In recent years, smart energy meters have been deployed to enable monitoring of energy use data with hourly or sub-hourly temporal resolution. The concurrent rise of information technologies and data analytics enabled the development of novel applications such as customer segmentation, load profiling, demand response, energy forecasting, and anomaly detection. We try to unlock the power of smart meter data to understand the building energy performance comprehensively. More information can be found in https://github.com/intelligent-environments-lab/ProfileClustering.
Publications
– J.Y. Park, X. Yang, C. Miller, P. Arjunan, & Z. Nagy, “Apples or Oranges? Identification of fundamental load shape profiles for benchmarking buildings using a large and diverse dataset”, Applied Energy, vol. 236, pp 1280-1295, 10.1016/j.apenergy.2018.12.025
– J.Y. Park, C. Miller, & Z. Nagy, “A data-driven load shape profile based building benchmarking: Comparing DOE reference buildings with a large metering dataset”, IBPSA, Rome, Italy, September 2019
