Journal Article

FZJ-2018-04028

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Modeling long correlation times using additive binary Markov chains: Applications to wind generation time series

Weber, J.FZJ* ; Zachow, C. ; Witthaut, D. (Corresponding author)FZJ*

2018
Inst. Woodbury, NY

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Please use a persistent id in citations: http://hdl.handle.net/2128/19618  doi:10.1103/PhysRevE.97.032138

Abstract: Wind power generation exhibits a strong temporal variability, which is crucial for system integration in highly renewable power systems. Different methods exist to simulate wind power generation but they often cannot represent the crucial temporal fluctuations properly. We apply the concept of additive binary Markov chains to model a wind generation time series consisting of two states: periods of high and low wind generation. The only input parameter for this model is the empirical autocorrelation function. The two-state model is readily extended to stochastically reproduce the actual generation per period. To evaluate the additive binary Markov chain method, we introduce a coarse model of the electric power system to derive backup and storage needs. We find that the temporal correlations of wind power generation, the backup need as a function of the storage capacity, and the resting time distribution of high and low wind events for different shares of wind generation can be reconstructed.

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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)
3. CoNDyNet - Kollektive Nichtlineare Dynamik Komplexer Stromnetze (PIK_082017) (PIK_082017)

Appears in the scientific report 2018

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Database coverage:
; ; ; Current Contents - Physical, Chemical and Earth Sciences ; Ebsco Academic Search ; 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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