Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/145055
Title: Peer-to-peer energy trading in smart grid considering power losses and network fees
Authors: Paudel, Amrit
Sampath, Lahanda Purage Mohasha Isuru
Yang, Jiawei
Gooi, Hoay Beng
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2020
Source: Paudel, A., Sampath, L. P. M. I., Yang, J., & Gooi, H. B. (2020). Peer-to-peer energy trading in smart grid considering power losses and network fees. IEEE Transactions on Smart Grid, 11(6), 4727-4737. doi:10.1109/tsg.2020.2997956
Project: A1990b0060
Journal: IEEE Transactions on Smart Grid
Abstract: Peer-to-peer (P2P) energy trading is one of the promising approaches for implementing decentralized electricity market paradigms. In the P2P trading, each actor negotiates directly with a set of trading partners. Since the physical network or grid is used for energy transfer, power losses are inevitable, and grid-related costs always occur during the P2P trading. A proper market clearing mechanism is required for the P2P energy trading between different producers and consumers. This paper proposes a decentralized market clearing mechanism for the P2P energy trading considering the privacy of the agents, power losses as well as the utilization fees for using the third party owned network. Grid-related costs in the P2P energy trading are considered by calculating the network utilization fees using an electrical distance approach. The simulation results are presented to verify the effectiveness of the proposed decentralized approach for market clearing in P2P energy trading.
URI: https://hdl.handle.net/10356/145055
ISSN: 1949-3053
DOI: 10.1109/tsg.2020.2997956
Rights: © 2020 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 or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/tsg.2020.2997956
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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