Advanced Performance Monitoring in Steam Surface Condensers

Source: AIChE
  • Type:
    Conference Presentation
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    AIChE Member Credits 0.5
    AIChE Members $19.00
    AIChE Graduate Student Members Free
    AIChE Undergraduate Student Members Free
    Non-Members $29.00
  • Conference Type:
    AIChE Spring Meeting and Global Congress on Process Safety
  • Presentation Date:
    April 11, 2022
  • Duration:
    30 minutes
  • Skill Level:
    Intermediate
  • PDHs:
    0.50

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Steam surface condensers are integral parts of power, cogeneration, and ethylene plants. Their performance directly impacts the plant’s capacity and ultimately influences operating costs and the bottom line. Inefficient operation of condensers leads to lost power production, increased operation costs (due to higher fuel usage), increased carbon dioxide emissions, and reduced profit margins. Utilizing cloud based advanced analytics and “near” real time data empowers plant operators to react more quickly and accurately evaluate the performance of their steam surface condenser, validate the effectiveness of chemical treatments in preventing fouling, and make critical decisions to improve fuel and water consumption, and lower greenhouse gas emissions.

Steam surface condensers are complex systems with many correlated process variables. As a result, it is generally difficult to discern minor reductions in efficiency with conventional monitoring techniques until the losses become significant especially in power plants that cycle operations to meet changing market conditions. Incremental performance losses can increase the consumption of non-renewable energy sources and increase air pollution which will have a negative impact on environment. To identify and analyze inefficiencies, steam power plant operators have traditionally relied on univariate approach, manual data sets and estimates that often took days to compile. The use of advanced analytics and on-line monitoring tools with normalization functionality and a modified statistical process control strategy allows operations to track cooling performance and clearly distinguish between common cause variation (variation attributable to normal changes in the various operating parameters) and special cause variation (variation due to a statistically significant, unexpected event such as fouling or air ingress). Visualizing the outputs from these tools and advanced analytics through a cloud-based data management platform and dashboard provides for remote, 24-7 secure access to critical information. The improved speed of data collection, instantaneous analysis and remote access enables plant operators to respond faster to issues and make more informed data-driven decisions.

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Do you already own this?

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Individuals

AIChE Member Credits 0.5
AIChE Members $19.00
AIChE Graduate Student Members Free
AIChE Undergraduate Student Members Free
Non-Members $29.00
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