Day-ahead Optimization of Frequency Containment Reserve for Renewable Energies and Storage

This work focuses on calculating the available amount of frequency containment reserve (FCR) for a hybrid power plant containing a wind or solar power plant and a supporting storage. The amount of FCR has to be determined day-ahead and is linked to a high reliability requirement by the transmission system operators which is especially challenging for renewable power plants due to their weather dependency. To overcome this challenge, probabilistic forecasts are needed. A probabilistic forecast includes the current weather forecast and information about forecast errors. The determination of the forecast error is even more challenging if a storage is included because of the temporal dependencies between the errors of consecutive hours. The presented method firstly uses copula theory to model the power forecast error of a renewable power plant and the FCR demand including temporal dependencies. Secondly the amount of FCR which can be provided by the hybrid power plant is optimized based on power output and FCR demand day-ahead scenarios. The genetic algorithm is used to solve the problem and a wind and solar power plant are compared regarding their potential to provide FCR. In addition, the potential of different product lengths for the FCR bids is investigated.