GP Strategies Corp.
Developing an effective method to capture gains or losses from outage and maintenance work is a valuable time investment. Reductions in auxiliary load improve the net station performance, reduce equipment wear and enhance availability, meaning tracking those factors has a clear value and return on investment (ROI).
The data in the graph below was automatically generated by performance monitoring software and exported into a spreadsheet program. Pre-outage data is in yellow, and post-outage data is in blue. Boiler maintenance and repair lowered the operating fan current by 150 amps at full load. This calculates to a nearly 1-megawatt reduction in auxiliary load, a very positive result. Without monitoring this data, you cannot know whether your maintenance methods need rethinking or augmentation.
Key components
If you have worked at a power station for any length of time, you have a mental list of systems and equipment that concern you most. These elements could cause or prevent a trip, delay a start-up, injure someone, have a poor maintenance history, significantly affect capacity or reduce performance. Soliciting input for your list is a good way to incorporate lessons already learned. If you do not already have it, now might be a good time to secure some baseline data.
Check the instruments
With a list of critical components, look at the instrumentation used for monitoring and control. Motor current, pump flows, temperatures, valve positions and pressures should all behave in much the same way under similar conditions. Deviations from this norm are key initial indicators that performance is starting to degrade.
It’s also helpful to review the instrumentation outputs when the plant is shut down. Current and fluid flow in nonoperating systems should be zero, and significant deviations from that can point to improper monitoring and regulation of a system. Checking the offline state only takes a few minutes and may lead to significant findings.
Compare baseline data
For the selected equipment, gather pre-outage baseline data. An effective method is to compare the performance data against a capacity-driven variable. Some examples of data comparison include motor current versus flow, fuel flow versus generation and valve position versus output. Using an effective performance and conditioning monitoring software can significantly improve data analysis, allowing plant personnel to take appropriate action for improvements.
Post-outage analysis
Wait a few weeks for the equipment status and operations to return to a steady state before starting a serious evaluation of the data. This allows for the equipment to run and a sufficient data pool to develop. Why did it change like that? By how much? In what direction? Answering these questions is an important step in analyzing the efficacy of the work performed.
Sometimes results are counterintuitive. Replacing air heater seals for a coal plant can lead to a drop in the gas-side efficiency simply because there is less cold air mixing with the hotter exit gas. Similar drops in reheat turbine efficiencies are seen with N2 seal replacement on common casing turbines.
Spreadsheet tools can automate graphic generation, the visual representation of results. These results, both good and bad, should be shared with operational and maintenance staff for feedback.
Implementation is straightforward: Look at the system performance before and after the shutdown. Not all results are as distinctive as in the figure shown earlier, but the data gathered serves as a valuable comparative standard for the future.
For more information on maintenance assessments and performance monitoring software, contact Jim Kuhn at jkuhn@gpstrategies.com.
