Abstract
This paper describes the intelligent maintenance scheduling of a captive thermal plant using intelligent computational techniques such as Simulated Annealing (SA). A case study pertaining to a captive power plant for an aluminium smelter has been formulated using reliability-based objective function including statutory safety norms as constraints. As the utilities catered for captive power plants are very sensitive to power failure, the reliability of power supply has been evaluated by the Loss of Load Probability (LOLP) index for the optimum schedule.
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