Universität zu Köln

Weber, Juliane, Zachow, Christopher and Witthaut, Dirk ORCID: 0000-0002-3623-5341 (2018). Modeling long correlation times using additive binary Markov chains: Applications to wind generation time series. Phys. Rev. E, 97 (3). COLLEGE PK: AMER PHYSICAL SOC. ISSN 2470-0053

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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.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Weber, Juliane UNSPECIFIED UNSPECIFIED UNSPECIFIED Zachow, Christopher UNSPECIFIED UNSPECIFIED UNSPECIFIED Witthaut, Dirk UNSPECIFIED orcid.org/0000-0002-3623-5341 UNSPECIFIED
URN:	urn:nbn:de:hbz:38-192376
DOI:	10.1103/PhysRevE.97.032138
Journal or Publication Title:	Phys. Rev. E
Volume:	97
Number:	3
Date:	2018
Publisher:	AMER PHYSICAL SOC
Place of Publication:	COLLEGE PK
ISSN:	2470-0053
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language RENEWABLE ELECTRICITY SYSTEMS; EUROPEAN POWER-SYSTEM; MEMORY FUNCTIONS; DEGREES-C; STORAGE; OUTPUT; REANALYSIS; WEATHER; SPEEDS Multiple languages Physics, Fluids & Plasmas; Physics, Mathematical Multiple languages
Refereed:	Yes
URI:	http://kups.ub.uni-koeln.de/id/eprint/19237