CN106503845A - A kind of charging station method of allocation plan that is schemed based on V with HS algorithms - Google Patents
A kind of charging station method of allocation plan that is schemed based on V with HS algorithms Download PDFInfo
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- CN106503845A CN106503845A CN201610915926.2A CN201610915926A CN106503845A CN 106503845 A CN106503845 A CN 106503845A CN 201610915926 A CN201610915926 A CN 201610915926A CN 106503845 A CN106503845 A CN 106503845A
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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
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
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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
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- G—PHYSICS
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- G07F—COIN-FREED OR LIKE APPARATUS
- G07F15/00—Coin-freed apparatus with meter-controlled dispensing of liquid, gas or electricity
- G07F15/003—Coin-freed apparatus with meter-controlled dispensing of liquid, gas or electricity for electricity
- G07F15/005—Coin-freed apparatus with meter-controlled dispensing of liquid, gas or electricity for electricity dispensed for the electrical charging of vehicles
Abstract
The invention discloses a kind of charging station method of allocation plan that is schemed based on V with HS algorithms.First, expected by charging queue time, estimate the charging station scope that builds in planning region；Secondly, many factors such as charge requirement, region characteristic are considered, to take, in the Construction and operation cost of charging station, way of charging, the target that cost and the queue time cost three that arrives at a station set up charging station allocation plan；Finally, random generation charging station site location in planned range, and one-dimensional vector is encoded into site location, each charging station service range delimited with Voronoi diagram (abbreviation V figures) and generate initial harmony vector, searched for using harmony（Harmony Search,HS）Algorithm is tried to achieve solution and is stored in harmony data base (Harmony memory, HM in), harmony data base is updated by study harmony data base, tone fine setting, until reaching harmony data base update times, charging station allocation plan desired value is found, charging station allocation plan optimal case is determined.Synthesis many factors of the invention, solving speed are fast, can find optimal value.
Description
Technical field：
The present invention relates to a kind of charging station method of allocation plan that is schemed based on V with HS algorithms, belongs to electric automobile charging station layout
Planning technology field.
Background technology：
Under the A clear guidance of government policy, current electric automobile recoverable amount breaks through 500,000, and the popularization speed of electric automobile
Degree will continue to accelerate.In order to meet the convenience of people's charging, it is necessary to build perfect electrically-charging equipment to ensure electric automobile
Charge requirement.Charging station is the important component part of charging electric vehicle facility, has extremely important effect.Accordingly, it would be desirable to
Rational deployment plans charging station construction, is automobile user provides convenient efficiently charging service.Existing charging station arrangement
Planing method：One is that Consideration is very few, it is impossible to comprehensively describe charging station programming and distribution feature；Two is the optimizing algorithm that selects
Excessively single, it is impossible to which that multiple variables are calculated, cause speed slow or optimizing effect excessively poor.
Charging station planning relates generally to addressing, constant volume and the scheme optimal selection problem of charging station.Location problem to charging station
In main consideration planning region, the spatio-temporal distribution of charging electric vehicle load, the electrical network quality of power supply and construction cost, come
Determine the rational position of electric automobile charging station.The constant volume problem of charging station is mainly considered to determine planning region scope
On, determine charging station capacity with Queueing Theory Method to meet charging electric vehicle demand in region as target.Preferred to scheme
Problem mainly takes cost with the Construction and operation cost of charging station, way of charging and the queue time cost that arrives at a station is as optimizing mesh
Mark, carries out the preferred of programme.Charging station allocation plan needs to consider many factors that the Mathematical Modeling of optimization problem is comprising crowd
Multi-variable type, general mathematical method are unsuitable for solving.It is thus desirable to joint V figures and HS algorithms are to charging station allocation plan model
Solved.
Voronoi diagram (abbreviation V figures) is also known as Thiessen polygon.V figures can be regarded as by each growing point of growth point setExpanded to surrounding with same uniform velocity, till meeting, expansion terminates shape
Scheme into V.The V figures for possessing closest characteristic are extensive in terms of the fields such as meteorological, mapping, archaeology, especially geographical facility addressing
Application, is also applied to substation locating and sizing in power system.V map generalization methods are broadly divided into for algorithm characteristic
Vector method of formation and grid method of formation.At present, the GIS-Geographic Information System of highest version（GIS）Software and highest version MATLAB software are all
V map generalizations, V figures order " voronoi " of such as MATLAB 7.9 can be conveniently realized.Although V figures have many suitable addressings
Key property, but V figures are a kind of local optimums by given growing point divided region, lack the ability of global optimizing.
And in musical performance, memory of the musicians by oneself, by adjusting repeatedly the tone of each musical instrument in band, most
A beautiful harmony state is reached eventually.Z.W.Geem etc. receives this inspired by phenomenon, it is proposed that harmonic search algorithm（Harmony
Search, HS）.Harmonic search algorithm is a kind of heuristic full search algorithm for coming out recently, in many combinatorial optimization problems
In obtained successful Application.Property more preferable compared with genetic algorithm, simulated annealing and TABU search is illustrated on relevant issues
Energy.
HS algorithms can also provide initial solution at random, it is also possible in advance using other heuristic scheduling algorithms or other method structures
Into a preferable initial solution.As HS algorithms are mainly based upon neighborhood search, the quality of initial solution is affected on search performance
Very big.The optimization problem of very complicated constraint is more especially carried, and the initial solution for being given at random is likely to infeasible, or even
It also is difficult to find feasible solution by multi-step searching, now should be directed to specific Complex Constraints, using heuritic approach or other sides
Method finds out a feasible solution as initial solution.It is thus desirable to a kind of new charging station method of allocation plan is carried out by combining V figures
Random selection initial solution, improves operation efficiency.
Content of the invention：
It is an object of the invention to overcoming the shortcomings of above-mentioned prior art and providing that a kind of solving speed is fast, find filling for optimal value
Power station method of allocation plan.
The purpose of the present invention can be reached by following measure：A kind of charging station arrangement based on V figures and HS algorithms advises
The method of drawing, it is characterised in which comprises the steps：
（One）Charging station scope is built in estimation planning region：
Planning region in electric automobile total quantity is first estimated, then pass through formulaTry to achieve
Total charging pile quantity, whereinFor charging electric vehicle queue time expect,,
For charging stationSet,For charging stationThe charging pile quantity of construction；,For electricity in planning region
Electrical automobile total quantity,Charge daily probability for electric automobile,For the charging electric vehicle period, thenObey Poisson distribution, table
Show the quantity of electric automobile arrival charging station in the unit interval；, and ensure,Access for charging pile
The charging electric vehicle time, thenFor charging pile service intensity；ThenFor all idle probability of charging pile；
If,For the queue time maximum expected value of charging electric vehicle, whenFor integer
When, the quantity of charging pile fromStart to increase successively, whereinIt is more than or equal to x's
Smallest positive integral；WhenFor non-integer when, the quantity of charging pile fromStart to increase successively, untilTill；WithIncrease and reduce rapidly, satisfaction is found in circulationWhen；
Set the charging pile quantitative range of charging station configuration, then build in planning region and fill
Power station quantityScope be, it is calculated as follows：
To eachHS algorithm optimizing is carried out, corresponding optimum harmony vector sum target function value is obtained；Then from all
OptimumSelect minimum, and corresponding parameter is exported, including charging station quantity, theIndividual charging station fills
Electric stake quantity, electric automobile is in charging stationThe queue time of charging is expected, charging station year Construction and operation into
This, user charges, and way is middle aged to take cost, user arrives at a station and waits in line year cost；
（Two）Build charging station allocation plan target：
On the premise of user's charge requirement is met, to take cost in the Construction and operation cost of charging station, way of charging and arrive at a station
Target of the queue time cost three for charging station allocation plan；With 1 year as unit of account, the social year assembly of charging station
ThisDefinition：, whereinFor charging station year Construction and operation cost,Charging for user, way is middle aged to take cost,Arrive at a station for user and wait in line year cost；
Year Construction and operation cost includes year fixed investment and annual operating and maintenance cost；Fixed investment mainly includes charging pile, soil, distribution
Transformer and the cost of investment of other auxiliary equipments, operating cost mainly include charging station staff salary and equipment operation dimension
Shield expense；Fixed investment and operating cost are all charging pile quantityFunction；Year Construction and operation cost is expressed as, wherein
,；For charging stationYear fixed investment function,For charging stationAnnual operating and maintenance cost function,ForWithFunction is
Number（）,For charging stationSet；WFor the investment that immobilizes, build including business building and road auxiliary
Expense,qFor relevant with the charging pile unit price investment coefficient in station,eIt is the equivalent investment coefficient relevant with charging pile quantity, including
Floor space, distribution transformer capacity and cable expense；For discount rate,Depreciable life for charging station；
User's charging way middle age, time-consuming cost was expressed as；WhereinFor city
Travel time cost coefficient,Charge daily probability for electric automobile,For urban transportation average overall travel speed,For filling
Electric demand pointElectric automobile quantity,For charge requirement pointArrive charging stationUrban road distance,For charging station
Set,For belonging to charging stationCharge requirement pointSet；
User arrives at a station and waits in line year cost and be expressed as；
WhereinFor Urban Traffic time cost coefficient,Charge daily probability for electric automobile,Charging for electric automobile
StandThe queue time expectation of charging,For charge requirement pointElectric automobile quantity,For charging stationSet,For belonging to charging stationCharge requirement pointSet；
The model constraints of the present invention is divided into two big class：The first kind travels distance restraint for charging, and is expressed as, whereinFor charge requirement pointArrive charging stationUrban road away from
From,For set charging operating range to greatest extent,For charging stationSet,For belonging to charging stationFill
Electric demand pointSet；Equations of The Second Kind is constrained for charging distance between sites, is expressed as,
WhereinFor charge requirement pointArrive charging stationUrban road distance,For charge requirement pointArrive charging stationCity
The air line distance of road,For charging stationWithAir line distance,For the minimum range between charging station,
For charging station,Set；
（Three）Joint V figure and HS Algorithm for Solving charging station allocation plan desired values：
Set upIndividual charging station method of allocation plan, is charged comprising the following steps that for station arrangement's planning using HS algorithms：
Step 1：Generate initial harmony vector
Generated in planned range at randomIndividual charging station site location, such as,
And coding generation is carried out to site locationDimensional vector；
V figures are generated using site location, each charging station service range delimited, using formulaPoint
In each charging station charging pile number is not calculated, judge whether in constraint
In condition and range, if in the range of, storing initial harmony vectorial and its vectorial, otherwise re-start this step；
Step 2：Generate harmony data base
HMS initial harmony vector is generated and by formula according to step 1Meter
Calculate correspondingIt is stored in HM in the lump, according toIt is ranked up from small to large：
In formula,ForRank matrix；
Step 3：Generate new harmony
Each tone of new explanationPass through following 3 kinds
Mechanism is produced：(1) learn harmony data base；(2) tone fine setting；(3) tone is randomly choosed；
1st variable of new explanationHaveP HMCPProbability be selected fromAny one value of middle respective column, has (1-P HMCR) general
Rate is selected fromAny one value of (but in range of variables) outward, i.e.,
In formula：randFor [0,1] upper equally distributed random number；
If new toneFrom harmony data base, tone fine setting to be carried out to which, concrete operations are as follows：
In formula,bwBandwidth is finely tuned for tone,randFor the random number being evenly distributed on [- 1,1],PARFor finely tuning probability；
Other tones of new explanation in the same manner, are converted into new site location with new interpreter code：,
V figures are generated, the new explanation for generating is judged according to constraints, as new harmony if meeting the requirements, and calculate
Fresh target functional value, otherwise re-start this step；
Step 4：Update harmony data base
IfIt is better thanIn worst, then by new harmonySubstitute former worst harmony, and the row of re-starting
Sequence, otherwise abandons the new harmony；Concrete operations are as follows：
Wherein,For worst harmony vector；
Step 5：Repeat step 3 and step 4, until harmony data base update times reachTill；The optimum harmony vector of storage and
Its corresponding object function, and corresponding parameter is exported, including.
In order to further realize the purpose of the present invention, describedqValue 0.7,eValue 0.4,Value 3%,Value
5 years；Value 0.8,Value 0.3Value 50Km/h, Value 58 times.
The Mathematical Modeling of charging station allocation plan has a lot of variables, including charge requirement point in transformer station and its coverage
Composition set variable, charging station site location composition continuous variable, each charging station service vehicle array into discrete change
The integer variable of amount, charging station quantity and its charger configuration composition.For such optimization problem, traditional optimization is difficult to
Solve.
Concrete derivation algorithm of the invention is that joint V is schemed and HS algorithms are to charging station allocation plan model solution.HS algorithms will
The harmony of musical instrument tone is analogous to the solution vector of optimization problem, and evaluation is each corresponding target function value.Algorithm introduces two
Major parameter, i.e. data base value (Harmony Memory Considering Rate, HMCR) and fine setting probability (Pitch
Adjusting Rate, PAR).Algorithm produces harmony initial solution first, and be put into harmony data base (Harmony memory,
HM, in), the quantity of wherein harmony initial solution is defined as harmony data base size (Harmony memory size, HMS)；Then
?The new harmony of interior random search, specific practice is：0～1 random number rand is randomly generated, if rand<HMCR, then newly
Harmony existsInterior random search is obtained；Otherwise, variable is in possible codomain range searching value.Again with PAR to taking from
Interior new harmony carries out local dip, in order to rectify a deviation.Finally, judge whether new harmony target function value is better thanInterior is worst
Harmony, if so, then updates harmony storehouse, and constantly iteration, until it reaches predetermined creation number of timesT max Till.
The size of HMS is an important parameter of HS algorithms, and why HS is with higher ability of searching optimum, very great Cheng
The presence of HMS is depended on degree.In general, HMS is bigger, and the ability for finding global optimum region is stronger.But due to HS algorithms
It is that multiple spot is started simultaneously at and scanned for, with the increase of HMS, amount of calculation will become big, finally search optimum so as to have influence on
The speed of harmony.
HMCR is another important parameter of HS algorithms, and its span is the random number between 0～1, and it determines every time
The producing method of new harmony in production process.In HS algorithms, when producing because of new harmony, each variable all relies on HMCR, therefore
HMCR should take larger value.Tone PAR in harmony search plays a part of to control Local Search, search can be made to flee from local and searched
Rope, its value are typically taken between 0.1 to 0.5.
The present invention can produce following good effect compared with the prior art：
The present invention consider charging station Construction and operation cost, charge way in take cost with arrive at a station queue time into
On the basis of this, it is proposed that using V figures and the charging station method of allocation plan of HS algorithms.In present invention statistical rules region first
Electric automobile quantity, is expected to estimate total charging pile quantity in the queue time that charging station charges using electric automobile, is led to
The charging pile quantitative range for setting charging station configuration is crossed calculating charging station quantity；Secondly random generationSit individual charging station site
Mark, and generation harmony vector X is encoded to which；Lack the shortcoming of global optimizing ability for solving V figures, global random using possessing
The HS algorithms of optimizing ability combine solution with V figures, calculate corresponding desired value further according to harmony vector, learned by memory
Practise, tone fine setting produces new harmony, determines V figure growing points with the decoding of new harmony；Finally divide with reference to V figure convex polygons feature
Match somebody with somebody in coverage, charging pile of the maximum queue time charged in charging station with electric automobile to determine each charging station
Quantity is put, global optimizing purpose has been reached.
The present invention need not provide charging station site to be selected, can effectively solving service range electric automobile rule pockety
The problem of drawing, can automatically generate site and scale according to electric automobile distribution, and provide each charging station planning region division, make charging
Stand Construction and operation cost, take cost and the queue time cost minimization that arrives at a station in way of charging, method is effectively practical.
Solution procedure of the present invention is for urban life area, the electric automobile charging station planning problem of business district, first counts
Electric automobile quantity in planning region, then each coverage is generated by Voronoi diagram, and determine electronic vapour in each service area
Car quantity, is then constrained with maximum queue time and determines the configuration standard for building charger in each service area, finally utilized
HS algorithms search for generation site and scale automatically, make charging station Construction and operation cost, user take cost and queuing in charging on the way
Waiting time cost minimization, the problem of effectively solving planned range electric automobile charging station rational deployment planning, method are effectively real
With.
Description of the drawings：
Fig. 1 is that the V figures and HS algorithms combined optimization of the present invention solve flow chart；
Fig. 2 is the charging station addressing result of the present invention and service range division figure；
Fig. 3 is the optimum programming Dynamic Evolution figure of the V-HS and V-PSO algorithms of the present invention.
Specific embodiment：
Below in conjunction with the accompanying drawings the specific embodiment of the present invention is elaborated：
Embodiment：A kind of charging station method of allocation plan that is schemed based on V with HS algorithms, which comprises the steps：
（One）Charging station scope is built in estimation planning region：
Planning region in electric automobile total quantity is first simply estimated, then pass through formula
Try to achieve total charging pile quantity, whereinFor charging electric vehicle queue time expect,,
For charging stationSet,For charging stationThe charging pile quantity of construction；,For electronic vapour in planning region
Car total quantity,Charge daily probability for electric automobile,For the charging electric vehicle period, thenPoisson distribution is obeyed, unit is represented
In time, electric automobile reaches the quantity of charging station；, and ensure,Access for charging pile electronic
The automobile charging interval, thenFor charging pile service intensity；ThenFor all idle probability of charging pile.
If（Queue time maximum expected value for charging electric vehicle）, by taking
The inverse function of formula is seeking the quantity of charging pile, more difficult.Therefore, whenFor integer when, the quantity of charging pile fromStart to increase successively, whereinIt is the smallest positive integral more than or equal to x；WhenFor non-
During integer, the quantity of charging pile fromStart to increase successively, untilTill.With
?Increase and reduce rapidly, satisfaction is found in a small amount of circulationWhen.
Set the charging pile quantitative range of charging station configuration, then built-in in planning region
If charging station quantityScope be, it is calculated as follows：
To eachHS algorithm optimizing is carried out, corresponding optimum harmony vector sum target function value is obtained.Then from all
OptimumSelect minimum, and corresponding parameter is exported, including charging station quantity, theIndividual charging station fills
Electric stake quantity, electric automobile is in charging stationThe queue time of charging is expected, charging station year Construction and operation into
This, user charges, and way is middle aged to take cost, user arrives at a station and waits in line year cost.
（Two）Build charging station allocation plan target：
On the premise of user's charge requirement is met, to take cost in the Construction and operation cost of charging station, way of charging and arrive at a station
Target of the queue time cost three for charging station allocation plan.With 1 year as unit of account, the social year assembly of charging station
ThisDefinition：, whereinFor charging station year Construction and operation cost,Charging for user, way is middle aged to take cost,Arrive at a station for user and wait in line year cost.
Year Construction and operation cost includes year fixed investment and annual operating and maintenance cost.Fixed investment mainly includes charging pile, soil, matches somebody with somebody
Piezoelectric transformer and the cost of investment of other auxiliary equipments, operating cost mainly include charging station staff salary and equipment operation dimension
Shield expense.Charging pile quantity embodies charging station scale, and charging pile is more, and service electric automobile quantity is more, and floor space is bigger,
Corresponding Land Purchase and the fixed investment of distribution transformer and other auxiliary equipments are bigger, while managerial staff member is more, fortune
Row maintenance cost is also bigger, and therefore charging pile is the decisive factor of Construction and operation cost.Fixed investment and operating cost are all charging piles
QuantityFunction.Year Construction and operation cost is expressed as, wherein,
.For charging stationYear fixed investment function,For charging stationAnnual operating and maintenance cost
Function,ForWithThe coefficient of function（）,For charging stationCollection
Close；WFor the investment that immobilizes, construction cost is aided in including business building and road,qFor relevant with charging pile unit price throwing in station
Money coefficient（Optimal value 0.7）,eIt is the equivalent investment coefficient relevant with charging pile quantity（Optimal value 0.4）, including taking up an area face
Product, distribution transformer capacity and cable expense；For discount rate（Optimal value 3%）,Depreciable life for charging station（Most
Good value 5 years）.
User's charging way middle age, time-consuming cost was mainly determined by charging operating range, was expressed as.WhereinFor Urban Traffic time cost coefficient（Optimal value 0.8）,For
Electric automobile charges probability daily（Optimal value 0.3）,For urban transportation average overall travel speed（Optimal value 50km/h）,For charge requirement pointElectric automobile quantity,For charge requirement pointArrive charging stationUrban road distance,For
Charging stationSet,For belonging to charging stationCharge requirement pointSet.
User arrive at a station wait in line year cost expected by charging electric vehicle and arrive at a station queue time expect determine
Fixed, it is expressed as.WhereinFor Urban Traffic time cost coefficient
（Optimal value 0.8）,Charge daily probability for electric automobile（Optimal value 0.3）,It is electric automobile in charging station
The queue time expectation of charging,For charge requirement pointElectric automobile quantity,For charging stationSet,For belonging to charging stationCharge requirement pointSet.
The model constraints of the present invention is divided into two big class：The first kind travels distance restraint for charging, for avoiding user over long distances
Travel and charge, the traveling that charges distance restraint is expressed as, whereinFor
Charge requirement pointArrive charging stationUrban road distance,For set charging operating range to greatest extent,For charging
StandSet,For belonging to charging stationCharge requirement pointSet；Equations of The Second Kind is constrained for charging distance between sites, for avoiding
Charging station arrangement is excessively intensive, and distance between sites constraint representation is,
WhereinFor charge requirement pointArrive charging stationUrban road distance,For charge requirement pointArrive charging stationCity road
The air line distance on road,For charging stationWithAir line distance,For the minimum range between charging station,
For charging station,Set.
（Three）Joint V figure and HS Algorithm for Solving charging station allocation plan desired values：
Following foundationIndividual charging station method of allocation plan, illustrates the concrete step for being charged station arrangement's planning using HS algorithms
Suddenly.
Step 1：Generate initial harmony vector：
Generated in planned range at randomIndividual charging station site location, such as,
And coding generation is carried out to site locationDimensional vector.
V figures are generated using site location, each charging station service range delimited, using formula
In each charging station charging pile number is calculated respectively, judge whether about
In beam condition and range, if in the range of, storing initial harmony vectorial and its vectorial, otherwise re-start this step
Suddenly.
Step 2：Generate harmony data base
HMS is generated according to step 1（Harmony data base size）Individual initial harmony vector by formulaCalculate correspondingHM is stored in the lump（Harmony data base）In, according toIt is ranked up from small to large：
In formula,ForRank matrix.
Step 3：Generate new harmony
Each tone of new explanationBy following 3 kinds of mechanism
Produce：(1) learn harmony data base；(2) tone fine setting；(3) tone is randomly choosed.
WithAs a example by, other tones of new explanation are in the same manner：1st variable of new explanationHaveP HMCP（Wherein HMCP is data base
Value）Probability be selected fromAny one value of middle respective column, has (1-P HMCR) probability be selected fromOutward (but in variable model
In enclosing) any one value, i.e.,
In formula：randFor [0,1] upper equally distributed random number.
If new toneFrom harmony data base, tone fine setting to be carried out to which, concrete operations are as follows：
In formula,bwBandwidth is finely tuned for tone,randFor the random number being evenly distributed on [- 1,1],PARFor finely tuning probability.
New site location is converted into new interpreter code：, generate
V schemes, and the new explanation for generating is judged according to constraints, as new harmony if meeting the requirements, and calculate new mesh
Offer of tender numerical value, otherwise re-start this step.
Step 4：Update harmony data base
IfIt is better thanIn worst, then by new harmonyFormer worst harmony is substituted, and is ranked up again,
The new harmony is otherwise abandoned.Concrete operations are as follows：
Wherein,For worst harmony vector.
Step 5：Repeat step 3 and step 4, until harmony data base update times reach（Optimal value 58 times）For
Only.The optimum harmony of storage is vectorial and its corresponding object function, and corresponding parameter is exported, including.
Site and its coverage divide as shown in Fig. 2 dot represents charge requirement point, the charging station that triangle is represented
Site layout, near the center of gravity of charge requirement, and coverage is well defined, and efficiently solves electric automobile skewness
Planning problem.Fig. 3 be charging station planning number be 10 when, be respectively adopted V figure and HS algorithms joint solve（V-HS）, V figure and
PSO algorithms joint is solved（V-PSO）Dynamic Evolution.V-HS algorithms asking for optimum society's total annual cost this target,
Iterations is less, can find optimal solution, and better astringency faster.
Claims (2)
1. a kind of based on V figure and HS algorithms charging station method of allocation plan, it is characterised in which comprises the steps：
（One）Charging station scope is built in estimation planning region：
Planning region in electric automobile total quantity is first estimated, then pass through formulaTry to achieve total
Charging pile quantity, whereinFor charging electric vehicle queue time expect,,For
Charging stationSet,For charging stationThe charging pile quantity of construction；,For electronic vapour in planning region
Car total quantity,Charge daily probability for electric automobile,For the charging electric vehicle period, thenPoisson distribution is obeyed, represents single
In the time of position, electric automobile reaches the quantity of charging station；, and ensure,Electricity is accessed for charging pile
The electrical automobile charging interval, thenFor charging pile service intensity；
ThenFor all idle probability of charging pile；
If,For the queue time maximum expected value of charging electric vehicle, whenFor whole
During number, the quantity of charging pile fromStart to increase successively, whereinIt is more than or equal to x
Smallest positive integral；WhenFor non-integer when, the quantity of charging pile fromStart to increase successively, untilTill；WithIncrease and reduce rapidly, satisfaction is found in circulationWhen；
Set the charging pile quantitative range of charging station configuration, then build in planning region and fill
Power station quantityScope be, it is calculated as follows：
To eachHS algorithm optimizing is carried out, corresponding optimum harmony vector sum target function value is obtained；Then from all
OptimumSelect minimum, and corresponding parameter is exported, including charging station quantity, theIndividual charging station
Charging pile quantity, electric automobile is in charging stationThe queue time of charging is expected, build fortune in charging station year
Row cost, user charges, and way is middle aged to take cost, user arrives at a station and waits in line year cost；
（Two）Build charging station allocation plan target：
On the premise of user's charge requirement is met, to take cost in the Construction and operation cost of charging station, way of charging and arrive at a station
Target of the queue time cost three for charging station allocation plan；With 1 year as unit of account, the social year assembly of charging station
ThisDefinition：, whereinFor charging station year Construction and operation into
This,Charging for user, way is middle aged to take cost,Arrive at a station for user and wait in line year cost；
Year Construction and operation cost includes year fixed investment and annual operating and maintenance cost；Fixed investment mainly includes charging pile, soil, distribution transformer
Device and the cost of investment of other auxiliary equipments, operating cost mainly include charging station staff salary and equipment operation maintenance
Expense；Fixed investment and operating cost are all charging pile quantityFunction；Year Construction and operation cost is expressed as, wherein
,；For charging stationYear fixed investment function,For charging stationAnnual operating and maintenance cost function,ForWithFunction
Coefficient（）,For charging stationSet；WFor the investment that immobilizes, build including business building and road auxiliary
If expense,qFor relevant with the charging pile unit price investment coefficient in station,eIt is the equivalent investment coefficient relevant with charging pile quantity, bag
Include floor space, distribution transformer capacity and cable expense；For discount rate,Depreciable life for charging station；
User's charging way middle age, time-consuming cost was expressed as；WhereinGo out for city
Row time cost coefficient,Charge daily probability for electric automobile,For urban transportation average overall travel speed,For charging
Demand pointElectric automobile quantity,For charge requirement pointArrive charging stationUrban road distance,For charging stationCollection
Close,For belonging to charging stationCharge requirement pointSet；
User arrives at a station and waits in line year cost and be expressed as；Wherein
For Urban Traffic time cost coefficient,Charge daily probability for electric automobile,It is electric automobile in charging stationCharge
Queue time expect,For charge requirement pointElectric automobile quantity,For charging stationSet,For
Belong to charging stationCharge requirement pointSet；
The model constraints of the present invention is divided into two big class：The first kind travels distance restraint for charging, and is expressed as, whereinFor charge requirement pointArrive charging stationCity road
Road distance,For set charging operating range to greatest extent,For charging stationSet,For belonging to charging
StandCharge requirement pointSet；Equations of The Second Kind is constrained for charging distance between sites, is expressed as, whereinFor charge requirement pointArrive charging stationCity
Road distance,For charge requirement pointArrive charging stationThe air line distance of urban road,For charging stationWith's
Air line distance,For the minimum range between charging station,For charging station,Set；
（Three）Joint V figure and HS Algorithm for Solving charging station allocation plan desired values：
Set upIndividual charging station method of allocation plan, is charged comprising the following steps that for station arrangement's planning using HS algorithms：
Step 1：Generate initial harmony vector
Generated in planned range at randomIndividual charging station site location, such as, and
Coding generation is carried out to site locationDimensional vector；
V figures are generated using site location, each charging station service range delimited, using formula
In each charging station charging pile number is calculated respectively, judge whether about
In beam condition and range, if in the range of, storing initial harmony vectorial and its vectorial, otherwise re-start this step
Suddenly；
Step 2：Generate harmony data base
HMS initial harmony vector is generated and by formula according to step 1Calculate
AccordinglyIt is stored in HM in the lump, according toIt is ranked up from small to large：
In formula,ForRank matrix；
Step 3：Generate new harmony
Each tone of new explanationPass through following 3 kinds of machines
Reason is produced：(1) learn harmony data base；(2) tone fine setting；(3) tone is randomly choosed；
1st variable of new explanationHaveP HMCPProbability be selected fromAny one value of middle respective column, has (1-P HMCR) general
Rate is selected fromAny one value of (but in range of variables) outward, i.e.,
In formula：randFor [0,1] upper equally distributed random number；
If new toneFrom harmony data base, tone fine setting to be carried out to which, concrete operations are as follows：
In formula,bwBandwidth is finely tuned for tone,randFor the random number being evenly distributed on [- 1,1],PARFor finely tuning probability；
Other tones of new explanation in the same manner, are converted into new site location with new interpreter code：
, V figures are generated, the new explanation for generating are judged according to constraints, as new harmony if meeting the requirements, and calculate
Fresh target functional value, otherwise re-start this step；
Step 4：Update harmony data base
IfIt is better thanIn worst, then by new harmonyFormer worst harmony is substituted, and is ranked up again,
The new harmony is otherwise abandoned；Concrete operations are as follows：
Wherein,For worst harmony vector；
Step 5：Repeat step 3 and step 4, until harmony data base update times reachTill；The optimum harmony vector of storage
And its corresponding object function, and corresponding parameter is exported, including.
2. according to claim 1 a kind of based on V figure and HS algorithms charging station method of allocation plan, it is characterised in that institute
StateqValue 0.7,eValue 0.4,Value 3%,Value 5 years；Value 0.8,Value 0.3Value 50km/ H, Value 58 times.
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