Statistical impact quantification of peer-to-peer energy trading on power flows of power distribution networks

Gan, Wei, Zhou, Yue ORCID: https://orcid.org/0000-0002-6698-4714, Wu, Jianzhong ORCID: https://orcid.org/0000-0001-7928-3602 and Abeysinghe, Sathsara 2024. Statistical impact quantification of peer-to-peer energy trading on power flows of power distribution networks. Presented at: IEEE Conference on Energy Internet and Energy System Integration (EI2), Hangzhou, China, 15-18 December 2023. 2023 IEEE 7th Conference on Energy Internet and Energy System Integration (EI2). IEEE, pp. 4517-4522. 10.1109/EI259745.2023.10513181

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Abstract

As distributed energy resources become increasingly prevalent within power distribution networks (PDN), the emergence of peer-to-peer (P2P) energy trading stands out as a crucial solution for effective resource management. However, a pressing question remains: How does P2P energy trading universally influence PDN's peak flows? To bridge this knowledge gap, our paper firstly proposes a statistical evaluation method for quantifying P2P energy trading's impact on network flows based on the development of statistically similar PDN generation. This innovative approach is designed to generate PDNs that bear similarities to a wide range of real-world PDNs in terms of topological and electrical characteristics. Thereby, it ensures findings are not constrained to singular networks, but applicable universally. A novel PDN operational model incorporating P2P energy trading is also proposed, where an impact quantification indicator is introduced to reflect and optimize the overall network peak flows without compromising operational cost of peers. Numerical results based on real-world British PDNs are provided to validate the effectiveness of the proposed method.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Published Online
Status:	Published
Schools:	Engineering
Publisher:	IEEE
Last Modified:	12 Jun 2024 10:00
URI:	https://orca.cardiff.ac.uk/id/eprint/169608

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