Data Reconciliation for power systems monitoring: Application to a microturbine-based test rig

In this study the techniques of Data Reconciliation and Gross Error Detection have been applied to a microturbine-based test rig installed at the Thermochemical Power Group (TPG) laboratory of the University of Genoa, Italy. These techniques have been developed in the field of chemical engineering during the past 55 years with the purpose of reducing the effect of random errors and also eliminating systematic gross errors in the data by exploiting the relationships that are known to exist between different variables of a process (e.g. energy and mass balances). Two different applications of Data Reconciliation have been carried out: first the entire test rig was studied, generating a set of measurements affected just by random error; second, only the recuperator was taken into account using real measurements coming from a steady state test performed on the plant. The purpose of the former is to show the capability of Data Reconciliation in the adjustment of the measurements so that they can respect the constraints (balance equations). This application is somehow an "ideal application" of Data Reconciliation. Latter since gross errors are often present in the measurements coming from a real plant, a "real or experimental application" of Data Reconciliation was considered for a subsystem of the plant in which the actual measurements from plant probes were used. The objective was to understand if the measured values of temperature, pressure and mass flow rate at the inlet and outlet of the recuperator were physically compatible and reliable. Measured value affected by gross error was identified, focusing on its effect over all the other measurements during DR calculation. (C) 2013 Elsevier Ltd. All rights reserved.