CN113962613A - New energy automobile automatic charging pile quantity matching method and system - Google Patents

New energy automobile automatic charging pile quantity matching method and system Download PDF

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CN113962613A
CN113962613A CN202111565259.7A CN202111565259A CN113962613A CN 113962613 A CN113962613 A CN 113962613A CN 202111565259 A CN202111565259 A CN 202111565259A CN 113962613 A CN113962613 A CN 113962613A
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automatic charging
charging pile
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李建威
汤岳澎
孙超
邹巍涛
霍为炜
朱晋
周稼铭
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Beijing Institute of Technology BIT
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Abstract

The invention discloses a method and a system for automatically matching the number of charging piles of a new energy automobile, wherein the method comprises the following steps: determining an application scene of a target automatic charging pile, executing a first operation when the application scene is a fixed application scene, and executing a second operation when the application scene is a random application scene; the first operation is executed as follows: determining the number of the target automatic charging piles and the number of the electric vehicles matched with each target automatic charging pile based on the first constraint set and the target function; the objective function is a function which aims at maximizing profit of a charging pile operation side; the second operation is executed as follows: and determining the number of the target automatic charging piles and the number of the electric vehicles matched with each target automatic charging pile based on the second constraint set and the target function. The invention realizes the application of one automatic charging pile for multiple vehicles in different scenes, and improves the effective utilization rate of the automatic charging pile.

Description

New energy automobile automatic charging pile quantity matching method and system
Technical Field
The invention relates to the technical field of electric automobile charging, in particular to a method and a system for automatically matching the number of charging piles of a new energy automobile.
Background
In recent years, the development of new energy automobile industry represented by pure electric automobiles has achieved tremendous achievement, the technical level is remarkably improved, the industrial system is gradually improved, the output and sales volume and the retention volume of the electric automobiles are increased year by year, and the new stage of accelerated development is achieved. However, there are some short boards in the ecological chain of the electric vehicle industry, wherein the shortage in the charging service link has become a key factor restricting the development of the electric vehicle.
The electric pile is all for manual electric pile that fills basically to current, and a electric pile that fills only can charge to the electric automobile who parks on its both sides parking stall, has the problem that charge efficiency is low, availability factor is low. These problems will eventually cause great inconvenience to the daily charging requirements of the electric vehicle users, which is not favorable for the further popularization of the electric vehicles.
At present, although some enterprises or research institutions propose the concept of automatic charging pile, the problem of low effective utilization rate of the charging pile still cannot be solved based on the traditional mode of 'single pile to single vehicle', and the construction cost of the automatic charging pile is high, so that one side of the charging station is difficult to obtain profits from the automatic charging pile of 'single pile to single vehicle'.
To this, can adopt the automatic electric pile that fills of "a stake is to many cars" mode, can improve the effective utilization who fills electric pile to a certain extent, make full use of existing charging resource. Because the environment in actual charging station or parking area has certain complexity, this kind of automatic electric pile that fills of one-to-many when actual scene is used, electric automobile quantity that electric pile matches simultaneously need confirm different values according to the different characteristics of actual scene.
Based on the above problems, a method for automatically matching the number of charging piles of a new energy automobile is urgently needed.
Disclosure of Invention
The invention aims to provide a new energy automobile automatic charging pile quantity matching method and system, so that automatic charging piles of one pile for multiple vehicles are applied in different scenes, and the effective utilization rate of the automatic charging piles is improved.
In order to achieve the purpose, the invention provides the following scheme:
a method for matching the number of automatic charging piles of a new energy automobile comprises the following steps:
determining an application scene of a target automatic charging pile, executing a first operation when the application scene is a fixed application scene, and executing a second operation when the application scene is a random application scene; the target automatic charging pile is an automatic charging pile for multiple vehicles;
the execution process of the first operation is as follows:
determining a construction mode of an automatic target charging pile in the fixed application scene;
determining the charging requirements of a target user group; the charging requirement comprises the total number of users with the charging requirement, the charging frequency corresponding to each user, single expected charging time and charging starting time;
determining a first set of constraints based on the charging demand and the construction mode; the first constraint set comprises three constraint conditions, wherein the total number of users with charging requirements is less than or equal to a first value, the 0.9 time duration of the total charging requirements is less than or equal to a second value, and the time utilization rate of the charging pile is greater than or equal to a third value;
determining the number of the target automatic charging piles and the number of electric vehicles matched with each target automatic charging pile based on the first constraint set and an objective function; the objective function is a function which aims at maximizing profit of a charging pile operator side;
the execution process of the second operation is as follows:
determining a construction mode of an automatic target charging pile in the random application scene;
determining an electric vehicle quantity curve of the random application scene; the electric vehicle quantity curve represents the quantity of electric vehicles which need to be charged at each moment in a specified time period;
determining a second constraint set according to the electric vehicle quantity curve and the construction mode; the second constraint set comprises three constraint conditions, namely that the maximum value is less than or equal to a fourth value, 0.9 time of total charging demand time is less than or equal to a fifth value, and the time utilization rate of the charging pile is greater than or equal to a sixth value; the maximum value is the maximum value of the number of the electric automobiles in the electric automobile number curve;
and determining the number of the target automatic charging piles and the number of the electric automobiles matched with each target automatic charging pile based on the second constraint set and an objective function.
Optionally, the construction mode is a mode in which m target automatic charging piles are built together, and each target automatic charging pile serves electric vehicles parked in n surrounding parking spaces.
Optionally, the determining the electric vehicle quantity curve of the random application scenario specifically includes:
prediction of random application scenarios using gaussian process methodsTMoment electric automobile quantity curvex(T)；
Method for predicting charging time requirements of electric vehicles in random application scene by using Monte Carlo methodtA probability density curve of (a);
based on the electric automobile quantity curvex(T)And the probability density curve is used for determining the number of the electric automobiles needing to be charged at each moment in the specified time period of the random application scene, so that the electric automobile number curve of the random application scene is obtained.
Optionally, the first constraint set includes three constraint conditions, which are respectively:
Figure 198524DEST_PATH_IMAGE001
（1）；
Figure 973713DEST_PATH_IMAGE002
（2）；
Figure 999480DEST_PATH_IMAGE003
（3）；
wherein the content of the first and second substances,N max indicating the total number of users having a need for charging,
Figure 504410DEST_PATH_IMAGE004
represents a first value;t ope represents the operation time of the target automatic charging pile,
Figure 802668DEST_PATH_IMAGE005
a second value is represented which is a function of,
Figure 393049DEST_PATH_IMAGE006
which indicates the total charge demand period of time,t req indicating a charging time period required by a user;r lim which is indicative of a third value of the value,
Figure 199069DEST_PATH_IMAGE007
，
Figure 292927DEST_PATH_IMAGE008
the sum of the idle times of the automatic charging piles is taken for all targets.
Optionally, the second constraint set includes three constraint conditions, which are respectively:
Figure 27665DEST_PATH_IMAGE009
（1）；
Figure 839763DEST_PATH_IMAGE010
（2）；
Figure 950938DEST_PATH_IMAGE011
（3）；
wherein the content of the first and second substances,N max the maximum value is represented by the number of lines,
Figure 663417DEST_PATH_IMAGE004
represents a fourth value;t ope represents the operation time of the target automatic charging pile,
Figure 569056DEST_PATH_IMAGE005
a fifth value is represented as a function of,
Figure 868450DEST_PATH_IMAGE006
which indicates the total charge demand period of time,t req indicating a charging time period required by a user;r lim a sixth value is represented as a function of,
Figure 783317DEST_PATH_IMAGE007
，
Figure 851767DEST_PATH_IMAGE008
the sum of the idle times of the automatic charging piles is taken for all targets.
Optionally, the construction process of the objective function is as follows:
constructing a cost function; the cost function comprises construction cost, maintenance cost and electricity purchasing cost;
constructing a revenue function; the revenue function comprises charging revenue and service revenue;
constructing a carbon emission penalty function;
and determining a target function according to the cost function, the income function and the carbon emission penalty function.
Optionally, the objective function is
Figure 426843DEST_PATH_IMAGE012
；
Wherein the content of the first and second substances,
Figure 213533DEST_PATH_IMAGE013
is a carbon emission influencing factor;
construction cost:
Figure 666511DEST_PATH_IMAGE014
，
Figure 589468DEST_PATH_IMAGE015
the construction cost of the ith target automatic charging pile is calculated, and m represents the number of the target automatic charging piles;
maintenance cost:
Figure 601024DEST_PATH_IMAGE016
，
Figure 609431DEST_PATH_IMAGE017
the maintenance cost of the automatic charging pile for the ith target;
the electricity purchasing cost is as follows:
Figure 866100DEST_PATH_IMAGE018
；
Figure 909142DEST_PATH_IMAGE019
the electricity price in the time period t;P EV the average charging power of a target automatic charging pile,
Figure 593065DEST_PATH_IMAGE020
automatically charging the utilization time of a pile for a target;t ope representing the operation time of an automatic target charging pile;
Figure 587303DEST_PATH_IMAGE021
，
Figure 382084DEST_PATH_IMAGE022
the sum of the idle time of all the target automatic charging piles is obtained;
and (4) yield:G=G e +G s ，G e in order to make the charging profitable,
Figure 279633DEST_PATH_IMAGE023
，Q EV charging electricity price formulated for the target automatic charging pile;G s for service to receiveThe advantages that the method is good for,
Figure 868877DEST_PATH_IMAGE024
，Lin order to be a basic service charge,k 2 a proportionality coefficient for service charge reduction, n being the number of electric vehicles served by a target automatic charging pile;
carbon emission penalty:
Figure 851877DEST_PATH_IMAGE025
，
Figure 683304DEST_PATH_IMAGE026
the amount of carbon emissions generated for power generation on the grid side during the period t,
Figure 435359DEST_PATH_IMAGE027
is the carbon number per unit carbon emission.
The utility model provides an automatic electric pile quantity matching system that fills of new energy automobile, includes:
the application scene determining module is used for determining an application scene of the target automatic charging pile, executing a first sub-module when the application scene is a fixed application scene, and executing a second sub-module when the application scene is a random application scene; the target automatic charging pile is an automatic charging pile for multiple vehicles;
the first sub-module includes:
the first construction mode determining unit is used for determining a construction mode of the automatic target charging pile in the fixed application scene;
the charging demand determining unit is used for determining the charging demand of a target user group; the charging requirement comprises the total number of users with the charging requirement, the charging frequency corresponding to each user, single expected charging time and charging starting time;
a first constraint set determination unit configured to determine a first constraint set based on the charging demand and the construction mode; the first constraint set comprises three constraint conditions, wherein the total number of users with charging requirements is less than or equal to a first value, the 0.9 time duration of the total charging requirements is less than or equal to a second value, and the time utilization rate of the charging pile is greater than or equal to a third value;
the first optimization unit is used for determining the number of the target automatic charging piles and the number of the electric vehicles matched with each target automatic charging pile based on the first constraint set and an objective function; the objective function is a function which aims at maximizing profit of a charging pile operator side;
the second sub-module includes:
the second construction mode determining unit is used for determining a construction mode of the target automatic charging pile in the random application scene;
the electric vehicle quantity curve determining unit is used for determining an electric vehicle quantity curve of the random application scene; the electric vehicle quantity curve represents the quantity of electric vehicles which need to be charged at each moment in a specified time period;
the second constraint set determining unit is used for determining a second constraint set according to the electric vehicle quantity curve and the construction mode; the second constraint set comprises three constraint conditions, namely that the maximum value is less than or equal to a fourth value, 0.9 time of total charging demand time is less than or equal to a fifth value, and the time utilization rate of the charging pile is greater than or equal to a sixth value; the maximum value is the maximum value of the number of the electric automobiles in the electric automobile number curve;
the second optimization unit is used for determining the number of the target automatic charging piles and the number of the electric vehicles matched with each target automatic charging pile based on the second constraint set and an objective function; the objective function is a function which aims at maximizing profit of the charging pile operation side.
Optionally, the construction mode is a mode in which m target automatic charging piles are built together, and each target automatic charging pile serves electric vehicles parked in n surrounding parking spaces.
Optionally, the objective function is
Figure 461084DEST_PATH_IMAGE012
；
Wherein the content of the first and second substances,
Figure 931380DEST_PATH_IMAGE013
is a carbon emission influencing factor;
construction cost:
Figure 832078DEST_PATH_IMAGE014
，
Figure 438639DEST_PATH_IMAGE015
the construction cost of the ith target automatic charging pile is calculated, and m represents the number of the target automatic charging piles;
maintenance cost:
Figure 900845DEST_PATH_IMAGE016
，
Figure 124016DEST_PATH_IMAGE017
the maintenance cost of the automatic charging pile for the ith target;
the electricity purchasing cost is as follows:
Figure 798711DEST_PATH_IMAGE018
；
Figure 525358DEST_PATH_IMAGE019
the electricity price in the time period t;P EV the average charging power of a target automatic charging pile,
Figure 125841DEST_PATH_IMAGE020
automatically charging the utilization time of a pile for a target;t ope representing the operation time of an automatic target charging pile;
Figure 305150DEST_PATH_IMAGE021
，
Figure 49115DEST_PATH_IMAGE022
the sum of the idle time of all the target automatic charging piles is obtained;
and (4) yield:G=G e +G s ，G e in order to make the charging profitable,
Figure 630269DEST_PATH_IMAGE023
，Q EV charging electricity price formulated for the target automatic charging pile;G s in order to make a service gain possible,
Figure 667233DEST_PATH_IMAGE024
，Lin order to be a basic service charge,k 2 a proportionality coefficient for service charge reduction, n being the number of electric vehicles served by a target automatic charging pile;
carbon emission penalty:
Figure 599417DEST_PATH_IMAGE025
，
Figure 881494DEST_PATH_IMAGE026
the amount of carbon emissions generated for power generation on the grid side during the period t,
Figure 317154DEST_PATH_IMAGE027
is the carbon number per unit carbon emission.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
the invention discloses a new energy automobile automatic charging pile quantity matching method and system. The invention realizes the application of one automatic charging pile for multiple vehicles in different scenes, and improves the effective utilization rate of the automatic charging pile.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in 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 inventive exercise.
Fig. 1 is an overall flowchart of an automatic charging pile quantity matching method for a new energy automobile according to the invention;
FIG. 2 is a schematic diagram of the layout of an automatic charging pile and a parking space according to the present invention;
FIG. 3 is a graph illustrating the charging duration requirements of each electric vehicle according to the present invention
Figure 26484DEST_PATH_IMAGE028
Probability density curve of
Figure 678920DEST_PATH_IMAGE029
A schematic diagram;
fig. 4 is a schematic flow chart of the method for automatically matching the number of charging piles of the new energy automobile according to the invention;
fig. 5 is a schematic structural diagram of the automatic charging pile quantity matching system for the new energy automobile.
Detailed Description
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 only a part of the embodiments of the present invention, and not all of the embodiments. 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.
The invention aims to provide a new energy automobile automatic charging pile quantity matching method, which can meet the charging requirement of an electric automobile user side and improve the time utilization rate of an automatic charging pile.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
Example one
As shown in fig. 1, the embodiment provides a new energy automobile automatic charging pile quantity matching method, and the method is used in different scenes, such as residential community parking lots, commercial building parking lots, office building parking lots and the like, and parking lots or charging stations equipped with one-to-multiple automatic charging piles (hereinafter referred to as target automatic charging piles).
When carrying out automatic electric pile quantity matching of filling, consider when satisfying electric automobile user side demand of charging, improve automatic time utilization who fills electric pile, follow the profit maximize principle that fills electric pile operation side to the carbon emission that draws in the electric wire netting side is to filling the punishment of electric pile operation side, including following step:
step 1: carrying out statistical analysis on the charging habits of a target user group of a charging station or a parking lot according to an actual application scene, and predicting the charging requirements of the target user group; the charging requirement comprises information such as charging frequency, single expected charging time, charging starting time and the like.
Step 2: and modeling the charging requirement to be met by the charging station or the parking lot so as to enable the charging requirement to meet the requirement.
And step 3: and modeling the charging pile time utilization rate of the charging station or the parking lot to ensure that the charging pile time utilization rate meets the requirement.
And 4, step 4: and establishing a cost model of the charging station or the parking lot provided with the target automatic charging pile.
And 5: and establishing a profit model of the charging station or the parking lot provided with the target automatic charging pile.
Step 6: and (4) considering the punishment of the carbon emission of the power generation side of the power grid to the operation side of the charging pile, and introducing the punishment cost generated by the carbon emission into an economic model.
And 7: according to the models obtained in the steps, an economic model aiming at maximizing profit of the charging pile operation side is established;
and 8: and (4) solving the economic model obtained in the step (7) by adopting a particle swarm algorithm to obtain the optimal number of the automatic charging piles of the parking lot or the charging station with the target automatic charging piles and the optimal number of the single automatic charging pile matched with the automobile.
According to the method for matching the number of the new energy vehicles in the automatic charging piles, the parking lot or the charging station provided with the target automatic charging piles is constructed in a mode that m target automatic charging piles are built together, and each target automatic charging pile can serve electric vehicles parked in n parking spaces around the target automatic charging pile. However, at the same time, one target automatic charging pile can only charge one electric vehicle in n parking spaces around the target automatic charging pile, and the target automatic charging pile can decide when to charge the electric vehicle according to a corresponding scheduling method. As shown in fig. 2, the number of target automatic charging piles is m =3, and one charging pile matches the number of cars n = 4.
For the statistical analysis process described in step 1, for different scenes, the charging habits of the target user group can be statistically analyzed according to different statistical methods.
For an application scene with a relatively fixed target user group, such as a residential district parking lot, the charging habit information set of all users with charging requirements in the residential district can be acquired in a field investigation mode
Figure 764688DEST_PATH_IMAGE030
Wherein x is the total number of users having charging requirements in the cell, and the information required to be obtained for each user includes
Figure 320434DEST_PATH_IMAGE031
，
Figure 200666DEST_PATH_IMAGE032
For the purpose of the charging frequency, it is,
Figure 841862DEST_PATH_IMAGE033
for the duration of a single charge,
Figure 964277DEST_PATH_IMAGE034
is the charging start time.
For application scenes with relatively random target user groups, such as underground garages of shopping malls, a Gaussian process method can be adopted to predict the market operation time period
Figure 374530DEST_PATH_IMAGE035
Electric automobile quantity curve entering garage at any momentx(T)Predicting the charging time period requirement of each electric vehicle shown in fig. 3 by using the monte carlo methodProbability density curve of t, assuming it follows a normal distribution
Figure 425662DEST_PATH_IMAGE036
Wherein, in the step (A),
Figure 554155DEST_PATH_IMAGE037
the average value of the required charging time of all the electric vehicles,
Figure 214682DEST_PATH_IMAGE038
is the standard deviation. According to the curvex(T)Sum mean value
Figure 213862DEST_PATH_IMAGE039
The curve of the number of the cars needing to be charged at each moment of the underground garage of the market can be approximately predictedx req (T)。
For the charging demand model described in step 2, for a general charging station or parking lot, the maximum number of vehicles entering is less than the total number of parking spaces, that is, the charging demand model is satisfied
Figure 435896DEST_PATH_IMAGE009
。
Wherein the content of the first and second substances,N max for maximum number of vehicles entering the charging station, for a cell parking lot,N max taking the total number x of electric automobile users in the community, for an underground garage of a shopping mall,N max taking the curve obtained abovex req (T)Is measured.
Meanwhile, the charging station or the parking lot should meet the charging duration requirement of most electric vehicle users as much as possible, but under the condition of being extremely busy, a small part of requirements cannot be met, and the charging station or the parking lot is required to meet at least 90% of charging requirements. The total charging time provided by the charging pile should meet the requirement
Figure 51685DEST_PATH_IMAGE040
。
Wherein the content of the first and second substances,t ope for charging station operating time (hours), for a cellParking lot retrievablet ope =24For the underground garage of the market, it is advisablet ope The time of the market business.
Figure 250323DEST_PATH_IMAGE006
The total charging requirement duration of all electric vehicle users can be calculated according to the user charging habit information set A for the residential area parking lot; for the underground garage of the market, the curve can be usedx(T)And average of charge duration requirements
Figure 104009DEST_PATH_IMAGE038
An approximate estimate is obtained.
For the charging pile time utilization rate model in the step 3, the charging pile time utilization rate can be expressed as
Figure 762524DEST_PATH_IMAGE041
Wherein
Figure 600030DEST_PATH_IMAGE008
The sum of the idle time of all charging piles can be calculated according to the charging habit information set A of the user for the parking lot of the residential area; for the underground garage of the market, the garage can be used according to the curvex(T)And average of charge duration requirements
Figure 369402DEST_PATH_IMAGE038
An approximate estimate is obtained.
In order to achieve the aim of improving the utilization rate of the charging pile, the obtained time utilization rate of the charging pile is greater than a given valuer lim I.e. by
Figure 310551DEST_PATH_IMAGE042
。
For the cost model in step 4, the cost model of the charging station is composed of three parts, namely construction cost, maintenance cost and electricity purchasing cost.
Construction cost
Figure 874388DEST_PATH_IMAGE014
Wherein
Figure 199190DEST_PATH_IMAGE015
In order to reduce the construction cost of a single charging pile,
Figure 5210DEST_PATH_IMAGE043
whereinC p In order to charge the cost of the pile body,C m for the cost of the robot arm and the attached devices,
Figure 99068DEST_PATH_IMAGE044
，
Figure 833805DEST_PATH_IMAGE045
the cost of the automatic charging mechanical arm and the accessory device corresponding to one parking space is reduced.
Cost of maintenance
Figure 645904DEST_PATH_IMAGE046
Wherein
Figure 22658DEST_PATH_IMAGE017
In order to account for the maintenance costs of a single charging post,
Figure 227416DEST_PATH_IMAGE017
when n does not exceed a critical value ncTime, linear with n:
Figure 133055DEST_PATH_IMAGE047
whereink 1 For maintenance cost
Figure 432450DEST_PATH_IMAGE048
The scaling factor by which the value is increased,
Figure 81737DEST_PATH_IMAGE049
to keep the basic maintenance costs unaffected by n,
Figure 648722DEST_PATH_IMAGE050
is the maximum value of the maintenance cost.
Cost of electricity purchase
Figure 990842DEST_PATH_IMAGE051
Wherein
Figure 511953DEST_PATH_IMAGE052
For the power price of the power grid in a certain period of time, according to the time-of-use power price curve of the power grid
Figure 699352DEST_PATH_IMAGE053
Determining:
Figure 887888DEST_PATH_IMAGE054
；P EV the average power for charging one charging pile can be given according to the average value of the quick charging power of a common electric automobile in order to improve the charging efficiency;
Figure 633865DEST_PATH_IMAGE055
the utilization time of one charging pile is provided.
Charging station revenue model for step 5 charging station revenueG=G e +G s 。
WhereinG e In order to make the charging profitable,
Figure 642272DEST_PATH_IMAGE056
，Q EV the charging electricity price established for the charging station can be given according to the consumption level of the construction position of the charging station;
G s in order to make a service gain possible,
Figure 898941DEST_PATH_IMAGE057
，Lconsidering that the larger n is, the longer the waiting time is expected by the user, the service fee is basically reduced according to the value of n,k 2 the proportionality coefficient for the service charge reduction is given according to the psychological characteristics of the users in the region.
For the carbon emission model in the step 6, certain punishment is carried out on the charging station by considering the carbon emission and the carbon price of the power generation at the power grid side, and the punishment on the carbon emission is carried out
Figure 941983DEST_PATH_IMAGE058
Wherein
Figure 593282DEST_PATH_IMAGE059
The carbon emission generated by power generation at different time intervals on the power grid side can be given according to the actual condition of a local power plant;
Figure 88986DEST_PATH_IMAGE060
the carbon value per carbon emission can be referred to as a given value.
For the economic model in the step 7, the objective function of maximizing the profit of the charging pile operation side is
Figure 149345DEST_PATH_IMAGE012
Wherein
Figure 46894DEST_PATH_IMAGE013
The impact factor for carbon emissions in the charging station economy model may be given according to the region in consideration of the importance of carbon emissions.
The constraint condition is
Figure 636139DEST_PATH_IMAGE061
。
For the optimal solution described in step 8, the particle swarm algorithm objective function is adopted to solve the optimal solution, so that the optimal solution of the number m of charging piles and the number n of vehicles matched with a single charging pile, which maximizes the profit of the operation side of the charging pile, is obtained.
Example two
As shown in fig. 4, the method for matching the number of the automatic charging piles of the new energy automobile provided by the embodiment includes:
step 401: determining an application scene of a target automatic charging pile, and executing a first operation 402 when the application scene is a fixed application scene, and executing a second operation 403 when the application scene is a random application scene; the target automatic charging pile is an automatic charging pile for multiple vehicles.
The first operation 402 is performed by:
and determining a construction mode of the target automatic charging pile in the fixed application scene.
Determining the charging requirements of a target user group; the charging requirement comprises the total number of users with the charging requirement, the charging frequency corresponding to each user, single expected charging time and charging starting time.
Determining a first set of constraints based on the charging demand and the construction mode; the first constraint set comprises three constraint conditions, wherein the total number of users with charging demands is smaller than or equal to a first value, the time length of 0.9 time of the total charging demands is smaller than or equal to a second value, and the time utilization rate of the charging pile is larger than or equal to a third value.
Determining the number of the target automatic charging piles and the number of electric vehicles matched with each target automatic charging pile based on the first constraint set and an objective function; the objective function is a function aiming at maximizing profit of a charging pile operator side.
The second operation 403 is executed as follows:
and determining a construction mode of the target automatic charging pile in the random application scene.
Determining an electric vehicle quantity curve of the random application scene; the electric vehicle number curve represents the number of electric vehicles which need to be charged at each moment in a specified time period.
Determining a second constraint set according to the electric vehicle quantity curve and the construction mode; the second constraint set comprises three constraint conditions, namely that the maximum value is less than or equal to a fourth value, 0.9 time of total charging demand time is less than or equal to a fifth value, and the time utilization rate of the charging pile is greater than or equal to a sixth value; the maximum value is the maximum value of the number of the electric automobiles in the electric automobile number curve.
And determining the number of the target automatic charging piles and the number of the electric automobiles matched with each target automatic charging pile based on the second constraint set and an objective function.
The construction mode is a mode of co-constructing m target automatic charging piles, and each target automatic charging pile serves electric vehicles parked on n parking spaces around.
The determining of the electric vehicle quantity curve of the random application scene specifically includes:
prediction of random application scenarios using gaussian process methodsTMoment electric automobile quantity curvex(T)。
Method for predicting charging time requirements of electric vehicles in random application scene by using Monte Carlo methodtProbability density curve of (1).
Based on the electric automobile quantity curvex(T)And the probability density curve is used for determining the number of the electric automobiles needing to be charged at each moment in the specified time period of the random application scene, so that the electric automobile number curve of the random application scene is obtained.
Optionally, the first constraint set includes three constraint conditions, which are respectively:
Figure 117673DEST_PATH_IMAGE001
（1）；
Figure 716145DEST_PATH_IMAGE002
（2）；
Figure 310943DEST_PATH_IMAGE003
（3）；
wherein the content of the first and second substances,N max indicating the total number of users having a need for charging,
Figure 539930DEST_PATH_IMAGE004
represents a first value;t ope represents the operation time of the target automatic charging pile,
Figure 744647DEST_PATH_IMAGE005
a second value is represented which is a function of,
Figure 848607DEST_PATH_IMAGE006
which indicates the total charge demand period of time,t req indicating a charging time period required by a user;r lim which is indicative of a third value of the value,
Figure 720748DEST_PATH_IMAGE007
，
Figure 917374DEST_PATH_IMAGE008
the sum of the idle times of the automatic charging piles is taken for all targets.
The second constraint set includes three constraint conditions, which are:
Figure 343807DEST_PATH_IMAGE009
（1）；
Figure 782616DEST_PATH_IMAGE010
（2）；
Figure 978105DEST_PATH_IMAGE011
（3）；
wherein the content of the first and second substances,N max the maximum value is represented by the number of lines,
Figure 814474DEST_PATH_IMAGE004
represents a fourth value;t ope represents the operation time of the target automatic charging pile,
Figure 259362DEST_PATH_IMAGE005
a fifth value is represented as a function of,
Figure 705125DEST_PATH_IMAGE006
which indicates the total charge demand period of time,t req indicating a charging time period required by a user;r lim a sixth value is represented as a function of,
Figure 286279DEST_PATH_IMAGE007
，
Figure 824708DEST_PATH_IMAGE008
the sum of the idle times of the automatic charging piles is taken for all targets.
The construction process of the objective function comprises the following steps:
constructing a cost function; the cost function includes construction cost, maintenance cost and electricity purchase cost.
Constructing a revenue function; the revenue function includes charging revenue and service revenue.
And constructing a carbon emission penalty function.
And determining a target function according to the cost function, the income function and the carbon emission penalty function.
The objective function is
Figure 724268DEST_PATH_IMAGE012
；
Wherein the content of the first and second substances,
Figure 6345DEST_PATH_IMAGE013
is a carbon emission influencing factor.
Construction cost:
Figure 442006DEST_PATH_IMAGE014
，
Figure 151336DEST_PATH_IMAGE015
and (5) the construction cost of the ith target automatic charging pile is obtained, and m represents the number of the target automatic charging piles.
Maintenance cost:
Figure 305236DEST_PATH_IMAGE016
，
Figure 889539DEST_PATH_IMAGE017
and (5) automatically charging the maintenance cost of the ith target.
The electricity purchasing cost is as follows:
Figure 179706DEST_PATH_IMAGE018
；
Figure 794358DEST_PATH_IMAGE019
is the electricity price in the time period t.P EV The average charging power of a target automatic charging pile,
Figure 169976DEST_PATH_IMAGE020
automatically charging the utilization time of a pile for a target;t ope representing the operation time of an automatic target charging pile;
Figure 292391DEST_PATH_IMAGE021
，
Figure 437064DEST_PATH_IMAGE022
the sum of the idle times of the automatic charging piles is taken for all targets.
And (4) yield:G=G e +G s ，G e in order to make the charging profitable,
Figure 222618DEST_PATH_IMAGE023
，Q EV charging electricity price formulated for the target automatic charging pile;G s in order to make a service gain possible,
Figure 351111DEST_PATH_IMAGE024
，Lin order to be a basic service charge,k 2 and n is the number of the electric vehicles served by the target automatic charging pile for the proportionality coefficient of service charge reduction.
Carbon emission penalty:
Figure 11637DEST_PATH_IMAGE025
，
Figure 541975DEST_PATH_IMAGE026
the amount of carbon emissions generated for power generation on the grid side during the period t,
Figure 29588DEST_PATH_IMAGE027
is the carbon number per unit carbon emission.
EXAMPLE III
As shown in fig. 5, the automatic electric pile quantity matching system that fills that this embodiment provided includes:
an application scenario determining module 501, configured to determine an application scenario of the target automatic charging pile, execute a first sub-module when the application scenario is a fixed application scenario, and execute a second sub-module when the application scenario is a random application scenario; the target automatic charging pile is an automatic charging pile for multiple vehicles.
The first sub-module 502 includes:
and the first construction mode determining unit is used for determining the construction mode of the automatic charging pile for the target in the fixed application scene.
The charging demand determining unit is used for determining the charging demand of a target user group; the charging requirement comprises the total number of users with the charging requirement, the charging frequency corresponding to each user, single expected charging time and charging starting time.
A first constraint set determination unit configured to determine a first constraint set based on the charging demand and the construction mode; the first constraint set comprises three constraint conditions, wherein the total number of users with charging demands is smaller than or equal to a first value, the time length of 0.9 time of the total charging demands is smaller than or equal to a second value, and the time utilization rate of the charging pile is larger than or equal to a third value.
The first optimization unit is used for determining the number of the target automatic charging piles and the number of the electric vehicles matched with each target automatic charging pile based on the first constraint set and an objective function; the objective function is a function aiming at maximizing profit of a charging pile operator side.
The second sub-module 503 includes:
and the second construction mode determining unit is used for determining the construction mode of the target automatic charging pile in the random application scene.
The electric vehicle quantity curve determining unit is used for determining an electric vehicle quantity curve of the random application scene; the electric vehicle number curve represents the number of electric vehicles which need to be charged at each moment in a specified time period.
The second constraint set determining unit is used for determining a second constraint set according to the electric vehicle quantity curve and the construction mode; the second constraint set comprises three constraint conditions, namely that the maximum value is less than or equal to a fourth value, 0.9 time of total charging demand time is less than or equal to a fifth value, and the time utilization rate of the charging pile is greater than or equal to a sixth value; the maximum value is the maximum value of the number of the electric automobiles in the electric automobile number curve.
The second optimization unit is used for determining the number of the target automatic charging piles and the number of the electric vehicles matched with each target automatic charging pile based on the second constraint set and an objective function; the objective function is a function which aims at maximizing profit of the charging pile operation side.
The construction mode is a mode of co-constructing m target automatic charging piles, and each target automatic charging pile serves electric vehicles parked on n parking spaces around.
The objective function is
Figure 114219DEST_PATH_IMAGE012
；
Wherein the content of the first and second substances,
Figure 345480DEST_PATH_IMAGE013
is a carbon emission influencing factor.
Construction cost:
Figure 228860DEST_PATH_IMAGE014
，
Figure 887375DEST_PATH_IMAGE015
and (5) the construction cost of the ith target automatic charging pile is obtained, and m represents the number of the target automatic charging piles.
Maintenance cost:
Figure 990460DEST_PATH_IMAGE016
，
Figure 759833DEST_PATH_IMAGE017
the maintenance cost of the automatic charging pile for the ith target;
the electricity purchasing cost is as follows:
Figure 999184DEST_PATH_IMAGE018
；
Figure 327135DEST_PATH_IMAGE019
the electricity price in the time period t;P EV the average charging power of a target automatic charging pile,
Figure 651937DEST_PATH_IMAGE020
automatically charging the utilization time of a pile for a target;t ope representing the operation time of an automatic target charging pile;
Figure 225001DEST_PATH_IMAGE021
，
Figure 584438DEST_PATH_IMAGE022
the sum of the idle times of the automatic charging piles is taken for all targets.
And (4) yield:G=G e +G s ，G e in order to make the charging profitable,
Figure 584755DEST_PATH_IMAGE023
，Q EV charging electricity price formulated for the target automatic charging pile;G s in order to make a service gain possible,
Figure 662433DEST_PATH_IMAGE024
，Lin order to be a basic service charge,k 2 and n is the number of the electric vehicles served by the target automatic charging pile for the proportionality coefficient of service charge reduction.
Carbon emission penalty:
Figure 272143DEST_PATH_IMAGE025
，
Figure 486087DEST_PATH_IMAGE026
the amount of carbon emissions generated for power generation on the grid side during the period t,
Figure 657305DEST_PATH_IMAGE027
is the carbon number per unit carbon emission.
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. For the system disclosed by the embodiment, the description is relatively simple because the system corresponds to the method disclosed by the embodiment, and the relevant points can be referred to the method part for description.
The principles and embodiments of the present invention have been described herein using specific examples, which are provided only to help understand the method and the core concept of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.

Claims (10)

1. The utility model provides a new energy automobile automatic charging pile quantity matching method which is characterized by comprising the following steps:
determining an application scene of a target automatic charging pile, executing a first operation when the application scene is a fixed application scene, and executing a second operation when the application scene is a random application scene; the target automatic charging pile is an automatic charging pile for multiple vehicles;
the execution process of the first operation is as follows:
determining a construction mode of an automatic target charging pile in the fixed application scene;
determining the charging requirements of a target user group; the charging requirement comprises the total number of users with the charging requirement, the charging frequency corresponding to each user, single expected charging time and charging starting time;
determining a first set of constraints based on the charging demand and the construction mode; the first constraint set comprises three constraint conditions, wherein the total number of users with charging requirements is less than or equal to a first value, the 0.9 time duration of the total charging requirements is less than or equal to a second value, and the time utilization rate of the charging pile is greater than or equal to a third value;
determining the number of the target automatic charging piles and the number of electric vehicles matched with each target automatic charging pile based on the first constraint set and an objective function; the objective function is a function which aims at maximizing profit of a charging pile operator side;
the execution process of the second operation is as follows:
determining a construction mode of an automatic target charging pile in the random application scene;
determining an electric vehicle quantity curve of the random application scene; the electric vehicle quantity curve represents the quantity of electric vehicles which need to be charged at each moment in a specified time period;
determining a second constraint set according to the electric vehicle quantity curve and the construction mode; the second constraint set comprises three constraint conditions, namely that the maximum value is less than or equal to a fourth value, 0.9 time of total charging demand time is less than or equal to a fifth value, and the time utilization rate of the charging pile is greater than or equal to a sixth value; the maximum value is the maximum value of the number of the electric automobiles in the electric automobile number curve;
and determining the number of the target automatic charging piles and the number of the electric automobiles matched with each target automatic charging pile based on the second constraint set and an objective function.
2. The method for matching the number of the new energy automobile automatic charging piles according to claim 1, wherein the construction mode is a mode in which m target automatic charging piles are built together, and each target automatic charging pile serves electric automobiles parked in n surrounding parking spaces.
3. The method for matching the number of the automatic charging piles of the new energy automobile according to claim 1, wherein the determining of the electric automobile number curve of the random application scene specifically comprises:
prediction of random application scenarios using gaussian process methods
Figure 772191DEST_PATH_IMAGE001
Moment electric automobile quantity curve
Figure 882230DEST_PATH_IMAGE002
；
Method for predicting charging time requirements of electric vehicles in random application scene by using Monte Carlo method
Figure 302847DEST_PATH_IMAGE003
A probability density curve of (a);
based on the electric automobile quantity curve
Figure 680476DEST_PATH_IMAGE002
And the probability density curve is used for determining the number of the electric automobiles needing to be charged at each moment in the specified time period of the random application scene, so that the electric automobile number curve of the random application scene is obtained.
4. The method for matching the number of the automatic charging piles of the new energy automobile according to claim 2, wherein the first constraint set comprises three constraint conditions which are respectively as follows:
Figure 528346DEST_PATH_IMAGE004
（1）；
Figure 125681DEST_PATH_IMAGE005
（2）；
Figure 84410DEST_PATH_IMAGE006
（3）；
wherein the content of the first and second substances,
Figure 83590DEST_PATH_IMAGE007
indicating the total number of users having a need for charging,
Figure 836782DEST_PATH_IMAGE008
represents a first value;
Figure 419948DEST_PATH_IMAGE009
represents the operation time of the target automatic charging pile,
Figure 916788DEST_PATH_IMAGE010
a second value is represented which is a function of,
Figure 832792DEST_PATH_IMAGE011
which indicates the total charge demand period of time,
Figure 960148DEST_PATH_IMAGE012
indicating a charging time period required by a user;
Figure 328812DEST_PATH_IMAGE013
which is indicative of a third value of the value,
Figure 65562DEST_PATH_IMAGE014
，
Figure 836072DEST_PATH_IMAGE015
the sum of the idle times of the automatic charging piles is taken for all targets.
5. The method for matching the number of the automatic charging piles of the new energy automobile according to claim 2, wherein the second constraint set comprises three constraint conditions which are respectively as follows:
Figure 399908DEST_PATH_IMAGE004
（1）；
Figure 990290DEST_PATH_IMAGE005
（2）；
Figure 94512DEST_PATH_IMAGE006
（3）；
wherein the content of the first and second substances,
Figure 922790DEST_PATH_IMAGE007
the maximum value is represented by the number of lines,
Figure 952801DEST_PATH_IMAGE008
represents a fourth value;
Figure 233741DEST_PATH_IMAGE016
represents the operation time of the target automatic charging pile,
Figure 610496DEST_PATH_IMAGE010
a fifth value is represented as a function of,
Figure 355598DEST_PATH_IMAGE011
which indicates the total charge demand period of time,
Figure 792395DEST_PATH_IMAGE017
indicating a charging time period required by a user;
Figure 560631DEST_PATH_IMAGE018
a sixth value is represented as a function of,
Figure 239612DEST_PATH_IMAGE014
，
Figure 839220DEST_PATH_IMAGE015
the sum of the idle times of the automatic charging piles is taken for all targets.
6. The method for matching the number of the automatic charging piles of the new energy automobile according to claim 1, wherein the construction process of the objective function is as follows:
constructing a cost function; the cost function comprises construction cost, maintenance cost and electricity purchasing cost;
constructing a revenue function; the revenue function comprises charging revenue and service revenue;
constructing a carbon emission penalty function;
and determining a target function according to the cost function, the income function and the carbon emission penalty function.
7. The method for matching the number of the automatic charging piles of the new energy automobile according to claim 1, wherein the objective function is
Figure 446919DEST_PATH_IMAGE019
；
Wherein the content of the first and second substances,
Figure 702451DEST_PATH_IMAGE020
is a carbon emission influencing factor;
construction cost:
Figure 686588DEST_PATH_IMAGE021
，
Figure 875124DEST_PATH_IMAGE022
the construction cost of the ith target automatic charging pile is calculated, and m represents the number of the target automatic charging piles;
maintenance cost:
Figure 919303DEST_PATH_IMAGE023
，
Figure 957404DEST_PATH_IMAGE024
the maintenance cost of the automatic charging pile for the ith target;
the electricity purchasing cost is as follows:
Figure 682914DEST_PATH_IMAGE025
；
Figure 991536DEST_PATH_IMAGE026
the electricity price in the time period t;
Figure 206617DEST_PATH_IMAGE027
the average charging power of a target automatic charging pile,
Figure 436741DEST_PATH_IMAGE028
automatically charging the utilization time of a pile for a target;
Figure 497101DEST_PATH_IMAGE009
representing the operation time of an automatic target charging pile;
Figure 158764DEST_PATH_IMAGE014
，
Figure 810325DEST_PATH_IMAGE015
the sum of the idle time of all the target automatic charging piles is obtained;
and (4) yield:
Figure 262166DEST_PATH_IMAGE029
，
Figure 126217DEST_PATH_IMAGE030
in order to make the charging profitable,
Figure 675010DEST_PATH_IMAGE031
，
Figure 966314DEST_PATH_IMAGE032
charging electricity price formulated for the target automatic charging pile;
Figure 239924DEST_PATH_IMAGE033
in order to make a service gain possible,
Figure 173245DEST_PATH_IMAGE034
，
Figure 310965DEST_PATH_IMAGE035
in order to be a basic service charge,
Figure 773171DEST_PATH_IMAGE036
a proportionality coefficient for service charge reduction, n being the number of electric vehicles served by a target automatic charging pile;
carbon emission penalty:
Figure 199604DEST_PATH_IMAGE037
，
Figure 405457DEST_PATH_IMAGE038
the amount of carbon emissions generated for power generation on the grid side during the period t,
Figure 663263DEST_PATH_IMAGE039
is the carbon number per unit carbon emission.
8. The utility model provides an automatic electric pile quantity matching system that fills of new energy automobile which characterized in that includes:
the application scene determining module is used for determining an application scene of the target automatic charging pile, executing a first sub-module when the application scene is a fixed application scene, and executing a second sub-module when the application scene is a random application scene; the target automatic charging pile is an automatic charging pile for multiple vehicles;
the first sub-module includes:
the first construction mode determining unit is used for determining a construction mode of the automatic target charging pile in the fixed application scene;
the charging demand determining unit is used for determining the charging demand of a target user group; the charging requirement comprises the total number of users with the charging requirement, the charging frequency corresponding to each user, single expected charging time and charging starting time;
a first constraint set determination unit configured to determine a first constraint set based on the charging demand and the construction mode; the first constraint set comprises three constraint conditions, wherein the total number of users with charging requirements is less than or equal to a first value, the 0.9 time duration of the total charging requirements is less than or equal to a second value, and the time utilization rate of the charging pile is greater than or equal to a third value;
the first optimization unit is used for determining the number of the target automatic charging piles and the number of the electric vehicles matched with each target automatic charging pile based on the first constraint set and an objective function; the objective function is a function which aims at maximizing profit of a charging pile operator side;
the second sub-module includes:
the second construction mode determining unit is used for determining a construction mode of the target automatic charging pile in the random application scene;
the electric vehicle quantity curve determining unit is used for determining an electric vehicle quantity curve of the random application scene; the electric vehicle quantity curve represents the quantity of electric vehicles which need to be charged at each moment in a specified time period;
the second constraint set determining unit is used for determining a second constraint set according to the electric vehicle quantity curve and the construction mode; the second constraint set comprises three constraint conditions, namely that the maximum value is less than or equal to a fourth value, 0.9 time of total charging demand time is less than or equal to a fifth value, and the time utilization rate of the charging pile is greater than or equal to a sixth value; the maximum value is the maximum value of the number of the electric automobiles in the electric automobile number curve;
the second optimization unit is used for determining the number of the target automatic charging piles and the number of the electric vehicles matched with each target automatic charging pile based on the second constraint set and an objective function; the objective function is a function which aims at maximizing profit of the charging pile operation side.
9. The system according to claim 8, wherein the construction mode is a mode in which m target automatic charging piles are built together, and each target automatic charging pile serves electric vehicles parked in n surrounding parking spaces.
10. The system according to claim 8, wherein the objective function is
Figure 60484DEST_PATH_IMAGE019
；
Wherein the content of the first and second substances,
Figure 974214DEST_PATH_IMAGE020
is a carbon emission influencing factor;
construction cost:
Figure 983758DEST_PATH_IMAGE021
，
Figure 299333DEST_PATH_IMAGE022
the construction cost of the ith target automatic charging pile is calculated, and m represents the number of the target automatic charging piles;
maintenance cost:
Figure 103341DEST_PATH_IMAGE023
，
Figure 566683DEST_PATH_IMAGE024
the maintenance cost of the automatic charging pile for the ith target;
the electricity purchasing cost is as follows:
Figure 816137DEST_PATH_IMAGE025
；
Figure 782956DEST_PATH_IMAGE026
the electricity price in the time period t;
Figure 289023DEST_PATH_IMAGE027
the average charging power of a target automatic charging pile,
Figure 708503DEST_PATH_IMAGE028
automatically charging the utilization time of a pile for a target;
Figure 263113DEST_PATH_IMAGE009
representing the operation time of an automatic target charging pile;
Figure 84438DEST_PATH_IMAGE014
，
Figure 994363DEST_PATH_IMAGE015
the sum of the idle time of all the target automatic charging piles is obtained;
and (4) yield:
Figure 166718DEST_PATH_IMAGE029
，
Figure 56177DEST_PATH_IMAGE030
in order to make the charging profitable,
Figure 200850DEST_PATH_IMAGE031
，
Figure 783141DEST_PATH_IMAGE032
charging electricity price formulated for the target automatic charging pile;
Figure 442793DEST_PATH_IMAGE033
in order to make a service gain possible,
Figure 135942DEST_PATH_IMAGE034
，
Figure 368078DEST_PATH_IMAGE035
in order to be a basic service charge,
Figure 121271DEST_PATH_IMAGE036
a proportionality coefficient for service charge reduction, n being the number of electric vehicles served by a target automatic charging pile;
carbon emission penalty:
Figure 2639DEST_PATH_IMAGE037
，
Figure 765059DEST_PATH_IMAGE038
the amount of carbon emissions generated for power generation on the grid side during the period t,
Figure 415483DEST_PATH_IMAGE039
is the carbon number per unit carbon emission.
CN202111565259.7A 2021-12-21 2021-12-21 New energy automobile automatic charging pile quantity matching method and system Pending CN113962613A (en)

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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115660223A (en) * 2022-12-12 2023-01-31 佛山隆深机器人有限公司 Big data based hydrogenation scheduling system and method
CN117081059A (en) * 2023-08-24 2023-11-17 国网北京市电力公司 Optimal control method, device, equipment and medium for charging and replacing power station cluster
CN117875672A (en) * 2024-03-11 2024-04-12 云南山高新能源有限公司 Electric vehicle charging station management system

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115660223A (en) * 2022-12-12 2023-01-31 佛山隆深机器人有限公司 Big data based hydrogenation scheduling system and method
CN115660223B (en) * 2022-12-12 2023-04-11 佛山隆深机器人有限公司 Big data-based hydrogenation scheduling system and method
CN117081059A (en) * 2023-08-24 2023-11-17 国网北京市电力公司 Optimal control method, device, equipment and medium for charging and replacing power station cluster
CN117081059B (en) * 2023-08-24 2024-06-11 国网北京市电力公司 Optimal control method, device, equipment and medium for charging and replacing power station cluster
CN117875672A (en) * 2024-03-11 2024-04-12 云南山高新能源有限公司 Electric vehicle charging station management system
CN117875672B (en) * 2024-03-11 2024-06-04 云南山高新能源有限公司 Electric vehicle charging station management system

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Application publication date: 20220121