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Emma Tegling
Researcher at Royal Institute of Technology
Publications - 33
Citations - 423
Emma Tegling is an academic researcher from Royal Institute of Technology. The author has contributed to research in topics: Control theory & Voltage droop. The author has an hindex of 10, co-authored 26 publications receiving 339 citations. Previous affiliations of Emma Tegling include Johns Hopkins University & Massachusetts Institute of Technology.
Papers
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Journal ArticleDOI
The Price of Synchrony: Evaluating the Resistive Losses in Synchronizing Power Networks
TL;DR: The resistive power losses that are incurred in keeping a network of synchronous generators in a synchronous state are investigated and it is shown that the price of synchrony is more dependent on a network's size than its topology.
Proceedings ArticleDOI
Coherence in synchronizing power networks with distributed integral control
TL;DR: In this paper, the authors consider frequency control of synchronous generator networks and study transient performance under both primary and secondary frequency control under random step changes in power loads and evaluate performance in terms of expected deviations from a synchronous frequency over the synchronization transient; what can be thought of as lack of frequency coherence.
Proceedings ArticleDOI
Improving performance of droop-controlled microgrids through distributed PI-control
TL;DR: This paper investigates transient performance of inverter-based microgrids in terms of the resistive power losses incurred in regulating frequency under persistent stochastic disturbances and shows that the distributed PI-controller has the potential to significantly improve performance by reducing transient power losses.
Journal ArticleDOI
On the Coherence of Large-Scale Networks With Distributed PI and PD Control
Emma Tegling,Henrik Sandberg +1 more
TL;DR: This work addresses known performance limitations of the standard consensus protocol and proposes distributed proportional integral and proportional derivative controllers that relax these limitations and achieve bounded variance, in cases where agents can access an absolute measurement of one of their states.
Journal ArticleDOI
On Fundamental Limitations of Dynamic Feedback Control in Regular Large-Scale Networks
TL;DR: This paper addresses the question of whether dynamic feedback controllers perform better than static (memoryless) ones when subject to locality constraints, and presents a general technical framework for the analysis of stability and performance of spatially invariant systems in the limit of large networks.