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About

About

I received the B.Sc. degree  in Electrical Engineering graduated from the Federal University of Pará in 2013, Brasil, and MSc. in Electrical Engineering from the Federal University of Santa Catarina in 2015, where  I am currently persuing the PhD degree. In August of 2017, I joined INESC TEC as researcher of the Power and Energy Center (CPES). I have experience in the Electric Engineering field, namely in the automatic and control systems and electric power systems, with focus in power system state and topology estimation and numeric methods applied to the power system real-time modelling. 

Interest
Topics
Details

Details

  • Name

    Victor Silva Freitas
  • Cluster

    Power and Energy
  • Role

    Research Assistant
  • Since

    15th August 2017
001
Publications

2018

Algoritmos Meméticos Aplicados à Identificação de Sistemas e Sintonização de Controladores PID

Authors
Sousa, AL; Vidal, JF; Silva, OF; Freitas, VS;

Publication

Abstract

2018

Hybrid systems control applied to wind power forecasting deviation considering PHS

Authors
Rezende, I; Silva, JM; Miranda, V; Freitas, V; Dias, BH;

Publication
SBSE 2018 - 7th Brazilian Electrical Systems Symposium

Abstract
This paper proposes a methodology using Hybrid Control System (HS) to manage the integration of Variable Renewable Electricity Sources (VRES). The HS define a combination of discrete and continuous signals, in this case, discrete by Pump-Hydro-Storage (PHS) and continuous performance is the Wind Power (WP). The coupling of Wind Power and PHS to produce a dispatchable power output could be a significant benefit to those in an energy trading system. Improving VRES prediction reduces system dispatch errors, however does not give total economic opportunities to the generator. Increased dispatchable backup power generation can improve the system's ability to handle deviations of WP, as verified when the proposed approach is applied to Brazilian and Portuguese power system. © 2018 IEEE.

2017

Robust State Estimation Based on Orthogonal Methods and Maximum Correntropy Criterion

Authors
Freitas, V; Coasta, AS; Miranda, V;

Publication
2017 IEEE MANCHESTER POWERTECH

Abstract
This paper presents an orthogonal implementation for power system state estimators based on the Maximum Correntropy Criterion (MCC). The proposed approach leads to a numerically robust estimator which exhibits self -healing properties, in the sense that gross errors in analog measurements are automatically rejected. As a consequence, robust estimates are produced without the need of running the state estimator again after bad data identification and removal. Numerical robustness is achieved by means of a specialized orthogonal algorithm based on fast Givens Rotations, which is able to handle the dynamic measurement weighting mechanism implied by the Parzen window concept associated to MCC. Results for a 3 -bus test system are presented to properly illustrate the Correntropy principles, and several case studies conducted on the IEEE 30 -bus and 57 -bus benchmark systems are used to validate the proposed methodology.

2017

Merging conventional and phasor measurements in state estimation: A multi-criteria perspective

Authors
Tavares, B; Freitas, V; Miranda, V; Costa, AS;

Publication
2017 19th International Conference on Intelligent System Application to Power Systems (ISAP)

Abstract

2015

Integrated State & topology estimation based on a priori topology information

Authors
Freitas, V; Costa, AS;

Publication
2015 IEEE Eindhoven PowerTech

Abstract