多联机空调系统在线能耗测量方法研究
Research on online energy consumption metering methods for variable refrigerant flow air conditioning systems
摘要：
实时运行能耗是实现多联机节能运行和智能控制的基础数据，但因成本原因，实际运行的多联机空调系统很少安装功率表对其能耗进行实时监测，因此研发低成本且具有工程精度的实时能耗测量方法对于多联机的节能降碳具有重要意义。本文提出了适用于单片机运行的频率-电流曲面拟合法和适用于云端大数据运算的神经网络自学习法，实验结果表明，2种在线能耗测量算法均具有良好的测量精度，在名义制冷、名义制热、最大制冷、低温制热和除霜等工况及在各种工况下自由切换连续45 h运行时，对多联机系统总功率的测量误差均在±5%以内。
Abstract：
Real-time operation energy consumption is the basic data of the energy-saving operation and online smart control for variable refrigerant flow (VRF) systems. However, power meter is rarely installed on VRF systems for energy consumption monitoring in real projects due to their high cost. As a result, research on economy and accurate real-time energy consumption measuring method for VRF systems is of great significance for energy saving and carbon reduction. In this paper, a frequency-current surface fitting method in single chip microcomputer cases and a neural network self-learning method in cloud big data cases are proposed. Experimental results illustrate that both two methods show high measurement accuracy. The measurement errors of the total power of the VRF system distribute within ±5% in various operating conditions including nominal cooling, nominal heating, maximum cooling, low temperature heating, defrosting and 45 h free switching operating conditions.
Keywords:variable refrigerant flow unit; energy consumption; online metering; data fitting; neural network