2023ICERD8-C06 -- Sensitivity Analysis of VRF Systems in Hot Climate Buildings: Kuwait Case PDF

The adoption of variable refrigerant flow (VRF) systems in commercial and residential buildings is on the rise due to their flexibility and efficiency. Accurate prediction of cooling loads requires a comprehensive understanding of building design and operational parameters, which are subject to various uncertainties that must be considered for reliable results. Conventional practice involves oversized heating, ventilation, and air conditioning (HVAC) systems to minimize performance uncertainties. However, this approach leads to increased capital and operating expenses, inefficient space utilization, and excessive greenhouse gas emissions. This study presents a framework for assessing the impact of operational and design uncertainties on key performance indicators in Kuwaiti residential buildings with VRF systems, including annual cooling load, total energy consumption, HVAC electricity usage per conditioned floor area, VRF system cost, and the cooling electricity consumption to total energy consumption ratio (R). Additionally, an artificial neural network (ANN)-based model has been developed to predict output parameters for residential buildings. Thirteen uncertainty parameters, encompassing building characteristics, occupants, building energy systems, VRF variables, and lighting conditions, were evaluated in the study. The sensitivity analysis of the input uncertainty parameters on the output variables was conducted using various statistical methods. Results from the sensitivity analysis indicate that the cooling set-point has the most significant impact on the energy consumption of residential buildings among the variables examined.