Storage sizing for grid connected hybrid wind and storage power plants taking into account forecast errors autocorrelation

Andrea Michiorri (1) , Jesus Lugaro (1) , Nils Siebert (1) , Robin Girard (1) , Georges Kariniotakis (1)

1 PERSEE - Centre Procédés, Énergies Renouvelables, Systèmes Énergétiques

This paper describes a research on the influence of wind power prediction error autocorrelation on the sizing of storage coupled with a wind farm. The stochastic nature of renewable energies resources such as wind speed or solar radiation represents a challenge for the grid integration of renewable energy plants. The imbalances between renewable power predictions and realised production are generally penalised by system operators since additional reserves are required to maintain the stability of the grid. The coupling of storage devices with renewable energy plants is one of the solutions studied to reduce those imbalances. In this work, a methodology to manage imbalances and to size storage in order to achieve a determined level of controllability is proposed. It is applied to a specific use case: the integration of a combined wind-storage plant in French Guyana. The influence of the autocorrelations of errors on the battery size is investigated in detail and a methodology for producing wind prediction errors time series is presented.

Mots clés: Correlation Analysis; Wind; Sizing; forecast error; Storage; Forecast

Domaines: Sciences de l'ingénieur [physics]

Andrea Michiorri, Jesus Lugaro, Nils Siebert, Robin Girard, Georges Kariniotakis. Storage sizing for grid connected hybrid wind and storage power plants taking into account forecast errors autocorrelation. Renewable Energy, 2018, 117, pp.380-392. ⟨10.1016/j.renene.2017.10.070⟩. ⟨hal-01626067⟩