Abstract
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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Acknowledgments
This work was partly supported by the Estonian Research Council grants no. PRG1463, PRG658, by the State Shared Service Centre’s Cross-Sectoral Mobility Measure through the project “R8EST”; by the European Union’s Horizon Europe research and innovation programme under the grant agreement No 101120657, project ENFIELD (European Lighthouse to Manifest Trustworthy and Green AI) and by the Estonian Centre of Excellence in Energy Efficiency, ENER (grant TK230) funded by the Estonian Ministry of Education and Research.
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Matson, M., Vassiljeva, K., Parts, T.M., Kose, A., Petlenkov, E., Belikov, J. (2025). Building Potential Energy Savings Estimation Through Portfolio-Based Modeling. In: Jørgensen, B.N., Ma, Z.G., Wijaya, F.D., Irnawan, R., Sarjiya, S. (eds) Energy Informatics. EI.A 2024. Lecture Notes in Computer Science, vol 15272. Springer, Cham. https://doi.org/10.1007/978-3-031-74741-0_2
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DOI: https://doi.org/10.1007/978-3-031-74741-0_2
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