CN103996078A - Charging and discharging optimization control method for electric vehicle cluster - Google Patents

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

Electric automobile cluster discharges and recharges optimal control method

Technical field

The present invention relates to the interactive field of electric automobile and electrical network, particularly a kind of electric automobile cluster discharges and recharges optimal control method.

Background technology

Research to running car behavior pattern shows, the time of annual 96% left and right of most of family cars is in suspended state.Therefore, can realize electric automobile and electrical network two-way interaction by electric automobile and electrical network interaction (being Vehicle-to-Grid, V2G) technology.Application V2G technology, rationally discharges and recharges strategy by formulating, and overall arrangement electric automobile discharges and recharges behavior, travel under the prerequisite of demand meeting user, by two-way dump energy controlled feedback to electrical network.

For solve electric automobile distribute disperse, the feature such as quantity is large, difficult management, researchist has proposed the concept of electric automobile cluster (Electric Vehicle Aggregator), is also electric automobile commission merchant.It refers to the aggregation of the electric automobile of some, and the of certain scale load dispatched and stored energy capacitance will become charging electric vehicle control, participate in the important form of electricity market.So far, V2G scheduling is directly dispatched and is changed to graded dispatching by electrical network gradually.Electric automobile commission merchant and electrical network (Aggregator-to-Grid are realized in schedule level one center, A2G) scheduling between, the scheduling between electric automobile and electric automobile commission merchant (Vehicle-to-Aggregator, V2A) is realized at second-level dispatching center.

At present almost only be confined to schedule level one for the research of V2G scheduling, can only provide electric automobile total discharge and recharge arrangement, not yet decompose on each electric automobile, can fundamentally not solve V2G scheduling problem.Secondly, electric automobile, as the vehicles, considers that user uses car convenience, and it discharges and recharges behavior and has randomness, and current scheduling model is not all considered this problem.

Summary of the invention

The object of the invention is to overcome above-mentioned deficiency, provide a kind of electric automobile cluster to discharge and recharge optimal control method, the method discharges and recharges electric automobile to arrange to decompose on each electric automobile, has realized the coordination control between electrical network and electric automobile.

The object of the invention is to be achieved through the following technical solutions:

A kind of electric automobile cluster discharges and recharges optimal control method, comprises the following steps:

1) electric automobile commission merchant sets up the interactive information database of each electric automobile;

2) electric automobile commission merchant determines the dispatching priority of each electric automobile according to interactive information, and concrete method is:

2-1) in interactive information, choose or utilize interactive information to calculate every right of priority evaluation index of electric automobile, and after analyzing, setting up right of priority assessment indicator system;

2-2) every right of priority evaluation index of electric automobile is carried out to standardization;

2-3) determine information entropy and the weight of every right of priority evaluation index, and the dispatching priority of each electric automobile is carried out to comprehensive evaluation;

3) electric automobile commission merchant sorts, classifies electric automobile dispatching sequence according to dispatching priority comprehensive evaluation result, and formulates the integrated scheduling optimisation strategy of electric automobile;

4) set up objective function, and implement operation plan according to the definite net result of objective function, thereby control the behavior that discharges and recharges of electric automobile.

Further, step 1) described in interactive information database comprise current data and the historical data of period, capacity, battery loss degree and capacity outside the plan that electric automobile user declares to electric automobile commission merchant, and capacity outside the plan refers to the capacity that electric automobile is taken away because running counter to operation plan.

Further, step 2-2) described in right of priority evaluation index comprise user's credibility, active volume ratio, available period than and battery loss degree;

Active volume ratio is expressed as: ${\mathrm{\φ}}_S=\min (\frac{S_0-S_1}{(H_0-H_1)P},1)---\left(2\right)$

Available period ratio is expressed as:

In formula: S ₀, H ₀for the initial active volume of electric automobile and time hop count; S ₁, H ₁for the called capacity of electric automobile and past tense hop count; P is that electric automobile fills/put power.

Further, step 2-1) described in right of priority assessment indicator system be:

Battery loss degree is reverse index, i.e. the more little more priority scheduling of battery loss degree;

Active volume is than being forward index, i.e. more greatly more priority scheduling of available volume ratio;

The available period, can be with the period than more little more priority scheduling than being reverse index;

User's credibility is forward index, i.e. more greatly more priority scheduling of credibility.

Further, step 2-2) described in standardization adopt be linear pattern standardization formula:

$d_{\mathrm{ij}}=\frac{x_{\mathrm{ij}}-{\min x}_{\mathrm{ij}}}{{\max x}_{\mathrm{ij}}-{\min }_{\mathrm{ij}}}---\left(4\right)$

Or

$d_{\mathrm{ij}}=\frac{{\max x}_{\mathrm{ij}}-x_{\mathrm{ij}}}{{\max x}_{\mathrm{ij}}-{\min x}_{\mathrm{ij}}}---\left(5\right)$

Wherein, d _ijrepresent standardization desired value afterwards; x _ijrepresent i electric automobile j item index; Minx _ijrepresent the minimum value of all objects of j item index; Maxx _ijrepresent the maximal value of all objects of j item index.

Further, step 2-3) the described concrete grammar that the dispatching priority of each electric automobile is carried out to comprehensive evaluation is:

1) information entropy of calculating j item index, computing formula is:

$E_j=-\frac{1}{1\mathrm{nn}}\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{p}_{\mathrm{ij}}\ln p_{\mathrm{ij}}j=\mathrm{1,2},\·\·\·,K---\left(6\right)$

In formula: n is electric automobile quantity, and K is evaluation index quantity, and has if p _ij=0, definition $\underset{p_{\mathrm{ij}}\→0}{\lim }{p}_{\mathrm{ij}}\ln p_{\mathrm{ij}}=0;$

2) weight of calculating indices, computing formula is:

$w_j=\frac{1-E_j}{K-\underset{j=1}{\overset{K}{\mathrm{\Σ}}}{E}_j}---\left(7\right)$

3) each electric automobile dispatching priority is carried out to comprehensive evaluation, computing formula is:

$V_i=\underset{j=1}{\overset{K}{\mathrm{\Σ}}}{w}_j{d}_{\mathrm{ij}}.---\left(8\right)$

Further, step 3) described in electric automobile dispatching sequence is classified, be divided into from high to low priority scheduling, back scheduling and do not dispatch according to each electric automobile right of priority comprehensive evaluation value.

Further, step 4) described in objective function have 2, objective function one always discharges and recharges the sum of squares of deviations minimum of power and the given operation plan of scheduling institution for electric automobile commission merchant compass of competency electric automobile at day part, its formula is:

$\min f=\min \underset{t=1}{\overset{H}{\mathrm{\Σ}}}{(\underset{n=1}{\overset{N_{k,m}}{\mathrm{\Σ}}}{P}_{m,n}\left(t\right)-P_{v,m}\left(t\right))}^2---\left(9\right)$

Wherein: P _m,n(t) real power of n electric automobile under m electric automobile commission merchant while being period t; N _k,m(t) be period t commission merchant m scheduling electric automobile sum; P _v,m(t) m agential operation plan while being the given period t of scheduling institution;

The dispatch reliability that objective function two is electric automobile is the highest, and its formula is:

$\begin{array}{c}\max f_{\mathrm{reliabilit\; y}}\left(t\right)=\max \{\underset{i_0=1}{\overset{N_{r,m}\left(t\right)}{\mathrm{\Π}}}(1-p_{i_0})+\underset{i_1}{\mathrm{\Σ}}(\underset{i_0=1}{\overset{N_{r,m}\left(t\right)}{\mathrm{\Π}}}(1-p_{i_0})/(1-p_{i_1}))\\ +\underset{i_1,i_2}{\mathrm{\Σ}}(\underset{i_0=1}{\overset{N_{r,m}\left(t\right)}{\mathrm{\Π}}}(1-p_{i0})/[(1-p_{i_1})(1-p_{i_2})\left]\right)+\·\·\·\\ +\underset{i_1,i_2,\·\·\·,i_q}{\mathrm{\Σ}}(\underset{i_0=1}{\overset{N_{r,m}\left(t\right)}{\mathrm{\Π}}}(1-p_{i_0})/[(1-p_{i_1})\·\·\·(1-p_{i_q})\left]\right)\}\end{array}---\left(10\right)$

In formula: N _r,m(t) the electric automobile demand of m commission merchant period t during for consideration scheduling nargin; for numbering i ₁, i ₂..., i _qelectric automobile user credibility; i ₁, i ₂..., i _qfor set 1,2 ..., nv (t) } in the combination of q element, nv (t) contains the quantity of back scheduling electric automobile and q=N for period t _r,m(t)-N _k,m(t).

The invention has the advantages that: the invention has made up the deficiency of existing V2G scheduling model composition decomposition problem, from having realized in essence the interactive hierarchy of control of coordinating of electric automobile and electrical network, provide practicable theoretical foundation for electric automobile participates in electrical network interaction, further accelerated electric automobile promotion rate.

Other advantage of the present invention, target and feature will be set forth to a certain extent in the following description, and to a certain extent, based on will be apparent to those skilled in the art to investigating below, or can be instructed from the practice of the present invention.The objects and other advantages of the present invention can be passed through instructions below, claims, and in accompanying drawing, specifically noted structure realizes and obtains.

Brief description of the drawings

In order to make the object, technical solutions and advantages of the present invention clearer, below in conjunction with accompanying drawing, the present invention is described in further detail, wherein:

Fig. 1 is the schematic flow sheet that electric automobile cluster of the present invention discharges and recharges optimal control method;

Fig. 2 is the electric automobile dispatching priority classification schematic diagram that electric automobile cluster of the present invention discharges and recharges optimal control method.

Embodiment

Below in conjunction with accompanying drawing, the present invention is described in further detail.

Fig. 1 is the schematic flow sheet that electric automobile cluster of the present invention discharges and recharges optimal control method, and with reference to Fig. 1, the method comprises the following steps: 1) electric automobile commission merchant sets up the interactive information database of each electric automobile; 2) electric automobile commission merchant determines the dispatching priority of each electric automobile according to interactive information, concrete method is: 2-1) in interactive information, choose or utilize interactive information to calculate every right of priority evaluation index of electric automobile, and after analyzing, set up right of priority assessment indicator system; 2-2) every right of priority evaluation index of electric automobile is carried out to standardization; 2-3) determine information entropy and the weight of every right of priority evaluation index, and the dispatching priority of each electric automobile is carried out to comprehensive evaluation; 3) electric automobile commission merchant sorts, classifies electric automobile dispatching sequence according to dispatching priority comprehensive evaluation result, and formulates the integrated scheduling optimisation strategy of electric automobile; 4) set up objective function, and implement operation plan according to the definite net result of objective function, thereby control the behavior that discharges and recharges of electric automobile.

Step 1) described in interactive information database comprise current data and the historical data of period, capacity, battery loss degree and capacity outside the plan that electric automobile user declares to electric automobile commission merchant, and capacity outside the plan refers to the capacity that electric automobile is taken away because running counter to operation plan.

Step 2-2) described in right of priority evaluation index comprise user's credibility, active volume ratio, available period than and battery loss degree;

Active volume ratio is expressed as: ${\mathrm{\φ}}_S=\min (\frac{S_0-S_1}{(H_0-H_1)P},1)---\left(2\right)$

Available period ratio is expressed as:

In formula: S ₀, H ₀for the initial active volume of electric automobile and time hop count; S ₁, H ₁for the called capacity of electric automobile and past tense hop count; P is that electric automobile fills/put power.

Suppose that the electric automobile quantity that certain commission merchant declares power supply is 20, it declares information and historical interactive data is as shown in table 1.In table 1, recorded that electric automobile user declares to electric automobile commission merchant can scheduling slot, can scheduling capacity, the data message of battery loss degree, capacity outside the plan and historical scheduling capacity.Within one day, be divided into 24 periods, as shown in table 1, the period that 20 automobiles are declared only comprises 1,2 and 3, therefore need not consider the scheduling situation of other periods.

Table 1 electric automobile is declared information and historical interactive data

Can calculate the each electric automobile index value of day part according to the data in table 1 and formula (1), (2), (3), comprise that active volume is than the numerical value of F1, credibility F2 and battery loss F3.

Period as shown in table 21 electric automobile index value.Wherein "-" represents not declare plan.The index value of period 2 and period 3 also can obtain with same method.

Each electric automobile index value of table 2 period 1

For each period, only determine dispatching priority to declaring inside the plan electric automobile, described declare inside the plan referring to and declared the interaction plan of this period and had the residue can scheduling capacity.

Step 2-1) described in right of priority assessment indicator system be:

Battery loss degree is reverse index, i.e. the more little more priority scheduling of battery loss degree;

Active volume is than being forward index, i.e. more greatly more priority scheduling of available volume ratio;

The available period, can be with the period than more little more priority scheduling than being reverse index;

User's credibility is forward index, i.e. more greatly more priority scheduling of credibility.

Step 2-2) described in standardization adopt be linear pattern standardization formula:

$d_{\mathrm{ij}}=\frac{x_{\mathrm{ij}}-{\min x}_{\mathrm{ij}}}{{\max x}_{\mathrm{ij}}-{\min }_{\mathrm{ij}}}---\left(4\right)$

Or

$d_{\mathrm{ij}}=\frac{{\max x}_{\mathrm{ij}}-x_{\mathrm{ij}}}{{\max x}_{\mathrm{ij}}-{\min x}_{\mathrm{ij}}}---\left(5\right)$

Wherein, d _ijrepresent standardization desired value afterwards; x _ijrepresent i electric automobile j item index; Minx _ijrepresent the minimum value of all objects of j item index; Maxx _ijrepresent the maximal value of all objects of j item index.

Formula (4) is the standardization formula of forward index, the standardization formula that formula (5) is reverse index.

Each electric automobile index of period 1 the results are shown in Table 3 according to the decision matrix after formula (4) or formula (5) standardization, and wherein "-" represents not inside the plan.

Each index standardization of table 3 period 1 result

Step 2-3) the described concrete grammar that the dispatching priority of each electric automobile is carried out to comprehensive evaluation is:

1) information entropy of calculating j item index, computing formula is:

$E_j=-\frac{1}{1\mathrm{nn}}\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{p}_{\mathrm{ij}}\ln p_{\mathrm{ij}}j=\mathrm{1,2},\·\·\·,K---\left(6\right)$

In formula: n is electric automobile quantity, and K is evaluation index quantity, and has if p _ij=0, definition $\underset{p_{\mathrm{ij}}\→0}{\lim }{p}_{\mathrm{ij}}\ln p_{\mathrm{ij}}=0;$

2) weight of calculating indices, computing formula is:

$w_j=\frac{1-E_j}{K-\underset{j=1}{\overset{K}{\mathrm{\Σ}}}{E}_j}---\left(7\right)$

3) each electric automobile dispatching priority is carried out to comprehensive evaluation, computing formula is:

$V_i=\underset{j=1}{\overset{K}{\mathrm{\Σ}}}{w}_j{d}_{\mathrm{ij}}.---\left(8\right)$

Calculate each indication information entropy E according to formula (6) and formula (7) _j, weight w _jas shown in table 4.

Each indication information entropy of table 4 period 1 and weight

For each indication information entropy E of period 2,3 _jwith weight w _j, also can take said method to calculate and obtain.

Utilize formula (8) can obtain 1,2,3 each electric automobile priority scheduling power comprehensive evaluation numerical value of each period and this numerical value is sorted, as shown in table 5.

The each electric automobile priority scheduling power of table 5 and sequence

Fig. 2 is the electric automobile dispatching priority classification schematic diagram that electric automobile cluster of the present invention discharges and recharges optimal control method.With reference to Fig. 2, step 3) described in electric automobile dispatching sequence is classified, be divided into from high to low priority scheduling, back scheduling and do not dispatch according to each electric automobile right of priority comprehensive evaluation value.

In concrete enforcement, scheduling strategy is as follows:

Each period sorts from high to low according to this period electric automobile dispatching priority comprehensive evaluation value, consider electric automobile scheduling capacity nargin, the electric automobile that electric automobile commission merchant therefrom chooses sufficient amount participates in operation plan, be that the electric automobile quantity that commission merchant formulates operation plan actual demand is N, top n priority scheduling in the sequence of right of priority comprehensive evaluation value, remainder all belongs to back scheduling, declare interactive plan but not selected for not dispatching part, in actual mechanical process, Capacity Margin desirable 10%～50%, can adjust according to actual conditions.

Objective function one is electric automobile commission merchant compass of competency electric automobile always discharges and recharges power and the given operation plan of scheduling institution sum of squares of deviations minimum at day part, and its formula is:

$\min f=\min \underset{t=1}{\overset{H}{\mathrm{\Σ}}}{(\underset{n=1}{\overset{N_{k,m}}{\mathrm{\Σ}}}{P}_{m,n}\left(t\right)-P_{v,m}\left(t\right))}^2---\left(9\right)$

Wherein: P _m,n(t) real power of n electric automobile under m electric automobile commission merchant while being period t; N _k,m(t) be period t commission merchant m scheduling electric automobile sum; P _v,m(t) m agential operation plan while being the given period t of scheduling institution.

The dispatch reliability that objective function two is electric automobile is the highest, and its formula is:

$\begin{array}{c}\max f_{\mathrm{reliabilit\; y}}\left(t\right)=\max \{\underset{i_0=1}{\overset{N_{r,m}\left(t\right)}{\mathrm{\Π}}}(1-p_{i_0})+\underset{i_1}{\mathrm{\Σ}}(\underset{i_0=1}{\overset{N_{r,m}\left(t\right)}{\mathrm{\Π}}}(1-p_{i_0})/(1-p_{i_1}))\\ +\underset{i_1,i_2}{\mathrm{\Σ}}(\underset{i_0=1}{\overset{N_{r,m}\left(t\right)}{\mathrm{\Π}}}(1-p_{i0})/[(1-p_{i_1})(1-p_{i_2})\left]\right)+\·\·\·\\ +\underset{i_1,i_2,\·\·\·,i_q}{\mathrm{\Σ}}(\underset{i_0=1}{\overset{N_{r,m}\left(t\right)}{\mathrm{\Π}}}(1-p_{i_0})/[(1-p_{i_1})\·\·\·(1-p_{i_q})\left]\right)\}\end{array}---\left(10\right)$

In formula: N _r,m(t) the electric automobile demand of m commission merchant period t during for consideration scheduling nargin; for numbering i ₁, i ₂..., i _qelectric automobile credibility; i ₁, i ₂..., i _qfor set 1,2 ..., nv (t) } in the combination of q element, nv (t) contains the quantity of back scheduling electric automobile and q=N for period t _r,m(t)-N _k,m(t).

Be subject to the constraint of following condition:

$\left\{\begin{array}{c}{n}_{c,m}\left(t\right)\≤n_{c,m}^{\max }\left(t\right)\\ n_{\mathrm{dc},m}\left(t\right)\≤n_{\mathrm{dc},m}^{\max }\left(t\right)\end{array}\right.$

In formula: n _c,m(t), n _{dc, m}(t) represent respectively to formulate under electric automobile commission merchant m the electric automobile quantity of charging plan and electric discharge plan; represent respectively all electric automobile quantity of declaring charging plan and electric discharge plan under electric automobile commission merchant m;

$\left\{\begin{array}{c}\underset{i=1}{\overset{n_{c,m}\left(t\right)}{\mathrm{\Σ}}}{p}_{c,\mathrm{mi}}\≤\underset{i=1}{\overset{n_{c,m}^{\max }\left(t\right)}{\mathrm{\Σ}}}{p}_{c,\mathrm{mi}}\\ \underset{i=1}{\overset{n_{\mathrm{dc},m}\left(t\right)}{\mathrm{\Σ}}}{p}_{\mathrm{dc},\mathrm{mi}}\≤\underset{i=0}{\overset{n_{\mathrm{dc},m}^{\max }\left(t\right)}{\mathrm{\Σ}}}{p}_{\mathrm{dc},\mathrm{mi}}\end{array}\right.$

In formula: p _{c, mi}, p _{dc, mi}represent respectively the power that discharges and recharges of i electric automobile under commission merchant m;

Because electric automobile commission merchant region within the jurisdiction is limited, the electric automobile total amount in this region is also limited, and therefore, the electric automobile total amount that each commission merchant can dispatch has the upper limit.

$n_{c,m}^{\max }\left(t\right)+n_{\mathrm{dc},m}^{\max }\left(t\right)\≤N_{m,t}^{\max }$

In formula: for moment t electric automobile commission merchant m region within the jurisdiction electric automobile total amount.

n _rc,m(t)＝γn _c,m(t)，n _rdc,m(t)＝γn _dc,m(t)

In formula: n _{rc, m}(t), n _{rdc, m}(t) while representing to consider nargin respectively, under electric automobile commission merchant m, formulate the electric automobile demand of charging plan and electric discharge plan; γ is nargin.

Dispatch with aforementioned scheduling strategy, when not considering time for subsequent use, only need determine that operation plan specifically controls the behavior that discharges and recharges of electric automobile according to the result of objective function one, 1,2,3 three period electric automobile operation plan is in table 6.Wherein 1 represents to be scheduled, and 0 represents not to be scheduled, and "-" represents not declare this period operation plan, and T1, T2, T3 represent respectively 1,2,3 three period.

Three period electric automobile operation plans of table 6

According to the operation plan of showing in table 6, that can analyze each electric automobile declares active volume and the situation of the capacity that is scheduled, as shown in table 7.Wherein S0 is for declaring active volume, and S1 is the capacity of being scheduled.

Electric automobile capacity scheduling situation of all periods of table 7 (unit: kW)

In contrast table 1, electric automobile is declared information, can find that completely not invoked electric automobile (is numbered 3,5,7,9,10) have at least two indexs on the low side, wherein except electric automobile 9, all the other all do not exceed 0.5 to credibility, and battery loss is all more than 10%; Incomplete invoked electric automobile (being numbered 15,17,18,19) have one or above index poor, affected comprehensive evaluation value; Complete invoked electric automobile indices is better and comparatively balanced.

In the time that consideration is for subsequent use, need to consider objective function one and objective function two simultaneously.Suppose that electric automobile runs counter to the probability Normal Distribution N (0.85,0.1 of plan ²), while considering that electric automobile nargin is 10%, as shown in table 8 containing scheduling result for subsequent use.

The operation plan that table 8 is 10% containing nargin

While considering that electric automobile nargin is 10%, 20%, 30%, day part operation plan reliability is as shown in table 9.

Table 9 is 10%, 20% and 30% dispatch reliability containing nargin

Contrasting four kinds of situations can find, when not considering that time for subsequent use, day part commission merchant dispatch reliability is very low, along with the electric automobile scale of back scheduling increases, commission merchant's dispatch reliability also increases thereupon, and in this example, when for subsequent use while reaching 30%, day part dispatch reliability all exceedes 90%.

For Capacity Margin value, unsuitable excessive also unsuitable too small.Crossing senior general causes capacity compensation cost higher; Too smallly may cause off-capacity and cause operation plan to implement.The setting of its value is mainly relevant to electric automobile user entirety credibility, in the time that user's entirety credibility is higher, and the desirable lower value of Capacity Margin, in the time that user's entirety credibility is lower, desirable high value.

Finally explanation is, above preferred embodiment is only unrestricted in order to technical scheme of the present invention to be described, although the present invention is described in detail by above preferred embodiment, but those skilled in the art are to be understood that, can make various changes to it in the form and details, and not depart from the claims in the present invention book limited range.

Claims (8)

1. electric automobile cluster discharges and recharges an optimal control method, it is characterized in that: comprise the following steps:

1) electric automobile commission merchant sets up the interactive information database of each electric automobile;

2) electric automobile commission merchant determines the dispatching priority of each electric automobile according to interactive information, and concrete method is:

2-1) in interactive information, choose or utilize interactive information to calculate every right of priority evaluation index of electric automobile, and after analyzing, setting up right of priority assessment indicator system;

2-2) every right of priority evaluation index of electric automobile is carried out to standardization;

2-3) determine information entropy and the weight of every right of priority evaluation index, and the dispatching priority of each electric automobile is carried out to comprehensive evaluation;

3) electric automobile commission merchant sorts, classifies electric automobile dispatching sequence according to dispatching priority comprehensive evaluation result, and formulates the integrated scheduling optimisation strategy of electric automobile;

4) set up objective function, and implement operation plan according to the definite net result of objective function, thereby control the behavior that discharges and recharges of electric automobile.

2. electric automobile cluster according to claim 1 discharges and recharges optimal control method, it is characterized in that: step 1) described in interactive information database comprise current data and the historical data of period, capacity, battery loss degree and capacity outside the plan that electric automobile user declares to electric automobile commission merchant, and capacity outside the plan refers to the capacity that electric automobile is taken away because running counter to operation plan.

3. electric automobile cluster according to claim 1 discharges and recharges optimal control method, it is characterized in that: step 2-2) described in right of priority evaluation index comprise user's credibility, active volume ratio, available period than and battery loss degree;

Active volume ratio is expressed as:

Available period ratio is expressed as:

In formula: S ₀, H ₀for the initial active volume of electric automobile and time hop count; S ₁, H ₁for the called capacity of electric automobile and past tense hop count; P is that electric automobile fills/put power.

4. electric automobile cluster according to claim 1 discharges and recharges optimal control method, it is characterized in that step 2-1) described in right of priority assessment indicator system be:

Battery loss degree is reverse index, i.e. the more little more priority scheduling of battery loss degree;

Active volume is than being forward index, i.e. more greatly more priority scheduling of available volume ratio;

The available period, can be with the period than more little more priority scheduling than being reverse index;

User's credibility is forward index, i.e. more greatly more priority scheduling of credibility.

5. electric automobile cluster according to claim 1 discharges and recharges optimal control method, it is characterized in that: step 2-2) described in standardization adopt be linear pattern standardization formula:

Or

Wherein, d _ijrepresent standardization desired value afterwards; x _ijrepresent i electric automobile j item index; Minx _ijrepresent the minimum value of all objects of j item index; Maxx _ijrepresent the maximal value of all objects of j item index.

6. electric automobile cluster according to claim 1 discharges and recharges optimal control method, it is characterized in that step 2-3) the described concrete grammar that the dispatching priority of each electric automobile is carried out to comprehensive evaluation is:

1) information entropy of calculating j item index, computing formula is:

In formula: n is electric automobile quantity, and K is evaluation index quantity, and has if p _ij=0, definition

2) weight of calculating indices, computing formula is:

3) each electric automobile dispatching priority is carried out to comprehensive evaluation, computing formula is:

。

7. electric automobile cluster according to claim 1 discharges and recharges optimal control method, it is characterized in that, step 3) described in electric automobile dispatching sequence is classified, be divided into from high to low priority scheduling, back scheduling and do not dispatch according to each electric automobile right of priority comprehensive evaluation value.

8. electric automobile cluster according to claim 1 discharges and recharges optimal control method, it is characterized in that: step 4) described in objective function have 2, objective function one is electric automobile commission merchant compass of competency electric automobile always discharges and recharges power and the given operation plan of scheduling institution sum of squares of deviations minimum at day part, and its formula is:

Wherein: P _m,n(t) real power of n electric automobile under m electric automobile commission merchant while being period t; N _k,m(t) be period t commission merchant m scheduling electric automobile sum; P _v,m(t) m agential operation plan while being the given period t of scheduling institution;

The dispatch reliability that objective function two is electric automobile is the highest, and its formula is:

In formula: N _r,m(t) the electric automobile demand of m commission merchant period t during for consideration scheduling nargin; for numbering i ₁, i ₂..., i _qelectric automobile user credibility; i ₁, i ₂..., i _qfor set 1,2 ..., nv (t) } in the combination of q element, nv (t) contains the quantity of back scheduling electric automobile and q=N for period t _r,m(t)-N _k,m(t).