Integration of Spatial Analysis and Dynamic Systems for Predicting Energy Use Intensity in Office Buildings under Tropical Monsoon Climate I A Rahardjo, I Garniwa, B Sudiarto, S Muslim, R Syam, and F Wadjdi
Department of Electrical Engineering, Universitas Indonesia, Margonda Raya Street, West Java 16424, Indonesia
Abstract
Understanding the intricate interplay between climatic conditions and building energy consumption is paramount for enhancing the predictive modeling of Energy Use Intensity (EUI), especially in areas characterized by tropical monsoon climates. This research examined the implications of different indoor air conditioning setpoints and thermal gradients on electrical energy consumption within office buildings. Data were conducted in three distinct thermal conditions (24oC, 22oC, and 20oC) over two consecutive 24-hour periods. The analysis indicated that reduced indoor temperature setpoints markedly escalated energy consumption, with usage increasing from 3,518 Wh at 24oC to 5,710 Wh at 20oC. Regression analysis indicated that the temperature differential between indoor and outdoor conditions served as a robust predictor of energy consumption (R2 = 0.946), whereas outdoor temperature alone demonstrated limited explanatory capacity (R2 = 0.101). A comprehensive model that integrated both variables enhanced the predictive capability (R2 = 0.961). These findings were further substantiated by rigorous statistical diagnostics and the absence of multicollinearity. The results underscore the vital necessity of integrating spatial and dynamic thermal variables into energy forecasting models. The proposed methodology contributes to the development of more precise spatially-informed energy planning, facilitating adaptive strategies for energy-efficient building design in humid tropical environments.
Keywords: Spatial-Predicting-Energy Use Intensity-Office Buildings-Tropical Monsoon Climate
