| 1 |
Unsupervised energy prediction in a Smart Grid context using reinforcement cross-building transfer learning
Mocanu E, Nguyen PH, Kling WL, Gibescu M
Energy and Buildings, 116, 646, 2016 |
| 2 |
Pseudo dynamic transitional modeling of building heating energy demand using artificial neural network
Paudel S, Elmtiri M, Kling WL, Le Corre O, Lacarriere B
Energy and Buildings, 70, 81, 2014 |
| 3 |
Future residential load profiles: Scenario-based analysis of high penetration of heavy loads and distributed generation
Asare-Bediako B, Kling WL, Ribeiro PF
Energy and Buildings, 75, 228, 2014 |
| 4 |
Scenario-based modelling of future residential electricity demands and assessing their impact on distribution grids
Veldman E, Gibescu M, Slootweg H, Kling WL
Energy Policy, 56, 233, 2013 |
| 5 |
HVDC connection of offshore wind farms to the transmission system
Bresesti P, Kling WL, Hendriks RL, Vailati R
IEEE Transactions on Energy Conversion, 22(1), 37, 2007 |
| 6 |
Impacts of wind power on thermal generation unit commitment and dispatch
Ummels BC, Gibescu M, Pelgrum E, Kling WL, Brand AJ
IEEE Transactions on Energy Conversion, 22(1), 44, 2007 |
| 7 |
Representing wind turbine electrical generating systems in fundamental frequency simulations
Slootweg JG, Polinder H, Kling WL
IEEE Transactions on Energy Conversion, 18(4), 516, 2003 |
