改进遗传算法在变风量空调系统中的应用  

Application of improved genetic algorithm in VAV air conditioning system

作　　者：黄艺新 张九根[1] 赵丹[1] 

机构地区：[1]南京工业大学电气工程与控制科学学院,江苏南京211800

出　　处：《计算机工程与设计》2016年第9期2416-2420,2428,共6页Computer Engineering and Design

摘　　要：为对变风量空调系统进行全面节能优化控制,使整个系统在最佳运行状态下运行,提出一种改进遗传算法。根据模拟退火算法在局部搜索中的优势,将退火历程加入至变异操作,改善遗传算法在局部搜索时动力不足的问题;将模拟退火的状态接受函数用于精英选择,避免精英选择容易出现早熟的情况。结合变风量空调系统优化问题的特点,设计算法的具体流程。利用改进前后的两种算法对优化问题进行求解和仿真分析,其结果表明,改进遗传算法具有更好的寻优效果。To take comprehensive energy saving optimization control over the variable air volume air conditioning system,making the whole system run in the best running state,an improved genetic algorithm was proposed.According to the advantages of simulated annealing algorithm in local search,the annealing mutation was added to the course to solve the insufficient power problem when local search was carried out using genetic algorithm.The accept function of simulated annealing state was used to select elite,avoiding premature proneness situation.Combined with the features of VAV system design optimization,the algorithm processes were designed specifically.The original algorithm and the improved algorithm were used to solve the optimization problem and the simulation analysis was carried out.The results show that the improved genetic algorithm has better search results.

关 键 词：变风量中央空调 节能优化 改进遗传算法 模拟退火算法 仿真 

分 类 号：TP182[自动化与计算机技术—控制理论与控制工程]