摘要
目的研究蓄冷系统模糊控制,缓解电力生产和供应,减少城市烟尘和二氧化碳CO2的排放.方法引入ANFIS的"高木-关野(Takagi-Sugeno)"模型进行冰蓄冷系统模糊控制器设计.应用自适应神经模糊控制模型原理,建立了蓄冷量自适应神经模糊控制模型.结果利用减法聚类进行初始化后,形成输入载冷剂进口温度,载冷剂流速,蓄冷时间和输出蓄冷量之间的控制关系,蓄冷量模糊控制器的控制过程比较平稳,控制过程收敛性能都比较好,比较符合实际的运行情况,训练均方根误差最小为3.04288×10-4.结论解决了因冷负荷过大出现蓄冰装置释冷提前结束而不得不启用制冷机组的问题.
The ice thermal storage technology can alleviate the electricity production and supply as well as reduce CO2 and smoke emissions in cities. The fuzzy modeling and controlling theory of adaptive fuzzy inference system are applied to the ice storage equipment~ phase change heat transfer simulation. The principle of ANFIS is discussed and the controlling model is established. The fuzzy controlling relationship is calculated among refrigerant inlet temperature,refrigerant flow, storage time and the storage volume y by initialization of the subtractive clustering method. The control storage process of fuzzy controller and convergence performance is relatively stable in accord with the experimental results. The minimal trained mean square root error is 3.04288 ×10^-4. The optimum controlling strategy plays roles in economic operation of the ice thermal storage system.
出处
《沈阳建筑大学学报（自然科学版）》
CAS
北大核心
2010年第2期365-368,共4页
Journal of Shenyang Jianzhu University：Natural Science
基金
辽宁省教育厅基金项目(2008Z176)
住房和城乡建设部项目(2008-k4-1)
辽宁省重点实验室开放基金项目(JN-200912
JN-200911)
关键词
冰蓄冷
模糊建模与控制
预测
经济运行
ice thermal storage
fuzzy modeling and controlling
prediction
economic operation
