Coal-fired units are increasingly expected to operate at varying loads while simultaneously dealing with various operational influences as well as fuel variations. Maintaining unit load availability while managing adverse effects of various operational issues such as, flue gas temperature excursions at the SCR inlet, high steam temperatures and the like presents significant challenges. Dynamic adjustment of sootblowing activities and different operational parameters is required to effectively control slagging, fouling and achieve reliability in unit operation.

Closed-loop optimizers aim to reduce ongoing manual adjustments by control operators and provide consistency in unit operation. Such optimizers are typically computer software-based and work by interfacing an algorithmic and/or artificial intelligence based decision making system to plant control system [1]. KCP&L is in the process of implementing Siemens SPPA-P3000 combustion and sootblowing optimizers at several Units.

The Sootblowing Optimizer solution determines the need for sootblowing based on dynamic plant operating conditions, equipment availability and plant operational drivers. The system then generates sootblower activation signals for propagation in a closed-loop manner to the existing sootblower control system at ‘optimal’ times.

SPPA-P3000 Sootblowing Optimizer has been successfully installed at Hawthorn Unit 5, a 594-MW, wall-fired boiler, firing 100 percent Powder River Basin coal. This paper discusses implementation approach as well as operational experience with the Sootblowing Optimizer and presents longer-term operational trends showing unit load sustainability and heat rate improvement.

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