基于外部参照优化算法的空调系统节能控制

Energy saving control of air conditioning system based on an external reference optimization algorithm

分析了当前空调系统能耗优化算法存在的不足,根据空调系统非线性与时滞性的特点,提出了采用多目标粒子群优化算法进行寻优计算。将空调系统分为3个目标解,寻取多目标最优解Pareto前沿,根据Pareto前沿求得空调系统整体能耗最优值。普通多目标粒子群算法收敛性相对较差、仿真时间较长,提出了外部参照的多目标粒子群改进算法来提高收敛性与快速性。通过仿真实验和能耗分析对比发现,相较于其他算法,该改进算法的优化节能效果更佳。

Analyses the shortcomings of the current energy consumption optimization algorithm for air conditioning system,and proposes a multi-objective particle swarm optimization(PSO)algorithm according to the characteristics of non-linearity and time delay of air conditioning system.Divides the air conditioning system into three target solutions,and finds the multi-objective optimal Pareto frontiers.According to Pareto frontiers,obtains the optimal value of overall energy consumption of air conditioning system.Because the convergence of the ordinary multi-objective PSO algorithm is relatively poor and the simulation time is too long,proposes an external reference multi-objective PSO algorithm to improve the convergence and rapidity. The simulation experiment and energy consumption analysis show that compared with other algorithms,the optimization and energy saving effect of the improved algorithm is better.