Energy Information Networks & Systems lab
Low-carbon energy systems that are technically reliable, economically sensible, and secure against intentional cyber attacks will be critical for our future.
Germany
Pinned Repositories
CESM
Compact Energy System Modeling Tool
CompetitiveLEM
Game-theoretic analysis of suppliers’ pricing power in thermal-electric local energy markets
DNN_MCMC4DH
Deep Learning-enabled MCMC for Probabilistic State Estimation in District Heating Grids
DNN_SOC4DHS
Code basis for the paper Stochastic Optimal Control for Nonlinear Systems based on Sampling & Deep Learning by A. Bott, K.. Kuroptev and F. Steinke
LBM4DH
This Repo contains the code base for the paper "Efficient Training of Learning-Based Thermal Power Flow for 4th Generation District Heating Grids" by Andreas Bott, Mario Beykirch, and Florian Steinke
PSCC2024-SwitchSelection
A tool that solves a variation of the SwitchSelection problem for MV distribution grids. This repository accompanies our contribution to PSCC 2024.
Energy Information Networks & Systems lab's Repositories
EINS-TUDa/DNN_MCMC4DH
Deep Learning-enabled MCMC for Probabilistic State Estimation in District Heating Grids
EINS-TUDa/CESM
Compact Energy System Modeling Tool
EINS-TUDa/DNN_SOC4DHS
Code basis for the paper Stochastic Optimal Control for Nonlinear Systems based on Sampling & Deep Learning by A. Bott, K.. Kuroptev and F. Steinke
EINS-TUDa/CompetitiveLEM
Game-theoretic analysis of suppliers’ pricing power in thermal-electric local energy markets
EINS-TUDa/LBM4DH
This Repo contains the code base for the paper "Efficient Training of Learning-Based Thermal Power Flow for 4th Generation District Heating Grids" by Andreas Bott, Mario Beykirch, and Florian Steinke
EINS-TUDa/PSCC2024-SwitchSelection
A tool that solves a variation of the SwitchSelection problem for MV distribution grids. This repository accompanies our contribution to PSCC 2024.