CN104680258A - Method and device for dispatching electric taxi - Google Patents

Abstract

The invention discloses a method and device for dispatching an electric taxi. The method comprises the following steps: A, according to a predetermined time interval, collecting data of the electric taxi and a charging facility; B, optimally dispatching the charging of the electric taxi by an ordered time charging strategy, an ordered space charging strategy or an ordered time and space combined charging strategy, wherein the ordered time charging strategy comprises maximization of the time utilization efficiency of a charging facility of a charging station, minimization of the time of charging service of the electric taxi and minimization of time-category load variance from the electric taxi to an electric region distribution network; the ordered space charging strategy comprises maximization of the space utilization efficiency of the charging facility of the charging station, minimization of a displacement distance of charging the electric taxi and minimization of time-category load variance from the electric taxi to the electric region distribution network. Through the use of the method and device for dispatching the electric taxi, the usage rate of charging equipment in the charging station can be increased.

Description

Electric taxi dispatching method and device

Technical field

The present invention relates to technical field of new energies, particularly relate to city electric car Charge Management technical field.

Background technology

Along with the development of auto industry technology and the raising of Living consumption, China's automobile guarantee-quantity increases rapidly.But meanwhile, worldwide energy shortage and problem of environmental pollution are also day by day serious.Electric automobile, as the vehicles of new generation, with advantages such as its energy-saving and environmental protection, is subject to the extensive concern of national governments.Wherein, electric taxi, as the Demonstration Application of electric automobile, in the city operations such as Beijing, Shenzhen, in future, will have more electric taxi and will replace fuel vehicle.

But, due to its operation characteristic of electric taxi, need to increase the service time as far as possible, current fill technical conditions soon under, an electric taxi is by state-of-charge (State of Charge, SOC) from 0% to 100%, adopt the rate of charge of 0.5C, need two hours to complete charging.Under unordered charging, its duration of charging of electric taxi Stochastic choice, often cause electric taxi charge load in time, spatially skewness, there is charging jam in part-time section and part charging station.The manual service taked at present is relatively passive, does not play the effect of scheduling in order.

Moreover charging station carries out the medium of energy exchange as electric taxi and electrical network, in operation and scheduling, all electrical network and electric taxi user are had a huge impact.The orderly operation of charging station realizes the basis that extensive electric taxi charges in order.And, in charging station electric taxi charge in order for improve charging station run economy and improve operational efficiency have great importance.

As shown in Figure 1, electric taxi selects charging station nearby to the law of electric charges of current charging station; After vehicle pull-in, idle charging pile is selected to charge; If without idle charging pile, then can select to continue to wait for, or select other charging stations to charge.After vehicle completes charging, leave charging station.

If large-scale electric taxi enters the commercialization epoch, continue to continue to use chaotic like this law of electric charges, charging service cannot meet the charge requirement of existing user.This unordered charging method, by the operational efficiency of the experience and charging station that have a strong impact on electric taxi user, also threatens to the stability of power distribution network and security simultaneously.

Summary of the invention

In view of this, the object of the invention is to overcome the deficiencies in the prior art, a kind of electric taxi dispatching method and device are provided, electric taxi is utilized to have the distinguishing feature of mobility over time and space, participate in the prerequisite of scheduling at electric taxi under, within the scope of Time and place, electric taxi is controlled in order.

In order to realize this object, the technical scheme that the present invention takes is as follows.

A kind of electric taxi dispatching method, described method comprises:

A, to schedule interval gather electric taxi and electrically-charging equipment data;

B, with orderly time charging strategy, ordered space charging strategy or in order space-time unite charging strategy scheduling is optimized to electric taxi charging, determine to charge in order scheduling strategy,

Wherein in order time charging strategy comprises the time utilization maximizing efficiency of charging station electrically-charging equipment, electric taxi charging service time minimum and the time domain load variance of electric taxi to regional distribution network and minimizes;

The space efficiency utilization that ordered space charging strategy comprises charging station electrically-charging equipment maximizes, electric taxi charging displacement minimizes and minimizes with the Space Categories load variance of electric taxi to regional distribution network;

Orderly space-time unite charging strategy comprises the optimization aim of orderly time charging strategy and ordered space charging strategy.

In steps A, gather that electric taxi and electrically-charging equipment data comprise electric taxi numbering data, the position data of electric taxi, the state-of-charge of electric taxi, electric taxi carrying destination, the running state data of electric taxi and the running state data of electrically-charging equipment, current charging vehicle state-of-charge, electrically-charging equipment charging are estimated excess time, wait charging vehicle information.

Especially, described predetermined time interval is every 15 minutes image data.

In addition, in step B, with orderly time charging strategy, ordered space charging strategy or orderly space-time unite charging strategy, electric taxi operation constraint and the constraint of electric taxi battery are comprised to the constraint that electric taxi charging is optimized scheduling, wherein,

Electric taxi runs constraint and comprises: electric taxi has fixing charging times, electric taxi within per time cycle, and when going back to station, it selects that charging station is in multiple charging station one, electric taxi has enough electricity after completing back the carrying task before standing and returns charging station;

The constraint of electric taxi battery comprises: the state-of-charge SOC of the charge power in electric taxi charging process between the charge power bound of electrically-charging equipment, in electric taxi operational process is thereon between lower limit.

In orderly time charging strategy, the time utilization maximizing efficiency of charging station electrically-charging equipment is:

$F_{1,\mathrm{time}}=\min \underset{t=1}{\overset{T}{\mathrm{\Σ}}}{(\underset{m=1}{\overset{M}{\mathrm{\Σ}}}{x}_{\mathrm{mt}}{P}_m-\frac{1}{T}\underset{t=1}{\overset{T}{\mathrm{\Σ}}}\underset{m=1}{\overset{M}{\mathrm{\Σ}}}{x}_{\mathrm{mt}}{P}_m)}^2,$

Wherein, x _mtfor time-optimized decision variable, P _mfor the charge power of electric taxi m, M is the quantity of electric taxi, and T is total activation duration,

Electric taxi charging service minimal time turns to:

$F_{2,\mathrm{time}}=\underset{m=1}{\overset{M}{\mathrm{\Σ}}}(T_{m,b}+T_{m,w}+T_{m,c}),$

Wherein, T _m,b, T _m,wand T _m,cbe respectively the in transit time of electric taxi m in charging service process, stand-by period and duration of charging,

The time domain load variance of electric taxi to regional distribution network is minimised as:

$F_{3,\mathrm{time}}=\min \underset{t=1}{\overset{T}{\mathrm{\Σ}}}{(P_t-{\stackrel{\‾}{P}}_T)}^2,$

Wherein, P _tfor regional distribution network is in the burden with power of moment t, for the average load of regional distribution network in time domain.

In ordered space charging strategy, the space efficiency utilization of charging station electrically-charging equipment is maximum to be turned to:

$F_{1,\mathrm{space}}=\min \underset{n=1}{\overset{N}{\mathrm{\Σ}}}{(\underset{m=1}{\overset{M}{\mathrm{\Σ}}}{x}_{\mathrm{mn}}{P}_m-\frac{C_n}{\underset{j=1}{\overset{N}{\mathrm{\Σ}}}{C}_n}\underset{m=1}{\overset{M}{\mathrm{\Σ}}}{x}_{\mathrm{mn}}{P}_m)}^2,$

Wherein, x _mnfor the decision variable of space optimization, P _mfor the charge power of electric taxi m, M is the quantity of electric taxi, and N is charging station quantity in region, C _nfor the electrically-charging equipment quantity in charging station n,

Electric taxi charging displacement is minimised as:

$F_{2,\mathrm{space}}=\underset{i=1}{\overset{M}{\mathrm{\Σ}}}{L}_{m,\mathrm{travel}},$

Wherein, L _{m, travel}for the displacement in the charging service process of electric taxi m,

The Space Categories load variance of electric taxi to regional distribution network is minimised as:

$F_{3,\mathrm{space}}=\min \underset{n_{\mathrm{bus}}=1}{\overset{N_{\mathrm{bus}}}{\mathrm{\Σ}}}{(P_{n_{\mathrm{bus}}}-{\stackrel{\‾}{P}}_{N_{\mathrm{bus}}})}^2,$

Wherein, for regional distribution network is at n _busthe burden with power of node, for regional distribution network is in the average load of Space Categories.

In addition in step B, adopt degree of membership by objective fuzzy for orderly time charging strategy, ordered space charging strategy or orderly space-time unite charging strategy, form fuzzy object,

${\mathrm{\&mu;}}_x\left(x\right)=\left\{\begin{array}{ccc}0& f_i\left(x\right)\&le;c_{i\min }& \\ \frac{f_i\left(x\right)-c_{i\min }}{c_{i\max }-c_{i\min }}& c_{i\min }<f_i\left(x\right){<c}_{i\max }& i=\mathrm{1,2,3}\\ 1& f_i\left(x\right)\&GreaterEqual;c_{i\max }& \end{array}\right.,$

Wherein, f _ix () refers to i-th target of obfuscation; μ _ix () refers to target f _ithe degree of membership of (x); c _{i min}and c _{i max}feeling the pulse with the finger-tip mark f respectively _ithe boundary up and down of (x), c _{i min}refer to the optimal-adaptive angle value of single goal, c _{i max}refer to the initial value fitness value of corresponding target,

Afterwards, comprehensively single object optimization is formed to multiple degree of membership:

F＝max(μ ₁,μ ₂,μ ₃)。

After forming single object optimization, comprise further and use particle swarm optimization to obtain optimum results, comprising:

$v_{\mathrm{id}}^{k+1}=\mathrm{\&omega;}\left(k\right)v_{\mathrm{id}}^k+c_1{r}_1(p_{\mathrm{id}}-z_{\mathrm{id}}^k)+c_2{r}_2(p_{\mathrm{gd}}-z_{\mathrm{id}}^k),$

$z_{\mathrm{id}}^{k+1}=z_{\mathrm{id}}^k+v_{\mathrm{id}}^{k+1},$

$\mathrm{\&omega;}\left(k\right)={\mathrm{\&omega;}}_{\mathrm{start}}-({\mathrm{\&omega;}}_{\mathrm{start}}-{\mathrm{\&omega;}}_{\mathrm{end}}){\left(\frac{k}{T}\right)}^2,$

Wherein, represent particle position variable, represent particle rapidity variable, p _id, p _gdrepresent individual optimal solution and group optimal solution respectively, c ₁, c ₂for constant, r ₁, r ₂for random number, ω (k) is inertia weight, ω _startand ω _endbe respectively starting and ending weight, k and T is respectively the total algebraically of current iteration algebraic sum iteration.

A kind of electric taxi dispatching device, comprises electric taxi monitor supervision platform, electrically-charging equipment monitor supervision platform and control center of charging in order, wherein,

Electric taxi monitor supervision platform, electrically-charging equipment monitor supervision platform are respectively used to interval to schedule and gather electric taxi and electrically-charging equipment data;

Orderly charging control center is used for being optimized scheduling with orderly time charging strategy, ordered space charging strategy or orderly space-time unite charging strategy to electric taxi charging, determines to charge in order scheduling strategy,

Wherein in order time charging strategy comprises the time utilization maximizing efficiency of charging station electrically-charging equipment, electric taxi charging service time minimum and the time domain load variance of electric taxi to regional distribution network and minimizes;

The space efficiency utilization that ordered space charging strategy comprises charging station electrically-charging equipment maximizes, electric taxi charging displacement minimizes and minimizes with the Space Categories load variance of electric taxi to regional distribution network;

Orderly space-time unite charging strategy comprises the optimization aim of orderly time charging strategy and ordered space charging strategy.

Wherein utilize Ethernet or communication network that the electric taxi collected and electrically-charging equipment data are transferred to control center of charging in order, and the orderly charging scheduling strategy utilizing communication network control center of charging in order to be determined is transferred to electric taxi user.

By adopting electric taxi dispatching method of the present invention and device, the charging load that can reduce charging station, time, spatially unbalanced, makes the electrically-charging equipment utilization rate in charging station be improved.

In addition, by adopting electric taxi dispatching method of the present invention and device, the charging waiting time of electric taxi can be reduced, and shorten the charging distance of electric taxi.

In addition, by adopting electric taxi dispatching method of the present invention and device, the impact of charging station for distribution network system can also be reduced, therefore improving stability and the security of power distribution network.

Accompanying drawing explanation

Fig. 1 is the schematic flow sheet of the unordered charging of electric taxi in prior art.

Fig. 2 is the structural drawing of electric taxi dispatching device in embodiment of the present invention.

Fig. 3 is the schematic flow sheet of electric taxi dispatching method in embodiment of the present invention.

Fig. 4 is the Comparative result schematic diagram of electric taxi dispatching method and the unordered charging of electric taxi in embodiment of the present invention.

Fig. 5 is the Comparative result schematic diagram of electric taxi dispatching method and the unordered charging of electric taxi in embodiment of the present invention.

Embodiment

Below in conjunction with accompanying drawing, the present invention is elaborated.

The example embodiment that following discloses are detailed.But concrete structure disclosed herein and function detail are only the objects for describing example embodiment.

But should be appreciated that, the present invention is not limited to disclosed concrete example embodiment, but covers all modifications, equivalent and the alternative that fall within the scope of the disclosure.In the description to whole accompanying drawing, identical Reference numeral represents identical element.

Should be appreciated that, term "and/or" as used in this comprises one or morely relevant lists any of item and all combinations simultaneously.Should be appreciated that in addition, when parts or unit are called as " connection " or " coupling " to another parts or unit, it can be directly connected or coupled to miscellaneous part or unit, or also can there is intermediate member or unit.In addition, other words being used for describing relation between parts or unit should be understood according to identical mode (such as, " between " to " directly ", " adjacent " to " direct neighbor " etc.).

As shown in Figure 2, electric taxi dispatching device of the present invention comprises electric taxi monitor supervision platform, electrically-charging equipment monitor supervision platform and control center of charging in order, wherein,

Electric taxi monitor supervision platform, electrically-charging equipment monitor supervision platform are respectively used to interval to schedule and gather electric taxi and electrically-charging equipment data;

Orderly charging control center is used for being optimized scheduling with orderly time charging strategy, ordered space charging strategy or orderly space-time unite charging strategy to electric taxi charging, determines to charge in order scheduling strategy,

Wherein in order time charging strategy comprises the time utilization maximizing efficiency of charging station electrically-charging equipment, electric taxi charging service time minimum and the time domain load variance of electric taxi to regional distribution network and minimizes;

The space efficiency utilization that ordered space charging strategy comprises charging station electrically-charging equipment maximizes, electric taxi charging displacement minimizes and minimizes with the Space Categories load variance of electric taxi to regional distribution network;

Orderly space-time unite charging strategy comprises the optimization aim of orderly time charging strategy and ordered space charging strategy.

As a specific embodiment of the present invention, utilize Ethernet or communication network that the electric taxi collected and electrically-charging equipment data are transferred to control center of charging in order, and the orderly charging scheduling strategy utilizing communication network control center of charging in order to be determined is transferred to electric taxi user.Such as data transfer mode has two kinds, and one is Ethernet data transmission, a kind of by 2G/3G network service.Wherein, inner at charging station, Ethernet is utilized charging equipment monitor supervision platform, electric taxi monitor supervision platform and control center of charging in order to be intercomed mutually, every Fixed Time Interval, by the present data transmission of charging equipment monitor supervision platform, electric taxi monitor supervision platform to control center of charging in order.In the orderly control center of charging station, the orderly method for optimizing scheduling of control center is utilized to obtain the orderly charging scheduling strategy of electric taxi.In addition, in the communication of electric taxi and charging station, then use 2G/3G Internet Transmission, on the one hand electric taxi real-time running data is sent to electric taxi monitor supervision platform, orderly charging scheduling strategy charging station control center obtained on the other hand sends corresponding electric taxi user to.

Correspondingly, electric taxi dispatching method of the present invention comprises the following steps:

A, to schedule interval gather electric taxi and electrically-charging equipment data;

B, with orderly time charging strategy, ordered space charging strategy or in order space-time unite charging strategy scheduling is optimized to electric taxi charging, determine to charge in order scheduling strategy,

Wherein in order time charging strategy comprises the time utilization maximizing efficiency of charging station electrically-charging equipment, electric taxi charging service time minimum and the time domain load variance of electric taxi to regional distribution network and minimizes;

The space efficiency utilization that ordered space charging strategy comprises charging station electrically-charging equipment maximizes, electric taxi charging displacement minimizes and minimizes with the Space Categories load variance of electric taxi to regional distribution network;

Orderly space-time unite charging strategy comprises the optimization aim of orderly time charging strategy and ordered space charging strategy.

Therefore, by adopting electric taxi dispatching method of the present invention and device, the charging load that can reduce charging station, time, spatially unbalanced, makes the charging equipment utilization rate in charging station be improved.

In addition, by adopting electric taxi dispatching method of the present invention and device, the charging waiting time of electric taxi can be reduced, and shorten the charging distance of electric taxi.

In an embodiment, in steps A, gather that electric taxi and electrically-charging equipment data comprise electric taxi numbering data, the position of electric taxi, the state-of-charge of electric taxi, electric taxi carrying destination, the running state data of electric taxi and the running state data of electrically-charging equipment, current charging vehicle state-of-charge, electrically-charging equipment charging are estimated excess time, wait charging vehicle information.

In addition, the predetermined time interval of described image data can be chosen according to actual conditions, and such as, in an embodiment, described predetermined time interval is for carry out data acquisition every 15 minutes.

Below by way of different embodiment, technical scheme of the present invention is described.

First introduce scheduling strategy, the target of scheduling strategy and optimization is closely related, specifically comprises:

1. improve time, the space availability ratio of charging station electrically-charging equipment.

Due to the operation characteristic of electric taxi, charging equipment efficiency is in time range, skewness weighs, thus cause vehicle to be charged to concentrate selection some periods to charge, which decrease charging equipment time availability, cause partial period charging pile idle, and the phenomenon that partial period charging is queued up.Equally, spatially also there will be charge profile unbalanced, thus cause vehicle to be charged to concentrate selection charging station to charge, while which decreasing charging equipment time and space utilization rate, negative effect is brought to the overall development of charging station.

From the angle of charging station operator, to improve time of electrically-charging equipment, space availability ratio for target, charging taxi is distributed according to time, space, by the time of charging vehicle, spatial character equalization, the charging load that can reduce charging station, time, spatially unbalanced, makes the charging equipment utilization rate in charging station higher.

$F_{1,\mathrm{time}}=\min \underset{t=1}{\overset{T}{\mathrm{\&Sigma;}}}{(\underset{m=1}{\overset{M}{\mathrm{\&Sigma;}}}{x}_{\mathrm{mt}}{P}_m-\frac{1}{T}\underset{t=1}{\overset{T}{\mathrm{\&Sigma;}}}\underset{m=1}{\overset{M}{\mathrm{\&Sigma;}}}{x}_{\mathrm{mt}}{P}_m)}^2---\left(1\right)$

$F_{1,\mathrm{space}}=\min \underset{n=1}{\overset{N}{\mathrm{\&Sigma;}}}{(\underset{m=1}{\overset{M}{\mathrm{\&Sigma;}}}{x}_{\mathrm{mn}}{P}_m-\frac{C_n}{\underset{j=1}{\overset{N}{\mathrm{\&Sigma;}}}{C}_n}\underset{m=1}{\overset{M}{\mathrm{\&Sigma;}}}{x}_{\mathrm{mn}}{P}_m)}^2---\left(2\right)$

Wherein, t=1,2 ..., T; M=1,2 ..., M; N=1,2 ..., N;

In formula (1) and (2), M and N is respectively electric taxi charging station quantity in the quantity of electric taxi and region; T is total activation duration; x _mtand x _mnbe respectively time-optimized and the decision variable of space optimization.In addition, P _mfor the charge power of electric taxi m, C _nfor the electrically-charging equipment quantity of charging station n.

2. electric taxi user charging service time minimum and the displacement that causes due to charging service minimize.

Above-mentioned target 1 mainly analyzes the uneven of this charging power load distributing based on the angle of charging station, and target 2 analyzes in the angle of electric taxi user, in time domain, with electric taxi user charging service shortest time for target; In Space Categories, minimize with the displacement that electric taxi causes due to charging service.Wherein the charging service time comprises time in transit from carrying destination to charging station, charging station stand-by period and duration of charging three part, and wherein time in transit and charging stand-by period are all can optimized amount.The space displacement caused due to charging service then refers to when electric taxi has charge requirement, the distance of the space movement caused owing to going to charging station to carry out charging between carrying last time and next carrying.

$F_{2,\mathrm{time}}=\underset{m=1}{\overset{M}{\mathrm{\&Sigma;}}}(T_{m,b}+T_{m,w}+T_{m,c})---\left(3\right)$

$F_{2,\mathrm{space}}=\underset{i=1}{\overset{M}{\mathrm{\&Sigma;}}}{L}_{m,\mathrm{travel}}---\left(4\right)$

In formula, T _m,b, T _m,w, T _m,crefer to the in transit time of electric taxi m in charging service process, stand-by period and duration of charging respectively.And L _{m, travel}then refer to the space transfer distance of electric taxi m in charging service process.

3. electric taxi charging minimizes the negative effect of regional distribution network

In the present invention, in order to model simplification, the load variance index in the time of regional distribution network and space is utilized to assess the space-time impact of electric taxi charging station on regional distribution network.Load variance index effectively can weigh the fluctuation situation of region load, and load fluctuation Shaoxing opera is strong, then can cause that the feeder loss of regional distribution network is larger, voltage is more unstable.Therefore, by control overhead variance, the adverse effect of the charging load of electric taxi charging station can well be controlled, shown in (5) ~ (6).

$F_{3,\mathrm{time}}=\min \underset{t=1}{\overset{T}{\mathrm{\&Sigma;}}}{(P_t-{\stackrel{\&OverBar;}{P}}_T)}^2---\left(5\right)$

$F_{3,\mathrm{space}}=\min \underset{n_{\mathrm{bus}}=1}{\overset{N_{\mathrm{bus}}}{\mathrm{\&Sigma;}}}{(P_{n_{\mathrm{bus}}}-{\stackrel{\&OverBar;}{P}}_{N_{\mathrm{bus}}})}^2---\left(6\right)$

In formula, P _twith represent that regional distribution network is at the burden with power of moment t and n respectively _busthe burden with power of node, the two is respectively the measurement in time and space; And with then represent the average load of time and Space Categories respectively.

Therefore, in embodiments of the present invention, in orderly time charging strategy, the time utilization maximizing efficiency of charging station electrically-charging equipment is:

$F_{1,\mathrm{time}}=\min \underset{t=1}{\overset{T}{\mathrm{\&Sigma;}}}{(\underset{m=1}{\overset{M}{\mathrm{\&Sigma;}}}{x}_{\mathrm{mt}}{P}_m-\frac{1}{T}\underset{t=1}{\overset{T}{\mathrm{\&Sigma;}}}\underset{m=1}{\overset{M}{\mathrm{\&Sigma;}}}{x}_{\mathrm{mt}}{P}_m)}^2,$

Electric taxi charging service minimal time turns to:

$F_{2,\mathrm{time}}=\underset{m=1}{\overset{M}{\mathrm{\&Sigma;}}}(T_{m,b}+T_{m,w}+T_{m,c}),$

The time domain load variance of electric taxi to regional distribution network is minimised as:

$F_{3,\mathrm{time}}=\min \underset{t=1}{\overset{T}{\mathrm{\&Sigma;}}}{(P_t-{\stackrel{\&OverBar;}{P}}_T)}^2,$

In addition, in ordered space charging strategy, the space efficiency utilization of charging station electrically-charging equipment is maximum to be turned to:

$F_{1,\mathrm{space}}=\min \underset{n=1}{\overset{N}{\mathrm{\&Sigma;}}}{(\underset{m=1}{\overset{M}{\mathrm{\&Sigma;}}}{x}_{\mathrm{mn}}{P}_m-\frac{C_n}{\underset{j=1}{\overset{N}{\mathrm{\&Sigma;}}}{C}_n}\underset{m=1}{\overset{M}{\mathrm{\&Sigma;}}}{x}_{\mathrm{mn}}{P}_m)}^2,$

Electric taxi charging displacement is minimised as:

$F_{2,\mathrm{space}}=\underset{i=1}{\overset{M}{\mathrm{\&Sigma;}}}{L}_{m,\mathrm{travel}},$

The Space Categories load variance of electric taxi to regional distribution network is minimised as:

$F_{3,\mathrm{space}}=\min \underset{n_{\mathrm{bus}}=1}{\overset{N_{\mathrm{bus}}}{\mathrm{\&Sigma;}}}{(P_{n_{\mathrm{bus}}}-{\stackrel{\&OverBar;}{P}}_{N_{\mathrm{bus}}})}^2,$

In addition, in the electric taxi dispatching method step B of the specific embodiment of the invention, with orderly time charging strategy, ordered space charging strategy or orderly space-time unite charging strategy, electric taxi operation constraint and the constraint of electric taxi battery are comprised to the constraint that electric taxi charging is optimized scheduling, wherein, electric taxi operation constraint comprises:

Electric taxi has fixing charging times S in every period of time T, namely

$\underset{t=1}{\overset{T}{\mathrm{\&Sigma;}}}{x}_{m,t}=S,$

Electric taxi its selection charging station when going back to station is one in N number of charging station, namely

$\underset{n=1}{\overset{N}{\mathrm{\&Sigma;}}}{x}_{m,n}=1,$

After carrying task before electric taxi completes go back to station, there is enough electricity and return charging station, namely

L _operation≤DM；

Wherein L _operationrefer to the operation total kilometrage between electric taxi twice charging, DM then refers to the continual mileage of electric taxi.

Electric taxi battery constraint comprise: the charge power in electric taxi charging process between the charge power bound of electrically-charging equipment, namely

P _c-min≤ P _c≤ P _c-max, P _c-minand P _c-maxbe respectively lower limit and the upper limit of charge power,

State-of-charge SOC in electric taxi operational process is thereon between lower limit, namely

SOC _min≤SOC _mt≤SOC _max。

Multiple optimization aim when depositing, the scheduling problem of electric taxi is actual is a multi-objective optimization question above.Usually, right to use heavy punishment function method or fuzz method solve similar problem.Wherein, weight penalty function method often needs subjective setting or draws suitable weight coefficient through test of many times, and fuzzy rule utilizes degree of membership by objective fuzzy, and forms Fuzzy Multiobjective.Therefore, do not need to set weight coefficient, thus objectively to solve.

Therefore, in the present invention's embodiment, adopt degree of membership by objective fuzzy for orderly time charging strategy, ordered space charging strategy or orderly space-time unite charging strategy, form fuzzy object,

${\mathrm{\&mu;}}_x\left(x\right)=\left\{\begin{array}{ccc}0& f_i\left(x\right)\&le;c_{i\min }& \\ \frac{f_i\left(x\right)-c_{i\min }}{c_{i\max }-c_{i\min }}& c_{i\min }<f_i\left(x\right){<c}_{i\max }& i=\mathrm{1,2,3}\\ 1& f_i\left(x\right)\&GreaterEqual;c_{i\max }& \end{array}\right.,$

Wherein, f _ix () refers to i-th target of obfuscation; μ _ix () refers to target f _ithe degree of membership of (x); c _{i min}and c _{i max}feeling the pulse with the finger-tip mark f respectively _ithe boundary up and down of (x), c _{i min}refer to the optimal-adaptive angle value of single goal, c _{i max}refer to the initial value fitness value of corresponding target,

Afterwards, comprehensively single object optimization is formed to multiple degree of membership:

F＝max(μ ₁,μ ₂,μ ₃)。

After forming single object optimization, the specific embodiment of the invention comprises use particle swarm optimization further and asks for optimum results, particle swarm optimization is proposed in nineteen ninety-five by Kennedy and Eberhart the earliest, the advantage fast because of its search speed and search capability is strong, the optimization in each field is widely adopted in calculating.Equally, population is carrying out the process of particle iterative search, is also to carry out in the neighborhood of previous generation optimum solution, also has the problem being absorbed in locally optimal solution.Therefore, in solution procedure of the present invention, elementary particle group method is improved, on the one hand, when optimizing process is absorbed in locally optimal solution, carry out mandatory jumping out; On the other hand, the inertia weight of innovatory algorithm, shown in (14) ~ (16), avoids optimizing process to be absorbed in locally optimal solution.Comprise:

$v_{\mathrm{id}}^{k+1}=\mathrm{\&omega;}\left(k\right)v_{\mathrm{id}}^k+c_1{r}_1(p_{\mathrm{id}}-z_{\mathrm{id}}^k)+c_2{r}_2(p_{\mathrm{gd}}-z_{\mathrm{id}}^k),$

$z_{\mathrm{id}}^{k+1}=z_{\mathrm{id}}^k+v_{\mathrm{id}}^{k+1},$

$\mathrm{\&omega;}\left(k\right)={\mathrm{\&omega;}}_{\mathrm{start}}-({\mathrm{\&omega;}}_{\mathrm{start}}-{\mathrm{\&omega;}}_{\mathrm{end}}){\left(\frac{k}{T}\right)}^2,$

Wherein, represent particle position variable, represent particle rapidity variable, p _id, p _gdrepresent individual optimal solution and group optimal solution respectively, c ₁, c ₂for constant, r ₁, r ₂for random number, ω (k) is inertia weight, ω _startand ω _endbe respectively starting and ending weight, k and T is respectively the total algebraically of current iteration algebraic sum iteration.

Although construct single optimization aim for fuzz method in foregoing, particle swarm optimization is asked for optimal result and is illustrated, but those skilled in that art are understood that, electric taxi dispatching method of the present invention is not limited to utilize fuzz method to construct simple target, is also not limited to utilize particle swarm optimization to solve.Such as can also use the classical method such as linear programming, quadratic programming, and artificial intelligence approach etc. obtains optimum results, can't have influence on the realization of technical solution of the present invention.

Below utilize one more specifically example so that technique effect of the present invention to be described, suppose, in a region 50km × 30km, to distributed 8 charging stations, the electrically-charging equipment number of each charging station is respectively [1,2,2,1,1,2,3,1] platform; Electric taxi quantity is 100, and its initial position is randomly dispersed in regional center; The station SOC that returns of electric taxi meets N (0.5,0.1) distribution.

The unordered charge mode of prior art:

In electric taxi operation process, be in unordered charged state, i.e. charge mode nearby, represent electric taxi and charging station there is no interactive communication condition under operational process, shown in Fig. 1.Prescribing a time limit if electric taxi occurs that SOC is low to moderate under setting runs warning, when completing this carrying task, namely selecting nearest charging station to charge; If electric taxi is at the end of certain carrying process, when finding that current dump energy cannot complete carrying task next time, then nearest charging station is selected to charge.

In addition, adopt electric taxi dispatching method of the present invention and device, on the basis of charging station and electric taxi two-way communication, minimize with the time utilization maximizing efficiency of charging station electrically-charging equipment, electric taxi charging service time minimum and the electric taxi time domain load variance to regional distribution network; The space efficiency utilization of charging station electrically-charging equipment maximizes, electric taxi charging displacement minimizes and is minimised as optimization aim with the Space Categories load variance of electric taxi to regional distribution network, to charge in order scheduling from time, space and space-time unite category.The result as Fig. 4 and Fig. 5 can be obtained.Wherein, Fig. 4 is the contrast of unordered, the orderly time scheduling of electric taxi and space-time combined dispatching charging load.As shown in Figure 4, in electric taxi dispatching method of the present invention, relative to space-time unite Optimized Operation strategy, independent orderly time scheduling is more obvious for the optimal control effect in time domain.In addition, Fig. 5 is the contrast that electric taxi is unordered, ordered space is dispatched and space-time combined dispatching charging station is selected, as shown in Figure 5, in electric taxi dispatching method of the present invention, relative to space-time unite Optimized Operation strategy, independent ordered space scheduling is more obvious for the optimal control effect in Space Categories.

It should be noted that; above-mentioned embodiment is only the present invention's preferably embodiment; can not limiting the scope of the invention be understood as, not depart under concept thereof of the present invention, all protection scope of the present invention is belonged to modification to any subtle change that the present invention does.

Claims (10)

1. an electric taxi dispatching method, described method comprises:

A, to schedule interval gather electric taxi and electrically-charging equipment data;

B, with orderly time charging strategy, ordered space charging strategy or in order space-time unite charging strategy scheduling is optimized to electric taxi charging, determine to charge in order scheduling strategy,

Wherein in order time charging strategy comprises the time utilization maximizing efficiency of charging station electrically-charging equipment, electric taxi charging service time minimum and the time domain load variance of electric taxi to regional distribution network and minimizes;

The space efficiency utilization that ordered space charging strategy comprises charging station electrically-charging equipment maximizes, electric taxi charging displacement minimizes and minimizes with the Space Categories load variance of electric taxi to regional distribution network;

Orderly space-time unite charging strategy comprises the optimization aim of orderly time charging strategy and ordered space charging strategy.

2. according to the electric taxi dispatching method described in claim 1, it is characterized in that, in steps A, gather that electric taxi and electrically-charging equipment data comprise electric taxi numbering data, the position data of electric taxi, the state-of-charge of electric taxi, electric taxi carrying destination, the running state data of electric taxi and the running state data of electrically-charging equipment, current charging vehicle state-of-charge, electrically-charging equipment charging are estimated excess time, wait charging vehicle information.

3. according to the electric taxi dispatching method described in claim 2, it is characterized in that, described predetermined time interval is every 15 minutes image data.

4. according to the electric taxi dispatching method described in claim 1, it is characterized in that, with orderly time charging strategy, ordered space charging strategy or orderly space-time unite charging strategy, electric taxi operation constraint and the constraint of electric taxi battery are comprised to the constraint that electric taxi charging is optimized scheduling in step B, wherein

Electric taxi runs constraint and comprises: electric taxi has fixing charging times, electric taxi within per time cycle, and when going back to station, it selects that charging station is in multiple charging station one, electric taxi has enough electricity after completing back the carrying task before standing and returns charging station;

The constraint of electric taxi battery comprises: the state-of-charge SOC of the charge power in electric taxi charging process between the charge power bound of electrically-charging equipment, in electric taxi operational process is thereon between lower limit.

5., according to the electric taxi dispatching method described in claim 1, it is characterized in that, in orderly time charging strategy,

The time utilization maximizing efficiency of charging station electrically-charging equipment is:

$F_{1,\mathrm{time}}=\min \underset{t=1}{\overset{T}{\mathrm{\&Sigma;}}}{(\underset{m=1}{\overset{M}{\mathrm{\&Sigma;}}}{x}_{\mathrm{mt}}{P}_m-\frac{1}{T}\underset{t=1}{\overset{T}{\mathrm{\&Sigma;}}}\underset{m=1}{\overset{M}{\mathrm{\&Sigma;}}}{x}_{\mathrm{mt}}{P}_m)}^2,$

Wherein, x _mtfor time-optimized decision variable, P _mfor the charge power of electric taxi m, M is the quantity of electric taxi, and T is total activation duration,

Electric taxi charging service minimal time turns to:

$F_{2,\mathrm{time}}=\underset{m=1}{\overset{M}{\mathrm{\&Sigma;}}}(T_{m,b}+T_{m,w}+T_{m,c}),$

Wherein, T _m,b, T _m,wand T _m,cbe respectively the in transit time of electric taxi m in charging service process, stand-by period and duration of charging,

The time domain load variance of electric taxi to regional distribution network is minimised as:

$F_{3,\mathrm{time}}=\min \underset{t=1}{\overset{T}{\mathrm{\&Sigma;}}}{(P_t-{\stackrel{\&OverBar;}{P}}_T)}^2,$

Wherein, P _tfor regional distribution network is in the burden with power of moment t, for the average load of regional distribution network in time domain.

6., according to the electric taxi dispatching method described in claim 1, it is characterized in that, in ordered space charging strategy,

The space efficiency utilization of charging station electrically-charging equipment is maximum to be turned to:

$F_{1,\mathrm{space}}=\min \underset{n=1}{\overset{M}{\mathrm{\&Sigma;}}}{(\underset{m=1}{\overset{M}{\mathrm{\&Sigma;}}}{x}_{\mathrm{mn}}{P}_m-\frac{C_n}{\underset{j=1}{\overset{N}{\mathrm{\&Sigma;}}}{C}_n}\underset{m=1}{\overset{M}{\mathrm{\&Sigma;}}}{x}_{\mathrm{mn}}{P}_m)}^2,$

Wherein, x _mnfor the decision variable of space optimization, P _mfor the charge power of electric taxi m, M is the quantity of electric taxi, and N is charging station quantity in region, C _nfor the electrically-charging equipment quantity in charging station n

Electric taxi charging displacement is minimised as:

$F_{2,\mathrm{space}}=\underset{i=1}{\overset{M}{\mathrm{\&Sigma;}}}{L}_{m,\mathrm{travel}},$

Wherein, L _{m, travel}for the displacement in the charging service process of electric taxi m,

The Space Categories load variance of electric taxi to regional distribution network is minimised as:

$F_{3,\mathrm{space}}=\min \underset{n_{\mathrm{bus}}=1}{\overset{N_{\mathrm{bus}}}{\mathrm{\&Sigma;}}}{(P_{n_{\mathrm{bus}}}-{\stackrel{\&OverBar;}{P}}_{N_{\mathrm{bus}}})}^2,$

Wherein, for regional distribution network is at n _busthe burden with power of node, for regional distribution network is in the average load of Space Categories.

7. according to the electric taxi dispatching method described in claim 1, it is characterized in that, in step B, adopt degree of membership by objective fuzzy for orderly time charging strategy, ordered space charging strategy or orderly space-time unite charging strategy, form fuzzy object,

${\mathrm{\&mu;}}_x\left(x\right)=\left\{\begin{array}{cc}0& f_i\left(x\right)\&le;c_{i\min }\\ \frac{f_i\left(x\right)-c_{i\min }}{c_{i\max }-c_{i\min }}& c_{i\min }<f_i\left(x\right)<c_{i\max }\\ 1& f_i\left(x\right)\&GreaterEqual;c_{i\max }\end{array}\right.,i=\mathrm{1,2,3},$

Wherein, f _ix () refers to i-th target of obfuscation; μ _ix () refers to target f _ithe degree of membership of (x); c _{i min}and c _{i max}feeling the pulse with the finger-tip mark f respectively _ithe boundary up and down of (x), c _{i min}refer to the optimal-adaptive angle value of single goal, c _{i max}refer to the initial value fitness value of corresponding target,

Afterwards, comprehensively single object optimization is formed to multiple degree of membership:

F＝max(μ ₁,μ ₂,μ ₃)。

8. according to the electric taxi dispatching method described in claim 7, it is characterized in that, after forming single object optimization, comprise further and use particle swarm optimization to obtain optimum results, comprising:

$v_{\mathrm{id}}^{k+1}=\mathrm{\&omega;}\left(k\right)v_{\mathrm{id}}^k+c_1{r}_1(p_{\mathrm{id}}-z_{\mathrm{id}}^k)+c_2{r}_2(p_{\mathrm{gd}}-z_{\mathrm{id}}^k),$

$z_{\mathrm{id}}^{k+1}=z_{\mathrm{id}}^k+v_{\mathrm{id}}^{k+1},$

$\mathrm{\&omega;}\left(k\right)={\mathrm{\&omega;}}_{\mathrm{start}}-({\mathrm{\&omega;}}_{\mathrm{start}}-{\mathrm{\&omega;}}_{\mathrm{end}}){\left(\frac{k}{T}\right)}^2,$

Wherein, represent particle position variable, represent particle rapidity variable, p _id, p _gdrepresent individual optimal solution and group optimal solution respectively, c ₁, c ₂for constant, r ₁, r ₂for random number, ω (k) is inertia weight, ω _startand ω _endbe respectively starting and ending weight, k and T is respectively the total algebraically of current iteration algebraic sum iteration.

9. an electric taxi dispatching device, comprises electric taxi monitor supervision platform, electrically-charging equipment monitor supervision platform and control center of charging in order, wherein,

Electric taxi monitor supervision platform, electrically-charging equipment monitor supervision platform are respectively used to interval to schedule and gather electric taxi and electrically-charging equipment data;

Orderly charging control center is used for being optimized scheduling with orderly time charging strategy, ordered space charging strategy or orderly space-time unite charging strategy to electric taxi charging, determines to charge in order scheduling strategy,

Wherein in order time charging strategy comprises the time utilization maximizing efficiency of charging station electrically-charging equipment, electric taxi charging service time minimum and the time domain load variance of electric taxi to regional distribution network and minimizes;

The space efficiency utilization that ordered space charging strategy comprises charging station electrically-charging equipment maximizes, electric taxi charging displacement minimizes and minimizes with the Space Categories load variance of electric taxi to regional distribution network;

Orderly space-time unite charging strategy comprises the optimization aim of orderly time charging strategy and ordered space charging strategy.

10. according to the electric taxi dispatching device described in claim 9, it is characterized in that, utilize Ethernet or communication network that the electric taxi collected and electrically-charging equipment data are transferred to control center of charging in order, and the orderly charging scheduling strategy utilizing communication network control center of charging in order to be determined is transferred to electric taxi user.