An application of the Proper Orthogonal Decomposition method to the thermo-economic optimization of a dual pressure, combined cycle powerplant

In this paper the set of starting data for the POD-RBF procedure has been obtained by the CAMEL-Pro (TM) process simulator. The proposed procedure does not require the generation of a complete simulated set of results at each iteration step of the optimization, because POD constructs a very accurate approximation to the function described by a relatively small number of initial simulations, and thus "new" points in design space can be extrapolated without recurring to additional and expensive process simulations. Thus, the often taxing computational effort needed to iteratively generate numerical process simulations of incrementally different configurations is substantially reduced by replacing much of it by easy-to-perform matrix operations.

This paper presents a thermo-economic optimization of a combined cycle power plant obtained via the Proper Orthogonal Decomposition-Radial Basis Functions (POD-RBF) procedure. POD, also known as "Karhunen-Loewe decomposition" or as "Method of Snapshots" is a powerful mathematical method for the low-order approximation of highly dimensional processes for which a set of initial data is known in the form of a discrete and finite set of experimental (or simulated) data: the procedure consists in constructing an approximated representation of a matricial operator that optimally "represents" the original data set on the basis of the eigenvalues and eigenvectors of the properly re-assembled data set. By combining POD and RBF it is possible to construct, by interpolation, a functional (parametric) approximation of such a representation.