A novel air balancing method based on an improved perceptron under multiple constraints for the energy conservation of ventilation system

Abstract

Air balancing is a key technology for improving indoor environmental quality and reducing ventilation system energy consumption. Existing air balancing methods just considered damper angles and fan control voltages, combined as single constraint strategy to balance air. Fan power, as the direct parameter affecting system electricity consumption, has not been included in air balancing modelling. On the other hand, single constraint strategy makes current methods inflexible to maintain airflow accuracy and energy efficiency together. This paper proposes a novel air balancing energy-saving model with multiple constraint control strategy. Damper angle, fan control voltage, and fan power are combined by an improved perceptron model. It is aimed at minimizing ventilation system energy consumption, by achieving optimal airflow accuracy and energy conservation. The proposed improved perceptron under multiple constraints (IPMC) method is validated on the experimental system with 5 terminals, air balancing relative errors within 6.0 %. Compared with the current high-precision and energy-saving methods in references, IPMC reduces energy consumption by 12.0 % and 7.6 %, respectively, with improved airflow prediction accuracy. The proposed air balancing method has three innovation: 1) Constrained by the fan power, the IPMC method improves ventilation energy efficiency; 2) Independent and flexible constraints enable more accurate airflow control; 3) Integrated by an improved perceptron, multiple constraints consider airflow prediction accuracy and energy conservation at the same time. This method is expected to better satisfy airflow demand and reduce effectively energy consumption of ventilation system, thus improving building ventilation energy utilization efficiency without losing thermal comfort and indoor air quality.