Abstract

In this study, a generic framework has been developed for using exergy as a dynamic measure for energy efficiency of process control systems. The proposed framework begins by restating the exergy balance in terms of nonlinear state space; followed by partitioning of input variables. The exergy balance is then linearized, and added to the plant model to construct an extended state space model which has unknown number of non-physical states. The numerical method of sub space state space system identification is applied to determine the extended model matrices along with the system order. Laplace transform is then applied to convert the extended state space into a multi-input-single-output (MISO) formula for estimating the lost work. In the next step, an scalar index is suggested for representing the steady and transient parts of the dynamic lost work. The proposed index which is defined in the time domain is transformed into Laplace domain for consistency with the formulated MISO lost work. The suggested framework is tested for two case studies; (1) selection of the control variables for a CSTR, and (2) selection of the tray number for inferential control of a distillation column. The results confirm the generality of the proposed framework not only for exergetical optimization of control systems but also for disclosing the thermodynamically unrealizable structures.

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