CN114493040A - Energy storage vehicle scheduling method, system and device - Google Patents
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Abstract
The invention discloses a dispatching method, a system and a device of an energy storage vehicle, which comprises the steps of firstly obtaining the charging station information of each charging station in the current period, wherein the charging station information comprises the total power consumption of the charging station and the occupation information of the charging position, then determining the pressure state of each charging station in the current period according to the charging station information, determining a first charging station to be supported in the current period according to the pressure state, and finally controlling each energy storage vehicle to go to the corresponding first charging station, wherein the energy storage vehicle is a movable device for charging vehicles, can control the energy storage vehicle stopped in the charging station with a smaller pressure state to go to the charging station with a larger pressure state for supporting, so that the charging station with a larger pressure state can support more vehicles for charging, and then alleviate the pressure state of charging station, improve car owner's experience of charging, in addition, the energy storage car charging resource of the less charging station of pressure state has still effectively been utilized.
Description
Technical Field
The invention relates to the field of charging station management, in particular to a method, a system and a device for dispatching an energy storage vehicle.
Background
Along with the increase of electric vehicle quantity, the charging pressure of charging station increases thereupon, because a charging station only has the charging position of fixed quantity, can only charge for the vehicle of fixed quantity simultaneously, so the charging station that sets up in different places has different charging pressure, for example, set up the charging station of core highway section and usually have more vehicle to charge, lead to this charging station to explode easily, influenced car owner's experience of charging, and set up the charging station of marginal highway section and usually have less vehicle to charge or even not have the vehicle, make the charging resource of the charging station of marginal highway section wasted.
Disclosure of Invention
The invention aims to provide a dispatching method, a dispatching system and a dispatching device of energy storage vehicles, which can control the energy storage vehicles parked in the charging stations with smaller pressure state to go to the charging stations with larger pressure state for supporting, so that the charging stations with larger pressure state can support more vehicles for charging, further the pressure state of the charging stations is reduced, the charging experience of vehicle owners is improved, and in addition, the charging resources of the energy storage vehicles of the charging stations with smaller pressure state are effectively utilized.
In order to solve the technical problem, the invention provides a scheduling method of an energy storage vehicle, which comprises the following steps:
the method comprises the steps of obtaining charging station information of each charging station in a current period, wherein the charging station information comprises total power consumption and charging position occupation information of the charging stations;
determining the pressure state of each charging station in the current period according to each piece of charging station information;
determining a first charging station to be supported according to the pressure state of each charging station in the current period;
and controlling each energy storage vehicle to go to the corresponding first charging station, wherein the energy storage vehicle is used for charging the vehicle.
Preferably, when each energy storage vehicle is controlled to go to the corresponding first charging station, the method further includes:
determining the current electric quantity and the current position of the energy storage vehicle;
judging whether the current electric quantity is lower than a first preset electric quantity or not;
if yes, controlling a second charging station closest to the energy storage vehicle in front of the energy storage vehicle to charge the energy storage vehicle based on the current position, and after determining that the self-charging is finished, moving to the corresponding first charging station;
and if not, the user goes to the corresponding first charging station.
Preferably, the controlling the second charging station closest to the energy storage vehicle in front of the energy storage vehicle to charge the energy storage vehicle based on the current position includes:
sending the current position and the current electric quantity of the energy storage vehicle to a first neural network model so as to determine a first running route of the energy storage vehicle, wherein the first neural network model is obtained by training running routes between the current position of the energy storage vehicle and each charging station, and charging time and queuing time of the energy storage vehicle corresponding to the current period of each charging station in advance;
and controlling the energy storage vehicle to go to the second charging station closest to the energy storage vehicle according to the first running route to charge the energy storage vehicle.
Preferably, before controlling a second charging station closest to the energy storage vehicle in front of the energy storage vehicle to charge the energy storage vehicle based on the current position, the method further includes:
and generating a support signal containing the current position and the current electric quantity of the energy storage vehicle and sending the support signal to the second charging station so that the second charging station can determine the information of the energy storage vehicle.
Preferably, before controlling each energy storage vehicle to go to the corresponding first charging station, the method further includes:
acquiring state information of each energy storage vehicle;
judging whether the state information is state information indicating that the energy storage vehicle is idle or not;
if the current state of the energy storage vehicle is not the state information indicating the idleness of the energy storage vehicle, judging that the current state of the energy storage vehicle is an unavailable state;
if the current electric quantity of the energy storage vehicle is the state information indicating that the energy storage vehicle is idle, judging whether the current electric quantity of the energy storage vehicle is larger than a second preset electric quantity;
if the current state of the energy storage vehicle is larger than the second preset electric quantity, judging that the current state of the energy storage vehicle is an available state;
if the current state of the energy storage vehicle is smaller than the second preset electric quantity, judging that the current state of the energy storage vehicle is an unavailable state;
control each energy storage car to go to self corresponding first charging station includes:
and controlling each energy storage vehicle in the available state to go to the corresponding first charging station.
Preferably, when each energy storage vehicle is controlled to go to the corresponding first charging station, the method further includes:
judging whether road congestion exists within a preset distance in front of the current running route of the energy storage vehicle;
and if the road congestion exists, controlling the energy storage vehicle to go to a corresponding first charging station from another driving route which does not have the road congestion within the preset distance ahead.
Preferably, the determining a first charging station to be backed up according to the pressure state of each charging station in the current cycle includes:
determining the current position of each energy storage vehicle;
sending the current position of each energy storage vehicle and the pressure state of each charging station in the current period to a second neural network model so as to determine a second running route of each energy storage vehicle, wherein the second neural network model is obtained by training running routes between the current position of each energy storage vehicle and each charging station and charging station information of each charging station in the current period in advance;
control each energy storage car to go to self corresponding first charging station includes:
and controlling each energy storage vehicle to go to the corresponding first charging station according to the second running route.
Preferably, the second neural network model is a DNN neural network model.
The application also provides a dispatch system of energy storage car, includes:
the charging station information acquisition unit is used for acquiring charging station information of each charging station in a current period, wherein the charging station information comprises total power consumption and charging position occupation information of the charging stations;
the pressure state determining unit is used for determining the pressure state of each charging station in the current period according to each piece of charging station information;
a first charging station determination unit, configured to determine a first charging station to be backed up according to a pressure state of each charging station in the current cycle;
and the energy storage vehicle control unit is used for controlling each energy storage vehicle to go to the corresponding first charging station, and the energy storage vehicle is used for charging the vehicle.
The application also provides a scheduling device of energy storage car, includes:
a memory for storing a computer program;
and the processor is used for realizing the steps of the energy storage vehicle scheduling method when executing the computer program.
The invention provides a dispatching method, a system and a device of an energy storage vehicle, which comprises the steps of firstly obtaining the charging station information of each charging station in the current period, wherein the charging station information comprises the total power consumption of the charging station and the occupation information of the charging position, then determining the pressure state of each charging station in the current period according to the charging station information, determining a first charging station to be supported in the current period according to the pressure state, and finally controlling each energy storage vehicle to go to the corresponding first charging station, wherein the energy storage vehicle is a movable device for charging vehicles, can control the energy storage vehicle parked in the charging station with a smaller pressure state to go to the charging station with a larger pressure state for supporting, so that the charging station with the larger pressure state can support more vehicles for charging, and then alleviate the pressure state of charging station, improve car owner's experience of charging, in addition, the energy storage car charging resource of the less charging station of pressure state has still effectively been utilized.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed in the prior art and the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
Fig. 1 is a flowchart of a scheduling method of an energy storage vehicle provided in the present application;
fig. 2 is a schematic structural diagram of a dispatching system of an energy storage vehicle provided in the present application;
fig. 3 is a schematic structural diagram of a scheduling device of an energy storage vehicle provided in the present application.
Detailed Description
The core of the invention is to provide a dispatching method, a system and a device of energy storage vehicles, which can control the energy storage vehicles parked in the charging stations with smaller pressure state to go to the charging stations with larger pressure state for supporting, so that the charging stations with larger pressure state can support more vehicles for charging, further the pressure state of the charging stations is reduced, the charging experience of vehicle owners is improved, and in addition, the charging resources of the energy storage vehicles of the charging stations with smaller pressure state are effectively utilized.
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, fig. 1 is a flowchart of a scheduling method of an energy storage vehicle provided in the present application, where the method includes:
s11: acquiring charging station information of each charging station in a current period, wherein the charging station information comprises total power consumption and charging position occupation information of the charging station;
in the application, it is considered that in the prior art, charging stations are independent, the charging station system is only a charging station system for a single charging station, and the charging stations cannot support each other, when a certain charging station is in a charging peak, charging positions of some charging stations are often full, and vehicles do not come before to be charged in some charging stations. The charging position occupation information is the charging position occupation information on the charging piles which are arranged in each charging station and used for charging the vehicles, the number of the charging piles in one charging station is fixed, and the position of one charging pile for charging the vehicles is also fixed; the total power consumption is that the total power consumption of the charging station is required to be included in the charging station information because the charging station information includes the total power consumption of the charging station when the vehicles of different vehicle types need different power consumption during charging, and when all the vehicles to be charged need to be charged with large power consumption currently, although there is a free charging position, the charging capability of the charging station is not enough to charge more vehicles.
S12: determining the pressure state of each charging station in the current period according to the information of each charging station;
because the number of the charging piles and the positions of the charging piles for charging the vehicles are fixed, the number of the vehicles in the charging station and the remaining idle positions can be determined according to the charging position occupation information in each charging station, and it can be seen that in one charging station, when the vehicles charged in the charging station are all of the same type, the fewer the vehicles are charged, the more the idle positions are, the smaller the pressure state of the charging station is, and further, when the charging position occupation information is consistent, the lower the total power consumption is, the smaller the pressure state of the charging station is. Based on the charging position occupation information and the total power consumption, the final pressure state of each charging station can be determined. In the determination of the pressure state, the pressure state may be determined by using a DNN (Deep Neural Networks) Neural network model, the DNN neural network model is determined by charging station information and weights of all charging stations in advance, the pressure state z obtained by each charging station finally is sigma wi xi + b, and finally an activation function sigma (z) in the DNN neural network model is added, wherein z is a pressure state of each charging station, wi is a weight corresponding to each charging station, xi is charging station information of each charging station, b is a value representing an average total power consumption level of each charging station calculated from power, the value may be a variance or standard deviation equivalent value determined according to the corresponding total power consumption of the charging station in each historical period, and σ (z) is an activation function of the DNN neural network model itself.
S13: determining a first charging station to be supported according to the pressure state of each charging station in the current period;
after the final pressure state of each charging station is determined, according to the ranking of the pressure state of each charging station, the charging station with the pressure state arranged before a first preset ranking can be determined as the first charging station to be supported, specifically, the preset ranking can be that whether the charging position of each charging station is full or the total power consumption exceeds the charging capacity of the charging station in a sorting mode.
S14: and controlling each energy storage vehicle to go to a corresponding first charging station, wherein the energy storage vehicles are used for charging the vehicles.
After the first charging stations to be supported, that is, which charging stations need to be supported, are determined, the energy storage vehicles are allocated with respective corresponding traveling routes, and the energy storage vehicles are controlled to travel to the first charging stations corresponding to the energy storage vehicles, so that the pressure of the first charging stations is reduced. In order to obtain the optimal running route of each energy storage vehicle, the DNN neural network model is obtained by training the pressure state of each charging station in the current period and the running route between each energy storage vehicle and each charging station in advance, the running route of each energy storage vehicle is calculated by a depth-preferred search traversal algorithm, specifically, the current position of the energy storage vehicle is a, the position of the first charging station corresponding to the energy storage vehicle is b, and the available running route from a to b is recorded as i, i is [1, 2, 3 … i ═ i]The value in the set i is the number corresponding to the available travel routes from a to b, the time spent by the energy storage vehicle when the i-th route goes from a to b is marked as Ti, the set of all available travel routes and unavailable travel routes from a to b of the energy storage vehicle is marked as N, and therefore the time spent by each available travel route from a to b of the energy storage vehicle is firstly calculated, and the shortest time is marked in each Ti
The time is the fastest time when the energy storage vehicle goes from the place a to the place b, the driving route corresponding to the value i is the shortest route from the place a to the place b of the energy storage vehicle, and the depth is preferably searched and traversedThe algorithm is modeled as follows:
it should be noted that Ti may be calculated from the length of the path and the average speed of the energy storage vehicle, and when determining each driving route from a to b of the energy storage vehicle, the driving routes between a to b may be determined according to map software or other software, and some of the routes where there is no accident such as traffic jam or road repair may be determined as available driving routes, and the unavailable driving routes are driving routes where there is traffic jam or road repair.
The invention provides a dispatching method, a system and a device of an energy storage vehicle, which comprises the steps of firstly obtaining the charging station information of each charging station in the current period, wherein the charging station information comprises the total power consumption of the charging station and the occupation information of the charging position, then determining the pressure state of each charging station in the current period according to the charging station information, determining a first charging station to be supported in the current period according to the pressure state, and finally controlling each energy storage vehicle to go to the corresponding first charging station, wherein the energy storage vehicle is a movable device for charging vehicles, can control the energy storage vehicle parked in the charging station with a smaller pressure state to go to the charging station with a larger pressure state for supporting, so that the charging station with the larger pressure state can support more vehicles for charging, and then alleviate the pressure state of charging station, improve car owner's experience of charging, in addition, the energy storage car charging resource of the less charging station of pressure state has still effectively been utilized.
On the basis of the above-described embodiment:
as a preferred embodiment, it is preferable that, while controlling each energy storage vehicle to travel to its corresponding first charging station, the method further includes:
determining the current electric quantity and the current position of the energy storage vehicle;
judging whether the current electric quantity is lower than a first preset electric quantity or not;
if yes, controlling a second charging station closest to the energy storage vehicle in front of the energy storage vehicle to charge the energy storage vehicle based on the current position, and after determining that the self-charging is finished, moving to a corresponding first charging station;
and if not, the user goes to a first charging station corresponding to the user.
In order to enable the energy storage vehicle to smoothly go to the first charging station, in the application, when the energy storage vehicle goes to the corresponding first charging station in the front, the time for actually reaching the first charging station is slower than the ideal arrival time due to various practical emergencies such as traffic jam, traffic lights, pedestrians and the like, because the electric quantity of the energy storage vehicle is always consumed on the road going to the first charging station, when the time for the energy storage vehicle to go to the first charging station is prolonged, the electric quantity consumed by the energy storage vehicle is increased, on the road for the energy storage vehicle to the first charging station, if the current electric quantity of the energy storage vehicle is judged to be lower than the first preset electric quantity, the current electric quantity of the energy storage vehicle is not enough to reach the first charging station, or the residual electric quantity of the energy storage vehicle is not much after the energy storage vehicle reaches the first charging station, and the vehicle which is close to the second charging station closest to the energy storage vehicle needs to be controlled, wherein the current electric quantity of the energy storage vehicle is lower than the first preset electric quantity, so that the energy storage vehicle can be charged to the second charging station closest to the first charging station And the energy storage vehicle is charged in the second charging station until the charging completion condition is met, and then the energy storage vehicle is controlled to go to the first charging station, so that the problem that the energy storage vehicle is anchored after the electric quantity on the road going to the first charging station is exhausted or the residual electric quantity is too little to provide charging service for the vehicles charged before when the energy storage vehicle reaches the first charging station is solved.
As a preferred embodiment, controlling a second charging station closest to the energy storage vehicle in front of the energy storage vehicle to charge the energy storage vehicle based on the current position comprises:
the method comprises the steps that the current position and the current electric quantity of an energy storage vehicle are sent to a first neural network model so as to determine a first running route of the energy storage vehicle, and the first neural network model is obtained by training running routes between the current position of the energy storage vehicle and each charging station, and charging time and queuing time of the energy storage vehicle corresponding to the current period of each charging station in advance;
and controlling a second charging station closest to the energy storage vehicle before the energy storage vehicle to charge the energy storage vehicle according to the first driving route.
In order to realize that the energy storage vehicle controls the energy storage vehicle to go to a nearest second charging station for charging when the current electric quantity is lower than a first preset electric quantity, in the application, the first neural network model may be but is not limited to a first neural network model constructed according to DNN, the first neural network model can determine a charging station nearest to the energy storage vehicle and a running route of the energy storage vehicle to the nearest charging station, it needs to be noted that, considering that too many vehicles which are being charged may occur in each charging station and therefore queuing charging is needed, the queuing time refers to the time from queuing to charging of the energy storage vehicle after the energy storage vehicle arrives at the second charging station in the current period.
Specifically, for example, when there are j charging stations in total, the names of the charging stations are respectively marked as X1 and X2 … Xj, when a first charging station corresponding to the energy storage vehicle is X1, if the current electric quantity is lower than a first preset electric quantity, the energy storage vehicle needs to be controlled to move to other charging stations, at this time, the energy storage vehicle moves to the charging stations from the current position and has i traveling routes with different quantities, respectively, different traveling routes of the same charging station are respectively marked as Xj-1 and Xj-2 … Xj-i, the time required for the energy storage vehicle to move to the corresponding charging station from the different traveling routes is Tj, the time required for the energy storage vehicle to move to the charging station according to the ith traveling route is marked as Tj-Xj-i, the queuing time of the energy storage vehicle in the current period of the Xj charging station is Tj-wait, the charging time is Tj-charge, the traveling time for the energy storage vehicle to move to the charging station from the Xj charging station again is T-X1 as T-X1, at this time, the first neural network model can adopt a depth-preferred search algorithm to determine the time of the energy storage vehicle from the front to the second charging station to charge the energy storage vehicle to the first charging station and then to the second charging station according to the parameters, the time is marked as T-total, the T-total is (Tj-Xj-i) + (Tj-wait) + (Tj-charge) + (T-X1), the time represents that the energy storage vehicle starts from the current position and then charges the energy storage vehicle after arriving at the Xj charging station, the energy storage vehicle goes to the X1 charging station after being charged, the time used when the energy storage vehicle arrives at the X1 charging station is determined, the shortest time is determined in each T-total, the shortest time is min-T-total, and which charging station the energy storage vehicle needs to take as the second charging station can be determined according to the min-T-total corresponding to each energy storage vehicle.
In addition, considering that the queuing times of the charging stations in the periods are different, a queuing model or a multilevel queuing model can be preset to determine the queuing times of the charging stations in the periods, so that the first neural network model can determine the queuing times, and the application does not limit the queuing model of the staff specifically.
As a preferred embodiment, before controlling the energy storage vehicle to charge itself at the second charging station closest to the energy storage vehicle in front of the energy storage vehicle based on the current position, the method further includes:
and generating a support signal containing the current position and the current electric quantity of the energy storage vehicle and sending the support signal to the second charging station so that the second charging station can determine the information of the energy storage vehicle.
In order to improve the charging efficiency of the energy storage vehicle, in the application, when the current electric quantity of the energy storage vehicle is less than a first preset electric quantity, the energy storage vehicle is controlled to go to a second charging station according to a first driving route to charge the energy storage vehicle, in order to charge the energy storage vehicle in time when the energy storage vehicle arrives at the second charging station, after the current electric quantity of the energy storage vehicle is determined to be less than the first preset electric quantity, a support signal containing the current position and the current electric quantity of the energy storage vehicle is sent to the second charging station, so that the second charging station determines the residual electric quantity of the energy storage vehicle and the time required by the energy storage vehicle to arrive at the second charging station, further, a worker in the second charging station prepares a position for charging the energy storage vehicle in advance according to the residual electric quantity of the energy storage vehicle and the time for arriving at the second charging station, and the energy storage vehicle can be charged in time after arriving at the second charging station, the efficiency of charging the energy storage vehicle is improved; in addition, when the energy storage vehicle runs out of electricity or is in a situation of being broken down due to other reasons, the current position of the energy storage vehicle is sent to the second charging station, and workers in the second charging station can go to the energy storage vehicle to support the energy storage vehicle conveniently.
As a preferred embodiment, before controlling each energy storage vehicle to go to its corresponding first charging station, the method further includes:
acquiring state information of each energy storage vehicle;
judging whether the state information is the state information indicating that the energy storage vehicle is idle or not;
if the current state of the energy storage vehicle is not the state information indicating the idleness of the energy storage vehicle, judging that the current state of the energy storage vehicle is an unavailable state;
if the current electric quantity of the energy storage vehicle is the state information indicating that the energy storage vehicle is idle, judging whether the current electric quantity of the energy storage vehicle is larger than a second preset electric quantity;
if the current state of the energy storage vehicle is larger than the second preset electric quantity, judging that the current state of the energy storage vehicle is a usable state;
if the current state of the energy storage vehicle is smaller than the second preset electric quantity, judging that the current state of the energy storage vehicle is an unavailable state;
control each energy storage car and go to the first charging station that self corresponds, include:
and controlling each energy storage vehicle in the available state to go to the corresponding first charging station.
In order to save workload, in the application, it is considered that there are some energy storage vehicles which do not need to be scheduled in the same period, for example, when the pressure state of the charging station a in the current period is large, the energy storage vehicle parked in the charging station a does not need to be scheduled, but the energy storage vehicle is continuously parked in the charging station a, or the energy storage vehicle fails or is being charged, the energy storage vehicle does not need to be scheduled. The current state of the energy storage vehicle is divided into an available state and an unavailable state, when the pressure state of the charging station where the energy storage vehicle is located is small in the current period and the energy storage vehicle is not abnormal, the current state of the energy storage vehicle can be determined to be the available state, and when the pressure state of the charging station where the energy storage vehicle is located is large in the current period or the energy storage vehicle is abnormal, the current state of the energy storage vehicle is determined to be the unavailable state. When the energy storage vehicle is controlled to move to the corresponding first charging station, the energy storage vehicle in the available state is only required to be controlled, the energy storage vehicle in the unavailable state is not required to be controlled, and the workload of controlling the energy storage vehicle is saved.
In addition, considering that the states of the energy storage vehicle are various, for example, the abnormality of the energy storage vehicle may be that the energy storage vehicle is being maintained, is being moved, has a fault or is being charged, and the states are all unavailable states, and the state information indicating that the energy storage vehicle is idle refers to state information when the energy storage vehicle is not abnormal, specifically to states that the energy storage vehicle is not being maintained, is not being moved, and has no fault or the like, but at this time, it is considered that the electric quantity stored in the energy storage vehicle is limited, and the energy storage vehicle consumes the electric quantity while driving, in order to avoid that the remaining electric quantity of the energy storage vehicle after the energy storage vehicle reaches the first charging station is insufficient to charge the vehicle, and even the electric quantity of the energy storage vehicle is exhausted during driving, after determining that the state information of the energy storage vehicle is the state information indicating that the energy storage vehicle is idle, it is necessary to determine whether the current electric quantity of the energy storage vehicle is greater than a second preset electric quantity, when the current electric quantity of the energy storage vehicle is larger than the second preset electric quantity, the current state of the energy storage vehicle is judged to be an available state, and the energy storage vehicle with insufficient electric quantity is prevented from being dispatched.
As a preferred embodiment, when each energy storage vehicle is controlled to go to its corresponding first charging station, the method further includes:
judging whether road congestion exists within a preset distance in front of a current running route of the energy storage vehicle;
and if the road congestion exists, controlling the energy storage vehicle to go to the corresponding first charging station from another running route which does not have the road congestion within the preset distance in front.
In order to enable the energy storage vehicle to reach the first charging station corresponding to the energy storage vehicle more quickly, in the application, considering that the energy storage vehicle may encounter a sudden road congestion situation on the road going to the first charging station, for example, a sudden road maintenance or a sudden traffic jam occurs on the original running route of the energy storage vehicle, so that the energy storage vehicle may be blocked on the running route, and thus cannot go to the first charging station in time, in order to avoid such a situation, on the road going to the first charging station corresponding to the energy storage vehicle, it may be determined whether there is a road congestion situation in a preset distance in front of the current running road of the energy storage vehicle, specifically, it may be determined according to map software that the situation of each road is present, or it may be determined according to a camera arranged on the energy storage vehicle, for example, when the situation of the current running route of the energy storage vehicle on the map software suddenly changes from smooth congestion to congestion, according to the change of the map software, the condition that the road congestion exists in the preset distance in front of the current running route can be known, and the method for judging whether the road congestion exists in the running route is not limited.
After determining that the current running route of the energy storage vehicle has a road congestion, the energy storage vehicle is controlled to go to a corresponding first charging station from the running route without the road congestion, for example, the current position of the energy storage vehicle is determined first, then the current position of the energy storage vehicle is sent to a pre-trained neural network model, a new route for the energy storage vehicle to go to the corresponding first charging station is calculated through the neural network model, when the energy storage vehicle runs to the position X along the route a and the energy storage vehicle runs to the position a, if it is determined that a road congestion exists in 500 meters in front of the route a at the moment, the neural network model determines a running route without the road congestion, namely a route B, from the position X to the position a of the energy storage vehicle, namely a route B, of the energy storage vehicle from the position X to the charging station a, namely a route B of the route without the road congestion exists in 500 meters, and then the energy storage vehicle is controlled to go to the charging station A according to the route B, so that the energy storage vehicle can avoid the condition of road congestion and further can reach the charging station A more quickly.
In addition, the neural network model may be specifically a multiplexing first neural network model, or may be a new neural network model obtained by training in advance the running routes between the current position of the energy storage vehicle and each charging station and the congestion information of each running route, which is not limited in the present application.
As a preferred embodiment, determining a first charging station to be backed up according to the pressure state of each charging station in the current cycle includes:
determining the current position of each energy storage vehicle;
sending the current position of each energy storage vehicle and the pressure state of each charging station in the current period to a second neural network model so as to determine a second running route of each energy storage vehicle, wherein the second neural network model is obtained by training the running routes between the current position of each energy storage vehicle and each charging station and the charging station information of each charging station in the current period in advance;
control each energy storage car and go to the first charging station that self corresponds, include:
and controlling each energy storage vehicle to go to the corresponding first charging station according to the second running route.
Considering that the energy storage vehicle needs a period of time to move to a corresponding first charging station, in a real situation, the distance between the two charging stations is usually long, and the energy storage vehicle can encounter various situations to cause late arrival during running, in order to enable the energy storage vehicle to reach the corresponding first charging station in time, in the application, the total power consumption and the charging position occupation information of each charging station at different time points can be collected in advance, the second neural network model predicts the possible pressure states of each charging station in different time periods according to the total power consumption and the charging position occupation information of historical charging stations, the second neural network model can also obtain the time and the route of the energy storage vehicle to each charging station according to the historical running route between the current position of the energy storage vehicle and each charging station, and then the second neural network model can control the corresponding second charging station before the energy storage vehicle in advance according to the predicted pressure states of each charging station after the preset time period A charging station. For example, when the cycle interval is 4 hours, the charging station information of each charging station is acquired at 0 point time, 4 point time … 16 point time … 20 point time and each charging station, meanwhile, a charging station information acquisition system is installed in each charging station, so that the charging station information of each charging station at the whole point time of each hour is acquired in advance to be learned by a second neural network model, the second neural network model can determine the electricity consumption peak period, the electricity consumption valley period and the like of each charging station, if the pressure state of the charging station A at 16 points is known to be 30% through learning by the second neural network model, but the pressure state of the charging station A at 17 points and the pressure state of the charging station at 18 points are both 100%, although the pressure state of the charging station A at the moment is known to be smaller when the charging station information of the charging station A is acquired at 16 points, the pressure state of the charging station A at 17 points and 18 points of the current cycle is the maximum, after learning, the second neural network model can predict that the pressure state of the charging station A is maximum at 17 and 18 points, so that the corresponding energy storage vehicle is controlled to move to the charging station A at 16 points, so that the energy storage vehicle can support the charging station A in advance.
In addition, in order to reduce the load of the neural network model, two neural network models can be set as a second neural network model together, wherein one neural network model is used for determining the pressure state of each charging station in the current period, and the model is obtained by training the charging station information of each charging station in advance; and the other neural network model is used for determining the running route of each energy storage vehicle according to the pressure state and the position of each energy storage vehicle, and is obtained by training the pressure state of each charging station in the current period and the running route between the current position of each energy storage vehicle and each charging station in advance.
As a preferred embodiment, the second neural network model is a DNN neural network model.
The DNN neural network model is also called MLP (Multi-Layer perceptron), and the neural network Layer inside the DNN is divided into three layers, i.e., an input Layer, a hidden Layer and an output Layer, where the first Layer of the DNN is usually the input Layer. The last layer is an output layer, the middle layers are hidden layers, the DNN layers are fully connected, namely any neuron on the ith layer is connected with any neuron on the (i + 1) th layer, and the DNN can be input and output by more than one layer, so that data such as a driving route between each energy storage vehicle and each charging station and the pressure state of each charging station in the current period can be flexibly classified, regressed, clustered and the like.
Referring to fig. 2, fig. 2 is a schematic structural diagram of a dispatching system of an energy storage vehicle provided in the present application, where the system includes:
a charging station information acquiring unit 11, configured to acquire charging station information of each charging station in a current period, where the charging station information includes total power consumption and charging position occupation information of the charging station;
a pressure state determination unit 12, configured to determine a pressure state of each charging station in the current cycle according to each charging station information;
a first charging station determination unit 13 configured to determine a first charging station to be backed up according to a pressure state of each charging station in a current cycle;
and the energy storage vehicle control unit 14 is used for controlling each energy storage vehicle to go to the corresponding first charging station, and the energy storage vehicle is used for charging the vehicle.
For detailed description of the energy storage vehicle dispatching system provided in the present application, please refer to the above-mentioned embodiment of the energy storage vehicle dispatching method, which is not described herein again.
Referring to fig. 3, fig. 3 is a schematic structural diagram of a dispatching device of an energy storage vehicle provided in the present application, the device includes:
a memory 21 for storing a computer program;
and the processor 22 is used for implementing the steps of the dispatching method of the energy storage vehicle when executing the computer program.
For detailed description of the scheduling device for energy storage vehicles provided in the present application, please refer to the above embodiments of the scheduling method for energy storage vehicles, which are not described herein again.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
It is further noted that, in the present specification, relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
Claims (10)
1. The dispatching method of the energy storage vehicle is characterized by comprising the following steps:
the method comprises the steps of obtaining charging station information of each charging station in a current period, wherein the charging station information comprises total power consumption and charging position occupation information of the charging stations;
determining the pressure state of each charging station in the current period according to each piece of charging station information;
determining a first charging station to be supported according to the pressure state of each charging station in the current period;
and controlling each energy storage vehicle to go to the corresponding first charging station, wherein the energy storage vehicle is used for charging the vehicle.
2. The energy storage vehicle dispatching method according to claim 1, wherein when each energy storage vehicle is controlled to travel to the corresponding first charging station, the method further comprises:
determining the current electric quantity and the current position of the energy storage vehicle;
judging whether the current electric quantity is lower than a first preset electric quantity or not;
if yes, controlling a second charging station closest to the energy storage vehicle in front of the energy storage vehicle to charge the energy storage vehicle based on the current position, and after determining that the self-charging is finished, moving to the corresponding first charging station;
and if not, the user goes to the corresponding first charging station.
3. The energy storage vehicle dispatching method of claim 2, wherein controlling a second charging station in front of the energy storage vehicle, which is closest to the energy storage vehicle, to charge the energy storage vehicle based on the current position comprises:
sending the current position and the current electric quantity of the energy storage vehicle to a first neural network model so as to determine a first running route of the energy storage vehicle, wherein the first neural network model is obtained by training running routes between the current position of the energy storage vehicle and each charging station, and charging time and queuing time of the energy storage vehicle corresponding to the current period of each charging station in advance;
and controlling the energy storage vehicle to go to the second charging station closest to the energy storage vehicle according to the first running route to charge the energy storage vehicle.
4. The energy storage vehicle dispatching method according to claim 2, wherein before controlling the energy storage vehicle to charge itself at a second charging station closest to the energy storage vehicle in front of the energy storage vehicle based on the current position, the method further comprises:
and generating a support signal containing the current position and the current electric quantity of the energy storage vehicle and sending the support signal to the second charging station so that the second charging station can determine the information of the energy storage vehicle.
5. The energy storage vehicle dispatching method according to claim 1, wherein before controlling each energy storage vehicle to go to the corresponding first charging station, the method further comprises:
acquiring state information of each energy storage vehicle;
judging whether the state information is state information indicating that the energy storage vehicle is idle or not;
if the current state of the energy storage vehicle is not the state information indicating the idleness of the energy storage vehicle, judging that the current state of the energy storage vehicle is an unavailable state;
if the current electric quantity of the energy storage vehicle is the state information indicating that the energy storage vehicle is idle, judging whether the current electric quantity of the energy storage vehicle is larger than a second preset electric quantity;
if the current state of the energy storage vehicle is larger than the second preset electric quantity, judging that the current state of the energy storage vehicle is an available state;
if the current state of the energy storage vehicle is smaller than the second preset electric quantity, judging that the current state of the energy storage vehicle is an unavailable state;
control each energy storage car to go to self corresponding first charging station includes:
and controlling each energy storage vehicle in the available state to go to the corresponding first charging station.
6. The energy storage vehicle dispatching method according to claim 1, wherein when each energy storage vehicle is controlled to travel to the corresponding first charging station, the method further comprises:
judging whether road congestion exists within a preset distance in front of the current running route of the energy storage vehicle;
and if the road congestion exists, controlling the energy storage vehicle to go to a corresponding first charging station from another driving route which does not have the road congestion within the preset distance ahead.
7. The dispatching method of energy storage vehicles according to any one of claims 1 to 6, wherein determining the first charging station to be supported according to the pressure state of each charging station in the current period comprises:
determining the current position of each energy storage vehicle;
sending the current position of each energy storage vehicle and the pressure state of each charging station in the current period to a second neural network model so as to determine a second running route of each energy storage vehicle, wherein the second neural network model is obtained by training running routes between the current position of each energy storage vehicle and each charging station and charging station information of each charging station in the current period in advance;
control each energy storage car to go to self corresponding first charging station includes:
and controlling each energy storage vehicle to go to the corresponding first charging station according to the second running route.
8. The method for dispatching energy storage vehicles according to claim 7, wherein the second neural network model is a DNN neural network model.
9. A dispatch system of an energy storage vehicle, comprising:
the charging station information acquisition unit is used for acquiring charging station information of each charging station in a current period, wherein the charging station information comprises total power consumption and charging position occupation information of the charging stations;
the pressure state determining unit is used for determining the pressure state of each charging station in the current period according to each piece of charging station information;
a first charging station determination unit, configured to determine a first charging station to be backed up according to a pressure state of each charging station in the current cycle;
and the energy storage vehicle control unit is used for controlling each energy storage vehicle to go to the corresponding first charging station, and the energy storage vehicle is used for charging the vehicle.
10. The utility model provides a scheduling device of energy storage car which characterized in that includes:
a memory for storing a computer program;
a processor for implementing the steps of the method of dispatching an energy storage vehicle as claimed in any one of claims 1 to 8 when executing the computer program.
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