Load Disaggregation Based on Aided Linear Integer Programming
This work addresses load disaggregation for energy management systems, but it appears incremental as it builds upon existing linear integer programming methods.
The paper tackled the problem of load disaggregation by proposing an aided linear integer programming (ALIP) system that enhances conventional methods with additional constraints, state diagram corrections, median filtering, and linear programming refinement, resulting in improved performance over the conventional system.
Load disaggregation based on aided linear integer programming (ALIP) is proposed. We start with a conventional linear integer programming (IP) based disaggregation and enhance it in several ways. The enhancements include additional constraints, correction based on a state diagram, median filtering, and linear programming-based refinement. With the aid of these enhancements, the performance of IP-based disaggregation is significantly improved. The proposed ALIP system relies only on the instantaneous load samples instead of waveform signatures, and hence does not crucially depend on high sampling frequency. Experimental results show that the proposed ALIP system performs better than the conventional IP-based load disaggregation system.