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

TL;DR
This paper develops a simulation-based model for intraday power market prices using fundamental drivers, improving probabilistic forecasting especially in the distribution tails, and revealing market efficiency and volatility factors.
Contribution
It introduces a novel modeling strategy for intraday price distributions based on fundamental variables, validated through a German market study, with improved forecast accuracy.
Findings
Significant improvement in tail forecast accuracy.
Market efficiency indicated by limited explanatory power of fundamentals for expected returns.
Volatility driven by merit-order regime, time to delivery, and cross-border order book closure.
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…
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Taxonomy
TopicsElectric Power System Optimization · Energy Load and Power Forecasting · Market Dynamics and Volatility
MethodsNone
