Continuous improvement in emission reductions requires evaluating contributions from every
source. One contributor, intelligent sootblowing (ISB), using boiler wall mounted
thermocouples, gas temperature sensors, and enthalpy calculations, has, for many years,
contributed to reduced NOx and CO emissions. A new, no non-sense approach, to furnace
ISB is challenging traditional methods and the frequent, but necessary, adjustments. Based on
the highly successful Griffin platform, a new ISB method evaluates the probability of furnace
cleanliness with consideration for slagging rate variation. Statistical methodologies are
employed, improving the decision of “where” to clean based on the probability of a clean
wall surface based on heat flux and elapsed time, as well as the decision “when” to clean
based on a slagging index driven by heat flux, FEGT, reheat spray flow, and unit load. For
one customer, this method resulted in a 73% reduction in water cleaning operations in the
furnace with an estimated savings of $560/day in fuel cost and a lower risk of water wall tube
rupture due to thermal cycling. The statistical approach reduces the dependence on arbitrary
set points and allows the system to easily adapt to dynamic boiler conditions and it's built on
an open platform that allows the plant engineers to easily tune the operation or even modify
the logic.
-
Speakers
-
Tom W. Ziegler, Principle Performance Engineer, Ameren Missouri
-
Wade Baumgartner, President, Constrained Optimization, Inc.