This paper proposes the integration of vanadium redox flow battery (VRFBs) with photovoltaic (PV) systems to enhance energy storage efficiency and demand response mechanisms, particularly time-of-use (TOU) pricing, to enhance energy efficiency and reduce electricity costs. VRFBs, known for their scalability, long lifespan, and high efficiency, are utilized to address the intermittent nature of renewable energy generation. The study focuses on optimizing energy management through particle swarm optimization (PSO), enabling precise control of peak shaving and energy utilization. The methodology incorporates real world profiles from a university dormitory, simulating monthly power demands. The integration of PV systems as 5 kW with VRFBs as 5 kW/3 kWh demonstrates significant benefits, including reduced reliance on grid power, effectively stores excess solar energy, discharging during high demand hours and minimizing energy wastage. The simulation results show that the VRFBs reduces electricity costs and carbon emission by up to 32 and 28%, respectively. Moreover, the PSO algorithm identifies optimal power peak shave points and charge point, further enhancing system reliability and cost efficiency. These findings underscore the potential of VRFBs as a critical solution for renewable energy integration, supporting Thailand’s carbon neutrality goals and contributing to global sustainability efforts.

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Peak Shaving and Energy Storage Optimization with VRFBs: A Case Study in Thailand

  • Teeranart Chatchawanthatri,
  • Kittapon Chatwongtong,
  • Pirutchada Musigapong,
  • Tosaphol Ratniyomchai

摘要

This paper proposes the integration of vanadium redox flow battery (VRFBs) with photovoltaic (PV) systems to enhance energy storage efficiency and demand response mechanisms, particularly time-of-use (TOU) pricing, to enhance energy efficiency and reduce electricity costs. VRFBs, known for their scalability, long lifespan, and high efficiency, are utilized to address the intermittent nature of renewable energy generation. The study focuses on optimizing energy management through particle swarm optimization (PSO), enabling precise control of peak shaving and energy utilization. The methodology incorporates real world profiles from a university dormitory, simulating monthly power demands. The integration of PV systems as 5 kW with VRFBs as 5 kW/3 kWh demonstrates significant benefits, including reduced reliance on grid power, effectively stores excess solar energy, discharging during high demand hours and minimizing energy wastage. The simulation results show that the VRFBs reduces electricity costs and carbon emission by up to 32 and 28%, respectively. Moreover, the PSO algorithm identifies optimal power peak shave points and charge point, further enhancing system reliability and cost efficiency. These findings underscore the potential of VRFBs as a critical solution for renewable energy integration, supporting Thailand’s carbon neutrality goals and contributing to global sustainability efforts.