Volume 04: Proceedings of 11th International Conference on Applied Energy, Part 3, Sweden, 2019

Automated Parameter Identification: Robust Model Validation of a Compression Chiller Based on an Uncertainty and Consistency Analysis Oliver Doelle, Arvid Amthor, Christoph Ament

Abstract

For a wider utilization of model-based control e.g. for energy management systems, their installation and maintenance costs must be reduced. A possible solution is the automated identification of the different asset model parameters. However, robust model validation methods are necessary in order to guarantee an adequate performance in practice without additional manual review. This paper presents a model validation method for energy conversion units based on an uncertainty and consistency analysis of the extrapolated energy efficiency ratio (EER). First, the approach is described in detail. Afterwards, the advantages of the concept over validation methods based on model accuracy are illustrated with a case study of a compression chiller. Only the presented approach ensured a robust validation of the chiller models.

Keywords model predictive control, automated parameter identification, energy management system, compression chiller, confidence interval

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