PhD Defence: Konstantina Valogianni
In her dissertation ‘Sustainable Electric Vehicle Management using Coordinated Machine Learning’, ERIM’s Konstantina Valogianni investigates how intelligent algorithms can support electricity customers in their complex decisions within the electricity grid.
Konstantina Valogianni defended her dissertation in the Senate Hall at Erasmus University Rotterdam on Thursday, 30 June 2016 at 15:30. Her supervisor was Prof. ir. H.W.G.M van Heck and her co-supervisor was Prof. W. Ketter. Other members of the Doctoral Committee were Prof. M.B.M. de Koster (RSM), Prof. A. Gupta (UMN), Prof. R. Unland (University of Duisberg-Essen), Prof. M. Gini (Umn), Dr J. van Dalen (RSM), Dr J. Collins (Umn), and Dr Andreas Symeonidis (Auth).
About Konstantina Valogianni
Konstantina Valogianni was born on January 23, 1988 in Larisa, Greece. She has studied Electrical and Computer Engineering in Aristotle University of Thessaloniki, Greece, where she specialized in computer software and electronics. In September 2011, Konstantina started her Ph.D. with the department of Technology & Operations Management at Rotterdam School of Management, Erasmus University. In 2014, she spent three months as a visiting scholar at Carlson School of Management, University of Minnesota. Her research interests include electricity markets, artificial intelligence, data-driven algorithmic design, intelligent agents. Alongside with her Ph.D. Konstantina has worked as a researcher for the FP7 EU-funded project Cassandra. Her work has appeared in the proceedings of various conferences such as the Conference of Advancement on Artificial Intelligence (AAAI), International Conference on Autonomous Agents and Multiagent Systems (AAMAS), International Conference on Information Systems (ICIS), Conference on Information Systems and Technology (CIST), Winter Conference in Business Intelligence (WCBI).
Apart from her research activities, Konstantina has been involved in teaching of the master courses ``Designing Business Applications", ``Next Generation Business Applications" and ``Programming for Managers", and has supervised MSc theses.
As of September 2016, Konstantina will be employed as an Assistant Professor of Information Systems at IE Business School, Madrid, Spain.
Thesis Abstract
The purpose of this dissertation is to investigate how intelligent algorithms can support electricity customers in their complex decisions within the electricity grid. In particular, we focus on how electric vehicle (EV) owners can be supported in their charging and discharging decision, benefiting from the information available. We examine the problem from different standpoints and show the benefits for each involved stakeholder dependent on the market conditions. In the first essay, we take the perspective of an individual EV owner and design an intelligent algorithm, which learning from her preferences and driving and consumption information, proposes optimized charging and discharging recommendations. In the second essay, we extend the first one by incorporating the EV within a smart home with a photovoltaic panel. The main goal of this study is to examine how accurate solar generation forecasting can be useful for charging the EV and make the best out of renewable sources. We propose a supervised learning algorithm which estimates the solar generation output from the weather conditions. In the third essay, we examine problem from the grid operator’s point of view, taking a top-down approach. We propose an auction mechanism which has as its main goal to service as many EV owners as possible, given a certain grid capacity. In the fourth essay, we propose a hybrid mechanism which combines benefits from top-down and bottom-up approaches. This mechanism is based on dynamic price functions that are able to incentivize EV customers to delay their charging duration when there is no urgency. Overall, this dissertation contributes to the academic literature with new algorithms that can leverage the power of data available and personalize EV charging recommendations. It also contributes to practice by providing useful insights to the involved stakeholders such as grid operators, energy utility companies, individual customers and automotive companies with respect to creating the right incentives for EV adoption. Finally, it adds to the very important discussion about sustainability, since it proposes ways to reduce carbon footprint and benefit the most from the available renewable sources.
· View and download Konstantina's dissertation
Photos: Chris Gorzeman / Capital Images
