Optimisation of design and operational management for hybrid power plants and energy storage technologies by means of wind and PV power nowcasting
- Nowcasting of wind power feed-in of individual wind turbines (WT) and of wind farms by combining high temporal resolution long-range lidar measurements at a wind turbine with further meteorological data. The combination of the data and derivation of predictions will be carried out with a state-of-the-art machine learning method. Machine learning methods will also be developed to improve persistence forecasting in order to extend the time domain of the lidar measurements as much as possible.
- Nowcasting of PV power with high spatial and temporal resolution for regions. This involves on-site measurements with a cloud camera with high temporal resolution (<=1 minute) combined with satellite data (temporal resolution of 15 minutes). Predictions are generated with the help of machine learning methods.
- Extension of the P2IONEER model to enable the use of nowcasting. The model is extended to allow the use of nowcasting and is thus developed into a universal tool for the design, optimization and operation of combined renewable energy power plants. The operators and technical interfaces will be adapted in order to automate use of the model as far as possible. The coupling of power and gas grids and the resulting reduced grid loads will be closely investigated.
VORKAST is lead by the Centre for Solar Energy and Hydrogen Research Baden-Württemberg (ZSW).
- New Windfors Project “VORKAST” Launched (1/09/2014) Short term forecasts of wind and photovoltaics output are important parameters for an optimal operation of combined renewable energy power plants. For this reason, several WindFors partners submitted a proposal for a research project on this topic to the Federal Ministry for Economic Affairs and Energy. The proposal was approved and the VORKAST project launched …
- WindForS at WindEurope 2018 (22/09/2018) Lots of people from WindForS will be presenting papers and posters at the 2018 WindEurope conference in Hamburg. We’ll have: Professor Po Wen Cheng will be chairing the session on new approaches to drivetrains, yaw, converters, cables, … and airborne. Ines Würth from U. Stuttgart talking about her results from the VORKAST project Kolja Müller from U. Stuttgart presenting …
- New WindForS Project: Minute-scale Power Forecasts (7/12/2018) What is the best way of predicting the energy produced by an offshore wind energy plant in the next few minutes, and how big is the uncertainty of the prediction in the event of major changes in wind speed? These and other questions will be investigated in ParkCast, a new WindFoS project led by Ines Würth at Stuttgart Wind Energy (SWE) …
- I. Würth, M. Wigger, P.W. Cheng (2016). “Nowcasting the Power Output of a Wind Turbine using a Long Range Lidar”. Presented at ISARS 2016, Varna, Bulgaria. Download