CN115100896B - Electric demand response bus dispatching method considering opportunity charging strategy - Google Patents
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Abstract
The invention discloses an electric demand response bus dispatching method considering an opportunity charging strategy. And distributing the passenger destination to different lines based on the passenger destination, combining the lines, distributing the lines to different electric buses for operation, and deciding a charging strategy of a continuous operation line on which the quick charging pile station is arranged. And updating the passenger allocation scheme by adopting a variable neighborhood searching algorithm, so as to obtain a better operation and charging plan and obtain a final electric demand response bus driving route and schedule. The method realizes that a plurality of continuous lines are utilized to be charged in the departure gap each time, and the charging time is determined according to the requirements of passengers, so that the effect of maximizing the productivity under the limited fleet scale is achieved, and the electric performance of demand response buses is enabled to exert the greatest benefit.
Description
Technical Field
The invention relates to the technical field of electric demand response bus dispatching considering charge and discharge, in particular to an electric demand response bus dispatching method considering an opportunity charging strategy.
Background
In recent years, the problems of energy shortage and environmental pollution caused by the development of urban traffic are increasingly prominent, and urban traffic systems are rapidly developed for relieving the situation. The electric bus has the advantages of low operation cost, less pollution, quick deployment, convenient maintenance and the like, and the electrified use can effectively solve the problems of energy shortage and environmental pollution. The electric demand response bus is used as a personalized flexible bus operation mode, passenger travel demand information and electric bus initial position information can be acquired through an artificial intelligence technology, an Internet of things technology and big data service before operation, an electric demand response bus dispatching model with operation plans and charging plans being cooperatively optimized is further constructed, passenger destinations are distributed to different lines, the lines are combined and distributed to different electric buses for operation, optimal dispatching of vehicles is achieved, most reasonable allocation of operation capacity is achieved, charging strategies on continuous operation lines with rapid charging pile stations are arranged are decided, and therefore the electric benefit of the demand response bus is exerted to the greatest extent.
The existing electric demand response buses are mostly based on the technical means of artificial intelligence technology, internet of things technology, big data technology and the like to analyze the operation and line passenger flow rules of the buses, so that the operation scheduling of the electric demand response buses is realized. However, in the prior art, the following disadvantages exist in the complicated electric demand response bus dispatching design method considering the opportunistic charging strategy:
1. in the operation scheduling of the conventional electric buses, the charging plans of the electric buses are generally arranged based on a constant schedule, so that the influence of the endurance mileage on the operation schedule of the electric buses is minimized, but the conventional electric buses cannot flexibly adjust the charging plans according to the requirements of passengers, so that the optimization of the conventional electric buses has a limited space;
2. in the existing electric demand response bus system, a charging strategy of partial charging and full charging is considered, and a charging plan is combined with an operation plan, but electric quantity is required to be supplemented by deliberately bypassing a charging station or a power exchange station in the operation process, so that a vehicle cannot be put into operation scheduling during charging, and the utilization rate of the electric demand response bus is reduced;
3. In recent years, a plurality of charging piles are arranged at electric bus stations, so that quick power supply can be realized in a short time in an operation gap in a quick charging mode, but the power supply strategy only considers the electric quantity required by a single journey, and ignores the electric quantity required by a journey connected with the electric bus stations, so that the charging strategy is single, and the opportunity charging strategy cannot be combined with an operation plan more efficiently.
Therefore, how to provide an efficient opportunistic charging strategy, so that an operation plan and a charging plan are tightly combined, and the maximum benefit of giving play to the electric demand response bus under the limited fleet size is a problem to be solved by those skilled in the art.
Disclosure of Invention
The invention provides an electric demand response bus dispatching method considering an opportunity charging strategy, which is based on the technical means of artificial intelligence technology, internet of things technology, big data technology and the like, acquires passenger travel demand information and electric bus initial position information before operation of an electric demand response bus, builds an electric demand response bus dispatching model with cooperative optimization of an operation plan and a charging plan.
In order to achieve the above object, the technical scheme of the present invention is as follows:
an electric demand response bus dispatching method considering an opportunity charging strategy comprises the following steps:
step 1: acquiring passenger travel demand information and electric bus initial position information, wherein the passenger travel demand information comprises the number of passengers on demand points, passenger destinations and expected riding time, the electric bus initial position information comprises initial positions of electric buses distributed at different stations, a total objective function capable of minimizing operation cost and charging cost is constructed, and the total objective function is initialized by combining an electric demand response bus operation experience value and charging and discharging characteristics so as to obtain initialized electric demand response bus operation parameters, battery parameters, power consumption coefficients and charging rates;
the total objective function comprises five items, wherein the first item is the fixed use cost of each electric demand response bus; the second term is the electric demand response bus fixed departure cost; the third term is the cost of punishing the waiting time of passengers of the electric demand response buses; the fourth item is the operation time cost of the electric demand response bus; the fifth item is the charging cost of the electric demand response bus;
Step 2: according to the passenger destination, under the condition of meeting the constraint of passenger capacity and battery capacity, acquiring an initial driving route of each electric bus;
step 3: according to the initial driving route, determining a charging strategy of the electric buses after arriving at the station to determine whether charging is needed, charging time and waiting time after full charging, and generating an initial timetable of each electric bus corresponding to the initial driving route according to the charging strategy;
collecting passenger travel demand information and electric bus initial position information, statistically analyzing departure stations and arrival stations of passengers and expected riding time, carrying out bus operation scheduling according to initial positions of buses, distributing passengers destined for the same destination to a journey according to the passenger travel information, connecting the journey of which the destination and the origin are the same station into a line, operating the line by one electric bus, generating an initial driving route of each electric bus, and adopting an enumeration algorithm to determine a charging strategy of the electric bus after arriving at the stations, namely whether charging is needed, the charging time and the waiting time after full charging;
Generating an initial timetable corresponding to the initial driving route of each electric bus according to the departure time, the driving time, the charging time and the waiting time of the bus;
the driving time is the time from the station to the demand point, the time from the demand point to the demand point and the time from the demand point to the station, the time is a known fixed value, and the departure time, the charging time and the waiting time are variables which need to be decided;
step 4: and optimizing the current initial driving route and schedule according to the initial driving route and the initial schedule, searching a passenger allocation scheme, and optimizing a vehicle driving plan and a station charging plan by cooperation based on the acceptance criteria of the passenger allocation scheme until the optimal driving route and schedule of the electric demand response bus are obtained.
Further, the total objective function is specifically:
wherein J is the total objective function, lambda 0 For electric demand response bus fixed use cost lambda 1 For electric demand response bus fixed departure cost lambda 2 Punishment cost, lambda, for electric demand response bus system unit passenger waiting time 3 For electric demand response bus system unit operation time cost lambda 4 For the unit charging cost of the electric demand response bus system, N=P U D is the set of electric demand response bus driving nodes, P is the set of passenger traveling demands, D is the set of electric demand response bus stops, K is the set of electric demand response bus, I is the set of electric demand response bus trips, and s p B is the number of passengers at the demand point p p For the desired ride time of the demand point p, t n，n′ For the travel time between two driving nodes n and n', V k For a variable with a value of 0 or 1, indicating whether the electric demand response bus is used or not; u (U) k，i For a variable with a value of 0 or 1, indicating whether the electric demand response bus k runs a journey i or not;for a variable with a value of 0 or 1, indicating whether the demand point p is allocated to the journey i of the electric demand response bus k; />In order to take a variable with a value of 0 or 1, whether the travel i of the electric demand response bus k passes from the driving node n to the driving node n'; />The electric demand response bus k is an integer variable, and represents the time when the travel i of the electric demand response bus k reaches a demand point p; c (C) k，i And the electric demand response bus k is an integer variable, and represents the charging time of the bus k at the station after the journey i is ended.
Further, the generating the initial driving route of each electric bus in the step 2 includes the following steps:
1) Calculating the number of passengers of the electric demand response buses so as to meet the passenger capacity constraint:
where Ik is the travel set operated by the electric demand responsive bus k, s q For the number of passengers at demand point q, p' is the set of passenger travel demands,responding the number of passengers at the point p when the journey i of the bus k passes through the point q from the point p for the electric demand; />For a variable with a value of 0 or 1, indicating whether the travel i of the electric demand response bus k is from the demand point p to the demand point q; n=p u.d is a set of electric demand-response bus driving nodes, P is a set of passenger travel demands, D is a set of electric demand-response bus stops, and K is a set of electric demand-response bus vehicles;
2) Calculating the power consumption of the electric demand response bus to meet the battery capacity constraint:
wherein D is a collection of electric demand response bus stations, alpha, beta is a power consumption coefficient related to the carrying capacity, alpha, beta is a dimensionless parameter, omega' is the empty vehicle net weight, omega is the unit passenger weight, and e k，i The power consumption of the journey i of the bus k is responded for the electric demand;to take a variable with a value of 0 or 1, the electric demand response bus k shows whether the journey i is from the station d to the demand point p; t is t d，p The travel time from the station d to the demand point p; / >Responding the number of passengers at the p point when the travel i of the bus k passes through the n point from the p point for the electric demand; />For a variable with a value of 0 or 1, indicating whether the travel i of the electric demand response bus k is from the demand point p to the driving node n; t is t p，n The driving time from the demand point p to the driving node n is set; p is a collection of passenger travel demands; n is a driving node; n=p u D is a set of electric demand response bus driving nodes; k is a set of electric demand response buses;
3) To assign passengers destined for the same destination to the same journey:
wherein u is p For the purpose of passenger pM is an infinitely positive number, < ->To take a variable with a value of 0 or 1, the electric demand response bus k is represented whether the journey i goes to the station d; d is a station of the electric bus; p is a set of passenger travel demands, D is a set of electric demand response bus stops, and K is a set of electric demand response buses; />For a variable with a value of 0 or 1, indicating whether the demand point p is allocated to the journey i of the electric demand response bus k;
4) Connecting the travel of the destination and the origin which are the same station into a line and ensuring the balance of the vehicle in and out:
in the method, in the process of the invention,to take a variable with a value of 0 or 1, the electric demand response bus k represents whether the journey i passes from the station d to the demand point p; / >To take a variable with a value of 0 or 1, the electric demand response bus k represents whether the journey i passes from the demand point p to the station d; p is a collection of passenger travel demands; u (U) k，i For a variable with a value of 0 or 1, indicating whether the electric demand response bus k runs a journey i or not; n=p u D is a set of electric demand response bus driving nodes, D is a set of electric demand response bus stations, and K is a set of electric demand response bus vehicles; />For a variable with a value of 0 or 1, indicating whether the travel i of the electric demand response bus k is from the demand point p to the demand point q;
5) An initial travel route of the electric demand response bus is generated.
Further, the generating the initial schedule corresponding to the initial driving route of each electric bus in the step 3 includes the following steps:
step 3.1: according to the initial driving route, generating an initial timetable based on driving time under the condition that the driving time of driving nodes is only considered without considering the driving time, charging time and waiting time;
step 3.2: according to the initial timetable, a charging strategy of the electric bus after arriving at the station is decided so as to determine whether charging is needed, the charging time and the waiting time after full charging, and the total objective function value is minimum;
Step 3.3: and adding departure time, charging time and waiting time of the electric bus to the initial schedule based on the driving time, and generating an initial schedule corresponding to the initial driving route finally.
Further, the charging strategy for deciding the electric bus to arrive at the station in the step 3.2 is specifically a charging strategy for deciding the electric bus to arrive at the station based on an enumeration algorithm, and the method comprises the following steps:
1) Calculating departure time of electric bus when starting operation according to travel route of electric response busIn the range of departure timeEnumerating all possible departure times in minutes, +.>Indicating the expected ride time of the first passenger on the first line r in trip i;
2) Judging the charging condition when arriving at the station according to the departure time when the electric bus starts to operate, and calculating the electric quantity of the electric bus after arriving at the station according to the electric demandJudging the electric quantity when arriving at the station +.>Whether the amount of power required for servicing the next trip can be met +.>If-> Then charging is necessary ifIt is possible to choose whether charging is required, wherein +.>Representing electric quantity of electric demand response bus k reaching station after finishing journey i, wherein ARR is reaching station, B cap For battery capacity, SOC is the amount of charge, the upper limit of the SOC is set to 90%, and the lower limit of the SOC is set to 20%; e, e k，i+1 Representing the power consumption of the electric demand in response to the journey i+1 of the bus k;
3) Calculating charging time according to the charging condition when the vehicle arrives at the station, and if the vehicle arrives at the station and needs to be charged, then the vehicle is in the necessary charging time rangeEnumerating all possible charging times in minutes, if it is possible to choose whether charging is required, within a selectable charging time rangeEnumerating all possible charging times, wherein the charging time is in minutes, and θ is the charging rate;
4) Judging the waiting time according to the charging time, if the time required by the electric response bus to be fully charged isJudging the waiting time of the fully-charged presence station, within the waiting time range +.>Enumerating all possible waiting time values, and if the charging time is smaller than the fully charged time, setting the waiting time to be 0;
5) In combination with the enumerated departure time, charge time and wait time, a combination of departure time, charge time and wait time is selected that minimizes the objective function.
Further, the driving route and schedule of the electric demand response bus obtained in the step 4 includes the following steps:
Step 4.1: obtaining an initial driving route and an initial timetable of the electric demand response bus;
step 4.2: optimizing the current initial driving route and the schedule, searching a passenger allocation scheme, and updating the current initial driving route and the initial schedule;
step 4.3: judging whether the updated driving route and schedule are accepted or not based on the acceptance criterion of the passenger allocation scheme;
step 4.4: and according to the acceptance criteria of the passenger allocation scheme, the vehicle running plan and the station charging strategy are cooperatively optimized until the optimal running route and schedule of the electric demand response bus are obtained.
Further, whether the updated driving route and schedule in the step 4.3 are accepted or not is determined based on the simulated annealing algorithm, which specifically includes:
step 4.3.1: calculating an objective function value of the updated passenger allocation scheme;
step 4.3.2: if the newly obtained objective function value is smaller than the original objective function value, then receiving a new passenger allocation scheme, executing step 4.3.4, otherwise, calculating a probability valueStep 4.3.3 is performed, wherein E j For the new objective function value obtained after iteration E i For the current objective function value, T is the current temperature value, and k is the attenuation coefficient;
step 4.3.3: judging whether the current probability value is smaller than the set probability value, if so, accepting a new passenger allocation scheme, otherwise, executing a step 4.3.4;
step 4.3.4: judging whether a stopping condition is reached, namely whether the set iteration times are reached, if so, obtaining an optimal driving route and a schedule, otherwise, updating the current temperature, and returning to the step 4.3.
The invention has the beneficial effects that:
the invention discloses an electric demand response bus dispatching method considering an opportunity charging strategy, which fully considers the traveling demand of passengers and the charging demand of an electric response bus, and completes electric demand response bus dispatching based on the opportunity charging strategy, thereby realizing the problems that the traveling demand of the passengers can be fully met, the vehicle can be put into operation during charging through dispatching arrangement, the utilization rate of the electric demand response bus is improved, the existing electricity supplementing strategy only considers the electric quantity required by a single journey and ignores the electric quantity required by the journey connected with the electric demand response bus, and the opportunity charging strategy cannot be combined with an operation plan more efficiently by cooperatively optimizing the vehicle traveling plan and the station charging strategy.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the drawings that are needed in the embodiments or the description of the prior art will be briefly described below, it will be obvious that the drawings in the following description are some embodiments of the present invention, and that other drawings can be obtained according to these drawings without inventive effort to a person skilled in the art.
Fig. 1 is a flow chart of an electric demand response bus dispatching method considering an opportunistic charging strategy.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The embodiment provides an electric demand response bus dispatching method considering an opportunity charging strategy, as shown in fig. 1, comprising the following steps:
Step 1: acquiring passenger travel demand information and electric bus initial position information, wherein the passenger travel demand information comprises the number of passengers on demand points, passenger destinations and expected riding time, the electric bus initial positions are distributed on different stations, a total objective function which simultaneously minimizes operation cost and charging cost is constructed, and an electric demand response bus operation parameter, a battery parameter, a power consumption coefficient and a charging rate are initialized by combining an electric demand response bus operation experience value and charging and discharging characteristics;
step 2: according to the destination of the passengers, under the condition of meeting the constraint of passenger capacity and battery capacity, the passengers going to the same destination are distributed to one journey, and the journey of which the destination and the originating place are the same station is connected into one line, and the electric buses operate, so that an initial driving route of each electric bus is generated;
step 3: according to the initial driving route, adopting an enumeration algorithm to determine a charging strategy of the electric buses after arriving at the station, namely whether charging is needed or not, charging time and waiting time after full charging, and generating an initial timetable corresponding to the initial driving route of each electric bus according to the departure time, the charging time and the waiting time;
Step 4: according to the initial driving route and schedule, optimizing the current initial driving route and schedule based on a variable neighborhood search algorithm, searching a passenger allocation scheme with smaller objective function value, applying a simulated annealing algorithm as an acceptance criterion for controlling a new passenger allocation scheme, and optimizing a vehicle driving plan and a station charging plan in a cooperative manner until the optimal driving route and schedule of the electric demand response bus are obtained.
The method comprises the steps of collecting passenger travel demand information and electric bus initial position information, statistically analyzing departure stations and arrival stations of passengers and expected riding time, flexibly and reasonably carrying out bus operation scheduling according to initial positions of buses, distributing passengers destined for the same destination to a route according to the passenger travel information, connecting the route of the destination and the originating place of the same station into a route, and operating by one electric bus, thereby generating an initial driving route of each electric bus, and solving the problem that the conventional electric buses uniformly arrange a charging plan of the buses based on a constant schedule and can not flexibly adjust the charging plan according to the passenger demands. The method has the advantages that an enumeration algorithm is adopted to determine the charging strategy of the electric buses after the electric buses arrive at the station, namely whether the electric buses need to be charged or not, the charging time and the waiting time after the electric buses are fully charged, an initial timetable corresponding to an initial driving route of each electric bus is generated according to the departure time, the charging time and the waiting time, and the operation plan is combined with the charging plan, so that the problem that the electric buses cannot be put into operation scheduling when the electric buses are charged by deliberately bypassing a charging station or a power exchanging station to supplement electric quantity is solved, the utilization rate of the electric buses is reduced, meanwhile, the electric quantity when the electric buses arrive at the station is calculated according to the time of the charging strategy, whether the electric quantity required by the next journey is met or not is judged, the problem that only the electric quantity required by a single journey is considered in the past, and the electric quantity required by the journey connected with the electric buses is ignored is solved, and the charging strategy is single, so that the problem that the opportunity charging strategy and the operation plan cannot be combined with the operation plan is solved more efficiently is solved.
Further, the total objective function is specifically:
wherein J is the total objective function, lambda 0 For electric demand response bus fixed use cost lambda 1 For electric demand response bus fixed departure cost lambda 2 Punishment cost, lambda, for electric demand response bus system unit passenger waiting time 3 For electric demand response bus system unit operation time cost lambda 4 For the unit charging cost of the electric demand response bus system, N=P U D is the set of electric demand response bus driving nodes, P is the set of passenger traveling demands, D is the set of electric demand response bus stops, K is the set of electric demand response bus, I is the set of electric demand response bus trips, and s p B is the number of passengers at the demand point p p For the desired ride time of the demand point p, t n，n′ For the travel time between two driving nodes n and n', V k For a variable with a value of 0 or 1, indicating whether the electric demand response bus is used or not; u (U) k，i For a variable with a value of 0 or 1, indicating whether the electric demand response bus k runs a journey i or not;to take a variable of 0 or 1, it is indicated whether the demand point p is assigned to the electric demand response bus kA stroke i; />In order to take a variable with a value of 0 or 1, whether the travel i of the electric demand response bus k passes from the driving node n to the driving node n'; / >The electric demand response bus k is an integer variable, and represents the time when the travel i of the electric demand response bus k reaches a demand point p; c (C) k，i And the electric demand response bus k is an integer variable, and represents the charging time of the bus k at the station after the journey i is ended.
The total objective function comprises five items, wherein the first item is the fixed use cost of each electric demand response bus; the second term is the electric demand response bus fixed departure cost; the third term is the cost of punishing the waiting time of passengers of the electric demand response buses; the fourth item is the operation time cost of the electric demand response bus; the fifth item is the cost of charging the electric demand-responsive bus. The objective function takes the charging cost of the electric demand response buses as the cost considering opportunistic charging, and effectively improves the utilization rate of the electric demand response buses while guaranteeing the travel demands of passengers.
The parameters initialized in step 1 include the following: the electric demand responds to bus operation parameters such as the maximum operation time of each journey, the maximum journey number of each electric bus and the passenger capacity; battery parameters such as battery capacity, upper battery capacity limit, and lower battery capacity limit; the charge rate, i.e. the charge power of the fast charge; the power consumption coefficient is the power consumption coefficient related to the load capacity.
Further, the generating the initial driving route of each electric bus in the step 2 includes the following steps:
1) Calculating the number of passengers of the electric demand response buses so as to meet the passenger capacity constraint:
wherein I is k Is driven by electric powerTravel set for k operation of demand response bus s q For the number of passengers at demand point q, p' is the set of passenger travel demands,responding the number of passengers at the point p when the journey i of the bus k passes through the point q from the point p for the electric demand;
wherein, the passenger capacity constraint is specifically:
in θ cap Is the maximum passenger capacity of the vehicle.
2) Calculating the power consumption of the electric demand response bus to meet the battery capacity constraint:
wherein D is a collection of electric demand response bus stations, α, β is a power consumption coefficient related to the load capacity, α= 0.00122, β=1.038, α, β is a dimensionless parameter, specifically α= 0.00122, β=1.038, ω' is the empty vehicle net weight, ω is the unit passenger weight, e k，i The power consumption of the journey i of the bus k is responded for the electric demand;
wherein, the battery capacity constraint is specifically:
the (12) and (13) ensure that the electric demand responds to the battery capacity constraint conditions satisfied by buses at the departure of the station and after arrival at the station,for the electric demand to respond to the electric quantity of travel i of bus k when the station starts, DEP starts for the station, For responding the electric quantity of the electric demand after the journey i of the bus k arrives at the station, ARR is the electric quantity of the electric demand arrives at the station, and E is the electric quantity of the electric demand lo E is the lower bound of the battery SOC up Is the upper bound of the battery SOC;
3) To assign passengers destined for the same destination to the same journey:
equations (4) and (5) ensure that the destination of passengers assigned to the same trip is the same, u p For the destination of passenger p, M is an infinitely positive number, < >>To take a variable with a value of 0 or 1, the electric demand response bus k is represented whether the journey i goes to the station d;
4) Connecting the travel of the destination and the origin which are the same station into a line and ensuring the balance of the vehicle in and out:
the balance of the in-out station in the operation process of the electric response bus is ensured by the steps (6) to (10),to take a variable with a value of 0 or 1, the electric demand response bus k represents whether the journey i passes from the station d to the demand point p; />To take a variable with a value of 0 or 1, the electric demand response bus k represents whether the journey i passes from the demand point p to the station d;
5) An initial travel route of the electric demand response bus is generated.
Specifically, combining the steps 1 to 4, based on the travel information of the passengers, randomly distributing the passengers with the same destination to the same journey under the condition of meeting the constraint of passenger capacity and battery capacity, and generating an initial travel route of the electric demand response bus; generating an initial travel route of the electric response bus, which comprises starting from a station, connecting demand points in the journey, and finally going to the destination of passengers in the journey to form a journey of the electric demand response bus, and connecting the journey operated by each electric bus to form the initial travel route of each electric response bus.
Further, the generating the initial schedule corresponding to the initial driving route of each electric bus in the step 3 includes the following steps:
step 3.1: according to the initial driving route, generating an initial timetable based on driving time under the condition that the driving time of driving nodes is only considered without considering the driving time, charging time and waiting time;
specifically, the driving time is the time from the station to the demand point, the time from the demand point to the demand point, and the time from the demand point to the station, which are known fixed values, and the departure time, the charging time, and the waiting time are variables that need to be decided.
Step 3.2: according to the initial timetable, a charging strategy of the electric bus after arriving at the station is decided so as to determine whether charging is needed, the charging time and the waiting time after full charging, and the total objective function value is minimum;
step 3.3: and adding departure time, charging time and waiting time of the electric bus to the initial schedule based on the driving time, and generating an initial schedule corresponding to the initial driving route finally.
Further, the step 3.2 of deciding the charging policy after the electric bus arrives at the station, specifically deciding the charging policy after the electric bus arrives at the station based on an enumeration algorithm, includes the following steps:
1) Calculating departure time when the electric bus starts to operate, wherein the departure time is within the value rangeEnumerating all possible departure times in minutes, +.>Indicating the expected ride time of the first passenger on the first line r in trip i;
2) Calculating electric quantity after electric demand response bus arrives at stationJudging whether or not the electric quantity at the time of arrival at the station can satisfy the electric quantity required for servicing the next trip +.>If->Then charging is necessary ifIt is possible to choose whether charging is required, wherein +.>Representing the electric quantity of the electric demand response bus k reaching the station after the journey i is ended, B cap For battery capacity, SOC is the amount of charge, the upper limit of the SOC is set to 90%, and the lower limit of the SOC is set to 20%;
3) If the vehicle must be charged after arriving at the station, the vehicle is charged within the necessary charging time rangeEnumerating all possible charging times in minutes, if it is possible to choose whether charging is required, then +.>Enumerating all possible charging times, wherein the charging time is in minutes, and θ is the charging rate;
4) If the charging time is the time required by full chargeJudging the waiting time of the fully-charged presence station, within the waiting time range +. >Enumerating all possible waiting time values, and if the charging time is smaller than the fully charged time, setting the waiting time to be 0;
5) In combination with the enumerated departure time, charge time and wait time, a combination of departure time, charge time and wait time is selected that minimizes the objective function.
Further, the driving route and schedule of the electric demand response bus obtained in the step 4 includes the following steps:
step 4.1: obtaining an initial driving route and an initial timetable of the electric demand response bus;
step 4.2: searching a passenger allocation scheme based on optimizing the current initial driving route and the schedule, and updating the initial driving route and the initial schedule which are obtained currently;
specifically, based on a variable neighborhood search algorithm, a passenger allocation scheme is changed through an exchange operator, an inversion operator and an insertion operator, a new electric demand response bus driving route and a schedule corresponding to the route are generated, whether the newly generated driving route and the schedule meet constraint conditions is judged, and if not, parallelization processing is carried out on the newly generated driving route and the schedule;
step 4.3: judging whether the updated driving route and schedule are accepted or not based on the acceptance criterion of the passenger allocation scheme;
Specifically, a simulated annealing algorithm is adopted to judge whether a newly generated driving route and a schedule are accepted, if a smaller objective function value is obtained at the moment, the new solution is accepted, otherwise, the new solution is accepted based on a set probability value;
step 4.4: and according to the acceptance criteria of the passenger allocation scheme, the vehicle running plan and the station charging strategy are cooperatively optimized until the optimal running route and schedule of the electric demand response bus are obtained.
Further, in the step 4.3, determining whether the updated driving route and schedule are accepted based on the simulated annealing algorithm specifically includes:
step 4.3.1: calculating an objective function value of the updated passenger allocation scheme;
step 4.3.2: if the newly obtained objective function value is smaller than the original objective function value, then receiving a new passenger allocation scheme, executing step 4.3.4, otherwise, calculating a probability valueStep 4.3.3 is performed, wherein E j For the new objective function value obtained after iteration E i For the current objective function value, T is the current temperature value, and k is the attenuation coefficient;
step 4.3.3: judging whether the current probability value is smaller than the set probability value, if so, accepting a new passenger allocation scheme, otherwise, executing a step 4.3.4;
Step 4.3.4: judging whether a stopping condition is met, if so, obtaining an optimal driving route and a schedule, otherwise, updating the current temperature, and returning to the step 4.3;
specifically, judging whether a stopping condition is reached at the moment, if so, obtaining an optimal electric demand response bus driving route and schedule, otherwise, reducing the current temperature, and generating a new passenger allocation scheme again through a variable neighborhood search operator.
In this embodiment, the passenger demand points are in discrete random distribution, the initial station position of the vehicle is known before the vehicle starts to operate every day, and the terminal station of each journey of the vehicle is determined according to the destination of the passenger. The initial station, the position of the passenger demand point and the destination station form a journey of the electric demand response bus. In order to calculate the power consumption of each journey more accurately, the influence of the load capacity on the power consumption is considered, and the power consumption is increased linearly along with the increase of the total mass of the vehicle along with the number of passengers on the vehicle.
The method provided by the embodiment can efficiently solve the NP-hard problem, takes the minimum total cost of the electric demand response bus system as a design target, considers the operation gap between each journey of the electric demand response bus to carry out opportunistic charging, selects a corresponding charging strategy according to the demand of passengers, flexibly decides the departure time, the charging time and the waiting time, and realizes the efficient fusion of the operation plan and the charging plan, thereby utilizing the minimum fleet number to operate the electric demand response bus system and maximizing the benefit after the electric demand response bus is electrified.
In summary, the scheduling method of the electric demand response bus considering the opportunistic charging strategy provided by the embodiment of the invention has the following advantages compared with the prior art:
1. the mutual restriction of the operation plan and the charging plan is considered, the charging plan is adjusted according to the operation plan, the charging time and the waiting time of the vehicle at the station are flexibly changed, otherwise, the change of the charging plan can also influence the operation route and the schedule, and a new collaborative optimization mechanism of the electric demand response bus system operation plan and the charging plan is formed;
2. the scheduling of the electric demand response buses based on the opportunity charging strategy is completed, the vehicles are subjected to opportunity charging in operation gaps through charging piles distributed by the stations after one journey is completed, and various charging strategies are considered, for example, when the passenger demand is large, the vehicles select the charging strategy that the electric quantity required by the next journey is met by not charging the electric quantity and then walking or not fully charging the electric quantity, and the charging strategy that the passenger demand is fully charged or continuously waits after fully charging the electric quantity after the passenger demand is small and then fully charging the electric quantity is selected to the stations are met;
3. The simulated annealing algorithm is integrated under the framework of the neighborhood searching algorithm, the approximate optimal solution can be accurately found in the limited memory and time resources, the algorithm solving time obtained through experimental simulation is within 10-15 minutes, the higher solving efficiency is achieved, the error between the approximate solution and the accurate solution solved based on Cplex is within 5%, and the solving time is improved by about 50%; the method has low requirements on hardware configuration and higher solving efficiency, and after the requirements of passengers with different scales are tested, the algorithm can be kept converged in different scenes, and meanwhile, the solving efficiency is not greatly influenced after the requirement points are increased.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the invention.
Claims (5)
1. An electric demand response bus dispatching method considering an opportunity charging strategy is characterized in that: the method comprises the following steps:
Step 1: acquiring passenger travel demand information and electric bus initial position information, wherein the passenger travel demand information comprises the number of passengers on demand points, passenger destinations and expected riding time, the electric bus initial position information comprises initial positions of electric buses distributed at different stations, a total objective function capable of minimizing operation cost and charging cost is constructed, and the total objective function is initialized by combining an electric demand response bus operation experience value and charging and discharging characteristics so as to obtain initialized electric demand response bus operation parameters, battery parameters, power consumption coefficients and charging rates;
the total objective function comprises five items, wherein the first item is the fixed use cost of each electric demand response bus; the second term is the electric demand response bus fixed departure cost; the third term is the cost of punishing the waiting time of passengers of the electric demand response buses; the fourth item is the operation time cost of the electric demand response bus; the fifth item is the charging cost of the electric demand response bus;
step 2: according to the passenger destination, under the condition of meeting the constraint of passenger capacity and battery capacity, acquiring an initial driving route of each electric bus;
Step 3: according to the initial driving route, determining a charging strategy of the electric buses after arriving at the station to determine whether charging is needed, charging time and waiting time after full charging, and generating an initial timetable of each electric bus corresponding to the initial driving route according to the charging strategy;
the step 3 of generating the initial schedule corresponding to the initial driving route of each electric bus comprises the following steps:
step 3.1: according to the initial driving route, generating an initial timetable based on driving time under the condition that the driving time of driving nodes is only considered without considering the driving time, charging time and waiting time;
step 3.2: according to the initial timetable, a charging strategy of the electric bus after arriving at the station is decided so as to determine whether charging is needed, the charging time and the waiting time after full charging, and the total objective function value is minimum;
the charging strategy for deciding the electric bus to arrive at the station in the step 3.2 is specifically based on an enumeration algorithm, and comprises the following steps:
1) Calculating departure time when the electric bus starts to operate according to the travel route of the electric response bus, wherein the departure time is within the value range of the departure time Enumerating all possible departure times in minutes, +.>Indicating the expected ride time of the first passenger on the first line r in trip i;
2) Judging the charging condition when arriving at the station according to the departure time when the electric bus starts to operate, and calculating the electric quantity of the electric bus after arriving at the station according to the electric demandJudging the electric quantity when arriving at the station +.>Whether the amount of power required for servicing the next trip can be met +.>If-> Then a charging is necessary if->It is possible to choose whether charging is required, wherein +.>Representing electric quantity of electric demand response bus k reaching station after finishing journey i, wherein ARR is reaching station, B cap For battery capacity, SOC is the amount of charge, the upper limit of the SOC is set to 90%, and the lower limit of the SOC is set to 20%; e, e k，i+1 Representing the power consumption of the electric demand in response to the journey i+1 of the bus k;
3) Calculating charging time according to the charging condition when the vehicle arrives at the station, and if the vehicle arrives at the station and needs to be charged, then the vehicle is in the necessary charging time rangeEnumerating all possible charging times in minutes, if it is possible to choose whether charging is required, within a selectable charging time rangeEnumerating all possible charging times, wherein the charging time is in minutes, and θ is the charging rate;
4) Judging the waiting time according to the charging time, if the time required by the electric response bus to be fully charged isJudging the waiting time of the fully-charged presence station, within the waiting time range +.>Enumerating all possible waiting time values, and if the charging time is smaller than the fully charged time, setting the waiting time to be 0;
5) Selecting a combination of departure time, charging time and waiting time which minimizes the objective function by combining the enumerated departure time, charging time and waiting time;
step 3.3: adding departure time, charging time and waiting time of the electric bus to an initial schedule based on the driving time, and generating an initial schedule corresponding to the initial driving route finally;
the driving time is the time from the station to the demand point, the time from the demand point to the demand point and the time from the demand point to the station, the time is a known fixed value, and the departure time, the charging time and the waiting time are variables which need to be decided;
step 4: and optimizing the current initial driving route and schedule according to the initial driving route and the initial schedule, searching a passenger allocation scheme, and optimizing a vehicle driving plan and a station charging plan by cooperation based on the acceptance criteria of the passenger allocation scheme until the optimal driving route and schedule of the electric demand response bus are obtained.
2. The method for scheduling the electric demand response buses taking into account the opportunistic charging strategy according to claim 1, wherein the total objective function is specifically:
wherein J is the total objective function, lambda 0 For electric demand response bus fixed use cost lambda 1 For electric demand response bus fixed departure cost lambda 2 Punishment cost, lambda, for electric demand response bus system unit passenger waiting time 3 For electric demand response bus system unit operation time cost lambda 4 For the unit charging cost of the electric demand response bus system, N=P U D is the set of electric demand response bus driving nodes, P is the set of passenger traveling demands, D is the set of electric demand response bus stops, K is the set of electric demand response bus, I is the set of electric demand response bus trips, and s p B is the number of passengers at the demand point p p For the desired ride time of the demand point p, t n，n′ For the travel time between two driving nodes n and n', V k For a variable with a value of 0 or 1, indicating whether the electric demand response bus is used or not; u (U) k，i To take a value of 0 or 1, the variable represents whether the electric demand response bus k operates or notA procedure i;for a variable with a value of 0 or 1, indicating whether the demand point p is allocated to the journey i of the electric demand response bus k; / >In order to take a variable with a value of 0 or 1, whether the travel i of the electric demand response bus k passes from the driving node n to the driving node n'; />The electric demand response bus k is an integer variable, and represents the time when the travel i of the electric demand response bus k reaches a demand point p; c'. k，i And the electric demand response bus k is an integer variable, and represents the charging time of the bus k at the station after the journey i is ended.
3. The electric demand response bus dispatching method considering the opportunity charging strategy according to claim 1, wherein the generating the initial driving route of each electric bus in the step 2 comprises the following steps:
1) Calculating the number of passengers of the electric demand response buses so as to meet the passenger capacity constraint:
wherein I is k For travel sets operated by electric demand responsive buses k, s q For the number of passengers at demand point q, p' is the set of passenger travel demands,responding the number of passengers at the point p when the journey i of the bus k passes through the point q from the point p for the electric demand; />To take a variable with a value of 0 or 1, it is indicated whether the journey i of the electric demand response bus k is from demandThe point p is up to the demand point q; n=p u.d is a set of electric demand-response bus driving nodes, P is a set of passenger travel demands, D is a set of electric demand-response bus stops, and K is a set of electric demand-response bus vehicles;
2) Calculating the power consumption of the electric demand response bus to meet the battery capacity constraint:
wherein D is a collection of electric demand response bus stations, alpha, beta is a power consumption coefficient related to the carrying capacity, alpha, beta is a dimensionless parameter, omega' is the empty vehicle net weight, omega is the unit passenger weight, and e k，i The power consumption of the journey i of the bus k is responded for the electric demand;to take a variable with a value of 0 or 1, the electric demand response bus k shows whether the journey i is from the station d to the demand point p; t is t d，p The travel time from the station d to the demand point p; />Responding the number of passengers at the p point when the travel i of the bus k passes through the n point from the p point for the electric demand; />For a variable with a value of 0 or 1, indicating whether the travel i of the electric demand response bus k is from the demand point p to the driving node n; t is t p，n The driving time from the demand point p to the driving node n is set; p is a collection of passenger travel demands; n is a driving node; n=p u D is a set of electric demand response bus driving nodes; k is a set of electric demand response buses;
3) To assign passengers destined for the same destination to the same journey:
wherein u is p For the destination of passenger p, M is an infinitely positive number,to take a variable with a value of 0 or 1, the electric demand response bus k is represented whether the journey i goes to the station d; d is a station of the electric bus; p is a set of passenger travel demands, D is a set of electric demand response bus stops, and K is a set of electric demand response buses; / >For a variable with a value of 0 or 1, indicating whether the demand point p is allocated to the journey i of the electric demand response bus k;
4) Connecting the travel of the destination and the origin which are the same station into a line and ensuring the balance of the vehicle in and out:
in the method, in the process of the invention,to take a variable with a value of 0 or 1, the electric demand response bus k represents whether the journey i passes from the station d to the demand point p; />To take a variable with a value of 0 or 1, the electric demand response bus k represents whether the journey i passes from the demand point p to the station d; p is a collection of passenger travel demands; u (U) k，i For a variable with a value of 0 or 1, indicating whether the electric demand response bus k runs a journey i or not; n=p u D is a set of electric demand response bus driving nodes, D is a set of electric demand response bus stations, and K is a set of electric demand response bus vehicles; />For a variable with a value of 0 or 1, indicating whether the travel i of the electric demand response bus k is from the demand point p to the demand point q;
5) An initial travel route of the electric demand response bus is generated.
4. The electric demand response bus dispatching method considering the opportunity charging strategy according to claim 1, wherein the step 4 of obtaining the optimal driving route and schedule of the electric demand response bus comprises the following steps:
Step 4.1: obtaining an initial driving route and an initial timetable of the electric demand response bus;
step 4.2: optimizing the current initial driving route and the schedule, searching a passenger allocation scheme, and updating the current initial driving route and the initial schedule;
step 4.3: judging whether the updated driving route and schedule are accepted or not based on the acceptance criterion of the passenger allocation scheme;
step 4.4: and according to the acceptance criteria of the passenger allocation scheme, the vehicle running plan and the station charging strategy are cooperatively optimized until the optimal running route and schedule of the electric demand response bus are obtained.
5. The method for scheduling the electric demand-response bus taking into account the opportunistic charging policy according to claim 4, wherein the step 4.3 of determining whether the updated travel route and schedule are accepted based on the simulated annealing algorithm is specifically:
step 4.3.1: calculating an objective function value of the updated passenger allocation scheme;
step 4.3.2: if the newly obtained objective function value is smaller than the original objective function value, then receiving a new passenger allocation scheme, executing step 4.3.4, otherwise, calculating a probability value Step 4.3.3 is performed, wherein E j For the new objective function value obtained after iteration E i For the current objective function value, T is the current temperature value, and k is the attenuation coefficient;
step 4.3.3: judging whether the current probability value is smaller than the set probability value, if so, accepting a new passenger allocation scheme, otherwise, executing a step 4.3.4;
step 4.3.4: judging whether a stopping condition is reached, namely whether the set iteration times are reached, if so, obtaining an optimal driving route and a schedule, otherwise, updating the current temperature, and returning to the step 4.3.
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