Abstract
In this research, a malfunction diagnosis method based on the enhanced exergy concept is applied to quantify the anomalies' sources in a real integrated solar combined cycle system (ISCCS). A comprehensive parametric study is performed to evaluate the malfunction indicators and the overall performance of the power plant by varying the substantial operating parameters under single and multi-malfunction conditions. Then, the fast and elitist non-dominated sorting genetic algorithm (NSGA-II) is applied to maximise the net power and minimise the total exergy destruction rate of the system under a multi-malfunction condition.
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