S
Stefanos Delikaraoglou
Researcher at Massachusetts Institute of Technology
Publications - 34
Citations - 442
Stefanos Delikaraoglou is an academic researcher from Massachusetts Institute of Technology. The author has contributed to research in topics: Electric power system & Flexibility (engineering). The author has an hindex of 10, co-authored 30 publications receiving 244 citations. Previous affiliations of Stefanos Delikaraoglou include Technical University of Denmark & École Polytechnique Fédérale de Lausanne.
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Journal ArticleDOI
Stochastic Unit Commitment in Low-Inertia Grids
Matthieu Paturet,Uros Markovic,Stefanos Delikaraoglou,Evangelos Vrettos,Petros Aristidou,Gabriela Hug +5 more
TL;DR: In this paper, the authors studied the unit commitment problem in a power network with low levels of rotational inertia and derived frequency-related constraints from a uniform system frequency response model that incorporates dynamics and controls of both synchronous generators and grid-forming inverters.
Posted Content
Stochastic Unit Commitment in Low-Inertia Grids
Matthieu Paturet,Uros Markovic,Stefanos Delikaraoglou,Evangelos Vrettos,Petros Aristidou,Gabriela Hug +5 more
TL;DR: A computationally efficient approach is proposed that allows to recast the nadir constraint by introducing appropriate bounds on relevant decision variables of the UC model to preserve the mixed-integer linear formulation of the stochastic UC model.
Proceedings ArticleDOI
On quantification of flexibility in power systems
TL;DR: In this article, the authors defined the locational flexibility and a unified framework to compare it against forecast uncertainty is introduced, where both metrics are expressed in terms of ramping rate, power and energy and consider the network constraints.
Journal ArticleDOI
Setting Reserve Requirements to Approximate the Efficiency of the Stochastic Dispatch
TL;DR: A new method to compute reserve requirements that bring the outcome of sequential markets closer to the stochastic energy and reserves co-optimization in terms of cost efficiency is proposed.
Journal ArticleDOI
Chance-constrained optimal power flow with non-parametric probability distributions of dynamic line ratings
TL;DR: A DC-Optimal Power Flow (DCOPF) algorithm is proposed that accounts for DLR uncertainty by means of Chance-Constraints to determine the optimal day-ahead dispatch taking the cost of reserve procurement into account.