. SOC [3]..3 ( ) ( 3G ) : : 3: ( Fig. Hierarchicalandzonalarchitecturefor ) dispatchingelectricvehicles ( )... 4: / : (SOC) 5: ; BrackenJ McGil

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36 0 6 0 Vol.36 No. June00 DOI:0.3969/j.issn.000-06.0..006 3 (. 3007;. / 0003; 3. 330006) : ( ) ; AMPL/IPOP AMPL/CPLEX 5 IEEE30 : ; ; ; 0 [] [-4] (VG) [5] VG ; [6] [7] [8] [] ( ) ( ) [9] ; : [0] ; :0--7; :0-0- (507457745); 5 (0-007-03); ( ) IEEE30 (-007-0) 30

. SOC [3]..3 ( ) ( 3G ) : : 3: ( Fig. Hierarchicalandzonalarchitecturefor ) dispatchingelectricvehicles ( )... 4: / : (SOC) 5: ; 4 5... BrackenJ McGilJ 973 [4] / 3

036() ;X= [X X X N0 ] ;X k=[x k x k x k ] [5] [6] k ;Y k [7] : k J = max F(xyy ym) ;ykmt k m x () 烅烆 s.t.g(x) 0 t ykmt= ykmt= - ykmt=0 J i = max fi(xyy ym) y i () 烅 ;n k k 烆 s.t.gi(xyy ym) 0 :F( ) ;x ) ;G( ) N ;fi( ) i ;yi P Git = P Dit +P Eit +U it U j t(g ij cosθijt + j= i ;gi( ) i 烅 B ij sinθijt) N. Q Git =Q Dit+U it U j t(g ij sinθijt-b ij cosθijt ) 烆 j=.. (6) :t [];P Git Q Git i ( t ;P Dit Q Dit ) i t ;P Eit i t ;U it i t ;N ;G ij B ij ;θijt t ) P min Gi P Git P max Gi : t [] (7) min F = X - Y k= t= ( N 0 P dt + kt -P k=x ) d + N 0 α fk(x k Y k ) (3) k= P d = 熿 t= ( N 0 P dt + k=x k) yk yk yk ykm ykm ykm t (4) 燄 (5) { Q min Gi :P max Gi P min Gi Q Git Q max Gi i ; Q max Gi Q min Gi i 3) n ykn k ykn k ykn k n k 燀 k 燅 - : ;P dt P kmdcha x kt P kmcha t [] m= m= t / (0) ;P d ;x kt :P kmch P kmdch k k t x kt>0 x kt<0 m ; k A=I kmtk avail I kmt k m ;N 0 ;α I kmt= I kmt=0 Ui min :U i max U min U it Ui max t [] (8) i i 4) P lt P l max t [] (9) :P lt l t ;P l max l 5) 3

( CPLEX k avail MINOSIPOPSNOPKNIRO ) AMPL /.. AMPL IPOP3.8.0 [9] AMPL / CPLEX. k : min fk(x k Y k )= Y k P kmch n k t= ( kmt -x m=p k) t ykmt = () P kmt = 烅 0 ykmt =0 () 烆 -P kmdch ykmt =- :P kmt k m ) S kmt+ = 烅 S kmt + ηchpkmchδt S kmt β km S kmt - PkmdchΔt 烆 β km η dch ykmt = ykmt =0 ykmt =- (3) :S kmt k m t SOC; η ch η dch ; β km k m ;Δt (3) ) S min S kmt S max (4) :S max S min SOC 3) ykmt =0 t<t kms t kme (5) :t kms t kme k m 4) / S kmtkme S km (6) :S kmtkme S km k m Fig. Flowchartforsolvingbi-leveloptimal SOC dispatchingmodelwithelectricvehicles SOC 4 3 4. AMPL [8] 33

036() f fe(x)= f : exp - ( x+4-μ ) e f = N 0 槡 ( σ ) e πσe P - ( dt + ykt -P ) d t= k= 0<x μ (7) 烅 N 0 n k f = k= t= ( kmt -x m=p k) e - 烅 exp - ( x-μ ) t 槡 ( e σ ) e πσe 烆 :ykt k 烆 μ e -<x 4 t (9) (7) f : μ e=7.47;σe=3.4 ;f fm(x)= 槡 πσmx exp - ( lnx-μ m ) (0) ( σ m ) : 4. 5 IEEE30 μ m=.98;σm=.4 A A5 5 IEEE30 [0] A A A A A3 SOC :00 :00 SOC 90% h 5 695 8 ( [] A A) A α () A ( SOC ) A A4 α=exp n-0 () ( 3 ) 009 :n 0 [] [3] d A A6 A A7 (8) (0) 4.3 fs(x)= ( ) ( ) exp - ( x-μ ) s 0<x μ 槡 πσs σ s+ s 烅 exp - ( x-4-μ ) s 槡 πσs σ s 烆 μ s+<x 4 (8) : μ s=8.9;σs=3.4 able Comparisonsofsystemloadlevelindexes /MW / MW 84.4 79.9 04.5 9.0 80.8 0. 69.3 8.9 50.4 : 34

3 / : ; ; 5 AMPL/ 3 Fig.3 Comparisonamonguncoordinatedcharging IPOP AMPL/CPLEX paternoptimalchargingpaternanddischargingpatern 5 : IEEE30 ; VG 4.4 (htp://aeps.sgepri.sgcc. com.cn/aeps/ch/index.aspx) 3 ( α=α=000 α ) PowerandEnergySocietyGeneralMeetingonConversionand 3 DeliveryofElectricalEnergyinthestCenturyJuly0-4 able Comparisonsofeachevaluationindexunder threepenaltycoeficients 008PitsburghPAUSA:6p. f α= 65.43 8.09 α=000 80.60 0.4 α=exp ( n-0 3 ) 65.76 0.7 : (α=) / 87-83. [4] ; (α=000) f []SCHNEIDER KGERKENSMEYER CKINNER-MEYER Metal.Impactassessmentofplug-inhybridvehiclesonPacific Northwestdistribution systems[c]// Proceedings ofieee []FERN NDEZ L PROM N G SCOSSEN Retal Assessment of the impact of plug-in electric vehicles on distributionnetworks[j].ieee rans on Power Systems 06():06-3. [3]PURUS G ASUWANAPINGKARL PJOHNSON D etal.impactofelectricvehiclesonpowerdistributionnetworks [C]// Proceedings of IEEE Vehicle Power and Propulsion Conference September 7-0 009 Dearborn MI USA:. [J]. 035(4):8-3. 35

036() XU LizhongYANG GuangyaXU Zhaoetal.Impactsof electricvehiclechargingondistributionnetworksin Denmark [J].AutomationofElectricPowerSystems035(4):8-3. [5]KEMPON WLEENDRE S.Electric vehiclesasa new powersourceforelectricutilities[j].ransportationresearch: PartD997(3):57-75. [6]. [6]. [J]. 035(4):-0. ZHAOJunhuaWEN FushuanYANG Aiminetal.Impacts ofelectricvehiclesonpowersystemsaswelastheassociated dispatchingandcontrolproblem [J].Automation of Electric PowerSystems035(4):-0. [7]CARAMANIS MFOSER J M. Management of electric vehiclechargingto mitigaterenewablegenerationintermitency anddistributionnetworkcongestion[c]// Proceedingsofthe 48th IEEE Conference on Decision and Control December 5-8009ShanghaiChina:477-47. [8]. [9]W CHER ABIEGLERL.Ontheimplementationofan [J]. 0034(0):-9. interior-point filter line-search algorithm for large-scale ZHAOJunhuaWEN FushuanXUE Yushengetal.Power system stochastic economic dispatch considering uncertain nonlinear programming[j]. 00606():5-57. Mathematical Programming outputsfromplug-inelectricvehiclesand windgenerators[j]. AutomationofElectricPowerSystems0034(0):-9. [0]ALSAC OSCO B.Optimalloadflow withsteady-state security[j].ieee ransonpowerapparatusandsystems [9]CLEMEN-NYNSKHAESEN EDRIESENJ.heimpact ofcharging plug-in hybrid electric vehicles on a residential distributiongrid[j].ieee ranson PowerSystems00 5():37-380. [0]. generationschedulingwithloadvariationrateconsidered[j]. [J]. 035(4):6-67. AutomationofElectricPowerSystems0083(8):30-34. ZOU WenWU FubaoLIU Zhihong.Centralizedcharging []Federal Highway Administration U.S. Department of strategiesofplug-in hybridelectricvehiclesunderelectricity ransportation.009 nationalhouseholdtravelsurvey[eb/ marketsbased on spotpricing[j].automation of Electric OL].[0-09-5].htp://nhts.ornl.gov. PowerSystems035(4):6-67. [3]. []. [J]. 0034():6-30. [J]. 035(4):4-9. IAN LitingSHIShuanglongJIAZhuo.Astatisticalmodel YU DayangSONGShuguangZHANGBoetal.Synergistic forcharging powerdemand ofelectricvehicles[j].power dispatchofpevschargingandwindpowerinchineseregional System echnology0034():6-30. powergrids[j].automationofelectricpowersystems0 35(4):4-9. []BESSRJMAOS M A.Economicandtechnicalmanagement ofanaggregationagentforelectricvehicles:aliteraturesurvey [EB/OL].[0-09-5].htp://onlinelibrary.wiley.com/ doi/0.00/etep.565/abstract. [3]CALLAWAY DSHISKENSIA.Achievingcontrolabilityof electricloads[j].proceedings oftheieee099(): 84-99. [4]BRACKEN J MCGILL J. Mathematicalprograms with optimization problems in the constraints [J]. Operations Research973():37-44. [5]. [J]. 0088(6):-7. FAN Hong CHENG HaozhongJIN Huazhenget al. ransmissionnetworkbi-levelprogrammingmodelconsidering economyandreliabilityandhybridalgorithm[j].proceedings ofthecsee0088(6):-7. [J]. 0059(9):-5. WANGShufenWANZhongpingFAN Hengetal.Reactive poweroptimization modelanditshybridalgorithm basedon bilevelprogramming[j].powersystem echnology005 9(9):-5. [7]. [M]. : 003. [8]FOURER RGAY D MKERNIGHAN B W.AMPL:a modelinglanguageformathematicalprogramming[m].nded. PacificGroveCAUSA:Brooks/ColehomsonLearning003. 97493(3):745-75. []. [J]. 0083(8):30-34. YU Jiaxi BAI Xuefeng GUO Zhizhong et al. Daily (986) : E-mail:yaoweifeng986@gmail.com (980) : E-mail:fuxiharp@gmail.com (965) : E-mail:fushuan.wen@ gmail.com 36

AChargingandDischargingDispatchingStrategyforElectricVehiclesBasedonBi-levelOptimization YAO Weifeng ZHAO Junhua WEN Fushuan XUE Yusheng XIN Jianbo 3 (.ColegeofElectricalEngineeringZhejiangUniversityHangzhou3007China;.StateGridElectricPowerResearchInstituteNanjing0003China; 3.JiangxiElectricPowerResearchInstituteNanchang330006China) Abstract:heextensiveintegrationofnumerousplug-inelectricvehicles(PEVs)intoapowersystemcouldproducesignificant negativeimpactsonthesecureandeconomicoperationofthepowersystemconcernedifthechargingproceduresofpevsare uncoordinated.giventhisthehierarchicalandzonaldispatchingarchitectureisadoptedandanewbi-leveloptimizationmodel ispresentedforcoordinatingthecharging/dischargingschedulesofthepevs.heupper-levelmodelisdevotedtominimizing thesystemloadvariancesoastoimplementpeakloadshiftingbydispatchingeachelectricvehicleaggregator (EVA)andthe loweroneisaimed attracingthe dispatching scheme determined bythe upperdecision-makerthroughfiguring outan appropriatecharginganddischargingschedulesthroughoutaspecifiedday.wohighlyeficientcommercialsolversampl/ IPOPandAMPL/CPLEXrespectivelyareemployedtosolvethedevelopedoptimizationproblem.FinalyamodifiedIEEE 30-bussystem with5evasisemployedtodemonstratethebasiccharacteristicsofdevelopedmodelandmethod. hisworkissupportedbynationalnaturalsciencefoundationofchina (No.5074No.57745 )aprojectfrom JiangxiPowerCompany(No.0-007-03)andaprojectfrom ycoelectronics(shanghai)co.ltd.(no.-007-0). Keywords:electricvehicle;vehicletogrid (VG);charginganddischargingoptimization;hierarchicalandzonaldispatching; bi-levelop timization 櫧櫧櫧櫧櫧櫧櫧櫧櫧櫧櫧櫧櫧櫧櫧櫧櫧櫧櫧櫧櫧櫧櫧櫧櫧櫧櫧櫧櫧櫧櫧櫧櫧櫧櫧櫧櫧櫧櫧櫧櫧櫧櫧櫧櫧櫧櫧櫧櫧 ( continuedfrompage) (963) : E-mail:liuruiye@hit.edu.cn (986) : E-mail:huanglei@ms.giec.ac.cn WindPowerForecastingBasedonDynamicNeuralNetworks LIU Ruiye HUANG Lei (.SchoolofElectricalEngineeringandAutomationHarbinInstituteofechnologyHarbin5000China;.GuangzhouInstituteofEnergyConversionChineseAcademyofSciencesGuangzhou50630China) Abstract:heprecisionofwindpowerforecastisveryimportantintheselectionofwindfarmsiteandintheintegrationand operationofpowersystem withincreasingpenetrationofwindpower.compared withstaticneuralnetworkstwodynamic neuralnetwork modelslocalyrecurrenttime-delayneuralnetwork modelandglobalyrecurrenttime-delayneuralnetwork modelareproposedfortheforecastingofa windfarm outputinordertosimulatethetime-seriescharacteristicofthe generationseries.odemonstratetheefectivenessthemodelsareappliedandtestedonawindfarmlocatedinthenorthof China.Baseonnumericalmeteorologicalpredictionshourlyforecastsupto4hoursaheadareproducedforthewindfarm. Simulationresultsdemonstratethatthedynamicneuralnetworkmodelsoutperformthestaticonesintheforecastofwindpower withtime-seriescharacteristic. hisworkissupportedbythenationalhighechnologyresearchanddevelopmentprogram ofchina (863Program) (No.0AA05A05). Keywords:windpower;windpowerforecast;neuralnetwork;recurrenttime-delayneuralnetwork;timeseries 37