CN106203719A - A kind of electric automobile accesses the load forecasting method of electrical network - Google Patents
A kind of electric automobile accesses the load forecasting method of electrical network Download PDFInfo
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Abstract
The invention discloses a kind of electric automobile and access the load forecasting method of electrical network, according to statistical principle, first electric automobile a number of in estimation range is carried out statistical inquiry and forms statistical model, utilize statistical model in whole estimation range electric automobile access electrical network load prediction, take into full account user behavior emulation obtain the impact that network load is produced by electric automobile.Compared with load prediction with the most single existing self behavior of consideration electric automobile, this method is used to embody the subjective behavior of user, it is prone to combine with original simulation algorithm, is especially suitable for when relating to the carry calculation when a large amount of electric automobiles access electrical network and user behavior mode is uncertain.
Description
Technical field
The invention belongs to Load Prediction In Power Systems and planning field, the load relating to a kind of electric automobile access electrical network is pre-
Survey method, it is contemplated that the user behavior impact on charging electric vehicle.
Background technology
At present, countries in the world government pays much attention to the development of electric automobile, and USDOE will set up 2,000,000,000 dollars of governments
Fund subsidizes battery and the parts development that pure electric automobile of future generation needs.A large amount of charging electric vehicles are mainly at night, and this was both
Electric load curve can be improved, improve the economic benefit of electrical network, the purpose of environmental protection can be realized again.
China's electric automobile starting more developed country is late, but development is quickly.Each car manufactures actively puts into research and development
The ranks of electric automobile.For meeting the charge requirement of electric automobile, each province is all in the construction carrying forward vigorously charging station and charging pile.
In April, 2010, " electric car conduction formula charging inlet ", " electric automobile charging station General Requirement ", " batteries of electric automobile management
Communication protocol between system and off-board charger " and " light-duty hybrid power electric automobile energy consumption amount test method " 4 states
Family's standard is put into effect, and country also implements subsidy support policy to the new-energy automobile including electric automobile.China is
Put into effect many supports on policy and promote the fast development of ev industry, in recent years in Beijing, Shanghai, Guangzhou, the city such as Shenzhen
City has built up many electric automobile charging stations, and the popularization and application of electric automobile enter the critical period.
The method being presently considered electric automobile load prediction considers the charge-discharge characteristic of electric automobile itself, the most mostly
Consider the subjective initiative of user.User behavior is the key factor affecting electric automobile power demand, has randomness.To electricity
Electrical automobile produces the user behavior of impact and mainly includes initiation of charge time and two aspects of daily travel, user's charging interval
More concentrating, the required charge power provided of electrical network is the biggest；And daily travel reflects the power consumption on user's same day, in day travels
Journey can be reflected by initiation of charge capacity, and under certain charge power, distance travelled is relevant to duration of charge.Charging
Power, initiation of charge time and the distribution situation of initiation of charge capacity impact charging electric vehicle power over time.
Summary of the invention
Goal of the invention: access the load prediction of electrical network to carry out a large amount of electric automobile, the present invention provides a kind of electronic vapour
Car accesses the load forecasting method of electrical network, takes into account the user behavior of electric automobile, it is possible to conveniently realizes a large amount of electric automobile and accesses
The carry calculation of electrical network.
Technical scheme: to achieve these goals, the electric automobile of the present invention accesses the load forecasting method of electrical network, including
Following steps:
(1) sum of certain class electric automobile in estimation range is determined, and the charging capacity of electric automobile and charge power；
(2) such electric automobile of predetermined number is carried out locating and tracking, obtain the charge data of these electric automobiles, build
Statistical model between user behavior and the power demand of electric automobile in this estimation range vertical, described charge data includes: rise
Begin charging interval and initiation of charge capacity；
(3) initiation of charge time of such electric automobile and initiation of charge capacity are determined respectively according to described statistical model
Probability distribution；
(4) respectively according to initiation of charge time and the probability distribution stochastic generation of initiation of charge capacity of such electric automobile
Initiation of charge time and initiation of charge capacity, every a pair initiation of charge time and initiation of charge capacity represent an electric automobile
Charge data, the quantity of the charging electric vehicle data of stochastic generation is the sum of such electric automobile in this estimation range；
(5) for any one electric automobile in such electric automobile, according to its charging capacity, initiation of charge capacity,
Charge power is calculated its vehicle charging duration；
(6) each the electric automobile to such electric automobile, according to its initiation of charge time and charging duration, is filled
Electrical power carries out cumulative obtaining such electric automobile in this estimation range and accessing the load of electrical network in one day and add up.
Beneficial effect: in the present invention, the load forecasting method of electric automobile access electrical network takes into account the subjective behavior of user with each
The practical situation in area, it is easy to combine with original simulation algorithm, is especially suitable for when relating to when a large amount of electric automobiles access
Load flow calculation when electrical network and user behavior mode are uncertain.Use the inventive method, it is possible to obtain electronic vapour more accurately
Car accesses the electrical network prediction data to load, to Power System Planning, runs and dispatch the directive significance providing good.
Accompanying drawing explanation
Fig. 1 is the flow chart of the load forecasting method that electric automobile accesses electrical network in the present invention；
Fig. 2 is quick charge total load power figure on the one；
Fig. 3 is typical day load curve figure.
Detailed description of the invention:
It is described in further detail with reference to the accompanying drawings and in conjunction with the embodiments to the present invention.But the invention is not restricted to
The example gone out.
As it is shown in figure 1, electric automobile accesses the load forecasting method of electrical network in the present invention, comprise the following steps:
(1) according to country's Development of Electric Vehicles planning and the planning in each province and city, various types of electricity in determining estimation range respectively
Total EV, charging capacity and the charge power of electrical automobile (bus, officer's car, taxi etc.)；
(2) electric automobile to a certain kind, the electric automobile choosing this kind predetermined number carries out locating and tracking, obtains
The charge data of these electric automobiles, sets up the statistics between user behavior and the power demand of electric automobile in this estimation range
Model, described charge data includes: initiation of charge time, initiation of charge capacity and charging duration, for certain electric automobile, profit
Can know that it started to charge up to reaching from the initiation of charge time with its charging capacity, initiation of charge capacity (SOC), charge power
Charging duration needed for charging capacity.
According to statistical principle in the present invention, first electric automobile a number of in estimation range is carried out statistical inquiry
Form statistical model, utilizing statistical model, the electric automobile in whole estimation range is accessed the load prediction of electrical network.
The user behavior of electric automobile generally can according to traffic department or the survey data of statistical department, or utilize vehicle-mounted
The modes such as the information acquisition device that online global positioning system (GPS), residential quarter configure are tracked record, obtain used for electric vehicle
The charging behavior at family and charge data, analyze the way of act of each user charging.
The present invention utilizes probability statistics function to represent its way of act, adds up mould accordingly according to the selection of user behavior
Type:
Normal distribution:
Poisson distribution:
It is uniformly distributed:
Exponential:
Wherein, g is function, and μ is average, and σ is variance；
(3) all kinds of electronic vapour in determining this estimation range respectively according to the statistical model of the user behavior of all kinds of electric automobiles
The initiation of charge time of car and the probability distribution of initiation of charge capacity (SOC)；
Initiation of charge capacity SOC is relevant, according to formula to electric automobile daily travel number d:
Wherein dmMileage number is exercised for maximum.Simulate the probability distribution being best suitable for certain type electric automobile initiation of charge capacity SOC, can
To be the superposition of multiple probability distribution.
(4) respectively according to the initiation of charge time of all kinds of electric automobiles and the probability distribution of initiation of charge capacity (SOC) with
Machine generates the charging electric vehicle data of respective numbers, initiation of charge time and initiation of charge capacity；
(5) for a certain electric automobile, it is calculated it according to its charging capacity, initiation of charge capacity, charge power
Vehicle charging duration；
(6) to electric automobile various types of in estimation range, according to its initiation of charge time and charging duration, merit of being charged
Rate carries out cumulative obtaining such electric automobile in this estimation range and accessing the load of electrical network in one day and add up.
For intraday a certain minute, certain class electric automobile accessed the carry calculation formula of electrical network and is:
In formula, LiRepresenting i-th minute total charge power, N is the total amount of such electric automobile, Pn,iIt is n-th electric automobile
At the charge power of i-th minute, if electric automobile is not in charged state, this value is 0, and even corresponding moment electric motor car does not has
It is charged, does not then add up the charge power of this electric motor car when calculated load.
Embodiment 1:
In the present embodiment, the electric automobile in estimation range includes: bus and taxi, utilizes the inventive method pair
The quick charge mode that uses electric automobile in this estimation range accesses load produced by electrical network and is analyzed prediction.
The sum being understood this area's electric bus by relevant statistics is 6000, and the sum of electric taxi is
44000.The initiation of charge time of electric taxi is respectively 8:00 and 20:00 of every day, and the electric bus charging interval needs
Avoid resident trip peak period of going to work, therefore the initiation of charge time is 10:00,14:30 and 19:30 of every day.Because of Electric Transit
Operation is stopped after car 0:00 in evening, can be to use trickle charge mode, the present embodiment does not accounts for this charging modes of trickle charge, therefore is not added with
Discuss.
Can show that the initiation of charge time of electric taxi uses Poisson distribution with uniform by the matching of mass data
The mode that distribution combines, probability distribution corresponding for 8:00 is P (480)+U (0,5), and probability distribution corresponding for 20:00 is P
(1200)+U(0,5)；Initiation of charge capacity SOC uses Poisson distribution and is uniformly distributed the mode combined, and probability distribution is P
(0.1458)+U(0,2)。
The initiation of charge time obtaining electric bus again by mass data matching uses Poisson distribution with equal equally
The mode that even distribution combines, probability distribution corresponding for 10:00 is P (600)+U (0,20), 14:30 correspondence P (870)+U (0,
20), 19:30 correspondence P (1170)+U (0,20)；Initiation of charge capacity SOC uses Poisson distribution and is uniformly distributed the side combined
Formula, probability distribution corresponding for 10:00 is P (0.1458)+U (0,2), and other periods are P (0.1458)+U (0,5).Utilize this
Bright method finally draws employing one day total load power of quick charge, and (this figure uses a minute system, 0 corresponding diagram 3 as shown in Figure 2
In 0:00).
As seen from Figure 2, near 6:00,10:00,14:30 and 20:00, load occurs in that significantly increase, and this is
Electric automobile due to a large amount of quick charges accesses the impact of electrical network.Contrast with Fig. 3 typical day load curve, it appeared that electronic
Automobile accesses electrical network, makes load valley have the increase of any when 6:00,12:30, makes load peak slightly when 14:30,20:30
There is increase.It is while peak value increases that this explanation electric automobile accesses electrical network, also has and certain fills out paddy effect.This is primarily due to
The behavior that user is different is caused.Accordingly, it is considered to the load prediction of user behavior, for Power System Planning, run and adjust
Degree has great significance.
The ultimate principle of the present invention, principal character and advantage have more than been shown and described.Those skilled in the art should
Understand, the present invention is not limited by above-mentioned specific embodiment, the description in above-mentioned specific embodiment and description be intended merely to into
One step explanation the present invention principle, without departing from the spirit and scope of the present invention, the present invention also have various change and
Improving, these changes and improvements both fall within scope of the claimed invention.The scope of protection of present invention is wanted by right
Book and equivalent thereof is asked to define.
Claims (3)
1. the load forecasting method of an electric automobile access electrical network, it is characterised in that the method comprises the following steps:
(1) sum of certain class electric automobile in estimation range is determined, and the charging capacity of electric automobile and charge power；
(2) such electric automobile of predetermined number being carried out locating and tracking, obtain the charge data of these electric automobiles, setting up should
Statistical model between user behavior and the power demand of electric automobile in estimation range, described charge data includes: initial fill
Electricity time and initiation of charge capacity；
(3) initiation of charge time and the probability of initiation of charge capacity of such electric automobile is determined respectively according to described statistical model
Distribution；
(4) initiate according to the initiation of charge time of such electric automobile and the probability distribution stochastic generation of initiation of charge capacity respectively
Charging interval and initiation of charge capacity, every a pair initiation of charge time and initiation of charge capacity represent the charging of an electric automobile
Data, the quantity of the charging electric vehicle data of stochastic generation is the sum of such electric automobile in this estimation range；
(5) for any one electric automobile in such electric automobile, according to its charging capacity, initiation of charge capacity, charging
Power calculation obtains its vehicle charging duration；
(6) each the electric automobile to such electric automobile, according to its initiation of charge time and charging duration, merit of being charged
Rate carries out cumulative obtaining such electric automobile in this estimation range and accessing the load of electrical network in one day and add up.
Electric automobile the most according to claim 1 accesses the load forecasting method of electrical network, it is characterised in that in step (6)
When carrying out load statistics, for intraday a certain minute, certain class electric automobile accesses the carry calculation formula of electrical network and is:
In formula, LiRepresenting i-th minute total charge power, N is the total amount of such electric automobile, Pn,iIt is that n-th electric automobile is i-th
Minute charge power, if electric automobile is not in charged state, this value is 0.
Electric automobile the most according to claim 1 and 2 accesses the load forecasting method of electrical network, it is characterised in that described pre-
The electric motor car surveyed in region has variety classes, when carrying out load prediction, obtains according to step (1) every class electric automobile to (6)
Take its load accessing electrical network, then the load that all kinds electric automobile accesses electrical network is overlapped obtaining in this estimation range
All electric automobiles access the load of electrical network.
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| CN201610561978.4A CN106203719A (en) | 2016-07-15 | 2016-07-15 | A kind of electric automobile accesses the load forecasting method of electrical network |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109768610A (en) * | 2019-03-05 | 2019-05-17 | 国家电网有限公司 | The charging method and system of electric vehicle |
| CN109919393A (en) * | 2019-03-22 | 2019-06-21 | 国网上海市电力公司 | A kind of charging load forecasting method of electric taxi |
| CN110968915A (en) * | 2019-12-02 | 2020-04-07 | 国网浙江省电力有限公司绍兴供电公司 | Electric vehicle charging load prediction method |
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| EP2759439A1 (en) * | 2013-01-25 | 2014-07-30 | Volvo Car Corporation | Method and user interface system of a vehicle for providing an energy level gauge relative to a vehicle range meter |
| CN103257571A (en) * | 2013-04-22 | 2013-08-21 | 东南大学 | Air conditioning load control strategy making method based on direct load control |
| CN104978610A (en) * | 2015-07-01 | 2015-10-14 | 国家电网公司 | Power grid demand side dispatchable capacity prediction method and power dispatching method |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109768610A (en) * | 2019-03-05 | 2019-05-17 | 国家电网有限公司 | The charging method and system of electric vehicle |
| CN109919393A (en) * | 2019-03-22 | 2019-06-21 | 国网上海市电力公司 | A kind of charging load forecasting method of electric taxi |
| CN109919393B (en) * | 2019-03-22 | 2023-08-29 | 国网上海市电力公司 | Charging load prediction method for electric taxi |
| CN110968915A (en) * | 2019-12-02 | 2020-04-07 | 国网浙江省电力有限公司绍兴供电公司 | Electric vehicle charging load prediction method |
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Application publication date: 20161207 |