Conveners
Postprocessing
- Sebastian Lerch (University of Marburg, Germany)
As the Met Office retires legacy deterministic data feeds and moves towards ensemble forecasting, a challenge arises in maintaining delivery of spot forecast products, including those supporting renewable energy applications. Rather than replicating existing data feeds, a new project is taking a fresh approach to understand requirements. Starting with plain-English questions to understand how...
Accurate forecasts of regional wind power production are crucial for power system operation and planning. Total generation in the coming hours and days depends strongly on both weather forecasts and time-varying production capacity. We propose a probabilistic forecasting approach based on Bernstein Quantile Networks (BQN) to predict aggregated power production from multiple wind farms without...
The ENTSO-E Transparency Platform provides comprehensive European electricity market data essential for renewable energy forecasting and operations. We present entsoe-apy, an open-source Python library enabling access to all ENTSO-E RESTful API endpoints with seamless data retrieval.
The package features automatic request splitting for large queries, intelligent retries, and consistent...
Accurate weather forecasting plays an increasingly important role in today's society, with implications in hydrological modelling, renewable energy production, and civil service operations. To improve the reliability of ensemble weather forecasts, post-processing of said forecasts is frequently employed. However, many variables of interest, such as precipitation or wind speed, exhibit highly...
