A high-fidelity, spatially distributed dynamic model
of a supercritical
pulverized coal-fired boiler was developed for calculating transient
thermal profiles of the boiler tubes, which are often not measured
or unmeasurable in industrial settings due to the harsh operating
conditions. Rigorous models of the subcritical and supercritical steam
properties, which can be highly nonlinear, were used to capture the
transition between two-phase and one-phase flow, respectively, as
supercritical boilers frequently transition through the critical point
during load-following operation. The transient boiler model was also
used for data reconciliation and parameter estimation for the purpose
of model validation against industrial data. An approach was developed
to reduce the size of the large-scale reconciliation problem by focusing
on the implementation of bias terms for the reconciled variables,
which can be estimated in place of the reconciled variables themselves.
In addition, a functional approximation of the reconciliation problem
was defined so that it can be more simply optimized. Combining this
functional approximation optimization with reformulation of the reconciliation
problem considering measurement biases can significantly improve the
tractability of many such large-scale problems. The validated boiler
model was then used to study transient responses under load-following
operation with specific attention on the calculation of unmeasurable
variables.