A Three-Layer Scheduling Framework with Dynamic Peer-to-Peer Energy Trading for Multi-Regional Power Balance

Tianmeng Yang, Jicheng Liu, Wei Feng, Zelong Chen, Yumin Zhao and Suhua Lou ()
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Tianmeng Yang: Northeast Branch of State Grid Corporation of China, Shenyang 110180, China
Jicheng Liu: Northeast Branch of State Grid Corporation of China, Shenyang 110180, China
Wei Feng: Northeast Branch of State Grid Corporation of China, Shenyang 110180, China
Zelong Chen: Northeast Branch of State Grid Corporation of China, Shenyang 110180, China
Yumin Zhao: Northeast Branch of State Grid Corporation of China, Shenyang 110180, China
Suhua Lou: State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Wuhan 430074, China

Energies, 2024, vol. 17, issue 24, 1-15

Abstract: This paper addresses the critical challenges of renewable energy integration and regional power balance in smart grids, which have become increasingly complex with the rapid growth of distributed energy resources. It proposes a novel three-layer scheduling framework with a dynamic peer-to-peer (P2P) trading mechanism to address these challenges. The framework incorporates a preliminary local supply–demand balance considering renewable energy, followed by an inter-regional P2P trading layer and, ultimately, flexible resource deployment for final balance adjustment. The proposed dynamic continuous P2P trading mechanism enables regions to autonomously switch roles between buyer and seller based on their internal energy status and preferences, facilitating efficient trading while protecting regional privacy. The model features an innovative price update mechanism that initially leverages historical trading data and dynamically adjusts prices to maximize trading success rates. To address the heterogeneity of regional resources and varying energy demands, the framework implements a flexible trading strategy that allows for differentiated transaction volumes and prices. The effectiveness of the proposed framework is validated through simulation experiments using k-means clustered typical daily data from four regions in Northeast China. The results demonstrate that the proposed approach successfully promotes renewable energy utilization, reduces the operational costs of flexible resources, and achieves an efficient inter-regional energy balance while maintaining regional autonomy and information privacy.

Keywords: P2P energy trading; renewable energy integration; dynamic price mechanism; regional power balance; flexible resource schedule (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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