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ID:23800595
大小:2.17 MB
页数:62页
时间:2018-11-10
《含多风电场的电力系统随机优化调度研究》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、进粒子群算法进行计算。通过以荷兰地区两个风场为例,表明本文构建的Gumbel.Copula分布可以更好地刻画多个风电场出力的联合分布,提高对风电场出力的估算精度,并有效地描述其尾部相关性。基于IEEE.9节点系统检验表明,本文提出的随机优化调度模型及其转化方法,提高了模型的求解速率,并提高了系统调度计划的可行性、灵活性、鲁棒性,从而为大规模风电并网系统的优化调度提供了理论基础,更为系统调度员在信息不确定的情况下迅速作出合理的优化调度方案提供了有力的工具。关键词:相关性;CopuIa;机会约束规划;抽样
2、平均近似法;粒子群算法IIABSTRACTInordertosolvetheproblemofenergyshortageandenvironmentalpollution,renewableenergygenerationiswidelyconcerned.Windbecomesanimportantformofrenewableenergygenerationduetoitsnon—pollution,renewablityandotherexcellentfeatures.However,unl
3、iketraditionalenergygeneration,therandomnessandintermittenceofthewindspeed,makingwindpoweralsohasarandom,non.schedulingfeature,whichbringsenormousdifficultiesandchallengestothesafeandeconomicoperationofpowersystem,whenlarge·scalewindpowerincorporatedint
4、opowergrid.Therefore,studyingoptimalschedulingproblemofpowersystemswithwindpowerisofgreattheoreticalsignificanceandapplicationvalue.Powerconvertedbywindmustbeincommandandcontrolofthedispatchingsvstemwithsuchlinksastransmission,transformation,distributio
5、nanduse,uItimatelyyoucanfeedtotheusers.However,windpowerdependsentirelyonthewindconditions,presentstrongrandomicity,intermittent,periodicityandvolatility.Alongwiththeincreaseofwindturbinescapacityinstalled,theexistingtechnicallevelalsounabletoaccurately
6、forecastthewindpower,whichmakesthewindpowerschedulingmoredifficult.Intheoptimalschedulingofpowersystemwithwindpower,itisnecessarytocalculatetheProbabilityDistributionofwindpowerfromwindfarm,inordertoassessthemaximumwindpowerthatcanbeincorporatedintothes
7、ystem,SOthattoachievesecurityandeconomicdispatchofthepowersvetem.However,withtheconstructionofSmartGrid,large‘scalewindpowerconnectedtopowergrid,andwindatdifferentlocationsmaycomefromthesameorigin.SOthattheirwindpowerhasasignificantdegreeofcorrelation.S
8、othatoutputsfrommultiplewindfarescharacteristicsisdifferentfromsinglewindfarm,thereforeitisnecessarytoanalysisthejointdistributionforoutputsfrommultiplewindfams.Inviewofthis,thispaperusesWeibulldistributionfunctiontocharacterizet
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