Understanding and managing the rate of boiler fouling in a power plant enables more efficient operation and better maintenance planning. Due to high process variation during normal operations, creating a real-time and historical measurement of boiler fouling is extremely difficult. After a 1 year failed effort of generating a fouling model with Excel, engineers turned to Seeq.
Seeq can effectively categorize operating data to identify time periods where all operating conditions are comparable. When these “apples-to-apples” conditions are identified, users can plot how hard the boiler is working to achieve a specific output level. This solution using Seeq was implemented in less than an hour.
The boiler output analysis generated in Seeq was used to assess and improve several processes which amount to several hundred thousand dollars of savings per year. It allowed engineers to understand which modes of operation contributed to increased fouling, as well as the effect of maintenance and other treatments. Shutdown planning was improved by enabling engineers to predict when fouling would reach an unacceptable level. Finally, the impact of fouling was represented in a dollar amount based on fuel costs.
On top of the monetary savings for the initial boiler analysis, all the steps to generate the boiler analysis can be documented in Seeq’s Journal. This collaborative tool allows engineers to review the analysis, make changes to it, and apply it across other boiler assets in the future. This scalability not only eliminates duplicated efforts, but also allows companies to greatly increase the savings from each analysis by applying them across the entire enterprise.