Load Disaggregation (Modeling Individual Appliance Power Generation & Consumption in Real-Time)
- National Renewable Energy Lab. (NREL), Golden, CO (United States)
We developed a machine learning-based load disaggregation method to estimate the real-time output of individual appliances from the whole-house measurements. We first learn the important features associated with each type of appliances using the ground truth consumption data of individual appliances potentially available for a small set of houses equipped with submeters. The learned features are then be used to estimate the power generation/consumption of the appliances from the whole-house consumption. This developed load disaggregation software includes two steps. The first step is to identify the on/off status of different appliances using a classification method, and the second step is to estimate the appliance output using a regression method.
- Project Type:
- Closed Source
- Site Accession Number:
- SWR-22-33
- Software Type:
- Scientific
- Research Organization:
- National Renewable Energy Laboratory (NREL), Golden, CO (United States)
- Sponsoring Organization:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Solar Energy Technologies OfficePrimary Award/Contract Number:AC36-08GO28308
- DOE Contract Number:
- AC36-08GO28308
- Code ID:
- 73278
- OSTI ID:
- code-73278
- Country of Origin:
- United States
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