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Frequent Auctions for Intraday Electricity Markets

Christoph Graf, Thomas Kuppelwieser, and David Wozabal

Year: 2024
Volume: Volume 45
Number: Number 1
DOI: 10.5547/01956574.45.1.cgra
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Abstract:
Continuous trading is currently becoming the standard for intraday electricity markets. In this paper, we propose frequent auctions as a viable alternative. We argue that batching orders in auctions potentially leads to lower liquidity cost, more reliable, less noisy price signals, and allows for better alignment of market outcomes with the technical realities of the transmission grid. In an empirical study, we compare the German continuous intraday market with counterfactual outcomes from frequent auctions. We find that traded volumes tend to be higher for continuous trading; however, the auction market benefits from lower liquidity costs and less noisy price signals. Furthermore, we critically discuss the suitability of continuous trading in the presence of network constraints and technical restrictions of conventional units. Taken together these findings suggest that in sparsely traded intraday markets, pooling orders in frequent auctions may be beneficial.



Simulation-based Forecasting for Intraday Power Markets: Modelling Fundamental Drivers for Location, Shape and Scale of the Price Distribution

Simon Hirsch and Florian Ziel

Year: 2024
Volume: Volume 45
Number: Number 3
DOI: 10.5547/01956574.45.3.shir
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Abstract:
During the last years, European intraday power markets have gained importance for balancing forecast errors due to the rising volumes of intermittent renewable generation. However, compared to day-ahead markets, the drivers for the intraday price process are still sparsely researched. In this paper, we propose a modelling strategy for the location, shape and scale parameters of the return distribution in intraday markets, based on fundamental variables. We consider wind and solar forecasts and their intraday updates , outages, price information and a novel measure for the shape of the merit-order, derived from spot auction curves as explanatory variables. We validate our modelling by simulating price paths and compare the probabilistic forecasting performance of our model to benchmark models in a forecasting study for the German market. The approach yields significant improvements in the forecasting performance, especially in the tails of the distribution. At the same time, we are able to derive the contribution of the driving variables. We find that, apart from the first lag of the price changes, none of our fundamental variables have explanatory power for the expected value of the intraday returns. This implies weak-form market efficiency as renewable forecast changes and outage information seems to be priced in by the market. We find that the volatility is driven by the merit-order regime, the time to delivery and the closure of cross-border order books. The tail of the distribution is mainly influenced by past price differences and trading activity. Our approach is directly transferable to other continuous intraday markets in Europe.





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