| Grant number: | 20/16635-9 |
| Support Opportunities: | Scholarships in Brazil - Post-Doctoral |
| Start date: | March 01, 2021 |
| End date: | June 30, 2022 |
| Field of knowledge: | Engineering - Electrical Engineering - Power Systems |
| Principal Investigator: | Fernando Pinhabel Marafão |
| Grantee: | Hildo Guillardi Júnior |
| Host Institution: | Instituto de Ciência e Tecnologia. Universidade Estadual Paulista (UNESP). Campus de Sorocaba. Sorocaba , SP, Brazil |
| Associated research grant: | 16/08645-9 - Interdisciplinary research activities in electric smart grids, AP.TEM |
Abstract Smart Grids represent a new electrical system architecture that should, over the next decades, consolidate itself in a scenario with different devices (meters, electronic converters, sensors, etc.) distributed and with different degrees of communication, automation and intelligence, in favor of the increasingly efficient and intelligent use of energy generation, distribution or consumption systems. However, to achieve this scenario with electrical systems provided with large volumes of information, some level of intelligence and with possibilities of communication between network agents, much remains to be studied, researched, developed or improved in terms of equipment and methodologies of operation, control and supervision of the electrical networks. In this context, the concept of Virtual Power Plants (VPP) emerges, which corresponds to a central controller for the management of the electric network, which holds detailed information on the availability of distributed energy resources, meteorological information, energy tariffs, as well as historical profile and real-time measurements of loads (demand), enabling efficient energy management in associated networks. Thus, this project proposes a detailed study of the concept of VPPs for applications in low voltage networks, especially considering the particularities of the Brazilian electrical system. We will seek to create conditions for the development of methodologies and computational techniques suitable for the automatic and coordinated management of distributed energy resources and demand, using data provided / extracted from power meters, generators and energy storages distributed over the network, as well as other information that dynamically impact the cost or availability of energy in the studied networks. | |
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