{"title":"A fully decentralized spatiotemporal decomposition method for real-time peer-to-peer trading in distribution network","authors":"Jianquan Zhu, Wenhao Liu, Langsen Fang, Ruibing Wu, Jiajun Chen","doi":"10.1016/j.segan.2025.101729","DOIUrl":null,"url":null,"abstract":"<div><div>High penetration of distributed renewable energy (DRE) promotes the development of peer-to-peer (P2P) trading. In this study, P2P trading is extended from a deterministic single-period model to a stochastic multi-period model, which considers the interaction of both spatial and temporal dimensions. A stochastic dual dynamic programming (SDDP)-based decentralized method is proposed to coordinate this spatiotemporal effect. In the spatial dimension, the impact of bilateral transactions on power flow is considered by prosumers independently based on the cumulative effect of branch capacity and bus voltage shift, which protects the privacy of P2P trading while preventing power flow violation. In the temporal dimension, the influence between periods is coordinated by prosumers based on the state of charge (SOC), which gives them overview abilities to handle future uncertainties. Besides, the dynamic cut-set selecting strategy is presented to improve the solving efficiency of SDDP. Numerical simulations demonstrate the effectiveness of the proposed method, which can reduce the computational time by 52 %.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"43 ","pages":"Article 101729"},"PeriodicalIF":4.8000,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sustainable Energy Grids & Networks","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352467725001110","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 0
Abstract
High penetration of distributed renewable energy (DRE) promotes the development of peer-to-peer (P2P) trading. In this study, P2P trading is extended from a deterministic single-period model to a stochastic multi-period model, which considers the interaction of both spatial and temporal dimensions. A stochastic dual dynamic programming (SDDP)-based decentralized method is proposed to coordinate this spatiotemporal effect. In the spatial dimension, the impact of bilateral transactions on power flow is considered by prosumers independently based on the cumulative effect of branch capacity and bus voltage shift, which protects the privacy of P2P trading while preventing power flow violation. In the temporal dimension, the influence between periods is coordinated by prosumers based on the state of charge (SOC), which gives them overview abilities to handle future uncertainties. Besides, the dynamic cut-set selecting strategy is presented to improve the solving efficiency of SDDP. Numerical simulations demonstrate the effectiveness of the proposed method, which can reduce the computational time by 52 %.
期刊介绍:
Sustainable Energy, Grids and Networks (SEGAN)is an international peer-reviewed publication for theoretical and applied research dealing with energy, information grids and power networks, including smart grids from super to micro grid scales. SEGAN welcomes papers describing fundamental advances in mathematical, statistical or computational methods with application to power and energy systems, as well as papers on applications, computation and modeling in the areas of electrical and energy systems with coupled information and communication technologies.