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| Hauptseite > Publikationsdatenbank > A new Markov-chain-related statistical approach for modelling synthetic wind power time series > print |
| Hauptseite > Publikationsdatenbank > A new Markov-chain-related statistical approach for modelling synthetic wind power time series > print |
| 001 | 190181 | ||
| 005 | 20220930130042.0 | ||
| 024 | 7 | _ | |a 10.1088/1367-2630/17/5/055001 |2 doi |
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| 100 | 1 | _ | |a Pesch, T. |0 P:(DE-Juel1)142000 |b 0 |e Corresponding Author |
| 245 | _ | _ | |a A new Markov-chain-related statistical approach for modelling synthetic wind power time series |
| 260 | _ | _ | |a [Bad Honnef] |c 2015 |b Dt. Physikalische Ges. |
| 336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1432123307_11927 |2 PUB:(DE-HGF) |
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| 336 | 7 | _ | |a article |2 DRIVER |
| 520 | _ | _ | |a The integration of rising shares of volatile wind power in the generation mix is a major challenge forthe future energy system. To address the uncertainties involved in wind power generation, modelsanalysing and simulating the stochastic nature of this energy source are becoming increasinglyimportant. One statistical approach that has been frequently used in the literature is the Markov chainapproach. Recently, the method was identified as being of limited use for generating wind time serieswith time steps shorter than 15–40 min as it is not capable of reproducing the autocorrelationcharacteristics accurately. This paper presents a new Markov-chain-related statistical approach that iscapable of solving this problem by introducing a variable second lag. Furthermore, additional featuresare presented that allow for the further adjustment of the generated synthetic time series. Theinfluences of the model parameter settings are examined by meaningful parameter variations. Thesuitability of the approach is demonstrated by an application analysis with the example of the windfeed-in in Germany. It shows that—in contrast to conventional Markov chain approaches—thegenerated synthetic time series do not systematically underestimate the required storage capacity tobalance wind power fluctuation. |
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| 770 | _ | _ | |a Focus on Networks, Energy and the Economy |
| 773 | _ | _ | |a 10.1088/1367-2630/17/5/055001 |g Vol. 17, no. 5, p. 055001 - |0 PERI:(DE-600)1464444-7 |n 5 |p 055001 |t New journal of physics |v 17 |y 2015 |x 1367-2630 |
| 856 | 4 | _ | |u dx.doi.org/10.1088/1367-2630/17/5/055001 |
| 856 | 4 | _ | |u https://juser.fz-juelich.de/record/190181/files/1367-2630_17_5_055001.pdf |y OpenAccess |
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