Stochastic Bi-Objective Optimization for Closed Wet Cooling Tower Systems Based on a Simplified Analytical Model

A fast and accurate representation of heat and mass transfer processes of closed-wet cooling tower (CWCT) systems for optimal design and optimization is still challenging, especially considering the impact of uncertain weather conditions. This study develops a systematic approach for the stochastic bi-objective optimization of CWCT systems based on a simplified analytical model. The analytical model is established using an effectiveness-Number of Transfer Units method, which is used as a surrogate model of the CWCT systems, and is embedded in the stochastic non-linear programming model for seeking the optimums of two competing objectives. A tailored decomposition strategy is proposed to convert the original problem into multiple bi-objective optimization sub-problems by sequentially discretizing the design and uncertain spaces. Each bi-objective optimization problem is solved using an augmented e -constraint method, resulting in a set of Pareto solutions. An efficient decision-making method, namely Technique for Order Preference by Similarity to Ideal Situation, is applied for selecting the preferred solution out of the Pareto solutions obtained. From an illustrative case study, we conclude that the stochastic approach outperforms the deterministic approach since it allows for a certain design margin of heat exchanger area to reduce the impact of the variability in weather.