Abstract
This paper proposes a fuzzy model for reliability evaluation of captive power plant maintenance scheduling optimizing safety and reliability incorporating uncertain forced outage rate and load representation. Such a model is a combination of probabilistic fuzzy state (PROFUST) model and fuzzy load model. In PROFUST model, fuzzy numbers represent the failure and repair rates of generating units because it is inadequate from pragmatic prospective to represent them by crisp numbers. As the maintenance tends to be based on experience-based skills, therefore the fuzzy forced outage rate (fuzzy FOR) based on expert evaluation reflects the condition of operation and maintenance of thermal generating units more realistically compared to a constant failure and repair rate model yielding constant FOR value. The uncertainties due to load forecasting lead to fuzzy load model. Particularly the utilities catered by captive power plants are very sensitive to power failure and the reliability evaluation corroborates the effect of uncertainties through fuzzy loss of load probability (FLOLP) index. Case studies for the maintenance scheduling of a captive power plant catering to an aluminum smelter have been formulated based on both classical probabilistic as well as fuzzy model and comparisons of FLOLP demonstrate the efficacy of the proposed model.
Published Version
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