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Energy management

Data-Driven Approach for Electricity Consumption Benchmarking in Multi Residential Buildings

Strategic Insights

— 2 min read

A new study from researchers at Kyungpook National University in South Korea has introduced a streamlined data-driven framework for building energy benchmarking. The research, supported by the Korea Institute of Energy Technology Evaluation & Planning (KETEP), aims to enhance energy efficiency and encourage conservation efforts. By integrating publicly available data on building information, electricity consumption, and weather data, the researchers developed a predictive model that estimates monthly electricity consumption and evaluates energy efficiency. The model was applied to evaluate 1,768 buildings in Seoul and Daegu, classifying 235 as Grade 1 (highest efficiency), 728 as Grade 2, 355 as Grade 3, 326 as Grade 4, and 124 as Grade 5 (lowest efficiency).

Key Takeaways:

  • The research introduced a data-driven framework for building energy benchmarking that utilizes publicly available data to simplify the process.
  • The framework integrates databases encompassing building information, electricity consumption data, and weather data, and incorporates models for predicting monthly electricity consumption and evaluating energy efficiency.
  • The predictive model developed by the researchers estimates monthly electricity consumption, producing results that are used to calculate energy use scores and classify buildings into five energy-efficiency grades (Grade 1: highest efficiency, Grade 5: lowest efficiency).
  • Analysis of buildings with similar specifications in Seoul showed that older buildings tended to have lower energy efficiency than newer constructions, suggesting potential gains from retrofitting and other improvements.
  • The framework aims to assist building owners, managers, and policymakers in understanding energy performance patterns and identifying opportunities for energy conservation.
  • The research was supported by the Korea Institute of Energy Technology Evaluation & Planning (KETEP) and has been peer-reviewed.

Statistics:

  • 1,768 buildings in Seoul and Daegu were evaluated using the developed predictive model.
  • 235 buildings were classified as Grade 1 (highest efficiency), accounting for 13.4% of the evaluated buildings.
  • 728 buildings were classified as Grade 2, accounting for 41.2% of the evaluated buildings.
  • 355 buildings were classified as Grade 3, accounting for 20.1% of the evaluated buildings.
  • 326 buildings were classified as Grade 4, accounting for 18.5% of the evaluated buildings.
  • 124 buildings were classified as Grade 5 (lowest efficiency), accounting for 7.0% of the evaluated buildings.
  • The research analyzed buildings with similar specifications in Seoul, showing that older buildings tend to have lower energy efficiency than newer constructions (average age of Grade 1 buildings: 6 years; average age of Grade 5 buildings: 22 years).

Sources:

  • Data-driven Approach for Electricity Consumption Benchmarking of Multi Residential Buildings. Energy and Buildings, 2025;345.
  • Elsevier Science Sa, PO Box 564, 1001 Lausanne, Switzerland.
  • Korea Institute of Energy Technology Evaluation & Planning (KETEP).
  • Kyungpook National University, Dept Convergence & Fus Syst Engn, Sangju 37224, South Korea.
  • NewsRx. Findings from Kyungpook National University Has Provided New Data on Information Technology (Data-driven Approach for Electricity Consumption Benchmarking of Multi Residential Buildings). Information Technology Newsweekly. October 21, 2025; p 210.

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