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000916723 1001_ $$0P:(DE-Juel1)190571$$aLi, Chuan$$b0$$eCorresponding author$$ufzj
000916723 1112_ $$aIECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society$$cBrussels$$d2022-10-17 - 2022-10-20$$wBelgium
000916723 245__ $$aA Real-Time Simulation Framework to Evaluate the Scheduling of V2G in Distribution Networks
000916723 260__ $$bIEEE$$c2022
000916723 29510 $$aIECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society : [Proceedings] - IEEE, 2022. - ISBN 978-1-6654-8025-3 - doi:10.1109/IECON49645.2022.9968520
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000916723 500__ $$ahttps://ieeexplore.ieee.org/abstract/document/9968520
000916723 520__ $$aThis paper presents a real-time simulation framework for the evaluation of V2G scheduling applications in distribution networks. Mathematical models of electric vehicles (EVs), uni- and bi-directional charging stations (CSs), and Battery Energy Storage System (BESS) are introduced for power management analysis. A power management (PM) algorithm for peak load shaving via BESS, and Vehicle-to-Grid (V2G) technology is presented to exercise the framework. The overall framework is validated by considering the impact of high penetration of EVs on the campus network of Forschungszentrum Jülich, and the V2G-based mitigation solution.
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000916723 7001_ $$0P:(DE-Juel1)186779$$aCarta, Daniele$$b1$$ufzj
000916723 7001_ $$0P:(DE-Juel1)179029$$aBenigni, Andrea$$b2$$ufzj
000916723 773__ $$a10.1109/IECON49645.2022.9968520$$p1-6
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