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Fog Computing Model to Orchestrate the Consumption and Production of Energy in Microgrids

1
Computer Department, Federal University of Bahia (UFBA), Salvador 40170110, Brazil
2
Computer Department, Federal University of MS (UFMS), Ponta Pora 79907414, Brazil
3
Computer Department, Federal University of Itajuba (UNIFEI), Itajuba 37500903, Brazil
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(11), 2642; https://doi.org/10.3390/s19112642
Received: 4 April 2019 / Revised: 4 June 2019 / Accepted: 5 June 2019 / Published: 11 June 2019
(This article belongs to the Section Intelligent Sensors)
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Abstract

Energy advancement and innovation have generated several challenges for large modernized cities, such as the increase in energy demand, causing the appearance of the small power grid with a local source of supply, called the Microgrid. A Microgrid operates either connected to the national centralized power grid or singly, as a power island mode. Microgrids address these challenges using sensing technologies and Fog-Cloudcomputing infrastructures for building smart electrical grids. A smart Microgrid can be used to minimize the power demand problem, but this solution needs to be implemented correctly so as not to increase the amount of data being generated. Thus, this paper proposes the use of Fog computing to help control power demand and manage power production by eliminating the high volume of data being passed to the Cloud and decreasing the requests’ response time. The GridLab-d simulator was used to create a Microgrid, where it is possible to exchange information between consumers and generators. Thus, to understand the potential of the Fog in this scenario, a performance evaluation is performed to verify how factors such as residence number, optimization algorithms, appliance shifting, and energy sources may influence the response time and resource usage. View Full-Text
Keywords: smart grid; microgrid; fog; cloud; energy distribution model; power grid; performance evaluation smart grid; microgrid; fog; cloud; energy distribution model; power grid; performance evaluation
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Barros, E.B.C.; Filho, D.M.L.; Batista, B.G.; Kuehne, B.T.; Peixoto, M.L.M. Fog Computing Model to Orchestrate the Consumption and Production of Energy in Microgrids. Sensors 2019, 19, 2642.

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