State-of-the-art and prospects for peer-to-peer transaction-based energy system

JOGUNOLA, Olamide, IKPEHAI, Augustine, ANOH, Kelvin, ADEBISI, Bamidele, HAMMOUDEH, Mohammad, SON, Sung-Yong and HARRIS, Georgina (2017). State-of-the-art and prospects for peer-to-peer transaction-based energy system. Energies, 10 (12), p. 2106.

[img]
Preview
PDF
Ikpehai-StateOfTheArt(Vor).pdf - Published Version
Creative Commons Attribution.

Download (1MB) | Preview
Official URL: https://www.mdpi.com/1996-1073/10/12/2106
Open Access URL: https://www.mdpi.com/1996-1073/10/12/2106 (Published version)
Link to published version:: https://doi.org/10.3390/en10122106
Related URLs:

    Abstract

    © 2017 by the authors. Licensee MDPI, Basel, Switzerland. Transaction-based energy (TE) management and control has become an increasingly relevant topic, attracting considerable attention from industry and the research community alike. As a result, new techniques are emerging for its development and actualization. This paper presents a comprehensive review of TE involving peer-to-peer (P2P) energy trading and also covering the concept, enabling technologies, frameworks, active research efforts and the prospects of TE. The formulation of a common approach for TE management modelling is challenging given the diversity of circumstances of prosumers in terms of capacity, profiles and objectives. This has resulted in divergent opinions in the literature. The idea of this paper is therefore to explore these viewpoints and provide some perspectives on this burgeoning topic on P2P TE systems. This study identified that most of the techniques in the literature exclusively formulate energy trade problems as a game, an optimization problem or a variational inequality problem. It was also observed that none of the existing works has considered a unified messaging framework. This is a potential area for further investigation.

    Item Type: Article
    Uncontrolled Keywords: proactive prosumer; energy trading; peer-to-peer (P2P) communication; smart micro-grid (SMG); survey; optimization; game theory; multi-agent system (MAS); 09 Engineering; 02 Physical Sciences
    Identification Number: https://doi.org/10.3390/en10122106
    Page Range: p. 2106
    SWORD Depositor: Symplectic Elements
    Depositing User: Symplectic Elements
    Date Deposited: 26 Feb 2019 16:48
    Last Modified: 26 Feb 2019 16:48
    URI: http://shura.shu.ac.uk/id/eprint/23882

    Actions (login required)

    View Item View Item

    Downloads

    Downloads per month over past year

    View more statistics