CN112885141B - Guide access and charging optimization method suitable for parking lot electric vehicle - Google Patents

Guide access and charging optimization method suitable for parking lot electric vehicle Download PDF

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CN112885141B
CN112885141B CN202110154595.6A CN202110154595A CN112885141B CN 112885141 B CN112885141 B CN 112885141B CN 202110154595 A CN202110154595 A CN 202110154595A CN 112885141 B CN112885141 B CN 112885141B
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parking lot
charging
electric automobile
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electric quantity
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CN112885141A (en
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梁宁
李鹏程
刘志坚
刘杰
宋琪
罗灵琳
余宸昕
自超
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Kunming University of Science and Technology
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    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/14—Traffic control systems for road vehicles indicating individual free spaces in parking areas
    • G08G1/145—Traffic control systems for road vehicles indicating individual free spaces in parking areas where the indication depends on the parking areas
    • G08G1/148—Management of a network of parking areas
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L53/00—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles
    • G—PHYSICS
    • G07—CHECKING-DEVICES
    • G07F—COIN-FREED OR LIKE APPARATUS
    • G07F15/00—Coin-freed apparatus with meter-controlled dispensing of liquid, gas or electricity
    • G07F15/003—Coin-freed apparatus with meter-controlled dispensing of liquid, gas or electricity for electricity
    • G07F15/005—Coin-freed apparatus with meter-controlled dispensing of liquid, gas or electricity for electricity dispensed for the electrical charging of vehicles
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/60—Other road transportation technologies with climate change mitigation effect
    • Y02T10/70—Energy storage systems for electromobility, e.g. batteries
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/60—Other road transportation technologies with climate change mitigation effect
    • Y02T10/7072—Electromobility specific charging systems or methods for batteries, ultracapacitors, supercapacitors or double-layer capacitors
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/80—Technologies aiming to reduce greenhouse gasses emissions common to all road transportation technologies
    • Y02T10/92—Energy efficient charging or discharging systems for batteries, ultracapacitors, supercapacitors or double-layer capacitors specially adapted for vehicles
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y02T90/10—Technologies relating to charging of electric vehicles
    • Y02T90/12—Electric charging stations
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y02T90/10—Technologies relating to charging of electric vehicles
    • Y02T90/14—Plug-in electric vehicles

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Abstract

The invention discloses a guiding access method suitable for an electric automobile in a parking lot, which comprises the following steps: s1, establishing a traffic network adjacency matrix; s2, determining the selection sequence of the electric automobile parking lots according to the adjacency matrix of the traffic network; and S3, determining the guiding access result of the electric vehicle according to the remaining vacant charging parking spaces in the parking lot and the guiding feasibility limiting conditions. Disclosed is a charge optimization method, including: and S4, optimizing the charging and discharging power of the parking lot on the basis of taking the standby compensation into account according to the guiding access result of the electric automobile. According to the invention, the guide feasibility limiting conditions are introduced to obtain the guide access result of the electric automobile parking lot, after the guide occurs, the number of waiting accesses of electric automobiles in the parking lot is obviously reduced at each moment, the waiting access phenomenon of the parking lot is further relieved, and the actual access time of the corresponding electric automobiles is obviously prolonged compared with the prior art; according to the guiding access result, the charging and discharging power of the parking lot is optimized, and the daily profit of the parking lot operator is guaranteed.

Description

Guide access and charging optimization method suitable for parking lot electric vehicle
Technical Field
The invention relates to a guiding access and charging optimization method suitable for an electric automobile in a parking lot, and belongs to the field of electric automobile charging energy management.
Background
Due to the infrastructure construction speed, the contradiction between the electric vehicle and the charging infrastructure is increasingly prominent. After the electric automobile arrives at the parking lot, if enough charging devices are lacked, the electric automobile can be connected to the power grid only after waiting for other vehicles to leave. A large number of electric vehicles which are connected in an unordered mode aggravate the situation that the electric vehicles wait for connection in a parking lot, the actual connection time of the electric vehicles is shortened, and the capacity of the electric vehicles for participating in providing auxiliary standby is further influenced. Therefore, in order to avoid the phenomenon, a vehicle-network-friendly interactive comprehensive guiding strategy and an operation mode need to be established, and the standby potential of the electric vehicle is excavated in a mode of coordinating the access of the electric vehicle. The traditional electric vehicle charging guiding method has limitations, such as: when the electric automobile guiding mechanism is established, the guiding feasibility among different parking lots is not considered by focusing on the interior of a single parking lot. The parking lot operation goal is generally pursued to be maximized, and the proposed access discrimination mechanism is not easily accepted by users. When the research electric automobile participates in providing standby power, the limitation of the number of charging facilities is not considered, and the accuracy of the model is influenced.
Disclosure of Invention
The invention provides a guiding access method suitable for an electric automobile in a parking lot, which is characterized in that a guiding feasibility limiting condition is introduced to obtain a guiding access result of the electric automobile parking lot; the charging optimization method suitable for the electric automobile in the parking lot is provided, and charging and discharging power of the parking lot is further optimized according to a guiding access result.
The technical scheme of the invention is as follows:
a guiding access method suitable for an electric automobile in a parking lot comprises the following steps:
step S1, establishing a traffic network adjacency matrix;
step S2, determining the selection sequence of the electric automobile parking lots according to the adjacency matrix of the traffic network;
and step S3, determining the guiding access result of the electric vehicle according to the remaining vacant charging parking spaces in the parking lot and the guiding feasibility limiting conditions.
The step S1 specifically includes:
s1.1: selecting a traffic network node based on the urban road network space structure;
s1.2: establishing a traffic network connection graph by taking the distance between different traffic network nodes as a basis;
s1.3: establishing an adjacent matrix of an urban road network; the adjacency matrix stores the traffic network connectivity graph in the guidance center server in the form of an adjacency matrix, if a connection arc exists between two nodes, the corresponding element in the adjacency matrix is 1, and if not, the element is 0;
s1.4: and (3) using the path length between the two nodes to replace the position with the value of 1 in the adjacency matrix, modifying all the points with the data of 0 in the adjacency matrix, setting the value of infinity, and taking the modified adjacency matrix as the traffic network adjacency matrix.
The step S2 specifically includes: based on the traffic network adjacency matrix, the shortest path length between the traffic network adjacency matrix and each parking lot node is respectively obtained for different traffic network nodes by using a Floyd shortest path algorithm; determining the corresponding parking lot selection sequence from near to far according to the shortest path length aiming at different traffic network nodes; the parking lot classification in the sorting process comprises a preferred parking lot and an alternative parking lot.
The step S3 specifically includes:
s3.1, uploading the predicted arrival time, the predicted departure time, the predicted driving mileage of the electric automobile and the data of the electric automobile travel end node to a guide center server by the signing user in advance to finish the reservation process;
s3.2, after receiving the reservation data uploaded by the vehicle owner, the guidance center server reads parking lot selection sequencing in the guidance center server according to the travel ending node of the electric vehicle, and the preferred parking lot in the sequencing is used as a target parking lot;
and S3.3, determining a guide access result of the electric vehicle according to the remaining vacant charging parking spaces in the parking lot and the guide feasibility limiting conditions.
The S3.3 comprises the following specific processes:
s3.3.1, whether the target parking lot has an empty charging parking space:
if yes, directly accessing the target parking lot; otherwise f is 1, S3.3.2 is executed; wherein f represents an alternative parking lot;
s3.3.2, whether the parking lot candidate f satisfies the guidance feasibility limiting condition:
if so, S3.3.3 is performed; otherwise, accessing the target parking lot;
s3.3.3, whether the spare parking lot f has an empty charging space:
if yes, accessing an alternative parking lot f; otherwise, f +1, S3.3.2 is performed.
The guidance feasibility limiting conditions include:
remaining mileage condition:
dr(i)≥D(i,k)-D(i,j)
in the formula: d (i, j) and D (i, k) respectively represent the distance between the travel end node of the electric automobile i and the preferred parking lot j and the alternative parking lot k, and Dr(i) The remaining driving range of the electric automobile i is represented and can be calculated by the following formula:
Figure BDA0002932909770000031
in the formula: eh(i)、L100(i) Respectively representing the battery capacity and the hundred kilometers of power consumption and SOC of the electric automobile is(i) Represents the initial state of charge, SOC, of the electric vehicle iminRepresenting the lower limit of the state of charge of the electric vehicle, and d (i) representing the predicted driving mileage of the electric vehicle i;
economic conditions are as follows:
Edem(i,k)[πch_pri-πsub]≤Edem(i,j)πch_pri
in the formula: pich_priRepresenting a unit price of charging a parking lot without considering guidance compensation, pisubFor compensation of charge per unit for the lead generation owner, Edem(i,j)、Edem(i, k) respectively represent the charging electric quantity required to be obtained when the electric automobile i is accessed into the preferred parking lot j and the alternative parking lot k, and the charging electric quantity can be respectively calculated by the following formula:
Figure BDA0002932909770000032
Figure BDA0002932909770000033
and (3) guiding mileage conditions:
Lmax(i)≥D(i,k)-D(i,j)
in the formula: l ismax(i) The maximum acceptable guide mileage of the electric vehicle i is indicated, and the numerical value is preset by the vehicle owner at the time of signing up.
A charging optimization method suitable for an electric automobile in a parking lot comprises a guiding access method and further comprises the following steps:
and step S4, optimizing the charging and discharging power of the parking lot on the basis of taking the standby compensation into consideration according to the guiding access result of the electric automobile.
The step S4 specifically includes:
s4.1, aiming at the accessed electric automobile individual, respectively determining whether the electric automobile individual meets the participation condition of the controlled charging and discharging process based on the corresponding battery electric quantity at each moment after the electric automobile individual is accessed into the charging parking space, and executing the step S4.2 aiming at the electric automobile individual in the controlled charging and discharging state;
s4.2, determining a calculation model of the upper and lower standby declaration results of the parking lot, wherein the specific process is as follows:
s4.2.1, respectively calculating the upper and lower limits of the electric quantity fluctuation of the corresponding electric automobile monomer aiming at the electric automobile participating in the controlled charging and discharging process;
s4.2.2, solving the upper and lower limits of the electric quantity fluctuation of the corresponding parking lot by an accumulation form based on the calculation results of the upper and lower limits of the electric quantity fluctuation of the electric automobile monomer participating in the controlled charging and discharging process at each moment of each electric automobile parking lot;
s4.2.3, calculating the upper limit of the charging and discharging power of each moment of the parking lot by accumulating the upper limit of the charging and discharging power of the electric automobile participating in the controlled charging and discharging process aiming at each electric automobile parking lot; wherein, the lower limit of the charging and discharging power is defaulted to 0;
s4.2.4, building a calculation model of upper and lower standby declaration result of the parking lot based on the upper limit of charging and discharging power of the parking lot and the calculation results of the upper and lower limits of corresponding electric quantity fluctuation;
s4.3, based on the calculation model of the upper and lower spare declaration result of the parking lot constructed in the step S4.2.4, selecting the goal of maximizing the daily profit of the electric automobile parking lot operator, and optimizing the charging and discharging power of the parking lot under the condition of considering the spare compensation, wherein the concrete steps are as follows:
an objective function:
Figure BDA0002932909770000041
in the formula: pich(i) Indicating the charging cost unit price of the ith electric automobile, wherein the value depends on whether the guidance occurs or not; elb(i) The charging electric quantity obtained by the ith electric automobile is represented and determined according to the principle of the reserved electric quantity and the actually obtained electric quantity;
Figure BDA0002932909770000042
respectively represents the compensation cost of the upper and lower spare units,
Figure BDA0002932909770000043
respectively represents the upper and lower standby application amount of the parking lot s in the time period t, pie(t) represents the unit price of power sold by the power grid during the period t,
Figure BDA0002932909770000044
representing charging and discharging power, N, of the parking lot s during a period of ttRepresents the number of the reserved time intervals of the electric automobile in one day, Nh、NsRespectively representing the number of the electric automobiles and the number of the parking lots; Δ t represents the length of the electric vehicle reservation period t;
constraint conditions are as follows:
charging power constraint
Figure BDA0002932909770000045
In the formula:
Figure BDA0002932909770000046
representing the charging power upper limit of the parking lot s in the time period t, and obtaining the charging power upper limit by accumulating the charging power upper limits corresponding to all the electric automobiles belonging to the parking lot s in the time period t;
Figure BDA0002932909770000047
the binary variable refers to a binary variable generated in the charging process of the parking lot s in the t time period, the parking lot s in the charging state in the t time period is represented by a numerical value of 1, and the parking lot s in the non-charging state in the t time period is represented by a numerical value of 0;
discharge power confinement
Figure BDA0002932909770000048
In the formula:
Figure BDA0002932909770000049
representing the upper limit of the discharge power of the parking lot s in the time period t, and obtaining the upper limit of the discharge power corresponding to the electric automobile belonging to the parking lot s in all the time periods t by accumulating;
Figure BDA00029329097700000410
the parking lot s is a binary variable indicating the discharging process of the parking lot s in the t time period, the parking lot s in the t time period is in a discharging state when the numerical value is 1, and the parking lot s in the t time period is in a non-discharging state when the numerical value is 0;
parking lot electric quantity fluctuation constraint
Figure BDA0002932909770000051
In the formula:
Figure BDA0002932909770000052
respectively corresponding to the upper and lower electric quantity fluctuation bounds of the parking lot s in the time period t, and obtaining the electric quantity fluctuation bounds of the electric automobile belonging to the parking lot s in all the time periods t by accumulating the upper and lower electric quantity fluctuation bounds corresponding to the electric automobiletotal(s, t) represents the amount of power fluctuation in the parking lot s during the period t, as can be seenSolving the following formula to obtain:
Figure BDA0002932909770000053
in the formula:
Figure BDA0002932909770000054
representing charging and discharging power, eta, of parking lots s during a period of Tch、ηdisRespectively representing the charging and discharging efficiency of the electric automobile, wherein delta T represents the length of the reserved time period T of the electric automobile;
avoiding simultaneous charging and discharging constraints
Figure BDA0002932909770000055
The limiting conditions for the electric automobile to participate in the controlled charging and discharging process include the following two types: a warranty power condition and an expected power condition; only when the electric quantity of the battery of the electric automobile is not less than the bottom-guaranteed electric quantity and the expected electric quantity can be met, the electric automobile participates in the controlled charging and discharging process; otherwise, it will be in an uncontrolled charging state; the specific analysis is as follows:
if the electric automobile does not meet the condition of bottom-guaranteed electric quantity and does not meet the condition of expected electric quantity, the electric automobile is in an uncontrolled charging state, the corresponding charging power is constant as the maximum charging power, and the electric automobile does not participate in the discharging process;
if the electric automobile meets the condition of bottom-guaranteed electric quantity but does not meet the condition of expected electric quantity, the electric automobile is in an uncontrolled charging state, the corresponding charging power is constant as the maximum charging power, and the electric automobile does not participate in the discharging process;
if the electric automobile does not meet the bottom-guaranteed electric quantity condition but meets the expected electric quantity condition, the electric automobile is charged at the maximum charging power and does not participate in discharging until the bottom-guaranteed electric quantity condition is met, and then participates in the controlled charging and discharging process;
if the electric automobile meets the condition of bottom-guaranteed electric quantity and meets the condition of expected electric quantity, the electric automobile is controlled to be charged and dischargedThe electric state, the charging power of the electric automobile is controlled by the parking lot operator, and can be adjusted within a certain range; meanwhile, the electric automobile can participate in the discharging process, and the lower limit of the residual electric quantity corresponding to the discharging process is the bottom-protection electric quantity Ems；
The bottom-protecting electric quantity condition is specifically as follows:
the battery electric quantity of the electric automobile i reaches the bottom-protecting electric quantity EmsCorresponding time t ofms(i) Can be described as:
Figure BDA0002932909770000056
in the formula: t is tms(i) Indicating that the battery power of the electric automobile i reaches the bottom-guaranteed power EmsCorresponding time of tinj(i) Indicating the actual access charging time of the electric vehicle i, EmsRepresents a predetermined reserve power, Pchmax(i) Represents the maximum charging power of the electric vehicle i, Er(i) The battery capacity of the electric automobile i at the actual access charging moment can be calculated by the following formula:
Figure BDA0002932909770000061
in the formula: es(i) The initial electric quantity corresponding to the electric automobile i is represented, D (i) the predicted driving mileage of the electric automobile i is represented, D (i) the distance between the travel end node of the electric automobile i and the parking lot actually accessed is represented, and if the electric automobile is accessed into the preferred parking lot, D (i) the distance D (i, j) between the travel end node of the electric automobile i and the preferred parking lot j is represented; if the electric automobile is connected to the alternative parking lot, D (i) corresponds to the distance D (i, k) between the travel end node of the electric automobile i and the alternative parking lot k;
the expected charge condition is described as:
Pchmax(i)ηch[tdep(i)-tms(i)]≥Eexp(i)-Ems
in the formula: eexp(i) Indicating electric vehicle i correspondsDesired amount of electricity, tdep(i) Indicating the departure time of the electric vehicle i; if the electric quantity of the battery is larger than E when the electric automobile is connected to the charging momentmsE in the above formulamsCorrespondingly adjusting the battery electric quantity E at the moment of connecting the battery to the charging devicer(i)，tms(i) And correspondingly adjusting the actual access charging time of the electric automobile.
The invention has the beneficial effects that: according to the invention, the guide feasibility limiting conditions are introduced to obtain the guide access result of the electric automobile parking lot, after the guide occurs, the number of waiting accesses of electric automobiles in the parking lot is obviously reduced at each moment, the waiting access phenomenon of the parking lot is further relieved, and the actual access time of the corresponding electric automobiles is obviously prolonged compared with the prior art; and furthermore, according to the guiding access result, the charging and discharging power of the parking lot is optimized, and the daily profit of the parking lot operator is guaranteed.
Drawings
FIG. 1 is a flow chart of a method of the present invention;
FIG. 2 is a structure of a traffic network connectivity graph according to the present invention;
FIG. 3 is a flow chart of parking lot selection according to the present invention;
FIG. 4 is a traffic road network connection diagram constructed based on an actual road network structure in a certain place in southwest in the embodiment;
fig. 5 shows the waiting number of electric vehicles at each time in the parking lot according to the embodiment.
Detailed Description
Example 1: as shown in fig. 1, a guidance access method suitable for an electric vehicle in a parking lot includes the following steps:
step S1, establishing a traffic network adjacency matrix;
step S2, determining the selection sequence of the electric automobile parking lots according to the adjacency matrix of the traffic network;
and step S3, determining the guiding access result of the electric vehicle according to the remaining vacant charging parking spaces in the parking lot and the guiding feasibility limiting conditions.
A charging optimization method suitable for an electric automobile in a parking lot comprises a guiding access method and further comprises the following steps:
and step S4, optimizing the charging and discharging power of the parking lot on the basis of taking the standby compensation into consideration according to the guiding access result of the electric automobile.
Example 2: as shown in fig. 1 to 5, a guidance access and charging optimization method suitable for an electric vehicle in a parking lot includes the following specific steps:
step S1, establishing a traffic network adjacency matrix;
s1.1: on the basis of carrying out statistics and summary aiming at the construction positions of a traffic network and an electric automobile parking lot, selecting representative places such as parking lots, shopping malls and the like as traffic network nodes based on a city road network space structure;
s1.2: establishing a traffic network connectivity graph by taking the distance between different traffic network nodes as a basis, wherein the specific structure is shown in figure 2;
s1.3: establishing an adjacent matrix of an urban road network; the adjacency matrix stores the traffic network connectivity graph in the guidance center server in the form of an adjacency matrix, if a connection arc exists between two nodes, the corresponding element in the adjacency matrix is 1, and if not, the element is 0;
s1.4: and (3) using the path length between the two nodes to replace the position with the value of 1 in the adjacency matrix, modifying all the points with the data of 0 in the adjacency matrix, setting the value of infinity, and taking the modified adjacency matrix as the traffic network adjacency matrix.
Based on the traffic network connectivity graph shown in fig. 2, the corresponding traffic network adjacency matrix is as follows:
Figure BDA0002932909770000071
wherein G denotes a 12-node traffic network adjacency matrix in the embodiment, and ∞ denotes a setting change value to infinity.
And step S2, determining the selection sequence of the electric automobile parking lots according to the traffic network adjacency matrix.
The step S2 specifically includes: based on the traffic network adjacency matrix, the shortest path length between the traffic network adjacency matrix and each parking lot node is respectively obtained for different traffic network nodes by using a Floyd shortest path algorithm; determining the corresponding parking lot selection sequence from near to far according to the shortest path length aiming at different traffic network nodes; the parking lot classification in the sequencing process comprises a preferred parking lot and an alternative parking lot;
taking the traffic network connectivity graph shown in fig. 2 as an example, the parking lots corresponding to different traffic network nodes are selected in the following sequence:
table 1 different journey end node corresponding parking lot selecting sequence
Figure BDA0002932909770000081
As can be seen from table 1, the guided model can determine the corresponding parking lot selection sequence for different nodes according to the traffic network related parameter information.
And step S3, determining the guiding access result of the electric vehicle according to the remaining vacant charging parking spaces in the parking lot and the guiding feasibility limiting conditions. The method comprises the following specific steps:
and 3, requiring the subscriber to upload the data of the predicted arrival time, the predicted departure time, the predicted driving mileage of the electric automobile and the data of the electric automobile journey end node to the guide center server in advance to finish the reservation process (the predicted arrival time and the predicted departure time are used for assisting the calculation of the vacant charging parking space; when the electric automobile arrives before the predicted arrival time, the electric automobile waits, when the vehicle does not arrive at the predicted arrival time, the parking space is reserved, when the vehicle does not leave at the predicted departure time, the electric automobile is removed by the intervention of workers, and other arrangements according with application scenes can be carried out according to the uploaded data). In the waiting process, the electric automobile can select a non-charging parking space to stop.
After receiving the reservation data uploaded by the car owner, the guidance center server determines guidance access to the parking lots by reading the electric car parking lots determined in the guidance center server according to the travel ending nodes of the electric cars and on the basis of fully inspecting the remaining vacant charging parking lots of the parking lots and the guidance feasibility limiting conditions, and the specific flow is shown in fig. 3.
In order to reduce the occurrence of the waiting access phenomenon, the model only guides the electric automobile to the alternative parking lot on the premise that the target parking lot does not have the vacant charging facility, the electric automobile meets the requirement of the relevant guiding limiting condition, and the alternative parking lot has the vacant charging facility. Further, the guidance feasibility limiting conditions include:
(1) remaining mileage condition
In order to reduce the battery loss caused by the guiding process, the contract stipulates that only the remaining driving range of the electric automobile can meet the driving range increment caused by the guiding, the model can guide the electric automobile to go to an alternative charging station, and the specific mathematical form corresponding to the limiting condition of the remaining driving range is as follows:
dr(i)≥D(i,k)-D(i,j)
in the formula: d (i, j) and D (i, k) respectively represent the distance between the travel end node of the electric automobile i and the preferred parking lot j and the alternative parking lot k, and Dr(i) The remaining driving range of the electric automobile is represented and can be calculated according to the following formula:
Figure BDA0002932909770000091
in the formula: eh(i)、L100(i) Respectively representing the battery capacity and the hundred kilometers of power consumption and SOC of the electric automobile is(i) Represents the initial state of charge, SOC, of the electric vehicle iminThe lower limit of the state of charge of the electric automobile is represented, D (i) represents the predicted driving mileage of the electric automobile, and D (i, j) represents the distance between the travel end node of the electric automobile i and the preferred parking lot j.
(2) Economic condition
The contract sets up unit charging compensation cost to compensate for the electric automobile after the guide takes place, and in order to guarantee the economic benefits of the owner, the contract stipulates that the electric automobile only has the guide condition when the alternative charging station is accessed to be profitable, and the economic conditions are as follows in a specific form.
Edem(i,k)[πch_pri-πsub]≤Edem(i,j)πch_pri
In the formula, pich_priRepresenting a unit price of charging a parking lot without considering guidance compensation, pisubFor compensation of charge per unit for the lead generation owner, Edem(i,j)、Edem(i, k) respectively represent the charging electric quantity required to be obtained when the electric automobile i is accessed into the preferred parking lot j and the alternative parking lot k, and the charging electric quantity can be respectively calculated by the following formula:
Figure BDA0002932909770000092
Figure BDA0002932909770000093
in the formula, L100(i) The power consumption of the electric automobile is represented by hundred kilometers, the distances between the travel end node of the electric automobile i and the preferred parking lot j and the distance between the travel end node of the electric automobile i and the alternative parking lot k are represented by D (i), and the driving range of the electric automobile i is represented by D (i).
(3) Guiding mileage condition
In consideration of the compliance desire of the user, the contract sets a guiding mileage limiting condition, which is specifically as follows:
Lmax(i)≥D(i,k)-D(i,j)
in the formula, Lmax(i) And D (i, j) and D (i, k) respectively represent the distances between the journey end node of the electric automobile i and the preferred parking lot j and the alternative parking lot k.
Taking the electric vehicle with the route end node located at the node 1 of the communication graph of the traffic network shown in fig. 2 as an example, the guidance feasibility limiting condition determines that the parking lot corresponding to the electric vehicle is selected in the sequence of a → C → B → D by reading the data stored inside the system. At this time, the parking lot a will be determined as the target parking lot, and the parking lot B, C, D will be the candidate parking lot.
Then, whether the target parking lot a has an empty charging facility is examined, and if yes, the guidance feasibility limiting condition directly guides the electric vehicle to the parking lot a for access.
When the parking lot A does not have an empty charging facility, determining that the electric automobile is guided to be connected into the parking lot according to the following steps:
1): selecting the parking lot C as an alternative parking lot, and executing the step 2);
2): whether the alternative parking lot meets the guiding feasibility limiting conditions such as the remaining driving mileage condition, the economic condition and the guiding mileage condition is judged: if so, then execute 3); if not, directly guiding the electric automobile to go to a target parking lot A;
3): whether spare parking area possesses vacant charging parking stall: if the spare charging parking place is available, guiding the electric automobile to go to the alternative parking lot; if not, execute 4);
4): updating the alternative parking lot selection result, and sequentially selecting the parking lots B, D as alternative parking lots to execute the steps 2) and 3);
5): and if the alternative parking lots C, B, D cannot meet the electric automobile access requirement, guiding the electric automobile to the target parking lot A.
Step S4: and optimizing the charging and discharging power of the parking lot on the basis of taking the standby compensation into account according to the guiding access result of the electric automobile.
Step S4 is based on the electric vehicle guidance access result and the electric vehicle operating state, and based on the parking lot charging and discharging power upper limit and electric quantity fluctuation upper and lower bound calculation results on the basis of determining whether the electric vehicle satisfies the constraint condition for participating in the controlled charging and discharging process, and on the premise of fully considering the electric vehicle access charging and discharging and reserve capacity compensation mechanism, optimizes the charging and discharging power of the parking lot, and specifically includes the following steps:
s4.1, aiming at the accessed electric automobile individual, respectively determining whether the electric automobile individual meets the participation condition of the controlled charging and discharging process based on the corresponding battery electric quantity at each moment after the electric automobile individual is accessed into the charging parking space, and executing the step S4.2 aiming at the electric automobile individual in the controlled charging and discharging state;
furthermore, the electric automobile participates in the controlled charging and discharging process only when the electric quantity of the battery of the electric automobile is not less than the bottom-guaranteed electric quantity and the expected electric quantity of the battery of the electric automobile can be met; otherwise it will be in an uncontrolled state of charge.
If the electric automobile does not meet the condition of bottom electricity quantity (namely the corresponding electric automobile battery electricity quantity is less than E)ms) When the expected electric quantity condition is not met, the electric automobile is in an uncontrolled charging state, the corresponding charging power is constant to be the maximum charging power, and the electric automobile does not participate in the discharging process;
if the electric automobile meets the condition of bottom electricity conservation (namely the corresponding electric automobile battery electricity is less than E)ms) When the expected electric quantity condition is not met, the electric automobile is in an uncontrolled charging state, the corresponding charging power is constant to be the maximum charging power, and the electric automobile does not participate in the discharging process;
if the electric automobile does not meet the condition of bottom electricity quantity (namely the corresponding electric automobile battery electricity quantity is less than E)ms) When the expected electric quantity condition is met, the electric automobile is charged at the maximum charging power and does not participate in discharging (namely, is in an uncontrolled charging state) until the bottom-guaranteed electric quantity condition is met, and then participates in a controlled charging and discharging process;
if the electric automobile meets the condition of bottom electricity conservation (namely the corresponding electric automobile battery electricity is less than E)ms) When the expected electric quantity condition is met, the electric automobile is in a controlled charging and discharging state, and the charging power of the electric automobile is controlled by a parking lot operator and can be adjusted within a certain range; meanwhile, the electric automobile can participate in the discharging process, and the lower limit of the residual electric quantity corresponding to the discharging process is the bottom-protection electric quantity Ems；
Based on the above analysis, the limitation conditions for the electric vehicle to participate in the controlled charging and discharging process specifically include the following two types:
(1) and (3) bottom electricity quantity keeping condition:
the battery electric quantity of the electric automobile i reaches the bottom-protecting electric quantity EmsCorresponding time t ofms(i) Can be described as:
Figure BDA0002932909770000111
in the formula, tms(i) Indicating that the battery capacity of the electric vehicle i reaches EmsCorresponding time of tinj(i) Indicating the actual access charging time of the electric vehicle i, EmsIndicating the amount of reserve power, Pchmax(i) Represents the maximum charging power, η, of the electric vehicle ichRepresenting the charging efficiency of the electric vehicle (the charging efficiency is consistent in the embodiment, and different charging efficiencies can be set according to different electric vehicles as required), Er(i) The battery capacity of the electric automobile i at the actual access charging moment can be calculated by the following formula:
Figure BDA0002932909770000112
in the formula, Es(i) The initial electric quantity corresponding to the electric automobile i is represented, D (i) the predicted driving mileage of the electric automobile i is represented, D (i) the distance between the travel end node of the electric automobile i and the parking lot actually accessed is represented, and if the electric automobile is accessed into the preferred parking lot, D (i) the distance D (i, j) between the travel end node of the electric automobile i and the preferred parking lot j is represented; if the electric automobile is connected to the alternative parking lot, D (i) corresponds to the distance D (i, k) between the travel end node of the electric automobile i and the alternative parking lot k.
(2) The expected electric quantity condition is as follows:
the desired charge condition may be described as:
Pchmax(i)ηch[tdep(i)-tms(i)]≥Eexp(i)-Ems
in the formula, Pchmax(i) Represents the maximum charging power, η, of the electric vehicle ichIndicating the charging efficiency of the electric vehicle, Eexp(i) Indicating that the electric vehicle i corresponds to the expected electric quantity, EmsAnd representing the preset bottom-guaranteed electric quantity. t is tdep(i) Indicates the departure time, t, of the electric vehicle ims(i) Indicating that the battery capacity of the electric vehicle i reaches EmsThe corresponding time of (2); if the electric quantity of the battery is larger than E when the electric automobile is connected to the charging momentmsE in the above formulamsCorrespondingly adjusting the battery electric quantity E at the moment of connecting the battery to the charging devicer(i)，tms(i) And correspondingly adjusting the actual access time of the electric automobile.
S4.2, determining a calculation model of the upper and lower standby declaration results of the parking lot, wherein the specific process is as follows:
s4.2.1, respectively calculating the upper and lower limits of the electric quantity fluctuation of the corresponding electric automobile monomer aiming at the electric automobile participating in the controlled charging and discharging process;
the electric vehicle single body electric quantity fluctuation upper bound can be calculated by the following formula:
Figure BDA0002932909770000121
in the formula, Eub(i, t) represents the corresponding electric quantity fluctuation upper bound calculation result of the electric automobile i in the t period, Emax(i) Represents the upper bound of the battery capacity of the electric automobile, Er(i) And the battery capacity at the access charging moment corresponding to the electric automobile i is shown. Pchmax(i) Represents the upper limit of the charging power of the electric vehicle i, etachIndicates the charging efficiency, t, of the electric vehicleinj(i) Represents the actual charging time, t, of the electric vehicle idep(i) Corresponding to the departure time of the electric vehicle i, Eexp(i) Indicating the expected amount of electric power of the electric vehicle i.
For the electric automobile, the battery electric quantity is not less than the bottom-protection electric quantity at the moment of chargingr(i)≥Ems) The corresponding electric quantity fluctuation lower bound of the electric vehicle monomer can be calculated by the following formula:
Figure BDA0002932909770000122
in the formula, Elb(i, t) represents the corresponding electric quantity fluctuation lower bound calculation result of the electric automobile i in the t period, Pchmax(i)、Pdismax(i) Respectively represents the upper limits of charging and discharging power, eta, of the electric automobile ich、ηdisRespectively show the charging and discharging efficiencies of the electric vehicle. EmsIndicating a preset reserve capacity, Er(i) Representing the battery capacity at the moment of access charging corresponding to the electric vehicle i, Eexp(i) Indicating the expected amount of electric power of the electric vehicle i. t is tinj(i) Represents the actual charging time, t, of the electric vehicle ims(i) Indicating that the battery capacity of the electric vehicle i reaches EmsCorresponding time of tdep(i) Corresponding to the departure time of the electric automobile i;
when the electric vehicle is connected to the charging moment, the battery electric quantity is less than the bottom-protected electric quantity (E)r(i)<Ems) The corresponding electric quantity fluctuation lower bound of the electric vehicle monomer can be calculated by the following formula:
Figure BDA0002932909770000131
in the formula, Elb(i, t) represents the corresponding electric quantity fluctuation lower bound calculation result of the electric automobile i in the t period, Pchmax(i) Represents the upper limit of the charging power of the electric vehicle i, etachIndicating the charging efficiency of the electric vehicle. EmsIndicating a preset reserve capacity, Er(i) Representing the battery capacity at the moment of access charging corresponding to the electric vehicle i, Eexp(i) Indicating the expected amount of electric power of the electric vehicle i. t is tinj(i) Represents the actual charging time, t, of the electric vehicle ims(i) Indicating that the battery capacity of the electric vehicle i reaches EmsCorresponding time of tdep(i) Corresponding to the departure time of the electric vehicle i.
S4.2.2, solving the upper bound of electric quantity fluctuation corresponding to the parking lot s in the t period by an accumulation form based on the calculation results of the upper bound and the lower bound of electric quantity fluctuation of the electric automobile monomer in the controlled charging and discharging processes aiming at each electric automobile parking lot
Figure BDA0002932909770000132
And lower bound
Figure BDA0002932909770000133
S4.2.3 controlled charging and discharging based on participation in each electric car parking lotIndividual parameters of the range electric vehicles, the upper limit of the charging and discharging power of each electric vehicle are accumulated, and the upper limit of the charging and discharging power of each time period of the parking lot is calculated
Figure BDA0002932909770000134
Figure BDA0002932909770000135
Wherein, the lower limit of the charging and discharging power is defaulted to 0;
s4.2.4, building a parking lot upper and lower standby declaration result calculation model based on the parking lot charging and discharging power upper limit and the corresponding electric quantity fluctuation upper and lower bound calculation results.
The formula for calculating the upper and lower standby results declared at each time of the parking lot is as follows:
Figure BDA0002932909770000136
Figure BDA0002932909770000137
in the formula (I), the compound is shown in the specification,
Figure BDA0002932909770000138
respectively representing the upper and lower standby declaration amounts of the parking lot s in the time period t,
Figure BDA0002932909770000139
Figure BDA00029329097700001310
and respectively corresponding to the calculation results of the upper and lower bounds of the electric quantity fluctuation of the parking lot.
Figure BDA00029329097700001311
Respectively representing the upper limits of charging and discharging power of the parking lot s during the period t,
Figure BDA00029329097700001312
respectively representing charging and discharging of the parking lot s in the time period of tPower, ηch、ηdisRespectively represents the charging and discharging efficiency of the electric automobile, and delta t represents the length of the reserved time period t of the electric automobile.
S4.3, based on the calculation model of the upper and lower spare declaration result of the parking lot constructed in the step S4.2.4, selecting the goal of maximizing the daily profit of the electric automobile parking lot operator, and optimizing the charging and discharging power of the parking lot under the condition of considering the spare compensation, wherein the method specifically comprises the following steps:
(1) objective function
Figure BDA0002932909770000141
In the formula, pich(i) The charging cost unit price of the ith electric automobile is represented, and the value depends on whether the guidance occurs or not (if the guidance occurs, the value is (pi)ch_pri－πsub) (ii) a Otherwise is pich_pri(ii) a Guidance is considered to have occurred only if guidance from the target parking lot into the alternative parking lot is available). Elb(i) And the charging electric quantity obtained by the ith electric automobile is determined according to the rule of the reserved electric quantity and the actually obtained electric quantity.
Figure BDA0002932909770000142
Respectively represents the compensation cost of the upper and lower spare units,
Figure BDA0002932909770000143
Figure BDA0002932909770000144
the upper and lower spare claim amounts respectively representing the parking lot s for the time period t may be based on step S4.2.4. Pie(t) represents the unit price of power sold by the power grid during the period t,
Figure BDA0002932909770000145
respectively representing the charging and discharging power of the parking lot s during the period t. N is a radical oftIndicates the number of reserved time periods of the electric vehicle, Nh、NsRespectively representing the number of electric vehicles and parking lots, and Δ t representing the period length (the present embodiment)Example 30 min);
(2) constraint conditions
Charging power constraint
Figure BDA0002932909770000146
In the formula:
Figure BDA0002932909770000147
represents the charging power of the parking lot s for the period t,
Figure BDA0002932909770000148
represents the upper limit of the charging power of the parking lot s for the period t.
Figure BDA0002932909770000149
And in order to indicate a binary variable occurring in the charging process of the parking lot s in the t time period, a numerical value of 1 indicates that the parking lot s is in a charging state in the t time period, and a numerical value of 0 indicates that the parking lot s is in a non-charging state in the t time period.
Discharge power confinement
Figure BDA00029329097700001410
In the formula:
Figure BDA00029329097700001411
represents the discharge power of the parking lot s for the period t,
Figure BDA00029329097700001412
represents the upper limit of the discharge power of the parking lot s for the period t.
Figure BDA00029329097700001413
And in order to indicate a binary variable generated in the discharging process of the parking lot s in the t period, a numerical value of 1 indicates that the parking lot s is in a discharging state in the t period, and a numerical value of 0 indicates that the parking lot s is in a non-discharging state in the t period.
Parking lot electric quantity fluctuation constraint
Figure BDA00029329097700001414
In the formula:
Figure BDA00029329097700001415
and respectively corresponding to the upper and lower electric quantity fluctuation bounds of the parking lot s in the time period t, and obtaining the electric quantity fluctuation bounds of all the electric vehicles belonging to the parking lot s in the time period t by accumulating. Etotal(s, t) represents the electric quantity fluctuation value of the parking lot s in the period of t, and can be obtained by solving the following formula.
Figure BDA0002932909770000151
In the formula: etotal(s, t) represents a fluctuation value of the electric quantity of the parking lot s for a period t,
Figure BDA0002932909770000152
representing charging and discharging power, eta, of parking lots s during a period of Tch、ηdisRespectively representing the charging and discharging efficiencies of the electric automobile, and delta T represents the length of a single scheduling period.
Avoiding simultaneous charging and discharging constraints
Figure BDA0002932909770000153
In the formula:
Figure BDA0002932909770000154
and in order to indicate a binary variable occurring in the charging process of the parking lot s in the t time period, a numerical value of 1 indicates that the parking lot s is in a charging state in the t time period, and a numerical value of 0 indicates that the parking lot s is in a non-charging state in the t time period.
Figure BDA0002932909770000155
A numerical value of 1 represents the position of the parking lot s in the t periodIn the discharging state, a value of 0 indicates that the parking lot s is in the non-discharging state during the period t.
In order to show the implementation effect of the invention, simulation analysis is carried out based on the actual road network structure in a certain place in southwest, and the steps S1-S4 in the patent are sequentially executed. The detailed parameter setting information of the simulation analysis is as follows:
(1) the starting time is set to 12:00 in the morning, the reserved time interval of the electric automobile is set to 30min, the number of time intervals is 48, and the time scale of the standby market is 1 h.
(2) The traffic network connectivity graph is shown in fig. 4, the road network system comprises 6 electric vehicle parking lots, the positions of the parking lots are distributed as shown in the figure, the number of the charging piles allowed in each parking lot is set to be 150, and the total number of the electric vehicles is set to be 1000.
(3) The charging service provided by the parking lot is charged for 1 yuan/kWh, the upper and lower spare unit prices are set to 0.05 yuan/kWh, and the electric vehicle parameters and the grid peak-valley electricity prices are respectively shown in tables 2 and 3 below.
TABLE 2 simulation electric vehicle parameters
Figure BDA0002932909770000156
TABLE 3 Peak to valley electricity price data
Figure BDA0002932909770000157
Taking the guidance access result of the electric vehicles with the road network structure shown in fig. 4 as an example, the waiting access quantity of the electric vehicles in the parking lot at each moment is shown in fig. 5.
It is obvious that, the guide takes place the back, and the parking area waits to insert quantity and obviously descends corresponding to electric automobile in every moment, and the parking area waits to insert the phenomenon and has further been alleviated, and it is longer than preceding showing and promoting to correspond electric automobile actual access duration.
The income and cost in the daily operation process of the parking lot are shown in the following table 4:
TABLE 4 daily operating income and cost composition of parking lot
Figure BDA0002932909770000161
As shown in table 4, under the guiding access condition, the charging fee income of the parking lot is increased from 4933.26 yuan to 5495.99 yuan, and the corresponding electricity purchasing cost is also obviously increased, which indicates that the reservation access requirement of the vehicle owner is better guaranteed. Meanwhile, the results in table 4 show that after the guidance model is introduced, the daily operation profit of the parking lot is increased from 5995.60 yuan to 6616.81 yuan, and the participation intention of the parking lot operator is ensured at the same time.
In addition, the results in table 4 show that, compared with the non-guidance case, the upper and lower spare compensation revenue of the parking lot and the V2G service revenue are greatly improved, which indicates that the spare potential of the corresponding electric vehicle in the parking lot is further exploited, and the capacity of the electric vehicle participating in the spare market and the power supply capacity of the V2G are further enhanced after the model is accessed.
While the present invention has been described in detail with reference to the embodiments shown in the drawings, the present invention is not limited to the embodiments, and various changes can be made without departing from the spirit of the present invention within the knowledge of those skilled in the art.

Claims (7)

1. The utility model provides a guide access method suitable for parking area electric automobile which characterized in that: the method comprises the following steps:
step S1, establishing a traffic network adjacency matrix;
step S2, determining the selection sequence of the electric automobile parking lots according to the adjacency matrix of the traffic network;
step S3, determining a guiding access result of the electric vehicle according to the remaining vacant charging parking spaces in the parking lot and the guiding feasibility limiting conditions;
the step S3 specifically includes:
s3.1, uploading the predicted arrival time, the predicted departure time, the predicted driving mileage of the electric automobile and the data of the electric automobile travel end node to a guide center server by the signing user in advance to finish the reservation process;
s3.2, after receiving the reservation data uploaded by the vehicle owner, the guidance center server reads parking lot selection sequencing in the guidance center server according to the travel ending node of the electric vehicle, and the preferred parking lot in the sequencing is used as a target parking lot;
s3.3, determining a guiding access result of the electric vehicle according to the remaining vacant charging parking spaces in the parking lot and the guiding feasibility limiting conditions;
the guidance feasibility limiting conditions include:
remaining mileage condition:
dr(i)≥D(i,k)-D(i,j)
in the formula: d (i, j) and D (i, k) respectively represent the distance between the travel end node of the electric automobile i and the preferred parking lot j and the alternative parking lot k, and Dr(i) The remaining driving range of the electric automobile i is represented and can be calculated by the following formula:
Figure FDA0003367344450000011
in the formula: eh(i)、L100(i) Respectively representing the battery capacity and the hundred kilometers of power consumption and SOC of the electric automobile is(i) Represents the initial state of charge, SOC, of the electric vehicle iminRepresenting the lower limit of the state of charge of the electric vehicle, and d (i) representing the predicted driving mileage of the electric vehicle i;
economic conditions are as follows:
Edem(i,k)[πch_pri-πsub]≤Edem(i,j)πch_pri
in the formula: pich_priRepresenting a unit price of charging a parking lot without considering guidance compensation, pisubFor compensation of charge per unit for the lead generation owner, Edem(i,j)、Edem(i, k) respectively represent the charging electric quantity required to be obtained when the electric automobile i is accessed into the preferred parking lot j and the alternative parking lot k, and the charging electric quantity can be respectively calculated by the following formula:
Figure FDA0003367344450000021
Figure FDA0003367344450000022
and (3) guiding mileage conditions:
Lmax(i)≥D(i,k)-D(i,j)
in the formula: l ismax(i) The maximum acceptable guide mileage of the electric vehicle i is indicated, and the numerical value is preset by the vehicle owner at the time of signing up.
2. The guidance access method suitable for the electric automobile in the parking lot according to claim 1, characterized in that: the step S1 specifically includes:
s1.1: selecting a traffic network node based on the urban road network space structure;
s1.2: establishing a traffic network connection graph by taking the distance between different traffic network nodes as a basis;
s1.3: establishing an adjacent matrix of an urban road network; the adjacency matrix stores the traffic network connectivity graph in the guidance center server in the form of an adjacency matrix, if a connection arc exists between two nodes, the corresponding element in the adjacency matrix is 1, and if not, the element is 0;
s1.4: and (3) using the path length between the two nodes to replace the position with the value of 1 in the adjacency matrix, modifying all the points with the data of 0 in the adjacency matrix, setting the value of infinity, and taking the modified adjacency matrix as the traffic network adjacency matrix.
3. The guidance access method suitable for the electric automobile in the parking lot according to claim 1, characterized in that: the step S2 specifically includes: based on the traffic network adjacency matrix, the shortest path length between the traffic network adjacency matrix and each parking lot node is respectively obtained for different traffic network nodes by using a Floyd shortest path algorithm; determining the corresponding parking lot selection sequence from near to far according to the shortest path length aiming at different traffic network nodes; the parking lot classification in the sorting process comprises a preferred parking lot and an alternative parking lot.
4. The guidance access method suitable for the electric automobile in the parking lot according to claim 1, characterized in that: the S3.3 comprises the following specific processes:
s3.3.1, whether the target parking lot has an empty charging parking space:
if yes, directly accessing the target parking lot; otherwise f is 1, S3.3.2 is executed; wherein f represents an alternative parking lot;
s3.3.2, whether the parking lot candidate f satisfies the guidance feasibility limiting condition:
if so, S3.3.3 is performed; otherwise, accessing the target parking lot;
s3.3.3, whether the spare parking lot f has an empty charging space:
if yes, accessing an alternative parking lot f; otherwise, f +1, S3.3.2 is performed.
5. The charging optimization method suitable for the electric automobile in the parking lot is characterized by comprising the following steps of: the method of any of claims 1-4, further comprising:
and step S4, optimizing the charging and discharging power of the parking lot on the basis of taking the standby compensation into consideration according to the guiding access result of the electric automobile.
6. The charge optimization method for the electric vehicle in the parking lot according to claim 5, wherein: the step S4 specifically includes:
s4.1, aiming at the accessed electric automobile individual, respectively determining whether the electric automobile individual meets the participation condition of the controlled charging and discharging process based on the corresponding battery electric quantity at each moment after the electric automobile individual is accessed into the charging parking space, and executing the step S4.2 aiming at the electric automobile individual in the controlled charging and discharging state;
s4.2, determining a calculation model of the upper and lower standby declaration results of the parking lot, wherein the specific process is as follows:
s4.2.1, respectively calculating the upper and lower limits of the electric quantity fluctuation of the corresponding electric automobile monomer aiming at the electric automobile participating in the controlled charging and discharging process;
s4.2.2, solving the upper and lower limits of the electric quantity fluctuation of the corresponding parking lot by an accumulation form based on the calculation results of the upper and lower limits of the electric quantity fluctuation of the electric automobile monomer participating in the controlled charging and discharging process at each moment of each electric automobile parking lot;
s4.2.3, calculating the upper limit of the charging and discharging power of each time period of the parking lot by accumulating the upper limit of the charging and discharging power of the electric automobile in the controlled charging and discharging process aiming at each electric automobile parking lot; wherein, the lower limit of the charging and discharging power is defaulted to 0;
s4.2.4, building a calculation model of upper and lower standby declaration result of the parking lot based on the upper limit of charging and discharging power of the parking lot and the calculation results of the upper and lower limits of corresponding electric quantity fluctuation;
s4.3, based on the calculation model of the upper and lower spare declaration result of the parking lot constructed in the step S4.2.4, selecting the goal of maximizing the daily profit of the electric automobile parking lot operator, and optimizing the charging and discharging power of the parking lot under the condition of considering the spare compensation, wherein the concrete steps are as follows:
an objective function:
Figure FDA0003367344450000031
in the formula: pich(i) Indicating the charging cost unit price of the ith electric automobile, wherein the value depends on whether the guidance occurs or not; elb(i) The charging electric quantity obtained by the ith electric automobile is represented and determined according to the principle of the reserved electric quantity and the actually obtained electric quantity;
Figure FDA0003367344450000041
respectively represents the compensation cost of the upper and lower spare units,
Figure FDA0003367344450000042
respectively represents the upper and lower standby application amount of the parking lot s in the time period t, pie(t) represents a time period t of the power grid saleThe unit price of electricity is as high as,
Figure FDA0003367344450000043
representing charging and discharging power, N, of the parking lot s during a period of ttRepresents the number of the reserved time intervals of the electric automobile in one day, Nh、NsRespectively representing the number of the electric automobiles and the number of the parking lots; Δ t represents the length of the electric vehicle reservation period t;
constraint conditions are as follows:
charging power constraint
Figure FDA0003367344450000044
In the formula:
Figure FDA0003367344450000045
representing the charging power upper limit of the parking lot s in the time period t, and obtaining the charging power upper limit by accumulating the charging power upper limits corresponding to all the electric automobiles belonging to the parking lot s in the time period t;
Figure FDA0003367344450000046
the binary variable refers to a binary variable generated in the charging process of the parking lot s in the t time period, the parking lot s in the charging state in the t time period is represented by a numerical value of 1, and the parking lot s in the non-charging state in the t time period is represented by a numerical value of 0;
discharge power confinement
Figure FDA0003367344450000047
In the formula:
Figure FDA0003367344450000048
representing the upper limit of the discharge power of the parking lot s in the time period t, and obtaining the upper limit of the discharge power corresponding to the electric automobile belonging to the parking lot s in all the time periods t by accumulating;
Figure FDA0003367344450000049
the parking lot s is a binary variable indicating the discharging process of the parking lot s in the t time period, the parking lot s in the t time period is in a discharging state when the numerical value is 1, and the parking lot s in the t time period is in a non-discharging state when the numerical value is 0;
parking lot electric quantity fluctuation constraint
Figure FDA00033673444500000410
In the formula:
Figure FDA00033673444500000411
respectively corresponding to the upper and lower electric quantity fluctuation bounds of the parking lot s in the time period t, and obtaining the electric quantity fluctuation bounds of the electric automobile belonging to the parking lot s in all the time periods t by accumulating the upper and lower electric quantity fluctuation bounds corresponding to the electric automobiletotal(s, t) represents the electric quantity fluctuation value of the parking lot s in the period of t, and can be obtained by solving the following formula:
Figure FDA00033673444500000412
in the formula:
Figure FDA00033673444500000413
representing charging and discharging power, eta, of parking lots s during a period of Tch、ηdisRespectively representing the charging and discharging efficiency of the electric automobile, wherein delta T represents the length of the reserved time period T of the electric automobile;
avoiding simultaneous charging and discharging constraints
Figure FDA00033673444500000414
7. The charge optimization method for the electric vehicle in the parking lot according to claim 6, wherein: the limiting conditions for the electric automobile to participate in the controlled charging and discharging process include the following two types: a warranty power condition and an expected power condition; only when the electric quantity of the battery of the electric automobile is not less than the bottom-guaranteed electric quantity and the expected electric quantity can be met, the electric automobile participates in the controlled charging and discharging process; otherwise, it will be in an uncontrolled charging state; the specific analysis is as follows:
if the electric automobile does not meet the condition of bottom-guaranteed electric quantity and does not meet the condition of expected electric quantity, the electric automobile is in an uncontrolled charging state, the corresponding charging power is constant as the maximum charging power, and the electric automobile does not participate in the discharging process;
if the electric automobile meets the condition of bottom-guaranteed electric quantity but does not meet the condition of expected electric quantity, the electric automobile is in an uncontrolled charging state, the corresponding charging power is constant as the maximum charging power, and the electric automobile does not participate in the discharging process;
if the electric automobile does not meet the bottom-guaranteed electric quantity condition but meets the expected electric quantity condition, the electric automobile is charged at the maximum charging power and does not participate in discharging until the bottom-guaranteed electric quantity condition is met, and then participates in the controlled charging and discharging process;
if the electric automobile meets the condition of bottom-guaranteed electric quantity and meets the condition of expected electric quantity, the electric automobile is in a controlled charging and discharging state, and the charging power of the electric automobile is controlled by a parking lot operator and can be adjusted within a certain range; meanwhile, the electric automobile can participate in the discharging process, and the lower limit of the residual electric quantity corresponding to the discharging process is the bottom-protection electric quantity Ems；
The bottom-protecting electric quantity condition is specifically as follows:
the battery electric quantity of the electric automobile i reaches the bottom-protecting electric quantity EmsCorresponding time t ofms(i) Can be described as:
Figure FDA0003367344450000051
in the formula: t is tms(i) Indicating that the battery power of the electric automobile i reaches the bottom-guaranteed power EmsCorresponding time of tinj(i) Indicating the actual access charging time of the electric vehicle i, EmsRepresents a predetermined reserve power, Pchmax(i) Represents the maximum charging power of the electric vehicle i，Er(i) The battery capacity of the electric automobile i at the actual access charging moment can be calculated by the following formula:
Figure FDA0003367344450000052
in the formula: es(i) The initial electric quantity corresponding to the electric automobile i is represented, D (i) the predicted driving mileage of the electric automobile i is represented, D (i) the distance between the travel end node of the electric automobile i and the parking lot actually accessed is represented, and if the electric automobile is accessed into the preferred parking lot, D (i) the distance D (i, j) between the travel end node of the electric automobile i and the preferred parking lot j is represented; if the electric automobile is connected to the alternative parking lot, D (i) corresponds to the distance D (i, k) between the travel end node of the electric automobile i and the alternative parking lot k;
the expected charge condition is described as:
Pchmax(i)ηch[tdep(i)-tms(i)]≥Eexp(i)-Ems
in the formula: eexp(i) Represents the expected electric quantity, t, of the electric vehicle idep(i) Indicating the departure time of the electric vehicle i; if the electric quantity of the battery is larger than E when the electric automobile is connected to the charging momentmsE in the above formulamsCorrespondingly adjusting the battery electric quantity E at the moment of connecting the battery to the charging devicer(i)，tms(i) And correspondingly adjusting the actual access charging time of the electric automobile.
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Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106643783A (en) * 2016-12-28 2017-05-10 国网天津市电力公司东丽供电分公司 Shortest path Thiessen polygon-based electric vehicle charging station searching method
CN109886501A (en) * 2019-03-06 2019-06-14 昆明理工大学 A kind of electric car charge and discharge Multipurpose Optimal Method
CN110189545A (en) * 2019-06-26 2019-08-30 广州小鹏汽车科技有限公司 Dispatching method of parking, device, storage medium and the computer equipment of vehicle
CN110515380A (en) * 2019-08-22 2019-11-29 北京交通大学 Shortest path planning method based on turning weight constraints
CN110880054A (en) * 2019-11-27 2020-03-13 国网四川省电力公司天府新区供电公司 Planning method for electric network car booking charging and battery changing path
CN111220168A (en) * 2019-11-29 2020-06-02 安徽江淮汽车集团股份有限公司 Method and device for planning charging path of electric vehicle and storage medium
CN111402621A (en) * 2020-02-17 2020-07-10 国网安徽电动汽车服务有限公司 Intelligent vehicle scheduling method and device for large-scale parking charging station of electric vehicle
CN112037504A (en) * 2020-09-09 2020-12-04 深圳市润腾智慧科技有限公司 Vehicle parking scheduling management method and related components thereof

Family Cites Families (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103985268B (en) * 2014-03-04 2017-04-05 江南大学 A kind of intelligent parking position abduction mechanism algorithm based on optimum berth model
JP6965696B2 (en) * 2017-11-09 2021-11-10 トヨタ自動車株式会社 Information provision system and information provision method of charging station, and server used for it
KR102036781B1 (en) * 2018-02-12 2019-10-25 동의대학교 산학협력단 System and Method for Guiding Shortest Path in Parking Lots using Adjacent Node Pairing
CN108599267B (en) * 2018-04-17 2020-09-01 上海电力学院 Unit combination scheduling method considering electric vehicle traveling correlation
CN111402596B (en) * 2020-02-17 2021-02-12 国网安徽电动汽车服务有限公司 Intelligent commercialized large-scale parking charging field for electric automobile

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106643783A (en) * 2016-12-28 2017-05-10 国网天津市电力公司东丽供电分公司 Shortest path Thiessen polygon-based electric vehicle charging station searching method
CN109886501A (en) * 2019-03-06 2019-06-14 昆明理工大学 A kind of electric car charge and discharge Multipurpose Optimal Method
CN110189545A (en) * 2019-06-26 2019-08-30 广州小鹏汽车科技有限公司 Dispatching method of parking, device, storage medium and the computer equipment of vehicle
CN110515380A (en) * 2019-08-22 2019-11-29 北京交通大学 Shortest path planning method based on turning weight constraints
CN110880054A (en) * 2019-11-27 2020-03-13 国网四川省电力公司天府新区供电公司 Planning method for electric network car booking charging and battery changing path
CN111220168A (en) * 2019-11-29 2020-06-02 安徽江淮汽车集团股份有限公司 Method and device for planning charging path of electric vehicle and storage medium
CN111402621A (en) * 2020-02-17 2020-07-10 国网安徽电动汽车服务有限公司 Intelligent vehicle scheduling method and device for large-scale parking charging station of electric vehicle
CN112037504A (en) * 2020-09-09 2020-12-04 深圳市润腾智慧科技有限公司 Vehicle parking scheduling management method and related components thereof

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