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Modeling Applications of Flow Battery for Optimal Energy Management of Blockchain Mining

Abdulghaffari, Amir Salar | 2023

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 56625 (46)
  4. University: Sharif University of Technology
  5. Department: Energy Engineering
  6. Advisor(s): Moeini Eghtaei, Moein
  7. Abstract:
  8. In recent years, the high energy consumption of blockchain technology has led to the creation of major problems such as more greenhouse gas emissions and additional pressure on the power grid. In this regard, the emerging technology of flow batteries for large-scale electricity storage might be a suitable choice to overcome both problems. In this research, a novel interdisciplinary methodology has been developed to optimize the flow battery design in different scenarios of energy systems with blockchain mining electricity demand. In this methodology, a new electrochemical model was developed for the vanadium redox flow battery with a no-mixing design, and its results were validated on experimental data. Then, the model was reduced for battery design in the context of energy systems engineering. Thus, the techno-economic model of the battery energy storage system was optimized in different energy system scenarios. The computations were done by establishing a heuristic algorithm based on trial-and-error to quickly and accurately solve the constraint nonlinear optimization problem. Investigations on scenarios such as; peak shaving of grid electricity with various approaches, and planning a stand-alone renewable microgrid of solar and wind energy, revealed that the optimal design of the battery can reduce the investment cost of energy systems between 4% and 35% in the first scenario and by 13% in the latter one. In addition, it was found that the optimal price per kilowatt-hour of vanadium redox flow battery during application in the renewable system could be more than 35% cheaper than other scenarios
  9. Keywords:
  10. Redox Flow Batteries (RFB) ; Renewable Energy Resources ; Electrochemical Modeling ; Blockchain ; Applied Optimization ; Peak Shaving

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