电力系统短期负荷预计——时间序列的分解集合算法  

Short Term Load Forecasting: New Decomposition Aggregation Algorithm with the Function of Time Series Adjustment

作　　者：高晓萍[1] 单渊达[1] 阎欣[1] 

机构地区：[1]东南大学电气工程系

出　　处：《东南大学学报（自然科学版）》1997年第3期136-140,共5页Journal of Southeast University：Natural Science Edition

摘　　要：电力系统短期负荷预计——时间序列的分解集合算法高晓萍单渊达阎欣（东南大学电气工程系，南京２１００１８）系统发电出力必须随时紧跟系统负荷的变化，这是对电力系统运行的基本要求．但负荷是随机变化的，特别是在不长的时段里，对负荷进行变化幅度很大时，负荷精确...In order to efficiently predict the variable state of the system load as accurately as possible, a new kind of decomposition aggregation algorithm with the function of time series adjustment is suggested. It maintains all the advantages of ARIMA model and avoid disaduantages like the long sampling time and relatively low forecasting accuracy. Simulation results show that the forecasting accuracy is greatly improved.

关 键 词：电力系统 负荷预测 短期负荷预测 时间序列 

分 类 号：TM715[电气工程—电力系统及自动化]