Title: The Effect of Input Parameter Variation on the Accuracy of a Vanadium Redox Flow Battery Simulation Model
Authors: Zugschwert, Christina
Dundálek, Jan
Leyer, Stephan
Hadji-Minaglou, Jean-Régis
Kosek, Juraj
Pettinger, Karl-Heinz
Citation: ZUGSCHWERT, CH. DUNDÁLEK, J. LEYER, S. HADJI-MINAGLOU, J. KOSEK, J. PETTINGER, K. The Effect of Input Parameter Variation on the Accuracy of a Vanadium Redox Flow Battery Simulation Model. Batteries, 2021, roč. 7, č. 1, s. nestránkováno. ISSN: 2313-0105
Issue Date: 2021
Publisher: MDPI
Document type: článek
URI: 2-s2.0-85099994636
ISSN: 2313-0105
Keywords in different language: vanadium redox flow battery;redox flow battery;modeling;energy storage;grey box simulation model;parameter optimization process;integrated energy system simulations;model parametrization;applications
Abstract in different language: Accurately predicting battery behavior, while using low input data, is highly desirable in embedded simulation architectures like grid or integrated energy system analysis. Currently, the available vanadium redox flow battery (VRFB) models achieve highly accurate predictions of electrochemical behavior or control algorithms, while the optimization of the required input data scope is neglected. In this study, a parametrization tool for a DC grey box simulation model is developed using measurements with a 10 kW/100 kWh VRFB. An objective function is applied to optimize the required input data scope while analyzing simulation accuracy. The model is based on a differential-algebraic system, and an optimization process allows model parameter estimation and verification while reducing the input data scope. Current losses, theoretical storage capacity, open circuit voltage, and ohmic cell resistance are used as fitting parameters. Internal electrochemical phenomena are represented by a self-discharge current while material related losses are represented by a changing ohmic resistance. Upon reducing input data the deviation between the model and measurements shows an insignificant increase of 2% even for a 60% input data reduction. The developed grey box model is easily adaptable to other VRFB and is highly integrable into an existing energy architecture.
Rights: © authors
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