Bidirectional demand analysis for electric vehicles
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Abstract (EN)
In this thesis, the technical and economic impacts of electric vehicles operating on a feeder with high energy demand in the city of Batman were evaluated through the implementation of G2V and V2G technologies. Within the scope of the V2G model, the potential for selling the energy stored in EV batteries on an hourly basis in Turkey's electricity market via the EPİAŞ Day-Ahead Market was analyzed, and cost-effectiveness was assessed under different scenarios. On the G2V side, the impact of EV charging schedules on the system's load profile was evaluated, revealing the vehicles' load-balancing capacity. Furthermore, the operational data obtained from simulations were integrated into artificial intelligence-based demand forecasting models to enhance system predictability. The results of the study indicate that electric vehicles can create value for regional energy systems from both technical and economic perspectives. It has been determined that, with proper planning, the integration of V2G and G2V technologies into energy markets can significantly contribute to grid flexibility and the sustainable management of energy systems.
Author
Ferhat Mirkan
How to Cite
Ferhat Mirkan (Master Thesis). Bidirectional demand analysis for electric vehicles, 2025, Batman University.
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