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About

Vladimiro Miranda was born in Porto, Portugal. He graduated in Electrical Engineering in 1977 and received the Ph.D. degree in Electrical Engineering from FEUP, the Faculty of Engineering of the University of Porto, Portugal, in 1982. He joined FEUP in 1981 and joined INESC in 1985, a top R&D institute in Portugal where he came to be coordinator of the area of Power Systems during the 90’s.

He was a member of the Board of Directors of INESC TEC, Portugal - an R&D private non-profit organization recognized by the Ministry of Science and with the University of Porto as the main associate - for 18 years until June 2018, and holds presently the following responsibilities:

  • Full Professor (Professor Catedrático) at FEUP, University of Porto, Portugal
  • Director-President of INESC P&D Brasil, an R&D private non-profit organization with headquarters in São Paulo, Brazil.
  • Associate Director at INESC TEC, International Affairs.
  • Member of the Doctoral Council of UTAD (University of Trás os Montes e Alto Douro), Portugal.

He is International Scientific Advisor for:

  • IRESEN, Agency associated to the Ministry of Energy, Morocco
  • Hong Kong Polytechnic University, China
  • Instituto de Investigación Tecnológica (Madrid), Spain
  • Instituto de Energía Eléctrica (San Juan), Argentina
  • Laboratory for Biologic and Chemical Defense of the Portuguese Army, Portugal

He was invited as Honorary Professor of the Novi Sad University, Serbia, and was President of INESC Macau, China. In 1996 and 1997 he stayed as Visiting Full Professor in the University of Macau, China. In 2005 he was Visiting Professor at the Federal University of Pará (UFPA), Brazil, and in 2015-2018 he was visiting researcher at the Federal University of Santa Catarina (UFSC), Brazil.

Prof. Miranda has been serving in the Administration Board of spin-off companies created within the INESC system. He has also served as research project evaluator for the governmental science organizations of Portugal, Norway, Croatia, South Africa, Chile, Brazil and Argentina. For the Government of this latter country, he acted as external auditor in the process of evaluation of research institutions.

He has supervised, co-supervised or cooperated in the supervision of a large number of PhD and MSc theses e power systems in several countries and universities such as in Portugal, Brazil, Argentina, Bosnia, China, Ecuador, Norway or Sweden. 

He has been responsible for many research projects at international level, in the European Union, United States and Brazil, and has authored or co-authored over 200 publications, especially in areas related with Power Systems and the application of Computational Intelligence to Power Systems.

He has been a member (at times the chairman) of the organizing or scientific committees of several important conferences in his areas of expertise such as PMAPS, ISAP, IEEE Power Tech, etc.

Prof. Miranda is an IEEE Fellow.

He is the recipient in 2013 of the IEEE Power Engineering Society Ramakumar Family Renewable Energy Excellence Award.

He is a member of the IEEE Distinguished Lecturer Program.

Curriculum LATTES:  http://lattes.cnpq.br/5824178098755298

Scopus Author ID: 35581693000  -  AuthenticusID: R-000-HPD

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Interest
Topics
Details

Details

  • Name

    Vladimiro Miranda
  • Cluster

    Power and Energy
  • Role

    Associate Director
  • Since

    01st March 1985
007
Publications

2022

Bayesian Inference Approach for Information Fusion in Distribution System State Estimation

Authors
Massignan, JAD; London, JBA; Bessani, M; Maciel, CD; Fannucchi, RZ; Miranda, V;

Publication
IEEE Trans. Smart Grid

Abstract
This paper presents a three-phase Distribution System State Estimator (DSSE) based on a Bayesian inference approach to manage different sampling rates of typical sources of information present in distribution networks. Such information comes from smart meters, supervisory control and data acquisition (SCADA) measurements, phasor measurement units and typical load profiles from pseudo measurements. The temporal aspect of the measurement set is incorporated in the estimation process by using a sampling layer concept, dealing separately with each group of measurements according to the respective updating rate. A Bayesian information fusion procedure provides the final estimation. The proposed DSSE consists in a multiple stage estimator that combines a prior model for the state variables, updated by new observations from measured values in each sampling layer, through Maximum a Posteriori estimation. This work also introduces an orthogonal method for the information fusion numerical solution, to tackle the severe ill-conditioning associated with practical distribution systems. Simulations with IEEE distribution test feeders and a Brazilian real distribution feeder illustrate the features of the proposed DSSE and its applicability. By exploring the concept of credibility intervals, the method is able to detect events on the grid, such as subtle load variation and contingencies, while maintaining accuracy. © 2010-2012 IEEE.

2021

Forecasting Energy Technology Diffusion in Space and Time: Model Design, Parameter Choice and Calibration

Authors
Heymann, F; vom Scheidt, F; Soares, FJ; Duenas, P; Miranda, V;

Publication
IEEE Transactions on Sustainable Energy

Abstract

2021

Pneuma: entrepreneurial science in the fight against the COVID-19 pandemic - a tale of industrialisation and international cooperation

Authors
Mendonça, JM; Cruz, N; Vasconcelos, D; Sá-Couto, C; Moreira, AP; Costa, P; Mendonça, H; Pereira, A; Naimi, Z; Miranda, V;

Publication
Journal of Innovation Management

Abstract
When the COVID-19 pandemic hits Portugal in early March 2020, medical doctors, engineers and researchers, with the encouragement of the Northern Region Health Administration, teamed up to develop and build, locally and in a short time, a ventilator that might eventually be used in extreme emergency situations in the hospitals of northern Portugal. This letter tells you the story of Pneuma, a low-cost emergency ventilator designed and built under harsh isolation constraints, that gave birth to derivative designs in Brazil and Morocco, has been industrialized with 200 units being produced and is now looking forward to the certification as a medical device that will possibly support a go-to-market launch. Open intellectual property (IP), multidisciplinarity teamwork, fast prototyping and product engineering have shortened to a few months an otherwise quite longer idea-to-product route, clearly demonstrating that when scientific and engineering knowledge hold hands great challenges can be successfully faced.

2021

Multi-objective identification of critical distribution network assets in large interruption datasets

Authors
Marcelino, CG; Torres, V; Carvalho, L; Matos, M; Miranda, V;

Publication
International Journal of Electrical Power and Energy Systems

Abstract
Performance indicators, such as the SAIFI and the SAIDI, are commonly used by regulatory agencies to evaluate the performance of distribution companies (DisCos). Based on such indicators, it is common practice to apply penalties or grant rewards if the indicators are greater to or less than a given threshold. This work proposes a new multi-objective optimization model for pinpointing the critical assets involved in outage events based on past performance indicators, such as the SAIDI and the System Average Interruption Duration Exceeding Threshold (SAIDET) indexes. Our approach allows to retrieve the minimal set of assets in large historical interruption datasets that most contribute to past performance indicators. A case study using a real interruption dataset between the years 2011–2104 from a Brazilian DisCo revealed that the optimal inspection plan according to the decision maker preferences consist of 332 equipment out of a total of 5873. This subset of equipment, which contribute 61.90% and 55.76% to the observed SAIFI and SAIDET indexes in that period, can assist managerial decisions for preventive maintenance actions by prioritizing technical inspections to assets deemed as critical. © 2021

2020

An orthogonal method for solving maximum correntropy-based power system state estimation

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

Publication
IET Generation, Transmission & Distribution

Abstract

Supervised
thesis

2021

An optimization framework to estimate the active and reactive power flexibility in the TSO-DSO interface

Author
João Pedro Vasques Vieira da Silva

Institution
UP-FEUP

2021

Integrated Renewable Storage Systems Under Artificial Intelligence Decision Models

Author
Tiago João Amorim Abreu

Institution
UP-FEUP

2021

Self-Learning Artificial Intelligence for Laser Induced Breakdown Spectroscopy: Data Analysis and System Control

Author
Alberto Sousa Lima Mesquita dos Santos

Institution
UP-FEUP

2021

Development of strategies for energy storage in distribution grid with RES

Author
Piedy Del Mar Agamez Arias

Institution
UP-FEUP

2021

Resilience Enhancement Solutions for Distribution Networks

Author
Inês Maria Afonso Trigo de Freitas Alves

Institution
UP-FEUP