Grey-box modeling, as one of the three fundamental modeling techniques for building
energy models, has many advantages compared with black-box modeling and white-box …

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 …

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 …

Abstract Model Predictive Control (MPC) is a promising technique to address growing needs
for heating, ventilation, and air-conditioning (HVAC) systems to operate more efficiently and …

We present CasADi, an open-source software framework for numerical optimization. CasADi
is a general-purpose tool that can be used to model and solve optimization problems with a …

Managing supply and demand in the electricity grid is becoming more challenging due to
the increasing penetration of variable renewable energy sources. As significant end-use …

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

Abstract Model predictive control (MPC) has shown great potential in improving building
performance and saving energy. However, after over 20 years of research, it is yet to be …

Physics-based battery models are important tools in battery research, development, and
control. To obtain useful information from the models, accurate parametrization is essential …

Building and district energy systems become increasingly complex, requiring accurate
simulation and optimization of systems that combine building envelope, heating ventilation …