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《基于改進(jìn)多目標(biāo)粒子群算法含風(fēng)電場(chǎng)電力系統(tǒng)優(yōu)化調(diào)度》由會(huì)員上傳分享,免費(fèi)在線閱讀,更多相關(guān)內(nèi)容在行業(yè)資料-天天文庫(kù)。
1、第41卷第17期電力系統(tǒng)保護(hù)與控制V_01.41N0.172013年9月1日PowerSystemProtectionandControlSep.1,2013基于改進(jìn)多目標(biāo)粒子群算法的含風(fēng)電場(chǎng)電力系統(tǒng)優(yōu)化調(diào)度盧錦玲,苗雨陽(yáng),張成相,任惠(1.華北電力大學(xué)電氣與電子工程學(xué)院,河北保定071003;2.國(guó)網(wǎng)河北省電力公司正定縣供電分公司河北正定050800;3.山東電力集團(tuán)公司臨沂供電公司,山東I臨沂276000)摘要:由于風(fēng)電具有隨機(jī)性和波動(dòng)性的特點(diǎn),常規(guī)電力系統(tǒng)分析、調(diào)度及控制方式受到了新的挑戰(zhàn)。深入研究了含風(fēng)電場(chǎng)的電力系統(tǒng)優(yōu)化調(diào)度問(wèn)題,建立了基于多目標(biāo)粒
2、子群算法的調(diào)度模型,在該模型中考慮發(fā)電成本、污染氣體排放量及風(fēng)電場(chǎng)輸出功率短期波動(dòng)引起的系統(tǒng)運(yùn)行風(fēng)險(xiǎn),在約束條件中加入了正負(fù)旋轉(zhuǎn)備用容量,從而減小了風(fēng)電波動(dòng)和預(yù)測(cè)誤差對(duì)系統(tǒng)的影響程度。算法設(shè)計(jì)上,通過(guò)引入遺傳算子對(duì)多目標(biāo)粒子群算法搜索機(jī)組組合的能力進(jìn)行改進(jìn),提高了該模型的全局尋優(yōu)能力。10機(jī)系統(tǒng)算例結(jié)果分析表明,所提方法正確有效,且能夠減少尋優(yōu)過(guò)程中不可行解、解決各優(yōu)化目標(biāo)之間的沖突性,使所有目標(biāo)函數(shù)盡可能達(dá)到最優(yōu)。關(guān)鍵詞:風(fēng)電;優(yōu)化調(diào)度;遺傳算子;多目標(biāo)粒子群Powersystemoptimaldispatchconsideringwindfarmsba
3、sedonimprovedmulti-objectiveparticleswarmalgorithmLUJin·ling,MIAOYu—yang,ZHANGCheng—xiang,RENHui(1.SchoolofElectricalandElectronicEngineering,NorthChinaElectricPowerUniversity,Baoding071003,China;2.HebeiZhengdingPowerSupplyCompany,StateGridElectricPowerCompany,Zhengding050800,Chin
4、a;3.LinyiPowerCompany,ShangdongElectricPowerGroupCorporation,Linyi276000,China)Abstract:Windpowerhasthecharacteristicsofrandomnessandvolatility,SOconventionalpowersystemanalysis,dispatchandcontrolmeetnewchallenges.Thispaperstudiesthetopicofpowersystemoptimaldispatchincludingwindfa
5、rmsindetail,establishesadispatchmodelbasedonmulti-objectiveparticleswarmalgorithm.Thismodelconsiderstherunningriskcausedbycostofpowergeneration,emissionsofpollutinggases,andshort-termfluctuationsofwindfarmoutputpower,addsreservepositiveandnegativerotationcapacityintoconstraints,th
6、usreducestheimpactofpowerfluctuationsandpredictionerroronthesystem.Thesearchingunitabilityofmulti-targetparticleswarmalgorithmismodifiedbymixinggeneticoperatorsinalgorithmdesign.Thecapabilityofglobaloptimizationofthemodelissharplyimproved.Thesimulationresultoften—generatorsystemsh
7、owsthattheproposedmethodiScorrectandeffective,anditcannotonlyreducetheirifeasiblesolutionsintheoptimizationprocess.butalsoresolvetheconflictbetweenthevariousoptimizationtargets,ensuringalltheobjectivefunctionasoptimalaspossible.ThisworkissupportedbyNationalNaturalScienceFoundation
8、ofChinafNo.51107140).Keywords:win