool comprising several electric vehicles (EVs), comprising the steps: - Determining the respective charging flexibilities of the charging pairs ([EVSE / EV]-1 - [EVSE / EV]-n) allocated to the pool of electric vehicles (EV) and charging points (EVSE); - Establishing a mains frequency-dependent PRL power curve (P PRL ) for each charging pair ([EVSE / EV]-1 to [EVSE / EV]-n) based on its respective charging flexibility; - Transferring the PRL performance curves (P PRL ) of the charging pairs ([EVSE / EV]-1 - [EVSE / EV]-n) to associated charging controllers, which are configured to charge the associated electric vehicle (EV) at least depending on a current grid frequency (f) according to its PRL power curve (P PRL ) to control; - Establishing, by the pooling instance (Pl), an overall PRL performance curve (P PRL | p ), which is an aggregation of PRL performance curves (P PRL) individual charging pairs ([EVSE / EV]-1 - [EVSE / EV]-n) corresponds; and - Calculating the control power provided by the electric vehicles (EVs) of the pool based on the overall PRL power curve (P PRL | p ). [2] Method according to claim 1, wherein the individual PRL power curves (P PRL ) are set up locally at the charging pairs ([EVSE / EV]-1 - [EVSE / EV]-n), are reported to the pooling instance (Pl), and the pooling instance (Pl) derives the overall PRL power curve (P) from this. PRL | p ) compiled by aggregation. [3] The method of claim 1, wherein - the charging flexibilities of the charging pairs assigned to the pool ([EVSE / EV]-1 to [EVSE / EV]-n) are reported to the pooling instance (Pl) and - the pooling instance (Pl) from which the individual PRL performance curves (P) PRL ) for each charging pair ([EVSE / EV]-1 - [EVSE / EV]-n) and transmits it to the associated charging controllers. [4] The method of claim 1, wherein - the charging flexibilities of the charging pairs assigned to the pool ([EVSE / EV]-1 - [EVSE / EV]-n) are reported to the pooling instance (Pl), - the pooling instance (Pl) from which the overall PRL performance curve (P) PRL | p ) sets up, - the pooling instance (Pl) from the overall PRL performance curve (P PRL | p ) the individual PRL performance curves (P PRL ) for each charging pair ([EVSE / EV]-1 - [EVSE / EV]-n) by disaggregation and transmits to the associated charging controllers. [5] Method according to any one of the preceding claims, wherein - the charging points are components of local power grids that are connected via an energy meter (SM, EM) to a power supply network (EVN) as the receiver of the control power, - the mains frequency (f) is monitored via the energy meters (SM, EM), - the tracked grid frequency (f) is transmitted to at least one charging controller of the local power grid, by means of which charging of at least one charging pair ([EVSE / EV]-1 - [EVSE / EV]-n) can be controlled and - the charging control system charges at least one of the charging pairs it can control ([EVSE / EV]-1 - [EVSE / EV]-n) using the respective PRL power curve (P PRL ) controls. [6] Method according to one of the preceding claims, wherein a single PRL power curve (P PRL ) for a charging pair ([EVSE / EV]-1 [EVSE / EV]-n) of a particularly continuous function of the requested control power with the properties - for f ≤ f PRL,min : : P PRL (f) = - P PRL,min with f PRL,min a predetermined lower frequency threshold below a target mains frequency (f0) and P PRL,min a maximum control power that can be discharged by the electric vehicle (EV), - for f PRL,min < f < f PRL,max : K PRL(f) with f PRL,max a predetermined upper frequency threshold above the target mains frequency (f0) and K PRL (f) a curve segment that is at least partially linear and increases monotonically with higher network frequencies (f), - for f ≥ f PRL,max : P PRL (f) = P PRL,max with P PRL,max corresponds to the maximum control power that can be charged by the electric vehicle (EV). [7] Method according to one of the preceding claims, wherein the charging controller controls a charging process of the electric vehicle (EV) of the associated charging pair ([EVSE / EV]-1 - [EVSE / EV]-n) based on a charging curve (P ges ) performs an overlay of an associated baseline (P bas ) with the PRL performance curve (P PRL ) corresponds. [8] Method according to any of the preceding claims, wherein the overall PRL power curve (P PRL | p ) is set up such that the overall PRL performance curve (P PRL| p ) when approaching at least one of the frequency thresholds (f PRL,max , f PRL,max ) against the associated predetermined minimum and / or maximum primary control power (P PRL,min , P PRL,max ) flattens out. [9] Method according to one of the preceding claims, wherein when the mains frequency (f) is within a dead range of f0 - f Tmin ≤ f ≤ f0 + f Tmax around the target frequency (f0), from which no primary control power is called upon. [10] Method according to any of the preceding claims, wherein the overall PRL power curve (P PRL | p ) is reorganized at regular intervals. [11] Method according to any of the preceding claims, wherein the overall PRL power curve (P PRL | p ) is reorganized due to an event. [12] Method according to one of the preceding claims, wherein the calculation of the control power is based on the total PRL power curve (P PRL | p ) is carried out using the pooling instance (Pl) and the result of the calculation is reported or transmitted to at least one corresponding market participant (EMA, EVN). [13] Method according to any one of claims 1 to 11, wherein the calculation of the control power is based on the total PRL power curve (P PRL | p ) is carried out in such a way that the overall PRL performance curve (P) established by means of the pooling instance (Pl) PRL | p ) reported to at least one relevant market participant (EMA, EVN) and the at least one relevant market participant (EMA, EVN) calculates the control power from this. [14] Computer program product comprising code which, when executed on a data processing device, performs the method according to any of the preceding claims. [15] Control system comprising several charging pairs ([EVSE / EV]-1 to [EVSE / EV]-n) of respective electric vehicles (EV) and charging points (EVSE), the charging processes of which can be controlled by means of a charging controller, and a central pooling instance (Pl) coupled to the respective charging controllers in terms of data technology, wherein the control system is configured to carry out the method according to one of claims 1 to 13.

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