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ODJEL ZA POUZDANOST

Objavljeno: 10. 10. 2016. u 12:26
Poziv na predavanje: Computational...

Odjel za pouzadnost Hrvatske sekcije IEEE-a poziva vas na predavanje

Computational Intelligence for Smart Cities: RES Integration and Plug-In Hybrid Electric Vehicles for a New Paradigm to address Proper Energy Policies and Sustainable Transport

koje će se održati prof.dr. Francesco Grimaccia sa Politecnico di Milano, Department of Energy, Milan, Italy, u petak 14. 10. 2016. u 10:30 sati u Hotelu Osijek, soba Lipa, Osijek.

Sažetak predavanja i životopis predavača pogledajte u nastavku obavijesti.

Sažetak predavanja:
Nowadays, the population growth and urbanization phenomena require new model to manage a distributed generation of energy sources, even conventional and unconventional renewables, and a correct energy policy is expected to address both people life style and environmental concerns. Among various kinds of renewable energy, the so called V-RES (Variable RES) power generation are becoming an opportunity for economical growth and rethink the entire power system model towards the Smart City concept.

Moreover, alternative non-conventional energy sources (e.g. recovering energy from traffic) or micro sources such as fuel cells and microturbines, have been also used in recent years for energy generation. A correct strategy to address proper energy policies needs to understand common features of the renewable energy but also the structure of the TSO-DSO power grid. Computational Intelligence represents a powerful tool to face optimization problems and forecasting issues in this context: power electronic can provide flexibility for the DG operations, but other important leverages such as Storage (V2G) and Electric Market can play a crucial role.

Thus, for proper operation of real Smart Cities, energy management strategies are important to regulate the output powers of each DG as well as their integration into the power network using ICT technologies and evolutionary computation algorithms.

Kratki životopis predavača:
Born in 1979, Master Degree in Mechanical Engineering from Politecnico di Milano University in 2003, PhD in Electrical Engineering (Cum Laude) in 2007 from the same institution. 
As part of his training, he took part in several international courses including Computational Electromagnetics in Packaging, Interconnects, and PCB Design (University of Maryland), Computational EM for Antenna Analysis (European School of Antennas), Data and Models in Engineering, Science and Business (MIT in Boston), Evolutionary Computation in Finance and Economics (NTU, Singapore), and other courses on Project Management, Intellectual Property and Technology Transfer.
Since 2001 is active in theoretical and experimental research, dedicated to the study and development of innovative optimization methods in the evolutionary computation field for engineering applications. In 2004 he received the Young Scientist Award fo the article "Genetical Swarm Optimization: A New Hybrid Evolutionary Algorithm For Electromagnetics". In 2005 he started a collaboration with the University of Queensland (Brisbane, Australia) on the subject of WSN for monitoring applications on the Barrier Reef. In the European Seventh Framework Programme he has participated in several activities and research projects concerning in particular topics of ICT, UAVs and Energy.
In 2016 he received the Best Paper Award at IEEE PES for an article on UAV technologies in O&M operations in PV plant monitoring and control.
He has published over 100 publications in journals, conference proceedings and book contributions on the topics of RES integration, forecasting tools and computational intelligence techniques. He is member of the IEEE society, CIS, SPIE and Vice-President of the Italian electrical society AEIT.
He is now professor at Department of Energy of Politecnico di Milano University and member of the steering board of the same institution.

Leonardo Jelenković
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KONTAKTI
 
Mandatno razdoblje 
do 31.12.2017.

 

Srete Nikolovski

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Leonardo Jelenković

Dopredsjednik odjela
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