Published by and Copyright © 2008
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Siemens AGEnergyFossil Power GenerationInstrumentation, Controls & Electrical
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D3PPM_FR_PPL_e_V1-2Order No. E50001-G230-A170-V1-4A00
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Subject to change without prior notice.The information in this document containsgeneral descriptions of the technical optionsavailable, which may not apply in all cases.The required technical options shouldtherefore be specified in the contract.
Diagnostic Suite References
Answers for energy.
PPL Generation detected faults earlier with the lateston-line monitoring technology
SPPA-D3000 Plant Monitor detected faults early in Unit 3 of thePPL Brunner Island power plant. The data source is the EmersonOvation with PI system.
The Result
Reduced costs through optimizedmaintenance that can be planned morereadily
Increased availability throughcomprehensive monitoring of all plant data
Early detection of impending faults ordeviations from normal conditions
Longer lifetime by detecting faults evenunder changing operating conditions
SPPA-D3000 Plant Monitor
detected impending damage in steady-state andcyclic operation by continuously comparingcurrent operating data against the normalresponse in trial.
The Plant
The PPL Brunner Island coal-fired power plant inYork Haven, Pennsylvania, USA – with an outputof 1,470 MW – is one of the largest fossil fueledpower plants within the PPL Corporation’sgeneration subsidiary. Unit 3 generates 780 MWwith a steam turbine.
The Task
During maintenance work, damage is oftendetected on sliding contact bearings without anyindication of a fault during operation. The causeand development of the damage usually is unclearand has to be analyzed retrospectively at a highresearch effort. The task thus was to detectimpending faults early enough to allow damage tobe detected and rectified at the very onset.
Our Solution
During a reference installation, the SPPA-D3000Plant Monitor accurately identified a transientproblem prior to the event during a blind study ofpre-and post-event historical data. The Monitorcompared the measurement data with the learnednormal response of the plant. The system learnedthis autonomously from the historical data oftrouble-free optimized operation. The data sourcesfor this are all the existing archives, in this casethe PI system. Critical deviation was detectedunambiguously in real time; the cause of the faultwas pin-pointed immediately through correlationwith all the available reference data. The decisiveaspect here was that Plant Monitor deliveredaccurate warnings and instructions for analysis forboth steady-state and transient operatingconditions.
“The ability to monitor steady-state andtransient processes real time and on-lineoffers outstanding support for maintenanceand is a big step forward from classical limitmonitoring. If we can detect machinehealth issues during transient and steady-state operation, there is an opportunity toavoid consequential damages.”
Joeseph Murach, Supervisor-EquipmentReliability, PPL Generation, LLC
Instrumentation, Controls & Electrical
