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About

About

I have an Integrated Masters in Electrical and Computer Engineering from the Faculty of Engineering of the University of Porto, obtained in 2012. After graduation, I gained industrial experience in the IT consulting sector, followed by a scholarship to develop graphical interfaces for the Operational Research Group of the Faculty of Economics.


In 2014, I joined the Centre for Power Systems (CPES) of INESC TEC, where I focused on the development of advanced tools for the monitoring and control of electrical distribution networks. In addition, in 2015 I enrolled in MIT Portugal's Ph.D. programme in Sustainable Energy Systems.


My work mainly revolves around improving traditional analytical approaches and leveraging large amounts of data to create innovative, data-driven solutions. At the intersection of technology, research and sustainability, my research and experience have made tangible contributions in real-world environments faced by energy distribution companies. This has been demonstrated through consulting services provided to private entities, as well as active involvement in European pilot projects.

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Publications

2023

Data-driven Assessment of the der Flexibility Impact on the LV Grid Management

Authors
Fritz, B; Sampaio, G; Bessa, J;

Publication
2023 IEEE Belgrade PowerTech, PowerTech 2023

Abstract
Low voltage (LV) grids face a challenge of effectively managing the growing presence of new loads like electric vehicles and heat pumps, along with the equally growing installation of rooftop photovoltaic panels. This paper describes practical applications of sensitivity factors, extracted from smart meter data (i.e., without resorting to grid models), to i) link voltage problems to different costumers/devices and their location in the grid, ii) manage the flexibility provided by distributed energy resources (DERs) to regulate voltage, and iii) assess favorable locations for DER capacity extensions, all with the aim of supporting the decision-making process of distribution system operators (DSOs) and the design of incentives for customers to invest in DERs. The methods are tested by running simulations based on historical meter data on six grid models provided by the EU-Joint Research Center. The results prove that it is feasible to implement advanced LV grid analysis and management tools despite the typical limitations in its electrical and topological characterisation, while avoiding the use of computationally heavy tools such as optimal power flows. © 2023 IEEE.

2022

Conditional parametric model for sensitivity factors in LV grids: A privacy-preserving approach

Authors
Sampaio, G; Bessa, RJ; Goncalves, C; Gouveia, C;

Publication
ELECTRIC POWER SYSTEMS RESEARCH

Abstract
The deployment of smart metering technologies in the low voltage (LV) grid created conditions for the application of data-driven monitoring and control functions. However, data privacy regulation and consumers' aversion to data sharing may compromise data exchange between utility and customers. This work presents a data-driven method, based on smart meter data, to estimate linear sensitivity factors for three-phase unbalanced LV grids, which combines a privacy-preserving protocol and varying coefficients linear regression. The proposed method enables centralized and peer-to-peer learning of the sensitivity factors. Potential applications for the sensitivity factors are demonstrated by solving voltage violations or computing operating envelopes in a LV grid without resorting to its network topology or electrical parameters.

2022

Local flexibility need estimation based on distribution grid segmentation

Authors
Retorta, F; Gouveia, C; Sampaio, G; Bessa, R; Villar, J;

Publication
International Conference on the European Energy Market, EEM

Abstract
This work presents a methodology to segment the MV electric grid into grid zones for which the active power flexibility needs that solve the forecasted voltage and current issues are computed. This methodology enables the Distribution System Operator (DSO) to publish flexibility needs per zones, allowing aggregators to offer flexibility by optimizing their portfolio of resources in each grid zone. A case study is used to support the methodology results and its performance, showing the feasibility of solving grid issues by activating flexibility per grid zones according to the proposed methodology. © 2022 IEEE.

2022

Euniversal's smart grid solutions for the coordinated operation & planning of MV and LV networks with high EV integration

Authors
Sampaio, G; Gouveia, C; Bessa, R; Villar, J; Retorta, F; Carvalho, L; Merckx, C; Benothman, F; Promel, F; Panteli, M; Mourão, RL; Louro, M; Águas, A; Marques, P;

Publication
CIRED Porto Workshop 2022: E-mobility and power distribution systems

Abstract

2021

Functional Scalability and Replicability Analysis for Smart Grid Functions: The InteGrid Project Approach

Authors
Menci, SP; Bessa, RJ; Herndler, B; Korner, C; Rao, BV; Leimgruber, F; Madureira, AA; Rua, D; Coelho, F; Silva, JV; Andrade, JR; Sampaio, G; Teixeira, H; Simoes, M; Viana, J; Oliveira, L; Castro, D; Krisper, U; Andre, R;

Publication
ENERGIES

Abstract
The evolution of the electrical power sector due to the advances in digitalization, decarbonization and decentralization has led to the increase in challenges within the current distribution network. Therefore, there is an increased need to analyze the impact of the smart grid and its implemented solutions in order to address these challenges at the earliest stage, i.e., during the pilot phase and before large-scale deployment and mass adoption. Therefore, this paper presents the scalability and replicability analysis conducted within the European project InteGrid. Within the project, innovative solutions are proposed and tested in real demonstration sites (Portugal, Slovenia, and Sweden) to enable the DSO as a market facilitator and to assess the impact of the scalability and replicability of these solutions when integrated into the network. The analysis presents a total of three clusters where the impact of several integrated smart tools is analyzed alongside future large scale scenarios. These large scale scenarios envision significant penetration of distributed energy resources, increased network dimensions, large pools of flexibility, and prosumers. The replicability is analyzed through different types of networks, locations (country-wise), or time (daily). In addition, a simple replication path based on a step by step approach is proposed as a guideline to replicate the smart functions associated with each of the clusters.