CN104461689A - Power system frequency modulation controllable electric automobile quantity dynamic change simulation method based on Monte Carlo - Google Patents
Power system frequency modulation controllable electric automobile quantity dynamic change simulation method based on Monte Carlo Download PDFInfo
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- CN104461689A CN104461689A CN201410723008.0A CN201410723008A CN104461689A CN 104461689 A CN104461689 A CN 104461689A CN 201410723008 A CN201410723008 A CN 201410723008A CN 104461689 A CN104461689 A CN 104461689A
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Abstract
The invention relates to a power system frequency modulation controllable electric automobile quantity dynamic change simulation method based on Monte Carlo, and belongs to the technical fields of electric automobiles and an access grid thereof. The method comprises the following steps: firstly, initializing relevant parameters of electric automobiles, secondly, judging types of the electric automobiles, and determining in/out controllable state time tables of all the electric automobiles, thirdly, making statistics and analyzing the time tables, so as to obtain the controllable electric automobile quantity N'in (ti) and the out controllable electric automobile quantity N'iout (ti) within every moment in a region, fourthly, computing the cumulative quantity of automobiles at in/out controllable state, and fifthly, computing the quantity of controllable electric automobiles. The method can properly compute the quantity of the controllable electric automobiles in the region, so as to obtain the quantity dynamic change of various types of the controllable electric automobiles participating in frequency modulation, meanwhile, the method fills the gap in the technical filed, and lays a solid theoretical foundation for deeply researching electric automobiles participating in frequency modulation.
Description
Technical field
The invention belongs to electric automobile and access electric power network technique field thereof, relate to a kind of electric system frequency modulation controllable electric automobile Number dynamics change modeling method based on Monte Carlo.
Background technology
Electric automobile and electrical network interaction (Vehicle-to-Grid, V2G) technology, refer to that electric automobile is under slave mode, a kind of new technique of the two-way exchange of realization and electric network information and energy.The energy content of battery, it is emphasised that batteries of electric automobile is except absorbing except energy from electrical network, can be fed back to electrical network time necessary by this technology.V2G system is the high-end comprehensive application system integrating numerous technology such as power electronics, communication, scheduling, metering and workload demand side management, and what its embodied is the energy storage effect of batteries of electric automobile.Utilize V2G technology, electric automobile can be made to provide multiple assistant service to electrical network, as: the adjustment of peak load shifting, frequency, spinning reserve etc.
Only have when electric automobile is in controllable state, electric automobile could provide frequency to adjust assistant service to electrical network, and namely electric automobile participates in electric system frequency modulation.Therefore, when studying certain period electric automobile participation frequency modulation, when first must obtain this, how the situation of change of controllable electric automobile quantity in segment limit, could participate in system frequency modulation by research electric automobile further, and the impact on whole regional power system frequency.
At present, comparatively rare to the controllable electric automobile number change research participating in system frequency modulation in certain period.The electric automobile of the existing actual operation of certain scale of more external countries, can obtain the real data of part electric automobile access electrical network quantity, and then the controllable electric automobile number change of estimation participation system frequency modulation.And it is domestic, electric automobile is still in the marketing stage at initial stage, and the quantity of electric automobile is very limited, lacks real data and supports as research, and the domestic research for electric automobile participation system frequency modulation is actually rare, lacks the algorithm research of the controllable electric automobile number change of participation system frequency modulation.
Therefore, a kind of method can carrying out rationally estimation to the change of electric system frequency modulation controllable electric automobile Number dynamics is badly in need of at present.
Summary of the invention
In view of this, the object of the present invention is to provide a kind of electric system frequency modulation controllable electric automobile Number dynamics change modeling method based on Monte Carlo, the method carrys out the ruuning situation of stochastic simulation electric automobile by adopting monte carlo method, and then the quantity of controllable electric automobile in statistical regions.
For achieving the above object, the invention provides following technical scheme:
Based on an electric system frequency modulation controllable electric automobile Number dynamics change modeling method for Monte Carlo, comprise the following steps:
Step one: initialization electric automobile correlation parameter;
Step 2: judge electric automobile classification, determines the entry/exit controllable state timetable of all electric automobiles respectively according to different classifications;
Step 3: statistical study timetable, what obtain each moment in region enters controllable state electric automobile quantity N '
in(t
i) and go out controllable state electric automobile quantity N'
out(t
i);
Step 4: the accumulative vehicle number calculating entry/exit controllable state;
Step 5: the quantity calculating controllable electric automobile.
Further, in step 2, electric automobile classification can be divided into electric bus, electronic officer's car, electronic private car; Wherein:
Electric bus and electronic officer's car obtain entry/exit controllable state timetable as follows:
1) moment of electric automobile access electrical network is determined;
2) initial SOC is extracted;
3) charging duration is calculated;
4) calculate into the controllable state moment;
5) the controllable state moment is determined;
6) the entry/exit controllable state timetable of electric bus and electronic officer's car is obtained;
Electronic private car obtains entry/exit controllable state timetable as follows:
1) period is determined belonging to the access electrical network moment;
2) the access electrical network moment is extracted;
3) initial SOC is extracted;
4) charging duration is calculated;
5) calculate into the controllable state moment;
6) period belonging to the controllable state moment is determined;
7) the controllable state moment is extracted;
8) the entry/exit controllable state timetable of electronic private car is obtained.
Further, in step 2, adopt monte carlo method to carry out statistical study to data, obtain the entry/exit controllable state timetable of all electric automobiles in region.
Beneficial effect of the present invention is: the invention provides a kind of electric system frequency modulation controllable electric automobile Number dynamics change modeling method based on Monte Carlo, can be good at calculating the quantity of controllable electric automobile in region, calculate the Number dynamics change that all kinds of controllable electric automobile participates in system frequency modulation, simultaneously, fill up the blank of this technical field, for further investigation electric automobile participates in system frequency modulation, establish solid theoretical foundation.
Accompanying drawing explanation
In order to make object of the present invention, technical scheme and beneficial effect clearly, the invention provides following accompanying drawing and being described:
Fig. 1 is the schematic flow sheet of the method for the invention;
Fig. 2 is the state transition diagram of electric automobile;
Fig. 3 is the number change situation of controllable electric automobile.
Embodiment
Below in conjunction with accompanying drawing, the preferred embodiments of the present invention are described in detail.
Fig. 1 is the schematic flow sheet of the method for the invention, and as shown in the figure, this method comprises the following steps: step one: initialization electric automobile correlation parameter; Step 2: judge electric automobile classification, determines the entry/exit controllable state timetable of all electric automobiles respectively according to different classifications; Step 3: statistical study timetable, what obtain each moment in region enters controllable state electric automobile quantity N '
in(t
i) and go out controllable state electric automobile quantity N'
out(t
i); Step 4: the accumulative vehicle number calculating entry/exit controllable state; Step 5: the quantity calculating controllable electric automobile.
Wherein, in step 2, adopt monte carlo method to carry out statistical study to data, obtain the entry/exit controllable state timetable of all electric automobiles in region.Electric automobile classification can be divided into electric bus, electronic officer's car, electronic private car; Electric bus and electronic officer's car obtain entry/exit controllable state timetable as follows: the moment 1) determining electric automobile access electrical network; 2) initial SOC is extracted; 3) charging duration is calculated; 4) calculate into the controllable state moment; 5) the controllable state moment is determined; 6) the entry/exit controllable state timetable of electric bus and electronic officer's car is obtained; Electronic private car obtains entry/exit controllable state timetable as follows: 1) determine the period belonging to the access electrical network moment; 2) the access electrical network moment is extracted; 3) initial SOC is extracted; 4) charging duration is calculated; 5) calculate into the controllable state moment; 6) period belonging to the controllable state moment is determined; 7) the controllable state moment is extracted; 8) the entry/exit controllable state timetable of electronic private car is obtained.
In order to fully set forth this method, now the state status of electric automobile is illustrated as follows:
As shown in Figure 2, usually, compare the automobile quantity that various parking site is parked, the automobile quantity on the way travelled is few.Equally, in the future that electric automobile is popularized in a large number, such situation will be similar.Electric automobile at various parking sites such as such as work unit parking lot, parking lot, residential quarter, parking lots, commercial entertainment district, can access electrical network by attaching plug in the future efficiently and easily.
Electronic vehicle attitude comprises transport condition, charged state, controllable state and idle condition.Electric automobile is constantly changed between these 4 states.
Transport condition:
Car owner extracts electric car power supply plug for the demand of driving, and makes electric automobile depart from electrical network.Electric automobile transfers transport condition to by idle condition or controllable state (state produces thus, belongs to controllable state).
Charged state:
After car owner arrives destination, inserting electric car power supply plug is battery charging, and electric automobile accesses electrical network immediately.For the electric automobile that access power grid time is shorter, its state transfers charged state to by transport condition immediately; For the electric automobile that access power grid time is longer, only has initial charged value SOC during access electrical network
0be less than into entering controlled charged value SOC during controllable state
m, its state just transfers charged state to by transport condition.In addition, be in the electric automobile of controllable state owing to participating in system frequency modulation, its SOC may be caused too low, then electric automobile can transfer charged state (this situation also belongs to controllable state) to by controllable state, to ensure that electric automobile is before entering transport condition, have enough SOC, as shown in phantom in Figure 2.It is pointed out that the electric automobile being in charged state can not responding system fm control signal.
Controllable state:
If the time of electric automobile access electrical network is shorter, so it participates in the DeGrain of system frequency modulation.Therefore, for the electric automobile that access power grid time is longer, if SOC
0< SOC
m, treat that its charging makes battery SOC rise to SOC
mtime, electric automobile transfers controllable state to by charged state; If SOC
0>=SOC
m, after electric automobile access electrical network, can skip charged state, directly transfer controllable state to by transport condition.Above two kinds of situations all belong to into controllable state.Only be in the electric automobile of controllable state, ability responding system fm control signal, thus provide frequency modulation service to electrical network.
Along with the fluctuation of system frequency, participate in frequency-modulating process at electric automobile, its battery, by time discharge and recharge, with responding system fm control signal, thus causes battery SOC to produce fluctuation.For preventing battery from overcharging, can limit the SOC upper limit is SOC
max.Equally, for avoiding battery over-discharge can, can limit SOC lower limit is SOC
min.At restriction SOC lower limit SOC
mintime, if consider the randomness of electric automobile main time of using cars and the requirement to vehicle continuation of the journey, then SOC
minbe worth larger; If do not consider above-mentioned factor, only in order to avoid battery over-discharge can, then SOC
minbe worth less.The fluctuation range of batteries of electric automobile SOC is at (SOC
min, SOC
max) between.
Above-mentioned SOC
mcan be calculated by formula (1).
Idle condition:
For the electric automobile being transferred to charged state by controllable state, and the electric automobile that access power grid time is shorter, after its charging plan completes, transfer idle condition to by charged state.
Only be in the electric automobile of controllable state, ability responding system fm control signal, thus participate in electric system frequency modulation.Therefore, the dynamic change modeling algorithm model of controllable electric automobile quantity must first be set up.The controllable electric automobile quantity in a certain moment in region, is carved into controllable state and the electric automobile quantity going out controllable state when depending on this.In one day time range, along with the change of each electric automobile controllable state, in region, controllable electric automobile quantity will present the process of dynamic change.The change of research controllable state, just must analyze in conjunction with the traveling rule of electric automobile and State Transferring characteristic.
The present invention adopts monte carlo method to carry out the ruuning situation of stochastic simulation electric automobile:
If initial time is t
0, in region, the electric automobile access electrical network moment is t
1, according to the analysis of aforementioned electric automobile controllable state part, if charging electric vehicle duration is T
2, electric automobile can be obtained thus and enter controllable state moment t
3for:
t
3＝t
1+T
2(2)
Due to SOC
0with SOC
mrelative size, according to the two kinds of situation analysis entering controllable state, can T be drawn
2calculating formula be:
In formula, E
evfor the battery capacity of single electric automobile, P
evfor the charge power of single electric automobile, η
evfor charge efficiency.
Controllable state moment t is gone out for electric automobile
4.From aforementioned go out controllable state partial analysis, if electric automobile transfers transport condition to by controllable state, so t
4be exactly that electric automobile departs from the electrical network moment, also namely car owner drives to go on a journey start time.Now, t
4obey probability distribution.If electric automobile transfers charged state to by controllable state, participating in the time of frequency modulation in order to extend electric automobile, can fast charge mode be adopted, in the short period before entering transport condition, rapid raising battery SOC, to meet requirement when electric automobile sets out with higher SOC.After considering time margin, the maximum duration that fills soon can be set to certain value.Once the traveling of electric automobile is set out the moment (namely depart from electrical network moment) determine, deduct and maximumly fill duration soon, t
4can determine.
Adopt the access electrical network moment t of monte carlo method random sampling electric automobile
1, initial charged value SOC during access electrical network
0with go out controllable state moment t
4, constantly the entry/exit controllable state of each electric automobile of simulation, finally obtains the entry/exit controllable state timetable of all electric automobiles in region.
By carrying out statistical study to electric automobile entry/exit controllable state timetable, what can obtain each moment in region enters controllable state electric automobile quantity N '
in(t
i) and go out controllable state electric automobile quantity N'
out(t
i), can calculate by formula (4) and formula (5) the accumulative electric automobile quantity N that t enters controllable state
in(t) and the accumulative electric automobile quantity N going out controllable state
out(t).
In addition, if t
0the initial controllable electric automobile quantity in moment is N
0.So, the controllable electric automobile quantity N of t
ct () is such as formula shown in (6).
N
c(t)＝N
0+N
in(t)-N
out(t) (6)
According to the traveling rule of all kinds of electric automobile and the State Transferring characteristic of electric automobile, in conjunction with the dynamic change analogy method of controllable electric automobile quantity, can determine or suppose that the parameter of all kinds of electric automobile participation system frequency modulation is as described below.
1) bus.It is just longer that electric bus only accesses power grid time at night, just can enter controllable state and participate in frequency modulation.Electric bus is stopped transport night, there is not the stochastic problems of time of using cars, therefore can suppose SOC
minbe 0.1.Like this, electric bus participates in frequency modulation and SOC may be caused too low, and it goes out controllable state should transfer charged state (fast charge mode) to by controllable state.After taking into account time margin, suppose that the maximum duration that fills soon is 1h.In addition, for the consideration of administrative convenience, public transport company can unify the access electrical network moment t of all electric bus in arrangement region
1for 23:00, departing from the electrical network moment (i.e. electric bus operation start time) is 5:30 in second day morning.
2) officer's car.Situation and the electric bus of electronic officer's car are similar.Therefore, the SOC of electronic officer's car is supposed
minbe 0.1, the maximum duration that fills soon is 1h, access electrical network moment t
1for 18:00, departing from the electrical network moment is 7:00 in second day early morning.
3) taxi.Electric taxi whole day most of time is substantially all in normal operating condition (i.e. transport condition), and that is, in one day 24 hours, electric taxi access power grid time is all shorter.Therefore, electric taxi is not suitable for participation system frequency modulation.
4) private car.Electronic private car is the storage period in work unit and parking lot, residential quarter longer (namely accessing power grid time longer), shorter in the storage period in parking lot, commercial entertainment district.It accesses the power grid time longer period on weekdays, for car owner arrives to coming off duty the departure time after work unit morning, and before working in morning time to next day of coming off duty or get home after amusement and recreation sets out.Suppose that car owner After Hours goes the ratio of amusement and recreation to be 10% on weekdays.
For electronic private car, except it travels rule, the stochastic problems of car owner's time of using cars also should be considered, and the requirement to vehicle continuation of the journey, then SOC
mincomparatively large, assuming that SOC
minbe 0.6.So it is transfer transport condition to by controllable state that electronic private car goes out controllable state.
In sum, electronic private car access electrical network moment t
1(assuming that t between 8:00-9:00
1obedience is uniformly distributed, i.e. t
1~ U (8,9)), and between 17:30-19:00, (car owner After Hours directly drives to go home, and does not go amusement and recreation.Assuming that t
1obedience is uniformly distributed, i.e. t
1~ U (17.5,19)), or between 21:00-22:30, (car owner After Hours goes amusement and recreation immediately, does not drive immediately to go home.Assuming that t
1obedience is uniformly distributed, i.e. t
1~ U (21,22.5)).The electronic private car disengaging electrical network moment (namely goes out controllable state moment t
4) between 7:30-8:30 (assuming that t
4obedience is uniformly distributed, i.e. t
4~ U (7.5,8.5)), and (assuming that t between 17:00-18:30
4obedience is uniformly distributed, i.e. t
4~ U (17,18.5)).
Apart from the above parameters, other parameter of all kinds of electric automobile is as shown in table 1.
The parameter of all kinds of electric automobile of table 1
By the controllable electric automobile Population number dynamic imitation algorithm of the aforementioned participation electric system frequency modulation based on Monte Carlo, analog computation can show that all kinds of controllable electric automobile participates in the Number dynamics change of system frequency modulation as shown in Figure 3.
What finally illustrate is, above preferred embodiment is only in order to illustrate technical scheme of the present invention and unrestricted, although by above preferred embodiment to invention has been detailed description, but those skilled in the art are to be understood that, various change can be made to it in the form and details, and not depart from claims of the present invention limited range.
Claims (3)
1., based on an electric system frequency modulation controllable electric automobile Number dynamics change modeling method for Monte Carlo, it is characterized in that: comprise the following steps:
Step one: initialization electric automobile correlation parameter;
Step 2: judge electric automobile classification, determines the entry/exit controllable state timetable of all electric automobiles respectively according to different classifications;
Step 3: statistical study timetable, what obtain each moment in region enters controllable state electric automobile quantity N '
in(t
i) and go out controllable state electric automobile quantity N'
out(t
i);
Step 4: the accumulative vehicle number calculating entry/exit controllable state;
Step 5: the quantity calculating controllable electric automobile.
2. a kind of electric system frequency modulation controllable electric automobile Number dynamics change modeling method based on Monte Carlo according to claim 1, it is characterized in that: in step 2, electric automobile classification can be divided into electric bus, electronic officer's car, electronic private car; Wherein:
Electric bus and electronic officer's car obtain entry/exit controllable state timetable as follows:
1) moment of electric automobile access electrical network is determined;
2) initial SOC is extracted;
3) charging duration is calculated;
4) calculate into the controllable state moment;
5) the controllable state moment is determined;
6) the entry/exit controllable state timetable of electric bus and electronic officer's car is obtained;
Electronic private car obtains entry/exit controllable state timetable as follows:
1) period is determined belonging to the access electrical network moment;
2) the access electrical network moment is extracted;
3) initial SOC is extracted;
4) charging duration is calculated;
5) calculate into the controllable state moment;
6) period belonging to the controllable state moment is determined;
7) the controllable state moment is extracted;
8) the entry/exit controllable state timetable of electronic private car is obtained.
3. a kind of electric system frequency modulation controllable electric automobile Number dynamics change modeling method based on Monte Carlo according to claim 1, it is characterized in that: in step 2, adopt monte carlo method to carry out statistical study to data, obtain the entry/exit controllable state timetable of all electric automobiles in region.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN110829474A (en) * | 2019-11-21 | 2020-02-21 | 国电南瑞南京控制系统有限公司 | Method and system for supporting dynamic security of power grid by using big data intelligent energy storage |
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| US20100161482A1 (en) * | 2008-12-22 | 2010-06-24 | Nathan Bowman Littrell | System and method for roaming billing for electric vehicles |
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