2 citations · 4 across the 3 of their papers we have counts for
3 papers
A Deep Learning Framework for Heat Demand Forecasting using Time-Frequency Representations of Decomposed Features
Adithya Ramachandran, Satyaki Chatterjee, Thorkil Flensmark B. Neergaard +3
District Heating Systems are essential infrastructure for delivering heat to consumers across a geographic region sustainably, yet efficient management relies on optimizing diverse…
Heat Demand Forecasting with Multi-Resolutional Representation of Heterogeneous Temporal Ensemble
Adithya Ramachandran, Satyaki Chatterjee, Siming Bayer +2
One of the primal challenges faced by utility companies is ensuring efficient supply with minimal greenhouse gas emissions. The advent of smart meters and smart grids provide an un…
Prediction of Household-level Heat-Consumption using PSO enhanced SVR Model
Satyaki Chatterjee, Siming Bayer, Andreas Maier
In combating climate change, an effective demand-based energy supply operation of the district energy system (DES) for heating or cooling is indispensable. As a consequence, an acc…