Wind power prediction based on numerical and statistical models

Journal of Wind Engineering and Industrial Aerodynamics

Volumn 112, Issue , 2013, Pages 25-38

  Stathopoulos, Christos ^a   Kaperoni, Akrivi ^a   Galanis, George ^a,b   Kallos, George ^a  

^a UNIVERSITY OF ATHENS   (Greece)

^b HELLENIC NAVAL ACADEMY   (Greece)

Author keywords

Kalman filters; Numerical atmospheric models; Wind power

Indexed keywords

KALMAN FILTERS; NUMERICAL MODELS; PREDICTIVE ANALYTICS; WIND POWER;

ATMOSPHERIC MODEL; ATMOSPHERIC SYSTEMS; ENVIRONMENTAL CONDITIONS; POWER ESTIMATIONS; POWER PREDICTIONS; REAL-TIME APPLICATION; STATISTICAL PREDICTION MODEL; WIND POWER PREDICTIONS;

WEATHER FORECASTING;

EID: 84869875436     PISSN: 01676105     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jweia.2012.09.004     Document Type: Article

References (37)

1. Bremnes J.B. Probabilistic wind power forecasts using local quantile regression. Wind Energy 2004, 7(1):47-54.
2. Chatfied C. Time-series Forecasting 2000, Chapman & Hall/ CRC.
3. Christoffersen, P.F., 1998. Evaluating interval forecasts. International Economic Review, 39, 841-862.
4. Clancy R., Kaitala J., Zambreski L. The Fleet Numerical Oceanography Center Global Spectral Ocean Wave Model. Bulletin of the American Meteorological Society 1986, 67:498-512.
5. Cotton W.R., Pielke R.A., Walko R.L., Liston G.E., Tremback C.J., Jiang H., McAnelly R.L., Harrington J.Y., Nicholls M.E., Carrio G.G., McFadden J.P. RAMS 2001: current status and future directions. Meteor. Atmospheric Physics 2003, 82:5-29.
6. Crochet P. Adaptive Kalman filtering of 2-metre temperature and 10-metre wind-speed forecasts in Iceland. Meteorological Applications 2004, 11:173-187.
7. Eskridge R.E., Ku J.Y., Rao S.T., Porter P.S., Zurbenko I.G. Separating different scales of motion in time series of meteorological variables. Bulletin of the American Meteorological Society 1997, 78(7):1473-1483.
8. Galanis G., Anadranistakis M. A one dimensional Kalman filter for the correction of near surface temperature forecasts. Meteorological Applications 2002, 9:437-441.
9. Galanis G., Louka P., Katsafados P., Kallos G., Pytharoulis I. Applications of Kalman filters based on non-linear functions to numerical weather predictions. Annales Geophysicae 2006, 24:2451-2460.
10. Galanis G., Chu P.C., Kallos G. Statistical post processes for the improvement of the results of numerical wave models. A combination of Kolmogorov-Zurbenko and Kalman filters. Journal of Operational Oceanography 2011, 4(1):23-31.
11. Giebel, G., Landberg, L., Nielsen, T.S., 2001, The ZEPHYR project: The next generation prediction system. In: Proceedings of the 2001 European Wind Energy Conference, EWEC'01, Copenhagen, Denmark, June 2001, pp. 777-780.
12. Janjic Z.I. The step-mountain eta coordinate model: Further developments of the convection, viscous sublayer, and turbulence closure schemes. Monthly Weather Review 1994, 122:927-945.
13. Joensen A.K., Madsen H., Nielsen T.S. Non-Parametric Statistical Methods for Wind Power Prediction 1997, EWEC'97, Dublin, Denmark.
14. Joensen, A.K., Giebel, G., Landberg, L., Madsen, H., Nielsen, H.A., 1999, Model output statistics applied to wind power prediction. In: Wind Energy for the Next Millennium, European Wind Energy Conference, Nice, France, 1-5 March 1999, pp. 1177-1180.
15. Kallos G., 1997, The regional weather forecasting system SKIRON. In: Proceedings, Symposium on Regional Weather Prediction on Parallel Computer Environments, 15-17 October 1997, Athens, Greece, 9 pp.
16. Kallos, G., Lagouvardos, K., 1997: Atmospheric Modeling Simulations over the Eastern USA with the RAMS3b Model for the Summer 1995. Final Report to Electric Power Research Institute, Palo Alto, CA, 69 pp.
17. Kalman R.E. A new approach to linear filtering and prediction problems. Transactions on ASME Series D 1960, 82:35-45.
18. Kalman R.E., Bucy R.S. New results in linear filtering and prediction problems. Transactions on ASME Series D 1961, 83:95-108.
19. Kalnay E. Atmospheric Modeling, Data Assimilation and Predictability 2002, 341. Cambridge University Press.
20. Lagouvardos, K., Kotroni, V., Nickovic, S., Kallos, G., 1996. Evidence of a winter tropical storm over eastern Mediterranean: simulations with the Regional Atmospheric Modelling System (RAMS) and the ETA/NMC model. In: Proceedings of the 7th International Conference on Mesoscale Processes, 9-13 September, Reading, UK.
21. Landberg, L., 1994. Short-term Predictions of Local Wind Conditions. Ph.D. thesis, Riso National Laboratory, Denmark.
22. Landberg L.A. Mathematical look at a physical power prediction model. Wind Energy 1998, 1:23-28.
23. Madsen H. Models and Methods for Predicting Wind Power, Department of Mathematical Modelling 1996, Technical University of Denmark, Denmark.
24. Madsen, H.K., Sejling, T.S., Nielsen, H.Aa., U.S., 1995,Wind power prediction tool in control dispatch centres, ELSAM-report (ISBN 87-87090-25-2), 190 pp.
25. Mahrer Y., Pielke R.A. The effects of topography on sea and land breezes in a two-dimensional numerical model. Monthly Weather Review 1977, 105:1151-1162.
26. Mavromatidis E., Kallos G. An investigation of cold cloud formation with a 3-D model with explicit microphysics. Journal of Geophysical Research 2003, 108:4420-4441.
27. Nielsen, H. Aa., Nielsen, T.S., Madsen, H., 2004. Using quantile regression to extend an existing wind power forecasting system with probabilistic forecasts. In Proceedings of the 2004 European Wind Energy Conference, EWEC'04, Scientific Track, London, United Kingdom, pp. 34-38.
28. Nielsen, T.S., Madsen, H., 1997, Using Meteorological Forecasts in On-line Predictions of Wind Power, Technical Report IMM-REP-1997-31, Informatics and Mathematical Modelling, Technical University of Denmark, Lyngby, Denmark.
29. Nielsen T.S., Joensen A., Madsen H., Landberg L., Giebel G. A new reference for predicting wind power. Wind Energy 1999, 1:29-34.
30. Papadopoulos A., Katsafados P., Kallos.G. Regional weather forecasting for marine application. Global Atmosphere and Ocean System 2001, 8(2-3):219-237.
31. Pelland S., Galanis G., Kallos G. Solar and photovoltaic forecasting through post-processing of the global environmental multiscale numerical weather prediction model. Progress in Photovoltaics: Research and Applications 2011, 10.1002/pip.1180.
32. Persson A. Kalman filtering a new approach to adaptive statistical interpretation of numerical meteorological forecasts. ECMWF Newsletter 1990.
33. Rao S.T., Zurbenko I.G., Neagu R., Porter P.S., Ku J.Y., Henry R.F. Space and Time Scales in Ambient Ozone Data. Bulletin of the American Meteorological Society 1997, 78(10):2153-2166.
34. Silva A.P., Moulin L.S. Confidence intervals for neural network based short-term load forecasting. IEEE Transactions on Power Systems 2000, 15(4).
35. Wilks D. Statistical Methods in the Atmospheric Sciences 1995, Academic Press.
36. Willmott C., Robesonb Scott M., Matsuuraa Kenji Short communication. A refined index of model performance. International Journal of Climatology 2011.
37. Zurbenko, I.G.: The spectral Analysis of Time Series. North-Holland, 248 pp,1986.