2010 IEEE 11th International Conference on Probabilistic Methods Applied to Power Systems 2010
DOI: 10.1109/pmaps.2010.5528983
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Very short-term probabilistic wind power forecasting based on Markov chain models

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Cited by 68 publications
(40 citation statements)
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“…The Markov chain model takes into account the time correlation and has been frequently used for the generation of synthetic wind speed series [17]. We adopt this approach in our study.…”
Section: Wind Speedmentioning
confidence: 99%
“…The Markov chain model takes into account the time correlation and has been frequently used for the generation of synthetic wind speed series [17]. We adopt this approach in our study.…”
Section: Wind Speedmentioning
confidence: 99%
“…ar a [11] has introduced a new proposal to involve uncertainties in Fuzzy Markov Chains by using Interval Type-2 Fuzzy Sets (IT2 FS). Carpinone et al [12] have proposed the method which is based on the use of discrete time Markov chain models of a proper order and also developed wind power time series analysis. Adnan and Islam [13] have presented a technique for voice correction and interpolation using Markov chain detection.…”
Section: Related Workmentioning
confidence: 99%
“…In (Carpinone et al, 2010) they are here used to develop a probabilistic forecasting method that allows to provide estimates of future wind power generation, not only as point forecasts, but also as estimate of the probability distributions associated to the point forecasts.…”
Section: Very Short Term Wind Forecastmentioning
confidence: 99%