CN112436536B - Charging guiding method and system for new energy automobile on expressway - Google Patents
Charging guiding method and system for new energy automobile on expressway Download PDFInfo
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- H—ELECTRICITY
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- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/28—Arrangements for balancing of the load in a network by storage of energy
- H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
- H02J3/322—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means the battery being on-board an electric or hybrid vehicle, e.g. vehicle to grid arrangements [V2G], power aggregation, use of the battery for network load balancing, coordinated or cooperative battery charging
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- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
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Abstract
The utility model provides a highway new energy automobile charging guiding method and system, which comprises the following steps of obtaining the current position and the remaining mileage of a new energy automobile; calculating a reachable charging service area according to the remaining mileage and the current position; when the service areas where the electric quantity of the new energy automobile can only reach are only the preset number, the new energy automobile is guided to go to the charging service area with the lowest discount coefficient and free charging piles for charging; according to the method, the lowest discount coefficient is distributed to the service area where the new energy automobile user is most hoped to charge, the highest discount coefficient is distributed to the service area where the new energy automobile user is least hoped to charge, so that the new energy automobile is guided to enter the service area where the control system expects the new energy automobile user, and through an intelligent new energy automobile guiding method, more efficient load scheduling and balancing are achieved.
Description
Technical Field
The disclosure relates to the technical field of new energy charging control, in particular to a charging guiding method and system for a new energy automobile on a highway.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
Due to the rapid development of the industry, a large amount of non-renewable energy is consumed, resulting in a rapid decrease in the reserve amount of non-renewable energy and environmental problems such as environmental deterioration and global warming. In order to save non-renewable energy and protect ecological environment, sustainable development is sought, and countries around the world have already vigorously researched to efficiently utilize renewable energy and construct comprehensive energy systems. The utilization technology of wind energy and light energy is mature at present, the wind energy is sufficient at night generally, the quantity of the wind energy is relatively small in the daytime, and the light energy exists only in the daytime due to the uncontrollable property of the wind energy and the light energy. Much wind energy can be abandoned only in the electricity consumption valley period at night, and much light energy can be abandoned in the electricity consumption valley period in the day. In addition, the power load changes greatly during a day, and the frequency, voltage, power of the line and current of the whole power system are changed due to the load changes, which has a great influence on the stability of the power system. In order to reduce the load peaks, the load valleys are filled. The load peak-valley difference of the power grid is reduced, and the power load needs to be subjected to peak clipping and valley filling when the power generation and the power utilization tend to be balanced. The existing new energy automobile has huge reserve, each new energy automobile can be regarded as an independent storage battery, and the new energy automobile can be charged, peak clipping and valley filling can be controlled.
The inventor of the present disclosure finds that, most of the existing methods for reducing night electricity prices are used for guiding new energy vehicles to charge at night to achieve the purpose of peak clipping and valley filling, and such methods for guiding new energy vehicles to charge are too simple and rough to achieve effective load scheduling and balance adjustment.
Disclosure of Invention
In order to solve the defects of the prior art, the invention provides a highway new energy automobile charging guiding method and system, the lowest discount coefficient is distributed to a service area where new energy automobile users are most hoped to be charged, the highest discount coefficient is distributed to a service area where new energy automobile users are least hoped to be charged, so that the new energy automobiles are guided to enter the service area where the control system expects the new energy automobiles to go, and more efficient load scheduling and balancing are achieved through an intelligent new energy automobile guiding method.
In order to achieve the purpose, the following technical scheme is adopted in the disclosure:
the first aspect of the disclosure provides a charging guiding method for a new energy automobile on a highway, which includes the following steps:
acquiring the current position and the remaining mileage of the new energy automobile;
calculating a reachable charging service area according to the remaining mileage and the current position;
when the service areas that the electric quantity of the new energy automobile can only reach are only preset in number, the new energy automobile is guided to go to the charging service area with the lowest discount coefficient and free charging piles to charge.
As some possible implementation manners, when the remaining capacity of the new energy automobile can only reach the service areas with the preset number, a preset discount coefficient is allocated to each service area which can be reached by different new energy automobiles in real time, and discount coefficients of all service areas of the same new energy automobile are different.
By way of further limitation, the charging fee paid by the user is the product of the electric charge charged by the charging pile and the discount coefficient, the lowest discount coefficient is allocated to the service area where the new energy automobile is most expected to be charged, and the highest discount coefficient is allocated to the service area where the new energy automobile is least expected to be charged.
As a further limitation, the discount coefficients of each service area are assigned by adopting a Q-Learning reinforcement Learning method.
As a further limitation, the Q-Learning reinforcement Learning method includes a plurality of actions, each action correspondingly selects a service area, the state is a power load interval and the rising and falling trends of the power load, and the reward function is the inverse of the absolute value of the power load obtained by subtracting the action from the current power load multiplied by a certain coefficient;
and continuously updating the Qtable, giving the lowest discount coefficient to the action with the highest Q value in the state, and finally giving the highest discount coefficient to the action with the lowest Q value in the state.
The utility model discloses the second aspect provides a highway new energy automobile bootstrap system that charges, includes:
a data acquisition module configured to: acquiring current position information and remaining mileage of the new energy automobile;
a service area acquisition module configured to: calculating a reachable charging service area according to the remaining mileage and the current position;
a charge guidance module configured to: when the service areas where the electric quantity of the new energy automobile can only reach are only preset in number, the new energy automobile is guided to go to the charging service area with the lowest discount coefficient and free charging piles for charging.
The third aspect of the present disclosure provides an expressway new energy automobile charging system, including:
the system comprises a plurality of charging subsystems, a data server and at least one mobile terminal;
the charging subsystem at least comprises a storage battery charger, a storage battery, a battery electric quantity sensor, an inverter and a charging pile, wherein a power grid power supply is connected with the storage battery through a first power electronic switch, the storage battery is connected with the inverter through a second power electronic switch, the power grid power supply is connected with the charging pile through a third power electronic switch, the inverter is connected with the charging pile, and the charging pile is provided with an electric charge pricing module and a display module;
be equipped with radar detection module on the parking stall that charges, each electric control element of charging subsystem all with data server communication connection, data server and mobile terminal communication connection.
The fourth aspect of the present disclosure provides a charging method for a new energy automobile on an expressway, and a charging system for a new energy automobile on an expressway according to the third aspect of the present disclosure includes the following steps:
the mobile terminal executes the highway new energy automobile charging guiding method in the first aspect of the disclosure;
when the power load of the power grid is in a valley, the first power electronic switch is turned on to charge the storage battery, the second power electronic switch is turned off, the third power electronic switch is turned on, and the power grid power supply supplies power for the charging pile;
when the power load is in a peak, if the reading of the battery electric quantity sensor is not zero, the first power electronic switch is closed, the second power electronic switch is opened, the third power electronic switch is closed, and the storage battery supplies power for the charging pile;
if the battery capacity is zero, the first power electronic switch is closed, the second power electronic switch is closed, the third power electronic switch is opened, the power grid power supply supplies power to the charging pile, the storage battery is not charged, and charging is resumed until the power load is smaller than the preset value.
A fifth aspect of the present disclosure provides a medium, on which a program is stored, which when executed by a processor implements the steps in the charging guidance method for a new energy vehicle on an expressway according to the first aspect of the present disclosure.
A sixth aspect of the present disclosure provides an electronic device, which includes a memory, a processor, and a program stored in the memory and executable on the processor, and when the processor executes the program, the steps in the charging guidance method for a new energy vehicle on a highway according to the first aspect of the present disclosure are implemented.
Compared with the prior art, the beneficial effect of this disclosure is:
1. according to the highway new energy automobile charging guiding method and system, the lowest discount coefficient is distributed to the service area where the new energy automobile user is most hoped to charge, the highest discount coefficient is distributed to the service area where the new energy automobile user is least hoped to charge, so that the new energy automobile is guided to enter the service area where the control system expects the new energy automobile user to go, and through an intelligent new energy automobile guiding method, more efficient load scheduling and balancing are achieved.
2. According to the charging guiding method and system for the new energy automobile on the expressway, the Q-Learning reinforcement Learning method is adopted to assign the discount coefficients of each service area, the Qtable is continuously updated through the updating formula, the lowest discount coefficient is given to the action with the highest Q value in the state, the highest discount coefficient is given to the action with the lowest Q value in the state, and efficient matching control of the discount coefficients and power load scheduling is achieved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the disclosure, illustrate embodiments of the disclosure and together with the description serve to explain the disclosure and are not to be construed as limiting the disclosure.
Fig. 1 is a schematic flow diagram of a charging guidance method for a new energy automobile on a highway provided by embodiment 1 of the present disclosure.
Fig. 2 is a schematic structural diagram of a charging guidance system for a new energy automobile on a highway provided in embodiment 3 of the present disclosure.
Fig. 3 is a structural diagram of a large-capacity storage battery and a storage cabinet provided in embodiment 3 of the present disclosure.
Fig. 4 is a flowchart of a procedure of a mobile terminal APP provided in embodiment 3 of the present disclosure.
In the figure, 1, a power electronic switch; 2. a battery charger; 3. a large capacity storage battery; 3-1, a storage battery interface; 3-2, lead-acid storage battery for energy storage; 3-2-1, a battery anode; 3-2-2, a battery negative electrode; 3-3, a battery storage cabinet; 4. a battery level sensor; 5. a power electronic switch; 6. an inverter; 7. a power electronic switch; 8. charging piles; 9. an electric charge pricing module; 10. a display module; 11. charging pile parking spaces; 12. a radar monitoring module; 13. an electric wire; 14. a data server; 15. network connection; 16. a mobile terminal.
Detailed Description
The present disclosure is further described with reference to the following drawings and examples.
It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the disclosure. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments according to the present disclosure. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
The embodiments and features of the embodiments in the present disclosure may be combined with each other without conflict.
Example 1:
as shown in fig. 1, an embodiment 1 of the present disclosure provides a charging guidance method for a new energy vehicle on an expressway, including the following steps:
acquiring the current position and the remaining mileage of the new energy automobile;
calculating a reachable charging service area according to the remaining mileage and the current position;
when the service areas where the electric quantity of the new energy automobile can only reach are only preset in number, the new energy automobile is guided to go to the charging service area with the lowest discount coefficient and free charging piles for charging.
When the residual electric quantity of the new energy automobile can only reach the service areas with the preset number, a preset discount coefficient is distributed to each service area which can be reached by different new energy automobiles in real time, and the discount coefficients of all the service areas of the same new energy automobile are different.
The charging fee paid by the user is the product of the electric charge counted by the charging pile and the discount coefficient, the lowest discount coefficient is distributed to the service area where the new energy automobile is most hoped to be charged, and the highest discount coefficient is distributed to the service area where the new energy automobile is least hoped to be charged.
And assigning discount coefficients of each service area by adopting a Q-Learning reinforcement Learning method.
The Q-Learning reinforcement Learning method comprises a plurality of actions, wherein each action correspondingly selects a service area, the states of the service areas are power load intervals and the rising and falling trends of the power loads, and a reward function is that the reciprocal of the absolute value of the power load obtained by subtracting the action from the current power load is multiplied by a certain coefficient;
and continuously updating the Qtable, giving the lowest discount coefficient to the action with the highest Q value in the state, and finally giving the highest discount coefficient to the action with the lowest Q value in the state.
More specifically:
firstly, three discount coefficients gamma (gamma > 0) are preset, such as 0.5, 1.3 and 2, and when the residual electricity of the new energy automobile is expected to reach three service areas only, the three preset discount coefficients gamma are distributed to the three service areas which can be reached by different users in real time;
the charging fee paid by the user is the charging fee multiplied by a discount coefficient gamma of the charging module for charging the electric charge of the charging pile, the discount coefficients gamma of different users in the same service area are possibly different, the lowest discount coefficient gamma is distributed to the service area most expecting the charging of the new energy automobile user, and the highest discount coefficient gamma is distributed to the service area least expecting the charging of the new energy automobile user, so that the new energy automobile is guided to enter the service area which the control system expects the new energy automobile user to go to;
the essence of charging when the new energy automobile enters different service areas is that charging is carried out at different times, for example, the current time is t 0 The required time of the new energy automobile to reach the first service area, the second service area and the third service area is t respectively 1 、t 2 And t 3 So t can be selected in the time interval of t3 0 +t 1 、t 0 +t 2 And t 0 +t 3 The time is used as a charging time, thereby adjusting the power load.
Example 2:
the embodiment 2 of the present disclosure provides a highway new energy automobile bootstrap system that charges, includes:
a data acquisition module configured to: acquiring current position information and remaining mileage of the new energy automobile;
a service area acquisition module configured to: calculating an reachable charging service area according to the remaining mileage and the current position;
a charge guidance module configured to: when the service areas where the electric quantity of the new energy automobile can only reach are only preset in number, the new energy automobile is guided to go to the charging service area with the lowest discount coefficient and free charging piles for charging.
The working method of the system is the same as the charging guiding method of the new energy automobile on the highway provided in embodiment 1, and details are not repeated here.
Example 3:
as shown in fig. 2 to 4, embodiment 3 of the present disclosure provides a charging system for a new energy automobile on an expressway, including a plurality of charging subsystems, a data server, and a mobile terminal carrying a control APP;
each charging subsystem comprises a power electronic switch 1, a storage battery charger 2, a large-capacity storage battery 3, a battery electric quantity sensor 4, a power electronic switch 5, an inverter 6, a power electronic switch 7, a charging pile 8, an electric charge pricing module 9, a display module 10, a charging parking space 11, a radar detection module 12, a power line 13, a data server 14, a network connection line 15 and a mobile terminal APP16;
each charging pile 8 is provided with a large-capacity storage battery 3, the large-capacity storage battery 3 comprises a battery anode 3-2-1, a battery cathode 3-2-2 and a battery storage cabinet 3-3, the storage battery charger 2 is used for charging the storage battery 3, the storage battery 3 is charged by adopting a power grid power supply, and electricity is supplied to the charging pile 8 when the storage battery 3 discharges;
the power electronic switch 1 controls whether the storage battery 3 is charged or not, the power electronic switch 5 controls whether the storage battery 3 supplies power to the charging pile 8 or not, the power electronic switch 7 controls whether a power grid supplies power to the charging pile 8 or not, and the inverter 6 converts direct current output by the storage battery 3 into alternating current to supply to the charging pile 3;
the radar detection module 12 is installed in the ground center of the charging pile parking space 11 to detect whether the charging pile 8 is used or not; the battery electric quantity sensor 4 acquires the battery electric quantity information, and the electric charge pricing module 9 acquires the electric price information of the data server 14 and gives charging electric charges by combining the electric quantity used by the user;
power electronic switch 1, fill electric pile 3, battery level sensor 4, power electronic switch 5, power electronic switch 7, charges of electricity pricing module 9 and radar detection module 12 all with 14 electric information connection of data server, data server 14 with load control APP's mobile terminal through limited or wireless network connection.
The high-capacity storage battery 3 is formed by connecting a plurality of lead-acid storage batteries 3-2 for energy storage in series and then in parallel, the temperature range of the battery is wide, the battery can normally run in a temperature environment of-30-60 ℃, the low-temperature performance is good, the battery can be used even in a region with low temperature, and the capacity consistency is good. When the storage batteries are used in series and parallel connection, the consistency is kept, and the charge acceptance is good; in an unstable charging environment, the charging device has stronger charging acceptance capacity and long service life, reduces the maintenance and repair cost and reduces the overall investment of the system; the high-capacity storage battery is stored in the battery storage cabinet 3-3, the battery storage cabinet is provided with a plurality of small compartments, the compartments are connected with one another through leads, and the compartments store a single lead-acid storage battery for energy storage, so that later maintenance is facilitated.
The charging subsystem main body is two branches connected in parallel, the first branch is a power grid power supply, a power electronic switch 1, a storage battery charger 1, a high-capacity storage battery 3, a power electronic switch 5, an inverter 6 and a charging pile 8 which are sequentially connected; the second branch is formed by sequentially connecting a power grid power supply, a power electronic switch 7 and a charging pile 8; battery level sensor 4 connects on battery 3, and radar detection module 12 is installed at the parking stall center, and the module 9 of charging of price of electricity is installed on filling electric pile 8.
The electricity charge pricing module 9 obtains charging electricity charge by multiplying the electricity price, the electricity consumption and the discount coefficient, a charging code is displayed on the display module, and the data server 14 receives the power load state of the power grid to control the power electronic switch;
the power electronic switches (1, 5, 7) of the charging subsystem are switched on and off under the control of the data server 14, and the specific control strategy is as follows:
when the power load of the power grid is in a low ebb, the power electronic switch 1 is opened to charge the storage battery 3, the power electronic switch 5 closes the power electronic device 7, and the power of the charging pile is turned on to come from the power grid;
when the power load is in a peak, if the reading of the battery electric quantity sensor 4 is not zero, the power electronic switch 1 closes the power electronic switch 5, opens the power electronic switch 7 and closes the storage battery 3 to supply power to the charging pile;
if the battery capacity is zero, the power electronic switch 1 is closed, the power electronic switch 5 is closed, the power electronic switch 7 is opened, the power grid supplies power to the charging pile 3, the storage battery 3 is not charged, and the charging is not performed until the power load is smaller than the preset value.
The control APP is application software installed on the user intelligent mobile terminal 16 and has functions of navigation, data acquisition and charging recommendation of the charging pile reservation;
after a user opens an APP, the APP acquires position information of a mobile terminal, the position information enters a map navigation system, and all servers provided with charging piles on a display route are displayed as grey icons;
the APP obtains the information of the electric quantity and the remaining mileage of the automobile after the user is connected with the new energy automobile through the mobile terminal Bluetooth or the data line;
the APP calculates the reachable charging service area to be highlighted according to the remaining mileage and the current position, and the charging service area is displayed as a green icon;
when the number of service areas to which the electric quantity of the new energy automobile can only reach is three, the APP recommends the charging service area with the lowest discount coefficient and the idle charging pile;
the user can fill electric pile through the reservation of mobile terminal APP, and the effective time of reservation is 20 minutes, and the automatic cancellation of reservation after 20 minutes, the electric pile that is reserved will show on display module 10 and has reserved.
The data server 14 related to this embodiment can timely acquire power grid power load information and storage battery capacity information, control the opening and closing information of the power electronic switches (1, 5, 7), also can acquire information of the radar detection module 12 and a reservation charging pile request of a user to obtain which charging piles are in an idle state, and send idle charging pile information to the mobile terminal.
And (3) a control algorithm:
Q-Learning is a value-based algorithm in a reinforcement Learning algorithm, wherein Q is the expectation that the Action a (a belongs to A, A is the set of all actions) can obtain the benefit when Q (S, a) is in the S State at a certain moment (S belongs to S, S is the set of all states), and the environment feeds back the corresponding reward rewardr according to the Action of agent, so the main idea of the algorithm is to construct State and Action into a Q-table to store the Q value, and then the Action capable of obtaining the maximum benefit is selected according to the Q value.
The updating formula of the Q-table is as follows: q (s, a) ← Q (s, a) + alpha [ r + gamma max a′ Q(s′,a′)-Q(s,a)]Where α is the learning rate and γ is the rewarding decay coefficient. In the system, three action actions are selected, namely a first service area, a second service area and a third service area are selected respectively, the states are power load intervals and the rising and falling trends of the power load, and the reward function is the inverse number of the absolute value of the power load obtained by subtracting the action from the current power load and is multiplied by a coefficient k. And continuously updating the Qtable through an updating formula, and finally giving the lowest discount coefficient to the action with the highest Q value in the state and giving the highest discount coefficient to the action with the lowest Q value in the state.
Example 4:
the embodiment 4 of the present disclosure provides a medium, on which a program is stored, and the program, when executed by a processor, implements the steps in the charging guidance method for a new energy automobile on an expressway according to embodiment 1 of the present disclosure.
Example 5:
the embodiment 5 of the present disclosure provides an electronic device, which includes a memory, a processor, and a program stored in the memory and capable of running on the processor, where the processor executes the program to implement the steps in the charging guidance method for a new energy vehicle on a highway according to embodiment 1 of the present disclosure.
As will be appreciated by one of skill in the art, embodiments of the present disclosure may be provided as a method, system, or computer program product. Accordingly, the present disclosure may take the form of a hardware embodiment, a software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present disclosure may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, optical storage, and the like) having computer-usable program code embodied therein.
The present disclosure is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the disclosure. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above may be implemented by a computer program, which may be stored in a computer readable storage medium and executed by a computer to implement the processes of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), or the like.
The above description is only a preferred embodiment of the present disclosure and is not intended to limit the present disclosure, and various modifications and changes may be made to the present disclosure by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present disclosure should be included in the protection scope of the present disclosure.
Claims (6)
1. A charging guiding method for a new energy automobile on a highway is characterized by comprising the following steps: the method comprises the following steps:
acquiring the current position and the remaining mileage of the new energy automobile;
calculating a reachable charging service area according to the remaining mileage and the current position;
when the service areas where the electric quantity of the new energy automobile can only reach are only the preset number, the new energy automobile is guided to go to the charging service area with the lowest discount coefficient and free charging piles for charging;
when the number of the service areas where the electric quantity of the new energy automobile can only reach is preset, distributing a preset discount coefficient to each service area where different new energy automobiles can reach in real time, wherein the discount coefficients of all the service areas of the same new energy automobile are different; assigning discount coefficients of each service area by adopting a Q-Learning reinforcement Learning method;
the Q-Learning reinforcement Learning method comprises a plurality of actions, each action correspondingly selects a service area, the states are power load intervals and the rising and falling trends of the power loads, and a reward function is that the reciprocal of the absolute value of the power load obtained by subtracting the action from the current power load is multiplied by a certain coefficient;
and continuously updating the Qtable, giving the lowest discount coefficient to the action with the highest Q value in the state, and finally giving the highest discount coefficient to the action with the lowest Q value in the state.
2. The charging guiding method for the new energy automobile on the expressway according to claim 1, comprising the steps of:
the charging fee paid by the user is the product of the electric charge charged by the charging pile and the discount coefficient, the lowest discount coefficient is distributed to the service area most expecting the charging of the new energy automobile, and the highest discount coefficient is distributed to the service area least expecting the charging of the new energy automobile.
3. The utility model provides a highway new energy automobile bootstrap system that charges which characterized in that: the method comprises the following steps:
a data acquisition module configured to: acquiring current position information and remaining mileage of the new energy automobile;
a service area acquisition module configured to: calculating a reachable charging service area according to the remaining mileage and the current position;
a charge guidance module configured to: when the service areas only capable of reaching the electric quantity of the new energy automobile are only preset in number, the new energy automobile is guided to go to the charging service area with the lowest discount coefficient and free charging piles for charging;
when the number of the service areas where the electric quantity of the new energy automobile can only reach is preset, distributing a preset discount coefficient to each service area where different new energy automobiles can reach in real time, wherein the discount coefficients of all the service areas of the same new energy automobile are different; assigning discount coefficients of each service area by adopting a Q-Learning reinforcement Learning method;
the Q-Learning reinforcement Learning method comprises a plurality of actions, wherein each action correspondingly selects a service area, the states of the service areas are power load intervals and the rising and falling trends of the power loads, and a reward function is that the reciprocal of the absolute value of the power load obtained by subtracting the action from the current power load is multiplied by a certain coefficient;
and continuously updating the Qtable, giving the lowest discount coefficient to the action with the highest Q value in the state, and finally giving the highest discount coefficient to the action with the lowest Q value in the state.
4. The utility model provides a highway new energy automobile charging system which characterized in that: the method comprises the following steps:
the system comprises a plurality of charging subsystems, a data server and at least one mobile terminal;
the charging subsystem at least comprises a storage battery charger, a storage battery, a battery electric quantity sensor, an inverter and a charging pile, wherein a power grid power supply is connected with the storage battery through a first power electronic switch, the storage battery is connected with the inverter through a second power electronic switch, the power grid power supply is connected with the charging pile through a third power electronic switch, the inverter is connected with the charging pile, and the charging pile is provided with an electric charge pricing module and a display module;
the charging parking space is provided with a radar detection module, each electric control element of the charging subsystem is in communication connection with a data server, and the data server is in communication connection with the mobile terminal;
the charging system for the expressway new energy automobile comprises the following steps:
the mobile terminal executes the charging guiding method of the new energy automobile on the expressway according to any one of claims 1-2;
when the power load of the power grid is in a low ebb, the first power electronic switch is turned on to charge the storage battery, the second power electronic switch is turned off, the third power electronic switch is turned on, and the power grid power supply supplies power to the charging pile;
when the power load is in a peak, if the reading of the battery electric quantity sensor is not zero, the first power electronic switch is closed, the second power electronic switch is opened, the third power electronic switch is closed, and the storage battery supplies power for the charging pile;
if the battery capacity is zero, the first power electronic switch is closed, the second power electronic switch is closed, the third power electronic switch is opened, the power grid power supply supplies power to the charging pile, the storage battery is not charged, and charging is resumed until the power load is smaller than the preset value.
5. A medium having a program stored thereon, wherein the program, when executed by a processor, implements the steps in the charging guidance method for a new energy vehicle for an expressway according to any one of claims 1 to 2.
6. An electronic device comprising a memory, a processor and a program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of the charging guidance method for new energy vehicles on highway according to any one of claims 1-2.
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