CN109050284A - A kind of electric car charge and discharge electricity price optimization method considering V2G - Google Patents
A kind of electric car charge and discharge electricity price optimization method considering V2G Download PDFInfo
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Abstract
The invention discloses a kind of electric car charge and discharge electricity price optimization methods for considering V2G, include: the basic structure founding mathematical models according to more micro-grid systems, the charge and discharge cost, the operating cost of more micro-grid systems and optimization constraint condition of electric car are obtained according to mathematical model；Establish the bicyclic Optimized model of more micro-grid systems, the power of the charge and discharge for the optimal electric car that inner ring optimizes is used to calculate the operating cost of more micro-grid systems in outer ring optimization, the charge and discharge electricity price for the optimal electric car that outer ring optimizes is used to calculate the charge and discharge cost of electric car, runs bicyclic Optimized model and inner ring optimization is made to obtain the charge and discharge cost of minimum electric car, the power of the charge and discharge of optimal electric car, the operating cost of minimum more micro-grid systems and the charge and discharge electricity price of optimal objective electric car with the multiple circulation of outer ring optimization.The present invention considers the game in the micro-grid system of region between different micro-capacitance sensors, the economy of further lifting system overall operation.
Description
Technical field
The invention belongs to more micro-grid system economical operation fields, fill more particularly, to a kind of electric car for considering V2G
Discharge electricity price optimization method.
Background technique
As the important channel for ensureing energy security, the low-carbon economy that makes the transition, the research of electric car and its related content is just
Extensive concern by countries in the world.Conventional fuel oil automobile can generate a large amount of pollutions, to environment due to the combusts fossil energy
Cause bad influence；And electric car using electric energy driven, well solved carbon emission and disposal of pollutants the problem of.
However, electric car, which largely accesses power grid, to affect greatly the safe and stable operation of electric system, therefore, it is necessary to use
Suitable mode is scheduled electric car, reduces the negative effect that electric car charges to power grid.
On the other hand, gradualling mature with the enhancing of energy conservation and environmental awareness and the relevant technologies, using renewable energy as
Main energy sources and the micro-grid system constructed is having been more and more widely used.Since micro-capacitance sensor itself scale is smaller, and
Mainly using renewable energy such as wind-powered electricity generation, photovoltaics, therefore have the characteristics that low-carbon environment-friendly, flexible operation.But renewable energy
Source has the characteristics that power output is unstable, is affected by weather, it is therefore desirable to be equipped with expensive energy storage device, reduce system fortune
Capable economy.
To solve the above-mentioned problems, electric car enters network technology (V2G) and has obtained extensive concern.Using electric car as
Energy storage device, while energy storage characteristic is moved using it, the spanning space-time of energy is carried out between multiple microgrids moves.It is existing at present big
Quantity research is dedicated to optimizing the operation of electric car by way of controlling electric car charge-discharge electric power, to improve
The stability and economy of system operation, but these are studied target of interest and are confined to the unilaterally charge and discharge to electric car
It is scheduled control, is offered by adjusting each micro-capacitance sensor to the charge and discharge of electric car without considering, guides electric car
Charge and discharge behavior, to further increase the economy of system overall operation.It can be seen that there are systems integrally to transport for the prior art
The poor technical problem of capable economy.
Summary of the invention
Aiming at the above defects or improvement requirements of the prior art, the present invention provides a kind of electric cars for considering V2G to fill
Discharge electricity price optimization method, thus solves the prior art technical problem poor there are the economy of system overall operation.
To achieve the above object, the present invention provides a kind of electric car charge and discharge electricity price optimization method for considering V2G, packets
It includes:
(1) according to the basic structure of more micro-grid systems, founding mathematical models obtain filling for electric car according to mathematical model
Electric discharge cost, the operating cost of more micro-grid systems and optimization constraint condition；
(2) using the charge and discharge cost minimization of electric car as target, by micro-capacitance sensor each in more micro-grid systems institute per hour
There is the power of the charge and discharge of electric car as optimized variable, economic load dispatching is carried out to electric car, obtains optimal electric car
Charge and discharge power；
(3) according to electric energy quotation is bought and sold between power distribution network and more micro-grid systems, the initial discharge electricity price of electric car is obtained
With the initial charge electricity price of electric car, become using the electric discharge electricity price of electric car and the charging electricity price of electric car as optimization
Amount, with the minimum target of the operating cost of more micro-grid systems, puts electric car under the premise of meeting optimization constraint condition
Electricity price and the charging electricity price of electric car optimize, and obtain the charge and discharge electricity price of optimal electric car；
(4) step (2) is optimized as inner ring, step (3) optimizes as outer ring, establishes the bicyclic optimization of more micro-grid systems
Model, the power of the charge and discharge for the optimal electric car that inner ring optimizes are used to calculate more micro-grid systems in outer ring optimization
Operating cost, the charge and discharge electricity price for the optimal electric car that outer ring optimizes are used to calculate the charge and discharge cost of electric car,
Running bicyclic Optimized model makes inner ring optimization obtain charge and discharge cost, the mesh of target electric car with the multiple circulation of outer ring optimization
Mark power, the operating cost of the more micro-grid systems of target and the charge and discharge electricity price of target electric car of the charge and discharge of electric car.
Further, step (1) includes:
According to the basic structure of more micro-grid systems, founding mathematical models, the mathematical model includes: the charge and discharge of electric car
Electric model, wind-power electricity generation prediction model and photovoltaic power generation prediction model, obtain optimizing about according to the charging and recharging model of electric car
The operating cost of beam condition, the charge and discharge cost of electric car and more micro-grid systems obtains wind according to wind-power electricity generation prediction model
Power generator cost of investment obtains photovoltaic module cost of investment according to photovoltaic power generation prediction model；
The charging and recharging model of the electric car includes electric car access when electric car accesses more micro-grid systems
The electric car when charging and recharging model and electric car of micro-capacitance sensor are in driving status does not access the charging and recharging model of micro-capacitance sensor.
Further, the charge and discharge cost of electric car are as follows:
Wherein, CEVtlFor the charge and discharge cost of electric car, PEVBi, j, tFor i-th of micro-capacitance sensor jth electric car in t
The power of moment charge and discharge, pEViFor the charge and discharge quotation of i-th of micro-capacitance sensor, NEViFor the electric car quantity of i-th of micro-capacitance sensor,
N is micro-capacitance sensor number, and T is scheduling duration.
Further, the operating cost of more micro-grid systems are as follows:
CTCi=min (CPVi+CWTi+CEVi+CGi)
Wherein, CTCMSFor the operating cost of more micro-grid systems, CTCiFor the operating cost of i-th of micro-capacitance sensor, CPVi、GWTi、
CEVi、CGiRespectively indicate the operation of the photovoltaic module cost of investment, wind-driven generator cost of investment, electric car of i-th of micro-capacitance sensor
Cost and power grid power trade cost obtain i-th of micro-capacitance sensor with electricity price with the power that exchanges of i-th of micro-capacitance sensor according to power distribution network
Power grid power trade cost.
Further, optimization constraint condition includes: network trend Constraints of Equilibrium, electric car capacity-constrained, electric car
Energy exchange power constraint, the micro-capacitance sensor of power constraint, micro-capacitance sensor and power distribution network are offered to the charge and discharge of electric car and are constrained,
Network trend Constraints of Equilibrium are as follows: PPVi, t+PWTi, t+PEVBi, t+PGi, t=PLi, t
Electric car capacity-constrained are as follows: EEVB min≤EEVBi, j, t≤EEVB max
Electric car power constraint are as follows: PEVB min≤PEVBi, j, t≤PEVB max
The energy exchange power constraint of power distribution network are as follows: PEVB min≤PGi, t≤PEVB max
Micro-capacitance sensor is offered to the charge and discharge of electric car and is constrained are as follows: PDE≥ηCEVηDEVpCE
Wherein, PPVi, tGenerated output for i-th of micro-capacitance sensor in t moment photovoltaic module, PWTi, tIt is i-th of micro-capacitance sensor in t
The generated output of moment wind-driven generator, PEVBi, tFor i-th of micro-capacitance sensor all electric cars t moment charge and discharge power,
PLi, tLoad for i-th of micro-capacitance sensor in t moment, EEVB minFor the electricity minimum value of electric car, EEVB maxFor electric car
Electricity maximum value, PEVB minFor the minimum power of electric car, PEVB maxFor the maximum power of electric car, pDEFor electric car
Electric discharge electricity price, pCEFor the charging electricity price of electric car, PEVBi, j, tFor i-th of micro-capacitance sensor jth electric car in t moment
The power of charge and discharge, EEVBi, j, tThen indicate electricity of the jth electric car of i-th of micro-capacitance sensor in t moment, ηCEVFor electronic vapour
The charge efficiency of vehicle, ηDEVFor the discharging efficiency of electric car, PGi, tFunction is exchanged in t moment with i-th of micro-capacitance sensor for power distribution network
Rate.
Further, step (2) includes:
(2-1) using using the power of micro-capacitance sensor each in the more micro-grid systems charge and discharge of all electric cars per hour as
The optimized variable of particle swarm algorithm, the particle of constituent particle group's algorithm；
(2-2) calculates the charge and discharge cost of the electric car of each particle, by the charge and discharge of electric car in all particles
The global optimum that the minimum value of cost recycles for the first time as inner ring；
(2-3) updates speed and the position of particle using the more new formula of the Position And Velocity of particle swarm algorithm, calculates more
The charge and discharge cost of the electric car of particle after new is compared with the global optimum of one cycle before inner ring, is taken wherein most
Small value is the new global optimum of inner ring；
(2-4) repeats step (2-3) repeatedly, obtains the charge and discharge cost of optimal electric car and its corresponding optimal electronic
The power of the charge and discharge of automobile.
Further, step (3) includes:
(3-1) is using each micro-capacitance sensor to electric car charge and discharge electricity price as each dimension of particle each in particle swarm algorithm
The value of degree, obtains population, according to electric energy quotation is bought and sold between power distribution network and more micro-grid systems, obtains initially putting for electric car
Electricity price and the initial charge electricity price of electric car utilize the power of the charge and discharge of optimal electric car for initializing population
The operating cost for calculating more micro-grid systems of each particle, using the operating cost minimum value of more micro-grid systems of all particles as
The initial global optimum of outer ring；
(3-2) updates speed and the position of particle using the more new formula of the Position And Velocity of particle swarm algorithm, calculates more
The operating cost of more micro-grid systems of particle after new is compared with a preceding global optimum for outer ring, takes wherein minimum value
For the new global optimum of outer ring；
(3-3) repeats step (3-2) repeatedly, obtains the operating cost of optimal more micro-grid systems and its corresponding optimal electronic
The charge and discharge electricity price of automobile.
In general, through the invention it is contemplated above technical scheme is compared with the prior art, can obtain down and show
Beneficial effect:
(1) present invention optimizes same in the operating cost of charge and discharge cost and more micro-grid systems to electric car
When, it is contemplated that the game in more micro-grid systems between different micro-capacitance sensors.Each micro-capacitance sensor is using certain Developing Tactics itself
Charge and discharge electricity price, thus the further economy of lifting system overall operation.
(2) the charge and discharge cost optimization of electric car proposed by the invention and the run cost optimization of more micro-grid systems are
Bicyclic collaboration Optimized model.The inner ring of model carries out economic load dispatching to electric car, makes electric car in the case of certain certain electricity price
Operating cost be optimal；Outer ring is then optimized the price of electric car charge and discharge, mutually competing in multiple micro-capacitance sensors
In the case where striving, the charge and discharge by optimizing and revising each micro-capacitance sensor are offered, and reduce the operating cost of each micro-capacitance sensor itself, to subtract
The total operating cost of mini system.Inner ring be combined with each other with outer ring, the operation to the integrated system of multiple micro-capacitance sensors and electric car
It optimizes.
(3) charge and discharge electricity price proposed by the invention optimization and the bicyclic Cooperative Evolutionary of economic load dispatching are suitable for inclusion in
There is the region micro-grid system of multiple micro-capacitance sensors.Electric car can carry out in systems energy spanning space-time and move, both can be with
It using the variation of different time sections electricity price, also can use the different electricity prices of each micro-capacitance sensor, provide charge and discharge service for system,
To make the cost of whole system reduce to a certain extent.Micro-capacitance sensor can adjust certainly according to the operation data of power grid simultaneously
Body electricity price guides electric car charge and discharge, to obtain more profits to a certain extent.The present invention can be used to instruct region micro-
The charge and discharge price of different micro-capacitance sensors, improves the operational efficiency of system, reduces system operation cost in network system.
Detailed description of the invention
Fig. 1 is a kind of process of electric car charge and discharge electricity price optimization method for considering V2G provided in an embodiment of the present invention
Figure；
Fig. 2 is the structure chart of more micro-grid systems provided in an embodiment of the present invention；
Fig. 3 is inner ring economic load dispatching flow chart provided in an embodiment of the present invention；
Fig. 4 is outer ring optimized flow chart provided in an embodiment of the present invention.
Specific embodiment
In order to make the objectives, technical solutions, and advantages of the present invention clearer, with reference to the accompanying drawings and embodiments, right
The present invention is further elaborated.It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, and
It is not used in the restriction present invention.As long as in addition, technical characteristic involved in the various embodiments of the present invention described below
Not constituting a conflict with each other can be combined with each other.
As shown in Figure 1, a kind of electric car charge and discharge electricity price optimization method for considering V2G, comprising:
(1) according to the basic structure of more micro-grid systems, founding mathematical models obtain filling for electric car according to mathematical model
Electric discharge cost, the operating cost of more micro-grid systems and optimization constraint condition；
(2) using the charge and discharge cost minimization of electric car as target, by micro-capacitance sensor each in more micro-grid systems institute per hour
There is the power of the charge and discharge of electric car as optimized variable, economic load dispatching is carried out to electric car, obtains optimal electric car
Charge and discharge power；
(3) according to electric energy quotation is bought and sold between power distribution network and more micro-grid systems, the initial discharge electricity price of electric car is obtained
With the initial charge electricity price of electric car, become using the electric discharge electricity price of electric car and the charging electricity price of electric car as optimization
Amount, with the minimum target of the operating cost of more micro-grid systems, puts electric car under the premise of meeting optimization constraint condition
Electricity price and the charging electricity price of electric car optimize, and obtain the charge and discharge electricity price of optimal electric car；
(4) step (2) is optimized as inner ring, step (3) optimizes as outer ring, establishes the bicyclic optimization of more micro-grid systems
Model, the power of the charge and discharge for the optimal electric car that inner ring optimizes are used to calculate more micro-grid systems in outer ring optimization
Operating cost, the charge and discharge electricity price for the optimal electric car that outer ring optimizes are used to calculate the charge and discharge cost of electric car,
Running bicyclic Optimized model makes inner ring optimization obtain charge and discharge cost, the mesh of target electric car with the multiple circulation of outer ring optimization
Mark power, the operating cost of the more micro-grid systems of target and the charge and discharge electricity price of target electric car of the charge and discharge of electric car.
As shown in Fig. 2, the more micro-grid systems considered in the present invention include multiple relatively independent micro-capacitance sensors, according to
The difference of its position and function is divided into residential quarter micro-capacitance sensor and Office Area (shopping centre) micro-capacitance sensor.One is had in each micro-capacitance sensor
The photovoltaic generating module (PV) and small-sized wind power generator (WT) of constant volume and a number of bidirectional electric automobile charge and discharge
Facility.Each micro-capacitance sensor is connected with bulk power grid, and exchanging for electric energy can be carried out between bulk power grid, to guarantee the steady of power supply
It is qualitative.The structure of two kinds of micro-capacitance sensors is although similar, but it is different that electricity price used by electric energy exchanges is carried out between bulk power grid.It is logical
It crosses bicyclic optimization method to optimize the charge and discharge quotation of micro-capacitance sensor and the operation of electric car, to reduce system operation
Totle drilling cost.
Specifically, step (1) includes: according to the basic structure of more micro-grid systems, founding mathematical models, the mathematical model
It include: the charging and recharging model, wind-power electricity generation prediction model and photovoltaic power generation prediction model of electric car, according to filling for electric car
Discharging model obtains optimization constraint condition, the operating cost of the charge and discharge cost of electric car and more micro-grid systems, according to wind-force
Power generation prediction model obtains wind-driven generator cost of investment, obtains photovoltaic module cost of investment according to photovoltaic power generation prediction model；
The charging and recharging model of the electric car includes electric car access when electric car accesses more micro-grid systems
The electric car when charging and recharging model and electric car of micro-capacitance sensor are in driving status does not access the charging and recharging model of micro-capacitance sensor.
The charging and recharging model of electric car access micro-capacitance sensor are as follows:
Wherein, PEVBi, j, tIt is power of the jth electric car of i-th of micro-capacitance sensor in t moment charge and discharge, PEVBi, j, tGreatly
It indicates to discharge when 0, and PEVBi, j, tCharging is indicated when less than 0；EEVBi, j, tThen indicate the jth electric car of i-th of micro-capacitance sensor
In the electricity of t moment, σEVFor self-discharge rate, Δ t is the time interval of scheduling, ηCEVFor the charge efficiency of electric car, ηDEVFor
The discharging efficiency of electric car.
Electric car does not access the charging and recharging model of micro-capacitance sensor are as follows:
Wherein, d is the time of electric automobile during traveling,For i-th of micro-capacitance sensor jth electric car in t moment row
The distance sailed, CdFor the power consumption (kWh/km) of electric automobile during traveling unit distance.
The charge and discharge cost of electric car are as follows:
Wherein, CEVtlFor the charge and discharge cost of electric car, PEVBi, j, tFor i-th of micro-capacitance sensor jth electric car in t
The power of moment charge and discharge, pEViFor the charge and discharge quotation of i-th of micro-capacitance sensor, charging electricity price is used when electric car charging, when
Using electric discharge electricity price when electric car discharges；NEViFor the electric car quantity of i-th of micro-capacitance sensor, N is micro-capacitance sensor number, and T is to adjust
Spend duration.
The operating cost of more micro-grid systems are as follows:
CTCi=min (CPVi+CWTi+CEVi+CGi)
Wherein, CTCMSFor the operating cost of more micro-grid systems, CTCiFor the operating cost of i-th of micro-capacitance sensor, CPVi、GWTi、
CEVi、CGiRespectively indicate the operation of the photovoltaic module cost of investment, wind-driven generator cost of investment, electric car of i-th of micro-capacitance sensor
Cost and power grid power trade cost obtain i-th of micro-capacitance sensor with electricity price with the power that exchanges of i-th of micro-capacitance sensor according to power distribution network
Power grid power trade cost.
The operating cost of electric car are as follows:
Wherein, NEViFor the electric car quantity of i-th of micro-capacitance sensor, CconstFor the conversion of single motor automobile charge and discharge device
To daily cost of investment, CBDiFor the depreciable cost of electric car generated battery in charge and discharge process.
The power grid power trade cost of i-th of micro-capacitance sensor are as follows:
Wherein, CgiFor the electricity price of power distribution network and t-th of micro-capacitance sensor, PGi, tIt is power distribution network and i-th of micro-capacitance sensor in t moment
Exchange power, CECGi, tFor power distribution network and i-th of micro-capacitance sensor t moment environment punishment cost.
Optimization constraint condition include: network trend Constraints of Equilibrium, electric car capacity-constrained, electric car power constraint,
The energy exchange power constraint of micro-capacitance sensor and power distribution network, micro-capacitance sensor are offered to the charge and discharge of electric car and are constrained,
Network trend Constraints of Equilibrium are as follows: PPVi, t+PWTi, t+PEVBi, t+PGi, t=PLi, t
Electric car capacity-constrained are as follows: EEVB min≤EEVBi, j, t≤EEVB max
Electric car power constraint are as follows: PEVB min≤PEVBi, j, t≤PEVB max
The energy exchange power constraint of power distribution network are as follows: PEVB min≤PGi, t≤PEVB max
Micro-capacitance sensor is offered to the charge and discharge of electric car and is constrained are as follows: pDE≥ηCEVηDEVPCE
Wherein, PPVi, tGenerated output for i-th of micro-capacitance sensor in t moment photovoltaic module, PWTi, tIt is i-th of micro-capacitance sensor in t
The generated output of moment wind-driven generator, PEVBi, tFor i-th of micro-capacitance sensor all electric cars t moment charge and discharge power,
PLi, tLoad for i-th of micro-capacitance sensor in t moment, EEVB minFor the electricity minimum value of electric car, EEVB maxFor electric car
Electricity maximum value, PEVB minFor the minimum power of electric car, PEVB maxFor the maximum power of electric car, pDEFor electric car
Electric discharge electricity price, pCEFor the charging electricity price of electric car.
As shown in figure 3, step (2) includes:
(2-1) inputs photovoltaic, wind generator system processing data and electricity price, using by micro-capacitance sensor each in more micro-grid systems
Optimized variable of the power of the charge and discharge of all electric cars as particle swarm algorithm per hour, the particle of constituent particle group's algorithm
Wherein, IMGiFor the power matrix of i-th of micro-capacitance sensor, IMG1For the power matrix of the 1st micro-capacitance sensor, IMG2It is the 2nd
The power matrix of micro-capacitance sensor, IMGNFor the power matrix of n-th micro-capacitance sensor, for photovoltaic module and wind-driven generator, power is permanent big
In equal to 0；For electric car, when power is greater than 0, electric car discharges to micro-capacitance sensor, and otherwise electric car charges；Work as friendship
When changing power greater than 0, micro-capacitance sensor is to power distribution network power purchase, and otherwise electric energy is sold to power distribution network by micro-capacitance sensor.Initialization individual is optimal
It is worth (power of the charge and discharge of optimal electric car) and global optimum (the charge and discharge cost of optimal electric car), by initial value
It is set as biggish value.
(2-2) initializes particle swarm algorithm particle, the charge and discharge cost of the electric car of each particle is calculated, by all grains
The global optimum that the minimum value of the charge and discharge cost of electric car recycles for the first time as inner ring in son；
(2-3) updates speed and the position of particle using the more new formula of the Position And Velocity of particle swarm algorithm, calculates after updating
The charge and discharge cost of electric car of particle be compared with the global optimum of one cycle before inner ring, take wherein minimum value be interior
The new global optimum of ring；The more new formula of the speed of particle swarm algorithm are as follows:
The more new formula of the position of particle swarm algorithm are as follows:In formula, Vi kFor the speed in i-th of particle kth time iteration
Degree；PBest, i kIt is the individual optimal solution of i-th of particle at the kth iteration；Gbest kBe in group all particles in kth time iteration
When globally optimal solution；Xi kFor the position after i-th of particle kth time iteration；W is weighted factor, its size is determined to working as
Preceding speed inherit number, general value is between 0.1 to 0.9；c1、c2Referred to as Studying factors generally take c1=c2=2；ξ,
Pseudo random number of the η between (0,1)；The Position And Velocity of particle is all limited in certain range.
(2-4) repeats step (2-3) repeatedly, until on the iterative calculation number that cycle-index reaches particle swarm algorithm setting
It is limited to stop, obtains optimal scheduling strategy: the charge and discharge of the charge and discharge cost of optimal electric car and its corresponding optimal electric car
The power of electricity.
Step (3) includes:
(3-1) is using each micro-capacitance sensor to electric car charge and discharge electricity price as each dimension of particle each in particle swarm algorithm
The value of degree, obtains population:
According to the minimum value for buying and selling electric energy quotation between power distribution network and micro-capacitance sensorWith maximum valueObtain electronic vapour
The initial discharge electricity price p of vehicleDEWith the initial charge electricity price p of electric carCE,
Wherein, k1For the first coefficient, k2For the second coefficient.
According to electric energy quotation is bought and sold between power distribution network and more micro-grid systems, the initial discharge electricity price and electricity of electric car are obtained
The initial charge electricity price of electrical automobile utilizes each grain of the power calculation of the charge and discharge of optimal electric car for initializing population
The operating cost of more micro-grid systems of son, using the operating cost minimum value of more micro-grid systems of all particles as the initial of outer ring
Global optimum；
(3-2) updates speed and the position of particle using the more new formula of the Position And Velocity of particle swarm algorithm, calculates more
The operating cost of more micro-grid systems of particle after new is compared with a preceding global optimum for outer ring, takes wherein minimum value
For the new global optimum of outer ring；
(3-3) repeats step (3-2) repeatedly, obtains the operating cost (global optimum) of optimal more micro-grid systems and its right
The charge and discharge electricity price (individual optimal value) for the optimal electric car answered.
As shown in figure 4, running bicyclic Optimized model and including:
Input system parameter initializes individual optimal value and global optimum, sets biggish value for initial value, initially
Outside the pale of civilization ring particle swarm algorithm particle, enabling outer loop cycles number is 1, initializes inner ring particle swarm algorithm particle, enables inner ring circulation time
Number is 1, calculates the charge and discharge cost of the electric car of each particle, utilizes the charge and discharge cost of electric car in all particles
Minimum value more new individual optimal value (power of the charge and discharge of optimal electric car) and global optimum, when inner ring cycle-index is small
When being equal to inner ring circulation preset value, according to inner ring individual optimal value (power of the charge and discharge of optimal electric car) and it is global most
The figure of merit updates the position and speed of inner ring population, then carries out inner ring circulation again；When inner ring cycle-index is followed greater than inner ring
When ring preset value, the corresponding individual optimal value of outer ring population and global optimum are arranged according to the result of inner ring particle swarm algorithm
Value is updated when outer loop cycles number is less than or equal to outer loop cycles predicted value according to outer ring individual optimal value and global optimum
Then the position and speed of outer ring population carries out outer loop cycles again.When outer loop cycles number is greater than outer loop cycles predicted value
When, the economic load dispatching result of electric car and the optimum results of micro-capacitance sensor charge and discharge quotation are obtained, i.e., are as follows: target electric car
Charge and discharge cost, the power of the charge and discharge of target electric car, the operating cost of the more micro-grid systems of target and target electric car
Charge and discharge electricity price.
As it will be easily appreciated by one skilled in the art that the foregoing is merely illustrative of the preferred embodiments of the present invention, not to
The limitation present invention, any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should all include
Within protection scope of the present invention.
Claims (7)
1. a kind of electric car charge and discharge electricity price optimization method for considering V2G characterized by comprising
(1) according to the basic structure of more micro-grid systems, founding mathematical models obtain the charge and discharge of electric car according to mathematical model
Cost, the operating cost of more micro-grid systems and optimization constraint condition；
(2) using the charge and discharge cost minimization of electric car as target, by micro-capacitance sensor each in more micro-grid systems all electricity per hour
The power of the charge and discharge of electrical automobile carries out economic load dispatching as optimized variable, to electric car, obtains filling for optimal electric car
The power of electric discharge；
(3) according to electric energy quotation is bought and sold between power distribution network and more micro-grid systems, the initial discharge electricity price and electricity of electric car are obtained
The initial charge electricity price of electrical automobile, using the electric discharge electricity price of electric car and the charging electricity price of electric car as optimized variable,
Under the premise of meeting optimization constraint condition, with the minimum target of the operating cost of more micro-grid systems, to the electric discharge electricity of electric car
The charging electricity price of valence and electric car optimizes, and obtains the charge and discharge electricity price of optimal electric car；
(4) step (2) is optimized as inner ring, step (3) optimizes as outer ring, establishes the bicyclic optimization mould of more micro-grid systems
Type, the power of the charge and discharge for the optimal electric car that inner ring optimizes are used to calculate the fortune of more micro-grid systems in outer ring optimization
Row cost, the charge and discharge electricity price for the optimal electric car that outer ring optimizes are used to calculate the charge and discharge cost of electric car, fortune
The bicyclic Optimized model of row makes inner ring optimization with outer ring optimization, and repeatedly circulation obtains charge and discharge cost, the target of target electric car
The operating cost of the more micro-grid systems of the power of the charge and discharge of electric car, target and the charge and discharge electricity price of target electric car.
2. a kind of electric car charge and discharge electricity price optimization method for considering V2G as described in claim 1, which is characterized in that institute
Stating step (1) includes:
According to the basic structure of more micro-grid systems, founding mathematical models, the mathematical model includes: the charge and discharge mould of electric car
Type, wind-power electricity generation prediction model and photovoltaic power generation prediction model obtain optimization constraint item according to the charging and recharging model of electric car
The operating cost of part, the charge and discharge cost of electric car and more micro-grid systems obtains wind-force hair according to wind-power electricity generation prediction model
Motor cost of investment obtains photovoltaic module cost of investment according to photovoltaic power generation prediction model；
The charging and recharging model of the electric car includes that electric car when electric car accesses more micro-grid systems accesses micro- electricity
The electric car when charging and recharging model and electric car of net are in driving status does not access the charging and recharging model of micro-capacitance sensor.
3. a kind of electric car charge and discharge electricity price optimization method for considering V2G as claimed in claim 1 or 2, which is characterized in that
The charge and discharge cost of the electric car are as follows:
Wherein, CEVtlFor the charge and discharge cost of electric car, PEVBi, j, tFor i-th of micro-capacitance sensor jth electric car in t moment
The power of charge and discharge, PEViFor the charge and discharge quotation of i-th of micro-capacitance sensor, NEViFor the electric car quantity of i-th of micro-capacitance sensor, N is
Micro-capacitance sensor number, T are scheduling duration.
4. a kind of electric car charge and discharge electricity price optimization method for considering V2G as claimed in claim 1 or 2, which is characterized in that
The operating cost of more micro-grid systems are as follows:
CTCi=mm (CPVi+CWi+CEVi+CGi)
Wherein, CTCMSFor the operating cost of more micro-grid systems, CTCiFor the operating cost of i-th of micro-capacitance sensor, CPVi、CWTi、CEVi、CGi
Respectively indicate the photovoltaic module cost of investment of i-th of micro-capacitance sensor, wind-driven generator cost of investment, the operating cost of electric car and
Power grid power trade cost obtains the power grid of i-th of micro-capacitance sensor with electricity price with the power that exchanges of i-th of micro-capacitance sensor according to power distribution network
Power trade cost.
5. a kind of electric car charge and discharge electricity price optimization method for considering V2G as claimed in claim 1 or 2, which is characterized in that
The optimization constraint condition includes: network trend Constraints of Equilibrium, electric car capacity-constrained, electric car power constraint, micro- electricity
The energy exchange power constraint of net and power distribution network, micro-capacitance sensor are offered to the charge and discharge of electric car and are constrained,
Network trend Constraints of Equilibrium are as follows: PPVi, t+PWTi, t+PEVBi, t+PGi, t=PLi, t
Electric car capacity-constrained are as follows: EEVBmin≤EEVBi, j, t≤EEVBmax
Electric car power constraint are as follows: PEVBmin≤PEVBi, j, t≤PEVBmax
The energy exchange power constraint of power distribution network are as follows: PEVBmin≤PGi, t≤PEVBmax
Micro-capacitance sensor is offered to the charge and discharge of electric car and is constrained are as follows: PDE≥ηCEVηDEVPCE
Wherein, PPVi, tGenerated output for i-th of micro-capacitance sensor in t moment photovoltaic module, PWTi, tIt is i-th of micro-capacitance sensor in t moment
The generated output of wind-driven generator, PEVBi, tFor power of all electric cars in t moment charge and discharge of i-th of micro-capacitance sensor, PLi, t
Load for i-th of micro-capacitance sensor in t moment, EEVBminFor the electricity minimum value of electric car, EEVBmaxFor the electricity of electric car
Maximum value, PEVBminFor the minimum power of electric car, PEVBmaxFor the maximum power of electric car, pDEFor the electric discharge of electric car
Electricity price, pCEFor the charging electricity price of electric car, PEVBi, j, tFor i-th of micro-capacitance sensor jth electric car in t moment charge and discharge
Power, EEVBi, j, tThen indicate electricity of the jth electric car of i-th of micro-capacitance sensor in t moment, ηCEVFor filling for electric car
Electrical efficiency, ηDEVFor the discharging efficiency of electric car, PGi, tPower is exchanged in t moment with i-th of micro-capacitance sensor for power distribution network.
6. a kind of electric car charge and discharge electricity price optimization method for considering V2G as claimed in claim 1 or 2, which is characterized in that
The step (2) includes:
(2-1) is using using the power of micro-capacitance sensor each in the more micro-grid systems charge and discharge of all electric cars per hour as particle
The optimized variable of group's algorithm, the particle of constituent particle group's algorithm；
(2-2) calculates the charge and discharge cost of the electric car of each particle, by the charge and discharge cost of electric car in all particles
Minimum value as inner ring for the first time circulation global optimum；
(2-3) updates speed and the position of particle using the more new formula of the Position And Velocity of particle swarm algorithm, calculates after updating
The charge and discharge cost of electric car of particle be compared with the global optimum of one cycle before inner ring, take wherein minimum value
For the new global optimum of inner ring；
(2-4) repeat step (2-3) repeatedly, obtain optimal electric car charge and discharge cost and its corresponding optimal electric car
Charge and discharge power.
7. a kind of electric car charge and discharge electricity price optimization method for considering V2G as claimed in claim 1 or 2, which is characterized in that
The step (3) includes:
(3-1) is using each micro-capacitance sensor to electric car charge and discharge electricity price as each dimension of particle each in particle swarm algorithm
Value, obtains population, according to electric energy quotation is bought and sold between power distribution network and more micro-grid systems, obtains the initial discharge electricity of electric car
The initial charge electricity price of valence and electric car utilizes the power calculation of the charge and discharge of optimal electric car for initializing population
The operating cost of more micro-grid systems of each particle, using the operating cost minimum value of more micro-grid systems of all particles as outer ring
Initial global optimum；
(3-2) updates speed and the position of particle using the more new formula of the Position And Velocity of particle swarm algorithm, calculates after updating
The operating cost of more micro-grid systems of particle be compared with a preceding global optimum for outer ring, take wherein minimum value be outer
The new global optimum of ring；
(3-3) repeat step (3-2) repeatedly, obtain optimal more micro-grid systems operating cost and its corresponding optimal electric car
Charge and discharge electricity price.
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