Jesus Lago
Jesus Lago
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Zitiert von
Zitiert von
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
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
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
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
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
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
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
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
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
Electricity Price Forecasting: The Dawn of Machine Learning
A Jędrzejewski, J Lago, G Marcjasz, R Weron
IEEE Power and Energy Magazine 20 (3), 24-31, 2022
Making the most of short-term flexibility in the balancing market: Opportunities and challenges of voluntary bids in the new balancing market design
K Poplavskaya, J Lago, S Strömer, L de Vries
Energy Policy 158, 112522, 2021
A probabilistic building characterization method for district energy simulations
I De Jaeger, J Lago, D Saelens
Energy and Buildings 230, 110566, 2021
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
Electricity price forecasting in European Day Ahead Markets: a greedy consideration of market integration
T Van Der Heijden, J Lago, P Palensky, E Abraham
IEEE Access 9, 119954-119966, 2021
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 29 (5), 1891-1906, 2020
A data driven method for optimal sensor placement in multi-zone buildings
G Suryanarayana, J Arroyo, L Helsen, J Lago
Energy and Buildings 243, 110956, 2021
Neural networks in day-ahead electricity price forecasting: Single vs. multiple outputs
G Marcjasz, J Lago, R Weron
arXiv preprint arXiv:2008.08006, 2020
A market framework for grid balancing support through imbalances trading
J Lago, K Poplavskaya, G Suryanarayana, B De Schutter
Renewable and Sustainable Energy Reviews 137, 110467, 2021
Efficient temperature estimation for thermally stratified storage tanks with buoyancy and mixing effects
A Soares, J Camargo, J Al-Koussa, J Diriken, J Van Bael, J Lago
Journal of Energy Storage 50, 104488, 2022
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
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