Dr K. (Konstantina) Valogianni
Konstantina Valogianni is a PhD candidate in the Department of Technology and Operations Management at Rotterdam School of Management, Erasmus University. Her research is oriented to the energy domain and the agent-based representation of the entities in the energy market with special focus on the balancing aspect. Konstantina holds a BSc and MSc degree in Electrical and Computer Engineering (Electronics and Computers Specialization) from Aristotle University of Thessaloniki, Greece. Currently she is interested in applications of machine learning and artificial intelligence in the liberalized energy maket. Konstantina is member of the Learning Agents Research Group at Erasmus (LARGE) and Future Energy Business at Erasmus University Rotterdam. Her work is strongly related to the Power Trading Agent Competition.
PhD Track Sustainable Electric Vehicle Management using Coordinated Machine Learning
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.
- Keywords
- Electric vehicles, coordination, machine learning, algorithmic design, energy informatics, sustainability, smart charging
- Time frame
- 2011 - 2016
Publications
Abstract (1)
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Academic (1)
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Collins, J., Ketter, W., Valogianni, K., & de Weerdt, M. (2012). Constructing and operating a large - scale simulation of retail electric power markets. Abstract from Statistical Challenges in Electronic Commerce Research 2012.
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Article (5)
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Academic (4)
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Ketter, W., Schroer, K., & Valogianni, K. (2023). Information Systems Research for Smart Sustainable Mobility: A Framework and Call for Action. Information Systems Research, 34(3), 1045-1065. https://doi.org/10.1287/ISRE.2022.1167
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Schallehn, F., & Valogianni, K. (2022). Sustainability awareness and smart meter privacy concerns: The cases of US and Germany. Energy Policy, 161, Article 112756. https://doi.org/10.1016/j.enpol.2021.112756
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Valogianni, K., Ketter, W., Collins, J., & Zhdanov, D. (2020). Sustainable Electric Vehicle Charging using Adaptive Pricing. Production and Operations Management, 29(6), 1550-1572. https://doi.org/10.1111/poms.13179
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Ketter, W., & Valogianni, K. (2016). Effective demand response for smart grids: Evidence from a real-world pilot. Decision Support Systems, 91, 48-66. https://doi.org/10.1016/j.dss.2016.07.007
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Professional (1)
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Valogianni, K. (2016). Stable energy: the road ahead for electric cars. RSM Discovery - Management Knowledge, 27(3), 14-16. http://hdl.handle.net/1765/93313
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Conference proceeding (24)
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Academic (24)
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Valogianni, K., Gupta, A., Ketter, W., Sen, S., & van Heck, E. (2019). Real-time Electric Vehicle Charging Using Optimal Grid Resources. In Winter Conference on Business Analytics (WCBA-19)
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Valogianni, K., Ketter, W., Collins, J., & Adomavicius, G. (2019). Heterogeneous Electric Vehicle Charging Coordination: A Variable Charging Speed Approach. In Proceedings of the 52nd Hawaii International Conference on System Sciences https://doi.org/10.24251/HICSS.2019.444
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Valogianni, K., Ketter, W., Collins, J., & Zhdanov, D. (2018). Facilitating a Sustainable Electric Vehicle Transition through Consumer Utility Driven Pricing. In International Conference on Information Systems (ICIS-18)
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Valogianni, K., Gupta, A., Ketter, W., Sen, S., & van Heck, E. (2016). Using Optimal Grid Resources For Coordinating Electrical Vehicle Charging. In Winter Conference on Business Intelligence (WCBI-16)
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Valogianni, K., Ketter, W., & Collins, J. (2015). A Multiagent Approach to Variable-Rate Electric Vehicle Charging Coordination. In Bordini, Elkind, Weiss, Yolum (Ed.), Proceedings of the 14th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2015) (pp. 1131-1139)
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Valogianni, K., Ketter, W., Collins, J., & Adomavicius, G. (2015). A Dynamic Pricing Mechanism to Coordinate Electric Vehicle Charging. In 2015 Winter Conference on Business Intelligence (WCBI)
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Valogianni, K., Gupta, A., Ketter, W., Sen, S., & van Heck, E. (2015). Maximizing Social Welfare in Grid Resource Allocation for Electric Vehicle Charging. In Conference on Information Systems and Technology (CIST 2015)
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Valogianni, K., Ketter, W., Collins, J., & Zhdanov, D. (2015). Sustainable Electric Vehicle Charging: A Data-driven Approach. In In 25th ICIS Workshop of Information Technologies and Systems (WITS 2015), Fort Worth, Texas
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Valogianni, K., Ketter, W., & John Collins, JC. (2015). A Hybrid Mechanism to Coordinate Electric Vehicle Charging. In AAAI Workshop on Trading Agent Design and Analysis (TADA-15)
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Valogianni, K., Gupta, A., Ketter, W., Sen, S., & van Heck, E. (2015). Maximizing Social Welfare in Grid Resource Allocation for Electric Vehicle Charging. In Workshop on Information Technology and Systems (WITS)
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Valogianni, K., Ketter, W., & Collins, J. (2014). Learning to Schedule Electric Vehicle Charging given Individual Customer Preferences. In Alessio Lomuscio, Paul Scerri, Ana Bazzan, and Michael Huhns (Ed.), Proceedings of the 13th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2014) (pp. 1591-1592). International Foundation for Autonomous Agents and Multiagent Systems.
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Valogianni, K., Ketter, W., Collins, J., & Zhdanov, D. (2014). Effective Management of Electric Vehicle Storage using Smart Charging. In Twenty-Eighth AAAI Conference on Artificial Intelligence (AAAI-14) (pp. 472-478). Association for the Advancement of Artificial Intelligence. http://hdl.handle.net/1765/51352
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Valogianni, K., Ketter, W., Collins, J., & Zhdanov, D. (2014). Enabling Sustainable Smart Homes: An Intelligent Agent Approach. In ICIS: International Conference on Information Systems Association for Information Systems (AIS).
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Valogianni, K., Ketter, W., Collins, J., & Zhdanov, D. (2014). Adaptive Learning Agents for Electric Vehicle Customer Decision Support. In Conference on Information Systems and Technology (CIST-14)
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Valogianni, K., Ketter, W., de Weerdt, M., & Collins, J. (2013). Influence of the Consumers Risk Attitude on the Introduction of Electric Vehicles. In Winter Conference on Business Intelligence
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Valogianni, K., Ketter, W., de Weerdt, M., & Collins, J. (2013). Modeling Electric Vehicle Customers and Learning a Heuristic Charging Behavior. In AAMAS - Fourth International Workshop on Agent Technologies for Energy Systems (ATES 2013) (pp. 1-8).
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Valogianni, K., Ketter, W., & Collins, J. (2013). Smart Charging of Electric Vehicles using Intelligent Software Agents. In Workshop on Information Technology and Systems (WITS)
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Valogianni, K., Ketter, W., & John Collins, JC. (2013). Smart Charging Algorithms for Electric Vehicles using Learning Mechanisms. In AAAI Workshop on Trading Agent Design and Analysis (TADA-13)
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Valogianni, K., Ketter, W., & Collins, J. (2013). Smart charging of electric vehicles using reinforcement learning. In Trading Agent Design and Analysis - Papers from the 2013 AAAI Workshop, Technical Report (pp. 41-48). AI Access Foundation.
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Valogianni, K., Ketter, W., de Weerdt, M., & Collins, J. (2012). Analysis of Smart Grid Balancing using Realistic Customer Models. In - (pp. 1-15)
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Richter, A., van der Laan, E., Ketter, W., & Valogianni, K. (2012). Transitioning from the traditional to the smart grid: Lessons learned from closed-loop supply chains. In IEEE - International Conference on Smart Grid Technology, Economics and Policies. Nuremberg, Germany
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Kahlen, M., Valogianni, K., Ketter, W., & van Dalen, J. (2012). A Profitable Business Model for Electric Vehicle Fleet Owners. In International Conference on Smart Grid Technology, Economics and Policies (SG-TEP 2012) (pp. 1-5). IEEE Xplore. https://doi.org/10.1109/SG-TEP.2012.6642395
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Valogianni, K., Ketter, W., de Weerdt, M., & Collins, J. (2012). Increasing Social Welfare and Individual Savings using Economic Incentives for Electric Vehicles. In Workshop on Information Technology and Systems (WITS-12)
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Ketter, W., Collins, J., Valogianni, K., & de Weerdt, M. (2012). Constructing and operating a large-scale simulation of retail electric power markets. In 8th Symposium on Statistical Challenges in Electronic Commerce Research (SCECR 2012)
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Doctoral Thesis (1)
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Internal (1)
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Valogianni, K. (2016). Sustainable Electric Vehicle Management using Coordinated Machine Learning. [Doctoral Thesis, Erasmus University Rotterdam]. Erasmus University Rotterdam (EUR).
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PhD Track (1)
- Role: Member Doctoral Committee
- PhD Candidate: Mohammad Ansarin
- Time frame: 2015 - 2021
Events (2)
Address
María de Molina, 11
28006 Madrid
María de Molina 11
28006 Madrid
Spain
Supervisory Team
