Buildings are responsible for about 40 % of the energy consumption and CO2 emissions. The course develops computational skills in Python for modelling and problem solving of coupled heat transfer with special applications to optimize energy consumption for indoor climate control.
Face to face
Lecture module 1
· thermal transfer: conduction, convection, and radiation
Lecture module 2
· continuous and discrete models
· thermal networks
· transforming the thermal networks into state-space and transfer functions
· coupling the models
Tutorial 1: Read weather data and calculate solar radiation:
1) introduction to linear algebra and tools (Python, Numpy, Matplotlib);
2) use Pyhton for reading (weather) data
3) calculating the solar load
Tutorial 2: Simple wall
1) physical analysis and mathematical models
2) discretization of mathematical models
3) numerical stability
4) implementation
Tutorial 3: Simple building in free-running: controlled natural ventilation
1) physical analysis and mathematical models
2) discussion of examples
3) implementation
Tutorial 4: Simple building controlled by an HVAC system
1) physical analysis and mathematical models
2) discussion of examples
3) implementation
Accompanied individual mini-project:
Intelligent control of a single zone building
Autonomous group project:
Students define their own subject on indoor climate control, for example:
- dynamic insulation,
- dynamic solar protection,
- control of floor-heating and fan coils,
- influence of set-point setback,
- control of intermittently heated buildings,
- model predictive control.
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