Power flow traceable P2P electricity market segmentation and cost allocation

Chengwei Lou, Jin Yang, Eduardo Vega Fuentes, Yue Zhou, Liang Min, James Yu and Nand Kishor Meena

Energy, 2024, vol. 290, issue C

Abstract: This study explores peer-to-peer (P2P) electricity trading, emphasizing not just the export and consumption, but also the feasible physical supply of electricity and the use of distribution network assets. Building on a transaction-oriented dynamic power flow tracing model, a novel P2P market architecture is proposed. This architecture integrates the electricity market with the power network, considering technical constraints, network losses, and asset usage. The network is segmented into potential markets using second-order cone programming (SOCP), with an optimization problem introduced for loss-allocation. This problem merges network physical analysis and variable outputs from distributed energy resources (DERs). A graph-based P2P electricity trading model is designed to determine optimal transaction cost allocation and maximize benefits for both DERs and consumers. A case study on a modified IEEE 33-node test feeder substantiates the benefits of this market structure, demonstrating increased revenues for DERs and reduced bills for consumers compared to traditional feed-in-tariffs.

Keywords: Power distribution networks; Distributed energy resources; Dynamic power flow tracing; Loss allocation; P2P electricity market (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:290:y:2024:i:c:s0360544223035144

DOI: 10.1016/j.energy.2023.130120

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