Modeling of vanadium redox battery by field analysis and neural network approach

Author

Xin Qiu ; Nguyen, Tu A. ; Crow, Mariesa L. ; Elmore, Andrew Curtis

Author_Institution

Dept. of Electr. & Comput. Eng., Missouri Univ. of Sci. & Technol., Rolla, MO, USA

fYear

2014

fDate

Feb. 28 2014-March 1 2014

Firstpage

1

Lastpage

7

Abstract

The vanadium redox flow battery is well-suited for renewable energy applications. This paper studies VRB use within a microgrid system from a practical perspective. A reduced order circuit model of the VRB was introduced. Experimental field data are collected to estimate the key parameters of the VRB system. Methods of predicting major parasitic losses are proposed. Loss models include the circulation pumps and the HVAC system that regulates the environment of the VRB enclosure. The HVAC system can draw a significant amount of the VRB power considerably impacting its overall efficiency, but this is usually ignored by other theoretical models.

Keywords

HVAC; distributed power generation; neural nets; reduced order systems; secondary cells; vanadium; HVAC system; VRB; circulation pumps; field analysis; loss models; microgrid system; neural network approach; reduced order circuit model; renewable energy; vanadium redox flow battery; Artificial neural networks; Batteries; Containers; Integrated circuit modeling; Microgrids; System-on-chip;

fLanguage

English

Publisher

ieee

Conference_Titel

Power and Energy Conference at Illinois (PECI), 2014

Conference_Location

Champaign, IL

Type

conf

DOI

10.1109/PECI.2014.6804553

Filename

6804553