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Sobre

Sobre

Filipe Azevedo obteve o grau de licenciado em 1999, o grau de Mestre em 2003, ambos em Engenharia Electrotécnica e de Computadores na Faculdade de Engenharia da Universidade do Porto (FEUP), Portugal, e concluiu o Doutoramento em 2008 na Universidade de Trás-os-Montes e Alto Douro (UTAD), Portugal. Actualmente é Professor Adjunto no ISEP/IPP - Instituto Superior de Engenharia do Porto - Politécnico do Porto e Investigador no INESC TEC, Portugal. As suas áreas favoritas de investigação são Economia aplicada aos mercados de energia eléctrica, Técnicas de Apoio à Decisão aplicadas aos problemas Economicos na área de Engenharia, aplicações de Inteligência Artificial (I. A.), Smartgrids e integração da produção de energias renováveis nos sistemas de energia. Filipe Azevedo possui também interesses em problemas relacionados com Segurança Nacional, criptografia e encriptação. 

Tópicos
de interesse
Detalhes

Detalhes

  • Nome

    Filipe Azevedo
  • Cluster

    Energia
  • Cargo

    Investigador Sénior
  • Desde

    01 setembro 2011
001
Publicações

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.

2016

Price forecasting and validation in the Spanish electricity market using forecasts as input data

Autores
Ortiz, M; Ukar, O; Azevedo, F; Mugica, A;

Publicação
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS

Abstract
The electricity sector has been subjected to major changes in the last few years. Previously, there existed a regulated system where electric companies could know beforehand the amount of energy each generator would produce, hence basing their largely operational strategy on cost minimization in order to increase their profits. In Spain, from 1988 till 1997, electricity prices were established by the 'Marco Legal Estable' Stable Legal Framework, where the Ministry of Industry and Energy acknowledged the existence of certain generation costs related to each type of technology. It was an industrial sector with no actual competition and therefore, with very few controllable risks. In the aftermath of the electricity market liberalization competition and uncertainty arose. Electricity spot prices became highly volatile due to the specific characteristics of electricity as a commodity. Long-term contracts allowed for hedge funds to act against price fluctuation in the electricity market. As a consequence, developing an accurate electricity price forecasting model is an extremely difficult task for electricity market agents. This work aims to propose a methodology to improve the limitations of those methodologies just using historical data to forecast electricity prices. In this manner, and in order to gain access to more recent data, instead of using natural gas prices and electricity load historical data, a regression model to forecast the evolution of natural gas prices, and a model based on artificial neural networks (ANN) to forecast electricity loads, are proposed. The results of these models are used as input for an electricity price forecast model. Finally, and to demonstrate the effectiveness of the proposed methodology, several study cases applied to the Spanish market, using real price data, are presented.

2014

Analysis of electricity market prices using multidimensional scaling

Autores
Azevedo, F; Machado, JT;

Publicação
Mathematical Methods in Engineering

Abstract
This paper studies the impact of the energy upon electricity markets using Multidimensional Scaling (MDS). Data from major energy and electricity markets is considered. Several maps produced by MDS are presented and discussed revealing that this method is useful for understanding the correlation between them. Furthermore, theresults help electricity markets agents hedging against Market Clearing Price (MCP) volatility. © Springer Science+Business Media Dordrecht 2014.

2013

Multidimensional scaling analysis of electricity market prices

Autores
Azevedo, F; Machado, JT;

Publicação
Intelligent Systems, Control and Automation: Science and Engineering

Abstract
This paper studies the impact of energy and stock markets upon electricity markets using Multidimensional Scaling (MDS). Historical values from major energy, stock and electricity markets are adopted. To analyze the data several graphs produced by MDS are presented and discussed. This method is useful to have a deeper insight into the behavior and the correlation of the markets. The results may also guide the construction models, helping electricity markets agents hedging against Market Clearing Price (MCP) volatility and, simultaneously, to achieve better financial results. © 2013, Springer Science+Business Media Dordrecht.

2012

Analysis of Electricity Markets Using Multidimensional Scaling

Autores
Filipe Azevedo; J. Tenreiro Machado

Publicação
EEM 2012 - 9th International Conference on the European Electricity Market, pp.1-4, Florence, Itália

Abstract
This paper studies the impact of the energy upon electricity markets using Multidimensional Scaling (MDS). MDS is a computational and statistical technique that produces a spatial representation of similarity between objects through factors of relatedness. MDS represents in a low dimensional map data points whose similarities are defined in a higher dimensional space. Data from major energy and electricity markets is considered. Several maps produced by MDS are presented and discussed revealing that this method is useful for understanding the correlation between them. Furthermore, the results help electricity markets agents hedging against Market Clearing Price (MCP) volatility.

Teses
supervisionadas

2021

Media aggregation: developing and applying a method to create user-centered aggregators

Autor
Hugo Vaz Neves

Instituição
UP-FEUP

2020

Desenvolvimento de um Sistema de Reconhecimento Facial

Autor
SARA RAQUEL DOS SANTOS RODRIGUES

Instituição
IPP-ISEP

2020

Uma Visão sobre a Tecnologia Blockchain: Domínios de Aplicação e Especificidades na Cadeia de Abastecimento

Autor
EDGAR EMANUEL LEITÃO TAVEIRA

Instituição
IPP-ISEP

2019

Plano Diretor Municipal de Iluminação Pública para o Município de Ovar

Autor
TIAGO EMANUEL POLIDO ESTEVES

Instituição
IPP-ISEP

2019

Anteprojeto de um plano diretor municipal de iluminação pública

Autor
MANUEL ANTÓNIO MOREIRA RIBEIRO

Instituição
IPP-ISEP