Nonlinear Models for Short-time Load Forecasting
β Scribed by Philippe Lauret; Mathieu David; Didier Calogine
- Book ID
- 116426010
- Publisher
- Elsevier
- Year
- 2012
- Weight
- 412 KB
- Volume
- 14
- Category
- Article
- ISSN
- 1876-6102
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This paper proposes one-day-ahead load forecasting using daily updated weekday load models and weekly updated bias models for everyday-of-the-week loads. The load characteristics are examined first for actual data from Kyushu Electric Power Company and weather stations in Kyushu throughout 1982. The
## Abstract Forecasting for nonlinear time series is an important topic in time series analysis. Existing numerical algorithms for multiβstepβahead forecasting ignore accuracy checking, alternative Monte Carlo methods are also computationally very demanding and their accuracy is difficult to contro