Journal Article

FZJ-2015-03109

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png A new Markov-chain-related statistical approach for modelling synthetic wind power time series

Pesch, T. (Corresponding Author)FZJ* ; Schröders, S. ; Allelein, H. J.FZJ* ; Hake, J. F.FZJ*

2015
Dt. Physikalische Ges. [Bad Honnef]

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Please use a persistent id in citations: http://hdl.handle.net/2128/8623  doi:10.1088/1367-2630/17/5/055001

Abstract: 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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Contributing Institute(s):

1. Systemforschung und Technologische Entwicklung (IEK-STE)

Research Program(s):

1. 153 - Assessment of Energy Systems – Addressing Issues of Energy Efficiency and Energy Security (POF3-153) (POF3-153)
2. VH-NG-1025 - Helmholtz Young Investigators Group "Efficiency, Emergence and Economics of future supply networks" (VH-NG-1025_20112014) (VH-NG-1025_20112014)

Appears in the scientific report 2015

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Database coverage:
; ; ; ; Current Contents - Physical, Chemical and Earth Sciences ; IF < 5 ; JCR ; SCOPUS ; Science Citation Index ; Science Citation Index Expanded ; Thomson Reuters Master Journal List ; Web of Science Core Collection

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