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Details

  • Name

    David Emanuel Rua
  • Cluster

    Power and Energy
  • Role

    Area Manager
  • Since

    01st October 2009
004
Publications

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.

2018

Data economy for prosumers in a smart grid ecosystem

Authors
Bessa, RJ; Rua, D; Abreu, C; Machado, P; Andrade, JR; Pinto, R; Gonçalves, C; Reis, M;

Publication
e-Energy 2018 - Proceedings of the 9th ACM International Conference on Future Energy Systems

Abstract
Smart grids technologies are enablers of new business models for domestic consumers with local flexibility (generation, loads, storage) and where access to data is a key requirement in the value stream. However, legislation on personal data privacy and protection imposes the need to develop local models for flexibility modeling and forecasting and exchange models instead of personal data. This paper describes the functional architecture of an home energy management system (HEMS) and its optimization functions. A set of data-driven models, embedded in the HEMS, are discussed for improving renewable energy forecasting skill and modeling multi-period flexibility of distributed energy resources. © 2018 Copyright held by the owner/author(s).

2018

Advanced energy management for demand response and microgeneration integration

Authors
Abreu, C; Rua, D; Machado, P; Pecas Lopes, JAP; Heleno, M;

Publication
20th Power Systems Computation Conference, PSCC 2018

Abstract
Energy management is a key tool that will enable consumers to optimize their energy use according to different objectives. Allow users to insert their energy use preferences combined with the effective configuration and control of existing devices (loads and microgeneration) is the basis, in this paper, to design adaptable energy optimization algorithms that are capable of outputting feasible, understandable and useful actions, automated and/or manual, for the activation of the existing portfolio of flexible devices. This paper presents an advanced energy management system as an innovative platform that intends to accomplish real energy optimization schemes to support demand response, promote the energy efficiency and contribute towards renewable integration. © 2018 Power Systems Computation Conference.

2018

Microgrid Demonstration Projects and Pilot Sites

Authors
Gouveia, C; Moreira, C; Rua, D; Peças Lopes, J;

Publication
Microgrids Design and Implementation

Abstract

2017

Multi-temporal Optimal Power Flow for voltage control in MV networks using Distributed Energy Resources

Authors
Meirinhos, JL; Rua, DE; Carvalho, LM; Madureira, AG;

Publication
ELECTRIC POWER SYSTEMS RESEARCH

Abstract
Large-scale integration of variable Renewable Energy Sources (RES) brings significant challenges to grid operation that require new approaches and tools for distribution system management, particularly concerning voltage control. Therefore, an innovative approach for voltage control at the MV level is presented. It is based on a preventive day-ahead analysis that uses data from load/RES forecasting tools to establish a plan for operation of the different Distributed Energy Resources (DER) for the next day. The approach is formulated as a multi-temporal Optimal Power Flow (OPF) solved by a meta-heuristic, used to tackle complex multi-dimensional problems. The tuning of the meta-heuristic parameters was performed to ensure the robustness of the proposed approach and enhance the performance of the algorithm. It was tested through simulation in a large scale test network with good results.

Supervised
thesis

2017

Energy Management Service Design - an exploratory case study for Portuguese household

Author
Emil Goyushzada

Institution
UP-FEUP

2017

DESIGN AND IMPLEMENTATION OF SMART STRATEGIES TOWARD ENHANCED ENERGY MANAGEMENT OF BUILDINGS

Author
Cláudia Rocha Abreu

Institution
UP-FEUP

2016

Data mining no âmbito da monitorização não-intrusiva de cargas

Author
Ana Inês Soares Pinto Oliveira Soares

Institution
UP-FEP