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Electrical vehicles charging and discharging scheduling for the cloud-based energy management service

Electrical vehicles charging and discharging scheduling for the cloud-based energy management service

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The electric vehicles (EVs) have been dramatically increased and popularized in recent years. The ability to export the power to the grid via the vehicle -to -grid (V2G) technology makes the EVs become the promising solutions for reducing the peak demand in the power grid but could also severely increase the fluctuated penetration if no scheduling mechanisms are deployed. Therefore, it is an essential task to provide the optimal EV charging and discharging scheduling. However, to practically reinforce the scheduling relies not only on the ability to offer it in the efficient, reliable and scalable approaches, but also on the willingness of the participation from EVs owners. The cloud -based energy management service (EMS) satisfies the needs to practically deploy the scheduling mechanisms for the heterogeneous EVs and provide the incentives for customers' participation. The cloud computing is introduced with its characteristics and is utilized for the design of an extensive cloud -based framework, which provides the energy management as a service (EMaaS) to suggest the optimal electricity usage and trading options for every participated customer. The framework and the procedure of the cloud -based EMS are illustrated, and the EVs charging and discharging scheduling for the cloud -based EMS is formulated and implemented. The scheduling results for both EVs with and without the V2G ability are discussed with various examples.

Chapter Contents:

  • List of abbreviation
  • 3.1 Introduction
  • 3.2 Cloud computing
  • 3.3 Cloud-based energy management service
  • 3.3.1 Framework and utilized data
  • 3.3.2 Procedure
  • 3.4 Electrical vehicles for the cloud-based energy management service
  • 3.5 Scheduling results discussion
  • 3.6 Conclusion
  • References

Inspec keywords: energy management systems; vehicle-to-grid; power generation scheduling; electric vehicle charging; cloud computing

Other keywords: heterogeneous EVs; discharging scheduling; optimal EV charging; cloud-based energy management service; V2G ability; vehicle-to-grid technology; electric vehicles; peak demand; optimal electricity usage; cloud-based EMS; power grid; energy management as a service

Subjects: Distributed power generation; Internet software; Power engineering computing; Transportation; Power system management, operation and economics

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