Predicting Cooling Load and Energy Consumption of Coconut Oil as Phase Change Material for Thermal Management in a Residential Building using Artificial Neural Network

Abstract

Reducing energy consumption in buildings is crucial for minimizing environmental impacts and improving energy efficiency. In the building industry, air-conditioning systems account for most of the energy consumption. The passive use of thermal energy storage (TES) incorporated into building envelopes has been proven to reduce energy consumption. Therefore, this research examines the application of TES in residential structures, employing coconut oil as the Phase Change Material (PCM). The assessment of coconut oil's effectiveness as a thermal storage medium in a residential building situated in tropical climates is conducted using EnergyPlus software. The thermal comfort, including the indoor temperature and relative humidity, were compared with and without PCM. The results demonstrate that using coconut oil can stabilize thermal comfort, thereby reducing both the cooling load and energy consumption. Finally, an Artificial Neural Network was employed to predict energy consumption based on daily fluctuations in outdoor temperature and relative humidity, resulting in a strong correlation. The modeling results found that the energy consumption and the cooling load reached a maximum of 2797,435 W and 28,009.4 kJ. This research would be valuable in the early phases of building design when simulating the built environment using PCM at the tropical.