Humboldt-Universität zu Berlin - High Dimensional Nonstationary Time Series

SFB649DP2016 035

Time-Adaptive Probabilistic Forecasts of Electricity Spot Prices with
Application to Risk Management

Brenda López Cabrera
Franziska Schulz

The increasing exposure to renewable energy has amplied the need for risk management in electricity markets. Electricity price risk poses a major challenge to market participants. We propose an approach to model and forecast
electricity prices taking into account information on renewable energy production. While most literature focuses on point forecasting, our methodology
forecasts the whole distribution of electricity prices and incorporates spike risk, which is of great value for risk management. It is based on
functional principal component analysis and time-adaptive nonparametric density estimation techniques. The methodology is applied to electricity market data from Germany. We find that renewable infeed effects both, the location and the shape of spot price densities. A comparison with benchmark methods and an application to risk management are provided.

electricity prices; residual load, probabilistic forecasting, value at risk,
expected shortfall, functional data analysis

JEL Classification:
C1, Q41, Q47