A new approach to exploit seasonal forecasts in Enel’s decision-making process

Abstract

In the frame of the EU Horizon 2020 SECLIFIRM project, Enel exploits the SEAsonal forecast System 5 (SEAS5) of the European Center for Medium- Range Weather Forecasts (ECMWF) to assess their added value on the company’s decision-making process. The assessment is performed on five case studies that were selected over Enel’s international domain. The work illustrated in this article shows the state of the art of three case studies focused on extreme events occurred in Italy between 2015 and 2016, that led to problematic and quantifiable impacts for the energy industry. The probabilistic information of spatially aggregated SEAS5 forecasts are combined with the ECMWF ReAnalysis 5 (ERA5) weather model to derive an ad-hoc dataset for variables of 2-m temperature, total precipitation, and 10-m wind speed. Forecasts are then integrated to Enel’s models, and their impact on the best hedging strategy is later evaluated through a performance indicator that compares solutions obtained with climatology, seasonal forecasts and actual weather data. As a first step, the quality of seasonal forecasts is assessed through an error analysis. Preliminary results on SEAS5 show that temperature values tend to fit ERA5 climatology. Improvements with respect to ERA5 climatology are observed for wind and total precipitation variables. As expected, a progressive enhancement of SEAS5 performance is obtained at shorter lead times. Further steps in the project will be dedicated to the application of seasonal forecasts to renewable electricity production and power demand models, and the relative impact assessment on Enel’s decision-making process.