Wang, Ruichi, Wu, Jiande, Qian, Zhongnan, Lin, Zhengyu and He, Xiangning (2017). A graph theory based energy routing algorithm in Energy Local Area Network (e-LAN). IEEE Transactions on Industrial Informatics, 13 (6), 3275 - 3285.
Abstract
The energy internet concept has been considered as a new development stage of the Smart Grid, which aims to increase the energy transmission efficiency and optimise the energy dispatching in time and space. Energy router is a core device in the energy internet and it connects all the devices together into a net structure and manages power flows among them. The research work presented in this paper described the energy router’s structure and function expectations from the network perspective, and improved the existing energy router design. Open-shortest-path first (OSPF) protocol and virtual circuit switching mode are referenced from the Internet in the energy local area network (e-LAN) design. This paper proposed a design of an energy routing algorithm based on graph theory in an e-LAN. A lowest-cost routing selection algorithm is designed according to the features of power transmission, and a source selection and routing design algorithm is proposed for very heavy load conditions. Both algorithms have been verified by case analyses.
Publication DOI: | https://doi.org/10.1109/TII.2017.2713040 |
---|---|
Additional Information: | © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers Funding: National Nature Science Foundation of China (51577170); and EU H2020 research and innovation programme (734769). |
Uncontrolled Keywords: | energy internet,energy router,routing algorithm,smart grid |
Publication ISSN: | 1551-3203 |
Last Modified: | 06 Nov 2024 08:09 |
Date Deposited: | 14 Jun 2017 14:00 | PURE Output Type: | Article |
Published Date: | 2017-12-01 |
Published Online Date: | 2017-06-07 |
Accepted Date: | 2017-05-28 |
Authors: |
Wang, Ruichi
Wu, Jiande Qian, Zhongnan Lin, Zhengyu ( 0000-0001-7733-2431) He, Xiangning |