Person: Valogianni, Konstantina
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Konstantina
Last Name
Valogianni
Affiliation
IE University
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IE Business School
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Information Systems and Technology
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Publication Multiple Vickrey Auctions for Sustainable Electric Vehicle Charging(International Conference on Information Systems (ICIS), 2019-12) Valogianni, Konstantina; Gupta, Alok; Ketter, Wolfgang; Sen, Soumya; Heck, Eric van; https://ror.org/02jjdwm75Electric vehicles (EVs) are important contributors to a sustainable future. However, uncontrolled EV charging in the smart grid is expected to stress its infrastructure, as it needs to accommodate extra electricity demand coming from EV charging. We propose an auction mechanism to optimally schedule EV charging in a sustainable manner so that the grid is not overloaded. Our solution has lower computational complexity, compared to state-of-the-art mechanisms, making it easily applicable to practice. Our mechanism creates electricity peak demand reduction, which is important for improving sustainability in the grid, and provides optimized charging speed design recommendations so that raw materials are not excessively used. We prove the optimal conditions that must hold, so that different stakeholder objectives are satisfied. We validate our mechanism on real-world data and examine how different trade-offs affect social welfare and revenues, providing a holistic view to grid stakeholders that need to satisfy potentially conflicting objectives.Publication Facilitating a Sustainable Electric Vehicle Transition through Consumer Utility Driven Pricing(International Conference on Information Systems (ICIS), 2018-12) Valogianni, Konstantina; Ketter, Wolfgang; Zhdanov, Dmitry; Collins, John; https://ror.org/02jjdwm75A transition to an electrified transportation system is widely assumed to be an important step along the road to environmental sustainability. However, large penetrations of electric vehicles (EVs) may put electricity grids under critical strain, since peaks in electricity demand are likely to increase radically. Efforts to manage demand peaks through pricing schemes may create new peaks at low-price periods, if large numbers of EV owners try to benefit from low prices. We propose a pricing method, called consumer utility driven pricing, which learns from EV owners’ reactions to sub-optimal prices and adjusts announced prices accordingly. We evaluate our results in simulations, where we find that consumer utility driven pricing outperforms current electricity pricing schemes. We test our method in matching both flat and extremely volatile demand profiles and we see that in both cases it performs closely to what it is theoretically possible under perfect information.Publication Heterogeneous Electric Vehicle Charging Coordination: A Variable Charging Speed Approach(2019-01-08) Valogianni, Konstantina; Ketter, Wolfgang ; Collins, John; Adomavicius, Gediminas; https://ror.org/02jjdwm75We present a coordination mechanism that reduces peak demand coming from EV charging, supports grid stability and environmental sustainability. The proposed mechanism accounts for individual commuting preferences, as well as desired states of charge by certain deadlines, which can serve as a proxy for range anxiety. It can shape EV charging toward a desired profile, without violating individual preferences. Our mechanism mitigates herding, which is typical in populations where all agents receive the same price signals and make similar charging decisions. Furthermore, it assumes no prior knowledge about EV customers and therefore learns preferences and reactions to prices dynamically. We show through simulations that our mechanism induces a less volatile demand and lower peaks compared to currently used benchmarks.