CN109146135B - Optimization method for sharing electric bicycle station pile equipment - Google Patents

Optimization method for sharing electric bicycle station pile equipment Download PDF

Info

Publication number
CN109146135B
CN109146135B CN201810789944.XA CN201810789944A CN109146135B CN 109146135 B CN109146135 B CN 109146135B CN 201810789944 A CN201810789944 A CN 201810789944A CN 109146135 B CN109146135 B CN 109146135B
Authority
CN
China
Prior art keywords
station
electric bicycle
user
pile
site
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN201810789944.XA
Other languages
Chinese (zh)
Other versions
CN109146135A (en
Inventor
胡郁葱
龚隽
陈枝伟
黎俊廷
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
South China University of Technology SCUT
Original Assignee
South China University of Technology SCUT
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by South China University of Technology SCUT filed Critical South China University of Technology SCUT
Priority to CN201810789944.XA priority Critical patent/CN109146135B/en
Publication of CN109146135A publication Critical patent/CN109146135A/en
Application granted granted Critical
Publication of CN109146135B publication Critical patent/CN109146135B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • G06Q10/043—Optimisation of two dimensional placement, e.g. cutting of clothes or wood
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/06—Buying, selling or leasing transactions
    • G06Q30/0645—Rental transactions; Leasing transactions

Landscapes

  • Business, Economics & Management (AREA)
  • Engineering & Computer Science (AREA)
  • Accounting & Taxation (AREA)
  • Economics (AREA)
  • Human Resources & Organizations (AREA)
  • Strategic Management (AREA)
  • Development Economics (AREA)
  • Finance (AREA)
  • Marketing (AREA)
  • General Business, Economics & Management (AREA)
  • Theoretical Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Physics & Mathematics (AREA)
  • Game Theory and Decision Science (AREA)
  • Tourism & Hospitality (AREA)
  • Quality & Reliability (AREA)
  • Operations Research (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Electric Propulsion And Braking For Vehicles (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

The invention discloses an optimization method for sharing the allocation of electric bicycle station piles, which comprises the following steps: 1) selecting a range of a service mode to be provided for sharing the electric bicycle, and collecting and acquiring basic data of a system of the sharing electric bicycle; 2) according to the obtained basic data, a double-queue queuing model is used for estimating the delay of the user station in combination with the charging characteristic of the station; 3) the user use experience is mainly considered, the total delay of a user station is taken as an optimization target, the constraints of conditions such as builders and stations are considered, and a shared electric bicycle station stake allocation model is established; 4) and solving the shared electric bicycle station pile allocation model to obtain the pile allocation scheme of each station. The invention can be suitable for system scale design work under different requirements, can minimize total delay of user stations, effectively controls the aspects of the number of vehicle piles, the capital cost and the like, can actively promote the construction of an urban shared electric bicycle system, and has practical popularization value.

Description

Optimization method for sharing electric bicycle station pile equipment
Technical Field
The invention relates to the technical field of urban shared electric bicycle system planning, in particular to an optimization method for shared electric bicycle station pile allocation.
Background
The shared bicycle is considered to be one of effective ways for solving urban traffic problems such as traffic jam, exhaust emission, energy crisis and the like, but the popularization of the shared bicycle is hindered by factors such as travel distance, mountain terrain, adverse weather and the like. Since electric bicycles are favored by citizens due to their advantages of comfort, labor saving, low carbon, economy, etc., the development of electric bicycle sharing is considered as one of the development directions of the fourth generation bicycle sharing system. The electric bicycle sharing test projects are developed in succession in domestic and foreign cities, operators mostly refer to experience of a bicycle sharing system, and sharing services are provided by building stations with a certain number of charging piles and electric bicycles.
However, unlike bicycle sharing, electric bicycles have charging problems, which can have a large impact on the design of the sharing system, especially the site stake equipment. Electric bicycle charges at the website and probably causes the circumstances such as no car can borrow, no stake can go back to reduce the turnover rate of filling electric pile and electric bicycle. The electric bicycle sharing site needs to meet the requirement only when a certain amount of vehicle pile allocation is achieved, but is limited by site land, construction, operation capital and the like in actual planning work, theoretical research on the shared electric bicycles at home and abroad at present is mostly analyzed from the aspects of system architecture, user data, influence factors, operation experience, site selection and the like, the design problem of the vehicle pile allocation at the site is less concerned, and meanwhile, the use experience of users is not considered, so that the vehicle pile allocation at the electric bicycle sharing site needs to be researched.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides an optimization method for shared electric bicycle station pile allocation.
In order to achieve the purpose, the technical scheme provided by the invention is as follows: an optimization method for sharing electric bicycle station pile equipment comprises the following steps:
1) selecting a range of a service mode to be provided for sharing the electric bicycles, and collecting and acquiring basic information of the system of the sharing electric bicycles, wherein the basic information comprises four parts, namely site information, cell information, demand information and cost information;
2) according to the obtained basic data, a double-queue queuing model is used for estimating the delay of the user station in combination with the charging characteristic of the station;
3) the user use experience is mainly considered, the total delay of a user station is taken as an optimization target, the constraints of conditions such as builders and stations are considered, and a shared electric bicycle station stake allocation model is established;
4) and solving the shared electric bicycle station pile allocation model to obtain the pile allocation scheme of each station.
In the step 1), the site information comprises specific positions of planned or constructed sites, site land properties, site areas, other service facility allocation conditions of the sites, electric bicycle turnover rates and charging pile turnover rates, and the charging pile turnover rates can be obtained through historical data or by referring to turnover rate data of similar regions in a forecast manner; the cell information comprises traffic cell division conditions of a service area and cell information of a station; the demand information refers to the time-space distribution of the shared origin-destination points of the electric bicycles among all the traffic cells and can be obtained through the data prediction of the travel characteristics of residents in a service area, the travel willingness of the electric bicycles, historical travel records, the travel demand of the electric bicycles in the same region and the like; the cost information comprises the price of the electric bicycle, the price of the charging pile, the price of the electricity charge, the unit inventory cost and other operation and construction expenses, and can be acquired through market research.
In step 2), estimating the station delay of the user by using a double-queue queuing model, comprising the following steps:
2.1) determining the number of the electric bicycles and the charging piles at each station, wherein the calculation formulas of the electric bicycles and the charging piles are as follows:
Figure GDA0003009329800000021
Figure GDA0003009329800000022
in the formula, bxNumber of electric bicycles for station x; u. ofxThe number of charging piles at site x;
Figure GDA0003009329800000023
the electric bicycle turnover rate at station x;
Figure GDA0003009329800000024
the charging pile turnover rate of site x; q. q.sxThe user traffic of site x can be divided into traffic borrowing traffic qbike,xAnd a car return flow qpile,xI.e. qx＝qbike,x+qpile,x；
2.2) estimating the average charging time of the electric bicycle, wherein the estimation formula is as follows:
Figure GDA0003009329800000025
in the formula, texAverage charging time for station x; e.g. of the typeuThe electric quantity consumed by the electric bicycle per unit distance of travel; e.g. of the typefThe amount of power required for a user to travel is assumed to be linearly related to the user's travel distance s, i.e. ef＝seu；eoThe initial electric quantity of the battery; k is the battery loss coefficient; c is the battery capacity; omegaxCharging efficiency for site x; vxCharging the voltage of the pile for site x; i isxCharging the electric pile for site x; an expected value for E (-) -;
2.3) establishing a station queuing model, namely considering the idle charging piles and the non-idle charging piles as being distributed in a centralized way, abstracting a shared station into a queuing system consisting of two queues with mutual influence, namely a car borrowing queue and a car returning queue, and considering the arrival of the car borrowing and returning users as a poisson process if the observation time interval delta t is divided into small enough and the arrival of the users is assumed to be independent. The method comprises the following specific steps:
for the vehicle borrowing queue, when ux≤bxThe vehicle borrowing queue is a user arrival rate lambdabike,xThe service rate of the electric bicycle is mubike,xParallel service desk is uxAnd a capacity of bxM/M/u ofx/bxA queuing system; when u isx＞bxThe vehicle borrowing queue is a user arrival rate lambdabike,xThe service rate of the electric bicycle is mubike,xA parallel service desk is bxAnd a capacity of bxM/M/b ofx/bxA queuing system. The user borrowing arrival rate of the station x is lambdabike,x＝qbike,xΔ t/60, electric bicycle service rate of station x is μbike,x＝Δt/(60tex)；
For the returning queue, the returning queue is a queue with a user arrival rate of lambdapile,xAnd the service rate of the charging pile is mupile,xParallel service desk is uxAnd a capacity of uxM/M/u ofx/uxA queuing system. The arrival rate of the car returning user at the station x is lambdapile,x＝qpile,xDelta t/60, site x charging pile service rate mupile,xThe frequency of the electric bicycle being borrowed;
2.4) estimating the station delay of the user, wherein the station delay of the user refers to the stay time of the user at the station, and the station delay is calculated according to the size relation between the electric bicycles and the number of the piles at the station by the following conditions:
when ux≤bxIn time, the loss rate of the vehicle borrowing queue is obtained
Figure GDA0003009329800000031
In the formula, Pbike,0xProbability of no-one-to-receive-borrow-service for site x;
Figure DEST_PATH_IMAGE001
the user loss rate for borrowing the vehicle for site x; etabike,xThe number of people in site x who are receiving service for a car loan; rhobike,xUtilization ratio, rho, of electric bicycles at station xbike,x＝λbike,x/μbike,x；
Thus, when u can be obtainedx≤bxThe borrowing user station delay of the time station x is as follows:
Figure GDA0003009329800000041
in the formula (I), the compound is shown in the specification,
Figure GDA0003009329800000042
a user station delay for borrowing of station x; l isbike,xIs the average value of the queue length of the vehicle borrowing queue,
Figure GDA0003009329800000043
μpile,xservice rate for the queue of return cars, also the frequency with which the electric bicycles of the station are borrowed, i.e. mupile,x＝λbike,x(1-Pbx)；
And station x's return user station delays
Figure GDA0003009329800000044
(ii) when ux＞bxThen, only the number of the service desks is needed to be changed from uxBecome bxThe same reason can be obtained by delaying the stop of the car borrowing and returning users.
In step 3), establishing a shared electric bicycle station pile configuration model, comprising the following steps:
3.1) the following assumptions were made for the model set-up:
the shared electric bicycle flow is unidirectional, and any station has the functions of borrowing and returning the electric bicycle;
secondly, each station is provided with an electric bicycle and a charging pile with the same specification, the same charging voltage and charging current are provided, the linear correlation between the battery power consumed by a user when going out and the distance of the user is finished, and if the actual data of the probability distribution related to the charging demand of the user can be obtained, the homogeneity assumption can be removed;
thirdly, the travel demand is concentrated on a certain point of a traffic cell, but the point is not necessarily the centroid of the cell, and the demand of each cell is the high peak hour obtained according to OD survey without considering the travel in the cell;
returning the vehicles to the parking center by the aid of the parking center, wherein the parking center is provided with a plurality of parking points, the parking points are distributed according to the distribution of the parking points, and the parking center is provided with a plurality of parking points;
the power grid capacity can meet the construction and operation requirements of the shared electric bicycle system;
3.2) the user use experience is considered in an important mode, the delay of the user on the site is reduced as far as possible, the total delay (sum of the site stay time of all users) of the user sites in the system is minimum as an optimization target, and an objective function is established:
Figure GDA0003009329800000051
wherein X is the collection of stations in the electric bicycle sharing system, then
Figure GDA0003009329800000052
qbike,xThe borrowed traffic volume for site x;
Figure GDA0003009329800000053
a user station delay for borrowing of station x; q. q.spile,xIs the return traffic for station x;
Figure GDA0003009329800000054
delaying the station of the user returning the station x; when Z reaches the minimum, the total delay of the user station of the system is optimal;
3.3) according to the established objective function, considering from three aspects of users, constructors and sites, determining constraint conditions of the model:
flow conservation constraint is required to be met, and the travel production and the attraction of a traffic cell are respectively the sum of the traffic borrowing flow and the traffic returning flow of a station of the cell, namely:
Figure GDA0003009329800000055
wherein A is the set of traffic cells, then
Figure GDA0003009329800000056
OiAnd DiRespectively representing the travel production and the attraction of the traffic cell i; deltax,iIs the relation variable of the station x and the traffic cell i, if the station x is on the traffic cell i, deltax,i1 is ═ 1; else δx,i＝0；qbike,xThe borrowed traffic volume for site x; q. q.spile,xIs the return traffic for station x;
secondly, construction cost is restrained, the construction cost mainly comprises purchase cost of the charging pile and the electric bicycle, namely:
Figure GDA0003009329800000057
wherein X is the collection of stations in the electric bicycle sharing system, then
Figure GDA0003009329800000058
cb、cuThe unit price of the electric bicycle and the unit price of the charging pile are respectively; bxNumber of electric bicycles for station x; u. ofxThe number of charging piles at site x; cfThe upper limit of construction capital;
the operation cost is restrained, and the operation cost comprises electric charge, inventory cost and other operation cost, namely:
Figure GDA0003009329800000061
wherein X is the collection of stations in the electric bicycle sharing system, then
Figure GDA0003009329800000062
bxNumber of electric bicycles for station x; e.g. of the typefThe electric quantity required by the user for going out; e.g. of the typeoThe initial electric quantity of the battery; c. CeUnit price of electricity charge; h is the proportion of the electric bicycles stored in the warehouse; c. CiIs the unit inventory cost; c. CoThe rest operation expenses except the electricity fee and the inventory expense are taken as the shared site per hour; cvAn upper operating capital limit;
fourthly, the quantity of the charging piles is controlled according to the total quantity, namely:
Figure GDA0003009329800000063
wherein X is the collection of stations in the electric bicycle sharing system, then
Figure GDA0003009329800000064
uxThe number of charging piles at site x; u. ofmaxThe maximum value of the charging pile is allowed to be equipped for the system;
control the stake quantity of charging of every website, promptly:
Figure GDA0003009329800000065
wherein X is the collection of stations in the electric bicycle sharing system, then
Figure GDA0003009329800000066
uxThe number of charging piles at site x;
Figure GDA0003009329800000067
the maximum value of the charging piles is allowed to be equipped for the station;
sixthly, controlling the number of the electric bicycles from the total amount, namely:
Figure GDA0003009329800000068
wherein X is the collection of stations in the electric bicycle sharing system, then
Figure GDA0003009329800000069
bxNumber of electric bicycles for station x; bmaxMaximum allowable system for equipping electric bicycles;
seventhly, controlling the number of the electric bicycles at each station, namely:
Figure GDA00030093298000000610
wherein X is the collection of stations in the electric bicycle sharing system, then
Figure GDA00030093298000000611
bxNumber of electric bicycles for station x;
Figure GDA00030093298000000612
maximum allowable electric bicycle equipping for station;
ensuring that the station meets the minimum scale requirement, namely:
Figure GDA0003009329800000071
wherein X is the collection of stations in the electric bicycle sharing system, then
Figure GDA0003009329800000072
bxNumber of electric bicycles for station x; u. ofxThe number of charging piles at site x; ubminThe number of the charging piles and the electric bicycles is the minimum value of the station.
The method for solving the shared electric bicycle station stake allocation model in the step 4) is a heuristic algorithm, selectable algorithms comprise a genetic algorithm, an ant colony algorithm, a simulated annealing method and a neural network method, and the overall solving idea is as follows:
making Q ═ Q [ Q ]xIs multiplied by X, element qxIs the site traffic. According to the station flow, the borrowing and returning flow, the number of equipped vehicle piles, the station delay and the like of each station can be obtained by using the formula in the step 2);
determining an initial solution according to rules of a corresponding algorithm;
thirdly, generating a plurality of neighborhood solutions through neighborhood functions under the control of key parameters of the algorithm;
fourthly, according to the acceptance criterion: updating the current state in a deterministic, probabilistic or chaotic way;
adjusting the key parameters according to the key parameter modification criterion;
judging whether the iteration stopping condition is met according to the convergence criterion of the algorithm, if so, obtaining the final optimization result of the problem, otherwise, returning to the step three.
Compared with the prior art, the invention has the following advantages and beneficial effects:
the invention is based on the user experience, considers various factors such as cost, user demand and use experience, and obtains the optimization method for sharing the electric bicycle station vehicle stake allocation with the minimum total user delay.
Drawings
FIG. 1 is a flow chart of the method of the present invention.
Fig. 2 is a layout diagram of a shared electric bicycle station and a traffic cell according to an embodiment of the present invention.
Fig. 3 is a schematic diagram of traffic occurrence of electric bicycles shared by traffic districts according to an embodiment of the present invention.
Fig. 4 is a schematic view of the electric bicycle traffic attraction shared by the traffic districts according to the embodiment of the present invention.
Fig. 5 is a schematic view of a stake mounting scheme for a shared electric bicycle station in an embodiment of the invention.
Detailed Description
The present invention will be described in further detail with reference to examples and drawings, but the present invention is not limited thereto.
As shown in fig. 1, the method for optimizing the shared electric bicycle station pile equipment provided by the present embodiment includes the following steps:
1) selecting a range of a service mode to be provided for sharing the electric bicycles, and collecting and acquiring basic information of the system of the sharing electric bicycles, wherein the basic information comprises four parts, namely site information, cell information, demand information and cost information; the station information comprises specific positions of planned or constructed stations, station land property, station area, station other service facility allocation conditions, electric bicycle turnover rate and charging pile turnover rate, and the charging pile turnover rate can be obtained through historical data or by referring to turnover rate data of the same type of region in a forecast manner; the cell information comprises traffic cell division conditions of a service area and cell information of a station; the demand information refers to the time-space distribution of the shared origin-destination points of the electric bicycles among all the traffic cells and can be obtained through the data prediction of the travel characteristics of residents in a service area, the travel willingness of the electric bicycles, historical travel records, the travel demand of the electric bicycles in the same region and the like; the cost information comprises the price of the electric bicycle, the price of the charging pile, the price of the electricity charge, the unit inventory cost and other operation and construction expenses, and can be acquired through market research. The range selection and data acquisition are as follows:
in 15 traffic districts in a certain area, 65 shared stations are planned to be constructed, as shown in fig. 2. The shared electric bicycle traffic occurrence amount of each cell is shown in fig. 3, the attraction amount is shown in fig. 4, and other relevant parameters are shown in table 1.
Table 1 associated input parameters
Figure GDA0003009329800000081
2) Estimating the station delay of the user by using a double-queue queuing model, comprising the following steps:
2.1) determining the number of the electric bicycles and the charging piles at each station, wherein the calculation formulas of the electric bicycles and the charging piles are as follows:
Figure GDA0003009329800000091
Figure GDA0003009329800000092
in the formula, bxNumber of electric bicycles for station x; u. ofxThe number of charging piles at site x;
Figure GDA0003009329800000093
the electric bicycle turnover rate at station x;
Figure GDA0003009329800000094
the charging pile turnover rate of site x; q. q.sxThe user traffic of site x can be divided into traffic borrowing traffic qbike,xAnd a car return flow qpile,xI.e. qx＝qbike,x+qpile,x；
2.2) estimating the average charging time of the electric bicycle, wherein the estimation formula is as follows:
Figure GDA0003009329800000095
in the formula, texAverage charging time for station x; e.g. of the typeuThe electric quantity consumed by the electric bicycle per unit distance of travel; e.g. of the typefThe amount of power required for a user to travel is assumed to be linearly related to the user's travel distance s, i.e. ef＝seu；eoThe initial electric quantity of the battery; k is the battery loss coefficient; c is the battery capacity; omegaxCharging efficiency for site x; vxCharging the voltage of the pile for site x; i isxCharging the electric pile for site x; an expected value for E (-) -;
2.3) establishing a station queuing model, namely considering the idle charging piles and the non-idle charging piles as being distributed in a centralized way, abstracting a shared station into a queuing system consisting of two queues with mutual influence, namely a car borrowing queue and a car returning queue, and considering the arrival of the car borrowing and returning users as a poisson process if the observation time interval delta t is divided into small enough and the arrival of the users is assumed to be independent. The method comprises the following specific steps:
for the vehicle borrowing queue, when ux≤bxThe vehicle borrowing queue is a user arrival rate lambdabike,xThe service rate of the electric bicycle is mubike,xParallel service desk is uxAnd a capacity of bxM/M/u ofx/bxA queuing system; when u isx＞bxThe vehicle borrowing queue is a user arrival rate lambdabike,xThe service rate of the electric bicycle is mubike,xA parallel service desk is bxAnd a capacity ofbxM/M/b ofx/bxA queuing system. The user borrowing arrival rate of the station x is lambdabike,x＝qbike,xΔ t/60, electric bicycle service rate of station x is μbike,x＝Δt/(60tex)；
For the returning queue, the returning queue is a queue with a user arrival rate of lambdapile,xAnd the service rate of the charging pile is mupile,xParallel service desk is uxAnd a capacity of uxM/M/u ofx/uxA queuing system. The arrival rate of the car returning user at the station x is lambdapile,x＝qpile,xDelta t/60, site x charging pile service rate mupile,xThe frequency of the electric bicycle being borrowed;
2.4) estimating the station delay of the user, wherein the station delay of the user refers to the stay time of the user at the station, and the station delay is calculated according to the size relation between the electric bicycles and the number of the piles at the station by the following conditions:
when ux≤bxIn time, the loss rate of the vehicle borrowing queue is obtained
Figure GDA0003009329800000101
In the formula, Pbike,0xProbability of no-one-to-receive-borrow-service for site x;
Figure 300289DEST_PATH_IMAGE001
the user loss rate for borrowing the vehicle for site x; etabike,xThe number of people in site x who are receiving service for a car loan; rhobike,xUtilization ratio, rho, of electric bicycles at station xbike,x＝λbike,x/μbike,x；
Thus, when u can be obtainedx≤bxThe borrowing user station delay of the time station x is as follows:
Figure GDA0003009329800000102
in the formula (I), the compound is shown in the specification,
Figure GDA0003009329800000103
a user station delay for borrowing of station x; l isbike,xIs the average value of the queue length of the vehicle borrowing queue,
Figure GDA0003009329800000104
μpile,xservice rate for the queue of return cars, also the frequency with which the electric bicycles of the station are borrowed, i.e. mupile,x＝λbike,x(1-Pbx)；
And station x's return user station delays
Figure GDA0003009329800000105
(ii) when ux＞bxThen, only the number of the service desks is needed to be changed from uxBecome bxThe same reason can be obtained by delaying the stop of the car borrowing and returning users.
3) The method for establishing the shared electric bicycle station pile allocation model comprises the following steps:
3.1) the following assumptions were made for the model set-up:
the shared electric bicycle flow is unidirectional, and any station has the functions of borrowing and returning the electric bicycle;
secondly, each station is provided with an electric bicycle and a charging pile with the same specification, the same charging voltage and charging current are provided, the linear correlation between the battery power consumed by a user when going out and the distance of the user is finished, and if the actual data of the probability distribution related to the charging demand of the user can be obtained, the homogeneity assumption can be removed;
thirdly, the travel demand is concentrated on a certain point of a traffic cell, but the point is not necessarily the centroid of the cell, and the demand of each cell is the high peak hour obtained according to OD survey without considering the travel in the cell;
returning the vehicles to the parking center by the aid of the parking center, wherein the parking center is provided with a plurality of parking points, the parking points are distributed according to the distribution of the parking points, and the parking center is provided with a plurality of parking points;
the power grid capacity can meet the construction and operation requirements of the shared electric bicycle system;
3.2) the user use experience is considered in an important mode, the delay of the user on the site is reduced as far as possible, the total delay (sum of the site stay time of all users) of the user sites in the system is minimum as an optimization target, and an objective function is established:
Figure GDA0003009329800000111
wherein X is the collection of stations in the electric bicycle sharing system, then
Figure GDA0003009329800000112
qbike,xThe borrowed traffic volume for site x;
Figure GDA0003009329800000113
a user station delay for borrowing of station x; q. q.spile,xIs the return traffic for station x;
Figure GDA0003009329800000114
delaying the station of the user returning the station x; when Z reaches the minimum, the total delay of the user station of the system is optimal;
3.3) according to the established objective function, considering from three aspects of users, constructors and sites, determining constraint conditions of the model:
flow conservation constraint is required to be met, and the travel production and the attraction of a traffic cell are respectively the sum of the traffic borrowing flow and the traffic returning flow of a station of the cell, namely:
Figure GDA0003009329800000121
wherein A is the set of traffic cells, then
Figure GDA0003009329800000128
OiAnd DiRespectively representing the travel production and the attraction of the traffic cell i; deltax,iIs the relation variable of the station x and the traffic cell i, if the stationPoint x is on traffic cell i, δx,i1 is ═ 1; else δx,i＝0；qbike,xThe borrowed traffic volume for site x; q. q.spile,xIs the return traffic for station x;
secondly, construction cost is restrained, the construction cost mainly comprises purchase cost of the charging pile and the electric bicycle, namely:
Figure GDA0003009329800000122
wherein X is the collection of stations in the electric bicycle sharing system, then
Figure GDA0003009329800000123
cb、cuThe unit price of the electric bicycle and the unit price of the charging pile are respectively; bxNumber of electric bicycles for station x; u. ofxThe number of charging piles at site x; cfThe upper limit of construction capital;
the operation cost is restrained, and the operation cost comprises electric charge, inventory cost and other operation cost, namely:
Figure GDA0003009329800000124
wherein X is the collection of stations in the electric bicycle sharing system, then
Figure GDA0003009329800000125
bxNumber of electric bicycles for station x; e.g. of the typefThe electric quantity required by the user for going out; e.g. of the typeoThe initial electric quantity of the battery; c. CeUnit price of electricity charge; h is the proportion of the electric bicycles stored in the warehouse; c. CiIs the unit inventory cost; c. CoThe rest operation expenses except the electricity fee and the inventory expense are taken as the shared site per hour; cvAn upper operating capital limit;
fourthly, the quantity of the charging piles is controlled according to the total quantity, namely:
Figure GDA0003009329800000126
wherein X is the collection of stations in the electric bicycle sharing system, then
Figure GDA0003009329800000127
uxThe number of charging piles at site x; u. ofmaxThe maximum value of the charging pile is allowed to be equipped for the system;
control the stake quantity of charging of every website, promptly:
Figure GDA0003009329800000131
wherein X is the collection of stations in the electric bicycle sharing system, then
Figure GDA0003009329800000132
uxThe number of charging piles at site x;
Figure GDA0003009329800000133
the maximum value of the charging piles is allowed to be equipped for the station;
sixthly, controlling the number of the electric bicycles from the total amount, namely:
Figure GDA0003009329800000134
wherein X is the collection of stations in the electric bicycle sharing system, then
Figure GDA0003009329800000135
bxNumber of electric bicycles for station x; bmaxMaximum allowable system for equipping electric bicycles;
seventhly, controlling the number of the electric bicycles at each station, namely:
Figure GDA0003009329800000136
wherein X is the collection of stations in the electric bicycle sharing system, then
Figure GDA0003009329800000137
bxNumber of electric bicycles for station x;
Figure GDA0003009329800000138
maximum allowable electric bicycle equipping for station;
ensuring that the station meets the minimum scale requirement, namely:
Figure GDA0003009329800000139
wherein X is the collection of stations in the electric bicycle sharing system, then
Figure GDA00030093298000001310
bxNumber of electric bicycles for station x; u. ofxThe number of charging piles at site x; ubminThe number of the charging piles and the electric bicycles is the minimum value of the station.
4) And solving the shared electric bicycle station pile allocation model to obtain the pile allocation scheme of each station. Comprises the following steps:
4.1) the method for solving the shared electric bicycle station stake fitting model is a heuristic algorithm, selectable algorithms comprise a genetic algorithm, an ant colony algorithm, a simulated annealing method and a neural network method, and the overall solving idea is as follows:
making Q ═ Q [ Q ]xIs multiplied by X, element qxIs the site traffic. According to the station flow, the borrowing and returning flow, the number of equipped vehicle piles, the station delay and the like of each station can be obtained by using the formula in the step 2);
determining an initial solution according to rules of a corresponding algorithm;
thirdly, generating a plurality of neighborhood solutions through neighborhood functions under the control of key parameters of the algorithm;
fourthly, according to the acceptance criterion: updating the current state in a deterministic, probabilistic or chaotic way;
adjusting the key parameters according to the key parameter modification criterion;
judging whether the iteration stopping condition is met according to the convergence criterion of the algorithm, if so, obtaining the final optimization result of the problem, otherwise, returning to the step three.
4.2) solving is carried out by adopting a genetic algorithm in the embodiment, and the solving result is shown in figure 5, so that the vehicle pile allocation scheme of each station is obtained.
The above description is only for the preferred embodiments of the present invention, but the protection scope of the present invention is not limited thereto, and any person skilled in the art can substitute or change the technical solution of the present invention and the inventive concept within the scope of the present invention, which is disclosed by the present invention, and the equivalent or change thereof belongs to the protection scope of the present invention.

Claims (4)

1. An optimization method for sharing electric bicycle station pile equipment is characterized by comprising the following steps:
1) selecting a range of a service mode to be provided for sharing the electric bicycles, and collecting and acquiring basic information of the system of the sharing electric bicycles, wherein the basic information comprises four parts, namely site information, cell information, demand information and cost information;
2) according to the obtained basic data, a double-queue queuing model is used for estimating the station delay of the user by combining the charging characteristics of the station, and the method comprises the following steps:
2.1) determining the number of the electric bicycles and the charging piles at each station, wherein the calculation formulas of the electric bicycles and the charging piles are as follows:
Figure FDA0003009329790000011
Figure FDA0003009329790000012
in the formula, bxNumber of electric bicycles for station x; u. ofxThe number of charging piles at site x;
Figure FDA0003009329790000013
the electric bicycle turnover rate at station x;
Figure FDA0003009329790000014
the charging pile turnover rate of site x; q. q.sxThe user traffic of site x is divided into the traffic borrowing traffic qbike,xAnd a car return flow qpile,xI.e. qx＝qbike,x+qpile,x；
2.2) estimating the average charging time of the electric bicycle, wherein the estimation formula is as follows:
Figure FDA0003009329790000015
in the formula, texAverage charging time for station x; e.g. of the typeuThe electric quantity consumed by the electric bicycle per unit distance of travel; e.g. of the typefThe amount of power required for a user to travel is assumed to be linearly related to the user's travel distance s, i.e. ef＝seu；eoThe initial electric quantity of the battery; k is the battery loss coefficient; c is the battery capacity; omegaxCharging efficiency for site x; vxCharging the voltage of the pile for site x; i isxCharging the electric pile for site x; an expected value for E (-) -;
2.3) establishing a station queuing model, namely considering the idle charging piles and the non-idle charging piles as being distributed in a centralized way, abstracting a shared station into a queuing system consisting of two queues which have mutual influence on a car borrowing queue and a car returning queue, and considering the arrival of the car borrowing and returning users as a poisson process if the observation time interval delta t is divided to reach a set value and the arrival of each user is assumed to be mutually independent; the method comprises the following specific steps:
for the vehicle borrowing queue, when ux≤bxThe vehicle borrowing queue is a user arrival rate lambdabike,xThe service rate of the electric bicycle is mubike,xParallel service desk is uxAnd a capacity of bxM/M/u ofx/bxA queuing system; when u isx＞bxThe vehicle borrowing queue is a user arrival rate lambdabike,xThe service rate of the electric bicycle is mubike,xA parallel service desk is bxAnd a capacity of bxM/M/b ofx/bxA queuing system; the user borrowing arrival rate of the station x is lambdabike,x＝qbike,xΔ t/60, electric bicycle service rate of station x is μbike,x＝Δt/(60tex)；
For the returning queue, the returning queue is a queue with a user arrival rate of lambdapile,xAnd the service rate of the charging pile is mupile,xParallel service desk is uxAnd a capacity of uxM/M/u ofx/uxA queuing system; the arrival rate of the car returning user at the station x is lambdapile,x＝qpile,xDelta t/60, site x charging pile service rate mupile,xThe frequency of the electric bicycle being borrowed;
2.4) estimating the station delay of the user, wherein the station delay of the user refers to the stay time of the user at the station, and the station delay is calculated according to the size relation between the electric bicycles and the number of the piles at the station by the following conditions:
when ux≤bxIn time, the loss rate of the vehicle borrowing queue is obtained
Figure FDA0003009329790000021
In the formula, Pbike,0xProbability of no-one-to-receive-borrow-service for site x;
Figure 832546DEST_PATH_IMAGE001
the user loss rate for borrowing the vehicle for site x; etabike,xThe number of people in site x who are receiving service for a car loan; rhobike,xUtilization ratio, rho, of electric bicycles at station xbike,x＝λbike,x/μbike,x；
Thus, when u is obtainedx≤bxThe borrowing user station delay of the time station x is as follows:
Figure FDA0003009329790000022
in the formula (I), the compound is shown in the specification,
Figure FDA0003009329790000023
a user station delay for borrowing of station x; l isbike,xIs the average value of the queue length of the vehicle borrowing queue,
Figure FDA0003009329790000031
μpile,xthe service rate for the queue of return cars, and also the frequency with which the electric bicycles of the station are borrowed, i.e.
Figure FDA0003009329790000032
And station x's return user station delays
Figure FDA0003009329790000033
(ii) when ux＞bxThen, only the number of the service desks is needed to be changed from uxBecome bxThe station delay of the car borrowing and returning users can be obtained by the same principle;
3) the user use experience is mainly considered, the total delay of a user station is taken as an optimization target, the constraints of builders and station conditions are considered, and a shared electric bicycle station vehicle pile allocation model is established;
4) and solving the shared electric bicycle station pile allocation model to obtain the pile allocation scheme of each station.
2. The optimization method for sharing the configuration of the electric bicycle station piles as claimed in claim 1, wherein in step 1), the station information comprises specific positions of planned or constructed stations, station land properties, station areas, station other service facility configuration conditions, electric bicycle turnover rates and charging pile turnover rates, and the charging pile turnover rates are obtained through historical data or by referring to turnover rate data of the same type of regions; the cell information comprises traffic cell division conditions of a service area and cell information of a station; the demand information refers to the time-space distribution of the shared electric bicycle origin-destination points among all the traffic cells, and is obtained through the travel characteristics of residents in a service area, the travel willingness of the electric bicycle, historical travel records and the travel demand data prediction of the electric bicycle in the same region; the cost information comprises the price of the electric bicycle, the price of the charging pile, the price of the electricity charge, the unit inventory cost and other operation and construction expenses, and is obtained through market research.
3. The method for optimizing the configuration of the shared electric bicycle station stake set-up as claimed in claim 1, wherein in step 3), a model for the configuration of the shared electric bicycle station stake set-up is established, comprising the following steps:
3.1) the following assumptions were made for the model set-up:
the shared electric bicycle flow is unidirectional, and any station has the functions of borrowing and returning the electric bicycle;
secondly, each station is provided with an electric bicycle and a charging pile with the same specification, the same charging voltage and charging current are provided, the linear correlation between the battery power consumed by a user when going out and the distance of the user is finished, and if the actual data of the probability distribution related to the charging demand of the user can be obtained, the homogeneity assumption can be removed;
thirdly, the travel demand is concentrated on a certain point of a traffic cell, but the point is not necessarily the centroid of the cell, and the demand of each cell is the high peak hour obtained according to OD survey without considering the travel in the cell;
returning the vehicles to the parking center by the aid of the parking center, wherein the parking center is provided with a plurality of parking points, the parking points are distributed according to the distribution of the parking points, and the parking center is provided with a plurality of parking points;
the power grid capacity can meet the construction and operation requirements of the shared electric bicycle system;
3.2) the user use experience is mainly considered, the delay of the user on the site is reduced as much as possible, the total delay of the user site in the system, namely the sum of the site residence time of all the users is the minimum as an optimization target, and an objective function is established:
Figure FDA0003009329790000041
wherein X is the collection of stations in the electric bicycle sharing system, then
Figure FDA0003009329790000042
qbike,xThe borrowed traffic volume for site x;
Figure FDA0003009329790000043
a user station delay for borrowing of station x; q. q.spile,xIs the return traffic for station x;
Figure FDA0003009329790000044
delaying the station of the user returning the station x; when Z reaches the minimum, the total delay of the user station of the system is optimal;
3.3) according to the established objective function, considering from three aspects of users, constructors and sites, determining constraint conditions of the model:
flow conservation constraint is required to be met, and the travel production and the attraction of a traffic cell are respectively the sum of the traffic borrowing flow and the traffic returning flow of a station of the cell, namely:
Figure FDA0003009329790000045
wherein A is the set of traffic cells, then
Figure FDA0003009329790000046
OiAnd DiRespectively representing the travel production and the attraction of the traffic cell i; deltax,iIs a station x and a traffic celli, if site x is on traffic cell i, δx,i1 is ═ 1; else δx,i＝0；qbike,xThe borrowed traffic volume for site x; q. q.spile,xIs the return traffic for station x;
secondly, construction cost is restrained, the construction cost comprises purchase cost of the charging pile and the electric bicycle, namely:
Figure FDA0003009329790000051
wherein X is the collection of stations in the electric bicycle sharing system, then
Figure FDA0003009329790000052
cb、cuThe unit price of the electric bicycle and the unit price of the charging pile are respectively; bxNumber of electric bicycles for station x; u. ofxThe number of charging piles at site x; cfThe upper limit of construction capital;
the operation cost is restrained, and the operation cost comprises electric charge, inventory cost and other operation cost, namely:
Figure FDA0003009329790000053
wherein X is the collection of stations in the electric bicycle sharing system, then
Figure FDA0003009329790000054
bxNumber of electric bicycles for station x; e.g. of the typefThe electric quantity required by the user for going out; e.g. of the typeoThe initial electric quantity of the battery; c. CeUnit price of electricity charge; h is the proportion of the electric bicycles stored in the warehouse; c. CiIs the unit inventory cost; c. CoThe rest operation expenses except the electricity fee and the inventory expense are taken as the shared site per hour; cvAn upper operating capital limit;
fourthly, the quantity of the charging piles is controlled according to the total quantity, namely:
Figure FDA0003009329790000055
wherein X is the collection of stations in the electric bicycle sharing system, then
Figure FDA0003009329790000056
uxThe number of charging piles at site x; u. ofmaxThe maximum value of the charging pile is allowed to be equipped for the system;
control the stake quantity of charging of every website, promptly:
Figure FDA0003009329790000057
wherein X is the collection of stations in the electric bicycle sharing system, then
Figure FDA0003009329790000061
uxThe number of charging piles at site x;
Figure FDA0003009329790000062
the maximum value of the charging piles is allowed to be equipped for the station;
sixthly, controlling the number of the electric bicycles from the total amount, namely:
Figure FDA0003009329790000063
wherein X is the collection of stations in the electric bicycle sharing system, then
Figure FDA0003009329790000064
bxNumber of electric bicycles for station x; bmaxMaximum allowable system for equipping electric bicycles;
seventhly, controlling the number of the electric bicycles at each station, namely:
Figure FDA0003009329790000065
wherein X is the collection of stations in the electric bicycle sharing system, then
Figure FDA0003009329790000066
bxNumber of electric bicycles for station x;
Figure FDA0003009329790000067
maximum allowable electric bicycle equipping for station;
ensuring that the station meets the minimum scale requirement, namely:
Figure FDA0003009329790000068
wherein X is the collection of stations in the electric bicycle sharing system, then
Figure FDA0003009329790000069
bxNumber of electric bicycles for station x; u. ofxThe number of charging piles at site x; ubminThe number of the charging piles and the electric bicycles is the minimum value of the station.
4. The method of claim 1 for optimizing shared electric bicycle site stake equipment, wherein: in the step 4), the method for solving the shared electric bicycle station pile configuration model is a heuristic algorithm, the selected algorithm comprises a genetic algorithm, an ant colony algorithm, a simulated annealing method and a neural network method, and the overall solution thought is as follows:
making Q ═ Q [ Q ]xIs multiplied by X, element qxFor the station flow, the borrowing and returning vehicle flow, the number of equipped vehicle piles and the station of each station can be obtained by using the formula in the step 2) according to the station flowDelaying;
determining an initial solution according to rules of a corresponding algorithm;
thirdly, generating a plurality of neighborhood solutions through neighborhood functions under the control of key parameters of the algorithm;
fourthly, according to the acceptance criterion: updating the current state in a deterministic, probabilistic or chaotic way;
adjusting the key parameters according to the key parameter modification criterion;
judging whether the iteration stopping condition is met according to the convergence criterion of the algorithm, if so, obtaining the final optimization result of the problem, otherwise, returning to the step three.
CN201810789944.XA 2018-07-18 2018-07-18 Optimization method for sharing electric bicycle station pile equipment Active CN109146135B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201810789944.XA CN109146135B (en) 2018-07-18 2018-07-18 Optimization method for sharing electric bicycle station pile equipment

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201810789944.XA CN109146135B (en) 2018-07-18 2018-07-18 Optimization method for sharing electric bicycle station pile equipment

Publications (2)

Publication Number Publication Date
CN109146135A CN109146135A (en) 2019-01-04
CN109146135B true CN109146135B (en) 2021-06-08

Family

ID=64801084

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201810789944.XA Active CN109146135B (en) 2018-07-18 2018-07-18 Optimization method for sharing electric bicycle station pile equipment

Country Status (1)

Country Link
CN (1) CN109146135B (en)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113642757B (en) * 2021-06-01 2024-02-27 北京慧辰资道资讯股份有限公司 Method and system for planning construction of charging pile of Internet of things based on artificial intelligence

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105760949A (en) * 2016-02-04 2016-07-13 国网山东省电力公司经济技术研究院 Optimizing configuration method for amount of chargers of electromobile charging station
CN106022514A (en) * 2016-05-12 2016-10-12 华南理工大学 Public electric bicycle leasing point address-selecting method based on trip chain
CN106779176A (en) * 2016-11-25 2017-05-31 北京交通大学 Electric taxi fills electrically-charging equipment configuration and constant volume method in station soon

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105760949A (en) * 2016-02-04 2016-07-13 国网山东省电力公司经济技术研究院 Optimizing configuration method for amount of chargers of electromobile charging station
CN106022514A (en) * 2016-05-12 2016-10-12 华南理工大学 Public electric bicycle leasing point address-selecting method based on trip chain
CN106779176A (en) * 2016-11-25 2017-05-31 北京交通大学 Electric taxi fills electrically-charging equipment configuration and constant volume method in station soon

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
李建军 等.基于排队模型的电动汽车充电粧数量优化设计.《数学的实践与认识》.2017,第47卷(第9期), *

Also Published As

Publication number Publication date
CN109146135A (en) 2019-01-04

Similar Documents

Publication Publication Date Title
CN110895638B (en) Active power distribution network model establishment method considering electric vehicle charging station site selection and volume fixing
CN109523051B (en) Electric automobile charging real-time optimization scheduling method
Li et al. Price incentive-based charging navigation strategy for electric vehicles
Bayram et al. Electric power allocation in a network of fast charging stations
CN109492791B (en) Inter-city expressway network light storage charging station constant volume planning method based on charging guidance
CN109711630A (en) A kind of electric car fast charge station addressing constant volume method based on trip probability matrix
CN109447410A (en) A kind of charging station site selecting method considering urban road network traffic operating status
CN109190813B (en) Shared bicycle region putting planning method based on double-layer planning
CN108596667B (en) Electric automobile real-time charging electricity price calculation method based on Internet of vehicles
CN108573317B (en) Method for optimally controlling charging and discharging strategies of power change station
Li et al. Direct vehicle-to-vehicle charging strategy in vehicular ad-hoc networks
CN106951999A (en) The modeling of a kind of travel modal and the moment Combination selection that sets out and analysis method
CN102708427A (en) System and method for analyzing and determining influence of large-scale charging pile to community distribution system
CN109657993A (en) A kind of automatic demand response method of energy local area network energy-storage system based on non-cooperative game
CN111523930A (en) Planning method for site selection and service range division of urban electric taxi charging station
CN110705864B (en) Site selection and volume fixing method for charging station
CN110232219A (en) A kind of schedulable capacity ratification method of electric car based on data mining
CN108133329B (en) Electric automobile travel and charging demand analysis method considering charging feedback effect
CN114021880A (en) Charging station site selection and volume fixing method based on electric vehicle volume
CN115510672A (en) Electric micro-trip vehicle battery replacement demand prediction method under perception environment of Internet of things
Luo et al. Location and capacity model of charging station for electric vehicles based on commuting demand
CN111861145A (en) Method for configuring service area electric vehicle charging station considering highway network
CN109146135B (en) Optimization method for sharing electric bicycle station pile equipment
CN115907227B (en) Double-layer collaborative optimization method for expressway fixed and mobile charging facilities
Bai et al. Multi-objective planning for electric vehicle charging stations considering TOU price

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant