曲阜师范大学学报（自然科学版）2026，Vol.52Issue(2)：74-78,5.DOI:10.3969/j.issn.1001-5337.202502.019
基于ARIMA模型的V2G电能质量缺失数据预测
V2G power quality loss data prediction based on improved ARIMA
摘要
Abstract
To address the problem of missing power quality data in smart grids,this study proposes a prediction method based on truncated singular value decomposition(SVD)and the autoregressive integrated moving average(ARIMA)model.The proposed approach represents power quality data from different time slices as a matrix and performs missing data prediction at the matrix level.Experimental re-sults demonstrate that,compared to other classical missing data prediction methods,the proposed method not only achieves high prediction accuracy but also significantly reduces computational overhead.关键词
智能电网/电能质量/缺失数据填补/ARIMAKey words
smart grid/power quality/missing data imputation/ARIMA分类
信息技术与安全科学引用本文复制引用
孙华玲,马飞,闫超..基于ARIMA模型的V2G电能质量缺失数据预测[J].曲阜师范大学学报（自然科学版）,2026,52(2):74-78,5.基金项目
山东省重点研发计划(2025CXGC010113). （2025CXGC010113）
