Data Reconciliation Analysis
Data Reconciliation is a mathematical model used to obtain a balance in the
processes handling continuous materials flows (e.g. energy production,
energy distribution, water treatments and chemical plants).
When measured data do not satisfy the balance equations – because of
measurements errors – it is possible to adjust the measured data to obey
the balance constraints. The adjustment of measured values through
methods, using statistical theory of errors, is called reconciliation.
The optimization model will be obtained by modelling the process in order to faithfully represent the mass and energy balance and the losses that we are interested to highlight.
The model will be entirely implemented on PI AF environment and it will benefit of standard AVEVA\OSIsoft functions.
The approach is to derive information from sensor data, by using a proprietary library performing non-linear data reconciliation and integrating thermodynamics computation