CN107618392A - The charging electric vehicle load Stochastic accessing control system and method for charging pile self-decision - Google Patents
The charging electric vehicle load Stochastic accessing control system and method for charging pile self-decision Download PDFInfo
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- CN107618392A CN107618392A CN201710910375.5A CN201710910375A CN107618392A CN 107618392 A CN107618392 A CN 107618392A CN 201710910375 A CN201710910375 A CN 201710910375A CN 107618392 A CN107618392 A CN 107618392A
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- 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
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- 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
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- 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
-
- 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
- Y02T90/16—Information or communication technologies improving the operation of electric vehicles
Abstract
The present invention relates to the charging electric vehicle load Stochastic accessing control system and method for a kind of charging pile self-decision, belong to electric automobile intelligent charge field.The system includes control decision maker and some intelligent charging spots, control decision maker obtains current control area electricity price and load information, and according to load curve, the accidental access method designed by the present invention, calculate charging initial time probability distribution corresponding to the user of different charging durations, and control instruction is issued to each intelligent charging spot, the time finally started to charge up according to the determine the probability of respective accessing user by charging pile.This method has good peak load shifting effect, network load fluctuation can be stabilized, reduce automobile user charging cost, and whole control flow is by control area equipment complete independently, communication and control without centralization, it is easy to implement, system cost is low, is charged in order suitable for fairly large private savings electric automobile residential area.
Description
Technical field
The invention belongs to electric automobile intelligent charge field, is related to a kind of charging electric vehicle load of charging pile self-decision
Stochastic accessing control system and method.
Background technology
In today that energy and environment problem is prominent all the more, electric automobile is as the cleaning new energy vehicles just by people
Increasing concern.As electric automobile popularity rate is constantly increasing, problem is also following, because network system lacks
Necessary control device, being arrived when peak times of power consumption, a large amount of unordered chargings of electric automobile will cause huge impact to power network,
Easily cause overload, threaten power grid security with stably.Specially increase power equipment capacity if peak of power consumption is dealt with, meeting again
Electric cost is raised, reduces electric power resource utilization rate.
A large amount of theoretical researches show with emulation measured result, if energy reasonable arrangement charging electric vehicle behavior, makes full use of
Power distribution network paddy period resource, existing electric power resource deposit can meet charging electric vehicle demand completely.Charging electric vehicle
Load Stochastic accessing is the study hotspot of new energy field at present, is badly in need of a set of effective charge control strategy in order, helps to match somebody with somebody
Power network peak load shifting, load fluctuation is stabilized, reduce user's charging cost.
The content of the invention
In view of this, it is an object of the invention to provide a kind of charging electric vehicle load of charging pile self-decision to connect at random
Enter control system and method.
To reach above-mentioned purpose, the present invention provides following technical scheme：
A kind of charging electric vehicle load Stochastic accessing control system of charging pile self-decision, includes intelligent charging spot and control
Decision maker processed, the intelligent charging spot are connected by communication channel with control decision maker；
There is the control decision maker information to receive, parameter calculates and parameter issues function, and wherein information receives work(
It can be used to receiving and updating same day electricity price and information on load, and generate load curve；Parameter computing function is filled for obtaining starting
Electric moment probability density distribution table；Parameter issues function and initiation of charge moment probability density distribution table is sent into intelligent charge
Stake, make charging pile according to plan start and stop；
The intelligent charging spot receives the probability density distribution table from decision maker, and actually defeated according to electric automobile
The charging duration entered, the final start-stop charging interval is independently calculated, and charging work is carried out according to the time.
A kind of charging electric vehicle load random access control method of charging pile self-decision, this method are voluntarily joined all
Automobile user with charging in order is arranged in the unified control targe period and charged, and comprises the following steps：
S1：Control area load data generation load curve, determines control targe period start/stop time；
S2：Divide control targe period and charging duration：Objective time interval is divided into N number of portion by control decision maker first
Point, and the charging duration to accessing electric automobile carries out by stages processing according to Time segments division situation；
S3：Calculate objective time interval each several part load margin：By load prediction results a few days ago, control targe period routine is drawn
Load curve, set reference load value；According to load curve and reference load value, the N number of part for calculating control time division is right
Should be in the load margin of reference load value, result of calculation is using as the foundation for determining charging initial time probability distribution；
S4：Calculate charging initial time probability distribution：For different charging durations, charging is met before being left away with charge user
Premised on demand, satisfactory initiation of charge time range is obtained, and it is abundant to read load corresponding to various pieces in the range of this
Degree, load margin is higher, selects the probability in the part initial time charging bigger.
Further, step S2 is specially：Objective time interval is divided into N number of part, each part by control decision maker first
Length be set to M, then by access electric automobile charging duration be divided into following section：(0,1.5M),(1.5M,2.5M),…
((N-1.5)M,(N-0.5)M),((N-0.5)M,+∞)(0,1.5M)。
Further, in step S3, the reference load value is：During the control targe drawn according to load prediction results a few days ago
In section conventional load curve, a certain value not less than peak load in the period；
In step S3, the difference of load margin load value of each several part for the reference load value and in the period.
Further, also include before the step S1：The electric automobile that charges in order is participated in when accessing intelligent charging spot,
Exit time or demand state of charge information need to be inputted.
Further, also include after the step S4：The charged shape of exit time or demand that charging pile inputs according to user
State information calculates charging duration, according to section where charging duration, searches its corresponding initiation of charge moment probability distribution table, by
Probability distribution table determined using the initial time of which part of objective time interval as the time finally started to charge up at random, until
Charging terminates.
The beneficial effects of the present invention are：The present invention offer orderly charging scheme of Stochastic accessing can be realized will be a large amount of electronic
Automobile charging load is transferred to the electricity price paddy period so that the electric power resource of load valley period is fully used, and reaches peak clipping
Fill valley, the effect stabilized load fluctuation, reduce peak-valley difference, because a large amount of electric automobiles charge in paddy electricity valency, the charging of user
Cost will substantially reduce, and reach the doulbe-sides' victory of grid side and user side interests.Control flow of the present invention receives and renewal electricity except online
Outside valency and load data, remaining flow can be achieved in internal system, and the charging pile odd-numbered day need to only receive a control instruction, nothing
Need, in real time with master station communication or communicating with one another, without the communication and control of centralization, to be easy to implement, cost is relatively low, suitable for compared with
Charged in order extensive private savings electric automobile residential area.
Brief description of the drawings
In order that the purpose of the present invention, technical scheme and beneficial effect are clearer, the present invention provides drawings described below and carried out
Explanation：
Fig. 1 provides charging electric vehicle load Stochastic accessing control system Organization Chart for the present invention；
Fig. 2 calculates schematic diagram for paddy period load margin in the present invention.
Fig. 3 is control strategy flow chart of the present invention.
Embodiment
Below in conjunction with accompanying drawing, the preferred embodiments of the present invention are described in detail.
Present example provides a kind of charging electric vehicle load Stochastic accessing control system, the system architecture such as Fig. 1 institutes
Show, include charging strategy controller and more coupled intelligent charging spots.The charging strategy controller has information
The function with handling, control instruction issues is received, wherein information receives is used to receive same day electricity price and load letter with processing function
Breath, load prediction results a few days ago are read, and thus formulate paddy next day, law of electric charges period；Control instruction issues function and will had determined that
Law of electric charges be sent to every intelligent charging spot, make each charging pile by regular start and stop, realize charging in order.The intelligent charge
Stake is kept communicating with charging strategy controller, and itself start and stop is controlled according to control instruction；User is accessing the intelligent charging spot
When, charging duration information need to be provided, and choose whether to participate in charge in order；The intelligent charging spot perform in order charging when with
Trickle charge pattern is charged, it is characterised in that charge power is held essentially constant.
Present example also provides a kind of charging electric vehicle load random access control method of charging pile self-decision, should
The automobile user that all non-valley rate periods access intelligent charging spot and are willing to participate in charging in order is arranged in by method to be worked as
Evening to next day paddy rate period is uniformly charged.This method comprises the following steps：
Step 1：The paddy period is divided：System is N number of part first by paddy Time segments division, if paddy Period Length is 8
Hour, then it can be that interval is divided into 8 deciles with 1 hour, also can further be segmented according to required precision.
Step 2：Each several part load margin after calculating the paddy period respectively：By load prediction results a few days ago, show that the paddy period is normal
Load curve is advised, chooses a certain value not less than paddy period peak load as reference load value, the value and remaining each several part
The difference of load value is the load margin of corresponding part；
Step 3：Each charging duration is generated to inductive charging initial time probability density distribution：If per partial-length after N deciles
For M, following section will be divided the charging interval into：(0,1.5M),(1.5M,2.5M),…((N-1.5)M,(N-0.5)M),((N-
0.5)M,+∞)(0,1.5M).To ensure that target electric automobile completes predetermined charging duration within the paddy period, it is corresponding with per section
Different initiation of charge time ranges, each several part period each self-corresponding load margin within the range and load margin sum
Ratio, be the part-time turn into the initiation of charge time probability.
2 it is specifically described embodiments of the present invention below in conjunction with the accompanying drawings.Example is by the paddy period (23 in accompanying drawing 2:00-7:00)
Divide 8 deciles into, it is every partly to continue 1 hour.The user that now all kinds of satisfactions are participated in orderly charge condition is made such as by its duration that charges
Lower processing：
Duration charged in 7.5 hours and the above, gives tacit consent to 3:00 is midpoint, covers whole paddy period charging.
Duration charge below 7.5 hours, is distributed by following rule：
6.5-7.5 hour：When initial time may be scheduled on 23 or when 0, probability is respectively
5.5-6.5 hour：When initial time may be scheduled on 23,0,1, probability is respectively
1.5-5.5 hour arrangement method is by that analogy；
Less than 1.5 hours：Integral point when initial time is distributed in 23-6, probability are respectively
Wherein S represents each several part area in Fig. 2, and its meaning is load margin corresponding to the part.(total) the expression 1-8 areas of S
Domain total load nargin, S (1-7) represent the load margin of region 1 to 7, by that analogy；Px(Y beginnings) represents charging hourage using x in
The probability that the vehicle of the heart starts to charge up at the Y moment, such as P6(23 begin) represent charging hourage 5.5-6.5 hours vehicle in
The probability started to charge up when 23.
Need to leave in advance in above charging schedules if any user, then the charging interval corresponding be advanced to when being left with user
Between terminate simultaneously.
The present invention's divides functional control flow as shown in Figure 3.
Finally illustrate, preferred embodiment above is merely illustrative of the technical solution of the present invention and unrestricted, although logical
Cross above preferred embodiment the present invention is described in detail, it is to be understood by those skilled in the art that can be
Various changes are made to it in form and in details, without departing from claims of the present invention limited range.
Claims (6)
1. the charging electric vehicle load Stochastic accessing control system of a kind of charging pile self-decision, it is characterised in that include intelligence
Charging pile and control decision maker, the intelligent charging spot are connected by communication channel with control decision maker；
There is the control decision maker information to receive, parameter calculates and parameter issues function, and wherein information receive capabilities are used
In receiving and update same day electricity price and information on load, and generate load curve；When parameter computing function is used to obtain initiation of charge
Carve probability density distribution table；Parameter issues function and initiation of charge moment probability density distribution table is sent into intelligent charging spot, makes
Charging pile is according to plan start and stop；
The intelligent charging spot receives the probability density distribution table from decision maker, and actually entered according to electric automobile
Charge duration, the final start-stop charging interval is independently calculated, and carry out charging work according to the time.
2. the charging electric vehicle load random access control method of a kind of charging pile self-decision, it is characterised in that this method will
All automobile users for voluntarily participating in charging in order are arranged in the unified control targe period and charged, including following step
Suddenly：
S1：Control area load data generation load curve, determines control targe period start/stop time；
S2：Divide control targe period and charging duration：Objective time interval is divided into N number of part by control decision maker first, and
By stages processing is carried out according to Time segments division situation to the charging duration for accessing electric automobile；
S3：Calculate objective time interval each several part load margin：By load prediction results a few days ago, control targe period conventional load is drawn
Curve, set reference load value；According to load curve and reference load value, the N number of part for calculating control time division corresponds to
The load margin of reference load value, result of calculation is using as the foundation for determining charging initial time probability distribution；
S4：Calculate charging initial time probability distribution：For different charging durations, meet charge requirement before being left away with charge user
Premised on, satisfactory initiation of charge time range is obtained, and load margin corresponding to various pieces in the range of this is read, bear
Lotus nargin is higher, selects the probability in the part initial time charging bigger.
3. a kind of charging electric vehicle load random access control method of charging pile self-decision according to claim 2,
Characterized in that, step S2 is specially：Objective time interval is divided into N number of part, the length of each part by control decision maker first
Degree is set to M, then the charging duration for accessing electric automobile is divided into following section：(0,1.5M),(1.5M,2.5M),…((N-
1.5)M,(N-0.5)M),((N-0.5)M,+∞)(0,1.5M)。
4. a kind of charging electric vehicle load random access control method of charging pile self-decision according to claim 2,
Characterized in that, in step S3, the reference load value is：The control targe period drawn according to load prediction results a few days ago is normal
Advise in load curve, a certain value not less than peak load in the period；
In step S3, the difference of load margin load value of each several part for the reference load value and in the period.
5. a kind of charging electric vehicle load random access control method of charging pile self-decision according to claim 2,
Characterized in that, also include before the step S1：The electric automobile for participating in charging in order needs defeated when accessing intelligent charging spot
Enter exit time or demand state of charge information.
6. a kind of charging electric vehicle load random access control method of charging pile self-decision according to claim 5,
Characterized in that, also include after the step S4：Exit time or demand the state-of-charge letter that charging pile inputs according to user
Breath calculates charging duration, according to section where charging duration, its corresponding initiation of charge moment probability distribution table is searched, by probability
Distribution table is determined using the initial time of which part of objective time interval as the time finally started to charge up at random, until charging
Terminate.
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Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN108270231A (en) * | 2018-02-05 | 2018-07-10 | 重庆卓谦科技有限公司 | Intelligent charging spot load random access control system and method |
| CN109353242A (en) * | 2018-11-13 | 2019-02-19 | 国网电动汽车（山西）服务有限公司 | A kind of intelligent charging spot system realizes the charging algorithm of two-way orderly charge and discharge |
| CN109910671A (en) * | 2019-03-11 | 2019-06-21 | 三峡大学 | Electric car V2G control method based on intelligent charging spot |
| CN110422075A (en) * | 2019-07-11 | 2019-11-08 | 饶国兰 | A kind of charging pile equipped with key delay charge function |
| CN110979083A (en) * | 2019-11-28 | 2020-04-10 | 同济大学 | Bidirectional charge and discharge control system and method for electric automobile |
| CN111274469A (en) * | 2020-02-27 | 2020-06-12 | 百度在线网络技术（北京）有限公司 | Charging control method and device based on block chain, electronic equipment and medium |
| CN111422094A (en) * | 2020-03-11 | 2020-07-17 | 国网辽宁省电力有限公司大连供电公司 | Charge-discharge coordination optimization control method for distributed charging pile |
| CN111917113A (en) * | 2020-08-19 | 2020-11-10 | 合肥博软电子科技有限公司 | Power grid load allowance calculation system and method and charging pile access power distribution method |
| CN114179667A (en) * | 2021-12-09 | 2022-03-15 | 国网重庆市电力公司营销服务中心 | Electric vehicle charging control method and device, electronic equipment and medium |
| CN116544920A (en) * | 2023-05-09 | 2023-08-04 | 南京邮电大学 | Residential area electric automobile night charging optimal control method, equipment and storage medium |
| CN116811646A (en) * | 2023-08-29 | 2023-09-29 | 国网浙江省电力有限公司杭州供电公司 | Electric automobile group charging control method, device, equipment and medium |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN108270231A (en) * | 2018-02-05 | 2018-07-10 | 重庆卓谦科技有限公司 | Intelligent charging spot load random access control system and method |
| CN109353242B (en) * | 2018-11-13 | 2021-11-09 | 国网电动汽车（山西）服务有限公司 | Charging algorithm for realizing bidirectional ordered charging and discharging of intelligent charging pile system |
| CN109353242A (en) * | 2018-11-13 | 2019-02-19 | 国网电动汽车（山西）服务有限公司 | A kind of intelligent charging spot system realizes the charging algorithm of two-way orderly charge and discharge |
| CN109910671A (en) * | 2019-03-11 | 2019-06-21 | 三峡大学 | Electric car V2G control method based on intelligent charging spot |
| CN110422075A (en) * | 2019-07-11 | 2019-11-08 | 饶国兰 | A kind of charging pile equipped with key delay charge function |
| CN110979083A (en) * | 2019-11-28 | 2020-04-10 | 同济大学 | Bidirectional charge and discharge control system and method for electric automobile |
| CN110979083B (en) * | 2019-11-28 | 2022-09-20 | 同济大学 | Bidirectional charge and discharge control system and method for electric automobile |
| CN111274469A (en) * | 2020-02-27 | 2020-06-12 | 百度在线网络技术（北京）有限公司 | Charging control method and device based on block chain, electronic equipment and medium |
| CN111274469B (en) * | 2020-02-27 | 2023-10-17 | 百度在线网络技术（北京）有限公司 | Charging control method and device based on block chain, electronic equipment and medium |
| CN111422094A (en) * | 2020-03-11 | 2020-07-17 | 国网辽宁省电力有限公司大连供电公司 | Charge-discharge coordination optimization control method for distributed charging pile |
| CN111917113A (en) * | 2020-08-19 | 2020-11-10 | 合肥博软电子科技有限公司 | Power grid load allowance calculation system and method and charging pile access power distribution method |
| CN111917113B (en) * | 2020-08-19 | 2022-05-13 | 合肥博软电子科技有限公司 | Power grid load allowance calculation system and method and charging pile access power distribution method |
| CN114179667A (en) * | 2021-12-09 | 2022-03-15 | 国网重庆市电力公司营销服务中心 | Electric vehicle charging control method and device, electronic equipment and medium |
| CN114179667B (en) * | 2021-12-09 | 2023-12-01 | 国网重庆市电力公司营销服务中心 | Electric automobile charging control method and device, electronic equipment and medium |
| CN116544920A (en) * | 2023-05-09 | 2023-08-04 | 南京邮电大学 | Residential area electric automobile night charging optimal control method, equipment and storage medium |
| CN116544920B (en) * | 2023-05-09 | 2024-03-26 | 南京邮电大学 | Residential area electric automobile night charging optimal control method, equipment and storage medium |
| CN116811646A (en) * | 2023-08-29 | 2023-09-29 | 国网浙江省电力有限公司杭州供电公司 | Electric automobile group charging control method, device, equipment and medium |
| CN116811646B (en) * | 2023-08-29 | 2023-11-14 | 国网浙江省电力有限公司杭州供电公司 | Electric automobile group charging control method, device, equipment and medium |
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