SpecialIssue 2022 : Forecasting Prices in Power Markets

Dear Colleagues,

The increasing liberalization and interconnection of power markets, and the growing importance of renewable energies, storage and demand response lead to complex electricity price formation on power markets. To reduce carbon emissions and the impact of climate change, accurate forecasts are required for efficient decision making. This concerns all forecasting horizons, ranging from short-term horizons with substantial impact from meteorological conditions, whereas long-term forecasts are mainly influenced by economical, regulatory and technological risk. Power has unique characteristics (especially concerning required system balance and storage opportunities) not found in other commodities. Usually, electricity price data may exhibit specific characteristics, like

(i) (time-varying) autoregressive effects and (in)stationarity

(ii) calendar effects (daily, weekly and annual seasonality, holiday effects, clockchange)

(iii) (time-varying) volatility and higher moment effects

(iv) (positive and negative) price spikes

(v) price clustering.

Some of these effects may be explained by external input data available at prediction time. However, electricity price forecasting remains a challenging task. We welcome scientific contributions on forecasting power/electricity prices that give insights into a better understanding of power price dynamics for all kinds of forecasting horizons and power markets (e.g., derivative markets, spot markets, day-ahead markets, intraday and balancing markets). We particularly welcome contributions in the area of probabilistic forecasting using all kinds of methods. This may be suitable for statistical time series prediction methods or machine learning methods, like gradient boosting machines (GBM) or artificial neural networks (ANN). In this Special Issue, we invite submissions exploring cutting-edge research and recent advances that address the above and related challenges.