Prediction of extreme price occurrences in the German day-ahead electricity market
Journal
Quantitative finance
ISSN
1469-7688
ISSN-Digital
1469-7696
Type
journal article
Date Issued
2016-09-14
Author(s)
Hagfors, Lars Ivar
;
Kamperud, Hilde Hørthe
;
;
Prokopczuk, Marcel
;
Sator, Alma
;
Westgaard, Sjur
Abstract
Understanding the mechanisms that drive extreme negative and positive prices in day-ahead electricity prices is crucial for managing risk and market design. In this paper, we consider the problem of understanding how fundamental drivers impact the probability of extreme price occurrences in the German day-ahead electricity market. We develop models using fundamental variables to predict the probability of extreme prices. The dynamics of negative prices and positive price spikes differ greatly. Positive spikes are related to high demand, low supply and high prices the previous days, and mainly occur during the morning and afternoon peak hours. Negative prices occur mainly during the night and are closely related to low demand combined with high wind production levels. Furthermore, we do a closer analysis of how renewable energy sources, hereby photovoltaic and wind power, impact the probability of negative prices and positive spikes. The models confirm that extremely high and negative prices have different drivers, and that wind power is particularly important in relation to negative price occurrences. The models capture the main drivers of both positive and negative extreme price occurrences and perform well with respect to accurately forecasting the probability with high levels of confidence. Our results suggest that probability models are well suited to aid in risk management for market participants in day-ahead
Language
English
HSG Classification
contribution to scientific community
Publisher
Taylor & Francis
Publisher place
London
Volume
16
Number
12
Subject(s)
Eprints ID
248680
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EEX_Spike_Predicton_April_30_2016.pdf
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Format
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