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LCC/RAM Simulation in Support of Gas Turbine Power Plant Forecasting

[+] Author Affiliations
Neil Winchester

Data Systems & Solutions, Gateshead, Tyne and Wear, UK

Steve Hall

Data Systems & Solutions, Reston, VA

Paper No. IJPGC2003-40160, pp. 321-328; 8 pages
doi:10.1115/IJPGC2003-40160
From:
  • International Joint Power Generation Conference collocated with TurboExpo 2003
  • 2003 International Joint Power Generation Conference
  • Atlanta, Georgia, USA, June 16–19, 2003
  • Conference Sponsors: Power Division
  • ISBN: 0-7918-3692-4 | eISBN: 0-7918-3677-0
  • Copyright © 2003 by ASME

abstract

The activity of Life-Cycle Cost (LCC) forecasting using Reliability, Availability, and Maintainability (RAM) modeling techniques is not new, but there have been recent developments which have resulted in a fundamental change in the usefulness of LCC forecasting to designers, owners, operators, and maintainers of power plants. These changes provide the means for optimizing Operation and Maintenance (O&M) activities many years in advance with a high degree of accuracy. The primary changes have been advances in technology and the introduction of Monte Carlo-based discrete event simulation technology to perform RAM forecasting. Simulation based LCC forecasting can be used to determine the optimum operating and maintenance support scenarios. Main areas of optimization include the initial and through life cost, spares inventory holding, maintenance scheduling, logistics, etc. By allowing various scenarios to be explored in a simulation environment, LCC forecasting provides an accurate and cost effective method for optimizing costs — an activity with a very high Return On Investment (ROI) value proposition. This paper describes the methodology undertaken and the results that can be obtained from the application of automated, simulation-based LCC forecasting technology to the analysis of gas turbine based generating units.

Copyright © 2003 by ASME

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