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Enhancing the efficiency of kW-class vanadium redox flow batteries by flow factor modulation: An experimental method

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  • Guarnieri, Massimo
  • Trovò, Andrea
  • Picano, Francesco

Abstract

The paper presents a control method of the electrolyte flow factor in kW-class Vanadium Redox Flow Batteries that minimizes transport losses without affecting the battery's electrical performance. This method uses experimental data acquired on a 9 kW/27 kWh test facility at varying operating conditions. The effects of overpotentials on the polarization curves are then modeled as non-linear electrical resistances that vary with the stack current, state of charge and electrolyte flow rates. Our analysis of these variables shows that the optimal performance is found if the flow factor is modulated during operation according to stack current and the battery state, so as to minimize the overall flow-dependent losses. The optimal profiles have been identified as functions of the battery's operating conditions. Based on these results, a dynamic control for the electrolyte flow rates has been implemented at a software level (i.e. without modifying the hardware of the test facility), which is capable of maximizing the round-trip efficiency and exceeds the performance achieved with a constant flow factor strategy, as proposed in previous literature. The implementation of the optimal flow rate control requires a preliminary test campaign to collect performance data, which are then used in the control protocol to manage the battery's operation. This scheme is easily implementable at a software level in other industrial redox flow batteries.

Suggested Citation

  • Guarnieri, Massimo & Trovò, Andrea & Picano, Francesco, 2020. "Enhancing the efficiency of kW-class vanadium redox flow batteries by flow factor modulation: An experimental method," Applied Energy, Elsevier, vol. 262(C).
    • Handle: RePEc:eee:appene:v:262:y:2020:i:c:s0306261920300441
    DOI: 10.1016/j.apenergy.2020.114532
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    1. Joseph Oyekale & Mario Petrollese & Vittorio Tola & Giorgio Cau, 2020. "Impacts of Renewable Energy Resources on Effectiveness of Grid-Integrated Systems: Succinct Review of Current Challenges and Potential Solution Strategies," Energies, MDPI, vol. 13(18), pages 1-48, September.
    2. Shu-Ling Huang & Chi-Ping Li & Chia-Chin Chang & Chen-Chen Tseng & Ming-Wei Wang & Mei-Ling Chen, 2020. "Real-Time Monitoring of the Thermal Effect for the Redox Flow Battery by an Infrared Thermal Imaging Technology," Energies, MDPI, vol. 13(24), pages 1-19, December.
    3. Ouyang, Tiancheng & Zhang, Mingliang & Qin, Peijia & Tan, Xianlin, 2024. "Flow battery energy storage system for microgrid peak shaving based on predictive control algorithm," Applied Energy, Elsevier, vol. 356(C).

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