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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
041
Publicações

2022

Identification of Typical and Anomalous Patterns in Electricity Consumption

Autores
Fidalgo, JN; Macedo, P;

Publicação
APPLIED SCIENCES-BASEL

Abstract
Nontechnical losses in electricity distribution networks are often associated with a countries’ socioeconomic situation. Although the amount of global losses is usually known, the separation between technical and commercial (nontechnical) losses will remain one of the main challenges for DSO until smart grids become fully implemented and operational. The most common origins of commercial losses are energy theft and deliberate or accidental failures of energy measuring equipment. In any case, the consequences can be regarded as consumption anomalies. The work described in this paper aims to answer a request from a DSO, for the development of tools to detect consumption anomalies at end-customer facilities (HV, MV and LV), invoking two types of assessment. The first consists of the identification of typical patterns in the set of consumption profiles of a given group or zone and the detection of atypical consumers (outliers) within it. The second assessment involves the exploration of the load diagram evolution of each specific consumer to detect changes in the consumption pattern that could represent situations of probable irregularities. After a representative period, typically 12 months, these assessments are repeated, and the results are compared to the initial ones. The eventual changes in the typical classes or consumption scales are used to build a classifier indicating the risk of anomaly.

2022

Decision support system for long-term reinforcement planning of distribution networks

Autores
Fidalgo, JN; Azevedo, F;

Publicação
ELECTRIC POWER SYSTEMS RESEARCH

Abstract
The last decade has witnessed a growing tendency to promote deeper exploitation of power systems infrastructure, postponing investments in networks reinforcement. In particular, the literature on smart grids research often emphasizes their potential to defer investments. The study reported in this paper analyses the impact of reinforcement decisions, comparing the long-term costs associated with different network conditions and economic analysis parameters. The results support the conclusion that network reinforcement deferral is not a panacea, as it often generates costly situations in the long-term. The challenge is not to find new ways to postpone investments, but to find the most beneficial criterion to trigger the grid reinforcements actions. Another contribution of the present work is a decision support system to identify the most economical network reinforcement criterion in terms of the peak to capacity ratio.

2021

Non-Intrusive Load Monitoring for Household Disaggregated Energy Sensing

Autores
Paulos J.P.; Nuno Fidalgo J.; Gama J.;

Publicação
2021 IEEE Madrid PowerTech, PowerTech 2021 - Conference Proceedings

Abstract

2021

Detection and Mitigation of Extreme Losses in Distribution Networks

Autores
Paulos J.P.; Fidalgo J.N.; Saraiva J.T.; Barbosa N.;

Publicação
2021 IEEE Madrid PowerTech, PowerTech 2021 - Conference Proceedings

Abstract

2021

Estimation of the Global Amount of Mandatory Investments for Distribution Network Expansion Planning

Autores
MacEdo P.M.; Fidalgo J.N.; Saraiva J.T.;

Publicação
2021 IEEE Madrid PowerTech, PowerTech 2021 - Conference Proceedings

Abstract

Teses
supervisionadas

2021

Previsão de preços de mercado baseada em Deep Learning

Autor
Ana Rita Martins Cruz e Silva

Instituição
UP-FEUP

2021

Gestão e Atualização Automática de Firmware para Câmaras de Videovigilância em Shop Floor

Autor
LUÍS MIGUEL PINTO LISBOA

Instituição
IPP-ISEP

2021

Linguistic and Emotion-based Identification of Tweets with Fake News: A Case Study

Autor
Vitor Sexto Bernardes

Instituição
UP-FCUP

2021

Estimação automática do estado de um manipulador robótico sobre-sensorizado

Autor
João Pedro Ribeiro Moreira

Instituição
UP-FEUP

2021

Previsão de consumo de médio e longo prazo

Autor
André Marques Rodrigues

Instituição
UP-FEUP