55th International Universities Power Engineering Conference - UPEC 2020, Turin (Italy) Online. 01-04 septiembre 2020
Resumen:
The progressive development of local energy communities requires the reorganization of the energy production and consumption, with a new energy system in which the technical and commercial decision-making process need to be decentralized from central authorities to distributed entities properly coordinated. This will be increasingly aided by the spread of IoT systems capable of interacting among distributed resources. The technical and commercial energy management burden will be then shared among cooperating IoT devices, which will perform the necessary optimization and control operations. In this context, a Decentralized Genetic Algorithm (DGA) methodology, able to perform a wide spectrum of power system optimizations in a fully decentralized fashion is introduced. This paper aim at developing a DGA management procedure, tested considering a model for a local energy market and an automated distributed resource scheduling in a local energy community. The testing is performed through a HIL experimental setup, which proves the effectiveness of the methodology proposed, as well as a Blockchain platform.
Palabras clave: Energy communities , local energy markets , real time simulation , Internet of Things , Distributed Optimization , Genetic Algorithms
DOI: 
https://doi.org/10.1109/UPEC49904.2020.9209855
Publicado en UPEC 2020, pp: 1-6, ISBN: 978-1-7281-1079-0
Fecha de publicación: 2020-09-30.
Cita:
M. Mureddu, M. Galici, E. Ghiani, F. Pilo, A decentralized market solver for local energy communities, 55th International Universities Power Engineering Conference - UPEC 2020, Turin (Italy) Online. 01-04 septiembre 2020. En: UPEC 2020: Conference proceedings, ISBN: 978-1-7281-1079-0
