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Sobre

Sobre

Professr Associado desde 2011 na Faculda de de Engenhgaria da Universidade do Porto (FEUP).

Doutorado em 1995 em Engenharia Eletrotécnica e Computadores na FEUP.

Licenciado em 1984 em Engenharia Eletrotécnica e Computadores na FEUP.

Investigador do INESC TEC desde 1985.

Tópicos
de interesse
Detalhes

Detalhes

  • Nome

    José Nuno Fidalgo
  • Cluster

    Energia
  • Cargo

    Investigador Sénior
  • Desde

    25 junho 1985
030
Publicações

2019

Impact of Climate Changes on the Portuguese Energy Generation Mix

Autores
Nuno Fidalgo, JN; Jose, DD; Silva, C;

Publicação
2019 16TH INTERNATIONAL CONFERENCE ON THE EUROPEAN ENERGY MARKET (EEM)

Abstract
Global climate change is currently a focus issue because of its impacts on the most diverse natural systems and, consequently, the development of humanity. The electricity sector is a major contributor to climate change because of its long-standing dependence on fossil fuels. However, the energy paradigm is changing, and renewable sources tend to play an increasingly important role in the energy mix in Portugal. Due to the strong relationship between renewable energies and climate-related natural resources, the climate change phenomenon could have considerable effects on the electricity sector. This paper analyzes the effects of climate change on the energy mix in Portugal in the medium / long term (up to 2050). The proposed methodology is based on the simulation of climate scenarios and projections of installed power by type and consumption. The combinations of these conditions are inputted to an energy accounting simulation tool, able to combine all information and provide a characterization of the system state for each case. The most favorable forecasted scenarios indicate that a fully renewable electricity system is achievable in the medium term, in line with the objectives of the European Union, as long as investments in renewable sources continue to be stimulated in the coming years.

2018

The Use of Smart Grids to Increase the Resilience of Brazilian Power Sector to Climate Change Effects

Autores
Jose, DD; Nuno Fidalgo, JN;

Publicação
TECHNOLOGICAL INNOVATION FOR RESILIENT SYSTEMS (DOCEIS 2018)

Abstract
Climate change has been a much-commented subject in the last years. The energy sector is a major responsible for this event and one of the most affected by it. Increasing the participation of renewable is a way to mitigate these effects. However, a system with large share of renewables (like Brazil) is more vulnerable to climate phenomena. This article analyzes the implementation of smart grids as a strategy to mitigate and adapt the electricity sector to climate change. Different climate and energy sector scenarios were simulated using a bottom-up approach with an accounting model. The results show that smart grids can help save energy, increase network resilience to natural hazards and reduce operational, maintenance costs and investments in new utilities. It would also allow tariffs diminution because of generation and losses costs reductions.

2018

Load and electricity prices forecasting using Generalized Regression Neural Networks

Autores
Paulos, JP; Fidalgo, JN;

Publicação
2018 INTERNATIONAL CONFERENCE ON SMART ENERGY SYSTEMS AND TECHNOLOGIES (SEST)

Abstract
Over time, the electricity price and energy consumption are increasingly growing their weight as prime foundations of the electrical sector, with their analysis and forecasts being targeted as key elements for the stable maintenance of electricity markets. The advent of smart grids is escalating the importance of forecasting because of the expected ubiquitous monitoring and growing complexity of a data-rich ever-changing milieu. So, the increasing data volatility will require forecasting tools able to rapidly readjust to a dynamic environment. The Generalized Regression Neural Network (GRNN) approach is a solution that has recently re-emerged, emphasizing good performance, fast run-times and ease of parameterization. The merging of this model with more conventional methods allows us to obtain more sturdy solutions with shortened training times, when compared to conventional Artificial Neural Networks (ANN). Overall, the performance of the GRNN, although slightly inferior to that of the ANN, is suitable, but linked to much lower training times. Ultimately, the GRNN would be a proper solution to blend with the latest smart grids features, which may require much reduced forecasting training times.

2018

The Use of Smart Grids to Increase the Resilience of Brazilian Power Sector to Climate Change Effects

Autores
de São José, D; Fidalgo, JN;

Publicação
IFIP Advances in Information and Communication Technology - Technological Innovation for Resilient Systems

Abstract

2018

Improving electricity price forecasting trough data segmentation based on artificial immune systems

Autores
Fidalgo, JN; Da Rocha, EFNR;

Publicação
International Conference on the European Energy Market, EEM

Abstract
The price evolution in electricity market with large share of renewables often exhibits a deep volatility, triggered by external factors such as wind and water availability, load level and also by business strategies of market agents. Consequently, in many real applications, the performance of electricity price is not appropriate. The goal of this article is to analyze the available market data and characterize circumstances that affect the evolution of prices, in order to allow the identification of states that promote price instability and to confirm that class segmentation allows increasing forecast performance. A regression technique (based on Artificial Neural Networks) was applied first to the whole set and then to each class individually. Performances results showed a clear advantage (above 20%) of the second approach when compared to the first one. © 2018 IEEE.

Teses
supervisionadas

2019

Identificação de perfis típicos e de anomalias de consumo

Autor
Eduardo Miguel Reis Gonçalves Moreira

Instituição
UP-FEUP

2019

Classificação do desempenho energético de edifícios residenciais com base em algoritmos imunológicos

Autor
José Pedro Oliveira Martins da Silva Alves

Instituição
UP-FEUP

2018

Identificação de perfis típicos e de anomalias de consumo

Autor
Eduardo Miguel Reis Gonçalves Moreira

Instituição
UP-FEUP

2018

Climate changes in Brazil: The use of smart grids as a mitigation and adaptation strategy

Autor
Débora Regina de São José

Instituição
UP-FEUP

2018

Alterações climáticas e o impacto no mix energético em Portugal

Autor
Carlos Eduardo Pires da Silva

Instituição
UP-FEUP