Modelling and estimation of vanadium redox flow batteries: a review
Redox flow batteries are one of the most promising technologies for large-scale energy storage, especially in applications based on renewable energies. In this context, considerable efforts have been made in the last few years to overcome the limitations and optimise the performance of this technolo...
| Authors: | , , , |
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| Format: | article |
| Publication Date: | 2022 |
| Country: | España |
| Institution: | Universitat Politècnica de Catalunya (UPC) |
| Repository: | UPCommons. Portal del coneixement obert de la UPC |
| Language: | English |
| OAI Identifier: | oai:upcommons.upc.edu:2117/375346 |
| Online Access: | https://hdl.handle.net/2117/375346 https://dx.doi.org/10.3390/batteries8090121 |
| Access Level: | Open access |
| Keyword: | Energy storage Storage batteries Redox flow battery modelling Vanadium redox flow battery State observer Parameter estimation State of charge State of health Energia -- Emmagatzematge Acumuladors Àrees temàtiques de la UPC::Enginyeria elèctrica |
| Summary: | Redox flow batteries are one of the most promising technologies for large-scale energy storage, especially in applications based on renewable energies. In this context, considerable efforts have been made in the last few years to overcome the limitations and optimise the performance of this technology, aiming to make it commercially competitive. From the monitoring point of view, one of the biggest challenges is the estimation of the system internal states, such as the state of charge and the state of health, given the complexity of obtaining such information directly from experimental measures. Therefore, many proposals have been recently developed to get rid of such inconvenient measurements and, instead, utilise an algorithm that makes use of a mathematical model in order to rely only on easily measurable variables such as the system’s voltage and current. This review provides a comprehensive study of the different types of dynamic models available in the literature, together with an analysis of the existing model-based estimation strategies. Finally, a discussion about the remaining challenges and possible future research lines on this field is presented. |
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