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

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)...

Full description

Saved in:
Bibliographic Details
Published in:Energies (Basel) 2024-12, Vol.17 (24), p.6239
Main Authors: Yang, Tianmeng, Liu, Jicheng, Feng, Wei, Chen, Zelong, Zhao, Yumin, Lou, Suhua
Format: Article
Language:English
Subjects:
Alternative energy
Alternative energy sources
Coal-fired power plants
Costs
dynamic price mechanism
Electricity
Energy consumption
Energy industry
Energy storage
Energy trading
flexible resource schedule
Hydroelectric power
P2P energy trading
Prices
Prices and rates
regional power balance
Regions
renewable energy integration
Renewable resources
Securities trading
Solar energy
Success
Supply & demand
Supply and demand
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:1996-1073
1996-1073
DOI:10.3390/en17246239