Glenn Reynders
Glenn Reynders
Vito | EnergyVille üzerinde doğrulanmış e-posta adresine sahip
Alıntı yapanlar
Alıntı yapanlar
IEA EBC annex 67 energy flexible buildings
SØ Jensen, A Marszal-Pomianowska, R Lollini, W Pasut, A Knotzer, ...
Energy and Buildings 155, 25-34, 2017
Potential of structural thermal mass for demand-side management in dwellings
G Reynders, T Nuytten, D Saelens
Building and Environment 64, 187-199, 2013
Characterizing the energy flexibility of buildings and districts
RG Junker, AG Azar, RA Lopes, KB Lindberg, G Reynders, R Relan, ...
Applied energy 225, 175-182, 2018
Quality of grey-box models and identified parameters as function of the accuracy of input and observation signals
G Reynders, J Diriken, D Saelens
Energy and Buildings 82, 263-274, 2014
Generic characterization method for energy flexibility: Applied to structural thermal storage in residential buildings
G Reynders, J Diriken, D Saelens
Applied energy 198, 192-202, 2017
Energy flexible buildings: An evaluation of definitions and quantification methodologies applied to thermal storage
G Reynders, RA Lopes, A Marszal-Pomianowska, D Aelenei, J Martins, ...
Energy and Buildings 166, 372-390, 2018
Implementation and verification of the IDEAS building energy simulation library
F Jorissen, G Reynders, R Baetens, D Picard, D Saelens, L Helsen
Journal of Building Performance Simulation 11 (6), 669-688, 2018
CO2-abatement cost of residential heat pumps with active demand response: demand-and supply-side effects
D Patteeuw, G Reynders, K Bruninx, C Protopapadaki, E Delarue, ...
Applied Energy 156, 490-501, 2015
Quantifying the impact of building design on the potential of structural storage for active demand response in residential buildings
G Reynders
Bottom-up modelling of the Belgian residential building stock: impact of building stock descriptions
C Protopapadaki, G Reynders, D Saelens
Proceedings of the 9th International Conference on System Simulation in …, 2014
A generic quantification method for the active demand response potential of structural storage in buildings
G Reynders, J Diriken, D Saelens
14th International Conference of IBPSA-Building Simulation 2015, BS 2015 …, 2015
Thermal performance characterization using time series data-IEA EBC Annex 58 Guidelines
H Madsen, P Bacher, G Bauwens, AH Deconinck, G Reynders, S Roels, ...
Technical University of Denmark, 2015
Impact of building geometry description within district energy simulations
I De Jaeger, G Reynders, Y Ma, D Saelens
Energy 158, 1060-1069, 2018
Impact of spatial accuracy on district energy simulations
I De Jaeger, G Reynders, D Saelens
Energy Procedia 132, 561-566, 2017
58, Reliable Building Energy Performance Characterisation Based on Full Scale Dynamic Measurements
I Annex
InWorkshop in Preparation of New IEA EBC Annex Project—Brussels April, 19, 2016
Bottom-up modeling of the Belgian residential building stock: influence of model complexity
G Reynders, J Diriken, D Saelens
SSB 2014, 1-19, 2014
Towards the characterization of the heat loss coefficient via on-board monitoring: Physical interpretation of ARX model coefficients
M Senave, G Reynders, P Bacher, S Roels, S Verbeke, D Saelens
Energy and Buildings 195, 180-194, 2019
Sources of energy flexibility in district heating networks: building thermal inertia versus thermal energy storage in the network pipes
A Vandermeulen, G Reynders, B van der Heijde, D Vanhoudt, ...
Proceedings of the Urban Energy Simulation Conference 2018, 1-9, 2018
A simulation exercise to improve building energy performance characterization via on-board monitoring
M Senave, G Reynders, S Verbeke, D Saelens
Energy Procedia 132, 969-974, 2017
Assessment of data analysis methods to identify the heat loss coefficient from on-board monitoring data
M Senave, S Roels, G Reynders, S Verbeke, D Saelens
Energy and Buildings 209, 109706, 2020
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Makaleler 1–20