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This study identifies key building characteristics influencing energy flexibility using thermal mass as energy storage. By implementing the elementary effects test and variance-based sensitivity analysis, combined with building stock modelling and artificial neural networks, it is revealed that parameter importance is influenced by the chosen key performance indicator, building type, and interaction effects. For the available thermal storage capacity, the most critical factors are gross building volume, setpoint modulation, building construction, thermal transmittance of the wall, and heat emission system, with first-order indices of 0.22, 0.12, 0.11, 0.07 and 0.05 and total effect indices (including interaction effects with other parameters) of 0.34, 0.20, 0.29, 0.14 and 0.19 respectively. For the flexibility index (an indicator describing a building’s ability to shift energy), key parameters include the energy flexibility threshold, energy flexibility signal, heat emission system, building construction, and setpoint modulation, with first-order indices of 0.24, 0.13, 0.09, 0.04 and 0.04 and total effect indices of 0.51, 0.41, 0.26, 0.15 and 0.09 respectively. Analyzing parameters independently without considering interaction effects (i.e. higher-order effects) may lead to incorrect conclusions. The findings also highlight significant differences when considering subgroups of buildings, with geometry being more crucial for multi-family houses and building construction and heat emission system being more important for older and smaller buildings. This study offers valuable insights for designing energy-flexible buildings and developing demand response strategies, while also estimating the storage potential of thermal mass in buildings, aiding the transition to sustainable energy systems.
Heidenthaler et al. (Sun,) studied this question.
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