CN107248010A - The Optimization Scheduling of meter and Load aggregation business and electric automobile response reliability - Google Patents
The Optimization Scheduling of meter and Load aggregation business and electric automobile response reliability Download PDFInfo
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Abstract
The present invention relates to a kind of meter and the Optimization Scheduling of Load aggregation business and electric automobile response reliability, belong to intelligent grid field.Electric automobile electric discharge marginal cost and supply side cost of electricity-generating are calculated, it is determined that the up-and-down boundary of electric discharge electricity price；Introduce consumer psychology principle and characterize uncertainty of the automobile user to Respondence to the Price of Electric Power；Formulate the electric discharge electricity price pricing strategy of meter and LA and EV response reliabilities；Realize that reduction network loss, operating cost and user side maximization of economic benefit, as target, set up LA the and EV Optimal Operation Models based on space-time discharge and recharge electricity price using power network；Output node EV discharge and recharges electricity price, EV charge status, LA response conditions and system call plan.The electric discharge electricity price and LA for effectively formulating EV according to system call policy response reliability level interrupt compensation electricity price, formulation corresponding dispatching response plan.
Description
Technical field
The invention belongs to intelligent grid field, be related to it is a kind of count and Load aggregation business and electric automobile response reliability it is excellent
Change dispatching method.
Background technology
It is existing both at home and abroad at present to cross very much the achievement in research for being directed to electric automobile discharge and recharge.Luo X etc. set up single electronic vapour
The urgent level index of car charging, further analyzes electric automobile charge-discharge electric power automated toing respond under the conditions of virtual public electricity price
Strategy, realizes frequency modulation and stabilizes the power swing that power grid wind access is produced.Flath C M etc. point out, temporal real-time electricity
Valency and node electricity price spatially, region electricity price can play good guiding function to electric automobile, realize electric voltage equalization, peak clipping
Fill valley etc..Pan Zhanghui etc. is from electricity market angle, and user side electric automobile agent is competing using simulation Generation Side power plant
The mode of valency online, is set up the Optimal Operation Model for being discharged and being bidded based on Demand-side, realizes power network peak load shifting and reduction user
The target of side charging cost.Numb show model etc. is further studied on Load aggregation business's Research foundation, spatially sets up node congestion
The dual-layer optimization scheduling model of electricity price, upper strata is from supply side, it is considered to which cost of electricity-generating minimizes and sets up direct current optimal power flow mould
Type obtains Nodal congestion price；Lower floor is from Demand-side, according to the Nodal congestion price of upper layer transfers, it is considered to the expense that charges,
Battery loss and period of reservation of number set up Model for Multi-Objective Optimization, then by discharge and recharge feedback loading after optimization to upper strata, with reality
Existing user and the maximization of economic benefit of power network.Consumer psychology principle is applied to retouch by Chang Fangyu etc. from user side
Response condition of the demanding side of the electrical power net user to tou power price price differential is stated, how research effectively formulates tou power price price and corresponding
Charge peak Pinggu period, guide user power utilization, realize reduction peak load rate and operator, the economic benefit win-win of user
Target.Such method mainly guides electric automobile discharge and recharge by electricity price, it is intended to meet power network peak load shifting and user's economy,
Rarely have meter and electric automobile response to exist uncertain, strategy execution has risk.
Research is responded mainly for electric automobile certainty at present, is rarely had meter and is responded uncertain research.Pan Zhanghui and
Ma Jinxiang etc. considers that electric automobile response is uncertain, and the former is by the way of promise breaking punishment, and the latter, which takes, sets up user's letter
User response situation is rewarded with grade storehouse, it is possible in the promise breaking of reduction electric automobile to a certain degree, lifting power network
Operational reliability.But promise breaking punishment reduces user's enthusiasm to a certain degree, and excitation reward without will response it is uncertain compared with
High electric automobile rejects operation plan to bring schedule risk.
The content of the invention
In view of this, counted and Load aggregation business and electric automobile response reliability it is an object of the invention to provide a kind of
Optimization Scheduling.Consider electric automobile electric discharge marginal cost and supply side cost of electricity-generating, it is determined that the up-and-down boundary of electric discharge electricity price,
Introduce consumer psychology principle and characterize uncertainty of the automobile user to Respondence to the Price of Electric Power, formulate meter and Load aggregation business and
The electric discharge electricity price pricing strategy of electric automobile response reliability, and then set up Load aggregation business based on discharge and recharge electricity price and electronic
Automobile Optimal Operation Model.Finally, realize reduction network loss, operating cost and user side maximization of economic benefit as mesh using power network
Mark, sets up the Load aggregation business based on space-time discharge and recharge electricity price and electric automobile Optimal Operation Model.
To reach above-mentioned purpose, the present invention provides following technical scheme：
The Optimization Scheduling of meter and Load aggregation business and electric automobile response reliability, comprises the following steps：
S1：Electric automobile (Electric Vehicle, EV) electric discharge marginal cost and supply side cost of electricity-generating are calculated, so that
It is determined that the up-and-down boundary of electric discharge electricity price；
S2：Introduce consumer psychology principle and characterize uncertainty of the automobile user to Respondence to the Price of Electric Power；
S3：Formulate meter and the electric discharge electricity of Load aggregation business (Load Aggregator, LA) and electric automobile response reliability
Valency pricing strategy；
S4：Set up the Load aggregation business based on discharge and recharge electricity price and electric automobile Optimal Operation Model；Realized and dropped with power network
Low network loss, operating cost and user side maximization of economic benefit are target, set up the Load aggregation based on space-time discharge and recharge electricity price
Business and electric automobile Optimal Operation Model；Output node electric automobile discharge and recharge electricity price, electric automobile charge status, load gather
Close business's response condition and system call plan.
Further, the step S1 specifically includes following steps：
S101：Calculate EV benefit function CE_S,t=ρdis,tQE,t-CE_Loss,t, wherein：CE_S,tRepresent period t user side EV
Electric discharge benefit；ρdis,tRepresent the actual discharge electricity price of period t user side EV, CE_Loss,tRepresent EV cost depletions；QE,tTable
Show charge/discharge electricity amount；
Work as CE_S,tWhen >=0, EV is obtained in the acceptable unit of electrical energy electric discharge electricity price lower bound ρ of period tEV_dis,t；
S102：Calculate the benefit function C of Utilities Electric Co.G_S,t=CGrid,t-ρGr_dis,tQE,t, wherein CGrid,tRepresent that electric power is public
Take charge of cost；ρGr_dis,tRepresent the acceptable EV unit of electrical energy electric discharge electricity price of period t Utilities Electric Co., QE,tIt is expressed as new increment life insurance；
Work as CG_S,tWhen >=0, the acceptable EV unit of electrical energy electric discharge electricity price upper bound ρ of Utilities Electric Co. is obtainedGr_dis,t。
Further, the step S2 specifically includes following steps：
S201：Calculate electric discharge Respondence to the Price of Electric Power degree η：
kE=ηE,max/(ρGr_dis,t-ρEV_dis,t)
In formula：ρdis,tRepresent the actual discharge electricity price of period t user side EV；ρEV_dis,tRepresent dead band threshold values, i.e., it is critical to put
Electricity price；ρGr_dis,tRepresent the acceptable EV unit of electrical energy electric discharge electricity price of period t Utilities Electric Co.；ηGr_dis,tRepresent saturation region valve
Value, i.e. saturation electric discharge electricity price；ηE,maxRepresent the saturation value of EV user response percentages；kERepresent EV user response curve linears area
Slope；
S202：Response curve of the EV user to electricity price of discharging, wherein abscissa table are characterized with the form of piecewise linear function
Show the electric discharge electricity price that grid operator formulates, ordinate represents the corresponding electric discharge Respondence to the Price of Electric Power percentage of EV user, that is, discharge electricity
Valency responsiveness；The intersection point of curve and abscissa is (ρEV_dis,t, 0), wherein ρEV_dis,tRepresent critical electric discharge electricity price, i.e. user couple
The minimum value that electricity price is begun to respond to；Saturation region turning point is (ρGr_dis,t,ηE,max), wherein ρGr_dis,tSaturation electric discharge electricity price is represented,
I.e. user response reaches capacity, and the electricity price critical value that response fluctuation can approximately be ignored.
Further, the step S3 specifically includes following steps：
S301：If δ~N (u, σ2), δmin,δmaxFor known two real numbers, δ meets δmin≤δ≤δmaxThe mathematics of condition
Probability distribution is cutting gearbox, is designated as N (u, σ2,δmin,δmax), the mathematic(al) representation of its probability density function is：
It is desired for：
In formula：Represent the probability density function of standardized normal distribution；Φ (δ) represents cumulative distribution function；
S302：After LA and EV coordinated schedulings, the scheduling strategy response reliability of user side is：
γ E (t)=1-fp(t)
In formula：γE(t) the scheduling strategy response reliability of period t all user responses is represented；Represent electric discharge electricity price
The quantity of EV user responses after lower optimization；γLA,kRepresent k-th of LA response reliability；PLA1,k、PLA0,kRepresent respectively k-th
Bearing power before and after LA demand responses, Qdis,nRepresent the electric energy total amount that vehicle n user can discharge；QE,tRepresent Utilities Electric Co.
Newly-increased generating electricity；QEV,n(t) vehicle n response electricity is represented；
S303：Determine that EV user and LA each need the load capacity of response.
Further, the step S4 specifically includes following steps：
S401：Consider from user side angle, LA demand responses and EV user's discharge and recharge maximization of economic benefit, its target letter
Number is：
CLA_price,k(t)=hk(PLA1,k(t)-PLA0,k(t))ρprice,k(t)
In formula：T represents scheduling slot number；N represents electric automobile total quantity；ρch,t、ρdis,tDischarge and recharge electricity price is represented respectively；
Pch,n(t)、Pdis,n(t) charge-discharge electric power of period t vehicle n is represented respectively；ηch、ηdisEV efficiency for charge-discharge is represented respectively；
statech,n(t)、statedis,n(t) the charge and discharge state of period t vehicle n is represented respectively；PLA1,k、PLA0,kRepresent k-th of LA optimization
Load power before and after adjustment；ρLA_price,k(t) represent that period t interrupts compensation electricity price, multiple compensation way is compensated using height；hk
() represents high compensation multiple transfer function；ρprice,k(t) Spot Price of k-th of LA of period t is represented；K represents LA numbers；
CEV,tRepresent that period t power network pays EV financial cost；CLA,tRepresent that period t power network pays LA response cost；
S402：Consider from grid side angle, the ability that time horizon maximizes excavation user side demand response enters one to model
After step optimization, user side electricity consumption maximization of economic benefit, grid side expects the scheduling strategy response reliability highest, its target letter
Number is：
S403：To sum up：
f1And f2Two object function dimensions are different, and normalization adaptive weighting method is used to object function by multiple-objection optimization
Problem is converted into single-objective problem, and specific normalization conversion formula is as follows：
It is processed into by normalization after same dimension, after adaptive weighting method, the object function of model is：
Min f=λ1f1+λ2f2
In formula：λ1、λ2Represent that user side economic benefit and grid side scheduling strategy response reliability are each in Optimized model respectively
From the size of proportion, i.e. preference coefficient, its constraints is：
λ1+λ2=1, and λ1>=0, λ2≥0
Constraints is except considering node voltage constraint, electric automobile power constraint, electric automobile discharge and recharge time-constrain, bear
Lotus polymerization business can interrupt power constraint it is outer, it is also contemplated that electricity tariff constraint is：
S404：Output node electric automobile discharge and recharge electricity price, electric automobile charge status, Load aggregation business's response condition
With system call plan.
The beneficial effects of the present invention are：The meter of the present invention and the discharge and recharge electricity price Optimal Operation Model of time scale can have
Imitate the electric discharge electricity price and LA that EV is formulated according to system call policy response reliability level and interrupt compensation electricity price, and formulate phase
The dispatching response plan answered.In addition, scheduling strategy response reliability level is higher, EV electric discharge electricity price is lower, and LA's interrupts
Compensate electricity price to rise, EV response discharge electricity amounts are reduced, and user side economic benefit will be caused to decline；It is only big when compensation electricity price can be interrupted
When EV discharges electricity price, the economic benefit that LA can interrupt electricity acquisition reduces the economic benefit loss caused higher than EV discharge capacities,
User side economic benefit will be made to go up.
Brief description of the drawings
In order that the purpose of the present invention, technical scheme and beneficial effect are clearer, the present invention provides drawings described below and carried out
Explanation：
Fig. 1 is automobile user electric discharge Respondence to the Price of Electric Power curve map；
Fig. 2 is the node power distribution net schematic diagrames of IEEE 33；
Fig. 3 is influence schematic diagram of the scheduling strategy response reliability level to electricity pricing；
Fig. 4 is influence schematic diagram of the scheduling strategy response reliability level to user side economic benefit；
Fig. 5 is Optimized Operation strategic process figure；
Fig. 6 is day charge-discharge power demand curve map；
Fig. 7 is line voltage distribution map；
Fig. 8 is grid nodes distribution of electricity prices figure；
Fig. 9 is node space-time power dispatching figure.
Embodiment
Below in conjunction with accompanying drawing, the preferred embodiments of the present invention are described in detail.
The electric energy Q that each node time sequence of known spatial changesE, make in the time scale under each node further excellent
Change, grid operator considers to formulate the rational electricity price of discharge and recharge in real time, guides EV (electric automobile) user's charge and discharge of each period
Electricity and LA (Load aggregation business) demand response, realize peak load shifting and ensure operation of power networks stability；EV user and LA are examined respectively
Consider when discharge and recharge and demand response, realize itself maximization of economic benefit.
1 discharge and recharge electricity price boundary value is determined
In view of the electricity market mechanism of current China, EV and LA are equivalent to network load, therefore the electricity price C that chargesch,t
Using the node electricity price ρ of system real-time releaseprice,t。
Consider power network income and conventional electric power generation stand-by cost, meter and EV user's loss and stand-by cost, formulate rational
Electric discharge electricity price, encourages EV user's active response dispatching of power netwoks.
(1) EV benefit functions and electric discharge electricity price lower bound
EV cost depletions CE_Loss,tIt is made up of two parts, cost depletions C caused by discharge processE_dis,tAnd battery life
Loss conversion cost CE_L,t.I.e.：
CE_Loss,t=CE_dis,t+CE_L,t (1)
Discharging efficiency cost depletions in discharge process, with current charging electricity price and the product representation of loss electric energy, are as used
The fixed cost at family, is interpreted as the fixed cost that user participates in lose during release regulation electric energy.
CE_dis,t=ρpri_ch,tQE,t (2)
In formula：ρpri_ch,tFor charging electricity price；QE,tThe electric energy discharged for needed for EV.
Document (Meijer, consideration [J] the electric power network techniques of high gift prestige traffic characteristicses in the grid-connected research of electric automobile, 2015,
39(12):3549-3555.、AhlertKH,Block C.Assessingthe impact ofprice forecast
errors onthe economics of distributed storage systems[C]//System Sciences
(HICSS),2010 43rd Hawaii International Conference on.Hawaii,IEEE,2010:1-10.)
In mention battery use cost and can characterize battery life.The cost C that battery overall performance is degenerated is caused by cycle charge-dischargeE_L,t
With charge/discharge electricity amount QE,tInto substantially linear relation, i.e.,：
In formula：It is constant for the cost depletions coefficient caused by cycle charging.
EV benefit function is the difference of EV incomes and EV cost depletions：
CE_S,t=ρdis,tQE,t-CE_Loss,t (4)
In formula：CE_S,tRepresent the electric discharge benefit of period t user side EV；ρdis,tRepresent the actual discharge of period t user side EV
Electricity price.
From formula (4), to ensure that EV user loses without interests, work as CE_S,tWhen >=0, as EV is acceptable in period t
Unit of electrical energy electric discharge electricity price lower bound ρEV_dis,t, as shown in formula (5), the wish of user's rationality participation has been fully demonstrated, has been ensured certainly
Market dispatch is participated on the basis of body loss.
(2) Utilities Electric Co.'s benefit function and the electric discharge electricity price upper bound
Utilities Electric Co. cost CGrid,tTo increase generating Q newlyE,tWhen, choose traditional standby from performance driving economy angle and generate electricity
The unit that equal consumed energy ratio is minimum in unit is calculated, such as formula (6).
CGEN,i(t)=ai+biPgen,i(t)+ciPgen,i(t)2 (8)
In formula：Pgen,i(t) generator i active power output is represented；CGEN,i(t) represent that Utilities Electric Co. increases newly respectively
Generating QE,tWhen cost of electricity-generating and original cost of electricity-generating.
When the conventional electric power generation stand-by cost of period t Utilities Electric Co.'s saving is used to compensate EV electric discharges, the benefit letter of Utilities Electric Co.
Number CG_S,tAs shown in formula (9).
CG_S,t=CGrid,t-ρGr_dis,tQE,t (9)
Ensure Utilities Electric Co.'s profit, i.e. CG_S,t≥0.Remember CGrid,t/QE,tRepresent the acceptable EV unit of electrical energy of Utilities Electric Co.
Electricity price of discharging upper bound ρGr_dis,t, convolution (6)-(9) derive the electricity price upper bound ρ that Utilities Electric Co. receivesGr_dis,t, such as formula (10) institute
Show.
ρGr_dis,t=bi+ciQE,t+2ciPgen,i(t) (10)
Formula (10) is property QE,tOne timing, the acceptable unit of electrical energy electric discharge electricity price upper bound of Utilities Electric Co..
EV user response mechanism under 2 electric discharge electricity prices
The research of user response behavior is shown according to consumer psychology principle, response of the user to electricity price has one most
I feels poor (critical threshold values), i.e., when compensation electricity price does not reach critical threshold values, user response is insensitive, is defined as response unwise
Sensillary area domain (equivalent to dead band)；When compensating electricity price more than critical threshold values, the sound of linear correlation will be presented in user with compensation electricity price
Answer effect, be defined as responding the range of linearity (equivalent to linear zone)；Compensation electricity price persistently increases, but user response has saturation
Value, i.e., when compensating electricity price more than a saturation value, user will not further respond, and be defined as zone of saturation (quite
In saturation region).According to principles above, define EV user responses percentage and characterize the electric discharge electricity that EV user is formulated grid operator
Valency responsiveness, i.e., when grid operator implements different electric discharge electricity price (compensating electricity price), the EV user with dump energy rings
The quantity answered accounts for the percentage of all EV numbers of users with dump energy.
Electric discharge Respondence to the Price of Electric Power degree η be：
kE=ηE,max/(ρGr_dis,t-ρEV_dis,t) (12)
In formula：ρEV_dis,tRepresent dead band threshold values (critical electric discharge electricity price)；ηGr_dis,tRepresenting saturation region threshold values, (saturation is discharged
Electricity price)；ηE,maxRepresent the saturation value of EV user response percentages；kERepresent EV user response curve linears area slope.
Response curve of the EV user to electricity price of discharging is characterized with the form of piecewise linear function, as shown in Figure 1.It is wherein horizontal to sit
Mark represents the electric discharge electricity price that grid operator formulates, and ordinate represents the corresponding electric discharge Respondence to the Price of Electric Power percentage of EV user, that is, put
Electric Respondence to the Price of Electric Power degree, point A, B represent dead band turning point and saturation region turning point respectively.Its physical meaning illustrates as shown in table 1.
The response theory concept of table 1 is illustrated
The electric discharge electricity price pricing strategy of 3 meters and LA and EV response reliabilities
The pricing strategy of " being responded by matter " is proposed, during height electric discharge electricity price, it is more to cut load capacity, pays the utmost attention to high reliability
User response, when cutting load capacity and still having vacancy, it is considered to low reliability user response；In low discharge electricity price, load capacity is cut
It is less, only consider part high reliability user's preferential answering.
First, it is considered to which the promise breaking electricity that disengaging power network in EV user responses midway is caused is distributed in non-negative interval [0, Qdis,n]
It is interior, wherein Qdis,nThe electric energy total amount that vehicle n user can discharge is represented, therefore, EV promise breaking models consider that normal state point is blocked in application
Cloth come simulate EV user break a contract electricity random distribution.If δ~N (u, σ2), δmin,δmaxFor known two real numbers, δ is met
δmin≤δ≤δmaxThe mathematical probabilities of condition are distributed as cutting gearbox, are designated as N (u, σ2,δmin,δmax).Its probability density letter
Several mathematic(al) representations are：
It is desired for：
In formula：Represent the probability density function of standardized normal distribution；Φ (δ) represents cumulative distribution function.
Real-life all types of user, it is considered to which demand responses of the LA based on excitation has certain property obligated, and is
Simplified analysis, its LA response reliability γLARequirement of all types of user to power supply reliability is defined as, constant is set to.LA and EV is assisted
After key degree, the scheduling strategy response reliability of user side is：
γE(t)=1-fp(t) (16)
In formula：γE(t) the scheduling strategy response reliability of period t all user responses is represented；Represent electric discharge electricity price
The quantity of EV user responses after lower optimization；γLA,kRepresent k-th of LA response reliability；PLA1,k、PLA0,kRepresent respectively k-th
Bearing power before and after LA demand responses；Qdis,nRepresent the electric energy total amount that vehicle n user can discharge；QE,tRepresent Utilities Electric Co.
Newly-increased generating electricity；QEV,n(t) vehicle n response electricity is represented.
Pass through above-mentioned theory, it is considered to the requirement of the scheduling strategy response reliability of grid operator, you can according to EV user and
LA response reliability level, determines that EV user and LA each need the load capacity of response, further according to EV electric discharge Respondence to the Price of Electric Power
Model is that can determine that electric discharge electricity price.
The Optimal Operation Model of 4 meters and LA and EV time scales
User side
Consider from user side angle, it is desirable to LA demand responses and EV user's discharge and recharge maximization of economic benefit, its target letter
Number is：
CLA_price,k(t)=hk(PLA1,k(t)-PLA0,k(t))ρprice,k(t) (21)
In formula：T represents scheduling slot number；N represents electric automobile total quantity；ρch,t、ρdis,tDischarge and recharge electricity price is represented respectively；
Pch,n(t)、Pdis,n(t) charge-discharge electric power of period t vehicle n is represented respectively；ηch、ηdisEV efficiency for charge-discharge is represented respectively；
statech,n(t)、statedis,n(t) the charge and discharge state of period t vehicle n is represented respectively；PLA1,k、PLA0,kRepresent k-th of LA optimization
Load power before and after adjustment；ρLA_price,k(t) represent that period t interrupts compensation electricity price, multiple compensation way is compensated using height；hk
() represents high compensation multiple transfer function；ρprice,k(t) Spot Price of k-th of LA of period t is represented；K represents LA numbers；
CEV,tRepresent that period t power network pays EV financial cost；CLA,tRepresent that period t power network pays LA response cost.
Grid side
After time horizon maximizes the ability for excavating user side demand response to the further optimization of model, user side electricity consumption economy
Maximizing the benefits, and grid side then expects the scheduling strategy response reliability highest, its object function is：
In summary, this is a multiple target considered in terms of user side and grid side two, the optimization of multiple constraint
Problem, i.e.,：
F is known in analysis1And f2Two object function dimensions are different, therefore, adaptive using normalization to the object function of this model
Multi-objective optimization question is converted into single-objective problem by the method for weighting.Specific normalization conversion formula is as follows：
It is processed into by normalization after same dimension, after adaptive weighting method, the object function of model is：
Minf=λ1f1+λ2f2 (25)
In formula：λ1、λ2Represent that user side economic benefit and grid side scheduling strategy response reliability are each in Optimized model respectively
From the size of proportion, i.e. preference coefficient, its constraints is as follows：
λ1+λ2=1, and λ1>=0, λ2≥0 (26)
Constraints is except considering node voltage constraint, electric automobile power constraint, electric automobile discharge and recharge time-constrain, bear
Lotus polymerization business can interrupt power constraint etc. it is outer, it is also contemplated that electricity tariff constraint is as follows：
5 example data and basic model
EV space-times discharge and recharges is considered in power distribution network, therefore bibliography (He L, Yang J, Yan J, et al.A bi-
layer optimization based temporal and spatial scheduling for large-scale
electric vehicles[J].Applied Energy,2016,168:179-192.) the modification Node power distribution systems of IEEE 33
Exemplified by, checking puies forward the validity of model and algorithm herein, and node destination is classified and the topological structure of power network is shown in Fig. 2, is generated electricity
Side and distribution network users are connected by simplified transformer and transmission line of electricity, and the unit parameter and coefficient correlation that node 1 is connected are shown in
Table A 1, reference capacity 100MVA, voltage class 12.66kV.Choose node 2,21,24 and be used as Office Area load access point, node
6th, 10,30 as business Recreation area load access point, and node 16,18,33 is respectively mounted as residential block load access point, each node
There are EV charging/discharging apparatus and control of intelligent terminal.LA can outage capacity take the 10% of Real-time Load, interruptible load with high compensation ginseng
Number and response reliability level are shown in Table A2.EV relevant parameters and quantity ask for bibliography, and (Li Zhenkun, Tian Yuan, Dong Chengming wait
Distributed power source plans [J] Automation of Electric Systems, 2014,38 (16) in power distribution network containing electric automobile based on probabilistic loadflow:
60-66.), (Yang Jiajia, Zhao Junhua, Wen Fushuan wait void of the containing electric automobile and Wind turbines to battery cost of compensation bibliography
Intend Bidding strategy for power plant [J] Automation of Electric Systems, 2014,38 (13):92-102.), permeability selects 50%, Dian Xing
EV space-time discharge and recharge typical sampling discharge and recharge load curves are typical as shown in fig. 6, each node LA is superimposed after EV day charging and discharging curves
Shown in day node active power tables of data A3.The upper limit δ of truncated distributionmax=Qdis,n, correspond to EV user and persistently respond electric discharge electricity price
Until scheduling is completed；The lower limit δ of its truncated distributionmin=0, correspondence EV user has neither part nor lot in response, and average and variance are set as u=
0, σ=Qdis,n。
The node system unit parameters of 1 IEEE of Table A 33
Note：Generator G1~G3 is located at node 1.
The interruptible load with high compensation parameter of Table A 2
The typical day day part node load (unit of Table A 3:MW)
Basic example considers to be electrically accessed under grid condition in EV initial sample charge and discharges, and it is carried out with reference to node load data
Optimal load flow is calculated, and space-time voltage's distribiuting, each node electricity price and each node power dispatch situation is obtained, such as Fig. 7, Fig. 8 and Fig. 9 institute
Show.Find out from voltage's distribiuting, node 18,33 occurs voltage in the load peak period 14,19 less than 0.95, to power grid operation
Bring threat.From different loads in node electricity price analysis, time scale to that should have during different node electricity prices, such as load peak
The higher node electricity price of section 14-19 correspondences, the relatively low node electricity price of correspondence, is the need of time scale before the load valley period 9
Ask response to provide to ensure；On Spatial Dimension, same period each node electricity price is different, is that the demand response of Spatial Dimension is carried
Condition is supplied.
Influence of the 5.1 scheduling strategy response reliabilities to electricity pricing strategy
Because electricity price of discharging is discharged only for EV, equivalent to power termination is cut down, each node disjoint responds the tune of space layer
Degree plan, analysis method is identical, therefore chooses the progress example case study of typical residential block node 18.Fig. 3 Reactive scheduling strategies
Response reliability level is in 0.5 (ignoring response reliability), 0.85,0.9,0.95 (response reliability maximization) four kinds of situations
Under, discharge EV electricity price, LA interrupt the influence of electricity pricing.The influence of scheduling strategy response reliability is mainly reflected in：With
System call policy response reliability level is improved, and user side is meets dispatching of power netwoks policy response reliability requirement, and scheduling rings
The high LA of reliability level is answered to interrupt electricity increase, Interrupted load management rises, and EV discharge capacities are reduced, electric discharge electricity price reduction,
The user higher the purpose is to reject the uncertainty in EV response electric discharges, it is reliable that safeguards system scheduling strategy is performed.Wherein,
Period 18 is relatively low due to cutting down electricity, causes in the acceptable electric discharge electricity price lower limits of EV electric discharge electricity price acceptable higher than power network
Limit, therefore discharge scenario is invalid, user side can only select LA to interrupt electricity replacement.Therefore period electric discharge electricity price is chosen EV and can connect
The electric discharge electricity price lower limit received is as signal.
Impact analysis of the 5.2 scheduling strategy response reliabilities to economic benefit
For the different influences to scheduling scheme economic benefit of checking scheduling strategy response reliability level, direct configuration scheduling
The parameter value of policy response reliability is that equidistant numerical value is analyzed, and the user side economic benefit cost of scheduling scheme is with scheduling
The variation tendency of policy response reliability level is as shown in Figure 4.Fig. 4 is shown as system call policy response level requirement is carried
Height, user side economic benefit is on a declining curve, is because a large amount of high economic benefits but relatively low EV electric discharges of response reliability are given up
Abandon, and low economic well-being of workers and staff but the higher LA of response reliability can interrupt electricity introducing.Exist in scheduling strategy response reliability level
Occur flex point at 0.90, be because can interrupt electricity it is larger after cause Interrupted load management to be discharged electricity price (Fig. 3 higher than now EV
(d)), i.e. LA loses by interrupting the economic benefit that electricity is obtained higher than the economic benefit that the reduction of EV discharge capacities is caused, and causes user
The rise of side economic benefit.Therefore, the optimal solution to user side economic benefit is brought shadow by scheduling strategy response reliability level
Ring.
As shown in figure 5, the brief step of Optimized Operation strategy is：
Step one：Read the electric energy Q that each node time sequence of space nodes electricity price and space changesE；
Step 2：Ensure in the case of electric automobile trip, urgently spent using charging and the electric abundant intensity in side is to used for electric vehicle
Family is sorted, and obtains electric automobile power adjustable bound；
Step 3：According to user's history electricity consumption data, prediction obtain typical load polymerization business load power curve and can
Interrupt response power bound；
Step 4：The meter and time scale discharge and recharge electricity price set up according to Load aggregation business and electric automobile response reliability
Optimal Operation Model, which is solved, obtains electric automobile electric discharge electricity price；
Step 5：Result judgement, if meet stopping criterion for iteration, no, return to step one recalculates space nodes electricity
Valency and the electric energy Q changed with each node time sequence in spaceE, and compute repeatedly；It is to go to step six；
Step 6：Output node electric automobile discharge and recharge electricity price, electric automobile charge status, Load aggregation business response feelings
Condition and system call plan.
Finally illustrate, preferred embodiment above is merely illustrative of the technical solution of the present invention and unrestricted, although logical
Cross above preferred embodiment the present invention is described in detail, it is to be understood by those skilled in the art that can be
Various changes are made to it in form and in details, without departing from claims of the present invention limited range.
Claims (5)
1. the Optimization Scheduling of meter and Load aggregation business and electric automobile response reliability, it is characterised in that：This method includes
Following steps：
S1：Electric automobile (ElectricVehicle, EV) electric discharge marginal cost and supply side cost of electricity-generating are calculated, so that it is determined that
The up-and-down boundary for electricity price of discharging；
S2：Introduce consumer psychology principle and characterize uncertainty of the automobile user to Respondence to the Price of Electric Power；
S3：The electric discharge electricity price for formulating meter and Load aggregation business (LoadAggregator, LA) and electric automobile response reliability is determined
Valency strategy；
S4：Set up the Load aggregation business based on discharge and recharge electricity price and electric automobile Optimal Operation Model；Reduction net is realized with power network
Damage, operating cost and user side maximization of economic benefit are target, set up Load aggregation business based on space-time discharge and recharge electricity price and
Electric automobile Optimal Operation Model；Output node electric automobile discharge and recharge electricity price, electric automobile charge status, Load aggregation business
Response condition and system call plan.
2. the Optimization Scheduling of meter as claimed in claim 1 and Load aggregation business and electric automobile response reliability, it is special
Levy and be：The step S1 specifically includes following steps：
S101：Calculate EV benefit function CE_S,t=ρdis,tQE,t-CE_Loss,t, wherein：CE_S,tRepresent putting for period t user side EV
Electric benefit；ρdis,tRepresent the actual discharge electricity price of period t user side EV, CE_Loss,tRepresent EV cost depletions；QE,tExpression is filled
Discharge electricity amount；
Work as CE_S,tWhen >=0, EV is obtained in the acceptable unit of electrical energy electric discharge electricity price lower bound ρ of period tEV_dis,t；
S102：Calculate the benefit function C of Utilities Electric Co.G_S,t=CGrid,t-ρGr_dis,tQE,t, wherein CGrid,tRepresent Utilities Electric Co. into
This；ρGr_dis,tRepresent the acceptable EV unit of electrical energy electric discharge electricity price of period t Utilities Electric Co., QE,tIt is expressed as new increment life insurance；
Work as CG_S,tWhen >=0, the acceptable EV unit of electrical energy electric discharge electricity price upper bound ρ of Utilities Electric Co. is obtainedGr_dis,t。
3. the Optimization Scheduling of meter as claimed in claim 1 and Load aggregation business and electric automobile response reliability, it is special
Levy and be：The step S2 specifically includes following steps：
S201：Calculate electric discharge Respondence to the Price of Electric Power degree η：
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kE=ηE,max/(ρGr_dis,t-ρEV_dis,t)
In formula：ρdis,tRepresent the actual discharge electricity price of period t user side EV；ρEV_dis,tDead band threshold values is represented, i.e., critical electric discharge electricity
Valency；ρGr_dis,tRepresent the acceptable EV unit of electrical energy electric discharge electricity price of period t Utilities Electric Co.；ηGr_dis,tSaturation region threshold values is represented, i.e.,
Saturation electric discharge electricity price；ηE,maxRepresent the saturation value of EV user response percentages；kERepresent EV user response curve linears area slope；
S202：Response curve of the EV user to electricity price of discharging is characterized with the form of piecewise linear function, wherein abscissa represents electricity
The electric discharge electricity price that network operation business is formulated, ordinate represents the corresponding electric discharge Respondence to the Price of Electric Power percentage of EV user, that is, electricity price of discharging is rung
Response；The intersection point of curve and abscissa is (ρEV_dis,t, 0), wherein ρEV_dis,tCritical electric discharge electricity price is represented, i.e., user is to electricity price
The minimum value begun to respond to；Saturation region turning point is (ρGr_dis,t,ηE,max), wherein ρGr_dis,tSaturation electric discharge electricity price is represented, that is, is used
Family response reaches capacity, and the electricity price critical value that response fluctuation can approximately be ignored.
4. the Optimization Scheduling of meter as claimed in claim 1 and Load aggregation business and electric automobile response reliability, it is special
Levy and be：The step S3 specifically includes following steps：
S301：If δ~N (u, σ2), δmin,δmaxFor known two real numbers, δ meets δmin≤δ≤δmaxThe mathematical probabilities of condition point
Cloth is cutting gearbox, is designated as N (u, σ2,δmin,δmax), the mathematic(al) representation of its probability density function is：
It is desired for：
In formula：Represent the probability density function of standardized normal distribution；Φ (δ) represents cumulative distribution function；
S302：After LA and EV coordinated schedulings, the scheduling strategy response reliability of user side is：
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In formula：γE(t) the scheduling strategy response reliability of period t all user responses is represented；Represent excellent under electric discharge electricity price
The quantity of EV user responses after change；γLA,kRepresent k-th of LA response reliability；PLA1,k、PLA0,kRepresent that k-th of LA is needed respectively
Ask the bearing power before and after response, Qdis,nRepresent the electric energy total amount that vehicle n user can discharge；QE,tRepresent that Utilities Electric Co. increases newly
Generating electricity；QEV,n(t) vehicle n response electricity is represented；
S303：Determine that EV user and LA each need the load capacity of response.
5. the Optimization Scheduling of meter as claimed in claim 1 and Load aggregation business and electric automobile response reliability, it is special
Levy and be：The step S4 specifically includes following steps：
S401：Consider from user side angle, LA demand responses and EV user's discharge and recharge maximization of economic benefit, its object function
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ρLA_price,k(t)=hk(PLA1,k(t)-PLA0,k(t))ρprice,k(t)
In formula：T represents scheduling slot number；N represents electric automobile total quantity；ρch,t、ρdis,tDischarge and recharge electricity price is represented respectively；Pch,n
(t)、Pdis,n(t) charge-discharge electric power of period t vehicle n is represented respectively；ηch、ηdisEV efficiency for charge-discharge is represented respectively；
statech,n(t)、statedis,n(t) the charge and discharge state of period t vehicle n is represented respectively；PLA1,k、PLA0,kRepresent k-th of LA optimization
Load power before and after adjustment；ρLA_price,k(t) represent that period t interrupts compensation electricity price, multiple compensation way is compensated using height；hk
() represents high compensation multiple transfer function；ρprice,k(t) Spot Price of k-th of LA of period t is represented；K represents LA numbers；
CEV,tRepresent that period t power network pays EV financial cost；CLA,tRepresent that period t power network pays LA response cost；
S402：Consider from grid side angle, the ability that time horizon maximizes excavation user side demand response is further excellent to model
After change, user side electricity consumption maximization of economic benefit, grid side expects the scheduling strategy response reliability highest, its object function
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S403：To sum up：
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f1And f2Two object function dimensions are different, and normalization adaptive weighting method is used to object function by multi-objective optimization question
Single-objective problem is converted into, specific normalization conversion formula is as follows：
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It is processed into by normalization after same dimension, after adaptive weighting method, the object function of model is：
Min f=λ1f1+λ2f2
In formula：λ1、λ2User side economic benefit and grid side scheduling strategy response reliability each institute are represented in Optimized model respectively
The size of accounting weight, i.e. preference coefficient, its constraints is：
λ1+λ2=1, and λ1>=0, λ2≥0
Constraints is gathered except the constraint of consideration node voltage, electric automobile power constraint, electric automobile discharge and recharge time-constrain, load
Close business can interrupt power constraint it is outer, it is also contemplated that electricity tariff constraint is：
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S404：Output node electric automobile discharge and recharge electricity price, electric automobile charge status, Load aggregation business response condition and it is
System operation plan.
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