基于群智能的暖通空调输配系统拓扑描述方法和关键参数辨识

Description of HVAC System and Identification of Flowrates and Pressures in HVAC Based on Collective Intelligence System

暖通空调系统的高效控制是降低建筑能耗的重要手段。暖通空调输配系统不仅产生能耗,而且决定着冷热量是否按照冷热负荷需求的分布正确输配到建筑不同位置。由于流体输配网络的复杂性,暖通空调输配系统的优化控制难度较高。本文开展群智能技术在暖通空调输配系统控制方面的应用研究,提出1种分布式并行辨识算法,用来识别未直接测量的暖通空调输配系统节点的流量和压力。文章将所提出的描述方法应用于典型建筑的暖通空调输配系统,并在简化的输配网络实例中对提出的关键参数辨识算法进行了验证。

The efficient control of the HVAC system is important for the reduction of energy consumptions in buildings. The water and air distribution network of the HVAC system not only leads to energy consumption but also determines whether the coldness and heat are distributed properly in the building according to the cooling and heating load. The optimal control of the HVAC distribution system is complex due to the scale of the network and the coupling effects between HVAC devices. This paper proposed a novel distributed control system using standard computing processing nodes, which is called the Collective Intelligence System(CIS). The proposed method was validated using a typical HVAC system in a real office building. The description of the HVAC system and the identification of flow rates and pressures of the distribution network was demonstrated using the decentralized identification algorithm.