Sergio Motta

Sergio Motta

Research Scientist

  • Phone+358401730518

Research activity per year

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Personal profile

Research interests

My main research interests are in Artificial Intelligence applications in Power Systems. Most recently, I have been involved in projects regarding reliability studies in both transmission, distribution and local level; Microgrid technologies and operations; and DC distribution networks.

Short bio

Sergio Ricardo da Motta Pires (Sergio Motta) is originally from the sunny Natal, Rio Grande do Norte, in the Northeast of Brazil. He got a BSc. in Electrical Engineering from Universidade Federal do Rio Grande do Norte in 2014, after one year of exchange studies in Renewable Energies at University of Dundee, Scotland, in 2013. After obtaining his bachelor's degree, Sergio worked as a lecturer and assistant researcher before going once again abroad to pursue his Masters studies. Sergio completed his MSc. in Smart Electrical Networks and Systems (SENSE) from InnoEnergy Master School, with a double-degree from the Royal Institute of Technology (KTH) in Sweden and the Polytechnical University of Catalunya (UPC) in Spain. He continued his career in research in the field of Smart Grids, joining VTT's Power Systems and Renewables team in 2018 as a Research Scientist.

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 7 - Affordable and Clean Energy

Education/Academic qualification

Engineering, Master, MSc. Smart Electrical Networks and Systems (SENSE), KTH Royal Institute of Technology

1 Aug 20151 Oct 2017

Award Date: 1 Dec 2017

Engineering, Bachelor, Federal University of Rio Grande do Norte (UFRN)

1 Jan 200927 Feb 2014

Award Date: 27 Feb 2014

Engineering, Doctorate

1 Aug 2019 → …

Skills and expertise

  • Artificial Intelligence
  • Microgrids
  • DC systems
  • Power System Reliability
  • Data Analysis


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