CN103996078B - Charging and discharging optimization control method for electric vehicle cluster - Google Patents
Charging and discharging optimization control method for electric vehicle cluster Download PDFInfo
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Abstract
The invention belongs to the field of interaction of electric vehicles and a power grid and discloses a charging and discharging optimization control method for an electric vehicle cluster. The method comprises the following steps: (1) an electric vehicle agent establishes an interactive information data base of electric vehicles; (2) the electric vehicle agent determines the dispatching priorities of the electric vehicles according to interactive information; (3) the electric vehicle agent sorts and classifies the electric vehicle dispatching sequence according to a comprehensive evaluation result of the dispatching priorities, and makes an integral dispatching optimization strategy of the electric vehicles; (4) an objective function is established. The charging and discharging optimization control method for the electric vehicle cluster makes up the shortfall of composition decomposition of an existing V2G dispatching model, a coordinating control system for interaction of the electric vehicles and the power grid is achieved, a feasible theory basis is provided for interaction of the electric vehicles and the power grid, and the popularization speed of the electric vehicles is further accelerated.
Description
Technical field
The present invention relates to electric automobile and electrical network interaction field, particularly to a kind of electrically optimized control of electric automobile cluster charge and discharge
Method processed.
Background technology
Research to running car behavioral pattern shows, the time of most of family car whole years 96% about is in stagnation of movement
State.Therefore, it can to realize electric automobile by electric automobile with electrical network interaction (i.e. Vehicle-to-Grid, V2G) technology
With electrical network two-way interaction.Application V2G technology, by formulate reasonable discharge and recharge strategy, overall arrangement electric automobile discharge and recharge behavior,
On the premise of meeting user's traveling demand, by two-way for dump energy controlled feedback to electrical network.
In order to solve that electric automobile distribution dispersion, quantity is big, difficult management the features such as, research worker proposes electric automobile
The concept of cluster (Electric Vehicle Aggregator), is also electric automobile agent.It refers to a number of electricity
The aggregation of electrical automobile, schedulable load of certain scale and stored energy capacitance, will become charging electric vehicle control, participation
The important form of electricity market.So far, V2G scheduling is gradually directly dispatched to graded dispatching conversion from electrical network.Schedule level one center
Realize the scheduling between electric automobile agent and electrical network (Aggregator-to-Grid, A2G), electricity is realized at second-level dispatching center
Scheduling between electrical automobile and electric automobile agent (Vehicle-to-Aggregator, V2A).
Research currently for V2G scheduling is almost limited only to schedule level one, can only provide the total discharge and recharge of electric automobile
Arrange, not yet decompose on each electric automobile, have not been able to fundamentally solve V2G scheduling problem.Secondly, electric automobile conduct
It is contemplated that user uses car convenience, its discharge and recharge behavior has randomness to the vehicles, and current scheduling model does not all consider
This problem.
Content of the invention
It is an object of the invention to overcoming above-mentioned deficiency, provide a kind of electric automobile cluster discharge and recharge optimal control method,
The method decomposes electric automobile discharge and recharge arrangement on each electric automobile the association it is achieved that between electrical network and electric automobile
Regulation and control system.
The purpose of the present invention is achieved through the following technical solutions：
A kind of electric automobile cluster discharge and recharge optimal control method, comprises the following steps：
1) electric automobile agent sets up the interactive information data base of each electric automobile；
2) electric automobile agent determines the dispatching priority of each electric automobile according to interactive information, and specific method is：
2-1) selection or the every priority evaluation index calculating electric automobile using interactive information in interactive information,
And after being analyzed, set up priority assessment indicator system；
2-2) every priority evaluation index of electric automobile is standardized processing；
2-3) determine comentropy and the weight of every priority evaluation index, and the dispatching priority of each electric automobile is entered
Row overall merit；
3) electric automobile agent according to dispatching priority comprehensive evaluation result, electric automobile dispatching sequence is ranked up,
Classification, and formulate the integrated scheduling optimisation strategy of electric automobile；
4) set up object function, and the final result being determined according to object function implements operation plan, thus controlling electronic
The discharge and recharge behavior of automobile.
Further, step 1) described in interactive information data base include automobile user to electric automobile agent Shen
The period of report, capacity, battery loss degree and the plan current data of exterior capacity and historical data, and plan exterior capacity refer to electronic
The capacity that automobile is taken away because running counter to operation plan.
Further, step 2-2) described in priority evaluation index include user's credibility, active volume ratio, available
Period ratio and battery loss degree；
Active volume ratio is expressed as：
Available period ratio is expressed as：
In formula：S0、H0For the initial active volume of electric automobile and when hop count；S1、H1For the called capacity of electric automobile and
Past tense hop count；P is electric automobile discharge charge power.
Further, step 2-1) described in priority assessment indicator system be：
Battery loss degree is reverse index, and that is, battery loss degree is more little more priority scheduling；
Active volume is than for positive index, you can with Capacity Ratio is more big more priority scheduling；
The available period is than for reverse index, you can with the period than more little more priority scheduling；
User's credibility is positive index, and that is, credibility is more big more priority scheduling.
Further, step 2-2) described in standardization use linear type standardization formula：
Or
Wherein, dijRepresent the desired value after standardization；xijRepresent i-th electric automobile jth item index；minxijRepresent
The minima of all objects of jth item index；maxxijRepresent the maximum of all objects of jth item index.
Further, step 2-3) the described dispatching priority to each electric automobile carries out the concrete grammar of overall merit
For：
1) calculate the comentropy of jth item index, computing formula is：
In formula：N is electric automobile quantity, and K is evaluation index quantity, and hasIf pij=0, definition
2) calculate the weight of indices, computing formula is：
3) overall merit is carried out to each electric automobile dispatching priority, computing formula is：
Further, step 3) described in electric automobile dispatching sequence is classified, that is, preferential according to each electric automobile
Power comprehensive evaluation value is divided into priority scheduling, back scheduling from high to low and does not dispatch.
Further, step 4) described in object function have 2, object function one be electric automobile agent administrative area
The sum of squares of deviations that domain electric automobile gives operation plan in the total charge-discharge electric power of day part and scheduling institution is minimum, and its formula is：
Wherein：Pm,nT () is the actual power of m-th electric automobile agent lower n-th electric automobile during period t；Nk,m
T () is period t agent m scheduling electric automobile sum；Pv,mM-th agential tune when () gives period t for scheduling institution t
Degree plan；
Object function two is the dispatch reliability highest of electric automobile, and its formula is：
In formula：Nr,mT () is the electric automobile demand of m-th agent period t when considering scheduling nargin；For numbering i1, i2,...,iqAutomobile user credibility；i1, i2,...,iqFor set 1,2 ...,
Nv (t) } in q element combination, nv (t) contains the quantity of back scheduling electric automobile, and q=N for period tr,m(t)-Nk,m
(t).
It is an advantage of the current invention that：The invention compensate for the deficiency of existing V2G scheduling model composition decomposition problem, from
Substantially achieve that electric automobile and electrical network are interactive to coordinate control system, be that electric automobile participates in electrical network interaction and provide conscientiously may be used
The theoretical basiss of row, further speed up electric automobile promotion rate.
The further advantage of the present invention, target and feature will be illustrated to a certain extent in the following description, and
And to a certain extent, will be apparent to those skilled in the art based on to investigating hereafter, or can
To be instructed from the practice of the present invention.The objects and other advantages of the present invention can pass through description below, and right will
Structure specifically noted in book, and accompanying drawing is asked to realize and to obtain.
Brief description
In order that the object, technical solutions and advantages of the present invention are clearer, below in conjunction with accompanying drawing the present invention is made into
The detailed description of one step, wherein：
Fig. 1 is the schematic flow sheet of electric automobile cluster discharge and recharge optimal control method of the present invention；
Fig. 2 is that the electric automobile dispatching priority classification of electric automobile cluster discharge and recharge optimal control method of the present invention is illustrated
Figure.
Specific embodiment
Below in conjunction with the accompanying drawings the present invention is described in further detail.
Fig. 1 is the schematic flow sheet of electric automobile cluster discharge and recharge optimal control method of the present invention, with reference to Fig. 1, the method
Comprise the following steps：1) electric automobile agent sets up the interactive information data base of each electric automobile；2) electric automobile agent
Determine the dispatching priority of each electric automobile according to interactive information, specific method is：2-1) selection or profit in interactive information
Calculate every priority evaluation index of electric automobile with interactive information, and set up priority evaluation index body after being analyzed
System；2-2) every priority evaluation index of electric automobile is standardized processing；2-3) determine that every priority evaluation refers to
Target comentropy and weight, and overall merit is carried out to the dispatching priority of each electric automobile；3) electric automobile agent according to
Dispatching priority comprehensive evaluation result is ranked up, classifies to electric automobile dispatching sequence, and formulates the entirety tune of electric automobile
Degree optimisation strategy；4) set up object function, and the final result being determined according to object function implements operation plan, thus controlling electricity
The discharge and recharge behavior of electrical automobile.
Step 1) described in interactive information data base include period that automobile user declares to electric automobile agent,
The current data of capacity, battery loss degree and plan exterior capacity and historical data, and plan exterior capacity refers to electric automobile because disobeying
The capacity carried on the back operation plan and take away.
Step 2-2) described in priority evaluation index include user's credibility, active volume ratio, available period ratio and
Battery loss degree；
Active volume ratio is expressed as：
Available period ratio is expressed as：
In formula：S0、H0For the initial active volume of electric automobile and when hop count；S1、H1For the called capacity of electric automobile and
Past tense hop count；P is electric automobile discharge charge power.
Assume certain agent declare power supply electric automobile quantity be 20, it declares information and history interactive data such as table
Shown in 1.The schedulable period that automobile user declares, schedulable capacity, battery is have recorded to electric automobile agent in table 1
The data message of extent of deterioration, plan exterior capacity and history scheduling capacity.It is divided within one day 24 periods, as shown in table 1,20
The period that automobile is declared only comprises 1,2 and 3, therefore without the dispatch situation considering other periods.
Table 1 electric automobile declares information and history interactive data
Day part each electric automobile index value can be calculated according to the data in table 1 and formula (1), (2), (3),
Including the numerical value than F1, credibility F2 and battery loss F3 for the active volume.
1 electric automobile index value of period as shown in table 2.Wherein "-" represents the plan of not declaring.Period 2 and period 3
Index value can also be obtained with same method.
2 period of table 1 each electric automobile index value
For each period, only determine dispatching priority to declaring inside the plan electric automobile, described declaring is inside the plan
Refer to declare the interactive plan of this period and had remaining schedulable capacity.
Step 2-1) described in priority assessment indicator system be：
Battery loss degree is reverse index, and that is, battery loss degree is more little more priority scheduling；
Active volume is than for positive index, you can with Capacity Ratio is more big more priority scheduling；
The available period is than for reverse index, you can with the period than more little more priority scheduling；
User's credibility is positive index, and that is, credibility is more big more priority scheduling.
Step 2-2) described in standardization use linear type standardization formula：
Or
Wherein, dijRepresent the desired value after standardization；xijRepresent i-th electric automobile jth item index；minxijRepresent
The minima of all objects of jth item index；maxxijRepresent the maximum of all objects of jth item index.
Formula (4) is the standardization formula of positive index, and formula (5) is the standardization formula of reverse index.
Period 1 each electric automobile index the results are shown in Table 3 according to the decision matrix after formula (4) or formula (5) standardization,
Wherein "-" represents not inside the plan.
3 period of table 1 each criterion result
Step 2-3) the described dispatching priority to each electric automobile concrete grammar that carries out overall merit is：
1) calculate the comentropy of jth item index, computing formula is：
In formula：N is electric automobile quantity, and K is evaluation index quantity, and hasIf pij=0, definition
2) calculate the weight of indices, computing formula is：
3) overall merit is carried out to each electric automobile dispatching priority, computing formula is：
Each indication information entropy E is calculated according to formula (6) and formula (7)j, weight wjAs shown in table 4.
4 period of table 1 each indication information entropy and weight
Each indication information entropy E for the period 2,3jWith weight wjIt is also possible to take said method to calculate obtain.
Using available 1,2,3 each period each electric automobile priority scheduling power overall merit numerical value of formula (8) i.e. and right
This numerical value is ranked up, as shown in table 5.
Table 5 each electric automobile priority scheduling power and sequence
Fig. 2 is that the electric automobile dispatching priority classification of electric automobile cluster discharge and recharge optimal control method of the present invention is illustrated
Figure.With reference to Fig. 2, step 3) described in electric automobile dispatching sequence is classified, that is, comprehensive according to each electric automobile priority
Evaluation of estimate is divided into priority scheduling, back scheduling from high to low and does not dispatch.
In being embodied as, scheduling strategy is as follows：
Each period is sorted from high to low according to this period electric automobile dispatching priority comprehensive evaluation value it is considered to electronic vapour
Car scheduling capacity nargin, electric automobile agent therefrom chooses sufficient amount of electric automobile and participates in operation plan, i.e. agent
The electric automobile quantity formulating operation plan actual demand is N, then top n priority scheduling in the sequence of priority comprehensive evaluation value,
Remainder belongs to back scheduling, declared interactive plan but not selected be then not scheduling portion, actual mechanical process
In, Capacity Margin can use 10%～50%, can be adjusted according to practical situation.
Object function one is electric automobile agent compass of competency electric automobile in the total charge-discharge electric power of day part and scheduling
The sum of squares of deviations that mechanism gives operation plan is minimum, and its formula is：
Wherein：Pm,nT () is the actual power of m-th electric automobile agent lower n-th electric automobile during period t；Nk,m
T () is period t agent m scheduling electric automobile sum；Pv,mM-th agential tune when () gives period t for scheduling institution t
Degree plan.
Object function two is the dispatch reliability highest of electric automobile, and its formula is：
In formula：Nr,mT () is the electric automobile demand of m-th agent period t when considering scheduling nargin；For numbering i1, i2,...,iqElectric automobile credibility；i1, i2,...,iqFor set 1,2 ..., nv
(t) } in q element combination, nv (t) contains the quantity of back scheduling electric automobile, and q=N for period tr,m(t)-Nk,m(t).
Constrained by following condition：
In formula：nc,m(t), ndc,mT () represents formulation charging plan and plan of discharging under electric automobile agent m respectively
Electric automobile quantity；Represent all under electric automobile agent m respectively and declare charging plan and discharge gage
The electric automobile quantity drawn；
In formula：pc,mi, pdc,miRepresent the charge-discharge electric power of i-th electric automobile under agent m respectively；
Because electric automobile agent region within the jurisdiction is limited, the electric automobile total amount in this region is also limited, therefore, each generation
The electric automobile total amount that reason business can dispatch has the upper limit.
In formula：For moment t electric automobile agent m region within the jurisdiction electric automobile total amount.
nrc,m(t)=γ nc,m(t), nrdc,m(t)=γ ndc,m(t)
In formula：nrc,m(t), nrdc,m(t) respectively represent consideration nargin when electric automobile agent m under formulate charge plan and
The electric automobile demand of electric discharge plan；γ is nargin.
It is scheduling with aforementioned scheduling strategy, when not considering standby, only need to be determined according to the result of object function one and adjust
The concrete discharge and recharge behavior controlling electric automobile of degree plan, 1,2,3 three period electric automobile operation plans are shown in Table 6.Wherein 1 table
Show scheduled, 0 expression is not scheduled, and "-" represents does not declare this period operation plan, and T1, T2, T3 represent 1,2,3 three respectively
Period.
6 three period electric automobile operation plans of table
According to the operation plan shown in table 6, that can analyze each electric automobile declares active volume and scheduled appearance
The situation of amount, as shown in table 7.Wherein S0 is to declare active volume, and S1 is scheduled capacity.
The all period electric automobile capacity scheduling situation (units of table 7：kW)
In contrast table 1, information declared by electric automobile, it can be found that be not called upon completely electric automobile (numbering is 3,5,7,
9,10) at least two indexs are low, wherein credibility in addition to electric automobile 9 remaining all not less than 0.5, battery loss all exists
More than 10%；Completely not invoked electric automobile (numbering is 15,17,18,19) has one or more index poor, have impact on
Comprehensive evaluation value；Completely invoked electric automobile indices preferably and more equalize.
When considering standby, need to consider object function one and object function two simultaneously.Assume that plan run counter to by electric automobile
Probability Normal Distribution N (0.85,0.12) it is considered to when electric automobile nargin is 10%, containing standby scheduling result such as table 8
Shown.
The operation plan that table 8 is 10% containing nargin
When considering electric automobile nargin for 10%, 20%, 30%, day part operation plan reliability is as shown in table 9.
Table 9 containing nargin be 10%, 20% and 30% dispatch reliability
Contrast four kinds of situations it is found that when not considering standby, day part agent's dispatch reliability is very low, with
The electric automobile scale of back scheduling increases, and agent's dispatch reliability is consequently increased, and reaches 30% when standby in this example
When, day part dispatch reliability is all more than 90%.
For Capacity Margin value, unsuitable excessive also unsuitable too small.It is excessive that to will result in capacity compensation relatively costly；Cross I
Off-capacity can be caused to lead to operation plan cannot implement.The main credibility phase overall with automobile user of the setting of its value
Close, when user's entirety credibility is higher, Capacity Margin can use lower value, when user's entirety credibility is relatively low, can use higher
Value.
Finally illustrate, preferred embodiment above only in order to technical scheme to be described and unrestricted, although logical
Cross above preferred embodiment the present invention to be described in detail, it is to be understood by those skilled in the art that can be
In form and various changes are made to it, without departing from claims of the present invention limited range in details.
Claims (4)
1. a kind of electric automobile cluster discharge and recharge optimal control method it is characterised in that：Comprise the following steps：
1) electric automobile agent sets up the interactive information data base of each electric automobile；
2) electric automobile agent determines the dispatching priority of each electric automobile according to interactive information, and specific method is：
2-1) selection or the every priority evaluation index being calculated electric automobile using interactive information in interactive information, are gone forward side by side
Priority assessment indicator system is set up after row analysis；
2-2) every priority evaluation index of electric automobile is standardized processing；
2-3) determine comentropy and the weight of every priority evaluation index, and the dispatching priority of each electric automobile is carried out comprehensive
Close and evaluate；
3) electric automobile agent is ranked up to electric automobile dispatching sequence according to dispatching priority comprehensive evaluation result, divides
Class, and formulate the integrated scheduling optimisation strategy of electric automobile；
4) set up object function, and the final result being determined according to object function implements operation plan, thus controlling electric automobile
Discharge and recharge behavior；
Step 1) described in interactive information data base include period, the appearance that automobile user is declared to electric automobile agent
The current data of amount, battery loss degree and plan exterior capacity and historical data, and plan exterior capacity refers to electric automobile because running counter to
Operation plan and the capacity taken away；
Step 2-1) described in priority evaluation index include user's credibility, active volume ratio, available period ratio and battery
Extent of deterioration；
Active volume ratio is expressed as：
Available period ratio is expressed as：
In formula：S0、H0For the initial active volume of electric automobile and when hop count；S1、H1For the called capacity of electric automobile and mistake
Hop count when going；P is electric automobile discharge charge power；
Step 2-1) described in priority assessment indicator system be：
Battery loss degree is reverse index, and that is, battery loss degree is more little more priority scheduling；
Active volume is than for positive index, you can with Capacity Ratio is more big more priority scheduling；
The available period is than for reverse index, you can with the period than more little more priority scheduling；
User's credibility is positive index, and that is, credibility is more big more priority scheduling；
Step 4) described in object function have 2, object function one exists for electric automobile agent compass of competency electric automobile
The sum of squares of deviations that the total charge-discharge electric power of day part and scheduling institution give operation plan is minimum, and its formula is：
Wherein：Pm,nT () is the actual power of m-th electric automobile agent lower n-th electric automobile during period t；Nk,mT () is
Period t agent m scheduling electric automobile sum；Pv,mM-th agential scheduling meter when () gives period t for scheduling institution t
Draw；
Object function two is the dispatch reliability highest of electric automobile, and its formula is：
In formula：Nr,mT () is the electric automobile demand of m-th agent period t when considering scheduling nargin；For
Numbering i1, i2,...,iqAutomobile user credibility；i1, i2,...,iqFor q element in set { 1,2 ..., nv (t) }
Combination, nv (t) contains the quantity of back scheduling electric automobile, and q=N for period tr,m(t)-Nk,m(t).
2. electric automobile cluster discharge and recharge optimal control method according to claim 1 it is characterised in that：Step 2-2) in
Described standardization uses linear type standardization formula：
Or
Wherein, dijRepresent the desired value after standardization；xijRepresent i-th electric automobile jth item index；minxijRepresent jth
The minima of the item all objects of index；max xijRepresent the maximum of all objects of jth item index.
3. electric automobile cluster discharge and recharge optimal control method according to claim 1 is it is characterised in that step 2-3) institute
State the dispatching priority to each electric automobile and carry out the concrete grammar of overall merit and be：
1) calculate the comentropy of jth item index, computing formula is：
In formula：N is electric automobile quantity, and K is evaluation index quantity, and hasIf pij=0, definition
2) calculate the weight of indices, computing formula is：
3) overall merit is carried out to each electric automobile dispatching priority, computing formula is：
4. electric automobile cluster discharge and recharge optimal control method according to claim 1 is it is characterised in that step 3) in institute
State and electric automobile dispatching sequence is classified, be divided into from high to low preferentially according to each electric automobile priority comprehensive evaluation value
Scheduling, back scheduling and not dispatching.
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| CN104461689B (en) * | 2014-12-02 | 2017-06-16 | 重庆大学 | Power system frequency modulation controllable electric automobile Number dynamics change modeling method based on Monte Carlo |
| CN107681729B (en) * | 2015-12-24 | 2020-06-05 | 合肥工业大学 | Multi-port converter for electric vehicle cluster charging and discharging |
| CN106203720B (en) * | 2016-07-15 | 2019-06-14 | 合肥工业大学 | A kind of schedulable capacity prediction methods of Multiple Time Scales electric car cluster |
| CN106945558A (en) * | 2017-03-31 | 2017-07-14 | 天津大学 | Cluster electric automobile V2G control strategies |
| CN107482680B (en) * | 2017-08-28 | 2020-06-05 | 南京工程学院 | Electric vehicle dispatching method based on islanding division |
| CN107545369A (en) * | 2017-09-04 | 2018-01-05 | 重庆大学 | The electric automobile cluster orderly dispatching method in real time of meter and user's participation |
| US10583750B1 (en) | 2018-09-20 | 2020-03-10 | Honda Motor Co., Ltd. | Dealership energy management system for charging incoming customer vehicles with inventory vehicles and method thereof |
| CN111369741B (en) * | 2020-03-13 | 2021-09-07 | 南京润北智能环境研究院有限公司 | System for matching multiple parking lots with shared parking spaces and electric vehicles in electric power market |
| CN111724080A (en) * | 2020-06-29 | 2020-09-29 | 南京工程学院 | Mobile charging pile group scheduling method considering battery pack health state balance |
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