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Buildings significantly impact global energy use and emissions. One potential way to improve performance and reduce energy demand is by applying advanced control algorithms. This, however, requires a detailed cost-benefit analysis. We present a data-driven methodology for assessing commercial buildings’ potential savings with advanced control techniques, focusing on the EU context. The approach uses hourly energy consumption data from 15 buildings to identify consumption patterns, cluster buildings, and predict energy savings without the need for physical inspections. The proposed method is validated using shopping malls as a case study.

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Building Potential Energy Savings Estimation Through Portfolio-Based Modeling

  • 会议论文

  • 发表日期：

    2025年

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  • Margarita Matson,
  • Kristina Vassiljeva,
  • Tuule Mall Parts,
  • Ahmet Kose,
  • Eduard Petlenkov,
  • Juri Belikov

摘要

Buildings significantly impact global energy use and emissions. One potential way to improve performance and reduce energy demand is by applying advanced control algorithms. This, however, requires a detailed cost-benefit analysis. We present a data-driven methodology for assessing commercial buildings’ potential savings with advanced control techniques, focusing on the EU context. The approach uses hourly energy consumption data from 15 buildings to identify consumption patterns, cluster buildings, and predict energy savings without the need for physical inspections. The proposed method is validated using shopping malls as a case study.