Carla Silva Gonçalves
Carla Gonçalves is a Postdoctoral Researcher at the Centre for Power and Energy Systems in INESC TEC. In 2021, she obtained a Ph.D. in Applied Mathematics from the Faculty of Sciences of the University of Porto (FCUP). She received the M.Sc. in Applied Mathematics from FCUP, in 2015. From 2015 to 2019, she was involved in a wide range of energy forecast consulting collaborations between INESC TEC and the industry: REN (Portugal), EDP Renewables (Spain), RTE (France), and EDP Gestão da Produção de Energia (Portugal). Until 2022, she was associated with the H2020 Smart4RES project, and since 2023, she is taking part in the European ENERSHARE and GREEN.DAT.AI projects. Her research has been focused on probabilistic and collaborative forecasting methods, with a special emphasis on renewable energies, data privacy, and monetization. During her scientific career, she has co-authored 13 scientific papers (6 Q1 journals with impact factors between 3.818 and 8.310, and 7 international conference proceedings) and has submitted a patent (currently pending). She also served as an Invited Auxiliary Professor at the University of Porto for two semesters.
Projects
PriceMining
Application of advanced data analytics techniques to wholesale electricity market prices (i.e., day-ahead and regulation reserve) in order to extract conclusions from data dependencies, patterns and behaviors. Causality analysis of day-ahead market prices, regulation reserve volume and prices.
CampusREN2021
Publications
Data Science for Next Generation Renewable Energy Forecasting - Highlight Results from the Smart4RES Project
Kariniotakis, G;Camal, S;Sossan, F;Nouri, B;Lezaca, J;Lange, M;Alonzo, B;Libois, Q;Pinson, P;Bessa, R;Goncalves, C;
2021
IET Conference Proceedings
A Blockchain-based Data Market for Renewable Energy Forecasts
Coelho, F;Silva, F;Goncalves, C;Bessa, R;Alonso, A;
2022
2022 FOURTH INTERNATIONAL CONFERENCE ON BLOCKCHAIN COMPUTING AND APPLICATIONS (BCCA)
A critical overview of privacy-preserving approaches for collaborative forecasting
Goncalves, C;Bessa, RJ;Pinson, P;
2021
INTERNATIONAL JOURNAL OF FORECASTING
Conditional parametric model for sensitivity factors in LV grids: A privacy-preserving approach
Sampaio, G;Bessa, RJ;Goncalves, C;Gouveia, C;
2022
ELECTRIC POWER SYSTEMS RESEARCH
Supervised theses
Deep Learning for Improved Detection of Subtle
José Carlos Nunes Maurício
M - 2024
UP-FCUP