DTU Compute
Richard Petersens Plads DTU - Building 324 DK-2800 Kgs. Lyngby

Dynamic Calculation Methods For Building Energy Assessment - Programme

The summer school is from 9AM to 5PM every day.

A more detailed programme will follow later.

  1. Preparation exercise for participants.
    Some homework will be given to the participants in order to a get a minimum homogeneous starting level with the objective of optimising the usefulness of lectures. As homework some reading material will be recommended. Participants will be asked to solve as preparation exercise and report step by step, the analysis and validation carried out as clear and illustrative as possible. The report will be submitted to the organisers.
  2. Building Physics and hints on experimental setup.
    This lecture will provide the necessary background information on building physics to support the development of mathematical models for energy performance assessment. This includes basic knowledge of thermo dynamic processes, in particular heat transfer and the impact of solar radiation. Topics like thermal conduction, convection and radiation will be presented as well as thermal mass. Using data-series for analysis the students will be introduced to the complexity of the physical process and how to translate the available information in mathematical models, e.g. the importance of model simplification of building physics represented by measured signals. Also the issue of standardisation will be presented, e.g. laboratory testing of building products and in-situ measurements for building energy performance assessment.
  3. Models and model building
    Linear input-output models.
    Topics such as, identification, formulation, estimation, and validation are presented. Furthermore, impulse response models, transfer function models, frequency domain models, ARMAX and Box-Jenkins models and how to use these techniques to estimate values like the UA-value, gA-value and time constants of a building or a component. Software tools.
    State-space models. Topics such as, identification, formulation, estimation, validation and Kalman Filter techniques are presented. In addition, lumped parameter models, RC-models, Grey-box models, and combining information from data with prior information from physics. How to use these techniques to estimate detailed physical quantities like the heat capacitance, window areas, solar aperture, effect from wind speed, nonlinear heat transfer, non-stationary heat transfer.
    Simulation, Prediction and Control. A short introduction to the use of the previously considered models for those purposes. The difference between simulation and prediction will be discussed as well as uncertainty in simulations and predictions. As an example the optimal control of heat pumps will be presented.
  4. How to obtain results using different models and methods.
    The presented analysis and validation approaches will be step by step illustrated using a very simple and well documented case study.
    The U value of a well-known quite simple opaque wall will be estimated using different analysis approaches. The simplicity of this component allows the application of a wide variety of analysis approaches with different degree of complexity, capabilities and accuracy. This simplicity also allows isolate and highlight the effects of the different analysed aspects, from the effects of other assumptions about the test component and its boundaries that could be necessary if more complex case study were considered.
    The different approaches will be presented "bottom to top", starting from the simples and, gradually increasing complexity highlighting and discussing the main features added by each level by the corresponding modelling approach. The following approaches will be considered: average and pseudo-dynamic methods, transfer function models (using the statistical software R) and continuous-time state space models (using CTSM-R).

For PhD students
In order to receive 2.5 ECTS points on PhD level, the students must:

  1. Hand in the solution to a preparing exercise before the Summer School starts. This exercise will be theoretical and will use simulated data
  2. Follow the Summer School.
  3. Hand in reports on the exercises during the Summer School (appropriate time with assistance is reserved for carrying out the exercises).

Additional 2.5 ECTS points can be achieved by carrying out and reporting a proposed exercise or an individual project (related to the students own PhD project) after attending the summer school.