PL248511B1 - Electric vehicle charging station and autonomous system and method for adapting the operation of electric vehicle charging stations to the conditions prevailing in the power grid - Google Patents

Abstract

The subject of the application is a charging station (CS) for electric vehicles and an autonomous system (100) and a method for adapting the operation of a charging station (CS) for electric vehicles to the conditions prevailing in the power grid, in particular with particular emphasis on the characteristics of the lighting network. The charging station (CS) has at least one autonomous control system (ACS), which system comprises a communication module, a charging control module, a database module and a prediction module cooperating with each other, wherein the prediction module intended to detect and predict loads and disturbances in the network circuit (NC) on the basis of historical data and/or generated statistical models and/or a rule-based system is connected to a communication module carrying out data transmission between devices/receivers connected to the network circuit (NC), wherein the communication module is coupled to a database module intended to store parameters of the operating state of said devices/receivers connected to the network circuit (NC) and to a charging control module dynamically adjusting the characteristics of the charging current of the electric vehicle in relation to the parameters of the operating state of the devices/receivers connected to the network circuit (NC).

Description

FIELD OF INVENTION

The subject of the invention is an electric vehicle charging station and an autonomous system and method for adapting the operation of an electric vehicle charging station to the conditions prevailing in the power grid, in particular with particular emphasis on the characteristics of the lighting network, allowing for the prediction of its operation and control of the operating parameters of the devices operating therein, with particular emphasis on the maximum transmission power of the circuit in which they operate.

This invention pertains to the broadly understood field of electromobility, which addresses both the technical and operational aspects of electric vehicles, technologies, and the key aspect of electric vehicle charging infrastructure. The present solution therefore addresses both the scope of mechatronics and combines mechanical, electrical, and computer engineering, including IT systems, to design and manufacture a modern charging station with an autonomous system and method for adapting the charging station's operation to the conditions prevailing in the power grid, with particular emphasis on the characteristics of the lighting network.

The present solution essentially involves a control system that can be installed in the charging station and the charging station itself, which adjusts operating parameters, including the maximum charging current of the electric vehicle, to the conditions prevailing in the power grid. Additionally, the solution according to the invention provides control of external devices integrated with the power grid, with particular attention to the characteristics of the lighting network. For example, the use of lighting fixtures equipped with appropriate devices allows, for example, to reduce electricity consumption, i.e., the power consumed, and thus enables increased charging power of the electric vehicle via the charging station according to the invention, while simultaneously increasing the number of charging points.

Generally, external components in the control system are controlled by switching them on/off or by setting the device's operating mode, for example, by reducing the luminous flux and power of a lighting fixture. This allows, in the event of grid overload (e.g., when the connection power limit is reached) or other problems are detected (e.g., when reactive power is identified), unnecessary devices to be disconnected from the grid or devices to be connected to the grid to improve its quality. An example of this would be the use of a reactive power compensator in the case of reactive power problems.

Furthermore, the invention encompasses monitoring of external and internal parameters using a grid monitoring device included in the autonomous system according to the invention, which is designed to monitor current parameters of the power grid. Furthermore, the invention encompasses a prediction module included in the charging station according to the invention, which is designed to detect and predict load and disturbances in the power grid.

BACKGROUND OF THE INVENTION

Vehicles with alternative drives or using alternative fuels are a crucial step towards sustainable mobility. With the development of electromobility, particularly the use of electric vehicles, there is a growing demand for the charging infrastructure necessary to support this type of vehicle, including charging stations. Despite the growing number of public charging points, their number is still insufficient. As energy demand continues to grow rapidly, and will continue to do so in the future, power shortages have become a serious problem. Furthermore, the problem concerns not only energy generation but also the limitations of existing energy infrastructures and the challenges associated with utilizing them optimally without costly investments in their reconstruction.

The significant development of electromobility is just beginning and will continue for the next dozen or so years. It's worth noting, however, that the profitability of using vehicles with this type of drive is largely dependent on the availability of appropriate charging infrastructure, including charging stations. This factor influences the convenience of traveling with an electric vehicle, which in turn is of significant importance for the dynamics of the sector's further development. Environmental regulations in many countries, including the European Union, could accelerate the construction of the required infrastructure by requiring developers and building owners to install charging stations.

From the perspective of the development of electromobility in Poland, the expansion of publicly accessible charging infrastructure is essential. While residents of single-family homes can easily recharge their electric vehicle batteries from a standard outlet, residents of apartment buildings without private parking spaces typically lack this option, so providing them with convenient access to public charging stations is a priority. In the future, the number of charging points should reach hundreds of thousands, ensuring that electric vehicles can be charged from the power grid virtually anywhere, including the lighting network, which currently poses numerous technical challenges.

One of the main problems encountered in lighting infrastructure is high inrush current, which in some cases can be several dozen times greater than the nominal current. Increased current consumption in sodium-vapor luminaires can last from several to several minutes. In such a case, when the charging station according to the invention is connected in the circuit, the lighting circuit is switched on sequentially to turn on the lighting. Additionally, other loads connected to the network, in this case the lighting infrastructure (e.g., luminous advertising such as billboards, etc.), can be switched off during the switch-on process, or the charging parameters using the charging station according to the invention are reduced, ensuring that the permissible connection power is not exceeded.

Charging station parameters (e.g., charging current) may be limited to some extent by the luminous flux intensity of the luminaires if the current drawn is close to the maximum current limit of the mains circuit. According to current standards in the lighting industry (including CEN EN 13201, CIE 115, ANSEIES RP-8, and others), luminous intensity is influenced by dynamic parameters that change over time. Examples of such dynamic parameters include: the level of ambient light illuminating the streets, information about parked cars, vehicle traffic volume, pedestrian traffic volume, weather conditions, etc. By analyzing these dynamic parameters, we can adjust the luminous flux intensity of the luminaires based on them, which in turn allows us to reduce or increase the current consumption of the luminaires and thus increase or decrease the electric vehicle charging current for individual charging stations according to the invention. For example, if a road is illuminated in accordance with the CEN EN 13201-2:2015 lighting standard and has a defined lighting class of M2, meaning it should be illuminated with a minimum light level of 1.5 cd/ ^m2 , a change in traffic (below 65% of the maximum possible traffic on a multi-lane road according to CEN/TR 13201-1:2014) to a lower level allows for a change in the lighting class from M2 to M3, for which the minimum luminance level is specified at 1 cd/ ^m2 . Therefore, it is possible to reduce the flux and generate savings of around 30%. Further reduction in traffic (below 35% of the maximum vehicle traffic level on the road) generates further savings of up to 50%. In light of the above, there is potential to reduce power consumption and increase the charging current of the charging station according to the invention.

Charging stations and charging points that are part of the charging infrastructure for road public transport should meet technical and operational requirements ensuring their safe use, including the safe operation of electricity networks and access to charging stations.

DESCRIPTION OF THE STATE OF THE ART

The state of the art offers numerous charging stations, systems, and methods for charging electric vehicles using charging stations connected to the power grid. However, most of these solutions fail to address the issues associated with power grid overload, particularly the characteristics of the lighting network due to the high electricity demand associated with connecting a large number of electric vehicles to the grid for simultaneous charging.

A charging station, also commonly referred to as a car charger, is an electrical device used to charge batteries and other electric vehicles equipped with a battery, where the electricity to the charging station is supplied from an external power grid. A charging station can operate on single-phase or multi-phase mains circuits. A mains circuit is defined as one of the aforementioned mains circuit types (for example, single-, two-, or three-phase). An electric vehicle, in turn, includes both passenger cars and trucks, but can also include two-wheelers such as electric bicycles, motorcycles, electric scooters, etc.

The prior art discloses U.S. Patent Application No. US20190092182A1 entitled "A System for Efficient Charging of Distributed Vehicle Batteries," which describes a system for efficiently charging distributed vehicle batteries, wherein each vehicle battery is capable of being connected to a battery charger connected to the power grid via an electromechanical switch of a switching battery controller communicating with a system control center, wherein the control center is adapted to provide a switching schedule for the electromechanical switch of the respective switching battery controller based on power consumption forecasts calculated by said control center for the switching battery controllers in response to power measurements reported by the switching battery controllers and based on a power consumption schedule and/or a power production schedule of the energy resources of said power grid. The prior art invention, however, does not solve the problem of real-time power grid overload; it primarily focuses on the problem of failure to provide energy for charging and to activate additional resources to provide it. Additionally, schedule-based control completely eliminates its use in situations where the circuit is connected to receivers with a power exceeding the power of the mains, which operate dynamically, reacting to current problems.

Also known in the art is U.S. patent application No. US20210101502A1 titled "Apparatus and method for predicting failure of electric car charger," which describes an apparatus and method for predicting failure of electric car chargers. This solution uses the environment around the electric car charger as input, using artificial intelligence technology. A method of operating an electronic device that predicts failure of an electric car charger may include: obtaining sensor data measured by a sensor; obtaining information about an area showing the area of a first electric car charger; obtaining weather information at the time the sensor data in the area was measured; creating a failure prediction model based on an artificial neural network; creating training data; training a failure prediction model based on the training data; creating input data; obtaining an output about the operating state of the first electric car charger; and predicting the possibility of failure of the first electric car charger based on the output. This prior art invention is undoubtedly a useful solution for predicting device lifespan. However, the prior art invention itself does not analyze aspects related to load and negative phenomena (such as reactive power) in the network, which do not affect device lifespan. Therefore, the present solution is not applicable in situations where the number of receivers increases, exceeding the network's transmission capacity.

Additionally, the prior art includes Chinese patent application No. CN110271436A1 titled "Electric vehicle reservation charging control method and system," which presents a method and system for controlling electric vehicle charging reservations. The present invention describes a charging station that, through communication with an electric vehicle, can estimate the charging time of an electric vehicle and also incorporates a reservation system. However, the present invention addresses micro, not macro, scales. Connecting a large number of charging stations to the power grid can lead to grid overload issues and control issues to ensure optimal power consumption. The solution described here does not analyze the collective impact on the power grid of connecting a large number of charging stations.

Chinese patent application No. CN105337324A1, titled "Intelligent charging strategy for controlling charging time of an electric car," is also known, which presents an intelligent charging strategy for an electric vehicle when the electric vehicle is connected to the electricity distribution network. A control device is installed on the vehicle-mounted electric vehicle charger and is used to obtain information about the electric vehicle's charging and control the start/stop of charging. The electric vehicle charger is connected to the power grid via a socket. The charging management system can obtain information about the electric vehicle's charging and control the electric vehicle's charging time via the control device. It can also obtain information about the power grid load and other information related to the system's operation while connected to the power grid. The charging management system performs an optimization operation that not only verifies the usage time but also adjusts its parameters to extend the service life of the distribution transformer. In particular, it optimizes the start/stop of electric vehicle charging, thereby reducing the loss of service life of the distribution transformer and user costs. However, the solution in question, like the solution described above, also does not analyze the operation of other devices in the power grid, nor integration with other receivers such as street lighting fixtures.

Another Chinese patent application, No. CN106655421A1, titled "Multifunctional car charger," is also known in the art. It discloses a multifunctional charger containing a set of filters and various charging units that draw energy for charging from a photovoltaic panel and, when not in use, return any excess energy to the power grid. However, this solution does not solve problems related to changes in the operating characteristics of the power grid, such as spikes in current consumption, such as those observed in lighting networks when switching on an entire lighting circuit.

In the case of lighting networks to which a charging station is connected, prior art solutions are known that integrate the charging station with a pole and other components placed on it, such as a photovoltaic panel. An example of such a prior art solution is Chinese patent application no. CN113154321A1 titled "Multifunctional street lamp system," which discloses a multifunctional street lamp and vehicle charger system mounted on a street lamp. This system allows the street lamp to perform multiple functions while efficiently utilizing the street lamp's space. However, this solution focuses on supplying power to the circuit via the PV panel, failing to address the issues that may arise when a group of charging stations are connected to the lighting network. Furthermore, it does not address the practical issue of switching on lighting or operating multiple charging stations in a lighting network, where the combined current can exceed the permissible parameters of the lighting network.

Finally, Chinese patent application No. CN109560577A, titled "Control method and system for alternating current - direct current hybrid distributed renewable energy system," is also known, presenting a method and control system for a hybrid distributed renewable energy system combining AC and DC. This solution describes the charging process and method, including mixed AC and DC generators, along with electric vehicle batteries that can generate energy for the grid using V2G technologies. The solution essentially focuses on a system that generates energy from renewable energy sources and delivers it to the charging station, introducing a micro-capacitance sensor management system (MCSMS) and a micro-capacitance sensor (MCS). The prior art describes energy balancing, not the balancing of power consumption and quality parameters, as in the solution according to the claimed invention.

Chinese patent application No. CN110979084A1, titled "Charging control method, system, and device for electric vehicle charging station," presents a method, system, and device for controlling charging at an electric vehicle charging station. The method involves obtaining historical daily loads of the transformer and the station, then using these data to determine forecasts and daily load plans for the station. Charging power is controlled according to the plan, while simultaneously monitoring the actual total transformer consumption. When consumption exceeds the set limit, the system reduces the load to a second threshold (a pre-defined plan). Essentially, the presented prior art solution aims to maintain the transformer's operation within its rated power and enable the utilization of its reserve capacity. The architecture includes modules for load data acquisition, forecasting, active control, load evaluation, and passive control.

However, the present solution presents a different control method, based solely on transformer and station load statistics, rather than real-time demands or external factors. The content also suggests that the limitation is common to multiple charging points, which is different from the invention, where each charging point can request a different charging power (depending on the vehicle). Furthermore, it does not address issues related to the quality of network device operation.

Furthermore, the prior art also includes international application no. WO2013138781A1 titled "An electric vehicle charging station dynamically responding to power limit messages based on a recent history of power provided," which presents a method for controlling a single charging station based on a percentage limit on charging power. The limit is based on samples measured by the system and/or instructions transmitted from an external system. The solution essentially focuses on a method for limiting the charging station's operating power percentage based on messages/instructions transmitted based on a sample history of information solely regarding the value of power consumed. The prior art presents a method in which data is collected by a sensor and controlled from a single point, an external unit, unlike the solution according to the invention, which operates in a distributed manner (each charging station can assume management functions).

The state of the art in charging stations and electric vehicle charging systems and methods indicates a lack of solutions that adapt charging station operation to the conditions prevailing in the power grid. The above-described prior art solutions, and more broadly, solutions for electric vehicle charging, significantly, focus on selected elements of the electric vehicle charging infrastructure and do not address a holistic approach. The vast majority of prior art solutions fail to address aspects related to grid congestion due to high simultaneous energy demand, or the optimal utilization of available power in the power grid, particularly with particular emphasis on the characteristics of the lighting network. Therefore, the state of the art lacks a complementary solution that adapts charging station operation to the conditions prevailing in the power grid.

It should also be emphasized that the claimed solution according to the invention is a more universal solution compared to the state of the art, largely based on the available infrastructure, while maintaining a relatively low price compared to solutions available on the market.

THE ESSENCE OF THE INVENTION

The subject of this invention is the development of a completely new solution in the form of a charging station and an autonomous system and method for adapting the operation of the charging station to the conditions prevailing in the power grid, in particular with particular emphasis on the characteristics of the lighting network, which allows for the prediction of its operation and the control of the operating parameters of devices/receivers operating in it in real time, and as a result translates into ensuring appropriate availability of the charging service with a relatively shortened charging time and at the same time the safety of the network circuit to which the charging stations are connected.

The present solution according to the invention is also intended to provide such features and functionalities as:

• Protection of the circuit in which charging stations and other devices operate against overloading and exceeding the permissible power of the circuit connection;

• Optimal use of existing energy network resources, thereby minimizing the need for investments in the installation of new electric vehicle charging stations;

• Dynamic adjustment of the electric vehicle charging characteristics to the conditions in the power grid;

• Increasing the capacity/number of charging stations, thus ensuring greater access to this service for users of electric vehicles;

• Achieving synergy related to the charging of electric vehicles and the operation of other devices/receivers in one circuit, with particular emphasis on the characteristics of the lighting network;

• Using the savings that can be generated by modern controlled lighting infrastructure to increase the charging power of a charging station operating in the same circuit.

In order to achieve the above objectives, according to one aspect of the present invention, the present invention provides an electric vehicle charging station adapting its operation to the conditions prevailing in the power grid, in particular the lighting grid, wherein the charging station comprises an electric vehicle charging system with internal electronics in the form of at least one central processing unit operatively connected to a communication unit, a memory, and an input unit and an output unit providing an interface with a user, characterized in that it has at least one autonomous control system ACS, which system comprises a communication module 10, a charging control module 20, a database module 30 and a prediction module 40 cooperating with each other. The aforementioned prediction module 40 intended for detecting and predicting loads and disturbances in the NC network circuit based on historical data and/or generated statistical models and/or a rule-based system is connected to a communication module 10 carrying out data transmission between devices/receivers connected to the NC network circuit, wherein the communication module 10 is coupled to a database module 30 intended for storing parameters of the operating state of the aforementioned devices/receivers connected to the NC network circuit and to a charging control module 20 dynamically adjusting the characteristics of the charging current of the electric vehicle EV in relation to the parameters of the operating state of the devices/receivers connected to the NC network circuit.

Preferably, the said autonomous ACS control system is an independent component integrated outside the element built into the structure of the CS charging station.

According to a further aspect of the present invention, the present invention provides an autonomous system 100 for adapting the operation of an electric vehicle charging station to the conditions prevailing in the power grid, in particular a lighting network forming a plurality of common operating areas comprising a single-phase or multi-phase network circuit to which devices/receivers with different power consumption characteristics are connected, including devices/receivers equipped with controllers, characterized in that it comprises:

- at least one CS charging station with an autonomous ACS control system, connected to the NC network circuit;

- a network analyzer NA intended for monitoring and transmitting in real time dynamic parameters and/or parameters of the operating status of devices/receivers connected to the NC network circuit, wherein the network analyzer NA communicates with one of the CS charging stations equipped with at least one autonomous control system ACS, which becomes the master autonomous control system MACS in relation to the other CS charging stations, which then act as slave autonomous control systems SACS in the NC network circuit, wherein the master autonomous control system MACS, based on the said dynamic parameters and/or parameters of the operating status of devices/receivers connected to the NC network circuit, each time dynamically determines the target characteristic of the charging current of the electric vehicle EV connected to the CS charging station, taking into account the predetermined limit value of the maximum operating power of the NC network circuit.

Advantageously, the said network analyzer NA comprises a cooperating integration module with an electricity consumption meter of the circuit and/or a measurement module and a communication module, wherein the measurement module is a set of toroidal transformers intended to determine the current consumption in the power network for individual devices/receivers connected to the network circuit NC.

Preferably, the autonomous system 100 additionally has a central management system CMS comprising a cooperating communication module, an API module, a database module, a prediction module and a user interface module, intended to integrate information from devices/receivers connected to the NC network circuit via the NA network analyzer and communicating them via a communication medium.

Preferably, said communication medium is a Mesh radio network and/or WiFi and/or GSM or a serial bus and/or PLC.

According to yet a further aspect of the present invention, the present invention provides an autonomous method 200 for adapting the operation of an electric vehicle charging station to the conditions prevailing in a power grid, in particular a lighting grid forming a plurality of common operating areas, comprising connecting an electric vehicle to the charging station in a single-phase or multi-phase network circuit, wherein, before starting to charge the electric vehicle via the charging station, a charging current reservation request signal is transmitted, characterized in that:

upon reserving the charging current from among the ACS autonomous control systems located in the NC network circuit, a deterministic procedure for selecting one superior MACS autonomous control system is carried out autonomously and without the participation of the master system in relation to the remaining ACS autonomous control systems, which then act as slave SACS autonomous control systems, the selection being made on the basis of local and real-time measured parameters/signals, then to the superior MACS autonomous control system during the charging of the electric vehicle EV via the NA network analyzer and/or directly via devices/receivers connected to the NC network circuit, periodic signals on dynamic parameters and/or parameters of the operating status of devices/receivers connected to the NC network circuit are transmitted on request or in a cyclical manner, including at least information on the link operation quality parameters such as: phase currents, phase shift angle (φ) between current and voltage, harmonic distortions, phase occupancy and load states, whereas on the basis of the transmitted parameters via the superior autonomous control system MACS, the charging level is monitored in real time and the charging current characteristics are dynamically adjusted at least in terms of the charging current, harmonic distortions, phase shift angle (φ) between the current and voltage for each CS charging station of an electric vehicle EV, taking into account each time the predetermined limit value of the maximum operating power of the NC network circuit and/or via the superior autonomous control system MACS, the operation of devices/receivers operating in the NC network circuit is controlled in order to maintain the qualitative and quantitative parameters of the link and a watchdog signal is sent to the other autonomous control systems ACS in the NC network circuit. in the absence of a cyclic periodic signal, the operating parameters of the CS charging station are minimized via the autonomous control system ACS to a predetermined level of the minimum charging current defined in the CS charging station or the CS charging station is stopped to avoid overloading the NC network circuit and, in parallel, the re-election of the superior autonomous control system MACS is initiated.

Preferably, said charging current reservation request signal is transmitted to the superior autonomous control system MACS via the central management system CMS.

Preferably, the mentioned measurement of the operating status parameters of devices/receivers connected to the NC network circuit is performed using sets of toroidal transformers constituting the measuring module of the NA network analyzer, which induce voltage at the ends of their windings as a result of the influence of the magnetic field induced by the current flowing through the NC network circuit.

Preferably, the said dynamic parameters are determined on the basis of the level of astral light illuminating the streets and/or information about parked cars and/or vehicle traffic intensity and/or pedestrian traffic intensity and/or weather conditions occurring during the operation of the NC network circuit, wherein the determined dynamic parameters are used to regulate the operation of devices/receivers connected to the NC network circuit by increasing or decreasing the current consumption in the NC network circuit.

Advantageously, the said watchdog signal includes information on the current power available for use in the NC network circuit, by means of which the charging power of the CS charging stations operating under the control of the autonomous ACS control systems is increased and/or additional devices/receivers are connected to the NC network circuit, taking into account each time the predetermined limit value of the maximum operating power of the NC network circuit.

The envisaged solution according to the aspects proposed above provides an appropriate electric vehicle charging station and an autonomous system and method for adapting the operation of the electric vehicle charging station to the conditions prevailing in the power grid, in particular with particular emphasis on the characteristics of the lighting network, which enables reliable operation of the network infrastructure during network overload, using the designed elements and systems intended for monitoring, control and prediction according to the invention.

It's important to emphasize that lighting networks experience high inrush currents when luminaires are switched on, often several or even dozens of times greater than the nominal current. In this case, if the network includes operating charging stations, network overload and outages may occur. To counteract network overloads and outages, the solution according to the invention provides the ability to manage the switching of lighting fixtures, i.e., lighting points, thus reducing the aforementioned risk of network overload and/or limiting current consumption at charging stations.

Furthermore, it should be emphasized that the aforementioned aspect, i.e., reducing the luminous flux generated by luminaires, can result in reactive power and a decrease in grid performance, as well as the possibility of additional fees charged by electricity distributors. In the case of LED luminaires, it is quite common to reduce the nominal luminous flux of a luminaire to reduce the power consumed and, consequently, the fees charged by electricity distributors. However, this can have a negative effect. Reducing the luminous flux intensity causes reactive power. Depending on the type of luminaire, this effect can be visible with a reduction of the luminous flux by a few percent or by several dozen percent. Reactive power increases voltage drops in supply lines and transformers, causing greater active energy losses in transformers, power lines, and load circuits. This is a negative factor, and therefore, electricity distributors strive to reduce it. However, the problem is complex, as it depends on the type of network receiver. For example, in the case of sodium-vapor fixtures, we are dealing with inductive reactive power, while in the case of charging stations, we are dealing primarily with capacitive reactive power. Furthermore, we are dealing with temporal changes in its value. Dynamic management of this process is complex.

Additionally, for example, if reactive power occurs, if the system includes compensators with known compensation coefficients, they can be incorporated into the circuit (in sufficient quantity to compensate for the negative factors). In another embodiment, a change in the lighting parameters of a lighting fixture occurs, which does not generate reactive power by increasing the intensity of the generated light, or, on the contrary, increases the level of its generation in a manner opposite to that present in the network (for example, reactive power generated by sodium-vapor fixtures is inductive and can be compensated by LED fixtures, which generate capacitive reactive power). Furthermore, the lighting area is an excellent example of a network infrastructure with limited parameters that already exists and can be used for other purposes, provided the quality parameters of the network are maintained. This allows the installation of charging stations without the need to incur the costs associated with building your own electric vehicle charging infrastructure.

The advantage of the claimed solution is that the invention enables the ability to increase the availability of charging points, i.e., the number of charging stations that dynamically adjust their operating parameters (changing over time) to the prevailing conditions in the power grid, particularly in lighting infrastructure, which is characterized by highly dynamic changes in power consumption. Power balancing between charging stations and other devices/receivers connected to the network circuit is implemented to maximize the benefit of using the charging station (i.e., charging time and availability of electric vehicle charging), including, above all, the distribution of energy between charging stations. Furthermore, the claimed solution provides mass access to charging services while simultaneously utilizing existing network infrastructure, which is sometimes limited, especially when there is high demand for charging space.

Furthermore, an undoubted advantage of the present solution is the ability to use existing circuits to build a charging network, whose power may not be sufficient to ensure full operation of the charging station due to other installed and connected devices/receivers. Additional integration with lighting components and reactive power compensators (via control elements) provides benefits in the form of improved network quality by regulating network performance and mitigating negative factors related to system reactive power. Essentially, this allows for the generation of lighting savings by controlling luminaires and the ability to utilize the saved power in charging stations with an autonomous control system according to the invention, while ensuring that the limit parameters related to the circuit's operating power are not exceeded.

In light of the above, the present solution according to the invention, based on the elements and systems intended for monitoring, control and prediction, taking into account, among others, the prediction module (as well as statistical models, or in the simplest case, the schedule for switching on devices/receivers available in the network) and the transmitted information about the entire network, is able to take actions related to limiting the operating power of the charging station or switching off and on additional devices/receivers.

A drawback of the claimed solution is the risk of increased charging time (e.g., when all charging points are operational). However, it should be emphasized that this approach is intended for use of charging stations during periods of non-use of electric vehicles, where time is not a significant factor for the end user, and the key is to ensure access and reduce the cost of such a service, which involves charging an electric vehicle at lower energy consumption costs.

BRIEF DESCRIPTION OF THE DRAWINGS

The subject of the invention is shown in an embodiment with reference to the attached drawings, in which:

FIG. 1 shows an autonomous system that adapts the operation of an electric vehicle charging station to the conditions prevailing in the power grid according to one embodiment of the invention;

FIG. 2A-2B shows a diagram of the structure of an autonomous control system for an electric vehicle charging station that adapts its operation to the conditions prevailing in the power grid according to the invention;

FIG. 3 shows a scenario for charging electric vehicles using a method for adapting the operation of a charging station to power grid conditions according to one embodiment of the invention.

DETAILED DESCRIPTION OF THE INVENTION

The present invention will now be described in detail with reference to the accompanying Figures and embodiments. The present invention is not limited to the specific embodiments described herein.

In the presented embodiment, FIG. 1 illustrates an autonomous system 100 that adapts the operation of the EV charging station CS to the conditions prevailing in the power grid. In the example embodiment, the power grid is a lighting network, which is a multi-phase NC network circuit powered from a PP supply point. For the present embodiment, the NC network circuit is a single-phase NC network circuit, in which, for simplicity, a number of common operating areas (COAs) located in the lighting infrastructure can be specified, in which the CS charging stations are integrated with a lighting pole and other devices/receivers connected to the circuit, within which they cooperate to share electrical energy.

In principle, the NC network circuit has lighting poles connected to the circuit, equipped with optional lighting fixtures controlled by LC lighting controllers, wherein CS charging stations for electric vehicles (EV) are connected to the lighting poles, comprising both standard stations of any manufacturer and CS charging stations for electric vehicles (EV) with an autonomous control system (ACS) according to the invention, which system will be described in more detail below with reference to FIGS. 2A-2B. Furthermore, the NC network circuit has a network analyzer (NA) and a central management system (CMS) connected to its structure, as well as power receivers controlled by external controllers (EC) or power receivers with a known power consumption characteristic (CPC).

In the presented embodiment, the NA network analyzer connected to the NC network circuit is designed to monitor the status of the NC network circuit to provide information on the operating parameters of devices/receivers connected to the NC network circuit. The NA network analyzer consists of the following components: an integration module with the circuit's electricity consumption meter, a measurement module, and a communication module, which work together. The integration module with the circuit's electricity consumption meter integrates with electricity meters using an available link. In the example embodiment, integration can be achieved using the RS-485/232/Modbus interface currently available in energy meters. This module is optional, and if the measurement module is installed in the system, it may not be installed in the NA network analyzer (and vice versa, the measurement module may not be installed in the NA network analyzer if the integration module with the circuit's electricity consumption meter is installed). The measurement module measures parameters, particularly the NC network circuit currents and reactive power (i.e., acting as a meter). In an embodiment, the NC network circuit current measurement is performed using toroidal transformers, which induce a voltage at the ends of their windings due to the magnetic field induced by the current flowing through the NC network circuit. Both the measurement module and the integration module with the circuit's electricity consumption meter provide information about the current operating parameters of devices/receivers connected to the NC network circuit via a communication module, which is responsible for broadcasting this information to the autonomous control systems (ACS) and, in this embodiment, also to the central management system (CMS) according to one embodiment of the invention. In this embodiment, the autonomous control systems (ACS) are both integrated with the CS charging station and located outside the CS charging station.

The minimum set of broadcast signals in this case is: a request to send the current status of the device/receiver. This request may be cyclical, defining the intervals at which a message/signal regarding the device/receiver's operating status in the NC network circuit is to be sent, and to which devices in the NC network circuit. Furthermore, this request may be a request to send information about the current status of the device/receiver, or when one of the dynamic parameters changes, it may also remove the previously defined cyclicity of sending. In the implemented embodiment, the dynamic parameters include vehicle traffic intensity, pedestrian traffic intensity, and weather conditions (in this case, rain and snowfall), which affect the operation of the devices/receivers. For example, the intensity of luminous flux in a lighting fixture, and therefore the energy consumption of devices connected to the NC network circuit, depends on the intensity of vehicular traffic. If the traffic intensity decreases, the luminous intensity level of the lighting fixture is reduced, thus increasing the possibility of increasing the operating power of other devices/receivers operating in the NC network circuit, in this case the charging station according to the invention.

In one embodiment, the aforementioned CMS central management system can be an optional system that integrates data from several independent NC network circuits and allows an external user to monitor the operation of all NC network circuit elements. Regardless, the CMS central management system includes a communication module, an API module, a database module, a prediction module, and a user interface module, all of which work together. The communication module is responsible for communicating with the elements operating within the NC network circuit. The minimum set of signals in this case is: a request to send the status of an NC network circuit element (for each type of element, i.e. NA network analyzer, LC lighting controller, ACS autonomous control system, regardless of whether it is built into the structure of the CS charging station or not), retrieving information from the NC network circuit element about its status (in the case of initiating cyclic signals) sent to the LC lighting controllers: switching on a lighting fixture, switching off a lighting fixture, reducing the luminous intensity level of a lighting fixture, sending a new lighting fixture operation schedule, handling signals implemented in the ACS autonomous control system.

Furthermore, the CMS central management system implements a set of API commands through an API module. The API module is an independent module that implements a high-level set of commands that can be used by external systems to provide information about the operating environment of NC network circuits and sends requests to change the state of NC network circuit elements. An example of a module implementation could be a service based on REST services. Information about the circuit's operating environment is understood to mean any dynamic parameters defined above, which can be processed by the prediction module located in the CMS central management system and the ACS autonomous control system. Information about the NC network circuit's operating environment, as well as information about the operating parameters of the NC network circuit and its elements, is transferred and stored in the database module. This module collects historical data. The database module stores a complete history of the operation of all NC network circuit elements. Data from the database module can be used to create statistical models of the NC network circuits' operation and later transmit them to the ACS autonomous control system. A typical prediction model might take the form of a schedule for switching on devices/receivers operating in a NC network circuit, a rule-based system, or neural network parameters/models. The prediction module, in turn, is a component of the system that utilizes the created models. Examples of such implementations include various rule-based systems or more advanced prediction systems based on artificial intelligence (graph grammars, neural networks). The role of the prediction module is to implement control at a higher level than that of a standalone ACS control system. It has access to the operating status of many different NC network circuits. The final element is the user interface module. This module allows reading parameters stored in the database and executing any function on the monitored NC network circuits. The user can perform any operation to change the operating status.

Another element of the NC network circuit, the aforementioned LC lighting controller, is integrated with the lighting pole's luminaire and is designed to monitor and change its operating parameters. The LC lighting controller consists of the following components: a communication module, a control module, and a luminaire integration module, which all work together. This communication module is also responsible for communicating with the remaining NC network circuit components, including the central management system (CMS). This module transmits periodic signals about the device's operation and receives signals to control its operation. The minimum set of control signals includes: switching the luminaire on, switching the luminaire off, reducing the luminaire's luminous intensity, adopting a new device operating schedule (i.e., the luminaire's operating characteristics and luminous flux intensity as a function of time, in the example embodiment, depending on vehicle traffic volume, pedestrian traffic volume, and current weather conditions), and a request to send the current device operating status. As previously defined, the request to send the current device operating status can be cyclical, defining the intervals at which a message/signal regarding the device's operating status in the NC network circuit should be sent, and to which devices in the NC network circuit. The transmitted signals are processed by the control module. This module implements the logic associated with each signal and is responsible for transmitting signals to the luminaire. The control module may be a microprocessor that stores the device's operating characteristics (e.g., the luminaire's switching schedule) and the current operating status in its memory. This module communicates directly with the luminaire integration module. The luminaire integration module is responsible for direct communication with the luminaire (i.e., its controller/power supply). The physical luminaire is controlled via a dedicated interface. An example of such an implementation is control via a DALI or 1-10V interface. This module not only executes the control module's commands but also retrieves operating parameters provided by the luminaire (controller/power supply). These parameters are periodically transmitted to the communication module, which sends them on request or, as in the example embodiment, cyclically to the autonomous ACS control system. The lighting fixture integration module can be expanded with sensors allowing for verification of the lighting fixture's operating current, generated reactive power, etc. These parameters can be transmitted via the power supply connector or independently measured by a dedicated circuit connected in series before the lighting fixture's power supply circuit.

In the example embodiment, communication between devices connected to the NC network circuit generally takes place via a mesh network, but can also occur via a serial bus, Wi-Fi, PLC, or other communication medium. In the example embodiment, communication can be dedicated to a specific device or based on broadcasting a message to all controllers and devices operating in the NC network circuit. Each element of the NC network circuit contains a communication module. The communication module is responsible for transmitting signals between the NC network circuit elements. Examples of communication mediums include a radio network (including mesh and Wi-Fi networks), a GSM network, or the PLC standard (communication via electronic wires). Depending on the communication medium used, signals in the communication module can take on the role of signals with a specific structure or commands implemented at a higher communication layer (an example would be the REST API interface created on the HTTP layer, which is implemented on the TCP layer, which in turn is implemented on the Ethernet layer).

Devices connected to the NC network circuit can also communicate with the central management system (CMS), as mentioned above. The central management system (CMS) collects information from various devices/receivers in the NC network circuit, stores data, and transmits messages to control elements (in the example embodiment: a CS charging station, an LC lighting controller, and an external EC controller). The external EC controller is an example of a controller that minimally implements on/off functions. In the example embodiment, the external EC controller consists of a communication module implementing two signals: on/off. This module will be responsible for communication and for closing or opening the contacts that connect the external device to the NC network circuit. It should be noted that communication with the central management system (CMS) is optional and redundant to communication with the current control element that takes over control in the NC network circuit. The control element taking over the control in the NC network circuit in the embodiment example is one of the autonomous ACS control systems according to the invention integrated with the CS charging station.

In the embodiment shown in FIGS. 2A-2B, two variants of a diagram of the structure of a CS charging station according to the invention are illustrated, which is connected to an autonomous system 100 that adapts the operation of the CS charging station for electric vehicles (EVs) to the conditions prevailing in the power grid. In the first variant, FIG. 2A illustrates a diagram in which the EV charging system 50 directly cooperates with the EV charging control module 20, which is a component of the ACS autonomous control system according to the invention. In the second variant, FIG. 2B illustrates a diagram in which the EV charging system 50 cooperates with the control module 20, which is a component of the ACS autonomous control system according to the invention, via the EV charging control module 60. Regardless of the variant, it is worth emphasizing here that the ACS autonomous control system according to the invention can also be an independent component occurring outside the integrated element built into the structure of the CS charging station.

The autonomous ACS control system controls the operation of the CS charging station and generally has two operating modes:

- ACS 1 operating mode for controlling the integrated CS charging station, and

- ACS2 operating mode for controlling the integrated CS charging station and any component operating in a common NC network circuit, acting as a master MACS autonomous control system. We assume that at any given time, in the NC network circuit, only one ACS autonomous control system can act as the MACS, and the remaining ACS autonomous control systems then act as slave SACS autonomous control systems in the NC network circuit. The ACS autonomous control system consists of the following components: communication module 10, charging control module 20, database module 30, and prediction module 40, which work together. Communication module 10 is responsible for communication with the rest of the system.

In the ACS1 operating mode, the autonomous ACS control system implements the following set of messages/signals: a request to change charging parameters, and to send the current device status. A request to send the current device status, similarly to the above-described description, may be cyclical, defining the intervals at which a message/signal regarding the operating status of a device/receiver in the NC network circuit is to be sent, and to which devices/receivers in the NC network circuit. Furthermore, this request may be a request to send information about the current device/receiver status or, when one of the dynamic parameters changes, it may also remove the previously defined cyclicality of the sending, the device/receiver operating status, signals needed to establish the MACS in its absence (i.e., no signals are received about its operation), and a configuration write signal to the prediction module 40, wherein the change may be triggered by the central CMS management system.

In turn, the ACS autonomous control system in ACS2 mode additionally implements the following set of messages/signals: a signal confirming MACS operation, a request to send the status of an NC network circuit element (for each type of element: NA network analyzer, LC lighting controller, ACS autonomous control system), and obtaining information from the element regarding its operating status. In the case of the LC lighting controller, the set of messages/signals is as follows: switching on a luminaire, switching off a luminaire, reducing the luminaire's light intensity, sending a new luminaire operation schedule, and recording an external parameter that can be used in the prediction module.

The operating parameters of the components are stored in database module 30, although implementation considerations assume that minimal current values will be stored. An example implementation of database module 30 would be the memory of a microcontroller controlling the system. Each change in the state of database module 30 triggers actions in prediction module 40.

Based on the stored configuration, the aforementioned prediction module 40 controls the NC network circuit according to an adopted strategy aimed at preventing the entire NC network circuit from exceeding the established operating power and minimizing negative quality parameters of the NC network circuit (for example, reactive power). Essentially, the prediction module 40 determines the operating parameters of the NC network circuit components based on current data (including the aforementioned data on vehicle traffic intensity, planned lighting intensity schedule, etc.), as well as historical data and created statistical models (including machine learning). It is assumed that information about the demand for the charging service in a similar period in the past is known, and therefore the characteristics of changes in lighting intensity of the lighting fixtures over a predefined time and other operating parameters of the system (NC network circuit current) are also known. Therefore, we know when there will be a risk of overloading the NC network circuit. This knowledge also provides opportunities to create additional value-added services. These are not the subject of the invention, but demonstrate its practical application. It becomes possible to estimate and create a function of the user's EV charging time relative to the function of lost benefits by the system 100. This provides the potential for creating forward contracts. By specifying a longer charging time, the user can limit the electric vehicle's charging power in the future and allow other users of the NC network circuit to use the charging service. The aforementioned prediction module 40 communicates directly with the EV charging control module 20, which manages the EV charging parameters, i.e., the charging current. In turn, the charging control module 20 accepts a request to change parameters directly from the communication module 10. In addition to controlling the charging current, the charging control module 20 allows for reading system operating parameters such as charging current, device operating temperature (and thus the ability to monitor and protect against overheating of the charging system), EV connection status, and EV operating status. Any changes to the CS charging station's operation are recorded in database module 30.

FIG. 3 shows a charging scenario for an electric vehicle (EV) using a method 200 according to the invention for adapting the operation of a CS charging station to the conditions prevailing in the power grid, according to one embodiment of the invention. In this case, one of the CS charging stations, together with the autonomous control system (ACS), plays a superior role in relation to other autonomous control systems (ACS) present in the NC network circuit, becoming the master autonomous control system (MACS). The master autonomous control system (MACS) then controls the operation of devices/receivers operating in the NC network circuit. The aforementioned MACS is responsible for controlling devices operating in the NC network circuit and transmits a watchdog signal to other devices/receivers, for example, in this embodiment, to LC lighting controllers, external EC controllers, including autonomous control systems (ACS), which then act as slave autonomous control systems (SACS). The watchdog signal contains information on the current power reserve in the NC network circuit. This reserve can be used to connect other devices/receivers to the NC network circuit, or to increase the charging power of CS charging stations already operating under the control of autonomous control systems (ACS). Decisions regarding the use of the reserve are made by the MACS based on currently available information. This will be described in more detail in the example implementation of the invention below.

The MACS master autonomous control system defined in this way periodically sends a message about the NC network circuit status – message/signal [B1] – for the <T_LIFE> value defined in system 100. This message provides information that system 100 is functioning correctly for devices operating in the NC network circuit. If the message/signal is not sent for a predefined period longer than the <T_LIFE> value, the CS charging stations with the ACS integrated autonomous control system themselves agree on a new MACS master autonomous control system. During the period when the MACS is not agreed, the CS charging stations operate at the minimum predefined charging power. In turn, devices operating in the NC network circuit send information about their status – message/signal [B2]. This information is also sent to the MACS, which records the status. The status is sent when the CS charging station's operating status changes (e.g., connection of a new electric vehicle (EV), interruption of charging, change of charging parameters, etc.). This is done cyclically, in the embodiment at least once an hour.

When an electric vehicle (EV) is connected to a charging station (CS) (message/signal [L1], charging begins with the minimum charging parameters set at the CS charging station. In parallel, information about the charging start is sent to the MACS (message/signal [L2]) and the charging parameters are coordinated (message/signal [L3]. After receiving information about possible charging parameters, the CS charging station changes the EV's charging parameters (message/signal [L4]). This changes the value of the control signal, which informs the EV about a possible power increase. The MACS and the ACS involved in charging monitor the charging process. Local monitoring of the charging level involves cyclical coordination of possible charging parameters. These devices communicate with each other. The communication medium can be a mesh network, Wi-Fi, PLC, GSM, or other network. Both controllers supervise the network and the implementation of predefined functions, such as turning on and off lighting (message/signal [L7]), or other devices/receivers connected to the NC network circuit (message/signal [L8]. The MACS master autonomous control system, based on the current status, decides whether it is necessary to change the EV charging parameters. The MACS notifies the ACS autonomous control system of this fact to the activated CS charging station by sending the appropriate information – message/signal [L5]. The CS charging station adjusts the charging parameters – message/signal [L6] – with the EV. Changing the charging parameters on the hardware side involves changing the signals sent to the EV being charged (and in the case of AC charging, this is most often achieved by changing the frequency of the control signal generated by the CS charging station). This situation can occur multiple times during a single EV charging. The CS charging station operates until a charging termination event occurs – message/signal [L7]. This can occur, for example, after the EV is disconnected, an external request to end charging is sent to the CS charging station, or an independent decision by the controller. After the charging completion event occurs - message/signal [L7], the CS charging station notifies the MACS that the electric vehicle charging has been completed.

EXAMPLE OF THE INVENTION IMPLEMENTATION

To better illustrate the essence of the solution according to the invention and its benefits, let us assume that in the power network, in our case the lighting infrastructure, the following devices/receivers with different power consumption characteristics are connected to the NC network circuit, in this case a 1-phase circuit, such as:

• two 3.6 kW (16A) CS charging stations without an autonomous ACS control system, but with a known CPC power consumption characteristic (maximum operating power is 7.2 kW), • thirty 100 W LED luminaires with an external EC controller illuminating streets (power of 3 kW, but during switching on due to the 10-fold switching current we have an instantaneous power consumption of around 30 kW), • twenty 200 W sodium luminaires with an external EC controller illuminating streets (power of 2 kW, but during switching on due to the 10-fold switching current we have an instantaneous power consumption of around 20 kW), and • one electronic advertising billboard with a known power consumption of a maximum of 1 kW, which we treat as a receiver with a known CPC power consumption characteristic.

First, we will consider the case in which the system operates without an autonomous ACS control system, i.e., in accordance with the state of the art, in which the components mentioned above, including lighting fixtures, are controlled according to a programmed operation schedule, where the NC network circuit is turned on and off at a specific time of day (according to the same time). With this assumption, we achieve an operating power of 15.2 kW, and the circuit must be designed for a load of 78.2 kW (we assume that the switching current of the lighting fixtures will be 10 times greater than the rated current, and the cable cross-section must allow for the increased power consumption, i.e.:

Iw value* (number of LED luminaires * Pc value of LED luminaires + number of Sodium luminaires * Pc value of Sodium luminaires) = Pc value where:

Iw - a factor determining how much the switching current of the lighting fixture is greater than the nominal operating current of the lighting fixture (for simplicity, we assume the same factor for LED and sodium luminaires)

Pc - power consumption of the lighting fixture; therefore, for the example in question we have:

* (30 * 100W + 20 * 200W) = 70 kW plus the power of receivers with known CPC characteristics (7.2 kW + 1 kW = 8.2 kW), i.e. a total of 78.2kW.

In this case, it should be noted that during normal operation (except when switching on lighting fixtures), devices/receivers consuming an additional 63.0 kW of power may be connected to the NC network circuit. In light of the above, this enables the installation of a CS charging station with an autonomous ACS control system according to the invention. The following are connected to the NC network circuit:

• sixteen CS charging stations with a maximum power of 7.2 kW with an autonomous ACS control system according to the invention,

In this case, the total operating power of the CS charging station with the autonomous ACS control system at full load is 115.2 kW, which exceeds the capacity of the NC network circuit defined above. However, reducing the charging power to 3.6 kW results in a total charging power of approximately 57.6 kW. In light of the above, this value is acceptable for the operation of the system according to the invention. Therefore, it is possible to set the minimum charging current in the autonomous ACS control system to 3.6 kW. At this power, for hours that do not coincide with the switching on of lighting fixtures, the CS charging station will begin charging the electric vehicle (EV). Then, after coordinating the operating conditions with the master autonomous MACS control system, it will set the target charging characteristic. For example, if other CS charging stations are not operating, it will recommend increasing the charging power of a single station to 7.2 kW. If charging occurs during the lighting-on period, the MACS master autonomous control system will inform the user to reduce charging power to 0W during the luminaires' on-time period. The NA network analyzer provides an additional safety measure by monitoring the operating current in the NC network circuit (in this case, a single-phase circuit) and transmitting information to the MACS master autonomous control system about the current power consumption of all components (in this case, devices/receivers) operating in the NC network circuit. The MACS master autonomous control system can respond to overloads ad-hoc by controlling devices/receivers operating in the NC network circuit (in this case, all devices/receivers equipped with appropriate controllers, e.g., in the case of luminaires, LC lighting controllers).

In the presented implementation example, the additional installation of LC lighting controllers on the luminaires will generate additional savings. Furthermore, it allows for real-time control of the luminaires, thus increasing the dynamics associated with the operation of a CS charging station equipped with an autonomous ACS control system. Applicable lighting standards in Europe (CEN EN 13201) and the US (ANSEIES RP-8) legally regulate safe lighting levels for road users and limit negative environmental impacts. Lighting intensity depends on dynamic factors. Examples include atmospheric conditions, such as the weather, and the number of vehicles currently on the road. By measuring these elements (vehicle traffic is typically measured using induction loops) and transmitting this information to a CS charging station equipped with an autonomous ACS control system, for example, in one embodiment via the central management system (CMS), we can reduce the luminous intensity of the luminaires, and therefore the power consumed by the luminaires. For example, according to the adopted CEN EN 13201-2:2015 standard, reducing the luminance level from lighting class M2 (required luminance level is 1.5 cd/ ^m² ) to M4 (required luminance level is 0.75 cd/ ^m² ) yields significant savings. The luminance level can be reduced when, for example, on a multi-lane road, traffic volume drops from 50% to below 15% of the total road capacity. Reductions can also occur as a result of other factors, such as clearing the road of parked vehicles. Reducing the luminance level by two levels allows for a reduction in luminaire power (from 1.5 cd/ ^m² to 0.75 cd/ ^m² ) by approximately 50%. If this occurs on both illuminated road sections, the power can be reduced from 7 kW to 3.5 kW. This reduction makes it possible to install an additional CS charging station with an autonomous ACS control system according to the invention or to better balance the power using CS charging stations already operating in the circuit.

Depending on the type of luminaires used, inductive or capacitive reactive power may occur when light intensity is reduced. In the example discussed, the reactive power may exceed 1 VAR. This negatively impacts the quality of the NC network circuit. To eliminate this phenomenon, it is possible to install additional reactive power compensators (in the simplest version, these are chokes) connected to the NC network circuit via an external EC controller. If this phenomenon is detected by the NA network analyzer, the ACS autonomous control system, according to the invention, acting as the master MACS autonomous control system, can order the activation of selected compensators to eliminate the negative phenomenon.

In the presented embodiment, thanks to the use of the solution according to the invention, on the one hand we have the ability to increase the availability of CS charging station points in the lighting infrastructure with optimal management of the charging time of electric vehicles EV, and on the other hand we have the ability to eliminate negative phenomena in the form of reactive power or overexposure that may appear on the lighting infrastructure.

The foregoing description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to the disclosed embodiment are possible, including all such changes, modifications, and variations as fall within the spirit and scope of the appended claims. The generic principles defined herein may therefore be applied to other embodiments without departing from the scope of the invention. Therefore, the present invention is not intended to be limited to the embodiments disclosed herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

The present solution according to the invention therefore offers, using the above-mentioned technical means, as indicated in Figures from FIG. 1 to FIG. 3, an electric vehicle charging station and an autonomous system and method for adapting the operation of an electric vehicle charging station to the conditions prevailing in the power grid, in particular with particular regard to the characteristics of the lighting network, using designed elements and systems intended for monitoring, control and prediction.

APPLICATION OF THE INVENTION

The present invention will find applications in the broadly understood electromobility industry, particularly in electric vehicle charging infrastructure. The invention will also find applications in power grids, particularly in lighting networks, where there is a risk of overloading or degradation of network quality parameters due to devices/receivers with varying power consumption characteristics, including charging stations.

An example of an area in which the invention can be applied is the existing energy infrastructure, in particular the lighting infrastructure, in which switching on lighting fixtures and operations related to reducing the light level cause periodic changes in power consumption and the appearance of reactive power.

LIST OF REFERENCE NOTATIONS

100 autonomous system

200 autonomous way

CS charging station

EV electric vehicle

COA shared work area

ACS autonomous control system communication module charging control module database module prediction module vehicle charging system

CMS central management system

NC network circuit

NA network analyzer

PP power point

LC lighting controller

EC external controller

MACS Master Autonomous Control System

SACS slave autonomous control system

CPC known power consumption characteristics

Claims (11)

1. An electric vehicle charging station adapting its operation to the conditions prevailing in the power grid, in particular the lighting grid, wherein the charging station comprises an electric vehicle charging system with internal electronics in the form of at least one central processing unit operationally connected to a communication unit, a memory, and an input unit and an output unit, providing an interface with a user, characterized in that it has at least one autonomous control system (ACS), which system comprises a communication module (10), a charging control module (20), a database module (30) and a prediction module (40) cooperating with each other, wherein the prediction module (40) intended to detect and predict loads and disturbances in the network circuit (NC) on the basis of historical data and/or generated statistical models and/or a rule-based system is connected to a communication module (10) carrying out data transmission between devices/receivers connected to the network circuit (NC), wherein the communication module (10) is coupled to the module (30) a database intended to store the operating status parameters of the said devices/receivers connected to the network circuit (NC) and with a charging control module (20) dynamically adjusting the characteristics of the charging current of the electric vehicle (EV) in relation to the operating status parameters of the devices/receivers connected to the network circuit (NC). 2. Charging station (CS) according to claim 1, characterized in that the autonomous control system (ACS) is an independent component integrated outside the element built into the structure of the charging station (CS). 3. Autonomous system (100) adapting the operation of an electric vehicle charging station to the conditions prevailing in the power grid, in particular a lighting network creating many common work areas containing a single-phase or multi-phase network circuit to which devices/receivers with different power consumption characteristics are connected, including devices/receivers equipped with controllers, characterized in that it comprises: - at least one charging station (CS) according to any one of claims 1 to 2, connected to a network circuit (NC); - a network analyzer (NA) intended for monitoring and transmitting in real time dynamic parameters and/or parameters of the operating status of devices/receivers connected to the network circuit (NC), wherein the network analyzer (NA) communicates with one of the charging stations (CS) equipped with at least one autonomous control system (ACS), which becomes a superior autonomous control system (MACS) in relation to the remaining charging stations (CS), which then act as subordinate autonomous control systems (SACS) in the network circuit (NC), wherein the superior autonomous control system (MACS), on the basis of said dynamic parameters and/or parameters of the operating status of devices/receivers connected to the network circuit (NC), dynamically determines each time the target characteristic of the charging current of an electric vehicle (EV) connected to the charging station (CS), taking into account each time the predetermined limit value of the maximum operating power of the network circuit (NC). 4. Autonomous system (100) according to claim 3, characterized in that the network analyzer (NA) comprises a module for integration with the circuit's electricity consumption meter and/or a measurement module and a communication module cooperating with each other, wherein the measurement module is a set of toroidal transformers intended to determine the current consumption in the power network for individual devices/receivers connected to the network circuit (NC). 5. Autonomous system (100) according to claim 3, characterized in that it additionally has a central management system (CMS) comprising a cooperating communication module, an API module, a database module, a prediction module and a user interface module, intended to integrate information from devices/receivers connected to the network circuit (NC) via a network analyzer (NA) and communicating them via a communication medium. 6. Autonomous system (100) according to claim 5, characterized in that the communication medium is a Mesh radio network and/or WiFi and/or GSM or a serial bus and/or PLC. 7. An autonomous method (200) for adapting the operation of an electric vehicle charging station to the conditions prevailing in the power grid, in particular a lighting network creating a plurality of common operating areas, comprising connecting an electric vehicle to the charging station in a single-phase or multi-phase network circuit, wherein before starting to charge the electric vehicle via the charging station, a charging current reservation request signal is transmitted, characterised in that: upon reserving the charging current from among the autonomous control systems (ACS) located in the network circuit (NC), a deterministic procedure for selecting one superior autonomous control system (MACS) is carried out autonomously and without the participation of the master system in relation to the remaining autonomous control systems (ACS), which then act as slave autonomous control systems (SACS), the selection being made on the basis of local and real-time measured parameters/signals, then to the superior autonomous control system (MACS) during the charging of the electric vehicle (EV) via a network analyzer (NA) and/or directly via devices/receivers connected to the network circuit (NC), periodic signals on dynamic parameters and/or parameters of the operating status of devices/receivers connected to the network circuit (NC) are transmitted on request or in a cyclical manner, including at least information on the link operation quality parameters such as: phase currents, phase shift angle (φ) between current and voltage, harmonic distortions, phase occupancy and load states, wherein on the basis of the parameters transmitted via the master autonomous control system (MACS) the charging level is monitored in real time and the characteristics of the charging current are dynamically adjusted at least in terms of the charging current, harmonic distortions, phase shift angle (φ) between the current and voltage for each charging station (CS) of the electric vehicle (EV), taking into account each time the predetermined limit value of the maximum operating power of the network circuit (NC) and/or via the master autonomous control system (MACS) the operation of devices/receivers operating in the network circuit (NC) is controlled in order to maintain the qualitative and quantitative parameters of the link and a watchdog signal is sent to the other autonomous control systems (ACS) in the network circuit (NC), in the absence of a cyclic periodic signal via the autonomous control system (ACS) the operating parameters of the charging station (CS) are minimized to a predetermined level of the minimum charging current defined in the charging station (CS) or the operation of the charging station (CS) is stopped to avoid overloading the network circuit (NC) and in parallel, the re-election of the master autonomous control system (MACS) is initiated. 8. An autonomous method (200) according to claim 7, characterized in that the charging current reservation request signal is transmitted to a superior autonomous control system (MACS) via a central management system (CMS). 9. An autonomous method (200) according to claim 7, characterized in that said measurement of the operating status parameters of devices/receivers connected to the network circuit (NC) is performed by means of sets of toroidal transformers constituting the measuring module of the network analyzer (NA), which induce voltage at the ends of their windings as a result of the action of the magnetic field induced by the current flowing through the network circuit (NC). 10. An autonomous method (200) according to claim 7, characterized in that said dynamic parameters are determined based on the level of astral light illuminating the streets and/or information about parked cars and/or vehicle traffic intensity and/or pedestrian traffic intensity and/or weather conditions occurring during the operation of the network circuit (NC), wherein the determined dynamic parameters are used to regulate the operation of devices/receivers connected to the network circuit (NC) by increasing or decreasing the current consumption in the network circuit (NC). PL 248511 Β1 11. An autonomous method (200) according to claim 7, characterized in that said watchdog signal comprises information on the current power available for use in the network circuit (NC), by means of which the charging power of charging stations (CS) operating under the control of autonomous control systems (ACS) is increased and/or additional devices/receivers are connected to the network circuit (NC), taking into account a predetermined limit value of the maximum operating power of the network circuit (NC).