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TecnoLógicas

Print version ISSN 0123-7799On-line version ISSN 2256-5337

Abstract

SANCHEZ-SILVERA, Alfredo; GUARNIZO-MARIN, José Guillermo; FORERO-GARCIA, Edwin Francisco  and  MONTENEGRO-MARTINEZ, Davis. Decentralized Energy Management System Based on Multi-agents to Operate Multiple Microgrids. TecnoL. [online]. 2021, vol.24, n.51, pp.94-119.  Epub Oct 04, 2021. ISSN 0123-7799.  https://doi.org/10.22430/22565337.1880.

Microgrids have experienced a significant development in recent years because they represent a technical alternative to respond to contingencies in electrical distribution networks and increase the level of distributed generation, among other benefits. The objective of this study is to design an architecture based on multi-agent systems that can be used to manage the operating mode of a distributed microgrid system in an islanded environment. In such architecture, the correct connection of the common bus that links all the microgrids with the multi-agent system is maintained, and overloads and deep discharges in the batteries are avoided. The methodology implemented here is empirical-analytical. The simulation is based on a review of the state of the art that was conducted to find a strategy that can coordinate a composite microgrid system where the microgrids are connected to the same distribution system operating in islanded mode. The system was simulated using OpenDSS-G and Python. The results obtained suggest that a decentralized energy management system based on the theory of multi-agent systems can have important benefits; for example, the autonomous nature of microgrids for power generation in non-interconnected areas. Finally, multi-agent theory can be employed to create more reliable distributed generation systems (due to their autonomous decision-making capacity), meet the electrical demands of neighboring microgrids, and jointly prevent overcharges and deep discharges in batteries.

Keywords : Microgrids; multi agent systems; electrical energy management; distributed system; OpenDSS G simulation.

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