473631 Simplified Model of a Redox Flow Battery for Deriving Design and Dispatch Strategies in a Resource Planning Tool

Monday, November 14, 2016: 4:10 PM
Powell (Hilton San Francisco Union Square)
Bharatkumar Suthar1, Michael Scioletti2, Alexandra Newman2 and Paul Kohl3, (1)Department of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA, (2)Department of Mechanical Engineering, Colorado School of Mines, Golden, CO, (3)School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA

Energy resource planning tools (ERPTs) that integrate an energy storage technology with renewable energy sources require representative models for the energy storage resources. ERPTs may involve use of optimization framework to select the optimal mix of resources and dispatch strategies. Such optimization problems can involve a yearlong time frame and several energy resources. Hence use of linear models is desirable for faster convergence of the optimization problem.

Flow battery technology has emerged as one of the potential storage candidates which can be used for stationary energy storage systems. The flexibility of scaling energy and power independently may give these systems an advantage over other energy storage technologies for applications where the energy is high and power demand is low. Flow battery systems exhibit nonlinear behavior during charging and discharging which is typical of electrochemical energy storage systems. Hence there is a need to develop a simplified (preferably linear) model without undue compromise of the underlying physics of the batteries.

Rather than modeling a flow battery as an ideal, finite source of energy with constant energy efficiency, a simple model incorporating the electrochemical behavior of a redox flow battery was developed. This model enables the optimizer to (i) choose energy and power independently (design decision) and (ii) access the performance of the chosen battery size (dispatch decision) in order to derive the optimal energy mix. The talk will also focus on quantification of errors associated with the simple model compared with the nonlinear representation.


The work presented herein was funded by the Office of Naval Research.

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See more of this Session: Battery and Energy Storage Technologies
See more of this Group/Topical: Transport and Energy Processes