A Decentralized Market Solver for Local Energy Communities

Mureddu, Mario
Conceptualization
;
Galici, Marco
Software
;
Ghiani, Emilio
Writing – Review & Editing
;
Pilo, Fabrizio
Writing – Review & Editing
2020-01-01

Abstract

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
2020
Inglese
2020 55th International Universities Power Engineering Conference (UPEC)
978-1-7281-1078-3
IEEE
STATI UNITI D'AMERICA
1
6
6
2020 55th International Universities Power Engineering Conference (UPEC)
Contributo
Esperti anonimi
1-4 Sept. 2020
Torino
internazionale
scientifica
Energy communities, local energy markets, real time simulation, Internet of Things, Distributed Optimization, Genetic Algorithms
no
4 Contributo in Atti di Convegno (Proceeding)::4.1 Contributo in Atti di convegno
Mureddu, Mario; Galici, Marco; Ghiani, Emilio; Pilo, Fabrizio
273
4
4.1 Contributo in Atti di convegno
reserved
info:eu-repo/semantics/conferencePaper
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