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ID:37392443
大小:6.71 MB
页数:110页
时间:2019-05-23
《基于知识发现的电力需求复合预测研究》由会员上传分享,免费在线阅读,更多相关内容在学术论文-天天文库。
1、华北电力大学(保定)博士学位论文基于知识发现的电力需求复合预测研究姓名:李春祥申请学位级别:博士专业:技术经济及管理指导教师:乞建勋;牛东晓20090501华北电力大学博士学位论文摘要AbstractPowerdemandforecastingisanimportantfoundationworkforpowersystemplanningandoperation.Itprovidesfoundationforpowercompaniestosetoutpurchaseofelectricityandpowerproductionplansandalsodispla
2、ysallimportantguaranteeforgridsecureandeconomicoperation.Powerdemandindicatorswillbesubjecttoallkindsoffactors.TheoriesandmethodsofknowledgediscoveryCanbeusedtominetheintrinsiclawofindicatorsvaryingandmutualrelationwithinfluencefactors.Theprimaryworkdoneinpowerdemandforecastinginthispa
3、perisasfollows.Firstly,acompoundforecastingmodelbasedonthreeindexquantitiesisresearchedandputforward.Threeindexquantitiesaretotalindexquantity,increasingindexquantityandindexgrowthrate.Convertingpredictionindicatorsequenceintothreeindexquantitiessequencesandproceedinganalysisandforecas
4、tingrespectivelyforthem,afterthatdosynthesistogetfinalforecastingresult,whichiscalledcompoundforecasting.Inthispaper,powerdemandisdividedintoquantityofelectricityforecastingandelectricloadprediction,andgreyassociationanalysisisappliedtoanalyzethemutualrelationbetweenquantityofelectrici
5、tyindicatorandinfluencefactors.Anachievementmodelofcompoundforecastingispresentedon,whichiscomprehensivemodelofquantityofelectricitycompoundforecasting.Itbenefitsfromcombinationforecastingidea.Atfirst,ananalytichierarchyprocessmodelisconstructedtoanalyzeandestimatethethreeindexquantiti
6、esrespectively,thenselectingoutoptimalforecastingmodelforeachindexquantity,inwhichevaluationcriterioninvolvemodelforecastingerror,fittingdegreeofmodel,experttrustdegreeofthemodelandconfidencelevelofthetrendofforecastingresults.Andthen,twosynthesismethodsareresearched,whicharesynthesism
7、ethodbasingforecastingefficiencydegreeandradialbasicfunctionneuralnetworksynthesizemodel,andcomparerelativemeritsofthem.Finally,throughinstanceanalysistocontrastdominantofthecomprehensivemodeltotraditionalmodels.Compoundforecastingmethodologyinapositiontoviatoanalyzeforecastedindices
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