風(fēng)電場(chǎng)風(fēng)速和輸出功率的多尺度預(yù)測(cè)研究.pdf

1、蘭州理工大學(xué)碩士學(xué)位論文風(fēng)電場(chǎng)風(fēng)速和輸出功率的多尺度預(yù)測(cè)研究姓名：李輝申請(qǐng)學(xué)位級(jí)別：碩士專業(yè)：檢測(cè)技術(shù)及自動(dòng)化裝置指導(dǎo)教師：王曉蘭20100501風(fēng)電場(chǎng)風(fēng)速和輸l5功率的多尺度預(yù)測(cè)研究AbstractWindenergyasanonpollutingandrenewableenergyhasattractedgreatattentionovertheworldandbecomeoneoftherapiddevelopedformofpo

2、wergenerationThemainmethodofexploitationandutilizationofwindenergyiSthelargescalepowergenerationconnectedwithgridatpresentWindspeedandpowerpredictionisanessentialissueforwindfarmmaintenanceoptimalpowerflowbetweenpowernet

3、workandwindfarms，electricitymarketingbidding，powersystemscheduling，andenergystorageplanningandschedulingWindpowerasanintermittentenergyhasstrongrandomnessandiSdifficulttobecontrolled，andusuallythefluctuationrangeofspeeda

4、ndtheoutputpowerisverylargeBecauseofthesereasons，itisdifficulttocontrolthevoltage，reactivepowerandpeakpowerpresentingchallengesforsecurit5stabilityandschedulingofthepowergridWhenthewindpowerinstalledcapacityreachesacerta

5、inproportion，theeffectivewaytosolvethisproblemiStheaccuratepredictionoftheoutputpowerinwindfarmsWindpowerforecastingcanbedividedbythetimescales，whichincludeshorttermforecasting，medium—termforecastingandlongtermforecastin

6、gHoweverthepresuppositionoftheaccurateforecastofthewindpoweriSaccurateforecastofthewindspeedConsideringthecharacteristicsofwindspeed，ashorttermwindspeedforecastingmethodbasedonempiricalmodedecomposition(EMD)andleastsquar

7、esupportvectormachine(LSSVM)methodhasbeenproposed；amediumtermwindspeedforecastingmodeliSbasedonwaveletdecomposition(WnandLSSVMmethodhasbeenproposed；along—termwindempiricalmodedecomposition(EMD)andbeenproposedinthispapers

8、peedforecastingmodelisbasedonrecursiveleastsquare(RLS)methodhasAccordingtothemultiscalewindspeedforecastingvalues，consideringtheinfluencingfactorsandthelossesofthewindfarm，theshortterm，medium—termandlongtermoutputpowerfo

9、recastofthewindfarmcanbeobtainedKeywards：Windpowergeneration；Windspeedforecasting；Outputpowerforecasting；Leastsquaresupportvectormachine(tSSVM)；Wavelettransform(wa3；Empiricalmodedecomposition(EMD)；Recursiveleastsquare(RL