(491b) Minimum Total Annualized Cost for a Power Plant Using the IDEAS Framework with Incremental Cost Function

Tighter environmental regulations and the increase in energy and rapid energy cost increases channel engineering design into low-capital and low-operating input plants that maximize revenue in product/energy form. To achieve this goals, a series of optimization objectives can be stipulated, such as minimum capital cost (MCC), minimum total annualized cost (MTAC), minimum utility cost, maximum power generation and so on. Conventional methods approach the optimization design as a combinatorial problem by creating a pre-established network (superstructure) that is then solved. Such superstructure-based methods cannot guarantee global optimality.

In this work we apply the infinite-dimensional state-space (IDEAS) framework with the MCC and MTAC objective functions to the design of a power generating plant that uses solar energy stored in a heat conducting fluid to generate power through commonly used industrial cycles. The aforementioned objective functions are chosen so as to reflect economies of scale and are thus reverse convex functions of the corresponding characteristics of the corresponding units (heat exchanger's heat exchange area, compressor's power consumption, turbine's power generation, etc). An infinite number of linear equations is used to describe the feasible region. Global solution of this infinite-dimensional optimization problem is pursued through a branch and bound, truncation, underestimation procedure that is guaranteed to converge in the limit to the global optimum. The capital cost of the units conforming the plant can be expressed not only using a linear cost function, but can also be expressed by a function with linear dependence on the characteristic of the unit, and an incremental cost corresponding to an infinitesimally small unit. Software developed at UCLA will then be used to automatically generate a globally optimal flowsheet of a power generating plant.