电气技术2025，Vol.26Issue(4)：37-43,7.
基于马尔科夫残差修正-自回归滑动平均模型的负荷预测
Load forecasting based on Markov residual correction-autoregressive moving average model
摘要
Abstract
To improve the forcasting accuracy of short and medium term loads,this article proposes an autoregressive moving average model based on Markov residual correction.The autoregressive moving average model is used to predict the load and calculate the residual,and the Markov residual correction algorithm is used to correct the prediction results.The engineering case verification shows that the average absolute error of load forecasting obtained by the autoregressive moving average model is 13.67%.After Markov residual correction,the average absolute error of load forecasting is 6.912%,and the prediction accuracy is improved by 49.4%.It is concluded that the load forecasting model proposed in this article has certain significance for guiding industrial users in short and medium term loads forecasting.关键词
负荷预测/马尔科夫修正/自回归滑动平均/中短期特性Key words
load forecasting/Markov correction/autoregressive moving average/short and medium term characteristics引用本文复制引用
惠杰,刘博嘉,赵树生,胡全丹,曾先锋..基于马尔科夫残差修正-自回归滑动平均模型的负荷预测[J].电气技术,2025,26(4):37-43,7.基金项目
国家电网有限公司总部管理科技项目(5400-202426185A-1-1-ZN) （5400-202426185A-1-1-ZN）
