Short Term Load Forecasting Using a New Time Series Modelling
Publish place: 14th International Power System Conference
Publish Year: 1378
Type: Conference paper
Language: English
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Document National Code:
PSC14_124
Index date: 21 September 2007
Short Term Load Forecasting Using a New Time Series Modelling abstract
This paper presents a new time series modelling for short term load forecasting, which can model the valuable experiences of the expert operators. This approach can accurately forecast the hourly loads of weekdays, as well as, of weekends and public holidays. It is shown that the proposed method can provide more accurate results than the conventional techniques, such as artificial neural networks or Box-Jenkins models. In addition to hourly loads, daily peak load is an important problem for dispatching centers of a power network. Most of the common load forecasting approaches do not consider this problem. It is shown that the proposed method can exactly forecast the daily peak load of a power system. Obtained results from extensive testing on the Iran's power system network confirm the validity of the developed approach.
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Short Term Load Forecasting Using a New Time Series Modelling authors
NIMA AMJADY
Department of Electrical Engineering, Semnan University Semnan, Wan
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