CN104361416A - Power-grid double-layer optimized dispatching method considering large-scale electric automobile access - Google Patents

Abstract

The invention belongs to the field of electric power system operation and dispatch and relates to a power-grid double-layer optimized dispatching method considering large-scale electric automobile access. Charging and discharging strategies of electric automobiles are researched from two aspects of a power transmission network and a power distribution network, the optimal charging time of the electric automobiles is determined through the power transmission network, further the optimal charging positions of the electric automobiles in the power distribution network are guided, and the load of the power distribution network is centralized on a certain node of the power transmission network, as shown in figure 1. In the power-grid double-layer optimized dispatching method, the coordination effect of wind power, basic load, a thermal generator set and charging and discharging of the electric automobiles is further considered comprehensively, and effective suggestions are proposed for the charging and discharging time and positions of the electric automobiles by means of a model.

Description

A kind ofly consider the electrical network dual-layer optimization dispatching method that extensive electric automobile accesses

Technical field

The invention belongs to Operation of Electric Systems and scheduling field, relate to a kind of electrical network dual-layer optimization dispatching method that extensive electric automobile accesses of considering.

Background technology

At present, coal is still very high in primary energy consumption proportion, although coal resources rich reserves, the greenhouse gases caused in its productive consumption process and pollutant excess emissions, increase day by day to the pressure of environmental protection.In addition, explored oil, natural gas reserves wretched insufficiency.Therefore, build stable, economic, clean, safe energy supply system and face a series of significant challenge.

Electric automobile (Electric Vehicle, EV) is as the energy-efficient, environment-friendly automobiles of a new generation, and be use electric power to replace traditional oil to drive automobile, can alleviate energy-intensive trend, be the inexorable trend of automobile industry development.And electric automobile has the dual identity of controllable burden and power supply, during charging, it can be considered the load of electrical network, can be considered the power supply of electrical network during electric discharge, and electric automobile is that the economical operation improving electrical network provides opportunity.But if large-scale electric automobile accesses electrical network simultaneously, its unordered discharge and recharge behavior brings powerful impact by electrical network, may make electrical network running overload, affects security and the economy of electrical network.Therefore, the electric automobile of access electrical network is included in the Scheduling System of electrical network, discharge and recharge strategy unified by research electric automobile, and this has important theory value and practical significance for the economy improving operation of power networks while meeting charging electric vehicle demand.

At present, scholar tackle electric automobile access electrical network carried out large quantity research.But yet there are no report and the related article of studying electric automobile discharge and recharge strategy from power transmission network and power distribution network double level.About the research of this respect is also in blank.

Summary of the invention

The present invention mainly solves the technical matters existing for prior art; Provide a kind of discharge and recharge strategy from power transmission network and power distribution network two hierarchical research electric automobiles, draw the electric automobile optimum duration of charging from power transmission network, and then instruct optimum a kind of of charge position of electric automobile in power distribution network to consider the electrical network dual-layer optimization dispatching method that extensive electric automobile accesses.

The present invention also has an object to be solve the technical matters existing for prior art; Provide a kind of coordinative role having considered wind-powered electricity generation, Ji He and thermal power generation unit and electric automobile discharge and recharge, and with this model, effective a kind of of suggestion is proposed to the time of electric automobile discharge and recharge and position and consider the electrical network dual-layer optimization dispatching method that extensive electric automobile accesses.

Above-mentioned technical matters of the present invention is mainly solved by following technical proposals:

A kind ofly consider the electrical network dual-layer optimization dispatching method that extensive electric automobile accesses, it is characterized in that, based on the foundation of Optimized model, comprise: the upper strata Optimized model based on Unit Combination model and the lower floor's Optimized model based on optimal load flow model, described lower floor's Optimized model based on optimal load flow model sets up based on the result of the upper strata Optimized model of Unit Combination model, specifically:

Model one: based on the upper strata Optimized model of Unit Combination model, be defined as power transmission network Optimized model, concrete grammar is: with comprise coal-fired cost, the PM2.5 discharge capacity of thermal power generation unit and start-up and shut-down costs, user's charging cost, wind cutting cost six aspects social cost for minimum target; With system charge balance, retain regulation margin capacity, the exerting oneself of generator, the climbing rate of unit, the minimum operation of unit and unused time, the quantity of electric automobile and discharge and recharge time, wind cutting electricity for constraint condition, obtain the power transmission network Optimized model based on Unit Combination model, the result that this Optimized model obtains is the electric automobile discharge and recharge quantity of t under scene s;

Model two: based on lower floor's Optimized model of optimal load flow model, be defined as the foundation of distribution network Optimized model, optimum results based on the acquisition from power transmission network: the electric automobile discharge and recharge quantity optimization result of t under scene s, obtain the optimal location of electric automobile discharge and recharge in power distribution network, concrete grammar is for optimal objective with the minimal energy loss of power distribution network; With electric automobile quantity in meritorious and reactive balance, node voltage size, power distribution network safety condition, node electric automobile battery charger quantity, region and total electric automobile quantity for constraint condition draws the Optimized model of power distribution network;

The electrical network dual-layer optimization dispatching method of this consideration extensive electric automobile access, based on described two Optimized models, comprises the following steps:

Step 1, the optimization of power transmission network, finds the electric automobile optimum discharge and recharge time; Based on from different electricity price curves and electric automobile permeability, consider that user's electric automobile use habit and user accept situation, the level and smooth situation of load curve to discharge and recharge price, and be minimum target with social cost; Contrast draws the price curve guiding user to realize the optimum duration of charging, instructs electric automobile optimum discharge and recharge position in power distribution network further;

Step 2: the optimization of distribution network, finds the optimum discharge and recharge position of electric automobile; Based on the actual service condition of electric automobile user, in conjunction with the optimum results of transmission line of electricity, electric automobile charge-discharge region is divided into residential quarter, shopping centre and Office Area, and arranges mobility status in electric automobile 24 hours in proportion according to actual conditions; Contrast the electric automobile distribution mobility status without electric automobile and different proportion, minimum for target with via net loss, draw the optimum discharge and recharge position of electric automobile.

The present invention is from the discharge and recharge strategy of power transmission network and power distribution network two hierarchical research electric automobiles, the electric automobile optimum duration of charging is drawn from power transmission network, and then instruct the optimum charge position of electric automobile in power distribution network, and the load of distribution network all concentrates on a certain node on power transmission network as shown in Figure 1.The present invention has also considered the coordinative role of wind-powered electricity generation, Ji He and thermal power generation unit and electric automobile discharge and recharge, and proposes effective suggestion with this model to the time of electric automobile discharge and recharge and position.The method emulates power transmission network with the transmission system of 10 monoblock holding 110MW wind energy turbine set, emulates power distribution network with the distributed power grid of IEEE33 node, because all scenes do not have interrelated, so the present invention only studies a kind of scene.

A kind ofly consider the electrical network dual-layer optimization dispatching method that extensive electric automobile accesses above-mentioned, it is characterized in that, described power transmission network Optimized model based on following objective function:

$\min \underset{t=1}{\overset{T}{\mathrm{\Σ}}}\underset{i=1}{\overset{N_g}{\mathrm{\Σ}}}{S}_{i,t}{u}_{i,t}(1-u_{i,t-1})+E\left\{\underset{t=1}{\overset{T}{\mathrm{\Σ}}}\right[\underset{i=1}{\overset{N_g}{\mathrm{\Σ}}}(F_i\left(P_{i,t}^s\right)+C_e{E}_i\left(P_{i,t}^s\right))u_{i,t}+U_t^s+\underset{w=1}{\overset{W}{\mathrm{\Σ}}}{C}_w\mathrm{\Δ}{P}_{w,t}^s\left]\right\}$

Wherein, T is time sum, N _gbe the sum of firepower unit, W is the sum of wind energy turbine set; E{} represents the mathematical expectation under all scenes; u _i,tbe the running status of unit i in t, 1 represents operation, and 0 represents shutdown; C _eit is the punishment cost of PM2.5 burst size; C _wcut wind power cost, the wind cutting electricity of t period that is wind energy turbine set under scene s, the probability of scene is Pr ^s.

A kind ofly consider the electrical network dual-layer optimization dispatching method that extensive electric automobile accesses above-mentioned, in described power transmission network Optimized model, minimum target is based on following formula and definition:

Minimum target one: coal-fired cost, in electric system, the coal-fired cost of fired power generating unit is the quadratic function of unit output;

$F_i\left(P_{i,t}^s\right)=a_i+b_i{P}_{i,t}^s+c_i{P}_{i,t}^{s2}$

Wherein, a _i, b _iand c _iit is the positive coal-fired coefficient of unit i; unit i the exerting oneself of t under scene s;

Minimum target two: PM2.5 discharge capacity, according to electrical energy production need for environment, exhaust emissions also should be taken into account; China affects very serious by haze, thermal power generation is the main source of PM2.5; As an optimization aim, the discharge capacity of fired power generating unit PM2.5 can be expressed as the quadratic function of unit output;

$E_i\left(P_{i,t}^s\right)=\mathrm{Aar}\·\mathrm{\ω}\·(1-\mathrm{\η}/100)\·({\mathrm{\α}}_i+{\mathrm{\β}}_i{P}_{i,t}^s+{\mathrm{\γ}}_i{P}_{i,t}^{s2})/10000$

Wherein, Aar is dust average weight percent (%) in coal, and default value is 20; ω is the conversion coefficient (%) that flue dust is converted into PM2.5, and default value is 5.1; η is that discharge reduces coefficient (%), and default value is 99; The discharge capacity of a unit is proportional to coal consumption amount, α _i, β _iand γ _iit is the consumption coal measures number of unit;

Minimum target three: start cost, the start cost restarting the thermal power generation unit of shutdown is relevant with the temperature of boiler; In the present invention, the step function of the start-up cost relevant with temperature is relevant to the transit time of warm start with cold start-up;

$S_{i,t}=\left\{\begin{array}{cc}{S}_i^h& T_i^{\mathrm{off}}<X_{i,t}^{\mathrm{off}}\&le;H_i^{\mathrm{off}}\\ S_i^c& X_{i,t}^{\mathrm{off}}>H_i^{\mathrm{off}}\end{array}\right.$

$H_i^{\mathrm{off}}=T_i^{\mathrm{off}}+T_i^c$

Wherein, the warm start cost of unit i, the cold start-up cost of unit i, it is the lasting unused time of unit i at period t; the minimum lasting unused time of unit i, it is the unit i cold start-up time;

Minimum target four: shutdown cost, the shutdown cost of thermal electric generator group is constant, is 0 in modular system intermediate value;

Minimum target five: user's charging cost, user's charging cost is the economic consumption of all electric automobile users, can deduct electric discharge income calculate by charging cost;

$U_t^s={\mathrm{\&rho;}}_{c,t}{N}_{c,t}^s{P}_c\mathrm{\&Delta;t}-{\mathrm{\&rho;}}_{d,t}{N}_{d,t}^s{P}_d\mathrm{\&Delta;t}$

Wherein, ρ _c,tand ρ _d,tthe discharge and recharge electricity price of t respectively; with the electric automobile discharge and recharge quantity of t under scene s respectively; P _cand P _dthe average charge-discharge electric power of electric automobile respectively; Δ t is time span, is one hour in the present invention;

Minimum target six: cut wind power cost, takes into account objective function by the target of cutting wind power cost minimum.

A kind ofly consider the electrical network dual-layer optimization dispatching method that extensive electric automobile accesses above-mentioned, in described power transmission network Optimized model, constraint condition is based on following formula and definition:

Constraint condition one: electric quantity balancing, the subject matter of electric power system dispatching ensures the equilibrium of supply and demand, so must meet the needs of basic load and charging electric vehicle any time from the electricity of the genset of all operations, the discharge capacity of electric automobile and wind energy turbine set;

$\underset{i=1}{\overset{N_g}{\mathrm{\&Sigma;}}}\left(u_{i,t}{P}_{i,t}^s\right)+P_d{N}_{d,t}^s+\underset{w=1}{\overset{W}{\mathrm{\&Sigma;}}}(P_{w,t}^s-\mathrm{\&Delta;}{P}_{w,t}^s)=D_t+P_c{N}_{c,t}^s,\&ForAll;t\&Element;T,\&ForAll;s\&Element;S$

Wherein, D _tthe basic load of t, the prediction wind-force of the t of wind energy turbine set under scene s;

Constraint condition two: spinning reserve, in order to improve the reliability of system, it is necessary for leaving sufficient spinning reserve; $\underset{i=1}{\overset{N_g}{\mathrm{\&Sigma;}}}\left(u_{i,t}{P}_i^{\max }\right)+P_d{N}_{d,t}^s+\underset{w=1}{\overset{W}{\mathrm{\&Sigma;}}}(P_{w,t}^s-\mathrm{\&Delta;}{P}_{w,t}^s)\&GreaterEqual;D_t+P_c{N}_{c,t}^s+R_t,\&ForAll;t\&Element;T,\&ForAll;s\&Element;S$ Wherein, the maximum output of unit i, R _tit is the stand-by equipment of t system;

Constraint condition three: generator output retrains, each unit has oneself units limits, and restriction range is as follows:

$P_i^{\min }{u}_{i,t}\&le;P_{i,t}^s\&le;P_i^{\max }{u}_{i,t},\&ForAll;i\&Element;N_g,\&ForAll;t\&Element;T,\&ForAll;s\&Element;S$

Wherein, it is the minimum load of unit i;

Constraint condition four: climbing rate, the variation range of exerting oneself in each unit adjacent time inter is by the constraint of climbing rate;

$-R_{d,i}\&le;P_{i,t}^s-P_{i,t-1}^s\&le;R_{u,i},\&ForAll;i\&Element;N_g,\&ForAll;t\&Element;T,\&ForAll;s\&Element;S$

Wherein, R _u,iand R _d,ithe upper and lower climbing rate of unit i respectively;

Constraint condition five: minimum start/unused time, no matter whether a unit is in operation, and this unit must keep start or cut-off operation minimum time before change running status, so minimum start/unused time can be expressed as follows:

$(X_{i,t}^{\mathrm{on}}-T_i^{\mathrm{on}})(u_{i,t}-u_{i,t+1})\&GreaterEqual;0,\&ForAll;i\&Element;N_g,\&ForAll;t\&Element;T$

$(X_{i,t}^{\mathrm{off}}-T_i^{\mathrm{off}})(u_{i,t+1}-u_{\mathrm{it}})\&GreaterEqual;0,\&ForAll;i\&Element;N_g,\&ForAll;t\&Element;T$

Wherein, with represent that unit i keeps the duration of operation and off-mode in t respectively; with represent the unit i minimum startup and shutdown time respectively;

Constraint condition six: electric automobile quantity, in each moment, the electric automobile quantity that can be used for discharge and recharge can be calculated by lower surface function;

$N_{c,t}^s\&le;N_{c,t}^{\max },\&ForAll;t\&Element;T,\&ForAll;s\&Element;S$

$N_{d,t}^s\&le;N_{d,t}^{\max },\&ForAll;t\&Element;T,\&ForAll;s\&Element;S$

Wherein, with represent that t can be used for the maximum number of discharge and recharge electric automobile respectively;

Constraint condition seven: discharge and recharge time, in order to provide sufficient electric energy to electric automobile, the duration of charging can not be too short; Leave sufficient electricity to make electric automobile and meet trip needs; All electric automobile discharge and recharge time-constrains are as follows;

$\underset{t=1}{\overset{T}{\mathrm{\&Sigma;}}}{N}_{c,t}^s\mathrm{\&Delta;t}=N_c^{\max }\mathrm{\&Delta;}{t}_c,\&ForAll;s\&Element;S$

$\underset{t=1}{\overset{T}{\mathrm{\&Sigma;}}}{N}_{d,t}^s\mathrm{\&Delta;t}=N_d^{\max }\mathrm{\&Delta;}{t}_d,\&ForAll;s\&Element;S$

Wherein, with representative can be used for the electric automobile total quantity of discharge and recharge respectively; Δ t _cwith Δ t _drepresent the electric automobile average discharge and recharge time respectively;

Constraint condition eight: wind cutting amount retrains, the relation of wind cutting amount and wind-force prediction is expressed as follows;

$0\&le;\mathrm{\&Delta;}{P}_{w,t}^s\&le;P_{w,t}^s,\&ForAll;w\&Element;W,\&ForAll;t\&Element;T,\&ForAll;s\&Element;S$

Wherein, represent prediction wind-force.

A kind ofly consider the electrical network dual-layer optimization dispatching method that extensive electric automobile accesses above-mentioned, described distribution network Optimized model is based on following objective function:

$\min E\left[\underset{t=1}{\overset{T}{\mathrm{\&Sigma;}}}{P}_{\mathrm{Loss},t}^s\right]$

Wherein, E [*] represents the mathematical expectation of all scenes, the all network loss of power distribution network in the t period.

A kind ofly consider the electrical network dual-layer optimization dispatching method that extensive electric automobile accesses above-mentioned, constraint condition is based on following formula and definition:

Constraint condition one: meritorious, reactive balance constraint, each node all must meet meritorious, reactive balance; So:

$P_{\mathrm{G\&alpha;},t}^s+P_d{N}_{\mathrm{d\&alpha;},t}^s-P_{\mathrm{D\&alpha;},t}-P_c{N}_{\mathrm{c\&alpha;},t}^s=0,\&ForAll;\mathrm{\&alpha;}\&Element;K,\&ForAll;t\&Element;T,\&ForAll;s\&Element;S$

$Q_{\mathrm{G\&alpha;},t}^s-Q_{\mathrm{D\&alpha;},t}-Q_{\mathrm{T\&alpha;},t}^s=0,\&ForAll;\mathrm{\&alpha;}\&Element;K,\&ForAll;t\&Element;T,\&ForAll;s\&Element;S$

Wherein, K is all nodes except balance node, with the node alpha active power that t sends under scene s and reactive power respectively; P _{d α, t}and Q _{d α, t}that node alpha t under scene s is gained merit and load or burden without work respectively; with node alpha t electric automobile discharge and recharge quantity under scene s respectively; with be node alpha t transmission meritorious and idle under scene s respectively, they are by following formulae discovery:

$P_{\mathrm{T\&alpha;},t}^s=V_{\mathrm{\&alpha;},t}^s\underset{j\&Element;\mathrm{\&alpha;}}{\mathrm{\&Sigma;}}{V}_{j,t}^s(G_{\mathrm{\&alpha;j}}\cos {\mathrm{\&theta;}}_{\mathrm{\&alpha;j},t}^s+B_{\mathrm{\&alpha;j}}\sin {\mathrm{\&theta;}}_{\mathrm{\&alpha;j},t}^s)$

$Q_{\mathrm{T\&alpha;},t}^s=V_{\mathrm{\&alpha;},t}^s\underset{j\&Element;\mathrm{\&alpha;}}{\mathrm{\&Sigma;}}{V}_{j,t}^s(G_{\mathrm{\&alpha;j}}\sin {\mathrm{\&theta;}}_{\mathrm{\&alpha;j},t}^s-B_{\mathrm{\&alpha;j}}\cos {\mathrm{\&theta;}}_{\mathrm{\&alpha;j},t}^s)$

Wherein, with the voltage of node alpha and j t under scene s respectively; G _{α j}and B _{α j}be admittance matrix be respectively real number and imaginary part; it is the phase differential of node alpha and j t under scene s;

Constraint condition two: node voltage retrain, in order to ensure the quality of power supply and power grid security, node voltage must meet minimum and maximum constraint;

$V_{\mathrm{\&alpha;},\min }\&le;V_{\mathrm{\&alpha;},t}^s\&le;V_{\mathrm{\&alpha;},\max },\&ForAll;\mathrm{\&alpha;}\&Element;K,\&ForAll;t\&Element;T,\&ForAll;s\&Element;S$

Wherein, V _{α, max}and V _{α, min}the top/bottom latitude of node voltage respectively;

Constraint condition three: power system security constraints, in order to ensure the safe operation of electrical network, the transmission capacity of circuit should limit within the specific limits;

$\left|P_{\mathrm{\&alpha;j},t}^s\right|{\&le;P}_{\mathrm{\&alpha;j},\max },\&ForAll;\mathrm{\&alpha;},j\&Element;K,\&ForAll;t\&Element;T,\&ForAll;s\&Element;S$

Wherein, P _{α j, max}it is the maximum transfer capacity of circuit α-j; the transmission electricity of transmission line of electricity α-j t under scene s, can by following formulae discovery:

$\left|P_{\mathrm{\&alpha;j},t}^s\right|=|V_{\mathrm{\&alpha;},t}^s{V}_{j,t}^s(G_{\mathrm{\&alpha;j}}\cos {\mathrm{\&theta;}}_{\mathrm{\&alpha;j},t}^s+B_{\mathrm{\&alpha;j}}\sin {\mathrm{\&theta;}}_{\mathrm{\&alpha;j},t}^s)-{V_{\mathrm{\&alpha;},t}^s}^2{G}_{\mathrm{\&alpha;j}}|$

Constraint condition four: the number constraint of node charging pile; Each node has the charging pile of some, so the electric automobile maximum quantity that can be connected to electrical network retrains by the part that cooks noodle:

$0\&le;N_{\mathrm{c\&alpha;},t}^s,N_{\mathrm{d\&alpha;},t}^s\&le;N_{\mathrm{\&alpha;},\max },\&ForAll;\mathrm{\&alpha;}\&Element;K,\&ForAll;t\&Element;T,\&ForAll;s\&Element;S$

Wherein, N _{α, max}the quantity of node alpha charging pile;

Constraint condition five: region electric automobile number constraint, due to the mobility of electric automobile, in region, the quantity of electric automobile is change; The electric automobile quantity that can be used for discharge and recharge in certain region can be expressed as follows:

$\underset{\mathrm{\&alpha;}\&Element;i}{\mathrm{\&Sigma;}}{N}_{\mathrm{c\&alpha;},t}^s=N_{\mathrm{ci},t}^s,i=\mathrm{resid},\mathrm{comme},\mathrm{office},\&ForAll;t\&Element;T,\&ForAll;s\&Element;S$

$\underset{\mathrm{\&alpha;}\&Element;i}{\mathrm{\&Sigma;}}{N}_{\mathrm{d\&alpha;},t}^s=N_{\mathrm{di},t}^s,i=\mathrm{resid},\mathrm{comme},\mathrm{office},\&ForAll;t\&Element;T,\&ForAll;s\&Element;S$

Wherein, with represent that i t under scene s in region can be used for the quantity of the electric automobile of discharge and recharge respectively;

Constraint condition six: electric automobile total amount retrains, and the sum that can be used for the electric automobile of discharge and recharge in region should meet upper strata operation plan;

$\underset{i\&Element;I}{\mathrm{\&Sigma;}}{N}_{\mathrm{ci},t}^s=N_{c,t}^s,\&ForAll;t\&Element;T,\&ForAll;s\&Element;S$

$\underset{i\&Element;I}{\mathrm{\&Sigma;}}{N}_{\mathrm{di},t}^s=N_{d,t}^s,\&ForAll;t\&Element;T,\&ForAll;s\&Element;S$

Wherein, I represents all regions; with represent the quantity of t discharge and recharge electric automobile under scene s respectively, this is determined the operation plan of power distribution network by power transmission network.

Therefore, tool of the present invention has the following advantages: 1. reasonable in design, and structure is simple, and noise is less and completely practical; 2. output zero point of whole proving installation can not variation with temperature and changing, and reduces test error thus to a great extent; 3. the output signal of whole device can not be made to produce non-linear.

Accompanying drawing explanation

Fig. 1 is the structural representation of power transmission network and power distribution network in bi-level optimal model involved in the present invention.

Fig. 2 a is electric automobile discharge and recharge price curve (constant price) involved in the embodiment of the present invention.

Fig. 2 b is electric automobile discharge and recharge price curve (timesharing charge) involved in the embodiment of the present invention.

Fig. 2 c is electric automobile discharge and recharge price curve (time-shared charge that price is different) involved in the embodiment of the present invention.

Fig. 3 a is the Unit Combination result of case 1 in the scene 1 involved by the embodiment of the present invention.

Fig. 3 b is the Unit Combination result of case 2 in the scene 1 involved by the embodiment of the present invention.

Fig. 3 c is the Unit Combination result of case 3 in the scene 1 involved by the embodiment of the present invention.

Fig. 3 d is the Unit Combination result of case 4 in the scene 1 involved by the embodiment of the present invention.

Fig. 3 e is the Unit Combination result of case 5 in the scene 1 involved by the embodiment of the present invention.

Fig. 3 f is the Unit Combination result of case 6 in the scene 1 involved by the embodiment of the present invention.

Fig. 4 a is the electric automobile discharge and recharge plan of case 2 in the scene 1 involved by the embodiment of the present invention.

Fig. 4 b is the electric automobile discharge and recharge plan of case 3 in the scene 1 involved by the embodiment of the present invention.

Fig. 4 c is the electric automobile discharge and recharge plan of case 4 in the scene 1 involved by the embodiment of the present invention.

Fig. 4 d is the electric automobile discharge and recharge plan of case 5 in the scene 1 involved by the embodiment of the present invention.

Fig. 4 e is the electric automobile discharge and recharge plan of case 6 in the scene 1 involved by the embodiment of the present invention.

Fig. 5 is electric automobile flowing information in a network involved in the embodiment of the present invention.

Fig. 6 is basic load curve involved in the embodiment of the present invention.

Fig. 7 a is charging electric vehicle program results in the case 8 involved by the embodiment of the present invention.

Fig. 7 b is electric automobile electric discharge program results in the case 8 involved by the embodiment of the present invention.

Fig. 8 a is charging electric vehicle program results in the case 9 involved by the embodiment of the present invention.

Fig. 8 b is electric automobile electric discharge program results in the case 9 involved by the embodiment of the present invention.

Fig. 9 is balance node load curve involved in the embodiment of the present invention.

Figure 10 is via net loss curve in the power distribution network involved by the embodiment of the present invention.

Embodiment

Below by embodiment, and by reference to the accompanying drawings, technical scheme of the present invention is described in further detail.

One, concrete grammar of the present invention is first introduced:

The present invention is based on the foundation of two Optimized models, comprise: the upper strata Optimized model based on Unit Combination model and the lower floor's Optimized model based on optimal load flow model, described lower floor's Optimized model based on optimal load flow model sets up based on the result of the upper strata Optimized model based on Unit Combination model, is specifically described as follows:

(1) based on the upper strata optimisation strategy of Unit Combination (UC) model

From the angle of transmission system, upper strata optimization coordinate firepower genset and electric automobile are the containment in order to the better economic benefit and wind-powered electricity generation obtaining operation of power networks.Consider randomness and the intermittence of wind-powered electricity generation, propose and a kind ofly coordinate the relation between genset, electric automobile and wind-power electricity generation, basic load based on scene UC model a few days ago.

A. objective function.

In order to optimize wind-powered electricity generation, electric automobile and thermal power generation unit, the object of upper layer functions makes the social cost comprising six aspects minimum, and this can describe in detail below.

1. coal-fired cost.

In electric system, the coal-fired cost of fired power generating unit is the quadratic function of unit output.

$F_i\left(P_{i,t}^s\right)=a_i+b_i{P}_{i,t}^s+c_i{P}_{i,t}^{s2}---\left(1\right)$

Here a _i, b _iand c _iit is the positive coal-fired coefficient of unit i. unit i the exerting oneself of t under scene s.

2.PM2.5 discharge capacity.

According to electrical energy production need for environment, exhaust emissions also should be taken into account.China affects very serious by haze, thermal power generation is the main source of PM2.5.As an optimization aim, the discharge capacity of fired power generating unit PM2.5 can be expressed as the quadratic function of unit output.

$E_i\left(P_{i,t}^s\right)=\mathrm{Aar}\&CenterDot;\mathrm{\&omega;}\&CenterDot;(1-\mathrm{\&eta;}/100)\&CenterDot;({\mathrm{\&alpha;}}_i+{\mathrm{\&beta;}}_i{P}_{i,t}^s+{\mathrm{\&gamma;}}_i{P}_{i,t}^{s2})/10000---\left(2\right)$

Here Aar is dust average weight percent (%) in coal, and default value is 20.ω is the conversion coefficient (%) that flue dust is converted into PM2.5, and default value is 5.1.η is that discharge reduces coefficient (%), and default value is 99.The discharge capacity of a unit is proportional to coal consumption amount, α _i, β _iand γ _iit is the consumption coal measures number of unit.

3. start cost.

The start cost restarting the thermal power generation unit of shutdown is relevant with the temperature of boiler.In the present invention, the step function of the start-up cost relevant with temperature is relevant to the transit time of warm start with cold start-up.

$S_{i,t}=\left\{\begin{array}{cc}{S}_i^h& T_i^{\mathrm{off}}<X_{i,t}^{\mathrm{off}}\&le;H_i^{\mathrm{off}}\\ S_i^c& X_{i,t}^{\mathrm{off}}>H_i^{\mathrm{off}}\end{array}\right.---\left(3\right)$

$H_i^{\mathrm{off}}=T_i^{\mathrm{off}}+T_i^c---\left(4\right)$

Here, the warm start cost of unit i, the cold start-up cost of unit i, it is the lasting unused time of unit i at period t. the minimum lasting unused time of unit i, it is the unit i cold start-up time.

4. shut down cost.

The shutdown cost of thermal electric generator group is constant, is 0. in modular system intermediate value

5. user's charging cost.

User's charging cost is the economic consumption of all electric automobile users, can deduct electric discharge income calculate by charging cost.

$U_t^s={\mathrm{\&rho;}}_{c,t}{N}_{c,t}^s{P}_c\mathrm{\&Delta;t}-{\mathrm{\&rho;}}_{d,t}{N}_{d,t}^s{P}_d\mathrm{\&Delta;t}---\left(5\right)$

Here, ρ _c,tand ρ _d,tthe discharge and recharge electricity price of t respectively; with the electric automobile discharge and recharge quantity of t under scene s respectively; P _cand P _dthe average charge-discharge electric power of electric automobile respectively; Δ t is time span, is one hour in the present invention.

6. cut wind power cost.

In order to improve the utilization of regenerative resource, cutting wind power cost should take into account objective function.

Although exerting oneself of unit can adjust to some extent according to different scenes, the generation schedule of general unit determined by load prediction a few days ago.So our optimization aim is that start cost and electric system mathematical expectation sum of operating cost under different scene are minimum.Therefore, consider thermal power generation unit, electric automobile user, wind-powered electricity generation and electrical network, the objective function that upper strata is optimized can be expressed as follows.

$\min \underset{t=1}{\overset{T}{\mathrm{\&Sigma;}}}\underset{i=1}{\overset{N_g}{\mathrm{\&Sigma;}}}{S}_{i,t}{u}_{i,t}(1-u_{i,t-1})+E\left\{\underset{t=1}{\overset{T}{\mathrm{\&Sigma;}}}\right[\underset{i=1}{\overset{N_g}{\mathrm{\&Sigma;}}}(F_i\left(P_{i,t}^s\right)+C_e{E}_i\left(P_{i,t}^s\right))u_{i,t}+U_t^s+\underset{w=1}{\overset{W}{\mathrm{\&Sigma;}}}{C}_w\mathrm{\&Delta;}{P}_{w,t}^s\left]\right\}---\left(6\right)$

Here, T is time sum, N _gbe the sum of firepower unit, W is the sum of wind energy turbine set.E{} represents the mathematical expectation under all scenes.U _i,tbe the running status of unit i in t, 1 represents operation, and 0 represents shutdown.C _eit is the punishment cost of PM2.5 burst size.C _wcut wind power cost, the wind cutting electricity of t period that is wind energy turbine set under scene s, the probability of scene is Pr ^s

B. constraint condition.

1. electric quantity balancing.

The subject matter of electric power system dispatching ensures the equilibrium of supply and demand.So the needs of basic load and charging electric vehicle any time must be met from the electricity of the genset of all operations, the discharge capacity of electric automobile and wind energy turbine set.

$\underset{i=1}{\overset{N_g}{\mathrm{\&Sigma;}}}\left(u_{i,t}{P}_{i,t}^s\right)+P_d{N}_{d,t}^s+\underset{w=1}{\overset{W}{\mathrm{\&Sigma;}}}(P_{w,t}^s-\mathrm{\&Delta;}{P}_{w,t}^s)=D_t+P_c{N}_{c,t}^s,\&ForAll;t\&Element;T,\&ForAll;s\&Element;S---\left(7\right)$

Here, D _tthe basic load of t, the prediction wind-force of the t of wind energy turbine set under scene s.

2. spinning reserve.

In order to improve the reliability of system, it is necessary for leaving sufficient spinning reserve.

$\underset{i=1}{\overset{N_g}{\mathrm{\&Sigma;}}}\left(u_{i,t}{P}_i^{\max }\right)+P_d{N}_{d,t}^s+\underset{w=1}{\overset{W}{\mathrm{\&Sigma;}}}(P_{w,t}^s-\mathrm{\&Delta;}{P}_{w,t}^s)\&GreaterEqual;D_t+P_c{N}_{c,t}^s+R_t,\&ForAll;t\&Element;T,\&ForAll;s\&Element;S---\left(8\right)$

Here, the maximum output of unit i, R _tit is the stand-by equipment of t system.

3. generator output constraint.

Each unit has oneself units limits, and restriction range is as follows:

$P_i^{\min }{u}_{i,t}\&le;P_{i,t}^s\&le;P_i^{\max }{u}_{i,t},\&ForAll;i\&Element;N_g,\&ForAll;t\&Element;T,\&ForAll;s\&Element;S---\left(9\right)$

Here, it is the minimum load of unit i.

4. climbing rate.

The variation range of exerting oneself in each unit adjacent time inter is by the constraint of climbing rate.

$-R_{d,i}\&le;P_{i,t}^s-P_{i,t-1}^s\&le;R_{u,i},\&ForAll;i\&Element;N_g,\&ForAll;t\&Element;T,\&ForAll;s\&Element;S---\left(10\right)$

Here, R _u,iand R _d,ithe upper and lower climbing rate of unit i respectively.

5. minimum start/unused time.

No matter whether a unit is in operation, and this unit must keep start or cut-off operation minimum time before change running status, so minimum start/unused time can be expressed as follows:

$(X_{i,t}^{\mathrm{on}}-T_i^{\mathrm{on}})(u_{i,t}-u_{i,t+1})\&GreaterEqual;0,\&ForAll;i\&Element;N_g,\&ForAll;t\&Element;T---\left(11\right)$

$(X_{i,t}^{\mathrm{off}}-T_i^{\mathrm{off}})(u_{i,t+1}-u_{\mathrm{it}})\&GreaterEqual;0,\&ForAll;i\&Element;N_g,\&ForAll;t\&Element;T---\left(12\right)$

Here, with represent that unit i keeps the duration of operation and off-mode in t respectively. with represent the unit i minimum startup and shutdown time respectively.

6. electric automobile quantity.

In each moment, the electric automobile quantity that can be used for discharge and recharge can be calculated by lower surface function.

$N_{c,t}^s\&le;N_{c,t}^{\max },\&ForAll;t\&Element;T,\&ForAll;s\&Element;S---\left(13\right)$

$N_{d,t}^s\&le;N_{d,t}^{\max },\&ForAll;t\&Element;T,\&ForAll;s\&Element;S---\left(14\right)$

Here, with represent that t can be used for the maximum number of discharge and recharge electric automobile respectively.

7. the discharge and recharge time.

In order to provide sufficient electric energy to electric automobile, the duration of charging can not be too short.Leave sufficient electricity to make electric automobile and meet trip needs.All electric automobile discharge and recharge time-constrains are as follows.

$\underset{t=1}{\overset{T}{\mathrm{\&Sigma;}}}{N}_{c,t}^s\mathrm{\&Delta;t}=N_c^{\max }\mathrm{\&Delta;}{t}_c,\&ForAll;s\&Element;S---\left(15\right)$

$\underset{t=1}{\overset{T}{\mathrm{\&Sigma;}}}{N}_{d,t}^s\mathrm{\&Delta;t}=N_d^{\max }\mathrm{\&Delta;}{t}_d,\&ForAll;s\&Element;S---\left(16\right)$

Here, with representative can be used for the electric automobile total quantity of discharge and recharge respectively.Δ t _cwith Δ t _drepresent the electric automobile average discharge and recharge time respectively.

8. wind cutting amount constraint.

The relation of wind cutting amount and wind-force prediction can be expressed as follows.

$0\&le;\mathrm{\&Delta;}{P}_{w,t}^s\&le;P_{w,t}^s,\&ForAll;w\&Element;W,\&ForAll;t\&Element;T,\&ForAll;s\&Element;S---\left(17\right)$

Here, represent prediction wind-force.

(2) based on lower floor's optimisation strategy of optimal load flow model (OPF).

It is supplementing upper strata optimization that lower floor optimizes.The balance node of distribution system is in the low-pressure side of step-down transformer, and high voltage side of transformer is the node of power transmission network.

Optimize based on the upper strata from power transmission network with optimum results, the target that lower floor optimizes is the optimal location of planning electric automobile discharge and recharge in power distribution network.The lower floor's Optimized model that the present invention proposes based on OPF model makes the electric energy loss of power distribution network minimum.

Consider the mobility of electric automobile user.A city can be divided into three typical functional areas: residential block, shopping centre and Office Area.By day, electric automobile great majority are docked in workspace.At night, electric automobile great majority are docked in family.

A. objective function.

The operation of distribution system is more prone to the energy loss reducing power transmission network, reduces the cost that power distribution network runs; Therefore reducing energy loss is target.All scenes are all the same concerning upper strata.Objective function can be defined as follows.

$\min E\left[\underset{t=1}{\overset{T}{\mathrm{\&Sigma;}}}{P}_{\mathrm{Loss},t}^s\right]$

Here, E [*] represents the mathematical expectation of all scenes, the all network loss of power distribution network in the t period.

B. constraint condition.

1. meritorious, reactive balance constraint.

Each node all must meet meritorious, reactive balance.So:

$P_{\mathrm{G\&alpha;},t}^s+P_d{N}_{\mathrm{d\&alpha;},t}^s-P_{\mathrm{D\&alpha;},t}-P_c{N}_{\mathrm{c\&alpha;},t}^s-P_{\mathrm{T\&alpha;},t}^s=0,\&ForAll;\mathrm{\&alpha;}\&Element;K,\&ForAll;t\&Element;T,\&ForAll;s\&Element;S---\left(18\right)$

$Q_{\mathrm{G\&alpha;},t}^s-Q_{\mathrm{D\&alpha;},t}-Q_{\mathrm{T\&alpha;},t}^s=0,\&ForAll;\mathrm{\&alpha;}\&Element;K,\&ForAll;t\&Element;T,\&ForAll;s\&Element;S---\left(19\right)$

Here, K is all nodes except balance node, with the node alpha active power that t sends under scene s and reactive power respectively.P _{d α, t}and Q _{d α, t}that node alpha t under scene s is gained merit and load or burden without work respectively. with node alpha t electric automobile discharge and recharge quantity under scene s respectively. with be node alpha t transmission meritorious and idle under scene s respectively, they can by following formulae discovery:

$P_{\mathrm{T\&alpha;},t}^s=V_{\mathrm{\&alpha;},t}^s\underset{j\&Element;\mathrm{\&alpha;}}{\mathrm{\&Sigma;}}{V}_{j,t}^s(G_{\mathrm{\&alpha;j}}\cos {\mathrm{\&theta;}}_{\mathrm{\&alpha;j},t}^s+B_{\mathrm{\&alpha;j}}\sin {\mathrm{\&theta;}}_{\mathrm{\&alpha;j},t}^s)---\left(20\right)$

$Q_{\mathrm{T\&alpha;},t}^s=V_{\mathrm{\&alpha;},t}^s\underset{j\&Element;\mathrm{\&alpha;}}{\mathrm{\&Sigma;}}{V}_{j,t}^s(G_{\mathrm{\&alpha;j}}\sin {\mathrm{\&theta;}}_{\mathrm{\&alpha;j},t}^s-B_{\mathrm{\&alpha;j}}\cos {\mathrm{\&theta;}}_{\mathrm{\&alpha;j},t}^s)---\left(21\right)$

Here, with the voltage of node alpha and j t under scene s respectively; G _{α j}and B _{α j}be admittance matrix be respectively real number and imaginary part; it is the phase differential of node alpha and j t under scene s.

2. node voltage constraint.

In order to ensure the quality of power supply and power grid security, node voltage must meet minimum and maximum constraint.

$V_{\mathrm{\&alpha;},\min }\&le;V_{\mathrm{\&alpha;},t}^s\&le;V_{\mathrm{\&alpha;},\max },\&ForAll;\mathrm{\&alpha;}\&Element;K,\&ForAll;t\&Element;T,\&ForAll;s\&Element;S---\left(22\right)$

Here, V _{α, max}and V _{α, min}the top/bottom latitude of node voltage respectively.

3. power system security constraints.

In order to ensure the safe operation of electrical network, the transmission capacity of circuit should limit within the specific limits.

$\left|P_{\mathrm{\&alpha;j},t}^s\right|{\&le;P}_{\mathrm{\&alpha;j},\max },\&ForAll;\mathrm{\&alpha;},j\&Element;K,\&ForAll;t\&Element;T,\&ForAll;s\&Element;S---\left(23\right)$

Here, P _{α j, max}it is the maximum transfer capacity of circuit α-j; the transmission electricity of transmission line of electricity α-j t under scene s, can by following formulae discovery:

$\left|P_{\mathrm{\&alpha;j},t}^s\right|=|V_{\mathrm{\&alpha;},t}^s{V}_{j,t}^s(G_{\mathrm{\&alpha;j}}\cos {\mathrm{\&theta;}}_{\mathrm{\&alpha;j},t}^s+B_{\mathrm{\&alpha;j}}\sin {\mathrm{\&theta;}}_{\mathrm{\&alpha;j},t}^s)-{V_{\mathrm{\&alpha;},t}^s}^2{G}_{\mathrm{\&alpha;j}}|---\left(24\right)$

4. the number constraint of node charging pile.

Each node has the charging pile of some, so the electric automobile maximum quantity that can be connected to electrical network retrains by the part that cooks noodle:

$0\&le;N_{\mathrm{c\&alpha;},t}^s,N_{\mathrm{d\&alpha;},t}^s\&le;N_{\mathrm{\&alpha;},\max },\&ForAll;\mathrm{\&alpha;}\&Element;K,\&ForAll;t\&Element;T,\&ForAll;s\&Element;S---\left(25\right)$

Here, N _{α, max}the quantity of node alpha charging pile.

5. region electric automobile number constraint.

Due to the mobility of electric automobile, in region, the quantity of electric automobile is change.The electric automobile quantity that can be used for discharge and recharge in certain region can be expressed as follows:

$\underset{\mathrm{\&alpha;}\&Element;i}{\mathrm{\&Sigma;}}{N}_{\mathrm{c\&alpha;},t}^s=N_{\mathrm{ci},t}^s,i=\mathrm{resid},\mathrm{comme},\mathrm{office},\&ForAll;t\&Element;T,\&ForAll;s\&Element;S---\left(27\right)$

$\underset{\mathrm{\&alpha;}\&Element;i}{\mathrm{\&Sigma;}}{N}_{\mathrm{d\&alpha;},t}^s=N_{\mathrm{di},t}^s,i=\mathrm{resid},\mathrm{comme},\mathrm{office},\&ForAll;t\&Element;T,\&ForAll;s\&Element;S---\left(28\right)$

Here, with represent that i t under scene s in region can be used for the quantity of the electric automobile of discharge and recharge respectively.

6. electric automobile total amount constraint.

The sum that can be used for the electric automobile of discharge and recharge in region should meet upper strata operation plan.

$\underset{i\&Element;I}{\mathrm{\&Sigma;}}{N}_{\mathrm{ci},t}^s=N_{c,t}^s,\&ForAll;t\&Element;T,\&ForAll;s\&Element;S---\left(29\right)$

$\underset{i\&Element;I}{\mathrm{\&Sigma;}}{N}_{\mathrm{di},t}^s=N_{d,t}^s,\&ForAll;t\&Element;T,\&ForAll;s\&Element;S---\left(30\right)$

Here, I represents all regions; with represent the quantity of t discharge and recharge electric automobile under scene s respectively, this is determined the operation plan of power distribution network by power transmission network.

Two, be the concrete case adopting method of the present invention to implement below:

This part, by with the system model comprising power transmission network and power distribution network so that the validity that dual-layer optimization is planned electric automobile discharge and recharge planning strategy to be described.To comprise 10 unit transmission systems of the wind energy turbine set of a 110MW to emulate power transmission network, power distribution network is emulated with IEEE33 node power distribution network, node 0 in IEEE33 node system is balance node, this node is the low-pressure side of step-down transformer, and the high-pressure side of transformer is the node of 10 monoblock power transmission networks.The load of distribution network concentrates on a certain node on power transmission network.

Transmission system emulates

The burden requirement of 10 monoblock and element characteristics reference literature [28].The Ramp Rate list of references [29] of monoblock.Suppose that unit start climbing rate and shutdown climbing rate equal the minimum load of monoblock.The startup and shutdown time is all 1h [30].The coal consumption coefficient of unit can be obtained by document [31].All scenes of wind-powered electricity generation can be obtained by document [32].Wind power output equals total installed capacity and is multiplied by scale-up factor 0.2.Spinning reserve capacity hypothesis is 10% of burden requirement, and total planning time is 24h.In power transmission network overlay area, the total quantity of electric automobile is 150000, supposes that all electric automobiles can participate in discharge and recharge.The average charge time of electric automobile and discharge time are 6h and 3h respectively.Electric automobile average charge power is 1.8W, and discharge and recharge frequency is 1 times/day.The present invention's electric automobile maximum quantity that hypothesis not can be used for discharge and recharge is in the same time constant.Consider some electric automobiles on the way, some electric automobiles are because worrying that battery life or SOC are unwilling to discharge to electrical network. with be set as 95% and 40% of electric automobile sum respectively.The punishment cost C of PM2.5 _eit is 3000 beautiful yuan/ton.Wind cutting punishment cost C _w100 dollars/MWh.

In order to analyze the impact that different electricity price curve and electric automobile permeability are optimized upper strata, in upper strata is optimized, consider six kinds of situations.The electricity price curve of discharge and recharge as shown in Figure 2.

Case 1: do not consider electric automobile in optimizing process.

Case 2: have 150000 amount electric automobiles in system, the electricity price of discharge and recharge is identical and be constant in one day, and discharge and recharge price curve is as shown in Fig. 2 (a).

Case 3: have 150000 amount electric automobiles in system, the identical but change with load in a day of the electricity price of discharge and recharge can be fluctuated to some extent, and discharge and recharge price curve is as shown in Fig. 2 (b).

Case 4: have 150000 amount electric automobiles in system, charging price is identical with case 3, and the cost ratio that discharges within heavy load time charging price is high, so more attractive to electric automobile electric discharge.Discharge and recharge price curve is as figure Fig. 2 (c).

Case 5: have 100000 electric automobiles in system, price curve is with case 4.

Case 6: have 50000 electric automobiles in system, price curve is with case 4.

Under six kinds of cases, the simulation result of objective function is as shown in table 1; As shown in Figure 3, electric automobile discharge and recharge plan as shown in Figure 4 for the simulation result of Unit Combination.

Through comparative analysis, consider social cost, the price curve of Unit Combination and the known case 4 of user's acceptance problem more easily realizes discharge and recharge plan, has more validity and practicality.Following table is the simulation result of objective function

B. power distribution network emulation

It is for IEEE33 Node power distribution system that lower floor optimizes, as Fig. 5.Node 0 is balance node, is the low voltage side of step-down transformer, and high-pressure side is the node of the power transmission network of upper surface analysis.In a power distribution system, rated capacity is 100MVA, and rated voltage is 12.66KV.The peak load of line parameter circuit value and node can refer to document [33,34].Basic load curve coefficients as shown in Figure 6.Identical with transmission system, in power distribution network electric automobile total quantity be proportional to the total load of power distribution network and power transmission network ratio, so electric automobile total quantity is 400 in power distribution network.Each network node can hold 50 electric automobiles.Electric automobile has 70% in residential block, and 20% in shopping centre, and 10% in Office Area.On daytime, most electric automobile is docked in workspace; In evening, most electric automobile berths at home.As Fig. 5 describes the impact of mobility on electrical network of electric automobile.The present invention only considers that electric automobile bulk migration characteristic and per moment can be used for the quantity of the electric automobile of discharge and recharge, and ignores mobility and the SOC of electric automobile.Because each scene does not have interrelated, for reducing calculated amount, only consider scene 1, probability is set to 1.

This part studies three cases.

Case 7: Design case based 1, does not consider electric automobile.

Case 8: Design case based 4, trizonal electric automobile information as shown in Figure 5.

Case 9: Design case based 4, residential block exchanges with case 8 mutually with the electric automobile information of Office Area.In this case, evening, most of electric automobile was docked in the place of far from equilibrium node, but daytime, most of electric automobile is docked in balance node place.This means that some electric energy will flow to balance node from the place of far from equilibrium node.

The simulation result of case 7,8,9 discharge and recharge plan is respectively as shown in Fig. 7, Fig. 9.

Comparison cases 8 and case 9, we draw the following conclusions: residential block is near the power distribution network side of step-down transformer, and Office Area is away from the node at transformer place, and such selection economy is higher.

Specific embodiment described in the present invention is only to the explanation for example of the present invention's spirit.Those skilled in the art can make various amendment or supplement or adopt similar mode to substitute to described specific embodiment, but can't depart from spirit of the present invention or surmount the scope that appended claims defines.

Claims (6)

1. consider the electrical network dual-layer optimization dispatching method of extensive electric automobile access for one kind, it is characterized in that, based on the foundation of Optimized model, comprise: the upper strata Optimized model based on Unit Combination model and the lower floor's Optimized model based on optimal load flow model, described lower floor's Optimized model based on optimal load flow model sets up based on the result of the upper strata Optimized model of Unit Combination model, specifically:

Model one: based on the upper strata Optimized model of Unit Combination model, be defined as power transmission network Optimized model, concrete grammar is: with comprise coal-fired cost, the PM2.5 discharge capacity of thermal power generation unit and start-up and shut-down costs, user's charging cost, wind cutting cost six aspects social cost for minimum target; With system charge balance, retain regulation margin capacity, the exerting oneself of generator, the climbing rate of unit, the minimum operation of unit and unused time, the quantity of electric automobile and discharge and recharge time, wind cutting electricity for constraint condition, obtain the power transmission network Optimized model based on Unit Combination model, the result that this Optimized model obtains is the electric automobile discharge and recharge quantity of t under scene s;

Model two: based on lower floor's Optimized model of optimal load flow model, be defined as the foundation of distribution network Optimized model, optimum results based on the acquisition from power transmission network: the electric automobile discharge and recharge quantity optimization result of t under scene s, obtain the optimal location of electric automobile discharge and recharge in power distribution network, concrete grammar is for optimal objective with the minimal energy loss of power distribution network; With electric automobile quantity in meritorious and reactive balance, node voltage size, power distribution network safety condition, node electric automobile battery charger quantity, region and total electric automobile quantity for constraint condition draws the Optimized model of power distribution network;

The electrical network dual-layer optimization dispatching method of this consideration extensive electric automobile access, based on described two Optimized models, comprises the following steps:

Step 1, the optimization of power transmission network, finds the electric automobile optimum discharge and recharge time; Based on from different electricity price curves and electric automobile permeability, consider that user's electric automobile use habit and user accept situation, the level and smooth situation of load curve to discharge and recharge price, and be minimum target with social cost; Contrast draws the price curve guiding user to realize the optimum duration of charging, instructs electric automobile optimum discharge and recharge position in power distribution network further;

Step 2: the optimization of distribution network, finds the optimum discharge and recharge position of electric automobile; Based on the actual service condition of electric automobile user, in conjunction with the optimum results of transmission line of electricity, electric automobile charge-discharge region is divided into residential quarter, shopping centre and Office Area, and arranges mobility status in electric automobile 24 hours in proportion according to actual conditions; Contrast the electric automobile distribution mobility status without electric automobile and different proportion, minimum for target with via net loss, draw the optimum discharge and recharge position of electric automobile.

2. a kind of electrical network dual-layer optimization dispatching method that extensive electric automobile accesses of considering according to claim 1, is characterized in that, described power transmission network Optimized model based on following objective function:

$\min \underset{t=1}{\overset{T}{\mathrm{\&Sigma;}}}\underset{i=1}{\overset{N_g}{\mathrm{\&Sigma;}}}{S}_{i,t}{u}_{i,t}(1-u_{i,t-1})+E\left\{\underset{t=1}{\overset{T}{\mathrm{\&Sigma;}}}\right[\underset{i=1}{\overset{N_g}{\mathrm{\&Sigma;}}}(F_i\left(P_{i,t}^s\right)+C_e{E}_i\left(P_{i,t}^s\right))u_{i,t}+U_t^s+\underset{w=1}{\overset{W}{\mathrm{\&Sigma;}}}{C}_w\mathrm{\&Delta;}{P}_{w,t}^s\left]\right\}$

Wherein, T is time sum, N _gbe the sum of firepower unit, W is the sum of wind energy turbine set; E{} represents the mathematical expectation under all scenes; u _i,tbe the running status of unit i in t, 1 represents operation, and 0 represents shutdown; C _eit is the punishment cost of PM2.5 burst size; C _wcut wind power cost, the wind cutting electricity of t period that is wind energy turbine set under scene s, the probability of scene is Pr ^s.

3. a kind of electrical network dual-layer optimization dispatching method that extensive electric automobile accesses of considering according to claim 2, it is characterized in that, in described power transmission network Optimized model, minimum target is based on following formula and definition:

Minimum target one: coal-fired cost, in electric system, the coal-fired cost of fired power generating unit is the quadratic function of unit output;

$F_i\left(P_{i,t}^s\right)=a_i+b_i{P}_{i,t}^s+c_i{P}_{i,t}^{s2}$

Wherein, a _i, b _iand c _iit is the positive coal-fired coefficient of unit i; unit i the exerting oneself of t under scene s;

Minimum target two: PM2.5 discharge capacity, according to electrical energy production need for environment, exhaust emissions also should be taken into account; China affects very serious by haze, thermal power generation is the main source of PM2.5; As an optimization aim, the discharge capacity of fired power generating unit PM2.5 can be expressed as the quadratic function of unit output;

$E_i\left(P_{i,t}^s\right)=\mathrm{Aar}\&CenterDot;\mathrm{\&omega;}\&CenterDot;(1-\mathrm{\&eta;}/100)\&CenterDot;({\mathrm{\&alpha;}}_i+{\mathrm{\&beta;}}_i{P}_{i,t}^s+{\mathrm{\&gamma;}}_i{P}_{i,t}^{s2})/10000$

Wherein, Aar is dust average weight percent (%) in coal, and default value is 20; ω is the conversion coefficient (%) that flue dust is converted into PM2.5, and default value is 5.1; η is that discharge reduces coefficient (%), and default value is 99; The discharge capacity of a unit is proportional to coal consumption amount, α _i, β _iand γ _iit is the consumption coal measures number of unit;

Minimum target three: start cost, the start cost restarting the thermal power generation unit of shutdown is relevant with the temperature of boiler; Herein, the step function of relevant with temperature start-up cost is relevant to the transit time of warm start with cold start-up;

$S_{i,t}=\left\{\begin{array}{cc}{S}_i^h& T_i^{\mathrm{off}}<X_{i,t}^{\mathrm{off}}\&le;H_i^{\mathrm{off}}\\ S_i^c& X_{i,t}^{\mathrm{off}}>H_i^{\mathrm{off}}\end{array}\right.$

$H_i^{\mathrm{off}}=T_i^{\mathrm{off}}+T_i^c$

Wherein, the warm start cost of unit i, the cold start-up cost of unit i, it is the lasting unused time of unit i at period t; the minimum lasting unused time of unit i, it is the unit i cold start-up time;

Minimum target four: shutdown cost, the shutdown cost of thermal electric generator group is constant, is 0 in modular system intermediate value;

Minimum target five: user's charging cost, user's charging cost is the economic consumption of all electric automobile users, can deduct electric discharge income calculate by charging cost;

$U_t^s={\mathrm{\&rho;}}_{c,t}{N}_{c,t}^s{P}_c\mathrm{\&Delta;t}-{\mathrm{\&rho;}}_{d,t}{N}_{d,t}^s{P}_d\mathrm{\&Delta;t}$

Wherein, ρ _c,tand ρ _d,tthe discharge and recharge electricity price of t respectively; with the electric automobile discharge and recharge quantity of t under scene s respectively; P _cand P _dthe average charge-discharge electric power of electric automobile respectively; Δ t is time span, is one hour herein;

Minimum target six: cut wind power cost, takes into account objective function by the target of cutting wind power cost minimum.

4. a kind of electrical network dual-layer optimization dispatching method that extensive electric automobile accesses of considering according to claim 2, it is characterized in that, in described power transmission network Optimized model, constraint condition is based on following formula and definition:

Constraint condition one: electric quantity balancing, the subject matter of electric power system dispatching ensures the equilibrium of supply and demand, so must meet the needs of basic load and charging electric vehicle any time from the electricity of the genset of all operations, the discharge capacity of electric automobile and wind energy turbine set;

$\underset{i=1}{\overset{N_g}{\mathrm{\&Sigma;}}}\left(u_{i,t}{P}_{i,t}^s\right)+P_d{N}_{d,t}^s+\underset{w=1}{\overset{W}{\mathrm{\&Sigma;}}}(P_{w,t}^s-{\mathrm{\&Delta;P}}_{w,t}^s)=D_t+P_c{N}_{c,t}^s,\&ForAll;t\&Element;T,\&ForAll;s\&Element;S$

Wherein, D _tthe basic load of t, the prediction wind-force of the t of wind energy turbine set under scene s;

Constraint condition two: spinning reserve, in order to improve the reliability of system, it is necessary for leaving sufficient spinning reserve; $\underset{i=1}{\overset{N_g}{\mathrm{\&Sigma;}}}\left(u_{i,t}{P}_i^{\max }\right)+P_d{N}_{d,t}^s+\underset{w=1}{\overset{W}{\mathrm{\&Sigma;}}}(P_{w,t}^s-{\mathrm{\&Delta;P}}_{w,t}^s)\&GreaterEqual;D_t+P_c{N}_{c,t}^s+R_t,\&ForAll;t\&Element;T,\&ForAll;s\&Element;S$ Wherein, the maximum output of unit i, R _tit is the stand-by equipment of t system;

Constraint condition three: generator output retrains, each unit has oneself units limits, and restriction range is as follows:

$P_i^{\min }{u}_{i,t}\&le;P_{i,t}^s\&le;P_i^{\max }{u}_{i,t},\&ForAll;i\&Element;N_g,\&ForAll;t\&Element;T,\&ForAll;s\&Element;S$

Wherein, it is the minimum load of unit i;

Constraint condition four: climbing rate, the variation range of exerting oneself in each unit adjacent time inter is by the constraint of climbing rate;

$-R_{d,i}\&le;P_{i,t}^s-P_{i,t-1}^s\&le;R_{u,i},\&ForAll;i\&Element;N_g,\&ForAll;t\&Element;T,\&ForAll;s\&Element;S$

Wherein, R _u,iand R _d,ithe upper and lower climbing rate of unit i respectively;

Constraint condition five: minimum start/unused time, no matter whether a unit is in operation, and this unit must keep start or cut-off operation minimum time before change running status, so minimum start/unused time can be expressed as follows:

$(X_{i,t}^{\mathrm{on}}-T_i^{\mathrm{on}})(u_{i,t}-u_{i,t+1})\&GreaterEqual;0,\&ForAll;i\&Element;N_g,\&ForAll;t\&Element;T$

$(X_{i,t}^{\mathrm{off}}-T_i^{\mathrm{off}})(u_{i,t+1}-u_{\mathrm{it}})\&GreaterEqual;0,\&ForAll;i\&Element;N_g,\&ForAll;t\&Element;T$

Wherein, with represent that unit i keeps the duration of operation and off-mode in t respectively; with represent the unit i minimum startup and shutdown time respectively;

Constraint condition six: electric automobile quantity, in each moment, the electric automobile quantity that can be used for discharge and recharge can be calculated by lower surface function;

$N_{c,t}^s\&le;N_{c,t}^{\max },\&ForAll;t\&Element;T,\&ForAll;s\&Element;S$

$N_{d,t}^s\&le;N_{d,t}^{\max },\&ForAll;t\&Element;T,\&ForAll;s\&Element;S$

Wherein, with represent that t can be used for the maximum number of discharge and recharge electric automobile respectively;

Constraint condition seven: discharge and recharge time, in order to provide sufficient electric energy to electric automobile, the duration of charging can not be too short; Leave sufficient electricity to make electric automobile and meet trip needs; All electric automobile discharge and recharge time-constrains are as follows;

$\underset{t=1}{\overset{T}{\mathrm{\&Sigma;}}}{N}_{c,t}^s\mathrm{\&Delta;t}=N_c^{\max }{\mathrm{\&Delta;t}}_c,\&ForAll;s\&Element;S$

$\underset{t=1}{\overset{T}{\mathrm{\&Sigma;}}}{N}_{d,t}^s\mathrm{\&Delta;t}=N_d^{\max }{\mathrm{\&Delta;t}}_d,\&ForAll;s\&Element;S$

Wherein, with representative can be used for the electric automobile total quantity of discharge and recharge respectively; Δ t _cwith Δ t _drepresent the electric automobile average discharge and recharge time respectively;

Constraint condition eight: wind cutting amount retrains, the relation of wind cutting amount and wind-force prediction is expressed as follows;

$0\&le;{\mathrm{\&Delta;P}}_{w,t}^s\&le;P_{w,t}^s,\&ForAll;w\&Element;W,\&ForAll;t\&Element;T,\&ForAll;s\&Element;S$

Wherein, represent prediction wind-force.

5. a kind of electrical network dual-layer optimization dispatching method that extensive electric automobile accesses of considering according to claim 1, it is characterized in that, described distribution network Optimized model is based on following objective function:

$\min E\left[\underset{t=1}{\overset{T}{\mathrm{\&Sigma;}}}{P}_{\mathrm{Loss},t}^s\right]$

Wherein, E [*] represents the mathematical expectation of all scenes, the all network loss of power distribution network in the t period.

6. a kind of electrical network dual-layer optimization dispatching method that extensive electric automobile accesses of considering according to claim 5, it is characterized in that, constraint condition is based on following formula and definition:

Constraint condition one: meritorious, reactive balance constraint, each node all must meet meritorious, reactive balance; So:

$P_{\mathrm{G\&alpha;},t}^s+P_d{N}_{\mathrm{d\&alpha;},t}^s-P_{\mathrm{D\&alpha;},t}-P_c{N}_{\mathrm{c\&alpha;},t}^s-P_{\mathrm{T\&alpha;},t}^s=0,\&ForAll;\mathrm{\&alpha;}\&Element;K,\&ForAll;t\&Element;T,\&ForAll;s\&Element;S$

$Q_{\mathrm{G\&alpha;},t}^s-Q_{\mathrm{D\&alpha;},t}-Q_{\mathrm{T\&alpha;},t}^s=0,\&ForAll;\mathrm{\&alpha;}\&Element;K,\&ForAll;t\&Element;T,\&ForAll;s\&Element;S$

Wherein, K is all nodes except balance node, with the node alpha active power that t sends under scene s and reactive power respectively; P _{d α, t}and Q _{d α, t}that node alpha t under scene s is gained merit and load or burden without work respectively; with node alpha t electric automobile discharge and recharge quantity under scene s respectively; with be node alpha t transmission meritorious and idle under scene s respectively, they are by following formulae discovery:

$P_{\mathrm{T\&alpha;},t}^s=V_{\mathrm{\&alpha;},t}^s\underset{j\&Element;\mathrm{\&alpha;}}{\mathrm{\&Sigma;}}{V}_{j,t}^s(G_{\mathrm{\&alpha;j}}\cos {\mathrm{\&theta;}}_{\mathrm{\&alpha;j},t}^s+B_{\mathrm{\&alpha;j}}\sin {\mathrm{\&theta;}}_{\mathrm{\&alpha;j},t}^s)$

$Q_{\mathrm{T\&alpha;},t}^s=V_{\mathrm{\&alpha;},t}^s\underset{j\&Element;\mathrm{\&alpha;}}{\mathrm{\&Sigma;}}{V}_{j,t}^s(G_{\mathrm{\&alpha;j}}\sin {\mathrm{\&theta;}}_{\mathrm{\&alpha;j},t}^s-B_{\mathrm{\&alpha;j}}\cos {\mathrm{\&theta;}}_{\mathrm{\&alpha;j},t}^s)$

Wherein, with the voltage of node alpha and j t under scene s respectively; G _{α j}and B _{α j}be admittance matrix be respectively real number and imaginary part; it is the phase differential of node alpha and j t under scene s;

Constraint condition two: node voltage retrain, in order to ensure the quality of power supply and power grid security, node voltage must meet minimum and maximum constraint;

$V_{\mathrm{\&alpha;},\min }\&le;V_{\mathrm{\&alpha;},t}^s\&le;V_{\mathrm{\&alpha;},\max },\&ForAll;\mathrm{\&alpha;}\&Element;K,\&ForAll;t\&Element;T,\&ForAll;s\&Element;S$

Wherein, V _{α, max}and V _{α, min}the top/bottom latitude of node voltage respectively;

Constraint condition three: power system security constraints, in order to ensure the safe operation of electrical network, the transmission capacity of circuit should limit within the specific limits;

$\left|P_{\mathrm{\&alpha;j},t}^s\right|\&le;P_{\mathrm{\&alpha;j},\max },\&ForAll;\mathrm{\&alpha;},j\&Element;K,\&ForAll;t\&Element;T,\&ForAll;s\&Element;S$

Wherein, P _{α j, max}it is the maximum transfer capacity of circuit α-j; the transmission electricity of transmission line of electricity α-j t under scene s, can by following formulae discovery:

$\left|P_{\mathrm{\&alpha;j},t}^s\right|=|V_{\mathrm{\&alpha;},t}^s{V}_{j,t}^s(G_{\mathrm{\&alpha;j}}\cos {\mathrm{\&theta;}}_{\mathrm{\&alpha;j},t}^s+B_{\mathrm{\&alpha;j}}\sin {\mathrm{\&theta;}}_{\mathrm{\&alpha;j},t}^s)-V_{\mathrm{\&alpha;},t}^{s2}{G}_{\mathrm{\&alpha;j}}|$

Constraint condition four: the number constraint of node charging pile; Each node has the charging pile of some, so the electric automobile maximum quantity that can be connected to electrical network retrains by the part that cooks noodle:

$0\&le;N_{\mathrm{c\&alpha;},t}^s,N_{\mathrm{d\&alpha;},t}^s\&le;N_{\mathrm{\&alpha;},\max },\&ForAll;\mathrm{\&alpha;}\&Element;K,\&ForAll;t\&Element;T,\&ForAll;s\&Element;S$

Wherein, N _{α, max}the quantity of node alpha charging pile;

Constraint condition five: region electric automobile number constraint, due to the mobility of electric automobile, in region, the quantity of electric automobile is change; The electric automobile quantity that can be used for discharge and recharge in certain region can be expressed as follows:

$\underset{\mathrm{\&alpha;}\&Element;i}{\mathrm{\&Sigma;}}{N}_{\mathrm{c\&alpha;},t}^s=N_{\mathrm{ci},t}^s,i=\mathrm{resid},\mathrm{comme},\mathrm{office},\&ForAll;t\&Element;T,\&ForAll;s\&Element;S$

$\underset{\mathrm{\&alpha;}\&Element;i}{\mathrm{\&Sigma;}}{N}_{\mathrm{d\&alpha;},t}^s=N_{\mathrm{di},t}^s,i=\mathrm{resid},\mathrm{comme},\mathrm{office},\&ForAll;t\&Element;T,\&ForAll;s\&Element;S$

Wherein, with represent that i t under scene s in region can be used for the quantity of the electric automobile of discharge and recharge respectively;

Constraint condition six: electric automobile total amount retrains, and the sum that can be used for the electric automobile of discharge and recharge in region should meet upper strata operation plan;

$\underset{i\&Element;I}{\mathrm{\&Sigma;}}{N}_{\mathrm{ci},t}^s=N_{c,t}^s,\&ForAll;t\&Element;T,\&ForAll;s\&Element;S$

$\underset{i\&Element;I}{\mathrm{\&Sigma;}}{N}_{\mathrm{di},t}^s=N_{d,t}^s,\&ForAll;t\&Element;T,\&ForAll;s\&Element;S$

Wherein, I represents all regions; with represent the quantity of t discharge and recharge electric automobile under scene s respectively, this is determined the operation plan of power distribution network by power transmission network.