Micha Kahlen

dblp:147/4774 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2015
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 first-authorGraphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Multi-agent systems · 100%
Interdisciplinary, comprehensive, and emerging computing
1 paper
Energy systems and smart grids · 100%

Topics — the 1 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Knowledge, reasoning and agents › Multi-agent systems › multi-robot coordination
market-based coordination
0.212015
Aggregating Electric Cars to Sustainable Virtual Power Plants: The Value of Flexibility in Future Electricity Markets · AAAI 2015

Methods — techniques the papers use, named apart from their topics

optimization · 0.4heuristic algorithm · 0.4
YearPublicationVenuePosition
2015 Aggregating Electric Cars to Sustainable Virtual Power Plants: The Value of Flexibility in Future Electricity Markets
abstract
Electric vehicles will play a crucial role in balancing the future electrical grid, which is complicated by many intermittent renewable energy sources. We developed an algorithm that determines for a fleet of electric vehicles, which EV at what price and location to commit to the operating reserve market to either absorb excess capacity or provide electricity during shortages (vehicle-2-grid). The algorithm takes the value of immobility into account by using carsharing fees as a reference point. A virtual power plant autonomously replaces cars that are committed to the operating reserves and are then rented out, with other idle cars to pool the risks of uncertainty. We validate our model with data from a free float carsharing fleet of 500 electric vehicles. An analysis of expected future developments (2015, 2018, and 2022) in operating reserve demand and battery costs yields that the gross profits for a carsharing operator increase between 7-12% with a negligible decrease in car availability (<0.01%).
Micha Kahlen, Wolfgang Ketter
AAAI1