CN110271448B - Charging scheduling method and system for charging station and charging station - Google Patents

Charging scheduling method and system for charging station and charging station Download PDF

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CN110271448B
CN110271448B CN201910497995.XA CN201910497995A CN110271448B CN 110271448 B CN110271448 B CN 110271448B CN 201910497995 A CN201910497995 A CN 201910497995A CN 110271448 B CN110271448 B CN 110271448B
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CN110271448A (en
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杨再跃
凡红林
陈士博
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Southwest University of Science and Technology
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L53/00—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles
    • B60L53/60—Monitoring or controlling charging stations
    • B60L53/62—Monitoring or controlling charging stations in response to charging parameters, e.g. current, voltage or electrical charge
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/60—Other road transportation technologies with climate change mitigation effect
    • Y02T10/70—Energy storage systems for electromobility, e.g. batteries
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/60—Other road transportation technologies with climate change mitigation effect
    • Y02T10/7072—Electromobility specific charging systems or methods for batteries, ultracapacitors, supercapacitors or double-layer capacitors
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y02T90/10—Technologies relating to charging of electric vehicles
    • Y02T90/12—Electric charging stations

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  • Power Engineering (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
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  • Electric Propulsion And Braking For Vehicles (AREA)

Abstract

The application is suitable for the technical field of new energy, and the embodiment of the application provides a charging scheduling method, a charging scheduling system and a charging station of the charging station, wherein the method comprises the following steps: acquiring the required charging amount, the starting charging time, the ending charging time, the maximum charging power and the rated power of a transformer of the charged electric automobile; acquiring peak power electricity prices in a settlement period and time-of-use electricity prices corresponding to different time slots; acquiring charging demand power of different electric vehicles in different time slots according to the demand charging amount, the starting charging time, the ending charging time, the maximum charging power and the rated power of a transformer in the charging station by combining the peak power price and the time-of-use price; according to the required charging power, the power supply output is carried out, reasonable charging distribution of the electric automobile is achieved, and the charging efficiency and the charging safety of the charging station are improved.

Description

Charging scheduling method and system for charging station and charging station
Technical Field
The application belongs to the technical field of new energy, and particularly relates to a charging scheduling method, a charging scheduling system and a charging station of the charging station.
Background
Today that environmental protection and resource protection received attention increasingly, as novel vehicle, electric automobile compares fuel automobile not only can reduce the oil energy resource consumption and can also realize zero pollutant discharge, and electric automobile replaces fuel automobile gradually becomes a trend. However, as electric vehicles are developed, their charging needs are increasing. In the present situation, after the electric vehicle reaches the charging station, the electric vehicle starts to be charged at the maximum charging power until the charging station is fully charged, and the charging strategy is used by most domestic charging stations.
The charging station is used as a main place for charging the electric vehicle, and the charging station is subjected to disordered charging behavior images of the existing electric vehicle, so that the power load of the charging station is high and large in fluctuation. The existing charging strategy not only influences the stability of the operation of a power grid, but also increases the operation cost and the operation efficiency of the charging station, reduces the safety of the charging station and influences the development of the electric automobile industry.
Disclosure of Invention
In view of this, embodiments of the present application provide a charging scheduling method for a charging station, a charging scheduling system, and a charging station, so as to solve the problems that the existing charging strategy not only affects the stability of power grid operation, but also increases the operation cost and operation efficiency of the charging station and reduces the safety of the charging station.
A first aspect of an embodiment of the present application provides a charging scheduling method for a charging station, including:
acquiring the required charging amount, the starting charging time, the ending charging time, the maximum charging power and the rated power of a transformer in a charging station of a charged electric vehicle;
acquiring a peak power electricity price and time-of-use electricity prices corresponding to different time slots in a settlement period, wherein the settlement period is divided into a plurality of time slots, and different time slots correspond to different charging starting time and different charging ending time of the electric vehicle;
acquiring charging demand power of different electric vehicles in different time slots according to the demand charging amount, the charging starting time, the charging ending time, the maximum charging power and the rated power of a transformer in the charging station in combination with the peak power price and the time-of-use price;
and performing power supply output according to the charging required power.
A second aspect of the embodiments of the present application provides a charging scheduling system, including:
the first acquisition module is used for acquiring the required charging amount, the charging starting time, the charging ending time, the maximum charging power and the rated power of a transformer in a charging station of the charged electric automobile;
the second acquisition module is used for acquiring peak power electricity prices in a settlement period and time-of-use electricity prices corresponding to different time slots, wherein one settlement period is divided into a plurality of time slots, and different time slots correspond to different time slots from the charging starting time to the charging ending time of different electric vehicles;
a third obtaining module, configured to obtain, according to the required charging amount, the start charging time, the end charging time, the maximum charging power, and a rated power of a transformer in the charging station, and in combination with the peak power price and the time-of-use price, charging required powers of different electric vehicles in different time slots;
and the power supply output module is used for carrying out power supply output according to the charging demand power.
A third aspect of embodiments of the present application provides a charging station, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the steps of the method according to the first aspect when executing the computer program.
A fourth aspect of embodiments of the present application provides a computer-readable storage medium, in which a computer program is stored, which, when executed by a processor, performs the steps of the method according to the first aspect.
A fifth aspect of the application provides a computer program product comprising a computer program which, when executed by one or more processors, performs the steps of the method as described in the first aspect above.
Therefore, according to the embodiment of the application, the required charging amount, the charging start time, the charging end time, the maximum charging power of the charged electric vehicle and the rated power of the transformer in the charging station are obtained, the peak power electricity price in the settlement period and the time-of-use electricity prices corresponding to different time slots are combined, the charging required powers of different electric vehicles in different time slots are calculated, power supply output is performed, charging scheduling is performed according to the charging requirements of different electric vehicles and the time slots corresponding to different charging times, reasonable charging distribution of the electric vehicles is achieved, the charging efficiency and the charging safety of the charging station can be improved, and the satisfaction degree of users can be increased.
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Fig. 1 is a first flowchart of a charging scheduling method for a charging station according to an embodiment of the present disclosure;
fig. 2 is a second flowchart of a charging scheduling method for a charging station according to an embodiment of the present disclosure;
fig. 3 is a structural diagram of a charging scheduling system of a charging station according to an embodiment of the present disclosure;
fig. 4 is a structural diagram of a charging station according to an embodiment of the present disclosure.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.
In order to explain the technical solution described in the present application, the following description will be given by way of specific examples.
Referring to fig. 1, fig. 1 is a first flowchart of a charging scheduling method for a charging station according to an embodiment of the present disclosure. As shown in fig. 1, a charging scheduling method for a charging station includes the following steps:
step 101, acquiring a required charging amount, a charging start time, a charging end time, a maximum charging power and a rated power of a transformer in a charging station of a charged electric vehicle.
The charged electric vehicle is the electric vehicle charged in the current charging station, and the number of the charged electric vehicles is at least one. When the electric vehicle is charged to the charging station, the charging requirement of the electric vehicle is submitted. In this step, the required charging amount, the charging start time, and the charging end time of the electric vehicle may be obtained based on the charging requirement submitted by the electric vehicle.
The charging starting time is the time for starting charging after the electric vehicle is in circuit connection with the charging station. The end charging time is the time for filling the required charging amount of the electric vehicle. The ending charging time can be calculated according to a required charging amount in a charging demand submitted by the electric vehicle.
After the electric vehicle is connected with the charging station, the charging station can detect the maximum charging power of the current electric vehicle. The rated power of the transformer in the charging station may indicate the maximum possible power output capability of the charging station within a safe range.
Wherein, this electric automobile that charges can include: all electric vehicles in one electricity consumption settlement period. Or all electric vehicles currently receiving charging in the charging station. Specific charging statistical objects can be determined according to different statistical periods.
Step 102, obtaining the peak power electricity price in a settlement period and the time-of-use electricity prices corresponding to different time slots.
And the settlement period is divided into a plurality of time slots, and different time slots are corresponding from the charging starting time to the charging ending time of the electric automobile.
Specifically, the one settlement period is one period, for example, one month, during which the power grid settles the electricity consumption of the charging station. The time length of each of the time slots divided by one settlement period may be equal and fixed, for example, 15 minutes. The actual division may be performed according to specific requirements, and is not specifically limited herein.
After the charging start time and the charging end time of one electric vehicle are determined, the time slots in one calculation cycle are divided to obtain corresponding time slots from the charging start time to the charging end time of different electric vehicles. The peak power electricity price and the time-of-use electricity price in the settlement period are both the expense information formulated and published by the power grid.
In order to reduce the high-load and highly-fluctuating electricity consumption units such as charging stations, the power grid charges the charging stations according to a special charging mode, namely, in addition to charging the charging stations according to the time-of-use electricity price (peak-valley electricity price) according to the electricity consumption time, in order to further suppress the possibility of occurrence of peak load of the charging stations, a penalty fee is charged for the maximum total charging power of the charging stations in a settlement period (for example, one month). Here, the peak power electricity rate in one settlement period is referred to as the penalty fee.
And 103, acquiring the charging demand power of different electric vehicles in different time slots according to the demand charging amount, the charging starting time, the charging ending time, the maximum charging power and the rated power of the transformer in the charging station in combination with the peak power price and the time-of-use price.
The charging demand power can be understood as the power to be supplied for charging the electric automobile by the charging station, and the charging demand power of different electric automobiles in different time slots is calculated so as to carry out charging scheduling on different electric automobiles in different time slots, and reasonable charging supply is carried out on the premise of meeting the charging demand of the electric automobiles.
The implementation process of the step is related to the content contained in the charged electric automobile. Specifically, as a preferred embodiment, wherein, if the charged electric vehicle includes: all electric vehicles in one electricity consumption settlement period.
Correspondingly, the acquiring charging demand power of different electric vehicles in different time slots according to the demanded charging amount, the start charging time, the end charging time, the maximum charging power and the rated power of the transformer in the charging station in combination with the peak power price and the time-of-use price includes:
the set of all time slots divided by one electricity consumption settlement period is recorded as
Figure BDA0002089269540000051
The set of all the electric vehicles charged in one electricity consumption settlement period is
Figure BDA0002089269540000052
Suppose that within a settlement period, there is
Figure BDA0002089269540000053
The vehicles are charged to the charging station and received, the charged electric vehicles are numbered according to the received sequence, and the charged electric vehicles are sequenced to obtain the set of all the electric vehicles charged in one electricity consumption settlement period as
Figure BDA0002089269540000054
Meanwhile, each time slot divided in a settlement period is numbered according to the time sequence, and the set of all electric vehicles charged in the electricity utilization settlement period is obtained as
Figure BDA0002089269540000055
For an electric vehicle, the charging power may not be 0 and its maximum charging power cannot be exceeded only when it is at a charging station. Therefore, the charging power of the electric vehicle satisfies the following constraints:
Figure BDA0002089269540000061
Figure BDA0002089269540000062
in the formula (I), the compound is shown in the specification,
Figure BDA0002089269540000063
-charging power (kW) of the electric vehicle i at time slot t;
Figure BDA0002089269540000064
-maximum charging power (kW) of electric car i;
ai-start charging time of electric vehicle i;
di-end charge time of electric vehicle i;
when t is a value belonging to
Figure BDA0002089269540000065
Do not belong to the set [ a ]i,di]In the case of (a) in (b),
Figure BDA0002089269540000066
since the charging demand of the electric vehicle must be completed before the electric vehicle leaves the charging station, the charging power of the electric vehicle satisfies the following constraints:
Figure BDA0002089269540000067
in the formula (I), the compound is shown in the specification,ei-required charge (kWh) of the electric vehicle i.
As shown in fig. 1, all electric vehicles in the charging station are connected to the same transformer that supplies power to the charging station. The sum of the loads of all electric vehicles in the charging station should not exceed the rated power of the transformer at any time, i.e.:
Figure BDA0002089269540000068
the price of electricity in the time slot t is c when scoring in one settlement periodtTo further reduce the impact of the charging station on the grid and increase the stability of the charging, the price charged for the peak power of the charging station in one settlement period is α yuan/kW. where ctAnd α are published in advance by the grid, known and fixed to the charging stations, the optimization problem of minimizing the total charging cost of the charging stations, given the certainty that the charging tasks of the electric vehicles received by each charging station are guaranteed to be completed, is as follows:
Figure BDA0002089269540000069
note the book
Figure BDA00020892695400000610
Under the condition that the charging demand information of all the electric vehicles in the whole settlement period is known, the optimization formula (4) can obtain a scheduling scheme x with global optimal cost.
Namely, the charging demand power x of different electric vehicles in different time slots is obtained according to the following constraint conditions:
Figure BDA0002089269540000071
Figure BDA0002089269540000072
Figure BDA0002089269540000073
Figure BDA0002089269540000074
Figure BDA0002089269540000075
wherein the content of the first and second substances,
Figure BDA0002089269540000076
Figure BDA0002089269540000077
for the charging power of the electric vehicle i in the time slot t,
Figure BDA0002089269540000078
the maximum charging power of the electric automobile i is obtained; a isiStarting charging time for the electric automobile i; diThe charging ending time of the electric automobile i is obtained; e.g. of the typeiThe required charge quantity of the electric automobile i is obtained; p is the rated power of the transformer in the charging station; c. CtThe time-of-use electricity price corresponding to the time slot t is α, which is the peak power electricity price.
However, in the actual charging station operation environment, since we do not know the charging requirement of the future electric vehicle at any time, and the maximum peak power is not before the end of the settlement period in a settlement period, and it is difficult to know the specific value, the optimization condition (4) can be applied to the electricity optimization of all electric vehicles at the end of the electricity settlement period.
Thus, as a further preferred embodiment, a simple but effective and easy to implement online optimization solution is provided.
Specifically, the charged electric vehicle may include: all electric vehicles currently receiving charging in the charging station.
Correspondingly, the acquiring charging demand power of different electric vehicles in different time slots according to the demand charging amount, the start charging time, the end charging time, the maximum charging power and the rated power of a transformer in the charging station, in combination with the peak power price and the time-of-use price, includes:
for convenience of exposition, definitions
Figure BDA0002089269540000079
The set of electric vehicles charged at the charging station for the current time slot t,
Figure BDA00020892695400000710
and a sliding window is used for covering all the corresponding time slots from the current time to the target charging ending time along with the time sliding.
For example, as shown in fig. 2, assuming that the charging station currently has only three electric vehicles charged, then
Figure BDA0002089269540000081
In sliding window technology, we only consider electric vehicles in the current charging station
Figure BDA0002089269540000082
And continuously update the charging information of the electric vehicle as time goes on, and
Figure BDA0002089269540000083
and
Figure BDA0002089269540000084
the information of (1).
As can be seen from the optimization condition (4) in the foregoing embodiment, the maximum peak power in one settlement period is an important component of the charging station cost. The maximum charging power in a settlement period is related to the charging information of the whole settlement period and is coupled with each time slot in the whole settlement period. Normally, the maximum peak power within a settlement period will not be too fluctuating for a long period of time and is easily analyzed from historical data. By passingPredicted maximum peak power v over the entire settlement periodpdAnd a maximum peak power v of the time slot from the beginning of a settlement period to the present time slotpvThe problems existing in the foregoing embodiments can be solved.
Thus, a new optimization procedure is used, which enables the new optimization procedure to automatically update the maximum peak power v generated up to now at the beginning of a settlement periodpvWith predicted maximum peak power v of one settlement periodpdMaximum value v between0. The constraint formula of the transformed optimization problem is as follows:
Figure BDA0002089269540000085
in the formula, v0-maximum charging power at the beginning of the settlement period to the present charging station and the maximum value (kW), i.e. v, of the predicted maximum charging power of the charging stationo＝max{vpv,vpd}；
v-in a time window
Figure BDA0002089269540000086
Maximum charging power and v of internal charging station0Maximum of (kW).
When t is a value belonging to
Figure BDA0002089269540000087
Do not belong to the set [ a ]i,di]In the case of (a) in (b),
Figure BDA0002089269540000088
along with the movement of the sliding window pane, if a new electric vehicle enters a charging station for charging, the optimization problem is solved again according to the current electric vehicle charging demand information set.
Wherein, in each process of solving the optimization problem, v can be converted into0Considered as a constant.
That is, the set of all time slots corresponding to the current time to the target end charging time is recorded as
Figure BDA0002089269540000091
The target charging ending time is the latest charging ending time in the charging ending time of at least one electric automobile;
recording the current time slot t, wherein the set of all electric vehicles receiving charging in the charging station is
Figure BDA0002089269540000092
Acquiring the charging demand power x of different electric vehicles in different time slots according to the following constraint conditions:
Figure BDA0002089269540000093
Figure BDA0002089269540000094
Figure BDA0002089269540000095
Figure BDA0002089269540000096
v0≤v
Figure BDA0002089269540000097
Figure BDA0002089269540000098
wherein the content of the first and second substances,
Figure BDA0002089269540000099
Figure BDA00020892695400000910
charging power of the electric automobile i in a time slot t;
Figure BDA00020892695400000911
the maximum charging power of the electric automobile i is obtained; a isiStarting charging time for the electric automobile i; diThe charging ending time of the electric automobile i is obtained; e.g. of the typeiThe required charge quantity of the electric automobile i is obtained; p is the rated power of the transformer in the charging station; v. ofo＝max{vpv,vpd}，vpvMaximum peak power, v, generated by the charging station from the starting time of a settlement period to the current timepdIs the predicted maximum peak power of the charging station in one settlement period; v is at
Figure BDA00020892695400000912
Maximum charging power and v of the charging station0Maximum value of (1); c. CtTime slot t corresponds to the time-of-use electricity price, and α is the peak power electricity price.
And 104, performing power supply output according to the charging required power.
The charging demand power is the calculated charging demand power of different electric vehicles in different time slots. And according to the calculation result, power supply output is carried out, so that charging scheduling is realized according to the charging requirements of different electric vehicles and time slots corresponding to different charging times, and reasonable charging distribution of the electric vehicles is realized.
Further, as an optional implementation manner, wherein the step 104 performs power supply output according to the charging demand power, includes:
acquiring the total load of the charging station in the time slot t according to the charging required power of the electric vehicle in different time slots
Figure BDA0002089269540000101
When power supply output is carried out, in addition to the charging scheduling of the electric vehicles in different time slots, specific charging arrangement of power supply output is carried out by considering the maximum charging demand power corresponding to different electric vehicles in the optimal solution, so as to obtain a scheduling strategy capable of improving the time efficiency of the charging station.
In particular, z is definedtThe total load of the charging station in the time slot t;
Figure BDA0002089269540000102
wherein
Figure BDA0002089269540000103
If the value of the optimal charging power of the electric vehicle i for the charging station in the time slot t is obtained by solving the constraint formula (5), then
Figure BDA0002089269540000104
Is prepared by reacting with
Figure BDA0002089269540000105
And (4) the optimal total load of the corresponding charging station in the time slot t.
It is worth noting that the cost of the charging station is only equal to ztRelating, i.e. constraining the value of equation (5) to z onlytIt is related. Therefore, for the constraint equation (5), the charging power of each electric vehicle therein
Figure BDA0002089269540000106
There may be a plurality of different solutions. As shown in FIG. 3, assume that there are two electric vehicles
Figure BDA0002089269540000107
Need to be in two time slots
Figure BDA0002089269540000108
The same power requirement is fulfilled. At the same time, the optimal solution obtained by the constraint equation (5) is
Figure BDA00020892695400001011
Then
Figure BDA0002089269540000109
And
Figure BDA00020892695400001010
are all constrainedThe optimal solution of equation (5). However, their total charging costs are the same, but the total charging time is different, i.e. the electric vehicle 1 can fulfill its charging needs in advance.
It is therefore instructive to find a time-efficient solution from the optimal solution of constraint equation (5). That is, a time-efficient solution is found from the calculated charging demand powers of different electric vehicles in different time slots. Therefore, the application efficiency of the charging pile can be improved for saving the resources of the charging pile for the charging station, and the satisfaction degree of a user can be increased due to the fact that the charging tasks of part of vehicles can be completed in advance.
Therefore, in order to reduce the total charging time while keeping the optimized value of the constraint equation (5), i.e., the total charging cost, constant, the constraint equation of the optimization problem is designed as follows:
Figure BDA0002089269540000111
in the formula, eiFor the required charge of the electric vehicle i, it can be seen that
Figure BDA0002089269540000112
Linearly decreases as t increases while giving the required charge amount eiSmaller electric vehicles have greater priority.
Therefore, the objective function of the formula (6) encourages the electric vehicle to be charged with high power as early as possible and give a high priority to the electric vehicle with a smaller electric quantity demand, so that the charging pile of the charging station can be released as soon as possible and the satisfaction of the owner of the electric vehicle is improved. In other words, under the condition that optimal solutions of the charging demand powers of different electric vehicles in different time slots are obtained, power supply output is performed by using the maximum charging demand powers corresponding to different electric vehicles in the optimal solutions. Wherein the required charge amounts of the different electric vehicles are inversely related to the charging priority.
Namely, based on the total load of the charging station in the time slot t, the charging demand power x of different electric vehicles in different time slots is obtained again according to the following constraint conditions:
Figure BDA0002089269540000113
and performing power supply output according to the charging required power obtained again.
This process, not only can promote the efficiency of charging station and can also increase user's satisfaction.
According to the embodiment of the application, the required charging amount of the charged electric automobile, the charging starting time, the charging ending time, the maximum charging power and the rated power of a transformer in the charging station are obtained, the peak power electricity price in the settlement period and the time-of-use electricity prices corresponding to different time slots are combined, the charging required power of different electric automobiles in different time slots is calculated, power supply output is carried out, charging scheduling is carried out according to the charging requirements of different electric automobiles and the time slots corresponding to different charging times, reasonable charging distribution of the electric automobiles is achieved, the efficiency of the charging station can be improved, and the satisfaction degree of users can be increased.
The embodiment of the application also provides different implementation modes of the charging scheduling method of the charging station.
In the operating environment of practical charging stations, people are all rational and they always want to reach their desired amount of electricity in the shortest time with the least charging costs. Therefore, most of the electric vehicle owners report more favorable charging demands to the owners, and the load states of the charging stations are ignored. The operation effect of the online charging scheduling strategy is reduced in a real charging station operation environment. Therefore, in order to maximize the operation efficiency of the charging station and improve the user satisfaction, a strategy for setting a reasonable price based on the load state of the charging station and the charging demand reported by the owner of the electric vehicle is provided, so that the win-win situation of the charging station and the owner of the electric vehicle is achieved.
Correspondingly, as an optional implementation manner, fig. 2 is a second flowchart of a charging scheduling method for a charging station according to an embodiment of the present application. As shown in fig. 2, a charging scheduling method for a charging station includes the following steps:
in step 201, the required charging amount and the maximum charging power of the requested electric vehicle requesting charging and the charging electric vehicle being charged in the charging station are obtained.
The requested electric vehicle is an electric vehicle which is not charged in the current charging station and is in a charging request state. The request electric vehicle and the charging electric vehicle are at least one.
When the electric vehicle needs to be charged to the charging station, the charging requirement of the electric vehicle is submitted.
In this step, the required charge amount of the electric vehicle is acquired not only by acquiring the required charge amount of the electric vehicle requested to be charged but also by acquiring the required charge amount of the charged electric vehicle being charged.
The acquisition of the maximum charging power of the electric vehicle is also performed by acquiring not only the maximum charging power of the requested electric vehicle requesting charging but also the maximum charging power of the charging electric vehicle being charged.
After the electric vehicle is connected with the charging station, the charging station can detect the maximum charging power of the electric vehicle.
Step 202, obtaining the maximum peak power expected in a settlement period, the peak power electricity price and the time-of-use electricity prices corresponding to different time slots.
Wherein one settlement period is divided into several time slots. "plurality" herein each refers to more than two.
Specifically, the expected maximum peak power in the one settlement period may be estimated from the maximum peak power in the historical settlement periods. Wherein the peak power electricity price and the time-of-use electricity price are prices shown by a power grid public.
In the present application, a settlement period is divided into a plurality of time slots, so each time slot corresponds to the time-of-use electricity price in the same settlement period, and different time slots may belong to the peak electricity utilization period or the valley electricity utilization period, so the time-of-use electricity prices corresponding to different time slots may be the same or different. Here, the time-of-use electricity prices corresponding to different time slots need to be acquired.
Step 203, according to the required charging amount and the maximum charging power, and by combining the expected maximum peak power, the peak power electricity price and the time-of-use electricity prices corresponding to different time slots, the charging fee required for the electric vehicle to be charged at different charging ending times and the charging price corresponding to different time slots from the charging starting time to the charging ending time are obtained.
The different charging ending time is obtained by estimating the required charging amount and the maximum charging power of the requested electric vehicle requesting charging according to the request, a plurality of charging ending times can be estimated, and the charging cost corresponding to the requested electric vehicle requesting charging in different charging ending times and the charging price corresponding to different time slots from the charging starting time to the charging ending time are deduced according to the plurality of charging ending times, the charging demand and the maximum charging power of the charging electric vehicle currently charging in the current charging station, the expected maximum peak power, the peak power electricity price and the time-of-use electricity price estimated by the charging station, and the optimal solution corresponding to the different charging ending times.
In this implementation process, as an optional implementation manner, the obtaining, according to the required charging amount and the maximum charging power, the charging fee corresponding to the requested electric vehicle at different charging ending times and the charging price corresponding to different time slots from the charging starting time to the charging ending time by combining the desired maximum peak power, the peak power electricity price, and the time-of-use electricity prices corresponding to different time slots according to the desired maximum peak power, the peak power electricity price, and the time-of-use electricity prices corresponding to different time slots includes:
and calculating the shortest charging demand time of the requested electric vehicle according to the demand charging amount and the maximum charging power of the requested electric vehicle.
And calculating the shortest charging demand time of the requested electric automobile according to the required charging amount and the maximum charging power of the requested electric automobile. After that, based on the shortest charging demand time, the plurality of end charging times are estimated, and the subsequent deduction is realized to find the optimal solution corresponding to different end charging times.
Namely, according to the shortest charging time, acquiring different charging ending times of the requested electric automobile and a corresponding time slot set from the charging starting time to the different charging ending times
Figure BDA0002089269540000141
The set of all electric vehicles including the requesting electric vehicle and the charging electric vehicle is
Figure BDA0002089269540000142
Specifically, the linear constraint formula (5) corresponding to the online scheduling policy or the linear constraint formula (4) corresponding to the offline scheduling algorithm may be solved by an existing algorithm or a solver.
The optimal solution of formula (5) is given as (x)*，v*). Considering that the charging requirement of the electric vehicle has the characteristics of portability, mobility and randomness, the setting of the charging mechanism needs to have the characteristics of efficiency, fairness and the stimulation of the owner of the electric vehicle to submit a reasonable requirement according to the operation state of the charging station. Thus, the following pricing strategy is proposed in the present embodiment.
Analysis shows that the maximum peak power in a settlement period is often changed little in the actual operation process of the charging station. The maximum peak power in a settlement period is used as an important component of the charging station cost, and the expected maximum peak power v of the settlement period can be obtained by analyzing historical data*Then using the predicted v*V replacing equation (5). The optimization problem of the minimized cost of the charging station becomes:
Figure BDA0002089269540000143
when t is a value belonging to
Figure BDA0002089269540000158
Do not belong to the set [ a ]i,di]In the case of (a) in (b),
Figure BDA0002089269540000151
wherein, α v*Is a constant. The maximum load of the charging station should not exceed v*. Theta is a constant, ct+ theta is the time-of-use electricity price c corresponding to the time slot ttAnd setting a charging price corresponding to the time slot t.
The price of charging and whether a charging station can provide sufficient charging power to charge an electric vehicle are of concern to the owner of the electric vehicle. However, a punitive charging of the peak power in one billing cycle results in the charging power of each electric vehicle in the charging station being coupled together. From the constraint (7-1), the charging power of each electric vehicle plays a quantifiable role in the influence of the peak power of a settlement period.
Introducing Lagrangian multipliers to constraints (7-1)
Figure BDA0002089269540000152
Then the partial Lagrangian function is
Figure BDA0002089269540000153
The corresponding dual problem is as follows:
Figure BDA0002089269540000154
since the objective function of (8) is linear and the constraints are affine, as known from the Slater condition, (7) has strong duality, so the optimal solution of (8) is also the optimal solution of (7).
Let us note λ*The value of the lagrange multiplier is obtained for the dual problem when optimal. The dual problem can be decomposed into an optimization problem that minimizes the charging cost for each electric vehicle owner:
Figure BDA0002089269540000155
wherein the content of the first and second substances,
Figure BDA0002089269540000156
charging price c corresponding to time slot ttAnd + theta is further adjusted to obtain a charging regulation charging price.
From the above analysis, the price charged for charging regulation and control
Figure BDA0002089269540000157
In this case, each electric vehicle can be charged at the personal minimum charging cost, and the electricity purchase cost of the charging station can be minimized, that is, the sum of the optimal charging power curve of each electric vehicle is also the optimal power output curve of the charging station. Equation (7) can be solved quickly by using existing algorithms, such as dual decomposition, or solver. Thus λ*Can be quickly solved. A pricing strategy that is reasonable based on the operating conditions of the charging stations can be easily determined.
Namely, according to the following constraints:
Figure BDA0002089269540000161
Figure BDA0002089269540000162
Figure BDA0002089269540000163
Figure BDA0002089269540000164
Figure BDA0002089269540000165
in solving the constraint conditions
Figure BDA0002089269540000166
Corresponding lagrange multiplier
Figure BDA0002089269540000167
If it is
Figure BDA0002089269540000168
Acquiring the corresponding charging price of the electric vehicle in different time slots from the charging starting time to the charging ending time under different charging ending times
Figure BDA0002089269540000169
And the charging cost corresponding to the charging time of the electric automobile at different ending times is requested
Figure BDA00020892695400001610
Wherein v is*Is the desired maximum peak power; a isiTo start the charging time; diTo end the charging time;
Figure BDA00020892695400001611
charging power of the electric automobile i in a time slot t; e.g. of the typeiThe required charge quantity of the electric automobile i is obtained;
Figure BDA00020892695400001612
the maximum charging power of the electric automobile i is obtained; c. Ctα is the peak power price;
Figure BDA00020892695400001613
an optimal solution for the Lagrangian multiplier; theta is a constant.
From the analysis, if
Figure BDA00020892695400001614
The charging station is low in load at present, and no time slot is needed to adjust the price. But only the charging load of the electric vehicle and reaches v*Just have
Figure BDA00020892695400001615
Figure BDA00020892695400001616
And if the charging cost is more than 0, the price of the electric automobile in the time slot is increased, and the charging cost of the charging station and the charging cost of each electric automobile can reach the optimum simultaneously, namely, each electric automobile is charged in the mode of the lowest charging cost, and the electricity purchasing cost of the charging station can also reach the minimum simultaneously. The electric vehicle is induced to transfer its charging demand to other time slots. Load exceeding v*The probability of (c) can be greatly reduced.
If the electric automobile i submits the leaving time d corresponding to the charging demandiThe larger, there is more scheduling space for charging stations to reduce the cost of purchasing electricity from the grid. Therefore, the electric vehicle i should get a discount on the charging fee. That is, the charging cost of the electric vehicle does not follow diThe increase of the charging schedule is increased, and the fairness and the rationality of the charging schedule are realized.
Also exist
Figure BDA00020892695400001617
The case (1). Some electric vehicles may be relatively urgent. They are more concerned about the charging duration of the electric vehicle than the charging cost. Thus, some relatively urgent need may arise, making the aforementioned constraint (7-1) difficult to satisfy. In this case, in order to make the problem solved by equation (7) feasible, the constraint (7-1) is first removed, then the charging power of the electric vehicle i in the time slot t, that is, the charging power of different electric vehicles in different time slots, is solved, and the total power supply power p of the charging station in different time slots is obtainedt，
Figure BDA0002089269540000171
Note the book
Figure BDA0002089269540000172
If p ismIf the charging time is more than p, the charging request of the electric automobile with the largest influence on the charging station is refused. If p ism< p when pt＞v*The charging station has a larger load in the time slots, and the price of the time slots is set as
Figure BDA0002089269540000173
The prices of other time slots are set to
Figure BDA0002089269540000174
If the electric vehicle i is allowed to be charged at the charging station, the total charge for charging is
Figure BDA0002089269540000175
Wherein, gamma (p)m-v*) This is a penalty for the expected peak power of the electric vehicle elevation charging station for an additional cost. Wherein gamma is a constant and represents the elevation v of the electric automobile i*The penalty factor of (2).
I.e. in solving constraints
Figure BDA0002089269540000176
Corresponding lagrange multiplier
Figure BDA0002089269540000177
Then, the method further comprises the following steps:
if it is
Figure BDA00020892695400001711
Then the following constraints are relied upon:
Figure BDA0002089269540000178
calculating the charging power of the electric automobile i in the time slot t
Figure BDA0002089269540000179
Obtaining the maximum total power supply power p of the charging station in all time slots from the starting charging time to the latest ending charging time in the different ending charging timesm；
If the maximum total power supply power is smaller than the rated power of the transformer in the charging station, acquiring the charging time of the requested electric automobile from the beginning under different charging ending timeCharging price corresponding to different time slots within charging time from time to end
Figure BDA00020892695400001710
And the charging cost corresponding to the charging time of the electric automobile at different ending times is requested
Figure BDA0002089269540000181
Wherein, in time slots in which the maximum total supply power of the charging station is greater than the desired maximum peak power,
Figure BDA0002089269540000182
in time slots in which the maximum total supply power of the charging station is less than or equal to the desired maximum peak power,
Figure BDA0002089269540000183
gamma is a constant.
The charging cost corresponding to different charging ending time and the charging price corresponding to different time slots from the charging starting time to the charging ending time of the electric vehicle with different requests under different charging requirements are obtained and calculated, the user is indicated to select the charging strategy in a better mode, and the charging load of a charging station and a power grid is reduced.
Step 204, displaying the charging fee corresponding to the requested electric vehicle at different charging ending time and the charging price corresponding to different time slots from the charging starting time to the charging ending time.
The steps realize a pricing strategy, a proper price can be determined for each time slot according to the charging requirement of a charging vehicle, and the load condition of different time slots of the charging station and the power grid price are combined to generate a corresponding charging fee and a charging price result to be displayed to a user, so that the optimal charging cost of each electric vehicle can be ensured, the user is driven to reasonably select the charging ending time, the charging behavior of the user is guided, the charging scheduling is realized according to the charging requirements of different electric vehicles and the time slots corresponding to different charging times, the reasonable charging distribution of the electric vehicles is realized, the efficiency of the charging station can be improved, the satisfaction degree of the user can be increased, and the win-win situation of the charging station and the owner of the electric vehicle can be achieved.
Step 205, obtaining the selection input of the target charging fee corresponding to the target charging ending time in different charging ending times by the user.
After the charging fees corresponding to the requested electric vehicle in different charging ending times and the charging prices corresponding to different time slots from the charging starting time to the charging ending time are displayed, the user can select a charging option to guide the charging behavior of the user.
Step 206, responding to the selection input, determining that the target charging ending time is the charging ending time of the requested electric automobile, and determining that the current time is the charging starting time of the target charging ending time.
When a user selects a charging scheme to charge the electric automobile, determining the starting charging time and the ending charging time of the current electric automobile corresponding to the charging scheme selected by the user.
After that, the step 207 of acquiring the required charging amount, the charging start time, the charging end time, the maximum charging power and the rated power of the transformer in the charging station of the charged electric vehicle may be started.
Step 207, acquiring the required charging amount, the charging start time, the charging end time, the maximum charging power and the rated power of the transformer in the charging station of the charged electric vehicle.
The implementation process of this step is the same as that of step 101 in the foregoing embodiment, and is not described here again.
Step 208, the peak power electricity price in a settlement period and the time-of-use electricity prices corresponding to different time slots are obtained.
And the settlement period is divided into a plurality of time slots, and different time slots are corresponding from the charging starting time to the charging ending time of the electric automobile.
The implementation process of this step is the same as that of step 102 in the foregoing embodiment, and is not described here again.
Step 209, obtaining the charging demand power of different electric vehicles in different time slots according to the demand charging amount, the starting charging time, the ending charging time, the maximum charging power, the rated power of the transformer in the charging station, and the peak power price and the time-of-use price.
The implementation process of this step is the same as that of step 103 in the foregoing embodiment, and is not described here again.
And step 210, performing power supply output according to the charging required power.
The implementation process of this step is the same as that of step 104 in the foregoing embodiment, and is not described here again.
In the embodiment of the present application, the implementation of the charging scheduling scheme of the charging station is briefly described as follows: if the electric automobile requires charging, the charging station can firstly provide a user with an optional charging expense meter and an electricity price meter related to the charging time of the user according to the load state of the charging station and the electric quantity required to be charged by an electric automobile owner, then the user selects a proper charging requirement according to the requirement of the user, and then, according to the charging task and the completion condition of the electric automobile in the station, an online scheduling strategy is operated to obtain an optimized charging station total power output curve
Figure BDA0002089269540000201
And finally, executing a scheduling strategy for increasing the time efficiency of the charging station, obtaining the optimized charging scheme of each vehicle, and charging each vehicle according to the optimized charging scheme.
For a brief explanation of the rationality and feasibility of the online pricing strategy proposed in the embodiments of the present application, a description is given in conjunction with specific charging station operation scenarios, which are as follows:
1) in case one, the charging station load is small. Suppose the electric vehicle in the charging station is an electric vehicle with time slot 1 at the charging station. The load on the charging station for time slot 1 is relatively small.
2) In case two, the charging station is heavily loaded. Suppose the electric vehicle in the charging station is the electric vehicle with time slot 55 at the charging station. The charging station is relatively heavily loaded at time slot 55.
For the first and second cases, it is assumed that the owner i of the electric vehicle (i.e. the electric vehicle i) submits a 60kW charging demand to the charging station, and the charging station detects that the maximum charging power of the electric vehicle is 60 kW/h. The charging station needs to give a charging cost table about the leaving time of the electric vehicle to the user for selection.
In two different situations, the charging cost of the electric vehicle cannot be reduced and the electricity price of each time slot cannot be changed even if the electric vehicle gives more scheduling flexibility because the charging load in the time slot 1 is not high and is not urgent. Pricing strategy in this case, the charging fee selection list and price given to the electric vehicle i are expected. In contrast, the charging station is loaded more heavily from time slot 55 to time slot 60, and if the charging process of the electric vehicle is not scheduled properly, the charging power of the electric vehicle is likely to reach the upper load limit of the charging station. However, comparing slot 57 to slot 66, the price of electricity for slots 55 and 56 is relatively low. Therefore, under the pricing strategy, the electricity prices of the time slots 55 and 56 are raised. If the leaving time of the electric vehicle i is later than the time slot 71, the charging cost thereof is reduced. This is because it avoids the time period in which the charging station is relatively urgent and the time period of high electricity price, so that the charging cost thereof is reduced.
From the above analysis, it can be seen that the charging scheduling policy proposed in the embodiment of the present application can determine a suitable price for each time slot according to the load conditions of different time slots of the charging station and the power grid price. The pricing strategy has the advantages that firstly, the electricity purchasing cost of the charging station can be guaranteed to be optimal on the premise that the charging cost of each electric vehicle is optimal. Secondly, the price of each time slot is the same for the owner of the electric vehicle requesting charging, i.e. the pricing mechanism has fairness. And finally, reasonable pricing can be set according to the load condition of the charging station, namely the price of the power grid, namely the rationality of the pricing is ensured.
Referring to fig. 3, fig. 3 is a structural diagram of a charging scheduling system of a charging station according to an embodiment of the present application, and for convenience of description, only a portion related to the embodiment of the present application is shown.
The charge scheduling system of the charging station comprises: a first obtaining module 301, a second obtaining module 302, a third obtaining module 303 and a power supply output module 304.
A first obtaining module 301, configured to obtain a required charging amount, a charging start time, a charging end time, a maximum charging power, and a rated power of a transformer in a charging station of a charged electric vehicle;
a second obtaining module 302, configured to obtain a peak power electricity price in a settlement period and time-of-use electricity prices corresponding to different time slots, where one settlement period is divided into a plurality of time slots, and different time slots correspond to different charging start times and different charging end times of the electric vehicle;
a third obtaining module 303, configured to obtain, according to the required charging amount, the start charging time, the end charging time, the maximum charging power, and a rated power of a transformer in the charging station, and by combining the peak power price and the time-of-use price, charging required powers of different electric vehicles in different time slots;
and a power supply output module 304, configured to output power supply according to the charging demand power.
Optionally, if the charged electric vehicle includes: if all the electric vehicles in one electricity consumption settlement period are used, the third obtaining module 303 is specifically configured to:
the set of all time slots divided by one electricity consumption settlement period is recorded as
Figure BDA0002089269540000211
The set of all the electric vehicles charged in one electricity consumption settlement period is
Figure BDA0002089269540000212
Acquiring the charging required power x of different electric vehicles in different time slots according to the following constraint conditions:
Figure BDA0002089269540000221
Figure BDA0002089269540000222
Figure BDA0002089269540000223
Figure BDA0002089269540000224
Figure BDA0002089269540000225
wherein the content of the first and second substances,
Figure BDA0002089269540000226
Figure BDA0002089269540000227
for the charging power of the electric vehicle i in the time slot t,
Figure BDA0002089269540000228
the maximum charging power of the electric automobile i is obtained; a isiStarting charging time for the electric automobile i; diThe charging ending time of the electric automobile i is obtained; e.g. of the typeiThe required charge quantity of the electric automobile i is obtained; p is the rated power of the transformer in the charging station; c. CtThe time-of-use electricity price corresponding to the time slot t is α, which is the peak power electricity price.
Optionally, if the charged electric vehicle includes: if all the electric vehicles currently receiving charging in the charging station are currently charged, the third obtaining module 303 is specifically configured to:
the set of all time slots corresponding to the current time to the target end charging time is recorded as
Figure BDA0002089269540000229
The target charging ending time is the latest charging ending time in the charging ending time of at least one electric automobile;
recording the current time slot t, wherein the set of all electric vehicles receiving charging in the charging station is
Figure BDA00020892695400002210
Acquiring the charging demand power x of different electric vehicles in different time slots according to the following constraint conditions:
Figure BDA00020892695400002211
Figure BDA00020892695400002212
Figure BDA00020892695400002213
Figure BDA00020892695400002214
v0≤v
Figure BDA00020892695400002215
Figure BDA00020892695400002216
wherein the content of the first and second substances,
Figure BDA0002089269540000231
Figure BDA0002089269540000232
charging power of the electric automobile i in a time slot t;
Figure BDA0002089269540000233
the maximum charging power of the electric automobile i is obtained; a isiStarting charging time for the electric automobile i; diThe charging ending time of the electric automobile i is obtained; e.g. of the typeiThe required charge quantity of the electric automobile i is obtained; p is the rated power of the transformer in the charging station; v. ofo＝max{vpv,vpd}，vpvMaximum peak power, v, generated by the charging station from the starting time of a settlement period to the current timepdIs the predicted maximum peak power of the charging station in one settlement period; v is at
Figure BDA0002089269540000234
Maximum charging power and v of the charging station0Maximum value of (1); c. CtTime slot t corresponds to the time-of-use electricity price, and α is the peak power electricity price.
Optionally, the power supply output module 304 is specifically configured to:
acquiring the total load of the charging station in the time slot t according to the charging required power of the electric vehicle in different time slots
Figure BDA0002089269540000235
Based on the total load of the charging station in the time slot t, acquiring the charging demand power x of different electric vehicles in different time slots again according to the following constraint conditions:
Figure BDA0002089269540000236
and performing power supply output according to the charging required power obtained again.
Optionally, the charge scheduling system of the charging station further includes:
the fourth acquisition module is used for acquiring the required charging amount and the maximum charging power of the requested electric vehicle requesting charging and the charging electric vehicle being charged in the charging station;
a fifth obtaining module, configured to obtain a maximum peak power expected in a settlement period, a peak power electricity price, and time-of-use electricity prices corresponding to different time slots, where one settlement period is divided into a plurality of time slots;
a sixth obtaining module, configured to obtain, according to the required charging amount and the maximum charging power, charging fees corresponding to different end charging times of the requested electric vehicle and charging prices corresponding to different time slots from a start charging time to an end charging time by combining the expected maximum peak power, the peak power electricity price, and time-of-use electricity prices corresponding to different time slots;
and the display module is used for displaying the charging cost corresponding to the electric automobile requested in different charging ending time and the charging price corresponding to different time slots from the charging starting time to the charging ending time.
Optionally, the sixth obtaining module is specifically configured to:
calculating the shortest charging demand time of the requested electric vehicle according to the demand charging amount and the maximum charging power of the requested electric vehicle;
according to the shortest charging time, acquiring different charging ending times of the requested electric automobile and corresponding time slot sets from the charging starting time to the different charging ending times
Figure BDA0002089269540000241
The set of all electric vehicles including the requesting electric vehicle and the charging electric vehicle is
Figure BDA0002089269540000242
According to the following constraints:
Figure BDA0002089269540000243
in solving the constraint conditions
Figure BDA0002089269540000244
Correspond toOf lagrange multiplier
Figure BDA0002089269540000245
If it is
Figure BDA0002089269540000246
Acquiring the charging price corresponding to different time slots from the charging starting time to the charging ending time of the requested electric automobile at different charging ending times
Figure BDA0002089269540000247
And the charging cost corresponding to the charging time of the electric automobile at different ending times is requested
Figure BDA0002089269540000248
Wherein v is*Is the desired maximum peak power; a isiTo start the charging time; diTo end the charging time;
Figure BDA0002089269540000249
charging power of the electric automobile i in a time slot t; e.g. of the typeiThe required charge quantity of the electric automobile i is obtained;
Figure BDA00020892695400002410
the maximum charging power of the electric automobile i is obtained; c. Ctα is the peak power price;
Figure BDA0002089269540000251
an optimal solution for the Lagrangian multiplier; theta is a constant.
Optionally, the sixth obtaining module is further configured to:
if it is
Figure BDA0002089269540000252
Then the following constraints are relied upon:
Figure BDA0002089269540000253
calculating the charging power of the electric automobile i in the time slot t
Figure BDA0002089269540000254
Obtaining the maximum total power supply power p of the charging station in all time slots from the starting charging time to the latest ending charging time in the different ending charging timesm；
If the maximum total power supply power is less than the rated power of the transformer in the charging station, acquiring the charging price corresponding to different time slots from the charging start time to the charging end time of the requested electric vehicle at different charging end times
Figure BDA0002089269540000255
And the charging cost corresponding to the charging time of the electric automobile at different ending times is requested
Figure BDA0002089269540000256
Wherein, in time slots in which the maximum total supply power of the charging station is greater than the desired maximum peak power,
Figure BDA0002089269540000257
in time slots in which the maximum total supply power of the charging station is less than or equal to the desired maximum peak power,
Figure BDA0002089269540000258
gamma is a constant.
Optionally, the charge scheduling system of the charging station further includes:
the seventh acquisition module is used for acquiring the selection input of the target charging cost corresponding to the target charging ending time in different charging ending times by the user;
the determining module is used for responding to the selection input, determining the target charging ending time as the charging ending time of the requested electric automobile, and determining the current time as the charging starting time of the target charging ending time;
and the step execution module is used for executing the steps of acquiring the required charging amount, the charging starting time, the charging ending time, the maximum charging power and the rated power of the transformer in the charging station of the charged electric automobile.
According to the embodiment of the application, the charging scheduling is carried out according to the charging demands of different electric vehicles and the time slots corresponding to different charging times, reasonable charging distribution of the electric vehicles is realized, the efficiency of the charging station can be improved, and the satisfaction degree of users can be increased.
The charging scheduling device of the charging station in the embodiment of the present application can implement each process of the embodiment of the charging scheduling method of the charging station, can achieve the same technical effect, and is not repeated here for avoiding repetition.
Fig. 4 is a structural diagram of a charging station according to an embodiment of the present disclosure. As shown in fig. 4, the charging station 4 of the embodiment includes: a processor 40, a memory 41 and a computer program 42 stored in said memory 41 and executable on said processor 40.
Illustratively, the computer program 42 may be partitioned into one or more modules/units that are stored in the memory 41 and executed by the processor 40. For example, the computer program 42 may be divided into a first obtaining module, a second obtaining module, a third obtaining module and a power supply output module, and the functions of the modules are as follows:
the first acquisition module is used for acquiring the required charging amount, the charging starting time, the charging ending time, the maximum charging power and the rated power of a transformer in a charging station of the charged electric automobile; the second acquisition module is used for acquiring peak power electricity prices in a settlement period and time-of-use electricity prices corresponding to different time slots, wherein one settlement period is divided into a plurality of time slots, and different time slots correspond to different time slots from the charging starting time to the charging ending time of different electric vehicles; a third obtaining module, configured to obtain, according to the required charging amount, the start charging time, the end charging time, the maximum charging power, and a rated power of a transformer in the charging station, and in combination with the peak power price and the time-of-use price, charging required powers of different electric vehicles in different time slots; and the power supply output module is used for carrying out power supply output according to the charging demand power.
The charging station 4 may include, but is not limited to, a processor 40, a memory 41. It will be appreciated by those skilled in the art that fig. 4 is merely an example of a charging station 4 and does not constitute a limitation of a charging station 4 and may include more or fewer components than shown, or some components in combination, or different components, for example the charging station may also include input output devices, network access devices, buses, etc.
The Processor 40 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 41 may be an internal storage unit of the charging station 4, such as a hard disk or a memory of the charging station 4. The memory 41 may also be an external storage device of the charging station 4, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), or the like, provided on the charging station 4.
The integrated modules/units, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. All or part of the flow in the method of the embodiments may be implemented by a computer program, and the computer program may be stored in a computer readable storage medium, and when the computer program is executed by a processor, the steps of the embodiments of the methods may be implemented. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, etc.
The above-mentioned embodiments are merely used to illustrate the technical solutions of the present application, and those skilled in the art should understand that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present application and are intended to be included within the scope of the present application.

Claims (11)

1. A charging scheduling method for a charging station, comprising:
acquiring the required charging amount, the starting charging time, the ending charging time, the maximum charging power and the rated power of a transformer in a charging station of a charged electric vehicle;
acquiring a peak power electricity price and time-of-use electricity prices corresponding to different time slots in a settlement period, wherein the settlement period is divided into a plurality of time slots, and different time slots correspond to different charging starting time and different charging ending time of the electric vehicle;
acquiring charging demand power of different electric vehicles in different time slots according to the demand charging amount, the charging starting time, the charging ending time, the maximum charging power and the rated power of a transformer in the charging station in combination with the peak power price and the time-of-use price;
and performing power supply output according to the charging required power.
2. The charge scheduling method of claim 1, wherein if the charged electric vehicle comprises: if all electric vehicles in an electricity consumption settlement period, obtaining the charging demand power of different electric vehicles in different time slots according to the demand charging amount, the starting charging time, the ending charging time, the maximum charging power and the rated power of a transformer in the charging station in combination with the peak power price and the time-of-use price, including:
the set of all time slots divided by one electricity consumption settlement period is recorded as
Figure FDA0002594529440000011
The set of all the electric vehicles charged in one electricity consumption settlement period is
Figure FDA0002594529440000012
Acquiring the charging required power x of different electric vehicles in different time slots according to the following constraint conditions:
Figure FDA0002594529440000021
Figure FDA0002594529440000022
Figure FDA0002594529440000023
Figure FDA0002594529440000024
Figure FDA0002594529440000025
wherein the content of the first and second substances,
Figure FDA0002594529440000026
Figure FDA0002594529440000027
for the charging power of the electric vehicle i in the time slot t,
Figure FDA0002594529440000028
the maximum charging power of the electric automobile i is obtained; a isiStarting charging time for the electric automobile i; diThe charging ending time of the electric automobile i is obtained; e.g. of the typeiThe required charge quantity of the electric automobile i is obtained; p is the rated power of the transformer in the charging station; c. CtThe time-of-use electricity price corresponding to the time slot t is α, which is the peak power electricity price.
3. The charge scheduling method of claim 1, wherein if the charged electric vehicle comprises: if all electric vehicles currently receiving charging in the charging station, the obtaining charging demand power of different electric vehicles in different time slots according to the demand charging amount, the start charging time, the end charging time, the maximum charging power, and the rated power of a transformer in the charging station, in combination with the peak power price and the time-of-use price, includes:
the set of all time slots corresponding to the current time to the target end charging time is recorded as
Figure FDA0002594529440000029
The target charging ending time is the latest charging ending time in the charging ending time of at least one electric automobile;
recording the current time slot t, wherein the set of all electric vehicles receiving charging in the charging station is
Figure FDA00025945294400000210
Acquiring the charging demand power x of different electric vehicles in different time slots according to the following constraint conditions:
Figure FDA0002594529440000031
wherein the content of the first and second substances,
Figure FDA0002594529440000032
Figure FDA0002594529440000033
charging power of the electric automobile i in a time slot t;
Figure FDA0002594529440000034
the maximum charging power of the electric automobile i is obtained; a isiStarting charging time for the electric automobile i; diThe charging ending time of the electric automobile i is obtained; e.g. of the typeiThe required charge quantity of the electric automobile i is obtained; p is the rated power of the transformer in the charging station; v. ofo＝max{vpv,vpd}，vpvMaximum peak power, v, generated by the charging station from the starting time of a settlement period to the current timepdIs the predicted maximum peak power of the charging station in one settlement period; v is at
Figure FDA0002594529440000035
Maximum charging power and v of the charging station0Maximum value of (1); c. CtTime slot t corresponds to the time-of-use electricity price, and α is the peak power electricity price.
4. The charging scheduling method according to claim 3, wherein the outputting power supply according to the charging demand power includes:
acquiring the total load of the charging station in the time slot t according to the charging required power of the electric vehicle in different time slots
Figure FDA0002594529440000036
Based on the total load of the charging station in the time slot t, acquiring the charging demand power x of different electric vehicles in different time slots again according to the following constraint conditions:
Figure FDA0002594529440000041
and performing power supply output according to the charging required power obtained again.
5. The charge scheduling method according to claim 1, wherein before the obtaining of the required charge amount, the start charge time, the end charge time, the maximum charge power of the charged electric vehicle and the rated power of the transformer in the charging station, the method further comprises:
acquiring a required charging amount and a maximum charging power of a requested electric vehicle requesting charging and a charging electric vehicle being charged in a charging station;
acquiring the expected maximum peak power, the peak power price and the time-of-use electricity prices corresponding to different time slots in a settlement period, wherein one settlement period is divided into a plurality of time slots;
according to the required charging amount and the maximum charging power, combining the expected maximum peak power, the peak power electricity price and the time-of-use electricity prices corresponding to different time slots, obtaining charging fees corresponding to different charging ending times of the requested electric automobile and charging prices corresponding to different time slots from the charging starting time to the charging ending time;
and displaying the charging cost corresponding to the electric automobile requested in different charging ending time and the charging price corresponding to different time slots from the charging starting time to the charging ending time.
6. The charge scheduling method of claim 5,
the acquiring, according to the demanded charging amount and the maximum charging power, charging fees corresponding to the requested electric vehicle at different ending charging times and charging prices corresponding to different time slots from the starting charging time to the ending charging time by combining the expected maximum peak power, the peak power electricity price and the time-of-use electricity prices corresponding to different time slots according to the demanded maximum peak power, the peak power electricity price and the time-of-use electricity prices corresponding to different time slots includes:
calculating the shortest charging demand time of the requested electric vehicle according to the demand charging amount and the maximum charging power of the requested electric vehicle;
according to the shortest charging demand time, acquiring different charging ending times of the requested electric automobile and corresponding time slot sets from the charging starting time to the different charging ending times
Figure FDA0002594529440000051
The set of all electric vehicles including the requesting electric vehicle and the charging electric vehicle is
Figure FDA0002594529440000052
According to the following constraints:
Figure FDA0002594529440000053
in solving the constraint conditions
Figure FDA0002594529440000054
Corresponding lagrange multiplier
Figure FDA0002594529440000055
If λt*If the charging time is more than or equal to 0, acquiring the charging price c corresponding to the electric automobile in different time slots from the charging starting time to the charging ending time under different charging ending timest+θ+λt*And the charging cost corresponding to the charging time of the electric automobile at different ending time
Figure FDA0002594529440000056
Wherein v is*Is the desired maximum peak power; a isiTo start the charging time; diTo end the charging time; x is the charging power of the electric vehicle,
Figure FDA0002594529440000057
charging power of the electric automobile i in a time slot t; e.g. of the typeiThe required charge quantity of the electric automobile i is obtained;
Figure FDA0002594529440000058
the maximum charging power of the electric automobile i is obtained; c. CtTime slot t corresponding time-of-use electricity price, α the peak power electricity price, lambdat*An optimal solution for the Lagrangian multiplier; theta is a constant.
7. The charge scheduling method of claim 6,
in the solution constraint condition
Figure FDA0002594529440000059
Corresponding lagrange multiplier
Figure FDA00025945294400000510
Then, the method further comprises the following steps:
if λt*Infinity, then the following constraint is followed:
Figure FDA0002594529440000061
calculating the charging power of the electric automobile i in the time slot t
Figure FDA0002594529440000062
Obtaining the latest charging ending time of the charging station from the charging starting time to the different charging ending timeMaximum total power supply p in all time slots within an electrical timem；
If the maximum total power supply power is less than the rated power of the transformer in the charging station, acquiring the charging price corresponding to different time slots from the charging start time to the charging end time of the requested electric vehicle at different charging end times
Figure FDA0002594529440000063
And the charging cost corresponding to the charging time of the electric automobile at different ending times is requested
Figure FDA0002594529440000064
Wherein, in time slots in which the maximum total supply power of the charging station is greater than the desired maximum peak power,
Figure FDA0002594529440000065
in time slots in which the maximum total supply power of the charging station is less than or equal to the desired maximum peak power,
Figure FDA0002594529440000066
gamma is a constant.
8. The charge scheduling method of claim 5,
after the step of displaying the charging cost corresponding to the requested electric vehicle at different charging ending times and the charging price corresponding to different time slots from the charging starting time to the charging ending time, the method further comprises the following steps:
acquiring selection input of a user for target charging cost corresponding to target charging ending time in different charging ending time;
responding to the selection input, determining that the target charging ending time is the charging ending time of the requested electric automobile, and determining that the current time is the charging starting time of the target charging ending time;
and executing the steps of acquiring the required charging amount, the charging starting time, the charging ending time, the maximum charging power and the rated power of the transformer in the charging station of the charged electric automobile.
9. A charge scheduling system, comprising:
the first acquisition module is used for acquiring the required charging amount, the charging starting time, the charging ending time, the maximum charging power and the rated power of a transformer in a charging station of the charged electric automobile;
the second acquisition module is used for acquiring peak power electricity prices in a settlement period and time-of-use electricity prices corresponding to different time slots, wherein one settlement period is divided into a plurality of time slots, and different time slots correspond to different time slots from the charging starting time to the charging ending time of different electric vehicles;
a third obtaining module, configured to obtain, according to the required charging amount, the start charging time, the end charging time, the maximum charging power, and a rated power of a transformer in the charging station, and in combination with the peak power price and the time-of-use price, charging required powers of different electric vehicles in different time slots;
and the power supply output module is used for carrying out power supply output according to the charging demand power.
10. A charging station comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the steps of the method according to any of claims 1 to 8 are implemented when the computer program is executed by the processor.
11. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 8.
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