It has been proven that advanced building control, like model predictive control (MPC), can
notably reduce the energy use and mitigate greenhouse gas emissions. However, despite …

Seasonal thermal energy storage can provide flexibility to smart energy systems and are
characterised by low cost per unit energy capacity and varying applicability to different …

Buildings need advanced control for the efficient and climate-neutral use of their energy
systems. Model predictive control (MPC) and reinforcement learning (RL) arise as two …

Climate change, increasing emissions and rising global temperatures have gradually
affected the way we think about the future of our planet. Urban areas possess significant …

Development of new building HVAC control algorithms has grown due to needs for energy
efficiency and operational flexibility. However, case studies demonstrating new algorithms …

In this study, the techno-economic performance of an integrated energy system, which
consisted of a biogas-fueled micro gas turbine, seasonal thermal energy storage using a …

We present a physics-constrained deep learning method to develop control-oriented models
of building thermal dynamics. The proposed method uses systematic encoding of physics …

District heating (DH) systems have been identified as an important component in efforts to
mitigate greenhouse gas emissions and achieve climate targets in the near future. Software …

Data centres produce waste heat, which can be utilized in district heating systems. However,
the mismatch between data centres' heat supply and district heating systems' heat demands …

The characteristic that describes the extent to which buildings and their systems maintain
their performance during shocks is called resilience. Building policies in the EU have …