中央空调冷冻水系统设备节能优化方法

针对中央空调冷冻水系统运行能耗高、系统设备参数难以随负荷变化而动态调节的问题，采用一种结合穷举法的自适应并行人工免疫算法(Adaptive parallel artificial immune algorithm combined with exhaustive method, EM-APAIA)优化系统设备在不同负荷下的运行参数，以降低冷冻水系统的运行能耗。首先建立了系统内各设备的功耗模型，以所有设备功耗最小作为冷冻水系统的优化控制目标。其次，采用EM-APAIA对冷冻水供水温度、冷冻水泵的运行台数和转速比等运行参数进行优化。在该算法中，对初始化方式、移民算子和变异概率进行了改进以及引进穷举法机制，增强了算法对冷冻水系统设备运行参数的优化能力。最后对某一实际中央空调冷冻水系统进行了仿真实验。结果表明：与常规设置相比，使用EM-APAIA对系统内各设备运行参数优化后，系统总能耗降低14.8%;同时相对于其他对比算法，该算法能得到更好的控制策略，且收敛速度快、稳定性强，可用于中央空调冷冻水系统内各设备的控制优化。

Equipment energy-saving optimization method for central air-conditioning chilled water system

Due to the high-energy consumption of chilled water system in the central air-conditioning and the difficulty in dynamic adjustment for system equipment parameters with load changes, an adaptive parallel artificial immune algorithm combined with exhaustive method (EM-APAIA) was proposed to optimize equipment operating parameters under different loads, so as to reduce the operation energy consumption of chilled water system. First, the power consumption model of each piece of equipment in the system was established, and the minimum power consumption of all the equipment was taken as the optimal control objective of the chilled water system. Then, EM-APAIA was used to optimize the operation parameters of the chilled water supply temperature, the number of chilled water pumps, and the speed ratio. In the algorithm, the initialization method, migration operator, and mutation probability were improved, and the exhaustive method mechanism was introduced, enhancing its ability to optimize the equipment operating parameters for the chilled water system. Finally, a simulation experiment was carried out on an actual chilled water system of central air-conditioning. Results show that compared with the conventional setting, the total energy consumption of the system was reduced by 14.8% after its equipment operating parameters were optimized by EM-APAIA. The algorithm not only achieved better control strategy than the comparison algorithms, but also exhibited fast convergence speed and strong stability, which can be better applied to the control optimization of the equipment in central air-conditioning chilled water system.