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About

About

I received the B.Sc degree in electrical engineering in 2014 from Federal University of Juiz de Fora, Brazil. Currently, I am pursuing the Ph.D. degree in electrical and computer engineering at the Faculty of Engineering of the University of Porto, Portugal. My research interests include several topics that address the application of computational intelligence to energy systems, especially bio-inspired algorithms.

Interest
Topics
Details

Details

  • Name

    Phillipe Vilaça Gomes
  • Cluster

    Power and Energy
  • Role

    Researcher
  • Since

    01st September 2014
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

A novel efficient method for multiyear multiobjective dynamic transmission system planning

Authors
Vilaca Gomes, PV; Saraiva, JT;

Publication
International Journal of Electrical Power & Energy Systems

Abstract

2017

Transmission System Planning Considering Solar Distributed Generation Penetration

Authors
Gomes, PV; Saraiva, JT;

Publication
2017 14TH INTERNATIONAL CONFERENCE ON THE EUROPEAN ENERGY MARKET (EEM 17)

Abstract
In recent years, power systems have been watching important advancements related with Plug-in-Electrical Vehicles (PEVs), Demand Side Management (DSM), Distributed Generation (DG), Microgrid and Smart Grid installations that directly affect distribution networks while impacting indirectly on Transmission studies. These changes will lead to an extra flexibility on the transmission-distribution boundary and to a significant modification of the load patterns, that are an essential input to planning studies. In this scope, this paper describes a multiyear Transmission Expansion Planning (TEP) solved by Evolutionary Particle Swarm Optimization (EPSO) and incorporating the impact of solar DG penetration. The primary substation load profiles and the solar generation profiles are taken into account on the planning problem. The numerical simulations were conducted using the IEEE 24 bus reliability test system in which the planning horizon is 3 years and the load growth is 2.5 % per year. If demand and solar DG peaks are coincident, then the liquid demand seen by the transmission network gets reduced enabling a reduction of investment costs. In the tested cases, these peaks were not coincident so that the optimal expansion plan remains unchanged even though the injected power from DG is large. This stresses the fact that solar DG may not on an isolated way contribute to alleviate the demand seen by transmission networks but should be associated with storage devices or demand side management programs.

2017

Multiyear Transmission Expansion Planning Under Hydrological Uncertainty

Authors
Vilaca Gomes, PV; Saraiva, JT;

Publication
2017 IEEE MANCHESTER POWERTECH

Abstract
Hydrothermal systems should be characterized by a transmission-intensive nature in order to deal with climatic phenomena which, for example, can determine dry conditions in one region while there are large rainfalls in another one. Thus, the grid must be robust to deal with the different export/import patterns among regions and accommodate several economic dispatches. This paper describes a multiyear probabilistic Transmission Expansion Planning, TEP, model that uses Evolutionary Particle Swarm Optimization (EPSO) to deal with the uncertainties present in hydrothermal systems. The numerical simulations were conducted using the IEEE 24 bus reliability test system in which the planning horizon is 10 years and the load growth is 2,5% per year. The results highlight the importance of adopting expansion strategies to reduce the risk and consider the inflow variations in this type of systems.

2017

Dynamic and static transmission network expansion planning via harmony search and branch & bound on a hybrid algorithm

Authors
de Oliveira, LE; Freitas, FD; da Silva, IC; Gomes, PV;

Publication
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Abstract
This work presents a method based on metaheuristics to solve the problem of Static (STNEP) and Dynamic (DTNEP) Transmission Network Expansion Planning in electrical power systems. The result of this formulation is mixed-integer nonlinear programming (MINLP), where the difficulties are intensified in the DTNEP by the temporal coupling. Therefore, a methodology was developed to reach the solution in three different stages: The first one is responsible for obtaining an efficient set of best candidate routes for the expansion; the metaheuristic optimization process, Harmony Search (HS), is used to find STNEP’s optimal solution and its neighborhood that provides a DTNEP candidate zone; lastly, a hybrid algorithm that mixes the HS and Branch & Bound (B&B) concepts is adapted to provide the optimal DTNEP. In this study, the lossless linearized modeling for load flow is used as a representation of the transmission network. Tests with the Garver and southern Brazilian systems were carried out to verify the performance method. The computational time saving for the STNEP and DTNEP prove the efficacy of the proposed method. © Springer International Publishing AG 2017.