Improving the Performance of an All-Vanadium Redox Flow Battery under Imbalance Conditions: Online Dynamic Optimization Approach
During the operation of an all-vanadium redox flow battery (VRFB), the electrolyte flow of vanadium is a crucial operating parameter, affecting both the system performance and operational costs. Thus, this study aims to develop an on-line optimal operational strategy of the VRFB. A dynamic model of...
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Published in | ACS sustainable chemistry & engineering Vol. 8; no. 36; pp. 13610 - 13622 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
American Chemical Society
14.09.2020
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Subjects | |
Online Access | Get full text |
ISSN | 2168-0485 2168-0485 |
DOI | 10.1021/acssuschemeng.0c02973 |
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Summary: | During the operation of an all-vanadium redox flow battery (VRFB), the electrolyte flow of vanadium is a crucial operating parameter, affecting both the system performance and operational costs. Thus, this study aims to develop an on-line optimal operational strategy of the VRFB. A dynamic model of the VRFB based on the mass transport equation coupled with electrochemical kinetics and a vanadium ionic diffusion is adopted to determine the optimal flow rate of the vanadium electrolyte by solving an on-line dynamic optimization problem, taking into account the battery capacity degradation due to electrolyte imbalance. Based on the measurement of modified open-circuit voltage, the extended Kalman filter (EKF) is implemented to estimate a change in the concentration of vanadium, which is used to on-line update the optimal vanadium flow rate. The results show that the on-line optimization of the vanadium flow rate incorporated with the EKF estimator can enhance the system efficiency (7.4% increase in state of charge) when the VRFB is operated under the intermittent current density. Also, it can prevent the battery voltage from reaching the limiting voltage before the battery achieves the desired state of charge. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 2168-0485 2168-0485 |
DOI: | 10.1021/acssuschemeng.0c02973 |