In January 2018, we attended the kickoff meeting of S2S4E, a project focused on sub-seasonal to seasonal forecast. S2S4E aims at offering an innovative service to improve renewable energy variability management. Along this 3-years long program, we will work on post-processing methodologies to bias-adjust sub-seasonal to seasonal forecast.
The H2020 project “Sub-seasonal to Seasonal climate predictions for Energy” (S2S4E), coordinated by the Barcelona Supercomputing Center (BSC), is a collaborative initiative involving 5 European research centers, 3 energy companies, 3 SMEs, and a large consultancy firm, funded with 5M€ for three years. Its primary aim is to develop an operational climate service to enhance the strategic planning capabilities of renewable energy producers, electricity network managers, and policymakers for sub-seasonal to seasonal timescales. The project acknowledges the growing significance of renewable energy, particularly wind power, in achieving the UN's Sustainable Development Goals and addressing environmental and energy-security issues. However, it also recognizes the challenges posed by the variability of renewable energy due to weather and climate impacts, which affect energy supply and demand.
S2S4E seeks to mitigate these challenges by introducing an innovative service aimed at improving the management of renewable energy variability. This involves the development of new research methods to extend the understanding and forecasting capabilities of weather conditions weeks to months ahead. A pivotal component of the project is the creation of a Decision Support Tool, co-designed with users, which integrates sub-seasonal to seasonal climate predictions with data on renewable energy production and electricity demand.
The expected long-term impact of S2S4E is to bolster the resilience of the European energy sector against climate variability and extreme events, ensuring a smoother transition to sustainable energy sources. This initiative represents a significant step forward in operational planning and strategic decision-making for the energy sector, leveraging advanced computational and climatic research to address the pressing needs of energy sustainability and security.
