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Evaluation of Fairness Schemes for Electric Vehicle Charging in Smart Grid Environments

This study investigates fairness schemes for distributing limited energy resources to electric vehicles (EVs) in a smart grid context. By developing metrics that incorporate customer energy requirements and desired departure times, the research compares different charging strategies, including Round Robin and Min-Max Delay Time (MMDT). Simulation results reveal that MMDT outperforms traditional methods by better meeting customer needs and reducing delays. The findings indicate that using information about desired departure times can greatly enhance charging efficiency, ensuring a higher percentage of vehicles depart on time.

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Evaluation of Fairness Schemes for Electric Vehicle Charging in Smart Grid Environments

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Presentation Transcript

  1. Smart Grid and Electric VehiclesInstructor: Nicholas F. MaxemchukMembers: YingjieZhouChen WangXiangyingQian

  2. Motivation • Objective Find out proper fairness schemes/metrics to meet the customers’ needs to a great extent. Customer : various energy requirement & desired departure time Available Energy : limited for some time Fairly distribute energy? Motivation & Objective

  3. Use Switch to control power supply (5 min interval) • Information : Energy requirement, desired departure time, battery level, energy available • Cars come to charge in a queue with Poisson dist.. • Each 5 min can only charge limited cars. • Different fairness schemes : Decide who will be charged, update charging queue for every 5 min. • When energy requirement is satisfied, remove the car from the queue. Model

  4. Round Robin Charged Not Charged New Arrivals Beginning of the queue Beginning of the queue Baseline System

  5. Min-Max Energy Requirement (MMER) • Only need the info. of Energy Requirement 5 units 10 units 8 units Beginning of the queue Fairness Scheme 1

  6. Min-Max Delay Time (MMDT) • New metric: N (spare time)= (desired departure time-current time)/5 -Units of energy required • First charge those cars with smallest N Units of energy required Spare time-N Fairness Scheme 2 Desired departure time Current time

  7. Simulation Environment

  8. Simulation Environment

  9. 3 Metrics of evaluation: • Fraction of delayed vehicles:= • Average delay for delayed vehicles: = • Average delay for all vehicles: = Simulation Environment

  10. Run each fairness scheme for successive (n=10) days. • Take the measurements from the day to ensure stable initializations. • Take the measurements till day to ensure the departure of all cars by the end of day. • For comparison, FCFS, FDFS Measurement

  11. MMER fairness scheme does not work well in terms of the metrics we applied because it takes no advantage of the information of departure time. It performs even worse than the baseline Round Robin. • MMDT fairness scheme generally achieves the best performance. • To ensure 95% cars departing without delay, Round Robin: R > 1.8 MMDT: R < 1.1 Contribution

  12. MMER shows the worst performance in comparison to other charging schemes. Result - 1

  13. MMER shows the worst performance in comparison to other charging schemes. zoom out Result - 1

  14. MMER shows the worst performance in comparison to other charging schemes. zoom out Result - 1

  15. MMER shows the worst performance in comparison to other charging schemes. Result - 1

  16. Compare Round Robin with two schemes which take the information of departure time into account. • It turns out that using the additional information can improve the performance. Result - 2

  17. Compare Round Robin with two schemes which take the information of departure time into account. • It turns out that using the additional information can improve the performance. Result - 2

  18. Compare Round Robin with two schemes which take the information of departure time into account. • It turns out that using the additional information can improve the performance. Result - 2

  19. In comparison to FDFS, MMDT fairness scheme achieves better performance when the available power is a little bit more than the required energy. Result - 3

  20. In comparison to FDFS, MMDT fairness scheme achieves better performance when the available power is a little bit more than the required energy. zoom out Result - 3

  21. In comparison to FDFS, MMDT fairness scheme achieves better performance when the available power is a little bit more than the required energy. Result - 3

  22. FDFS: Example

  23. MMDT fairness scheme achieves the best performance when the available power is a little bit more than the required energy. Result - 3

  24. Results from Uniform Distribution

  25. 1. Lie about Time (2 methods) • a. punish with extra time b. punished by fine • 2. Lie about Distance (2 methods) • a. punish with extra time (convert distance to time) 1 mile = 10 min • b. punished by fine Discussion of Lies

  26. Contract

  27. Thank you!

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