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Details

  • Name

    David Emanuel Rua
  • Cluster

    Power and Energy
  • Role

    Assistant Centre Coordinator
  • Since

    01st October 2009
024
Publications

2022

Towards a Cross-domain Semantically Interoperable Ecosystem

Authors
Tosic, M; Coelho, FA; Nouwt, B; Rua, DE; Tomcic, A; Pesic, S;

Publication
WSDM'22: PROCEEDINGS OF THE FIFTEENTH ACM INTERNATIONAL CONFERENCE ON WEB SEARCH AND DATA MINING

Abstract

2022

Practical Aspects of Active Distribution Networks

Authors
Abreu C.; Rua D.; Lopes J.P.;

Publication
Lecture Notes in Electrical Engineering

Abstract

2021

Functional Scalability and Replicability Analysis for Smart Grid Functions: The InteGrid Project Approach

Authors
Menci, SP; Bessa, RJ; Herndler, B; Korner, C; Rao, BV; Leimgruber, F; Madureira, AA; Rua, D; Coelho, F; Silva, JV; Andrade, JR; Sampaio, G; Teixeira, H; Simoes, M; Viana, J; Oliveira, L; Castro, D; Krisper, U; Andre, R;

Publication
ENERGIES

Abstract
The evolution of the electrical power sector due to the advances in digitalization, decarbonization and decentralization has led to the increase in challenges within the current distribution network. Therefore, there is an increased need to analyze the impact of the smart grid and its implemented solutions in order to address these challenges at the earliest stage, i.e., during the pilot phase and before large-scale deployment and mass adoption. Therefore, this paper presents the scalability and replicability analysis conducted within the European project InteGrid. Within the project, innovative solutions are proposed and tested in real demonstration sites (Portugal, Slovenia, and Sweden) to enable the DSO as a market facilitator and to assess the impact of the scalability and replicability of these solutions when integrated into the network. The analysis presents a total of three clusters where the impact of several integrated smart tools is analyzed alongside future large scale scenarios. These large scale scenarios envision significant penetration of distributed energy resources, increased network dimensions, large pools of flexibility, and prosumers. The replicability is analyzed through different types of networks, locations (country-wise), or time (daily). In addition, a simple replication path based on a step by step approach is proposed as a guideline to replicate the smart functions associated with each of the clusters.

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.

2018

Electric Vehicles Charging: Management and Control Strategies

Authors
Soares, FJ; Rua, D; Gouveia, C; Tavares, BD; Coelho, AM; Lopes, JAP;

Publication
IEEE VEHICULAR TECHNOLOGY MAGAZINE

Abstract
In this article, we present a holistic framework for the integration of electric vehicles (EVs) in electric power systems. Their charging management and control methodologies must be optimized to minimize the negative impact of the charging process on the grid and maximize the benefits that charging controllability may bring to their owners, energy retailers, and system operators. We have assessed the performance of these methods initially through steady-state computational simulations, and then we validated them in a microgrid (MG) laboratory environment. © 2018 IEEE.

Supervised
thesis

2018

The demand for healthcare services and resources: patterns, trends and challenges in healthcare delivery

Author
Sofia Cristina Guedes de Sousa e Cruz Gomes

Institution
UP-FEUP

2018

Towards solving a robust and sustainable Vehicle Routing Problem with Backhauls

Author
Maria João Martins dos Santos

Institution
UP-FEUP

2018

Escalamento de Inspetores de Aviação Civil no Brasil: Formalização do Problema e Metodologia de Resolução

Author
Marco Antonio Diniz Silva

Institution
UP-FEUP