IJLTEMAS International Journal of Latest Technology in Engineering, Management & Applied Science (IJLTEMAS) IJLTEMAS 2278-2540 IJLTEMAS 458 10.51583/IJLTEMAS.2026.150900109 Engineering Data-Driven Benchmarking of Building Energy Performance Using Electricity and Gas Consumption Data Levodo Joseph Department of Engineering and the Built Environment, University of Greater Manchester, UK United Kingdom (UK) Festus Ugiagbe Osamede Department of Engineering and the Built Environment, University of Greater Manchester, UK United Kingdom (UK) 15 9 2383 2392 26 09 2026 01 10 2026 19 10 2026 Building energy performance; Energy consumption; Building benchmarking; Data analytics; Decarbonisation. Abstract

Buildings are a major contributor to global energy demand, making improved building energy performance an important component of energy management and decarbonisation strategies. This paper assesses the energy performance of a portfolio of ten buildings using historical electricity and gas consumption data. Annual energy consumption and Energy Use Intensity (EUI), expressed in kWh/m²/year, were calculated to compare energy intensity across buildings of different floor areas. The results showed substantial variation in EUI, ranging from 78.01 to 476.45 kWh/m²/year, with a mean of 191.35 kWh/m²/year and a median of 136.24 kWh/m²/year. Buildings A and B recorded the highest EUI values at 476.45 and 410.53 kWh/m²/year, respectively, while Buildings H, I, and J recorded the lowest values. Electricity and gas consumption showed a strong positive correlation r = 0.98. The findings indicate that consumption-based benchmarking can provide a practical screening approach for identifying buildings that warrant further investigation. However, EUI should be interpreted as an indicator of energy intensity rather than a direct measure of energy efficiency because building function, occupancy, operating schedules, and weather conditions were not fully incorporated. The study provides a basis for prioritising further energy audits and operational assessments, with future research recommended to incorporate weather normalisation, occupancy characteristics, building-function classification, and end-use energy data.

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