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

By: Tang, Wanrong [author.].
Contributor(s): Zhang, Ying Jun (Angela) [author.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: SpringerBriefs in Electrical and Computer Engineering: Publisher: Cham : Springer International Publishing : Imprint: Springer, 2017Edition: 1st ed. 2017.Description: XI, 106 p. 24 illus., 23 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319458625.Subject(s): Electric power production | Computer networks  | Electrical Power Engineering | Computer Communication NetworksAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 621.31 Online resources: Click here to access online
Contents:
Introduction -- ORCHARD Algorithm for PEV Charging -- A MPC-based PEV Charging Scheduling -- Optimal BESS Control in Microgrids -- Conclusions and Future Work.
In: Springer Nature eBookSummary: 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.

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