Abstract

In the last three decades the vast majority of electricity price forecasting (EPF) research has concerned day-ahead markets. However, the rapid expansion of renewable generation—mostly wind and solar—have shifted the focus to intraday markets, which can be used to balance the deviations between positions taken in the day-ahead market and the actual demand and renewable generation. A recent EPF study claims that the German intraday, continuous-time market for hourly products is weak-form efficient, that is, that the best predictor for the so-called ID3-Price index is the most recent transaction price. Here, we undermine this claim and show that we can beat the naïve forecast by combining it with a prediction of a parameter-rich model estimated using the least absolute shrinkage and selection operator (LASSO). We further argue, that that if augmented with timely predictions of fundamental variables for the coming hours, the LASSO-estimated model itself can significantly outperform the naïve forecast.

Highlights

  • After performing a comprehensive empirical study on intraday electricity price forecasting and considering models with tens of thousands of regressors, Narajewski and Ziel [1] concludes that the German continuous-time market for hourly products is weak-form efficient, that is, that the best predictor is the most recent transaction price

  • To check whether fundamentals can help in forecasting the ID3-Price index in the German intraday market, we extend the baseline model to include load, wind power generation (WPG) and photovoltaic generation (PVG) forecasts and the corresponding errors, as well as the balancing volumes (Section 2.2 for details):

  • The forecasting accuracy is assessed in terms of two error measures: the mean absolute error (MAE) and the root mean squared error (RMSE)

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Summary

Introduction

After performing a comprehensive empirical study on intraday electricity price forecasting and considering models with tens of thousands of regressors, Narajewski and Ziel [1] concludes that the German continuous-time market for hourly products is weak-form efficient, that is, that the best predictor is the most recent transaction price. Their result is surprising and at the same time disappointing from a research perspective.

The ID3-Price Index and DA Prices
Exogenous Variables
Variance Stabilizing Transformation
The Naïve Benchmark
LASSO-Estimated Models
The Baseline Model
The Model with Exogenous Variables
The Model with Partial ID Prices
The Full Model
LASSO Estimation
Forecast Averaging
Forecast Evaluation
MAE and RMSE Errors
Conditional Predictive Ability
Why Does Ensembling Improve the Results?
Discussion and Conclusions
The Moment of Forecasting the ID3-Price Index
Selecting the LASSO Regularization Parameter
The Impact of Intraday Updates of the Fundamentals
Model Size
Directions for Future Research
Full Text
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