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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
005
Publications

2018

Technical-economic analysis for the integration of PV systems in Brazil considering policy and regulatory issues

Authors
Vilaca Gomes, PV; Knak Neto, NK; Carvalho, L; Sumaili, J; Saraiva, JT; Dias, BH; Miranda, V; Souza, SM;

Publication
Energy Policy

Abstract

2018

Solving security constrained optimal power flow problems: a hybrid evolutionary approach

Authors
Marcelino, CG; Almeida, PEM; Wanner, EF; Baumann, M; Weil, M; Carvalho, LM; Miranda, V;

Publication
APPLIED INTELLIGENCE

Abstract
A hybrid population-based metaheuristic, Hybrid Canonical Differential Evolutionary Particle Swarm Optimization (hC-DEEPSO), is applied to solve Security Constrained Optimal Power Flow (SCOPF) problems. Despite the inherent difficulties of tackling these real-world problems, they must be solved several times a day taking into account operation and security conditions. A combination of the C-DEEPSO metaheuristic coupled with a multipoint search operator is proposed to better exploit the search space in the vicinity of the best solution found so far by the current population in the first stages of the search process. A simple diversity mechanism is also applied to avoid premature convergence and to escape from local optima. A experimental design is devised to fine-tune the parameters of the proposed algorithm for each instance of the SCOPF problem. The effectiveness of the proposed hC-DEEPSO is tested on the IEEE 57-bus, IEEE 118-bus and IEEE 300-bus standard systems. The numerical results obtained by hC-DEEPSO are compared with other evolutionary methods reported in the literature to prove the potential and capability of the proposed hC-DEEPSO for solving the SCOPF at acceptable economical and technical levels.

2018

Security-Constrained Optimal Power Flow via Cross-Entropy Method

Authors
Carvalho, LD; Leite da Silva, AML; Miranda, V;

Publication
IEEE Transactions on Power Systems

Abstract

2018

Applying C-DEEPSO to solve Large Scale Global Optimization Problems

Authors
Marcelino, C; Almeida, P; Pedreira, C; Carvalho, L; Wanner, E;

Publication
2018 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC)

Abstract
In this paper, a hybrid single-objective metaheuristic, named as C-DEEPSO (Canonical Differential Evolutionary Particle Swarm Optimization), is proposed to solve large-scale optimization problems. C-DEEPSO can be viewed as an evolutionary algorithm with recombination rules borrowed from PSO or an swarm optimization method with selection and self-adaptiveness properties. To assess the algorithm performance, the algorithm is run over 15 benchmark continuous problems presented in CEC'2015. The algorithm is also applied over a real world large-scale problem. The results indicate that the proposed algorithm is an efficient and competitive method to handle such problems. The experimental results also show that the new approach reaches competitive results when compared to the reference algorithm DECC-G. An application of C-DEEPSO were perform to solve the electric dispatch in a large scale energy network, the IEEE 57 Bus-System. The results show that the algorithm is a good way to solve nonlinear problems respecting many constraints associated.

2017

Mitigation in the Very Short-term of Risk from Wind Ramps with Unforeseen Severity

Authors
Pinto, M; Miranda, V; Saavedra, O; Carvalho, L; Sumaili, J;

Publication
JOURNAL OF CONTROL AUTOMATION AND ELECTRICAL SYSTEMS

Abstract
This paper addresses a critical analysis of the impact of the wind ramp events with unforeseen magnitude in power systems at the very short term, modeling the response of the operational reserve against this type of phenomenon. A multi-objective approach is adopted, and the properties of the Pareto-optimal fronts are analyzed in cost versus risk, represented by a worst scenario of load curtailment. To complete this critical analysis, a study about the usage of the reserve in the event of wind power ramps is performed. A case study is used to compare the numerical results of the models based on stochastic programming and models that take a risk analysis view in the system with high level of wind power. Wind power uncertainty is represented by scenarios qualified by probabilities. The results show that the reliability reserve may not be adequate to accommodate unforeseen wind ramps and therefore the system may be at risk.

Supervised
thesis

2015

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

Author
João Teixeira

Institution
UP-FEUP