Welcome Message

In the evolution of the electrical systems in the smart grid context, the amount of data available is increasing considerably. Data-driven solutions are emerging as alternatives to model-based approaches. New tools are being developed to handle the flow of data gathered during time from different sources. The presentation highlights various aspects referring to data-driven approaches, from consistency of the data to the challenging task of transforming data into knowledge. Specific focus is set on the nature and quality of the data, the role of data uncertainty, and the role of the expert of the domain in verifying the meaningfulness of the available data and in identifying the most effective usage of the data in the smart grid applications. Biography: Gianfranco Chicco holds a PhD in Electrotechnics Engineering and is a Full Professor of Power and Energy Systems at Politecnico di Torino (POLITO) in Torino, Italy. He is a Fellow of the IEEE (Power and Energy Society). He received the title of “Doctor Honoris Causa” from the University Politehnica of Bucharest (Romania) and from the Technical University “Gheorghe Asachi” of Iasi (Romania) in 2017 and 2018, respectively. He is the vice-Chair of the IEEE Italy Section. More information about Prof. Gianfranco Chicco, please visit: http://icpse.org/keynote.html . Keynote Speaker October 22 | 11:20-12:00(GMT+3) Prof. Bikash Pal, IEEE Fellow, Imperial College London, UK Vice President of Publications, IEEE Power and Energy Society Editor-in-Chief of IEEE Transactions on Sustainable Energy (2012-2017) Editor-in-Chief of IET Generation, Transmission and Distribution (2005-2012) Speech Title: Robust Volt-Var Control in Power Distribution Abstract: Electrical generation, transmission and distribution systems all over the world have entered a period of significant renewal and technological change. There have been phenomenal changes/deployments in technology of generation driven by the worldwide emphasis on energy from wind and solar as a sustainable solution to our energy need. Increasingly energy demand from heating and transportation are being met by electricity. These changes have significantly influenced the planning, design, operation and control of the power distribution system. Accommodating uncertainties in renewable generation and demand forecast in a cost-effective manner is now a very complex optimization problem. This talk will share our recent research efforts Volt/VAr control (VVC) strategy in distribution systems to address the uncertainties. Efficient chance constrained conic optimisation technique accelerated through scenario reduction approach will be discussed to demonstrate the significant reduction of voltage violations when compared with the deterministic cases while not relaxing the conservativeness of the final solutions. It will also touch upon treatment of certain types of load characteristic in the proposed solution framework. Future research challenges and opportunities will be highlighted. Electrical generation, transmission and distribution systems all over the world have entered a period of significant renewal and technological change. There have been phenomenal changes/deployments in technology of generation driven by the worldwide emphasis on energy from wind and solar as a sustainable solution to our energy need. Increasingly energy demand from heating and transportation are being met by electricity. These changes have significantly influenced the planning, design, operation and control of the power distribution system. Accommodating uncertainties in renewable generation and demand forecast in a cost-effective manner is now a very complex optimization problem. This talk will share our recent research efforts Volt/VAr control (VVC) strategy in distribution systems to address the uncertainties. Efficient chance constrained conic optimisation technique accelerated through scenario reduction approach will be discussed to demonstrate the significant reduction of voltage violations when compared with the deterministic cases while not relaxing the conservativeness of the final solutions. It will also touch upon treatment of certain types of load characteristic in the proposed solution framework. Future research challenges and opportunities will be highlighted.