The circulating cooling water system (CCWS) is a commonly used auxiliary system in industrial production, and it is also one of the main energy-consuming systems. The operating conditions of the system vary with the temperature changes caused by seasons, day and night, causing different energy consumption. If the system still maintains conditions when the actual conditions change, energy would be wasted. Operation optimization for the system can improve the operation effect of the system, reduce energy consumption, and increase operating efficiency. Therefore, through operation mechanism analysis for the main energy-consuming components of the CCWS that has been put into use, an operation optimization model is established integrating the domain knowledge. After that, an adaptive differential evolution (ADE) algorithm is proposed by introducing the adaptive mutation and crossover operator to solve the model. According to the minimum circulating water volume and air volume required by the system under different working conditions, the optimal start-up combination mode and operating frequency of the water pumps and fans are determined. And then, the optimal opening values of the regulating valves and baffles in the system are determined, thereby saving the energy of the system. Considering system operation knowledge, the synchronous optimization of the operation mode and operation status of the components in the system is realized. Finally, the effectiveness of the optimization method is verified through a case study.
