Aging-aware NaS battery model in a stochastic wind-storage simulation framework

Pierre Haessig 1 Bernard Multon 1 Hamid Ben Ahmed 1 Stéphane Lascaud 2 Lionel Jamy 2
1 SATIE SETE - Systèmes d'Energie pour les Transports et l'Environnement
CSEE - Composants et Systèmes pour l'Energie Electrique
EDF R&D - EDF Division Recherche et Développement [Clamart]
Abstract : Dispatchability of wind power is significantly increased by the availability of day-ahead production forecast. However, forecast errors prevent a wind farm operator from holding a firm production commitment. An energy storage system (ESS) connected to the wind farm is thus considered to reduce deviations from the commitment. We statistically assess the performance of the storage in a stochastic framework where day-ahead forecast errors are modeled with an autoregressive model. This stochastic model, fitted on prediction/production data from an actual wind farm captures the significant correlation along time of forecast errors, which severely impacts the ESS performance. A thermo-electrical model for Sodium Sulfur (NaS) batteries reproduces key characteristics of this technology including charging/discharging losses, state-dependent electrical model and internal temperature variations. With help of a cost analysis which includes calendar and cycling aging, we show trade-offs in storage capacity sizing between deviation from commitment and storage costs due to energy losses and aging.
Type de document :
Communication dans un congrès
PowerTech 2013, Jun 2013, Grenoble, France. pp.1-6, 2013, 〈10.1109/PTC.2013.6652505〉
Liste complète des métadonnées

Littérature citée [10 références]  Voir  Masquer  Télécharger
Contributeur : Pierre Haessig <>
Soumis le : jeudi 19 septembre 2013 - 18:30:23
Dernière modification le : vendredi 1 décembre 2017 - 14:30:17
Document(s) archivé(s) le : vendredi 7 avril 2017 - 00:12:13


Fichiers produits par l'(les) auteur(s)



Pierre Haessig, Bernard Multon, Hamid Ben Ahmed, Stéphane Lascaud, Lionel Jamy. Aging-aware NaS battery model in a stochastic wind-storage simulation framework. PowerTech 2013, Jun 2013, Grenoble, France. pp.1-6, 2013, 〈10.1109/PTC.2013.6652505〉. 〈hal-00863903〉



Consultations de la notice


Téléchargements de fichiers