24-h electrical load data - a sequential or partitioned time series?

被引:35
作者
Fay, D [1 ]
Ringwood, JV
Condon, M
Kelly, M
机构
[1] Dublin City Univ, Dublin 9, Ireland
[2] NUI Maynooth, Maynooth, Kildare, Ireland
[3] Elect Supply Board, Dublin 2, Ireland
关键词
load forecasting; time series analysis; multi-layer perceptrons; principal component analysis;
D O I
10.1016/S0925-2312(03)00390-4
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Variations in electrical load are, among other things, hour of the day dependent, introducing a dilemma for the forecaster: whether to partition the data and use a separate model for each hour of the day (the parallel approach), or use a single model (the sequential approach). This paper examines which approach is appropriate for forecasting hourly electrical load in Ireland. It is found that, with the exception of some hours of the day, the sequential approach is superior. The final solution however, uses a combination of linear sequential and parallel neural models in a multi-time scale formulation. (C) 2003 Elsevier B.V. All rights reserved.
引用
收藏
页码:469 / 498
页数:30
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