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| Content Provider | IET Digital Library |
|---|---|
| Author | Rana, Rubi Bhattacharjee, Shayari Mishra, Sukumar |
| Abstract | Electric Vehicles (EVs) can be considered as a flexible source of energy which can receive some benefit in terms of incentives for selling their energy. For efficient and economic trading amongst the EV owners, various researchers have proposed a variety of preference based matching algorithms like College Admission Framework (CAF), Max-weight, Merge and Split, Gale-Shapley Algorithm and Brute-Force Algorithm etc, where buyer and seller EVs can exchange energy and receive better payoffs. Unlike the above mentioned algorithms, in this paper the participating entities do not submit the preferences menu (which contains preferred choices of sellers (of a buyer) and of buyers (for a seller)) to a central authority.) However, this paper proposes an assignment energy trading game where no central authority is needed, the matching algorithm is hosted on cloud which matches charging and discharging of EVs based on their aspiration level and bids. The contribution of the work is to deduce the bids and aspiration level of charging and discharging EVs which is not considered in any of the existing work. Another contribution of the work is the behavioral assignment game that eludes the need of integer linear programming problem and deduces the convergence of game by adjustments of aspiration levels. Futhermore, the entire algorithm is cloud hosted with no middleman hence trading EVs identities are concealed from each other making the system unbiased. The proposed game helps both the buyer and the seller side of EVs to achieve their best bids as well as by reducing grid dependency it boosts the profit margin of the charging stations (CS). |
| Starting Page | 371 |
| Ending Page | 380 |
| Page Count | 10 |
| Volume Number | 2 |
| e-ISSN | 25152947 |
| Issue Number | Issue 3, Sep (2019) |
| Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/iet-stg/2/3 |
| Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/10.1049/iet-stg.2019.0013 |
| Journal | IET Smart Grid |
| Publisher | The Institution of Engineering and Technology |
| Publisher Date | 2019-04-23 |
| Access Restriction | Open |
| Rights License | Creative Commons Attribution -Non Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) |
| Subject Keyword | Above-mentioned Algorithm Aspiration Level Assignment Energy Trading Game Assignment Matching-theoretic Game Behavioural Assignment Game Bids Brute-Force Algorithm Buyer Central Authority Charging Discharging EVs Charging EVs College Admission Framework Economic Trading Efficient Trading Electric Vehicle Energy Trading Framework Energy Trading Mechanism Entire Algorithm EV Owners EVs Identities Gale-Shapley Algorithm Game Theory Integer Programming Linear Programming Matching Algorithm Mobility Optimisation Technique Power System Economics Power System Managemen Power System Operation Proposed Game Seller EVs Time 24 H Transportation Transportation Industry |
| Content Type | Text |
| Resource Type | Article |
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