CN113222241B - Taxi quick-charging station planning method considering charging service guide and customer requirements - Google Patents

Taxi quick-charging station planning method considering charging service guide and customer requirements Download PDF

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CN113222241B
CN113222241B CN202110502052.9A CN202110502052A CN113222241B CN 113222241 B CN113222241 B CN 113222241B CN 202110502052 A CN202110502052 A CN 202110502052A CN 113222241 B CN113222241 B CN 113222241B
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刘洪�
秦婷
徐正阳
葛少云
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Abstract

A taxi fast charging station planning method considering charging service guide and customer requirements comprises the following steps: establishing a taxi fast charging station planning model considering charging service charge guidance and a client demand position: the method comprises the following steps that a charging behavior selection model, a planning layer mathematical model, an operation layer mathematical model and a fast charging station planning objective function of an electric taxi user are adopted; determining constraint conditions which need to be met by the taxi quick charging station planning model, wherein the constraint conditions comprise: the method comprises the following steps of (1) distance constraint of a charging station, access point capacity constraint of the charging station, upper and lower limit constraint of node voltage amplitude and maximum current constraint of a feeder line; and solving a taxi fast charging station planning model considering charging service charge guidance and the position required by the customer. The method and the system provided by the invention have the advantages that the actual distribution condition of the taxis to be charged after the operation of the quick charging station is simulated, the charging service cost in the station is adjusted, the charging behavior of the taxis is guided, the data information is corrected and perfected, the early-stage planning cost and the later-stage operation cost are considered in a unified way, and the potential supplementary cost in the later stage is reduced.

Description

Taxi quick-charging station planning method considering charging service guide and customer requirements
Technical Field
The invention relates to a planning method for a taxi quick charging station. In particular to a taxi quick charging station planning method considering charging service guidance and customer requirements, which meets the charging requirements and positions of customers and simultaneously considers charging service cost adjustment for charging guidance under the background that a large number of new energy vehicles enter a power distribution network system and a traffic network system.
Background
The quick charging station is an important part of public charging infrastructure, a balance is sought among reducing the investment construction and maintenance cost of the charging facility, providing convenient and high-quality charging service for electric vehicle users and reducing the influence of the electric vehicles on a power distribution network system through reasonable layout planning, mutual benefits and win-win among the electric vehicle users, charging facility operators and power grid companies are achieved, and further the development of the whole new energy vehicle industry is promoted.
At present, in the research of the design problem of the planning scheme of the quick charging station, the aspects of establishing a target function model in the direction of an innovation target and at multiple angles, researching different algorithms, realizing efficient and quick calculation and the like are mainly considered. A planning scheme for a quick charging station mainly comprises the three aspects of site selection and volume fixing, function model construction and problem algorithm optimization. In the aspect of locating and sizing, the number of charging stations is generally determined by predicting the charging demand in a planned area. And then, under the condition of randomly generating the station address, searching and determining the optimal station address in a large range through indexes such as station service radius, node interception flow, investment construction cost and the like. On the basis of determining the station address, the size of the capacity of the charging station is determined based on the queuing theory, the road intersection flow algorithm, the probability prediction method and other methods by mainly considering the factors such as the effective utilization rate of the charging facility, the investment construction cost, the service efficiency in the station and the like. In the aspect of function model construction, the construction of a multi-objective function model is mainly focused on. And (3) considering the construction of an economic objective function of one or more of electric vehicle users, charging facility operators and power grid companies, and solving the optimal value. In the solution algorithm optimization, uncertainty of space EV quantity prediction, uncertainty of EV user charging behavior and uncertainty of DG output are mainly considered, a processing method mainly comprises a scene analysis method and an opportunity constraint rule, and the uncertainty is converted into a deterministic variable for analysis. However, in the existing planning scheme, the user group considers more all electric automobiles, and the research on electric taxi user objects with public properties is less; meanwhile, the charging behavior selection tendency of the electric taxi is to go forward to a high-density crowd area and a high-load node, but the condition of unbalanced area load is aggravated only by considering the station building of the charging demand of taxi users; the electric taxi is used as a functional vehicle, and the client demand position around the station after charging is taken into consideration when the charging station is selected for charging. By researching and analyzing the series of problems and reasonably arranging, the effectiveness, the economy and the reliability of the planning scheme are improved.
Disclosure of Invention
The invention aims to solve the technical problem of providing a taxi quick charging station planning method which can uniformly consider the early planning cost and the later operation cost and reduce the potential later supplementary cost by considering charging service guide and customer requirements.
The technical scheme adopted by the invention is as follows: a taxi fast charging station planning method considering charging service guide and customer requirements comprises the following steps:
1) establishing a taxi fast charging station planning model considering charging service charge guidance and a client demand position, comprising the following steps of respectively establishing:
(1.1) selecting a model for the charging behavior of the electric taxi user;
(1.2) planning a layer mathematical model;
(1.3) running a layer mathematical model;
(1.4) planning an objective function of the quick charging station;
2) determining constraint conditions which need to be met by the taxi quick charging station planning model, wherein the constraint conditions comprise: the method comprises the following steps of (1) distance constraint of a charging station, access point capacity constraint of the charging station, upper and lower limit constraint of node voltage amplitude and maximum current constraint of a feeder line;
3) and solving a taxi fast charging station planning model considering charging service charge guidance and the position required by the customer.
According to the taxi fast charging station planning method considering the charging service guide and the customer requirements, the charging service cost in the station is adjusted by simulating the actual distribution condition of the taxis to be charged after the fast charging station operates, the charging behavior of the taxis is guided, the data information is corrected and perfected, the early-stage planning cost and the later-stage operation cost are considered in a unified manner, and the potential supplementary cost in the later stage is reduced; meanwhile, the consideration of the time consumption situation of the charging station and the position required by the next riding customer before the taxi is charged is increased, and a planning scheme which gives consideration to the economical efficiency and the reliability of the fast charging station operator (power grid side) and the electric taxi user is provided. On one hand, the electric taxi with public property is taken as a research object, and the research is less in the existing related research; on the other hand, from the perspective of 'resource balancing', the behavior selection of the electric taxi user is guided by formulating a charging service fee rule of the charging station.
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Fig. 1 is a flow chart for solving a taxi fast charge station planning model that considers charging service fee guidance and customer demand location.
Detailed Description
The taxi quick charging station planning method considering the charging service guide and the customer demand according to the present invention will be described in detail with reference to the embodiments and the accompanying drawings.
The reasonable planning and layout of the quick charging station needs to consider a plurality of factors such as local policy, environment, distribution network system bearing capacity and economic development level. The method mainly comprises the following three aspects: the number of the charging stations needing to be built in the planning area is determined, and the station addresses and the capacity of the charging stations are determined. The number value of the charger and the selection of the station to be selected can be obtained according to known data, the capacity of the charging station is influenced by the charging requirement of the station, and the behavior of the electric taxi can be guided by adjusting the service cost in the station, so that the actual charging requirement of the station is adjusted. Therefore, in order to meet the overall demand, station site optimization and station site capacity refinement in the planning area and provide a high-quality and high-efficiency planning scheme, an embedded optimization model of the taxi fast charging station considering charging service charge guidance and the customer demand position needs to be constructed. The number of the charging stations and the station addresses of the charging stations are planning layers, the charging behavior selection of the electric taxi in a centralized charging time period is simulated, the actual distribution situation of the charging demand is determined, and the station capacity is optimized to be an operation layer (an embedded layer). Wherein, the planning layer is divided into two parts: firstly, providing initial planning schemes of different station addresses and capacities for an operation layer, secondly, calculating and comparing the cost of target functions of different schemes, and determining an optimal site selection and volume fixing scheme. On one hand, the total N value range of the charging stations is obtained according to the total charging demand in the area, on the basis of giving a certain N value, the charging stations are randomly selected from the sites to be selected, and an initial site and capacity scheme is given after calculation; and on the other hand, according to the feedback information of the operation layer, obtaining the objective function value of the scheme after optimizing the capacity, and comparing the objective function value with other schemes to obtain the optimal planning scheme. The run level considers the boot and optimizes the amount of content in each station. Simulating the actual number of charging vehicles arriving at each station in a centralized charging time period in the operation process according to the initial station address capacity information provided by the planning layer, adjusting and optimizing the existing station service cost and capacity configuration, performing multiple loop iterations until the actual number of charging vehicles arriving at each station in the operation process is stable, outputting the information of the actual number of charging vehicles arriving at each station, the service cost of each station, the optimal configuration capacity and the like, and feeding back the information to the planning layer.
A taxi fast charging station planning method considering charging service guidance and customer requirements is characterized by comprising the following steps:
1) establishing a taxi fast charging station planning model considering charging service charge guidance and a client demand position, comprising the following steps of respectively establishing:
(1.1) selecting a model for the charging behavior of the electric taxi user; the electric taxi user charging behavior selection model comprises the following steps: the charging station selection probability model of a single electric taxi and the charging station selection probability model of multi-car navigation; wherein the content of the first and second substances,
(1.1.1) when the electric taxi user generates a charging demand, selecting a charging station within a charging radius meeting the residual electric quantity for charging. The charging stations are scattered points which are irregularly arranged, and when an electric taxi user selects, the selection model is also a scattered selection model. When the electric taxi decides to go to the charging station for charging, the distance between the current position of the taxi and the position of the charging station, the charging waiting time after the taxi arrives at the station, the distance from the next passenger to the boarding point before the charging is finished and the charge service cost in the station are considered. In the discrete selection model, the probability of selecting a station in a mode of maximum utility is higher for a selector. According to the maximum utility principle, the charging station selection probability model of a single electric taxi is as follows:
Figure BDA0003056787070000031
in the formula, PikoRepresenting that the starting point of a taxi is a traffic node i, and selecting the probability of going to a charging station k for charging; m is an optional charging station set, and k belongs to M; u shapeikRepresenting a utility function of the electric vehicle at the traffic node i for selecting the charging station k; t isidkCalculating the time for the owner to arrive at the charging station k from the traffic node i by the traveling time of the shortest path; t isiqkWaiting for the time after the owner arrives at the charging station k; t ismkThe time from the time when the owner finishes charging to the next passenger getting-on point is represented by the expected time when the owner starts to search the next passenger getting-on traffic node by a charging station k; pskCharging service consumption is carried out on the charge station k for the vehicle owner; delta is the unit time cost in the driving process, alpha, beta>0 represents the sensitive weight value of the influence degree of the time factor and the economic factor in the model on the decision;
(1.1.2) a plurality of taxis to be charged exist on one traffic node at the same time, each taxi decides to be charged, and the weight values of time and economy are different, namely alpha and beta are different. When a plurality of vehicles to be charged are simultaneously on one traffic node i, the selection probability of the vehicles for the charging station k is variable and uncertain. In order to solve the uncertainty problem, multi-scenario analysis is introduced, and under different scenarios, the probability model selected by the multi-vehicle navigation charging station is as follows:
Figure BDA0003056787070000032
in the formula, PikRepresenting the probability that the starting point of the taxi in each scene is a traffic node i and selecting a charging station k to carry out charging; prIs the probability of occurrence of scene r; r is the set of all scenes, R is one of the scenes, and R belongs to R; alpha is alpharAnd betarAnd representing the weight values corresponding to the time factor and the economic factor in the model under the scene r.
(1.2) planning a layer mathematical model; the mathematical model of the planning layer is as follows:
Figure BDA0003056787070000041
in the formula, QtaxiThe total number of the electric taxis in the planning area is; wtaxiThe rated capacity of the battery of the electric taxi; p is the rated charging power of a charger in the charging station; t iscIs a charging period; c. CminAnd cmaxThe minimum value and the maximum value of the number of chargers corresponding to the scale of the electric taxi charging station respectively; n represents the total number of charging stations in the planning area; n is a radical ofminAnd NmaxThe minimum value and the maximum value of the total number of the charging stations in the planning area.
(1.3) running a layer mathematical model; the running layer mathematical model comprises:
(1.3.1) Charge service fee guide model in electric taxi charging station
When the electric taxi enters the charging station for charging, the charging electricity price and the field service cost need to be paid, and the sum of the charging electricity price and the field service cost is represented by the charging service cost. The charging service cost of the station affects the selection of the user on the charging station, the larger the charging service cost is, the smaller the probability of selecting the station by the taxi is, and the larger the probability of selecting the station by the taxi is, so that the charging guidance of the electric taxi can be realized by adjusting the charging service cost of the charging station.
The charging service cost comprises charging electricity price and site service cost, and is guided by formulating graded charging service cost, and the specific expression is as follows:
Figure BDA0003056787070000042
in the formula, PskThe unit is element/degree for charging service cost; psk1For charging electricity prices, a general industrial and commercial electricity price standard, i.e., 0.695 yuan/degree, is implemented; psk2Is a field clothesThe service cost is that according to the current charging station charging standard in Beijing city, the upper limit standard of site service cost is 15% of the price of 92# gasoline per liter on the day; in order to avoid the resource waste caused by the unbalance of the charging vehicles arriving at the charging station, the charging station is charged by 0,
Figure BDA0003056787070000043
QtaxiThe charging service charge of the fast charging station is graded for an interval boundary, wherein,
Figure BDA0003056787070000044
for a charging period of time TcNumber of electric taxis arriving at charging station k, QtaxiThe total number of the electric taxis in the planning area.
(1.3.2) calculation of charging station capacity:
the number of the electric taxis arriving at the charging station in unit time accords with the Poisson distribution of the parameter lambda, the service time is normally distributed G, and the expectation is EtStandard deviation of Vt(ii) a Under the condition that the service time parameter is certain, the taxi enters the average waiting time of charging of a charging station
Figure BDA0003056787070000045
The expression is as follows:
Figure BDA0003056787070000046
charging device idle rate U:
Figure BDA0003056787070000051
Figure BDA0003056787070000052
in the formula (I), the compound is shown in the specification,
Figure BDA0003056787070000053
c is the number of chargers, mu is the average service rate of the chargers,
Figure BDA0003056787070000054
for a charging period of time TcThe number of electric taxis arriving at the charging station k; j represents the number of cycles;
the charging station total cost f (c) of the charging station in constant volume has the service cost of the charging station and the charging waiting cost of taxi users, and the optimal number of chargers in the charging station is determined by taking the minimum total cost in constant volume as a target:
Figure BDA0003056787070000055
Figure BDA0003056787070000056
cmin≤c≤cm
wherein c is the number of chargers, cmin、cmaxThe minimum value and the maximum value of the number of chargers, S, corresponding to the scale of the electric taxi charging station respectivelyeFor each unit idle cost of the charger, SwThe cost per unit time in order for a charging vehicle to arrive at the station in line waiting,
Figure BDA0003056787070000057
indicating the average waiting time period, T, of the charging vehiclemaxRepresenting the maximum waiting period that the vehicle can tolerate.
(1.4) planning an objective function of the quick charging station;
the planning objective function of the quick charging station is constructed, the economy of an operator (power grid side) of the quick charging station and the economy of an electric taxi user are considered, and the planning scheme with the minimum comprehensive cost of the charging station is solved. The main contents are the charging station construction cost, the maintenance cost, the annual cost of loss and the charging behavior cost of taxi users. The quick charging station planning objective function takes the minimum comprehensive cost of the charging station as an objective function, and is expressed as follows:
min F＝Cinv+Cm+Closs+Cuser (9)
in the formula, CinvAnnual construction costs for fast charging stations, CmFor maintenance annual costs of quick charging stations, ClossFor annual costs of charge loss at a quick charging station, CuserAnnual cost of charging behavior for taxi users; wherein the content of the first and second substances,
the calculation expression of the construction year cost of the quick charging station is as follows:
Figure BDA0003056787070000058
in the formula, CinvThe construction annual cost of the fast charging station is solved, M is the set of the fast charging stations of the electric taxis in the region,
Figure BDA0003056787070000059
for charging station k with number of motors, deltacdIs the price of a charger, skFor the capital cost of charging station k, r0In order to build the discount rate, z is the operating life of the charger;
the quick charging station maintenance annual cost calculation expression is as follows:
Cm＝ηmCinv (11)
in the formula, CmFor the maintenance annual cost of the rapid charging station, according to the proportion eta of the construction annual cost of the rapid charging stationmPerforming conversion;
the expression of the calculation of the annual loss cost of the quick charging station is as follows:
Figure BDA00030567870700000510
in the formula, ClossThe annual expense of the fast charging station, k is the fast charging station, M is the set of the fast charging stations of the electric taxis in the region,
Figure BDA0003056787070000061
the number of motors in the charging station k is,
Figure BDA0003056787070000062
and
Figure BDA0003056787070000063
respectively converting the line loss on the corresponding line of a single charger and the charging loss in the single charger, wherein gamma is the synchronous rate of the multiple chargers working simultaneously, TCIs a charging period;
the taxi user charging behavior annual cost calculation expression is as follows:
Figure BDA0003056787070000064
Figure BDA0003056787070000065
Figure BDA0003056787070000066
Figure BDA0003056787070000067
in the formula, CuserAnnual cost of charging taxi users, CusertTime cost in cost of charging behaviour for taxi users, CuserpCharging cost in the cost of charging behavior for taxi users, delta is the unit time cost of the taxi users, k is a quick charging station, M is a set of electric taxi quick charging stations, i is a traffic node, A is a set of traffic nodes in an area, and V is the total time of the taxi usersiNumber of electric taxis to be charged, P, for traffic node iikTo select the probability, t, of going from the traffic node i to the fast charge station kidkFor the time to go from the traffic node i to the fast charge station k,
Figure BDA0003056787070000068
the average waiting time T of the electric taxi in the fast charging station kmkThe expected time of the next passenger getting on the bus is represented by the time when the owner finishes charging and then starts from a charging station k to search the next passenger getting on the bus traffic node, WevikThe charging capacity, P, required for an electric taxi departing from a traffic node i to a fast charging station kskFor the service charge of the fast charging station k,
Figure BDA0003056787070000069
annual cost of charging behavior, P, for electric taxi users in scene rrThe probability of occurrence of a scene R, R is the set of all scenes, R is one of the scenes, R ∈ R.
2) Determining constraint conditions which need to be met by the taxi quick charging station planning model, wherein the constraint conditions comprise: the method comprises the following steps of (1) distance constraint of a charging station, access point capacity constraint of the charging station, upper and lower limit constraint of node voltage amplitude and maximum current constraint of a feeder line; wherein, the said:
(2.1) charging station distance constraint:
Figure BDA00030567870700000610
in the formula, Dkk′Represents the distance between two charging stations; xi represents a tortuosity coefficient of a road in a planning area;
Figure BDA00030567870700000611
is the linear distance between the two stations;
(2.2) charging station access point capacity constraint:
Pkl≤Plmax (15)
in the formula, PklRepresenting the charging power accessed at a load point l of the power distribution network; plmaxRepresenting the maximum value of the charging power which is allowed to be accessed to the load point l of the distribution network;
(2.3) upper and lower limit constraint of node voltage amplitude:
Vl min≤Vl≤Vl max (16)
in the formula, VlThe voltage amplitude of a load point l of the power distribution network is obtained; vl min，Vl maxRespectively representing the upper limit and the lower limit of the voltage amplitude of the load point l of the power distribution network;
(2.4) maximum feeder current constraint:
|Il|≤Ilmax,l∈L (17)
in the formula IlAnd IlmaxRespectively indicating the current at the load point l of the power distribution network and the maximum current allowed to flow; and L is a distribution network load point set.
3) And solving a taxi fast charging station planning model considering charging service charge guidance and the position required by the customer.
The model for solving and considering the taxi fast charging station planning model of the charging service charge guide and the customer demand position, as shown in fig. 1, includes:
(3.1) setting initial values of all parameters in a taxi fast charging station planning model;
(3.2) determining the range of the total number N of the charging stations in the planning area according to the initial value of each parameter in the mathematical model of the planning layer (N)min≤N≤Nmax)；
(3.3) setting an initial value N of the total number N of the charging stations in the planning area0＝NminSelecting from D addresses to be selected
Figure BDA0003056787070000071
An address scheme;
(3.4) is
Figure BDA0003056787070000072
Randomly ordering the address schemes, wherein Pro represents the serial number of each scheme; setting an initial value Pro-1;
(3.5) the charging demand in the whole planning region is averagely distributed to all stations in the Pro scheme, and the number of initial chargers, the service cost and the average waiting time of charging vehicles of all stations are calculated according to the running layer mathematical model and are used as initial information;
(3.6) simulating operation to obtain the actual number of the electric taxis of each charging station, adjusting the service cost of each charging station, and calculating the optimal number of chargers and the average waiting time of the optimal charging vehicles;
(3.7) comparing the optimal number of chargers and the average waiting time of the optimal charging vehicles in each station with the initial information, if the optimal number of chargers and the average waiting time of the optimal charging vehicles are inconsistent with the initial information, replacing the initial information with the optimal information, and returning to the step (3.6); if the two are consistent, the next step is carried out;
(3.8) calculating a planning objective function of the fast charging station, if the calculation result is superior to the set initial value, comparing the result with the constraint conditions, and if all the constraint conditions are met, taking the current calculation result as the initial value of the planning objective function of the fast charging station, and entering the step (3.9); otherwise, directly entering the step (3.9);
(3.9) Pro +1, and returning to the step (3.5) until reaching the step
Figure BDA0003056787070000073
Entering the next step;
(3.10)N0＝N0+1, returning to the step (3.3), and circularly calculating until N0>NmaxAnd solving the optimal planning scheme.

Claims (2)

1. A taxi fast charging station planning method considering charging service guidance and customer requirements is characterized by comprising the following steps:
1) establishing a taxi fast charging station planning model considering charging service charge guidance and a client demand position, comprising the following steps of respectively establishing:
(1.1) selecting a model for the charging behavior of the electric taxi user; the method comprises the following steps: the charging station selection probability model of a single electric taxi and the charging station selection probability model of multi-car navigation; wherein the content of the first and second substances,
(1.1.1) according to the maximum utility principle, the probability model for selecting the charging station of the single electric taxi is as follows:
Figure FDA0003498200690000011
in the formula, PikoRepresenting that the starting point of a taxi is a traffic node i, and selecting the probability of going to a charging station k for charging; m is an optional charging station set, and k belongs to M; u shapeikRepresenting a utility function of the electric vehicle at the traffic node i for selecting the charging station k; t isidkCalculating the time for the owner to arrive at the charging station k from the traffic node i by the traveling time of the shortest path; t isiqkWaiting for the time after the owner arrives at the charging station k; t ismkThe time from the time when the owner finishes charging to the next passenger getting-on point is represented by the expected time when the owner starts to search the next passenger getting-on traffic node by a charging station k; pskCharging service consumption is carried out on the charge station k for the vehicle owner; delta is the unit time cost in the driving process, alpha, beta>0 represents the sensitive weight value of the influence degree of the time factor and the economic factor in the model on the decision;
(1.1.2) in order to solve the uncertainty problem, multi-scenario analysis is introduced, and under different scenarios, the probability model selected by the multi-vehicle navigation charging station is as follows:
Figure FDA0003498200690000012
in the formula, PikRepresenting the probability that the starting point of the taxi in each scene is a traffic node i and selecting a charging station k to carry out charging; prIs the probability of occurrence of scene r; r is the set of all scenes, R is one of the scenes, and R belongs to R; alpha is alpharAnd betarRepresenting the weight values corresponding to the time factors and the economic factors in the model under the scene r;
(1.2) planning a layer mathematical model; the mathematical model of the planning layer is as follows:
Figure FDA0003498200690000013
in the formula, QtaxiThe total number of the electric taxis in the planning area is; wtaxiThe rated capacity of the battery of the electric taxi; p is the rated charging of the charger in the charging stationPower; t iscIs a charging period; c. CminAnd cmaxThe minimum value and the maximum value of the number of chargers corresponding to the scale of the electric taxi charging station respectively; n represents the total number of charging stations in the planning area; n is a radical ofminAnd NmaxThe minimum value and the maximum value of the total number of the charging stations in the planning area;
(1.3) running a layer mathematical model; the running layer mathematical model comprises:
(1.3.1) Charge service fee guide model in electric taxi charging station
The charging service cost comprises charging electricity price and site service cost, and is guided by formulating graded charging service cost, and the specific expression is as follows:
Figure FDA0003498200690000021
in the formula, PskThe unit is element/degree for charging service cost; psk1For charging electricity prices, a general industrial and commercial electricity price standard, i.e., 0.695 yuan/degree, is implemented; psk2For site service cost, according to the current charging station charging standard in Beijing, the upper limit standard of the site service cost is 15 percent of the price per liter of No. 92 gasoline on the day; in order to avoid the resource waste caused by the unbalance of the charging vehicles arriving at the charging station, the charging station is charged by 0,
Figure FDA0003498200690000022
QtaxiThe charging service charge of the fast charging station is graded for an interval boundary, wherein,
Figure FDA0003498200690000023
for a charging period of time TcNumber of electric taxis arriving at charging station k, QtaxiThe total number of the electric taxis in the planning area is;
(1.3.2) calculation of charging station capacity:
to a charging station in a unit of timeThe number of the electric taxis accords with the Poisson distribution of the parameter lambda, the service time is normally distributed G, and the expectation is EtStandard deviation of Vt(ii) a Under the condition that the service time parameter is certain, the taxi enters the average waiting time of charging of a charging station
Figure FDA0003498200690000024
The expression is as follows:
Figure FDA0003498200690000025
charging device idle rate U:
Figure FDA0003498200690000026
Figure FDA0003498200690000027
in the formula (I), the compound is shown in the specification,
Figure FDA0003498200690000028
c is the number of chargers, mu is the average service rate of the chargers,
Figure FDA0003498200690000029
for a charging period of time TcThe number of electric taxis arriving at the charging station k; j represents the number of cycles;
the charging station total cost f (c) of the charging station in constant volume has the service cost of the charging station and the charging waiting cost of taxi users, and the optimal number of chargers in the charging station is determined by taking the minimum total cost in constant volume as a target:
Figure FDA0003498200690000031
Figure FDA0003498200690000032
cmin≤c≤cmax
wherein c is the number of chargers, cmin、cmaxThe minimum value and the maximum value of the number of chargers, S, corresponding to the scale of the electric taxi charging station respectivelyeFor each unit idle cost of the charger, SwThe cost per unit time in order for a charging vehicle to arrive at the station in line waiting,
Figure FDA0003498200690000033
indicating the average waiting time period, T, of the charging vehiclemaxRepresents the maximum waiting period that the vehicle can tolerate;
(1.4) planning an objective function of the quick charging station; the quick charging station planning objective function takes the minimum comprehensive cost of the charging station as an objective function, and is expressed as follows:
minF＝Cinv+Cm+Closs+Cuser (9)
in the formula, CinvAnnual construction costs for fast charging stations, CmFor maintenance annual costs of quick charging stations, ClossFor annual costs of charge loss at a quick charging station, CuserAnnual cost of charging behavior for taxi users; wherein the content of the first and second substances,
the calculation expression of the construction year cost of the quick charging station is as follows:
Figure FDA0003498200690000034
in the formula, CinvThe construction annual cost of the fast charging station is solved, M is the set of the fast charging stations of the electric taxis in the region,
Figure FDA0003498200690000035
for charging station k with number of motors, deltacdIs the price of a charger, skFor charging stationsk capital cost, r0In order to build the discount rate, z is the operating life of the charger;
the quick charging station maintenance annual cost calculation expression is as follows:
Cm＝ηmCinv (11)
in the formula, CmFor the maintenance annual cost of the rapid charging station, according to the proportion eta of the construction annual cost of the rapid charging stationmPerforming conversion;
the expression of the calculation of the annual loss cost of the quick charging station is as follows:
Figure FDA0003498200690000036
in the formula, ClossThe annual expense of the fast charging station, k is the fast charging station, M is the set of the fast charging stations of the electric taxis in the region,
Figure FDA0003498200690000037
the number of motors in the charging station k is,
Figure FDA0003498200690000038
and
Figure FDA0003498200690000039
respectively converting the line loss on the corresponding line of a single charger and the charging loss in the single charger, wherein gamma is the synchronous rate of the multiple chargers working simultaneously, TCIs a charging period;
the taxi user charging behavior annual cost calculation expression is as follows:
Figure FDA00034982006900000310
Figure FDA00034982006900000311
Figure FDA00034982006900000312
Figure FDA00034982006900000313
in the formula, CuserAnnual cost of charging taxi users, CusertTime cost in cost of charging behaviour for taxi users, CuserpCharging cost in the cost of charging behavior for taxi users, delta is the unit time cost of the taxi users, k is a quick charging station, M is a set of electric taxi quick charging stations, i is a traffic node, A is a set of traffic nodes in an area, and V is the total time of the taxi usersiNumber of electric taxis to be charged, P, for traffic node iikTo select the probability, t, of going from the traffic node i to the fast charge station kidkFor the time to go from the traffic node i to the fast charge station k,
Figure FDA0003498200690000041
the average waiting time T of the electric taxi in the fast charging station kmkThe expected time of the next passenger getting on the bus is represented by the time when the owner finishes charging and then starts from a charging station k to search the next passenger getting on the bus traffic node, WevikThe charging capacity, P, required for an electric taxi departing from a traffic node i to a fast charging station kskFor the service charge of the fast charging station k,
Figure FDA0003498200690000042
annual cost of charging behavior, P, for electric taxi users in scene rrThe probability of occurrence of a scene R is shown, R is a set of all scenes, R is one of the scenes, and R belongs to R;
2) determining constraint conditions which need to be met by the taxi quick charging station planning model, wherein the constraint conditions comprise: the method comprises the following steps of (1) distance constraint of a charging station, access point capacity constraint of the charging station, upper and lower limit constraint of node voltage amplitude and maximum current constraint of a feeder line;
3) solving a taxi fast charging station planning model considering charging service charge guidance and a customer demand position; the method comprises the following steps:
(3.1) setting initial values of all parameters in a taxi fast charging station planning model;
(3.2) determining the range of the total number N of the charging stations in the planning region according to the initial value of each parameter in the mathematical model of the planning layer;
(3.3) setting an initial value N of the total number N of the charging stations in the planning area0＝NminSelecting from D addresses to be selected
Figure FDA0003498200690000043
An address scheme;
(3.4) is
Figure FDA0003498200690000044
Randomly ordering the address schemes, wherein Pro represents the serial number of each scheme; setting an initial value Pro-1;
(3.5) the charging demand in the whole planning region is averagely distributed to all stations in the Pro scheme, and the number of initial chargers, the service cost and the average waiting time of charging vehicles of all stations are calculated according to the running layer mathematical model and are used as initial information;
(3.6) simulating operation to obtain the actual number of the electric taxis of each charging station, adjusting the service cost of each charging station, and calculating the optimal number of chargers and the average waiting time of the optimal charging vehicles;
(3.7) comparing the optimal number of chargers and the average waiting time of the optimal charging vehicles in each station with the initial information, if the optimal number of chargers and the average waiting time of the optimal charging vehicles are inconsistent with the initial information, replacing the initial information with the optimal information, and returning to the step (3.6); if the two are consistent, the next step is carried out;
(3.8) calculating a planning objective function of the fast charging station, if the calculation result is superior to the set initial value, comparing the result with the constraint conditions, and if all the constraint conditions are met, taking the current calculation result as the initial value of the planning objective function of the fast charging station, and entering the step (3.9); otherwise, directly entering the step (3.9);
(3.9) Pro +1, and returning to the step (3.5) until reaching the step
Figure FDA0003498200690000045
Entering the next step;
(3.10)N0＝N0+1, returning to the step (3.3), and circularly calculating until N0＞NmaxAnd solving the optimal planning scheme.
2. The method for taxi fast-charge station planning considering charge service guide and customer demand according to claim 1, wherein the step 2) comprises:
(2.1) charging station distance constraint:
Figure FDA0003498200690000046
in the formula, Dkk′Represents the distance between two charging stations; xi represents a tortuosity coefficient of a road in a planning area;
Figure FDA0003498200690000051
is the linear distance between the two stations;
(2.2) charging station access point capacity constraint:
Pkl≤Plmax (15)
in the formula, PklRepresenting the charging power accessed at a load point l of the power distribution network; plmaxRepresenting the maximum value of the charging power which is allowed to be accessed to the load point l of the distribution network;
(2.3) upper and lower limit constraint of node voltage amplitude:
Vl mn≤Vl≤Vl max (16)
in the formula, VlThe voltage amplitude of a load point l of the power distribution network is obtained; vl min，Vl maxRespectively representing the upper limit and the lower limit of the voltage amplitude of the load point l of the power distribution network;
(2.4) maximum feeder current constraint:
|Il|≤Ilmax，l∈L (17)
in the formula IlAnd IlmaxRespectively indicating the current at the load point l of the power distribution network and the maximum current allowed to flow; and L is a distribution network load point set.
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