CN113554239A - Site selection and equipment capacity optimization method for electric bus charging and replacing power station - Google Patents

Site selection and equipment capacity optimization method for electric bus charging and replacing power station Download PDF

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CN113554239A
CN113554239A CN202110939679.0A CN202110939679A CN113554239A CN 113554239 A CN113554239 A CN 113554239A CN 202110939679 A CN202110939679 A CN 202110939679A CN 113554239 A CN113554239 A CN 113554239A
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charging
station
replacing
battery
electric bus
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吕应龙
段意强
符政鑫
许斯滨
许方园
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Guangdong University of Technology
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Guangdong University of Technology
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
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    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/12—Computing arrangements based on biological models using genetic models
    • G06N3/126—Evolutionary algorithms, e.g. genetic algorithms or genetic programming
    • 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
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Abstract

The invention discloses a method for optimizing site selection and equipment capacity of an electric bus charging and exchanging station, which comprises the following steps: acquiring operation data of the electric bus, and acquiring a location selection position variable of the charging and replacing station according to the operation data; establishing an electric bus running model, and calculating the number of battery replacing machines, chargers and standby batteries corresponding to the location selection position variables and a total cost function of the full life cycle; setting constraint conditions by taking the total cost function of the full life cycle as a target function to form a cost optimization model of the full life cycle; and optimizing the site selection position variable by using a genetic algorithm according to the full life cycle cost optimization model to obtain an optimal site selection position, wherein the number of corresponding battery replacing machines, chargers and standby batteries is used as an optimal value of the equipment capacity. According to the invention, on the premise of ensuring the normal operation of the electric bus, the location selection and the equipment capacity of the charging and exchanging station are optimized, so that the maximum utilization rate and the minimum cost of the charging and exchanging station are achieved, and the situations of facility idling and resource waste are avoided.

Description

Site selection and equipment capacity optimization method for electric bus charging and replacing power station
Technical Field
The invention relates to the technical field of traffic facility planning, in particular to a method for optimizing site selection and equipment capacity of an electric bus charging and exchanging station.
Background
The popularization of electric vehicles brings great challenges to the existing traffic infrastructure in cities, and a novel charging facility needs to be built to meet the charging requirements of the electric vehicles. The charging and replacing power station can provide charging service or quick replacement service for the power battery of the electric automobile, and compared with the charging station, the charging and replacing power station has the advantage that the electric automobile can be fully charged in a battery replacement mode in a short time. The charging and replacing station is very suitable for being used as a charging tool of an electric bus and an electric taxi, the vehicles belong to the company property, can be uniformly allocated, and use electric automobiles with uniform models, so that the charging and replacing station is specially used for the electric automobiles with the same models, and the working efficiency is improved.
Chinese patent application CN107031439A published in 2017, 8, and 11 provides a method for replacing batteries of electric buses running at night, wherein a charging device is arranged in a replacement station of a bus-returning yard, and the method is used for counting the electric quantity of the batteries of the buses when the buses exit and enter, the back-and-forth battery consumption of the buses and the remaining running shift n of the buses on the same day; the charging device is only arranged in a car-returning field, the address selection is unreasonable, and the normal operation of the electric bus cannot be satisfied; and the optimal scheme of the equipment capacity of the charging device is not specifically designed, so that facilities are idle, and resources are wasted.
Disclosure of Invention
The invention aims to overcome the defects of unreasonable site selection and equipment capacity of the charging and exchanging station in the prior art, and provides an optimization method of the site selection and the equipment capacity of the charging and exchanging station of the electric bus.
In order to solve the technical problems, the technical scheme of the invention is as follows:
the invention provides a method for optimizing site selection and equipment capacity of an electric bus charging and exchanging station, which comprises the following steps:
s1: acquiring operation data of the electric bus, and acquiring a location selection position variable of the charging and replacing station according to the operation data;
s2: establishing an electric bus running model, inputting operation data of the electric bus and an address selection position variable of a charging and replacing station, and calculating the equipment capacity corresponding to the address selection position variable of the charging and replacing station, namely the number of battery replacing machines, chargers and standby batteries;
s3: calculating a total life cycle cost function of the location position variable of the charging and replacing station according to the numbers of the battery replacing machines, the chargers and the standby batteries corresponding to the location position variable of the charging and replacing station;
s4: taking the total cost function of the full life cycle as a target function, and setting constraint conditions to form a cost optimization model of the full life cycle;
s5: optimizing the location selection position variable by using a genetic algorithm according to the full life cycle cost optimization model to obtain an optimal solution of the location selection position variable of the battery charging and replacing station, wherein the optimal solution is used as an optimal location selection position of the battery charging and replacing station;
s6: and taking the numbers of the battery replacing machine, the charger and the standby battery corresponding to the optimal address position of the charging and replacing station as the optimal value of the equipment capacity.
Preferably, the operation data of the electric bus comprises electric bus lines, total bus stop numbers, first-shift and last-shift departure time, departure interval time, number of times of departure in one day, distance between adjacent bus stops of the electric bus lines, running time between adjacent bus stops of the bus lines, serial numbers of the electric bus, battery capacity, low-power coefficient, battery replacing following operation time and simulation running days.
Preferably, the address selection position variable of the charging and replacing power station is recorded as Vec ═ x1 x2 x3 … xn]TWherein x isnRepresenting the nth bus stop, and the dimensionality is n multiplied by 1; the address selection position variable of the charging and replacing power station is expressed in a vector form, and each element represents the charging and replacing power station by using 0-1 discrete numbersAnd selecting an address, wherein 0 represents that the corresponding bus stop is not provided with a charging and replacing station, and1 represents that the corresponding bus stop is provided with the charging and replacing station.
If the total number of bus stops on the electric bus line is 5, the serial numbers of the bus stops are 1, 2, 3, 4 and5, the charging and replacing stations are arranged at the bus stop No. 1 and the bus stop No. 4, and the address selection position vector of the charging and replacing stations is Vec [ 10010 ]]T。
Preferably, the full lifecycle total cost function is specifically:
Figure BDA0003214340180000021
wherein sslcc represents the total cost function of the full lifecycle, sslccwRepresents the full life cycle cost of the w-th charging and switching station, ssn represents the total number of charging and switching stations, and pcwRepresenting the construction cost, mc, of the w-th charging and conversion station taking into account the capital recovery factorwRepresents the maintenance cost of the w-th charging and replacing station, ecywAnd the annual electricity utilization cost of the w-th charging and replacing power station is shown.
Preferably, the construction cost pc of the w-th charging and switching station considering the capital recovery factor is calculatedwThe specific hair-growing method comprises the following steps:
Figure BDA0003214340180000031
decw＝epv,w×pviaw×pvpc+ewt,w×swtc
pviaw＝fpvia(caw)
caw＝fca(smnw,cpnw,ebnw)
wherein, a represents interest rate, b represents service life of the charging and replacing power station; decwRepresents the construction cost, cc, of the distributed energy of the w-th charging and replacing stationwRepresenting the construction cost of the w-th charging and replacing power station; e.g. of the typepv,wDenotes a first decision coefficient, pviawSolar energy for showing w-th charging and replacing power stationPanel mounting area, pvpc represents the price per unit area of solar panel, ewt,wRepresenting a second judgment coefficient, wherein swtc represents the price of the wind driven generator; f. ofpvia(x) represents a calculation function of the installation area of the solar panel, cawRepresenting the building area of the w-th charging and replacing power station; f. ofca(. indicates) the building area calculation function, smnwIndicates the number of the battery changing machines of the w-th charging and changing station, cpnwIndicating the number of chargers in the w-th charging and replacing station, ebnwAnd the spare battery number of the w-th charging and replacing station is shown.
Preferably, the maintenance cost mc of the w-th charging and replacing power station is calculatedwThe specific hair-growing method comprises the following steps:
mcw＝fmc(smnw,cpnw,ebnw,caw,decw)
wherein f ismc(. indicates) maintenance cost calculation function, smnwIndicates the number of the battery changing machines of the w-th charging and changing station, cpnwIndicating the number of chargers in the w-th charging and replacing station, ebnwIndicates the number of standby batteries of the w-th charging and replacing station, cawIndicates the building area, ca, of the w-th charging and replacing stationwRepresents the building area, dec, of the w-th charging and replacing stationwRepresenting the construction cost of the distributed energy source of the w-th charging and replacing station.
Preferably, the annual electricity consumption cost ecy of the w-th charging and replacing power station is calculatedwThe specific hair-growing method comprises the following steps:
Figure BDA0003214340180000032
wherein ec isi,wThe electricity consumption cost of the w charging and replacing power station on the ith day is shown, and sdn represents the number of simulated operation days.
Preferably, the constraint condition includes a first constraint condition and a second constraint condition, and specifically includes:
the first constraint condition is: each electric bus line is provided with at least 1 charging and exchanging station;
the second constraint condition is as follows: the electric quantity of the battery unloaded by the electric bus is more than or equal to 0.
Preferably, in S5, the specific method for optimizing the location position variable according to the full life cycle cost optimization model by using the genetic algorithm to obtain the optimal solution of the location position variable of the battery charging and replacing station includes:
s51: setting an initial value of a genetic algorithm, comprising: the number of individuals nind, the iteration number gen, the chromosome crossing probability pc, the chromosome first variation probability pm1, the chromosome second variation probability pm2, the channel ggap and the constraint penalty coefficient punish; taking the address selection position variable of the charging and replacing station as an individual of the population;
s52: when the iteration number i is calculated to be 1, the fitness of each individual is as follows:
Figure BDA0003214340180000041
if the first constraint condition and the second constraint condition are simultaneously satisfied, the constraint penalty term conspun is 0; otherwise, the constraint penalty term conspun is punish;
traversing each individual, and calculating the fitness of each individual by using the same method until the number of the individuals is nind;
s53: determining the elite individuals by adopting a wheel disc degree method according to the fitness of each individual;
s54: crossing of Elite individuals:
generating a first random number rand1, rand1 ∈ (0, 1);
judging whether the chromosome crossing probability pc is greater than a first random number rand 1; if not, go to S55; otherwise, randomly pairing the elite individuals in the population pairwise to form c pairs;
generating a second random number rand2 and a third random number rand3, rand2 and rand3 belonging to the group (1, bstn), wherein the bstn represents the total number of bus stops;
judging whether the second random number rand2 is greater than the third random number rand 3; if so, exchanging numbers between (rand3, 1) to (rand2, 1) in the elite individual; otherwise, exchanging numbers between (rand2, 1) to (rand3, 1) in the elite individual;
traversing each pair of elite individuals until reaching c pairs, completing crossing of the elite individuals and obtaining (nind × ggap) elite individuals;
s55: variation of elite individuals;
s56: updating the population;
selecting nind individuals from the individuals in the population when the iteration number i is 1 and the crossed and mutated elite individuals as the individuals in the population at the next iteration;
s57: updating the iteration times, and calculating the fitness of each individual in the updated population until the iteration times gen are reached;
s58: and taking the individual with the highest fitness as the optimal solution of the addressing position variable of the charging and battery replacing station.
Preferably, the specific method for variation of elite individuals is as follows:
s551: generating a fourth random number rand4, rand4 belongs to (0, 1);
s552: judging whether the first variation probability pm1 of the chromosome is greater than a fourth random number rand 4; if so, the two positions are actually switched, and S553 is performed; otherwise, directly proceed to S553;
s553: generating a fifth random number rand5, rand5 belongs to (0, 1);
s554: judging whether the second mutation probability pm2 of the chromosome is greater than a fifth random number rand 5; if the absolute value is larger than the preset value, generating a sixth random number rand6, generating rand6 e (1, bstn), changing the number of the (ran6, 1) th bit in the elite individual, namely changing 0 to 1 or changing 1 to 0, and performing S555; otherwise, directly performing S555;
s555: and traversing each elite individual, and repeating S351-354 until (nind × ggap) elite individual variation is achieved.
Compared with the prior art, the technical scheme of the invention has the beneficial effects that:
the method comprises the steps of firstly, acquiring actual operation data of the electric bus, and acquiring a location selection position variable of a charging and replacing station according to the operation data; establishing an electric bus running model, and calculating the number of battery replacing machines, chargers and standby batteries corresponding to the address selection position variables of the charging and replacing station and the total life cycle cost; the method comprises the steps of taking a full life cycle total cost function as a target function, setting a constraint condition to form a full life cycle cost optimization model, optimizing an addressing position variable according to the full life cycle cost optimization model by utilizing a genetic algorithm to enable the full life cycle cost of a charging and switching station to be the lowest, taking the optimal solution of the corresponding addressing position variable as the optimal addressing position of the charging and switching station, and taking the number of corresponding battery switching machines, chargers and standby batteries as the optimal value of equipment capacity, so that the charging and switching station achieves the maximum utilization rate and the lowest cost, and the situations of facility idling and resource waste are avoided.
Drawings
Fig. 1 is a flowchart of an optimization method for site selection and device capacity of an electric bus charging and swapping station according to an embodiment.
Detailed Description
The drawings are for illustrative purposes only and are not to be construed as limiting the patent;
for the purpose of better illustrating the embodiments, certain features of the drawings may be omitted, enlarged or reduced, and do not represent the size of an actual product;
it will be understood by those skilled in the art that certain well-known structures in the drawings and descriptions thereof may be omitted.
The technical solution of the present invention is further described below with reference to the accompanying drawings and examples.
Examples
The embodiment provides a method for optimizing site selection and equipment capacity of an electric bus charging and exchanging station, as shown in fig. 1, the method includes:
s1: acquiring operation data of the electric bus, and acquiring a location selection position variable of the charging and replacing station according to the operation data;
the operation data of the electric bus comprises electric bus lines, the total number of bus stops, the departure time of the first shift and the last shift, the departure interval time, the number of times of departure in one day, the distance between the bus stops adjacent to the electric bus lines, the running time between the bus stops adjacent to the bus lines, the serial number of the electric bus, the battery capacity, the low-power coefficient, the battery replacing and following operation time and the simulation running days;
recording the variable of the location of charging and replacing power station as Vec ═ x1 x2 x3 … xn]TWherein x isnRepresenting the nth bus stop, and the dimensionality is n multiplied by 1; the location selection position variable of the charging and replacing station is expressed in a vector form, each element uses 0-1 discrete numbers to represent the location selection of the charging and replacing station, 0 represents that the corresponding bus stop is not provided with the charging and replacing station, and1 represents that the corresponding bus stop is provided with the charging and replacing station.
If the total number of bus stops on the electric bus line is 5, the serial numbers of the bus stops are 1, 2, 3, 4 and5, the charging and replacing stations are arranged at the bus stop No. 1 and the bus stop No. 4, and the variable quantity of the address selection position of the charging and replacing station is Vec (10010)]T；
S2: establishing an electric bus running model, inputting operation data of the electric bus and an address selection position variable of a charging and replacing station, and calculating the equipment capacity corresponding to the address selection position variable of the charging and replacing station, namely the number of battery replacing machines, chargers and standby batteries;
s21: establishing an electric bus running model, inputting the operation data and the address selection position variable of the charging and replacing station into the electric bus running model together, simulating the running of the electric bus, and obtaining the use data of the charging and replacing station; specifically, the method comprises the following steps:
s2101: setting the number binn of electric buses parked at the first station on the electric bus line j at nightj,w,(first)Number binn of electric buses parked at end station at nightj,w,(last)And initial electric quantity bp of the battery; wherein j represents the number of the electric bus line, the number of the w bus stop, first represents the first stop, and last represents the last stop;
s2102: judging whether a charging station is set at a first station on the electric bus line j; if the charging and exchanging station is set, executing S2103, otherwise executing S2104;
s2103: calculating the missing sum of the initial electric quantity of the batteries of all the electric buses parked at night on the first station of the electric bus line j, and recording the sum as bvtj,w,(first)(ii) a Charging all the electric buses parked at the first station on the electric bus line j at night to full power, namely the battery capacity bbc;
s2104: judging whether a charging station is set at the last station on the electric bus line j; if the charging and exchanging station is set, executing S2105, otherwise executing S2106;
s2105: calculating the sum of the loss of the battery electric quantity of all the electric buses stopped at the last station on the electric bus line j at night, and recording the sum as bvtj,w,(last)(ii) a Charging all electric buses parked at night on the last station of the electric bus line j to full power, namely the battery capacity bbc;
s2106: establishing an electric bus operating list Bustimable (i, j) (head → tail) and Bustimable (i, j) (tail → head); wherein, the Bustimable (i, j) (head → tail) represents the running condition of the electric bus from the head station to the tail station of the electric bus line j of the ith day, and the Bustimable (i, j) (tail → head) represents the running condition of the electric bus from the tail station to the head station of the electric bus line j of the ith day;
s2107: the number of departure shifts of the electric bus line j in one day is recorded as blsnjDetermining the operation data of the electric bus of the kth shift sent from the head station to the end station, and recording the operation data sent from the head station to the end station in an electric bus operation table Bustimable (i, j) (head → end); the operation data comprises an electric bus number, a departure time, battery electric quantity during departure, a battery replacement operation mark, a battery replacement position mark, the residual electric quantity of a replaced battery, a battery replacement operation starting time, a terminal arrival time, the electric quantity of the battery during the terminal arrival and a re-departure mark;
the following table is given as an example:
Figure BDA0003214340180000071
the 1 st line of data is the number of the electric bus; column 2 is departure time, in the present patent time example, 1 hour is converted to "1", and 5.3333 is 5 o' clock 20; column 3 is battery power at departure; column 4 is a battery replacement operation mark, where "1" represents that the battery of the electric bus is replaced in the current driving process, and "0" represents that the battery of the electric bus is not replaced in the current driving process; column 5 is a battery replacement position mark, which indicates that in the current driving process, the bus station where the battery of the electric bus is replaced is located, where "0" represents that the battery of the electric bus is not replaced in the current driving process, and "1" represents that the battery of the electric bus is replaced in the charging station of the bus station No. 1 in the current driving process; column 6 is the remaining capacity of the battery under replacement, and "0" indicates that the electric bus has not replaced the battery during the current driving; column 7 is the time when the battery replacement operation starts, "0" indicates that the electric bus has not replaced the battery during the current driving; column 8 is the time when the electric bus arrives at the end station on the bus operation line, in the embodiment of the patent, 1 hour is converted into '1'; the 9 th column is the electric quantity of the battery when the electric bus arrives at the end station; column 10 is a reissue flag indicating whether or not the electric bus has started from the end point after the electric bus reaches the end station of the current travel. If the electric bus starts from the first station to reach the last station and then starts from the last station to reach the first station, the reissue mark is set as '1', and if not, the reissue mark is set as '0';
s2108: according to the electric bus operation table burstification (i, j) (head → head), basic operation data of the k-th shift electric bus sent from the last station to the head station is determined and recorded in the electric bus operation table burstification (i, j) (head → head), specifically:
s210801: searching whether the running data sent from the head station to the end station exists in the electric bus running table (i, j) (head → end) or not, wherein the running data meets the condition that the time of arriving at the end station is not later than the time of departure from the end station in the kth shift and the electric bus which is not departed from the end station exists; if yes, go to S210802; otherwise, S210803 is executed;
s210802: selecting the electric bus which meets the condition and has the earliest arrival time as the electric bus which is dispatched at the last station of the kth shift; executing S210804 if the re-departure flag of the electric bus in the electric bus operation table busy (i, j) (first → end) is set to 1;
the following table is given as an example:
Figure BDA0003214340180000081
if the departure time of the electric bus departing at the kth shift last station is 7 points, the 8 th line of data in the table shows that all the electric buses arrive at the last station before 7 points; in the 10 th column, however, only the electric bus in the 5 th row starts again and is marked as 0, which indicates that other electric buses start after reaching the last stop, only the electric bus in the 5 th row does not start, the selector is used as the electric bus which starts at the last stop of the kth shift, and the re-starting mark is set as 1;
s210803: selecting any electric bus parked at the last station at night as the electric bus dispatched from the last station of the kth shift, and executing S210804;
s210804: and taking the serial number of the electric bus which is selected as the electric bus which is dispatched from the last station of the kth shift and the battery electric quantity during dispatching as basic operation data of the electric bus which is dispatched from the last station to the first station of the kth shift.
S2109: simulating the driving process of the electric bus of the kth shift of the electric bus line j on the ith day according to the electric bus operation table bus (i, j) (head → tail) and the bus (i, j) (head → head), acquiring detailed operation data of the electric bus of the kth shift from the last station to the head station, and recording the detailed operation data in the electric bus operation table bus (i, j) (head → tail), wherein the detailed operation data comprises the following specific steps:
s210901: according to the departure time of the kth shift, searching the serial number of the electric bus departing from the last station of the kth shift and the battery capacity during departure in a bus running table Bustimable (i, j) (last → first);
s210902: calculating the running speed of the electric bus which is dispatched at the last station of the kth shift between two adjacent bus stations:
bvj,t,u→u+1＝dj,u→u+1÷ctj,t(k),u→u+1
wherein, bvj,t,u→u+1Represents the driving speed d of the electric bus from the bus stop u to the bus stop u +1 in the time period t of the electric bus line jj,u→u+1Represents the distance, ct, from the bus stop u to the bus stop u +1 in the electric bus line jj,t(k),u→u+1Represent the kth class of electric buses in the j time period t of the electric bus lineThe travel time from bus stop u to bus stop u + 1; the time period t is determined by the departure time of the kth shift, and when the departure time of the kth shift is between t and t +1 hour, the running time of the shift is classified into the time period t; if the departure time of the kth shift is 10 o 'clock and 20 minutes, the travel time of the shift is classified into a time period of 10 o' clock;
s210903: calculating the power consumption of the electric bus which is dispatched from the last station of the kth shift from the bus station u to the bus station u + 1:
cbpj,u→u+1＝dj,u→u+1×f(bvj,t,u→u+1)
wherein, cbpj,u→u+1Representing the electric quantity consumed by the electric bus from the bus stop u to the bus stop u +1 on the electric bus line j, wherein f (x) represents a speed-energy consumption calculation function;
s210904: calculating the battery electric quantity of the electric bus which is dispatched at the last station of the kth shift and arrives at the bus station u + 1:
bpj,u+1＝bp-cbpj,u→u+1
wherein, bpj,u+1The method comprises the steps that the battery electric quantity of an electric bus arriving at a bus stop u +1 on an electric bus line j is represented, and bp represents the initial battery electric quantity;
s210905: recording the total driving time of the electric bus which is dispatched from the last station of the kth shift as bdt, and setting the initial value of bdt as 0, then:
bdt＝bdt0+ctj,t(k),u→u+1
wherein, bdt0An initial value representing a total travel time of the electric bus;
s210906: judging whether a charging station is arranged at the bus station u +1 or not; if yes, executing S210907; otherwise, S210910 is executed;
s210907: battery electric quantity bp for judging whether electric bus reaches bus station u +1j,u+1Whether the battery capacity is less than lbpc multiplied by bbc, wherein lbpc represents a low battery coefficient, and bbc represents the battery capacity; if the difference is less than the preset value, the electric bus replaces the battery in the charging and replacing station, and the bp is orderedj,u+1Bbc, executing S210908; otherwise, S210910 is executed;
s210908: calculating the starting time of replacing the battery:
btsu+1＝bltk+bdt
wherein, btsu+1Indicating the start of a battery change at bus stop u +1, bltkRepresenting the departure time of the kth shift;
s210909: adding one time of battery replacement operation time in the total running time of the electric bus dispatched at the last station of the kth shift:
bdt＝bdt0+ctj,t(k),u→u+1+sct
wherein sct represents a battery change operation time;
s210910: updating the bus stop, traversing the bus stop on the electric bus line j of the kth shift, and executing steps S210901-S210909; when the bus stop is updated every time, the total running time of the last electric bus is used as an initial value for calculating the total running time of the next electric bus;
s210911: calculating the arrival time of the electric bus which is dispatched from the last station of the kth shift to the terminal station:
atj,k＝bltk+bdt
wherein, atj,kThe arrival time of the electric bus which sends the bus at the last station of the kth shift to the terminal station is shown;
s210912: and taking the bus stop number, the battery electric quantity, the battery replacement starting time, the battery replacement operation mark, the arrival time of arriving at the terminal station and the battery electric quantity of arriving at the terminal station four times when the electric bus performs the battery replacement operation as detailed operation data of the k-th shift of the electric bus from the last station to the first station.
S2110: simulating all electric buses of all shifts of all electric bus lines in the ith day to obtain operation tables of the electric buses, namely the bus (i, j) (head → tail) and the bus (i, j) (tail → head) as use data of the charging and replacing station;
s22: calculating the power load data of all the charging and swapping stations according to the use data of the charging and swapping stations;
the method specifically comprises the following steps:
s2201: establishing a charging load recording table Electrotyplad (i, w) of a w charging and replacing station on the ith day, recording charging power values of the charging and replacing stations at different time intervals in the day, wherein the time interval granularity is 1 minute, the dimension is 1440 multiplied by 1, and 1440 represents 1440 minutes in the day; setting the charging power of a charging device in the charging and replacing station as P, wherein the charger is constant in charging power, and the battery is dismounted from the electric bus to immediately start charging;
s2202: judging whether the w-th charging and replacing station is arranged at the first station or the last station of the corresponding electric bus line; if yes, go to S2203; otherwise, S2207 is performed;
s2203: according to the number binn of the electric buses parked at the first station on the electric bus line j at nightj,w,(first)Number binn of electric buses parked at end station at nightj,w,(last)Bvt sum of the loss of initial electric quantity of batteries of all electric buses parked at the head station at nightj,w,(first)Bvt sum of the loss of battery capacity of all electric buses parked at end station at nightj,w,(last)And calculating the night charging time of the first station and the last station of the electric bus line j on the ith day:
bflctj,w,(first)＝bvtj,w,(first)÷(P×binnj,w,(first))
bflctj,w,(last)＝bvtj,w,(last)÷(P×binnj,w,(last))
wherein, bflctj,w,(first)Represents the night charging time of the first station of the ith day electric bus line j, bflctj,w,(last)Representing night charging time of the last station of the ith electric bus line j;
s2204: recording night charging power at a position corresponding to an electric capacity load (i, w) in a charging load recording table according to night charging time of a first station and a last station of an electric bus line j on the ith day;
suppose that: p50 kW, binnj,w,(first)＝4，bvtj,w,(last)When the departure time of the first shift of the electric bus line j is 5 points, the bflct is 300kWhj,w,(first)1.5 h; according to bflctj,w,(first)And the departure time of the first shift is known, the night charging time from 3 o ' clock to 30 o ' clock to 5 o ' clock is obtained, and the charging power is P x bin nj,w,(first)＝200kW；1440 rows of the charging load record table electrocotyload (i, w) each represents 1 minute, and when the 211 th row to 300 th row of the charging load record table electrocotyload (i, w) represent nighttime charging, the charging power of 200kw is added to the positions of the 211 th row to 300 th row;
s2205: searching the shift of battery replacement operation at the w-th charging and replacing station in the electric bus operation table (i, j) of all the bus lines in the ith day, and recording the total number of battery replacement operation as blssn;
s2206: setting r to represent the operation times of battery replacement, wherein r belongs to [0, blssn ];
s2207: searching the battery replacement starting time corresponding to the r-th battery replacement operation and the battery electric quantity reaching the station in the electric bus operation table robust (i, j) of all the bus lines in the ith day;
s2208: and (3) calculating the full charge time and the charging completion time of the battery to be unloaded in the r-th battery replacing operation:
Figure BDA0003214340180000111
fcbtr＝btsr+sct+pcbtr
wherein, pcbtrIndicating the full time for discharging the battery in the r battery replacing operation; bp of bprRepresenting the electric quantity of the unloaded battery in the r-th battery replacing operation, and determining the bus line j and the bus stop u +1, bp where the r-th battery replacing operation is positionedr＝bpj,u+1；
fcbtrIndicates the discharge completion time of the battery charge in the r-th battery replacement operation btsrRepresenting the starting time of the r time of battery replacement operation, and determining a bus line j and bus stops u +1, bts where the r time of battery replacement operation is positionedr＝btsu+1；
S2209: according to the full charge time and the charging completion time of the battery being unloaded in the r-th battery replacement operation, recording the charging power of the battery replacement operation at a position corresponding to a charging load recording table electric load (i, w), wherein the charging load data recorded in the charging load recording table electric load (i, w) is the electricity load data of the charging and replacing power station;
s2210: updating the battery replacement operation times r, traversing the battery replacement operation times r, and executing the steps S2207-S2209 until the total battery replacement operation number blssn is reached;
s2211: and setting the total number of the charging and replacing stations as ssn, updating the charging and replacing station w, traversing the charging and replacing station w, and executing the steps S2201-S2210 until the total number of the replacing stations ssn is reached.
S23: calculating the number of battery replacing motors, chargers and standby batteries of the charging and replacing station according to the power load data of the charging and replacing station;
the method specifically comprises the following steps:
s2301: a first battery replacement record table Swapnote1 is constructed, records of battery replacement operations at the w-th charging and replacing station are searched in the electric bus operation table Bustimable (i, j) of all bus routes in the i-th day, and the battery replacement starting time and the battery unloading electric quantity corresponding to each battery replacement operation are recorded in Swapnote 1; the row number of Swapnote1 is determined by the number of times of battery replacement operation performed by the w-th charging and replacing station on the ith day, and the column number is 3; the battery replacement starting time recorded in column 1 of Swapnote1, the battery removal capacity recorded in column 2, and the value set in column 3 is 0;
s2302: the recorded contents in the Swapnote1 are arranged in an ascending order according to the starting time of replacing the battery;
s2303: setting the theoretical number of spare batteries of the w charging and replacing power station on the ith day to ebni,w' then ebni,w' is equal to the number of rows of Swapnote1, and v is set to represent the v th row of Swapnote1, v e [1, ebni,w′-1]；
The number of times of battery replacement operation performed by the w-th charging and replacing station on the ith day is the number of rows of Swapnote1, and the theoretical number of spare batteries is ebni,wThe numerical value is equal to the number of rows of Swapnote1, which means that each time the batteries are replaced, the replaced batteries are all the batteries prepared in advance in the same day charging station; however, in actual operation, the electric buses of the following shift can be replaced by the electric buses of the previous shift after the batteries unloaded by the electric buses of the previous shift are fully charged, and only the protection is neededThe charging completion time of the battery unloaded from the previous shift is earlier than the arrival time of the next shift;
s2304: calculating the battery discharging charging completion time of the battery replacing operation corresponding to the v-th row of Swapnote 1:
Figure BDA0003214340180000121
wherein bcftvA discharged battery charge completion time indicating a battery replacement operation corresponding to the v-th row; swapnote1(v,1) indicates the record data of Swapnote1 line v, column 1, namely the time when the battery is replaced; swapnote1(v,2) indicates the record data of Swapnote1 line v and column 2, namely the power of the unloaded battery;
s2305: finding a battery replacement start time greater than bcft for column 1 record in Swapnot1vCorresponding battery replacement operation, and recording the minimum number of lines as minus1(ii) a If the battery replacement starting time is not greater than bcftvCorresponding to the battery replacement operation, the micro1Set to 0;
in this embodiment, when the battery of the electric bus needs to be replaced, the battery is replaced immediately after arriving at the station, that is, the arrival time is equal to the battery replacement start time, and the battery replacement start time is greater than bcftvThe time when the battery is replaced in the shift is later than the time when the battery is dismounted and the charging is finished, the fully charged battery can be replaced; when a certain shift meets the condition, the shift arriving later also meets the condition, and as Swapnote1 is arranged in ascending order according to the start time of battery replacement, the battery replacement is started from the shift with the minimum number of rows, that is, the electric bus arriving first replaces the battery first when the condition is met;
s2306: judging minimum1Whether or not it is 0; if not, executing S2307; if yes, go to S2311;
s2307: judgment Swapnote1 (minor)13) whether or not 0, Swapnote1 (minor)13) indicates the minimum in Swapnote11Data recorded in row 3 column; if yes, go to S2308; if not, executing S2309;
s2308: swapnote1 (minrow)13) set to 1, S2311 is performed;
firstly, whether the battery replacement starting time is larger than bcft is judgedvIf the shift (min 1 ≠ 0) exists, whether the battery replacement operation has been performed is judged again (Swapnote1 (min)13) is 0), the initial value of Swapnote1 column 3 is 0, which indicates that all the shift has not performed battery replacement operation, and when Swapnote1 column 3 is set to 1, which indicates that the shift has performed 1 battery replacement operation;
s2309: greater than bcft at the start of the remaining battery replacementvSearching the minimum line number in the corresponding battery replacing operation, and updating the minimum line number1；
When the battery of the electric bus which arrives at the station earliest and meets the condition is replaced, selecting the shift which arrives at the station earliest from the rest electric buses which meet the condition to replace the battery;
s2310: determining the updated minimum1Whether or not greater than ebni,zIf yes, go to S2311; otherwise, return to S2307, at which point Swapnote1 (minus)1Minrow in, 3)1To be updated minrow1；
The step is to judge whether all the electric buses meeting the conditions are searched;
s2311: updating the number v of rows of Swapnote1, traversing the number v of rows of Swapnote1, and executing the steps S2304-S2310 until the number v of rows reaches ebni,w′-1；
S2312: calculating the actual spare battery number ebn of the w charging and replacing power station on the ith dayi,z：
ebni,w＝ebni,w′-sum(Swapnote1(all,3))
Wherein sum (×) represents the summing operation, Swapnote1(all,3) represents all the data of Swapnote1 column 3;
summing all the data in the 3 rd column, wherein the obtained numerical value is the number of the batteries used by the late arrival electric bus and replaced by the early arrival electric bus, and the actual number of the batteries used in comparison can be obtained by subtracting the numerical value from the theoretical number of the standby batteries;
s2313: a second battery replacement record table Swapnote2 is constructed, records of battery replacement operations carried out at the w-th charging and replacing station are searched in the electric bus operation table Bustimable (i, j) of all the bus lines in the i-th day, and the battery replacement starting time corresponding to each battery replacement operation is recorded in Swapnote 2; the row number of Swapnote2 is determined by the number of times of battery replacement operation performed by the w-th charging and replacing station on the ith day, and the column number is 2; the time when the battery replacement starts recorded in column 1 of Swapnote1, the value in column 2 is set to 0;
s2314: the recorded contents in the Swapnote2 are arranged in an ascending order according to the starting time of replacing the battery;
s2315: setting the theoretical battery changing machine number of the w charging and changing station on the ith day to smni,w', then smni,w' is equal to the number of rows of Swapnote2, and setting x denotes the x-th row of Swapnote1, x ∈ [1, smni,w′-1]；
S2316: calculating the battery discharging charging completion time of the battery replacing operation corresponding to the x-th row of Swapnote 2:
bsftx＝Swapnote2(x,1)+sct
wherein bsftxA battery discharge completion time indicating a battery replacement operation corresponding to the x-th row; swapnote2(x,1) indicates record data of Swapnote2 row x, column 1, namely, the time of starting to replace the battery;
s2317: finding a battery replacement start time greater than bsft in Swapnot2 for column 1 recordsxCorresponding battery replacement operation, and recording the minimum number of lines as minus2(ii) a If the battery replacement starting time without the battery replacement operation is larger than bsftxCorresponding to the battery replacement operation, the micro2Set to 0;
s2318: judging minimum2Whether or not it is 0; if not, go to S2319; if yes, executing S2323;
s2319: judgment Swapnote2 (minor)22) whether or not 0, Swapnote2 (minor)22) indicates the minimum in Swapnote22Data recorded in row 2; if yes, executeS2320; if not, executing S2321;
s2320: swapnote2 (minrow)22) set to 1, S2323 is performed;
s2321: greater than bsft at the time of the start of the remaining replacement of the batteryxSearching the minimum line number in the corresponding battery replacing operation, and updating the minimum line number2；
S2322: determining the updated minimum2Whether is greater than smni,w' if yes, go to S2323; otherwise, return to S2319, at which time Swapnote2 (minus)2Minrow in 2)2To be updated minrow2；
S2323: updating the number x of lines of the Swapnote2, traversing the number x of lines of the Swapnote2, and executing the steps S2316-S2322 until the number x of lines reaches smni,w′-1；
S2324: calculating the actual number smn of battery changing machines of the w charging and changing station on the ith dayi,w：
smni,w＝smni,w′-sum(Swapnote2(all,2))
Wherein sum (×) represents the summing operation, Swapnote (all,2) represents all the data of column 2 of Swapnote 2;
s2325: updating the simulation operation days i, traversing the simulation operation days i, and executing the steps S2301-S2324 until the simulation operation days i reach the set maximum value sdn;
s2326: calculating the number of standby batteries of the w-th charging and replacing station:
Figure BDA0003214340180000151
wherein, ebnwRepresenting the number of standby batteries of the w-th charging and replacing station;
s2327: calculating the number of battery changing machines of the w-th charging and changing station:
Figure BDA0003214340180000152
wherein, smnwIndicates the w-th charge and dischargeThe number of battery changing machines of the power station;
s2328: calculating the number of chargers of the w-th charging and replacing station:
cpnw＝ebnw
wherein cpnwAnd represents the number of the w-th charging station chargers.
S3: calculating a total life cycle cost function of the location position variable of the charging and replacing station according to the numbers of the battery replacing machines, the chargers and the standby batteries corresponding to the location position variable of the charging and replacing station;
s4: taking the total cost function of the full life cycle as a target function, and setting constraint conditions to form a cost optimization model of the full life cycle;
the total life cycle cost function is specifically:
Figure BDA0003214340180000161
wherein sslcc represents the total cost function of the full lifecycle, sslccwRepresents the full life cycle cost of the w-th charging and switching station, ssn represents the total number of charging and switching stations, and pcwRepresenting the construction cost, mc, of the w-th charging and conversion station taking into account the capital recovery factorwRepresents the maintenance cost of the w-th charging and replacing station, ecywRepresenting the annual electricity consumption cost of the w-th charging and replacing power station;
the construction cost pc of the w-th charging and switching station considering capital recovery factorwThe method specifically comprises the following steps:
Figure BDA0003214340180000162
decw＝epv,w×pviaw×pvpc+ewt,w×swtc
pviaw＝fpvia(caw)
caw＝fca(smnw,cpnw,ebnw)
wherein, a represents interest rate, b represents service year of charging and replacing power stationLimiting; decwRepresents the construction cost, cc, of the distributed energy of the w-th charging and replacing stationwRepresenting the construction cost of the w-th charging and replacing power station; e.g. of the typepv,wDenotes a first decision coefficient, pviawShowing the installation area of the solar panel of the w-th charging and replacing station, pvpc showing the price of the solar panel per unit area, ewt,wRepresenting a second judgment coefficient, wherein swtc represents the price of the wind driven generator; f. ofpvia(x) represents a calculation function of the installation area of the solar panel, cawRepresenting the building area of the w-th charging and replacing power station; f. ofca(. indicates) the building area calculation function, smnwIndicates the number of the battery changing machines of the w-th charging and changing station, cpnwIndicating the number of chargers in the w-th charging and replacing station, ebnwRepresenting the number of standby batteries of the w-th charging and replacing station;
maintenance cost mc of the w-th charging and replacing power stationwThe method specifically comprises the following steps:
mcw＝fmc(smnw,cpnw,ebnw,caw,decw)
wherein f ismc(. indicates) maintenance cost calculation function, smnwIndicates the number of the battery changing machines of the w-th charging and changing station, cpnwIndicating the number of chargers in the w-th charging and replacing station, ebnwIndicates the number of standby batteries of the w-th charging and replacing station, cawIndicates the building area, ca, of the w-th charging and replacing stationwRepresents the building area, dec, of the w-th charging and replacing stationwRepresenting the construction cost of the distributed energy resources of the w-th charging and replacing station;
annual electricity utilization cost ecy of the w-th charging and replacing power stationwThe method specifically comprises the following steps:
Figure BDA0003214340180000171
wherein ec isi,wRepresenting the electricity consumption cost of the w charging and replacing power station on the ith day, and sdn represents the number of simulated operation days;
the constraint conditions include a first constraint condition and a second constraint condition, and specifically include:
the first constraint condition is: each electric bus line is provided with at least 1 charging and exchanging station;
the second constraint condition is as follows: the electric quantity of the battery unloaded by the electric bus is more than or equal to 0.
S5: optimizing the location selection position variable by using a genetic algorithm according to the full life cycle cost optimization model to obtain an optimal solution of the location selection position variable of the battery charging and replacing station, wherein the optimal solution is used as an optimal location selection position of the battery charging and replacing station;
s51: setting an initial value of a genetic algorithm, comprising: the number of individuals nind, the iteration number gen, the chromosome crossing probability pc, the chromosome first variation probability pm1, the chromosome second variation probability pm2, the channel ggap and the constraint penalty coefficient punish; taking the address selection position variable of the charging and replacing station as an individual of the population;
s52: when the iteration number i is calculated to be 1, the fitness of each individual is as follows:
Figure BDA0003214340180000172
if the first constraint condition and the second constraint condition are simultaneously satisfied, the constraint penalty term conspun is 0; otherwise, the constraint penalty term conspun is punish;
traversing each individual, and calculating the fitness of each individual by using the same method until the number of the individuals is nind;
s53: determining the elite individuals by adopting a wheel disc degree method according to the fitness of each individual;
s54: crossing of Elite individuals:
generating a first random number rand1, rand1 ∈ (0, 1);
judging whether the chromosome crossing probability pc is greater than a first random number rand 1; if not, go to S35; otherwise, randomly pairing the elite individuals in the population pairwise to form c pairs;
generating a second random number rand2 and a third random number rand3, rand2 and rand3 belonging to the group (1, bstn), wherein the bstn represents the total number of bus stops;
judging whether the second random number rand2 is greater than the third random number rand 3; if so, exchanging numbers between (rand3, 1) to (rand2, 1) in the elite individual; otherwise, exchanging numbers between (rand2, 1) to (rand3, 1) in the elite individual;
traversing each pair of elite individuals until reaching c pairs, completing crossing of the elite individuals and obtaining (nind × ggap) elite individuals;
s55: variation of elite individuals;
s551: generating a fourth random number rand4, rand4 belongs to (0, 1);
s552: judging whether the first variation probability pm1 of the chromosome is greater than a fourth random number rand 4; if so, the two positions are actually switched, and S553 is performed; otherwise, directly proceed to S553;
s553: generating a fifth random number rand5, rand5 belongs to (0, 1);
s554: judging whether the second mutation probability pm2 of the chromosome is greater than a fifth random number rand 5; if the absolute value is larger than the preset value, generating a sixth random number rand6, generating rand6 e (1, bstn), changing the number of the (ran6, 1) th bit in the elite individual, namely changing 0 to 1 or changing 1 to 0, and performing S555; otherwise, directly performing S555;
s555: and (5) traversing each elite individual, and repeating S551-554 until (nind × ggap) elite individual variation is achieved.
S56: updating the population;
selecting nind individuals from the individuals in the population when the iteration number i is 1 and the crossed and mutated elite individuals as the individuals in the population at the next iteration;
s57: updating the iteration times, and calculating the fitness of each individual in the updated population until the iteration times gen are reached;
s58: and taking the individual with the highest fitness as the optimal solution of the addressing position variable of the charging and battery replacing station.
S6: and taking the numbers of the battery replacing machine, the charger and the standby battery corresponding to the optimal address position of the charging and replacing station as the optimal value of the equipment capacity.
In this embodiment, the data of the total cost of the full life cycle of all the charging and replacing power stations is obtained by the following method:
calculating the building area of the w-th charging and replacing power station:
caw＝fca(smnw,cpnw,ebnw)
wherein, cawRepresents the building area of the w-th charging and replacing power station, fca() represents a building area calculation function;
in this embodiment, only the building area of the charging and replacing power station is considered as a function of the number of battery replacing machines, chargers and batteries in the charging and replacing power station;
calculating the construction cost of the w-th charging and replacing power station:
ccw＝fcc(smnw,cpnw,ebnw,caw)
wherein, ccwRepresents the construction cost of the w-th charging and replacing station, fcc() represents a construction cost calculation function;
calculating the electricity charge ec of the w charging and replacing power station in the ith dayi,w：
eci,w＝ECTi,w×Electricitygeneration(i,w)
Wherein, ECTi,wThe electricity price of the w charging and replacing power station in the ith day is represented, and the dimension is 1 x 1440;
the electric generation (i, w) is a distributed energy power generation meter of the w charging and replacing station on the ith day, and is calculated by the following formula:
Electricitygeneration(i,w)＝Electricityload(i,w)-DEPw
DEPw＝epv,w×fpv(ULIDw)×pviaw+ewt,w×fwt(WSDw)
epv,wdenotes a first decision coefficient, fpvRepresenting the calculation function of the generated power of the solar panel, ULIDwRepresenting the unit area illumination intensity data of the area where the w-th charging and replacing station is located; e.g. of the typewt,wDenotes a second determination coefficient, fwtRepresenting the calculation function of the generated power of the wind turbine, WSDwAnd representing the wind speed data of the area where the w-th charging and replacing power station is located.
In this embodiment, the charging and replacing power station mayInstalling a solar panel and a wind driven generator, but considering whether the place where the charging and replacing power station is located is suitable for generating power by using the distributed energy sources; therefore, the unit area illumination intensity data and the wind speed data of the area where the charging and replacing station is located need to be obtained to judge whether the distributed energy sources are suitable for power generation, and when the unit area illumination intensity data is excellent, the first judgment coefficient e is usedpv,wSetting the value to be 1, which indicates that the solar cell panel is suitable to be installed, or setting the value to be 0, which indicates that the solar cell panel is not suitable to be installed; when the wind speed data is excellent, the second determination coefficient ewt,wSetting the number to be 1 to indicate that the wind driven generator is suitable for installation, otherwise, setting the number to be 0 to indicate that the wind driven generator is not suitable for installation;
the embodiment has the following advantages:
(1) according to actual operation data of the electric buses on the existing electric bus line, charging and switching are arranged, and an electric bus running model is established. The method comprises the following steps that a model is used for simulating the running condition of electric buses with the same model on an electric bus line, wherein the most concerned is the battery power consumption condition of the electric buses, namely the use data of a charging station;
(2) in the embodiment, the charging and replacing stations can be arranged at the terminal stations (the head station and the tail station) of the electric bus line, when the electric bus is not in operation time, the electric bus stopped at the terminal stations can fully charge the electric quantity of the battery at low electricity price at night, and the electric quantity of the battery is fully charged when the bus is dispatched the next day;
(3) in the embodiment, the illumination and wind power conditions of the place where the charging and replacing station is located are considered, the solar cell panel and/or the wind driven generator are/is installed, and the battery is charged by utilizing distributed energy, so that the energy is saved;
(4) in the embodiment, the actual operation condition of the electric bus, the construction cost of the charging and replacing station, the maintenance cost of the charging and replacing station and the electricity consumption cost of the charging and replacing station are considered, the site selection position and the equipment capacity of the charging and replacing station are optimized by using a genetic algorithm, the optimal site selection position, the battery replacing machine, the charger and the optimal number of the standby batteries are obtained, the full life cycle cost of the charging and replacing station is the lowest on the premise that the normal operation of the electric bus is met, the construction cost and the maintenance cost are saved, the maximum utilization rate and the minimum cost of the charging and replacing station are achieved, and the situations that facilities are idle and resources are wasted are avoided.
It should be understood that the above-described embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the embodiments of the present invention. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the claims of the present invention.

Claims (10)

1. A method for optimizing site selection and equipment capacity of an electric bus charging and replacing station is characterized by comprising the following steps:
s1: acquiring operation data of the electric bus, and acquiring a location selection position variable of the charging and replacing station according to the operation data;
s2: establishing an electric bus running model, inputting operation data of the electric bus and an address selection position variable of a charging and replacing station, and calculating equipment capacity corresponding to the address selection position variable of the charging and replacing station, namely the number of battery replacing machines, chargers and standby batteries;
s3: calculating a total life cycle cost function of the location position variable of the charging and replacing station according to the numbers of the battery replacing machines, the chargers and the standby batteries corresponding to the location position variable of the charging and replacing station;
s4: taking the total cost function of the full life cycle as a target function, and setting constraint conditions to form a cost optimization model of the full life cycle;
s5: optimizing the location selection position variable by using a genetic algorithm according to the full life cycle cost optimization model to obtain an optimal solution of the location selection position variable of the battery charging and replacing station, wherein the optimal solution is used as an optimal location selection position of the battery charging and replacing station;
s6: and taking the numbers of the battery replacing machine, the charger and the standby battery corresponding to the optimal address position of the charging and replacing station as the optimal value of the equipment capacity.
2. The method as claimed in claim 1, wherein the operation data of the electric bus includes electric bus route, total number of bus stops, first and last departure times, departure interval time, number of departure times in one day, distance between adjacent bus stops of the electric bus route, running time between adjacent bus stops of the bus route, number of electric bus, battery capacity, low battery factor, battery following operation time and simulation running days.
3. The method as claimed in claim 2, wherein the location of the charging and replacing station and the optimization of the device capacity are described as Vec ═ x1 x2 x3 … xn]TWherein x isnRepresenting the nth bus stop, and the dimensionality is n multiplied by 1; the location selection position variable of the charging and replacing station is expressed in a vector form, each element uses 0-1 discrete numbers to represent the location selection of the charging and replacing station, 0 represents that the corresponding bus stop is not provided with the charging and replacing station, and1 represents that the corresponding bus stop is provided with the charging and replacing station.
4. The method for optimizing location and equipment capacity of an electric bus charging and exchanging station as claimed in claim 3, wherein the full life cycle total cost function is specifically:
Figure FDA0003214340170000021
wherein sslcc represents the total cost function of the full lifecycle, sslccwRepresents the full life cycle cost of the w-th charging and switching station, ssn represents the total number of charging and switching stations, and pcwRepresenting the construction cost, mc, of the w-th charging and conversion station taking into account the capital recovery factorwRepresents the maintenance cost of the w-th charging and replacing station, ecywAnd the annual electricity utilization cost of the w-th charging and replacing power station is shown.
5. Method for optimizing site selection and equipment capacity of electric bus charging and swapping stations according to claim 4, characterized in that the construction cost pc of the w-th charging and swapping station considering the capital recovery factorwThe method specifically comprises the following steps:
Figure FDA0003214340170000022
decw＝epv,w×pviaw×pvpc+ewt,w×swtc
pviaw＝fpvia(caw)
caw＝fca(smnw,cpnw,ebnw)
wherein, a represents interest rate, b represents service life of the charging and replacing power station; decwRepresents the construction cost, cc, of the distributed energy of the w-th charging and replacing stationwRepresenting the construction cost of the w-th charging and replacing power station; e.g. of the typepv,wDenotes a first decision coefficient, pviawShowing the installation area of the solar panel of the w-th charging and replacing station, pvpc showing the price of the solar panel per unit area, ewt,wRepresenting a second judgment coefficient, wherein swtc represents the price of the wind driven generator; f. ofpvia(x) represents a calculation function of the installation area of the solar panel, cawRepresenting the building area of the w-th charging and replacing power station; f. ofca(. indicates) the building area calculation function, smnwIndicates the number of the battery changing machines of the w-th charging and changing station, cpnwIndicating the number of chargers in the w-th charging and replacing station, ebnwAnd the spare battery number of the w-th charging and replacing station is shown.
6. The method as claimed in claim 5, wherein the maintenance cost mc of the w-th charging and replacing station iswThe method specifically comprises the following steps:
mcw＝fmc(smnw,cpnw,ebnw,caw,decw)
wherein f ismc(. indicates) maintenance cost calculation function, smnwIndicates the number of the battery changing machines of the w-th charging and changing station, cpnwIndicating the number of chargers in the w-th charging and replacing station, ebnwIndicates the number of standby batteries of the w-th charging and replacing station, cawIndicates the building area, ca, of the w-th charging and replacing stationwRepresents the building area, dec, of the w-th charging and replacing stationwRepresenting the construction cost of the distributed energy source of the w-th charging and replacing station.
7. The method as claimed in claim 6, wherein the annual energy cost ecy of the w-th charging and replacing station is determined by the location and equipment capacity optimization methodwThe method specifically comprises the following steps:
Figure FDA0003214340170000031
wherein ec isi,wThe electricity consumption cost of the w charging and replacing power station on the ith day is shown, and sdn represents the number of simulated operation days.
8. The method for optimizing location and equipment capacity of an electric bus charging and exchanging station according to claim 1, wherein the constraint condition includes a first constraint condition and a second constraint condition, and specifically includes:
the first constraint condition is: each electric bus line is provided with at least 1 charging and exchanging station;
the second constraint condition is as follows: the electric quantity of the battery unloaded by the electric bus is more than or equal to 0.
9. The method for optimizing the location and the equipment capacity of the electric bus charging and exchanging station according to claim 1, wherein in S5, the location position variables are optimized by using a genetic algorithm according to the full life cycle cost optimization model, and a specific method for obtaining the optimal solution of the location position variables of the charging and exchanging station is as follows:
s51: setting an initial value of a genetic algorithm, comprising: the number of individuals nind, the iteration number gen, the chromosome crossing probability pc, the chromosome first variation probability pm1, the chromosome second variation probability pm2, the channel ggap and the constraint penalty coefficient punish; taking the address selection position variable of the charging and replacing station as an individual of the population;
s52: when the iteration number i is calculated to be 1, the fitness of each individual is as follows:
Figure FDA0003214340170000032
if the first constraint condition and the second constraint condition are simultaneously satisfied, the constraint penalty term conspun is 0; otherwise, the constraint penalty term conspun is punish;
traversing each individual, and calculating the fitness of each individual by using the same method until the number of the individuals is nind;
s53: determining the elite individuals by adopting a wheel disc degree method according to the fitness of each individual;
s54: crossing of Elite individuals:
generating a first random number rand1, rand1 ∈ (0, 1);
judging whether the chromosome crossing probability pc is greater than a first random number rand 1; if not, go to S35; otherwise, randomly pairing the elite individuals in the population pairwise to form c pairs;
generating a second random number rand2 and a third random number rand3, rand2 and rand3 belonging to the group (1, bstn), wherein the bstn represents the total number of bus stops;
judging whether the second random number rand2 is greater than the third random number rand 3; if so, exchanging numbers between (rand3, 1) to (rand2, 1) in the elite individual; otherwise, exchanging numbers between (rand2, 1) to (rand3, 1) in the elite individual;
traversing each pair of elite individuals until reaching c pairs, completing crossing of the elite individuals and obtaining (nind × ggap) elite individuals;
s55: variation of elite individuals;
s56: updating the population;
selecting nind individuals from the individuals in the population when the iteration number i is 1 and the crossed and mutated elite individuals as the individuals in the population at the next iteration;
s57: updating the iteration times, and calculating the fitness of each individual in the updated population until the iteration times gen are reached;
s58: and taking the individual with the highest fitness as the optimal solution of the addressing position variable of the charging and battery replacing station.
10. The method for optimizing site selection and equipment capacity of the electric bus charging and exchanging station according to claim 9, wherein the concrete method for variation of elite individuals is as follows:
s551: generating a fourth random number rand4, rand4 belongs to (0, 1);
s552: judging whether the first variation probability pm1 of the chromosome is greater than a fourth random number rand 4; if so, the two positions are actually switched, and S553 is performed; otherwise, directly proceed to S553;
s553: generating a fifth random number rand5, rand5 belongs to (0, 1);
s554: judging whether the second mutation probability pm2 of the chromosome is greater than a fifth random number rand 5; if the absolute value is larger than the preset value, generating a sixth random number rand6, generating rand6 e (1, bstn), changing the number of the (ran6, 1) th bit in the elite individual, namely changing 0 to 1 or changing 1 to 0, and performing S555; otherwise, directly performing S555;
s555: and (5) traversing each elite individual, and repeating S551-554 until (nind × ggap) elite individual variation is achieved.
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