Name
Abstract | ||
|---|---|---|
Autonomous electric vehicles (AEVs) are gaining ground around the world. They are equipped with intelligent decision-making capabilities that allow them to optimize on their battery usage and engage in energy trading for profit maximization. This paper envisions a market model, where energy aggregators considers buying and selling electricity from AEVs. In this system, the aggregators reside on cloudlets at the edge of a cloud computing system for prompt communication and negotiation with AEVs. Whether they are parked or en-route, AEVs can be crowdsourced to provide energy to consumers at needed times. This study proposes double auction models to incentivize AEV agents to participate in the market based on their time preferences and energy pricing. The proposed system implements dynamic pricing structures, which are applicable to various scenarios of energy trading. To evaluate the proposed system, this paper provides extensive theoretical analysis and simulation experiments to demonstrate that the proposed auctioning models are computationally efficient, truthful, individually rational, and budget balanced. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/TVT.2019.2920531 | IEEE Transactions on Vehicular Technology |
Keywords | Field | DocType |
Computational modeling,Analytical models,Vehicle dynamics,Load modeling,Crowdsourcing,Electric vehicles,Companies | Dynamic pricing,Electricity,Computer science,Crowdsourcing,Computer network,Operations research,Vehicle dynamics,Profit maximization,Double auction,Negotiation,Cloud computing | Journal |
Volume | Issue | ISSN |
68 | 8 | 0018-9545 |
Citations | PageRank | References |
4 | 0.42 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| abdulsalam yassine | 1 | 229 | 23.42 |
| M. Shamim Hossain | 2 | 1171 | 83.62 |
| Ghulam Muhammad | 3 | 770 | 60.81 |
| Mohsen Guizani | 4 | 6456 | 557.44 |