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About

Dr. Leonel Carvalho was born in Espinho, Portugal, in 1985. He received his B.Sc., M.Sc., and Ph.D. degrees in Electrical Engineering from the Faculty of Engineering of the University of Porto (FEUP), Portugal, in 2006, 2008, and 2013, respectively. Currently, he is a senior researcher at INESC TEC. In 2011, he was a Visiting Researcher at the Institute of Electric Systems and Energy of the Federal University of Itajubá (UNIFEI), Minas Gerais, Brazil, where he was engaged in research activities related with the use of the Cross-Entropy Method for improving the Reliability Assessment of large-scale power systems. In 2014, he was the winner of the IEEE International Competition on the Application of Modern Heuristic Optimization Algorithms for Solving Optimal Power Flow Problems organized by the IEEE PES Working Group on Modern Heuristic Optimization, with the algorithm entitled “DEEPSO as a successful blend of evolutionary and swarm search strategies in the OPF challenge”. In 2015, he held the Auxiliary Professor position at the Universidade Lusíada of Vila Nova de Famalicão where he was responsible of several courses of the Licenciatura degree in Eletronic and Computer Engineering. Dr. Leonel has co-supervised several M.Sc. theses, one of which was granted the first place in 2015 edition of the prestigious REN Prize, which is an award aiming at distinguishing the best M.Sc. theses completed in Portuguese higher education institutions in the fields of Engineering, Economics, Mathematics, Physics, Chemistry, Information Systems and Computer Science. As a researcher in INESC TEC, he has been involved in several national and international R&D projects amongst which is worth highlighting the RESERVE project with the Portuguese TSO, the ARGUS project with the Argonne National Laboratory in the USA, the FP7 projects MERGE, STABALID, evolvDSO, and iTESLA and the H2020 project SENSIBLE. He has authored and co-authored several papers in peer-reviewed journals as well as in international conferences. His current research interests include power system Reliability Assessment and the application of Computational Intelligence algorithms to power system optimization problems.

Interest
Topics
Details

Details

  • Name

    Leonel Magalhães Carvalho
  • Cluster

    Power and Energy
  • Role

    Area Manager
  • Since

    18th February 2008
018
Publications

2020

Aggregated dynamic model of active distribution networks for large voltage disturbances

Authors
Fulgencio, N; Moreira, C; Carvalho, L; Lopes, JP;

Publication
Electric Power Systems Research

Abstract

2020

A Hierarchical Optimization Strategy for Energy Scheduling and Volt/var Control in Autonomous Clusters of Microgrids

Authors
Castro, MV; Moreira, C; Carvalho, LM;

Publication
IET Renewable Power Generation

Abstract

2019

An advanced platform for power system security assessment accounting for forecast uncertainties

Authors
Ciapessoni, E; Cirio, D; Pitto, A; Omont, N; Carvalho, LM; Vasconcelos, MH;

Publication
International Journal of Management and Decision Making

Abstract

2019

Impact of decision-making models in Transmission Expansion Planning considering large shares of renewable energy sources

Authors
Gomes, PV; Saraiva, JT; Carvalho, L; Dias, B; Oliveira, LW;

Publication
Electric Power Systems Research

Abstract

2019

Application of genetic algorithms and the cross-entropy method in practical home energy management systems

Authors
Abreu, C; Soares, I; Oliveira, L; Rua, D; Machado, P; Carvalho, L; Pecas Lopes, JAP;

Publication
IET RENEWABLE POWER GENERATION

Abstract
Home energy management systems (HEMSs) are important platforms to allow consumers the use of flexibility in their consumption to optimise the total energy cost. The optimisation procedure embedded in these systems takes advantage of the nature of the existing loads and the generation equipment while complying with user preferences such as air temperature comfort configurations. The complexity in finding the best schedule for the appliances within an acceptable execution time for practical applications is leading not only to the development of different formulations for this optimisation problem, but also to the exploitation of non-deterministic optimisation methods as an alternative to traditional deterministic solvers. This study proposes the use of genetic algorithms (GAs) and the cross-entropy method (CEM) in low-power HEMS to solve a conventional mixed-integer linear programming formulation to optimise the total energy cost. Different scenarios for different countries are considered as well as different types of devices to assess the HEMS operation performance, namely, in terms of outputting fast and feasible schedules for the existing devices and systems. Simulation results in low-power HEMS show that GAs and the CEM can produce comparable solutions with the traditional deterministic solver requiring considerably less execution time.

Supervised
thesis

2019

MOCAPIRA - Monte Carlo parallel implementation for reliability assessment

Author
Inês Maria Afonso Trigo de Freitas Alves

Institution
UP-FEUP

2015

Impacto do Erro da Previsão Eólica nas Necessidades a Longo-Prazo de Reserva Operacional

Author
João Teixeira

Institution
UP-FEUP