An investigation of energy consumption and cooling demand for residential buildings based on the adaptation of building models in Libya

Residential buildings account for a significant proportion of electricity consumption in Libya, where prolonged periods of high ambient temperatures result in extensive air-conditioning (AC) use. Improving building envelope design therefore offers considerable potential for reducing electricity demand and associated carbon emissions. This study investigates the effectiveness of building envelope adaptation strategies for improving the energy performance of Libyan residential buildings. Questionnaire data were collected from 724 households, as reported by Alafya and Maka (2025), to characterise residential building features and occupancy patterns. Based on these data, eight representative residential building models were developed and simulated using Integrated Environmental Solutions Virtual Environment (IESVE) with a 30-minute simulation time resolution. Three adaptation scenarios (A, B and C), incorporating improvements to external wall construction and roof insulation, were evaluated against baseline models. The results show that the proposed adaptations significantly reduced annual electricity consumption across all representative building types. Adaptation B achieved the greatest reduction for most building types, whereas Adaptation C produced the largest reduction for the 5BF model and Adaptation A performed best for the Villa model. Overall, annual electricity consumption was reduced by 12.37%–27.35%, depending on building type. These findings demonstrate that climate-responsive building envelope improvements can substantially reduce residential electricity consumption, peak electricity demand, and associated carbon emissions, providing practical guidance for energy-efficient residential design and policy development in Libya. The novelty of this study lies in evaluating climate-responsive adaptation strategies across representative Libyan residential building typologies using dynamic building energy simulation, providing evidence-based recommendations to improve energy efficiency in a region where such studies remain limited.