冰蓄冷技术控制系统优化研究

发布时间：2018-01-24 03:39

本文关键词： 冰蓄冷空调粒子群算法系统优化　出处：《低温与超导》2017年05期 　论文类型：期刊论文

【摘要】：随着空调的普及,它已经成为高峰期用电负荷增大的主要原因;冰蓄冷技术能够很好地解决在用电高峰期由于空调用电过多造成负荷过大的问题,实现电力资源的移峰填谷功能,但其也带来了总体电力消耗增加的问题。针对此问题,首先建立了与冰蓄冷空调系统相关的数学模型;然后,将系统最小寿命周期成本作为目标函数,采用粒子群算法(PSO,Particle Swarm Optimization)对冰蓄冷空调系统进行优化,并制定出最佳的运行策略。研究结果表明,方法在保证系统运行经济性的前提下,能够有效地降低冰蓄冷空调系统的电力消耗,实现冰蓄冷空调系统的优化,达到节省成本和资源的目的。
[Abstract]:With the popularity of air conditioning, it has become the main reason for the increase of peak load. Ice storage technology can solve the problem of excessive load caused by excessive power consumption of air conditioning during the peak period, and realize the function of shifting peak and filling valley of power resources. But it also brings about the problem of increasing the total power consumption. In view of this problem, the mathematical model related to the ice storage air conditioning system is first established. Then, the minimum life cycle cost of the system is taken as the objective function, and the particle swarm optimization (PSO) algorithm is used. Particle Swarm optimization is used to optimize the ice storage air conditioning system, and the optimal operation strategy is worked out. The method can effectively reduce the power consumption of the ice storage air conditioning system, realize the optimization of the ice storage air conditioning system, and achieve the purpose of saving the cost and resources under the premise of ensuring the operation economy of the system.
【作者单位】：南通航运职业技术学院;
【基金】：江苏省交通科技计划项目(车船动力系统节能减排技术研究:HYZX20150006)资助
【分类号】：TB657.2
【正文快照】： 1引言空调作为现代建筑中的标配设施,其耗电量占到城市耗电总量30%以上,占建筑物的总耗电量的60%以上,并且空调系统的用电量占高峰用电量的30%以上[1],是造成高峰期用电负荷增大的主要原因。目前,冰蓄冷空调技术是解决在用电高峰由于空调用电造成负荷过大的合理和有效方法,该

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