Forecasting optimum energy consumption and scenario analysis: A case study on detached houses in the United Arab Emirates

Abstract

The study aims to optimize energy consumption for cooling and lighting in the residential sector by examining the interaction of glass types, shading systems, and interior surface reflectance values in a standard house plan. Structured in four stages, the research began with developing a detailed building model to calculate energy consumption, focusing on glazing type, surface reflectance, and shading options. In the second stage, 120 scenarios were created to assess their impact on lighting and cooling energy requirements in residential buildings. The third stage used DALEC Software to analyze these variables under different conditions, integrating local climatic data to find meaningful correlations. Finally, the fourth stage compared these scenarios using cross-validation to identify the optimal combination for energy efficiency in the residential sector.

The findings, based on 120 scenarios analyzed using DALEC Software, show that different design decisions significantly affect energy consumption in hot, arid climates. The study found that increasing interior reflectance values reduces energy consumption for lighting and cooling in residential buildings. The most effective combination was Low EC Glass type and External Venetian Blind 450 shading system. Conversely, scenarios with no shading, very dark reflective surfaces, and SC-R Glass had high-energy consumption and are not recommended for residential buildings in hot climates.

This research stands out by addressing the complex interplay between architectural and landscape components to enhance energy efficiency in the residential sector, especially relevant in the context of rising global temperatures. Conducted in the UAE, the study aims to inform sustainable architectural practices in similar environments and provide a blueprint for global efforts to mitigate global warming through intelligent design.