Optimization Design Of Circulating Cooling Water System With Multiple Cooling Towers

The circulating cooling water system was widely used in chemical, electricity,oil refining and other industries. Its energy consumption was very high. The studyon optimizing energy, water and operational optimization of cooling water systemwas significant.In this paper, the model of cooling tower which was the most important part ofcirculating cooling water system was established and validated. Using the model tosimulate the cooling tower, the variations including the change of air dry bulbtemperature, air humidity and water temperature along the tower were received indifferent air conditions, various values of water to air mass ratio and different inletwater temperature. The cost model of circulating cooling water system wasestablished, a simple circulating cooling water system with a sole tower and a soleuser was as an example, the influence of heat transfer area, circulating water flow,outlet water temperature and water to air mass flow rate on cost was discussed. Fortwo towers and three-user system,the structure has six kinds, with the number ofusers and the cooling tower increasing, the kinds of matching program will increasein geometric. It can find the optimal of the whole system configuration by using GAquickly and accurately.An optimization algorithm based on genetic algorithm was established for themulti-tower circulating cooling water system, the total flow of cooling water, the air flow into the cooling tower,the combination of towers and heat exchanges, the areaof heat exchanger were selected as optimization variables and rigorousmathematical model of cooling tower was combined to calculate the outlet watertemperature, to find the best combination between heat exchangers and towers. Forthree-user system with two towers, using genetic algorithms to optimize thestructure and parameters simultaneously, the better system operating parameters thatincluded the total amount of water flow, air flow, the optimum inlet and outlet watertemperature of heat exchanger, water flow, the optimum heat exchange area and soon were obtained, the total cost of the cooling water system were reducedapproximately51.7%,47.4%,27.9%in three different air conditions. The resultindicated that the effect of optimization was obvious with using genetic algorithm tooptimize the structure and parameters simultaneously,.Large industrial examples were taken to optimize by using genetic algorithm.For MDI, in three different environmental conditions, the total cost of the coolingwater system were reduced approximately41%,31%,29%. The case of TDI witheight users was optimized by using single tower, two towers and three towers, inwhich configuration matching and parameters optimization simultaneously,optimization results show that the total cost of single tower reduced25%in aircondition, and the total cost of two towers and three towers both reduced about75%,these results suggested that the waste of resources can be reduced whileconfiguration and parameters optimization simultaneously. It provided reliabletheory for energy saving of the industrial cooling water system.