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@ARTICLE{Han:916236,
author = {Han, Chengyuan and Hilger, Hannes and Mix, Eva and
Böttcher, Philipp C. and Reyers, Mark and Beck, Christian
and Witthaut, Dirk and Gorjão, Leonardo Rydin},
title = {{C}omplexity and {P}ersistence of {P}rice {T}ime {S}eries
of the {E}uropean {E}lectricity {S}pot {M}arket},
journal = {PRX energy},
volume = {1},
number = {1},
address = {College Park, MD},
publisher = {American Physical Society},
reportid = {FZJ-2022-06037},
pages = {013002},
year = {2022},
abstract = {The large variability of renewable power sources is a
central challenge in the transition to a sustainable energy
system. Electricity markets are central for the coordination
of electric power generation. These markets rely evermore on
short-term trading to facilitate the balancing of power
generation and demand and to enable systems integration of
small producers. Electricity prices in these spot markets
show pronounced fluctuations, featuring extreme peaks as
well as occasional negative prices. In this article, we
analyze electricity price time series from the European
Power Exchange market, in particular the hourly day-ahead,
hourly intraday, and 15-min intraday market prices. We
quantify the fluctuations, correlations, and extreme events
and reveal different time scales in the dynamics of the
market. The short-term fluctuations show remarkably
different characteristics for time scales below and above 12
h. Fluctuations are strongly correlated and persistent below
12 h, which contributes to extreme price events and a strong
multifractal behavior. On longer time scales, they get
anticorrelated and price time series revert to their mean,
witnessed by a stark decrease of the Hurst coefficient after
12 h. The long-term behavior is strongly influenced by the
evolution of a large-scale weather pattern with a typical
time scale of four days. We elucidate this dependence in
detail using a classification into circulation weather
types. The separation in time scales enables a
superstatistical treatment, which confirms the
characteristic time scale of four days, and motivates the
use of q-Gaussian distributions as the best fit to the
empiric distribution of electricity prices.},
cin = {IEK-STE},
ddc = {530},
cid = {I:(DE-Juel1)IEK-STE-20101013},
pnm = {1112 - Societally Feasible Transformation Pathways
(POF4-111) / Verbundvorhaben CoNDyNet2: Kollektive
nichtlineare Dynamik komplexer Stromnetze (03EK3055B) /
HGF-ZT-I-0029 - Helmholtz UQ: Uncertainty Quantification -
from data to reliable knowledge (HGF-ZT-I-0029) / HDS LEE -
Helmholtz School for Data Science in Life, Earth and Energy
(HDS LEE) (HDS-LEE-20190612) /
Open-Access-Publikationskosten Forschungszentrum Jülich
(OAPKFZJ) (491111487)},
pid = {G:(DE-HGF)POF4-1112 / G:(BMBF)03EK3055B /
G:(DE-Ds200)HGF-ZT-I-0029 / G:(DE-Juel1)HDS-LEE-20190612 /
G:(GEPRIS)491111487},
typ = {PUB:(DE-HGF)16},
doi = {10.1103/PRXEnergy.1.013002},
url = {https://juser.fz-juelich.de/record/916236},
}