Peer-to-Peer energy trading considering the output uncertainty of distributed energy resources

Introducing P2P energy trading in the consumers’ local market makes the energy utilization rates of users improved significantly. However, the output uncertainty of distributed energy sources poses challenges to the normal conduct of the P2P transaction. The uncertainty sources have to pay for the r...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Yuanxing Xia, Qingshan Xu, Haiya Qian, Li Cai
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2022
Materias:	Peer-to-Peer energy trading Robust optimization Uncertainty management Electricity market Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/0e5e2085316e4022a342544193bce9b5
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:0e5e2085316e4022a342544193bce9b5
record_format	dspace
spelling	oai:doaj.org-article:0e5e2085316e4022a342544193bce9b52021-12-04T04:34:45ZPeer-to-Peer energy trading considering the output uncertainty of distributed energy resources2352-484710.1016/j.egyr.2021.11.001https://doaj.org/article/0e5e2085316e4022a342544193bce9b52022-04-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2352484721011458https://doaj.org/toc/2352-4847Introducing P2P energy trading in the consumers’ local market makes the energy utilization rates of users improved significantly. However, the output uncertainty of distributed energy sources poses challenges to the normal conduct of the P2P transaction. The uncertainty sources have to pay for the reserve resources for the possible power gap. The difference between the actual output and the day ahead market planning needs to be charged to punish the uncertainty producers. Therefore, a novel pricing strategy (uncertainty marginal price, UMP) is proposed in this aper to charge the uncertainty producers and credit the reserve resources. Voltage sensitivity coefficients, power transfer distribution factors and loss sensitivity factors are introduced to linearize the power flow model. The whole problem can be formulated as a robust model and decomposed into two subproblems. CCG algorithm is applied to solve the two-stage robust model. This new pricing strategy is verified on the IEEE-33 and 69 bus systems. Numerical results indicate that the proposed price increases with the rise of uncertainty level. The reference points of the system robustness can be chosen as the inflection points of the operation cost curves under different uncertainty levels.Yuanxing XiaQingshan XuHaiya QianLi CaiElsevierarticlePeer-to-Peer energy tradingRobust optimizationUncertainty managementElectricity marketElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENEnergy Reports, Vol 8, Iss , Pp 567-574 (2022)
institution	DOAJ
collection	DOAJ
language	EN
topic	Peer-to-Peer energy trading Robust optimization Uncertainty management Electricity market Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	Peer-to-Peer energy trading Robust optimization Uncertainty management Electricity market Electrical engineering. Electronics. Nuclear engineering TK1-9971 Yuanxing Xia Qingshan Xu Haiya Qian Li Cai Peer-to-Peer energy trading considering the output uncertainty of distributed energy resources
description	Introducing P2P energy trading in the consumers’ local market makes the energy utilization rates of users improved significantly. However, the output uncertainty of distributed energy sources poses challenges to the normal conduct of the P2P transaction. The uncertainty sources have to pay for the reserve resources for the possible power gap. The difference between the actual output and the day ahead market planning needs to be charged to punish the uncertainty producers. Therefore, a novel pricing strategy (uncertainty marginal price, UMP) is proposed in this aper to charge the uncertainty producers and credit the reserve resources. Voltage sensitivity coefficients, power transfer distribution factors and loss sensitivity factors are introduced to linearize the power flow model. The whole problem can be formulated as a robust model and decomposed into two subproblems. CCG algorithm is applied to solve the two-stage robust model. This new pricing strategy is verified on the IEEE-33 and 69 bus systems. Numerical results indicate that the proposed price increases with the rise of uncertainty level. The reference points of the system robustness can be chosen as the inflection points of the operation cost curves under different uncertainty levels.
format	article
author	Yuanxing Xia Qingshan Xu Haiya Qian Li Cai
author_facet	Yuanxing Xia Qingshan Xu Haiya Qian Li Cai
author_sort	Yuanxing Xia
title	Peer-to-Peer energy trading considering the output uncertainty of distributed energy resources
title_short	Peer-to-Peer energy trading considering the output uncertainty of distributed energy resources
title_full	Peer-to-Peer energy trading considering the output uncertainty of distributed energy resources
title_fullStr	Peer-to-Peer energy trading considering the output uncertainty of distributed energy resources
title_full_unstemmed	Peer-to-Peer energy trading considering the output uncertainty of distributed energy resources
title_sort	peer-to-peer energy trading considering the output uncertainty of distributed energy resources
publisher	Elsevier
publishDate	2022
url	https://doaj.org/article/0e5e2085316e4022a342544193bce9b5
work_keys_str_mv	AT yuanxingxia peertopeerenergytradingconsideringtheoutputuncertaintyofdistributedenergyresources AT qingshanxu peertopeerenergytradingconsideringtheoutputuncertaintyofdistributedenergyresources AT haiyaqian peertopeerenergytradingconsideringtheoutputuncertaintyofdistributedenergyresources AT licai peertopeerenergytradingconsideringtheoutputuncertaintyofdistributedenergyresources
_version_	1718372952022450176

Peer-to-Peer energy trading considering the output uncertainty of distributed energy resources

Ejemplares similares