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About

About

Pedro Macedo holds a M.Sc. degree in Electrical and Computer Engineering with specialisation in energy systems, from the Faculty of Engineering of the University of Porto (FEUP), since 2014.

Since then he develops his activity as a R&D in the area of System Planning and Reliability at the Centre for Power and Energy Systems (CPES), where he works in research projects in partnership with industry. He has been focusing his activity in the area of data mining and in the forecast models development applied to energy electrical systems.

Interest
Topics
Details

Details

  • Name

    Pedro Miguel Macedo
  • Cluster

    Power and Energy
  • Role

    Researcher
  • Since

    06th April 2015
008
Publications

2022

Identification of Typical and Anomalous Patterns in Electricity Consumption

Authors
Fidalgo, JN; Macedo, P;

Publication
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

The Value of Investments in Network Efficiency in Systems with a Large Integration of Distributed Renewable Generation

Authors
Fidalgo, JN; Paulos, JP; MacEdo, P;

Publication
International Conference on the European Energy Market, EEM

Abstract
This article analyzes the effects of the current policy trends - high levels of distributed generation (DG) and grid load/capacity ratio - on network efficiency. It starts by illustrating the network losses performance under different DG and load/capacity conditions. The second part concerns the simulation of network investments with the purpose of loss reduction for diverse system circumstances, including the impact of DG levels, energy cost, and discount rate. The attained results showed that DG, particularly large parks, have a negative impact on network efficiency: network losses tend to intensify with DG growth, under the current regulation. Furthermore, network investments in loss reduction would have a small global impact on network efficiency if the DG parks' connection lines are not included in the grid concession (not subjected to upgrade). Finally, the study determines that it is preferable to invest sooner, rather than to postpone the grid reinforcement for certain conditions, namely for low discount rates. © 2022 IEEE.

2021

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

Authors
Macedo, PM; Fidalgo, JN; Saraiva, JT;

Publication
2021 IEEE MADRID POWERTECH

Abstract

2020

Assessing the Impact of Investments in Distribution Planning

Authors
MacEdo, P; Fidalgo, JN; Tome Saraiva, J;

Publication
International Conference on the European Energy Market, EEM

Abstract

Supervised
thesis

2022

Planeamento de Investimentos na Rede de Distribuição com Base na Técnica Spike and Slab

Author
Hugo Francisco Rocha Costa

Institution
UP-FEUP

2021

Previsão de investimentos com base em informação esparsa

Author
João Pedro Espírito Santo Almeida

Institution
UP-FEUP

2020

Previsão de investimentos com base em informação esparsa

Author
João Pedro Espírito Santo Almeida

Institution
UP-FEUP