Theoretical basis for empirical model validation using parameters space analysis tools

A new methodology for empirical model validation has been proposed in the framework of the Task 22 (Building Energy Analysis Tools) of the International Energy Agency. It involves two main steps: checking model validity and diagnosis. First step aims to test the model performances by identification of significant disagreements between measurements and simulations. It rests on both residuals analysis techniques and comparisons between model outputs uncertainty bands and measurements uncertainty intervals. Second step intends to explain the differences observed between model simulations and measurements. A new approach for models diagnosis has been proposed. It rests on the analysis of the model parameters space. The main objective is to identify the changes in parameters values that are required for a significant model behaviour improvement. Diagnosis is then provided by comparison of such results with the knowledge we have about both the actual system and the model itself. Main mathematical tools for diagnosis are sensitivity analysis and optimisation techniques. The methodology and the underlying methods we are proposing are presented in the first part of the paper. In the second part, they are applied for testing modelling hypothesis in the framework of the thermal analysis of an actual building.