基于BP-ANN融合算法的短期電力負荷預(yù)測方法

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中圖分類號：TM732 文獻標志碼：A 文章編號：2095-2945（2025）20-0082-04

Abstract：As the scaleandcomplexityof the power systemcontinues toexpand，accurateshort-term power load forecasting hasbecomecrucialtothestableoperation，economicdispatchandenergymanagementof thepowersystem.Aimingatthe possiblelimitationsofBP-ANNalgorithminpredictingshort-termpowerloaddatasuchasasytofallintolocaloptimization andslowconvergencespeed，thispaperproposesashort-termpowerloadforecastingmethodbasedonBP-ANNfusionalgorith. ItisverifiedthroughexamplesthatthecorrelationcoeffientsofGA-BP-ANNandPSO-BP-ANNpredictionmodelsarehigher thanthoseofBP-ANN predictionmodel，andthepredictionerorsare lowerthan thoseofBP-ANNpredictionmodel.The resultsshowthat Short-termpowerloadforecasting methodsbasedonBP-ANNfusionalgorithmhavegoodapplicationprospects and can provide strong technical support for eficient operation and reasonable planning of power systems.

Keywords： particleswarm optimizationalgorithm; power load forecasting; BP-ANN; fusion algorithm; GA-BP-ANN

隨著社會的快速發(fā)展，目前各行各業(yè)用電需求不斷攀升，如工業(yè)生產(chǎn)規(guī)模擴大、居民生活電氣化程度越來越高（各類電器增多等），使得用電負荷呈現(xiàn)快速增長的態(tài)勢。（剩余5262字）