Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/122262
Título: Market segmentation for P2P energy trading based on power flow tracing
Autores/as: Lou, C.
Vega Fuentes, Eduardo 
Yang, J.
Meena, N. K.
Clasificación UNESCO: 33 Ciencias tecnológicas
Palabras clave: Distributed Energy Resources
Distribution Networks
Dynamic Power Flow Tracing
Losses Allocation
P2P Energy Trading
Fecha de publicación: 2022
Editor/a: IET - The Institution of Engineering and Technology
Conferencia: 13th Mediterranean Conference on Power Generation, Transmission, Distribution and Energy Conversion (MEDPOWER 2022)
Resumen: Peer-to-peer (P2P) energy trading is gaining the attention of prosumers avid to participate in the electricity markets. In most P2P energy trading analysis, the exchange accounts for the electricity export and import within the same time range ignoring the physical feasibility of the power supply from the generator to the consumer and the usage of the distribution network assets. In this work the feasible P2P market structure based on dynamic power flow tracing is explored. The market segmentation into potential markets is modelled and formulated by means of second-order cone programming. As a result, the active power marketentry limitations for prosumers are identified, the losses incurred by distributed energy resources in power transactions are approximated and the potential of the methodology is revealed, paving the way towards fair and transparent P2P electricity markets.
URI: http://hdl.handle.net/10553/122262
ISBN: 978-1-83953-844-5
ISSN: 2732-4494
DOI: 10.1049/icp.2022.3310
Fuente: 13th Mediterranean Conference on Power Generation, Transmission, Distribution and Energy Conversion (MEDPOWER 2022), Conference Proceedings [EISSN 2732-4494], v. 2022 (25), p. 100-103, (Enero 2022)
Colección:Actas de congresos
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