Data-driven approach for SOH estimation and alarms generation for complex on-grid energy storage systems

Autor: Karoui, Fathia, Ha, D-L., Delaplagne, T., Bouaziz, M-F., Vinit, L., Montaru, M.
Přispěvatelé: Département des Technologies Solaires (DTS), Laboratoire d'Innovation pour les Technologies des Energies Nouvelles et les nanomatériaux (LITEN), Institut National de L'Energie Solaire (INES), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Institut National de L'Energie Solaire (INES), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: Proceedings of the 36th European Photovoltaic Solar Energy Conference and Exhibition
EU PVSEC 2019-36th European Photovoltaic Solar Energy Conference and Exhibition
EU PVSEC 2019-36th European Photovoltaic Solar Energy Conference and Exhibition, Sep 2019, Marseille (FRANCE), France
Popis: International audience; On-grid energy storage systems are used increasingly worldwide in order to optimize the use of intermittent energies such as photovoltaics. An accurate estimation of the state of health of the batteries is necessary to optimise their lifetime and reduce their Levelized Cost of Storage. The misuse of these batteries leads to frequent failures. A robust analysis of the misuse events with automatic alarms generation will also be valuable to send warnings to the system end-user before failure. This paper presents advanced analysis of some of these systems based on new approaches of data-driven diagnosis and prognosis. Several PV-Storage systems have been monitored for four years and an original diagnostic and prognostic tool is developed for the analysis of the performance and defaults of such systems. This generic approach allowed to have a feedback on the performance of grid connected PVstorage systems with two storage technologies (Li-ion and NiNaCl2). Recently, the efficiency of this kind of systems have been analysed including the performance of batteries and power conversion systems. The analysis doesn’t include the state of health evolution and the alarms generation.
Databáze: OpenAIRE