no code implementations • 29 Oct 2023 • Gargya Gokhale, Niels Tiben, Marie-Sophie Verwee, Manu Lahariya, Bert Claessens, Chris Develder
Given its substantial contribution of 40\% to global power consumption, the built environment has received increasing attention to serve as a source of flexibility to assist the modern power grid.
no code implementations • 14 Nov 2022 • Ioanna Bouri, Manu Lahariya, Omer Nivron, Enrique Portales Julia, Dietmar Backes, Piotr Bilinski, Guy Schumann
Here, we offer the first global river flood prediction framework based on the newly published Caravan dataset.
no code implementations • 19 May 2022 • Manu Lahariya, Farzaneh Karami, Chris Develder, Guillaume Crevecoeur
These physics informed networks approximate the time-dependent relationship between control input and system response while enforcing the dynamics of the process in the neural network architecture.
no code implementations • 26 Mar 2022 • Manu Lahariya, Nasrin Sadeghianpourhamami, Chris Develder
A major challenge in todays power grid is to manage the increasing load from electric vehicle (EV) charging.
no code implementations • 3 Mar 2022 • Manu Lahariya, Nasrin Sadeghianpourhamami, Chris Develder
However, we note that the computationally expensive cost function adopted in the previous research leads to large training times, which limits the feasibility and practicality of the approach.
1 code implementation • 28 Feb 2022 • Manu Lahariya, Dries Benoit, Chris Develder
Addressing this need for publicly available and realistic data, we develop a synthetic data generator (SDG) for EV charging sessions.
no code implementations • 25 Feb 2022 • Manu Lahariya, Craig Innes, Chris Develder, Subramanian Ramamoorthy
We simulate the task of using DEA to pull a coin along a surface with frictional contact, using FEM, and evaluate the physics-informed model for simulation, control, and inference.