CN104680258A - Method and device for dispatching electric taxi - Google Patents
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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
Technical Field
The invention relates to the technical field of new energy, in particular to the technical field of urban electric vehicle charging management.
Background
With the development of the automobile industry technology and the improvement of the living standard of residents, the quantity of automobiles kept in China is rapidly increased. At the same time, however, worldwide energy shortage and environmental pollution problems are also increasing. Electric vehicles are a new generation of vehicles, and are widely concerned by governments of various countries due to the advantages of energy conservation, environmental protection and the like. The electric taxi is used as an exemplary application of an electric automobile, and already runs in cities such as Beijing and Shenzhen, and more electric taxis can replace fuel vehicles in the future.
However, due to the operating characteristics of the electric taxi, it is necessary to increase the operation time as much as possible, and under the current fast charging technical conditions, an electric taxi needs about two hours to complete charging from 0% to 100% of the State of Charge (SOC) with a charging rate of 0.5C. Under the condition of disordered charging, the electric taxi randomly selects the charging time, so that the charging load of the electric taxi is often unevenly distributed in time and space, and the charging congestion phenomenon occurs in part of time periods and part of charging stations. The manual service adopted at present is relatively passive and does not play a role in orderly scheduling.
And then, the charging station is used as a medium for energy exchange between the electric taxi and the power grid, and has great influence on the power grid and users of the electric taxi in operation and dispatching. The orderly operation of the charging station is the basis for realizing the orderly charging of the large-scale electric taxi. Moreover, orderly charging of the electric taxis in the charging station has important significance for improving the operating economy and the operating efficiency of the charging station.
The charging rule of the current charging station is shown in fig. 1, and an electric taxi selects a charging station nearby; after the vehicle enters the station, selecting an idle charging pile for charging; if no idle charging pile exists, the user can choose to wait continuously or choose other charging stations to charge. And when the vehicle finishes charging, leaving the charging station.
If a large-scale electric taxi enters a commercialized era, the unordered charging rule is continuously used, and the charging service cannot meet the charging requirement of the existing user. The unordered charging method can seriously affect the experience of electric taxi users and the operating efficiency of the charging station, and meanwhile threatens the stability and the safety of the power distribution network.
Disclosure of Invention
In view of the above, the present invention aims to overcome the defects in the prior art, and provide a method and a device for scheduling electric taxis, which utilize the obvious characteristic that electric taxis have mobility in time and space to orderly control electric taxis in time and space on the premise that electric taxis participate in scheduling.
In order to achieve the purpose, the invention adopts the following technical scheme.
An electric taxi dispatching method, comprising:
A. acquiring data of the electric taxi and the charging facility according to a preset time interval;
B. the electric taxi is optimally scheduled by an ordered time charging strategy, an ordered space charging strategy or an ordered space-time combined charging strategy, the ordered charging scheduling strategy is determined,
the ordered time charging strategy comprises the steps of maximizing the time utilization efficiency of charging facilities of the charging station, minimizing the charging service time of the electric taxis and minimizing the time category load variance of the electric taxis to a regional power distribution network;
the ordered space charging strategy comprises the steps of maximizing the space utilization efficiency of charging facilities of the charging station, minimizing the charging moving distance of the electric taxi and minimizing the space category load variance of the electric taxi to a regional power distribution network;
the ordered spatiotemporal joint charging strategy comprises optimization targets of an ordered time charging strategy and an ordered space charging strategy.
In the step A, the collected data of the electric taxi and the charging facility comprise electric taxi number data, electric taxi position data, electric taxi charge state, electric taxi passenger carrying destination, electric taxi running state data, charging facility running state data, current charging vehicle charge state, charging facility charging remaining time estimation and charging vehicle waiting information.
In particular, the predetermined time interval is data collected every 15 minutes.
In addition, the constraints of the step B for carrying out optimized scheduling on the charging of the electric taxi by the ordered time charging strategy, the ordered space charging strategy or the ordered space-time combined charging strategy comprise electric taxi running constraints and electric taxi battery constraints, wherein,
the electric taxi operation constraint comprises the following steps: the electric taxi has fixed charging times in each time period, the charging station is selected as one of the plurality of charging stations when the electric taxi returns to the station, and the electric taxi has enough electric quantity to return to the charging station after completing a passenger carrying task before returning to the station;
the electric taxi battery restraint comprises the following steps: the charging power of the electric taxi in the charging process is between the upper limit and the lower limit of the charging power of the charging facility, and the state of charge (SOC) of the electric taxi in the running process is between the upper limit and the lower limit.
In the ordered time charging strategy, the time utilization efficiency of the charging facility of the charging station is maximized as follows:
wherein x ismtFor time-optimized decision variables, PmThe charging power of the electric taxis M, the number of the electric taxis M and the total dispatching duration T,
the charging service time of the electric taxi is minimized as follows:
wherein, Tm,b、Tm,wAnd Tm,cRespectively representing the in-transit time, the waiting time and the charging time of the electric taxi m in the charging service process,
the time domain load variance of the electric taxi to the regional power distribution network is minimized as follows:
wherein, PtFor the active load of the regional distribution network at time t,the average load of the regional distribution network in the time domain is obtained.
In the ordered space charging strategy, the space utilization efficiency of the charging facility of the charging station is maximized as follows:
wherein x ismnDecision variables, P, for spatial optimizationmCharging power of M electric taxis, M is the number of electric taxis, N is the number of charging stations in the area, CnTo chargeThe number of charging facilities within the plant n,
the charging moving distance of the electric taxi is minimized as follows:
wherein L ism,travelFor the moving distance in the charging service process of the electric taxi m,
the space category load variance of the electric taxi to the regional power distribution network is minimized as follows:
wherein,for regional distribution networks in nbusThe active load of the node is the real load,the average load of the regional distribution network in the spatial domain is obtained.
In addition, in the step B, the target is fuzzified by adopting membership degrees for an ordered time charging strategy, an ordered space charging strategy or an ordered space-time combined charging strategy to form a fuzzy target,
wherein f isi(x) Refers to the ith target of fuzzification; mu.si(x) Is referred to as target fi(x) Degree of membership of; c. Ci minAnd ci maxRespectively refer to the target fi(x) Upper and lower limits of ci minRefers to the optimal fitness value of a single target, ci maxRefers to the initial fitness value of the corresponding target,
and then, comprehensively forming single-target optimization by the multiple membership degrees:
F＝max(μ1,μ2,μ3)。
after the single-target optimization is formed, further obtaining an optimization result by using a particle swarm method, wherein the method comprises the following steps:
wherein,the position of the particles is represented by a variable,representing the variation of particle velocity, pid、pgdRespectively representing an individual optimal solution and a population optimal solution, c1,c2Is a constant number r1,r2Is a random number, ω (k) is an inertial weight, ωstartAnd ωendRespectively, the initial and end weights, and k and T are respectively the current iteration algebra and the iteration total algebra.
An electric taxi dispatching device comprises an electric taxi monitoring platform, a charging facility monitoring platform and an ordered charging control center, wherein,
the electric taxi monitoring platform and the charging facility monitoring platform are respectively used for acquiring electric taxi and charging facility data according to a preset time interval;
the ordered charging control center is used for carrying out optimized scheduling on the charging of the electric taxi by an ordered time charging strategy, an ordered space charging strategy or an ordered space-time combined charging strategy, determining the ordered charging scheduling strategy,
the ordered time charging strategy comprises the steps of maximizing the time utilization efficiency of charging facilities of the charging station, minimizing the charging service time of the electric taxis and minimizing the time category load variance of the electric taxis to a regional power distribution network;
the ordered space charging strategy comprises the steps of maximizing the space utilization efficiency of charging facilities of the charging station, minimizing the charging moving distance of the electric taxi and minimizing the space category load variance of the electric taxi to a regional power distribution network;
the ordered spatiotemporal joint charging strategy comprises optimization targets of an ordered time charging strategy and an ordered space charging strategy.
The method comprises the steps of utilizing an Ethernet or a communication network to transmit collected electric taxi and charging facility data to an ordered charging control center, and utilizing the communication network to transmit an ordered charging scheduling strategy determined by the ordered charging control center to electric taxi users.
By adopting the method and the device for dispatching the electric taxi, the unbalance of the charging load of the charging station in time and space can be reduced, and the utilization rate of charging facilities in the charging station is improved.
In addition, by adopting the method and the device for dispatching the electric taxi, the charging waiting time of the electric taxi can be reduced, and the charging distance of the electric taxi can be shortened.
In addition, by adopting the electric taxi dispatching method and device disclosed by the invention, the influence of the charging station on the power distribution network system can be reduced, so that the stability and the safety of the power distribution network are improved.
Drawings
Fig. 1 is a schematic flow chart of disordered charging of an electric taxi in the prior art.
Fig. 2 is a structural diagram of an electric taxi dispatching apparatus according to an embodiment of the present invention.
Fig. 3 is a schematic flow chart of an electric taxi dispatching method in an embodiment of the invention.
Fig. 4 is a schematic diagram illustrating a comparison between a method for scheduling an electric taxi and a result of disordered charging of the electric taxi in the embodiment of the present invention.
Fig. 5 is a schematic diagram illustrating a comparison between a method for scheduling an electric taxi and a result of disordered charging of the electric taxi in the embodiment of the present invention.
Detailed Description
The present invention will be described in detail below with reference to the accompanying drawings.
Detailed exemplary embodiments are disclosed below. However, specific structural and functional details disclosed herein are merely for purposes of describing example embodiments.
It should be understood, however, that the intention is not to limit the invention to the particular exemplary embodiments disclosed, but to cover all modifications, equivalents, and alternatives falling within the scope of the disclosure. Like reference numerals refer to like elements throughout the description of the figures.
It will also be understood that the term "and/or" as used herein includes any and all combinations of one or more of the associated listed items. It will be further understood that when an element or unit is referred to as being "connected" or "coupled" to another element or unit, it can be directly connected or coupled to the other element or unit or intervening elements or units may also be present. Moreover, other words used to describe the relationship between components or elements should be understood in the same manner (e.g., "between" versus "directly between," "adjacent" versus "directly adjacent," etc.).
As shown in fig. 2, the electric taxi dispatching device of the present invention includes an electric taxi monitoring platform, a charging facility monitoring platform, and an ordered charging control center, wherein,
the electric taxi monitoring platform and the charging facility monitoring platform are respectively used for acquiring electric taxi and charging facility data according to a preset time interval;
the ordered charging control center is used for carrying out optimized scheduling on the charging of the electric taxi by an ordered time charging strategy, an ordered space charging strategy or an ordered space-time combined charging strategy, determining the ordered charging scheduling strategy,
the ordered time charging strategy comprises the steps of maximizing the time utilization efficiency of charging facilities of the charging station, minimizing the charging service time of the electric taxis and minimizing the time category load variance of the electric taxis to a regional power distribution network;
the ordered space charging strategy comprises the steps of maximizing the space utilization efficiency of charging facilities of the charging station, minimizing the charging moving distance of the electric taxi and minimizing the space category load variance of the electric taxi to a regional power distribution network;
the ordered spatiotemporal joint charging strategy comprises optimization targets of an ordered time charging strategy and an ordered space charging strategy.
As a specific embodiment of the present invention, the collected data of the electric taxi and the charging facility are transmitted to the ordered charging control center by using an ethernet or a communication network, and the ordered charging scheduling policy determined by the ordered charging control center is transmitted to the electric taxi user by using the communication network. For example, there are two data transmission modes, one is ethernet data transmission, and the other is communication through a 2G/3G network. The charging equipment monitoring platform, the electric taxi monitoring platform and the ordered charging control center are communicated with each other by utilizing the Ethernet inside the charging station, and current data of the charging equipment monitoring platform and the electric taxi monitoring platform are transmitted to the ordered charging control center at fixed time intervals. And obtaining an ordered charging scheduling strategy of the electric taxi by utilizing an ordered scheduling optimization method of the control center in the charging station ordered control center. In addition, in the communication between the electric taxi and the charging station, 2G/3G network transmission is utilized, on one hand, real-time running data of the electric taxi is transmitted to an electric taxi monitoring platform, and on the other hand, the ordered charging scheduling strategy obtained by the charging station control center is transmitted to a corresponding electric taxi user.
Correspondingly, the electric taxi dispatching method comprises the following steps:
A. acquiring data of the electric taxi and the charging facility according to a preset time interval;
B. the electric taxi is optimally scheduled by an ordered time charging strategy, an ordered space charging strategy or an ordered space-time combined charging strategy, the ordered charging scheduling strategy is determined,
the ordered time charging strategy comprises the steps of maximizing the time utilization efficiency of charging facilities of the charging station, minimizing the charging service time of the electric taxis and minimizing the time category load variance of the electric taxis to a regional power distribution network;
the ordered space charging strategy comprises the steps of maximizing the space utilization efficiency of charging facilities of the charging station, minimizing the charging moving distance of the electric taxi and minimizing the space category load variance of the electric taxi to a regional power distribution network;
the ordered spatiotemporal joint charging strategy comprises optimization targets of an ordered time charging strategy and an ordered space charging strategy.
Therefore, by adopting the electric taxi dispatching method and the electric taxi dispatching device, imbalance of charging load of the charging station in time and space can be reduced, and utilization rate of charging equipment in the charging station is improved.
In addition, by adopting the method and the device for dispatching the electric taxi, the charging waiting time of the electric taxi can be reduced, and the charging route of the electric taxi can be shortened.
In a specific embodiment, in step a, the collected data of the electric taxi and the charging facility includes number data of the electric taxi, a position of the electric taxi, a charge state of the electric taxi, a passenger carrying destination of the electric taxi, running state data of the charging facility, a current charge state of the charging vehicle, a charge remaining time estimation of the charging facility, and information of the waiting-to-charge vehicle.
In addition, the predetermined time interval for collecting data may be selected according to actual situations, for example, in one embodiment, the predetermined time interval is data collection every 15 minutes.
The technical solution of the present invention will be described below in different embodiments.
Firstly, introducing a scheduling strategy, wherein the scheduling strategy is closely related to an optimized target, and the scheduling strategy specifically comprises the following steps:
1. the time and space utilization rate of the charging facility of the charging station is improved.
Due to the operation characteristics of the electric taxi, the efficiency of the charging equipment is unbalanced in the time range, so that vehicles to be charged are intensively selected to be charged in a certain time period, the time utilization rate of the charging equipment is reduced, the charging pile is idle in partial time periods, and the charging queuing phenomenon in partial time periods is avoided. Similarly, the charging distribution is unbalanced in space, so that vehicles to be charged are intensively selected from one charging station for charging, the space-time utilization rate of charging equipment is reduced, and the overall development of the charging station is negatively affected.
From the perspective of a charging station operator, the charging taxis are distributed according to time and space with the aim of improving the time and space utilization rate of the charging facility, the time and space characteristics of the charging vehicles are averaged, the imbalance of the charging load of the charging station in time and space can be reduced, and the utilization rate of the charging equipment in the charging station is higher.
Wherein, T is 1, 2.. times.t; m ═ 1,2,. said, M; n is 1,2,. cndot.n;
in the formulas (1) and (2), M and N are the number of electric taxis and the number of electric taxi charging stations in the region respectively; t is the total scheduling duration; x is the number ofmtAnd xmnRespectively, are the decision variables for temporal optimization and spatial optimization. Furthermore, PmCharging power for electric taxi m, CnThe number of charging facilities for the charging station n.
2. The charging service time of the electric taxi user is minimized and the moving distance caused by the charging service is minimized.
The target 1 mainly aims at the angle of a charging station to analyze the uneven distribution of the charging load, and the target 2 is to analyze the uneven distribution of the charging load at the angle of an electric taxi user, and aims at minimizing the charging service time of the electric taxi user in the time range; in the space category, the moving distance of the electric taxi due to the charging service is minimized. Wherein the charging service time includes three parts of a time-in-transit from the passenger carrying destination to the charging station, a charging station waiting time, and a charging time, wherein the time-in-transit and the charging waiting time are both optimizable amounts. The spatial movement distance caused by the charging service refers to a distance of spatial movement caused by traveling to a charging station for charging between the last passenger and the next passenger when the electric taxi has a charging demand.
In the formula, Tm,b、Tm,w、Tm,cThe in-transit time, the waiting time and the charging time of the electric taxi m in the charging service process are respectively indicated. And L ism,travelThe spatial transfer distance of the electric taxi m in the charging service process is indicated.
3. Minimizing negative impact of electric taxi charging on regional distribution network
In the invention, for model simplification, the time and space influence of the electric taxi charging station on the regional power distribution network is evaluated by using the load variance indexes of the time and space of the regional power distribution network. The load variance index can effectively measure the fluctuation condition of the regional load, and the more severe the load fluctuation is, the larger the feeder loss and the more unstable the voltage of the regional power distribution network are. Therefore, by controlling the load variance, the adverse effect of the charging load of the electric taxi charging station can be well controlled, as shown in formulas (5) to (6).
In the formula, PtAndrespectively representing the active load and n of the regional distribution network at time tbusThe active load of the node is respectively the measurement of time and space; whileAndthe average load in the temporal and spatial domains is represented, respectively.
Therefore, in the embodiment of the present invention, in the ordered time charging policy, the time utilization efficiency of the charging facility of the charging station is maximized as follows:
the charging service time of the electric taxi is minimized as follows:
the time domain load variance of the electric taxi to the regional power distribution network is minimized as follows:
in addition, in the ordered space charging strategy, the space utilization efficiency of the charging facility of the charging station is maximized as follows:
the charging moving distance of the electric taxi is minimized as follows:
the space category load variance of the electric taxi to the regional power distribution network is minimized as follows:
in addition, in step B of the electric taxi scheduling method according to the specific embodiment of the present invention, the constraints of performing optimal scheduling on electric taxi charging by using the ordered time charging strategy, the ordered space charging strategy, or the ordered space-time combined charging strategy include electric taxi operation constraints and electric taxi battery constraints, where the electric taxi operation constraints include:
the electric taxi has a fixed charging time S within each time period T, i.e.
When the electric taxi returns to the station, the electric taxi selects the charging station as one of N charging stations, namely
The electric taxi has enough electric quantity to return to the charging station after completing the passenger carrying task before returning to the station, namely
Loperation≤DM；
Wherein L isoperationThe driving distance is the total driving distance between two times of charging of the electric taxi, and the DM is the driving distance of the electric taxi.
The electric taxi battery restraint comprises the following steps: the charging power of the electric taxi in the charging process is between the upper limit and the lower limit of the charging power of the charging facility, namely
Pc-min≤Pc≤Pc-max，Pc-minAnd Pc-maxRespectively a lower limit and an upper limit of the charging power,
the SOC of the electric taxi is between the upper limit and the lower limit during the running process, namely
SOCmin≤SOCmt≤SOCmax。
When a plurality of optimization targets coexist, the scheduling problem of the electric taxi is actually a multi-target optimization problem. Generally, a weight penalty function method or a fuzzy method is used to solve a similar problem. The weight penalty function method usually needs to subjectively set or obtain a proper weight coefficient through multiple tests, and the fuzzy rule fuzzifies the target by using the membership degree to form a fuzzy multi-target. Therefore, it is not necessary to set a weight coefficient, and objective solution is performed.
Therefore, in one embodiment of the present invention, the objective is fuzzified using membership to an ordered time charging strategy, an ordered space charging strategy, or an ordered spatio-temporal joint charging strategy to form a fuzzy objective,
wherein f isi(x) Refers to the ith target of fuzzification; mu.si(x) Is referred to as target fi(x) Degree of membership of; c. Ci minAnd ci maxRespectively refer to the target fi(x) Upper and lower limits of ci minRefers to the optimal fitness value of a single target, ci maxRefers to the initial fitness value of the corresponding target,
and then, comprehensively forming single-target optimization by the multiple membership degrees:
F＝max(μ1,μ2,μ3)。
after the single-target optimization is formed, the embodiment of the invention further comprises the step of obtaining an optimization result by using a particle swarm method, which is originally proposed by Kennedy and Eberhart in 1995, and has been widely adopted in optimization calculation in various fields due to the advantages of high search speed and strong search capability. Similarly, the particle swarm is also performed in the neighborhood of the previous generation optimal solution in the process of performing particle iterative search, and the problem of falling into the local optimal solution also exists. Therefore, the basic particle swarm method is improved in the solving process, on one hand, when the optimizing process falls into the local optimal solution, the forced jumping is carried out; on the other hand, the inertia weight of the algorithm is improved, as shown in equations (14) to (16), so that the optimization process is prevented from falling into a local optimal solution. The method comprises the following steps:
wherein,indicating the position of the particleThe variable quantity is set, and the variable quantity is set,representing the variation of particle velocity, pid、pgdRespectively representing an individual optimal solution and a population optimal solution, c1,c2Is a constant number r1,r2Is a random number, ω (k) is an inertial weight, ωstartAnd ωendRespectively, the initial and end weights, and k and T are respectively the current iteration algebra and the iteration total algebra.
Although the fuzzy method is used for constructing the single optimization target and the particle swarm optimization method is used for obtaining the optimal result, it should be understood by those skilled in the art that the electric taxi dispatching method is not limited to constructing the single target by using the fuzzy method, nor to solving by using the particle swarm optimization method. For example, the optimization result can be obtained by using methods such as classical linear programming and quadratic programming, and an artificial intelligence method, and the implementation of the technical scheme of the invention is not affected.
The technical effect of the present invention is explained below by using a more specific example, assuming that 8 charging stations are distributed in an area of 50km × 30km, and the number of charging facilities of each charging station is [1,2,2,1,1,2,3,1] respectively; the number of the electric taxis is 100, and the initial positions of the electric taxis are randomly distributed in the center of the area; the station return SOC of the electric taxi is in accordance with N (0.5,0.1) distribution.
Disordered charge mode of the prior art:
in the operation process of the electric taxi, the electric taxi is in an unordered charging state, namely a near charging mode, which represents the operation process of the electric taxi and the charging station under the condition of no interactive communication, and is shown in fig. 1. If the SOC of the electric taxi is lower than the set operation warning lower limit, selecting the nearest charging station for charging when the passenger carrying task is completed; and if the electric taxi finishes the passenger carrying process at a certain time and finds that the current residual electric quantity cannot complete the next passenger carrying task, selecting the nearest charging station for charging.
In addition, by adopting the electric taxi scheduling method and device, on the basis of bidirectional communication between the charging station and the electric taxi, the time utilization efficiency of the charging facility of the charging station is maximized, the charging service time of the electric taxi is minimized, and the time category load variance of the electric taxi to a regional power distribution network is minimized; the space utilization efficiency of charging facilities of the charging station is maximized, the charging moving distance of the electric taxis is minimized, and the space category load variance of the electric taxis on the regional power distribution network is minimized to serve as optimization targets, and orderly charging scheduling is carried out in the time, space and space-time combined category. The results of fig. 4 and 5 can be obtained. Fig. 4 is a comparison of charging loads of electric taxis in disorder and ordered time scheduling and space-time combined scheduling. As can be seen from fig. 4, in the electric taxi scheduling method of the present invention, compared with the space-time joint optimization scheduling strategy, the individual ordered time scheduling has a more obvious effect on the optimization control in the time domain. In addition, fig. 5 is a comparison between the unordered and ordered spatial scheduling of the electric taxi and the selection of the space-time joint scheduling charging station, and it can be known from fig. 5 that, in the electric taxi scheduling method of the present invention, the effect of the individual ordered spatial scheduling on the optimization control in the space category is more obvious compared with the space-time joint optimization scheduling strategy.
It should be noted that the above-mentioned embodiments are only preferred embodiments of the present invention, and should not be construed as limiting the scope of the present invention, and any minor changes and modifications to the present invention are within the scope of the present invention without departing from the spirit of the present invention.
Claims (10)
1. An electric taxi dispatching method, comprising:
A. acquiring data of the electric taxi and the charging facility according to a preset time interval;
B. the electric taxi is optimally scheduled by an ordered time charging strategy, an ordered space charging strategy or an ordered space-time combined charging strategy, the ordered charging scheduling strategy is determined,
the ordered time charging strategy comprises the steps of maximizing the time utilization efficiency of charging facilities of the charging station, minimizing the charging service time of the electric taxis and minimizing the time category load variance of the electric taxis to a regional power distribution network;
the ordered space charging strategy comprises the steps of maximizing the space utilization efficiency of charging facilities of the charging station, minimizing the charging moving distance of the electric taxi and minimizing the space category load variance of the electric taxi to a regional power distribution network;
the ordered spatiotemporal joint charging strategy comprises optimization targets of an ordered time charging strategy and an ordered space charging strategy.
2. The method for dispatching an electric taxi according to claim 1, wherein in the step a, the collected data of the electric taxi and the charging facility comprise data of a number of the electric taxi, position data of the electric taxi, a charge state of the electric taxi, a passenger carrying destination of the electric taxi, running state data of the charging facility, a current charge state of the charging vehicle, an estimation of charging remaining time of the charging facility, and information of waiting for the charging vehicle.
3. The method of claim 2, wherein the predetermined time interval is every 15 minutes.
4. The electric taxi dispatching method of claim 1, wherein the constraints on optimal dispatching of electric taxi charging in the ordered time charging strategy, the ordered space charging strategy or the ordered space-time combined charging strategy in step B include electric taxi operation constraints and electric taxi battery constraints, wherein,
the electric taxi operation constraint comprises the following steps: the electric taxi has fixed charging times in each time period, the charging station is selected as one of the plurality of charging stations when the electric taxi returns to the station, and the electric taxi has enough electric quantity to return to the charging station after completing a passenger carrying task before returning to the station;
the electric taxi battery restraint comprises the following steps: the charging power of the electric taxi in the charging process is between the upper limit and the lower limit of the charging power of the charging facility, and the state of charge (SOC) of the electric taxi in the running process is between the upper limit and the lower limit.
5. The method of claim 1, wherein in the ordered time charging strategy,
the time utilization efficiency of the charging facility of the charging station is maximized as follows:
wherein x ismtFor time-optimized decision variables, PmThe charging power of the electric taxis M, the number of the electric taxis M and the total dispatching duration T,
the charging service time of the electric taxi is minimized as follows:
wherein, Tm,b、Tm,wAnd Tm,cRespectively representing the in-transit time, the waiting time and the charging time of the electric taxi m in the charging service process,
the time domain load variance of the electric taxi to the regional power distribution network is minimized as follows:
wherein, PtFor the active load of the regional distribution network at time t,the average load of the regional distribution network in the time domain is obtained.
6. The method of claim 1, wherein in the ordered space charging strategy,
the space utilization efficiency of the charging facility of the charging station is maximized as follows:
wherein x ismnDecision variables, P, for spatial optimizationmCharging power of M electric taxis, M is the number of electric taxis, N is the number of charging stations in the area, CnFor the number of charging facilities in a charging station n
The charging moving distance of the electric taxi is minimized as follows:
wherein L ism,travelFor the moving distance in the charging service process of the electric taxi m,
the space category load variance of the electric taxi to the regional power distribution network is minimized as follows:
wherein,for regional distribution networks in nbusThe active load of the node is the real load,the average load of the regional distribution network in the spatial domain is obtained.
7. The method of claim 1, wherein in step B, the objective is fuzzified by membership to an ordered time charging strategy, an ordered space charging strategy or an ordered space-time combined charging strategy to form a fuzzy objective,
wherein f isi(x) Refers to the ith target of fuzzification; mu.si(x) Is referred to as target fi(x) Degree of membership of; c. Ci minAnd ci maxRespectively refer to the target fi(x) Upper and lower limits of ci minRefers to the optimal fitness value of a single target, ci maxRefers to the initial fitness value of the corresponding target,
and then, comprehensively forming single-target optimization by the multiple membership degrees:
F＝max(μ1,μ2,μ3)。
8. the method for dispatching electric taxis according to claim 7, wherein after the forming of the single-target optimization, further comprising obtaining the optimization result by using a particle swarm method, the method comprises:
wherein,the position of the particles is represented by a variable,representing the variation of particle velocity, pid、pgdRespectively representIndividual optimal solution and population optimal solution, c1,c2Is a constant number r1,r2Is a random number, ω (k) is an inertial weight, ωstartAnd ωendRespectively, the initial and end weights, and k and T are respectively the current iteration algebra and the iteration total algebra.
9. An electric taxi dispatching device comprises an electric taxi monitoring platform, a charging facility monitoring platform and an ordered charging control center, wherein,
the electric taxi monitoring platform and the charging facility monitoring platform are respectively used for acquiring electric taxi and charging facility data according to a preset time interval;
the ordered charging control center is used for carrying out optimized scheduling on the charging of the electric taxi by an ordered time charging strategy, an ordered space charging strategy or an ordered space-time combined charging strategy, determining the ordered charging scheduling strategy,
the ordered time charging strategy comprises the steps of maximizing the time utilization efficiency of charging facilities of the charging station, minimizing the charging service time of the electric taxis and minimizing the time category load variance of the electric taxis to a regional power distribution network;
the ordered space charging strategy comprises the steps of maximizing the space utilization efficiency of charging facilities of the charging station, minimizing the charging moving distance of the electric taxi and minimizing the space category load variance of the electric taxi to a regional power distribution network;
the ordered spatiotemporal joint charging strategy comprises optimization targets of an ordered time charging strategy and an ordered space charging strategy.
10. The electric taxi dispatching device according to claim 9, wherein the collected electric taxi and charging facility data are transmitted to the ordered charging control center through an ethernet or a communication network, and the ordered charging dispatching strategy determined by the ordered charging control center is transmitted to the electric taxi users through the communication network.
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