Global energy forecasting competition 2012

International Journal of Forecasting

Volumn 30, Issue 2, 2014, Pages 357-363

  Hong, Tao ^a   Pinson, Pierre ^b   Fan, Shu ^c  

^a SAS INSTITUTE INC   (United States)

^b TECHNICAL UNIVERSITY OF DENMARK   (Denmark)

^c MONASH UNIVERSITY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84897613657     PISSN: 01692070     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ijforecast.2013.07.001     Document Type: Editorial

References (9)

1. Athanasopoulos G., Hyndman R., Song H., Wu D. The tourism forecasting competition. International Journal of Forecasting 2011, 27(3):822-844.
2. Brown B.G., Katz R.W., Murphy A.H. Time series models to simulate and forecast wind speed and wind power. Journal of Climate and Applied Meteorology 1984, 23:1184-1195.
3. Giebel G., Brownsword R., Kariniotakis G., Denhard M., Draxl C. The state-of-the-art in short-term prediction of wind power: a literature overview (2nd ed.) 2011, Tech. Rep. EU project ANEMOS.plus. Available at:http://orbit.dtu.dk.
4. Hong, T. (2010). Short term electric load forecasting. North Carolina State University.
5. Hyndman R.J., Fan S. Density forecasting for long-term peak electricity demand. IEEE Transactions on Power Systems 2009, 25(2):1142-1153.
6. Matos M.A., Bessa R.J. Setting the operating reserve using probabilistic wind power forecasts. IEEE Transactions on Power Systems 2011, 26:594-603.
7. Monteiro C., Bessa R., Miranda V., Botterud A., Wang J., Conzelmann G. Wind power forecasting: state of the art 2009 2009, Tech. Rep., Argonne National Laboratory, Decision and Information Sciences Division, ANL/DIS-10-1.
8. Pinson P., Chevallier C., Kariniotakis G.N. Trading wind generation from short-term probabilistic forecasts of wind power. IEEE Transactions on Power Systems 2007, 22:1148-1156.
9. Tuohy A., Meibom P., Denny E., O'Malley M. Unit commitment for systems with significant wind penetration. IEEE Transactions on Power Systems 2009, 24:592-601.