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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
016
Publications

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.

2019

Load modeling of active low-voltage consumers and comparative analysis of their impact on distribution system expansion planning

Authors
Knak Neto, N; Abaide, ADR; Miranda, V; Vilaça Gomes, P; Carvalho, L; Sumaili, J; Bernardon, DP;

Publication
International Transactions on Electrical Energy Systems

Abstract
This paper proposes a new probabilistic model for active low-voltage prosumers suitable for distribution expansion planning studies. The load uncertainty of these consumers is considered through a range of load profiles by segmenting the energy consumption according to the different energy uses. Then, consumption adjustments are simulated using a nonhomogenous Poisson process based on the energy usage preferences and the financial gains according to the tariff scheme. A case study based on the modified IEEE 33-Bus test system with real data collected from a Brazilian distribution company is performed in order to analyze the impact of the load profiles in scenarios with high penetration of renewable distributed generation (DG). The experiments carried out reveal that considerable monetary savings in the expansion of the distribution grid can be achieved for this case study (up to 37%) as compared with the alternative with no active demand (AD) by exploiting the flexibility associated with the active behavior of prosumers as a response to price signals and/or by permitting adequate levels for the integration of DG into the distribution grid. © 2019 John Wiley & Sons, Ltd.

2019

Equivalent dynamic model of active distribution networks for large voltage disturbances

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

Publication
2019 IEEE Milan PowerTech, PowerTech 2019

Abstract
This paper proposes a 'grey-box' dynamic equivalent model for medium voltage active distribution networks, taking into account a heterogeneous fleet of generation technologies alongside the latest European grid codes requirements. It aims to properly represent the transient behavior of the system upon large voltage disturbances in the transmission side. The proposed equivalent model is composed by four main components: two equivalent generation units, one for converter-connected units' representation, and another accounting for the synchronous generation units' portfolio; an equivalent composite load model; and a battery energy storage system, also converter-connected to the grid. The model's parameters are estimated by an evolutionary particle swarm optimization algorithm, by comparing a fully-detailed model of a medium voltage distribution network with the equivalent model's frequency domain's responses of active and reactive power flows, at the boundary of distribution-transmission interface substation. © 2019 IEEE.

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
Accounting for the increasing uncertainties related to forecast of renewables is becoming an essential requirement while assessing the security of future power system scenarios. Project iTesla in the Seventh Framework Program (FP7) of the European Union (EU) tackles these needs and reaches several major objectives, including the development of a security platform architecture. In particular, the platform implements a stochastic dependence model to simulate a reasonable cloud of plausible 'future' states - due to renewable forecast - around the expected state, and evaluates the security on relevant states after sampling the cloud of uncertainty. The paper focuses on the proposed model for the uncertainty and its exploitation in power system security assessment process and it reports the relevant validation results. Copyright © 2019 Inderscience Enterprises Ltd.

Supervised
thesis

2018

Dynamic Distribution System Reconfiguration to Improve System Reliability Considering Renewables and Energy Storage

Author
Cláudio Miguel Marques Pinto dos Santos

Institution
UP-FEUP