Unlocking zero-cost flexibility in office buildings with adaptive comfort heating strategy and thermal mass utilization
Abstract
The growing share of renewable energy introduces significant variability and uncertainty in the electricity grid, increasing the need for demand-side flexibility. Buildings with controllable assets represent a promising source of flexibility. This study explores adaptive comfort heating strategies to unlock cost-free flexibility in the thermal mass of office buildings while maintaining comfort. A twofold methodology is proposed: a measurement study assessing the impact of adaptive setpoint adjustments on thermal comfort, and a simulation-based framework quantifying flexibility under diverse design and control strategies. The framework couples building simulations with a penalty-aware controller to optimize battery and heat pump operation in response to dynamic electricity prices or CO 2 intensity using mixed-integer linear programming. Applying the methodology to a 2511 m 2 Dutch office building shows that thermal mass delivers load shifting comparable to that of a 200 kWh battery. Analysis of eight variations of the case study, differing in layout, insulation, and window-to-wall ratio, further confirms these findings. Thermal mass provides 17.2 to 19.7 Wh/m2 of daily average shiftable load depending on comfort constraints, while the battery contributes 19.4 to 23.3 Wh/m2 under price-based and 10.7 to 16.1 Wh/m2 under CO 2 -based optimization. The battery’s high investment and embodied CO 2 limit its economic and environmental benefits compared to rooftop PV and cost-free thermal mass. Results also highlight the strong influence of window-to-wall ratio and office layout on potential shiftable electricity. Overall, adaptive comfort control strategies enable office buildings to provide cost-free flexibility that, when aggregated, can support renewable integration, balancing services, and grid resilience.
Fields of Study & Subjects
Smart Grid Energy Management
Building Energy and Comfort Optimization
Integrated Energy Systems Optimization
Publication details
- Journal / source
- Energy and Buildings
- Publisher
- Elsevier BV
- Volume
- 357
- Pages
- 117126–117126
- Publication date
- 11 February 2026
- Language
- EN