Forecasting spot electricity prices: Deep learning approaches and empirical comparison of traditional algorithms J Lago, F De Ridder, B De Schutter Applied Energy 221, 386–405, 2018 | 249 | 2018 |
Forecasting day-ahead electricity prices in Europe: the importance of considering market integration J Lago, F De Ridder, P Vrancx, B De Schutter Applied Energy 211, 890–903, 2018 | 123 | 2018 |
Thermal load forecasting in district heating networks using deep learning and advanced feature selection methods G Suryanarayana, J Lago, D Geysen, P Aleksiejuk, C Johansson Energy 157, 141-149, 2018 | 67 | 2018 |
Short-term forecasting of solar irradiance without local telemetry: A generalized model using satellite data J Lago, K De Brabandere, F De Ridder, B De Schutter Solar Energy 173, 566-577, 2018 | 25 | 2018 |
Fault diagnosis in low voltage smart distribution grids using gradient boosting trees N Sapountzoglou, J Lago, B Raison Electric Power Systems Research 182, 106254, 2020 | 8 | 2020 |
A 1-dimensional continuous and smooth model for thermally stratified storage tanks including mixing and buoyancy J Lago, F De Ridder, W Mazairac, B De Schutter Applied Energy 248, 640-655, 2019 | 8 | 2019 |
Building day-ahead bidding functions for seasonal storage systems: A reinforcement learning approach J Lago, E Sogancioglu, G Suryanarayana, F De Ridder, B De Schutter IFAC-PapersOnLine 52 (4), 488-493, 2019 | 5 | 2019 |
Periodic Optimal Control and Model Predictive Control of a Tethered Kite for Airborne Wind Energy J Lago University of Freiburg, 2016 | 5* | 2016 |
Forecasting day-ahead electricity prices: A review of state-of-the-art algorithms, best practices and an open-access benchmark J Lago, G Marcjasz, B De Schutter, R Weron arXiv preprint arXiv:2008.08004, 2020 | 3 | 2020 |
Effect of market design on strategic bidding behavior: Model-based analysis of European electricity balancing markets K Poplavskaya, J Lago, L de Vries Applied Energy 270, 115130, 2020 | 3 | 2020 |
Scenario-based Model Predictive Control Approach for Heating Systems in an Office Building T Pippia, J Lago, R De Coninck, J Sijs, B De Schutter 2019 IEEE 15th International Conference on Automation Science and …, 2019 | 3 | 2019 |
A probabilistic approach to allocate building parameters within district energy simulations I De Jaeger, J Lago, D Saelens Proceedings of the Urban Energy Simulation Conference 2018, 2018 | 3 | 2018 |
Optimal control strategies for seasonal thermal energy storage systems with market interaction J Lago, G Suryanarayana, E Sogancioglu, B De Schutter IEEE Transactions on Control Systems Technology, 2020 | 2 | 2020 |
Neural networks in day-ahead electricity price forecasting: Single vs. multiple outputs G Marcjasz, J Lago, R Weron arXiv preprint arXiv:2008.08006, 2020 | 2 | 2020 |
Warping model predictive control for application in control of a real airborne wind energy system J Lago, M Erhard, M Diehl Control Engineering Practice 78, 65-78, 2018 | 2 | 2018 |
Warping NMPC for Online Generation and Tracking of Optimal Trajectories J Lago, M Erhard, M Diehl IFAC-PapersOnLine 50 (1), 13252-13257, 2017 | 2 | 2017 |
A quadratically convergent primal decomposition algorithm with soft coupling for nonlinear parameter estimation D Kouzoupis, R Quirynen, JL Garcia, M Erhard, M Diehl 2016 IEEE 55th Conference on Decision and Control (CDC), 1086-1092, 2016 | 2 | 2016 |
A probabilistic building characterization method for district energy simulations I De Jaeger, J Lago, D Saelens Energy and Buildings 230, 110566, 2021 | 1 | 2021 |
A generalizable and sensor-independent deep learning method for fault detection and location in low-voltage distribution grids N Sapountzoglou, J Lago, B De Schutter, B Raison Applied Energy 276, 115299, 2020 | 1 | 2020 |
Scenario-based Nonlinear Model Predictive Control for Building Heating Systems T Pippia, J Lago, R De Coninck, B De Schutter arXiv preprint arXiv:2012.02011, 2020 | | 2020 |