A Case Study to Quantify Variability in Building Load Profiles

Recent technology development and penetration of advanced metering infrastructure (AMI), building control systems, the internet-of-things (IoT) in built environment are providing detailed information on operation, performance, user’s comfort behavior. Building owners can obtain a wide range energy consumption details at various levels time granularity to augment their decisions as they manage operation interact with grid. AMI data new level detail visibility that may enhance services assets smart grid domain make buildings inch closer becoming grid-interactive efficient (GEB). While utility-installed typically records 15, 30, or 60-minute resolution, building-owner-installed record one-minute sub-minute scales, about how much varies from one other (i.e. variability) finer resolutions than available AMI. This paper examines load profile sets presents framework study, define, extract, quantify analyze variability buildings’ profiles. The discussion its analysis is based case study an actual time-resolution set, collected 2019, for two Midwest state USA. result shows studies, end-use category not simply proportional consumption. Furthermore, distinct predictable daily patterns emerge categories. useful host applications including prediction, forecasting, modeling.