Unknown appliances detection for non-intrusive load monitoring based on vision transformer with an additional detection head

Q Zhao, W Liu, K Li, Y Wei, Y Han - Heliyon, 2024 - cell.com
Non-intrusive load monitoring (NILM) offers precise insights into equipment-level energy
consumption by analyzing current and voltage data from residential smart meters, thus …

SGAN: Appliance signatures data generation for NILM applications using GANs

C Gkoutroumpi, NV Gkalinikis, D Vrakas - Science and Information …, 2024 - Springer
The development and evolution of advanced energy system technologies is one of the most
important goals for the global community in recent years. In this effort, the utilization and …

Semi-supervised learning with flexible threshold for non-intrusive load monitoring

T Tang, K Li, C Su, Z Liu - Heliyon, 2024 - cell.com
Non-intrusive load monitoring (NILM) can obtain fine-grained power consumption
information for individual appliances within the user without installing additional hardware …

[HTML][HTML] Synergistic Non-Intrusive Load Monitoring: Dual-Model Training and Inference for Improved Load Disaggregation Prediction

M Bouchur, A Reinhardt - Energies, 2025 - mdpi.com
Load disaggregation is the process of identifying an individual appliance's power demand
within aggregate electrical load data. Virtually all recently proposed disaggregation methods …

A two Stage Mixed Integer Programming Model for Distributionally Robust State Based Non-Intrusive Load Monitoring

C Zhang, Z Chai, L Yang - IEEE Transactions on Consumer …, 2025 - ieeexplore.ieee.org
This paper presents a non-intrusive load monitoring (NILM) model based on two-stage
mixed-integer linear programming theory. Compared with other mixed integer optimization …