Network Loss Allocation for Peer- to- Peer Energy Trading among Prosumers in Virtual Power Plants

This paper proposes network Loss Allocation (LA) algorithm, addressing the often-overlooked issue of transmission losses in decentralized market mechanisms. Based on actual power flow directions between nodes, the algorithm ensures fair and transparent loss distribution. A P2P trading model incorporating this loss allocation mechanism is formulated and efficiently solved using the Alternating Direction Method of Multipliers (ADMM). Simulation results on the IEEE 14-bus system demonstrate that the proposed approach significantly reduces transmission losses, enhances overall economic performance, and improves prosumer participation. The method offers both theoretical and practical insights for developing fair and efficient distributed energy markets.

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Publication Details

Published
2025-07-25
DOI
https://doi.org/10.1109/aceee66257.2025.11148956
Primary Topic
Smart Grid Energy Management
Type
article
Field-Weighted Citation Impact
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article

Network Loss Allocation for Peer- to- Peer Energy Trading among Prosumers in Virtual Power Plants

Luhao Wang, Kezhen Han, Xingong Cheng, Yuanyuan Zhao et al.
Smart Grid Energy Management
article

Network Loss Allocation for Peer- to- Peer Energy Trading among Prosumers in Virtual Power Plants

Luhao Wang, Kezhen Han, Xingong Cheng, Yuanyuan Zhao, Shengnan Zhao, Qi Wang
article en

Abstract

This paper proposes network Loss Allocation (LA) algorithm, addressing the often-overlooked issue of transmission losses in decentralized market mechanisms. Based on actual power flow directions between nodes, the algorithm ensures fair and transparent loss distribution. A P2P trading model incorporating this loss allocation mechanism is formulated and efficiently solved using the Alternating Direction Method of Multipliers (ADMM). Simulation results on the IEEE 14-bus system demonstrate that the proposed approach significantly reduces transmission losses, enhances overall economic performance, and improves prosumer participation. The method offers both theoretical and practical insights for developing fair and efficient distributed energy markets.

University of Jinan (CN)
Openalex Percentile: Top 76%
Smart Grid Energy Management
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