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Short-term dynamics of day-ahead and intraday electricity prices

Short-term dynamics of day-ahead and intraday electricity prices Since the liberalization of electricity markets in the European Union, prices are subject to market dynamics. Hence, understanding the short-term drivers of electricity prices is of major interest to electricity companies and policymakers. Accordingly, this paper aims to study movements of prices in the combined German and Austrian electricity market.Design/methodology/approachThis paper estimates an autoregressive model with exogenous variables (ARX) in a two-step procedure. In the first step, both time series, which inherently feature seasonality, are de-seasonalized, and in the second step, the influence of all model variables on the two dependent variables, i.e. the day-ahead and intraday European Power Energy Exchange prices, is measured.FindingsThe results reveal that the short-term market is largely driven by seasonality, consumer demand and short-term feed-ins from renewable energy sources. As a contribution to the existing body of literature, this paper specifically compares the price movements in day-ahead and intraday markets. In intraday markets, the influences of renewable energies are much stronger than in day-ahead markets, i.e. by 24.12 per cent for wind and 116.82 per cent for solar infeeds.Originality/valueKnowledge on the price setting mechanism in the intraday market is particularly scarce. This paper contributes to existing research on this topic by deriving drivers in the intraday market and then contrasting them to the day-ahead market. A more thorough understanding is especially crucial for all stakeholders, who can use this knowledge to optimize their bidding strategies. Furthermore, the findings suggest policy implications for a more stable and efficient electricity market. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Energy Sector Management Emerald Publishing

Short-term dynamics of day-ahead and intraday electricity prices

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References (37)

Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
1750-6220
DOI
10.1108/ijesm-05-2016-0009
Publisher site
See Article on Publisher Site

Abstract

Since the liberalization of electricity markets in the European Union, prices are subject to market dynamics. Hence, understanding the short-term drivers of electricity prices is of major interest to electricity companies and policymakers. Accordingly, this paper aims to study movements of prices in the combined German and Austrian electricity market.Design/methodology/approachThis paper estimates an autoregressive model with exogenous variables (ARX) in a two-step procedure. In the first step, both time series, which inherently feature seasonality, are de-seasonalized, and in the second step, the influence of all model variables on the two dependent variables, i.e. the day-ahead and intraday European Power Energy Exchange prices, is measured.FindingsThe results reveal that the short-term market is largely driven by seasonality, consumer demand and short-term feed-ins from renewable energy sources. As a contribution to the existing body of literature, this paper specifically compares the price movements in day-ahead and intraday markets. In intraday markets, the influences of renewable energies are much stronger than in day-ahead markets, i.e. by 24.12 per cent for wind and 116.82 per cent for solar infeeds.Originality/valueKnowledge on the price setting mechanism in the intraday market is particularly scarce. This paper contributes to existing research on this topic by deriving drivers in the intraday market and then contrasting them to the day-ahead market. A more thorough understanding is especially crucial for all stakeholders, who can use this knowledge to optimize their bidding strategies. Furthermore, the findings suggest policy implications for a more stable and efficient electricity market.

Journal

International Journal of Energy Sector ManagementEmerald Publishing

Published: Sep 18, 2017

Keywords: Renewable energies; Pricing; Electricity; Modelling; Time series analysis; Autoregressive; External drivers; Weather influence

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