CN105857107B - A kind of charging electric vehicle navigation system based on real-time data of power grid - Google Patents
A kind of charging electric vehicle navigation system based on real-time data of power grid Download PDFInfo
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- CN105857107B CN105857107B CN201610327339.1A CN201610327339A CN105857107B CN 105857107 B CN105857107 B CN 105857107B CN 201610327339 A CN201610327339 A CN 201610327339A CN 105857107 B CN105857107 B CN 105857107B
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- 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
- B60L53/60—Monitoring or controlling charging stations
- B60L53/64—Optimising energy costs, e.g. responding to electricity rates
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- 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
- B60L53/30—Constructional details of charging stations
- B60L53/35—Means for automatic or assisted adjustment of the relative position of charging devices and vehicles
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/3453—Special cost functions, i.e. other than distance or default speed limit of road segments
- G01C21/3469—Fuel consumption; Energy use; Emission aspects
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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
-
- 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
- Y02T90/167—Systems integrating technologies related to power network operation and communication or information technologies for supporting the interoperability of electric or hybrid vehicles, i.e. smartgrids as interface for battery charging of electric vehicles [EV] or hybrid vehicles [HEV]
-
- 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
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S30/00—Systems supporting specific end-user applications in the sector of transportation
- Y04S30/10—Systems supporting the interoperability of electric or hybrid vehicles
- Y04S30/12—Remote or cooperative charging
Abstract
The invention discloses a kind of charging electric vehicle navigation system based on real-time data of power grid, including geography information module, display module, communication module, electric automobile scheduling computing module and electricity price computing module；Described communication module, electric automobile scheduling computing module, electricity price computing module and a part for geography information module forms server end, described display module and another part of geography information module form client, client interacts with user, and server-side processes data simultaneously return to it.The present invention combines the data of power network and the network of communication lines, can meet the needs of user and power network as far as possible simultaneously, while successfully planning the path of user, the shunting to vehicular traffic can also be played, the peak load shifting of power network, make operation of power networks more stable and other effects.
Description
Technical field
The present invention relates to technical field of navigation and positioning, specifically a kind of charging electric vehicle based on real-time data of power grid is led
Boat system.
Background technology
Found by the retrieval to prior art, american documentation literature US20310218458 (A1), open (bulletin) day
2013.8.22, a kind of navigation system designed for electric automobile is disclosed.The system to the getatability of destination by carrying out
Judge to calculate, and the row of getatability grade is carried out with whether needing by charging station charge in path according to final place
Practice, finally obtain reliable guidance path.But the technology does not have the effect of peak load shifting, and electricity for the power network in region
Electrical automobile flow can not obtain good distribution.
Chinese patent literature CN102009625A, open (bulletin) day 2011.4.13, disclose a kind of electric automobile and fill
Electricity makes a reservation for and navigation system.The system utilizes existing cell management system of electric automobile, monitors vehicle mounted dynamic battery electricity in real time
Amount, when the vehicle-mounted electrokinetic cell electricity of electric automobile is less than a certain threshold value, sent out by CAN interface to MCU main control module
Go out charge request, the type information of vehicle mounted dynamic battery, dump energy information, the position of electric automobile is obtained using GPS module
Information, velocity information pass to MCU main control module；Then MCU main control module is according to these information, find it is nearest, have
The charging station of the idle charging device matched with the vehicle-mounted electrokinetic cell of electric automobile is made a reservation for and navigated.But the technology is easily caused
Nearby without suitable charging station when less than threshold values, so as to eventually arrive at the situation of destination, while the technology also lacks
The weary effect for power network allotment.
The content of the invention
For above-mentioned the deficiencies in the prior art, the purpose of the present invention is to propose to a kind of electronic vapour based on real-time data of power grid
Car charging navigation system, combines the real time data of power network and the network of communication lines, has taken into full account the characteristics of electric car navigates, solved
Limitation of the dump energy to electric car path planning, influence and user of the electric car charging to power system load are in time
The problems such as demand economically.The present invention based on user and consider distribution network load electric automobile it is vehicle-mounted navigation system
System, contains route searching, electric stake search, the function of vehicle shunting, using the maximizing the benefits of charging station economical operation as target, with
It is constraints to meet automobile user charge requirement to greatest extent, based on simulated annealing and power network minimum peak valley differential mode
Type establishes the Optimized model of the orderly charge control of electric automobile, so as to realize the coordination charge control of electric automobile.
Technical scheme：
A kind of charging electric vehicle navigation system based on real-time data of power grid, its feature is, including geography information mould
Block, display module, communication module, electric automobile scheduling computing module and electricity price computing module；
Described communication module, electric automobile scheduling computing module, one of electricity price computing module and geography information module
Divide and form server end, described display module and another part of geography information module form client, client and user
Interact, server-side processes data simultaneously return to it.
Signal transmission relation：
Geography information module obtains geography information by OpenStreetMap Open Source Platform.In server end, geography letter
Geography information needed for ceasing that module is static and downloading, including information of section and intersection etc., these geography information are together with from electric power
The electric stake information and load information that system obtains, electric car scheduling computing module is transferred to together and is used for path planning.In visitor
Family end, geography information module dynamic obtains geography information from network, for show map.
Display module transmits the demand of user to communication module, i.e. departure place, the information such as destination and dump energy, and
Receive the routing information that server end planned from communication module, be shown on map.
Communication module receives the demand information of user, and feeds back to server end and carry out path planning, while temporal information
Electricity price computing module is transferred to calculate for Spot Price.Communication module returns routing information behind the good path of servers' layout
Back to display module.
Electric automobile scheduling computing module receives user's request from communication module, comprehensive electric stake information, provides possibility
Selected path, for alternative path using as the input of electricity price computing module and temporal information, power station loading condition calculates one jointly
Individual extent function.To be updated if being received the loading condition in so power station, conversely, scheduler module will recalculate it is feasible
Alternative path, repeat said process.
Electricity price computing module obtains the temporal information for coming from communication module, the alternative road from electric automobile scheduler module
Whether the receiving of alternative path is fed back to scheduling by footpath information and the loading condition of power system to try to achieve a satisfaction
Module.
Described geography information module includes：Geographic information encoding and Gray code part and geographic node message part.
Described display module includes：Importation, basic tool processing data part and path display portion.
Described communication module includes：TCP/IP hops and encapsulation JSON format transmissions part.
Described electricity price computing module includes electricity price renewal part and plant load k extent function F (k) calculating parts
Point.
Compared with prior art, the solution have the advantages that：
With reference to the data of power network and the network of communication lines, using maximization of economic benefit as target, user can be met as far as possible simultaneously
With the demand of power network.While successfully planning the path of user, the shunting to vehicular traffic, power network can also be played
Peak load shifting, make operation of power networks more stable and other effects.
Brief description of the drawings
Fig. 1 is the schematic diagram of the charging electric vehicle navigation system of the invention based on real-time data of power grid；
Fig. 2 is the class figure of basic tool processing data part in the present invention；
Fig. 3 is the class figure of path display portion in the present invention；
Fig. 4 is the schematic diagram of electricity price computing module in the present invention；
Fig. 5 is power system simulation model figure；
Fig. 6 is the class figure of communication module in the present invention；
Embodiment
The present invention is described in further detail below in conjunction with the accompanying drawings.
Electric automobile dispatches computing module 4
Electric automobile scheduling computing module 4 controls each electric automobile within each period using simulated annealing
Charge condition, reach the purpose to charge in order.For the planning of electric car fast charge, influence during charging for network load
It is the factor that must take into consideration.Especially when trip peak time, if being unable to the distribution situation of look-ahead electric automobile fast charge,
There is a possibility that over-burden for partial electric grid, the decline of the quality of power supply is caused.It is likely to occur during in order to solve charging electric vehicle
Clustering phenomena, this module add the algorithm of shunting in the navigation programming on basis, mainly influence electric car by two aspects
Charge profile.It is to realize excitation for navigation system users by adjusting the electricity price in each power station first, electricity transaction city at present
Fieldization has become the development trend in future, and the Real-Time Scheduling of electricity price is by as the feasible means of regulation trend.In traveling
In the case that journey is similar, the user of electric car can be diverted to the less power station of load under the attraction of electricity price, realize power network tide
The equiblibrium mass distribution of stream.Electric car navigation system automatic shield is enabled to cause potential danger to power network secondly by penalty function is set
The charging planning of danger, the long-term safety operation of power network is ensured in the case where ensureing user's usage comfort as far as possible.
Simulated annealing thought originates from the annealing process of solid, and solid is heated into sufficiently high temperature, then slowly
Cooling；During heating, solid interior particle raises with temperature and is changed into unordered shape, interior energy increase, and Slow cooling can make particle
Tend to be orderly.If cooling procedure is slow enough, then arbitrary temp solid can reach thermal balance in cooling, and be cooled to
The minimum interior energy state changed under temperature conditionss can be reached during low temperature.Electric automobile can be realized by application simulation annealing algorithm
Orderly charging, i.e., under conditions of user's charge requirement is met, reduce the power budget of each charging station as far as possible, realize system
The minimum of system energy.In order to realize the rational method of sampling of this module structure of such function so that from current time
During charged state i is transitioned into the charged state j of subsequent time, if the interior energy of new state is less than original state (i.e. Ej＜ Ei)
Then receive new state j as new state；Otherwise with probabilityReceive state j, wherein k is that Boltzmann is normal
Number, here it is common Metropolis criterions.
For charging electric vehicle
Wherein niFor the number of charging pile in i charged areas, N is that electric stake divides charged area number, mjiFor j moment approach
The electric car quantity of i charged areas.
Solution space：For single period j, its solution space is more huge, has N for each vehicle for needing to charge
Individual region can select, for the m of same periodjM is shared for electric automobilej× N kinds combine, in order to avoid progress need not
The search wanted, we carry out preliminary navigation programming to vehicle first, and recording it has the charged area of preference, so being capable of pole
The earth reduces the capacity of solution space.
Object function：
Because electric car access server has sequencing, therefore scheduling of charging is also required to by a progress, for each
The electric car k newly accessed, target are all the minimums for pursuing total system interior energy.
For and function f (Pk,Qk) load condition at the charging pile current time is then reflected, the growth rate of function is remote
Higher than the growth rate of load, i.e., the high load capacity of local electric stake may cause the overall interior energy E in this area excessive.By such
Mode can constrain the load condition of each electric stake, and the minimum value of overall interior energy means that charging load uniformly divides in the region
Match somebody with somebody, realize the function of charging in order.
Charging planning for electric automobile needs to consider the influence of multiple factors, including present period electricity price P, charging pile
Real-time Load L, have electric automobile total amount N of navigation needs etc. on road.These factors must be analyzed one by one to plan charging
The influence of process could improve algorithm details.
Present period electricity price P
Electricity price is an important factor for influenceing charging planning, and main pursue a goal is exactly that efficiency maximizes for a user
(including distance travelled is most short, and running time is most short, and charging electricity price is minimum).There is no optimal solution, but this mould as multi-objective problem
Block can make it meet the needs of user as far as possible according to the preference amendment navigation algorithm of user.Electricity price regulation and control electric power a kind of
The means of trend distribution are equally applicable in the charging planning of electric car, but are slightly different in trickle charge and avatar in fast charge.
Trickle charge is typically used in family, unit, user at home and during company the time it is relatively abundant, therefore electricity can be selected as far as possible
The valency relatively low period completes charging；Compared with being instantaneity for trickle charge, user's charge requirement can not urgently wait as long for fast charge,
Now user can select the relatively low power station of neighbouring electricity price and complete charging.This module mainly considers the charging planning of fast charge form,
Electricity price reaches the closely located situation in power station as a kind of positive motivator during fast charge as the above analysis
Under, the lower power station of electricity price is bigger to the attraction of user., can be effectively real by electricity price for fairly large power network
Now to effective shunting of electric car charging load.
The Real-time Load L of charging pile
The Real-time Load of charging pile is the main regulation and control object of this module, how in the case where meeting user's request as far as possible
The load of reasonable distribution charging pile, which is that this patent is main, to pursue a goal.The Real-time Load overload of charging pile is segmented into two kinds of feelings
Condition.On the one hand, charging pile localized clusters, therefore these electric stakes can be regarded as to an independent node on geographical position.And
When these charging pile positions are all occupied, even if the node influences less, can not also receive new user and fill on network load
Electricity.On the other hand, because the fast charge power of electric automobile is larger, when charging pile meets more charging electric vehicle demands at the same time
It is excessive to be likely to result in flowing into the trend of node, by tidal current analysis formulaUnderstand, such situation can make
The brownout of partial electric grid, influences the quality of power supply.Therefore the charging load reasonable distribution of electric automobile just being seemed to, have very much must
Will.
There is the electric automobile total amount N of navigation needs on road
There is the electric automobile quantity of navigation needs more, it is meant that potential charging load is bigger.When multiple users simultaneously
, it is necessary to which diplomatic carry out charging planning when accessing navigation system.It can such as expire in the idle section of electric automobile trip, charging pile
The charge requirement of all electric automobiles of foot, now the effect of navigation algorithm is little；And the peak period in trip is largely electronic
Car is poured in a piece of charged area, and the shunting to charging vehicle now can be effectively realized by using the algorithm of present case.
Realize step：
1) the initial electricity price of present period is determined, updates the load condition of charging pile.
2) user's access is waited, sends navigation requests.
3) navigation circuit is determined according to the starting point of user and destination, directly redirected 7) if without charging；Otherwise turn
4)。
4) 5) search of total rate of electricity factor, if being redirected 8) without suitable path, otherwise turns by way of the guidance path of charging device.
Electricity price can guide the selection of user as motivator.
5) guidance path searched out is fed back into power network computational load situation E, and quantization is provided according to extent function
The parameter k of congestion level, returns it to traffic net side.
6) network of communication lines redirects according to returning whether parameter k adopts current search path by probability selection if path is adopted
7) charging pile of planning approach, is otherwise deleted, is returned back to 4).Parameter k numerical value means more greatly power network as the above analysis
Load is more uneven (local overload), then the probability for adopting current search path is smaller.
7) user's searching route success, searching route is returned.Electricity price is finely tuned with load variations, is returned back to 1).
8) user's searching route fails, and returns back to 1).
Geography information module 2 from openstreetmap by extracting required traffic network data, with node, road class
Type, longitude and latitude scope, the form of this four parameters of correlation of nodes preserve.Wherein most importantly correlation of nodes and node
Latitude and longitude coordinates, it is possible thereby to which the road for obtaining one's respective area adjoins matrix.And the transport information matrix obtained cannot be directly used to
Calculate, it is necessary to which processing further to matrix obtains node incidence matrix and special dot matrix (actual node), main step
It is：
A) node present on map is screened, remove does not have the node of correlation with surroundings nodes.
B) car lane is only retained, because only considering the charging planning of electric automobile in present case.
C) branch road extremely complex to some road conditions carries out simplifying processing, because the complexity of wall scroll branch road is to present case
Analysis without substantial influence.
Display module 2
In display module 2, using the osmdroid open source projects provided based on Open Street Map
The map API for the amplification version that osmbonuspack open source projects provide.The former is that the good of Android MapView classes is replaced
Generation, the road geodata of increasing income provided completely using Open Street Map, the latter are the versions of the former function enhancing,
Provide and more specifically operated for map denotation.The application is should based on OSMNavigator basic under osmbonuspack
Obtained with extension.
Display module is divided into three parts：Importation 21, basic tool processing data part 22, path display portion
23。
Importation 21 is supplied to application user input navigation related content, including condition and the method for constraint.Should
Completed by android GUI component AutoCompleteTextView importation.AutoCompleteTextView has
The function of prompting possible legal location name is inputted according to user, history of the data therein from user inputs and from this
The location information of ground database.User can also be by obtaining a menu, Ran Hou on map view by long-press screen
Clicked in the menu jumped out and starting point is set or terminal is set, beginning and end is set directly on map view, and program
Directly obtain the geography information of beginning and end, such as longitude and latitude.Except the input in place, according to the characteristics of this patent, it is desirable to
User inputs the percentage of dump energy by SeekBar components.This percentage can be by manually from electric car return
Acquisition of information, or interact and obtain in direct and electric car embedded system from now on.
Basic tool processing data part 22, completed, realized by a static class MyMapUtil and class Vector
Geometry calculates required function.Its mostly important application has been the geometry of the path node information returned by server
The prompt message that feature calculation operates to driver, its oriented angle is calculated for two vectors of input, then corresponds to and drives
In the various operations that the person of sailing should do.Class figure is as indicated with 2.
Path display portion 23 is established on the interface provided in osmbonuspack, and expansion, which realizes, to be inherited from
RoadManager PowerRoadManager, Marker MyMarker is inherited from, is inherited from Overlay's
MyLocationOverlay, it is inherited from MarkerInfoWindow MyMarkerInforWindow and some is right
The display format that some modifications of OSMNavigator application source files want us adds.Below will be to these classes
Function be described：The object of a RoadGetter class is combined with object corresponding to PowerRoadManager.
The object of PowerRoadManager classes collects the input information of user from GUI, then obtains one by RoadGetter classes and return
Return from the path of server, hand over a main thread for android applications to realize GUI asynchronous refresh.MyMarker classes and path
Node icon display is related.The needs of original Marker classes can not meet us, because it can only set a kind of picture.And
, it is necessary to need the node of stopping for charging and the common node that passes through to make a distinction driver in the application of patent.The part
Represent to need the node to be charged with the icon of a plug in the application.MyLocationOverlay classes are mainly used in
The icon of modification instruction GPS location.MyMakerInforWindow classes are for the peculiar letter of more suitable display this patent
Breath, i.e., information relevant with electricity.By clicking on the node on map view, user can obtain some letters on the node
Breath, such as estimated electricity residual, the distance apart from terminal of estimation, and the configured information to driver's operation and corresponding figure
Piece.In the node of charging, the picture that the part also has instruction charging is prompted.In OSMNavigator main logic,
The RoadManager that path planning accesses need to be arranged to the PowerRoadManger of integration realization by the part, and be set above-mentioned
The corresponding picture resource for being used to prompt mentioned.In addition, it is necessary to by under Historic preservation in importation.So use every time
The location name that family uses can be all saved in main logic.Class figure is as shown in Figure 3.
Geography information module 1
Geography information module 1 is divided to for two parts：One carries out API with display module 2 and docks and realize the work(such as map denotation
Can, another part docks with electric automobile scheduling computing module 4, there is provided geographic node information during navigation.
What is docked with display module 2 is geographic information encoding and Gray code part 11.Coded portion by
OpenStreetMap (OSM) API is provided.The location name of input of the geographical Gray code part to user is analyzed, first
Inquire about in the local database, if not provided, obtaining correlation by the geographical Gray code function of osmbonuspack offers again
Geographical position.Its location name for acting on i.e. by user's input is converted into latitude and longitude information, then gives server.The process
It should more be completed by server, but for fixed user, they often have conventional beginning and end, these
Information is stored in local, is worked as caching, can mitigate the burden of server.
What is docked with electric automobile scheduling computing module 4 is geographic node message part 12.Geographic node message part will
Map resolves to node sparse matrix and the coordinates matrix corresponding to each node, transmits it to electric automobile scheduling and calculates mould
Block 4 is to be navigated.
Electricity price computing module 5
Electricity price computing module 5 includes electricity price renewal part 51 and plant load k extent function F (k) calculating sections 52.
Compared with traditional automobile, traditional automobile can disposably run hundreds of kilometer after oil is full of, and electric car is past
Toward can only run several hours and speed is not as good as orthodox car, therefore the navigation for being directed to electric car has to consider its electricity
The possibility that is exhausted halfway simultaneously introduces the mechanism of charging, and charging pile is included into navigation limit of consideration.
With the development of rapid nitriding, the electric car of an almost out of power can most be full of within half an hour soon, this
Mean that electric car has extremely strong charge power, this factor is must take into consideration in the electric network model of this module.For simplification, pass
The electric network model of system can be considered the network being made up of bus, circuit, load and generating set.
For bus x, its parameter includes：
F=(θ, Vm, P5, Q5)
Wherein, F represents a bus；θ represents the phase angle of the busbar voltage；VmRepresent the busbar voltage amplitude；PgRepresenting should
Bus injection is active；QgRepresent that bus injection is idle.
Typically, its injecting power is regular after a region capital construction is complete, even foreseeable,
That is the consumption habit of this area user has certain rule.However, the charging of electric car is uncertain, people
The position that can neatly select electric car to charge, so as to introduce new load in different buses；Or have external electronic
Car charges, or internal electric car does not charge internally.The load that thus electric car is brought can not use a static curve
Prediction, and must be constantly updated according to real-time condition.Therefore for the P in conventional modelgParameter we further represented
For Pg=Pgs-Pgd, wherein PgsRepresent the predictable part of power in traditional electric network model, PgdRepresent by electric car charge-carrying belt Lai
It is uncertain and must real-time update part.
Actual power equipment has the limitation to each parameter when running, for example power can not be excessive, and voltage can not be too low.
The limitation of each parameter can be described as during to i-th bus run：
For every circuit, the complex power that it undertakes can not exceed its load, i.e.,：
Wherein Pi,Qi,SI, maxActual flow through active and reactive of this circuit and the maximum that it can be carried are represented respectively
Complex power.
If representing the bus of certain circuit both ends inflow and outflow power with subscript f, t respectively, on i-th line road
Active loss can be expressed as：
ΔSi=Sf-St
If representing the resistance of this circuit with R, X represents the reactance of this circuit, then Circuit theory shows that circuit damages
Consumption meets relation：
When being navigated to electric car, it would be desirable to meet that institute described above is restricted.In addition, on this basis,
Utilities Electric Co. wishes that whole system can be run with minimum cost.The cost of operation of power networks mostlys come from going out for generating set
Power.If use respectivelyRepresent that the cost of i-th unit depends on unit in itself with active and reactive relation, its characteristic,
The totle drilling cost of operation of power networks is all unit cost sums, i.e.,Required by Utilities Electric Co. is exactly this
It is individual that its minimum value is got by the distribution of rational trend into instinctThus this module to be studied
It it is exactly one given object function and the optimization problem of multiple Complex Constraints conditions.
Selection by 9 buses, 3 generating sets into 9 node power networks as simulation model.Shown in its concrete form Fig. 5.
The information of these power networks preserves in the matrix form in 9 node power networks.In addition, it is not that electricity consumption situation of the user in one day, which can determine,
Disconnected change rather than static to can be write as a changeless matrix.In order to emulate this situation, this module is in selection
Each load position of simulated grid model first estimates the peak load that this point is likely to occur, and preserves；One is searched out afterwards
Bar can reflect data of a certain zone user electricity consumption with time fluctuation, between this group of data are mapped into 0 to 1 in proportion, i.e.,
Can according to network of communication lines transmission come period t select corresponding with period coefficient, maximum load is multiplied by, to simulate one day
The trend of middle dynamic change.
In simulations, it is assumed that in power network on nine buses, it is to be connected with the charging pile for being available for electric car to charge to have seven.Hand over
Logical net gives the period of charging, can also provide the charging pile that the electric car will select every time.Therefore, complete power network
Situation is exactly static physical arrangement, dynamic basic user load, plus the charging load of certain period node electric car.Often
When the secondary network of communication lines accesses power network, one charge period of power network and charging locality data can be given, power network constructs complete number according to this
According to.
In order to analyze the situation of power network, this module is using the computational methods of " optimal load flow ", thus this is just by model conversation
The equation and inequality condition that voltage, electric current, power etc. must are fulfilled for for one with the minimum target of cost, during power grid operation be
The optimization problem of constraint.
In addition, the equipment of power network such as bus, wire etc. have its ultimate load, when a near nodal element
It will not also wish what electric car charged to here anyway through fast full load, during power network.Therefore, power network should also be by each section
The loading condition of point returns to the network of communication lines.To each bus, its load factor is defined：
The peak load that the power flowed through on all branch roads that will be joined directly together with the bus can bear with the branch road
Compare, the load factor of the bus just takes the minimum value in these ratios.Because for a bus, as long as phase therewith
The circuit for also having light load even, then it can be always transferred load on this circuit to prevent certain line load
It is overweight.And electric load satisfaction now is complementary with load factor.
Communication module 3
Communication module 3 is divided to for two funtion parts：First, TCP/IP hops 31, send to user in display module
Information is received and is transferred to electricity price computing module 5 and electric automobile scheduling computing module 4.Second, encapsulation JSON format transmissions
Part 32, the information sent to electric automobile scheduling computing module 4 carry out the encapsulation of json forms and return to display module 2.
Communication module exchanges data with server end, starting point geographical coordinate from communication module to server end transmitting path,
Terminal geographical coordinate and information about power, electricity price computing module 5 will directly read the number with electric automobile scheduling computing module 4
According to, and it is further processed.
And the path-related information received from electric automobile scheduling computing module 4, this module is using JSON forms to it
It is packaged to facilitate transmission and parsing.JSON (JavaScript Object Notation) is that a kind of data of lightweight are handed over
Change form.JSON makes JSON turn into preferable data interchange language using the text formatting for being totally independent of language, these characteristics.
It is easy to people to read and write, while is also easy to machine parsing and generation.
The work specific object as corresponding to the RoadGetter classes of this module for receiving JSON files is completed, and such have recorded
Behind port corresponding to the IP and server program of server, after the inquiry request of user is initiated, in new thread asynchronously
A TCP is set up with server to connect, and the Query Information of above-mentioned user is sent to server, and input and wait by block type
Come from the result of calculation of server.In such, also achieve from the result of json forms to path data class RoadData
The parsing and conversion of corresponding object and from RoadData to the structure of class Road corresponding objects.In addition, to driver
The prompting of mobility operation, such as keep straight on, turn left, the prompt message such as turn around also is prescribed in such and the return according to server
As a result it is configured.Because the path node of reality is than path node that osmbonuspack (referring to display module 2) is provided
Will be complicated it is more, be the most significantly exactly, except the distance apart from terminal and the time also to be spent, remaining electricity etc. also by
Preserve.In addition, it is that the common node to be charged by node or needs stop is also necessary to distinguish this node
's.These work are completed by the PowerRoadNode for being inherited from RoadNode.Class figure is as shown in Figure 6.
The specifically used method of the present invention is as follows：
(1) user directly inputs place name, clicks on search and is searched or terminus is directly set in map view.
(2) user inputs residual power percentage.
(3) route searching of waiting for server.
(4) user enters navigation module, reads the electricity price data and load data at current time
When ignoring the load that electric car charging introduces, optimal load flow solves in the case of emulation only has user base load
Each charging pile position electricity price, it is as shown in table 1 below：
Obtain the loading level such as table 2 below of each node：
(5) navigation algorithm to route result solve simultaneously returned data
(6) it can be seen that what is shown is returned from the optimal path of server in map view.
It may need on the way to be charged in the case where beginning and end is the same, when electricity is less
(7) node on path is clicked on, it can be seen that corresponding prompt message.
It should be noted last that the above embodiments are merely illustrative of the technical solutions of the present invention and it is unrestricted, although ginseng
The present invention is described in detail according to preferred embodiment, it will be understood by those within the art that, can be to invention
Technical scheme is modified or equivalent substitution, and without departing from the spirit and scope of technical solution of the present invention, it all should cover
Among scope of the presently claimed invention.
Claims (5)
1. a kind of charging electric vehicle navigation system based on real-time data of power grid, it is characterised in that including geography information module
(1), display module (2), communication module (3), electric automobile scheduling computing module (4) and electricity price computing module (5)；
Described communication module (3), electric automobile scheduling computing module (4), electricity price computing module (5) and geography information module
(1) a part forms server end, and described display module (2) and another part of geography information module (1) form client
End, client interact with user, and server-side processes data simultaneously return to it；
In server end：
Described geography information module (1) obtains geography information, and is transferred to described electric automobile scheduling computing module (4) and uses
In path planning；
Described communication module (3) receives the user request information transmitted by display module (2), and is transferred to electric automobile scheduling
Computing module (4) carries out path planning, while temporal information is transferred into electricity price computing module (5) and calculated for Spot Price,
Path navigation information is returned to display module by communication module (3) after electric automobile scheduling computing module (4) has planned path
(2)；
The electric automobile scheduling computing module (4) receives the user request information from communication module (3), and electricity price calculates
The plant load satisfaction calculated of module (5), comprehensive electric stake information provide possible alternative path, and alternative path will be made
Input and temporal information for electricity price computing module, power station loading condition calculate an extent function jointly；If received
So the loading condition in power station will be updated, conversely, scheduler module will recalculate feasible alternative path, repeat above-mentioned mistake
Journey；
Described electricity price computing module (5), which obtains, to be come from the temporal information of communication module (3), dispatches calculating from electric automobile
The alternative path information of module (4) and the loading condition of power system, to calculate plant load satisfaction, and by alternative path
Receiving whether feed back to electric automobile scheduling computing module (4)；
In client：
Described geography information module (1) obtains geography information, and is transferred to described display module (2) and is used for show map；
Described display module (2) transmits the demand information of user to described communication module (3), and is connect from communication module (3)
The routing information planned is received, is shown on map.
2. the charging electric vehicle navigation system according to claim 1 based on real-time data of power grid, it is characterised in that institute
The geography information module (1) stated includes geographic information encoding and Gray code part (11) and geographic node message part (12).
3. the charging electric vehicle navigation system according to claim 1 based on real-time data of power grid, it is characterised in that institute
The display module (2) stated includes importation (21), basic tool processing data part (22) and path display portion (23).
4. the charging electric vehicle navigation system according to claim 1 based on real-time data of power grid, it is characterised in that institute
The communication module (3) stated includes TCP/IP hops (31) and encapsulation JSON format transmissions part (32).
5. the charging electric vehicle navigation system according to claim 1 based on real-time data of power grid, it is characterised in that institute
The electricity price computing module (5) stated includes electricity price renewal part (51) and plant load k extent function F (k) calculating sections
(52)。
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| CN107135222A (en) * | 2017-05-05 | 2017-09-05 | 深圳市牛牛智能设备有限公司 | For the communication equipment of self-service charging, server, self-service charging device and method |
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| DE102019121848A1 (en) * | 2019-08-14 | 2021-02-18 | Wobben Properties Gmbh | Method for operating a charging station for electric vehicles |
| CN110704943B (en) * | 2019-09-10 | 2021-06-04 | 浙江大学 | Parameterized intelligent simulation platform for interaction of electric vehicle pile vehicles |
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