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About

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

(end)

Details

Details

  • Name

    Vladimiro Miranda
  • Role

    Associate Director
  • Since

    01st March 1985
007
Publications

2023

A Data-Driven Approach to Estimate the Flexibility Maps in Multiple TSO-DSO Connections

Authors
Silva, J; Sumaili, J; Silva, B; Carvalho, L; Retorta, F; Staudt, M; Miranda, V;

Publication
IEEE TRANSACTIONS ON POWER SYSTEMS

Abstract
This paper presents a methodology to estimate flexibility existing on TSO-DSO borderline, for the cases where multiple TSO-DSO connections exist (meshed grids). To do so, the work conducted exploits previous developments regarding flexibility representation through the adoption of active and reactive power flexibility maps and extends the concept for the cases where multiple TSO-DSO connection exists, using data-driven approach to determine the equivalent impedance between TSO nodes, preserving the anonymity regarding sensitive grid information, such as the topology. This paper also provides numerical validation followed by real-world demonstration of the methodology proposed.

2023

Economic Analysis of a Hydrogen Power Plant in the Portuguese Electricity Market

Authors
Rodrigues, LM; Soares, T; Rezende, I; Fontoura, JP; Miranda, V;

Publication
ENERGIES

Abstract
Hydrogen is regarded as a flexible energy carrier with multiple applications across several sectors. For instance, it can be used in industrial processes, transports, heating, and electrical power generation. Green hydrogen, produced from renewable sources, can have a crucial role in the pathway towards global decarbonization. However, the success of green hydrogen production ultimately depends on its economic sustainability. In this context, this work evaluates the economic performance of a hydrogen power plant participating in the electricity market and supplying multiple hydrogen consumers. The analysis includes technical and economical details of the main components of the hydrogen power plant. Its operation is simulated using six different scenarios, which admit the production of either grey or green hydrogen. The scenarios used for the analysis include data from the Iberian electricity market for the Portuguese hub. An important conclusion is that the combination of multiple services in a hydrogen power plant has a positive effect on its economic performance. However, as of today, consumers who would wish to acquire green hydrogen would have to be willing to pay higher prices to compensate for the shorter periods of operation of hydrogen power plants and for their intrinsic losses. Nonetheless, an increase in green hydrogen demand based on a greater environmental awareness can lead to the need to not only build more of these facilities, but also to integrate more services into them. This could promote the investment in hydrogen-related technologies and result in changes in capital and operating costs of key components of these plants, which are necessary to bring down production costs.

2023

Evaluation of different bidding strategies for a battery energy storage system performing energy arbitrage - a neural network approach

Authors
Santos, P; Rezende, I; Soares, T; Miranda, V;

Publication
2023 19TH INTERNATIONAL CONFERENCE ON THE EUROPEAN ENERGY MARKET, EEM

Abstract
The rising potential for battery energy storage systems (BESS) to generate revenue in a market environment is addressed in this work, where a tool based on neural network predictions is proposed. The tool's main objective is predicting, based on historical data, the most lucrative out of three established bidding approaches for the participation of a BESS in the day-ahead energy market and thus aid the strategic bidding process of the BESS operator. Each of these bidding strategies reflects BESS's operator approach concerning bidding frequency and the tolerated risk of loss of profit from having its bids rejected, leading to the development of a conservative (strategy A), an aggressive (strategy B), and a moderate strategy (strategy C). A case study was then used to test the tool for a full year allowing to ascertain the assertiveness of this tool in predicting the best strategy, which for this case was above 88%.

2022

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 & 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.

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 TRANSACTIONS ON 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.

Supervised
thesis

2022

Explainable Artificial Intelligence for Fair and Transparent Biometrics

Author
Pedro David Carneiro Neto

Institution
UNL-FCTNOVA

2022

Provision of services for TSO through distribution resources in a local market

Author
Fábio Sester Retorta

Institution
UP-FEUP

2022

ATOMIUS - An application to support Bosch internal processes

Author
Tânia Filipa Amorim da Rocha

Institution
UM

2022

Trust in Computing - trust as a facilitator on the uptake (or appropriation) of technology (Confiança como um processo facilitador de adoção de tecnologia)

Author
Sónia Cláudia da Costa Sousa

Institution
UTAD

2022

Dimensionamento e Localização de Dispositivos de Armazenamento

Author
Vitor Eduardo da Silva Santos

Institution
UP-FEUP