CV Lattes
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Universidade de São Paulo (USP). Escola de Engenharia de São Carlos (EESC) (Institutional affiliation from the last research proposal) Birthplace: Brazil
Ricardo received the B.Sc. degree in Electrical Engineering with an emphasis in Computing from Educational Foundation of Barretos in 2006. He obtained the M.Sc. and Ph.D. degrees in Electrical Engineering from the São Carlos School of Engineering at the University of São Paulo (EESC/USP), in February 2009 and August 2011, respectively. He was an Adjunct and Associate Professor in the Department of Electrical Engineering at the Federal University of São Carlos (UFSCar), between January 2013 and January 2025. Currently, he is an Assistant Professor at the Department of Electrical and Computer Engineering at EESC/USP. He serves as a managing member of IEEE Task Force on Open Data Sets from the Power and Energy Society, as well as an Associate Editor of the International Journal of Electrical Engineering Education. He has experience in Embedded Systems, Digital Signal Processing and Machine Learning with applications mainly in the context of Smart Grids. (Source: Lattes Curriculum)
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Locating and identifying harmonic sources are essential procedures for power distribution systems, as they improve the monitoring of power quality and support utilities' decisions regarding actions aimed at mitigating the problems arising from harmonic distortions. In this sense, this research project presents an approach that should carry out the location and identification tasks embedde…
(Only some records are available in English at this moment)
Electricity demand has been constantly increasing, mainly in the last decade, as well as the solutions for the efficient use of electrical energy. Therefore, it is of great interest to the scientific community and energy sector the development of Nonintrusive Load Monitoring methodologies. In this sense, some NILM methodologies can be characterized as an optimization problem, being this t…
Due to the constant expansion of power distribution systems, there has been an increase in nonlinear loads (mainly those present in industrial environments) and a greater penetration of inverter-based distributed generators, being the most responsible for increasing the levels of harmonic distortions in medium voltage feeders. In this sense, monitoring and identifying the harmonic sources…
In recent years, the demand for electricity has been increasing rapidly and, for this reason, there is a need to efficiently use it. This way, the identification of residential loads enables such use for consumers and, moreover, is crucial for demand response programs. Therefore, the development of labeling algorithms is of great interest to the scientific community and the productive sec…
This scientific initiation project has as main objective the implementation of an approach based on Artificial Neural Networks (ANN) with the purpose of obtaining estimates of the energy price for the Ontario market - Canada. However, to meet this objective, it will be extracted features by calculating technical variables commonly used in financial markets. In the sequence, a selection of…
This research project has as main objective the use of the clustering algorithm named DAMICORE. For this purpose, the clustering algorithm will be employed based on Noninvasive Load Monitoring techniques to identify residential loads. Therefore, we intend to use only the instantaneous measurements of voltage and current, which are also necessary to calculate the energy consumption. Highli…
(Only some records are available in English at this moment)
| 9 / 7 | Completed research grants |
| 2 / 2 | Ongoing scholarships in Brazil |
| 13 / 13 | Completed scholarships in Brazil |
| 24 / 22 | All research grants and scholarships |
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