Abstract:
In the present work, a model based on experiments is presented to simultaneously optimize
all possible performance parameters as well as to ensure minimum energy consumption
from an induced draft cooling tower operating under a given set of conditions. Empirical
correlations are obtained for performance parameters such as range, approach, tower
characteristic ratio, effectiveness and evaporation rate against air and water flow rates,
which in turn are selected as discrete objective functions to formulate a multi-objective
optimization problem. Unlike previous studies which neglected the simultaneous consideration
of five performance parameters aimed at minimum possible power consumption,
here an unconstrained optimization of all objective functions is carried out using elitist Nondominated
Sorting Genetic Algorithm (NSGA-II). Considering five performance parameters,
the air flow rate has been estimated under a given water flow rate using a Decision Making
Matrix-based criterion. Among various performance parameters, the maximization of the
range for diverse water flow rates implicitly satisfies different loads imposed on the cooling
tower, thereby avoiding the necessity of formulating an additional constraint. Furthermore,
due to maximization of the approach and minimization of the evaporation rate, minimum
operating cost is ensured from the induced draft cooling tower
