Diagnosis and prognosis of complex energy storage systems: tools development and feedback on four installed systems

Fathia Karoui; Duy-Long Ha; Tony Delaplagne; Mohammed-Farouk Bouaaziz; Vincent Eudier; Matthias Lévy

Diagnosis and prognosis of complex energy storage systems: tools development and feedback on four installed systems

Fathia Karoui ^{1, 2, *} Duy-Long Ha ¹ Tony Delaplagne ¹ Mohammed-Farouk Bouaaziz ³ Vincent Eudier ⁴ Matthias Lévy ⁵

* Corresponding author

1 DTS - Département des Technologies Solaires

2 LITEN - Laboratoire d'Innovation pour les Technologies des Energies Nouvelles et les nanomatériaux

3 Sogeti (FRANCE)

4 Albioma

5 Corsica Sole

Abstract : Electrical Storage systems are used since many decades in stand-alone applications. Recently, their use in grid connected renewable energies installations increases not only the flexibility of these systems but also their complexity. The optimization of their operation in these systems is necessary for cost effectiveness and is a technical and scientific challenge. The research and development projects are increasing worldwide to tackle different aspects of these new solutions. This paper presents advanced analysis of some of these systems based on new approaches of data analytics. Four PV-Storage systems have been monitored for three years and an original diagnostic and prognostic tool is developed for the analysis of the performance and defaults of such systems. In addition, the generic approach presented in this paper allowed to have a feedback on the performance of grid connected PV-storage systems with two different storage technologies: Li-ion and NaNiCl2. The efficiency analysis includes the performance of batteries and power conversion systems. So, the objective here is to compare the usage and the performance of electrical storage systems along time within each power plant and also between the monitoring power plants using experts’ knowledge and data processing.

Document type :

Journal articles

Domain :

Engineering Sciences [physics] / Electric power

Computer Science [cs] / Databases [cs.DB]

Statistics [stat] / Applications [stat.AP]

Complete list of metadatas

https://hal-cea.archives-ouvertes.fr/cea-01937213
Contributor : Fathia Karoui <>
Submitted on : Friday, November 30, 2018 - 11:36:30 AM
Last modification on : Wednesday, July 31, 2019 - 3:12:44 PM
Long-term archiving on : Friday, March 1, 2019 - 1:57:35 PM

Karoui et al-2018-energy-proce...

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