Efficient Modeling and Forecasting of the Electricity Spot Price

TL;DR

This paper develops an advanced econometric model for European electricity prices that incorporates renewable energy sources and outperforms existing models in forecasting accuracy.

Contribution

It introduces a periodic VAR-TARCH model with renewable energy influences and employs an efficient reweighted lasso estimation method.

Findings

Model effectively captures renewable energy impacts on prices

Outperforms existing models in forecasting accuracy

Handles well-known features of German electricity prices

Abstract

The increasing importance of renewable energy, especially solar and wind power, has led to new forces in the formation of electricity prices. Hence, this paper introduces an econometric model for the hourly time series of electricity prices of the European Power Exchange (EPEX) which incorporates specific features like renewable energy. The model consists of several sophisticated and established approaches and can be regarded as a periodic VAR-TARCH with wind power, solar power, and load as influences on the time series. It is able to map the distinct and well-known features of electricity prices in Germany. An efficient iteratively reweighted lasso approach is used for the estimation. Moreover, it is shown that several existing models are outperformed by the procedure developed in this paper.