CN106816931A - The orderly charge control method of electric automobile charging station - Google Patents
The orderly charge control method of electric automobile charging station Download PDFInfo
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- CN106816931A CN106816931A CN201710137710.2A CN201710137710A CN106816931A CN 106816931 A CN106816931 A CN 106816931A CN 201710137710 A CN201710137710 A CN 201710137710A CN 106816931 A CN106816931 A CN 106816931A
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Classifications
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- H02J7/0027—
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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
- B60L53/80—Exchanging energy storage elements, e.g. removable batteries
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/004—Artificial life, i.e. computing arrangements simulating life
- G06N3/006—Artificial life, i.e. computing arrangements simulating life based on simulated virtual individual or collective life forms, e.g. social simulations or particle swarm optimisation [PSO]
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06315—Needs-based resource requirements planning or analysis
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/06—Electricity, gas or water supply
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- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
- H01M10/00—Secondary cells; Manufacture thereof
- H01M10/42—Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells
- H01M10/44—Methods for charging or discharging
- H01M10/441—Methods for charging or discharging for several batteries or cells simultaneously or sequentially
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
- H02J7/02—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries for charging batteries from ac mains by converters
-
- 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
- B60L2200/00—Type of vehicles
- B60L2200/24—Personal mobility 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
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02E60/10—Energy storage using 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
- Y02T10/70—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
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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
- Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02T90/10—Technologies relating to charging of electric vehicles
- Y02T90/14—Plug-in electric vehicles
-
- 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
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
Abstract
The present invention relates to a kind of orderly charge control method of electric automobile charging station, discretization battery charge state grade；Obtain electric automobile and change electric demand；The orderly charge model of electric charging station with Fill valley as target is built, and determines the fitness function of orderly charge control as index with the sum of squares of deviations of load；The optimal solution of the orderly charge control of electrical changing station is solved using improved cuckoo searching algorithm according to the fitness function established, the charging schedules table of battery is then formulated for electrical changing station according to the optimal solution for solving.The orderly charging and conversion electric control method for being easy to electrical changing station manager to operate, obtain comprising the electric automobile quantity for participating in changing electricity service per the period, participate in charging behavior changes the orderly charging and conversion electric scheduling scheduling of number of batteries electrical changing station, to meet while electrical changing station day-to-day operations, the effect to regional power grid Fill valley is realized.
Description
Technical field
It is more particularly to a kind of to be changed based on the electric automobile for improving cuckoo algorithm the present invention relates to a kind of electric vehicle engineering
The orderly charge control method in power station.
Background technology
Electric automobile as a kind of key technology of energy-saving and emission-reduction, be it is following solve approach that energy crisis generally has an optimistic view of it
One.With the constantly improve and its potentiality at cost-effective aspect of electric automobile cornering ability, automobile user group is not
Disconnected expansion.At present, electric car electric energy supply form has vehicle charging and changes electric two ways.Vehicle charges and can be divided into slotting
Fill (including filling soon and trickle charge) and wireless charging.Insert under mold filling formula, on the one hand, its energy supplement is time-consuming oversize for car owner,
General to want 4-5 hours (fill also needs to take more than 30 minutes soon), convenience far can not meet the requirement of people；On the other hand,
For its is social, the pattern needs foundation construction facility, is related to the multi-party harmony of interests (such as car owner, grid company, cell thing
Industry etc.), and because some problems are not yet coordinated and constrain the extensive construction of charging pile significantly.Wireless charging, also known as nothing
Line is powered, and is in the way of a kind of electromagnetic field to couple realizes that electric energy is transmitted as medium.Wireless charging has easy to use, peace
Entirely, no-spark and the advantages of Danger Electric shock risk, therefore, it was recognized that its application prospect in terms of charging electric vehicle.However,
Current electric automobile wireless power energy transfer efficiency lowly turns into the Main Bottleneck of its development of restriction.Additionally, either insert filling
Or wireless charging, charging electric vehicle load all has obvious time and spatial location laws, this is by the operation to power network
Great challenge is proposed with planning.
Based on rentable battery change power mode with the convenience of the rapidity of its energy recharge and Charge Management at present
Commercial technology pattern as the selection of user's tendency, power network attention, first, typically can be in 1 to 2 minute just using power mode is changed
Electric process is changed in completion, and its convenience is not defeated in current conventional oiling mode；Secondly, can be effective using concentrated management to battery
Avoid extensive electric automobile from charging at random the adverse effect brought to power network, or even can also be cooperateed with renewable energy power generation
Operation, it is to avoid green energy resource loses, reduces cost of electricity-generating.
To by changing the battery that electric service is changed, if just input grid charging is likely to result in distribution network line overload immediately,
Voltage Drop, distribution transformer overload, power distribution network peak-valley difference aggravation, the phenomenon at " on peak plus peak " occurs, so must be to electrical changing station
Change electricity be controlled by with charging service, to eliminate its adverse effect to power network.And existing have for electric automobile at present
The realization of sequence charge control is realized by controlling charge power, and this is difficult to be precisely controlled in practical application, because
For quantity and the time of the dispensing of rechargeable battery are more conveniently controlled in reality for electrical changing station manager.
The content of the invention
The present invention be directed to the problem to electric automobile charging station reasonable management, it is proposed that a kind of electric automobile charging station has
Sequence charge control method, the orderly charging and conversion electric control method for being easy to electrical changing station manager to operate obtains being changed comprising the participation per the period
The electric automobile quantity of electricity service, participate in charging behavior changes the orderly charging and conversion electric scheduling scheduling of number of batteries electrical changing station, to meet
While electrical changing station day-to-day operations, the effect to regional power grid Fill valley is realized.
The technical scheme is that：A kind of orderly charge control method of electric automobile charging station, specifically includes following step
Suddenly：
1) it is according to the size that battery charge state increment is changed in unit charging interval step-length that the state-of-charge of battery is discrete
Change, institute's band carrying capacity interval is divided into M grade：
2) the electric automobile demand information of electrical changing station inbound is obtained, day part inbound electric automobile sum, and in treating
Charge, charging neutralizes the electric automobile quantity of full state；
3) set up an orderly charging and conversion electric model, in electricity and battery charge control are changed electric automobile when the model is with t
Quantity u (t, m) of the m grades of state-of-charge battery that section input charges is controlled quentity controlled variable, to minimize the deviation square of load curve
Be target；
4) by improving cuckoo algorithm initialization Bird's Nest, obtain each charged grade and enter the numbers matrix u for chargingT×MWith
Charging Matrix C in optimization cycle TTxMAs initial Bird's Nest information, with improving cuckoo algorithm to step 3) in fill change in order
Electric model is solved, and the sum of squares of deviations of load curve is the fitness function in cuckoo algorithm, obtains charging and conversion electric arrangement
Table；
5) orderly charge control is carried out to the battery in electrical changing station according to the charging and conversion electric calendar for obtaining.
It is described with improving cuckoo algorithm to step 3) in order charging and conversion electric model carry out solution and comprise the following steps that：
(1), algorithm parameter is set and Bird's Nest information is initialized, the initialization Bird's Nest includes u in each Bird's NestT×MMatrix
And CT×MThe information of matrix, comprises the following steps that：
A, u (t, m) is randomly generated according to D (t, m), state-of-charge is in m in pond to be charged wherein in D (t, m) t periods
The number of batteries of level is D (t, m), and u (t, m) represents the m grades of number of state-of-charge grade battery that t periods decision-making input charges
Amount；
B, C (t, m) is calculated according to u (t, m), wherein C (t, m) is that state-of-charge is in m in the battery that the t periods are charging
The cell number of level；
C, judgementWhether set up, wherein N1 represents the quantity of charger in electrical changing station, if into
Vertical, then (t+1, m)=D (t, m)-u (t, m)+s (t, m), F (t+1)=F (t)-s (t)+f (t), and make t=t+1 turn to calculate D
To step D；If inequality is invalid, step A is gone to, wherein s (t, m) is to receive the t periods to change at electricity service and state-of-charge
In m grades of electric automobile quantity, F (t) represents the full electricity battery stockpile number of t periods electrical changing station, and s (t) is represented in the t periods and received
The electric automobile quantity of electricity service is changed, f (t) represents number of batteries just fully charged in the t periods；
D, judge t<Whether T sets up, T represent in optimization cycle it is total when hop count, if so, go to step A, if not into
It is vertical, go to step E；
E, end initialization, export initial Bird's Nest information；
(2), the sum of squares of deviations with load curve calculates each Bird's Nest fitness value and evaluates as fitness function；
(3), calculate levy flights searching route and binary translation is carried out to the path；
(4), the routing update Bird's Nest in (3rd) step, calculates the fitness value of each new Bird's Nest and evaluates；
(5) relatively bad nest, is given up with the probability selection of pa, the binary coding according to the bad nest given up generates its quantum
Position coding, recycles Quantum rotating gate to produce new Bird's Nest to substitute the nest being rejected, and calculates the fitness value of new nest and evaluates；
(6), select contemporary optimal solution and preserve, judge whether to meet iterated conditional, if meeting, step (1) is gone to, if not
Meet, go to step (7)；
(7) optimal solution, is exported.
Carrying out binary translation specific method to path in the step (3) is：
Liu Jianhua's formula is introduced into the conversion of levy flights searching route：
When step≤0,
Work as step>When 0,
Wherein, xm, xm+1Certain the position binary coding of m generations and m+1 for Bird's Nest is not represented, and step represents that Levy flies
The path of line search,Parameter μ, ν is the random number of Normal Distribution, and sig () represents Sigmond functions, β
It is parameter, its span is between [0,2].
Binary coding generates its quantum bit coding in the step (5), is exactly to be generated at random on interval [- 1,1]
Beta, bits of coded is the position of " 1 " in finding binary coding, if corresponding beta values are more than 0.5 on the position, is repaiied
0.5 is changed to, alpha quantum bit matrix are generated further according to the beta quantum bits changed.
The self adaptation anglec of rotation is defined as in the rotation of quantum door in the step (5)：
In formula：θminIt is minimum
The anglec of rotation, θmaxIt is the maximum anglec of rotation, fiRefer to choose i-th adaptive value of Bird's Nest, f in the Bird's Nest to be given upminIt is contemporary bird
Minimum adaptive value in nest, fmaxIt is the maximum adaptation value in contemporary Bird's Nest, gen is current number of iterations, and maxgen is that algorithm sets
The greatest iteration number put.
The beneficial effects of the present invention are：The orderly charge control method of electric automobile charging station of the present invention, can jump out part
Optimal solution, convergence rate is good, and the charging schedules scheme of gained can effectively play Fill valley use, and can be widely applied to electrical changing station has
Sequence charging and conversion electric control field.
Brief description of the drawings
Fig. 1 is the orderly charge control method flow chart of electric automobile charging station of the present invention；
Fig. 2 is the flow chart that the present invention improves cuckoo algorithm；
Fig. 3 is the moving model figure of the electric charging station of one embodiment of the invention；
Fig. 4 is that charging and conversion electric in order of the invention is controlled and the load chart under unordered charging；
Fig. 5 is the iteration convergence figure of improvement cuckoo algorithm in the embodiment of the present invention；
Iteration convergence figure when Fig. 6 is in the embodiment of the present invention using genetic algorithm.
Specific embodiment
The present invention provides a kind of orderly charging and conversion electric control method of electric automobile charging station.Specifically include as shown in Figure 1 as follows
Step：
First, it is according to the size that battery charge state increment is changed in unit charging interval step-length that the state-of-charge of battery is discrete
Change：Discretization battery charge state is characterized in：If state-of-charge is 1 when battery is full electric, the state-of-charge of empty battery is 0, if single
The charged increment that (such as 1h) charging causes in the scheduling time step-length of position is Δ SOC, then the carrying capacity interval that kth grade is represented is
[(k-1) Δ SOC, k Δ SOC), it is divided into M grade；
2nd, the electric automobile demand information of electrical changing station inbound is obtained, electricity is exchanged according to the electric automobile demand information for obtaining
Electric automobile in standing changes electricity, the charging to changing battery in electrical changing station and is controlled.
Electric automobile demand information includes：Day part inbound electric automobile sum, and in each grade state-of-charge
Electric automobile quantity.
Electricity and exchange battery charge control are changed electric automobile, including：It is determined that into the electric automobile number for changing electric service area
Amount ST×M, determine that each charged grade enters the numbers matrix u for chargingT×M, wherein T represent in optimization cycle it is total when hop count, M tables
Show the number of degrees of battery charge state point.
It is determined that into change electricity service electric automobile numbers matrix ST×MProcess, the matrix is the matrix of T rows M row,
Element is s (t, m) in matrix, and it is meant that the t periods receive to change electricity service and state-of-charge is in m grades of electric automobile quantity
It is s (t, m)；If having N in electrical changing station2Set battery replacement device, the time that often set battery replacement device completes once to service needs is Ds, t
Period, full electricity battery stockpile number was F (t), and it is E (t, m) to wait electric automobile quantity to be charged.
First pass through formulaS (t) is obtained, S (t) is to receive to change electric clothes
The sum of business, then passes throughS (t, m) is obtained, that is, determines that each charged grade receives
The quantity of electricity service is changed, the s (t, m) and S (t) that then will be obtained bring formula intoInspection, if being unsatisfactory for
Then appropriate to adjust s (t, m), because automobile is integer, and ratio is likely to be decimal, final to ensure all charging vapour in the t periods
Car sum with etc. the total ratio to be charged=m grades ratio that receives to charge with the quantity automobile number to be charged such as m grades, that is,
The automobile quantity that the carrying out for obtaining changes electricity service is integer.
Charging Matrix C in optimization cycle TT×MWith following characteristics：Charging Matrix CT×MIt is an integer square of T rows M
Battle array, element is c (t, m) in matrix, and it is meant that state-of-charge in the battery for charging the t periods is in m grades of cell number；Then
The quantity that t periods the first state-of-charge grade battery is in charged state is c (t, 1)=u (t, 1), when wherein u (t, 1) represents t
The quantity of the first state-of-charge grade battery that section decision-making input charges；T periods state-of-charge is in m grades of battery and is in and charges
The quantity of state is c (t, m)=c (t-1, m-1)+u (t, m), wherein：C (t-1, m-1) represents the electricity for charging the t-1 periods
State-of-charge is in m-1 grades of cell number in pond, and u (t, m) represents the m grades of state-of-charge grade that t periods decision-making input charges
The quantity of battery.
Just fully charged cell number is f (t)=c (t-1, M) in the t periods, wherein：C (t-1, M) was represented in the t-1 periods
State-of-charge is in the cell number of M grades (i.e. highest state-of-charge grade).
The full electricity battery stockpile number matrix F of electrical changing station in optimization cycle TT×1With following characteristics：Full electricity battery stock's matrix
FT×1It is an INTEGER MATRICES for the row of T rows 1, element is F (t) in matrix, its stock for being meant that the full electricity battery of t periods electrical changing station
Quantity is F (t)；Then F (t)=F (t-1)-S (t-1)+f (t-1), wherein：F (t-1) represents the full electricity battery of t-1 periods electrical changing station
Stockpile number, S (t-1) is represented and is received the electric automobile quantity for changing electricity service in the t-1 periods, and f (t-1) is represented in the t-1 periods just
Good fully charged number of batteries.
Electrical changing station numbers matrix D in pond to be charged in optimization cycle TT×MWith following characteristics：The matrix is a T rows M row
INTEGER MATRICES, element is D (t, m) in matrix, and it is meant that in the t periods that state-of-charge is in m grades of battery in pond to be charged
Quantity is D (t, m), then (t-1, m) (t-1, m) (t-1, m), (t-1 m) is represented and treated in the t-1 periods D+s-u D (t, m)=D in formula
State-of-charge is in m grades of number of batteries in rechargable battery, and (t-1 m) represents m grades of decision-making input charging in the t-1 periods to u
The quantity of state-of-charge grade battery, (t-1 m) represents that electricity service is changed in receiving and state-of-charge is in m grades in the t-1 periods to s
Electric automobile quantity.
3rd, set up an orderly charging and conversion electric model, in electricity and battery charge control are changed electric automobile when the model is with t
Quantity u (t, m) of the m grades of state-of-charge battery that section input charges is controlled quentity controlled variable, to minimize the deviation square of load curve
Be target, consider state-of-charge transfer characteristic, electrical changing station satisfaction demand, affiliated substation capacity limitation require etc. about
Beam.
4th, a kind of improved cuckoo algorithm is proposed, flow chart as shown in Figure 2 is above-mentioned orderly for solving by the algorithm
Charge model, solution efficiency is high, is difficult to be absorbed in local optimum, and solution obtains charging and conversion electric calendar.The algorithm is comprised the following steps：
The 1st, algorithm parameter is set and Bird's Nest position is initialized；2nd, the sum of squares of deviations with load curve calculates each bird as fitness function
Nest fitness value is simultaneously evaluated；3rd, calculate levy flights searching route and binary translation is carried out to the path；4th, according in the 3rd step
Routing update Bird's Nest, the fitness value for calculating each new Bird's Nest simultaneously evaluates；5th, relatively bad nest is given up with the probability selection of pa, according to
The binary coding of these bad nests given up generates its quantum bit coding, recycles Quantum rotating gate to produce new Bird's Nest to substitute quilt
The nest given up, calculates the fitness value of new nest and evaluates；6th, select contemporary optimal solution and preserve, judge whether to meet iteration bar
Part, if meeting, goes to step 1, if it is not satisfied, going to step 7；7th, optimal solution is exported.
Cuckoo algorithm initialization Bird's Nest is improved, u is included in each Bird's NestT×MMatrix and CT×MThe information of matrix, specific step
It is rapid as follows：1st, u (t, m) is randomly generated according to D (t, m)；2nd, C (t, m) is calculated according to u (t, m)；3rd, judgeWhether set up, wherein N1 represents the quantity of charger in electrical changing station, if so, then calculate D (t+1,
M)=D (t, m)-u (t, m)+s (t, m), F (t+1)=F (t)-S (t)+f (t), and t=t+1 is made, go to step 4；If inequality
It is invalid, then go to step 1；4th, t is judged<Whether T sets up, if so, step 1 is gone to, if not, go to step 5；5th, tie
Beam is initialized, and exports initial Bird's Nest information.
Conventional cuckoo algorithm can only solve continuous type optimization problem, herein by levy flight path discretizations,
Exactly carried out binary translation, it is so discrete after so that cuckoo algorithm can solve problem in terms of integer optimization also just
It is that the solution solved after so improving can only be nonnegative integer.Levy flights searching route two is entered in improvement cuckoo algorithm
System conversion：Liu Jianhua's formula is introduced into the conversion of levy flights searching route, it is specific as follows：
When step≤0,
Work as step>When 0,
Wherein, xm, xm+1Certain binary coding of m generations and m+1 for Bird's Nest is not represented, and step represents that Levy flies
The path of search,Parameter μ, ν is the random number of Normal Distribution, and sig () represents Sigmond letters
Number, β is a parameter, and without practical significance, its span typically takes 1.5 between [0,2].
Quantum bit coding is generated according to binary coding, random generation beta, finds binary system volume on interval [- 1,1]
Bits of coded is the position of " 1 " in code, if corresponding beta values are more than 0.5 on the position, is changed to 0.5, further according to repairing
The beta quantum bits generation alpha quantum bit matrix corrected one's mistakes.
Quantum door rotary course is a kind of self adaptation quantum rotation process, adaptively selected quantum rotation angle, it is to avoid by
In the anglec of rotation is long be absorbed in local optimum and the too small anglec of rotation when algorithmic statement time too long of phenomenon occur, it is implemented
Process is as follows：General Quantum rotating gate expression formula is：Then revolved by quantum
Revolving door update after quantum bit be：Wherein θiIt is i-th angle of the quantum bit rotation of individuality,
That is the anglec of rotation, the self adaptation anglec of rotation is defined as in the present invention：
In formula：θminIt is minimum
The anglec of rotation, θmaxIt is the maximum anglec of rotation, fiIt is i-th adaptive value of individuality, refers to choose in the Bird's Nest to be given up in the present invention
The i adaptive value of Bird's Nest, fminIt is the minimum adaptive value in contemporary Bird's Nest, fmaxIt is the maximum adaptation value in contemporary Bird's Nest, gen is
Current number of iterations, maxgen is the greatest iteration number that algorithm is set.So, if the Bird's Nest currently to be given up is preferable, adopt
Operation is updated with the less anglec of rotation of step-length produces new nest to substitute the nest given up, and if the nest to be given up is poor
When, the step-length of the anglec of rotation also accordingly becomes greatly to carry out the nearly search of quickly contracting, to expect to find more preferable nest to substitute
The Bird's Nest given up.So modified hydrothermal process had not only improve its search speed but also had not lost its search precision.
As shown in figure 3, having N in electric charging station1Individual charging pile, N2Set battery replacement device is (i.e. while most multipotency is N2Platform is electronic
Automobile is provided and changes electric service), battery sum is B blocks.Whole electrical changing station moving model can regard one as and is made up of electric automobile
Open loop queuing system and the big system that is coupled to form of a closed loop queuing system constituted by changing battery.T, electrical changing station is
There is E (t) electric motor car waiting electricity service to be changed, and now there is e (t) new electric automobile to enter electrical changing station, these are electronic
Automobile may directly change electricity service or change electricity into queue queue etc. is to be subjected, if the stand-by period is long, electric automobile may
Abandon changing electricity and sail out of electrical changing station, it is assumed that t has d (t) to abandon changing electricity, then actually enter and change electric field and carry out changing electric behavior
Electric automobile is s (t).The battery for charging in full electricity battery (FCB) and pond to be charged (DB) and charging place is constituted
One queuing system of closed loop.T, electrical changing station has the full electricity battery of F (t) blocks and D (t) blocks pond to be charged respectively, completes to change
After electricity service, there are s (t) blocks to leave full battery queue again, into pool queue to be charged.At the same time, there are f (t) block batteries complete
Into charging, into full battery queue, then electrical changing station manager according to different this moment of purpose decision-making allows u (t) blocks to treat
Rechargable battery is charged into charging place.(all s (t), F (t) etc. are referred on this time cross-section of t periods in this section
The quantity of all kinds of batteries)
Specific embodiment of the invention is illustrated with reference to one embodiment of the present of invention.In this embodiment, filled with somewhere
Based on electrical changing station service data, 1h is taken for a period, all batteries that change are same model in electrical changing station, with BYD
As a example by E6 battery parameters, charged using invariable power mode.Charger quantity is 100 in standing, and separate unit charger charge power is
40kw, it is 200 pieces to change battery sum, and every piece is changed battery capacity for 200kwh, and the state-of-charge of battery is divided into 5 etc.
Level, the predicted value such as following table of enter the station electric automobile quantity and its charged level condition of electrical changing station one day：
This day charging and conversion electric of electrical changing station is then obtained according to orderly charging and conversion electric control method of the present invention and arranges such as following table：
Fig. 4 shows that this is controlled and the load curve under unordered charging using the orderly charging and conversion electric described in invention；Generally by electricity
Electrical automobile battery is to change the unordered charge mode filled as electric charging station, i.e., do not consider the letter such as state-of-charge of station battery
Breath, only arranges it to charge until charging pile is completely in working condition by changing the sequencing that battery arrives at a station.In unordered charging
In the case of, easily there is " peak-to-peak overlap " phenomenon, the former load curve of contrast, the situation in the original load of power network and electrical changing station charging load
The sum of squares of deviations of the load curve after lower superposition charging load, peak value, peak-valley difference have more obvious increase；And use this
In the case of inventing the orderly charging and conversion electric control method for proposing, though the load curve peak value after superposition has slightly increase, its peak
Paddy difference and sum of squares of deviations have obvious reduction, illustrate the validity of orderly charging and conversion electric control method of the present invention,
And a kind of feasibility for improving cuckoo algorithm of the present invention.
The iteration convergence figure of cuckoo algorithm is improved in embodiments of the invention shown by Fig. 5；Same reality shown by Fig. 6
Iteration convergence figure when applying example using genetic algorithm.From fig. 6 it can be seen that genetic algorithm preconvergence speed, then
Phase convergence rate slows down, and is easier to be absorbed in locally optimal solution；And as seen from Figure 5, improved cuckoo algorithm preconvergence speed
Well, later stage (after the about the 60th generation) algorithm makes optimization problem jump out local optimum.In terms of algorithm parameter setting, cuckoo is improved
The Bird's Nest number of bird is less than the half of the population number of genetic algorithm, and its population diversity is better than genetic algorithm, and this explanation is originally
The described improvement cuckoo algorithm improvement of invention can improve the global diversity (i.e. global optimizing ability) of algorithm, while again not
Increase algorithm scale.To sum up, the improvement cuckoo algorithm for being carried is compared with genetic algorithm there is method to have superiority.
Claims (5)
1. the orderly charge control method of a kind of electric automobile charging station, it is characterised in that specifically include following steps：
1) according to state-of-charge discretization of the size by battery that battery charge state increment is changed in unit charging interval step-length, will
Institute's band carrying capacity interval is divided into M grade：
2) obtain electrical changing station inbound electric automobile demand information, day part inbound electric automobile sum, and in it is to be charged,
Charge and neutralize the electric automobile quantity of full state；
3) set up an orderly charging and conversion electric model, the model is thrown with the t periods in electricity and battery charge control are changed electric automobile
Quantity u (t, m) for entering m grades of state-of-charge battery of charging is controlled quentity controlled variable, is with the sum of squares of deviations for minimizing load curve
Target；
4) by improving cuckoo algorithm initialization Bird's Nest, obtain each charged grade and enter the numbers matrix u for chargingT×MAnd optimization
Charging Matrix C in cycle TTxMAs initial Bird's Nest information, with improving cuckoo algorithm to step 3) in charging and conversion electric mould in order
Type is solved, and the sum of squares of deviations of load curve is the fitness function in cuckoo algorithm, obtains charging and conversion electric calendar；
5) orderly charge control is carried out to the battery in electrical changing station according to the charging and conversion electric calendar for obtaining.
2. the orderly charge control method of electric automobile charging station according to claim 1, it is characterised in that described with improving
Cuckoo algorithm is to step 3) in order charging and conversion electric model carry out solution and comprise the following steps that：
(1), algorithm parameter is set and Bird's Nest information is initialized, the initialization Bird's Nest includes u in each Bird's NestT×MMatrix and
CT×MThe information of matrix, comprises the following steps that：
A, u (t, m) is randomly generated according to D (t, m), state-of-charge is in m grades in pond to be charged wherein in D (t, m) t periods
Number of batteries is D (t, m), and u (t, m) represents the m grades of quantity of state-of-charge grade battery that t periods decision-making input charges；
B, C (t, m) is calculated according to u (t, m), wherein C (t, m) is that state-of-charge is in m grades in the battery that the t periods are charging
Cell number；
C, judgementWhether set up, wherein N1 represents the quantity of charger in electrical changing station, if so, then
(t+1, m)=D (t, m)-u (t, m)+s (t, m), F (t+1)=F (t)-S (t)+f (t), and make t=t+1 go to step to calculate D
D；If inequality is invalid, step A is gone to, wherein s (t, m) is to receive the t periods to change electricity service and state-of-charge is in m grades
Electric automobile quantity, F (t) represents the full electricity battery stockpile number of t periods electrical changing station, and s (t) is represented and receive in the t periods and change electric clothes
The electric automobile quantity of business, f (t) represents number of batteries just fully charged in the t periods；
D, judge t<Whether T sets up, T represent in optimization cycle it is total when hop count, if so, go to step A, if not, turn
To step E；
E, end initialization, export initial Bird's Nest information；
(2), the sum of squares of deviations with load curve calculates each Bird's Nest fitness value and evaluates as fitness function；
(3), calculate levy flights searching route and binary translation is carried out to the path；
(4), the routing update Bird's Nest in (3rd) step, calculates the fitness value of each new Bird's Nest and evaluates；
(5) relatively bad nest, is given up with the probability selection of pa, the binary coding according to the bad nest given up generates its quantum bit and compiles
Code, recycles Quantum rotating gate to produce new Bird's Nest to substitute the nest being rejected, and calculates the fitness value of new nest and evaluates；
(6), select contemporary optimal solution and preserve, judge whether to meet iterated conditional, if meeting, go to step (1), if discontented
Foot, goes to step (7)；
(7) optimal solution, is exported.
3. the orderly charge control method of electric automobile charging station according to claim 2, it is characterised in that the step (3)
In binary translation specific method carried out to path be：
Liu Jianhua's formula is introduced into the conversion of levy flights searching route：
When step≤0,
As step ＞ 0,
Wherein, xm, xm+1Certain the position binary coding of m generations and m+1 for Bird's Nest is not represented, and step represents Levy flight search
Path,Parameter μ, ν is the random number of Normal Distribution, and sig () represents Sigmond functions, and β is ginseng
Number, its span is between [0,2].
4. the orderly charge control method of electric automobile charging station according to claim 3, it is characterised in that the step (5)
Middle binary coding generates its quantum bit coding, is exactly the random generation beta on interval [- 1,1], finds binary coding
Middle bits of coded is the position of " 1 ", if corresponding beta values are more than 0.5 on the position, is changed to 0.5, further according to modification
The beta quantum bits generation alpha quantum bit matrix crossed.
5. the orderly charge control method of electric automobile charging station according to claim 3, it is characterised in that the step (5)
The self adaptation anglec of rotation is defined as in middle quantum door rotation：
In formula：θminIt is minimum rotation
Angle, θmaxIt is the maximum anglec of rotation, fiRefer to choose i-th adaptive value of Bird's Nest, f in the Bird's Nest to be given upminIn being contemporary Bird's Nest
Minimum adaptive value, fmaxIt is the maximum adaptation value in contemporary Bird's Nest, gen is current number of iterations, and maxgen is that algorithm is set
Greatest iteration number.
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| CN107944712A (en) * | 2017-11-28 | 2018-04-20 | 国网上海市电力公司 | Concentrated electrical changing station addressing constant volume method based on the strong property of electric network composition |
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