ACN-Sim: An Open-Source Simulator for Data-Driven Electric Vehicle Charging Research

@article{Lee2019ACNSimAO,
  title={ACN-Sim: An Open-Source Simulator for Data-Driven Electric Vehicle Charging Research},
  author={Zachary J. Lee and Daniel Johansson and Steven H. Low},
  journal={Proceedings of the Tenth ACM International Conference on Future Energy Systems},
  year={2019}
}
Electric vehicles have recently garnered significant attention in the research community due to their potential has a large, highly controllable load which can be used in demand response, load shaping, and renewable energy integration. However, research into practical charging algorithms has been hampered by the lack of a widely available, realistic simulation environment. To meet this need in the community, we are releasing ACN-Sim, a data-driven, open-source simulator based on our experience… Expand
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References

SHOWING 1-10 OF 39 REFERENCES
ACN-Sim: An Open-Source Simulator for Data-Driven Electric Vehicle Charging Research
  • Zachary J. Lee, D. Johansson, S. Low
  • Computer Science
  • 2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)
  • 2019
TLDR
ACN-Sim is developed, a data-driven, open-source simulator based on the experience building and operating real-world charging systems which models the complexity of real charging systems, including battery charging behavior and unbalanced three-phase infrastructure. Expand
Large-Scale Adaptive Electric Vehicle Charging
  • Zachary J. Lee, Daniel Chang, +4 authors S. Low
  • Computer Science
  • 2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)
  • 2018
TLDR
This paper addresses the prohibitively high capital cost of installing large numbers of charging stations within a parking facility by oversubscribing key pieces of electrical infrastructure by introducing constraints to the EV charging problem which have not been considered in the literature, such as those imposed by unbalanced three-phase infrastructure. Expand
Adaptive Charging Networks: A Framework for Smart Electric Vehicle Charging
TLDR
It is found that in these realistic settings, the Adaptive Scheduling Algorithm can improve operator profit by 3.4 times over uncontrolled charging and consistently outperforms baseline algorithms when delivering energy in highly congested systems. Expand
A Review of Charge Scheduling of Electric Vehicles in Smart Grid
TLDR
This review covers the recent works done in the area of scheduling algorithms for charging EVs in smart grid and reviews the key results in this field following the classification proposed. Expand
EVLibSim: A tool for the simulation of electric vehicles' charging stations using the EVLib library
TLDR
EVLibSim is a tool for the simulation of EV activities at a charging station level that unifies EVLib’s primary functions such as the charging and dis-charging of batteries, battery swapping, as well as parking/inductive charging. Expand
Adaptive charging network for electric vehicles
TLDR
It is demonstrated, by simulating a charging algorithm on the baseline data, the large potential benefit of ACN in saving infrastructure costs. Expand
Smart Charging for Electric Vehicles: A Survey From the Algorithmic Perspective
TLDR
Important dominating factors for coordinated charging from three different perspectives are studied, in terms of smart grid oriented, aggregator-oriented, and customer-oriented smart charging. Expand
Clean vehicles as an enabler for a clean electricity grid
California has issued ambitious targets to decarbonize transportation through the deployment of electric vehicles (EVs), and to decarbonize the electricity grid through the expansion of bothExpand
Pricing EV charging service with demand charge
TLDR
An online scheduling algorithm based on model predictive control to determine charging rates for each EV in real-time is proposed and simulation results suggest that the online algorithm can approximate the offline optimal reasonably well. Expand
OPEN: An open-source platform for developing smart local energy system applications
TLDR
Case studies are presented, demonstrating how OPEN can be used for a range of smart local energy system applications due to its support of multiple model fidelities for simulation and control. Expand
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