93 citations · 110 across the 7 of their papers we have counts for
8 papers
A General Stochastic Optimization Framework for Convergence Bidding
Letif Mones, Sean Lovett
Convergence (virtual) bidding is an important part of two-settlement electric power markets as it can effectively reduce discrepancies between the day-ahead and real-time markets.…
Leveraging power grid topology in machine learning assisted optimal power flow
Thomas Falconer, Letif Mones
Machine learning assisted optimal power flow (OPF) aims to reduce the computational complexity of these non-linear and non-convex constrained optimization problems by consigning ex…
Deep learning architectures for inference of AC-OPF solutions
Thomas Falconer, Letif Mones
We present a systematic comparison between neural network (NN) architectures for inference of AC-OPF solutions. Using fully connected NNs as a baseline we demonstrate the efficacy…
Learning an Optimally Reduced Formulation of OPF through Meta-optimization
Alex Robson, Mahdi Jamei, Cozmin Ududec +1
With increasing share of renewables in power generation mix, system operators would need to run Optimal Power Flow (OPF) problems closer to real-time to better manage uncertainty.…
Preconditioners for the geometry optimisation and saddle point search of molecular systems
Letif Mones, Gabor Csanyi, Christoph Ortner
A class of preconditioners is introduced to enhance geometry optimisation and transition state search of molecular systems. We start from the Hessian of molecular mechanical terms,…
Some Remarks on Preconditioning Molecular Dynamics
Houssam AlRachid, Letif Mones, Christoph Ortner
We consider a Preconditioned Overdamped Langevin algorithm that does not alter the invariant distribution (up to controllable discretisation errors) and ask whether preconditioning…