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Power plant heat rate is a plant level performance parameter that indicates the economy of power production, equipment’s safety, and availability. In this paper, seven operating parameters, including the performance indices of integrated energy devices and the environmental conditions are incorporated for modeling the power plant heat rate by Artificial Neural Network (ANN), Support Vector Machine (SVM), and automated machine learning (AutoML) approach. The parametric significance order is determined by ANN and SVM-based Monte Carlo analytics and other machine learning-driven algorithms. Subsequently, the best-performing model is selected based on the external validation test and deployed for knowledge mining purposes. The improvement in the power plant heat rate by the parametric adjustment is achieved and subsequently, up to 3.12 percentage point (pp) increase in the thermal efficiency of …