CN109177802B - Electric automobile ordered charging system and method based on wireless communication - Google Patents

Electric automobile ordered charging system and method based on wireless communication Download PDF

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CN109177802B
CN109177802B CN201811217439.4A CN201811217439A CN109177802B CN 109177802 B CN109177802 B CN 109177802B CN 201811217439 A CN201811217439 A CN 201811217439A CN 109177802 B CN109177802 B CN 109177802B
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charging
vehicle
wireless communication
time
load
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CN109177802A (en
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刘福潮
王维洲
彭晶
余向前
郑晶晶
张建华
王伟
禄启龙
韩永军
岳琳
雷彩娟
张韵
韩为宏
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State Grid Gansu Integration Energy Service Co ltd
STATE GRID GASU ELECTRIC POWER RESEARCH INSTITUTE
State Grid Gansu Electric Power Co Ltd
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State Grid Gansu Integration Energy Service Co ltd
STATE GRID GASU ELECTRIC POWER RESEARCH INSTITUTE
State Grid Gansu Electric Power Co Ltd
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    • 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
    • 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
    • Y02T90/16—Information or communication technologies improving the operation of electric vehicles

Abstract

The invention provides an electric automobile ordered charging system and method based on wireless communication. The system comprises a system control unit, a first wireless communication module, a vehicle-mounted control unit, a vehicle-mounted display screen, a vehicle charging navigation module, a second wireless communication module, a charging pile and a third wireless communication module. In the method, a system control unit acquires historical data of conventional loads of a regional power system from a power distribution network to predict the conventional loads on the same day; when the owner prepares to charge, a charging preparation instruction is submitted through the vehicle-mounted display screen, and the vehicle charging navigation module provides a charging pile navigation scheme for the owner; the method comprises the following steps that after an owner arrives at a charging pile, predicted vehicle taking time is input through a vehicle-mounted display screen, vehicle information is transmitted to a system control unit in a data packet mode in a wireless communication mode, and the system control unit plans according to the vehicle information and wirelessly transmits charging planning information to a vehicle for charging; the vehicle owner selects the vehicle charging mode through the vehicle-mounted display screen.

Description

Electric automobile ordered charging system and method based on wireless communication
Technical Field
The invention belongs to the technical field of electric automobile ordered charging, and mainly relates to an electric automobile ordered charging system and method based on wireless communication.
Background
Energy-saving and new energy vehicles become the development direction of the global automobile industry, electric vehicles are widely popularized at home and abroad, and the accumulated output and sales volume of pure electric vehicles and plug-in hybrid electric vehicles is in a rapidly increasing trend. In recent years, governments in China promote a series of preferential policies for stimulating the market development of electric automobiles. Under the encouragement of policies, the electric automobile market is developed vigorously, and a certain market scale is formed in the future.
The large-scale charging behavior formed after the electric automobile is large-scale also becomes a topic of wide social attention. As a novel energy automobile, an electric automobile has an energy supply end which is a power grid. Although charging of a single vehicle into a power grid has no great influence on the power grid, when a large number of vehicles are charged into the power grid without arrangement, certain pressure is brought to the power grid, so that the load of the vehicles is increased, the power quality is reduced, the difficulty of operation control of the power grid is increased, and great harm is caused to a power system in terms of safety and stability. On one hand, the electric vehicle has considerable overall charge capacity, which may cause insufficient grid capacity, frequency shift and increased peak-to-valley difference of daily load, and on the other hand, the electric vehicle has huge excavation space for demand response potential as a load with schedulability.
The rise of the internet + brings opportunities of changing development modes for the power industry. By means of the high coverage rate and the high transmission efficiency of the internet, interaction between a power grid and users is achieved, demand side response is promoted, and the power grid is developed towards a more intelligent and efficient direction. In the electric automobile field of charging in order, the user passes through internet mobile terminal and is connected electric automobile and charging system, realizes the control to electric automobile behavior of charging, and the administrator of charging simultaneously can convey the orderly scheme of charging for user mobile terminal through the internet platform, and the two is connected through the internet and the interactive process is electric automobile car networking system operation mechanism promptly. The system realizes communication among a user, the electric automobile and the charging system through the internet mobile terminal, and is a carrier for implementing an ordered charging scheme.
Disclosure of Invention
The invention provides an electric vehicle ordered charging system based on wireless communication and a method thereof, aiming at the adverse effect of accessing a large-scale electric vehicle into a power grid disordered charging power grid and in order to fully exert the regulating effect of a charging load of the electric vehicle on the power grid. The invention realizes the orderly charging of the electric automobile by the guidance of time-of-use electricity price and the combination of the wireless communication technology, achieves the purposes of reducing the load peak-valley difference of the system, stabilizing the power change of the system as much as possible and the like, and effectively increases the power supply reliability of the power grid.
The technical scheme of the system is that the electric automobile ordered charging system based on wireless communication comprises: the system comprises a system control unit, a first wireless communication module, a vehicle-mounted control unit, a vehicle-mounted display screen, a vehicle charging navigation module, a second wireless communication module, a charging pile and a third wireless communication module;
the system control unit is connected with the first wireless communication module through a wire; the vehicle-mounted control unit is connected with the vehicle-mounted display screen through a wire; the vehicle-mounted control unit is connected with the vehicle charging navigation module through a wire; the vehicle-mounted control unit is connected with the second wireless communication module through a wire; the charging pile is connected with the third wireless communication module through a wire; the first wireless communication module is connected with the second wireless communication module in a wireless communication mode; the first wireless communication module is connected with the third wireless communication module in a wireless communication mode.
The vehicle-mounted control unit wirelessly transmits the current residual electric quantity of the vehicle, the rated capacity of the battery and the predicted vehicle taking time of the vehicle owner to the first wireless communication module through the second wireless communication module; the first wireless communication module transmits the current residual electric quantity of the vehicle, the rated capacity of the battery and the predicted vehicle taking time of the vehicle owner to the system control unit; the system control unit transmits a charging instruction of the planned charging time period to the first wireless communication module; the first wireless communication module wirelessly transmits a charging instruction of the planned charging time period to the third wireless communication module; and the third wireless communication module transmits a charging instruction of the planned charging time period to the charging pile.
The technical scheme of the system is that the electric automobile ordered charging method based on wireless communication specifically comprises the following steps:
step 1: the method comprises the steps that a system control unit obtains historical data of conventional loads of a regional power system from a power distribution network to predict the conventional loads of the current day;
step 2: when the owner prepares to charge, a charging preparation instruction is submitted through the vehicle-mounted display screen, the vehicle charging navigation module provides a charging pile navigation scheme for the owner, and charging interconnection is established when the owner arrives at the charging pile;
and step 3: the method comprises the following steps that after an owner arrives at a charging pile, predicted vehicle taking time is input through a vehicle-mounted display screen, vehicle information is transmitted to a system control unit in a data packet mode in a wireless communication mode, and the system control unit plans according to the vehicle information and wirelessly transmits charging planning information to a vehicle for charging;
and 4, step 4: the vehicle owner selects the vehicle charging mode through the vehicle-mounted display screen.
Preferably, the normal load prediction data in the step 1 is load data not including a charging load of the electric vehicle;
the conventional load on the day of prediction in the step 1 is as follows:
dividing 24 hours a day into Y periods every T hours, where Y is 24/T, then the daily regular load can be expressed as L1,L2,L3,...,LY；
Regarding the power load as a series y (T) which changes along with the time T, the power load is observed once every T hours;
taking historical power load data of the past M days as the conventional load historical data in the step 1, and observing and taking values of the conventional load historical data of the past M days every T hours, wherein the number of the historical power load data is N ═ M × 24/T;
historical power load data at t1,t2,….,tpThe observed value at the time is shown as
Figure BDA0001833905450000031
The predicted daily routine load at time t is then:
Figure BDA0001833905450000032
wherein p and q are ARMA model orders,
Figure BDA0001833905450000033
θ1,θ2,...,θqas a model parameter, atIs the value of the white noise sequence at time t, i.e. the initial time interference amount, at-1,at-2,...,at-qThe values of the white noise sequence at t-1, t-2, and t-q are equivalent to the initial time interference amount atInfluence on the first q steps, yt-1,yt-2,...,yt-pP load values that are past values;
carrying out statistical analysis on the autocorrelation coefficient and the partial correlation coefficient of the model by using historical load data so as to determine the order (p, q) of the model, training the historical power load data of the model for predicting M days before the day by using the historical power load data, and estimating model parameters by using a generalized recursive least square algorithm to establish an ARMA model;
preferably, the vehicle charging navigation module in the step 2 provides a charging pile navigation scheme for the vehicle owner:
the charging pile transmits the charging state to a third wireless communication module, the third wireless communication module transmits the charging state to a first wireless communication module, the first wireless communication module transmits the charging state to a system control unit, the system control unit transmits the charging pile with the idle charging state to the first wireless communication module and wirelessly transmits the charging pile with the idle charging state to a second wireless communication module through the first wireless communication module, and the vehicle-mounted control unit receives the charging pile with the idle charging state transmitted by the second wireless communication module and provides a nearest charging pile navigation scheme in the idle state for a vehicle owner by combining vehicle position information and road condition information through a vehicle charging navigation module;
preferably, in step 3, the vehicle information includes: time t for vehicle to reach charging stationstRated capacity B of vehicle batteryrAnd the battery electric quantity percentage SOC at the time of vehicle chargingst，
The vehicle-mounted control unit transmits the vehicle information to the second wireless communication module, and the second wireless communication module transmits the vehicle information to the first wireless communication module and transmits the vehicle information to the system control unit through the first wireless communication module;
in step 3, the system control unit carries out planning according to the vehicle information as follows:
dividing every T hours for 24 hours a day into 24/T periods, using j to represent the jth period in the day, and xjRepresenting the charging state of the electric automobile, the value states are 0 and 1, representing the charging state of the electric automobile in the jth time period, and xj1 represents charging, and conversely 0 represents no charging;
performing ordered charging optimization with the system load peak-valley difference as the minimum through a genetic algorithm, and moving the charging time to the valley period for charging in the vehicle parking time period;
specifically, the input quantities of the algorithm are: predicted vehicle taking time t of vehicle ownerenAnd time t when the vehicle arrives at the charging stationstRated capacity B of vehicle batteryrAnd the battery electric quantity percentage SOC at the time of vehicle chargingstIf the vehicle is in the parking area for the parking time tstayCan be expressed as:
tstay＝ten-tst
charging time tcCan be expressed as:
Figure BDA0001833905450000041
therein, SOCenThe battery electric quantity percentage at the moment of finishing charging, eta is the charging efficiency of the electric automobile, and P is the charging power;
at the time of parking tstayInternal charging time tcCan be converted into a parking period tstayNumber of internal charging time segments HcIs divided into Y time intervals 24 hours a day, the time length represented by each time interval is T hours, and the number of parking time intervals is HstayAnd number of charging periods HcCan be respectively expressed as:
Figure BDA0001833905450000042
Figure BDA0001833905450000043
in the formula (I), the compound is shown in the specification,
Figure BDA0001833905450000044
the symbol is rounded up, namely, even if the charging time length of the last charging period is less than T hours, the charging time is divided according to the time length of the T hours;
the optimization problem now turns into: number of charging periods HcNumber of parking hours HstayChange of inner distribution, electric vehicle state of charge xjIn the parking period HstayThe internal value is adjustable (0 or 1 is selected), and when the charging time period moves to the valley period, the corresponding valley period xjTake 1, rest uncharged period xj0 is taken, and the rest is done in the same way;
the optimization objective, which aims at reducing the load peak-to-valley difference, can be expressed as:
f＝min(Lmax-Lmin)
＝min[max(L1+Px1,L2+Px2,...,LY+PxY)-min(L1+Px1,L2+Px2,...,LY+PxY)]
wherein L is1,L2,L3,...,LYRepresenting the conventional load prediction value of each time interval in the Y time intervals of the day in the step 1, wherein P is the charging power of the electric automobile;
screening out the charging state x with reduced load peak-valley difference through iterative calculation of genetic algorithm1,x2,x3,...xYWhen the charging sequence is shifted to valley charging (x)jIn the valley period state of 1), the starting time of orderly charging the vehicle is changed from the arrival time tstMove to tst_yIn order to avoid the impact of frequent on-off charging of a large number of vehicles on the power grid, the charging period is continuous (x)jState of 1 continuous) the final moment of completion of the ordered charge is denoted tst_y+tcDue to the charging period t in the ordered charging mode and the autonomous charging modecAre all continuous and can pass through the charging period tcSetting up charging cost according to the time length of peak period, flat period and valley period;
the charging planning information in step 3 is: final time t for completion of ordered chargingst_y+tcAnd the final time t of the completion of the autonomous chargingst+tcCharging fee p of ordered charging mode1,totalCharging fee p of autonomous charging system2,total；
Specifically, charging cost p of the ordered charging mode is set according to the peak-valley condition of the load prediction in the step 11,totalCan be expressed as:
p1,total＝(t1,ppp+t1,fpf+t1,vpv)α1
wherein the content of the first and second substances,t1,pindicating the charging duration, t, of the orderly charged vehicle at the load peak while it is charging at the charging station1,fIndicating the charging duration, t, of the ordered charging vehicle during the load plateau when charging at the charging station1,vIndicating the charging duration, p, of the orderly charged vehicle during the load valley period when charging at the charging stationpIndicating the base electricity price, p, at peak loadfIndicating the base price of electricity, p, for the load plateauvIndicating the base electricity price, alpha, of the load trough period1Is an orderly charging electricity price coefficient;
according to the peak-valley condition of the load prediction in the step 1, obtaining the load peak-period time length, the load leveling-period time length and the load valley-period time length, and formulating the charging cost p of the autonomous charging mode2,totalCan be expressed as:
p2,total＝(t2,ppp+t2,fpf+t2,vpv)α2
wherein, t2,pIndicating the charging time at load peak, i.e. the load peak time, t, of the autonomous charging vehicle when charging at the charging station2,fIndicating the charging duration at load leveling, i.e. the load leveling duration, t, of the autonomous charging vehicle when charging at the charging station2,vRepresents a charging period in a load valley period, i.e., a load valley period, p, of the autonomous charging vehicle when the charging station is chargingpIndicating the base electricity price, p, at peak loadfIndicating the base price of electricity, p, for the load plateauvIndicating the base electricity price, alpha, of the load trough period2The self-charging electricity price coefficient;
the value range of the electricity price coefficient is as follows:
Figure BDA0001833905450000061
when the owner selects the ordered charging, the discount coefficient alpha is alpha1Taking a fraction of less than 1, alpha1The value range of the ordered charging electricity price coefficient is (1-M,1), in the divided Y time periods, the higher the proportion of the planned ordered charging time period in the valley period to the whole charging time period is, the higher the electricity fee discount strength is, and the lower the charging fee is；
When the owner selects the autonomous charging, the discount coefficient alpha is alpha2Taking a fraction, alpha, greater than 12The self-charging electricity price coefficient has a value range of (1,1+ M), the higher the proportion of the charging time in the load peak period to the whole charging period is, the higher the discount coefficient alpha is, the part smaller than 1 is taken, and the charging cost is;
the system control unit transmits charging planning information, namely the final time of finishing ordered charging, the final time of finishing autonomous charging, the charging cost of an ordered charging mode and the charging cost of an autonomous charging mode to the second wireless communication module through the first wireless communication module, and the vehicle-mounted control unit receives the charging planning information transmitted by the second wireless communication module and transmits the charging planning information to the vehicle-mounted display screen;
preferably, in step 4, the vehicle charging modes are two types:
the first is an ordered charging mode according to planning information, actively participates in the regulation and control of load peak clipping and valley filling of the power grid in system planning, the charging cost is low, and the charging time interval is a period of time in the vehicle parking time interval;
the second is a common autonomous charging mode, the charging cost is higher, but the charging can be carried out immediately after the charging interface is accessed;
the vehicle owner selects one of the vehicle charging modes to charge through the vehicle-mounted display screen.
Compared with the prior art, the invention has the following advantages:
the electric automobile orderly charging optimization mode based on wireless communication can greatly reduce the charging cost of the electric automobile for users, guide the electric automobile to the valley period as much as possible, and is beneficial to peak clipping and valley filling of a power grid.
The time-of-use electricity price is discounted and divided in real time according to the charging responsivity of the owner of the electric automobile, so that the ordered charging process of the whole system is more accurate and effective;
the charging pushing is carried out on the vehicle owner by considering the user response condition, so that the vehicle owner can participate in the ordered charging as fast as possible, and the ordered charging efficiency of the system is improved;
the electric vehicle charging controlled center selection is carried out by combining the trip willingness of the vehicle owner user based on the wireless communication technology, the vehicle charging navigation module can provide a charging navigation scheme by combining the road condition user, and the vehicle owner can autonomously decide whether to participate in ordered charging according to the self condition, so that the vehicle charging control system has high democratic property.
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FIG. 1: the structure of the system is shown schematically;
FIG. 2: the invention discloses an orderly charging flow chart of an electric automobile.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
FIG. 1 is a block diagram of the system architecture of the present invention. The technical scheme of the system is that the electric automobile ordered charging system based on wireless communication comprises: the system comprises a system control unit, a first wireless communication module, a vehicle-mounted control unit, a vehicle-mounted display screen, a vehicle charging navigation module, a second wireless communication module, a charging pile and a third wireless communication module;
the system control unit is connected with the first wireless communication module through a wire; the vehicle-mounted control unit is connected with the vehicle-mounted display screen through a wire; the vehicle-mounted control unit is connected with the vehicle charging navigation module through a wire; the vehicle-mounted control unit is connected with the second wireless communication module through a wire; the charging pile is connected with the third wireless communication module through a wire; the first wireless communication module is connected with the second wireless communication module in a wireless communication mode; the first wireless communication module is connected with the third wireless communication module in a wireless communication mode.
The vehicle-mounted control unit wirelessly transmits the current residual electric quantity of the vehicle, the rated capacity of the battery and the predicted vehicle taking time of the vehicle owner to the first wireless communication module through the second wireless communication module; the first wireless communication module transmits the current residual electric quantity of the vehicle, the rated capacity of the battery and the predicted vehicle taking time of the vehicle owner to the system control unit; the system control unit transmits a charging instruction of the planned charging time period to the first wireless communication module; the first wireless communication module wirelessly transmits a charging instruction of the planned charging time period to the third wireless communication module; and the third wireless communication module transmits a charging instruction of the planned charging time period to the charging pile.
The system control unit is a Dell business machine in a type selection mode; the first wireless communication module is selected to be an ESP8266WiFi chip; the vehicle-mounted control unit is selected to be an ARM processor; the vehicle-mounted display screen is selected from a JCP200-070 vehicle-mounted display; the vehicle charging navigation module is selected as an OEMStar GPS navigation module; the second wireless communication module is selected to be an ESP8266WiFi chip; the charging pile type is ZCJ21-A-32A220V series alternating current charging pile; the third wireless communication module is selected to be an ESP8266WiFi chip.
Embodiments of the present invention will be described below with reference to fig. 1 to 2. The specific technical scheme of the embodiment of the invention is an electric automobile ordered charging method based on wireless communication, which specifically comprises the following steps:
step 1: the method comprises the steps that a system control unit obtains historical data of conventional loads of a regional power system from a power distribution network to predict the conventional loads of the current day;
the conventional load prediction data in the step 1 is load data which does not contain the charging load of the electric automobile;
the conventional load on the day of prediction in the step 1 is as follows:
dividing every T0.5 hour of 24 hours a day into Y-48 periods, Y-24/T, the daily regular load can be expressed as L1,L2,L3,...,LY；
Regarding the power load as a series y (T) which changes along with the time T, the power load is observed once every T hours;
regarding historical power load data of past M-7 days as the conventional load historical data in step 1, observing and taking values of the conventional load historical data of the past M-7 days every T-0.5 hours, wherein the number of the historical power load data is N-24/T;
historical power load data at t1,t2,….,tpThe observed value at the time is shown as
Figure BDA0001833905450000081
The predicted daily routine load at time t is then:
Figure BDA0001833905450000082
wherein p and q are ARMA model orders,
Figure BDA0001833905450000083
θ1,θ2,...,θqas a model parameter, atIs the value of the white noise sequence at time t, i.e. the initial time interference amount, at-1,at-2,...,at-qThe values of the white noise sequence at t-1, t-2, and t-q are equivalent to the initial time interference amount atInfluence on the first q steps, yt-1,yt-2,...,yt-pP load values that are past values;
carrying out statistical analysis on the autocorrelation coefficient and the partial correlation coefficient of the model by using historical load data so as to determine the order (p, q) of the model, training the historical power load data of which the model predicts 7 days before M by adopting the historical power load data, and estimating model parameters by adopting a generalized recursive least square algorithm to establish an ARMA model;
step 2: when the owner prepares to charge, a charging preparation instruction is submitted through the vehicle-mounted display screen, the vehicle charging navigation module provides a charging pile navigation scheme for the owner, and charging interconnection is established when the owner arrives at the charging pile;
in the step 2, the vehicle charging navigation module provides a charging pile navigation scheme for the vehicle owner:
the charging pile transmits the charging state to a third wireless communication module, the third wireless communication module transmits the charging state to a first wireless communication module, the first wireless communication module transmits the charging state to a system control unit, the system control unit transmits the charging pile with the idle charging state to the first wireless communication module and wirelessly transmits the charging pile with the idle charging state to a second wireless communication module through the first wireless communication module, and the vehicle-mounted control unit receives the charging pile with the idle charging state transmitted by the second wireless communication module and provides a nearest charging pile navigation scheme in the idle state for a vehicle owner by combining vehicle position information and road condition information through a vehicle charging navigation module;
and step 3: the method comprises the following steps that after an owner arrives at a charging pile, predicted vehicle taking time is input through a vehicle-mounted display screen, vehicle information is transmitted to a system control unit in a data packet mode in a wireless communication mode, and the system control unit plans according to the vehicle information and wirelessly transmits charging planning information to a vehicle for charging;
the vehicle information in step 3 includes: time t for vehicle to reach charging stationstRated capacity B of vehicle batteryrAnd the battery electric quantity percentage SOC at the time of vehicle chargingst，
The vehicle-mounted control unit transmits the vehicle information to the second wireless communication module, and the second wireless communication module transmits the vehicle information to the first wireless communication module and transmits the vehicle information to the system control unit through the first wireless communication module;
in step 3, the system control unit carries out planning according to the vehicle information as follows:
dividing every T-0.5 hour of 24 hours a day into Y-24/T-48 periods, using j to represent j, xjRepresenting the charging state of the electric automobile, the value states are 0 and 1, representing the charging state of the electric automobile in the jth time period, and xj1 represents charging, and conversely 0 represents no charging;
performing ordered charging optimization with the system load peak-valley difference as the minimum through a genetic algorithm, and moving the charging time to the valley period for charging in the vehicle parking time period;
in particular, the input quantities of the algorithmComprises the following steps: predicted vehicle taking time t of vehicle ownerenAnd time t when the vehicle arrives at the charging stationstRated capacity B of vehicle batteryrAnd the battery electric quantity percentage SOC at the time of vehicle chargingstIf the vehicle is in the parking area for the parking time tstayCan be expressed as:
tstay＝ten-tst
charging time tcCan be expressed as:
Figure BDA0001833905450000101
therein, SOCenThe battery electric quantity percentage at the moment of finishing charging, eta is the charging efficiency of the electric automobile, and P is the charging power;
at the time of parking tstayInternal charging time tcCan be converted into a parking period tstayNumber of internal charging time segments HcIs divided into 48 time intervals of Y, each time interval represents 0.5 hour, and the number of parking time intervals is HstayAnd number of charging periods HcCan be respectively expressed as:
Figure BDA0001833905450000102
Figure BDA0001833905450000103
in the formula (I), the compound is shown in the specification,
Figure BDA0001833905450000104
the sign rounded up is expressed, that is, even if the charging time period of the last charging period is less than T0.5 hours, the charging time is divided into the charging time periods according to the time period of T0.5 hours;
the optimization problem now turns into: number of charging periods HcNumber of parking hours HstayChange of inner distribution, electric vehicle state of charge xjIn the parking period HstayThe internal value is adjustable (0 or 1 is selected), and when the charging time period moves to the valley period, the corresponding valley period xjTake 1, rest uncharged period xj0 is taken, and the rest is done in the same way;
the optimization objective, which aims at reducing the load peak-to-valley difference, can be expressed as:
f＝min(Lmax-Lmin)
＝min[max(L1+Px1,L2+Px2,...,LY+PxY)-min(L1+Px1,L2+Px2,...,LY+PxY)]
wherein L is1,L2,L3,...,LYRepresenting the conventional load prediction value of each time interval in the Y time intervals of the day in the step 1, wherein P is the charging power of the electric automobile;
screening out the charging state x with reduced load peak-valley difference through iterative calculation of genetic algorithm1,x2,x3,...xYWhen the charging sequence is shifted to valley charging (x)jIn the valley period state of 1), the starting time of orderly charging the vehicle is changed from the arrival time tstMove to tst_yIn order to avoid the impact of frequent on-off charging of a large number of vehicles on the power grid, the charging period is continuous (x)jState of 1 continuous) the final moment of completion of the ordered charge is denoted tst_y+tcDue to the charging period t in the ordered charging mode and the autonomous charging modecAre all continuous and can pass through the charging period tcSetting up charging cost according to the time length of peak period, flat period and valley period;
the charging planning information in step 3 is: final time t for completion of ordered chargingst_y+tcAnd the final time t of the completion of the autonomous chargingst+tcCharging fee p of ordered charging mode1,totalCharging fee p of autonomous charging system2,total；
Specifically, charging cost p of the ordered charging mode is set according to the peak-valley condition of the load prediction in the step 11,totalCan be expressed as:
p1,total＝(t1,ppp+t1,fpf+t1,vpv)α1
wherein, t1,pIndicating the charging duration, t, of the orderly charged vehicle at the load peak while it is charging at the charging station1,fIndicating the charging duration, t, of the ordered charging vehicle during the load plateau when charging at the charging station1,vIndicating the charging duration, p, of the orderly charged vehicle during the load valley period when charging at the charging stationpIndicating the base electricity price, p, at peak loadfIndicating the base price of electricity, p, for the load plateauvIndicating the base electricity price, alpha, of the load trough period1The value is 0.9, which is the ordered charging electricity price coefficient;
according to the peak-valley condition of the load prediction in the step 1, obtaining the load peak-period time length, the load leveling-period time length and the load valley-period time length, and formulating the charging cost p of the autonomous charging mode2,totalCan be expressed as:
p2,total＝(t2,ppp+t2,fpf+t2,vpv)α2
wherein, t2,pIndicating the charging time at load peak, i.e. the load peak time, t, of the autonomous charging vehicle when charging at the charging station2,fIndicating the charging duration at load leveling, i.e. the load leveling duration, t, of the autonomous charging vehicle when charging at the charging station2,vRepresents a charging period in a load valley period, i.e., a load valley period, p, of the autonomous charging vehicle when the charging station is chargingpIndicating the base electricity price, p, at peak loadfIndicating the base price of electricity, p, for the load plateauvIndicating the base electricity price, alpha, of the load trough period21.1 is the self-charging electricity price coefficient;
the value range of the electricity price coefficient is as follows:
Figure BDA0001833905450000121
when the owner selects the ordered charging, the discount coefficient alpha is alpha1Taking a fraction of less than 1, alpha1The value range of the ordered charging electricity price coefficient is (1-M,1), and in the divided Y time periods, the higher the proportion of the planned ordered charging time period in the valley period to the whole charging time period is, the higher the electricity fee discount strength is, and the lower the charging fee is;
when the owner selects the autonomous charging, the discount coefficient alpha is alpha2Taking a fraction, alpha, greater than 12The self-charging electricity price coefficient has a value range of (1,1+ M), the higher the proportion of the charging time in the load peak period to the whole charging period is, the higher the discount coefficient alpha is, the part smaller than 1 is taken, and the charging cost is;
the system control unit transmits charging planning information, namely the final time of finishing ordered charging, the final time of finishing autonomous charging, the charging cost of an ordered charging mode and the charging cost of an autonomous charging mode to the second wireless communication module through the first wireless communication module, and the vehicle-mounted control unit receives the charging planning information transmitted by the second wireless communication module and transmits the charging planning information to the vehicle-mounted display screen;
and 4, step 4: the vehicle owner selects a vehicle charging mode through the vehicle-mounted display screen;
in the step 4, the vehicle charging modes are two types:
the first is an ordered charging mode according to planning information, actively participates in the regulation and control of load peak clipping and valley filling of the power grid in system planning, the charging cost is low, and the charging time interval is a period of time in the vehicle parking time interval;
the second is a common autonomous charging mode, the charging cost is higher, but the charging can be carried out immediately after the charging interface is accessed;
the vehicle owner selects one of the vehicle charging modes to charge through the vehicle-mounted display screen.
Although the terms system control unit, first wireless communication module, vehicle control unit, vehicle display screen, vehicle charging navigation module, second wireless communication module, charging pile, third wireless communication module, etc. are used more herein, the possibility of using other terms is not excluded. These terms are used merely to more conveniently describe the nature of the invention and they are to be construed as any additional limitation which is not in accordance with the spirit of the invention.
It should be understood that the above description of the preferred embodiments is given for clarity and not for any purpose of limitation, and that various changes, substitutions and alterations can be made herein without departing from the spirit and scope of the invention as defined by the appended claims.

Claims (4)

1. The ordered charging method of the electric automobile ordered charging system based on the wireless communication is characterized in that the ordered charging system of the electric automobile based on the wireless communication comprises the following steps: the system comprises a system control unit, a first wireless communication module, a vehicle-mounted control unit, a vehicle-mounted display screen, a vehicle charging navigation module, a second wireless communication module, a charging pile and a third wireless communication module;
the system control unit is connected with the first wireless communication module through a wire; the vehicle-mounted control unit is connected with the vehicle-mounted display screen through a wire; the vehicle-mounted control unit is connected with the vehicle charging navigation module through a wire; the vehicle-mounted control unit is connected with the second wireless communication module through a wire; the charging pile is connected with the third wireless communication module through a wire; the first wireless communication module is connected with the second wireless communication module in a wireless communication mode; the first wireless communication module is connected with the third wireless communication module in a wireless communication mode; the vehicle-mounted control unit wirelessly transmits the current residual electric quantity of the vehicle, the rated capacity of the battery and the predicted vehicle taking time of the vehicle owner to the first wireless communication module through the second wireless communication module; the first wireless communication module transmits the current residual electric quantity of the vehicle, the rated capacity of the battery and the predicted vehicle taking time of the vehicle owner to the system control unit; the system control unit transmits a charging instruction of the planned charging time period to the first wireless communication module; the first wireless communication module wirelessly transmits a charging instruction of the planned charging time period to the third wireless communication module; the third wireless communication module transmits a charging instruction of the planned charging time period to the charging pile;
the ordered charging method comprises the following steps:
step 1: the method comprises the steps that a system control unit obtains historical data of conventional loads of a regional power system from a power distribution network to predict the conventional loads of the current day;
step 2: when the owner prepares to charge, a charging preparation instruction is submitted through the vehicle-mounted display screen, the vehicle charging navigation module provides a charging pile navigation scheme for the owner, and charging interconnection is established when the owner arrives at the charging pile;
and step 3: the method comprises the following steps that after an owner arrives at a charging pile, predicted vehicle taking time is input through a vehicle-mounted display screen, vehicle information is transmitted to a system control unit in a data packet mode in a wireless communication mode, and the system control unit plans according to the vehicle information and wirelessly transmits charging planning information to a vehicle for charging;
and 4, step 4: the vehicle owner selects a vehicle charging mode through the vehicle-mounted display screen;
the vehicle information in step 3 includes: time t for vehicle to reach charging stationstRated capacity B of vehicle batteryrAnd the battery electric quantity percentage SOC at the time of vehicle chargingst，
The vehicle-mounted control unit transmits the vehicle information to the second wireless communication module, and the second wireless communication module transmits the vehicle information to the first wireless communication module and transmits the vehicle information to the system control unit through the first wireless communication module;
in step 3, the system control unit carries out planning according to the vehicle information as follows:
dividing every T hours for 24 hours a day into 24/T periods, using j to represent the jth period in the day, and xjRepresenting the charging state of the electric automobile, the value states are 0 and 1, representing the charging state of the electric automobile in the jth time period, and xj1 represents charging, and conversely 0 represents no charging;
performing ordered charging optimization with the system load peak-valley difference as the minimum through a genetic algorithm, and moving the charging time to the valley period for charging in the vehicle parking time period;
in particular toThe input quantities of the algorithm are: predicted vehicle taking time t of vehicle ownerenAnd time t when the vehicle arrives at the charging stationstRated capacity B of vehicle batteryrAnd the battery electric quantity percentage SOC at the time of vehicle chargingstIf the vehicle is in the parking area for the parking time tstayCan be expressed as:
tstay＝ten-tst
charging time tcCan be expressed as:
Figure FDA0003097246850000021
therein, SOCenThe battery electric quantity percentage at the moment of finishing charging, eta is the charging efficiency of the electric automobile, and P is the charging power;
at the time of parking tstayInternal charging time tcCan be converted into a parking period tstayNumber of internal charging time segments HcIs divided into Y time intervals 24 hours a day, the time length represented by each time interval is T hours, and the number of parking time intervals is HstayAnd number of charging periods HcCan be respectively expressed as:
Figure FDA0003097246850000022
Figure FDA0003097246850000023
in the formula (I), the compound is shown in the specification,
Figure FDA0003097246850000024
the symbol is rounded up, namely, even if the charging time length of the last charging period is less than T hours, the charging time is divided according to the time length of the T hours;
the optimization problem now turns into: number of charging periods HcNumber of parking hours HstayInside divisionsChange of cloth, electric vehicle State of Charge xjIn the parking period HstayThe internal value is adjustable (0 or 1 is selected), and when the charging time period moves to the valley period, the corresponding valley period xjTake 1, rest uncharged period xj0 is taken, and the rest is done in the same way;
the optimization objective, which aims at reducing the load peak-to-valley difference, can be expressed as:
f＝min(Lmax-Lmin)
＝min[max(L1+Px1,L2+Px2,...,LY+PxY)-min(L1+Px1,L2+Px2,...,LY+PxY)]
wherein L is1,L2,L3,...,LYRepresenting the conventional load prediction value of each time interval in the Y time intervals of the day in the step 1, wherein P is the charging power of the electric automobile;
screening out the charging state x with reduced load peak-valley difference through iterative calculation of genetic algorithm1,x2,x3,...xYWhen the charging sequence is shifted to valley charging (x)jIn the valley period state of 1), the starting time of orderly charging the vehicle is changed from the arrival time tstMove to tst_yIn order to avoid the impact of frequent on-off charging of a large number of vehicles on the power grid, the charging period is continuous (x)jState of 1 continuous) the final moment of completion of the ordered charge is denoted tst_y+tcDue to the charging period t in the ordered charging mode and the autonomous charging modecAre all continuous and can pass through the charging period tcSetting up charging cost according to the time length of peak period, flat period and valley period;
the charging planning information in step 3 is: final time t for completion of ordered chargingst_y+tcAnd the final time t of the completion of the autonomous chargingst+tcCharging fee p of ordered charging mode1,totalCharging fee p of autonomous charging system2,total；
Specifically, charging cost p of the ordered charging mode is set according to the peak-valley condition of the load prediction in the step 11,totalCan be expressed as:
p1,total＝(t1,ppp+t1,fpf+t1,vpv)α1
wherein, t1,pIndicating the charging duration, t, of the orderly charged vehicle at the load peak while it is charging at the charging station1,fIndicating the charging duration, t, of the ordered charging vehicle during the load plateau when charging at the charging station1,vIndicating the charging duration, p, of the orderly charged vehicle during the load valley period when charging at the charging stationpIndicating the base electricity price, p, at peak loadfIndicating the base price of electricity, p, for the load plateauvIndicating the base electricity price, alpha, of the load trough period1Is an orderly charging electricity price coefficient;
according to the peak-valley condition of the load prediction in the step 1, obtaining the load peak-period time length, the load leveling-period time length and the load valley-period time length, and formulating the charging cost p of the autonomous charging mode2,totalCan be expressed as:
p2,total＝(t2,ppp+t2,fpf+t2,vpv)α2
wherein, t2,pIndicating the charging time at load peak, i.e. the load peak time, t, of the autonomous charging vehicle when charging at the charging station2,fIndicating the charging duration at load leveling, i.e. the load leveling duration, t, of the autonomous charging vehicle when charging at the charging station2,vRepresents a charging period in a load valley period, i.e., a load valley period, p, of the autonomous charging vehicle when the charging station is chargingpIndicating the base electricity price, p, at peak loadfIndicating the base price of electricity, p, for the load plateauvIndicating the base electricity price, alpha, of the load trough period2The self-charging electricity price coefficient;
the value range of the electricity price coefficient is as follows:
Figure FDA0003097246850000041
when the owner selects the ordered charging, the discount coefficient alpha is alpha1Get less than1 part, α1The value range of the ordered charging electricity price coefficient is (1-M,1), and in the divided Y time periods, the higher the proportion of the planned ordered charging time period in the valley period to the whole charging time period is, the higher the electricity fee discount strength is, and the lower the charging fee is;
when the owner selects the autonomous charging, the discount coefficient alpha is alpha2Taking a fraction, alpha, greater than 12The self-charging electricity price coefficient is in a value range of (1,1+ M), the higher the proportion of the charging time in the load peak period to the whole charging period is, the higher the discount coefficient alpha is, the part of more than 1 is taken, and the charging cost is;
the system control unit transmits charging planning information, namely the final time of the ordered charging completion, the final time of the autonomous charging completion, the charging cost of the ordered charging mode and the charging cost of the autonomous charging mode to the second wireless communication module through the first wireless communication module, and the vehicle-mounted control unit receives the charging planning information transmitted by the second wireless communication module and transmits the charging planning information to the vehicle-mounted display screen.
2. The ordered charging method of the electric vehicle ordered charging system based on wireless communication according to claim 1, wherein the general load prediction data in step 1 is load data not containing electric vehicle charging load;
the conventional load on the day of prediction in the step 1 is as follows:
dividing 24 hours a day into Y periods every T hours, where Y is 24/T, then the daily regular load can be expressed as L1,L2,L3,...,LY；
Regarding the power load as a series y (T) which changes along with the time T, the power load is observed once every T hours;
taking historical power load data of the past M days as the conventional load historical data in the step 1, and observing and taking values of the conventional load historical data of the past M days every T hours, wherein the number of the historical power load data is N ═ M × 24/T;
historical power load data at t1,t2,….,tpObservation of time of dayThe value is expressed as
Figure FDA0003097246850000053
The predicted daily routine load at time t is then:
Figure FDA0003097246850000051
wherein p and q are ARMA model orders,
Figure FDA0003097246850000052
θ1,θ2,...,θqas a model parameter, atIs the value of the white noise sequence at time t, i.e. the initial time interference amount, at-1,at-2,...,at-qThe values of the white noise sequence at t-1, t-2, and t-q are equivalent to the initial time interference amount atInfluence on the first q steps, yt-1,yt-2,...,yt-pP load values that are past values;
and carrying out statistical analysis on the autocorrelation coefficient and the partial correlation coefficient of the model by using the historical load data so as to determine the order (p, q) of the model, training the historical power load data of the model for predicting M days before the day by using the historical power load data, and estimating the model parameters by using a generalized recursive least square algorithm to establish an ARMA model.
3. The ordered charging method of the ordered charging system for electric vehicles based on wireless communication as claimed in claim 1, wherein the vehicle charging navigation module provides the vehicle owner with the charging pile navigation scheme in step 2 as follows:
the charging pile transmits the charging state to the third wireless communication module, the third wireless communication module transmits the charging state to the first wireless communication module, the first wireless communication module transmits the charging state to the system control unit, the system control unit transmits the charging pile with the idle charging state to the first wireless communication module, the charging pile with the idle charging state is wirelessly transmitted to the second wireless communication module by the first wireless communication module, the vehicle-mounted control unit receives the charging pile with the idle charging state transmitted by the second wireless communication module, and the vehicle charging navigation module combines the vehicle position information and the road condition information to provide a charging pile navigation scheme which is closest to the vehicle owner and is in the idle state.
4. The ordered charging method of the electric vehicle ordered charging system based on wireless communication according to claim 1, wherein the vehicle charging modes in step 4 are two types:
the first is an ordered charging mode according to planning information, actively participates in the regulation and control of load peak clipping and valley filling of the power grid in system planning, the charging cost is low, and the charging time interval is a period of time in the vehicle parking time interval;
the second is a common autonomous charging mode, the charging cost is higher, but the charging can be carried out immediately after the charging interface is accessed;
the vehicle owner selects one of the vehicle charging modes to charge through the vehicle-mounted display screen.
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