Jesus Lago
Title
Cited by
Cited by
Year
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
3192018
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
1502018
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
822018
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
312018
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
Applied Energy 293, 116983, 2021
162021
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
162020
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
152019
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
132020
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
102020
A market framework for grid balancing support through imbalances trading
J Lago, K Poplavskaya, G Suryanarayana, B De Schutter
Renewable and Sustainable Energy Reviews, 110467, 2020
52020
Periodic Optimal Control and Model Predictive Control of a Tethered Kite for Airborne Wind Energy
J Lago
University of Freiburg, 2016
5*2016
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
42019
Scenario-based nonlinear model predictive control for building heating systems
T Pippia, J Lago, R De Coninck, B De Schutter
Energy and Buildings 247, 111108, 2021
32021
Neural networks in day-ahead electricity price forecasting: Single vs. multiple outputs
G Marcjasz, J Lago, R Weron
arXiv preprint arXiv:2008.08006, 2020
32020
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
32019
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
32018
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
32018
A probabilistic building characterization method for district energy simulations
I De Jaeger, J Lago, D Saelens
Energy and Buildings 230, 110566, 2021
22021
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
22020
Warping NMPC for Online Generation and Tracking of Optimal Trajectories
J Lago, M Erhard, M Diehl
IFAC-PapersOnLine 50 (1), 13252-13257, 2017
22017
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