Deciphering domestic energy demand through household electricity and gas consumption

• Clustered energy usage patterns using 15-min smart meter data from 15,000 homes. • Identified peak electricity use in summer evenings and gas use in winter mornings. • Developed predictive models with R² of 0.912 for electricity, 0.877 for gas demand. • Analyzed impact of temperature, occupancy, and appliance use on energy patterns. . This study investigates residential electricity and gas demand in Iraq using smart meter data from 15,000 households between 2019 and 2023. The primary objective is to analyze temporal energy consumption patterns, focusing on the impact of environmental, behavioral, and household-specific factors. The results show that electricity consumption peaks during the afternoon, particularly between 12:00 and 14:00, with average usage reaching 2.3 to 2.6 kWh, while gas consumption increases in the winter months, especially in the early morning hours, driven by heating and cooking activities. The analysis of weekend versus weekday consumption reveals a 6.4% increase in electricity and a 3.1% rise in gas usage on weekends, indicating shifts in behavioral energy usage patterns. The study finds that predicted values closely match observed data, with a deviation of only 5% for electricity and 7% for gas, showcasing high model accuracy. The concept of "variability" is clarified as fluctuations in demand across different times of the day, which were reduced in households with efficient appliances, as identified from household energy audits linked to smart meters. The dataset also provides insights into the use of energy-efficient appliances, collected from utility-linked surveys and integrated household registration data. The findings offer valuable insights into demand-side energy management and are particularly relevant to urban Iraqi households but may also inform demand forecasting in similar regions with comparable climates and energy use behaviors. .