Low-Complexity Charging/Discharging Scheduling for Electric Vehicles at Home and Common Lots for Smart Households Prosumers

Mehrabidavoodabadi, Abbas and Kim, Kiseon (2018) Low-Complexity Charging/Discharging Scheduling for Electric Vehicles at Home and Common Lots for Smart Households Prosumers. IEEE Transactions on Consumer Electronics, 64 (3). pp. 348-355. ISSN 0098-3063

[img]
Preview
Text
SCI_Mehrabi_8430588.pdf - Accepted Version

Download (510kB) | Preview
Official URL: https://doi.org/10.1109/TCE.2018.2864548

Abstract

Plug-in electric vehicles are becoming one of indispensable prosumer electronics components for smart households and therefore, their cost efficient energy scheduling is one of the main challenging issues. In the current schemas, the charging and discharging interval of the vehicles are normally announced by the owners in advance leading to the suboptimal profit gain in some situations and hence consumers dissatisfaction. In this paper, we propose an efficient charging/discharging scheduling mechanism for electric vehicles in multiple homes common parking lot for smart households prosumers. The proposed mechanism takes into account the optimal interval allocation considering the instantaneous electricity load and the vehicles request pattern. Based on the data from the vehicles, a mixed optimization model is formulated by the central scheduler which aims to maximize the profit of consumers and is then solved using an effective algorithm. The optimization results are then sent to the system controller determining the interval and energy trading patterns between the power grid and the vehicles. The proposed algorithm has low complexity and ensures the energy satisfaction for all consumers. The performance of the scheduling schema is verified through multiple simulation scenarios.

Item Type: Article
Uncontrolled Keywords: Plug-in electric vehicles, home stations, charging and discharging, profit maximization, consumers satisfaction
Subjects: G400 Computer Science
G500 Information Systems
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Elena Carlaw
Date Deposited: 04 Jun 2020 12:09
Last Modified: 04 Jun 2020 12:15
URI: http://nrl.northumbria.ac.uk/id/eprint/43342

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics