Electricity Price Forecasting in the Irish Balancing Market

The continuing deployment of renewables and battery energy storage systems is likely to lead to increased price volatility Martinez-Anido et al. (2016); Eurostat (2022). The Balancing Market (BM) is the last stage for trading electric energy, exhibiting far higher volatility compared to both the Day-Ahead Market (DAM) and Intra Day Market (IDM). It plays an essential role (in particular in regions where storage of large quantities of electric energy is not economically convenient Mazzi & Pinson (2017)) as production and consumption levels must match during the operation of electric power systems. The growing importance of accurate forecasts of BM prices to participants is outlined in Ortner & Totschnig (2019), where forecast errors of variable renewable electricity will drive demand for BM participation. Historically, the focus on the DAM is intuitive, given that it is a cornerstone of the European electricity market. In addition, the datasets required for forecasting the DAM are widely available. The lack of analysis of the BM is likely the result of a combination of factors including not all jurisdictions having a BM, the rules governing it can differ from region to region and the identification and acquisition of the relevant datasets can be complicated and expensive (with no open access dataset). In recent years, given access to additional datasets and increasing GPU speeds, the application of Deep Learning (DL) models has become an attractive option.