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About

I received the B.Sc. degree in Applied Mathematics and Computer Science from the Faculty of Sciences of the University of Porto, Porto, Portugal, in 1991, and I got my MSc and PhD in Electrical and Computer Engineering (Power Systems area) in the Faculty of Engineering of the University of Porto, in 1995 and 2002, respectively.
In 1991, I joined INESC Porto where I'm DMS/EMS and System Operation Area Leader and Research Manager of Centre for Power and Energy Systems (CPES). Since 1995, I have been with the Faculty of Economics of the University of Porto, where I'm currently an Assistant Professor.
I have collaborated on several projects related to the development of DMS systems (including the European projects MORE MICROGRIDS, SuSTAINABLE, evolvDSO, Integrid), the application of soft computing techniques to power systems, namely, to the state estimation problem.

Interest
Topics
Details

Details

  • Name

    Jorge Correia Pereira
  • Cluster

    Power and Energy
  • Role

    Advisor to the Centre Coordinator
  • Since

    01st December 1991
023
Publications

2019

A new interior point solver with generalized correntropy for multiple gross error suppression in state estimation

Authors
Pesteh, S; Moayyed, H; Miranda, V; Pereira, J; Freitas, V; Simoes Costa, AS; London Jr, JBA;

Publication
Electric Power Systems Research

Abstract
This paper provides an answer to the problem of State Estimation (SE) with multiple simultaneous gross errors, based on Generalized Error Correntropy instead of Least Squares and on an interior point method algorithm instead of the conventional Gauss–Newton algorithm. The paper describes the mathematical model behind the new SE cost function and the construction of a suitable solver and presents illustrative numerical cases. The performance of SE with the data set contaminated with up to five simultaneous gross errors is assessed with confusion matrices, identifying false and missed detections. The superiority of the new method over the classical Largest Normalized Residual Test is confirmed at a 99% confidence level in a battery of tests. Its ability to address cases where gross errors fall on critical measurements, critical sets or leverage points is also confirmed at the same level of confidence. © 2019 Elsevier B.V.

2019

Impact of different central path neighborhoods on gross error identification in State Estimation with generalized correntropy interior point method

Authors
Moayyed, H; Pesteh, S; Miranda, V; Pereira, J;

Publication
2019 International Conference on Smart Energy Systems and Technologies (SEST)

Abstract

2019

On the development of a framework for the advanced monitoring of LV grids

Authors
Kotsalos, K; Marques, L; Sampaio, G; Pereira, J; Gouveia, C; Teixeira, H; Fernandes, R; Campos, F;

Publication
2019 International Conference on Smart Energy Systems and Technologies (SEST)

Abstract

2018

Probabilistic Low-Voltage State Estimation Using Analog-Search Techniques

Authors
Bessa, R; Sampaio, G; Miranda, V; Pereira, J;

Publication
2018 Power Systems Computation Conference (PSCC)

Abstract

2017

LV state estimation and TSO–DSO cooperation tools: results of the French field tests in the evolvDSO project

Authors
Viania Sebastian, M; Caujolle, M; Goncer Maraver, B; Pereira, J; Sumaili, J; Barbeiro, P; Silva, J; Bessa, R;

Publication
CIRED - Open Access Proceedings Journal

Abstract

Supervised
thesis

2018

Acesso móvel a plataforma de e-Science para Séries temporais

Author
Bruno Emanuel Cardoso Miranda Gonçalves

Institution
UP-FEUP

2017

State Estimation for Evolving Power Systems Paradigms

Author
Gil da Silva Sampaio

Institution
UP-FEP

2016

Power system automation architec - Contributions towards the application of system tools and higher level modeling languages

Author
Cláudio Manuel Pinto da Silva

Institution
UP-FEP

2015

Improving distribution state estimation robustness through optimal metering placement and sensor fusion techniques

Author
Jorge Miguel Mendes Alves

Institution
UP-FEP