A two-stage short-term load forecasting approach using temperature daily profiles estimation
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
http://link.springer.com/content/pdf/10.1007/s00521-017-3324-x.pdf
Reference48 articles.
1. Ramanathan R, Engle R, Granger CW et al (1997) Short-run forecasts of electricity loads and peaks. Int J Forecast 13:161–174. https://doi.org/10.1016/S0169-2070(97)00015-0
2. Huang S-J, Shih K-R (2003) Short-term load forecasting via ARMA model identification including non-Gaussian process considerations. IEEE Trans Power Syst 18:673–679. https://doi.org/10.1109/TPWRS.2003.811010
3. Sargunaraj S, Gupta DS, Devi S (1997) Short-term load forecasting for demand side management. IEE Proc Gener Transm Distrib 144:68–74. https://doi.org/10.1049/ip-gtd:19970599
4. Zarchan P, Musoff H (2005) Fundamentals of Kalman filtering: a practical approach. American Institute of Aeronautics and Astronautics, Virginia
5. Kyriakides E, Polycarpou M (2007) Short term electric load forecasting: a tutorial. In: Trends in neural computation. Springer, Berlin, pp 391–418
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