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Data-Driven Benchmarking of Building Energy Performance Using Electricity and Gas Consumption Data

Author

Listed:
  • Joseph Levodo

    (Department of Engineering and the Built Environment, University of Greater Manchester, UK)

  • Osamede Festus Ugiagbe

    (Department of Engineering and the Built Environment, University of Greater Manchester, UK)

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.

Suggested Citation

  • Joseph Levodo & Osamede Festus Ugiagbe, 2026. "Data-Driven Benchmarking of Building Energy Performance Using Electricity and Gas Consumption Data," International Journal of Latest Technology in Engineering, Management & Applied Science, RSIS International, vol. 15(9), pages 2383-2392, September.
  • Handle: RePEc:bjf:ijltem:v:15:y:2026:i:9:a:458
    DOI: 10.51583/IJLTEMAS.2026.150900109
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