New Method to Perform Data Reconciliation with OpenModelica and ThermoSysPro

Abstract

Data reconciliation aims at improving the accuracy of measurements by reducing the effect of random errors in the data. This is achieved by introducing redundancies on the measured quantities in the form of constraints based on fundamental physical laws such as mass, momentum and energy balance equations. These constraints are called the auxiliary conditions. Modelica is an equational language that was conceived to express models based on first principle physics for the purpose of behavioral simulation. This paper shows how to reuse such models for the purpose of data reconciliation. The novelty is to automatically extract the auxiliary conditions from the Modelica model. Then the reconciled values are computed using a least square method constrained by the auxiliary conditions, as specified by the VDI 2048 standard. The new method has been implemented in OpenModelica. A simple example built with ThermoSysPro illustrates the method in detail.