Steady-state data reconciliation for absorption refrigeration systems

Abstract

In this paper data reconciliation is applied to the steady-state operational data of a single-effect ammonia/water absorption chiller. The methodology includes the detection of steady-state, the application of systematic degrees of freedom analysis (in order to determine a suitable set of measured input variables for the absorption chiller model), and data reconciliation of the measurements (which included the treatment of gross errors). The reconciliation problem was solved using a two stage sequential approach in which the objective function is minimized in Matlab and the absorption chiller is simulated in the Engineering Equation Solver (EES). The Modified Iterative Measurement Test was used to detect the measurements that contain gross errors. This methodology makes it possible to identify and eliminate the sources of gross errors, and to obtain performance calculations that are in agreement with the laws of conservation.