Articles | Volume 5, issue 4
Wind Energ. Sci., 5, 1731–1741, 2020
Wind Energ. Sci., 5, 1731–1741, 2020
Research article
16 Dec 2020
Research article | 16 Dec 2020

A simple methodology to detect and quantify wind power ramps

Bedassa R. Cheneka et al.

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Cited articles

Bianco, L., Djalalova, I. V., Wilczak, J. M., Cline, J., Calvert, S., Konopleva-Akish, E., Finley, C., and Freedman, J.: A wind energy ramp tool and metric for measuring the skill of numerical weather prediction models, Weather Forecast., 31, 1137–1156, 2016. a, b, c
Borgnat, P. and Flandrin, P.: Stationarization via surrogates, J. Stat. Mech.: Theory and Experiment, 2009, P01001,, 2009. a
Borgnat, P., Flandrin, P., Honeine, P., Richard, C., and Xiao, J.: Testing stationarity with surrogates: A time-frequency approach, IEEE Transactions on Signal Processing, 58, 3459–3470, 2010. a
Bossavy, A., Girard, R., and Kariniotakis, G.: Forecasting Uncertainty Related to Ramps of Wind Power Production, European Wind Energy Conference and Exhibition 2010, EWEC 2010, April 2010, Warsaw, Poland, 9 pp., ISBN 9781617823107.Hal-00765885f, 2010. a, b
Coughlin, K., Murthi, A., and Eto, J.: Multi-scale analysis of wind power and load time series data, Renew. Energ., 68, 494–504, 2014. a
Short summary
Wind power ramps have important characteristics for the planning and integration of wind power production into electricity. We present a new and simple algorithm that detects wind power ramp characteristics. The algorithm classifies wind power production into ramp-ups, ramp-downs, and no-ramps; and it can detect wind power ramp characteristics that show a temporal increasing (decreasing) power capacity.