CN108133329A - Consider the electric vehicle trip of charging feedback effect and charge requirement analysis method - Google Patents
Consider the electric vehicle trip of charging feedback effect and charge requirement analysis method Download PDFInfo
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Abstract
A kind of electric vehicle trip for considering charging feedback effect and charge requirement analysis method：Automobile user trip requirements model under purpose ground mode；Trip and charge requirement sequential interaction analysis, there is electric quantity consumption model of the foundation based on trip requirements when user is in transport condition, the charge requirement based on fuzzy theory, which is established, when user is in and drives into state generates model, user establishes the electricity supplementary model for considering that electrically-charging equipment is abundance when being in resting state, user is in user's otherness decision based on charging feedback effect when sailing out of state；The sequential interactive simulation that user goes on a journey with charge requirement.The present invention can realize that automobile user trip requirements are interacted with the sequential of charge requirement, and analyze the variation tendency of user's charge requirement and the sluggishness of trip requirements and recovery.
Description
Technical field
The present invention relates to a kind of charging load prediction of electric vehicle and analysis methods.It is suitable for purpose more particularly to one kind
The electric vehicle trip of charging feedback effect divides with charge requirement the considerations of private savings automobile user charge requirement under ground mode
Analysis method.
Background technology
In face of the resource scarcity being on the rise and problem of environmental pollution, China has been turned on the fuel-engined vehicle timetable of prohibiting selling and grinds
Study carefully.Electric vehicle becomes the developing direction in new-energy automobile future and obtains because of its huge advantage in energy consumption and environmental-protecting performance
To greatly developing.Private car is the main object that following electric vehicle is popularized, because its resting state time is long, the transport condition time
Short trip feature and tend to destination charge mode, that is, carried out in docking process when being in and is long the purpose of job site
Charging.The universal of electronic private car will cause a large amount of charge requirements, and electronic private car user goes out under accurate analysis purpose ground mode
Row is electrically-charging equipment programming and distribution, the impact analysis of charging Load on Electric Power Grid, the distribution for considering electric vehicle access with charge requirement
The basis of the researchs such as net planning operation.
At present, have many scholars to study electric vehicle charge requirement problem.Due to the movement of electric vehicle
Property, charge requirement analysis is needed based on user goes on a journey rule simulation.User's trip rule analogy method is concentrated mainly on
Based on stochastic variable fitting, based on Trip chain and based on the probabilistic method of Spatial Dimension.But existing research is being charged
Think that electrically-charging equipment can fully meet any charge requirement during demand analysis more, do not account for electrically-charging equipment distribution to electronic vapour
The influence of vehicle charge requirement, and in fact the spatial and temporal distributions of electric vehicle charge requirement and the trip requirements of user can be set because of charging
It applies distribution difference and changes.
When carrying out the analysis of electric vehicle charge requirement, electrically-charging equipment abundance whether, can directly influence whether user generates
Whether charge requirement can obtain charging service in time, and then influence the state-of-charge of electric vehicle, and state-of-charge with
The trip requirements at family are interrelated.
Invention content
The technical problem to be solved by the invention is to provide one kind can accurately analyze electrically-charging equipment distribution to electric vehicle
The electric vehicle trip of the considerations of user's trip requirements and charge requirement influence charging feedback effect and charge requirement analysis method.
The technical solution adopted in the present invention is：A kind of electric vehicle trip for considering charging feedback effect and charge requirement
Analysis method includes the following steps：
1) automobile user trip requirements model under purpose ground mode
CX=[Lp,Ap,Xd,LT,Xt,AT,Tt]
In formula：LpFor departure place；ApFor parking site；XdFor mileage travelled；LTFor the moment of setting out；XtTo travel duration；
ATFor the cut-off time；TtFor the duration that stops；
2) trip and charge requirement sequential interaction analysis
Entire analytic process includes four kinds of states, first, establishing the electricity based on trip requirements when user is in transport condition
Consumption models are measured, second is that establishing the charge requirement based on fuzzy theory when user is in and drives into state generates model, third, using
The electricity supplementary model for considering that electrically-charging equipment is abundance is established in family when being in resting state, fourth, user is in base when sailing out of state
In user's otherness decision of charging feedback effect；
3) user's trip and the sequential interactive simulation of charge requirement
It sets first, carries out sequential interactive simulation by time interval of dt, [T-dt, T] interior user's trip state is constant；With
Unique step carries out user's trip and the sequential interactive simulation of charge requirement for clock propulsion mode, including：
(1) T=0 is initialized；
(2) initialising subscriber k=1；
(3) judge trip state of the user in [T-dt, T]；
(4) when user's trip state is when driving, according to electric quantity consumption model modification state-of-charge；When the trip shape of user
State is when driving into, judges the generation of charge requirement according to charge requirement generation model and abandons；When the trip state of user is stops
When staying, state-of-charge and charge requirement are updated according to electricity supplementary model；When the trip state of user is to sail out of, according to charged
State support determines charge requirement and trip requirements；
(5) as user k=k+1, (3) step and (4) step are repeated until traversing all users, is preserved each in [T-dt, T]
The charge requirement and trip requirements of user；
(6) T=T+dt repeats (2) step to (5) step until simulation cycle terminates.
The electric quantity consumption model based on trip requirements described in step 2) is that state is interior at [T-dt, T] to be when user goes on a journey
When driving, the electric quantity consumption model of foundation is as follows：
In formula：Dt is sequential interactive simulation time interval；SOCTRepresent the state-of-charge of T moment electric vehicles；SOCT-dtTable
Show the state-of-charge of T-dt moment electric vehicles；V is electric automobile during traveling average speed；XDFor electric vehicle course continuation mileage.
The charge requirement based on fuzzy theory described in step 2) generates model, is when user goes on a journey state at [T-dt, T]
Interior is when driving into, and the charge requirement generation model of foundation is as follows：
Wherein：
ASOC≥m2When, state-of-charge is complete sufficient for next stroke, without charge requirement, M (ASOC) value takes 0；
m1≤ASOC<m2When, ASOCCloser to m2, M (ASOC) closer to 0, ASOCCloser to m1, M (ASOC) closer to 1
In formula：F(ASOC,PT) represent that user drives into parking site P, state-of-charge abundance degree is ASOCWhen have charge requirement
Probability；PTRepresent the quantity of T moment parking site P residue charging piles；ASOCRepresent state-of-charge abundance degree；M(ASOC) represent ASOC
It is the degree of membership for having charge requirement to fuzzy set；m1For coefficient of elasticity；SOCTRepresent the state-of-charge of T moment electric vehicles；CEV
It is battery capacity；W represents unit mileage power consumption；C is reflection weather, road conditions constant；Xd_i+1Represent the row of user's stroke next time
Sail mileage；m2For fuzzy coefficient.
The abundance electricity supplementary model of the considerations of step 2) is described electrically-charging equipment, be when user go on a journey state [T-dt,
T] in for stop when, the electricity supplementary model of foundation is as follows：
In formula：SOCTRepresent the state-of-charge of T moment electric vehicles；SOCT-dtRepresent the charged of T-dt moment electric vehicles
State；Q is charging batteries of electric automobile power；Dt is sequential interactive simulation time interval；CEVIt is battery capacity；PT-dtRepresent T-
The quantity of dt moment parking site P residue charging piles.
If electric vehicle state-of-charge reaches 100% in holding process, which disappears user, and
State-of-charge is constant before sailing out of；Otherwise the user keeps charge requirement and continues to update its according to electricity supplementary model charged
State.
User's otherness decision based on charging feedback effect described in step 2) includes：
(1) state-of-charge support is calculated：
In formula, BSOCRepresent state-of-charge support；SOCTRepresent the state-of-charge of T moment electric vehicles；CEVIt is that battery holds
Amount；C is reflection weather, road conditions constant；W represents unit mileage power consumption；Xd_iRepresent the mileage travelled of this stroke of user；
(2) n is set1To support coefficient, charging feedback result is determined according to state-of-charge support
If BSOC≥n1, state-of-charge supports this stroke, and feedback result is：It can sail out of, user is made by sailing in the original plan
From decision, trip requirements are constant；
If BSOC<n1, state-of-charge cannot support this stroke, and feedback result is：It can not temporarily sail out of, i.e., user is practical
Parking site cannot be really sailed out of, sailing out of at this time is interpreted as user's original trip requirements；
When feedback result is when can not temporarily sail out of, user has difference due to the travel activity type of this stroke is different
Decision-making criterion：
When stroke classification is work, user's decision factor is influenced for arrival moment, and user's decision-making criterion is AT_0+ dt ＞
AT_max；
When stroke classification is leisure, user's decision factor is influenced for leisure duration, user's decision-making criterion is Tt_0- dt ＜
Tt_min；
When stroke classification is gone home to terminate trip, user's decision factor is influenced for arrival moment, user's decision-making criterion is
AT_0+dt>AT_max；
When stroke classification is to go home in short-term, without judging；
Wherein, AT_0For the cut-off time of user's original plan, AT_maxFor the tolerance moment the latest of user's parking, Tt_0For user
Original plan stay time, Tt_minThe most short tolerance duration stopped for user；
(3) user makes user's otherness decision according to stroke classification with corresponding criterion
(3.1) when this travel activity is gone home for work or after terminating to go on a journey, if meeting criterion AT_0+dt>AT_max, then
It makes and abandons the decision that electric vehicle takes other modes of transportation to continue this stroke, otherwise make and charge requirement is kept to wait for one
The decision of section time；
(3.2) when this travel activity is leisure, if meeting criterion Tt_0-dt<Tt_min, then make and abandon this stroke
Continue next stroke or terminate the decision of trip, otherwise make the decision that charge requirement is kept to wait for a period of time；
(3.3) when this travel activity is when going home in short-term, without judging, makes and abandon the next row of this stroke continuation
Journey or the decision for terminating trip.
This stroke of abandoning described in (3.3) of (3) step continues in next stroke, if day trip does not terminate, at this time
It needs to recalculate state-of-charge support B 'SOCIf B 'SOC≥n1Then user continue to make abandon this stroke continue next time
Stroke or the decision for terminating trip, otherwise make the decision that charge requirement is kept to wait for a period of time again.
Electric vehicle of abandoning described in (3.1) of (3) step takes other modes of transportation to continue this stroke, needs to consider
The possibility that user fetches electric vehicle, if user and electric vehicle position are misaligned, user does not reach also and abandons electronic vapour
At vehicle, it can not fetch；If position overlaps, and B 'SOC≥n1, then user successfully fetches electric vehicle and electric vehicle drive leaves,
Otherwise other modes of transportation is taken to leave again.
The considerations of of the invention charging feedback effect electric vehicle trip with charge requirement analysis method, with charging feedback mould
Analyzed based on type consider electrically-charging equipment it is abundance after the variation tendency of user charge requirement and the sluggishness of trip requirements and
Restore phenomenon.Start with from the basic research of modeling and simulation, more truly disclose and consider to use after electrically-charging equipment is abundance
Family go on a journey with charge requirement be closely connected and variation tendency, and then to consider electric vehicle access distribution network planning operation grind
Study carefully, electric vehicle charging Load on Electric Power Grid impact analysis especially electric vehicle electrically-charging equipment programming and distribution provide it is basic
Support.The present invention can realize that automobile user trip requirements are interacted with the sequential of charge requirement, and analyze user's charging
The variation tendency of demand and the sluggishness of trip requirements and recovery.
Description of the drawings
Fig. 1 is the flow chart of user's otherness decision based on charging feedback effect in the present invention；
In figure：Decision 1：By sailing out of in the original plan；Decision 2：Charge requirement is kept to wait for a period of time；Decision 3：Abandon this
Stroke continues next stroke or terminates trip；Decision 4：Abandoning electric vehicle takes other modes of transportation to continue this stroke
Fig. 2 a are the electric vehicle quantity that parking node H1 has charge requirement；
Fig. 2 b are the electric vehicle quantity that parking node R 3-R4 has charge requirement；
Fig. 2 c are the electric vehicle quantity that parking node W5-W8 has charge requirement；
Fig. 3 is the quantity that parking node H1 stops electric vehicle；
Fig. 4 is the automobile user quantity moment distribution for sailing out of parking node H1.
Specific embodiment
The electric vehicle trip of charging feedback effect of the considerations of with reference to embodiment and attached drawing to the present invention is needed with charging
Analysis method is asked to be described in detail.
The considerations of of the invention charging feedback effect electric vehicle trip with charge requirement analysis method, including walking as follows
Suddenly：
1) automobile user trip requirements model under purpose ground mode
User's charge requirement is closely related with trip requirements, user's trip again based on city traffic network and carrier,
Rationally trip requirements of the description user in city traffic network are to carry out the basis of charge requirement analysis.For electronic private car,
User is round-trip between certain several node of city traffic network, and go off daily structure is substantially relatively fixed, such as " work-go home ", " work
Work-leisure-is gone home " and " work-going home in short-term-lies fallow-goes home " etc..
Trip chain refers to artificial completion one or a several activities, in the company of certain time sequentially different trip purposes
Connect form.Return again to the spatial and temporal distributions of family by several strokes from family for above-mentioned user, Trip chain can retouch well
It states.For various travel components, user's trip requirements can use daily travel number, the trip start-stop place of each run and away from
From, trip the index expressions such as start/stop time and duration.The modeling of automobile user trip requirements is as follows under purpose ground mode：
CX=[Lp,Ap,Xd,LT,Xt,AT,Tt]
In formula：LpFor departure place；ApFor parking site；XdFor mileage travelled；LTFor the moment of setting out；XtTo travel duration；
ATFor the cut-off time；TtFor the duration that stops；
2) trip and charge requirement sequential interaction analysis
Entire analytic process includes four kinds of states, first, establishing the electricity based on trip requirements when user is in transport condition
Consumption models are measured, second is that establishing the charge requirement based on fuzzy theory when user is in and drives into state generates model, third, using
The electricity supplementary model for considering that electrically-charging equipment is abundance is established in family when being in resting state, fourth, user is in base when sailing out of state
In user's otherness decision of charging feedback effect；
(1) electric quantity consumption of electric vehicle is occurred along with the traveling of user, the electricity based on trip requirements
Consumption models are measured, are when user's trip state is when driving in [T-dt, T], the electric quantity consumption model of foundation is as follows：
In formula：Dt is sequential interactive simulation time interval；SOCTRepresent the state-of-charge of T moment electric vehicles；SOCT-dtTable
Show the state-of-charge of T-dt moment electric vehicles；V is electric automobile during traveling average speed；XDFor electric vehicle course continuation mileage.
(2) whether the charge requirement of user and electric vehicle state-of-charge are sufficient closely related for next stroke demand.
The charge requirement based on fuzzy theory generates model, is when user's trip state is to drive into [T-dt, T], builds
It is as follows that vertical charge requirement generates model：
Wherein：
ASOC≥m2When, state-of-charge is complete sufficient for next stroke, without charge requirement, M (ASOC) value takes 0；m1
≤ASOC<m2When, ASOCCloser to m2, M (ASOC) closer to 0, ASOCCloser to m1, M (ASOC) closer to 1
In formula：F(ASOC,PT) represent that user drives into parking site P, state-of-charge abundance degree is ASOCWhen have charge requirement
Probability；PTRepresent the quantity of T moment parking site P residue charging piles；ASOCRepresent state-of-charge abundance degree；M(ASOC) represent ASOC
It is the degree of membership for having charge requirement to fuzzy set；m1For coefficient of elasticity；SOCTRepresent the state-of-charge of T moment electric vehicles；CEV
It is battery capacity；W represents unit mileage power consumption；C is reflection weather, road conditions constant；Xd_i+1Represent the row of user's stroke next time
Sail mileage；m2For fuzzy coefficient.
According to the state-of-charge abundance degree of T moment users, non-resilient user and elastic user can be classified as.If ASOC<
m1, state-of-charge cannot meet next stroke, be defined as non-resilient user；If ASOC≥m1, state-of-charge can meet next row
Journey is defined as elastic user.Non-resilient user necessarily leads to charge requirement, is not required to Fuzzy Processing, and elastic user's charge requirement
It is fuzzy.
There is a need to consideration for elastic user, it provides charging service net the tolerance of charging service.When elasticity is used
For parking site where family when the T moment is without remaining charging pile, elastic user can actively abandon charge requirement.With reference to fuzzy theory
Leading to the problem of for user's charge requirement is converted into probability problem.The probability that non-resilient user generates charge requirement is 1, and elasticity is used
The probability that family generates charge requirement is M (ASOC) and be tolerant for charging service net.
(3) after model is generated using charge requirement and determines user's charge requirement, electrically-charging equipment in combined charge service network
Can abundance judgement user's charge requirement be met.Obtain charging service if abundant, and the state-of-charge of user according to
Charge power increases, otherwise constant.The considerations of described the abundance electricity supplementary model of electrically-charging equipment, be when user goes on a journey state
When in [T-dt, T] to stop, the electricity supplementary model of foundation is as follows：
In formula：SOCTRepresent the state-of-charge of T moment electric vehicles；SOCT-dtRepresent the charged of T-dt moment electric vehicles
State；Q is charging batteries of electric automobile power；Dt is sequential interactive simulation time interval；CEVIt is battery capacity；PT-dtRepresent T-
The quantity of dt moment parking site P residue charging piles.
If electric vehicle state-of-charge reaches 100% in holding process, which disappears user, and
State-of-charge is constant before sailing out of；Otherwise the user keeps charge requirement and continues to update its according to electricity supplementary model charged
State.
(4) when user's trip state is to sail out of in [T-dt, T], analog subscriber makes otherness decision, is filled with reflection
Electricity demanding is satisfied feedback effect of the situation to user's trip requirements.According to the charged shape of electricity supplementary model continuous updating user
On the basis of state and charge requirement, this stroke can be supported to determine that user's charge requirement is satisfied situation to going out by state-of-charge
The feedback result of row demand.As shown in Figure 1, user's otherness decision based on charging feedback effect includes：
(4.1) state-of-charge support is calculated：
In formula, BSOCRepresent state-of-charge support；SOCTRepresent the state-of-charge of T moment electric vehicles；CEVIt is that battery holds
Amount；C is reflection weather, road conditions constant；W represents unit mileage power consumption；Xd_iRepresent the mileage travelled of this stroke of user；
(4.2) n is set1To support coefficient, charging feedback result is determined according to state-of-charge support
If BSOC≥n1, state-of-charge supports this stroke, and feedback result is：It can sail out of, user is made by sailing in the original plan
From decision, trip requirements are constant；
If BSOC<n1, state-of-charge cannot support this stroke, and feedback result is：It can not temporarily sail out of, i.e., user is practical
Parking site cannot be really sailed out of, sailing out of at this time is interpreted as user's original trip requirements；
When feedback result is when can not temporarily sail out of, user has difference due to the travel activity type of this stroke is different
Decision-making criterion：
When stroke classification is work, user's decision factor is influenced for arrival moment, and user's decision-making criterion is AT_0+dt>
AT_max；
When stroke classification is leisure, user's decision factor is influenced for leisure duration, user's decision-making criterion is Tt_0-dt<
Tt_min；
When stroke classification is gone home to terminate trip, user's decision factor is influenced for arrival moment, user's decision-making criterion is
AT_0+dt>AT_max；
When stroke classification is to go home in short-term, without judging；
Wherein, AT_0For the cut-off time of user's original plan, AT_maxFor the tolerance moment the latest of user's parking, Tt_0For user
Original plan stay time, Tt_minThe most short tolerance duration stopped for user；
The principal element and criterion for influencing user's decision are shown in Table 1.
Table 1 influences the principal element and criterion of user's decision
(4.3) user makes user's otherness decision according to stroke classification with corresponding criterion
(4.3.1) when this travel activity for work or terminate trip after go home when, if meeting criterion AT_0+dt>AT_max,
It then makes and abandons the decision that electric vehicle takes other modes of transportation to continue this stroke, otherwise make and charge requirement is kept to wait for
The decision of a period of time；The electric vehicle of abandoning takes other modes of transportation to continue this stroke, need to consider that user will be electric
The possibility that electrical automobile is fetched, if user and electric vehicle position are misaligned, user does not reach also and abandons at electric vehicle, can not
It fetches；If position overlaps, and B 'SOC≥n1, then user successfully fetches electric vehicle and electric vehicle drive leaves, otherwise again
Other modes of transportation is taken to leave.
(4.3.2) when this travel activity for leisure when, if meeting criterion Tt_0- dt ＜ Tt_min, then make and abandon this row
Cheng Jixu strokes next time or the decision for terminating trip, otherwise make the decision that charge requirement is kept to wait for a period of time；
(4.3.3) when this travel activity for go home in short-term when, without judge, make abandon this stroke continue next time
Stroke or the decision for terminating trip.
Described this stroke of abandoning continues in next stroke, if day trip does not terminate, needs to recalculate at this time charged
State support B 'SOCIf B 'SOC≥n1Then user, which continues to make, abandons the next stroke of this stroke continuation or terminates trip
Otherwise decision makes the decision that charge requirement is kept to wait for a period of time again.
3) user's trip and the sequential interactive simulation of charge requirement
It sets first, carries out sequential interactive simulation by time interval of dt, [T-dt, T] interior user's trip state is constant；With
Unique step carries out user's trip and the sequential interactive simulation of charge requirement for clock propulsion mode, including：
(1) T=0 is initialized；
(2) initialising subscriber k=1；
(3) judge trip state of the user in [T-dt, T]；
(4) when user's trip state is when driving, according to electric quantity consumption model modification state-of-charge；When the trip shape of user
State is when driving into, judges the generation of charge requirement according to charge requirement generation model and abandons；When the trip state of user is stops
When staying, state-of-charge and charge requirement are updated according to electricity supplementary model；When the trip state of user is to sail out of, according to charged
State support determines charge requirement and trip requirements；
(5) as user k=k+1, (3) step and (4) step are repeated until traversing all users, is preserved each in [T-dt, T]
The charge requirement and trip requirements of user；
(6) T=T+dt repeats (2) step to (5) step until simulation cycle terminates.
Specific example is given below：
Emulation carries out under purpose ground mode, therefore Rational Simplification is made to city traffic network and provides simulation region intra domain user
The relevant information in the main parking lot (parking node) of parking, specifying information are as shown in table 2.Simulating area share 4000 it is electronic
Automobile.With reference to the technical parameter of daily output Leaf, the lithium battery capacity C of electric vehicleEV=48kWh travels 100km power consumption
E100=15kWh, course continuation mileage XD=160km, charge power q=6kW, traveling average speed v=40km/h.Assuming that electronic vapour
Vehicle starting state-of-charge meets the normal distribution of N (0.51,0.18).Reflect weather, the factors such as road conditions constant c for (1,1.5]
Random number.Coefficient of elasticity m1=1.2, fuzzy coefficient m2=2, support coefficient n1=1.05, sequential interactive simulation time interval dt
=15min.
Each parking nodal information of table 2
Emulation zone divides working day and day off to carry out continuous analog.Present invention assumes that the typical trip of three kinds of user job day
Structure proportion is respectively 52.8%, 24.1%, 23.1%.Ratio is 70% assuming that day off goes out, wherein 35% goes out
The row moment obeys the normal distribution of N (8.92,3.24), and 35% trip moment obeys the normal distribution of N (16.47,3.41)；It is surplus
30% user of remaininging does not go on a journey on day off.And assume that user job day leisure duration meets being uniformly distributed for [1,2] h, day off is full
Foot [1,5] h's is uniformly distributed.Research object of the present invention is electronic private car, therefore all electric vehicles are parked during initialization
In residential block, and user terminate trip after night return to residential block.The parking site of each run is random according to stroke classification
Extract, primary, leisure place only extracted for same user job place and is randomly selected every time, go on a journey for the first time the moment and it is next when
It carves and only extracts once, leisure duration is randomly selected every time.
The analog result of the 1st week is not used in order to weaken the influence of initialization, in interpretation of result.Because simulated time is longer,
The 2nd to 9 all analog results is taken to be analyzed, without loss of generality.With node H1 (residential block) charging pile that stops in city traffic network
For installing quantity variation, analyze electrically-charging equipment in charging service net and be distributed the shadow to electric vehicle charge requirement spatial and temporal distributions
It rings and due to user's charge requirement and the situation of change of user's trip requirements caused by trip requirements reciprocation.Each parking
The distribution situation of node charging pile is shown in Table 3.Wherein, --- -- represents that parking node H1 charging pile installings quantity is to change, example
Middle setting is step-length with 25, and 0 is changed to from 350.Remaining parking node installing charging pile quantity is as shown in table 3.
Each parking node charging pile distribution situation of table 3
When each parking node charging pile distribution table 3 Suo Shi according to changing, the situation of change for the node charge requirement that stops is such as
Shown in Fig. 2 a, Fig. 2 b Fig. 2 c.
It can be seen that with the reduction of parking node H1 installing charging pile quantity there is charging to need at the node H1 that stops by Fig. 2 a
The electric vehicle number curve asked all changes in trend and amplitude.In terms of trend, during charging pile abundance, working day charging
Demand concentrates on goes home to the next morning the period between setting out and can descend to zero at dusk, the distribution of day off charge requirement
More uniform, curve is " undaform "；As charging pile quantity is reduced, the distribution of working day charge requirement more disperses and declines process
Middle appearance " platform " can not drop to zero, and the decline of day off charge requirement is very slow, and curve is " step type "；Charging pile quantity
Be further reduced, working day charge requirement rise and fall very slowly, day off charge requirement is almost unchanged, working day and stop
Day is ceased without significant difference, and curve is " high order smooth pattern ".In terms of amplitude, it can be clearly seen that be first slowly increased the change sharply increased afterwards
Law.This is because when charging pile is very inadequate, a large amount of electric vehicles cannot supplement electricity for a long time, and user can not even drive
It sails electric vehicle trip and selects other modes of transportation, so that caused by charge requirement constantly accumulation.
With the reduction of parking node H1 installing charging pile quantity, parking node R 3-R4 it can be seen from Fig. 2 b and Fig. 2 c
With W5-W8 charge requirement curves first increases and then decreases in amplitude, it is always in trend " spike type ".Since parking node H1 is
Residential block, charge requirement unsatisfied user demand can be transferred to shopping centre and workspace parking node, therefore R3-R4 and
Charge requirement can increase at W5-W8.Charging pile quantity is reduced to a certain extent, and the degree that user's charge requirement is satisfied is lower,
Quite a few electric vehicle by user abandon parking node H1, so as to get up to shopping centre and workspace parking node it is electronic
Automobile quantity is greatly reduced, therefore charge requirement can reduce instead at R3-R4 and W5-W8.This reason can be by parking node
Electric vehicle stops the situation of change verification of quantity at H1, specific as shown in Figure 3.
The feedback that user is satisfied situation according to charge requirement makes different decisions, makes user's trip requirements occurrence law
Variation.For the 9th week, the situation of change of user's trip requirements is as shown in Figure 4.
Not homochromy pillar height degree, which is represented at the time of automobile user sails out of parking node H1, in Fig. 4 is in corresponding time interval
Interior quantity, Trendline sail out of the accumulated quantity of user when representing to the corresponding time interval upper limit.Analysis chart 4 as can be seen that with
The reduction of parking node H1 charging pile quantity, be accumulated to each time interval upper limit sails out of number of users general trend first to subtract
Increase after few.Be accumulated to each time interval upper limit sails out of number of users reduction, i.e., becomes at the time of user sails out of parking node H1
Evening illustrates that " sluggishness " occur in user's trip requirements, this is because charging pile lazy weight causes period of reservation of number is elongated to cause
's.Be accumulated to each time interval upper limit sails out of number of users increase, illustrates that " recovery " occur in user's trip requirements, this is because
When charging pile is very inadequate user abandon electric vehicle take other modes of transportation go on a journey caused by.
Wherein it is accumulated to 5:00、5:30、6:00、6:30 and 7:00 sail out of number of users reduce and increase amplitude it is smaller,
This is because charge requirement is not accumulated significantly also；Over time, 7 are accumulated to:30、8:00、8:30、9:00 sails out of
Number of users is reduced and increase variation is apparent, this is because 7:30-9:00 is working peak period, and charging pile deficiency goes on a journey to user
The influence of demand is maximum；It is accumulated to 9:30 and 10:00 amplitude of variation is smaller, and is accumulated to 11:00 and amplitude of variation smaller later,
It is since the sum for having the demand of sailing out of in these time intervals lacks.
The present invention models the trip requirements of electronic private car user under purpose ground mode, and completes user and go out
Row interacts closed-loop simulation with charge requirement sequential.The present invention has fully considered automobile user trip requirements and charge requirement
Reciprocation, thus charge requirement analysis result is more in line with real daily life, and can be that analysis electric vehicle accesses electric network influencing
Analysis, the construction of electric vehicle electrically-charging equipment provide Research foundation.
Claims (8)
1. a kind of electric vehicle trip for considering charging feedback effect and charge requirement analysis method, which is characterized in that including such as
Lower step：
1) automobile user trip requirements model under purpose ground mode
CX=[Lp,Ap,Xd,LT,Xt,AT,Tt]
In formula：LpFor departure place；ApFor parking site；XdFor mileage travelled；LTFor the moment of setting out；XtTo travel duration；ATFor
Cut-off time；TtFor the duration that stops；
2) trip and charge requirement sequential interaction analysis
Entire analytic process includes four kinds of states, disappears first, establishing the electricity based on trip requirements when user is in transport condition
Model is consumed, second is that establishing the charge requirement based on fuzzy theory when user is in and drives into state generates model, third, at user
The electricity supplementary model for considering that electrically-charging equipment is abundance is established when resting state, is based on filling fourth, user is in when sailing out of state
User's otherness decision of electric feedback effect；
3) user's trip and the sequential interactive simulation of charge requirement
It sets first, carries out sequential interactive simulation by time interval of dt, [T-dt, T] interior user's trip state is constant；It is walked with waiting
A length of clock propulsion mode carries out user's trip and the sequential interactive simulation of charge requirement, including：
(1) T=0 is initialized；
(2) initialising subscriber k=1；
(3) judge trip state of the user in [T-dt, T]；
(4) when user's trip state is when driving, according to electric quantity consumption model modification state-of-charge；When the trip state of user is
When driving into, the generation of charge requirement is judged according to charge requirement generation model and is abandoned；When the trip state of user is stops,
State-of-charge and charge requirement are updated according to electricity supplementary model；When the trip state of user is to sail out of, according to state-of-charge
Support determines charge requirement and trip requirements；
(5) as user k=k+1, (3) step and (4) step is repeated until traversing all users, preserves each user in [T-dt, T]
Charge requirement and trip requirements；
(6) T=T+dt repeats (2) step to (5) step until simulation cycle terminates.
2. the electric vehicle trip according to claim 1 for considering charging feedback effect and charge requirement analysis method,
It is characterized in that, the electric quantity consumption model based on trip requirements described in step 2), is when user goes on a journey state in [T-dt, T]
For when driving, the electric quantity consumption model of foundation is as follows：
In formula：Dt is sequential interactive simulation time interval；SOCTRepresent the state-of-charge of T moment electric vehicles；SOCT-dtRepresent T-
The state-of-charge of dt moment electric vehicles；V is electric automobile during traveling average speed；XDFor electric vehicle course continuation mileage.
3. the electric vehicle trip according to claim 1 for considering charging feedback effect and charge requirement analysis method,
Be characterized in that, the charge requirement based on fuzzy theory described in step 2) generates model, be when user go on a journey state [T-dt,
T] it is interior for when driving into, the charge requirement generation model of foundation is as follows：
Wherein：
ASOC≥m2When, state-of-charge is complete sufficient for next stroke, without charge requirement, M (ASOC) value takes 0；m1≤
ASOC<m2When, ASOCCloser to m2, M (ASOC) closer to 0, ASOCCloser to m1, M (ASOC) closer to 1
In formula：F(ASOC,PT) represent that user drives into parking site P, state-of-charge abundance degree is ASOCWhen have the probability of charge requirement；
PTRepresent the quantity of T moment parking site P residue charging piles；ASOCRepresent state-of-charge abundance degree；M(ASOC) represent ASOCTo mould
Paste collection has the degree of membership of charge requirement；m1For coefficient of elasticity；SOCTRepresent the state-of-charge of T moment electric vehicles；CEVIt is electricity
Tankage；W represents unit mileage power consumption；C is reflection weather, road conditions constant；Xd_i+1In the traveling for representing user's stroke next time
Journey；m2For fuzzy coefficient.
4. the electric vehicle trip according to claim 1 for considering charging feedback effect and charge requirement analysis method,
Be characterized in that, the considerations of step 2) is described the abundance electricity supplementary model of electrically-charging equipment, be when user goes on a journey state in [T-
Dt, T] in for stop when, the electricity supplementary model of foundation is as follows：
In formula：SOCTRepresent the state-of-charge of T moment electric vehicles；SOCT-dtRepresent the state-of-charge of T-dt moment electric vehicles；
Q is charging batteries of electric automobile power；Dt is sequential interactive simulation time interval；CEVIt is battery capacity；PT-dtWhen representing T-dt
Carve the quantity of parking site P residue charging piles.
5. the electric vehicle trip according to claim 4 for considering charging feedback effect and charge requirement analysis method,
It being characterized in that, if electric vehicle state-of-charge reaches 100% in holding process, which disappears user,
And state-of-charge is constant before sailing out of；Otherwise the user keeps charge requirement and is continued to update its lotus according to electricity supplementary model
Electricity condition.
6. the electric vehicle trip according to claim 1 for considering charging feedback effect and charge requirement analysis method,
It is characterized in that, user's otherness decision based on charging feedback effect described in step 2) includes：
(1) state-of-charge support is calculated：
In formula, BSOCRepresent state-of-charge support；SOCTRepresent the state-of-charge of T moment electric vehicles；CEVIt is battery capacity；c
For reflection weather, road conditions constant；W represents unit mileage power consumption；Xd_iRepresent the mileage travelled of this stroke of user；
(2) n is set1To support coefficient, charging feedback result is determined according to state-of-charge support
If BSOC≥n1, state-of-charge supports this stroke, and feedback result is：It can sail out of, user is made by sailing out of in the original plan
Decision, trip requirements are constant；
If BSOC<n1, state-of-charge cannot support this stroke, and feedback result is：It can not temporarily sail out of, i.e., user actually cannot be true
Parking site is just sailed out of, sailing out of at this time is interpreted as user's original trip requirements；
When feedback result is when can not temporarily sail out of, user has different determine due to the travel activity type of this stroke is different
Plan criterion：
When stroke classification is work, user's decision factor is influenced for arrival moment, and user's decision-making criterion is AT_0+dt>AT_max；
When stroke classification is leisure, user's decision factor is influenced for leisure duration, user's decision-making criterion is Tt_0-dt<Tt_min；
When stroke classification is gone home to terminate trip, user's decision factor is influenced for arrival moment, and user's decision-making criterion is AT_0+
dt>AT_max；
When stroke classification is to go home in short-term, without judging；
Wherein, AT_0For the cut-off time of user's original plan, AT_maxFor the tolerance moment the latest of user's parking, Tt_0For user's original meter
Draw stay time, Tt_minThe most short tolerance duration stopped for user；
(3) user makes user's otherness decision according to stroke classification with corresponding criterion
(3.1) when this travel activity is gone home for work or after terminating to go on a journey, if meeting criterion AT_0+dt>AT_max, then make
Abandon the decision that electric vehicle takes other modes of transportation to continue this stroke, otherwise make keep charge requirement wait for one section when
Between decision；
(3.2) when this travel activity is leisure, if meeting criterion Tt_0-dt<Tt_min, then make and abandon the continuation of this stroke
Next stroke or the decision for terminating trip, otherwise make the decision that charge requirement is kept to wait for a period of time；
(3.3) when this travel activity is when going home in short-term, without judging, make abandon this stroke continue next stroke or
Terminate the decision of trip.
7. the electric vehicle trip according to claim 6 for considering charging feedback effect and charge requirement analysis method,
It is characterized in that, this stroke of abandoning described in (3.3) of (3) step continues in next stroke, if day trip does not terminate, at this time
It needs to recalculate state-of-charge support B 'SOCIf B 'SOC≥n1Then user continue to make abandon this stroke continue next time
Stroke or the decision for terminating trip, otherwise make the decision that charge requirement is kept to wait for a period of time again.
8. the electric vehicle trip according to claim 6 for considering charging feedback effect and charge requirement analysis method,
It is characterized in that, the electric vehicle of abandoning described in (3.1) of (3) step takes other modes of transportation to continue this stroke, need to examine
Consider user's possibility for fetching electric vehicle, if user and electric vehicle position are misaligned, user do not reach also abandon it is electronic
At automobile, it can not fetch；If position overlaps, and B 'SOC≥n1, then user successfully fetch electric vehicle and electric vehicle drive from
It opens, otherwise other modes of transportation is taken to leave again.
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