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Manuel A Matos – CV Curto – primeira pessoa

Nasci no Porto (Portugal) a 8 de abril de 1955, concluí a licenciatura em Engenharia Eletrotécnica na Faculdade de Engenharia da Universidade do Porto – FEUP (1977) e completei o doutoramento em Sistemas de Energia em 1988, também na Universidade do Porto. Em novembro de 1996 recebi o título de Agregado.

 Em 1978 fui admitido no Departamento de Engenharia Eletrotécnica da FEUP, onde sou Professor Catedrático desde 2000. No período 1990-98, fui também diretor da Biblioteca da FEUP. No período 2001-2008 fui diretor de curso do Mestrado Em Gestão de Informação e sou atualmente diretor do Programa Doutoral em Sistemas Sustentáveis de Energia, integrado no Programa MIT-Portugal

Tenho lecionado unidades curriculares em cursos de licenciatura, mestrado e doutoramento, em Engenharia Eletrotécnica e Sistemas de Energia e orientado atividades de investigação de muitos estudantes dos três níveis. Também colaborei com a Escola de Gestão da Universidade do Porto, lecionando Ajuda à Decisão em cursos de mestrado. Sou membro do Senado da Universidade do Porto desde outubro de 2009.

Em 1985 aderi ao INESC (agora INESC TEC), onde desde 1996 coordeno o Centro de Sistemas de Energia, agrupando 60+ investigadores (incluindo 20+ doutorados). Sou atualmente o Presidente do Conselho Científico do INESC TEC. Estive envolvido em vários projetos de investigação e desenvolvimento nacionais, europeus e internacionais e em contratos de desenvolvimento e consultoria para operadores de rede, indústria, departamentos governamentais e Entidade Reguladora dos Serviços Energéticos.

Em particular, fui ou sou responsável pela equipa de investigação do INESC TEC nos projetos europeus “CARE” (Advanced Control Advice for power systems with large-scale integration of Renewable Energy sources), “MORE CARE” (More Advanced Control Advice for Secure Operation of Isolated Power Systems with Increased Renewable Energy Penetration and Storage), “ANEMOS.PLUS” (Advanced Tools for the Management of Electricity Grids with Large-Scale Wind Generation) e “evolvDSO” (Development of methodologies and tools for new and evolving DSO roles for efficient DRES integration in distribution networks). Sou atualmente o Investigador Principal do projeto “SusCity” (Urban data driven models for creative and resourceful urban transitions), financiado pela FCT (MPP-Testbed).

Também coordenei as equipas de investigação dos contratos “CCR” (Load Profiling and Distribution Network Characterization), com EDP Distribuição, Study on the Impact of Large Renewable Deployment on European Electricity Higher Voltage Systems (JRC-Institute for Energy), “RESERVES” (Mid and Long Term Evaluation of the adequacy of Operational Reserve levels in the Iberian Electric Power Systems), com os TSO of Portugal (REN) e Espanha (REE), “RECEP” (Development and testing of methodologies to determine the hosting capacity in the nodes of the National Grid of Portugal) (REN), “ReservaProb” (Software Module for helping setting the operational reserve of the National Electric System) (REN) e “MORA” (Long-term adequacy evaluation of reserves in a multi-area context) (REN). Estive ainda envolvido em ações consultoria relacionadas com a conceção de concurso públicos, nomeadamente o concurso de concessão de nova potência eólica em Portugal continental.

Os meus interesses científicos incluem modelização clássica e difusa de sistemas de energia, fiabilidade e otimização e ajuda à decisão, com aplicação em planeamento, integração de renováveis, integração de veículos elétricos e redes inteligentes. Participei na organização de conferências internacionais como PMAPS’2000, IEEE PPT’2001, ISAP’2015 and EEM’2016. Sou membro do the Editorial board da EPSR (Top Reviewer in 2010) e do Int J of Multicriteria Decision Making. Sou senior member do IEEE.

Tópicos
de interesse
Detalhes

Detalhes

  • Nome

    Manuel Matos
  • Cluster

    Energia
  • Cargo

    Coordenador de Centro
  • Desde

    01 abril 1985
027
Publicações

2020

Distributed multi-period three-phase optimal power flow using temporal neighbors

Autores
Pinto, R; Bessa, RJ; Sumaili, J; Matos, MA;

Publicação
Electric Power Systems Research

Abstract
The penetration of distributed generation in medium (MV) and low (LV) voltage distribution grids has been steadily increasing every year in multiple countries, thus creating new technical challenges in grid operation and motivating developments in distributed optimization for flexibility management. The traditional centralized optimal power flow (OPF) algorithm can solve technical constraints violation. However, computational efficiency, new technologies (e.g., edge computing) and control architectures (e.g., web-of-cells) are demanding for distributed approaches. This work formulates a novel distributed multi-period OPF for three-phase unbalanced grids that is essential when integrating energy storage units in operational planning (e.g., day-ahead) of LV or local energy community grids. The decentralized constrained optimization problem is solved with the alternating direction method of multipliers (ADMM) adapted for unbalanced LV grids and multi-period optimization problems. A 33-bus LV distribution grid is used as a case-study in order to define optimal battery storage scheduling along a finite time horizon that minimizes overall grid operational costs, while complying with technical constraints of the grid (e.g., voltage and current limits) and battery state-of-charge constraints. © 2020

2020

Participation of an EV Aggregator in the Reserve Market through Chance-Constrained Optimization

Autores
Faria, AS; Soares, T; Sousa, T; Matos, MA;

Publicação
ENERGIES

Abstract
The adoption of Electric Vehicles (EVs) will revolutionize the storage capacity in the power system and, therefore, will contribute to mitigate the uncertainty of renewable generation. In addition, EVs have fast response capabilities and are suitable for frequency regulation, which is essential for the proliferation of intermittent renewable sources. To this end, EV aggregators will arise as a market representative party on behalf of EVs. Thus, this player will be responsible for supplying the power needed to charge EVs, as well as offering their flexibility to support the system. The main goal of EV aggregators is to manage the potential participation of EVs in the reserve market, accounting for their charging and travel needs. This work follows this trend by conceiving a chance-constrained model able to optimize EVs participation in the reserve market, taking into account the uncertain behavior of EVs and their charging needs. The proposed model, includes penalties in the event of a failure in the provision of upward or downward reserve. Therefore, stochastic and chance-constrained programming are used to handle the uncertainty of a small fleet of EVs and the risk profile of the EV aggregator. Two different relaxation approaches, i.e., Big-M and McCormick, of the chance-constrained model are tested and validated for different number of scenarios and risk levels, based on an actual test case in Denmark with actual driving patterns. As a final remark, the McCormick relaxation presents better performance when the uncertainty budget increases, which is appropriated for large-scale problems.

2019

Trading Small Prosumers Flexibility in the Energy and Tertiary Reserve Markets

Autores
Iria, JP; Soares, FJ; Matos, MA;

Publicação
IEEE Transactions on Smart Grid

Abstract

2019

Optimal bidding strategy for an aggregator of prosumers in energy and secondary reserve markets

Autores
Iria, J; Soares, F; Matos, M;

Publicação
Applied Energy

Abstract

2019

Handling Renewable Energy Variability and Uncertainty in Power System Operation

Autores
Bessa, R; Moreira, C; Silva, B; Matos, M;

Publicação
Advances in Energy Systems

Abstract

Teses
supervisionadas

2019

Cost Allocation Model for Distribution Networks Considering Flexibility from Distributed Energy Resources

Autor
Miguel Ângelo Pereira da Cruz

Instituição
UP-FEUP

2019

SCUC com cargas difusas

Autor
José Carlos Ferreira Fidalgo

Instituição
UP-FEUP

2019

Application of Multi-Criteria Decision Aid (MCDA) in Decision Making: Mineral Resource Projects Investment Evaluation

Autor
Andreas Tuhafeni Salom

Instituição
UP-FEUP

2019

A chance-constrained approach for electric vehicle aggregator participation in the reserve market

Autor
António Sérgio Barbosa Faria

Instituição
UP-FEUP

2019

Optimal Participation of an Aggregator of Prosumers in the Electricity Markets

Autor
José Pedro Barreira Iria

Instituição
UP-FEUP