Cooling water systems are used to remove excess heat from a chemical process to the atmosphere. The primary components of these systems are the cooling tower and the heat exchanger network. There is a strong interaction between these individual components, thus their performances are interrelated. Most published research in this area has focused mainly on optimization of the individual components i.e. optimization of heat exchanger network or optimization of the cooling towers. This approach does not optimize the cooling water system as a whole. Previous research work in which a holistic approach was used is limited to cooling water systems with single cooling water source.
This work presents a technique for integrated optimization of complex cooling water systems. The system under consideration consists of multiple cooling towers each supplying a set of heat exchangers. A superstructural approach is employed to explore all possible combinations between the heat exchangers and the cooling towers. The cooling water reuse opportunities within the heat exchanger networks are also explored. A detailed mathematical model consisting of the cooling towers and the heat exchanger networks model is developed. Two practical scenarios are considered and the mathematical formulations for Case I and II yield nonlinear programing (NLP) and mixed integer nonlinear programming (MINLP) structure respectively.
Although the reuse/recycle philosophy offers a good debottlenecking opportunity, the topology of the associated cooling water network is more complex, hence prone to higher pressure drop than the conventional parallel design. This is due to an increased network pressure drop associated with additional reuse/recycle streams. Therefore, it is essential to consider pressure drop during the synthesis of cooling water networks where the reuse/recycle philosophy is employed. The on-going research in this area is only limited to cooling water networks consisting of a single cooling water source. The common technique used is mathematical optimization using either superstructural or non superstructural approach.
This work further presents a mathematical technique for pressure drop optimization in cooling water systems consisting of multiple cooling towers. The proposed technique is based on the Critical Path Algorithm and the superstructural approach. The Critical Path Algorithm is used to select the cooling water network with minimum pressure drop whilst the superstructural approach allows for cooling water reuse. The technique which was previously used in a cooling water network with single source is modified and applied in a cooling water network with multiple sources. The mathematical formulation is developed considering two cases. Both cases yield mixed integer nonlinear programming (MINLP) models. The cooling tower model is also used to predict the exit condition of the cooling tower given the inlet conditions from the cooling water network model.
The results show up to 29% decrease in total circulating cooling water flowrate when the cooling water system is debottlenecked without considering pressure drop. Consequently, the overall cooling towers effectiveness was improved by up to 5%. When considering pressure drop the results showed up to 26% decrease in total circulating water flowrate.