Abstract
In this paper, the artificial immune system paradigm is used to formulate a comprehensive and integrated framework for monitoring and control of advanced power plants. The proposed data-driven methodology is envisioned to address directly the complexity and multi-dimensionality of modern power plants and support their safe operation at desirable levels of performance under normal and abnormal conditions. Abnormal condition detection, identification, evaluation, and accommodation are addressed. A preliminary numerical simulation example using an integrated gasification combined cycle power plant illustrates the general concept and the proposed computational tools.
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