基于BP-ANN融合算法的短期电力负荷预测方法

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中图分类号：TM732 文献标志码：A 文章编号：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

随着社会的快速发展，目前各行各业用电需求不断攀升，如工业生产规模扩大、居民生活电气化程度越来越高（各类电器增多等），使得用电负荷呈现快速增长的态势。（剩余5262字）