Eric Bernardes Chagas Barros
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Eric Bernardes Chagas Barros has a total of 13 co-authors. Here are the top co-authors by number of shared publications:
- Maycon Leone Maciel Peixoto
UFBA
3 shared publications Bruno G. Batista
1 shared publication- Bruno Guazzelli Batista
UNIFEI
1 shared publication Bruno T. Kuehne
1 shared publication- Bruno Tardiole Kuehne
Fed. Univ. of Itajuba, Itajuba, Brazil
1 shared publication Damla Turgut
1 shared publication
Latest Publications
- 5 January 2025
- Published by Elsevier in Computer Networks
- Vol. 258
FOCCA: Fog–cloud continuum architecture for data imputation and load balancing in Smart Grids
- 5 January 2025
- Published by Elsevier in Computer Networks
- Vol. 258
FOCCA: Fog–cloud continuum architecture for data imputation and load balancing in Smart Grids
- Open Access
Fog Computing Model to Orchestrate the Consumption and Production of Energy in Microgrids
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.
Open AccessFog Computing Model to Orchestrate the Consumption and Production of Energy in Microgrids
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.