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Framework design and optimal bidding strategy for ancillary service provision from a peer-to-peer energy trading community

Zhou, Yue, Wu, Jianzhong, Song, Guanyu and Long, Chao 2020. Framework design and optimal bidding strategy for ancillary service provision from a peer-to-peer energy trading community. Applied Energy 278 , 115671. 10.1016/j.apenergy.2020.115671

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Abstract

As an innovative paradigm for electric power systems with a high penetration of distributed energy resources, peer-to-peer (P2P)energy trading enables direct energy trading between end customers, which is able to facilitate local power and energy balance and potentially support the operation of bulk power systems. In this paper, a framework was proposed to enable ancillary service provision from a P2P energy trading community, creating additional value for both customers in the community and power systems. Specifically, an ancillary service provision mechanism was designed along with P2P energy trading and residual balancing mechanisms to enable the power utility to obtain ancillary service from customers in a P2P energy trading community. Furthermore, the optimal bidding strategy of customers was figured out to maximize their benefits in the proposed mechanisms.Simulation studies were conducted based on a residential community in Great Britain. The results show that the proposed ancillary service mechanism can enable the power utility to obtain a significant or required amount of ancillary services of different types.The proposed mechanisms and optimal bidding strategy can achieve Pareto improvement for the revenue of each custome rand result in significantly higher social welfare for the whole community. It is also revealed that increasing ancillary service prices and installation rate of electric vehicles can increase the total amount of ancillary service provision and thus bring higher revenue for the customers in the community. By contrast, increasing installation of PV systems does not necessarily increase the amount of service provision.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Engineering
Publisher: Elsevier
ISSN: 0306-2619
Funders: EPSRC
Date of First Compliant Deposit: 10 August 2020
Date of Acceptance: 7 August 2020
Last Modified: 14 Sep 2020 13:20
URI: http://orca.cf.ac.uk/id/eprint/134127

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