Feeder Power Disaggregation: A Data-Efficient Matrix Completion Approach
This paper presents a data-driven algorithm for the feeder power disaggregation problem in distribution systems. Leveraging spatio-temporal power patterns in residential homes, residential power is discomposed into three components: sparse-switching loads, periodic loads, and photovoltaic (PV) generation, which are characterized through the design of two sparse matrices and a low-rank matrix. The matrix completion process is data-efficient because of the matrix sparsity and low rankness, along with the use of power system models. The proposed approach is tested using real-world residential data set on a 33-bus distribution system, demonstrating accurate power disaggregation with efficient matrix completion.
- Research Organization:
- National Renewable Energy Laboratory (NREL), Golden, CO (United States)
- Sponsoring Organization:
- USDOE Office of Electricity (OE)
- DOE Contract Number:
- AC36-08GO28308
- OSTI ID:
- 2222430
- Report Number(s):
- NREL/CP-5D00-88157; MainId:88932; UUID:9bd7671b-4dc1-4aad-929a-1b46a8a40bd8; MainAdminID:71156
- Resource Relation:
- Conference: Presented at the the 2023 IEEE Power & Energy Society General Meeting (PESGM), 16-20 July 2023, Orlando, Florida; Related Information: 84138
- Country of Publication:
- United States
- Language:
- English
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