Multiple Linear Model Analysis of Indoor Air Quality for Air Conditioning System in Office Building

Abstract

The building performance is measured through the power consumption of the air conditioning system and indoor air quality (IAQ) of the building spaces to provide sufficient cooling while at the same time satisfying thermal comfort. The multiple linear model of Piecewise linear (PWL) and Multiple Linear Regression (MLR) model is used to accurately estimate the power consumption of the air conditioning system considering IAQ parameters such as carbon dioxide concentration, indoor air temperature, and humidity. The IAQ parameters are usually modelled individually for the building without proper correlation with the power consumption of the air conditioning system. This problem makes the modelling results unrealistic to the building performance solutions. This paper focuses on identifying the relationship between power consumption with integrated IAQ parameters of CO₂ concentration, air temperature, and humidity for Air Conditioning Mechanical and Ventilation (ACMV) system in the office building. The results demonstrate the power consumption estimation model considering IAQ parameters for different time zones is accurate and acceptable with a percentage difference of less than 1 % from the real data. The power consumption estimation model can be used to predict future power consumption with optimum range values for IAQ parameters for sustainable utilisation of energy.