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Performance/Condition Monitoring and Optimization for Fossil Power Plants

[+] Author Affiliations
Komandur Sunder Raj

Power & Energy Systems Services, Oradell, NJ

Paper No. POWER2014-32002, pp. V001T05A002; 7 pages
  • ASME 2014 Power Conference
  • Volume 1: Fuels and Combustion, Material Handling, Emissions; Steam Generators; Heat Exchangers and Cooling Systems; Turbines, Generators and Auxiliaries; Plant Operations and Maintenance; Reliability, Availability and Maintainability (RAM); Plant Systems, Structures, Components and Materials Issues
  • Baltimore, Maryland, USA, July 28–31, 2014
  • Conference Sponsors: Power Division
  • ISBN: 978-0-7918-4608-7
  • Copyright © 2014 by ASME


Increased competition and consolidation of plant ownership have created a need for power companies to leverage technological advances and tools as they attempt to maximize generating asset value by doing more efficiently with less. Legacy-based, labor-intensive systems are being supplanted with automated, standardized systems for fleet-wide data collection, analysis, diagnostics and reporting.

Focus is also shifting from monitoring the performance/condition of individual plants and components to entire fleets for maximum economic benefit. Today’s virtual environment allows an enterprise to monitor in real time the performance and health of individual plants as well as an entire fleet for continuous learning and to sustain optimum performance.

This paper provides an overview of performance/condition monitoring and optimization for fossil power plants. It examines performance and condition monitoring models, their capabilities and benefits in analyzing plant issues and, some of the results that might be achieved. It discusses the key features and benefits of on-line monitoring systems and provides examples of key performance/condition data, parameters and indicators to monitor and diagnose operation, performance, health, economics, integrity, reliability and environmental issues. The paper also examines current performance/condition monitoring initiatives in the power industry.

Copyright © 2014 by ASME



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