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Optimal Charging Control of Electric Vehicles in Smart Grids [electronic resource] / by Wanrong Tang, Ying Jun (Angela) Zhang.

By: Contributor(s): Material type: TextSeries: SpringerBriefs in Electrical and Computer EngineeringPublisher: Cham : Springer International Publishing : Imprint: Springer, 2017Description: XI, 106 p. 24 illus., 23 illus. in color. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783319458625
Subject(s): Additional physical formats: Printed edition:: No titleDDC classification:
  • 621.317 23
Online resources:
Contents:
Introduction -- ORCHARD Algorithm for PEV Charging -- A MPC-based PEV Charging Scheduling -- Optimal BESS Control in Microgrids -- Conclusions and Future Work.
In: Springer eBooksSummary: This book introduces the optimal online charging control of electric vehicles (EVs) and battery energy storage systems (BESSs) in smart grids. The ultimate goal is to minimize the total energy cost as well as reduce the fluctuation of the total power flow caused by the integration of the EVs and renewable energy generators. Using both theoretic analysis and data-driven numerical results, the authors reveal the effectiveness and efficiency of the proposed control techniques. A major benefit of these control techniques is their practicality, since they do not rely on any non-causal knowledge of future information. Researchers, operators of power grids, and EV users will find this to be an exceptional resource. It is also suitable for advanced-level students of computer science interested in networks, electric vehicles, and energy systems.
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Introduction -- ORCHARD Algorithm for PEV Charging -- A MPC-based PEV Charging Scheduling -- Optimal BESS Control in Microgrids -- Conclusions and Future Work.

This book introduces the optimal online charging control of electric vehicles (EVs) and battery energy storage systems (BESSs) in smart grids. The ultimate goal is to minimize the total energy cost as well as reduce the fluctuation of the total power flow caused by the integration of the EVs and renewable energy generators. Using both theoretic analysis and data-driven numerical results, the authors reveal the effectiveness and efficiency of the proposed control techniques. A major benefit of these control techniques is their practicality, since they do not rely on any non-causal knowledge of future information. Researchers, operators of power grids, and EV users will find this to be an exceptional resource. It is also suitable for advanced-level students of computer science interested in networks, electric vehicles, and energy systems.