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Proceedings of the 24th National and 2nd International ISHMT-ASTFE Heat and Mass Transfer Conference (IHMTC-2017)

ISSN: 2688-7231 (Online)

A COMBINED ENERGY AND EXERGY OPTIMIZATION OF WET COOLING TOWER

Kuljeet Singh
Indian Institute of Technology Ropar, Rupnagar, Punjab, India

Ranjan Das
Department of Mechanical Engineering, Indian Institute of Technology Ropar, Rupnagar, Punjab, 140001, India

DOI: 10.1615/IHMTC-2017.650
pages 481-488

要約

For optimizing any thermal system, not only the energy-related performance, but the exergy-related performance also needs to be optimized. Within direct contact type mechanical cooling towers, simultaneous exchange of heat and mass occurs through two-phase flow mechanism. The heat and mass transfer phenomena within the tower can be improved if the energy consumption along with exergy destruction is minimized. Although the optimization of cooling towers based on only cost minimization, individual minimization of either energy consumption or exergy destruction satisfying either any given load or a desired range and approach can be found in some of the recent literature. But, it seems that a combined analysis aimed at simultaneous minimization of energy consumption and exergy destruction of cooling towers is not yet reported. Appreciating this fact, the present study fills the existing literature gap through combined minimization of energy consumption and exergy destruction.

The cooling tower is generally integrated to the condenser. Consequently, the amount of heat gained in the condenser must be rejected in the cooling tower. Based on this realization, during optimization of process parameters, the attainment of given heat load also needs to be ensured. This motivates the implementation of a constrained optimization method that minimizes the energy consumption and exergy destruction along with the satisfaction of a prescribed heat load. The optimization solver is aided by Augmented Lagrangian Genetic Algorithm (ALGA) that minimizes the objective function along with the load constraint. In the optimization problem, water and air mass flow rates and the water temperature gradient along the cooling tower act as control variables. To estimate the tower outlet parameters for the ALGA solver, the response surface-based second-order equation models are referred from the literature. Optimization results involving simultaneous minimization of energy and exergy destruction are reported for various operating conditions of the cooling tower.

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