Prof. Zita Vale

Polytechnic of Porto, ISEP, GECAD, Portugal

 

Presentation Topics (June 13): Artificial Intelligence Models for Power and Energy Applications: From Data-Driven to Knowledge-Based Approaches


Zita Vale is Principal Coordinator Professor at the School of Engineering (ISEP) of the Polytechnic of Porto (IPP) and Director of GECAD Research Group on Intelligent Engineering and Computing for Advanced Innovation and Developments. She is also a member of LASI – Associate Laboratory of Intelligent Systems, where she chairs the line on “Smart cities, mobility and energy”, one of the five LASI research lines. Her main interests regard the application of Artificial Intelligence Techniques to Power systems, including Knowledge based systems, Multi- agent systems, Neural Networks, Meta-heuristics, Optimization, Machine Learning, and Knowledge Discovery Techniques. She has been involved in more than 60 R&D projects from which she coordinated more than 30 projects. The main application fields of these projects are: – Smart Grids, with an intensive use of Renewable Energy Sources, Distributed Energy Resources and Distributed Generation, addressing the management of energy resources, the negotiation of DER in electricity markets, demand response, and electric vehicles; – Electricity markets, addressing prices and tariffs, decision-support for market participants, ancillary services, derivatives market, pricing and market simulation. She published over 900 works, including more than 180 papers in international scientific journals. She has been contributing to renowned international conferences as a member of the Program Committee, Program Chair, reviewer, and organizing special and panel sessions. She has been also keynote speaker in several conferences, guest editor and/or member of editorial board of scientific international journals. She also contributes to several scientific and technical committees and working groups. Currently, she chairs the Institute of Electrical and Electronic Engineers (IEEE) Power and Energy Society (PES) Working Group on Data Analysis and Mining and Task Force on Open Data Sets.