基于混沌理论的风电功率超短期多步预测的误差分析_杨茂

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1、------------------------------------------------------------------------------------------------基于混沌理论的风电功率超短期多步预测的误差分析_杨茂第45卷第4期2017年2月16日DOI:10.7667/PSPC160395电力系统保护与控制PowerSystemProtectionandControlVol.45No.4Feb.16,2017基于混沌理论的风电功率超短期多步预测的误差分析杨茂，刘红柳，季本明(东北电力大

2、学电气工程学院，吉林吉林132012)摘要：风电功率对电力系统的安全运行、合理调度等方面有不可忽视的影响。掌握风电功率预测误差的分布特性，对风资源的大规模开发利用具有重要意义。利用两种混沌预测方法进行风电功率超短期的预测。并且以东北某风电场的实测风电功率数据为例，分析了超短期风电功率预测误差的概率分布、预测误差与超前预测步数之间的关系、预测误差与风电场出力情况之间的关系以及预测误差与装机容量之间的关系。该研究为揭示风电功率超短期多步预测的误差构成及修正奠定了理论基础。关键词：风电功率；预测；误差；概率分布；混沌理论A

3、nalysisofultra-short-termpredictionerrorofwindpowerbasedonchaostheory——————————————————————————————————————------------------------------------------------------------------------------------------------YANGMao,LIUHongliu,JIBenming(SchoolofElectricalEngineering

4、,NortheastDianliUniversity,Jilin132012,China)Abstract:Windpowerhasabiginfluenceonthesafeoperationandrationalmanagementofelectricpowersystem.Itisusefultograspthedistributioncharacteristicsofwindpowerpredictionerrorforthelarge-scaledevelopmentandutilizationofwind

5、energy.Twochaosultra-short-termforecastingmethodsareusedtopredictwindpower.Thewindpowerdataofanortheastwindfarmistakenasanexampletoanalyzetheprobabilitydistributionofsingle-steppredictionerrorofwindpower,therelationshipbetweenthewindpowerpredictionerrorandthepr

6、edictionstepnumber,therelationshipbetweenthewindpowerpredictionerrorandthewindfarmoutputpower,andtherelationshipbetweenthewindpowerpredictionerrorandtheinstalledcapacity.Itlaysthetheoreticalfoundationfortheanalysisofthecompositionandcorrectionofthewindpowerpred

7、ictionerror.——————————————————————————————————————------------------------------------------------------------------------------------------------ThisworkissupportedbyNationalKeyBasicResearchProgramofChina(973Program)(No.2013CB228201),NationalNaturalScienceFoun

8、dationofChina(No.51307017),ScienceandTechnologyDevelopmentProgramofJilinProvince(No.20140520129JH),andSpecialProgramofIndustrialTechnologyResearchandDevelopmentofJilinProvin