基于改进自适应萤火虫群算法的空调送风温度优化控制

Optimal control of air conditioning supply air temperature based on improved AGSO algorithm

为了提高变风量空调(VAV)送风温度系统的控制精度,减少冷冻水系统能耗,提出一种基于改进自适应萤火虫群算法(AGSO)优化的PID控制策略。建立被控对象数学模型,引入混沌搜索和变异策略,改善基本萤火虫群算法后期容易陷入震荡和局部最优的问题,利用改进自适应萤火虫群算法对冷冻水阀-送风温度PID控制进行优化。实验结果表明:对比基本GSO-PID控制,改进AGSO-PID控制具有良好的鲁棒性和稳定性,送风温度温度误差降低约40%,冷冻水系统能耗降低约2.2 kW。

In order to improve the control accuracy of variable-air-volume(VAV) air conditioning supply air temperature system and reduce chilled water system energy consumption, a PID control strategy based on the improved adaptive glowworm swarm optimized algorithm(AGSO) optimization was proposed. A mathematical model of the controlled object was built, chaos search and variation strategy were introduced to improve the problem that the basic glowworm swarm optimized algorithm is easy to fall into oscillation and local optimum later, and the improved adaptive glowworm swarm optimized algorithm improved chilled water valve-air supply temperature PID control. The experimental results show that compared with the basic GSO—PID control, the improved AGSO—PID control has good robustness and stability, the temperature error is reduced by about 40%, and the chilled water system energy consumption is reduced by about 2.2 kW.